Proteome Dynamics Across the Blastogenic Cycle of Botryllus schlosseri Reveals Targets for Cell Immortalization

Proteome Dynamics Across the Blastogenic Cycle of Botryllus schlosseri Reveals Targets for Cell Immortalization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Proteome Dynamics Across the Blastogenic Cycle of Botryllus schlosseri Reveals Targets for Cell Immortalization Weizhen Dong, Maxime Leprêtre, Isabel R. Enriquez, Brenda P. Luu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8094443/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background The colonial tunicate Botryllus schlosseri undergoes a weekly blastogenic cycle in which old zooids regress while new buds proliferate. Despite this species’ advantages for studying coordinated proliferation and degeneration, proteome-level regulation across blastogenic stages and actionable targets for advancing proliferation of cell culture models remain undefined. Results DIA proteomics enabled quantitation of 15,156 unique peptides mapping to 3,155 unambiguous protein groups across zooids from four blastogenic cycle stages and takeover primary buds (TOB), with 1,432 proteins (45%) changing significantly across these stages. Principal component analysis (PCA) and network analyses revealed most distinct proteomes in TOB versus regressing takeover zooids (TOZ). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that TOB were enriched in DNA replication, cell cycle progression, ribosome biogenesis, and translation pathways, reflecting a strong proliferative and biosynthetic program. Analysis of differentially abundant proteins and enriched pathways across different blastogenic stages revealed that the regulation of cyclin-dependent kinase 1 (CDK1), CDK2, replication licensing, chromatin remodeling, proteostasis, and enhancing translation are central to the TOB proliferation program. In contrast, TOZ were enriched for pathways associated with stress responses, proteolysis, metabolic remodeling, and catabolism, indicating a proteomic signature of programmed degradation and macromolecular integrity control during zooid regression. Conclusions The pro- and anti-proliferative proteomic signatures identified CDK1, CDK2, histone deacetylase 2 (HDAC2), S-phase kinase-associated protein 1 (SKP1), and proliferating cell nuclear antigen (PCNA) as the major nodes to be targeted for manipulation of cell proliferation in vitro to overcome crisis/senescence and achieve reliable immortalization of tunicate cell lines. mass spectrometry proteomics Botryllus schlosseri cell proliferation asexual reproduction tunicates Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background The colonial tunicate Botryllus schlosseri (Fig. 1 A) has emerged as a compelling model organism for exploring the mechanisms of regeneration [ 1 , 2 ], aging [ 3 , 4 ], and stress resilience [ 5 , 6 ]. As the closest living invertebrate taxon relative to vertebrates [ 7 ], tunicates occupy a critical phylogenetic position that bridges evolutionary milestones, offering unique insights into the molecular underpinnings responsible for conservation, innovation, and loss of cellular and organismal processes during chordate phylogeny (Fig. S1 ). Botryllid tunicates stand out as the chordate phylogenetically closest to humans that are capable of whole-body regeneration during asexual reproduction and in response to injury. This trait has been lost in all vertebrates and most other chordates rendering B. schlosseri a unique model for studying molecular mechanisms that promote tissue regeneration, cell proliferation, and cell differentiation in chordates. Notably, B. schlosseri undergoes a synchronized weekly blastogenic cycle of asexual reproduction, during which old zooids degenerate and are replaced by new primary buds. First described by Sabbadin et al. [ 8 ], and then later reclassified and characterized in detail by Manni et al. [ 9 ], this cycle consists of four stages (A-D) and occurs within a zoid system enclosed by a tunic where three generations coexist and are connected by a communal vasculature. Adult zooids actively feed, while primary and secondary buds remain nutritionally dependent on the zooids. As the cycle progresses, primary buds develop through stages A to C, culminating in the takeover stage D (Fig. 1 B), where synchronized zooid regression and increased cellular turnover drive colony renewal. This cyclical process mirrors multiple aspects of growth, maturation, and programmed cell death common to vertebrates [ 10 ], thus providing an in vivo model for understanding conserved mechanisms of cellular turnover in chordates. Moreover, studying blastogenic takeover and injury-induced whole-body regeneration in botryllid tunicates offers an opportunity to identify molecular processes of chordates that can be targeted to promote tissue and whole-body regeneration by genetic or pharmacological intervention in vertebrates and other chordates lacking the ability of comprehensive tissue and whole-body regeneration. However, key limitations have impeded deeper mechanistic studies of B. schlosseri , including the scarcity of information on the proteome [ 11 ], which represents the main determinant of cellular and organismal structure and function, and the absence of established cell line models for high-throughput genetic screens. Addressing these gaps is essential for advancing functional investigations and for high-throughput genetic manipulation of cellular processes in a controlled environment to establish causality between gene function and phenotype. Despite its utility as an in vivo model, the lack of B. schlosseri cell lines limits the ability to manipulate and investigate cellular mechanisms in a controlled environment by high-throughput genetic engineering and other causality-aimed approaches. While some species and cell types can undergo spontaneous immortalization without the introduction of foreign elements [ 12 , 13 ], most species are believed to require targeted interventions to achieve stable, long-term cell growth [ 14 ]. With current approaches, isolated B. schlosseri primary cells exit the G 1 phase of the cell cycle and remain quiescent in G 0 after relatively short-term (1–3 weeks) primary culture and optimal conditions for long-term culture and exit from primary culture crisis/ senescence remain undefined [ 15 , 16 ]. Overcoming these challenges requires innovative strategies to enhance cell survival and proliferation while inhibiting senescence to overcome crisis in vitro . Mammalian cell lines have been successfully immortalized using viral oncoproteins, such as the SV40 large T antigen, or modifications of the cell cycle machinery, including the overexpression of human telomerase reverse transcriptase (hTERT) [ 17 – 19 ]. However, such methods often fail in non-mammalian systems, where conserved pathways like cell cycle regulation may rely on subtly divergent regulatory mechanisms that are still poorly characterized in aquatic invertebrates. To date, the only established strictly marine invertebrate cell lines include one derived from the phylum Porifera by spontaneous immortalization [ 20 ], a hybrid shrimp cell line (PmLyO-Sf9) generated by fusing Penaeus monodon lymphoid cells with Sf9 insect cells [ 21 ], and, more recently, cell lines established from scallop ( Chlamys farreri ) trochophore larvae [ 22 ], and sea urchin ( Lytechinus variegatus and Strongylocentrotus purpuratus ) embryos [ 23 ]. Terrestrial invertebrate models have offered limited insight applicable to aquatic invertebrates. Drosophila cells, for example, could be immortalized by overexpressing Ras V12 , but not Myc , highlighting that even targeting well-established oncogenes has varying effectiveness across species [ 24 ]. These outcomes underscore the importance of identifying species-specific targets rather than exclusively extrapolating target identification based on knowledge of mammalian or terrestrial invertebrate systems. Even core regulators such as cyclin-dependent kinases (CDKs) differ across lineages and primitive chordates have fewer CDK paralogs than mammals due to gene duplication events during early metazoan and vertebrate evolution. For instance, yeast encode only a single CDK (Cdc28) [ 25 ], while humans possess 21 CDK paralogs that include CDK4, a common target in mammalian immortalization protocols [ 26 ]. Moreover, CDK1 gene duplication has been reported in the tunicate Oikopleura [ 27 ]. Such variability suggests that successful strategies in non-mammalian systems will require a deeper understanding of their unique regulatory landscapes. Identification of species-specific molecular proteome signatures associated with physiological states of active proliferation and senescence will aid in the identification of potent species-specific regulators of cell growth and survival. Previous transcriptomic studies in B. schlosseri have provided valuable insight into pathways involved in stem cell activation, immune responses, and oxidative stress responses associated with aging [ 28 – 32 ]. The cellular processes of apoptosis and autophagy have been implicated in the degeneration of adult zooids, supporting the recycling of molecular building blocks and tissue turnover required for bud development [ 33 , 34 ]. However, these studies did not directly capture the proteins responsible for proliferation and senescence phenotypes during the blastogenic cycle. This knowledge gap is significant because mRNA and protein abundances are often not correlated well in mammalian and other chordate cells due to regulation at the translational and post-translational levels [ 35 – 38 ]. Moreover, transcriptomic analyses do not capture functional protein-level activity and post-translational modifications, which are critical for understanding dynamic changes in cellular phenotypes [ 39 ]. By contrast, proteomic analyses enable direct investigation of protein abundances, interactions, and modifications, providing a more complete view of cellular responses. Recent advances in mass spectrometry allow the quantification of thousands of proteins in a single sample based on defined sets of peptides that are used for targeted quantitation in all samples of interest. This quantitative data-independent acquisition (DIA) proteomics approach facilitates whole-proteome comparisons across conditions and the discovery of new molecular targets that drive phenotypes of interest [ 40 ]. By leveraging B. schlosseri ’s unique biology and label-free DIA proteomics, this study aims to comprehensively characterize proteome dynamics across different blastogenic stages to identify key proteins and molecular signatures associated with B. schlosseri cell proliferation and senescence. Initially, proteomics was performed across all blastogenic stages to capture global protein abundance regulation and identify corresponding functional adjustments during blastogenesis. Subsequently, a more focused proteomic follow-up study was conducted focusing on the blastogenic cycle stages that are most informative regarding critical regulators of cell proliferation and senescence. Results Distinct Proteomic Landscapes Throughout the Blastogenic Cycle Adult zooids and primary buds at specific blastogenic stages were classified as follows: Stage A zooids (SAZ), Stage B zooids (SBZ), Stage C zooids (SCZ), Takeover zooids (TOZ), and Takeover primary buds (TOB) (Fig. 1C). Secondary buds, due to their extremely small size, could not be physically separated from the primary buds and are assumed to contribute minimally to the primary bud proteome. Additionally, primary buds from stages A, B, and C were excluded due to the challenge of extracting sufficient protein from such small buds. To establish a foundational proteomics analysis of B. schlosseri at the individual zooid level, the proteomes of adult zooids across four blastogenic stages (SAZ, SBZ, SCZ, and TOZ) and emerging primary buds from the takeover stage (TOB) were examined. Colonies were genotyped to confirm unique identities (Fig. S2). No genotype-specific clustering or systematic bias was observed, and genotype effects were minor relative to stage differences. Thus, only blastogenic stage differences that are conserved across all genotypes used in this study were considered. Larvae released from field-collected colonies were settled on glass slides and maintained as laboratory colonies, which were subsequently used for dissection (Fig. 1D). A total of 15,156 unique peptides mapped to 3,155 unambiguous protein groups and were reliably quantified across all blastogenic stages. Among the identified proteins, 45% (1,432) exhibited statistically significant changes in abundance across stages (ANOVA, FDR < 0.1), demonstrating extensive proteomic remodeling throughout the blastogenic cycle. Principal Component Analysis (PCA) performed on these differentially abundant proteins (DAPs) demonstrated clear separation of expression patterns among blastogenic stages, with TOB exhibiting the most distinct proteome compared to adult zooids at all other stages (Fig. 2A). PC1, which explains 64% of the total variance, clearly discriminates TOB, SAZ, and TOZ, reflecting the major proteomic shifts associated with the transition from active adult zooids to degenerating zooids and the emergence of new primary buds. PC2 captures more subtle differences between SBZ and SCZ, corresponding to the progressive maturation of adult zooids prior to takeover. The distinct separation observed in PCA underscores the molecular coordination driving developmental renewal and programmed cell death in B. schlosseri. Co-expression Modules Reveal Distinct Functional Programs Weighted Gene Co-expression Network Analysis (WGCNA) performed on the DAPs identified two major modules with distinct expression trends across the blastogenic cycle (Fig. 2B). The first module, termed the proliferation module, contains 614 proteins whose abundance decreases from the TOB stage to the TOZ stage. In contrast, the second module, referred to as the degradation module, includes 628 proteins that increase in abundance over the same transition. These opposing trends highlight a coordinated switch from proliferative to degradative cellular programs as the blastogenic cycle progresses. The remaining 190 DAPs were not classified into any co-expression module. Protein abundance shifted most dramatically between the temporally adjacent TOB and SAZ stages, with DAPs exhibiting an average log₂ fold change (FC) of approximately 1. Later stage transitions showed progressively smaller shifts, culminating in the largest overall divergence between the earliest (TOB) and latest (TOZ) stages examined in this study (Fig. 2B). To interpret the biological relevance of these co-expression patterns, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for each module (Fig. 2C). Pathways associated with vertebrate-specific physiology, human diseases, or cell types absent from B. schlosseri were excluded from this analysis. The proliferation module (Fig. 2B, green, 614 proteins), which decreases in abundance from TOB to TOZ, was broadly enriched for pathways related to cellular proliferation, such as translational capacity, cell cycle progression, and macromolecular biosynthesis. The most enriched KEGG pathways were ribosome biogenesis (70 DAPs), DNA replication (14 DAPs) and proteasome function (27 DAPs). Other enriched pathways included cell cycle progression, macromolecular biosynthesis, mRNA surveillance, chromatin remodeling, and nucleocytoplasmic transport, reflecting coordinated regulation of processes essential for cell growth and division. In contrast, the degradation module (Fig. 2B, red, 628 proteins), which increases from TOB to TOZ, was enriched for catabolic and metabolic remodeling KEGG pathways. The most significant enrichment was seen in ATP-binding cassette (ABC) transporters (10 DAPs), followed by Peroxisome proliferator-activated receptor (PPAR) signaling (17 DAPs), calcium signaling (17 DAPs), peroxisome (21 DAPs), gap junction (11 DAPs), galactose metabolism (8 DAPs) and protein digestion and absorption (15 DAPs). These pathways likely support nutrient salvage, stress signaling, and orderly tissue breakdown / recycling during zooid regression. Confirmation of Pro- and Anti-Proliferative Protein Modules During Takeover To support the findings from the first study, a second study was conducted, focusing on the three most biologically distinct stages identified earlier: TOB, SAZ, and TOZ. To increase statistical power and improve proteome coverage, the number of biological replicates was expanded from three to seven per condition. This second study yielded 22,458 unique peptides mapping to 4,015 unambiguous protein groups. This result represents a 32.5% increase in peptide detection and a 27% increase in quantifiable proteins compared to the first study. Of the detected proteins, 2,919 were shared across both studies, accounting for 92.5% of the first and 72.7% of the second study. An additional 1,096 proteins were uniquely identified in the second study, while 236 were exclusive to the first (Fig. 3A). The improved detection is likely due to both the increased number of replicates and the use of a more inclusive spectral library, which was generated directly from DIA data [41] as opposed to separate DDA library construction in the first study. PCA of the 2,020 DAPs identified in the second study showed clear separation among TOB, SAZ, and TOZ, consistent with the pattern observed in the first study, with TOB and TOZ exhibiting the most distinct proteome differences (Fig. 3B). STRING enrichment analysis highlighted strong enrichment of biosynthetic and proliferative KEGG pathways, including ribosome (92 proteins), spliceosome (82 proteins), RNA transport (62 proteins), and DNA replication (19 proteins), along with multiple DNA repair pathways, RNA degradation, and proteasome activity, which were associated with primary buds. In contrast, phagosome (24 proteins), peroxisome (41 proteins), and lysosome (42 proteins) KEGG pathways were enriched in senescing zooids (Fig. 3C). Additional Gene Ontology (GO) terms associated with these functions, beyond those captured by KEGG pathways, were also significantly enriched or depleted and support the KEGG pathway trends (Supplementary Table 1, STRING permalink: https://version-12-0.string-db.org/cgi/globalenrichment?networkId=bR3BtYEnv3rk). Cell Cycle and Senescence Associated Proteins To identify proteins that may regulate the transition between proliferation and senescence, stage-specific expression was compared between TOB and TOZ, which are the two stages that showed the greatest proteome differences. DAPs that contributed to the cell cycle (ko04110) and cellular senescence (ko04218) KEGG pathways were further examined. To reduce redundancy, isoforms that shared the same KEGG annotation were collapsed, retaining a single representative per protein group. Using a significance threshold of FDR < 0.05 for TOB versus TOZ comparisons, 16 DAPs were identified in the cell cycle pathway (Table 1) and 15 in the cellular senescence pathway (Table 2). These proteins function in DNA replication, cell cycle checkpoints, chromatin remodeling, and as stress- and signaling-related regulators, with CDK1 and CDK2 represented in both pathways. DNA replication factors exhibited the most pronounced changes with proliferating cell nuclear antigen (PCNA) showing one of the greatest differential abundances between TOB and TOZ (log₂FC = 3.1, FDR = 8.8 × 10⁻¹⁰) (Fig. 4A). All six subunits of the minichromosome maintenance complex (MCM2, MCM3, MCM4, MCM5, MCM6, and MCM7), which form the core replicative helicase required for DNA unwinding during S phase, were greatly upregulated in TOB, suggesting increased licensing and replication initiation activity. CDK1 and CDK2 were also significantly upregulated (log₂FC = 1.9 and 1.5; FDR = 4 × 10⁻⁵ and 2 × 10⁻⁵) (Fig. 4B-C), consistent with progression through the G 2 /M and G 1 /S checkpoints, respectively. S-phase kinase-associated protein 1 (SKP1), a core component of the SCF E3 ubiquitin ligase complex, was increased in abundance in TOB (log₂FC = 1.1, FDR = 1.6 × 10⁻⁴) (Fig. 4D). Other proteins involved in mitotic checkpoint control and chromatid cohesion were also enriched. Structural maintenance of chromosomes protein 3 (SMC3), a subunit of the cohesin complex necessary for sister chromatid pairing, was more abundant in TOB (log₂FC = 1.0, FDR = 0.01). BUB3 mitotic checkpoint protein (BUB3), a conserved spindle assembly checkpoint regulator, was highly upregulated in TOB (log₂FC = 1.6, FDR = 2.1 × 10⁻⁸) (Fig. 4E), reflecting the need for mitotic surveillance during rapid proliferation. Histone deacetylase 2 (HDAC2), a class I histone modifier involved in chromatin compaction, was also significantly upregulated in TOB (log₂FC = 1.5, FDR = 3.2 × 10⁻⁶) (Fig. 4F). Notably, Histone deacetylase 1 (HDAC1) was not detected in the study, suggesting a potentially dominant role for HDAC2 in regulating chromatin state during cell cycle transitions in this system. Finally, several proteins annotated as members of the 14-3-3 protein family showed increased abundance in TOB. Although their specific isoforms could not be resolved from the blastp ortholog annotation, their enrichment suggests a potential regulatory role in checkpoint signaling or cell cycle coordination during blastogenesis. Within the cellular senescence pathway, several proteins displayed significant differential abundance between TOB and TOZ. The prolyl isomerase FK506-binding protein 4 (FKBP4), which has roles in protein folding and chaperone-mediated regulation, showed the strongest upregulation in TOB (log₂FC = 2.5, FDR = 2.9 × 10⁻⁹). Chromatin remodelers, histone-binding proteins RBBP7 and RBBP4, were also elevated in TOB (log₂FC = 1.8 and 1.0; FDR = 2.0 × 10⁻⁶ and 5.0 × 10⁻⁴), suggesting enhanced histone binding and nucleosome remodeling capacity during active proliferation. In addition to cell-cycle regulators, multiple proteins involved in translation were significantly enriched in TOB. Eukaryotic elongation factors (EEF2, EEF2K, EEF1G, EEF1D, EEF1B2) and initiation factors, including subunits of the eukaryotic translation initiation factor 3 (eIF3) complex (EIF3A-M), were consistently upregulated, indicating enhanced translational capacity in proliferative buds. These changes suggest that increased biosynthetic output is a key feature of TOB, supporting the elevated demand for protein synthesis during rapid cell division (Table 3). In contrast, multiple signaling and metabolic regulators were downregulated in TOB and enriched in TOZ. These included MAPK-activated protein kinase 3 (MK3) and B-Raf proto-oncogene serine/threonine kinase (BRAF) (log₂FC = -0.8 and -0.9; FDR = 1.4 × 10⁻² and 4.9 × 10⁻²), which are components of mitogen-activated protein kinase (MAPK) signaling. Similar regulation was observed for AKT Serine/Threonine Kinase (AKT1) (log₂FC = -1.1, FDR = 5.6 × 10⁻³), a key kinase in the PI3K-AKT pathway. Collectively, the results point to attenuation of mitogenic signaling in regressing zooids. Several calcium-binding proteins, including CALM2, CALML3, CALML4, and CALML6, were also significantly decreased in TOB (log₂FC = -0.6 to -1.7; FDR < 0.05), suggesting reduced calcium-dependent regulation of stress responses and apoptosis during high proliferation. Additional senescence-associated proteins, such as the adenine nucleotide translocator SLC25A31 (log₂FC = -0.7, FDR = 3.9 × 10⁻²), the cysteine protease calpain-1 (CAPN1) (log₂FC = -1.2, FDR = 6.7 × 10⁻⁴), and the small GTPase related RAS viral oncogene homolog 2 (RRAS2) (log₂FC = -1.3, FDR = 2.7 × 10⁻²), were all enriched in TOZ, highlighting mitochondrial, proteolytic, and Ras-family signaling contributions to the senescent phenotype. To facilitate cumulative comprehension and visualization of how these differentially abundant proteins interact, TOB vs. TOZ comparisons were mapped onto a curated network of signaling and regulatory pathways (Fig. 5). This pathway-level overview highlights the coordinated upregulation of DNA replication and cell-cycle regulators, including PCNA, CDK1/2, and the MCM complex, alongside increased activity of chromatin remodeling (Nucleosome Remodeling and Deacetylase [NuRD]) and proteolytic SKP1–Cullin–F-box (SCF) complexes. In contrast, canonical mitogen signaling nodes (RAS-BRAF-MEK-ERK, RRAS2-PI3K-AKT1-mTORC1) and the stress-responsive kinase MK3 were downregulated in TOB, consistent with a shift away from external mitogen input toward chromatin- and checkpoint-based control. Together, these findings provide a system-level proteomic framework and identifies key nodes within this framework that distinguish proliferative TOB from senescent TOZ. Discussion Proteome Changes During the Blastogenic Cycle The extensive proteomic remodeling which involved nearly half of the detected proteome observed across the blastogenic cycle of B. schlosseri reflects major biological transitions that define its stages of asexual reproduction. PCA results of the first study showed that, while each of the four adult stage are distinct from each other in terms of their proteome, the most significant molecular changes happen at the takeover stage between TOZ and TOB where adult zooids degenerate and primary buds transform into new zooids. Co-expression analyses corroborate with this pattern, the sharp co-expression transition from TOB to SAZ from both modules reflects the accelerated progression of the takeover phase into the adult stage, during which primary buds migrate to the colony center, open their siphons, and rapidly mature into adult zooids capable of independent feeding within just 36 hours [ 42 ]. During takeover, adult zooids regress through apoptosis and phagocytosis, while emerging buds initiate differentiation and proliferation. Cellular debris is cleared by circulating phagocytes and reutilized by developing buds as part of a colony-wide recycling mechanism [ 43 ]. Stem cell migration also occurs at this stage. Although somatic tissues experience weekly waves of apoptosis and phagocytosis, B. schlosseri colonies are capable of long-term regeneration and can live for many years. This longevity is supported by the repeated trafficking of stem cells into new niches, which protects them from destruction and enables sustained self-renewal [ 3 ]. These dynamics suggest that the timing of cell cycle re-entry and tissue-specific differentiation is tightly regulated throughout the blastogenic cycle particularly at the takeover stage. Functional Enrichment of a Coordinated Proliferation Program in TOB Functional enrichment analysis of the two co-expression modules revealed their association with proliferation and degradation programs. Enrichment of DNA replication and cell cycle-related functions in the proliferation module supports the presence of tightly controlled mitotic programs in emerging buds [ 44 ]. These processes are critical for maintaining genomic integrity while passing through cell cycle checkpoints and coordinating precise cell division across the colony. High telomerase activity reported in early budding stages further underscores the need for robust proliferative capacity to sustain continuous regeneration [ 45 ]. The proteasome also emerged as a central player, enriched in the proliferation module due to its role in protein turnover, proteostasis quality control, and cell cycle progression. Although proteasomal function emphasizes protein degradation, proteasome activation is also critical for proteostasis quality control in highly proliferative cells and its activation is consistent with the regulation of cyclins and cyclin-dependent kinase inhibitors via the ubiquitin-proteasome system (UPS) [ 46 , 47 ]. In a colonial invertebrate like B. schlosseri , synchronized regression and renewal likely depend on such precise proteostasis. Supporting this notion, stress response and protein quality control pathways were co-enriched, suggesting that proteasome-mediated degradation maintains developmental fidelity under fluctuating physiological conditions [ 48 ]. Enrichment of nucleocytoplasmic transport pathways further suggests active trafficking of regulatory proteins and RNAs between the nucleus and cytoplasm during rapid transitions. Ribosome biogenesis was also enriched during proliferative stages, further supporting a major role for proteostasis control during TOB maturation. Disruptions in ribosome production are known to impair cell growth and trigger cell cycle arrest, underscoring its importance in maintaining proliferative potential [ 49 ]. As a tightly regulated and energy-intensive process, ribosome biogenesis supports sustained protein synthesis, which in turn fuels biomass accumulation, cell cycle progression, and differentiation. In proliferating cells, particularly during development or regeneration, upregulation of ribosomal RNA transcription, processing, and ribosomal protein production ensures sufficient translational capacity to meet the demands of rapid cell division [ 50 ]. These functional signatures in B. schlosseri reinforce the importance of translational and proteasomal control as a key node linking growth signals to cell cycle regulation and tissue homeostasis. Together, these functional enrichments suggest that coordinated upregulation of cell cycle progression and proteostasis molecular machinery during takeover are essential for zooid renewal. Functional Enrichment of a Degradation Program in TOZ In contrast to the proliferation module, enrichment of ATP-binding cassette (ABC) transporters in the degradation module suggests increased membrane transport activity during zooid regression. These transporters may facilitate the controlled removal of metabolic byproducts or the transport of recycled nutrients from donor to acceptor cells, processes that are particularly important during large-scale tissue breakdown and remodeling [ 51 ]. Additional enrichment of peroxisome activity, calcium signaling, and protein digestion and absorption pathways reflects the early activation of catabolic processes that enable the recycling of cellular components to support new tissue development while minimizing inflammation [ 52 ]. Peroxisomal proteins, which are involved in lipid β-oxidation and detoxification of reactive oxygen species, may help mitigate oxidative damage and inflammation during tissue resorption [ 53 ]. This is especially relevant in B. schlosseri , where synchronous degeneration in densely packed zooids may create localized oxidative stress. Calcium signaling, which has major roles in regulating apoptosis, mitochondrial dynamics, and cytoskeletal remodeling [ 54 ], was also enriched during early regression stages but gradually declined. This trend may reflect the resolution of early remodeling events as regenerating tissues stabilize. Colonial ascidians often depend on localized tissue recycling to sustain growth in nutrient-limited environments [ 55 ]. Accordingly, the observed decline in proteases and related enzymes involved in protein degradation likely represents a transition from catabolic resource mobilization to anabolic biosynthesis. The enrichment of catabolic and metabolic remodeling pathways in the degradation module, which is highly expressed in regressing zooids, is consistent with a previous study that reported a markedly higher rate of apoptotic cells in collapsing zooids, particularly within the gut epithelium and the pyloric gland [ 56 ]. These functional modulations revealed by proteomics are consistent with a prior transcriptomic analysis that identified dynamic regulation of apoptosis-related genes across the blastogenic cycle, particularly during pre-takeover and takeover stages [ 57 ]. The current proteomic results extend these findings to the protein level and to a more comprehensive set of proteins, revealing regulation of pathways associated with proteolysis and cytoskeletal remodeling. These findings support the interpretation that zooid resorption is a tightly regulated, energy-coupled process involving coordinated degradation, recycling, and detoxification. In addition, the key proteins driving these processes have been determined. CDK1 as a Central Cell Cycle Regulator CDK1 is a master regulator of the cell cycle, essential for driving cells through the G₂/M transition and mitosis. In complex with cyclin B, CDK1 phosphorylates substrates required for chromatin condensation, nuclear envelope breakdown, and spindle assembly [ 58 ]. Beyond its canonical mitotic functions, CDK1 phosphorylates p53 at Ser315, influencing its stability and transcriptional activity and thereby linking cell cycle progression to the DNA damage response to maintain genomic integrity in proliferating cells [ 59 ]. CDK1’s functional centrality is further underscored by its ability to sustain cell cycle progression in yeast as the sole CDK [ 25 ] and to drive the mammalian cell cycle in the absence of other CDKs [ 60 ]. In this study, CDK1 displayed the most pronounced stage-specific increase, occupying a central position in the pathway network and connecting directly to cyclin B and the Anaphase-Promoting Complex/cyclosome (APC/C) complex to coordinate mitotic entry and exit. Its upregulation in TOB indicates active licensing of cells to progress through G₂/M, consistent with the proliferative phenotype of primary buds. CDK2 was also significantly elevated, pointing to enhanced G₁/S transition and S-phase progression. CDK2, when bound to cyclins E or A, drives replication origin licensing and nucleotide biosynthesis [ 61 ]. Although CDK2 is functionally redundant with CDK1 in some mammalian systems [ 62 ], its upregulation here suggests that both kinases cooperate to fine-tune replication timing and maintain genome stability. The strong increase in PCNA, a DNA polymerase processivity factor and widely used marker of proliferation [ 63 ], further supports robust engagement of the replication machinery. PCNA also coordinates mismatch repair and translesion synthesis [ 64 ], suggesting that buds not only increase DNA synthesis but also enhance genome maintenance during rapid proliferation. Together, the combined upregulation of CDK1, CDK2, and PCNA points to a streamlined but highly active cell cycle network that may compensate for the apparent absence of the CDK4-CDKN2 axis reported missing in urochordates [ 65 ]. Additional CDKs such as CDK5 and CDK20 were detected but unchanged in abundance, further supporting CDK1’s dominant role as the primary driver of proliferation during blastogenesis. DNA Replication Licensing All members of the MCM2-7 complex were significantly upregulated in TOB, consistent with their role as essential regulators of DNA replication licensing during the G₁ phase. The MCM2-7 complex forms the core of the pre-replicative helicase that is loaded onto origins of replication by the origin recognition complex (ORC), cell division cycle 6 (CDC6), and chromatin licensing and DNA replication factor (CDT1) [ 66 , 67 ]. Once recruited in late mitosis and early G₁, MCM2-7 marks replication origins as competent for DNA synthesis, a prerequisite for S-phase entry. In mammalian systems, CDK2-Cyclin E activity triggers the transition from licensing to initiation by phosphorylating licensing factors and activating the MCM helicase, thereby ensuring once-per-cell-cycle replication [ 68 , 69 ]. The increased abundance of MCM2-7 in proliferative buds suggests a robust replication licensing program, reinforcing their identity as the most actively dividing stage. Because defects in MCM loading can cause replication stress and genomic instability, elevated MCM2-7 may help safeguard genome integrity during the rapid and repeated cell cycles characteristic of B. schlosseri blastogenesis [ 70 , 71 ]. In this context, enhanced licensing capacity could reduce the likelihood of replication fork collapse and ensure faithful transmission of genetic material across successive budding cycles. Checkpoint Surveillance BUB3 was the only spindle assembly checkpoint protein detected in the study and was significantly upregulated in TOB. In the canonical mitotic checkpoint complex (MCC), BUB3 partners with mitotic arrest deficient 2 (MAD2) and spindle checkpoint protein BUBR1 to sequester cell division cycle 20 (CDC20), thereby delaying anaphase onset until all kinetochores are properly attached to spindle microtubules [ 72 ]. Through CDC20 sequestration, the MCC inhibits APC/C, preventing premature degradation of mitotic cyclins and sustaining CDK1 activity during metaphase to ensure faithful chromosome segregation. The elevated abundance of BUB3 suggests that primary buds maintain robust checkpoint signaling to preserve chromosomal stability during rapid mitotic cycles. Beyond its role in mitosis, BUB3 also contributes to genome stability during interphase by supporting efficient telomere replication and preventing replication stress [ 73 ]. This dual functionality may be especially important for B. schlosseri , where repeated rounds of blastogenesis require both faithful chromosome segregation and maintenance of telomere integrity. Given that chromosomal instability is a major barrier to long-term culture viability, sustained BUB3 activity could be critical for supporting both genomic fidelity and proliferative capacity, making it an informative biomarker and potential target for functional studies. Chromatin Remodeling Multiple subunits of the NuRD complex, including HDAC2, RBBP4, and RBBP7, were significantly upregulated in TOB, indicating coordinated activation of the chromatin remodeling machinery during budding. As the catalytic core, HDAC2 removes acetyl groups from histones to promote chromatin condensation and transcriptional repression of cell-cycle inhibitors such as p21 and p57 Kip2 , thereby facilitating CDK2 activation and G 1 /S progression [ 74 ]. Results from mammalian studies showed that loss of HDAC2 results in G 1 arrest [ 75 , 76 ], underscoring its importance for cell-cycle re-entry. In addition to histone deacetylation, HDAC2 also acts on non-histone substrates, linking NuRD activity to DNA replication and repair [ 77 ]. The concurrent upregulation of HDAC2, RBBP4, and RBBP7 suggests that TOB buds reinforce chromatin-mediated transcriptional control to sustain a proliferative transcriptional landscape. Notably, only HDAC2 was detected in this study, while HDAC1 was absent. This may indicate that HDAC2 is the primary histone deacetylase active during blastogenesis in B. schlosseri . The clinical relevance of HDAC2 overexpression in multiple cancers, where it drives proliferation and therapy resistance [ 78 , 79 ], further highlights its potential as a target for modulating proliferation and enhancing primary cell culture longevity in colonial tunicates. Proteostasis and Degradation SKP1 was significantly upregulated in TOB and represents a core scaffold of the SCF (SKP1-Cullin-F-box) E3 ubiquitin ligase complex. SKP1 links CUL1, RBX1, and SKP2, components that collectively mediate targeted proteolysis of cell cycle regulators. SCF complexes are critical for G₁/S transition, where they promote the ubiquitination and degradation of CDK inhibitors such as p21 and p27, thereby allowing CDK activation and S-phase entry [ 80 ]. They also ensure timely turnover of replication licensing factors and misfolded proteins, preventing re-replication and maintaining proteostasis [ 81 ]. The elevation of SKP1 in TOB is therefore consistent with a regulatory state that prioritizes rapid but orderly cell cycle progression. From a translational perspective, SKP1 and SCF dysregulation have been implicated in multiple cancers, including lung and prostate cancer, and pharmacological targeting of SKP1 has shown anti-tumor activity in preclinical models [ 82 ]. Its conserved and central role across species makes SKP1 a compelling candidate for manipulation in B. schlosseri to promote proliferative competence while preserving genome integrity. Biosynthesis and Translational Activation Primary buds exhibited significant upregulation of elongation factors along with multiple eIF3 subunits, indicating broad activation of the translational machinery. This upregulation suggests that buds increase biosynthetic capacity to meet the demands of accelerated proliferation. In metazoans, activation of biosynthetic pathways is commonly coordinated by the mTOR pathway, which promotes translation initiation and elongation through phosphorylation of targets such as S6K1 and 4E-BP1 [ 83 ]. The broad increase in initiation and elongation factors strongly support enhanced biosynthetic output resembling the downstream effects of mTOR activity. However, the molecular details associated with such enhanced biosynthetic activity likely differ from canonical PI3K-AKT-mTORC1 activation since in B. schlosseri RPS6KB2 (encoding S6K2) was detected but not significantly different in abundance. Integration of mitogen signaling, cell cycle checkpoint control, and chromatin regulation Despite the robust biosynthetic activation, several nodes of canonical mitogenic signaling were significantly downregulated in TOB relative to TOZ, including RRAS2, BRAF, and AKT1, which serve as central drivers of the RAS-BRAF-MEK-ERK and RRAS2-PI3K-AKT1-mTORC1 pathways. In mammalian systems, sustained PI3K-AKT activation can shift cells from growth toward senescence programs via mTORC1-dependent p53 accumulation and p21 induction, establishing a non-proliferative endpoint despite upstream “growth” signaling [ 84 ]. In parallel, AKT-driven increases in ROS promote replicative or premature senescence and can sensitize cells to ROS-mediated apoptosis, further illustrating that these pathways often mediate stress responses rather than cell-cycle entry when chronically engaged [ 85 ]. The reduction of these signaling nodes in proliferative buds thus suggests that in B. schlosseri the downstream pro-proliferative effects of these mitogen-dependent G₁ circuits are predominately mediated by activation (i.e. phosphorylation of AKT) rather than protein abundance and restricting levels of key pathway nodes may protect against the anti-proliferative effects of hyperactivation. An additional explanation is chromatin-level control may be more consequential in TOB. The upregulation of HDAC2, a catalytic subunit of the NuRD complex, supports this view, as HDAC2 represses the transcription of CDK inhibitors such as p21, thereby indirectly activating CDK2 and facilitating G₁/S transition. This chromatin-based control provides an alternative route for sustaining proliferation when canonical mitogen signaling nodes are reduced. By contrast, the higher abundance of RRAS2, BRAF, and AKT1 in TOZ may reflect a shift to a non-proliferative role for these pathways during the takeover stage. Rather than driving cell-cycle progression, their activity in this context may help delay cell death in certain compartments, coordinate tissue breakdown in a regulated manner, buffer stress responses such as oxidative stress or caspase activation to minimize inflammatory signals or even induce apoptosis by hyperactivation [ 86 – 88 ]. In mammalian systems, Ras and PI3K-AKT signaling are well-established mediators of cell survival, acting through inhibition of pro-apoptotic proteins, suppression of caspase activation, and modulation of Forkhead box O (FoxO) transcription factors [ 89 , 90 ]. More recently, in vivo work in Drosophila demonstrated that Akt1 is required for cells to survive executioner caspase activation and contribute to tissue regeneration [ 91 ], providing a direct precedent for the deployment of these pathways in degenerative or stress-laden contexts rather than for promoting proliferative capacity. Taken together, these findings raise the possibility that the differential protein abundance of these mitogen pathway components contribute to alternative roles between stages with Ras/AKT/BRAF signaling supplementing chromatin-based mechanisms in proliferative buds, while regressing zooids engage the pathway in a stress-adaptive, non-proliferative role [ 91 , 92 ]. Further supporting this conclusion is the significant downregulation of MK3 (MAPKAPK3) in TOB relative to TOZ. As a downstream effector of the p38 MAPK pathway, MK3 integrates stress signals to modulate cell-cycle checkpoints. In the G₁ phase, MK3 can promote the transcriptional upregulation of p21, thereby restraining CDK2 activity, while in G₂ MK3 inhibits CDC25 to block premature CDK1 activation, consistent with known roles of p38-MK2/3 signaling in checkpoint enforcement [ 93 ]. Through these mechanisms, MK3 enforces stress-dependent checkpoints at both G₁/S and G₂/M transitions. Its reduced abundance in TOB suggests a relaxation of stress-responsive checkpoint signaling, consistent with a pro-proliferative state in emerging buds. Candidate Proteins for Functional Manipulation of cell proliferation Efficient cell cycle re-entry, particularly through the G 1 /S transition, is a major bottleneck in establishing proliferative primary cultures [ 94 ]. The present study highlights several proteins whose regulation in proliferative buds nominates them as strong candidates for manipulation to sustain long-term proliferation of cell cultures. CDK1 emerges as the primary driver of proliferation, with marked upregulation and direct control over G₂/M progression, while CDK2 supports G₁/S transition and replication initiation. Given the absence of CDK4/6 in B. schlosseri ’s genome, CDK1 and CDK2 likely assume broader responsibility for both G₁/S and G₂/M transitions, making them especially compelling targets for manipulation. PCNA, a processivity factor and reliable marker of proliferation, provides a useful proxy for confirming active DNA synthesis and could serve as a readout of successful cell-cycle re-entry. In parallel, HDAC2 (NuRD complex) and SKP1 (SCF complex) may enhance immortalization prospects by repressing CDK inhibitors such as p21, thereby indirectly sustaining CDK2 activity. By contrast, pathways that were downregulated in proliferative buds, including RAS/BRAF/MEK/ERK and PI3K/AKT1/mTORC1, are not supported by this study as drivers of proliferation during the blastogenic cycle. This finding likely reflects the specific developmental context of budding, where the effects of canonical mitogen inputs are not yet clear. However, this conclusion does not preclude their relevance under cell culture conditions, which impose a very different selective environment. For example, β-catenin, which is encoded in the B. schlosseri genome, may still represent a viable manipulation target despite its lack of enrichment in this dataset, as its functional role often requires only modest protein abundance changes. Overall, these findings identify CDK1, CDK2, HDAC2, SKP1, and PCNA as the most compelling candidates for promoting cell-cycle re-entry and sustaining proliferation in B. schlosseri primary cultures. In addition to identifying molecular targets, our results suggest that primary buds should be prioritized over adult zooids as starting material for cell cultures, since buds display the strongest activation of proliferative and biosynthetic pathways. Conclusion This study provides the first proteome-wide map of the B. schlosseri blastogenic cycle at the individual zooid level, revealing stage-specific shifts in protein abundance that underpin proliferation of buds and regression of adult zooids during blastogenesis. Primary buds are characterized by upregulation of CDK1, CDK2, the MCM2-7 complex, and PCNA, together with chromatin remodeling and translational machinery, consistent with an active biosynthetic program driving rapid proliferation. In contrast, regressing zooids engage stress-induced and senescence-associated regulators, highlighting a tightly regulated process of orderly tissue degradation and recycling that minimizes inflammation. These findings position B. schlosseri as a powerful model for studying the coordination of proliferation and programmed degeneration in a naturally cycling developmental system. The study further nominates CDK1, CDK2, HDAC2, SKP1, and NuRD components as promising candidates for functional testing towards immortalization of primary cultures and validates B. schlosseri PCNA as a reliable molecular marker of proliferation. Ultimately, this work provides mechanistic insight into colonial budding, lays out a roadmap of molecular targets for establishing immortalized cell lines in a colonial tunicate, and provides a foundation for future studies on post-translational regulation and stem cell activity. Methods Animal Husbandry Wild colonies of B. schlosseri were collected from floating docks at Berkeley Marina, California (United States). Larvae of these wild colonies were generated via sexual reproduction and attached as oozooids to glass slides at the UC Davis Cole B facility within one week after field collection. These lab-born colonies were then reared adhering to glass and kept vertically in 2.8 L glass tanks with 30ppt standing artificial sea water (ASW) at a constant temperature of 20 °C and aerated by air stones as described previously [95]. All genotypes used in this study were raised from individually spawned, sexually reproduced oozooids and reared in separate tanks to avoid competition [96]. Colonies were fed twice a week with a combination of live algae ( Dunaliella, Tetraselmis, Isochry sis and Nannochloropsis ) and Roti-Rich Liquid Invertebrate Food (Florida Aqua Farms). ASW for each tank was fully changed every week, and colonies were gently cleaned once a week using soft brushes. All experimental colonies have been born and reared in stable lab conditions for at least 3 months, were in good health, and reproduced asexually via regular one-week blastogenic cycles. Tissue Dissection Colonies were carefully cleaned and photographed before dissection under a stereomicroscope (Leica EZ4 W). To determine the appropriate blastogenic stages, the development of buds and zooids was monitored daily. A healthy colony completes a full blastogenic cycle every 7 to 8 days. Using two sterile size 0 insect pins, the colony tunic was sliced open from the common atrial siphon to the oral siphon. Individual zooids were therefore exposed and carefully removed from the colony. Samples were kept on ice during dissection and snap-frozen in liquid nitrogen immediately afterwards, then transferred to a -80 °C freezer for storage. A total of at least 50 zooids collected from each of the four blastogenic stages (A, B, C, and Takeover) and 70 primary buds from the takeover stage for each genotype were pooled per sample to ensure sufficient protein recovery. A total of three genotypes were used for the first study for five blastogenic stages and a total of seven genotypes were used for the second study for proteomics of TOB, SAZ, and TOZ stages. Sample Preparation Sample preparations were performed as previously described [11] with few modifications. Briefly, tissues were homogenized in lysis buffer (8 M urea, 50 mM ammonium bicarbonate (Ambic)) using 1 mm zirconium beads (Benchmark D1032010) and shaking in a microtube homogenizer (Benchmark beadbag) at 3500 rpm for 30 seconds. Proteins taken from the supernatant were then reduced using 5mM dithiothreitol (DTT) for 10 min at 60°C and alkylated with 15mM iodoacetamide (IAA) in the dark at room temperature for 30 min. Remaining free IAA was quenched by further increasing DTT to 10mM. After protein quantification, urea was diluted with 50 mM Ambic and subjected to trypsin/Lys-C (Thermofisher A40007) digestion at a 1:50 trypsin to protein ratio at 37°C for 3 hours. Post-digestion peptide cleanup was performed using Pierce C-18 spin columns (Thermo Scientific 89870) according to the manufacturer protocol. Peptide concentration was quantified using Pierce fluorometric Quantitative Peptide Assay (Thermo Scientific 23290) before speedvac buffer exchange to 0.1% formic acid in LCMS water for LCMS analysis. LC-MS/MS Acquisition Liquid chromatography-mass spectrometry (LC-MS) acquisitions were performed following established protocols for quantitative label-free proteomics [11]. Briefly, 100 ng of total peptide per sample was injected using a Bruker nanoElute 2 UPLC system operated in single column mode and equipped with a 25 cm x 150 µm x 1.5 µm Pepsep XTREME C18 reversed-phase analytical column (Bruker Daltonics 1893476). Peptide separation was achieved using a linear gradient of 3% to 33% acetonitrile in 0.1% formic acid over 60 minutes at a flow rate of 600 nL/min. The column temperature was maintained at 50°C. Mass spectrometry was performed using a UHD-Quadrupole time-of-flight (QTOF) mass spectrometer operating in positive ion mode (Bruker Impact II) interfaced online with the UPLC via a captive spray ionization source (Bruker CSI). For the first study, each sample was acquired twice, first in DDA mode to enable construction of a spectral library for these samples with Fragpipe [97], and again using DIA acquiring MS2-only spectra. For the second study, only DIA was used but each DIA scan cycle of MS2 windows was supplemented by a corresponding MS1 spectrum to enable direct spectral library construction from these data. For the first study, each scan cycle consisted of 74 scan windows (390 - 1130 m/z) having a width of 10 ± 0.5 m/z and collected at a frequency of 50 Hz. For the second study, the same scan cycle parameters were applied except that each 1.5 sec scan cycle was preceded by acquisition of an MS1 spectrum obtained at the same scan rate (50 Hz) to enable annotation of corresponding precursor peptides and spectral library generation with Fragpipe without the need for a separate DDA run. Data Processing Mass spectrometry raw DDA data for study 1 were processed using FragPipe 22.0, which integrates the MSFragger search engine for peptide identification and quantification [98]. A spectral library was generated from the DDA runs and applied to the corresponding DIA data in Skyline [99] to extract and normalize transition peak areas by sample median abundance. Spectral libraries were filtered in Skyline to remove interferences and non-diagnostic ions as previously described [11]. For Study 2, DIA data were analyzed directly in FragPipe (v22.0) to generate a spectral library without additional DDA acquisition. The resulting library was imported into Skyline for filtering to exclude interferences and low-abundance proteins [11]. Spectral library annotation was based on the predicted B. schlosseri reference proteome from the most recent genome update [100]. Statistical Analysis For relative quantitation all transition peak abundances were exported from Skyline and then normalized and extrapolated to protein abundances using DirectLFQ [101]. Statistical comparisons were performed using the ProLFQua [102] package in R, applying ANOVA with multiple testing correction (FDR < 0.1) for study 1, and ANOVA and linear models with empirical Bayes moderation for study 2 to improve detection of differentially abundant proteins. To assess overall proteomic variation, Principal Component Analysis (PCA) (R package mixOmics) and hierarchical clustering were conducted on DAPs to visualize sample grouping and identify major sources of variation across conditions. Weighted Gene Co-expression Network Analysis Co-expression patterns were examined using Weighted Gene Co-expression Network Analysis (WGCNA) [103] to identify protein modules with coordinated expression changes across the blastogenic cycle. DAPs identified by ANOVA testing (FDR < 0.1) were selected for analysis after multiple testing correction. The soft-thresholding power (β) was determined based on the scale-free topology criterion, and the network was constructed using a "signed" network type, which considers only positive correlations between proteins. The Topological Overlap Matrix (TOM) was calculated with a signed TOMType, and the minimum module size was set to 20. Module detection was performed with the blockwiseModules function in R, and a merge cut height of 0.25 was applied to merge similar modules. Module-trait relationships were examined by correlating module eigengenes (MEs) with sample traits. To visualize the temporal dynamics of module expression across blastogenic stages, the average Log₂-transformed protein intensity for each module was plotted by condition. For each module, the mean Log₂ intensity of all proteins assigned to that module was calculated per biological replicate, and the group average and standard deviation were plotted across blastogenic stages. Functional Analysis Protein sequences derived from the B. schlosseri proteome were functionally annotated using a two-step approach. First, BLASTP searches were performed against the SwissProt database using DIAMOND, with no taxonomic restrictions to assign functional annotations. Only annotations with an E-value < 10 -3 were considered. In addition, eggNOG [104] was used to identify orthologous relationships and retrieve KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotations. For the first study, functional enrichment analyses were performed using the clusterProfiler [105] R package to identify over-represented KEGG pathways within each co-expression module identified by WGCNA. Over-representation analyses (ORA) were conducted using a customized functional database derived from eggNOG annotations. The background set included all proteins from the first study, and protein sets analyzed corresponded to those within each co-expression module identified by WGCNA. KEGG pathway enrichment was assessed using the enrichKEGG function, with the organism parameter set to "ko" (KEGG orthology). Statistical significance was assessed using the Benjamini-Hochberg (BH) multiple testing correction method, with pathways considered significantly enriched if the adjusted p-value (FDR) was < 0.1. To reduce redundancy, affinity propagation clustering was performed on significant pathways using the R package APCluster [106], and enriched pathways were visualized with ggplot2. Pathways that were vertebrate-specific, human disease-specific, or biologically irrelevant to B. schlosseri were manually filtered out prior to visualization. For the second study, differentially abundant proteins (DAPs) between TOB and TOZ were identified as described above and analyzed in STRING for functional enrichment. All significant DAPs were submitted using the “Proteins with Values/Ranks” input option against the predicted B. schlosseri reference proteome [100]. Enrichment results were subsequently examined with emphasis on KEGG pathways. Supplementary Methods Genotyping To confirm that the biological replicates used in this study represent independent genotypes, a panel of 12 polymorphic loci, the fusion-histocompatibility, or f uhc region, was tested across all seven B. schlosseri colonies. The fuhc region is responsible for allorecognition between colonies and encompasses the highly variable fester gene family, with a range of 7-13 alleles per individual according to recent study [107]. Colonies were bred from wild populations and maintained separately under laboratory conditions to ensure consistent environmental exposure during the experimental timeline. Genomic DNA was extracted from tissue samples from each colony using the PureLink Genomic DNA Mini Kit (ThermoFisher Scientific) following the manufacturer’s protocol with a modified 7-hour incubation period. PCR was performed in 25 μL reaction volumes containing 12.5 μL of 2x EmeraldAmp Max HS PCR Master Mix (Takara), 0.5 μL each of forward and reverse primers for each locus, and 11.5 μL of DNA sample (sample volumes were calculated depending on individual DNA concentration to yield 50 ng of DNA and supplemented with MilliQ water to reach 11.5 μL). The thermal cycling protocol included an initial denaturation step at 94°C for 3 minutes, followed by denaturation at 98°C for 10 seconds, annealing at locus-specific temperatures for 30 seconds, extension at 72°C for 30 seconds, a 30 cycle repeat and a final extension at 72°C for 5 minutes. Primer sets used for genotyping are listed in Supplementary Table 2. PCR products were visualized using gel electrophoresis on a 1.5% agarose gel stained with SYBR Safe DNA Gel Stain (ThermoFisher Scientific) and imaged using UVP ChemStudio PLUS (Analytik Jena) with the SYBR Safe emission filter. Allele sizes were compared against the GeneRuler 50 bp DNA Ladder (ThermoFisher Scientific) to identify polymorphic patterns. Each colony was found to have 4 alleles on average in this region at different combinations of loci, confirming each colony represents a distinct genotype. The presence of unique banding patterns at multiple loci, as seen in representative gel images included in Supplemental Fig. S2, confirms the presence of distinct genotypes. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials All MS proteomics data and metadata generated and analyzed in this study have been deposited and are publicly available in PanoramaPublic (https://panoramaweb.org/vwd01kl.url) and ProteomeXchange (PXD065460). Competing interests The authors declare that they have no competing interests. Funding The project is supported by NSF Grant MCB - 2127516. Authors' contributions WD and DK conceived and designed the study. WD performed the experiments and collected the data. WD and MLe conducted proteomic analyses and statistical evaluations. MLe and DK developed software scripts and contributed to data processing. IE carried out genotyping, and IE, BL, and MLi maintained the tunicate colonies in the laboratory. WD drafted the initial manuscript, and DK, MLe, and JH provided critical revisions and editing. DK secured funding and oversaw project administration. Acknowledgements We thank Baruch Rinkevich (Israel Oceanography & Limnological Research, National Institute of Oceanography) and Ayelet Voskoboynik (Hopkins Marine Station, Stanford University) for the advice on rearing B. schlosseri and dissection. We also thank Stefano Tiozzo for the improved reference proteome. References Voskoboynik A, Simon-Blecher N, Soen Y, Rinkevich B, De Tomaso AW, Ishizuka KJ, et al. Striving for normality: whole body regeneration through a series of abnormal generations. The FASEB Journal. 2007;21(7):1335–44. Ricci L, Salmon B, Olivier C, Andreoni-Pham R, Chaurasia A, Alié A, et al. The onset of whole-body regeneration in Botryllus schlosseri: morphological and molecular characterization. Frontiers in Cell and Developmental Biology. 2022;10:843775. Voskoboynik A, Weissman IL. Botryllus schlosseri, an emerging model for the study of aging, stem cells, and mechanisms of regeneration. Invertebrate Reproduction & Development. 2015 Jan 30;59(sup1):33–8. Munday R, Rodriguez D, Di Maio A, Kassmer S, Braden B, Taketa DA, et al. Aging in the colonial chordate, Botryllus schlosseri. Invertebrate Reproduction & Development. 2015 Jan 30;59(sup1):45–50. Tasselli S, Ballin F, Franchi N, Fabbri E, Ballarin L. Expression of genes involved in oxidative stress response in colonies of the ascidian Botryllus schlosseri exposed to various environmental conditions. Estuarine, Coastal and Shelf Science. 2017 Mar 5;187:22–7. Dijkstra J, Simkanin C. Intraspecific response of colonial ascidians to variable salinity stress in an era of global change. Mar Ecol Prog Ser. 2016 June 9;551:215–25. Delsuc F, Brinkmann H, Chourrout D, Philippe H. Tunicates and not cephalochordates are the closest living relatives of vertebrates. Nature. 2006 Feb;439(7079):965–8. Sabbadin A. Osservazioni sullo sviluppo, l’accrescimento e la riproduzione di Botryllus schlosseri (Pallas), in condizioni di laboratorio. Bolletino di zoologia. 1955 Jan;22(2):243–63. Manni L, Zaniolo G, Cima F, Burighel P, Ballarin L. Botryllus schlosseri: A model ascidian for the study of asexual reproduction. Developmental Dynamics. 2007;236(2):335–52. Anselmi C, Kowarsky M, Gasparini F, Caicci F, Ishizuka KJ, Palmeri KJ, et al. Two distinct evolutionary conserved neural degeneration pathways characterized in a colonial chordate. Proceedings of the National Academy of Sciences. 2022 July 19;119(29):e2203032119. Kültz D, Gardell AM, DeTomaso A, Stoney G, Rinkevich B, Rinkevich Y, et al. Deep quantitative proteomics of North American Pacific coast star tunicate (Botryllus schlosseri). PROTEOMICS. 2024;24(15):2300628. Saad MK, Yuen JSK, Joyce CM, Li X, Lim T, Wolfson TL, et al. Continuous fish muscle cell line with capacity for myogenic and adipogenic-like phenotypes. Sci Rep. 2023 Mar 29;13(1):5098. Vaughn JL, Goodwin RH, Tompkins GJ, McCawley P. The establishment of two cell lines from the insectspodoptera frugiperda (lepidoptera; noctuidae). In Vitro. 1977 Apr 1;13(4):213–7. Rinkevich B, Pomponi SA. Advancing marine invertebrate cell line research: four key knowledge gaps. In Vitro CellDevBiol-Animal. 2025 May 1;61(5):493–505. Rabinowitz C, Rinkevich B. Epithelial cell cultures from Botryllus schlosseri palleal buds: accomplishments and challenges. Methods Cell Sci. 2004 Jan 1;25(3):137–48. Qarri A, Kültz D, Gardell AM, Rinkevich B, Rinkevich Y. Improved Media Formulations for Primary Cell Cultures Derived from a Colonial Urochordate. Cells. 2023 Jan;12(13):1709. Hawley‐Nelson P, Vousden KH, Hubbert NL, Lowy DR, Schiller JT. HPV16 E6 and E7 proteins cooperate to immortalize human foreskin keratinocytes. The EMBO Journal. 1989 Dec;8(12):3905–10. Linzer DIH, Levine AJ. Characterization of a 54K Dalton cellular SV40 tumor antigen present in SV40-transformed cells and uninfected embryonal carcinoma cells. Cell. 1979 May 1;17(1):43–52. Bodnar AG, Ouellette M, Frolkis M, Holt SE, Chiu CP, Morin GB, et al. Extension of Life-Span by Introduction of Telomerase into Normal Human Cells. Science. 1998 Jan 16;279(5349):349–52. Hesp K, van der Heijden JME, Munroe S, Sipkema D, Martens DE, Wijffels RH, et al. First continuous marine sponge cell line established. Sci Rep. 2023 Apr 8;13(1):5766. Anoop BS, Puthumana J, Vazhappilly CG, Kombiyil S, Philip R, Abdulaziz A, et al. Immortalization of shrimp lymphoid cells by hybridizing with the continuous cell line Sf9 leading to the development of ‘ Pm LyO- Sf9 .’ Fish & Shellfish Immunology. 2021 June 1;113:196–207. Qin Z, Ji A, Yan M, Liu D, Li X, Hu X, et al. Establishment of the first marine mollusk cell line from scallop ( Chlamys farreri ) trochophore. Aquaculture Reports. 2025 Mar 15;40:102626. Castellano KR, Manner CJ, Kell RM, McAtee RM, Capozzi NM, Wray GA, et al. Genetically tractable embryonic cell lines from sea urchins Lytechinus variegatus and Strongylocentrotus purpuratus. Commun Biol. 2025 Oct 14;8(1):1457. Simcox A, Mitra S, Truesdell S, Paul L, Chen T, Butchar JP, et al. Efficient Genetic Method for Establishing Drosophila Cell Lines Unlocks the Potential to Create Lines of Specific Genotypes. PLOS Genetics. 2008 Aug 1;4(8):e1000142. Nasmyth K. Control of the yeast cell cycle by the Cdc28 protein kinase. Current Opinion in Cell Biology. 1993 Apr 1;5(2):166–79. Chotiner JY, Wolgemuth DJ, Wang PJ. Functions of cyclins and CDKs in mammalian gametogenesis†. Biology of Reproduction. 2019 Sept 1;101(3):591–601. Ma X, Øvrebø JI, Thompson EM. Evolution of CDK1 paralog specializations in a lineage with fast developing planktonic embryos. Frontiers in Cell and Developmental Biology. 2022;9:770939. Goldstein O, Mandujano-Tinoco EA, Levy T, Talice S, Raveh T, Gershoni-Yahalom O, et al. Botryllus schlosseri as a Unique Colonial Chordate Model for the Study and Modulation of Innate Immune Activity. Mar Drugs. 2021 Aug 9;19(8):454. Rosental B, Kowarsky M, Seita J, Corey DM, Ishizuka KJ, Palmeri KJ, et al. Complex mammalian-like haematopoietic system found in a colonial chordate. Nature. 2018 Dec;564(7736):425–9. Cima F, Perin A, Burighel P, Ballarin L. Protection from oxidative stress in immunocytes of the colonial ascidian Botryllus schlosseri: transcript characterization and expression studies. Biological Bulletin. 2017;232(3):199–210. Ben-Hamo O, Rosner A, Rabinowitz C, Oren M, Rinkevich B. Coupling astogenic aging in the colonial tunicate Botryllus schlosseri with the stress protein mortalin. Developmental Biology. 2018 Jan;433(1):33–46. Rodriguez D, Taketa DA, Madhu R, Kassmer S, Loerke D, Valentine MT, et al. Vascular aging in the invertebrate chordate Botryllus schlosseri. Frontiers in Molecular Biosciences. 2021;8:626827. Franchi N, Ballin F, Manni L, Schiavon F, Basso G, Ballarin L. Recurrent phagocytosis-induced apoptosis in the cyclical generation change of the compound ascidian Botryllus schlosseri. Developmental & Comparative Immunology. 2016;62:8–16. Cima F, Manni L, Basso G, Fortunato E, Accordi B, Schiavon F, et al. Hovering between death and life: natural apoptosis and phagocytes in the blastogenetic cycle of the colonial ascidian Botryllus schlosseri. Developmental & Comparative Immunology. 2010;34(3):272–85. Buccitelli C, Selbach M. mRNAs, proteins and the emerging principles of gene expression control. Nature Reviews Genetics. 2020 July 24;1–15. Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, et al. Global quantification of mammalian gene expression control. Nature. 2011 May 19;473(7347):337–42. Root L, Campo A, MacNiven L, Con P, Cnaani A, Kültz D. Nonlinear effects of environmental salinity on the gill transcriptome versus proteome of Oreochromis niloticus. Genomics. 2021;113:3235–49. Wang ZY, Leushkin E, Liechti A, Ovchinnikova S, Mößinger K, Brüning T, et al. Transcriptome and translatome co-evolution in mammals. Nature. 2020 Dec;588(7839):642–7. Leprêtre M, Hamar J, Urias MB, Kültz D. Comparative Proteomics of Salinity Stress Responses in Fish and Aquatic Invertebrates. PROTEOMICS. n/a(n/a):e202400255. Cui M, Cheng C, Zhang L. High-throughput proteomics: a methodological mini-review. Lab Invest. 2022 Nov;102(11):1170–81. Pino LK, Just SC, MacCoss MJ, Searle BC. Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries. Molecular & Cellular Proteomics. 2020 July 1;19(7):1088–103. Sabbadin A, Zaniolo G, Majone F. Determination of polarity and bilateral asymmetry in palleal and vascular buds of the ascidian Botryllus schlosseri. Developmental biology. 1975;46(1):79–87. Lauzon RJ, Ishizuka KJ, Weissman IL. A cyclical, developmentally-regulated death phenomenon in a colonial urochordate. Developmental Dynamics. 1992;194(1):71–83. Ballarin L, Manni L. Stem cells in sexual and asexual reproduction of Botryllus schlosseri (Ascidiacea, Tunicata): an overview. In: Rinkevich B, Matranga V, editors. Stem cells in marine organisms. Dordrecht: Springer Netherlands; 2009. p. 267–80. Laird DJ, Weissman IL. Telomerase maintained in self-renewing tissues during serial regeneration of the urochordate Botryllus schlosseri. Dev Biol. 2004 Sept 15;273(2):185–94. Goldberg AL. Protein degradation and protection against misfolded or damaged proteins. Nature. 2003 Dec;426(6968):895–9. Glickman MH, Ciechanover A. The Ubiquitin-Proteasome Proteolytic Pathway: Destruction for the Sake of Construction. Physiological Reviews. 2002 Apr;82(2):373–428. Tomanek L. Environmental Proteomics: Changes in the Proteome of Marine Organisms in Response to Environmental Stress, Pollutants, Infection, Symbiosis, and Development. Annual Review of Marine Science. 2011 Jan 15;3(Volume 3, 2011):373–99. Destefanis F, Manara V, Bellosta P. Myc as a Regulator of Ribosome Biogenesis and Cell Competition: A Link to Cancer. International Journal of Molecular Sciences. 2020 Jan;21(11):4037. Thomas G. An encore for ribosome biogenesis in the control of cell proliferation. Nat Cell Biol. 2000 May;2(5):E71–2. Rees DC, Johnson E, Lewinson O. ABC transporters: the power to change. Nat Rev Mol Cell Biol. 2009 Mar;10(3):218–27. Ballarin L, Schiavon F, Manni L. Natural Apoptosis During the Blastogenetic Cycle of the Colonial Ascidian Botryllus schlosseri: A Morphological Analysis. jzoo. 2010 Feb;27(2):96–102. Schrader M, Fahimi HD. Peroxisomes and oxidative stress. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 2006 Dec 1;1763(12):1755–66. Berridge MJ, Bootman MD, Roderick HL. Calcium signalling: dynamics, homeostasis and remodelling. Nat Rev Mol Cell Biol. 2003 July;4(7):517–29. Kürn U, Rendulic S, Tiozzo S, Lauzon RJ. Asexual Propagation and Regeneration in Colonial Ascidians. The Biological Bulletin. 2011 Aug;221(1):43–61. Tiozzo S, Ballarin L, Burighel P, Zaniolo G. Programmed cell death in vegetative development: Apoptosis during the colonial life cycle of the ascidian Botryllus schlosseri . Tissue and Cell. 2006 June 1;38(3):193–201. Campagna D, Gasparini F, Franchi N, Vitulo N, Ballin F, Manni L, et al. Transcriptome dynamics in the asexual cycle of the chordate Botryllus schlosseri. BMC Genomics. 2016 Apr 2;17(1):275. Enserink JM, Kolodner RD. An overview of Cdk1-controlled targets and processes. Cell Div. 2010 May 13;5(1):11. Kciuk M, Gielecińska A, Mujwar S, Mojzych M, Kontek R. Cyclin-dependent kinases in DNA damage response. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 2022 May; 1877(3):188716. Santamaría D, Barrière C, Cerqueira A, Hunt S, Tardy C, Newton K, et al. Cdk1 is sufficient to drive the mammalian cell cycle. Nature. 2007 Aug;448(7155):811–5. Honda R, Lowe ED, Dubinina E, Skamnaki V, Cook A, Brown NR, et al. The structure of cyclin E1/CDK2: implications for CDK2 activation and CDK2‐independent roles. The EMBO Journal. 2005 Feb 9;24(3):452–63. Fagundes R, Teixeira LK. Cyclin E/CDK2: DNA replication, replication stress and genomic instability. Frontiers in Cell and Developmental Biology. 2021;9:774845. Iatropoulos MJ, Williams GM. Proliferation markers. Experimental and Toxicologic Pathology. 1996 Feb 1;48(2):175–81. Kelman Z. PCNA: structure, functions and interactions. Oncogene. 1997 Feb;14(6):629–40. Yuki S, Sasaki S, Yamamoto Y, Murakami F, Sakata K, Araki I. Evolution of the Cdk4/6–Cdkn2 system in invertebrates. Genes to Cells. 2024;29(11):1037–51. Maiorano D, Lutzmann M, Méchali M. MCM proteins and DNA replication. Current Opinion in Cell Biology. 2006 Apr 1;18(2):130–6. Bell SP, Dutta A. DNA Replication in Eukaryotic Cells. Annual Review of Biochemistry. 2002 July 1;71(Volume 71, 2002):333–74. Diffley JFX. Regulation of Early Events in Chromosome Replication. Current Biology. 2004 Sept 21;14(18):R778–86. Sclafani RA, Holzen TM. Cell Cycle Regulation of DNA Replication. Annual Review of Genetics. 2007 Dec 1;41(Volume 41, 2007):237–80. Ge XQ, Jackson DA, Blow JJ. Dormant origins licensed by excess Mcm2–7 are required for human cells to survive replicative stress. Genes Dev. 2007 Dec 15;21(24):3331–41. Ibarra A, Schwob E, Méndez J. Excess MCM proteins protect human cells from replicative stress by licensing backup origins of replication. Proceedings of the National Academy of Sciences. 2008 July;105(26):8956–61. Larsen NA, Al-Bassam J, Wei RR, Harrison SC. Structural analysis of Bub3 interactions in the mitotic spindle checkpoint. Proceedings of the National Academy of Sciences. 2007 Jan 23;104(4):1201–6. Li F, Kim H, Ji Z, Zhang T, Chen B, Ge Y, et al. The BUB3-BUB1 Complex Promotes Telomere DNA Replication. Mol Cell. 2018 May 3;70(3):395-407.e4. Segré CV, Chiocca S. Regulating the Regulators: The Post-Translational Code of Class I HDAC1 and HDAC2. BioMed Research International. 2011;2011(1):690848. Harms KL, Chen X. Histone Deacetylase 2 Modulates p53 Transcriptional Activities through Regulation of p53-DNA Binding Activity. Cancer Res. 2007 Apr 4;67(7):3145–52. Wilting RH, Yanover E, Heideman MR, Jacobs H, Horner J, van der Torre J, et al. Overlapping functions of Hdac1 and Hdac2 in cell cycle regulation and haematopoiesis. EMBO J. 2010 Aug 4;29(15):2586–97. Miller KM, Tjeertes JV, Coates J, Legube G, Polo SE, Britton S, et al. Human HDAC1 and HDAC2 function in the DNA-damage response to promote DNA nonhomologous end-joining. Nat Struct Mol Biol. 2010 Sept;17(9):1144–51. Weichert W, Röske A, Gekeler V, Beckers T, Stephan C, Jung K, et al. Histone deacetylases 1, 2 and 3 are highly expressed in prostate cancer and HDAC2 expression is associated with shorter PSA relapse time after radical prostatectomy. Br J Cancer. 2008 Feb;98(3):604–10. Jung KH, Noh JH, Kim JK, Eun JW, Bae HJ, Xie HJ, et al. HDAC2 overexpression confers oncogenic potential to human lung cancer cells by deregulating expression of apoptosis and cell cycle proteins. Journal of Cellular Biochemistry. 2012;113(6):2167–77. Bai C, Sen P, Hofmann K, Ma L, Goebl M, Harper JW, et al. SKP1 Connects Cell Cycle Regulators to the Ubiquitin Proteolysis Machinery through a Novel Motif, the F-Box. Cell. 1996 July 26;86(2):263–74. Silverman JS, Skaar JR, Pagano M. SCF ubiquitin ligases in the maintenance of genome stability. Trends in Biochemical Sciences. 2012 Feb 1;37(2):66–73. Li X, Mamouni K, Zhao R, Bai L, Chen Y, Wu Y, et al. Novel Skp1 inhibitor has potent preclinical efficacy against castration-resistant prostate cancer. Br J Cancer. 2025 June;132(12):1188–99. Hay N, Sonenberg N. Upstream and downstream of mTOR. Genes Dev. 2004 Aug 15;18(16):1926–45. Astle MV, Hannan KM, Ng PY, Lee RS, George AJ, Hsu AK, et al. AKT induces senescence in human cells via mTORC1 and p53 in the absence of DNA damage: implications for targeting mTOR during malignancy. Oncogene. 2012 Apr;31(15):1949–62. Nogueira V, Park Y, Chen CC, Xu PZ, Chen ML, Tonic I, et al. Akt determines replicative senescence and oxidative or oncogenic premature senescence and sensitizes cells to oxidative apoptosis. Cancer Cell. 2008 Dec 9;14(6):458–70. Gao Y, Zhang D, Wang F, Zhang D, Li P, Wang K. BRAF V600E protect from cell death via inhibition of the mitochondrial permeability transition in papillary and anaplastic thyroid cancers. J Cell Mol Med. 2022 July;26(14):4048–60. Xu W, Zheng H, Fu Y, Gu Y, Zou H, Yuan Y, et al. Role of PI3K/Akt-Mediated Nrf2/HO-1 Signaling Pathway in Resveratrol Alleviation of Zearalenone-Induced Oxidative Stress and Apoptosis in TM4 Cells. Toxins (Basel). 2022 Oct 26;14(11):733. Balmanno K, Cook SJ. Tumour cell survival signalling by the ERK1/2 pathway. Cell Death Differ. 2009 Mar;16(3):368–77. Downward J. Ras signalling and apoptosis. Current Opinion in Genetics & Development. 1998 Feb 1;8(1):49–54. Kennedy SG, Kandel ES, Cross TK, Hay N. Akt/Protein Kinase B Inhibits Cell Death by Preventing the Release of Cytochrome c from Mitochondria. Mol Cell Biol. 1999 Aug;19(8):5800–10. Sun G, Ding X, Argaw Y, Guo X, Montell DJ. Akt1 and dCIZ1 promote cell survival from apoptotic caspase activation during regeneration and oncogenic overgrowth. Nat Commun. 2020 Nov 12;11(1):5726. Peiris TH, Ramirez D, Barghouth PG, Oviedo NJ. The Akt signaling pathway is required for tissue maintenance and regeneration in planarians. BMC Developmental Biology. 2016 Apr 11;16(1):7. Thornton TM, Rincon M. Non-Classical P38 Map Kinase Functions: Cell Cycle Checkpoints and Survival. Int J Biol Sci. 2008 Dec 19;5(1):44–52. Hume S, Dianov GL, Ramadan K. A unified model for the G1/S cell cycle transition. Nucleic Acids Research. 2020 Dec 16;48(22):12483–501. Rinkevich B, Shapira M. An improved diet for inland broodstock and the establishment of an inbred line form Botryllus schlosseri, a colonial sea squirt (Ascidiacea). Aquatic Living Resources. 1998 May 1;11(3):163–71. Taketa DA, Nydam ML, Langenbacher AD, Rodriguez D, Sanders E, De Tomaso AW. Molecular evolution and in vitro characterization of Botryllus histocompatibility factor. Immunogenetics. 2015 Oct 1;67(10):605–23. Kong AT, Leprevost FV, Avtonomov DM, Mellacheruvu D, Nesvizhskii AI. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry–based proteomics. Nat Methods. 2017 May;14(5):513–20. Demichev V, Szyrwiel L, Yu F, Teo GC, Rosenberger G, Niewienda A, et al. dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts. Nat Commun. 2022 July 8;13(1):3944. Pino LK, Searle BC, Bollinger JG, Nunn B, MacLean B, MacCoss MJ. The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. Mass Spectrom Rev. 2017;39(3):229–44. De Thier O, Lebel M, M.Tawfeeq M, Faure R, Dru P, Blanchoud S, et al. First chromosome-level genome assembly of the colonial chordate model Botryllus schlosseri (Tunicata). Gigascience. 2025 Jan 1;14:giaf097. Ammar C, Schessner JP, Willems S, Michaelis AC, Mann M. Accurate Label-Free Quantification by directLFQ to Compare Unlimited Numbers of Proteomes. Mol Cell Proteomics. 2023 July;22(7):100581. Wolski WE, Nanni P, Grossmann J, d’Errico M, Schlapbach R, Panse C. prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis. J Proteome Res. 2023 Mar 20;22(4):1092–104. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008 Dec 29;9(1):559. Jensen LJ, Julien P, Kuhn M, von Mering C, Muller J, Doerks T, et al. eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic Acids Research. 2008 Jan 1;36(suppl_1):D250–4. Xu S, Hu E, Cai Y, Xie Z, Luo X, Zhan L, et al. Using clusterProfiler to characterize multiomics data. Nat Protoc. 2024 Nov;19(11):3292–320. Bodenhofer U, Kothmeier A, Hochreiter S. APCluster: an R package for affinity propagation clustering. Bioinformatics. 2011 Sept 1;27(17):2463–4. Rodriguez-Valbuena H, Salcedo J, De Thier O, Flot JF, Tiozzo S, De Tomaso AW. Exceptional diversity of allorecognition receptors in a nonvertebrate chordate reveals principles of innate allelic discrimination. Proceedings of the National Academy of Sciences. 2025 Oct 28;122(43):e2519372122. Tables Table 1. Proteins annotated to the cell cycle KEGG pathway that are significantly enriched in takeover buds (TOB) relative to takeover zooids (TOZ). Protein ID Name Description TOB vs. TOZ log 2 FC TOB vs. TOZ FDR g16515.t1 MCM3 DNA replication licensing factor MCM3 3.20 1.07E-08 g12813.t1 PCNA Proliferating cell nuclear antigen 3.14 8.80E-10 g8245.t1 MCM2 DNA replication licensing factor MCM2 2.97 1.98E-08 g15498.t1 MCM5 DNA replication licensing factor MCM5 2.58 5.70E-07 g5003.t1 MCM7 DNA replication licensing factor MCM7 2.57 5.70E-07 g7006.t1 MCM4 DNA replication licensing factor MCM4 2.35 6.66E-07 g12939.t1 MCM6 DNA replication licensing factor MCM6 1.95 6.05E-06 g6262.t1 CDK1 Cyclin-dependent kinase 1 1.90 4.07E-05 g4249.t1 BUB3 Mitotic checkpoint protein BUB3 1.64 2.12E-08 g8176.t1 CDK2 Cyclin-dependent kinase 2 1.49 2.05E-05 g16459.t1 HDAC2 Histone deacetylase 2 1.48 3.21E-06 g13343.t1 SKP1 S-phase kinase-associated protein 1 1.10 1.63E-04 g7055.t1 SMC3 Structural maintenance of chromosomes protein 3 0.97 1.03E-02 g3091.t1 14-3-3 homologues 14-3-3 protein family (multiple isoforms) 0.67 1.26E-02 g7214.t1 14-3-3 homologues 14-3-3 protein family (multiple isoforms) 0.65 1.48E-02 g3093.t1 14-3-3 homologues 14-3-3 protein family (multiple isoforms) 0.55 2.30E-02 Abbreviations: log₂FC, log₂-transformed fold change; FDR, false discovery rate. Proteins were considered significantly enriched with FDR < 0.05. Table 2. Proteins annotated to the senescence KEGG pathway that are significantly enriched in takeover buds (TOB) relative to takeover zooids (TOZ). Protein ID Name Description TOB vs. TOZ log 2 FC TOB vs. TOZ FDR g10555.t1 FKBP4 FK506-binding protein 4 2.53 2.87E-09 g6262.t1 CDK1 Cyclin-dependent kinase 1 1.90 4.07E-05 g8433.t1 RBBP7 Histone-binding protein RBBP7 1.84 2.01E-06 g8176.t1 CDK2 Cyclin-dependent kinase 2 1.49 2.05E-05 g8750.t1 RBBP4 Histone-binding protein RBBP4 1.05 4.99E-04 g13710.t1 CALML4 Calmodulin-like protein 4 -0.64 4.54E-02 g11286.t1 SLC25A31 ADP/ATP translocase 4 -0.73 3.86E-02 g2262.t1 MK3 MAPK-activated protein kinase 3 -0.82 1.43E-02 g4884.t1 BRAF Serine/threonine-protein kinase B-Raf -0.86 4.89E-02 g1830.t1 AKT1 RAC-alpha serine/threonine-protein kinase -1.07 5.55E-03 g11271.t1 CALM2 Calmodulin-like protein 2 -1.20 1.09E-04 g2613.t1 CAPN1 Calpain-1 catalytic subunit -1.24 6.66E-04 g15547.t1 RRAS2 Ras-related protein R-Ras2 -1.29 2.66E-02 g6575.t1 CALML6 Calmodulin-like protein 6 -1.36 4.74E-03 g3428.t1 CALML3 Calmodulin-like protein 3 -1.74 9.73E-04 Abbreviations: log₂FC, log₂-transformed fold change; FDR, false discovery rate. Proteins were considered significantly enriched with FDR < 0.05. Table 3. Eukaryotic elongation factors and translation initiation factor 3 subunits detected in B. schlosseri proteomic study. Protein ID Name Description TOB_TOZ_log2FC TOB_TOZ_FDR g6116.t1 EEF1B2 Elongation factor 1-beta 2 0.76 1.65E-02 g15448.t1 EEF1D Elongation factor 1-delta 1.10 9.08E-05 g5674.t1 EEF1G Elongation factor 1-gamma 1.20 2.48E-05 g16622.t1 EEF2 Elongation factor 2 1.10 9.93E-06 g8702.t1 EEF2K Eukaryotic elongation factor 2 kinase 1.74 6.74E-04 g2023.t1 EIF3A Eukaryotic translation initiation factor 3 subunit A 1.33 1.32E-05 g14342.t1 EIF3B Eukaryotic translation initiation factor 3 subunit B 1.40 1.69E-05 g5249.t1 EIF3C Eukaryotic translation initiation factor 3 subunit C 1.20 7.53E-05 g2542.t1 EIF3D Eukaryotic translation initiation factor 3 subunit D 0.95 6.16E-03 g16921.t1 EIF3E Eukaryotic translation initiation factor 3 subunit E 1.12 5.43E-04 g2844.t1 EIF3F Eukaryotic translation initiation factor 3 subunit F 1.60 6.26E-06 g16953.t1 EIF3G Eukaryotic translation initiation factor 3 subunit G 1.38 4.46E-04 g16407.t1 EIF3H Eukaryotic translation initiation factor 3 subunit H 1.82 1.61E-06 g1065.t1 EIF3I Eukaryotic translation initiation factor 3 subunit I 1.89 1.78E-08 g16501.t1 EIF3J Eukaryotic translation initiation factor 3 subunit J 1.03 7.90E-03 g16236.t1 EIF3K Eukaryotic translation initiation factor 3 subunit K 1.35 6.16E-04 g11765.t1 EIF3L Eukaryotic translation initiation factor 3 subunit L 1.13 4.39E-03 g8379.t1 EIF3M Eukaryotic translation initiation factor 3 subunit M 1.64 1.61E-06 Eukaryotic elongation factors (EEF2, EEF2K, EEF1G, EEF1D, EEF1B2) and multiple subunits of the eukaryotic translation initiation factor 3 (eIF3) complex were identified in the proteomic studies. All were significantly upregulated in primary buds (TOB) relative to regressing zooids (TOZ), consistent with broad activation of the translational machinery to support proliferative demands. Abbreviations: log₂FC, log₂-transformed fold change; FDR, false discovery rate. Proteins were considered significantly enriched with FDR < 0.05. Additional Declarations No competing interests reported. Supplementary Files suppltable1.xlsx Supplementary Table 1. Gene Ontology (GO) terms enriched or depleted beyond those captured by KEGG pathway analysis. Provided as a separate Excel file. suppltable2.xlsx Supplementary Table 2. Primer sets used for genotyping were obtained from Rodriguez-Valbuena et al. (2025) [107]. Provided as a separate Excel file. S1.pdf Supplemental Figure 1. Phylogenetic placement of Botryllus schlosseri among model organisms. A phylogenetic tree illustrates the evolutionary relationships between major model organisms, highlighting the position of B. schlosseri within the chordate phylum. As a basal chordate diverging approximately 535 million years ago, B. schlosseri provides a valuable system for studying the evolution of regenerative capacity, development, and cell biology in relation to vertebrates. Created in BioRender. Dong, V. (2025) https://BioRender.com/q48egyl S2genotypes.pdf Supplemental Figure 2. Genotypic differentiation of Botryllus schlosseri colonies using 12 fester loci. PCR results are shown for 12 fester gene primer sets across seven B. schlosseri genotypes. Each column represents a distinct fester locus, and each row corresponds to a unique genotype. Genotypic identity is determined based on the unique combination of presence or absence patterns across the loci, enabling discrimination between colonies. 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07:21:53","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":256062,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/5bfa10e492c3d4aa894f9b88.html"},{"id":99906758,"identity":"0248102f-ce9e-41f6-a03c-f6306de11712","added_by":"auto","created_at":"2026-01-09 17:01:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":186096,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of the blastogenic cycle and proteomics workflow in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBotryllus schlosseri\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003cbr\u003e\n \u003c/strong\u003e(A) Photograph of \u003cem\u003eB. schlosseri\u003c/em\u003e colonies collected from the Berkeley Marina Harbor, growing on a mussel shell. Individual zooids within each colony measure up to 3 mm in length.\u003cstrong\u003e \u003c/strong\u003e(B) Microscopic view of a \u003cem\u003eB. schlosseri\u003c/em\u003e colony during the takeover stage. Senescing takeover zooids (TOZ) appear darker reddish than the proliferating takeover buds (TOB), which appear light orange. (C) Schematic illustration of the blastogenic cycle of \u003cem\u003eB. schlosseri\u003c/em\u003e, highlighting the key stages at the individual animal level: Stage A Zooid (SAZ), Stage B Zooid (SBZ), Stage C Zooid (SCZ), Takeover Zooid (TOZ), and Takeover Bud (TOB). (D) Larvae released from wild colonies are used to establish lab-grown colonies from oozooids, which are maintained individually and sampled at defined blastogenic stages.\u003c/p\u003e","description":"","filename":"Binder11.png","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/7d2260fc224ff382c0f39253.png"},{"id":100359595,"identity":"73f201ff-45bc-4496-85fd-9f1ede43c5ce","added_by":"auto","created_at":"2026-01-16 07:23:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlobal proteomics analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBotryllus schlosseri\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e across blastogenic stages (Study 1).\u003c/strong\u003e (A) Principal component analysis (PCA) of five blastogenic stages, TOB (Takeover Bud), SAZ (Stage A Zooid), SBZ (Stage B Zooid), SCZ (Stage C Zooid), and TOZ (Takeover Zooid), based on 1,432 proteins significantly different in abundance by ANOVA (FDR \u0026lt; 0.1). (B) Weighted Gene Co-expression Network Analysis (WGCNA) identified two major co-expression modules across blastogenic stages: a Proliferation module (green, 614 proteins) and a Degradation module (red, 628 proteins). The plot shows the average log₂ protein abundance for each module across stages, with shaded areas representing standard deviation (n = 3). (C) KEGG pathway enrichment results for proteins in the Proliferation (left) and Degradation (right) modules. Circle size represents the number of proteins mapped to each pathway, while color reflects enrichment score. Pathways specific to vertebrate physiology, human disease, or dependent on cell types absent in \u003cem\u003eB. schlosseri\u003c/em\u003e were excluded prior to visualization.\u003c/p\u003e","description":"","filename":"Binder12.png","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/c950a2710cb2c333509ad712.png"},{"id":99906759,"identity":"268d5713-f72c-403b-8a76-7db3f165357f","added_by":"auto","created_at":"2026-01-09 17:01:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":31376,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlobal proteomics analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBotryllus schlosseri\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e across blastogenic stages (Study 2).\u003c/strong\u003e (A) Venn diagram showing the overlap of total and differentially adundant proteins (FDR \u0026lt; 0.1) between two independent experiments. (B) Principal component analysis (PCA) based on 2,020 proteins significantly differentially abundant by ANOVA (FDR \u0026lt; 0.1), showing clear separation of samples from three blastogenic stages: TOB (Takeover Bud), SAZ (Stage A Zooid), and TOZ (Takeover Zooid). (C) KEGG pathway enrichment of differentially abundant proteins, shown as enrichment score bars annotated with protein counts and FDR values.\u003c/p\u003e","description":"","filename":"Binder13.png","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/50e9b51c6a74915a9f905c21.png"},{"id":100359238,"identity":"0c48cf45-b88c-46f5-93f5-a8c23407e088","added_by":"auto","created_at":"2026-01-16 07:21:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":37464,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProtein abundance across developmental stages in two independent studies of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBotryllus schlosseri\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eBoxplots show the log₂-transformed protein intensities for six key regulators of proliferation and chromatin control (PCNA, CDK1, CDK2, SKP1, BUB3, and HDAC2) measured in two independent proteomic studies (Study 1: n = 3 and Study 2: n = 7). Each box represents the interquartile range with the median line, and individual points indicate biological replicates. Conditions within each study are arranged chronologically along the blastogenic cycle, from the early stage (TOB) to the late stage (TOZ). Distinct colors denote specific blastogenic stages: TOB (green), SAZ (yellow), SBZ (gray), SCZ (blue), and TOZ (magenta).\u003c/p\u003e","description":"","filename":"Binder14.png","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/dfbf1fa41c12f70bcbe867be.png"},{"id":99906761,"identity":"f7d8386d-40f3-4906-9992-7164356e1664","added_by":"auto","created_at":"2026-01-09 17:01:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":45844,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegrated signaling and cell-cycle regulatory network highlighting differentially abundant proteins between TOB and TOZ. \u003c/strong\u003eSchematic representation of signaling pathways and cell-cycle regulators contrasting the most proliferative stage (TOB, emerging buds) with the most senescent stage (TOZ, regressing zooids). Proteins shown in red are significantly upregulated in TOB relative to TOZ, whereas proteins shown in blue are significantly downregulated. Canonical growth and survival signaling pathways are represented by RAS-BRAF-MEK-ERK and RRAS2-PI3K-AKT1-mTORC1, as well as WNT-β-catenin signaling. Inhibitory nodes include PTEN, which antagonizes PI3K signaling, and GSK3β, which targets β-catenin for degradation but is inhibited by AKT1. Chromatin-level transcriptional repression is represented by the NuRD complex (CHD3/4, HDAC2, MTA1-3, GATAD2A/B, MBD2/3, RBBP4/7), and protein turnover is regulated by the SCF complex (SKP1-CUL1-RBX1-SKP2). Mitotic fidelity is shown through the MCC (BUBR1, BUB3, MAD2, CDC20) that inhibits APC/C, and stress-responsive checkpoint control is indicated by the p38-MK3 pathway, which inhibits CDC25. Together, these data illustrate coordinated modulation of signaling, chromatin remodeling, and checkpoint control that distinguish proliferative buds from senescing zooids. Created in BioRender. Lepretre, M. (2025) https://BioRender.com/bvf2bsv\u003c/p\u003e","description":"","filename":"Binder15.png","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/e65fd0e7829bd49349e6ea1a.png"},{"id":100377369,"identity":"60de93dd-8094-4951-b6b9-82fdb49812d8","added_by":"auto","created_at":"2026-01-16 08:47:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1908465,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/b4d3d8a3-5f4f-4df6-b4cd-464a6e98f4d9.pdf"},{"id":99906764,"identity":"e900393b-1885-44e7-8a75-6fe6aa32ab40","added_by":"auto","created_at":"2026-01-09 17:01:34","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":417400,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1. Gene Ontology (GO) terms enriched or depleted beyond those captured by KEGG pathway analysis. \u003c/strong\u003eProvided as a separate Excel file.\u003c/p\u003e","description":"","filename":"suppltable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/fcfed3bcf1272863f19a2b27.xlsx"},{"id":99906765,"identity":"d96f1b0e-55c6-4a4b-9a8f-9d11b5548791","added_by":"auto","created_at":"2026-01-09 17:01:34","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 2. Primer sets used for genotyping were obtained from Rodriguez-Valbuena et al. (2025)\u003c/strong\u003e [107].\u003cstrong\u003e \u003c/strong\u003eProvided as a separate Excel file.\u003c/p\u003e","description":"","filename":"suppltable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/f71f88554b684e628f0242e7.xlsx"},{"id":100358710,"identity":"82b9baa8-ca4d-49a4-a60c-81cbed7d0c93","added_by":"auto","created_at":"2026-01-16 07:21:16","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":502013,"visible":true,"origin":"","legend":"\u003cp\u003eSupplemental Figure 1. Phylogenetic placement of Botryllus schlosseri among model organisms.\u003c/p\u003e\n\u003cp\u003eA phylogenetic tree illustrates the evolutionary relationships between major model organisms, highlighting the position of B. schlosseri within the chordate phylum. As a basal chordate diverging approximately 535 million years ago, B. schlosseri provides a valuable system for studying the evolution of regenerative capacity, development, and cell biology in relation to vertebrates. Created in BioRender. Dong, V. (2025) https://BioRender.com/q48egyl\u003c/p\u003e","description":"","filename":"S1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/b8e108719b79dd7c4081525b.pdf"},{"id":99906768,"identity":"6073d0fd-9e71-4908-8e39-7ab9e77942fe","added_by":"auto","created_at":"2026-01-09 17:01:34","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":799927,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Figure 2. Genotypic differentiation of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eBotryllus schlosseri\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e colonies using 12 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003efester\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eloci.\u003c/strong\u003e\u003cbr\u003e\nPCR results are shown for 12 \u003cem\u003efester\u003c/em\u003e gene primer sets across seven \u003cem\u003eB. schlosseri\u003c/em\u003e genotypes. Each column represents a distinct \u003cem\u003efester\u003c/em\u003elocus, and each row corresponds to a unique genotype. Genotypic identity is determined based on the unique combination of presence or absence patterns across the loci, enabling discrimination between colonies.\u003c/p\u003e","description":"","filename":"S2genotypes.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8094443/v1/e782235f3f411ce7c0f4448c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Proteome Dynamics Across the Blastogenic Cycle of Botryllus schlosseri Reveals Targets for Cell Immortalization","fulltext":[{"header":"Background","content":"\u003cp\u003eThe colonial tunicate \u003cem\u003eBotryllus schlosseri\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) has emerged as a compelling model organism for exploring the mechanisms of regeneration [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], aging [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and stress resilience [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As the closest living invertebrate taxon relative to vertebrates [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], tunicates occupy a critical phylogenetic position that bridges evolutionary milestones, offering unique insights into the molecular underpinnings responsible for conservation, innovation, and loss of cellular and organismal processes during chordate phylogeny (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Botryllid tunicates stand out as the chordate phylogenetically closest to humans that are capable of whole-body regeneration during asexual reproduction and in response to injury. This trait has been lost in all vertebrates and most other chordates rendering \u003cem\u003eB. schlosseri\u003c/em\u003e a unique model for studying molecular mechanisms that promote tissue regeneration, cell proliferation, and cell differentiation in chordates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNotably, \u003cem\u003eB. schlosseri\u003c/em\u003e undergoes a synchronized weekly blastogenic cycle of asexual reproduction, during which old zooids degenerate and are replaced by new primary buds. First described by Sabbadin et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and then later reclassified and characterized in detail by Manni et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], this cycle consists of four stages (A-D) and occurs within a zoid system enclosed by a tunic where three generations coexist and are connected by a communal vasculature. Adult zooids actively feed, while primary and secondary buds remain nutritionally dependent on the zooids. As the cycle progresses, primary buds develop through stages A to C, culminating in the takeover stage D (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), where synchronized zooid regression and increased cellular turnover drive colony renewal. This cyclical process mirrors multiple aspects of growth, maturation, and programmed cell death common to vertebrates [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], thus providing an \u003cem\u003ein vivo\u003c/em\u003e model for understanding conserved mechanisms of cellular turnover in chordates. Moreover, studying blastogenic takeover and injury-induced whole-body regeneration in botryllid tunicates offers an opportunity to identify molecular processes of chordates that can be targeted to promote tissue and whole-body regeneration by genetic or pharmacological intervention in vertebrates and other chordates lacking the ability of comprehensive tissue and whole-body regeneration.\u003c/p\u003e \u003cp\u003eHowever, key limitations have impeded deeper mechanistic studies of \u003cem\u003eB. schlosseri\u003c/em\u003e, including the scarcity of information on the proteome [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], which represents the main determinant of cellular and organismal structure and function, and the absence of established cell line models for high-throughput genetic screens. Addressing these gaps is essential for advancing functional investigations and for high-throughput genetic manipulation of cellular processes in a controlled environment to establish causality between gene function and phenotype. Despite its utility as an \u003cem\u003ein vivo\u003c/em\u003e model, the lack of \u003cem\u003eB. schlosseri\u003c/em\u003e cell lines limits the ability to manipulate and investigate cellular mechanisms in a controlled environment by high-throughput genetic engineering and other causality-aimed approaches. While some species and cell types can undergo spontaneous immortalization without the introduction of foreign elements [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], most species are believed to require targeted interventions to achieve stable, long-term cell growth [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. With current approaches, isolated \u003cem\u003eB. schlosseri\u003c/em\u003e primary cells exit the G\u003csub\u003e1\u003c/sub\u003e phase of the cell cycle and remain quiescent in G\u003csub\u003e0\u003c/sub\u003e after relatively short-term (1\u0026ndash;3 weeks) primary culture and optimal conditions for long-term culture and exit from primary culture crisis/ senescence remain undefined [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOvercoming these challenges requires innovative strategies to enhance cell survival and proliferation while inhibiting senescence to overcome crisis \u003cem\u003ein vitro\u003c/em\u003e. Mammalian cell lines have been successfully immortalized using viral oncoproteins, such as the SV40 large T antigen, or modifications of the cell cycle machinery, including the overexpression of human telomerase reverse transcriptase (hTERT) [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, such methods often fail in non-mammalian systems, where conserved pathways like cell cycle regulation may rely on subtly divergent regulatory mechanisms that are still poorly characterized in aquatic invertebrates. To date, the only established strictly marine invertebrate cell lines include one derived from the phylum Porifera by spontaneous immortalization [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], a hybrid shrimp cell line (PmLyO-Sf9) generated by fusing \u003cem\u003ePenaeus monodon\u003c/em\u003e lymphoid cells with Sf9 insect cells [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and, more recently, cell lines established from scallop (\u003cem\u003eChlamys farreri\u003c/em\u003e) trochophore larvae [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and sea urchin (\u003cem\u003eLytechinus variegatus\u003c/em\u003e and \u003cem\u003eStrongylocentrotus purpuratus\u003c/em\u003e) embryos [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTerrestrial invertebrate models have offered limited insight applicable to aquatic invertebrates. \u003cem\u003eDrosophila\u003c/em\u003e cells, for example, could be immortalized by overexpressing \u003cem\u003eRas\u003c/em\u003e\u003csup\u003eV12\u003c/sup\u003e, but not \u003cem\u003eMyc\u003c/em\u003e, highlighting that even targeting well-established oncogenes has varying effectiveness across species [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These outcomes underscore the importance of identifying species-specific targets rather than exclusively extrapolating target identification based on knowledge of mammalian or terrestrial invertebrate systems. Even core regulators such as cyclin-dependent kinases (CDKs) differ across lineages and primitive chordates have fewer CDK paralogs than mammals due to gene duplication events during early metazoan and vertebrate evolution. For instance, yeast encode only a single CDK (Cdc28) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], while humans possess 21 CDK paralogs that include CDK4, a common target in mammalian immortalization protocols [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, CDK1 gene duplication has been reported in the tunicate \u003cem\u003eOikopleura\u003c/em\u003e [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Such variability suggests that successful strategies in non-mammalian systems will require a deeper understanding of their unique regulatory landscapes. Identification of species-specific molecular proteome signatures associated with physiological states of active proliferation and senescence will aid in the identification of potent species-specific regulators of cell growth and survival.\u003c/p\u003e \u003cp\u003ePrevious transcriptomic studies in \u003cem\u003eB. schlosseri\u003c/em\u003e have provided valuable insight into pathways involved in stem cell activation, immune responses, and oxidative stress responses associated with aging [\u003cspan additionalcitationids=\"CR29 CR30 CR31\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The cellular processes of apoptosis and autophagy have been implicated in the degeneration of adult zooids, supporting the recycling of molecular building blocks and tissue turnover required for bud development [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, these studies did not directly capture the proteins responsible for proliferation and senescence phenotypes during the blastogenic cycle. This knowledge gap is significant because mRNA and protein abundances are often not correlated well in mammalian and other chordate cells due to regulation at the translational and post-translational levels [\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Moreover, transcriptomic analyses do not capture functional protein-level activity and post-translational modifications, which are critical for understanding dynamic changes in cellular phenotypes [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. By contrast, proteomic analyses enable direct investigation of protein abundances, interactions, and modifications, providing a more complete view of cellular responses. Recent advances in mass spectrometry allow the quantification of thousands of proteins in a single sample based on defined sets of peptides that are used for targeted quantitation in all samples of interest. This quantitative data-independent acquisition (DIA) proteomics approach facilitates whole-proteome comparisons across conditions and the discovery of new molecular targets that drive phenotypes of interest [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBy leveraging \u003cem\u003eB. schlosseri\u003c/em\u003e\u0026rsquo;s unique biology and label-free DIA proteomics, this study aims to comprehensively characterize proteome dynamics across different blastogenic stages to identify key proteins and molecular signatures associated with \u003cem\u003eB. schlosseri\u003c/em\u003e cell proliferation and senescence. Initially, proteomics was performed across all blastogenic stages to capture global protein abundance regulation and identify corresponding functional adjustments during blastogenesis. Subsequently, a more focused proteomic follow-up study was conducted focusing on the blastogenic cycle stages that are most informative regarding critical regulators of cell proliferation and senescence.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDistinct Proteomic Landscapes Throughout the Blastogenic Cycle\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdult zooids and primary buds at specific blastogenic stages were classified as follows: Stage A zooids (SAZ), Stage B zooids (SBZ), Stage C zooids (SCZ), Takeover zooids (TOZ), and Takeover primary buds (TOB) (Fig. 1C). Secondary buds, due to their extremely small size, could not be physically separated from the primary buds and are assumed to contribute minimally to the primary bud proteome. Additionally, primary buds from stages A, B, and C were excluded due to the challenge of extracting sufficient protein from such small buds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo establish a foundational proteomics analysis of \u003cem\u003eB. schlosseri\u003c/em\u003e at the individual zooid level, the proteomes of adult zooids across four blastogenic stages (SAZ, SBZ, SCZ, and TOZ) and emerging primary buds from the takeover stage (TOB) were examined. Colonies were genotyped to confirm unique identities (Fig. S2). No genotype-specific clustering or systematic bias was observed, and genotype effects were minor relative to stage differences. Thus, only blastogenic stage differences that are conserved across all genotypes used in this study were considered. Larvae released from field-collected colonies were settled on glass slides and maintained as laboratory colonies, which were subsequently used for dissection (Fig. 1D). A total of 15,156 unique peptides mapped to 3,155 unambiguous protein groups and were reliably quantified across all blastogenic stages. Among the identified proteins, 45% (1,432) exhibited statistically significant changes in abundance across stages (ANOVA, FDR \u0026lt; 0.1), demonstrating extensive proteomic remodeling throughout the blastogenic cycle.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrincipal Component Analysis (PCA) performed on these differentially abundant proteins (DAPs) demonstrated clear separation of expression patterns among blastogenic stages, with TOB exhibiting the most distinct proteome compared to adult zooids at all other stages (Fig. 2A). PC1, which explains 64% of the total variance, clearly discriminates TOB, SAZ, and TOZ, reflecting the major proteomic shifts associated with the transition from active adult zooids to degenerating zooids and the emergence of new primary buds. PC2 captures more subtle differences between SBZ and SCZ, corresponding to the progressive maturation of adult zooids prior to takeover. The distinct separation observed in PCA underscores the molecular coordination driving developmental renewal and programmed cell death in \u003cem\u003eB. schlosseri.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCo-expression Modules Reveal Distinct Functional Programs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWeighted Gene Co-expression Network Analysis (WGCNA) performed on the DAPs identified two major modules with distinct expression trends across the blastogenic cycle (Fig. 2B). The first module, termed the proliferation module, contains 614 proteins whose abundance decreases from the TOB stage to the TOZ stage. In contrast, the second module, referred to as the degradation module, includes 628 proteins that increase in abundance over the same transition. These opposing trends highlight a coordinated switch from proliferative to degradative cellular programs as the blastogenic cycle progresses. The remaining 190 DAPs were not classified into any co-expression module. Protein abundance shifted most dramatically between the temporally adjacent TOB and SAZ stages, with DAPs exhibiting an average log₂ fold change (FC) of approximately 1. Later stage transitions showed progressively smaller shifts, culminating in the largest overall divergence between the earliest (TOB) and latest (TOZ) stages examined in this study (Fig. 2B).\u003c/p\u003e\n\u003cp\u003eTo interpret the biological relevance of these co-expression patterns, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for each module (Fig. 2C). Pathways associated with vertebrate-specific physiology, human diseases, or cell types absent from \u003cem\u003eB. schlosseri\u003c/em\u003e were excluded from this analysis. The proliferation module (Fig. 2B, green, 614 proteins), which decreases in abundance from TOB to TOZ, was broadly enriched for pathways related to cellular proliferation, such as translational capacity, cell cycle progression, and macromolecular biosynthesis. The most enriched KEGG pathways were ribosome biogenesis (70 DAPs), DNA replication (14 DAPs) and proteasome function (27 DAPs). Other enriched pathways included cell cycle progression, macromolecular biosynthesis, mRNA surveillance, chromatin remodeling, and nucleocytoplasmic transport, reflecting coordinated regulation of processes essential for cell growth and division. \u0026nbsp;In contrast, the degradation module (Fig. 2B, red, 628 proteins), which increases from TOB to TOZ, was enriched for catabolic and metabolic remodeling KEGG pathways. The most significant enrichment was seen in ATP-binding cassette (ABC) transporters (10 DAPs), followed by Peroxisome proliferator-activated receptor (PPAR) signaling (17 DAPs), calcium signaling (17 DAPs), peroxisome (21 DAPs), gap junction (11 DAPs), galactose metabolism (8 DAPs) and protein digestion and absorption (15 DAPs). These pathways likely support nutrient salvage, stress signaling, and orderly tissue breakdown / recycling during zooid regression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfirmation of Pro- and Anti-Proliferative Protein Modules During Takeover\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo support the findings from the first study, a second study was conducted, focusing on the three most biologically distinct stages identified earlier: TOB, SAZ, and TOZ. To increase statistical power and improve proteome coverage, the number of biological replicates was expanded from three to seven per condition. This second study yielded 22,458 unique peptides mapping to 4,015 unambiguous protein groups. This result represents a 32.5% increase in peptide detection and a 27% increase in quantifiable proteins compared to the first study. Of the detected proteins, 2,919 were shared across both studies, accounting for 92.5% of the first and 72.7% of the second study. An additional 1,096 proteins were uniquely identified in the second study, while 236 were exclusive to the first (Fig. 3A). The improved detection is likely due to both the increased number of replicates and the use of a more inclusive spectral library, which was generated directly from DIA data\u0026nbsp;[41]\u0026nbsp;as opposed to separate DDA library construction in the first study. PCA of the 2,020 DAPs identified in the second study showed clear separation among TOB, SAZ, and TOZ, consistent with the pattern observed in the first study, with TOB and TOZ exhibiting the most distinct proteome differences (Fig. 3B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSTRING enrichment analysis highlighted strong enrichment of biosynthetic and proliferative KEGG pathways, including ribosome (92 proteins), spliceosome (82 proteins), RNA transport (62 proteins), and DNA replication (19 proteins), along with multiple DNA repair pathways, RNA degradation, and proteasome activity, which were associated with primary buds. In contrast, phagosome (24 proteins), peroxisome (41 proteins), and lysosome (42 proteins) KEGG pathways were enriched in senescing zooids (Fig. 3C). Additional Gene Ontology (GO) terms associated with these functions, beyond those captured by KEGG pathways, were also significantly enriched or depleted and support the KEGG pathway trends (Supplementary Table 1, STRING permalink: https://version-12-0.string-db.org/cgi/globalenrichment?networkId=bR3BtYEnv3rk).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell Cycle and Senescence Associated Proteins\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify proteins that may regulate the transition between proliferation and senescence, stage-specific expression was compared between TOB and TOZ, which are the two stages that showed the greatest proteome differences. DAPs that contributed to the cell cycle (ko04110) and cellular senescence (ko04218) KEGG pathways were further examined. To reduce redundancy, isoforms that shared the same KEGG annotation were collapsed, retaining a single representative per protein group. Using a significance threshold of FDR \u0026lt; 0.05 for TOB versus TOZ comparisons, 16 DAPs were identified in the cell cycle pathway (Table 1) and 15 in the cellular senescence pathway (Table 2). These proteins function in DNA replication, cell cycle checkpoints, chromatin remodeling, and as stress- and signaling-related regulators, with CDK1 and CDK2 represented in both pathways.\u003c/p\u003e\n\u003cp\u003eDNA replication factors exhibited the most pronounced changes with proliferating cell nuclear antigen (PCNA) showing one of the greatest differential abundances between TOB and TOZ (log₂FC = 3.1, FDR = 8.8 × 10⁻¹⁰) (Fig. 4A). All six subunits of the minichromosome maintenance complex (MCM2, MCM3, MCM4, MCM5, MCM6, and MCM7), which form the core replicative helicase required for DNA unwinding during S phase, were greatly upregulated in TOB, suggesting increased licensing and replication initiation activity. CDK1 and CDK2 were also significantly upregulated (log₂FC = 1.9 and 1.5; FDR = 4 × 10⁻⁵ and 2 × 10⁻⁵) (Fig. 4B-C), consistent with progression through the G\u003csub\u003e2\u003c/sub\u003e/M and G\u003csub\u003e1\u003c/sub\u003e/S checkpoints, respectively. S-phase kinase-associated protein 1 (SKP1), a core component of the SCF E3 ubiquitin ligase complex, was increased in abundance in TOB (log₂FC = 1.1, FDR = 1.6 × 10⁻⁴) (Fig. 4D). Other proteins involved in mitotic checkpoint control and chromatid cohesion were also enriched. Structural maintenance of chromosomes protein 3 (SMC3), a subunit of the cohesin complex necessary for sister chromatid pairing, was more abundant in TOB (log₂FC = 1.0, FDR = 0.01). BUB3 mitotic checkpoint protein (BUB3), a conserved spindle assembly checkpoint regulator, was highly upregulated in TOB (log₂FC = 1.6, FDR = 2.1 × 10⁻⁸) (Fig. 4E), reflecting the need for mitotic surveillance during rapid proliferation. Histone deacetylase 2 (HDAC2), a class I histone modifier involved in chromatin compaction, was also significantly upregulated in TOB (log₂FC = 1.5, FDR = 3.2 × 10⁻⁶) (Fig. 4F). Notably, Histone deacetylase 1 (HDAC1) was not detected in the study, suggesting a potentially dominant role for HDAC2 in regulating chromatin state during cell cycle transitions in this system. Finally, several proteins annotated as members of the 14-3-3 protein family showed increased abundance in TOB. Although their specific isoforms could not be resolved from the blastp ortholog annotation, their enrichment suggests a potential regulatory role in checkpoint signaling or cell cycle coordination during blastogenesis.\u003c/p\u003e\n\u003cp\u003eWithin the cellular senescence pathway, several proteins displayed significant differential abundance between TOB and TOZ. The prolyl isomerase FK506-binding protein 4 (FKBP4), which has roles in protein folding and chaperone-mediated regulation, showed the strongest upregulation in TOB (log₂FC = 2.5, FDR = 2.9 × 10⁻⁹). Chromatin remodelers, histone-binding proteins RBBP7 and RBBP4, were also elevated in TOB (log₂FC = 1.8 and 1.0; FDR = 2.0 × 10⁻⁶ and 5.0 × 10⁻⁴), suggesting enhanced histone binding and nucleosome remodeling capacity during active proliferation.\u003c/p\u003e\n\u003cp\u003eIn addition to cell-cycle regulators, multiple proteins involved in translation were significantly enriched in TOB. Eukaryotic elongation factors (EEF2, EEF2K, EEF1G, EEF1D, EEF1B2) and initiation factors, including subunits of the eukaryotic translation initiation factor 3 (eIF3) complex (EIF3A-M), were consistently upregulated, indicating enhanced translational capacity in proliferative buds. These changes suggest that increased biosynthetic output is a key feature of TOB, supporting the elevated demand for protein synthesis during rapid cell division (Table 3).\u003c/p\u003e\n\u003cp\u003eIn contrast, multiple signaling and metabolic regulators were downregulated in TOB and enriched in TOZ. These included MAPK-activated protein kinase 3 (MK3) and B-Raf proto-oncogene serine/threonine kinase (BRAF) (log₂FC = -0.8 and -0.9; FDR = 1.4 × 10⁻² and 4.9 × 10⁻²), which are components of mitogen-activated protein kinase (MAPK) signaling. Similar regulation was observed for AKT Serine/Threonine Kinase (AKT1) (log₂FC = -1.1, FDR = 5.6 × 10⁻³), a key kinase in the PI3K-AKT pathway. Collectively, the results point to attenuation of mitogenic signaling in regressing zooids.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeveral calcium-binding proteins, including CALM2, CALML3, CALML4, and CALML6, were also significantly decreased in TOB (log₂FC = -0.6 to -1.7; FDR \u0026lt; 0.05), suggesting reduced calcium-dependent regulation of stress responses and apoptosis during high proliferation. Additional senescence-associated proteins, such as the adenine nucleotide translocator SLC25A31 (log₂FC = -0.7, FDR = 3.9 × 10⁻²), the cysteine protease calpain-1 (CAPN1) (log₂FC = -1.2, FDR = 6.7 × 10⁻⁴), and the small GTPase related RAS viral oncogene homolog 2 (RRAS2) (log₂FC = -1.3, FDR = 2.7 × 10⁻²), were all enriched in TOZ, highlighting mitochondrial, proteolytic, and Ras-family signaling contributions to the senescent phenotype.\u003c/p\u003e\n\u003cp\u003eTo facilitate cumulative comprehension and visualization of how these differentially abundant proteins interact, TOB vs. TOZ comparisons were mapped onto a curated network of signaling and regulatory pathways (Fig. 5). This pathway-level overview highlights the coordinated upregulation of DNA replication and cell-cycle regulators, including PCNA, CDK1/2, and the MCM complex, alongside increased activity of chromatin remodeling (Nucleosome Remodeling and Deacetylase [NuRD]) and proteolytic SKP1–Cullin–F-box (SCF) complexes. In contrast, canonical mitogen signaling nodes (RAS-BRAF-MEK-ERK, RRAS2-PI3K-AKT1-mTORC1) and the stress-responsive kinase MK3 were downregulated in TOB, consistent with a shift away from external mitogen input toward chromatin- and checkpoint-based control. Together, these findings provide a system-level proteomic framework and identifies key nodes within this framework that distinguish proliferative TOB from senescent TOZ.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eProteome Changes During the Blastogenic Cycle\u003c/h2\u003e \u003cp\u003eThe extensive proteomic remodeling which involved nearly half of the detected proteome observed across the blastogenic cycle of \u003cem\u003eB. schlosseri\u003c/em\u003e reflects major biological transitions that define its stages of asexual reproduction. PCA results of the first study showed that, while each of the four adult stage are distinct from each other in terms of their proteome, the most significant molecular changes happen at the takeover stage between TOZ and TOB where adult zooids degenerate and primary buds transform into new zooids. Co-expression analyses corroborate with this pattern, the sharp co-expression transition from TOB to SAZ from both modules reflects the accelerated progression of the takeover phase into the adult stage, during which primary buds migrate to the colony center, open their siphons, and rapidly mature into adult zooids capable of independent feeding within just 36 hours [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. During takeover, adult zooids regress through apoptosis and phagocytosis, while emerging buds initiate differentiation and proliferation. Cellular debris is cleared by circulating phagocytes and reutilized by developing buds as part of a colony-wide recycling mechanism [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Stem cell migration also occurs at this stage. Although somatic tissues experience weekly waves of apoptosis and phagocytosis, \u003cem\u003eB. schlosseri\u003c/em\u003e colonies are capable of long-term regeneration and can live for many years. This longevity is supported by the repeated trafficking of stem cells into new niches, which protects them from destruction and enables sustained self-renewal [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These dynamics suggest that the timing of cell cycle re-entry and tissue-specific differentiation is tightly regulated throughout the blastogenic cycle particularly at the takeover stage.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFunctional Enrichment of a Coordinated Proliferation Program in TOB\u003c/h3\u003e\n\u003cp\u003eFunctional enrichment analysis of the two co-expression modules revealed their association with proliferation and degradation programs. Enrichment of DNA replication and cell cycle-related functions in the proliferation module supports the presence of tightly controlled mitotic programs in emerging buds [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. These processes are critical for maintaining genomic integrity while passing through cell cycle checkpoints and coordinating precise cell division across the colony. High telomerase activity reported in early budding stages further underscores the need for robust proliferative capacity to sustain continuous regeneration [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The proteasome also emerged as a central player, enriched in the proliferation module due to its role in protein turnover, proteostasis quality control, and cell cycle progression. Although proteasomal function emphasizes protein degradation, proteasome activation is also critical for proteostasis quality control in highly proliferative cells and its activation is consistent with the regulation of cyclins and cyclin-dependent kinase inhibitors via the ubiquitin-proteasome system (UPS) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In a colonial invertebrate like \u003cem\u003eB. schlosseri\u003c/em\u003e, synchronized regression and renewal likely depend on such precise proteostasis. Supporting this notion, stress response and protein quality control pathways were co-enriched, suggesting that proteasome-mediated degradation maintains developmental fidelity under fluctuating physiological conditions [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Enrichment of nucleocytoplasmic transport pathways further suggests active trafficking of regulatory proteins and RNAs between the nucleus and cytoplasm during rapid transitions. Ribosome biogenesis was also enriched during proliferative stages, further supporting a major role for proteostasis control during TOB maturation. Disruptions in ribosome production are known to impair cell growth and trigger cell cycle arrest, underscoring its importance in maintaining proliferative potential [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. As a tightly regulated and energy-intensive process, ribosome biogenesis supports sustained protein synthesis, which in turn fuels biomass accumulation, cell cycle progression, and differentiation. In proliferating cells, particularly during development or regeneration, upregulation of ribosomal RNA transcription, processing, and ribosomal protein production ensures sufficient translational capacity to meet the demands of rapid cell division [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These functional signatures in \u003cem\u003eB. schlosseri\u003c/em\u003e reinforce the importance of translational and proteasomal control as a key node linking growth signals to cell cycle regulation and tissue homeostasis. Together, these functional enrichments suggest that coordinated upregulation of cell cycle progression and proteostasis molecular machinery during takeover are essential for zooid renewal.\u003c/p\u003e\n\u003ch3\u003eFunctional Enrichment of a Degradation Program in TOZ\u003c/h3\u003e\n\u003cp\u003eIn contrast to the proliferation module, enrichment of ATP-binding cassette (ABC) transporters in the degradation module suggests increased membrane transport activity during zooid regression. These transporters may facilitate the controlled removal of metabolic byproducts or the transport of recycled nutrients from donor to acceptor cells, processes that are particularly important during large-scale tissue breakdown and remodeling [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Additional enrichment of peroxisome activity, calcium signaling, and protein digestion and absorption pathways reflects the early activation of catabolic processes that enable the recycling of cellular components to support new tissue development while minimizing inflammation [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Peroxisomal proteins, which are involved in lipid β-oxidation and detoxification of reactive oxygen species, may help mitigate oxidative damage and inflammation during tissue resorption [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. This is especially relevant in \u003cem\u003eB. schlosseri\u003c/em\u003e, where synchronous degeneration in densely packed zooids may create localized oxidative stress. Calcium signaling, which has major roles in regulating apoptosis, mitochondrial dynamics, and cytoskeletal remodeling [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], was also enriched during early regression stages but gradually declined. This trend may reflect the resolution of early remodeling events as regenerating tissues stabilize. Colonial ascidians often depend on localized tissue recycling to sustain growth in nutrient-limited environments [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Accordingly, the observed decline in proteases and related enzymes involved in protein degradation likely represents a transition from catabolic resource mobilization to anabolic biosynthesis. The enrichment of catabolic and metabolic remodeling pathways in the degradation module, which is highly expressed in regressing zooids, is consistent with a previous study that reported a markedly higher rate of apoptotic cells in collapsing zooids, particularly within the gut epithelium and the pyloric gland [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. These functional modulations revealed by proteomics are consistent with a prior transcriptomic analysis that identified dynamic regulation of apoptosis-related genes across the blastogenic cycle, particularly during pre-takeover and takeover stages [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The current proteomic results extend these findings to the protein level and to a more comprehensive set of proteins, revealing regulation of pathways associated with proteolysis and cytoskeletal remodeling. These findings support the interpretation that zooid resorption is a tightly regulated, energy-coupled process involving coordinated degradation, recycling, and detoxification. In addition, the key proteins driving these processes have been determined.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCDK1 as a Central Cell Cycle Regulator\u003c/h2\u003e \u003cp\u003eCDK1 is a master regulator of the cell cycle, essential for driving cells through the G₂/M transition and mitosis. In complex with cyclin B, CDK1 phosphorylates substrates required for chromatin condensation, nuclear envelope breakdown, and spindle assembly [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Beyond its canonical mitotic functions, CDK1 phosphorylates p53 at Ser315, influencing its stability and transcriptional activity and thereby linking cell cycle progression to the DNA damage response to maintain genomic integrity in proliferating cells [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. CDK1\u0026rsquo;s functional centrality is further underscored by its ability to sustain cell cycle progression in yeast as the sole CDK [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and to drive the mammalian cell cycle in the absence of other CDKs [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, CDK1 displayed the most pronounced stage-specific increase, occupying a central position in the pathway network and connecting directly to cyclin B and the Anaphase-Promoting Complex/cyclosome (APC/C) complex to coordinate mitotic entry and exit. Its upregulation in TOB indicates active licensing of cells to progress through G₂/M, consistent with the proliferative phenotype of primary buds. CDK2 was also significantly elevated, pointing to enhanced G₁/S transition and S-phase progression. CDK2, when bound to cyclins E or A, drives replication origin licensing and nucleotide biosynthesis [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Although CDK2 is functionally redundant with CDK1 in some mammalian systems [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], its upregulation here suggests that both kinases cooperate to fine-tune replication timing and maintain genome stability.\u003c/p\u003e \u003cp\u003eThe strong increase in PCNA, a DNA polymerase processivity factor and widely used marker of proliferation [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], further supports robust engagement of the replication machinery. PCNA also coordinates mismatch repair and translesion synthesis [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], suggesting that buds not only increase DNA synthesis but also enhance genome maintenance during rapid proliferation. Together, the combined upregulation of CDK1, CDK2, and PCNA points to a streamlined but highly active cell cycle network that may compensate for the apparent absence of the CDK4-CDKN2 axis reported missing in urochordates [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Additional CDKs such as CDK5 and CDK20 were detected but unchanged in abundance, further supporting CDK1\u0026rsquo;s dominant role as the primary driver of proliferation during blastogenesis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDNA Replication Licensing\u003c/h2\u003e \u003cp\u003eAll members of the MCM2-7 complex were significantly upregulated in TOB, consistent with their role as essential regulators of DNA replication licensing during the G₁ phase. The MCM2-7 complex forms the core of the pre-replicative helicase that is loaded onto origins of replication by the origin recognition complex (ORC), cell division cycle 6 (CDC6), and chromatin licensing and DNA replication factor (CDT1) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Once recruited in late mitosis and early G₁, MCM2-7 marks replication origins as competent for DNA synthesis, a prerequisite for S-phase entry. In mammalian systems, CDK2-Cyclin E activity triggers the transition from licensing to initiation by phosphorylating licensing factors and activating the MCM helicase, thereby ensuring once-per-cell-cycle replication [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. The increased abundance of MCM2-7 in proliferative buds suggests a robust replication licensing program, reinforcing their identity as the most actively dividing stage. Because defects in MCM loading can cause replication stress and genomic instability, elevated MCM2-7 may help safeguard genome integrity during the rapid and repeated cell cycles characteristic of \u003cem\u003eB. schlosseri\u003c/em\u003e blastogenesis [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. In this context, enhanced licensing capacity could reduce the likelihood of replication fork collapse and ensure faithful transmission of genetic material across successive budding cycles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCheckpoint Surveillance\u003c/h2\u003e \u003cp\u003eBUB3 was the only spindle assembly checkpoint protein detected in the study and was significantly upregulated in TOB. In the canonical mitotic checkpoint complex (MCC), BUB3 partners with mitotic arrest deficient 2 (MAD2) and spindle checkpoint protein BUBR1 to sequester cell division cycle 20 (CDC20), thereby delaying anaphase onset until all kinetochores are properly attached to spindle microtubules [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Through CDC20 sequestration, the MCC inhibits APC/C, preventing premature degradation of mitotic cyclins and sustaining CDK1 activity during metaphase to ensure faithful chromosome segregation. The elevated abundance of BUB3 suggests that primary buds maintain robust checkpoint signaling to preserve chromosomal stability during rapid mitotic cycles. Beyond its role in mitosis, BUB3 also contributes to genome stability during interphase by supporting efficient telomere replication and preventing replication stress [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. This dual functionality may be especially important for \u003cem\u003eB. schlosseri\u003c/em\u003e, where repeated rounds of blastogenesis require both faithful chromosome segregation and maintenance of telomere integrity. Given that chromosomal instability is a major barrier to long-term culture viability, sustained BUB3 activity could be critical for supporting both genomic fidelity and proliferative capacity, making it an informative biomarker and potential target for functional studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eChromatin Remodeling\u003c/h2\u003e \u003cp\u003eMultiple subunits of the NuRD complex, including HDAC2, RBBP4, and RBBP7, were significantly upregulated in TOB, indicating coordinated activation of the chromatin remodeling machinery during budding. As the catalytic core, HDAC2 removes acetyl groups from histones to promote chromatin condensation and transcriptional repression of cell-cycle inhibitors such as p21 and p57\u003csup\u003eKip2\u003c/sup\u003e, thereby facilitating CDK2 activation and G\u003csub\u003e1\u003c/sub\u003e/S progression [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Results from mammalian studies showed that loss of HDAC2 results in G\u003csub\u003e1\u003c/sub\u003e arrest [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e], underscoring its importance for cell-cycle re-entry. In addition to histone deacetylation, HDAC2 also acts on non-histone substrates, linking NuRD activity to DNA replication and repair [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. The concurrent upregulation of HDAC2, RBBP4, and RBBP7 suggests that TOB buds reinforce chromatin-mediated transcriptional control to sustain a proliferative transcriptional landscape. Notably, only HDAC2 was detected in this study, while HDAC1 was absent. This may indicate that HDAC2 is the primary histone deacetylase active during blastogenesis in \u003cem\u003eB. schlosseri\u003c/em\u003e. The clinical relevance of HDAC2 overexpression in multiple cancers, where it drives proliferation and therapy resistance [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e], further highlights its potential as a target for modulating proliferation and enhancing primary cell culture longevity in colonial tunicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eProteostasis and Degradation\u003c/h2\u003e \u003cp\u003eSKP1 was significantly upregulated in TOB and represents a core scaffold of the SCF (SKP1-Cullin-F-box) E3 ubiquitin ligase complex. SKP1 links CUL1, RBX1, and SKP2, components that collectively mediate targeted proteolysis of cell cycle regulators. SCF complexes are critical for G₁/S transition, where they promote the ubiquitination and degradation of CDK inhibitors such as p21 and p27, thereby allowing CDK activation and S-phase entry [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. They also ensure timely turnover of replication licensing factors and misfolded proteins, preventing re-replication and maintaining proteostasis [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. The elevation of SKP1 in TOB is therefore consistent with a regulatory state that prioritizes rapid but orderly cell cycle progression. From a translational perspective, SKP1 and SCF dysregulation have been implicated in multiple cancers, including lung and prostate cancer, and pharmacological targeting of SKP1 has shown anti-tumor activity in preclinical models [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. Its conserved and central role across species makes SKP1 a compelling candidate for manipulation in \u003cem\u003eB. schlosseri\u003c/em\u003e to promote proliferative competence while preserving genome integrity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBiosynthesis and Translational Activation\u003c/h2\u003e \u003cp\u003ePrimary buds exhibited significant upregulation of elongation factors along with multiple eIF3 subunits, indicating broad activation of the translational machinery. This upregulation suggests that buds increase biosynthetic capacity to meet the demands of accelerated proliferation. In metazoans, activation of biosynthetic pathways is commonly coordinated by the mTOR pathway, which promotes translation initiation and elongation through phosphorylation of targets such as S6K1 and 4E-BP1 [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. The broad increase in initiation and elongation factors strongly support enhanced biosynthetic output resembling the downstream effects of mTOR activity. However, the molecular details associated with such enhanced biosynthetic activity likely differ from canonical PI3K-AKT-mTORC1 activation since in \u003cem\u003eB. schlosseri\u003c/em\u003e RPS6KB2 (encoding S6K2) was detected but not significantly different in abundance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eIntegration of mitogen signaling, cell cycle checkpoint control, and chromatin regulation\u003c/h2\u003e \u003cp\u003eDespite the robust biosynthetic activation, several nodes of canonical mitogenic signaling were significantly downregulated in TOB relative to TOZ, including RRAS2, BRAF, and AKT1, which serve as central drivers of the RAS-BRAF-MEK-ERK and RRAS2-PI3K-AKT1-mTORC1 pathways. In mammalian systems, sustained PI3K-AKT activation can shift cells from growth toward senescence programs via mTORC1-dependent p53 accumulation and p21 induction, establishing a non-proliferative endpoint despite upstream \u0026ldquo;growth\u0026rdquo; signaling [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. In parallel, AKT-driven increases in ROS promote replicative or premature senescence and can sensitize cells to ROS-mediated apoptosis, further illustrating that these pathways often mediate stress responses rather than cell-cycle entry when chronically engaged [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. The reduction of these signaling nodes in proliferative buds thus suggests that in \u003cem\u003eB. schlosseri\u003c/em\u003e the downstream pro-proliferative effects of these mitogen-dependent G₁ circuits are predominately mediated by activation (i.e. phosphorylation of AKT) rather than protein abundance and restricting levels of key pathway nodes may protect against the anti-proliferative effects of hyperactivation. An additional explanation is chromatin-level control may be more consequential in TOB. The upregulation of HDAC2, a catalytic subunit of the NuRD complex, supports this view, as HDAC2 represses the transcription of CDK inhibitors such as p21, thereby indirectly activating CDK2 and facilitating G₁/S transition. This chromatin-based control provides an alternative route for sustaining proliferation when canonical mitogen signaling nodes are reduced.\u003c/p\u003e \u003cp\u003eBy contrast, the higher abundance of RRAS2, BRAF, and AKT1 in TOZ may reflect a shift to a non-proliferative role for these pathways during the takeover stage. Rather than driving cell-cycle progression, their activity in this context may help delay cell death in certain compartments, coordinate tissue breakdown in a regulated manner, buffer stress responses such as oxidative stress or caspase activation to minimize inflammatory signals or even induce apoptosis by hyperactivation [\u003cspan additionalcitationids=\"CR87\" citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. In mammalian systems, Ras and PI3K-AKT signaling are well-established mediators of cell survival, acting through inhibition of pro-apoptotic proteins, suppression of caspase activation, and modulation of Forkhead box O (FoxO) transcription factors [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. More recently, \u003cem\u003ein vivo\u003c/em\u003e work in \u003cem\u003eDrosophila\u003c/em\u003e demonstrated that Akt1 is required for cells to survive executioner caspase activation and contribute to tissue regeneration [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e], providing a direct precedent for the deployment of these pathways in degenerative or stress-laden contexts rather than for promoting proliferative capacity. Taken together, these findings raise the possibility that the differential protein abundance of these mitogen pathway components contribute to alternative roles between stages with Ras/AKT/BRAF signaling supplementing chromatin-based mechanisms in proliferative buds, while regressing zooids engage the pathway in a stress-adaptive, non-proliferative role [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther supporting this conclusion is the significant downregulation of MK3 (MAPKAPK3) in TOB relative to TOZ. As a downstream effector of the p38 MAPK pathway, MK3 integrates stress signals to modulate cell-cycle checkpoints. In the G₁ phase, MK3 can promote the transcriptional upregulation of p21, thereby restraining CDK2 activity, while in G₂ MK3 inhibits CDC25 to block premature CDK1 activation, consistent with known roles of p38-MK2/3 signaling in checkpoint enforcement [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Through these mechanisms, MK3 enforces stress-dependent checkpoints at both G₁/S and G₂/M transitions. Its reduced abundance in TOB suggests a relaxation of stress-responsive checkpoint signaling, consistent with a pro-proliferative state in emerging buds.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCandidate Proteins for Functional Manipulation of cell proliferation\u003c/h2\u003e \u003cp\u003eEfficient cell cycle re-entry, particularly through the G\u003csub\u003e1\u003c/sub\u003e/S transition, is a major bottleneck in establishing proliferative primary cultures [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. The present study highlights several proteins whose regulation in proliferative buds nominates them as strong candidates for manipulation to sustain long-term proliferation of cell cultures. CDK1 emerges as the primary driver of proliferation, with marked upregulation and direct control over G₂/M progression, while CDK2 supports G₁/S transition and replication initiation. Given the absence of CDK4/6 in \u003cem\u003eB. schlosseri \u0026rsquo;s\u003c/em\u003e genome, CDK1 and CDK2 likely assume broader responsibility for both G₁/S and G₂/M transitions, making them especially compelling targets for manipulation. PCNA, a processivity factor and reliable marker of proliferation, provides a useful proxy for confirming active DNA synthesis and could serve as a readout of successful cell-cycle re-entry. In parallel, HDAC2 (NuRD complex) and SKP1 (SCF complex) may enhance immortalization prospects by repressing CDK inhibitors such as p21, thereby indirectly sustaining CDK2 activity.\u003c/p\u003e \u003cp\u003eBy contrast, pathways that were downregulated in proliferative buds, including RAS/BRAF/MEK/ERK and PI3K/AKT1/mTORC1, are not supported by this study as drivers of proliferation during the blastogenic cycle. This finding likely reflects the specific developmental context of budding, where the effects of canonical mitogen inputs are not yet clear. However, this conclusion does not preclude their relevance under cell culture conditions, which impose a very different selective environment. For example, β-catenin, which is encoded in the \u003cem\u003eB. schlosseri\u003c/em\u003e genome, may still represent a viable manipulation target despite its lack of enrichment in this dataset, as its functional role often requires only modest protein abundance changes. Overall, these findings identify CDK1, CDK2, HDAC2, SKP1, and PCNA as the most compelling candidates for promoting cell-cycle re-entry and sustaining proliferation in \u003cem\u003eB. schlosseri\u003c/em\u003e primary cultures. In addition to identifying molecular targets, our results suggest that primary buds should be prioritized over adult zooids as starting material for cell cultures, since buds display the strongest activation of proliferative and biosynthetic pathways.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides the first proteome-wide map of the \u003cem\u003eB. schlosseri\u003c/em\u003e blastogenic cycle at the individual zooid level, revealing stage-specific shifts in protein abundance that underpin proliferation of buds and regression of adult zooids during blastogenesis. Primary buds are characterized by upregulation of CDK1, CDK2, the MCM2-7 complex, and PCNA, together with chromatin remodeling and translational machinery, consistent with an active biosynthetic program driving rapid proliferation. In contrast, regressing zooids engage stress-induced and senescence-associated regulators, highlighting a tightly regulated process of orderly tissue degradation and recycling that minimizes inflammation. These findings position \u003cem\u003eB. schlosseri\u003c/em\u003e as a powerful model for studying the coordination of proliferation and programmed degeneration in a naturally cycling developmental system. The study further nominates CDK1, CDK2, HDAC2, SKP1, and NuRD components as promising candidates for functional testing towards immortalization of primary cultures and validates \u003cem\u003eB. schlosseri\u003c/em\u003e PCNA as a reliable molecular marker of proliferation. Ultimately, this work provides mechanistic insight into colonial budding, lays out a roadmap of molecular targets for establishing immortalized cell lines in a colonial tunicate, and provides a foundation for future studies on post-translational regulation and stem cell activity.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003cdiv id=\"Sec30\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eAnimal Husbandry\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWild colonies of\u003cem\u003e\u0026nbsp;B. schlosseri\u003c/em\u003e were collected from floating docks at Berkeley Marina, California (United States). Larvae of these wild colonies were generated via sexual reproduction and attached as oozooids to glass slides at the UC Davis Cole B facility within one week after field collection. These lab-born colonies were then reared adhering to glass and kept vertically in 2.8 L glass tanks with 30ppt standing artificial sea water (ASW) at a constant temperature of 20 °C and aerated by air stones as described previously\u0026nbsp;[95]. All genotypes used in this study were raised from individually spawned, sexually reproduced oozooids and reared in separate tanks to avoid competition\u0026nbsp;[96]. Colonies were fed twice a week with a combination of live algae (\u003cem\u003eDunaliella, Tetraselmis, Isochry\u003c/em\u003esis and \u003cem\u003eNannochloropsis\u003c/em\u003e) and Roti-Rich Liquid Invertebrate Food (Florida Aqua Farms). ASW for each tank was fully changed every week, and colonies were gently cleaned once a week using soft brushes. All experimental colonies have been born and reared in stable lab conditions for at least 3 months, were in good health, and reproduced asexually via regular one-week blastogenic cycles.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTissue Dissection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eColonies were carefully cleaned and photographed before dissection under a stereomicroscope (Leica EZ4 W). To determine the appropriate blastogenic stages, the development of buds and zooids was monitored daily. A healthy colony completes a full blastogenic cycle every 7 to 8 days. Using two sterile size 0 insect pins, the colony tunic was sliced open from the common atrial siphon to the oral siphon. Individual zooids were therefore exposed and carefully removed from the colony.\u0026nbsp;Samples were kept on ice during dissection and snap-frozen in liquid nitrogen immediately afterwards, then transferred to a -80 °C freezer for storage. A total of at least 50 zooids\u0026nbsp;collected from each of the four blastogenic stages (A, B, C, and Takeover) and 70 primary buds from the takeover stage for each genotype were pooled per sample to ensure sufficient protein recovery. A total of three genotypes were used for the first study for five blastogenic stages and a total of seven genotypes were used for the second study for proteomics of TOB, SAZ, and TOZ stages.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSample Preparation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSample preparations were performed as previously described\u0026nbsp;[11]\u0026nbsp;with few modifications. Briefly, tissues were homogenized in lysis buffer (8 M urea, 50 mM ammonium bicarbonate (Ambic)) using 1 mm zirconium beads (Benchmark D1032010) and shaking in a microtube homogenizer (Benchmark beadbag) at 3500 rpm for 30 seconds. Proteins taken from the supernatant were then reduced using 5mM dithiothreitol (DTT) for 10 min at 60°C and alkylated with 15mM iodoacetamide (IAA) in the dark at room temperature for 30 min. Remaining free IAA was quenched by further increasing DTT to 10mM. After protein quantification, urea was diluted with 50 mM Ambic and subjected to trypsin/Lys-C (Thermofisher A40007) digestion at a 1:50 trypsin to protein ratio at 37°C for 3 hours. Post-digestion peptide cleanup was performed using Pierce C-18 spin columns (Thermo Scientific 89870) according to the manufacturer protocol. Peptide concentration was quantified using\u0026nbsp;Pierce fluorometric Quantitative Peptide Assay (Thermo Scientific 23290) before speedvac buffer exchange to 0.1% formic acid in LCMS water for LCMS analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLC-MS/MS Acquisition\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLiquid chromatography-mass spectrometry (LC-MS) acquisitions were performed following established protocols for quantitative label-free proteomics\u0026nbsp;[11]. Briefly, 100 ng of total peptide per sample was injected using a Bruker nanoElute 2 UPLC system operated in single column mode and equipped with a 25 cm x 150 µm x 1.5 µm Pepsep XTREME C18 reversed-phase analytical column (Bruker Daltonics 1893476). Peptide separation was achieved using a linear gradient of 3% to 33% acetonitrile in 0.1% formic acid over 60 minutes at a flow rate of 600 nL/min. The column temperature was maintained at 50°C. Mass spectrometry was performed using a UHD-Quadrupole time-of-flight (QTOF) mass spectrometer operating in positive ion mode (Bruker Impact II) interfaced online with the UPLC via a captive spray ionization source (Bruker CSI). For the first study, each sample was acquired twice, first in DDA mode to enable construction of a spectral library for these samples with Fragpipe\u0026nbsp;[97], and again using DIA acquiring MS2-only spectra. For the second study, only DIA was used but each DIA scan cycle of MS2 windows was supplemented by a corresponding MS1 spectrum to enable direct spectral library construction from these data. For the first study, each scan cycle consisted of 74 scan windows (390 - 1130 m/z) having a width of 10 ± 0.5 m/z and collected at a frequency of 50 Hz. For the second study, the same scan cycle parameters were applied except that each 1.5 sec scan cycle was preceded by acquisition of an MS1 spectrum obtained at the same scan rate (50 Hz) to enable annotation of corresponding precursor peptides and spectral library generation with Fragpipe without the need for a separate DDA run.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData Processing\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMass spectrometry raw DDA data for study 1 were processed using FragPipe 22.0, which integrates the MSFragger search engine for peptide identification and quantification\u0026nbsp;[98]. A spectral library was generated from the DDA runs and applied to the corresponding DIA data in Skyline\u0026nbsp;[99]\u0026nbsp;to extract and normalize transition peak areas by sample median abundance. Spectral libraries were filtered in Skyline to remove interferences and non-diagnostic ions as previously described\u0026nbsp;[11]. \u0026nbsp;For Study 2, DIA data were analyzed directly in FragPipe (v22.0) to generate a spectral library without additional DDA acquisition. The resulting library was imported into Skyline for filtering to exclude interferences and low-abundance proteins\u0026nbsp;[11]. Spectral library annotation was based on the predicted \u003cem\u003eB. schlosseri\u003c/em\u003e reference proteome from the most recent genome update\u0026nbsp;[100].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor relative quantitation all transition peak abundances were exported from Skyline and then normalized and extrapolated to protein abundances using DirectLFQ\u0026nbsp;[101]. Statistical comparisons were performed using the ProLFQua\u0026nbsp;[102]\u0026nbsp;package in R, applying ANOVA with multiple testing correction (FDR \u0026lt; 0.1) for study 1, and ANOVA and linear models with empirical Bayes moderation for study 2 to improve detection of differentially abundant proteins. To assess overall proteomic variation, Principal Component Analysis (PCA) (R package mixOmics) and hierarchical clustering were conducted on DAPs to visualize sample grouping and identify major sources of variation across conditions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWeighted Gene Co-expression Network Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCo-expression patterns were examined using Weighted Gene Co-expression Network Analysis (WGCNA)\u0026nbsp;[103]\u0026nbsp;to identify protein modules with coordinated expression changes across the blastogenic cycle. DAPs identified by ANOVA testing (FDR \u0026lt; 0.1) were selected for analysis after multiple testing correction. The soft-thresholding power (β) was determined based on the scale-free topology criterion, and the network was constructed using a \"signed\" network type, which considers only positive correlations between proteins. The Topological Overlap Matrix (TOM) was calculated with a signed TOMType, and the minimum module size was set to 20. Module detection was performed with the blockwiseModules function in R, and a merge cut height of 0.25 was applied to merge similar modules. Module-trait relationships were examined by correlating module eigengenes (MEs) with sample traits. To visualize the temporal dynamics of module expression across blastogenic stages, the average Log₂-transformed protein intensity for each module was plotted by condition. For each module, the mean Log₂ intensity of all proteins assigned to that module was calculated per biological replicate, and the group average and standard deviation were plotted across blastogenic stages.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunctional Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eProtein sequences derived from the \u003cem\u003eB. schlosseri\u003c/em\u003e proteome were functionally annotated using a two-step approach. First, BLASTP searches were performed against the SwissProt database using DIAMOND, with no taxonomic restrictions to assign functional annotations. Only annotations with an E-value \u0026lt; 10\u003csup\u003e-3\u003c/sup\u003e were considered. In addition, eggNOG\u0026nbsp;[104]\u0026nbsp;was used to identify orthologous relationships and retrieve KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotations.\u003c/p\u003e\n\u003cp\u003eFor the first study, functional enrichment analyses were performed using the clusterProfiler\u0026nbsp;[105]\u0026nbsp;R package to identify over-represented KEGG pathways within each co-expression module identified by WGCNA. Over-representation analyses (ORA) were conducted using a customized functional database derived from eggNOG annotations. The background set included all proteins from the first study, and protein sets analyzed corresponded to those within each co-expression module identified by WGCNA. KEGG pathway enrichment was assessed using the \u003cem\u003eenrichKEGG\u003c/em\u003e function, with the organism parameter set to \"ko\" (KEGG orthology). Statistical significance was assessed using the Benjamini-Hochberg (BH) multiple testing correction method, with pathways considered significantly enriched if the adjusted p-value (FDR) was \u0026lt; 0.1. To reduce redundancy, affinity propagation clustering was performed on significant pathways using the R package APCluster\u0026nbsp;[106], and enriched pathways were visualized with ggplot2. Pathways that were vertebrate-specific, human disease-specific, or biologically irrelevant to \u003cem\u003eB. schlosseri\u003c/em\u003e were manually filtered out prior to visualization.\u003c/p\u003e\n\u003cp\u003eFor the second study, differentially abundant proteins (DAPs) between TOB and TOZ were identified as described above and analyzed in STRING for functional enrichment. All significant DAPs were submitted using the “Proteins with Values/Ranks” input option against the predicted \u003cem\u003eB. schlosseri\u003c/em\u003e reference proteome\u0026nbsp;[100]. Enrichment results were subsequently examined with emphasis on KEGG pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGenotyping\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo confirm that the biological replicates used in this study represent independent genotypes, a panel of 12 polymorphic loci, the fusion-histocompatibility, or f\u003cem\u003euhc\u003c/em\u003e region, was tested across all seven \u003cem\u003eB. schlosseri\u003c/em\u003e colonies. The \u003cem\u003efuhc\u003c/em\u003e region is responsible for allorecognition between colonies and encompasses the highly variable fester gene family, with a range of 7-13 alleles per individual according to recent study [107]. Colonies were bred from wild populations and maintained separately under laboratory conditions to ensure consistent environmental exposure during the experimental timeline. Genomic DNA was extracted from tissue samples from each colony using the PureLink Genomic DNA Mini Kit (ThermoFisher Scientific) following the manufacturer’s protocol with a modified 7-hour incubation period. PCR was performed in 25 μL reaction volumes containing 12.5 μL of 2x EmeraldAmp Max HS PCR Master Mix (Takara), 0.5 μL each of forward and reverse primers for each locus, and 11.5 μL of DNA sample (sample volumes were calculated depending on individual DNA concentration to yield 50 ng of DNA and supplemented with MilliQ water to reach 11.5 μL). The thermal cycling protocol included an initial denaturation step at 94°C for 3 minutes, followed by denaturation at 98°C for 10 seconds, annealing at locus-specific temperatures for 30 seconds, extension at 72°C for 30 seconds, a 30 cycle repeat and a final extension at 72°C for 5 minutes. Primer sets used for genotyping are listed in Supplementary Table 2. PCR products were visualized using gel electrophoresis on a 1.5% agarose gel stained with SYBR Safe DNA Gel Stain (ThermoFisher Scientific) and imaged using UVP ChemStudio PLUS (Analytik Jena) with the SYBR Safe emission filter. Allele sizes were compared against the GeneRuler 50 bp DNA Ladder (ThermoFisher Scientific) to identify polymorphic patterns. Each colony was found to have 4 alleles on average in this region at different combinations of loci, confirming each colony represents a distinct genotype. The presence of unique banding patterns at multiple loci, as seen in representative gel images included in Supplemental Fig. S2, confirms the presence of distinct genotypes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll MS proteomics data and metadata generated and analyzed in this study have been deposited and are publicly available in PanoramaPublic (https://panoramaweb.org/vwd01kl.url) and ProteomeXchange (PXD065460).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project is supported by NSF Grant MCB - 2127516.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWD and DK conceived and designed the study. WD performed the experiments and collected the data. WD and MLe conducted proteomic analyses and statistical evaluations. MLe and DK developed software scripts and contributed to data processing. IE carried out genotyping, and IE, BL, and MLi maintained the tunicate colonies in the laboratory. WD drafted the initial manuscript, and DK, MLe, and JH provided critical revisions and editing. DK secured funding and oversaw project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Baruch Rinkevich (Israel Oceanography \u0026amp; Limnological Research, National Institute of Oceanography) and Ayelet Voskoboynik (Hopkins Marine Station, Stanford University) for the advice on rearing \u003cem\u003eB. schlosseri\u003c/em\u003e and dissection. We also thank Stefano Tiozzo for the improved reference proteome.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVoskoboynik A, Simon-Blecher N, Soen Y, Rinkevich B, De Tomaso AW, Ishizuka KJ, et al. Striving for normality: whole body regeneration through a series of abnormal generations. The FASEB Journal. 2007;21(7):1335\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eRicci L, Salmon B, Olivier C, Andreoni-Pham R, Chaurasia A, Ali\u0026eacute; A, et al. The onset of whole-body regeneration in Botryllus schlosseri: morphological and molecular characterization. Frontiers in Cell and Developmental Biology. 2022;10:843775.\u003c/li\u003e\n\u003cli\u003eVoskoboynik A, Weissman IL. Botryllus schlosseri, an emerging model for the study of aging, stem cells, and mechanisms of regeneration. Invertebrate Reproduction \u0026amp; Development. 2015 Jan 30;59(sup1):33\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eMunday R, Rodriguez D, Di Maio A, Kassmer S, Braden B, Taketa DA, et al. Aging in the colonial chordate, Botryllus schlosseri. Invertebrate Reproduction \u0026amp; Development. 2015 Jan 30;59(sup1):45\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eTasselli S, Ballin F, Franchi N, Fabbri E, Ballarin L. Expression of genes involved in oxidative stress response in colonies of the ascidian \u003cem\u003eBotryllus schlosseri\u003c/em\u003e exposed to various environmental conditions. Estuarine, Coastal and Shelf Science. 2017 Mar 5;187:22\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eDijkstra J, Simkanin C. Intraspecific response of colonial ascidians to variable salinity stress in an era of global change. Mar Ecol Prog Ser. 2016 June 9;551:215\u0026ndash;25.\u003c/li\u003e\n\u003cli\u003eDelsuc F, Brinkmann H, Chourrout D, Philippe H. Tunicates and not cephalochordates are the closest living relatives of vertebrates. Nature. 2006 Feb;439(7079):965\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eSabbadin A. Osservazioni sullo sviluppo, l\u0026rsquo;accrescimento e la riproduzione di \u003cem\u003eBotryllus schlosseri\u003c/em\u003e (Pallas), in condizioni di laboratorio. Bolletino di zoologia. 1955 Jan;22(2):243\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eManni L, Zaniolo G, Cima F, Burighel P, Ballarin L. Botryllus schlosseri: A model ascidian for the study of asexual reproduction. Developmental Dynamics. 2007;236(2):335\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eAnselmi C, Kowarsky M, Gasparini F, Caicci F, Ishizuka KJ, Palmeri KJ, et al. Two distinct evolutionary conserved neural degeneration pathways characterized in a colonial chordate. Proceedings of the National Academy of Sciences. 2022 July 19;119(29):e2203032119.\u003c/li\u003e\n\u003cli\u003eK\u0026uuml;ltz D, Gardell AM, DeTomaso A, Stoney G, Rinkevich B, Rinkevich Y, et al. Deep quantitative proteomics of North American Pacific coast star tunicate (Botryllus schlosseri). PROTEOMICS. 2024;24(15):2300628. \u003c/li\u003e\n\u003cli\u003eSaad MK, Yuen JSK, Joyce CM, Li X, Lim T, Wolfson TL, et al. Continuous fish muscle cell line with capacity for myogenic and adipogenic-like phenotypes. Sci Rep. 2023 Mar 29;13(1):5098.\u003c/li\u003e\n\u003cli\u003eVaughn JL, Goodwin RH, Tompkins GJ, McCawley P. The establishment of two cell lines from the insectspodoptera frugiperda (lepidoptera; noctuidae). In Vitro. 1977 Apr 1;13(4):213\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eRinkevich B, Pomponi SA. Advancing marine invertebrate cell line research: four key knowledge gaps. In Vitro CellDevBiol-Animal. 2025 May 1;61(5):493\u0026ndash;505.\u003c/li\u003e\n\u003cli\u003eRabinowitz C, Rinkevich B. Epithelial cell cultures from Botryllus schlosseri palleal buds: accomplishments and challenges. Methods Cell Sci. 2004 Jan 1;25(3):137\u0026ndash;48.\u003c/li\u003e\n\u003cli\u003eQarri A, K\u0026uuml;ltz D, Gardell AM, Rinkevich B, Rinkevich Y. Improved Media Formulations for Primary Cell Cultures Derived from a Colonial Urochordate. Cells. 2023 Jan;12(13):1709.\u003c/li\u003e\n\u003cli\u003eHawley‐Nelson P, Vousden KH, Hubbert NL, Lowy DR, Schiller JT. HPV16 E6 and E7 proteins cooperate to immortalize human foreskin keratinocytes. The EMBO Journal. 1989 Dec;8(12):3905\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eLinzer DIH, Levine AJ. Characterization of a 54K Dalton cellular SV40 tumor antigen present in SV40-transformed cells and uninfected embryonal carcinoma cells. Cell. 1979 May 1;17(1):43\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eBodnar AG, Ouellette M, Frolkis M, Holt SE, Chiu CP, Morin GB, et al. Extension of Life-Span by Introduction of Telomerase into Normal Human Cells. Science. 1998 Jan 16;279(5349):349\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eHesp K, van der Heijden JME, Munroe S, Sipkema D, Martens DE, Wijffels RH, et al. First continuous marine sponge cell line established. Sci Rep. 2023 Apr 8;13(1):5766.\u003c/li\u003e\n\u003cli\u003eAnoop BS, Puthumana J, Vazhappilly CG, Kombiyil S, Philip R, Abdulaziz A, et al. Immortalization of shrimp lymphoid cells by hybridizing with the continuous cell line \u003cem\u003eSf9\u003c/em\u003e leading to the development of \u0026lsquo;\u003cem\u003ePm\u003c/em\u003eLyO-\u003cem\u003eSf9\u003c/em\u003e .\u0026rsquo; Fish \u0026amp; Shellfish Immunology. 2021 June 1;113:196\u0026ndash;207.\u003c/li\u003e\n\u003cli\u003eQin Z, Ji A, Yan M, Liu D, Li X, Hu X, et al. Establishment of the first marine mollusk cell line from scallop (\u003cem\u003eChlamys farreri\u003c/em\u003e) trochophore. Aquaculture Reports. 2025 Mar 15;40:102626.\u003c/li\u003e\n\u003cli\u003eCastellano KR, Manner CJ, Kell RM, McAtee RM, Capozzi NM, Wray GA, et al. Genetically tractable embryonic cell lines from sea urchins Lytechinus variegatus and Strongylocentrotus purpuratus. Commun Biol. 2025 Oct 14;8(1):1457.\u003c/li\u003e\n\u003cli\u003eSimcox A, Mitra S, Truesdell S, Paul L, Chen T, Butchar JP, et al. Efficient Genetic Method for Establishing Drosophila Cell Lines Unlocks the Potential to Create Lines of Specific Genotypes. PLOS Genetics. 2008 Aug 1;4(8):e1000142.\u003c/li\u003e\n\u003cli\u003eNasmyth K. Control of the yeast cell cycle by the Cdc28 protein kinase. Current Opinion in Cell Biology. 1993 Apr 1;5(2):166\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eChotiner JY, Wolgemuth DJ, Wang PJ. Functions of cyclins and CDKs in mammalian gametogenesis\u0026dagger;. Biology of Reproduction. 2019 Sept 1;101(3):591\u0026ndash;601.\u003c/li\u003e\n\u003cli\u003eMa X, \u0026Oslash;vreb\u0026oslash; JI, Thompson EM. Evolution of CDK1 paralog specializations in a lineage with fast developing planktonic embryos. Frontiers in Cell and Developmental Biology. 2022;9:770939.\u003c/li\u003e\n\u003cli\u003eGoldstein O, Mandujano-Tinoco EA, Levy T, Talice S, Raveh T, Gershoni-Yahalom O, et al. Botryllus schlosseri as a Unique Colonial Chordate Model for the Study and Modulation of Innate Immune Activity. Mar Drugs. 2021 Aug 9;19(8):454.\u003c/li\u003e\n\u003cli\u003eRosental B, Kowarsky M, Seita J, Corey DM, Ishizuka KJ, Palmeri KJ, et al. Complex mammalian-like haematopoietic system found in a colonial chordate. Nature. 2018 Dec;564(7736):425\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eCima F, Perin A, Burighel P, Ballarin L. Protection from oxidative stress in immunocytes of the colonial ascidian Botryllus schlosseri: transcript characterization and expression studies. Biological Bulletin. 2017;232(3):199\u0026ndash;210.\u003c/li\u003e\n\u003cli\u003eBen-Hamo O, Rosner A, Rabinowitz C, Oren M, Rinkevich B. Coupling astogenic aging in the colonial tunicate Botryllus schlosseri with the stress protein mortalin. Developmental Biology. 2018 Jan;433(1):33\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eRodriguez D, Taketa DA, Madhu R, Kassmer S, Loerke D, Valentine MT, et al. Vascular aging in the invertebrate chordate Botryllus schlosseri. Frontiers in Molecular Biosciences. 2021;8:626827.\u003c/li\u003e\n\u003cli\u003eFranchi N, Ballin F, Manni L, Schiavon F, Basso G, Ballarin L. Recurrent phagocytosis-induced apoptosis in the cyclical generation change of the compound ascidian Botryllus schlosseri. Developmental \u0026amp; Comparative Immunology. 2016;62:8\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eCima F, Manni L, Basso G, Fortunato E, Accordi B, Schiavon F, et al. Hovering between death and life: natural apoptosis and phagocytes in the blastogenetic cycle of the colonial ascidian Botryllus schlosseri. Developmental \u0026amp; Comparative Immunology. 2010;34(3):272\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eBuccitelli C, Selbach M. mRNAs, proteins and the emerging principles of gene expression control. Nature Reviews Genetics. 2020 July 24;1\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eSchwanh\u0026auml;usser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, et al. Global quantification of mammalian gene expression control. Nature. 2011 May 19;473(7347):337\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eRoot L, Campo A, MacNiven L, Con P, Cnaani A, K\u0026uuml;ltz D. Nonlinear effects of environmental salinity on the gill transcriptome versus proteome of Oreochromis niloticus. Genomics. 2021;113:3235\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eWang ZY, Leushkin E, Liechti A, Ovchinnikova S, M\u0026ouml;\u0026szlig;inger K, Br\u0026uuml;ning T, et al. Transcriptome and translatome co-evolution in mammals. Nature. 2020 Dec;588(7839):642\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eLepr\u0026ecirc;tre M, Hamar J, Urias MB, K\u0026uuml;ltz D. Comparative Proteomics of Salinity Stress Responses in Fish and Aquatic Invertebrates. PROTEOMICS. n/a(n/a):e202400255.\u003c/li\u003e\n\u003cli\u003eCui M, Cheng C, Zhang L. High-throughput proteomics: a methodological mini-review. Lab Invest. 2022 Nov;102(11):1170\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003ePino LK, Just SC, MacCoss MJ, Searle BC. Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries. Molecular \u0026amp; Cellular Proteomics. 2020 July 1;19(7):1088\u0026ndash;103.\u003c/li\u003e\n\u003cli\u003eSabbadin A, Zaniolo G, Majone F. Determination of polarity and bilateral asymmetry in palleal and vascular buds of the ascidian Botryllus schlosseri. Developmental biology. 1975;46(1):79\u0026ndash;87.\u003c/li\u003e\n\u003cli\u003eLauzon RJ, Ishizuka KJ, Weissman IL. A cyclical, developmentally-regulated death phenomenon in a colonial urochordate. Developmental Dynamics. 1992;194(1):71\u0026ndash;83.\u003c/li\u003e\n\u003cli\u003eBallarin L, Manni L. Stem cells in sexual and asexual reproduction of Botryllus schlosseri (Ascidiacea, Tunicata): an overview. In: Rinkevich B, Matranga V, editors. Stem cells in marine organisms. Dordrecht: Springer Netherlands; 2009. p. 267\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eLaird DJ, Weissman IL. Telomerase maintained in self-renewing tissues during serial regeneration of the urochordate Botryllus schlosseri. Dev Biol. 2004 Sept 15;273(2):185\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eGoldberg AL. Protein degradation and protection against misfolded or damaged proteins. Nature. 2003 Dec;426(6968):895\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eGlickman MH, Ciechanover A. The Ubiquitin-Proteasome Proteolytic Pathway: Destruction for the Sake of Construction. Physiological Reviews. 2002 Apr;82(2):373\u0026ndash;428.\u003c/li\u003e\n\u003cli\u003eTomanek L. Environmental Proteomics: Changes in the Proteome of Marine Organisms in Response to Environmental Stress, Pollutants, Infection, Symbiosis, and Development. Annual Review of Marine Science. 2011 Jan 15;3(Volume 3, 2011):373\u0026ndash;99.\u003c/li\u003e\n\u003cli\u003eDestefanis F, Manara V, Bellosta P. Myc as a Regulator of Ribosome Biogenesis and Cell Competition: A Link to Cancer. International Journal of Molecular Sciences. 2020 Jan;21(11):4037.\u003c/li\u003e\n\u003cli\u003eThomas G. An encore for ribosome biogenesis in the control of cell proliferation. Nat Cell Biol. 2000 May;2(5):E71\u0026ndash;2.\u003c/li\u003e\n\u003cli\u003eRees DC, Johnson E, Lewinson O. ABC transporters: the power to change. Nat Rev Mol Cell Biol. 2009 Mar;10(3):218\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eBallarin L, Schiavon F, Manni L. Natural Apoptosis During the Blastogenetic Cycle of the Colonial Ascidian Botryllus schlosseri: A Morphological Analysis. jzoo. 2010 Feb;27(2):96\u0026ndash;102.\u003c/li\u003e\n\u003cli\u003eSchrader M, Fahimi HD. Peroxisomes and oxidative stress. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 2006 Dec 1;1763(12):1755\u0026ndash;66.\u003c/li\u003e\n\u003cli\u003eBerridge MJ, Bootman MD, Roderick HL. Calcium signalling: dynamics, homeostasis and remodelling. Nat Rev Mol Cell Biol. 2003 July;4(7):517\u0026ndash;29.\u003c/li\u003e\n\u003cli\u003eK\u0026uuml;rn U, Rendulic S, Tiozzo S, Lauzon RJ. Asexual Propagation and Regeneration in Colonial Ascidians. The Biological Bulletin. 2011 Aug;221(1):43\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eTiozzo S, Ballarin L, Burighel P, Zaniolo G. Programmed cell death in vegetative development: Apoptosis during the colonial life cycle of the ascidian \u003cem\u003eBotryllus schlosseri\u003c/em\u003e. Tissue and Cell. 2006 June 1;38(3):193\u0026ndash;201. \u003c/li\u003e\n\u003cli\u003eCampagna D, Gasparini F, Franchi N, Vitulo N, Ballin F, Manni L, et al. Transcriptome dynamics in the asexual cycle of the chordate Botryllus schlosseri. BMC Genomics. 2016 Apr 2;17(1):275.\u003c/li\u003e\n\u003cli\u003eEnserink JM, Kolodner RD. An overview of Cdk1-controlled targets and processes. Cell Div. 2010 May 13;5(1):11.\u003c/li\u003e\n\u003cli\u003eKciuk M, Gielecińska A, Mujwar S, Mojzych M, Kontek R. Cyclin-dependent kinases in DNA damage response. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 2022 May; 1877(3):188716.\u003c/li\u003e\n\u003cli\u003eSantamar\u0026iacute;a D, Barri\u0026egrave;re C, Cerqueira A, Hunt S, Tardy C, Newton K, et al. Cdk1 is sufficient to drive the mammalian cell cycle. Nature. 2007 Aug;448(7155):811\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eHonda R, Lowe ED, Dubinina E, Skamnaki V, Cook A, Brown NR, et al. The structure of cyclin E1/CDK2: implications for CDK2 activation and CDK2‐independent roles. The EMBO Journal. 2005 Feb 9;24(3):452\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eFagundes R, Teixeira LK. Cyclin E/CDK2: DNA replication, replication stress and genomic instability. Frontiers in Cell and Developmental Biology. 2021;9:774845.\u003c/li\u003e\n\u003cli\u003eIatropoulos MJ, Williams GM. Proliferation markers. Experimental and Toxicologic Pathology. 1996 Feb 1;48(2):175\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003eKelman Z. PCNA: structure, functions and interactions. Oncogene. 1997 Feb;14(6):629\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eYuki S, Sasaki S, Yamamoto Y, Murakami F, Sakata K, Araki I. Evolution of the Cdk4/6\u0026ndash;Cdkn2 system in invertebrates. Genes to Cells. 2024;29(11):1037\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eMaiorano D, Lutzmann M, M\u0026eacute;chali M. MCM proteins and DNA replication. Current Opinion in Cell Biology. 2006 Apr 1;18(2):130\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eBell SP, Dutta A. DNA Replication in Eukaryotic Cells. Annual Review of Biochemistry. 2002 July 1;71(Volume 71, 2002):333\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eDiffley JFX. Regulation of Early Events in Chromosome Replication. Current Biology. 2004 Sept 21;14(18):R778\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eSclafani RA, Holzen TM. Cell Cycle Regulation of DNA Replication. Annual Review of Genetics. 2007 Dec 1;41(Volume 41, 2007):237\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eGe XQ, Jackson DA, Blow JJ. Dormant origins licensed by excess Mcm2\u0026ndash;7 are required for human cells to survive replicative stress. Genes Dev. 2007 Dec 15;21(24):3331\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eIbarra A, Schwob E, M\u0026eacute;ndez J. Excess MCM proteins protect human cells from replicative stress by licensing backup origins of replication. Proceedings of the National Academy of Sciences. 2008 July;105(26):8956\u0026ndash;61.\u003c/li\u003e\n\u003cli\u003eLarsen NA, Al-Bassam J, Wei RR, Harrison SC. Structural analysis of Bub3 interactions in the mitotic spindle checkpoint. Proceedings of the National Academy of Sciences. 2007 Jan 23;104(4):1201\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eLi F, Kim H, Ji Z, Zhang T, Chen B, Ge Y, et al. The BUB3-BUB1 Complex Promotes Telomere DNA Replication. Mol Cell. 2018 May 3;70(3):395-407.e4.\u003c/li\u003e\n\u003cli\u003eSegr\u0026eacute; CV, Chiocca S. Regulating the Regulators: The Post-Translational Code of Class I HDAC1 and HDAC2. BioMed Research International. 2011;2011(1):690848.\u003c/li\u003e\n\u003cli\u003eHarms KL, Chen X. Histone Deacetylase 2 Modulates p53 Transcriptional Activities through Regulation of p53-DNA Binding Activity. Cancer Res. 2007 Apr 4;67(7):3145\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eWilting RH, Yanover E, Heideman MR, Jacobs H, Horner J, van der Torre J, et al. Overlapping functions of Hdac1 and Hdac2 in cell cycle regulation and haematopoiesis. EMBO J. 2010 Aug 4;29(15):2586\u0026ndash;97.\u003c/li\u003e\n\u003cli\u003eMiller KM, Tjeertes JV, Coates J, Legube G, Polo SE, Britton S, et al. Human HDAC1 and HDAC2 function in the DNA-damage response to promote DNA nonhomologous end-joining. Nat Struct Mol Biol. 2010 Sept;17(9):1144\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eWeichert W, R\u0026ouml;ske A, Gekeler V, Beckers T, Stephan C, Jung K, et al. Histone deacetylases 1, 2 and 3 are highly expressed in prostate cancer and HDAC2 expression is associated with shorter PSA relapse time after radical prostatectomy. Br J Cancer. 2008 Feb;98(3):604\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eJung KH, Noh JH, Kim JK, Eun JW, Bae HJ, Xie HJ, et al. HDAC2 overexpression confers oncogenic potential to human lung cancer cells by deregulating expression of apoptosis and cell cycle proteins. Journal of Cellular Biochemistry. 2012;113(6):2167\u0026ndash;77.\u003c/li\u003e\n\u003cli\u003eBai C, Sen P, Hofmann K, Ma L, Goebl M, Harper JW, et al. SKP1 Connects Cell Cycle Regulators to the Ubiquitin Proteolysis Machinery through a Novel Motif, the F-Box. Cell. 1996 July 26;86(2):263\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eSilverman JS, Skaar JR, Pagano M. SCF ubiquitin ligases in the maintenance of genome stability. Trends in Biochemical Sciences. 2012 Feb 1;37(2):66\u0026ndash;73. \u003c/li\u003e\n\u003cli\u003eLi X, Mamouni K, Zhao R, Bai L, Chen Y, Wu Y, et al. Novel Skp1 inhibitor has potent preclinical efficacy against castration-resistant prostate cancer. Br J Cancer. 2025 June;132(12):1188\u0026ndash;99.\u003c/li\u003e\n\u003cli\u003eHay N, Sonenberg N. Upstream and downstream of mTOR. Genes Dev. 2004 Aug 15;18(16):1926\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eAstle MV, Hannan KM, Ng PY, Lee RS, George AJ, Hsu AK, et al. AKT induces senescence in human cells via mTORC1 and p53 in the absence of DNA damage: implications for targeting mTOR during malignancy. Oncogene. 2012 Apr;31(15):1949\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eNogueira V, Park Y, Chen CC, Xu PZ, Chen ML, Tonic I, et al. Akt determines replicative senescence and oxidative or oncogenic premature senescence and sensitizes cells to oxidative apoptosis. Cancer Cell. 2008 Dec 9;14(6):458\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eGao Y, Zhang D, Wang F, Zhang D, Li P, Wang K. BRAF V600E protect from cell death via inhibition of the mitochondrial permeability transition in papillary and anaplastic thyroid cancers. J Cell Mol Med. 2022 July;26(14):4048\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eXu W, Zheng H, Fu Y, Gu Y, Zou H, Yuan Y, et al. Role of PI3K/Akt-Mediated Nrf2/HO-1 Signaling Pathway in Resveratrol Alleviation of Zearalenone-Induced Oxidative Stress and Apoptosis in TM4 Cells. Toxins (Basel). 2022 Oct 26;14(11):733.\u003c/li\u003e\n\u003cli\u003eBalmanno K, Cook SJ. Tumour cell survival signalling by the ERK1/2 pathway. Cell Death Differ. 2009 Mar;16(3):368\u0026ndash;77.\u003c/li\u003e\n\u003cli\u003eDownward J. Ras signalling and apoptosis. Current Opinion in Genetics \u0026amp; Development. 1998 Feb 1;8(1):49\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eKennedy SG, Kandel ES, Cross TK, Hay N. Akt/Protein Kinase B Inhibits Cell Death by Preventing the Release of Cytochrome c from Mitochondria. Mol Cell Biol. 1999 Aug;19(8):5800\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eSun G, Ding X, Argaw Y, Guo X, Montell DJ. Akt1 and dCIZ1 promote cell survival from apoptotic caspase activation during regeneration and oncogenic overgrowth. Nat Commun. 2020 Nov 12;11(1):5726.\u003c/li\u003e\n\u003cli\u003ePeiris TH, Ramirez D, Barghouth PG, Oviedo NJ. The Akt signaling pathway is required for tissue maintenance and regeneration in planarians. BMC Developmental Biology. 2016 Apr 11;16(1):7.\u003c/li\u003e\n\u003cli\u003eThornton TM, Rincon M. Non-Classical P38 Map Kinase Functions: Cell Cycle Checkpoints and Survival. Int J Biol Sci. 2008 Dec 19;5(1):44\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eHume S, Dianov GL, Ramadan K. A unified model for the G1/S cell cycle transition. Nucleic Acids Research. 2020 Dec 16;48(22):12483\u0026ndash;501.\u003c/li\u003e\n\u003cli\u003eRinkevich B, Shapira M. An improved diet for inland broodstock and the establishment of an inbred line form Botryllus schlosseri, a colonial sea squirt (Ascidiacea). Aquatic Living Resources. 1998 May 1;11(3):163\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eTaketa DA, Nydam ML, Langenbacher AD, Rodriguez D, Sanders E, De Tomaso AW. Molecular evolution and in vitro characterization of Botryllus histocompatibility factor. Immunogenetics. 2015 Oct 1;67(10):605\u0026ndash;23.\u003c/li\u003e\n\u003cli\u003eKong AT, Leprevost FV, Avtonomov DM, Mellacheruvu D, Nesvizhskii AI. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry\u0026ndash;based proteomics. Nat Methods. 2017 May;14(5):513\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eDemichev V, Szyrwiel L, Yu F, Teo GC, Rosenberger G, Niewienda A, et al. dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts. Nat Commun. 2022 July 8;13(1):3944.\u003c/li\u003e\n\u003cli\u003ePino LK, Searle BC, Bollinger JG, Nunn B, MacLean B, MacCoss MJ. The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. Mass Spectrom Rev. 2017;39(3):229\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eDe Thier O, Lebel M, M.Tawfeeq M, Faure R, Dru P, Blanchoud S, et al. First chromosome-level genome assembly of the colonial chordate model Botryllus schlosseri (Tunicata). Gigascience. 2025 Jan 1;14:giaf097.\u003c/li\u003e\n\u003cli\u003eAmmar C, Schessner JP, Willems S, Michaelis AC, Mann M. Accurate Label-Free Quantification by directLFQ to Compare Unlimited Numbers of Proteomes. Mol Cell Proteomics. 2023 July;22(7):100581.\u003c/li\u003e\n\u003cli\u003eWolski WE, Nanni P, Grossmann J, d\u0026rsquo;Errico M, Schlapbach R, Panse C. prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis. J Proteome Res. 2023 Mar 20;22(4):1092\u0026ndash;104.\u003c/li\u003e\n\u003cli\u003eLangfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008 Dec 29;9(1):559.\u003c/li\u003e\n\u003cli\u003eJensen LJ, Julien P, Kuhn M, von Mering C, Muller J, Doerks T, et al. eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic Acids Research. 2008 Jan 1;36(suppl_1):D250\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eXu S, Hu E, Cai Y, Xie Z, Luo X, Zhan L, et al. Using clusterProfiler to characterize multiomics data. Nat Protoc. 2024 Nov;19(11):3292\u0026ndash;320.\u003c/li\u003e\n\u003cli\u003eBodenhofer U, Kothmeier A, Hochreiter S. APCluster: an R package for affinity propagation clustering. Bioinformatics. 2011 Sept 1;27(17):2463\u0026ndash;4. \u003c/li\u003e\n\u003cli\u003eRodriguez-Valbuena H, Salcedo J, De Thier O, Flot JF, Tiozzo S, De Tomaso AW. Exceptional diversity of allorecognition receptors in a nonvertebrate chordate reveals principles of innate allelic discrimination. Proceedings of the National Academy of Sciences. 2025 Oct 28;122(43):e2519372122.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Proteins annotated to the cell cycle KEGG pathway that are significantly enriched in takeover buds (TOB) relative to takeover zooids (TOZ).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOB vs. TOZ log\u003csub\u003e2\u003c/sub\u003eFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOB vs. TOZ FDR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16515.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eMCM3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eDNA replication licensing factor MCM3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.07E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg12813.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003ePCNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eProliferating cell nuclear antigen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e8.80E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8245.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eMCM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eDNA replication licensing factor MCM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.98E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg15498.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eMCM5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eDNA replication licensing factor MCM5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e5.70E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg5003.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eMCM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eDNA replication licensing factor MCM7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e5.70E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg7006.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eMCM4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eDNA replication licensing factor MCM4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.66E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg12939.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eMCM6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eDNA replication licensing factor MCM6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.05E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg6262.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eCDK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eCyclin-dependent kinase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.07E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg4249.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eBUB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eMitotic checkpoint protein BUB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.12E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8176.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eCDK2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eCyclin-dependent kinase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.05E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16459.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eHDAC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eHistone deacetylase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e3.21E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg13343.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eSKP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eS-phase kinase-associated protein 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.63E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg7055.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003eSMC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eStructural maintenance of chromosomes protein 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.03E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg3091.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e14-3-3 homologues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e14-3-3 protein family (multiple isoforms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.26E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg7214.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e14-3-3 homologues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e14-3-3 protein family (multiple isoforms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.48E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg3093.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 87px;\"\u003e\n \u003cp\u003e14-3-3 homologues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e14-3-3 protein family (multiple isoforms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.30E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: log₂FC, log₂-transformed fold change; FDR, false discovery rate. Proteins were considered significantly enriched with FDR \u0026lt; 0.05.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Proteins annotated to the senescence KEGG pathway that are significantly enriched in takeover buds (TOB) relative to takeover zooids (TOZ).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOB vs. TOZ log\u003csub\u003e2\u003c/sub\u003eFC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOB vs. TOZ FDR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg10555.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eFKBP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eFK506-binding protein 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.87E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg6262.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCDK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCyclin-dependent kinase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.07E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8433.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eRBBP7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eHistone-binding protein RBBP7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.01E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8176.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCDK2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCyclin-dependent kinase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.05E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8750.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eRBBP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eHistone-binding protein RBBP4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.99E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg13710.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCALML4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCalmodulin-like protein 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.54E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg11286.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eSLC25A31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eADP/ATP translocase 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e3.86E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg2262.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eMK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eMAPK-activated protein kinase 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.43E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg4884.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eBRAF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eSerine/threonine-protein kinase B-Raf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.89E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg1830.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eAKT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eRAC-alpha serine/threonine-protein kinase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e5.55E-03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg11271.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCALM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCalmodulin-like protein 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.09E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg2613.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCAPN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCalpain-1 catalytic subunit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.66E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg15547.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eRRAS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eRas-related protein R-Ras2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.66E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg6575.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCALML6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCalmodulin-like protein 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.74E-03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg3428.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eCALML3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eCalmodulin-like protein 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e-1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e9.73E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: log₂FC, log₂-transformed fold change; FDR, false discovery rate. Proteins were considered significantly enriched with FDR \u0026lt; 0.05.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEukaryotic elongation factors and\u0026nbsp;translation initiation factor 3 subunits detected in \u003cem\u003eB. schlosseri\u003c/em\u003e proteomic study.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProtein ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eName\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOB_TOZ_log2FC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOB_TOZ_FDR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg6116.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEEF1B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eElongation factor 1-beta 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.65E-02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg15448.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEEF1D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eElongation factor 1-delta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e9.08E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg5674.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEEF1G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eElongation factor 1-gamma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e2.48E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16622.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEEF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eElongation factor 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e9.93E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8702.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEEF2K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic elongation factor 2 kinase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.74E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg2023.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.32E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg14342.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.69E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg5249.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e7.53E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg2542.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.16E-03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16921.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e5.43E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg2844.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.26E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16953.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.46E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16407.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.61E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg1065.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.78E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16501.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3J\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit J\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e7.90E-03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg16236.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6.16E-04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg11765.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4.39E-03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eg8379.t1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eEIF3M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 3 subunit M\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e1.61E-06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eEukaryotic elongation factors (EEF2, EEF2K, EEF1G, EEF1D, EEF1B2) and multiple subunits of the eukaryotic translation initiation factor 3 (eIF3) complex were identified in the proteomic studies. All were significantly upregulated in primary buds (TOB) relative to regressing zooids (TOZ), consistent with broad activation of the translational machinery to support proliferative demands. Abbreviations: log₂FC, log₂-transformed fold change; FDR, false discovery rate. Proteins were considered significantly enriched with FDR \u0026lt; 0.05.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-molecular-and-cell-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cebi","sideBox":"Learn more about [BMC Molecular and Cell Biology](https://bmcmolcellbiol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/cebi/default.aspx","title":"BMC Molecular and Cell Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"mass spectrometry, proteomics, Botryllus schlosseri, cell proliferation, asexual reproduction, tunicates","lastPublishedDoi":"10.21203/rs.3.rs-8094443/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8094443/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe colonial tunicate \u003cem\u003eBotryllus schlosseri\u003c/em\u003e undergoes a weekly blastogenic cycle in which old zooids regress while new buds proliferate. Despite this species\u0026rsquo; advantages for studying coordinated proliferation and degeneration, proteome-level regulation across blastogenic stages and actionable targets for advancing proliferation of cell culture models remain undefined.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDIA proteomics enabled quantitation of 15,156 unique peptides mapping to 3,155 unambiguous protein groups across zooids from four blastogenic cycle stages and takeover primary buds (TOB), with 1,432 proteins (45%) changing significantly across these stages. Principal component analysis (PCA) and network analyses revealed most distinct proteomes in TOB versus regressing takeover zooids (TOZ). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that TOB were enriched in DNA replication, cell cycle progression, ribosome biogenesis, and translation pathways, reflecting a strong proliferative and biosynthetic program. Analysis of differentially abundant proteins and enriched pathways across different blastogenic stages revealed that the regulation of cyclin-dependent kinase 1 (CDK1), CDK2, replication licensing, chromatin remodeling, proteostasis, and enhancing translation are central to the TOB proliferation program. In contrast, TOZ were enriched for pathways associated with stress responses, proteolysis, metabolic remodeling, and catabolism, indicating a proteomic signature of programmed degradation and macromolecular integrity control during zooid regression.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe pro- and anti-proliferative proteomic signatures identified CDK1, CDK2, histone deacetylase 2 (HDAC2), S-phase kinase-associated protein 1 (SKP1), and proliferating cell nuclear antigen (PCNA) as the major nodes to be targeted for manipulation of cell proliferation \u003cem\u003ein vitro\u003c/em\u003e to overcome crisis/senescence and achieve reliable immortalization of tunicate cell lines.\u003c/p\u003e","manuscriptTitle":"Proteome Dynamics Across the Blastogenic Cycle of Botryllus schlosseri Reveals Targets for Cell Immortalization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 17:01:27","doi":"10.21203/rs.3.rs-8094443/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-26T05:46:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T19:34:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248831097847925983710421346076956356842","date":"2026-02-06T11:36:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150812712513480821935244396797081912253","date":"2026-02-06T05:14:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-07T10:57:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-06T04:48:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-25T07:10:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-25T07:07:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Molecular and Cell Biology","date":"2025-11-12T09:07:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-molecular-and-cell-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cebi","sideBox":"Learn more about [BMC Molecular and Cell Biology](https://bmcmolcellbiol.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/cebi/default.aspx","title":"BMC Molecular and Cell Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1256d8d-209c-4bfa-8ba9-0ece3c34e288","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-09T17:01:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 17:01:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8094443","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8094443","identity":"rs-8094443","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}