Genome Amplification and Altered Transcriptome aid in Survival and Enhanced Protein Secretion in Tunicamycin-Resistant CHOK1 cells

Genome Amplification and Altered Transcriptome aid in Survival and Enhanced Protein Secretion in Tunicamycin-Resistant CHOK1 cells | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Biotechnology Journal This is a preprint and has not been peer reviewed. Data may be preliminary. 18 June 2025 V1 Latest version Share on Genome Amplification and Altered Transcriptome aid in Survival and Enhanced Protein Secretion in Tunicamycin-Resistant CHOK1 cells Authors : Priya Mishra and Sarika Mehra 0000-0003-3844-4726 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175027718.88363387/v1 Published Biotechnology Journal Version of record Peer review timeline 572 views 278 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Chinese Hamster Ovary (CHO) cells are the predominant host for the production of biotherapeutics; however, there remains a considerable potential to further enhance their cellular productivity. Adaptive laboratory evolution (ALE) combined with omics-based analysis has emerged as a promising approach towards generating host cell lines with desirable characteristics. In this study, CHOK1 cells were gradually adapted to tunicamycin (TM), an endoplasmic reticulum (ER) stressor, resulting in an 8-fold increase in resistance compared to the non-adapted cells. Notably, a 3 to 4-fold increase was seen in the amount of total secreted protein in the TM-adapted cells. Transcriptomic analysis revealed upregulation of several genes in the protein processing pathway, such as Dpagt1, the TM target gene, and ER stress response genes. The protein transport, secretion and ubiquitination pathways were also altered, potentially contributing to the increased protein secretion. Furthermore, genes participating in signalling cascades of PI3K-AKT, MAPK and Ras pathways were differentially expressed, thereby aiding in its survival and proliferation. Whole genome sequencing confirmed the amplification of a large genome segment of chromosome 4, which included several genes upregulated at the mRNA level, including Dpagt1. However, overexpression of the Dpagt1 gene alone in the non-adapted cells did not replicate the phenotype of TM-adapted cells, signifying the role of other genes present in the amplified region. Thus, the survival and increased protein secretion of TM-adapted cells can be attributed to a combination of transcriptional level changes and amplification of a large genome segment, underscoring the importance of ALE as a cell engineering strategy. Genome Amplification and Altered Transcriptome aid in Survival and Enhanced Protein Secretion in Tunicamycin-Resistant CHOK1 cells Priya Mishra 1 , Sarika Mehra 1,* 1 Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India *Email address : [email protected] Chinese Hamster Ovary (CHO) cells are the predominant host for the production of biotherapeutics; however, there remains a considerable potential to further enhance their cellular productivity. Adaptive laboratory evolution (ALE) combined with omics-based analysis has emerged as a promising approach towards generating host cell lines with desirable characteristics. In this study, CHOK1 cells were gradually adapted to tunicamycin (TM), an endoplasmic reticulum (ER) stressor, resulting in an 8-fold increase in resistance compared to the non-adapted cells. Notably, a 3 to 4-fold increase was seen in the amount of total secreted protein in the TM-adapted cells. Transcriptomic analysis revealed upregulation of several genes in the protein processing pathway, such as Dpagt1, the TM target gene, and ER stress response genes. The protein transport, secretion and ubiquitination pathways were also altered, potentially contributing to the increased protein secretion. Furthermore, genes participating in signalling cascades of PI3K-AKT, MAPK and Ras pathways were differentially expressed, thereby aiding in its survival and proliferation. Whole genome sequencing confirmed the amplification of a large genome segment of chromosome 4, which included several genes upregulated at the mRNA level, including Dpagt1. However, overexpression of the Dpagt1 gene alone in the non-adapted cells did not replicate the phenotype of TM-adapted cells, signifying the role of other genes present in the amplified region. Thus, the survival and increased protein secretion of TM-adapted cells can be attributed to a combination of transcriptional level changes and amplification of a large genome segment, underscoring the importance of ALE as a cell engineering strategy. Keywords: protein secretion, ER stress, tunicamycin, genome amplification, CHO cells Introduction Chinese Hamster Ovary (CHO) cells are one of the most common mammalian cell lines, used for the production of over 70% of biopharmaceuticals. In order to meet the increase in demand for biopharmaceuticals while simultaneously reducing overall cost, a key strategy is to engineer cell lines that combine high recombinant gene expression with high growth rate and increased protein productivity (Fischer et al., 2015). In comparison, plasma B-cells are known to exhibit exceptionally high antibody secretion rates greater than 200 pg/cell/day (Slifka et al., 1998). Although, specific productivities of recombinant proteins in CHO cells are much lower, their maximum theoretical capacity has been estimated to be 80-150 pg/cell/day (Gutierrez et al., 2020). To bridge this gap and boost productivity, numerous studies have focussed on modifying pathways related to protein secretion, metabolism, cell cycle, apoptosis, etc. (Amiri et al., 2023; Bandaranayake & Almo, 2014; J. Y. Kim et al., 2012). Protein production can be hindered by endoplasmic reticulum (ER) stress, where an imbalance between the incoming peptides and the ER processing capacity leads to the accumulation of unfolded proteins (Y. Zhou et al., 2018). To maintain homeostasis, cells activate the expression of multiple genes that enhance protein folding, secretion and degradation. However, prolonged stress leads to apoptosis (Walter & Ron, 2011). Numerous studies have employed genetic engineering to modulate the complex protein processing pathway to achieve improved secretion (Gutiérrez-González et al., 2019; Kalkan et al., 2023). There are multiple studies where overexpression of a single gene such as PDI, BiP, Atf4 has been employed to improve protein production (Borth et al., 2005; Haredy et al., 2011; Jiang et al., 2017; Tan et al., 2015; Tigges & Fussenegger, 2006). In recent years, overexpression of more than one transcription factor and chaperones are being explored. For example, CHO cells engineered to overexpress Hsp27 and Hsp70 (Y. Y. Lee et al., 2009), Myc and Xbp1s (Latorre et al., 2023), Blimp1 and Xbp1s (Torres & Dickson, 2021, 2022) exhibited improved secretion of the recombinant protein by 2 to 3-fold. Notably, the increase in titers was more in combination compared to single gene alone. Although numerous studies have reported enhanced productivity by targeting one or more genes, we are far from achieving the maximum theoretical productivity levels, reiterating the need to simultaneously modulate multiple pathways. An alternate approach to host cell line engineering is adaptive laboratory evolution. Widely used for bacterial systems (Dragosits & Mattanovich, 2013; Sandberg et al., 2019), evolution-based strategies have been minimally explored in mammalian systems, possibly due to technical challenges. A few examples include adaptation to glutamine-free media (Bort et al., 2010) and adaptation coupled with FACS to identify fast-growing cells (Weinguny et al., 2020). To improve recombinant protein titers or improve the expression of difficult-to-express bispecific antibodies, adaptation of CHOK1 cells to low temperatures (Sunley et al., 2008; Syddall et al., 2023) and a hydrogen peroxide-evolved CHO host cell (Mistry et al., 2021) have been explored. A key advantage of the adaptive evolution approach is the modulation of the entire cellular machinery simultaneously towards the phenotype, such as cellular growth and protein production. This is particularly useful for complex pathways such as the protein secretion pathway, as demonstrated in our earlier work, where recombinant CHO-DG44 cells adapted to tunicamycin (TM) provides evidence of activation of the unfolded protein response (UPR) pathway, leading to increased recombinant protein secretion (Chandrawanshi et al., 2020). Omics-based analyses have significantly enhanced our understanding of the cellular and molecular characteristics of engineered CHO cells, specifically with regards to protein secretion (Raab et al., 2024; Yusufi et al., 2017). Genes involved in protein secretion and transport have been found to be differentially expressed in many recombinant CHO cell lines under conditions of high productivity (Kantardjieff et al., 2010; Sha et al., 2018; Orellana et al., 2018). Although limited, proteomics, metabolomics, lipidomic and glycomics have also been applied for the characterization of CHO cells (Chong et al., 2012; Kaushik et al., 2020; Villiger et al., 2016; Y. Zhang et al., 2017). Multi-omics studies further elucidate the complexities in these cells; for example, to study the effect of varied pH on intracellular processes in recombinant CHO cells, authors employed transcriptomics, proteomics, metabolomics and glycomics (A. P. Lee et al., 2021). These omics-based approaches provide a comprehensive view of the changes occurring at the genome, transcriptome and proteome levels, helping to identify key genes and pathways that can be targeted for cell line development and bioprocess optimization. In this study, we employ a combinatorial approach integrating adaptive laboratory evolution and omics-based analysis to explore the underlying mechanisms of adaptation to TM and its impact on cell growth and protein secretion. We adapted CHOK1 suspension cells, to increasing concentrations of TM and assessed their growth, survival, and protein secretion. The mechanisms of adaptation and enhanced protein secretion were investigated through transcriptomic and whole genome sequencing analyses. 2. Materials and Methods 2.1 Cell Culturing A CHOK1 derived cell line, generated in-house was adapted to serum-free suspension culture. The suspension-adapted CHOK1 cells were cultured in a media containing 50% CHO-S-SFM II (Gibco-Invitrogen) and 50% Proprietary media (HiMedia) supplemented with 4mM Glutamine and 500 μg/mL Geneticin (HiMedia). The cells were grown at 37°C, 8% CO 2 under shaking at 110 RPM. Growth profile analysis was conducted in a batch mode with a 20 mL volume in an Erlenmeyer flask (Corning). The growth analysis was carried out in the presence and absence of TM (Sigma-Aldrich). The Trypan Blue exclusion dye method was used to determine the viable cell density (VCD) and viability of the cultures. 2.2 Adaptation of CHOK1 cells to TM Cells were seeded at a density of 0.6 million cells/mL in an Erlenmeyer flask (Corning) with a total volume of 10 mL. After 24 hours, tunicamycin or TM (Sigma-Aldrich) was added to the flask and incubated for 40 hours. Post incubation, the cells were centrifuged at 1200 RPM for 5 min and resuspended in fresh 10 mL complete media without TM. The cells were further incubated until at least 85-90% viability was reached. The cells were then passaged to a seeding density of 0.6 million cells/mL, and the process was repeated with the next TM concentration. Based on the increment seen in viability after 40 h of TM treatment and 24 h after removal of TM, along with the period of recovery, either the same or double TM concentration was used in the next round of treatment. The TM-adapted and non-adapted cells are referred to as CHO_TM and CHO_C, respectively. RNA was extracted from three biological replicates (about 10 million cells), each of CHO_C and CHO_TM (in the absence of TM) cultures on day 4. 2.3 Bradford Assay The total secreted protein in the CHO_C and CHO_TM batch cultures in the absence of TM was measured using Bradford’s assay (Kielkopf et al., 2020). The supernatant collected from each culture day was centrifuged to remove the cells. To 40 μL of standard/sample, 160 μL of Bradford reagent was added and read at 595 nm on a Multiplate reader (Molecular Devices). The total protein for each sample was determined by interpolating to the BSA standard plot from 0 to 60 μg/mL. not-yet-known not-yet-known not-yet-known unknown 2.4 RNA Library Preparation and Sequencing RNA extraction was done using TRI Reagent (Merck) as per the manufacturer’s protocol. The extracted RNA was quantified using a Qubit fluorometer (Thermo Fisher Scientific), and the RNA integrity was determined using 4150 TapeStation System (Agilent Technologies). RNA with RIN value ≥ 9 were proceeded for the library preparation. The TruSeq Stranded Total RNA Preparation kit (Illumina) was used to generate cDNA libraries as per the manufacturer’s protocol. The obtained libraries were quantified using a Qubit fluorometer (Thermo Fisher Scientific) and 4150 TapeStation System (Agilent Technologies). The validated libraries were normalised, pooled and sequenced on the Illumina platform. Pair-end sequencing was carried out, giving an output of at least 35 million reads per sample. The raw FASTQ files were analysed on the Galaxy platform (usegalaxy.org) (The Galaxy Community, 2022). 2.5 Differential Gene Expression Analysis The quality of the raw reads was verified using FASTQC ( Babraham Bioinformatics - FastQC A Quality Control Tool for High Throughput Sequence Data , n.d.) . The reverse-stranded data sets were aligned to the Chinese Hamster genome ( GCF_003668045.3 ) using the HISAT2 tool (D. Kim et al., 2015) . FeatureCount was used to map the aligned reads to the genes (Liao et al., 2014) . The read count output for all the genes obtained was used for differential expression analysis between CHO_C and CHO_TM samples using the DeSeq2 tool (Love et al., 2014) . The significant (p<0.05) differentially expressed genes (DEGs) were further processed for gene annotation and functional analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) (D. W. Huang et al., 2009; Sherman et al., 2022) . The cellular location and biological processes, according to GO ontology, were determined for all the significant DEGs. Further, the data was manually curated to categorise the cellular locations and biological processes of the DEGs. Additionally, these DEGs were mapped to KEGG pathways to identify the significant pathways in the CHO_TM cells. 2.6 Whole Genome Sequencing (WGS) Genomic DNA was extracted from CHO_C and CHO_TM cells (cultured without TM) using the TRI reagent (Merck) following the manufacturer’s protocol. The DNA was quantified using a Qubit fluorometer (Thermo Fisher Scientific) . DNA libraries for WGS were prepared using the Illumina DNA Prep kit (Illumina) using the manufacturer’s protocol. The obtained libraries were quantified and validated using a Qubit fluorometer (Thermo Fisher Scientific) and automated electrophoresis by the 4150 TapeStation system (Agilent Technologies). The paired-end sequencing of CHO_C and CHO_TM was performed on an Illumina platform. The sequencing gave an output of more than 50 million reads for CHO_C and CHO_TM cells, which is about 6X coverage of the CHOK1 genome. Analysis was performed on the Galaxy platform (usegalaxy.org) (The Galaxy Community, 2022) . not-yet-known not-yet-known not-yet-known unknown 2.7 WGS Analysis The FASTQ files were analysed for quality using the FASTQC tool (Babraham Bioinformatics - FastQC A Quality Control Tool for High Throughput Sequence Data, n.d.). Subsequently, the reads were aligned to the reference Chinese Hamster genome ( GCF_003668045.3) using the Bowtie2 tool (Langmead & Salzberg, 2012). The aligned reads were further mapped to the genes using the Samtools Bedcov tool (Danecek et al., 2021). For normalization, the total count method was used where the ratio of the total read counts was used as a scaling factor. Further, the coverage of each gene was normalized with respect to the gene length. Finally, normalisation was carried out using the median of the total coverage (Pereira et al., 2018). The log2fold change in the gene copy number was determined as the log2 ratio of the normalized coverage of CHO_TM with respect to the CHO_C. For genomic amplification analysis, genes with high copy number (log2fold change >±2)) were mapped to their chromosomal location in the Chinese Hamster (GCF_003668045.3) assembly. To identify the amplified genome segment, WGS reads from the CHO_TM and CHO_C were aligned to chromosome 4 (NC_048597.1) using Bowtie2 (Langmead & Salzberg, 2012). Based on the location of genes with increased copy numbers in CHO_TM, a genomic region from nucleotide 154988871 to 159969867 (~5 Mbp) was selected for detailed analysis. Coverage was computed in approximately 1000 segments of 5 kbp each using Samtools Bedcov (Danecek et al., 2021). 2.8 Relative Copy Number using qPCR Quantitative PCR (qPCR) was performed with 500ng genomic DNA using gene-specific primers (Table S1). The ΔΔCt method was used to determine the relative copy number of the genes of interest in CHO_TM cells with respect to CHO_C cells using beta-actin as the housekeeping gene (Prashad & Mehra, 2015). 2.9 Chromosome Analysis by Karyotyping Exponential cells of CHO_C and CHO_TM were treated with 0.25 μg/mL of Colcemid (Gibco-Invitrogen) for 16 hours. Post-treatment, 75 mM Potassium Chloride was added to the cells dropwise and incubated at 37°C for 15-20 min. Cells were fixed using Methanol: Acetic acid (3:1) solution. The metaphase cells were stored at -80ºC. For the preparation of the slides, cells were diluted 100-fold, and about 10 μL of it was dropped on a chilled slide to achieve an optimal spread of the chromosomes. The slides were dried, stained with DAPI (HiMedia) and imaged using a fluorescence microscope (Zeiss). By imaging, the average number of chromosomes were manually counted from at least 100 cells each for CHO_C and CHO_TM cells. 2.10 Overexpression of DPAGT1 in CHO_C cells CHO_C cells were seeded in 6-well plates at a density of 0.3 million cells/mL. After 24 hours, cells were transfected with a vector containing Dpagt1 under the control of the CMV promoter (TWIST Biosciences), using Lipofectamine 3000 (Invitrogen) according to the manufacturer’s instructions. Following transfection, cells were cultured in medium containing 200 µg/mL hygromycin for two weeks to select for stably transfected populations. The resulting stable pools were then expanded and used for growth analysis and evaluation under varying concentrations of TM. 2.11 Statistical Analysis Two-tailed student’s t-test was used to determine the statistical significance with at least three biological replicates. Data with * represents p-value <0.05, ** represents p-value <0.01, and *** represents p-value <0.001. Results and Discussion Adaptation of CHOK1 cells to TM Cells undergoing ER stress alter multiple cellular processes to restore homeostasis and prevent apoptosis. One of most widely studied responses is the unfolded protein response (UPR), that affects protein secretion during ER stress, and can lead to increase in titers. However, prolonged ER stress leads to apoptosis and therefore the increase in protein secretion rates is transient, limiting the practical utility of this response in bioprocessing. In contrast, an ER stress resistant cell line exhibits both increased secretion and survival. In this work, we develop an ER-stress resistant host cell line, to gain comprehensive understanding of how cells survive and modulate protein secretion under such conditions. The mechanism of resistance to an ER-stressor, tunicamycin (TM) was investigated in a suspension-adapted CHOK1 cell line. Using adaptive laboratory evolution, the cells were adapted through multiple rounds of increasing TM concentration starting from 50 ng/mL to 400 ng/mL, as depicted in Figure 1.A. Figure 1 : Adaptation of CHOK1 cells to TM and its characterisation: (A) Viability profile of the CHOK1 cells during adaptation. The subset depicts the three parameters of adaptation. (B) Growth profile of CHO_TM in the batch mode (n=3) in the presence (red-closed circle) and absence (red-open circle) of 400 ng/mL of TM was found to be similar to CHO_C (n=3) (black open square) Note that VCD and viability was significantly reduced in CHO_C cells treated with 400 ng/mL of TM (black closed square). TM was added on day 1, as indicated by the black arrow. Solid lines represent VCD, whereas dotted lines represent the viability. (C) The amount of the total protein secreted in the exponential phase of growth from day 4 to 7 was found to be significantly higher in CHO_TM (red bar) compared to CHO_C (black bar) (n=3). Note that TM was not added and the viability was >75% on all these days. *** represents p-value <0.001. Adaptation to TM was evaluated based on three key parameters (Figure 1.A subset). First, the extent of reduction in cell viability 40 hours post-TM treatment was noted, which improved over subsequent rounds of exposure, suggesting the development of resistance. Secondly, viability was measured 24 hours after TM removal. While an initial decline was evident, this too improved after multiple rounds of TM treatment (Figure 1.A). Third, time required for cells to recover to at least 85-90% viability was measured. In later adaptation rounds, cells consistently achieved over 90% viability immediately after TM removal, indicating that the cells have achieved resistance to TM. The adaptation was initiated with 50 ng/mL of TM and as the three parameters improved, the concentration of TM was increased by two-fold until 400 ng/ml was reached, beyond which the cells could not survive. Successful adaptation was thus confirmed by sustained viable cell density (VCD), stable viability metrics, and consistent improvement across the defined adaptation parameters. Cells that successfully adapted to TM are hereafter referred to as CHO_TM , while the non-adapted cells are designated as CHO_C. The effect of adaptation on the growth of CHO_TM and CHO_C cultures was assessed in batch mode. CHO_C cells treated with 400ng/mL showed significant reduction in both VCD and viability. However, CHO_TM cells exhibited comparable growth profiles in the presence and absence of TM, reaching a peak VCD of ~8 million cells/mL on day 6 with viability >95%, similar to untreated CHO_C cells (Figure 1.B). Notably, CHO_TM cells treated with 400 ng/ml of TM achieved a high VCD similar to CHO_C cells treated with 50 ng/ml of TM (data not shown), corresponding to an 8-fold increase in resistance to TM. Additionally, the amount of the total protein secreted was significantly increased in CHO_TM cultures compared to CHO_C (Figure 1.C). While the total protein secreted remained between 2 to 5 pg/cell/day in CHO_C cells, it reached up to 20 pg/cell/day in CHO_TM cultures, corresponding to a 3 to 4-fold increase. These findings demonstrate that adaptation of CHOK1 cells to TM not only preserved growth characteristics but also significantly enhanced the cells’ secretory capacity. Global changes in the CHO_TM cells To understand the mechanistic basis of TM resistance and increased protein secretion, a transcriptomic analysis of CHO_C and CHO_TM cells was performed in the absence of TM. A total of 1910 genes were significantly differentially expressed in CHO_TM relative to the CHO_C cells (p<0.05). Of these, 909 genes exhibited a log 2 fold change greater than ±1, comprising 572 upregulated and 337 down-regulated genes. The complete list of the differentially expressed genes (DEGs) is available in Supp_List1. Figure 2: Functional analysis of the DEGs in CHO_TM compared to CHO_C. The DEGs were manually curated and categorised for (A) cellular location and (B) biological processes. The DEGs presented have a significant log 2 fold change greater than ±1 with p<0.05. Green and red bars represent the upregulated and the downregulated DEGs, respectively. Figure 2 presents the classification of the DEGs based on their cellular location and biological process. Approximately 20% of the DEGs were identified as cell membrane-associated proteins (Figure 2.A) with majority being upregulated in CHO_TM. Notably, several of the top DEGs such as Nlrx1, Upk2, Thy1, Rasgef1b, upregulated by 6 to 10 log 2 fold (Table 1), encode membrane proteins, suggesting potential alterations in the membrane composition or function of CHO_TM cells. Given that majority of the membrane proteins are processed through ER; such increment in the number of membrane proteins is also indicative of enhanced ER activity and increased protein processing demands (Rapoport, 2007) . Additionally, about 8% of the DEGs were located in the nucleus, whereas 14.5% were associated with the cytoplasm and the extracellular region of the cell. In terms of the biological processes, about 21% of the DEGs participated in regulation and cell signalling (Figure 2.B), indicating an active cellular response to environmental stress. Genes related to metabolic process accounted for 6.5% of the DEGs while those involved in protein processing and transport contributed 5 to 6% of the DEGs. A smaller proportion of the DEGs were involved in cell cycle, DNA metabolism and apoptosis. Collectively, these transcriptional changes highlight the adaptive mechanisms employed by CHO_TM cells to counteract tunicamycin-induced stress. Table 1: List of the top significant DEGs. 100755030 Foxr1 forkhead box protein R1 10.9 100756089 Nlrx1 NLR family member X1 10.1 100759757 Upk2 uroplakin-2 isoform X2 8.2 118239631 LOC118239631 uncharacterized 7.6 100758237 Thy1 thy-1 membrane glycoprotein 7.6 100758523 Usp2 ubiquitin carboxyl-terminal hydrolase 2 isoform X1 7.4 100761756 LOC100761756 olfactory receptor 4P4 7.2 113836429 LOC113836429 uncharacterized 7.1 100768745 Tub tubby protein homolog isoform X2 6.8 100751984 Rasgef1b ras-GEF domain-containing family member 1B isoform X1 6.5 100751791 Dctd deoxycytidylate deaminase -11.0 113833306 LOC113833306 uncharacterized, transcript variant X5 -10.3 100757584 Tmem185b transmembrane protein 185B -9.2 113836636 CUNH5orf58 putative uncharacterized protein C5orf58 homolog -7.3 107978140 LOC107978140 uncharacterized, transcript variant X3 -6.9 113837663 LOC113837663 gap junction alpha-6 protein-like -6.6 113835067 LOC113835067 uncharacterized -6.4 113836100 LOC113836100 olfactory receptor 10J1-like -6.3 100752328 LOC100752328 H-2 class II histocompatibility antigen, I-E alpha chain -6.2 113833321 LOC113833321 uncharacterized -6.0 Altered protein processing pathway leads to improved protein secretion CHO_TM cells exhibit more than 3-fold increase in protein secretion rate compared to CHO_C cells. To ascertain the changes responsible for this phenotype, we delve deeper into the transcriptional changes associated with the protein processing pathways. The primary target of TM in cells is the enzyme DPAGT1, an integral membrane protein in the ER, that catalyses the transfer of N-acetylglucosamine from UDP-N-acetylglucosamine to a dolichyl phosphate, thereby initiating the process of N-glycosylation. The gene encoding for DPAGT1, was significantly upregulated by approximately 4 log 2 fold in CHO_TM cells, consistent with earlier findings of increased DPAGT1 activity in TM-resistant CHO cells (Criscuolo & Krag, 1982; Waldman et al., 1987). In addition to Dpagt1, genes such as Ostc, Galnt14 and Galnt18 involved in the transfer of glycan core structure to Asn and Ser/Thr in the process of N- and O- glycosylation, respectively, were found to be upregulated by up to 3 log 2 fold. Other genes participating in protein glycosylation, such as B3galnt1, B4galnt4, B4galt2 and B3gat1, were also differentially expressed. (Figure 3.A). Srd5a3, which plays a key role in dolichol biosynthesis, a critical precursor in N - glycosylation, was upregulated in CHO_TM cells . Furthermore, genes from sugar metabolism such as LOC100755423, LOC118237867, Fpgt, Gnpda1 and Nans that provide glycan substrates for post-translational modifications were differentially expressed. Such modulation of the PTM machinery seems to be driven by the increased protein-load inside the ER. Additionally, several molecular chaperones and ER stress-responsive transcription factors, such as Hyou1, Hspa5, Creb3l2 and Herpud2 were significantly upregulated in CHO_TM cells. These genes have been previously reported to be activated in response to ER stress (C.-H. Huang et al., 2014; Prashad & Mehra, 2015; Rao et al., 2021; Sampieri et al., 2019). Among them, Hypoxia-upregulated1, or Hyou1, responds to stress, including hypoxia, ER stress, glucose deficiency and TM and helps maintain homeostasis (Rao et al., 2021) by downregulating genes from the UPR pathway and attenuating IRE1 and JNK signalling pathways. In the period of adaptation, cells modulate the ER folding and the PTM machinery to maintain homeostasis in response to increased protein load. Overall, these transcriptional changes reflect significant modulation of ER-related gene expression in CHO_TM cells, likely contributing to their enhanced secretory phenotype and resistance to TM-induced stress. In addition to the modulation of ER-resident chaperones and transcription factors, genes involved in the ER to Golgi transport and subsequent secretion were also found to be differentially expressed in the CHO_TM cells (Figure 3.B). Maintaining vesicular trafficking is critical to sustain homeostasis inside a cell. Notably, Arcn1, Copz2 and Trappc4, involved in the ER to Golgi or retrograde vesicle-mediated transport of the proteins, were found to be upregulated by 2-3 log 2 fold. Such tuning of the transport gene is essential for an efficient movement of proteins inside the cells. Apart from these, the expression of genes involved in intracellular protein transport from the Golgi, including Vsp11, Sytl5, Arf6, Snx19, Vps26b and Arl11, were also differentially expressed in CHO_TM. The upregulation of these vesicular transport genes in the CHO_TM cells indicates the enhancement of the protein export process, thus enhancing protein secretion. Figure 3: Alteration of the protein processing pathway in CHO_TM. DEGs involved in (A) protein folding and post-translational modification (PTM) present in the ER, (B) Protein transport and secretion in the Golgi and (C) protein ubiquitination in the cytoplasm are shown. Green and red bars represent the upregulated and the downregulated DEGs, respectively. Numbers on each bar indicate the log 2 fold change in CHO_TM with respect to CHO_C. Representative DEGs are present in the figure; for the complete list, refer to the Supp_List2. DEGs participating in sugar metabolism are represented with coloured arrows depicting their upregulation (green) or downregulation (red). An additional strategy employed by cells to restore homeostasis following ER stress is the degradation of the misfolded or unfolded proteins through the endoplasmic reticulum-associated degradation (ERAD) pathway (Hwang & Qi, 2018) . The protein ubiquitination pathway, a key component of ERAD, is known to be activated under ER stress conditions (Qu et al., 2021) . In CHO_TM cells, more than 20 genes from the protein ubiquitination pathway were differentially expressed (Figure 3.C). Notably, peptidases such as, Usp2 and Usp18, participating in proteolysis, were upregulated by 6.9 and 1.25 log 2 fold, respectively. Genes with ubiquitin-ligase activity, such as Ube4a, Cbl, and Pdzrn3, were upregulated by more than 2 log 2 fold. Additionally, several ring finger proteins like Rnf183, Rnf144b and Rnf26, which function as a ubiquitin ligase, were increased by 2 to 4.5 log 2 fold. This selective upregulation in the adapted condition may represent a compensatory mechanism to manage increased protein load, aligning with the higher levels of total protein secretion observed in these cells. Overall, the results indicate that CHOK1 cells mitigate TM-induced ER stress by differential expression of genes involved in both protein secretion and degradation. Such coordinated transcriptional response likely contributed to the enhanced total protein secretion in the CHO_TM cells. Modulated cell signalling pathway promote cell survival and proliferation A key characteristic of CHO_TM cells is their ability to maintain growth and viability in the presence of TM. Notably, majority of the DEGs in CHO_TM cells were part of cell signalling and regulatory processes. Among these, the top DEG, Nlrx1, a member of the NOD-like receptor family, was upregulated by 10 log 2 fold in CHO_TM cells and is known to participate in various cellular responses. Overexpression of Nlrx1 has been reported to attenuate ER stress and modulate apoptotic pathways (Mi et al., 2024; Soares et al., 2014) , thereby playing a pivotal role in promoting cell survival and proliferation in CHO_TM cells. Another transcription factor associated with cellular stress response (Mota et al., 2021) , Foxr1, was also highly upregulated, by 10.9 log 2 fold, in the CHO_TM cells. In addition to the top DEGs, numerous genes associated with major signalling pathways, such as PI3K-AKT, MAPK, Ras, Hippo, TGF-beta, etc., were differentially expressed in CHO_TM cells. Among these, the PI3K-AKT, MAPK and Ras pathways, known to play a crucial role in cell survival and proliferation (Jerabek et al., 2022; H. Tang & Xue, 2017) , exhibited the highest number of DEGs, as illustrated in Figure 4. Multiple growth factors such as Fgf7, Vegfd, Efna5 and LOC100761504, along with Receptor Tyrosine Kinases (RTK) including Fgfr3, Flt1, Egfr, Tek and Fgfr2 were upregulated up to 2.6 log 2 fold. These growth factors and receptors are known to widely drive cell proliferation and expansion (Witsch et al., 2010) , suggesting that specific growth factors and ligands are upregulated in CHO_TM cells to fulfil the cellular demand to sustain growth and proliferation during adaptation. Within the PI3K-AKT signalling pathway, differential expression was observed in several extracellular matrix (ECM) proteins, particularly members of the collagen family (Col4a3, Col6a1, LOC100772575) and laminin family (Lamb3, Lama1). The ECM proteins and integrins influence multiple downstream cascade reactions that activate the PI3K-AKT signalling pathway, thereby promoting cell survival and expansion (Stupack & Cheresh, 2002; Yousefi et al., 2021) . Additionally, genes such as Mdm2, Ccne1 and Cdkn1a, which regulate p53 expression and are critical for cell cycle progression and survival (Abbas & Dutta, 2009; S. Zhang et al., 2023) , were also differentially expressed. Overall, these transcriptionally changes support the activation and modulation of the PI3K-AKT pathway as a key driver of the enhanced survival and growth phenotype observed in CHO_TM cells. Figure 4: Differentially expressed genes in the PI3K-AKT, MAPK and Ras signalling pathways in CHO_TM cells. The Venn diagram represents the unique and common genes among the three signalling pathways. The genes have been colour-coded based on the log 2 fold change (Upregulation: Green; Downregulation: Red). The details of the genes are present in Supp_List2. Several MAPK kinases from the well-characterised MAPK signalling pathway, known to regulate cell survival and proliferation (W. Zhang & Liu, 2002) , were differentially expressed in CHO_TM cells. The altered expression of growth factors and RTKs suggests activation of the MAPK pathway. Specifically, protein kinases such as Map3k13, Map4k3, Map3k5 and Map3k6 were found to be altered in CHO_TM along with downstream effector proteins. Activation of MAPK signalling in response to ER stress has been shown to modulate the survival-related cellular processes, including through MAPK phosphatases like DUSP4 (Darling & Cook, 2014; Li et al., 2011; Ratsada et al., 2020; L. Zhou et al., 2023) . Additionally, Rasgrp3, an activator of the Ras protein, was upregulated by 2.47 log 2 fold. This gene has been reported to be significantly correlated with enhanced cell proliferation in various cancer cell lines and tissues (Nagy et al., 2014; Zeng et al., 2014) , suggesting a similar pro-proliferative function in CHO_TM cells. The Ras signalling pathway, which serves as a central node in the communication between pathways, such as PI3K-AKT and MAPK (Berridge, 2014) also exhibited differential expression in CHO_TM cells. not-yet-known not-yet-known not-yet-known unknown Several GTP-binding proteins involved in initiating the Ras cascade, including Arf6, Gng10 and Gnb2 were differentially expressed. Furthermore, the expression of downstream effector genes such as phospholipases (Pla2g12a, Pld1), P21-activated kinases (LOC100758984, Pak3) and transcription factor Ets1 were also modulated. Collectively, the coordinated activation of the PI3K-AKT, MAPK and Ras signalling pathways drives the expression of multiple effector genes that promote survival, growth and proliferation in CHO_TM cells. Large genome segment amplification facilitates the resistance to TM CHO cells are reported to be genetically unstable, which can lead to variations in gene copy number (Derouazi et al., 2006; Vcelar, Jadhav, et al., 2018; Vcelar, Melcher, et al., 2018). To investigate the genetic basis of transcriptomic changes, WGS of CHO_C and CHO_TM cells was performed in the absence of TM. Gene coverage was assessed by aligning the sequencing reads to the Chinese hamster reference genome (GCF_003668045.3). Figure 5A presents a scatter plot of the RNASeq log 2 fold change with the corresponding WGS log 2 fold change of all the genes in CHO_TM relative to CHO_C cells. The WGS log 2 fold change is indicative of the relative gene copy number. Most genes that exhibited significant differential mRNA expression did not show corresponding changes in genomic copy number. However, a small subset of ~45 genes (RNASeq log 2 fold change greater than ±1) displayed a corresponding WGS log 2 fold ratio of greater than ±2. Notably, there was a strong linear correlation (R 2 = 0.9) between the RNASeq and WGS log 2 fold change values for these genes (Figure 5.B), suggesting a link between gene amplification and increased transcript abundance. Of the 45 genes, 43 were found to be amplified in the CHO_TM cells (Table S2). Among these, 10 genes were involved in protein processing, others belonged to, cell signalling (6), regulation (6), metabolism (6) and DNA metabolism (2). Notably, this set included the TM target gene, Dpagt1 and its neighbouring genes, namely, LOC100757539 and C2cd2l, with a relative coverage increase of 5 to 7 log 2 fold. Interestingly, majority of the amplified genes (35 out of 43), including Dpagt1, were located on chromosome 4 of the Chinese hamster genome. To assess the extent of this amplification, the coverage of a ~5 Mbp segment of Chromosome 4 was determined. This region encompassed 34 of the 35 amplified genes on chromosome 4. Although coverage varied across the region, a distinct 1.4 Mbp segment (highlighted in red) displayed consistent amplification, comprising 32 amplified genes along with the intergenic regions (Figure 5.C). Alignment of the 32 amplified genes based on their genomic order, revealed a consistent pattern in the RNASeq and WGS log 2 fold change data (Figure 5.D). The log 2 fold change ranged from 2 to 10 in both datasets, suggesting that the upregulation at the transcriptome level is likely due to an increase in the gene copy number. This was further validated by qPCR analysis of selected genes from the 1.4Mbp genome segment (Figure 5.E), which further confirmed the presence of genomic amplification in CHO_TM cells. To determine whether the amplification was localized or involved an entire chromosome, karyotyping of the CHO_TM and CHO_C cells was performed. Both cell lines showed an average of 18 chromosomes, indicating no gross chromosomal amplification in CHO_TM cells (Figure 5.F). Previous studies have demonstrated gene amplification in TM-resistant CHO cells, with amplified gene later identified as the Dpagt1 (Lehrman et al., 1988; Scocca et al., 1988). Similar mechanisms of genomic amplification have been reported in TM-resistant yeast, where duplication of chromosome II, which harbours ALG-7 gene (yeast homologue of Dpagt1), conferred resistance (Beaupere et al., 2018). Chromosome variability has also been observed in CHOK1 cells adapted to serum-free media (Huhn et al., 2022). Aneuploidy has been reported in TM-resistant Candida and heat-resistant yeast cells (Yang et al., 2021; Yona et al., 2012). Despite these findings, there are very few reports of genomic duplication in CHO cells. A recent study identified duplication of a large segment of chromosome 2 in a recombinant CHO cell line (Wei et al., 2024). Thus, the amplification of a large genomic region in CHO_TM cells not only confers resistance to TM but also improve their total protein secretion. In bacterial systems, a small number of mutations are often sufficient to generate a phenotype (Hubbard et al., 2021; Mundhada et al., 2017; Schaffner et al., 2014). In contrast, mammalian systems require more complex mechanisms, such as copy number variations across multiple genes or pathways to achieve a desired characteristic. These findings highlight the involvement of multiple genes in pathway engineering, underscoring the limitations of conventional genetic engineering approaches that target only a few genes. Interestingly, in CHO_TM, 1846 genes were significantly differentially expressed at the transcriptomic level in the CHO_TM cells without corresponding changes at the genome level. Among these, 13% belong to cell signalling, while 9.5% of the genes can be attributed to protein processing. About 15% were involved in metabolism, cytoskeleton and DNA metabolism. It is noteworthy that only 10 of the 172 total DEGs involved in protein processing (Figure 3) and one gene from the 69 DEGs from the PI3K-AKT/Ras/MAPK cell signalling pathways (Figure 4), respectively, were amplified (data not shown). This points to the combinatorial role of differential transcription and genome-level amplification, which facilitates the adaptation of cells to TM through enhanced survival and proliferation alongside increased protein secretion. Figure 5: Genetic basis of the differential expression in CHO_TM cells. A) Scatter plot comparing the WGS log 2 fold ratios with the RNASeq log 2 fold ratios of all genes. The ratios are CHO_TM versus CHO_C. All genes (31,661) are represented in grey and genes with RNASeq p-adj±1, WGS log 2 fold change >±2). A threshold of 0.5 was set for the normalized coverage to ensure that log 2 fold change of WGS was not due to lack of reads in either of the two cell lines. The correlation is based on the genes in blue. C) Genomic heterogeneity of a segment of CHO_TM cells in 5 Mbp segment of chromosome 4 of Chinese Hamster (GCF_003668045.3). The coverage of a 5 Mbp segment of chromosome 4 is shown. The red highlighted large amplified segment of ~1.4 Mbp includes 32 amplified genes whereas 2 amplified genes, are represented in the green region. Grey represents the coverage of the intergenic regions. For the complete list of amplified genes that map to chromosome 4, see Table S2. D) WGS (blue bars) and RNASeq (red dots) log 2 fold change of the 32 amplified genes in the ~1.4Mbp region as in the chromosome 4. E) Validation of duplication of the amplified region by qPCR analysis (n=4). F) Karyotype analysis of the CHO_C (black) and CHO_TM (red) cells (n=>100). not-yet-known not-yet-known not-yet-known unknown Dpagt1 alone cannot confer TM-resistance and enhanced protein secretion Further to assess the significance of genes in the amplified region; one of the prominent genes Dpagt1 which encodes the target of TM was selected for further analysis. To determine whether upregulation of this gene alone is sufficient to reproduce the phenotype observed in CHO_TM cells, Dpagt1 was overexpressed in CHO_C cells. Figure 6: Characterisation of CHO_DP cells. A) Growth profile of CHO_DP (red) in the batch mode (n=2) was found to be similar to CHO_C (n=2) (black). Solid lines represent VCD, whereas dotted lines represent the viability. B) The amount of the total protein secreted in the exponential phase of growth from day 4 to 7 was found to be similar in CHO_DP (red bar) and CHO_C (black bar) (n=3). Note that viability was >75% on all these days. Treatment of CHO_C (C) and CHO_DP (D) at 0 (blue), 50 (green), 100 (red), 400 (pink) and 800 (orange) ng/mL of TM showed similar trends in VCD (solid lines) and viability (dotted lines). Subset in D represents the difference in viability on day 4 between CHO_C (black) and CHO_DP (pink) treated with 400 and 800 ng/mL TM. * represents p-value <0.05. The resulting transfected cells, referred to as CHO_DP, exhibited a four-fold increase in Dpagt1 expression. These cells were subsequently scaled-up to assess their growth characteristics. CHO_C and CHO_DP cells exhibit similar growth profiles, attaining a maximum VCD of Additionally, no significant difference was observed in the total protein secreted during the exponential growth phase (day 4 to 7) by CHO_DP cells (Figure 6.B), indicating that Dpagt1 overexpression alone did not enhance secretory capacity. The sensitivity of CHO_C and CHO_DP cells to TM was evaluated across a range of concentrations (Figure 6.C and D). At lower TM concentrations (50 and 100 ng/mL), both cell lines maintained VCD and viability comparable to untreated controls. However, by the end of the culture period (day 8), CHO_DP remained viable; whereas CHO_C cells showed complete loss of viability. Exposure to higher concentrations (400 and 800 ng/mL) resulted in a marked reduction in VCD and viability in both CHO_C and CHO_DP cells. Notably, at day 4, CHO_DP cells maintained significantly higher viability than CHO_C cells when exposed to 400 and 800 ng/mL of TM (Figure 6.D_subset), suggesting a modest shift in TM sensitivity Despite this slight difference, Dpagt1 overexpression did not confer resistance to TM. Importantly, the level of DPAGT1 expression in CHO_TM cells, driven by genomic amplification, was substantially higher than that achieved via transfection in CHO_DP cells. Alternatively, additional genetic factors beyond Dpagt1 play a role in mediating the enhanced protein secretion and TM resistance observed in CHO_TM cells. This suggests that other genes within the amplified region may also contribute to the phenotype observed and thus should be investigated. Notably, the amplified region not only consists of protein secretion related genes but also cell signalling and transcription factors. Due to the intricate genetic networks and pathways in eukaryotic, especially mammalian cells, overexpression of a single gene typically does not produce substantial phenotypic changes. In contrast alterations across multiple interacting genes can have a profound impact on cellular behaviour (Nishimiya et al., 2013; Pieper et al., 2017; D. Tang et al., 2022; Torres & Dickson, 2022). Our WGS and transcriptomics data suggests the significance of genes involved in the protein secretory pathway and the cell signalling cascades towards the adapted phenotype. Presence of genes from both these pathways on the amplified region may be important and should be explored further. Conclusion In conclusion, CHOK1 cells subjected to adaptive laboratory evolution exhibited an 8-fold increase in resistance to TM and a 3 to 4-fold increase in the amount of total protein secreted. Transcriptomic analysis revealed significant modulation of the protein processing pathway and key cell signalling pathways, including PI3K-AKT, MAPK and Ras, potentially contributing to the higher protein secretion and enhanced survival of CHO_TM cells. Additionally, TM resistance in CHO_TM cells was associated with the amplification of a large genomic segment, containing several important genes including Dpagt1. Overall, the adaptation of CHO_TM cells was driven by a combination of transcriptomic and genomic modifications. Notably, Dpagt1 overexpression alone was insufficient to reproduce the TM-adapted phenotype. Future research will focus on whether targeting additional genetic elements can replicate this adaptation while simultaneously pursuing high-level recombinant protein expression through site-directed integration in these adapted cells, with a goal to push the limits of specific productivity. Author Contributions Priya Mishra: Methodology, Validation, Formal analysis, Investigation, Data curation, Writing - original draft, Visualization. Sarika Mehra: Conceptualization, Methodology, Software, Formal analysis, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition. Acknowledgements This work was supported by grants from the Department of Science and Technology (DST), Government of India (CRG/2022/007565) and the Wadhwani Research Centre for Bioengineering (WRCB), IIT Bombay. We thank the Next Generation Sequencing Platform (IoE) and the Spinning-Disc Confocal Microscopy, Central Facility, IIT Bombay. Priya Mishra acknowledges MHRD for her fellowship. Supplementary Information Supp_List1 consists of the details of all the significant DEGs. The DEGs in the protein processing and the PI3K-AKT, MAPK and Ras are enlisted in Supp_List2 . The Supplementary information file consists of the list of primers used in the study (Table S1) and list of amplified genes in CHO_TM (Table S2) . References Abbas, T., & Dutta, A. (2009). p21 in cancer: Intricate networks and multiple activities. Nature Reviews Cancer , 9 (6), 400–414. https://doi.org/10.1038/nrc2657Amiri, S., Adibzadeh, S., Ghanbari, S., Rahmani, B., Kheirandish, M. H., Farokhi-Fard, A., Dastjerdeh, M. S., & Davami, F. (2023). CRISPR-interceded CHO cell line development approaches. 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Current Opinion in Biotechnology , 53 , 151–157. https://doi.org/10.1016/j.copbio.2018.01.007 Information & Authors Information Version history V1 Version 1 18 June 2025 Peer review timeline Published Biotechnology Journal Version of Record 17 Dec 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Biotechnology Journal Keywords adaptive laboratory evolution biochemical engineering cho cells genetic engineering genomics metabolic engineering omics protein secretion synthetic biology systems biology transcriptomics Authors Affiliations Priya Mishra Indian Institute of Technology Bombay Department of Chemical Engineering View all articles by this author Sarika Mehra 0000-0003-3844-4726 [email protected] Indian Institute of Technology Bombay Department of Chemical Engineering View all articles by this author Metrics & Citations Metrics Article Usage 572 views 278 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Priya Mishra, Sarika Mehra. Genome Amplification and Altered Transcriptome aid in Survival and Enhanced Protein Secretion in Tunicamycin-Resistant CHOK1 cells. Authorea . 18 June 2025. 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