Synthetic nanoparticles for cell-type specific, spatially resolved miRNA loading and export in neural cells

Synthetic nanoparticles for cell-type specific, spatially resolved miRNA loading and export in neural cells | 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 Article Synthetic nanoparticles for cell-type specific, spatially resolved miRNA loading and export in neural cells Marianna Mignanelli, Giacomo Siano, Vincenzo Iannone, Arianna Scarlatti, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7775232/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Brain development and plasticity depend on specific microRNA (miRNA) expression patterns across cell types and subcellular compartments. Nevertheless, comprehensive profiling of localized brain miRNAs is still limited by challenges in isolating individual cell types or compartments and in detection sensitivity. To overcome these limitations, we advanced HIV-1 Gag’s ability to bind host miRNAs within Virus-like Particles to develop Synthetic Nano-Particles for Precise miRNA loading and export (SNaP). Our data establish SNaP’s modularity and portability to clinically-relevant neural cells, with particle yields matching benchmark packaging cells. SNaP integration with a cell-specific promoter enabled lineage-restricted miRNA export, while incorporating a Dendritic Localization Signal improved the specificity of postsynaptic miRNA recovery over traditional synaptosomes. Additional engineering with a miRNA-binding module synergistically boosted synaptic miRNA packaging in a sequence-independent manner. Collectively, our work positions SNaP as a technological advancement supporting the high-resolution, spatially resolved profiling of non-coding RNAs, adaptable to diverse polarized or heterogeneous tissues. Biological sciences/Biotechnology/Nanobiotechnology/Nanoparticles Biological sciences/Biotechnology/Nanobiotechnology/Nanostructures Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction MicroRNAs (miRNAs) are small, non-coding RNAs that serve as ubiquitous regulators of gene expression, orchestrating fundamental biological processes through post-transcriptional control 1 . In the Central Nervous System (CNS), miRNAs are dynamically regulated during development and exhibit cell-type-specific expression in the adult brain, underscoring their essential role in neuronal identity and function 2–5. . Beyond their compartmentalized expression, specific miRNA populations localize within synaptic compartments, where they modulate activity-dependent gene expression of plasticity-related products via translational control 6–10 . Given their critical role in brain homeostasis, miRNA dysregulation is linked to a wide range of neurological disorders 11,12 . Consequently, miRNAs are emerging as attractive candidates for CNS biomarker discovery, with the potential to surpass protein-based predictors in both sensitivity and specificity for early diagnosis 13 . Nevertheless, the implementation of brain miRNAs as CNS biomarkers remains challenging. Current approaches for local transcriptomics - such as those based on synaptosome isolation or microdissected neuropils - suffer from contamination by neighbouring cells or subcellular compartments, hindering accurate assignment of miRNA topology 14-16 . Moreover, bulk miRNA sequencing lacks the sensitivity to detect rare, spatially restricted miRNA species 17,18 . On the other hand, single cell small RNA profiling is still far from being widely and easily applicable to regionalized miRNAs due to their short length and adapter ligation biases 19 . Collectively, these limitations constrain our understanding of localized post-transcriptional regulation in the CNS and highlight the need for alternative strategies offering both enhanced spatial resolution and greater detection sensitivity 20 . Virus-like particles (VLPs) derived from the HIV-1 Gag polyprotein offer a promising platform in response to these challenges 21 . Gag self-assembles into VLPs through interactions with specific RNA motifs, a mechanism that naturally facilitates the selective encapsidation of RNAs—including host miRNAs—during HIV-1 replication 22,23 . Moreover, Gag exhibits substantial structural flexibility, tolerating genetic fusion with exogenous domains without compromising particle assembly or function 24 . These features have recently enabled the development of modular VLPs with programmable RNA-binding specificity and ancillary features 25 . In this study, we present SNaP (Synthetic Nano-Particles for Precise miRNA loading and export) , a Gag-based VLP platform designed to enable targeted recovery of miRNAs from complex CNS cell types. The SNaP system integrates modular domains to achieve (i) cell-type-specific miRNA loading, (ii) subcellular compartment targeting, and (iii) enhanced miRNA detection. We further demonstrate the feasibility of applying SNaP in both neuronal and microglial cell types, by equipping the SNaP constructs with cell-specific transcriptional control, highlighting its robustness in challenging cellular and tissue environments. Collectively, this work positions SNaP as a novel and versatile tool for spatially resolved, cell-type specific miRNA profiling in the CNS. Its modular design and compatibility with heterogeneous cell types establish a foundation for high-throughput applications in biomarker discovery and the investigation of compartmentalized RNA regulation in any clinically relevant tissue. Results 1. Cell-specific miRNA export Brain miRNAs display distinct cell type-specific expression patterns crucial for CNS development and function, yet accurately profiling their signatures in individual brain cells remains challenging 26 . To improve the resolution of miRNA profiling at the cell-type level, we exploited and advanced the inherent capacity of HIV-1 Gag virus-like particles (VLPs) to package host RNAs 23 by incorporating additional functional modules, resulting in the development of Synthetic Nano-Particles for Precise miRNA loading and export (SNaP). The first innovation at the core of this platform is the integration of a cell-specific promoter to drive Gag expression 27 , thereby confining SNaP nanoparticle formation and contextual miRNA export to desired cell populations. To validate this strategy, we established a simplified model of CNS cellular diversity using co-cultured immortalized hippocampal neurons (HT22) and microglial cells (BV-2). Within this system, we transiently directed SNaP production using either the CaMKII α or the Iba1 modules, enabling the selective generation of neuro- or glia- SNaP nanoparticles, respectively 28,29 ( Fig. 1A ). Immunostaining for the Gag p24 domain confirmed that Gag expression was strictly limited to the intended cell types, showing clear colocalization with the microglial marker CD11b and the neuronal marker HuC/D, respectively ( Fig. 1B ). Importantly, p24 antigen concentrations reflected robust yields of nanoparticles from both neuronal and microglial sources, supporting their utility for downstream RNA applications ( Fig. 1C ). To further assess the specificity of the SNaP system for cell-specific miRNA characterization, we performed RT-qPCR on the RNA extracted from supernatants, comparing the composition of miRNAs embedded within neuronal and microglial particles. SNaP particles generated by CaMKII α -driven expression preferentially encapsulated mmu-miR-127 and mmu-miR-433 , which we previously identified as neuronal-enriched ( Supplementary Fig. 1A) . Conversely, Iba1 -driven VLPs efficiently packaged microglial-associated miRNAs mmu-miR-142 and mmu-miR-223 ( Fig. 1D , Supplementary Fig. 1A ). Notably, overall miRNA expression levels were comparable between cultures expressing SNaP and mock controls, indicating that the observed selective loading was due to restricted nanoparticle production rather than changes in endogenous miRNA levels ( Supplementary Fig. 1B ). Collectively, these results establish SNaP as a versatile and effective platform for specifically capturing miRNAS into cell-type-specific VLPs and thereby isolate miRNAs from defined cell types within the complex cellular milieu of the brain. By enabling the selective export of miRNAs directly from targeted cell populations in situ, SNaP addresses critical obstacles of cell resolution and tissue accessibility that constrain conventional brain cell-specific transcriptomic approaches. 2. Synaptic miRNA detection Current miRNA profiling transcriptomic techniques are limited not only in cell-type resolution but also in accurately profiling miRNAs within specialized subcellular compartments, such as neuronal dendrites and axons, where local miRNAs play essential roles in modulating synaptic plasticity 14,30 . To address this challenge and building on SNaP’s demonstrated effectiveness for in situ miRNA loading and export in specific cell-types, we designed an additional module to restrict miRNA profiling at the subcellular level, specifically targeting the dendritic region of neurons. To enhance Virus-like particle-mediated miRNA loading within dendrites, we incorporated a 247-nucleotide dendritic localization signal (DLS) from the 3’ UTR of the PSD95 transcript into the Gag mRNA’s 3’ UTR. This sequence is well-established to be both necessary and sufficient for directing mRNA transport specifically to dendrites 31 thereby increasing the likelihood of VLP assembly in the dendritic/post-synaptic compartment, allowing in principle to enrich the loading of dendritic miRNA while minimising the contamination of miRNAs from presynaptic and somatic regions. To validate the effectiveness of the dendritic-targeting module, we transduced human iPSC-derived neuronal progenitors with VSV-G-pseudotyped lentiviral vectors encoding either the SNaP-DLS construct or a benchmark SNaP-only variant with no specific RNA localization sequence. Following viral transduction, cells were differentiated into cortical glutamatergic neurons, and supernatants were harvested at 28 days post-differentiation (DIV28) to concentrate the released viral-like nanoparticles ( Fig. 2A ). Immunofluorescence confirmed that neuronal maturation in SNaP-packaging cultures proceeded comparably to mock-transduced control cells, suggesting minimal disruption of neuronal physiology upon nanoparticle formation and budding ( Fig. 2B ). DLS engineering resulted in distinct differences in nanoparticle localization. While cells expressing the untargeted SNaP construct showed diffuse p24 immunoreactivity throughout both soma and neurites, those expressing SNaP-DLS displayed significantly increased p24 signal intensity within neurites compared to cell bodies ( Fig. 2B ). Correspondingly, incorporation of the DLS module in SNaP led to pronounced colocalization of p24 with the postsynaptic marker Homer 1 b/c, confirming precise dendritic targeting ( Fig. 2C ). Of note, SNaP particles remained readily detectable in the supernatant up to four weeks of differentiation ( Fig. 2D ). Moreover, this engineered targeting did not compromise overall miRNA export capacity, as sufficient total RNA levels were recovered for downstream analysis regardless of the spatial restriction of SNaP-DLS ( Supplementary Fig. 2A ). To assess whether the enhanced SNaP-DLS postsynaptic localization confers functional specificity for dendritic miRNA isolation, we examined the modules’s capacity to load three miRNA species with established dendritic and postsynaptic localization: hsa-miR-132, hsa-miR-134 , and hsa-miR-138 33 . Indeed, according to the engineered design, SNaP-DLS nanoparticles demonstrated superior enrichment for these molecules compared to untargeted SNaP-only controls ( Fig. 2E ). In contrast, SNaP-DLSfailed to efficiently loading three axonal miRNAs and a non-compartmentalized miRNA, underscoring their specificity for dendritic miRNA species ( Supplementary Fig. 2B ). Importantly, lentiviral transduction did not alter overall miRNA expression levels ( Supplementary Fig. 2C ), further validating the integrity of our observations. Given the precise targeting demonstrated by SNaP-DLS, we next benchmarked its performance against state-of-the-art methods. Comparing our qPCR-based profiles to the most comprehensive published dataset of human synaptosomal miRNAs 34 , we found that SNaP-DLS and traditional synaptosomal preparations achieved similar enrichment for hsa-miR-132 and hsa-miR-134 (Fig. 2F, left) . However, SNaP-DLS exhibited significantly lower recovery of hsa-miR-361 , a known presynaptic miRNA (mean recovery efficiency: 98.38% vs. 1.61%, Fig. 2F, right ). This difference highlights the superior spatial specificity afforded by SNaP-DLS, as opposed to conventional synaptosomal-based methods. Collectively, these results establish SNaP-DLS as a highly specific and effective platform for isolating dendritic miRNAs, significantly reducing the recovery of non-dendritic background compared to conventional synaptosomes. The DLS module thus provides an advanced tool for resolving the intricate landscape of compartmentalized miRNA expression, offering unprecedented precision for investigating neuronal miRNomes. 3. Improving the sensitivity for miRNA profiling Another major challenge in miRNA profiling, especially at the subcellular level, derives from their inherently short length and low abundance. This often limits the detection sensitivity for rare or transiently expressed, localized miRNA populations 35 . To overcome this limitation and enhance miRNA detection while minimizing co-isolation of other host RNA species, we fused the first two double-stranded RNA-binding domains of the Dicer cofactor TRBP (TAR RNA-binding protein) to the C-terminus of Gag. These modules were chosen for their well-established selective, sequence-independent binding to miRNAs and minimal affinity for other RNA classes 36,37 , they could be well suited for selective miRNA enrichment in the SNaP system. Additionally, their limited size ( ̴ 20.59 kDa for the two combined domains) was anticipated to minimally contribute to steric hindrance during VLP assembly. To initially validate the SNaP-TRBP system, we transiently packaged VLP nanoparticles in HEK-293T cells, a widely-used model for recombinant viral particle generation. As a benchmark, we used cells expressing a Gag-eGFP fusion protein, whose structure and assembly are well-documented 38 ( Fig. 3A). Immunoblotting for the Gag p24 domain confirmed that both the Gag-eGFP and SNaP-TRBP chimeric proteins were expressed at the expected sizes (~80 kDa and ~75 kDa, respectively), with no evidence of degradation by host proteases ( Supplementary Fig. 3A, left ). Both variants yielded high particle titres in the supernatant ( Fig. 3B and Supplementary Fig. 3A, right ). While a slight, not significant, reduction in p24 concentration was observed for TRBP-engineered particles over eGFP-expressing ones ( Fig. 3B ), this event was not attributable to protein-mediated toxicity ( Supplementary Fig. 3B ). Furthermore, transmission electron microscopy (TEM) excluded defects in particle assembly associated with TRBP fusion. Indeed, SNaP-TRBP particles retained a round morphology, a lipid membrane, and an electron-dense Gag core which was consistent with the shape and size of reference Gag-eGFP particles ( Fig. 3C ). Average p24 protein concentrations for both constructs also aligned with established benchmarks for Gag VLP production in HEK-293T cells 39 . Most importantly, incorporation of the TRBP module led to a marked increase in RNA loading efficiency by the SNaP platform ( Fig. 3D ). This enhancement was further supported by RNA electrophoresis, which showed an enrichment of small RNAs (10–40 nucleotides) in SNaP-TRBP particles compared to Gag-eGFP VLPs, consistent with selective miRNA packaging ( Fig. 3E and Supplementary Fig. 3C ). To further substantiate this enhanced specificity, we quantified the levels of the three most abundant miRNAs in HEK-293T cells ( hsa-miR-10a , hsa-miR-30e , and hsa-miR-186 40 ) cargo RNA isolated from SNaP-TRBP versus Gag-eGFP nanoparticles. Remarkably, SNaP-TRBP demonstrated significantly greater recovery of all three miRNAs ( Fig. 3F ). Again, endogenous levels of these miRNAs remained unchanged across conditions, indicating that VLP production did not disrupt basal miRNA expression ( Supplementary Fig. 3D ). Collectively, these findings demonstrate that TRBP functionalization substantially enhances the sensitivity and specificity of miRNA detection within the SNaP platform, positioning it as a robust, unbiased tool for miRNA profiling. 4. SNaP multi-domain engineering to achieve synergistic effects Our findings demonstrate that the DLS domain effectively drives SNaP packaging within the postsynaptic dendritic compartment. However, this module does not intrinsically increase miRNA packaging, as this property remains governed by the Gag core 23,41 . Given our finding that TRBP engineering markedly improves miRNA detection in gold-standard cell lines, we therefore investigated whether combining TRBP and DLS modules could synergistically boost SNaP’s postsynaptic miRNA recovery. To address the effect of dual functionalization on SNaP performance, we compared SNaP particles incorporating both TRBP and DLS domains (SNaP-TRBP-DLS) with those containing only the DLS domain (SNaP-DLS), both generated in mature mouse neurons ( Fig. 4A ). The production level of neuronal, TRBP-equipped chimeric SNAP particles was comparable to that observed in HEK-293T cells, as indicated by p24 levels (neurons mean= 100.6 ± 46.95 SEM pg/μl, HEK-293T mean= 309 ± 144 SEM pg/μl, Supplementary Fig. 4A and Fig.3B, respectively ), reinforcing the concept that mammalian neurons are capable of generating VLPs at levels comparable to those seen in established gold-standard cell lines. Importantly, TRBP functionalization resulted in an approximately tenfold increase in total RNA packaging efficiency compared to non-TRBP controls (SNaP-DLS mean= 26.96 ± 1.24 SEM; SNaP-TRBP-DLS mean= 276.1 ± 128.9 SEM, Supplementary Fig. 4B ). This enhanced RNA packaging did not compromise dendritic targeting, as indicated by similar levels of colocalization between SNaP particle signal and the postsynaptic marker Homer 1 b/c for both constructs (mean %ROI colocalized= 11.11 ± 0.97 SEM for SNAP-DLS; 12.22 ± 1.10 SEM for SNAP-TRBP-DLS, Fig.s 4B and 4C ). Both constructs notably showed higher colocalization than conventional Gag VLPs, confirming maintained targeting specificity upon dual functionalization ( Fig. 4C ). Further analysis on cargo total RNA confirmed that TRBP presence significantly amplified the postsynaptic miRNA collection ability of SNaP-DLS ( Fig. 4D ), independent of any changes in basal miRNA expression within transduced neurons ( Supplementary Fig. 4C ). Collectively, these results confirm the synergistic benefits of multi-domain engineering in the SNaP platform. The combination of precise subcellular targeting (via DLS) with enhanced miRNA packaging (via TRBP) simultaneously and significantly improves both the spatial resolution and the sensitivity of miRNA profiling, enabling robust recovery of compartmentalised miRNAs. Discussion This study presents SNaP, an original system to advance the unbiased, spatially resolved profiling of localized brain miRNAs. Standing apart from current local transcriptomics methods, SNaP is equipped with three functional modules that can operate either independently or synergistically to (i) accurately ascertain cell-type specific miRNA expression with minimal environmental interference, (ii) attain unparalleled spatial resolution for discriminating localized miRNA pools, and (iii) enhance miRNA detection sensitivity. Our approach is based on the unique ability of retroviral Gag polyproteins to interact with host noncoding RNAs during viral particle assembly 22,23 . Leveraging this property, we selectively expressed Gag in specific brain cell types to enable the encapsulation of cellular miRNAs within engineered Virus-Like Particles (VLPs) 42 . Among retroviruses, the HIV-1 Gag polyprotein was chosen as the foundation of our system due to its well-described ability to bind a broad range of host RNA species, potentially facilitating unbiased miRNA profiling 43 . Importantly, the modular and well-defined structure of Gag VLPs was deliberately selected to ensure uniform RNA content across replicates 44 , thereby upgrading SNaP’s reproducibility of cell-free miRNA profiling. This consistency could offer a substantial advantage over Extracellular Vehicles (EVs), as they frequently display variability in both composition and RNA content 45 . SNaP stands out from current local transcriptomics methods for its increased specificity in identifying localized miRNA pools with minimal contamination from surrounding environments 14,30 . The integration of a cell-specific promoter within the Gag cassette effectively confined miRNA packaging to target cell types 27 , even amidst the complexity of a heterogeneous culture system. Such minimal genetic manipulation makes SNaP-CSP broadly accessible for CNS applications where miRNAs play a crucial role in cell type or subtype commitment 20 . Adding a further layer of spatial complexity, SNaP serves as an exceptional system for exploring the intricate dynamics of intracellularly localized miRNAs involved in the regulation of neuroplasticity 11 . Incorporating a G-quadruplex within the DLS module strategically directed Gag localization to dendritic regions, significantly enhancing SNaP's ability to package postsynaptic miRNA species 31 . By massively reducing presynaptic miRNA incorporation, the DLS engineering approach surpassed the regional specificity offered by traditional synaptosome fractionation 34 . Together, these advancements position SNaP-CSP/DLS as a promising tool for elucidating local miRNA (dys-) regulation of CNS development and homeostasis at unparalleled spatial resolution. Through the analysis of SNaP-incorporated miRNAs across various mammalian cell models, we confirmed that Gag could effectively incorporate miRNAs without additional modifications, mirroring the RNA export efficiencies reported for HIV-1 infections 22 and other viral systems 46 . Nevertheless, while this inherent binding capacity meets the needs of many applications, exploring low-abundance miRNAs in specific subcellular compartments may require an advanced export potential 35,47 . To this end, we significantly boosted SNaP miRNA binding in a sequence-independent manner using the TRBP module 36,37 . SNaP-TRBP miRNA export was twice as effective as unmodified Gag VLPs in HEK-293T cells, with comparable improvements in neuron models. The integrated functionality of the TRBP and DLS domains further supports TRBP engineering as a promising approach for the large-scale recovery of compartmentalized miRNAs, particularly those located at synaptic sites. By increasing the sensitivity of localized transcriptome profiling, the SNaP-TRBP-DLS system offers the potential to advance our understanding of brain region-specific gene expression, extending even to rare cellular and subcellular miRNA populations 17,18 . The significant RNA packaging properties of the SNaP modular system support comprehensive genetic payload characterization using Next Generation Sequencing. By introducing a novel, sequence-independent approach to RNA profiling, our study overturns the prevailing focus in retroviral VLP engineering - which has emphasized restricting broad RNA packaging in favour of targeted therapeutic cargos 25,48 . Through bulk miRNA profiling, we anticipate that SNaP will enable the generation of comprehensive datasets detailing patterned miRNA alterations across a range of physiological and pathological conditions, thereby guiding the discovery of more specific and sensitive biomarkers associated with brain disorders 13 . Above all, this study provides the first evidence that engineered Gag VLPs can serve as robust platforms for the non-destructive miRNA profiling of cell-type-specific brain-derived cells. These findings align with earlier reports supporting chimeric nanoparticle packaging in clinically relevant lymphoid cell lines 25 . By facilitating spatially resolved miRNA profiling within intact tissues, not only do our findings demonstrate the scalability of SNaP for in vivo applications, but they also underscore its potential for the longitudinal evaluation of miRNA dynamics over time. To our knowledge, no other existing technology offers this combined capacity for high-resolution, real-time miRNA analysis in living brain tissues. Nevertheless, while our exploratory assessments offer valuable insights for these applications, we recognize that a more in-depth characterization of the viability and physiological state of packaging cells will be beneficial to fully substantiate future in vivo implementations. In summary, this study explores the modular capabilities of the chimeric SNaP platform, showcasing how its components can be synergistically combined to ultimately enhance local miRNA recovery and analysis. Additionally, it provides critical insights into optimizing retroviral particle packaging in clinically relevant cell types, with successful applications in both neuronal and glial cell models. Our research positions SNaP as an innovative tool for the cell-type specific profiling of non-coding small RNA in the cellular heterogeneous nervous tissue, offering portability to high-throughput and in vivo miRNA profiling applications. While our design primarily focuses on the CNS, the inherent flexibility of the SNaP approach opens avenues for future characterization of virtually any mammalian tissue exhibiting considerable cellular heterogeneity and/or polarization. Online Methods 1. Cell culture Human embryonic kidney HEK-293T cells (ATCC CRL-3216), immortalized HT22 hippocampal neurons, and immortalized BV-2 microglia were cultured routinely in Dulbecco’s Modified Eagle’s Medium (DMEM) with low glucose (EuroClone). The medium was supplemented with 10% heat-inactivated fetal bovine serum (FBS, EuroClone), 100 U/mL penicillin, and 100 µg/mL streptomycin (Sigma Aldrich, Milan, Italy). All cell lines were maintained under standard conditions at 37 °C with 5% CO2. Human integrated, inducible, and isogenic (i 3 ) iPSCs (as described by Wang et al., 2017 49 ) were generously provided by Dr. Michael Ward from NINDS/NIH. Cell handling and differentiation followed the protocol outlined by Fernandopulle et al., 2018 50 (detailed procedure outlined in Supplementary Information ). Culturing was performed until mature polarity was observed (4 weeks in vitro , as previously described by Wang et al., 2017 49 ). Mouse embryonic stem cells (mESCs), line E14Tg2A, handling and differentiation were performed according to the methods described by Bertacchi et al., 2013 51 , and Lupo et al., 2014 52 (refer to Supplementary Information for complete description). Cells were cultured until they reached full maturation,as described in Bertacchi et al, 2013 51 . 2. Molecular cloning Chimeric Gag proteins were cloned from an initial donor vector expressing the Rev-independent, codon-optimized HIV-1 Gag coding sequence, fused in-frame with eGFP, and under the regulation of the CMV promoter (pGag-eGFP, courtesy of the NIH AIDS Reagent Program, cat ARP11468). SNaP-CSP constructs have been generated as follows: the Gag insert from the pGag-eGFP plasmid, digested with BssHII and BamHI, was partially overlapped with the pAAV-CamKII vector (Addgene, cat. 64545), linearized with EcorV and BamHI, or the pAAV-mIba1 backbone (Addgene cat. 190163), digested with AgeI and NotI. To generate Gag-TRBP constructs the two double-strand RNA-binding domains (dsRBD1 and dsRBD2) from TRBP have been amplified by PCR out of the pcDNA-TRBP template (Addgene, cat. 15666) using the following primers to facilitate the insertion of an N-terminal, hydrophilic, 33 bp flexible linker (sequence: NRNGDPPVATM, GRAVY hydrophobicity score: -1.04) along with BamHI and NotI restriction sites to facilitate cloning: forward primer: 5’AAAACAGAAACGGGGATCCACCGGTCGCCACCATGGCGAT-3’; reverse primer: 5’-TCTAGAGCGGCCGCTTACAGCATTT-3’. The resulting Linker-TRBP insert was subcloned downstream of the Gag sequence of the pGag-eGFP construct using BamHI and NotI restriction digestion. To express chimeric Gag proteins in i 3 neurons and mouse embryonic stem cell (mESC)-derived neurons, the BssHII and NotI-digested Gag insert from pGag-eGFP was subcloned into the pBOB-EF-1-FastFUCCI-Puro vector (Addgene, cat.86849) upon removal of the FUCCI cassette via the same enzyme set (final construct: pBOB-EF-1α-Gag). To generate the pBOB-EF-1α-Gag-DLS construct, a 247 bp sequence corresponding to the dendritic localisation signal (DLS) was amplified from the Psd95 transcript, as described by Subramanian et al, 2011. This sequence was contained in a pCDNA3.1 vector (courtesy of the Laboratorio di Biologia Bio@SNS at Scuola Normale Superiore). PCR primers with BamHIand NotIrestriction sites were used for amplification (forward primer: 5’-ATAGGATCCTTAATGGCTTTTTTTTTTTCT-3’; reverse primer: 5’-ATAGCGGCCGCGTCTGTCTCTT-3’). These sites facilitated restriction-mediated cloning of the DLS sequence downstream the STOP codon in pBOB-EF-1α-Gag. For the pBOB-EF-1α-Gag-TRBP-DLS construct, we added the TRBP sequence to the pBOB-EF-1α-Gag-DLS vector linearized with NotI. 3. SNaP production HT22/BV-2 co-cultures. Both cell lines were pre-treated with the neutral sphingomyelinase inhibitor GW4869 (Sigma Aldrich, cat. 6823-69-4) at a concentration of 10 µM for 2 hours to partially inhibit extracellular vesicle (EV) secretion. GW4869-conditioned cells were then co-cultured in a HTT/BV-2 ratio of 110.000/60.000 cells and maintained in standard culture conditions as described above. The next day, co-cultures were transfected using Lipofectamine 2000 (ThermoFisher Scientific) or Glial-Mag (OZ Biosciences) for the transient expression of pAAV-CaMKII-Gag or pAAV-mIba1-Gag, respectively. A total of 4 µg of pAAV-CaMKII-Gag and 3 µg of pAAV-mIba1-Gag per well were used, following the respective manufacturers’ protocols. Mock-transfected cells were used as control. The culture medium was collected at 48- and 72-hours post-transfection, centrifuged at 1,200 rpm for 5 minutes, and filtered through a 0.45 µm PES filter to remove cellular debris. SNaP particles were concentrated approximately 500-fold by ultracentrifugation on a 20% (w/v) sucrose cushion inPBS. i 3 Neurons and mESC-derived neurons : doxycycline-induced i 3 neural progenitors were seeded onto Geltrex-coated 10 cm culture dishes at a density of 10 million cells per plate. During plating, cells were transduced with VSV-G-pseudotyped lentiviral vectors expressing pBOB-EF1α-Gag, pBOB-EF1α-Gag-DLS, or empty pBOB-Ef1α constructs (details on neural progenitor transduction in Supplementary Information ). The medium was fully replaced the following day, and neurons were maintained for four weeks in culture. mESC-derived neural progenitors were seeded at a density of 125,000 cells/cm² on poly-ornithine and laminin-coated wells at DIV7. They were then transduced with pBOB-EF1α-Gag-DLS, pBOB-EF1α-Gag-TRBP-DLS, or control pBOB-EF1α lentiviral vectors as described in Supplementary Information . Mock-transduced cells were used as control. Following lentiviral incubation, the culture medium was replaced with Neurobasal A, and neurons were cultured until full maturation, with daily medium replacement. SNaP particles from both i 3 and mESC-derived neurons were harvested from the media of mature cells and purified as described above. HEK-293T cells : Cells were seeded onto 10 cm culture dishes at a density of 5 million cells and co-transfected the next day using PEI. Transfections were performed using 25 µg of either pGag-eGFP or pGag-TRBP (control: Gag-free vector) and 5 µg of VSV-G plasmid, maintaining a 5:1 ratio. PEI/DNA complexes were formed in serum-free DMEM Low-Glucose, and were incubated for 10 minutes at room temperature before being added to the cells. Mock-transfected cells were used as control. Cells were then maintained overnight in Opti-MEM (Gibco) medium. From the following day, the culture medium was supplemented with the GW4869 EV-inhibitor (final concentration 10 µM). SNaP VLPs were then purified from culture medium collected at 48 and 72 hours post-transfection as described above. 4. Titration of SNaP particles The physical titer of SNaP particles was determined using a commercial enzyme-linked immunosorbent assay (ELISA) specific for the detection of the HIV p24 core antigen in cell culture supernatants (Innotest HIV antigen mAb assay; Fujirebio, cat. 81512), according to the manufacturer’s instructions. Absorbance was measured at 450 nm for p24 quantification, and the antigen concentration was determined by generating a standard curve from the control and performing a linear regression analysis. 5. SNaP Cargo RNA extraction A 300 μL aliquot of concentrated SNaP particle suspension was treated with RNase A (2 μg/μL) for 15 minutes at 37°C to degrade any extra-vesicular RNA. Total RNA was then isolated from both SNaP particles and producer cells using the miRNeasy Micro Kit (Qiagen, cat. 217084). While the standard protocol was applied for cell pellet samples, modifications were implemented for viral particle preparations. Specifically, after a 5-minute incubation in Qiazol lysis reagent (Qiagen), 10 mg/mL glycogen was added to the solubilized SNaP samples to enhance miRNA recovery. Phase separation was performed by adding 200 μL of chloroform, followed by RNA purification according to the manufacturer’s instructions. RNA purity was assessed via UV spectrophotometry. For cellular RNA, ribosomal RNA integrity was evaluated by confirming the 28S:18S rRNA ratio of 2:1, while RNA integrity from SNaP particles was assessed by automated electrophoresis as described in the Supplementary Information. 6. Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and determination of SNaP miRNA packaging efficiency For cDNA synthesis, 1 μg of cellular RNA or 100 ng of VLP RNA was reverse transcribed using the miR-X miRNA First-Strand Synthesis Kit (Takara, cat. 638315), according to the manufacturer’s protocol. RT-qPCR was performed on 5 μL of cDNA (diluted 1:100) in a total reaction volume of 20 μL using SSO Advanced Universal SYBR Green Supermix (BioRad, cat. 1725271). Forward primers were specific to the mature miRNA sequences, while the universal reverse primer provided with the kit targeted the poly(T) adapter sequence incorporated during cDNA synthesis. A comprehensive list of primers employed is available in Supplementary Information, Table 2 . PCR amplification was conducted on a Rotor-Gene Q cycler (Qiagen) with the following thermal cycling conditions: initial denaturation at 95°C for 2 minutes, followed by 35 cycles of 95°C for 30 seconds, 55°C for 30 seconds, and 72°C for 30 seconds. Primer specificity was verified by performing melting curve analysis from 65°C to 95°C, increasing in 0.5°C increments per second. Relative quantification of miRNA expression in packaging cells was calculated using the standard ΔΔCt method 53 , with U6 small nuclear RNA serving as the reference gene for normalization. For SNaP particle samples, as a suitable reference gene was unavailable, miRNA expression was determined via the ΔCt method, ensuring that equal amounts of input total RNA were used for all samples, in line with recommendations by Livak and Schmittgen 54 . ΔCts were determined as the difference between the C T values of SNaP particles and those obtained from the supernatant of matching mock-transfected/transduced cultures. To quantify the extent of miRNA encapsidation attributable to SNaP engineering, the so-obtained expression levels from chimeric particles were normalized to those from the corresponding benchmark samples. This ratio produced fold enrichment values, which we defined as “miRNA recovery efficiency”. The components of each comparative analysis are specified in the respective figures. 7. Immunofluorescence and colocalization analysis HT22 and BV-2 co-cultures were established by seeding 70,000 HT22 cells and 35,000 BV-2 cells per well in 8-well chamber slides (Nunc Lab-Tek, Thermo Fisher Scientific). The following day, transfection was performed with 250 ng of pCamkIIα-Gag plasmid for HT22 cells or 100 ng of pIba1-Gag plasmid for BV-2 cells, using Lipofectamine 2000 (Thermo Fisher Scientific) for neuronal cells and GlialMag Transfection Reagent (OZ Biosciences) for microglia, in accordance with manufacturer protocols. After 24 hours, the medium was replaced, and cultures were maintained for an additional 48 hours. Doxycycline-induced i 3 progenitors and DIV7 mESC-derived neuronal progenitors were seeded onto glass coverslips coated with Geltrex or polyornithine, respectively, at a density of 100,000 cells/cm². Lentiviral transduction with pBOB-Gag or pBOB-Gag-DLS vectors was carried out as described in Supplementary Information . Following transduction, the medium was refreshed after 24 hours, and cells were cultured under standard differentiation conditions until full maturation. HT22/ BV-2 co-cultures and i 3 neurons were fixed in 4% paraformaldehyde (PFA), rinsed in PBS, and permeabilized with 0.1% Triton X-100 for 5 minutes at room temperature. After additional PBS washes, nonspecific binding was blocked by incubation in 1% (w/v) BSA for 30 minutes. mESC-derived neurons were fixed in 2% PFA, blocked for 1 hour in PBS supplemented with 3% (w/v) BSA and 3% (v/v) FBS, and permeabilized in 0.5% (w/v) Triton X-100 in PBS. All samples were then incubated overnight at 4°C in a humidified chamber with primary antibodies diluted in blocking buffer (antibody list available in Supplementary Table 1 ). The following day, after washing in PBS, Alexa Fluor–conjugated secondary antibodies ( Supplementary Information, Table 1 ) were applied for 2 hours at room temperature. Nuclear counterstaining was performed using DAPI (1:100,000) for 10 minutes. Optical sections (512 x 512 pixels) were acquired using a Leica STELLARIS 5 confocal microscope. For whole-cell reconstruction, an average of 10 image stacks was loadingd with slices spaced 0.5 μm apart. Images were deconvolved for analysis using Fiji software (NIH, Bethesda). Colocalization between green Alexa 488 and far-red Alexa 633 signals [2] (corresponding to eGFP/p24 and Homer 1b/c, respectively) was quantified using the "coloc" tool in Imaris 7.2.3 software (Oxford Instruments), following the approach by Costes et al. 55 . To counteract the diffuse staining pattern of Homer 1b/c, coupled with the high density of plated cells, a region of interest (ROI) was defined that included only a single p24-positive neuron per imaged field. Using the ROI as a mask to exclude non-p24-expressing cells from the analysis, the percentage of colocalization was defined as the proportion of Gag-signal voxels overlapping with Homer 1b/c voxels within this selected region. Selected images had consistent ROI size and dimensions across all experiments. 8. Statistical analysis Statistical analyses and graphical representations were performed using Prism 8.0.2 (GraphPad Software Inc., CA, USA). To compare multiple groups, non-parametric Kruskal-Wallis tests followed by Dunn’s multiple comparisons post-hoc test were used. For comparisons between two groups, either Student’s t-test, Mann-Whitney U test, or Mood’s median test was applied, depending on the experimental design, as specified in the Fig. legends. A two-sided p-value below 0.05 was deemed statistically significant, with significance levels represented as * for p < 0.05, ** for p < 0.01, *** for p < 0.001, **** for p < 0.0001, and "n.s." for non-significant results. Exact p-values and further details regarding data presentation are provided in the respective Fig. legends. Declarations Data Availability The microarray dataset of synaptosomal miRNAs analyzed in this work is openly available at https://www.synapse.org/#!Synapse:syn26642975/files/, Synapse ID: syn26642975. All other data generated throughout this study are included in the manuscript and/or Supplementary Information. Acknowledgements The authors wish to acknowledge M. Calvello, S. Lisi, V. Liverani, A. Viegi, M. Sanguanini (Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Pisa) for their valuable technical assistance; L. Poliseno (Institute of Clinical Physiology, National Research Council of Pisa) for access to equipment. We are also grateful to Dr. M. Ward (NINDS, NIH) for providing human i 3 induced pluripotent stem cells (iPSCs), and the NIH AIDS reagent program for providing the mouse anti-HIV-1 p24 Monoclonal Antibody and the pGag-eGFP construct. The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by: EU funding within the Next-Generation EU-MUR PNRR TUSCANY HEALTH Ecosystem (THE) (project no. ECS_00000017) spoke 8 to AC. and CDP; Scuola Normale institutional funds to AC,; PRIN2022 to AC. M.C.C. and R.W.-M. are supported by the Wellcome Trust (grant ref. 223202/Z/21/Z). Author Information Authors and Affiliations Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Via G.Moruzzi 1, Pisa, 56126 Italy Marianna Mignanelli # , Giacomo Siano * , Arianna Scarlatti, Greta Ghiloni, Federico Cremisi, Ludovico Maggi, Antonino Cattaneo # Current address: BioPharmaceuticals R&D, AstraZeneca UK ltd, Cambridge Biomedical Campus, 1 Francis Crick Avenue, Cambridge CB2 0AA, UK * Current address: Department of neural signalling, F. Hoffmann- La Roche AG, Grenzacherstrasse 124, Basel, 4070, Switzerland Institute of Neuroscience, Italian National Research Council (CNR), Via G.Moruzzi 1, Pisa, 56126, Italy Giacomo Siano * , Vincenzo Iannone, Cristina Di Primio Institute of Life Sciences, School of Advanced Studies Sant’Anna, Via G.Moruzzi 1, Pisa, 56126, Italy. Emanuele Orsini † † Current address: Centre for Genetic Engineering and Biotechnology (ICGEB), Padriciano 99 Trieste, 34149, Italy Institute of Clinical Physiology, Italian National Research Council (CNR), Via G.Moruzzi 1, Pisa, 56126, Italy Milena Rizzo Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Road, Oxford OX1 3PT, United Kingdom Maria Claudia Caiazza, Richard Wade-Martins Kavli Institute for Neuroscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Park Road, Oxford OX1 3QU, United Kingdom Maria Claudia Caiazza, Richard Wade-Martins Department of Clinical and Experimental Medicine, University of Pisa, Via Savi 10, 56126 Pisa, Italy Alessandra Salvetti Contributions AC and CDP conceived the initial idea, C.D.P. conceived the project. C.D.P., M.M., G.S., M.R., M.C.C., contributed to the experimental design. M.M., V.I, A.S, E.O., L.M., G.G. conducted experiments. C.D.P. supervised the study. M.C.C. and R.W.M. supervised the human neuron work. A.C., F.C. and R.W.M. obtained research funding and contributed to critical supervision and project leadership. M.M. wrote, and AC and CDP revised the manuscript. All authors commented and approved the final version. Corresponding Authors Antonino Cattaneo ( [email protected] ), or Cristina Di Primio ( [email protected] ). Ethics declaration Conflicts of interest Marianna Mignanelli is currently an employee and stock owner at AstraZeneca UK ltd, UK. Giacomo Siano is currently employed at F. Hoffmann- La Roche AG, Switzerland. The remaining authors have no conflicts of interest to declare. References He, L. & Hannon, G. J. MicroRNAs: Small RNAs with a big role in gene regulation. Nature Reviews Genetics vol. 5 522–531 (2004). Jovicic, A. et al. Comprehensive expression analyses of neural cell-type-specific miRNAs identify new determinants of the specification and maintenance of neuronal phenotypes. Ann Intern Med 158, 5127–5137 (2013). Kawase-Koga, Y. et al. RNAase-III enzyme Dicer maintains signaling pathways for differentiation and survival in mouse cortical neural stem cells. J Cell Sci 123, 586–594 (2010). Sempere, L. F. et al. Expression Profiling of Mammalian MicroRNAs Uncovers a Subset of Brain-Expressed MicroRNAs with Possible Roles in Murine and Human Neuronal Differentiation. Genome Biol. 5 (2004). Schratt, G. M. et al. A brain-specific microRNA regulates dendritic spine development. Nature 439, 283–289 (2006). Hu, Z. & Li, Z. miRNAs in synapse development and synaptic plasticity. Current Opinion in Neurobiology vol. 45 24–31 (2017). Fénelon, K. et al. Deficiency of Dgcr8, a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex. Proc Natl Acad Sci U S A 108, 4447–4452 (2011). Aksoy-Aksel, A., Zampa, F. & Schratt, G. MicroRNAs and synaptic plasticity-a mutual relationship. Philosophical Transactions of the Royal Society B: Biological Sciences vol. 369 (2014). Ashraf, S. I., McLoon, A. L., Sclarsic, S. M. & Kunes, S. Synaptic protein synthesis associated with memory is regulated by the RISC pathway in Drosophila. Cell 124, 191–205 (2006). Banerjee, S., Neveu, P. & Kosik, K. S. A Coordinated Local Translational Control Point at the Synapse Involving Relief from Silencing and MOV10 Degradation. Neuron 64, 871–884 (2009). Brennan, G. P. & Henshall, D. C. MicroRNAs as regulators of brain function and targets for treatment of epilepsy. Nature Reviews Neurology vol. 16 506–519 (2020). Hoss, A. G., Labadorf, A., Beach, T. G., Latourelle, J. C. & Myers, R. H. microRNA profiles in Parkinson’s disease prefrontal cortex. Front Aging Neurosci 8, (2016). Condrat, C. E. et al. miRNAs as Biomarkers in Disease: Latest Findings Regarding Their Role in Diagnosis and Prognosis. Cells vol. 9 (2020). Perez, J. D. & Schuman, E. M. Subcellular RNA-seq for the Analysis of the Dendritic and Somatic Transcriptomes of Single Neurons. Bio Protoc 12, (2022). Trebesova, H. & Grilli, M. Synaptosomes: A Functional Tool for Studying Neuroinflammation. Encyclopedia 3, 406–418 (2023). Cajigas, I. J. et al. The Local Transcriptome in the Synaptic Neuropil Revealed by Deep Sequencing and High-Resolution Imaging. Neuron vol.74 453-466 (2012). Hücker, S. M. et al. Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells. Nat Commun 12, (2021). Piwecka, M., Rajewsky, N. & Rybak-Wolf, A. Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease. Nature Reviews Neurology vol. 19 346–362 (2023). Maji, R. K., Leisegang, M. S., Boon, R. A. & Schulz, M. H. Revealing microRNA regulation in single cells. Trends in Genetics vol. 41 522–536 (2025). Zolboot, N., Du, J. X., Zampa, F. & Lippi, G. MicroRNAs Instruct and Maintain Cell Type Diversity in the Nervous System. Frontiers in Molecular Neuroscience vol. 14 (2021). Martins, S. A. et al. How promising are HIV-1-based virus-like particles for medical applications. Frontiers in Cellular and Infection Microbiology vol. 12 (2022). Bogerd, H. P., Kennedy, E. M., Whisnant, A. W. & Cullen, B. R. Induced packaging of cellular micrornas into HIV-1 virions can inhibit infectivity. mBio 8, (2017). Cimarelli, A., Sandin, S., Ho¨glund, S., Ho¨glund, H. & Luban, J. Basic Residues in Human Immunodeficiency Virus Type 1 Nucleocapsid Promote Virion Assembly via Interaction with RNA. J Virol vol.74 (2000). Cervera, L. et al. Production of HIV-1-based virus-like particles for vaccination: achievements and limits. Appl Microbiol Biotechnol 103, 7367–7384 (2019). Horns, F. et al. Engineering RNA export for measurement and manipulation of living cells. Cell 186, 3642-3658.e32 (2023). McKenzie, A. T. et al. Brain Cell Type Specific Gene Expression and Co-expression Network Architectures. Sci Rep 8, (2018). Boulaire, J., Balani, P. & Wang, S. Transcriptional targeting to brain cells: Engineering cell type-specific promoter containing cassettes for enhanced transgene expression. Advanced Drug Delivery Reviews vol. 61 589–602 (2009). Ohsawa, K., Imai, Y., Sasaki, Y. & Kohsaka, S. Microglia/macrophage-specific protein Iba1 binds to fimbrin and enhances its actin-bundling activity. J Neurochem 88, 844–856 (2004). Yasuda, R., Hayashi, Y. & Hell, J. W. CaMKII: a central molecular organizer of synaptic plasticity, learning and memory. Nature Reviews Neuroscience vol. 23 666–682 (2022). Hafner, A. S., Donlin-Asp, P. G., Leitch, B., Herzog, E. & Schuman, E. M. Local protein synthesis is a ubiquitous feature of neuronal pre- And postsynaptic compartments. Science (1979) 364, (2019). Subramanian, M. et al. G-quadruplex RNA structure as a signal for neurite mRNA targeting. EMBO Rep 12, 697–704 (2011). Puhl, D. L., D’Amato, A. R. & Gilbert, R. J. Challenges of gene delivery to the central nervous system and the growing use of biomaterial vectors. Brain Research Bulletin vol. 150 216–230 (2019). Bicker, S., Lackinger, M., Weiß, K. & Schratt, G. MicroRNA-132, -134, and -138: a microRNA troika rules in neuronal dendrites. Cellular and molecular life sciences : CMLS vol. 71 3987–4005 (2014). Kumar, S. et al. Synaptosome microRNAs regulate synapse functions in Alzheimer’s disease. NPJ Genom Med 7, (2022). Koshiol, J., Wang, E., Zhao, Y., Marincola, F. & Landi, M. T. Strengths and limitations of laboratory procedures for microRNA detection. Cancer Epidemiology Biomarkers and Prevention vol. 19 907–911 (2010). Benoit, M. P. M. H. et al. The RNA-binding region of human TRBP interacts with microRNA precursors through two independent domains. Nucleic Acids Res 41, 4241–4252 (2013). Fareh, M. et al. TRBP ensures efficient Dicer processing of precursor microRNA in RNA-crowded environments. Nat Commun 7, 1–11 (2016). Gutiérrez-Granados, S., Cervera, L., Gòdia, F. & Segura, M. M. Characterization and quantitation of fluorescent Gag virus-like particles. BMC Proc 7, (2013). Cervera, L. et al. Generation of HIV-1 Gag VLPs by transient transfection of HEK 293 suspension cell cultures using an optimized animal-derived component free medium. J Biotechnol 166, 152–165 (2013). Panwar, B., Omenn, G. S. & Guan, Y. MiRmine: A database of human miRNA expression profiles. Bioinformatics 33, 1554–1560 (2017). Ganser-Pornillos, B. K., Yeager, M. & Sundquist, W. I. The structural biology of HIV assembly. Current Opinion in Structural Biology vol. 18 203–217 (2008). Liu, Y. et al. HIV-1 Sequence Necessary and Sufficient to Package Non-viral RNAs into HIV-1 Particles. J Mol Biol 429, 2542–2555 (2017). Chen, A. K. et al. MicroRNA binding to the HIV-1 Gag protein inhibits Gag assembly and virus production. Proc Natl Acad Sci U S A 111, (2014). de Marco, A. et al. Conserved and Variable Features of Gag Structure and Arrangement in Immature Retrovirus Particles. J Virol 84, 11729–11736 (2010). Veziroglu, E. M. & Mias, G. I. Characterizing Extracellular Vesicles and Their Diverse RNA Contents. Frontiers in Genetics vol. 11 (2020). Prel, A. et al. Highly efficient in vitro and in vivo delivery of functional RNAs using new versatile MS2-chimeric retrovirus-like particles. Mol Ther Methods Clin Dev 2, 15039 (2015). Benesova, S., Kubista, M. & Valihrach, L. Small rna-sequencing: Approaches and considerations for miRNA analysis. Diagnostics vol. 11 (2021). Segel, M. et al. Mammalian Retrovirus-like Protein PEG10 Packages Its Own mRNA and Can Be Pseudotyped for mRNA Delivery. Science Vol.373, 882-889 Wang, C. et al. Scalable Production of iPSC-Derived Human Neurons to Identify Tau-Lowering Compounds by High-Content Screening. Stem Cell Reports 9, 1221–1233 (2017). Fernandopulle, M. S. et al. Transcription Factor–Mediated Differentiation of Human iPSCs into Neurons. Curr Protoc Cell Biol 79, (2018). Bertacchi, M. et al. The positional identity of mouse ES cell-generated neurons is affected by BMP signaling. Cellular and Molecular Life Sciences 70, 1095–1111 (2013). Lupo, G. et al. From pluripotency to forebrain patterning: An in vitro journey astride embryonic stem cells. Cellular and Molecular Life Sciences vol. 71 2917–2930 (2014). Pfaffl, M. W. A New Mathematical Model for Relative Quantification in Real-Time RT-PCR. Nucleic Acids Research vol. 29 (2001). Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods 25, 402–408 (2001). Costes, S. V. et al. Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophys J 86, 3993–4003 (2004). Additional Declarations Yes there is potential Competing Interest. Marianna Mignanelli is currently an employee and stock owner at AstraZeneca UK ltd, UK. Giacomo Siano is currently employed at F. Hoffmann- La Roche AG, Switzerland. The remaining authors have no conflicts of interest to declare. Supplementary Files SupplementaryInformationNaturePublishinggroup.docx Supplementary Information - Nature publishing group Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7775232","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":530215334,"identity":"dd2437b7-af2e-4916-9803-b8876fa1525a","order_by":0,"name":"Marianna Mignanelli","email":"","orcid":"https://orcid.org/0000-0002-7994-4279","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Marianna","middleName":"","lastName":"Mignanelli","suffix":""},{"id":530215335,"identity":"cd9a11b3-b6dc-40c2-9186-24e08c7a7adb","order_by":1,"name":"Giacomo Siano","email":"","orcid":"","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Giacomo","middleName":"","lastName":"Siano","suffix":""},{"id":530215336,"identity":"117cb400-f3c8-416a-921d-6901cf6cf40d","order_by":2,"name":"Vincenzo Iannone","email":"","orcid":"","institution":"National Research Council (CNR) of Italy, Pisa","correspondingAuthor":false,"prefix":"","firstName":"Vincenzo","middleName":"","lastName":"Iannone","suffix":""},{"id":530215337,"identity":"c0423b2c-0628-4d88-a666-c503b691e587","order_by":3,"name":"Arianna Scarlatti","email":"","orcid":"","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Arianna","middleName":"","lastName":"Scarlatti","suffix":""},{"id":530215338,"identity":"30729d91-4cb0-4b38-89c9-a817b165334e","order_by":4,"name":"Emanuele Orsini","email":"","orcid":"","institution":"Institute of Life Sciences - School of Advanced Studies Sant'Anna","correspondingAuthor":false,"prefix":"","firstName":"Emanuele","middleName":"","lastName":"Orsini","suffix":""},{"id":530215339,"identity":"61ec22da-0ba6-4998-9ead-e7e3f473b1c2","order_by":5,"name":"Ludovico Maggi","email":"","orcid":"","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Ludovico","middleName":"","lastName":"Maggi","suffix":""},{"id":530215340,"identity":"c61a35fe-c0db-4462-bb38-b00687cf86ee","order_by":6,"name":"Milena Rizzo","email":"","orcid":"","institution":"Institute of Clinical Physiology - National Research Council of Italy","correspondingAuthor":false,"prefix":"","firstName":"Milena","middleName":"","lastName":"Rizzo","suffix":""},{"id":530215341,"identity":"1c1346f4-d8c0-4eca-b412-1962933b0c92","order_by":7,"name":"Maria Claudia Caiazza","email":"","orcid":"","institution":"Oxford Parkison's Disease Centre- Department of Physiology, Anatomy and Genetics (DPAG)- University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Claudia","lastName":"Caiazza","suffix":""},{"id":530215342,"identity":"08104909-26d8-44c0-bf96-46140a71ace3","order_by":8,"name":"Richard Wade-Martins","email":"","orcid":"","institution":"Oxford Parkison's Disease Centre- Department of Physiology, Anatomy and Genetics (DPAG)- University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Wade-Martins","suffix":""},{"id":530215343,"identity":"9e64143b-7e6a-4d47-81ad-ebf26e3437bf","order_by":9,"name":"Alessandra Salvetti","email":"","orcid":"","institution":"Department of Clinical and Experimental Medicine - Unviersity of Pisa","correspondingAuthor":false,"prefix":"","firstName":"Alessandra","middleName":"","lastName":"Salvetti","suffix":""},{"id":530215344,"identity":"ea88ccae-5878-4284-aa1c-ae3a2a371870","order_by":10,"name":"Greta Ghiloni","email":"","orcid":"","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Greta","middleName":"","lastName":"Ghiloni","suffix":""},{"id":530215345,"identity":"3d678665-5408-4d04-ba60-a0043a44ca4c","order_by":11,"name":"Federico Cremisi","email":"","orcid":"","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Federico","middleName":"","lastName":"Cremisi","suffix":""},{"id":530215346,"identity":"03df22ef-d86e-4c2f-811c-308f8bfbf9ef","order_by":12,"name":"Antonino Cattaneo","email":"","orcid":"","institution":"Scuola Normale Superiore","correspondingAuthor":false,"prefix":"","firstName":"Antonino","middleName":"","lastName":"Cattaneo","suffix":""},{"id":530215333,"identity":"051b816f-eedc-41a1-8087-7b37b4b2c23d","order_by":13,"name":"Cristina Di Primio","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIie3PvQrCMBDA8etilkDWBARfIV3URXwVi6CLg2MnORDiIvgAfQ/nQtbgrNRFCp0Lrg6m9aMINq4O+dPhAvnRC4DP95cFCCCrIaoHCgSrE3eT9IPQtCYuA1DfgcnzxB9DK2GJXl/L5bkHZKryeLnvMpEXeQzDVRvhh0jxVBYh0ssmNDKjIpkNQuNYTNJA2bfoAHmkBFois0VHoJusS0vGDTmZnwTtYjpqyJG6CTeB4kbqqareUhGxnfWt5ZZ9j21JXsY3PdqReXHBWzZmRBcC4xVr+8u7Tv01C/8EL+Xz+Xy+L90Bou5QRzo4M0wAAAAASUVORK5CYII=","orcid":"","institution":"National Research Council (CNR) of Italy, Pisa","correspondingAuthor":true,"prefix":"","firstName":"Cristina","middleName":"Di","lastName":"Primio","suffix":""}],"badges":[],"createdAt":"2025-10-03 17:00:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7775232/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7775232/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95897115,"identity":"e4b62246-bdcd-44f6-9f33-75a6b9f495ba","added_by":"auto","created_at":"2025-11-14 07:24:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":997073,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNaP nanoparticles efficiently package neuronal or microglial miRNAs in a brain cell co-culture System \u003c/strong\u003eA) Schematic representation of the experimental setup for the targeted production of the SNaP tool using a cell-specific promoter domain in HT22/BV-2 co-cultures. B) Representative confocal images showing cell-specific Gag expression (p24, yellow) in HT22 (neuronal marker HuC/D, red) and BV-2 cells (microglial marker CD11b, green). Mock-transfected cocultures used as control. Nuclei counterstained with DAPI (blue). Scale bar: 10 μm. C) Quantification of p24 levels in supernatants from co-cultures transfected with Neuro-SNaP or Microglia-SNaP constructs. Data represent mean ± SEM (n= 4 independent replicates). Mann-Whitney U test: p= 0.100, U= 3 (not significant). D) miRNA recovery efficiency in Microglia-SNaP relative to Neuro-SNap (for \u003cem\u003emmu-miR-127\u003c/em\u003e and \u003cem\u003emmu-miR-433\u003c/em\u003e) and in Neuro-SNaP versus Microglia-SNaP (for \u003cem\u003emmu-miR-142\u003c/em\u003e and \u003cem\u003emmu-miR-223\u003c/em\u003e). The definition of miRNA recovery efficiency is provided in \u003cem\u003eMaterials and Methods\u003c/em\u003e. Boxplots represent median fold changes with range (whiskers). Mann-Whitney U test: \u003cem\u003emmu-miR-127\u003c/em\u003e(p= 0.0079, U= 0),\u003cem\u003e mmu-miR-433\u003c/em\u003e (p= 0.023, U= 6), \u003cem\u003emmu-miR-142\u003c/em\u003e (p= 0.028, U= 0), \u003cem\u003emmu-miR-223\u003c/em\u003e (p= 0.04, U= 5).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7775232/v1/19638c54470c30687c9e5954.png"},{"id":95897118,"identity":"be30cedb-73ed-4ab3-b845-b882419dfe26","added_by":"auto","created_at":"2025-11-14 07:24:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1032621,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEngineering SNaP-DLS for enhanced postsynaptic targeting in human cortical glutamatergic neurons\u003c/strong\u003e. A) Schematic overview of the experimental design for SNaP-DLS production in human neurons. B) Representative confocal images of DIV28 neurons expressing SNaP or SNaP-DLS. Gag localization is visualized via p24 staining (green), postsynaptic compartments by Homer 1b/c (red), and nuclei by DAPI (blue). Mock-transduced neurons serving as control. Scale bar: 10 μm. C) Co-localization analysis of p24 with Homer 1b/c, shown as the percentage overlap in the region of interest (ROI). Data presented as violin plots, n= 30 (SNaP) and n= 25 (SNaP-DLS) ROIs from n= 2 independent experiments. Mann-Whitney U test: p\u0026lt;0.0001, U= 12. D) p24 antigen levels in the supernatants from i\u003csup\u003e3\u003c/sup\u003e neurons expressing SNaP or SNaP-DLS constructs. Data represent mean ± SEM (n= 3 independent particle productions per group). Mann-Whitney U test: p= 0.100, U= 0 (not significant). E) miRNA recovery efficiency in SNaP-DLS relative to SNaP for \u003cem\u003ehsa-miR-132\u003c/em\u003e,\u003cem\u003e hsa-miR-134\u003c/em\u003e, and \u003cem\u003ehsa-miR-138\u003c/em\u003e. The definition of miRNA recovery efficiency is provided in \u003cem\u003eMaterials and Methods\u003c/em\u003e. Boxplots show median fold change with range, adjusted for background miRNA levels in mock-transduced controls (n= 3-4 productions per group). Mann-Whitney U test: \u003cem\u003ehsa-miR-132\u003c/em\u003e (p= 0.043, U= 0), \u003cem\u003ehsa-miR-134\u003c/em\u003e (p= 0.043, U= 0), \u003cem\u003ehsa-miR-138\u003c/em\u003e (p= 0.043, U= 0). F) Comparison of miRNA recovery efficiency between synaptosomes (Kumar et al., 2022) and SNaP-DLS for \u003cem\u003ehsa-miR-132, hsa-miR-134\u003c/em\u003e (postsynaptic), and h\u003cem\u003esa-miR-361\u003c/em\u003e (presynaptic). Data represent the fraction of the total detected miRNA abundance in the combined synaptosome and SNaP nanoparticles datasets\u0026nbsp; n=4-5 per group). Adjusted p-values from Student’s t-test with Holm-Sidak correction: \u003cem\u003ehsa-miR-361\u003c/em\u003e (p\u0026lt;0.000001, t= 16.24), \u003cem\u003ehsa-miR-132\u003c/em\u003e (p= 0.95, t= 0.06, ns), \u003cem\u003ehsa-miR-134\u003c/em\u003e (p= 0.063, t= 2.66, ns), \u003cem\u003ehsa-miR-138\u003c/em\u003e (p\u0026lt;0.000001, t= 14.93).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7775232/v1/9b86bc13791b5e3f9675949e.png"},{"id":95897117,"identity":"be8c1bf0-9dbd-48cf-8f56-7b3333bd8c2f","added_by":"auto","created_at":"2025-11-14 07:24:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":547938,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnhancing host miRNA loading with the SNaP-TRBP system\u003c/strong\u003e. A) Schematic representation of the experimental framework for engineered SNaP production in HEK-293T cells. B) Quantification of p24 levels in the supernatants from producing cells. Data presented as mean ± SEM from n= 5 independent VLP production experiments per group. Two-tailed Mann-Whitney U test (p= 0.0556; U= 3; not significant). C) Representative Transmission Electron Microscopy (TEM) micrographs of chimeric SNaP-TRBP and reference Gag-eGFP particles isolated from HEK-293T supernatants. Right panels show magnified views of the left panel images. Scale bar: 100 nm. D) Comparative analysis of RNA packaging efficiency, calculated as the ratio of nanoparticle-extracted total RNA to p24 protein content in each sample, between eGFP- (control) and TRBP-functionalized nanoparticles. Box plots display median values with whiskers indicating the minimum and maximum across n= 5 VLP productions per group. Two-tailed Mann-Whitney U test (p= 0.0317, U= 2). E) Quantification of relative miRNA abundance, defined as the percentage of small RNAs within the 10–40 nucleotide range (highlighted in panel C, \u003cem\u003eSupplementary Fig. 3\u003c/em\u003e) relative to total small RNA content. The supernatant of mock-transfected cells is used as control. Data shown as box plots with median values and whiskers indicating the minimum and maximum across n= 5 VLP productions per group. Kruskal-Wallis test (p \u0026lt; 0.0001; statistic= 12.57), followed by Dunn’s post-hoc comparisons: Control vs. Gag-eGFP, p= 0.0763; Control vs. SNaP-TRBP, p= 0.0004; Gag-eGFP vs. SNaP-TRBP, p= 0.0763.\u003c/p\u003e\n\u003cp\u003eF) Comparative evaluation of miRNA recovery efficiency in SNaP-TRBP relative to Gag-eGFP VLPs for the top three miRNAs highly expressed in HEK-293T cells. The definition of miRNA recovery efficiency is provided in \u003cem\u003eMaterials and Methods\u003c/em\u003e. Results presented as box plots showing the median fold change with whiskers indicating the minimum and maximum (n = 5/7 VLP productions per group). Two-tailed Mann-Whitney test: \u003cem\u003ehsa-miR-10a\u003c/em\u003ep= 0.0476, U= 6; \u003cem\u003ehsa-miR-30e\u003c/em\u003e p= 0.0476, U= 6; \u003cem\u003ehsa-miR-186\u003c/em\u003e p= 0.0476, U= 6.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7775232/v1/c09ecb56bc776dfb764b40e3.png"},{"id":95897120,"identity":"54af8bae-acab-489d-ac1c-9e89ae862a48","added_by":"auto","created_at":"2025-11-14 07:24:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1127682,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSNaP’s\u003c/strong\u003e \u003cstrong\u003edual functionalization with DLS and TRBP modules enhances nanoparticle recovery of postsynaptic miRNAs.\u003c/strong\u003e A) Schematic representation of single (SNaP-DLS) and dual-engineered (SNaP-TRBP-DLS) VLP production in mouse embryonic stem cell (mESC)-derived neurons. B) Representative confocal microscopy images showing the localization of chimeric SNaP, SNaP-DLS, and SNaP-TRBP-DLS within mature packaging neurons, visualized via p24 staining (green). Postsynaptic compartments marked by Homer 1b/c (red), nuclei counterstained with DAPI (blue). Mock-transduced cells used as control. Scale bar: 50 μM. C) Quantification of p24 and Homer 1b/c colocalization, expressed as the percentage of ROI overlap. Statistical comparisons among SNaP (light gray), SNaP-DLS (dark gray), and SNaP-TRBP-DLS (red) groups were performed using a Kruskal-Wallis test (p= 0.0013, statistic= 13.23), followed by Dunn’s post-hoc analysis: SNaP vs. SNaP-DLS (p= 0.0036), SNaP vs. SNaP-TRBP-DLS (p= 0.0010), SNaP-DLS vs. SNaP-TRBP-DLS (p= 0.4077, not significant). Data presented as box plots showing the median with range (whiskers, n= 10–18 images per group from n= 2 independent experiments). D) Comparative analysis of nanoparticle miRNA recovery efficiency in SNaP-TRBP-DLS relative to SNaP-DLS for the triplet of postsynaptically localized miRNAs, expressed as detailed in \u003cem\u003eMaterials and Methods\u003c/em\u003e. Data adjusted for background miRNA levels in mock-transduced cell media and represented as median fold change with range (whiskers, n= 6–7 VLP productions per group). Two-tailed Mann-Whitney U test: \u003cem\u003emmu-miR-132\u003c/em\u003e (p= 0.0476, U= 6), \u003cem\u003emmu-miR-134\u003c/em\u003e (p= 0.0476, U= 6), \u003cem\u003emmu-miR-138\u003c/em\u003e (p= 0.0012, U= 0).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7775232/v1/3e1dfd08fa409fc725cdb629.png"},{"id":96708554,"identity":"ec3ca92d-d9c8-44f0-a6df-c8fa6ae404c2","added_by":"auto","created_at":"2025-11-25 10:04:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4695794,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7775232/v1/70d762e9-5f58-42d4-b0db-43bcce54969e.pdf"},{"id":95897116,"identity":"a371d82d-e9c6-4f57-a474-0fcf0eb19517","added_by":"auto","created_at":"2025-11-14 07:24:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":855476,"visible":true,"origin":"","legend":"Supplementary Information - Nature publishing group","description":"","filename":"SupplementaryInformationNaturePublishinggroup.docx","url":"https://assets-eu.researchsquare.com/files/rs-7775232/v1/e00f1f49a6cd7a7c812c463f.docx"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nMarianna Mignanelli is currently an employee and stock owner at AstraZeneca UK ltd, UK. Giacomo Siano is currently employed at F. Hoffmann- La Roche AG, Switzerland. The remaining authors have no conflicts of interest to declare.","formattedTitle":"Synthetic nanoparticles for cell-type specific, spatially resolved miRNA loading and export in neural cells","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMicroRNAs (miRNAs) are small, non-coding RNAs that serve as ubiquitous regulators of gene expression, orchestrating fundamental biological processes through post-transcriptional control\u003csup\u003e1\u003c/sup\u003e. In the Central Nervous System (CNS), miRNAs are dynamically regulated during development and exhibit cell-type-specific expression in the adult brain, underscoring their essential role in neuronal identity and function\u003csup\u003e2\u0026ndash;5.\u003c/sup\u003e. Beyond their compartmentalized expression, specific miRNA populations localize within synaptic compartments, where they modulate activity-dependent gene expression of plasticity-related products via translational control\u003csup\u003e6\u0026ndash;10\u0026nbsp;\u003c/sup\u003e. Given their critical role in brain homeostasis, miRNA dysregulation is linked to a wide range of neurological disorders\u003csup\u003e11,12\u003c/sup\u003e. Consequently, miRNAs are emerging as attractive candidates for CNS biomarker discovery, with the potential to surpass protein-based predictors in both sensitivity and specificity for early diagnosis\u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eNevertheless, the implementation of brain miRNAs as CNS biomarkers remains challenging. Current approaches for local transcriptomics - such as those based on synaptosome isolation or microdissected neuropils - suffer from contamination by neighbouring cells or subcellular compartments, hindering accurate assignment of miRNA topology\u003csup\u003e14-16\u003c/sup\u003e. Moreover, bulk miRNA sequencing lacks the sensitivity to detect rare, spatially restricted miRNA species\u003csup\u003e17,18\u003c/sup\u003e. On the other hand, single cell small RNA profiling is \u0026nbsp;still \u0026nbsp;far from being widely and easily applicable to regionalized miRNAs due to their short length and adapter ligation biases\u003csup\u003e19\u003c/sup\u003e. Collectively, these limitations constrain our understanding of localized post-transcriptional regulation in the CNS and highlight the need for alternative strategies offering both enhanced spatial resolution and greater detection sensitivity\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eVirus-like particles (VLPs) derived from the HIV-1 Gag polyprotein offer a promising platform in response to these challenges\u003csup\u003e21\u003c/sup\u003e. Gag self-assembles into VLPs through interactions with specific RNA motifs, a mechanism that naturally facilitates the selective encapsidation of RNAs\u0026mdash;including host miRNAs\u0026mdash;during HIV-1 replication\u003csup\u003e22,23\u003c/sup\u003e. Moreover, Gag exhibits substantial structural flexibility, tolerating genetic fusion with exogenous domains without compromising particle assembly or function\u003csup\u003e24\u003c/sup\u003e. These features have recently enabled the development of modular VLPs with programmable RNA-binding specificity and ancillary features\u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study, we present \u003cstrong\u003eSNaP (Synthetic Nano-Particles for Precise miRNA loading and export)\u003c/strong\u003e, a Gag-based VLP platform designed to enable targeted recovery of miRNAs from complex CNS cell types. The SNaP system integrates modular domains to achieve (i) cell-type-specific miRNA loading, (ii) subcellular compartment targeting, and (iii) enhanced miRNA detection. We further demonstrate the feasibility of applying SNaP in both neuronal and microglial cell types, by equipping the SNaP constructs with cell-specific transcriptional control, highlighting its robustness in challenging cellular and tissue environments.\u003c/p\u003e\n\u003cp\u003eCollectively, this work positions SNaP as a novel and versatile tool for spatially resolved, cell-type specific miRNA profiling in the CNS. Its modular design and compatibility with heterogeneous cell types establish a foundation for high-throughput applications in biomarker discovery and the investigation of compartmentalized RNA regulation in any clinically relevant tissue.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e1. Cell-specific miRNA export\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBrain miRNAs display distinct cell type-specific expression patterns crucial for CNS development and function, yet accurately profiling their signatures in individual brain cells remains challenging\u003csup\u003e26\u003c/sup\u003e. To improve the resolution of miRNA profiling at the cell-type level, we exploited and advanced the inherent capacity of HIV-1 Gag virus-like particles (VLPs) to package host RNAs\u003csup\u003e23\u003c/sup\u003e by incorporating additional functional modules, resulting in the development of Synthetic Nano-Particles for Precise miRNA loading and export (SNaP). The first innovation at the core of this platform is the integration of a cell-specific promoter to drive Gag expression\u003csup\u003e27\u003c/sup\u003e, thereby confining SNaP nanoparticle formation and contextual miRNA export to desired cell populations.\u003c/p\u003e\n\u003cp\u003eTo validate this strategy, we established a simplified model of CNS cellular diversity using \u0026nbsp;co-cultured immortalized hippocampal neurons (HT22) and microglial cells (BV-2). Within this system, we transiently directed SNaP production using either the \u003cem\u003eCaMKII\u003c/em\u003e\u003cem\u003e\u0026alpha;\u003c/em\u003e or the \u003cem\u003eIba1\u003c/em\u003e modules, enabling the selective generation of neuro- or glia- SNaP nanoparticles, respectively\u003csup\u003e28,29\u0026nbsp;\u003c/sup\u003e(\u003cem\u003eFig. 1A\u003c/em\u003e). Immunostaining for the Gag p24 domain confirmed that Gag expression was strictly limited to the intended cell types, showing clear colocalization with the microglial marker CD11b and the neuronal marker HuC/D, respectively (\u003cem\u003eFig. 1B\u003c/em\u003e). Importantly, p24 antigen concentrations reflected robust yields of nanoparticles from both neuronal and microglial sources, supporting their utility for downstream RNA applications (\u003cem\u003eFig. 1C\u0026nbsp;\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eTo further assess the specificity of the SNaP system for cell-specific miRNA characterization, we performed RT-qPCR on the RNA extracted from supernatants, comparing the composition of miRNAs embedded within neuronal and microglial particles. SNaP particles generated by \u003cem\u003eCaMKII\u003c/em\u003e\u003cem\u003e\u0026alpha;\u003c/em\u003e-driven expression preferentially encapsulated \u003cem\u003emmu-miR-127\u003c/em\u003e and \u003cem\u003emmu-miR-433\u003c/em\u003e, which we previously identified as neuronal-enriched (\u003cem\u003eSupplementary Fig. 1A)\u003c/em\u003e. Conversely, \u003cem\u003eIba1\u003c/em\u003e-driven VLPs efficiently packaged microglial-associated miRNAs \u003cem\u003emmu-miR-142\u003c/em\u003e and \u003cem\u003emmu-miR-223\u003c/em\u003e (\u003cem\u003eFig. 1D\u003c/em\u003e, \u003cem\u003eSupplementary Fig. 1A\u003c/em\u003e). Notably, overall miRNA expression levels were comparable between cultures expressing SNaP and mock controls, indicating that the observed selective loading was due to restricted nanoparticle production rather than changes in endogenous miRNA levels (\u003cem\u003eSupplementary Fig. 1B\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eCollectively, these results establish SNaP as a versatile and effective platform for specifically capturing miRNAS into cell-type-specific VLPs and thereby isolate miRNAs from defined cell types within the complex cellular milieu of the brain. By enabling the selective export of miRNAs directly from targeted cell populations in situ, SNaP addresses critical obstacles of cell resolution and tissue accessibility that constrain conventional brain cell-specific transcriptomic approaches.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Synaptic miRNA detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrent miRNA profiling transcriptomic techniques are limited not only in cell-type resolution but also in accurately profiling miRNAs within specialized subcellular compartments, such as neuronal dendrites and axons, where local miRNAs play essential roles in modulating synaptic plasticity\u003csup\u003e14,30\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo address this challenge and building on SNaP\u0026rsquo;s demonstrated effectiveness for \u003cem\u003ein situ\u003c/em\u003e miRNA loading and export in specific cell-types, we designed an additional module to restrict miRNA profiling at the subcellular level, specifically targeting the dendritic region of neurons. To enhance Virus-like particle-mediated miRNA loading within dendrites, we incorporated a 247-nucleotide dendritic localization signal (DLS) from the 3\u0026rsquo; UTR of the \u003cem\u003ePSD95\u003c/em\u003e transcript into the \u003cem\u003eGag\u003c/em\u003e mRNA\u0026rsquo;s 3\u0026rsquo; UTR. This sequence is well-established to be both necessary and sufficient for directing mRNA transport specifically to dendrites\u003csup\u003e31\u003c/sup\u003e thereby increasing the likelihood of VLP assembly in the dendritic/post-synaptic compartment, allowing in principle to enrich the loading of dendritic miRNA while minimising the contamination of miRNAs \u0026nbsp;from presynaptic and somatic regions.\u003c/p\u003e\n\u003cp\u003eTo validate the effectiveness of the dendritic-targeting module, we transduced human iPSC-derived neuronal progenitors with VSV-G-pseudotyped lentiviral vectors encoding either the SNaP-DLS construct or a benchmark SNaP-only variant with no specific RNA localization sequence. Following viral transduction, cells were differentiated into cortical glutamatergic neurons, and supernatants were harvested at 28 days post-differentiation (DIV28) to concentrate the released viral-like nanoparticles (\u003cem\u003eFig. 2A\u003c/em\u003e). Immunofluorescence confirmed that neuronal maturation in SNaP-packaging cultures proceeded comparably to mock-transduced control cells, suggesting minimal disruption of neuronal physiology upon nanoparticle formation and budding (\u003cem\u003eFig. 2B\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eDLS engineering resulted in distinct differences in nanoparticle localization. While cells expressing the untargeted SNaP construct showed diffuse p24 immunoreactivity throughout both soma and neurites, those expressing SNaP-DLS displayed significantly increased p24 signal intensity within neurites compared to cell bodies (\u003cem\u003eFig. 2B\u003c/em\u003e). Correspondingly, incorporation of the DLS module in SNaP led to pronounced colocalization of p24 with the postsynaptic marker Homer 1 b/c, confirming precise dendritic targeting (\u003cem\u003eFig. 2C\u003c/em\u003e). Of note, SNaP particles remained readily detectable in the supernatant up to four weeks of differentiation (\u003cem\u003eFig. 2D\u003c/em\u003e). Moreover, this engineered targeting did not compromise overall miRNA export capacity, as sufficient total RNA levels were recovered for downstream analysis regardless of the spatial restriction of SNaP-DLS (\u003cem\u003eSupplementary Fig. 2A\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eTo assess whether the enhanced SNaP-DLS postsynaptic localization confers functional specificity for dendritic miRNA isolation, we examined the modules\u0026rsquo;s capacity to load three miRNA species with established dendritic and postsynaptic localization: \u003cem\u003ehsa-miR-132, hsa-miR-134\u003c/em\u003e, and \u003cem\u003ehsa-miR-138\u003c/em\u003e\u003csup\u003e33\u003c/sup\u003e. Indeed, according to the engineered design, SNaP-DLS nanoparticles demonstrated superior enrichment for these molecules compared to untargeted SNaP-only controls (\u003cem\u003eFig. 2E\u003c/em\u003e). In contrast, SNaP-DLSfailed to efficiently loading three axonal miRNAs and a non-compartmentalized miRNA, underscoring their specificity for dendritic miRNA species (\u003cem\u003eSupplementary Fig. 2B\u003c/em\u003e). Importantly, lentiviral transduction did not alter overall miRNA expression levels (\u003cem\u003eSupplementary Fig. 2C\u003c/em\u003e), further validating the integrity of our observations.\u003c/p\u003e\n\u003cp\u003eGiven the precise targeting demonstrated by SNaP-DLS, we next benchmarked its performance against state-of-the-art methods. Comparing our qPCR-based profiles to the most comprehensive published dataset of human synaptosomal miRNAs\u003csup\u003e34\u003c/sup\u003e, we found that SNaP-DLS and traditional synaptosomal preparations achieved similar enrichment for \u003cem\u003ehsa-miR-132\u003c/em\u003e and \u003cem\u003ehsa-miR-134 (Fig. 2F, left)\u003c/em\u003e. However, SNaP-DLS exhibited significantly lower recovery of \u003cem\u003ehsa-miR-361\u003c/em\u003e, a known presynaptic miRNA\u003cem\u003e\u0026nbsp;\u003c/em\u003e(mean recovery efficiency: 98.38% vs. 1.61%, \u003cem\u003eFig. 2F, right\u003c/em\u003e). This difference highlights the superior spatial specificity afforded by SNaP-DLS, as opposed to conventional synaptosomal-based methods.\u003c/p\u003e\n\u003cp\u003eCollectively, these results establish SNaP-DLS as a highly specific and effective platform for isolating dendritic miRNAs, significantly reducing the recovery of non-dendritic background compared to conventional synaptosomes. The DLS module thus provides an advanced tool for resolving the intricate landscape of compartmentalized miRNA expression, offering unprecedented precision for investigating neuronal miRNomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Improving the sensitivity for miRNA profiling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnother major challenge in miRNA profiling, especially at the subcellular level, derives from their inherently short length and low abundance. This often limits the detection sensitivity for rare or transiently expressed, localized miRNA populations\u003csup\u003e35\u003c/sup\u003e. To overcome this limitation and enhance miRNA detection while minimizing co-isolation of other host RNA species, we fused the first two double-stranded RNA-binding domains of the Dicer cofactor TRBP (TAR RNA-binding protein) to the C-terminus of Gag. These modules were chosen for their well-established selective, sequence-independent binding to miRNAs and minimal affinity for other RNA classes\u003csup\u003e36,37\u003c/sup\u003e , they could be well suited for selective miRNA enrichment in the SNaP system. Additionally, their limited size ( \u0026nbsp;̴ 20.59 kDa for the two combined domains) was anticipated to minimally contribute to steric hindrance during VLP assembly.\u003c/p\u003e\n\u003cp\u003eTo initially validate the SNaP-TRBP system, we transiently packaged VLP nanoparticles in HEK-293T cells, a widely-used model for recombinant viral particle generation. As \u0026nbsp; a benchmark, we used cells expressing a Gag-eGFP fusion protein, whose structure and assembly are well-documented\u003csup\u003e38\u003c/sup\u003e (\u003cem\u003eFig. 3A).\u0026nbsp;\u003c/em\u003eImmunoblotting for the Gag p24 domain confirmed that both the Gag-eGFP and SNaP-TRBP chimeric proteins were expressed at the expected sizes (~80 kDa and ~75 kDa, respectively), with no evidence of degradation by host proteases (\u003cem\u003eSupplementary Fig. 3A, left\u003c/em\u003e). Both variants yielded high particle titres in the supernatant (\u003cem\u003eFig. 3B\u003c/em\u003e and \u003cem\u003eSupplementary Fig. 3A, right\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eWhile a slight, not significant, reduction in p24 concentration was observed for TRBP-engineered particles over eGFP-expressing ones (\u003cem\u003eFig. 3B\u003c/em\u003e), this event was not attributable to protein-mediated toxicity (\u003cem\u003eSupplementary Fig. 3B\u003c/em\u003e). Furthermore, transmission electron microscopy (TEM) excluded defects in particle assembly associated with TRBP fusion. Indeed, SNaP-TRBP particles retained a round morphology, a lipid membrane, and an electron-dense Gag core which was consistent with the shape and size of reference Gag-eGFP particles (\u003cem\u003eFig. 3C\u003c/em\u003e). Average p24 protein concentrations for both constructs also aligned with established benchmarks for Gag VLP production in HEK-293T cells\u003csup\u003e39\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMost importantly, incorporation of the TRBP module led to a marked increase in RNA loading efficiency by the SNaP platform (\u003cem\u003eFig. 3D\u003c/em\u003e). This enhancement was further supported by RNA electrophoresis, which showed an enrichment of small RNAs (10\u0026ndash;40 nucleotides) in SNaP-TRBP particles compared to Gag-eGFP VLPs, consistent with selective miRNA packaging (\u003cem\u003eFig. 3E\u003c/em\u003e and \u003cem\u003eSupplementary Fig. 3C\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eTo further substantiate this enhanced specificity, we quantified the levels of the three most abundant miRNAs in HEK-293T cells (\u003cem\u003ehsa-miR-10a\u003c/em\u003e, \u003cem\u003ehsa-miR-30e\u003c/em\u003e, and \u003cem\u003ehsa-miR-186\u003csup\u003e40\u003c/sup\u003e\u003c/em\u003e) cargo RNA isolated from SNaP-TRBP versus Gag-eGFP nanoparticles. Remarkably, SNaP-TRBP demonstrated significantly greater recovery of all three miRNAs (\u003cem\u003eFig. 3F\u003c/em\u003e). Again, endogenous levels of these miRNAs remained unchanged across conditions, indicating that VLP production did not disrupt basal miRNA expression (\u003cem\u003eSupplementary Fig. 3D\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eCollectively, these findings demonstrate that TRBP functionalization substantially enhances the sensitivity and specificity of miRNA detection within the SNaP platform, positioning it as a robust, unbiased tool for miRNA profiling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.\u003c/strong\u003e \u003cstrong\u003eSNaP\u003c/strong\u003e \u003cstrong\u003emulti-domain engineering to achieve synergistic effects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings demonstrate that the DLS domain effectively drives SNaP packaging within the postsynaptic dendritic compartment. However, this module does not intrinsically increase miRNA packaging, as this property remains governed by the Gag core\u003csup\u003e23,41\u003c/sup\u003e. Given our finding that TRBP engineering markedly improves miRNA detection in gold-standard cell lines, we therefore investigated whether combining TRBP and DLS modules could synergistically boost SNaP\u0026rsquo;s postsynaptic miRNA recovery.\u003c/p\u003e\n\u003cp\u003eTo address the effect of dual functionalization on SNaP performance, we compared SNaP particles incorporating both TRBP and DLS domains (SNaP-TRBP-DLS) with those containing only the DLS domain (SNaP-DLS), both generated in mature mouse neurons (\u003cem\u003eFig. 4A\u003c/em\u003e). The production level of neuronal, TRBP-equipped \u0026nbsp; chimeric SNAP particles was comparable to that observed in HEK-293T cells, as indicated by p24 levels (neurons mean= 100.6 \u0026plusmn; 46.95 SEM pg/\u0026mu;l, HEK-293T mean= 309 \u0026plusmn; 144 SEM pg/\u0026mu;l, \u003cem\u003eSupplementary Fig. 4A\u003c/em\u003e and \u003cem\u003eFig.3B, respectively\u003c/em\u003e), reinforcing the concept that mammalian neurons are capable of generating VLPs at levels comparable to those seen in established gold-standard cell lines. Importantly, TRBP functionalization resulted in an approximately tenfold increase in total RNA packaging efficiency compared to non-TRBP controls (SNaP-DLS mean= 26.96 \u0026plusmn; 1.24 SEM; SNaP-TRBP-DLS mean= 276.1 \u0026plusmn; 128.9 SEM, \u003cem\u003eSupplementary Fig. 4B\u003c/em\u003e). This enhanced RNA packaging did not compromise dendritic targeting, as indicated by similar levels of colocalization between SNaP particle signal and the postsynaptic marker Homer 1 b/c for both constructs (mean %ROI colocalized= 11.11 \u0026plusmn; 0.97 SEM for SNAP-DLS; 12.22 \u0026plusmn; 1.10 SEM for SNAP-TRBP-DLS, \u003cem\u003eFig.s 4B and 4C\u003c/em\u003e). \u0026nbsp;Both constructs notably showed higher colocalization than conventional Gag VLPs, confirming maintained targeting specificity upon dual functionalization (\u003cem\u003eFig. 4C\u003c/em\u003e). Further analysis on cargo total RNA confirmed that TRBP presence significantly amplified the postsynaptic miRNA collection ability of SNaP-DLS (\u003cem\u003eFig. 4D\u003c/em\u003e), independent of any changes in basal miRNA expression within transduced neurons (\u003cem\u003eSupplementary Fig. 4C\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003eCollectively, these results confirm the synergistic benefits of multi-domain engineering in the SNaP platform. The combination of precise subcellular targeting (via DLS) with enhanced miRNA packaging (via TRBP) simultaneously and significantly improves both the spatial resolution and the sensitivity of miRNA profiling, enabling robust recovery of compartmentalised miRNAs.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study presents SNaP, an original system to advance the unbiased, spatially resolved profiling of localized brain miRNAs. Standing apart from current local transcriptomics methods, SNaP is equipped with three functional modules that can operate either independently or synergistically to (i) accurately ascertain cell-type specific miRNA expression with minimal environmental interference, (ii) attain unparalleled spatial resolution for discriminating localized miRNA pools, and (iii) enhance miRNA detection sensitivity.\u003c/p\u003e\n\u003cp\u003eOur approach is based on the unique ability of retroviral Gag polyproteins to interact with host noncoding RNAs during viral particle assembly\u003csup\u003e22,23\u003c/sup\u003e. Leveraging this property, we selectively expressed Gag in specific brain cell types to enable the encapsulation of cellular miRNAs within engineered Virus-Like Particles (VLPs)\u003csup\u003e42\u003c/sup\u003e. Among retroviruses, the HIV-1 Gag polyprotein was chosen as the foundation of our system due to its well-described ability to bind a broad range of host RNA species, potentially facilitating unbiased miRNA profiling\u003csup\u003e43\u003c/sup\u003e. Importantly, the modular and well-defined structure of Gag VLPs was deliberately selected to ensure uniform RNA content across replicates\u003csup\u003e44\u003c/sup\u003e, thereby upgrading SNaP\u0026rsquo;s reproducibility of cell-free miRNA profiling. This consistency could offer a substantial advantage over Extracellular Vehicles (EVs), as they frequently display variability in both composition and RNA content\u003csup\u003e45\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eSNaP stands out from current local transcriptomics methods for its increased specificity in identifying localized miRNA pools with minimal contamination from surrounding environments\u003csup\u003e14,30\u003c/sup\u003e. The integration of a cell-specific promoter within the Gag cassette effectively confined miRNA packaging to target cell types\u003csup\u003e27\u003c/sup\u003e, even amidst the complexity of a heterogeneous culture system. Such minimal genetic manipulation makes SNaP-CSP broadly accessible for CNS applications where miRNAs play a crucial role in cell type or subtype commitment\u003csup\u003e20\u003c/sup\u003e. Adding a further layer of spatial complexity, SNaP serves as an exceptional system for exploring the intricate dynamics of intracellularly localized miRNAs involved in the regulation of neuroplasticity\u003csup\u003e11\u003c/sup\u003e. Incorporating a G-quadruplex within the DLS module strategically directed Gag localization to dendritic regions, significantly enhancing SNaP\u0026apos;s ability to package postsynaptic miRNA species\u003csup\u003e31\u003c/sup\u003e. By massively reducing presynaptic miRNA incorporation, the DLS engineering approach surpassed the regional specificity offered by traditional synaptosome fractionation\u003csup\u003e34\u003c/sup\u003e. Together, these advancements position SNaP-CSP/DLS as a promising tool for elucidating local miRNA (dys-) regulation of CNS development and homeostasis at unparalleled spatial resolution.\u003c/p\u003e\n\u003cp\u003eThrough the analysis of SNaP-incorporated miRNAs across various mammalian cell models, we confirmed that Gag could effectively incorporate miRNAs without additional modifications, mirroring the RNA export efficiencies reported for HIV-1 infections\u003csup\u003e22\u0026nbsp;\u003c/sup\u003eand other viral systems\u003csup\u003e46\u003c/sup\u003e . Nevertheless, while this inherent binding capacity meets the needs of many applications, exploring low-abundance miRNAs in specific subcellular compartments may require an advanced export potential\u003csup\u003e35,47\u003c/sup\u003e. To this end, we significantly boosted SNaP miRNA binding in a sequence-independent manner using the TRBP module\u003csup\u003e36,37\u003c/sup\u003e. SNaP-TRBP miRNA export was twice as effective as unmodified Gag VLPs in HEK-293T cells, with comparable improvements in neuron models. The integrated functionality of the TRBP and DLS domains further supports TRBP engineering as a promising approach for the large-scale recovery of compartmentalized miRNAs, particularly those located at synaptic sites. By increasing the sensitivity of localized transcriptome profiling, the SNaP-TRBP-DLS system offers the potential to advance our understanding of brain region-specific gene expression, extending even to rare cellular and subcellular miRNA populations\u003csup\u003e17,18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe significant RNA packaging properties of the SNaP modular system support comprehensive genetic payload characterization using Next Generation Sequencing. By introducing a novel, sequence-independent approach to RNA profiling, our study overturns the prevailing focus in retroviral VLP engineering - which has emphasized restricting broad RNA packaging in favour of targeted therapeutic cargos\u003csup\u003e25,48\u003c/sup\u003e. Through bulk miRNA profiling, we anticipate that SNaP will enable the generation of comprehensive datasets detailing patterned miRNA alterations across a range of physiological and pathological conditions, thereby guiding the discovery of more specific and sensitive biomarkers associated with brain disorders\u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAbove all, this study provides the first evidence that engineered Gag VLPs \u0026nbsp;can serve as robust platforms for the non-destructive miRNA profiling \u0026nbsp;of cell-type-specific \u0026nbsp;brain-derived cells. These findings align with earlier reports supporting chimeric nanoparticle packaging in clinically relevant lymphoid cell lines\u003csup\u003e25\u003c/sup\u003e. By facilitating spatially resolved miRNA profiling within intact tissues, not only do our findings demonstrate the scalability of SNaP for \u003cem\u003ein vivo\u003c/em\u003e applications, but they also underscore its potential for the longitudinal evaluation of miRNA dynamics over time. To our knowledge, no other existing technology offers this combined capacity for high-resolution, real-time miRNA analysis in living brain tissues. Nevertheless, while our exploratory assessments offer valuable insights for these applications, we recognize that a more in-depth characterization of the viability and physiological state of packaging cells will be beneficial to fully substantiate future \u003cem\u003ein vivo\u003c/em\u003e implementations.\u003c/p\u003e\n\u003cp\u003eIn summary, this study explores the modular capabilities of the chimeric SNaP platform, showcasing how its components can be synergistically combined to ultimately enhance local miRNA recovery and analysis. Additionally, it provides critical insights into optimizing retroviral particle packaging in clinically relevant cell types, with successful applications in both neuronal and glial cell models. Our research positions SNaP as an innovative tool for the cell-type specific profiling of non-coding small RNA in the cellular heterogeneous nervous tissue, offering portability to high-throughput and \u003cem\u003ein vivo\u003c/em\u003e miRNA profiling applications. While our design primarily focuses on the CNS, the inherent flexibility of the SNaP approach opens avenues for future characterization of virtually any mammalian tissue exhibiting considerable cellular heterogeneity and/or polarization.\u003c/p\u003e"},{"header":"Online Methods","content":"\u003cp\u003e\u003cstrong\u003e1. Cell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman embryonic kidney HEK-293T cells (ATCC CRL-3216), immortalized HT22 hippocampal neurons, and immortalized BV-2 microglia were cultured routinely in Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium (DMEM) with low glucose (EuroClone). The medium was supplemented with 10% heat-inactivated fetal bovine serum (FBS, EuroClone), 100 U/mL penicillin, and 100 \u0026micro;g/mL streptomycin (Sigma Aldrich, Milan, Italy). All cell lines were maintained under standard conditions at 37 \u0026deg;C with 5% CO2.\u003c/p\u003e\n\u003cp\u003eHuman integrated, inducible, and isogenic (i\u003csup\u003e3\u003c/sup\u003e) iPSCs (as described by Wang et al., 2017\u003csup\u003e49\u003c/sup\u003e) were generously provided by Dr. Michael Ward from NINDS/NIH. Cell handling and differentiation followed the protocol outlined by Fernandopulle et al., 2018\u003csup\u003e50\u003c/sup\u003e (detailed procedure outlined in \u003cem\u003eSupplementary Information\u003c/em\u003e). Culturing was performed until mature polarity was observed (4 weeks \u003cem\u003ein vitro\u003c/em\u003e, as previously described by Wang et al., 2017\u003csup\u003e\u0026nbsp; 49\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eMouse embryonic stem cells (mESCs), line E14Tg2A, handling and differentiation were performed according to the methods described by Bertacchi et al., 2013 \u003csup\u003e51\u003c/sup\u003e, and Lupo et al., 2014\u003csup\u003e52\u003c/sup\u003e (refer to \u003cem\u003eSupplementary Information\u003c/em\u003e for complete description). Cells were cultured until they reached full maturation,as described in Bertacchi et al, 2013\u003csup\u003e51\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eMolecular cloning\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChimeric Gag proteins were cloned from an initial donor vector expressing the Rev-independent, codon-optimized HIV-1 Gag coding sequence, fused in-frame with eGFP, and under the regulation of the CMV promoter (pGag-eGFP, courtesy of the NIH AIDS Reagent Program, cat ARP11468). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSNaP-CSP constructs have been generated as follows: the Gag insert from the pGag-eGFP plasmid, digested with BssHII and BamHI, was partially overlapped with the pAAV-CamKII vector (Addgene, cat. 64545), linearized with EcorV and BamHI, or the pAAV-mIba1 backbone (Addgene cat. 190163), digested with AgeI and NotI.\u003c/p\u003e\n\u003cp\u003eTo generate Gag-TRBP constructs the two double-strand RNA-binding domains (dsRBD1 and dsRBD2) from TRBP have been amplified by PCR out of the pcDNA-TRBP template (Addgene, cat. 15666) using the following primers to facilitate the insertion of an N-terminal, \u0026nbsp;hydrophilic, 33 bp flexible linker (sequence: NRNGDPPVATM, GRAVY hydrophobicity score: -1.04) along with \u0026nbsp;BamHI and NotI restriction sites to facilitate cloning: forward primer: 5\u0026rsquo;AAAACAGAAACGGGGATCCACCGGTCGCCACCATGGCGAT-3\u0026rsquo;; reverse primer: 5\u0026rsquo;-TCTAGAGCGGCCGCTTACAGCATTT-3\u0026rsquo;. The resulting Linker-TRBP insert was subcloned downstream of the Gag sequence of the pGag-eGFP construct using BamHI and NotI restriction digestion.\u003c/p\u003e\n\u003cp\u003eTo express chimeric Gag proteins in i\u003csup\u003e3\u003c/sup\u003e neurons and mouse embryonic stem cell (mESC)-derived neurons, the BssHII and NotI-digested Gag insert from pGag-eGFP was subcloned into the pBOB-EF-1-FastFUCCI-Puro vector (Addgene, cat.86849) upon removal of the FUCCI cassette via the same enzyme set (final construct: pBOB-EF-1\u0026alpha;-Gag). To generate the pBOB-EF-1\u0026alpha;-Gag-DLS construct, a 247 bp sequence corresponding to the dendritic localisation signal (DLS) was amplified from the \u003cem\u003ePsd95\u003c/em\u003e transcript, as described by Subramanian et al, 2011. This sequence was contained in a pCDNA3.1 vector (courtesy of the Laboratorio di Biologia Bio@SNS at Scuola Normale Superiore). PCR primers with BamHIand NotIrestriction sites were used for amplification (forward primer: 5\u0026rsquo;-ATAGGATCCTTAATGGCTTTTTTTTTTTCT-3\u0026rsquo;; reverse primer: 5\u0026rsquo;-ATAGCGGCCGCGTCTGTCTCTT-3\u0026rsquo;). These sites facilitated restriction-mediated cloning of the DLS sequence downstream the STOP codon in pBOB-EF-1\u0026alpha;-Gag. For the pBOB-EF-1\u0026alpha;-Gag-TRBP-DLS construct, we added the TRBP sequence to the pBOB-EF-1\u0026alpha;-Gag-DLS vector linearized with NotI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eSNaP production\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHT22/BV-2 co-cultures.\u0026nbsp;\u003c/em\u003eBoth cell lines were pre-treated with the neutral sphingomyelinase inhibitor GW4869 (Sigma Aldrich, cat. 6823-69-4) at a concentration of 10 \u0026micro;M for 2 hours to partially inhibit extracellular vesicle (EV) secretion. GW4869-conditioned cells were then co-cultured in a HTT/BV-2 ratio of 110.000/60.000 cells and maintained in standard culture conditions as described above. The next day, co-cultures were transfected using Lipofectamine 2000 (ThermoFisher Scientific) or Glial-Mag (OZ Biosciences) for the transient expression of pAAV-CaMKII-Gag or pAAV-mIba1-Gag, respectively. A total of 4 \u0026micro;g of pAAV-CaMKII-Gag and 3 \u0026micro;g of pAAV-mIba1-Gag per well were used, following the respective manufacturers\u0026rsquo; protocols. Mock-transfected cells were used as control. The culture medium was collected at 48- and 72-hours post-transfection, centrifuged at 1,200 rpm for 5 minutes, and filtered through a 0.45 \u0026micro;m PES filter to remove cellular debris. SNaP particles were concentrated approximately 500-fold by ultracentrifugation on a 20% (w/v) sucrose cushion inPBS.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ei\u003csup\u003e3\u003c/sup\u003e Neurons and mESC-derived neurons\u003c/em\u003e: doxycycline-induced i\u003csup\u003e3\u003c/sup\u003e neural progenitors were seeded onto Geltrex-coated 10 cm culture dishes at a density of 10 million cells per plate. During plating, cells were transduced with VSV-G-pseudotyped lentiviral vectors expressing pBOB-EF1\u0026alpha;-Gag, pBOB-EF1\u0026alpha;-Gag-DLS, or empty pBOB-Ef1\u0026alpha; constructs (details on neural progenitor transduction in \u003cem\u003eSupplementary Information\u003c/em\u003e). The medium was fully replaced the following day, and neurons were maintained for four weeks in culture. mESC-derived neural progenitors were seeded at a density of 125,000 cells/cm\u0026sup2; on poly-ornithine and laminin-coated wells at DIV7. They were then transduced with pBOB-EF1\u0026alpha;-Gag-DLS, pBOB-EF1\u0026alpha;-Gag-TRBP-DLS, or control pBOB-EF1\u0026alpha; lentiviral vectors as described in \u003cem\u003eSupplementary Information\u003c/em\u003e. Mock-transduced cells were used as control. Following lentiviral incubation, the culture medium was replaced with Neurobasal A, and neurons were cultured until full maturation, with daily medium replacement. SNaP particles from both i\u003csup\u003e3\u003c/sup\u003e and mESC-derived neurons were harvested from the media of mature cells and purified as described above.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHEK-293T cells\u003c/em\u003e: Cells were seeded onto 10 cm culture dishes at a density of 5 million cells and co-transfected the next day using PEI. Transfections were performed using 25 \u0026micro;g of either pGag-eGFP or pGag-TRBP (control: Gag-free vector) and 5 \u0026micro;g of VSV-G plasmid, maintaining a 5:1 ratio. PEI/DNA complexes were formed in serum-free DMEM Low-Glucose, and were incubated for 10 minutes at room temperature before being added to the cells. Mock-transfected cells were used as control. Cells were then maintained overnight in Opti-MEM (Gibco) medium. From the following day, the culture medium was supplemented with the GW4869 EV-inhibitor (final concentration 10 \u0026micro;M). SNaP VLPs were then purified from culture medium collected at 48 and 72 hours post-transfection as described above.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eTitration of SNaP particles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe physical titer of SNaP particles was determined using a commercial enzyme-linked immunosorbent assay (ELISA) specific for the detection of the HIV p24 core antigen in cell culture supernatants (Innotest HIV antigen mAb assay; Fujirebio, cat. 81512), according to the manufacturer\u0026rsquo;s instructions. Absorbance was measured at 450 nm for p24 quantification, and the antigen concentration was determined by generating a standard curve from the control and performing a linear regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eSNaP Cargo RNA extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 300 \u0026mu;L aliquot of concentrated SNaP particle suspension was treated with RNase A (2 \u0026mu;g/\u0026mu;L) for 15 minutes at 37\u0026deg;C to degrade any extra-vesicular RNA. Total RNA was then isolated from both SNaP particles and producer cells using the miRNeasy Micro Kit (Qiagen, cat. 217084). While the standard protocol was applied for cell pellet samples, modifications were implemented for viral particle preparations. Specifically, after a 5-minute incubation in Qiazol lysis reagent (Qiagen), 10 mg/mL glycogen was added to the solubilized SNaP samples to enhance miRNA recovery. Phase separation was performed by adding 200 \u0026mu;L of chloroform, followed by RNA purification according to the manufacturer\u0026rsquo;s instructions. RNA purity was assessed via UV spectrophotometry. For cellular RNA, ribosomal RNA integrity was evaluated by confirming the 28S:18S rRNA ratio of 2:1, while RNA integrity from SNaP particles was assessed by automated electrophoresis as described in the Supplementary Information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eQuantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and determination of SNaP miRNA packaging efficiency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor cDNA synthesis, 1 \u0026mu;g of cellular RNA or 100 ng of VLP RNA was reverse transcribed using the miR-X miRNA First-Strand Synthesis Kit (Takara, cat. 638315), according to the manufacturer\u0026rsquo;s protocol. RT-qPCR was performed on 5 \u0026mu;L of cDNA (diluted 1:100) in a total reaction volume of 20 \u0026mu;L using SSO Advanced Universal SYBR Green Supermix (BioRad, cat. 1725271). Forward primers were specific to the mature miRNA sequences, while the universal reverse primer provided with the kit targeted the poly(T) adapter sequence incorporated during cDNA synthesis. A comprehensive list of primers employed is available in \u003cem\u003eSupplementary Information, Table 2\u003c/em\u003e.\u0026nbsp;PCR amplification was conducted on a Rotor-Gene Q cycler (Qiagen) with the following thermal cycling conditions: initial denaturation at 95\u0026deg;C for 2 minutes, followed by 35 cycles of 95\u0026deg;C for 30 seconds, 55\u0026deg;C for 30 seconds, and 72\u0026deg;C for 30 seconds. Primer specificity was verified by performing melting curve analysis from 65\u0026deg;C to 95\u0026deg;C, increasing in 0.5\u0026deg;C increments per second.\u003c/p\u003e\n\u003cp\u003eRelative quantification of miRNA expression in packaging cells was calculated using the standard \u0026Delta;\u0026Delta;Ct method\u003csup\u003e53\u003c/sup\u003e, with U6 small nuclear RNA serving as the reference gene for normalization. For SNaP particle samples, as a suitable reference gene was unavailable, miRNA expression was determined via the \u0026Delta;Ct method, ensuring that equal amounts of input total RNA were used for all samples, in line with recommendations by Livak and Schmittgen\u003csup\u003e54\u003c/sup\u003e. \u0026nbsp;\u0026Delta;Cts were determined as the difference between the C\u003csub\u003eT\u003c/sub\u003e values of SNaP particles and those obtained from the supernatant of matching mock-transfected/transduced cultures. To quantify the extent of miRNA encapsidation attributable to SNaP engineering, the so-obtained expression levels from chimeric particles were normalized to those from the corresponding benchmark samples. This ratio produced fold enrichment values, which we defined as \u0026ldquo;miRNA recovery efficiency\u0026rdquo;. The components of each comparative analysis are specified in the respective figures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eImmunofluorescence and colocalization analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHT22 and BV-2 co-cultures were established by seeding 70,000 HT22 cells and 35,000 BV-2 cells per well in 8-well chamber slides (Nunc Lab-Tek, Thermo Fisher Scientific). The following day, transfection was performed with 250 ng of pCamkII\u0026alpha;-Gag plasmid for HT22 cells or 100 ng of pIba1-Gag plasmid for BV-2 cells, using \u003cem\u003eLipofectamine 2000\u003c/em\u003e (Thermo Fisher Scientific) for neuronal cells and GlialMag Transfection Reagent (OZ Biosciences) for microglia, in accordance with manufacturer protocols. After 24 hours, the medium was replaced, and cultures were maintained for an additional 48 hours.\u0026nbsp;Doxycycline-induced i\u003csup\u003e3\u003c/sup\u003e progenitors and DIV7 mESC-derived neuronal progenitors were seeded onto glass coverslips coated with Geltrex or polyornithine, respectively, at a density of 100,000 cells/cm\u0026sup2;. Lentiviral transduction with pBOB-Gag or pBOB-Gag-DLS vectors was carried out as described in \u003cem\u003eSupplementary Information\u003c/em\u003e. Following transduction, the medium was refreshed after 24 hours, and cells were cultured under standard differentiation conditions until full maturation.\u003c/p\u003e\n\u003cp\u003eHT22/ BV-2 co-cultures and i\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eneurons were fixed in 4% paraformaldehyde (PFA), rinsed in PBS, and permeabilized with 0.1% Triton X-100 for 5 minutes at room temperature. After additional PBS washes, nonspecific binding was blocked by incubation in 1% (w/v) BSA for 30 minutes. mESC-derived neurons were fixed in 2% PFA, blocked for 1 hour in PBS supplemented with 3% (w/v) BSA and \u0026nbsp;3% (v/v) FBS, and permeabilized in 0.5% (w/v) Triton X-100 in PBS. All samples were then incubated overnight at 4\u0026deg;C in a humidified chamber with primary antibodies diluted in blocking buffer (antibody list available in \u003cem\u003eSupplementary Table 1\u003c/em\u003e). The following day, after washing in PBS, Alexa Fluor\u0026ndash;conjugated secondary antibodies (\u003cem\u003eSupplementary Information, Table 1\u003c/em\u003e) were applied for 2 hours at room temperature. Nuclear counterstaining was performed using DAPI (1:100,000) for 10 minutes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOptical sections (512 x 512 pixels) were acquired using a Leica STELLARIS 5 confocal microscope. For whole-cell reconstruction, an average of 10 image stacks was loadingd with slices spaced 0.5 \u0026mu;m apart. Images were deconvolved for analysis using Fiji software (NIH, Bethesda). Colocalization between green Alexa 488 and far-red Alexa 633 signals [2] (corresponding to eGFP/p24 and Homer 1b/c, respectively) was quantified using the \u0026quot;coloc\u0026quot; tool in Imaris 7.2.3 software (Oxford Instruments), following the approach by Costes et al.\u003csup\u003e55\u003c/sup\u003e. To counteract the diffuse staining pattern of Homer 1b/c, coupled with the high density of plated cells, a region of interest (ROI) was defined that included only a single p24-positive neuron per imaged field. Using the ROI as a mask to exclude non-p24-expressing cells from the analysis, the percentage of colocalization was defined as the proportion of Gag-signal voxels overlapping with Homer 1b/c voxels within this selected region. Selected images had consistent ROI size and dimensions across all experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8.\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses and graphical representations were performed using Prism 8.0.2 (GraphPad Software Inc., CA, USA). To compare multiple groups, non-parametric Kruskal-Wallis tests followed by Dunn\u0026rsquo;s multiple comparisons post-hoc test were used. For comparisons between two groups, either Student\u0026rsquo;s t-test, Mann-Whitney U test, or Mood\u0026rsquo;s median test was applied, depending on the experimental design, as specified in the Fig. legends. A two-sided p-value below 0.05 was deemed statistically significant, with significance levels represented as * for p \u0026lt; 0.05, ** for p \u0026lt; 0.01, *** for p \u0026lt; 0.001, **** for p \u0026lt; 0.0001, and \u0026quot;n.s.\u0026quot; for non-significant results. Exact p-values and further details regarding data presentation are provided in the respective Fig. legends.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe microarray dataset of synaptosomal miRNAs analyzed in this work is openly available at https://www.synapse.org/#!Synapse:syn26642975/files/, Synapse ID: syn26642975. All other data generated throughout this study are included in the manuscript and/or Supplementary Information.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge M. Calvello, S. Lisi, V. Liverani, A. Viegi, M. Sanguanini (Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Pisa) for their valuable technical assistance; L. Poliseno (Institute of Clinical Physiology, National Research Council of Pisa) for access to equipment. We are also grateful to Dr. M. Ward (NINDS, NIH) for providing human i\u003csup\u003e3\u003c/sup\u003e induced pluripotent stem cells (iPSCs), and the NIH AIDS reagent program for providing the mouse anti-HIV-1 p24 Monoclonal Antibody and the pGag-eGFP construct.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by: EU funding within the Next-Generation EU-MUR PNRR TUSCANY HEALTH Ecosystem (THE) (project no. ECS_00000017) spoke 8 to AC. and CDP; Scuola Normale institutional funds to AC,;\u0026nbsp;PRIN2022 to AC. M.C.C. and R.W.-M. are supported by the Wellcome Trust (grant ref. 223202/Z/21/Z).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Via G.Moruzzi 1, Pisa, 56126 Italy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMarianna Mignanelli \u003csup\u003e#\u003c/sup\u003e, Giacomo Siano \u003csup\u003e*\u003c/sup\u003e, Arianna Scarlatti, Greta Ghiloni, Federico Cremisi, Ludovico Maggi, Antonino Cattaneo\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e#\u003c/sup\u003e Current address: BioPharmaceuticals R\u0026amp;D, AstraZeneca UK ltd, Cambridge Biomedical Campus, 1 Francis Crick Avenue, Cambridge CB2 0AA, UK\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e Current address: Department of neural signalling, F. Hoffmann- La Roche AG, Grenzacherstrasse 124, Basel, 4070, Switzerland\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitute of Neuroscience, Italian National Research Council (CNR), Via G.Moruzzi 1, Pisa, 56126, Italy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiacomo Siano\u003csup\u003e*\u003c/sup\u003e, Vincenzo Iannone, Cristina Di Primio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitute of Life Sciences, School of Advanced Studies Sant\u0026rsquo;Anna, Via G.Moruzzi 1, Pisa, 56126, Italy.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmanuele Orsini\u0026nbsp;\u003cstrong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003eCurrent address: Centre for Genetic Engineering and Biotechnology (ICGEB), Padriciano 99 \u0026nbsp;Trieste, 34149, Italy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitute of Clinical Physiology, Italian National Research Council (CNR), Via G.Moruzzi 1, Pisa, 56126, Italy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMilena Rizzo\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOxford Parkinson\u0026apos;s Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Road, Oxford OX1 3PT, United Kingdom\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMaria Claudia Caiazza, Richard Wade-Martins\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKavli Institute for Neuroscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Park Road, Oxford OX1 3QU, United Kingdom\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMaria Claudia Caiazza, Richard Wade-Martins\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Clinical and Experimental Medicine, University of Pisa, Via Savi 10, 56126 Pisa, Italy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlessandra Salvetti\u003c/p\u003e\n\u003cp\u003eContributions\u003c/p\u003e\n\u003cp\u003eAC and CDP conceived the initial idea, C.D.P. conceived the project. C.D.P., M.M., G.S., M.R., M.C.C., contributed to the experimental design. M.M., V.I, A.S, E.O., L.M., G.G. conducted experiments. C.D.P. supervised the study. M.C.C. and R.W.M. supervised the human neuron work. A.C., F.C. and R.W.M. obtained research funding and contributed to critical supervision and project leadership. M.M. wrote, and AC and CDP revised the manuscript. All authors commented and approved the final version.\u003c/p\u003e\n\u003cp\u003eCorresponding Authors\u003c/p\u003e\n\u003cp\u003eAntonino Cattaneo ([email protected]), or Cristina Di Primio ([email protected]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConflicts of interest\u003c/p\u003e\n\u003cp\u003eMarianna Mignanelli is currently an employee and stock owner at AstraZeneca UK ltd, UK. Giacomo Siano is currently employed at F. Hoffmann- La Roche AG, Switzerland. The remaining authors have no conflicts of interest to declare.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHe, L. \u0026amp; Hannon, G. J. MicroRNAs: Small RNAs with a big role in gene regulation. Nature Reviews Genetics vol. 5 522\u0026ndash;531 (2004).\u003c/li\u003e\n\u003cli\u003eJovicic, A. et al. Comprehensive expression analyses of neural cell-type-specific miRNAs identify new determinants of the specification and maintenance of neuronal phenotypes. Ann Intern Med 158, 5127\u0026ndash;5137 (2013).\u003c/li\u003e\n\u003cli\u003eKawase-Koga, Y. et al. RNAase-III enzyme Dicer maintains signaling pathways for differentiation and survival in mouse cortical neural stem cells. J Cell Sci 123, 586\u0026ndash;594 (2010).\u003c/li\u003e\n\u003cli\u003eSempere, L. F. et al. Expression Profiling of Mammalian MicroRNAs Uncovers a Subset of Brain-Expressed MicroRNAs with Possible Roles in Murine and Human Neuronal Differentiation. Genome Biol. 5 (2004).\u003c/li\u003e\n\u003cli\u003eSchratt, G. M. et al. A brain-specific microRNA regulates dendritic spine development. Nature 439, 283\u0026ndash;289 (2006).\u003c/li\u003e\n\u003cli\u003eHu, Z. \u0026amp; Li, Z. miRNAs in synapse development and synaptic plasticity. Current Opinion in Neurobiology vol. 45 24\u0026ndash;31 (2017).\u003c/li\u003e\n\u003cli\u003eF\u0026eacute;nelon, K. et al. Deficiency of Dgcr8, a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex. Proc Natl Acad Sci U S A 108, 4447\u0026ndash;4452 (2011).\u003c/li\u003e\n\u003cli\u003eAksoy-Aksel, A., Zampa, F. \u0026amp; Schratt, G. MicroRNAs and synaptic plasticity-a mutual relationship. Philosophical Transactions of the Royal Society B: Biological Sciences vol. 369 (2014).\u003c/li\u003e\n\u003cli\u003eAshraf, S. I., McLoon, A. L., Sclarsic, S. M. \u0026amp; Kunes, S. Synaptic protein synthesis associated with memory is regulated by the RISC pathway in Drosophila. Cell 124, 191\u0026ndash;205 (2006).\u003c/li\u003e\n\u003cli\u003eBanerjee, S., Neveu, P. \u0026amp; Kosik, K. S. A Coordinated Local Translational Control Point at the Synapse Involving Relief from Silencing and MOV10 Degradation. Neuron 64, 871\u0026ndash;884 (2009).\u003c/li\u003e\n\u003cli\u003eBrennan, G. P. \u0026amp; Henshall, D. C. MicroRNAs as regulators of brain function and targets for treatment of epilepsy. Nature Reviews Neurology vol. 16 506\u0026ndash;519 (2020).\u003c/li\u003e\n\u003cli\u003eHoss, A. G., Labadorf, A., Beach, T. G., Latourelle, J. C. \u0026amp; Myers, R. H. microRNA profiles in Parkinson\u0026rsquo;s disease prefrontal cortex. Front Aging Neurosci 8, (2016).\u003c/li\u003e\n\u003cli\u003eCondrat, C. E. et al. miRNAs as Biomarkers in Disease: Latest Findings Regarding Their Role in Diagnosis and Prognosis. Cells vol. 9 (2020).\u003c/li\u003e\n\u003cli\u003ePerez, J. D. \u0026amp; Schuman, E. M. Subcellular RNA-seq for the Analysis of the Dendritic and Somatic Transcriptomes of Single Neurons. Bio Protoc 12, (2022).\u003c/li\u003e\n\u003cli\u003eTrebesova, H. \u0026amp; Grilli, M. Synaptosomes: A Functional Tool for Studying Neuroinflammation. Encyclopedia 3, 406\u0026ndash;418 (2023).\u003c/li\u003e\n\u003cli\u003eCajigas, I. J. et al. The Local Transcriptome in the Synaptic Neuropil Revealed by Deep Sequencing and High-Resolution Imaging. Neuron vol.74 453-466 (2012).\u003c/li\u003e\n\u003cli\u003eH\u0026uuml;cker, S. M. et al. Single-cell microRNA sequencing method comparison and application to cell lines and circulating lung tumor cells. Nat Commun 12, (2021).\u003c/li\u003e\n\u003cli\u003ePiwecka, M., Rajewsky, N. \u0026amp; Rybak-Wolf, A. Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease. Nature Reviews Neurology vol. 19 346\u0026ndash;362 (2023).\u003c/li\u003e\n\u003cli\u003eMaji, R. K., Leisegang, M. S., Boon, R. A. \u0026amp; Schulz, M. H. Revealing microRNA regulation in single cells. Trends in Genetics vol. 41 522\u0026ndash;536 (2025).\u003c/li\u003e\n\u003cli\u003eZolboot, N., Du, J. X., Zampa, F. \u0026amp; Lippi, G. MicroRNAs Instruct and Maintain Cell Type Diversity in the Nervous System. Frontiers in Molecular Neuroscience vol. 14 (2021).\u003c/li\u003e\n\u003cli\u003eMartins, S. A. et al. How promising are HIV-1-based virus-like particles for medical applications. Frontiers in Cellular and Infection Microbiology vol. 12 (2022).\u003c/li\u003e\n\u003cli\u003eBogerd, H. P., Kennedy, E. M., Whisnant, A. W. \u0026amp; Cullen, B. R. Induced packaging of cellular micrornas into HIV-1 virions can inhibit infectivity. mBio 8, (2017).\u003c/li\u003e\n\u003cli\u003eCimarelli, A., Sandin, S., Ho\u0026uml;glund, S., Ho\u0026uml;glund, H. \u0026amp; Luban, J. Basic Residues in Human Immunodeficiency Virus Type 1 Nucleocapsid Promote Virion Assembly via Interaction with RNA. J Virol vol.74 (2000).\u003c/li\u003e\n\u003cli\u003eCervera, L. et al. Production of HIV-1-based virus-like particles for vaccination: achievements and limits. Appl Microbiol Biotechnol 103, 7367\u0026ndash;7384 (2019).\u003c/li\u003e\n\u003cli\u003eHorns, F. et al. Engineering RNA export for measurement and manipulation of living cells. Cell 186, 3642-3658.e32 (2023).\u003c/li\u003e\n\u003cli\u003eMcKenzie, A. T. et al. Brain Cell Type Specific Gene Expression and Co-expression Network Architectures. Sci Rep 8, (2018).\u003c/li\u003e\n\u003cli\u003eBoulaire, J., Balani, P. \u0026amp; Wang, S. Transcriptional targeting to brain cells: Engineering cell type-specific promoter containing cassettes for enhanced transgene expression. Advanced Drug Delivery Reviews vol. 61 589\u0026ndash;602 (2009).\u003c/li\u003e\n\u003cli\u003eOhsawa, K., Imai, Y., Sasaki, Y. \u0026amp; Kohsaka, S. Microglia/macrophage-specific protein Iba1 binds to fimbrin and enhances its actin-bundling activity. J Neurochem 88, 844\u0026ndash;856 (2004).\u003c/li\u003e\n\u003cli\u003eYasuda, R., Hayashi, Y. \u0026amp; Hell, J. W. CaMKII: a central molecular organizer of synaptic plasticity, learning and memory. Nature Reviews Neuroscience vol. 23 666\u0026ndash;682 (2022).\u003c/li\u003e\n\u003cli\u003eHafner, A. S., Donlin-Asp, P. G., Leitch, B., Herzog, E. \u0026amp; Schuman, E. M. Local protein synthesis is a ubiquitous feature of neuronal pre- And postsynaptic compartments. Science (1979) 364, (2019).\u003c/li\u003e\n\u003cli\u003eSubramanian, M. et al. G-quadruplex RNA structure as a signal for neurite mRNA targeting. EMBO Rep 12, 697\u0026ndash;704 (2011).\u003c/li\u003e\n\u003cli\u003ePuhl, D. L., D\u0026rsquo;Amato, A. R. \u0026amp; Gilbert, R. J. Challenges of gene delivery to the central nervous system and the growing use of biomaterial vectors. Brain Research Bulletin vol. 150 216\u0026ndash;230 (2019).\u003c/li\u003e\n\u003cli\u003eBicker, S., Lackinger, M., Wei\u0026szlig;, K. \u0026amp; Schratt, G. MicroRNA-132, -134, and -138: a microRNA troika rules in neuronal dendrites. Cellular and molecular life sciences : CMLS vol. 71 3987\u0026ndash;4005 (2014).\u003c/li\u003e\n\u003cli\u003eKumar, S. et al. Synaptosome microRNAs regulate synapse functions in Alzheimer\u0026rsquo;s disease. NPJ Genom Med 7, (2022).\u003c/li\u003e\n\u003cli\u003eKoshiol, J., Wang, E., Zhao, Y., Marincola, F. \u0026amp; Landi, M. T. Strengths and limitations of laboratory procedures for microRNA detection. Cancer Epidemiology Biomarkers and Prevention vol. 19 907\u0026ndash;911 (2010).\u003c/li\u003e\n\u003cli\u003eBenoit, M. P. M. H. et al. The RNA-binding region of human TRBP interacts with microRNA precursors through two independent domains. Nucleic Acids Res 41, 4241\u0026ndash;4252 (2013).\u003c/li\u003e\n\u003cli\u003eFareh, M. et al. TRBP ensures efficient Dicer processing of precursor microRNA in RNA-crowded environments. Nat Commun 7, 1\u0026ndash;11 (2016).\u003c/li\u003e\n\u003cli\u003eGuti\u0026eacute;rrez-Granados, S., Cervera, L., G\u0026ograve;dia, F. \u0026amp; Segura, M. M. Characterization and quantitation of fluorescent Gag virus-like particles. BMC Proc 7, (2013).\u003c/li\u003e\n\u003cli\u003eCervera, L. et al. Generation of HIV-1 Gag VLPs by transient transfection of HEK 293 suspension cell cultures using an optimized animal-derived component free medium. J Biotechnol 166, 152\u0026ndash;165 (2013).\u003c/li\u003e\n\u003cli\u003ePanwar, B., Omenn, G. S. \u0026amp; Guan, Y. MiRmine: A database of human miRNA expression profiles. Bioinformatics 33, 1554\u0026ndash;1560 (2017).\u003c/li\u003e\n\u003cli\u003eGanser-Pornillos, B. K., Yeager, M. \u0026amp; Sundquist, W. I. The structural biology of HIV assembly. Current Opinion in Structural Biology vol. 18 203\u0026ndash;217 (2008).\u003c/li\u003e\n\u003cli\u003eLiu, Y. et al. HIV-1 Sequence Necessary and Sufficient to Package Non-viral RNAs into HIV-1 Particles. J Mol Biol 429, 2542\u0026ndash;2555 (2017).\u003c/li\u003e\n\u003cli\u003eChen, A. K. et al. MicroRNA binding to the HIV-1 Gag protein inhibits Gag assembly and virus production. Proc Natl Acad Sci U S A 111, (2014).\u003c/li\u003e\n\u003cli\u003ede Marco, A. et al. Conserved and Variable Features of Gag Structure and Arrangement in Immature Retrovirus Particles. J Virol 84, 11729\u0026ndash;11736 (2010).\u003c/li\u003e\n\u003cli\u003eVeziroglu, E. M. \u0026amp; Mias, G. I. Characterizing Extracellular Vesicles and Their Diverse RNA Contents. Frontiers in Genetics vol. 11 (2020).\u003c/li\u003e\n\u003cli\u003ePrel, A. et al. Highly efficient in vitro and in vivo delivery of functional RNAs using new versatile MS2-chimeric retrovirus-like particles. Mol Ther Methods Clin Dev 2, 15039 (2015).\u003c/li\u003e\n\u003cli\u003eBenesova, S., Kubista, M. \u0026amp; Valihrach, L. Small rna-sequencing: Approaches and considerations for miRNA analysis. Diagnostics vol. 11 (2021).\u003c/li\u003e\n\u003cli\u003eSegel, M. et al. Mammalian Retrovirus-like Protein PEG10 Packages Its Own mRNA and Can Be Pseudotyped for mRNA Delivery. Science Vol.373, 882-889\u003c/li\u003e\n\u003cli\u003eWang, C. et al. Scalable Production of iPSC-Derived Human Neurons to Identify Tau-Lowering Compounds by High-Content Screening. Stem Cell Reports 9, 1221\u0026ndash;1233 (2017).\u003c/li\u003e\n\u003cli\u003eFernandopulle, M. S. et al. Transcription Factor\u0026ndash;Mediated Differentiation of Human iPSCs into Neurons. Curr Protoc Cell Biol 79, (2018).\u003c/li\u003e\n\u003cli\u003eBertacchi, M. et al. The positional identity of mouse ES cell-generated neurons is affected by BMP signaling. Cellular and Molecular Life Sciences 70, 1095\u0026ndash;1111 (2013).\u003c/li\u003e\n\u003cli\u003eLupo, G. et al. From pluripotency to forebrain patterning: An in vitro journey astride embryonic stem cells. Cellular and Molecular Life Sciences vol. 71 2917\u0026ndash;2930 (2014).\u003c/li\u003e\n\u003cli\u003ePfaffl, M. W. A New Mathematical Model for Relative Quantification in Real-Time RT-PCR. Nucleic Acids Research vol. 29 (2001).\u003c/li\u003e\n\u003cli\u003eLivak, K. J. \u0026amp; Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2-\u0026Delta;\u0026Delta;CT method. Methods 25, 402\u0026ndash;408 (2001).\u003c/li\u003e\n\u003cli\u003eCostes, S. V. et al. Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophys J 86, 3993\u0026ndash;4003 (2004).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7775232/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7775232/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Brain development and plasticity depend on specific microRNA (miRNA) expression patterns across cell types and subcellular compartments. Nevertheless, comprehensive profiling of localized brain miRNAs is still limited by challenges in isolating individual cell types or compartments and in detection sensitivity. To overcome these limitations, we advanced HIV-1 Gag’s ability to bind host miRNAs within Virus-like Particles to develop Synthetic Nano-Particles for Precise miRNA loading and export (SNaP). Our data establish SNaP’s modularity and portability to clinically-relevant neural cells, with particle yields matching benchmark packaging cells. SNaP integration with a cell-specific promoter enabled lineage-restricted miRNA export, while incorporating a Dendritic Localization Signal improved the specificity of postsynaptic miRNA recovery over traditional synaptosomes. Additional engineering with a miRNA-binding module synergistically boosted synaptic miRNA packaging in a sequence-independent manner. Collectively, our work positions SNaP as a technological advancement supporting the high-resolution, spatially resolved profiling of non-coding RNAs, adaptable to diverse polarized or heterogeneous tissues.","manuscriptTitle":"Synthetic nanoparticles for cell-type specific, spatially resolved miRNA loading and export in neural cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 07:24:09","doi":"10.21203/rs.3.rs-7775232/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a9d8a61-59ba-41cb-a085-da6ba86a2500","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56364004,"name":"Biological sciences/Biotechnology/Nanobiotechnology/Nanoparticles"},{"id":56364005,"name":"Biological sciences/Biotechnology/Nanobiotechnology/Nanostructures"}],"tags":[],"updatedAt":"2025-11-14T07:24:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 07:24:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7775232","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7775232","identity":"rs-7775232","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}