Biology subjects

Yang, A.

Publications and source records attributed to Yang, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Designing a reoriented H5 hemagglutinin to generate stem-directed, heterosubtypic immunity to influenza A viruses

Human infections with the highly pathogenic avian influenza viruses highlight the risk of novel pandemics, against which seasonal vaccines provide limited cross-protection. Whereas antibody responses to current vaccine candidates are typically biased toward the immunodominant and variable head region of hemagglutinin (HA), the stem region of HA is highly conserved and targeted by broadly neutralizing antibodies. Here we describe a reoriented H5 HA (reoH5HAPhe, based on A/Vietnam/1203/2004) displayed on alum as a vaccine candidate to elicit stem-directed antibody responses and confer cross-protective immunity. We show that a single immunization with reoH5HAPhe protected naive mice against heterologous H5N1 lethal challenge (A/Texas/37/2024), and boosting with reoH5HAPhe conferred complete heterologous protection in mice pre-immunized with seasonal vaccines. The stem-directed response elicited by reoH5HAPhe also protected against heterosubtypic H1N1 challenge in both naive and pre-immune mice. Electron microscopy polyclonal epitope mapping revealed that reoH5HAPhe elicited antibodies targeting the central stem and anchor epitopes on heterologous H5 and H1 HAs, alongside antibodies against the (H5) vestigial esterase or (H1) lateral patch epitopes. Despite limited cross-neutralizing activity, increased stem-directed responses with balanced IgG1 and IgG2 subclasses reduced viral replication and improved survival. Our results highlight antigen reorientation as an effective approach for designing variant-resilient vaccines and demonstrate the potential of reoH5HAPhe as an H5 pandemic influenza vaccine candidate that confers protective immunity against both emerging and seasonal influenza viruses.

immunology↗

bioRxiv2026

IL-2 and CD40L can establish and sustain a human B cell-mediated immune regulatory network

B cells can control inflammation, but the factors governing B cell-mediated immune regulatory network remain unclear. We report that IL-2/CD40L enable class-switched memory (CSM) B cells to acquire an immunosuppressive phenotype characterized by the expression of surface TIGIT as well as multiple other inhibitory receptors (PD-1, LAG-3, GITR, CD39, and CTLA-4) and soluble molecules (IL-10, granzyme B, and IL-35). TIGIT+ CSM B cells expressing functional CCR9 exhibit significant defects in total immunoglobulin secretion, while preserving IgA2 secretion. Furthermore, IL-2/CD40L-induced ex vivo-generated TIGIT+ CSM B cells suppress human T cell-mediated inflammation in a xenogeneic mouse model of acute graft-versus-host disease, while promoting IL-10-producing regulatory T cell (Treg) response. These findings identify IL-2/CD40L as key drivers of a B cell-mediated immune regulatory network, especially by generating TIGIT+ CSM B cells that can further promote Treg response. This study supports the development of TIGIT+ B cell-based therapy models for inflammatory diseases.

immunology↗

bioRxiv2026

Single-Cell Proteo-Transcriptomic Profiling Uncovers Post-Translational Regulatory Layers in Human Hematopoiesis

Background: Hematopoietic stem cells (HSCs) have the unique ability to produce all mature cell types in the blood and understanding the mechanisms governing their differentiation and renewal is a driving question in stem cell biology. While single-cell RNA sequencing has transformed our view of human hematopoiesis, mRNA abundance represents an incomplete proxy for functional cell states. Here, we apply single-cell multimodal profiling to simultaneously measure 280 surface and intracellular protein targets alongside whole transcriptomes within individual adult human hematopoietic stem and progenitor cells. Results: By directly coupling modalities within single cells, we show that protein-RNA correlations peak dynamically in transitioning intermediate progenitors across lineages, consistent with pervasive post-transcriptional mechanics underlying lineage choice. Furthermore, key transcription factor proteins maintain multilineage co-expression longer into commitment than their transcripts, demarcating a possible window of fate decision reversibility. Moreover, low and flat CTNNB1 mRNA levels mask late-erythroid {beta}-catenin protein enrichment, apparently pairing with E-cadherin expression and suggesting post-translational stabilization at the cell membrane. Conclusions: This dataset enables the observation of translational dynamics and RNA-protein relationships throughout the differentiation landscape at an unprecedented level of granularity. Together, our findings demonstrate that transcriptomics alone misses fundamental regulatory programs, establishing single-cell proteo-transcriptomics as a powerful tool for decoding human stem cell fate.

cell biology↗

bioRxiv2026

A conditional upper-bound design map for rhodopsin-augmented electro microbial CO2-to-biomass conversion

The value of rhodopsin proton pumps as light harvesters in electro-microbial CO2-to-biomass conversion depends on molecular photophysics, pathway energetics and reactor light delivery. We couple these scales for Cupriavidus necator, comparing Calvin-Benson-Bassham (CBB) and reductive glycine (rGlyP) assimilation. The model predicts a 17.9% dark rGlyP yield advantage, close to 16.5% measured in chemostats. At 568 nm, 100 PPFD and 45% membrane occupancy, light-derived ATP raises yield by 17% for rGlyP and 14% for CBB. Charging CO2 capture and formate electrosynthesis, a retinal-only reactor reaches 3.29% efficiency versus 2.56% in the dark. A carotenoid antenna raises this to 3.52% at the model-derived 70% transfer estimate and helps in 93.2% of uncertainty samples, but lowers efficiency at the thermodynamic limit by diverting photons from photovoltaics. Point-source CO2 cuts the relative light benefit from 38% to 8%. Rhodopsin is therefore most useful when upstream formate is energy-intensive, not as a general efficiency boost.

systems biology↗

bioRxiv2026

Complex enzyme active site scaffolding by iteratively detuned catalytic guidance

De novo enzyme design requires sequences whose structures reproduce prescribed catalytic geometries. This remains challenging for active sites that couple multiple catalytic residues, cofactors and substrates. Here we introduce the Catalytic Guidance Engine (CaGE), which optimizes designed sequences to satisfy complex sets of functional constraints by alternating constraint guided structure prediction trajectories with sequence design, gradually fading the strength of the constraint information over cycles to nudge the designed sequence towards satisfying all the constraints. We train RF3 to accept atom-pair distances and other design conditions, and use classifier-free guidance to fade their influence over multiple design cycles. We also develop training-free motif guidance protocols which operate at inference time by directly adjusting selected atoms towards the design target geometry during diffusion sampling. CaGE improves catalytic-motif geometry across a diverse enzyme benchmark and yields sequences that recover complex target active sites in independent AF3 predictions. We experimentally demonstrate the power of CaGE by designing active enzymes with complex catalytic sites: a nonheme-iron design positions four active-site residues around an iron centre and a transition-state ligand, and a PLP-dependent design positions four catalytic residues around a PLP cofactor with multiple functional groups. Active site substitutions and a 2.7[A] crystal structure support the designed mechanisms and structures. Thus, CaGE provides a route to functional de novo enzymes with complex active sites.

bioengineering↗

bioRxiv2026

Cerebral microthrombi promote focal Cav-1-dependent blood-brain barrier impairment, triggering neuroinflammation and neuronal damage after traumatic brain injury

Traumatic brain injury (TBI) is frequently accompanied by blood-brain barrier (BBB) dysfunction, yet the microvascular events that initiate barrier failure and secondary neural injury remain poorly understood. Using highly sensitive fluorescent nanoscale tracers, correlative light and electron microscopy, single-cell transcriptomics, and genetic manipulation of Caveolin-1 (Cav-1), we show that BBB leakage after TBI in mice occurs focally at sites of cerebral microthrombus formation. Endothelial cells adjacent to microthrombi remain structurally intact, but exhibit a distinct transcriptional program enriched in both thrombosis- and transcytosis-related genes, including Cav-1. Microthrombi promote Cav-1-dependent transcytosis and size-selective extravasation of blood-borne proteins, exposing the surrounding parenchyma to circulating factors and inducing focal microglia activation and neuronal damage in vivo. In human induced pluripotent stem cell-derived neurons, these proteins directly impaired neuronal structure and network function. Genetic deletion of Cav-1 markedly reduces microthrombus-associated BBB leakage, immune-cell diapedesis, microglial activation and neuronal loss, whereas endothelial re-expression of Cav-1 using AAVs restores leakage. Human TBI data reveal early dynamic coagulation dysregulation associated with adverse clinical outcome, focal cerebral vascular injury and endothelial transcriptional signatures consistent with reduced barrier integrity and increased caveolae-associated transport. Together, these findings identify cerebral microthrombi as focal sites of Cav-1-dependent BBB dysfunction and establish pathological endothelial transcytosis as a mechanistic link between post-traumatic microvascular thrombosis, blood protein extravasation and secondary neuronal injury. Targeting Cav-1-dependent transcytosis may therefore provide a strategy to limit pathological BBB permeability and secondary injury after TBI.

neuroscience↗

bioRxiv2026

A draft atlas of the human plasma proteome at isoform resolution

Key plasma protein, including albumin, complement system proteins, and coagulation factors circulate in biochemically and functionally distinct isoforms, or proteoforms. Despite the importance of these proteoforms being widely accepted, they are challenging to resolve systematically, and as a consequence, we still lack a more complete picture of the total proteoform diversity of the human plasma proteome. Here, we generated 3,114 intact protein fractions by extensively separating plasma according to isoelectric point and molecular weight. We then analysed these fractions by liquid chromatography data-independent acquisition mass spectrometry (DIA-MS) upon tryptic digestions, and combined the resultant data into a multidimensional, proteoform resolved atlas of the human plasma proteome. We report that 5,077 unequivocally detected plasma proteins circulate at least 179,049 distinct proteoforms, of which we detect 44,083, with a median of 11 proteoforms per protein, at high confidence. Substantially increasing the number of experimentally confirmed proteoforms, our atlas implies that the canonical protein forms account for less than half of the total protein mass in plasma. We detect the greatest proteoform diversity among the most abundant plasma proteins and those functioning in nutrient transport, complement and coagulation. Finally, our data clarifies discrepancies between the Olink and SomaScan proteomic platforms, as according to our atlas, these techniques provide correlated values for relatively abundant proteins with low to medium proteoform diversity, but struggle in the quantification of low-abundant proteins and on those which exist in many proteoforms. In sum, our data reveals extensive proteoform diversity of the human plasma proteome, and implies that proteoform diversity represents an enormous untapped reservoir for biomedical research and biomarker discovery.

biochemistry↗

bioRxiv2026

A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease

Blood provides an accessible window into human health, yet the absence of a peripheral blood mononuclear cells (PBMCs) reference with standardized immune cell annotations has constrained comparisons between single-cell RNA sequencing (scRNAseq) studies. Here, we present HARP (Human Cell Atlas Reference for PBMCs), an integrated atlas of ~9 million PBMCs from >2,600 donors across 15 studies spanning four continents, encompassing diverse populations, neonates to 97 years, across health and diverse immune-related diseases. We developed optimized integration workflows, including novel label-free metrics to assess integration quality, and generated community-driven consensus annotations for 192 immune cell subsets, identifying rare populations representing as few as 0.004% of PBMCs. HARP reveals coordinated cellular modules associated with age, sex, and disease, identifies female-biased interferon and inflammatory gene programs and their perturbation by COVID-19, and uncovers a novel sexual dimorphism in prostaglandin signaling. Finally, we introduce scTiger, a hierarchical label-transfer framework that accurately projects these 192 cell annotations onto ~18 million additional PBMCs, providing a robust and transferable reference for harmonizing future PBMC studies. HARP provides a high-resolution community-driven reference atlas for PBMC annotation and analysis, as a basis for emerging clinical applications of single-cell genomics.

immunology↗

bioRxiv2026

Rac1 and CHK1 Converge on Abi-1 to Regulate DNA Repair Dependency and Treatment Response in Human Cancers

Radiation therapy (RT) resistance remains a major clinical challenge, yet biomarkers guiding precision radiosensitization are lacking. We previously demonstrated that Rac1 promotes RT resistance in glioblastoma (GBM) by inducing Abi-1-S323 dephosphorylation and enhancing non-homologous end joining (NHEJ). Here, we identify Abi-1-S323 as a key regulator of DNA repair states and a determinant of therapeutic efficacy in human cancers. Clinically, loss of Abi-1-S323 phosphorylation was associated with poor outcomes in patients with RT-treated GBM. Bioinformatic analyses revealed that non-small cell lung cancer (NSCLC) and head and neck cancer (HNC) are among the cancers with frequent RAC1 amplification, suggesting that these tumor types may have increased Rac1-Abi-1 signaling activity. Loss of Abi-1-S323 phosphorylation also predicted poor outcomes in patients with RT-treated HNC. Consistent with these clinical observations, high Rac1 activity and low Abi-1-S323 phosphorylation were associated with enhanced DNA double-strand break repair and radioresistance in NSCLC and HNC models, whereas genetic or pharmacological inhibition of this signaling impaired DNA repair and radiosensitized tumors in vitro and in vivo. Mechanistically, we identified CHK1 as a kinase that phosphorylates Abi-1 at S323 and defines an alternative homologous recombination (HR)-dependent repair state. Tumors with high Rac1-Abi-1 signaling exhibited elevated NHEJ capacity and were selectively radiosensitized by Rac1 inhibition, whereas tumors with low Rac1-Abi-1 signaling displayed high CHK1 activity, preferentially relied on HR, and were selectively radiosensitized by CHK1 inhibition. These findings establish Abi-1-S323 as a biomarker defining therapeutically distinct DNA repair states and provide a framework for precision radiosensitization.

cancer biology↗

bioRxiv2026

40S Ribosome Remodeling Triggers 18S rRNA U-tailing and DIS3L2-dependent Decay

Eliminating defective ribosomes through quality control is essential for accurate protein synthesis. However, the mechanisms that commit ribosomal subunits to decay remain poorly defined. Here, we identify a tandem mechanism in which ubiquitin-mediated ribosome remodeling and 18S rRNA uridylation lead to 40S ribosomal subunit decay. Specifically, we use an in vitro reconstitution system to show that the atypical kinase RIOK3 displaces the ribosomal protein eS26 from 40S subunits, exposing the 3 end of 18S rRNA. Nanopore direct RNA sequencing and motif analyses reveal that this remodeling event promotes oligo-uridylation, generating uridylated 18S rRNA decay intermediates. We further show that this uridylated 18S rRNA is selectively degraded by the 3-5 exoribonuclease DIS3L2. Moreover, DIS3L2-mediated exoribonucleolytic cleavage triggers endoribonucleolytic decay of the 18S rRNA, amplifying turnover. Together, our findings define a stepwise mechanism in which ribosome remodeling and RNA tailing commit defective 40S subunits to elimination, establishing a mechanistic framework for ribosome surveillance in mammalian cells.

molecular biology↗

bioRxiv2026

AI-enabled rhodopsin design for blue-light enhanced bacterial growth

We developed an AI-guided design pipeline that generated and validated non-natural microbial rhodopsins with spectral properties not yet known in nature. The pipeline comprised a three-stage in silico design, a genetic algorithm (GA) for sequence generation, a stacked LASSO and XGBoost machine-learning (ML) regressor for spectral prediction and fitness ranking, and a Markov-based sequence plausibility filter to enforce proton pumping like characteristics. Four candidate rhodopsins (APR1, APR2, APR6, and APR7) targeting blue light absorption were designed and AlphaFold3 structural modelling predicted retinal binding pocket architecture consistent with outward proton-pumping function. Experimental characterisation confirmed that all four variants absorbed light at [~]410 nm and significantly promoted the growth of Cupriavidus necator under blue light illumination. This study demonstrates that AI-enabled design can engineer proteins with no natural precedent, generating light-harvesting rhodopsins with novel spectral properties while preserving biological function, marking a significant advance in programmable synthetic biology.

Synthetic Biology↗

bioRxiv2026

Satellite Glial Cells Drive Homeostatic Synaptic Structural Plasticity in Sympathetic Neurons

Sympathetic neuronal (SN) activity critically regulates the development and function of peripheral organs and tissues. The demonstration of activity-dependent modulation of SN output suggests that compensatory forms of plasticity could contribute to maintaining the stability of sympathetic circuits. Such plasticity mechanisms could act to restrain SN hyperactivity, a key driver of hypertension in humans and in the spontaneously hypertensive rat (SHR). In this study we examined how long-term changes in activity impact synaptic properties in postnatal sympathetic neuron cultures using chemogenetic and pharmacological manipulations and by examining the effects of enhanced activity of SHR neurons. We showed that bidirectional changes in neuronal activity resulted in homeostatic shifts in synaptic density to counteract long-term activity manipulations. In the absence of sympathetic satellite glial cells (SGCs) there was no synaptic compensation in the cultures. Direct chemogenetic activation of SGCs was sufficient to drive a decrease in synaptic sites and neuronal activity, while glial inhibition blocked activity-dependent synaptic compensation, demonstrating a role for the SGCs in homeostatic regulation of synaptic properties. We found that the SGCs responded to cholinergic signaling by downregulating the expression of the synaptic regulators NGF and TNF, suggesting that reciprocal signaling between SNs and SGCs acts to stabilize sympathetic output during long-term changes in circuit activity. Finally, we showed that these plasticity mechanisms are disrupted in postnatal SHR neurons, with an attenuated neuronal response to glia signaling during synapse formation and activity-dependent plasticity. Taken together, this work describes a new homeostatic activity-dependent plasticity mechanism in the peripheral nervous system.

neuroscience↗

bioRxiv2026

Phyllosphere and rhizosphere microbiomes empower Nicotiana tobacum complex traits dissection and prediction

Understanding how plant-associated microbiomes interact with host genome variation to influence agronomic traits is essential for advancing microbiomeassisted crop improvement. In this study, we characterized the phyllosphere and rhizosphere microbiomes of 164 diverse Nicotiana tabacum accessions using 16S rRNA sequencing and integrated these data with host genomic variation and 22 agronomic traits. The two microbiomes exhibited distinct taxonomic structures, diversity patterns, and predicted metabolic functions. Microbiome genomewide association studies identified extensive host genetic control over microbial abundance, including 49 shared genomic loci that explained nearly half of the heritable variation in both microbiomes. Microbiomewide association studies revealed biologically meaningful associations between specific ASVs and agronomic traits. However, network analysis demonstrated that microbial subcommunities, rather than individual taxa, contributed substantially to phenotypic variation. Then, colocalization analysis further identified genetic variants jointly influencing microbial abundance and metabolite traits, highlighting potential host-microbe-trait causal links. Incorporating microbiome data into genomic selection models, we successfully improved prediction accuracy for several traits, especially plant architecture and flowering. Together, this work provides a comprehensive populationlevel framework linking host genetics, microbiome composition, and agronomic traits in tobacco, offering new insights for microbiomeinformed breeding strategies.

plant biology↗

bioRxiv2025

Characterization of the pulmonary immune response induced by a highly protective tuberculosis vaccine using latent and acute infection mouse models

We utilized a mouse tuberculosis (TB) latency model to evaluate multiple candidate TB vaccines for their ability to prevent reactivation of a latent infection. Among the most promising vaccine regimens tested was BCG formulated in adjuvant (Adj) (dimethyl dioctadecyl-ammonium bromide (DDA) plus D-(+)-Trehalose 6,6-Dibehenate (TDB)) with rEsat-6 delivered subcutaneously (SC) followed by an intranasal (IN) administration of an adenovirus construct expressing a fusion of Esat-6 (E6) and antigen-85B (Ag85B) (AdE6-85B) before an aerosol M. tuberculosis challenge. We designated this vaccine regimen as BAA. BAA consistently prevented reactivation of 75 - 100% of immunized animals and was also highly and significantly protective against an acute aerosol infection with a consistent 2 - 3 log10 mycobacterial CFU reduction in the lungs relative to nonimmunized mice (Naive). Likewise, the BAA vaccine was significantly more protective than BCG or BCG+Adj controls. Interestingly, we found that pre-challenge frequencies of CD4+ tissue resident memory (TRM) T cells (CD69+PD-1+CXCR3+), and CD4+ populations bearing CD153 and P2X7R, which are markers for protection, were significantly elevated in the lungs of mice immunized with the BAA vaccine relative to control groups. Additionally, we found significantly higher frequencies of multifunctional CD4+ T cells from infected lungs expressing both IL-17A and TGF{beta} or IL-17A, TGF{beta} and IFN-{gamma} than in control groups. These findings suggest that vaccine regimens that establish a population of CD4+ TRM cells in the lungs prior to infection and populations of multifunctional CD4+ T cells after infection may help control an acute pulmonary infection and prevent progression to active disease. IMPORTANCETo help curtail the TB epidemic, a new vaccine should prevent progression from a latent infection to active disease. Correlates of protective immunity, however, are presently unclear, which impedes the development of an improved TB vaccine. Hence, we tested different vaccines for their ability to prevent reactivation using a mouse latency model and identified a highly efficacious formulation using this model and, also, after testing using an acute aerosol infection model. We then examined the pulmonary immune responses induced by this vaccine both before and after an aerosol challenge and identified immune markers as well as populations of multifunctional and tissue resident memory T cells that may serve as correlates of vaccine efficacy against progression to active TB disease and control of an acute infection.

immunology↗

bioRxiv2025

Cell type-resolved long-read transcriptomics of the human cortex reveals pervasive alternative splicing and disease-relevant isoforms

Alternative splicing generates extraordinary transcriptomic complexity in the human brain, yet the full-length isoform landscape across human cortical cell types remains uncharted. Combining fluorescence-activated nuclei sorting with long- and short-read RNA sequencing, we generated isoform-resolved transcriptomes for five major lineages of the adult human prefrontal and orbitofrontal cortex: GABAergic neurons, glutamatergic neurons, oligodendrocytes, astrocytes, and microglia. We cataloged over 220,000 full-length isoforms, [~]35-56% previously unannotated; novel transcripts were longer, more exon-rich, and predominantly protein-coding. Contrary to the neuron-centric view of cortical complexity, glial lineages, particularly oligodendrocytes and microglia, emerged as the most isoform-diverse populations in the cortex. Differential transcript usage and dominant isoform switching defined cell identity, with [~]59-62% of differentially regulated transcripts absent from current annotations. Critically, pathogenic variants were enriched >2-fold at novel splice boundaries within disease genes including POGZ, TARDBP, and PLP1, establishing isoform selection as a primary axis of cortical identity and exposing a layer of pathogenic variation invisible to canonical gene annotations.

genomics↗

bioRxiv2025

Deep Learning for Cognitive Task Presence Prediction from Dynamic Functional Connectivity

Dynamic functional connectivity (dFC) studies the time-varying coordination between brain regions measured with fMRI and is a potential biomarker for understanding cognitive dynamics and tracking the development of neurological disorders. However, a critical methodological challenge lies in the variability of dFC estimates across different dFC assessment methods, raising concerns about the reliability and interpretation of downstream findings. While deep learning (DL) models have demonstrated the ability to capture traditionally inaccessible data patterns in many disciplines, they encounter challenges when applied to neuroimaging data. For instance, the high dimensionality, noise, and temporal complexity inherent in dFC makes it challenging for DL models to extract meaningful and interpretable insights. In this study, we investigated how DL architectures can be developed and adapted to predict task presence over time from task-based dFC data, and additionally, how the choice of dFC assessment method influences the predictive performance of DL models. We developed and compared a convolutional neural network (CNN), a node-level classification graph convolutional network (GCN), and a graph-level classification GCN based on their ability to predict time points at which subjects were performing a cognitive task or at rest. In our study, the results indicate that both DL model architecture and dFC estimation methodology significantly impact task presence prediction capacity, while the specific task paradigm had minimal influence out of the limited types that were explored. This work offers a powerful benchmark for understanding the dynamics of underlying task-driven cognitive state transitions and the analytical flexibility limitations of dFC estimation methods and DL architectures.

neuroscience↗

bioRxiv2025

A chromatin fiber model explains cell-free DNA fragmentation signatures of active regulatory elements

Circulating cell-free DNA (cfDNA) assays are being widely adopted in oncology and maternal-fetal medicine. Patterns of cfDNA fragmentation can provide useful information about gene regulation and expression in human disease from a blood draw. Here, we demonstrate that enhancer RNA expression - a marker of enhancer activity - can be inferred from local patterns of cfDNA fragmentation. We define a transcriptional activation score (TAS) that predicts expression of enhancers and genes based on cfDNA fragment sizes and positions near transcriptional start sites (TSSs). The TAS identifies activity of cancer-associated enhancers in patients with cancer, distinguishes clinically relevant cancer subtypes, and identifies activation of enhancers associated with treatment resistance and therapy response. We propose a simple model to account for our findings based on chromatin fiber structure and the depletion of H1 histone proteins near active TSSs. Our model provides a unified framework that reconciles seemingly conflicting observations from prior fragmentomics studies. Broadly, this work enables blood-based assessments of gene regulation in cancer and non-oncologic diseases to inform pathobiology, diagnosis, and treatment selection.

genomics↗

bioRxiv2025

Proteome constrained metabolic modeling of Sus scrofa muscle stem cells for cultured meat production

Cultured meat has recently emerged as a sustainable alternative to the traditional livestock farming and gained attention as a promising future protein source. Herein, the Sus scrofa muscle stem cell is a commonly used cell source in the cell proliferation step of cultured meat production. However, a major bottleneck of large-scale cultivation is the inhibition by secreted and accumulated lactate and ammonium in the process of S. scrofa cell proliferation. To simulate the growth and metabolism of S. scrofa muscle stem cells under different lactate and ammonium concentrations, this study constructed the first proteome constrained metabolic model for the core metabolism of S. scrofa muscle stem cells, pcPigGEM2025. The relationship of lactate and ammonium levels with cellular metabolism was derived from growth and metabolomics data of two culture conditions with low and high initial ammonium concentrations, and then incorporated into metabolic flux simulation. Metabolic flux simulations for experimental conditions, along with perturbation simulations considering stressed non-growth associated maintenance and oxygen supply, demonstrated that pcPigGEM2025 could effectively characterize the response of the S. scrofa muscle stem cells growth and metabolism to varying environmental conditions, shedding light on model-aided control and optimization of the cultured meat production process. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/679571v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@a4526aorg.highwire.dtl.DTLVardef@1ee2d1org.highwire.dtl.DTLVardef@1bd4700org.highwire.dtl.DTLVardef@18079e6_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThe first proteome constrained metabolic model was built for S. scrofa myoblasts. C_LIO_LIThis model effectively simulated myoblast metabolism under lactate and NH4+ stress. C_LIO_LIPerturbation simulations showed that this model could also account for other stress. C_LIO_LIThis model enables in-silico control and optimization of cultured meat production. C_LI

bioengineering↗