Biology subjects

Mao, Z.

Publications and source records attributed to Mao, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Comprehensive bioinformatic analysis reveals novel potential diagnostic biomarkers associated with monocytes in osteoporosis

Osteoporosis affects millions of women globally. In this study, we applied bioinformatics methods to screen for novel diagnostic biomarkers of osteoporosis in women using the GSE62402 and GSE56814 datasets. PCSK5, ZNF225, and H1FX were used to construct a diagnostic model. ROC, calibration, and decision curve analyses were performed to assess the diagnostic performance on the training (GSE56814) and external (GSE56815) datasets. The expression level of model genes was validated in GEO datasets. Furthermore, five transcription factors (ETS1, NOTCH1, MAZ, ERG, and FLI1) were identified as common upstream regulators of model genes. PCSK5, ZNF225, and H1FX serve as novel diagnostic biomarkers, providing new insights into the pathogenesis of and treatment strategies for osteoporosis in women.

genetics↗

bioRxiv2026

Systematic mapping of emergent transcriptional states in interacting single-cell dyads by Cell-Cell-seq

Cell-cell interactions drive rapid and heterogeneous changes in gene expression, yet most transcriptomic methods either dissociate cells, losing pair identity and interaction timing, or infer communication indirectly from ligand-receptor co-expression. Here we present Cell-Cell-seq, a scalable workflow for profiling defined cell pairs ("dyads") with single-cell transcriptomic resolution. Cell-Cell-seq uses cavity-containing hydrogel microparticles (Nanovials) to confine two cells, synchronize contact onset, protect fragile conjugates during handling and sorting, and interface directly with droplet-based RNA sequencing. Using antigen-matched prostate tumor cells and engineered T cells as a model system, Cell-Cell-seq captured thousands of tumor-T cell dyads and revealed broad functional and transcriptional heterogeneity across interactions. Dyads unmasked transient activation programs that were obscured in standard well-plate co-culture, consistent with asynchronous contact in bulk assays. To distinguish interaction-induced programs from the composite nature of dyad transcriptomes, we developed a pseudo-mixing framework that generates in silico pseudo-dyads to construct an empirical null distribution under "no interaction," enabling statistically robust identification of emergent genes and partner-resolved attribution of responses. Dyad-resolved analysis further revealed coordinated cross-cell programs, including coupled chemokine expression consistent with bidirectional paracrine signaling and inverse coupling between tumor immunoregulatory programs and T cell activation. Finally, we introduce ccRepair to correct compositional dilution in mixed transcriptomes, improving interpretability while preserving genuine cross-cell coordination. Together, Cell-Cell-seq provides a generalizable platform for dissecting immune synapse biology and mapping interaction-dependent programs across heterogeneous cell populations, with applications in profiling tumor-immune communication and functionally screening immunotherapies.

bioengineering↗

bioRxiv2025

Rethinking Alzheimers: Novel miRNAs Illuminate a Disease Beyond the Brain

Alzheimers disease (AD) poses major health, social and economic challenges to the modern world. Despite the advances in understanding AD, our knowledge about its pathogenesis remains incomplete. Recent data suggest that circulating microRNAs (miRNAs) undergo complex changes in AD. Since these changes are yet to be comprehensively characterized, we investigated miRNAs in the context of AD using two meta-analytical approaches. We reproducibly identified 2895 miRNAs in a cohort of 4186 individuals from 22 studies. Here we show that 194 miRNAs exhibited widespread changes in AD, including some novel miRNAs not yet linked to AD. These novel AD miRNAs broaden the landscape of research on the role of miRNAs in AD. Targets of these miRNAs further uncovered many biological pathways that, to date, remain poorly understood in AD with several "AD miRNAs" never described in the brain. "AD miRNAs" described outside the brain significantly influenced interleukin signaling, Toll receptor signaling, p38 MAPK pathway and insulin/IGF pathway. Our results reveal a greater complexity of biological pathways involved in AD than previously thought and raise the question of whether AD is indeed a brain-specific and not a systemic disorder. These findings advance current understanding of AD pathogenesis and lay the ground for the development of next-generation AD biomarkers and design of miRNA-engaged therapies.

molecular biology↗

bioRxiv2025

Functionalizing hydrogel nanovials with vesicles mimicking antigen-presenting vesicles and cancer exosomes improves T cell capture and activation

Recent advances have demonstrated the application of microcavity-containing hydrogel microparticles, known as nanovials, for the massively parallel and high-throughput screening of therapeutic T cell populations for adoptive cell therapies. Nanovial cavities coated with peptide-MHC (pMHC) or antigen tetramers selectively bind to their cognate T cell receptor (TCR) or chimeric antigen receptor (CAR) to activate T cells and capture secreted cytokines. However, binding of tetramers or recombinantly expressed antigen by T cells is not always correlated with T cell activation or cytotoxicity as the binding interface is not fully representative of the natural immunological synapse formed between T cells and professional antigen-presenting cells (APCs). Here, we leverage the recent discovery of an ESCRT- and ALIX-binding region (EABR) sequence to generate antigen-presenting vesicles and cancer-mimicking exosomes from standard HEK293T and Expi293F cell cultures. EABR-mediated vesicles present natural, full-length oncologically-relevant membrane proteins embedded in lipid bilayers to functionalize the nanovial cavity with cell-like membranes. These hydrogel nanovials functionalized with the EABR-mediated vesicles show improved T cell capture of 1G4 T cells and enhanced activation of HER2 CAR-T cells compared to hydrogel surfaces functionalized with recombinantly-expressed soluble proteins.

bioengineering↗

bioRxiv2025

SynBioGPT: A Retrieval-Augmented Large Language Model Platform for AI-Guided Microbial Strain Development

Synthetic biology seeks to engineer microbial cell factories for sustainable bioproduction, yet the optimization of these systems is impeded by the complexity of metabolic engineering and the protracted timelines of iterative design-build-test-learn (DBTL) cycles. Traditional computational approaches, such as constraint-based modeling, provide valuable insights but demand extensive manual curation. Large language models (LLMs) hold promises for automating knowledge extraction and strain design, yet conventional models like GPT-4 suffer from outdated corpora and hallucination errors in domain-specific tasks. SynBioGPT v1.0, a Retrieval-Augmented Generation (RAG)-enhanced LLM, enhanced knowledge retrieval using vector search but often retrieved semantically similar yet contextually irrelevant documents. Here, we introduce SynBioGPT v2.0 (https://synbiogpt.biodesign.ac.cn), which mitigates these limitations by decomposing queries into sub-questions and employing keyword-based searches. Tested on a 100-question synthetic biology benchmark, SynBioGPT v2.0 achieved 98% accuracy with the Claude-3.7-sonnet backend, a 10% improvement over v1.0s 88% with Llama3-8B-Instruct. This advance highlight the efficacy of query decomposition and precise retrieval in enhancing LLM utility for synthetic biology.

synthetic biology↗

bioRxiv2025

Recruiting ESCRT to single-chain heterotrimer peptide-MHCI releases antigen-presenting vesicles that stimulate T cells selectively

Immune cells naturally secrete extracellular antigen-presenting vesicles (APVs) displaying peptide:MHC complexes to facilitate the initiation, expansion, maintenance, or silencing of immune responses. Previous work has sought to manufacture and purify these vesicles for cell-free immunotherapies. In this study, APV assembly and release is achieved in non-immune cells by transfecting HEK293T or Expi293F cells with a single-chain heterotrimer (SCT) peptide/major histocompatibility complex I (pMHCI) construct containing an ESCRT- and ALIX-binding region (EABR) sequence appended to the cytoplasmic tail; this EABR sequence recruits ESCRT proteins to induce the budding of APVs displaying SCT pMHCI. A comparison of multiple pMHCI constructs shows that inducing the release of APVs by the addition of an EABR sequence generalizes across SCT pMHCI constructs. Purified pMHCI/EABR APVs selectively stimulate IFN-{gamma} release from T cells presenting their cognate T cell receptor, demonstrating the potential use of these vesicles as a form of cell-free immunotherapy. Significance StatementImmune cells are known to naturally release pMHC-displaying extracellular vesicles (EVs), called antigen-presenting vesicles (APVs), which can orchestrate immune responses either directly or with the aid of antigen-presenting cells (APCs). For decades, researchers have pursued ways to replicate these APVs for immunotherapy by using chemically modified nanoparticles or by engineering the increased expression of APVs from immune cells which are typically low yield. Here we presents a broadly applicable platform for generating high concentrations of pMHCI-displaying APVs that can selectively modulate T cells, demonstrating a significant advance in the engineering of APVs for cell-free immunotherapy. The APVs presented here, and related APVs, could be translated into clinical therapies for modulating cancer progression or regulating autoimmunity in addition to their use as a tool to help characterize how endogenous extracellular vesicles influence the immune system.

immunology↗

bioRxiv2025

PD-1 prelimits both the cytotoxic and exhaustion potential in thymic CD8+ T cells and impacts the maintenance of peripheral tumor immunity

Durable T cell immunity against cancer depends on the continual replenishment of effector CD8+ T cells. Thymic output has been correlated with favorable prognosis in cancer patients across a range of ages, suggesting that the thymus is an important source for replenishing T cells capable of controlling cancer progression. However, the effector potential of thymic mature CD8+ T cells and their regulation have not been clearly defined. In this study, we identified the ability of thymic single positive CD8+ T cells to gain effector potential after thymic selection, but they are subject to the regulation of PD-1. We found a previously undisclosed role of PD-1 in limiting both the cytotoxic and exhaustion potential of thymic and peripheral CD8+ T cells. Our results show that although PD-1 inhibition facilitates the expansion of effector CD8+ T cells, effector CD8+ cells gradually lose their antitumor activity within tumor tissues due to advanced exhaustion in the absence of PD-1. Thus, although the preset effector potential in thymic mature CD8+ T cells allows them to rapidly respond to malignant cells in the periphery, PD-1, as a checkpoint, is embedded in the thymic mature CD8+ T cells after positive selection to balance their effector function from exaggeration and exhaustion. Therefore, we propose that a strategy capable of upholding the cytotoxic capacity and avoiding exhaustion of CD8+ T cells during the early stages of PD-1 inhibition therapy is needed to achieve durable antitumor immunity.

immunology↗

bioRxiv2025

Toward a privacy-preserving predictive foundation model of single-cell transcriptomics with federated learning and tabular modeling

The ability to pre-train on vast amounts of data to build foundation models (FMs) has achieved remarkable success in numerous domains, including natural language processing, computer vision, and, more recently, single-cell genomics--epitomized by GeneFormer, scGPT, and scFoundation. However, as single-cell FMs begin to train on increasingly large corpora, significant privacy and ethical concerns arise. Moreover, unlike text data, single-cell data is unordered and exhibits a unique tabular structure that most existing single-cell FMs overlook. In this study, we propose Tabula, a privacy-preserving and tabular-structure aware FM designed with federated learning (FL) and tabular modeling. Tabula combines the advantages of FMs and FL, enabling collaborative model training across multiple clients without compromising data privacy. In contrast to earlier single-cell FMs--which treat single-cell data like natural language (viewing cells as "words" defined by genes)--Tabula introduces a novel pretraining strategy that explicitly models the tabular structure of single-cell data. Extensive experimental results show that Tabula outperforms state-of-the-art methods in various downstream tasks (including cell type annotation, gene imputation, gene perturbation, multi-batch integration, and multi-omics integration) while requiring only half the data for pretraining and preserving data privacy. Furthermore, Tabula accurately reveals pairwise and even combinatorial regulatory logic across diverse biological systems, including hematopoiesis, pancreatic endogenesis, neurogenesis, and cardiogenesis. Thus, Tabula provides a new foundation model that explicitly incorporates the tabular nature of single-cell data alongside FL, paving the way for creating a "virtual cell" for human health under critical privacy preservation.

bioinformatics↗

bioRxiv2024

Probing Biomass Precursor Synthesis as a Key Factor in Microbial Adaptation to Unadapted Carbon Sources

Industrial microorganisms often face challenges in utilizing renewable substrates such as methanol, formate, and xylose. We present findings that the proportion of biomass precursors that must be synthesized from unadapted carbon sources is a critical determinant of the evolutionary driving force and minimal substrate requirements, using a new computational framework, AdaptUC. We predict metabolic engineering strategies for Adaptive Laboratory Evolution (ALE). These strategies enable microorganisms to co-utilize an adapted co-substrate and an unadapted carbon source or, in some cases, rely exclusively on the unadapted source. AdaptUC was validated through experimental records and literature, confirming its effectiveness in identifying gene knockout strategies. Case studies in Escherichia coli and Corynebacterium glutamicum highlight superior strategies with higher driving forces and reduced substrate requirements. This method has the potential to transform industrial biosynthesis by enabling more efficient use of renewable carbon sources. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/619944v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@36fe02org.highwire.dtl.DTLVardef@5e73fdorg.highwire.dtl.DTLVardef@110ffdaorg.highwire.dtl.DTLVardef@10d45dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Bursts of rapid diversification, dispersals out of southern Africa, and two origins of dioecy punctuate the evolution of Asparagus

The genus Asparagus arose approximately 9-15 million years ago (Ma) and transitions from hermaphroditism to dioecy (separate sexes) occurred [~]3-4 Ma. Roughly 27% of extant Asparagus species are dioecious, while the remaining are bisexual with monoclinous flowers. As such, Asparagus is an ideal model taxon for studying early stages of dioecy and sex chromosome evolution in plants. Until now, however, understanding of diversification and shifts from hermaphroditism to dioecy in Asparagus has been hampered by the lack of robust species tree estimates for the genus. In this study, a genus-wide phylogenomic analysis including 1726 nuclear loci and comprehensive species sampling supports two independent origins of dioecy in Asparagus--first in a widely distributed Eurasian clade, then again in a clade restricted to the Mediterranean Basin. Modeling of ancestral biogeography indicates that both dioecy origins were associated with range expansion out of southern Africa. Our findings also revealed several bursts of diversification across the phylogeny, including an initial radiation in southern Africa that gave rise to 12 major clades in the genus, and more recent radiations that have resulted in paraphyly and polyphyly among closely related species, as expected given active speciation processes. Lastly, we report that the geographic origin of domesticated garden asparagus (Asparagus officinalis L.) was likely in western Asia near the Mediterranean Sea. The presented phylogenomic framework for Asparagus is foundational for ongoing genomic investigations of diversification and functional trait evolution in the genus and contributes to its utility for understanding the origin and early evolution of dioecy and sex chromosomes. Significance StatementAsparagus is an important model system for studying dioecy (separate sexes) evolution in plants. Asparagus taxonomy has been challenging, likely due to rapid species diversifications leading to highly variable species with complicated relationships that are impossible to resolve with limited DNA-sequence data. Using phylogenomics and the largest species sampling to date, we show that all Asparagus lineages originated from an initial radiation in southern Africa and that separate range expansions out of southern Africa set the stage for two distinct origins of dioecy in Asparagus. Our findings provide a deeper understanding of species diversification and the role of long-distance dispersals in the evolution of dioecy. This study also illustrates the utility of phylogenomics for elucidating past and present speciation processes.

evolutionary biology↗

bioRxiv2024

NovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing

De novo peptide sequencing is a fundamental research area in mass spectrometry (MS) based proteomics. However, those methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) and the significance of de novo peptide-spectrum matches (PSMs). Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species), and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide sequencing methods on target-decoy spectra and to estimate their FDRs. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide sequencing methods, and how their performances depend on specific applications and the types of data. Our FDR estimation also shows that some tools may perform better than the others in distinguishing between de novo PSMs and random matches, and can be used to assess the significance of de novo PSMs.

bioinformatics↗

bioRxiv2024

In-depth investigation of the mechanisms of high and low residual feed intake regulating hens during the late laying period via liver and gut microbiota.

Residual feed intake (RFI) is a more accurate indicator of feed efficiency than the feed conversion ratio (FCR) and is widely used to measure the efficiency of livestock and poultry feed utilization. Typically, Low RFI (LRFI) implies higher feed conversion efficiency, while high RFI (HRFI) indicates lower feed conversion efficiency. This study systematically explored the differences between high and low RFI and the function of the liver and cecum microbes of hens during the late laying period by multiple-omics techniques and further explored the interaction among microorganisms, the function of tissues and organs, and body metabolism. The results showed that the length and mass of the digestive organs in the LRFI group were higher than those in the HRFI group as well as the chest width. Additionally, the key genes and metabolites regulating RFI in hens during the late laying phase were found to be ADCY2, ADCY8, CCKAR, ACSS2, FABP1, FABP4, and LysoPI (18:2(9Z,12Z)/0:0) in the liver. The levels of AST, HDL-C and ACTH in the serum were considered candidate markers influencing RFI. By conducting a microbiome-metabolome association analysis, we have identified the dominant and beneficial microbial community in the gut of LRFI groups, such as Oscillospirales, Ruminococcaceae, and Butyricicoccaceae, which offers a theoretical basis for understanding how the gut microbiota regulates RFI. These results will provide a scientific basis for the molecular mechanism of RFI phenotypic variation in late laying hens.

microbiology↗

bioRxiv2023

Targeting CD74-positive macrophages improves neoadjuvant therapy in cervical cancer as revealed by single-cell transcriptomics analysis

Uterine cervical cancer (UCC) has the second-highest mortality rate among malignant tumors of the female reproductive system. Immune checkpoint inhibitors (ICIs) have emerged as a promising therapeutic strategy for cervical cancer. However, the efficacy of PD-1 (programmed cell death protein 1) blockade combined with neoadjuvant chemotherapy (NACT) and the ensuing alterations within the tumor microenvironment need further investigation. We conducted single-cell RNA sequencing using 46,950 cells from nine sequential human cervical cancer tissues representing different stages of NACT and PD-1 blockade combination therapy. We delineated the trajectory of cervical epithelial cells and unveiled crucial factors involved in the combination therapy. Cell communication analysis revealed the inferred interaction strength decreased between T cell-cancer cells, while the communication between macrophage-cancer cells intensified after NACT therapy. We verified that macrophages are necessary for PD-1 blockade combination to exert antitumor effects in vitro. Detailed analysis unraveled the CD74-positive macrophages frequently interacted with the immunoreactive Epi 3 subgroup during neoadjuvant combination therapy. CD74 upregulation limited phagocytosis and stimulated M2 polarization. The CD74 blockade enhanced macrophage phagocytosis, resulting in decreased viability of cervical cancer cells in vitro and in vivo. This study unveils the dynamic microenvironment of UCC influenced by NACT and PD-1 blockade combination therapy, and targeting CD74 was a potential strategy to augment the therapy efficacy.

cancer biology↗

bioRxiv2023

The temporal progression of immune remodeling during metastasis.

Tumor metastasis requires systemic remodeling of distant organ microenvironments which impacts immune cell phenotypes, population structure, and intercellular communication networks. However, our understanding of immune phenotypic dynamics in the metastatic niche remains incomplete. Here, we longitudinally assayed lung immune cell gene expression profiles in mice bearing PyMT-driven metastatic breast tumors from the onset of primary tumorigenesis, through formation of the pre-metastatic niche, to the final stages of metastatic outgrowth. Computational analysis of these data revealed an ordered series of immunological changes that correspond to metastatic progression. Specifically, we uncovered a TLR-NF{kappa}B myeloid inflammatory program which correlates with pre-metastatic niche formation and mirrors described signatures of CD14+ activated MDSCs in the primary tumor. Moreover, we observed that cytotoxic NK cell proportions increased over time which illustrates how the PyMT lung metastatic niche is both inflammatory and immunosuppressive. Finally, we predicted metastasis-associated immune intercellular signaling interactions involving Igf1 and Ccl6 which may organize the metastatic niche. In summary, this work identifies novel immunological signatures of metastasis and discovers new details about established mechanisms that drive metastatic progression. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/539153v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1333376org.highwire.dtl.DTLVardef@77c937org.highwire.dtl.DTLVardef@3b78b1org.highwire.dtl.DTLVardef@70d497_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefMcGinnis et al. report a longitudinal scRNA-seq atlas of lung immune cells in mice bearing PyMT-driven metastatic breast tumors and identify immune cell transcriptional states, shifts in population structure, and rewiring of cell-cell signaling networks which correlate with metastatic progression. HighlightsO_LILongitudinal scRNA-seq reveals distinct stages of immune remodeling before, during, and after metastatic colonization in the lungs of PyMT mice. C_LIO_LITLR-NF{kappa}B inflammation correlates with pre-metastatic niche formation and involves both tissue-resident and bone marrow-derived myeloid cell populations. C_LIO_LIInflammatory lung myeloid cells mirror activated primary tumor MDSCs, suggesting that primary tumor-derived cues induce Cd14 expression and TLR-NF{kappa}B inflammation in the lung. C_LIO_LILymphocytes contribute to the inflammatory and immunosuppressive lung metastatic microenvironment, highlighted by enrichment of cytotoxic NK cells in the lung over time. C_LIO_LICell-cell signaling network modeling predicts cell type-specific Ccl6 regulation and IGF1-IGF1R signaling between neutrophils and interstitial macrophages. C_LI

immunology↗

bioRxiv2023

Defining T cell receptor repertoires using nanovial-based affinity and functional screening

The ability to selectively bind to antigenic peptides and secrete cytokines can define populations of cells with therapeutic potential in emerging T cell receptor (TCR) immunotherapies. We leverage cavity-containing hydrogel microparticles, called nanovials, each coated with millions of peptide-major histocompatibility complex (pMHC) monomers to isolate antigen-reactive T cells. T cells are captured and activated by pMHCs and secrete cytokines on nanovials, allowing sorting based on both affinity and function. The TCRs of sorted cells on nanovials are sequenced, recovering paired {beta}-chains using microfluidic emulsion-based single-cell sequencing. By labeling nanovials having different pMHCs with unique oligonucleotide-barcodes we could link TCR sequence to targets with 100% accuracy. We identified with high specificity an expanded repertoire of functional TCRs targeting viral antigens compared to standard techniques. One-sentence SummaryAffinity and secretion-based screening of antigen-specific T cells using nanovials defines a functional TCR repertoire

bioengineering↗

bioRxiv2023

Inferring membrane properties during clathrin-mediated endocytosis using machine learning

Endocytosis is a fundamental cellular process for eukaryotic cells to transport molecules into the cell. To understand the molecular mechanisms behind the process, researchers have obtained abundant biochemical information about the protein dynamics involved in endocytosis via fluorescence microscopy and geometric information about membrane shapes via electron tomography. However, measuring the biophysical information, such as the osmotic pressure and the membrane tension, remains a problem due to the small dimension of the endocytic invagination. In this work, we combine Machine Learning and Helfrich model of the membrane, as well as the dataset of membrane shapes extracted from the electron tomography to infer biophysical information about endocytosis. Our results show that Machine Learning is able to find solutions that both match the experimental profile and fulfill the membrane shape equations. Furthermore, we show that at the early stage of endocytosis, the inferred membrane tension is negative, which implies strong compressive forces acting at the boundary of the endocytic invagination. This method provides a generic framework to extract membrane information from the super-resolution imaging. SIGNIFICANCEEndocytosis is a fundamental cellular process that has been extensively studied with the help of fluorescence microscopy and electron microscopy. A large amount of data has been accumulated about the protein dynamics and the membrane shapes. In this work, we combine the widely used Helfrich model and experimental data of membrane shapes to infer the physical information about endocytosis, including the membrane tension and the osmotic pressure. Our work not only proves Machine Learning as a power tool is able to solve the complicated membrane shape equations, but also provides novel biological insights about the initiation of endocytosis in yeast cells.

biophysics↗

bioRxiv2022

The necessity of considering enzymes as compartments in constraint-based genomescale metabolic models

As the most widespread and practical digital representations of living cells, metabolic network models have become increasingly precise and accurate. By integrating cellular resources and abiotic constraints, the prediction functions were significantly expanded in recent years. However, we found that if unreasonable modeling methods were adopted due to the lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of L-serine and L-tryptophan. Specific analysis explains the application method of EcoETM-like model, demonstrating its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Finally, we provide a preliminary comparison of the thermodynamic feasibility of ammonia and glutamine as amino donors, which revealed that the direct utilization of ammonia does not have a decisive impact on the thermodynamic feasibility of the anthranilate pathway. Our work is of great value for the structural improvement of constraints-based models.

bioinformatics↗

bioRxiv2022

Resilient CD8+ T cells maintain a high cytotoxic capacity by balancing ROS via ME1 upregulation

Cytotoxic T lymphocytes (CTL) are indispensable in anti-tumor immunity. Although CTLs are prone to exhaustion in patients with advanced cancer, T cell resiliency explains the presence of tumor-reactive CTLs that are less exhausted, capable of cytolytic function, expansion, and rebound in response to immunotherapy to reject metastatic malignances. However, the features of resilient T cells have not been clearly defined. In this report, we demonstrate that peripheral CX3CR1+ CD8+ T cells with low mitochondrial membrane potential rebounded CTL function quickly after radiation therapy in patients with large tumor burden portraying their functional resiliency. Furthermore, CX3CR1+ CD8+ T cell with low, but not high, mitochondrial membrane potential are highly cytotoxic, accumulate less reactive oxygen species (ROS), and express more Malic enzyme 1 (ME1). ME1 overexpression increases ATP production in a glycolysisindependent manner while concurrently curtailing excessive ROS in activated CD8+ T cells; and expands CX3CR1+NKG7+ effector CD8+ T cells with enhanced cytotoxicity. Importantly, transfection of ME1 mRNA promotes tumoricidal activity in CD8+ T cells from patients with advanced cancers. Our study reveals a mechanism used by CTLs to balance excessive ROS via ME1 to maintain a metabolic and functional resiliency. Modification of ME1 expression in CTLs may be a novel method to improve the efficacy of cancer immunotherapy by preventing T cell exhaustion. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=191 SRC="FIGDIR/small/517988v3_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@12e0f36org.highwire.dtl.DTLVardef@e8d412org.highwire.dtl.DTLVardef@1baf57eorg.highwire.dtl.DTLVardef@14b2b43_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LICX3CR1+ and low Dy m identify functional resilient CD8+ T cells. C_LIO_LIResilient CD8+ T cells are highly cytotoxic and have less ROS. C_LIO_LIResilient CD8+ T cells express more ME1 that can balance extra ROS. C_LIO_LIME1 overexpression can promote CTL function of CD8+ T cells. C_LI

immunology↗