Biology subjects

Shi, H.

Publications and source records attributed to Shi, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Latent Regulatory Programs Generate Synthetic T Cell States with Enhanced Therapeutic Potential

Transcription factors (TFs) govern cell fate through coordinated gene-regulatory networks, yet the full potential of these networks to generate non-native, therapeutically advantageous cell states in vivo remains largely unexplored. We hypothesized that systematic gain-of-function (GOF) overexpression of TFs in CD8 T cells, central mediators of immune protection, could reveal latent, or "hidden," regulatory programs capable of generating synthetic T cell states with therapeutic utility. To test this, we developed single-cell GOF sequencing (scGOF-seq), a multiplexed platform for unbiased, in vivo mapping of GOF effects on T cell fate in immunocompetent mouse models of infection and cancer. scGOF-seq uncovered unexpected regulators of T cell differentiation and accumulation, including SOX2, OCT4, and GATA2, which are normally silenced during T cell differentiation. Notably, outside its native regulatory context, supraphysiologic cMyc GOF reprogrammed CD8 T cells into a synthetic stem-effector hybrid state, enabling >5,000-fold antigen-dependent expansion and antitumor activity, contrasting sharply with its native function in driving terminal differentiation. scGOF-seq further identified TF modules that cooperate with cMyc GOF to promote robust CD8 T cell responses in solid tumors. Together, these findings establish GOF perturbation as a powerful strategy for revealing latent immune regulatory programs and engineering synthetic immune states with therapeutic potential. One-Sentence SummaryIn vivo single-cell gain-of-function screening reveals latent transcriptional programs that can reprogram T cells into highly functional synthetic states.

immunology↗

bioRxiv2026

Indomethacin exerts both cyclooxygenase inhibition-dependent and independent mechanisms to enhance chemo-immunotherapy in mice

Nonsteroidal anti-inflammatory drugs (NSAIDs) primarily act by inhibiting cyclooxygenases (COX1 and COX2), thereby reducing production of the proinflammatory mediator prostaglandin E2 (PGE2). Because PGE2 is a critical driver of cancer progression and tumor immune evasion, this has motivated interest in combining NSAIDs with chemotherapy or immunotherapy for cancer treatment. However, since COX and PGE2 levels vary across tumor types, it remains unclear whether tumor PGE2 abundance solely dictates tumor response to NSAID-based therapies. Here, we investigated the therapeutic potential of indomethacin (Indo), a prototypical NSAID, in combination with cyclophosphamide (CTX), a widely used chemotherapeutic agent with immunostimulatory properties. Metronomic administration of Indo significantly enhanced the antitumor efficacy of CTX in multiple murine tumor models exhibiting variable COX2 and PGE2 levels, including CT26, MC38, 4T1 and A20. The antitumor effects of CTX+Indo required CD8 T cells and T-cell trafficking from tumor-draining lymph nodes and were further potentiated by anti-PD-1 blockade. Single-cell RNA sequencing (scRNA-seq) revealed that responsive CT26 tumors exhibited a reprogrammed tumor immune microenvironment (TIME), marked by increased effector CD8 T-cell infiltration, reduced immunosuppressive myeloid populations, and enhanced interferon signaling in tumor cells. Importantly, Indo retained therapeutic benefit following CTX even in tumors incapable of producing PGE2, demonstrating a critical contribution of COX-independent mechanisms, particularly inhibition of tumor-intrinsic oncogenic RAS signaling, to the enhanced efficacy of the CTX+Indo combination. Collectively, our results provide strong preclinical rationale for leveraging the COX/PGE2 and RAS dual inhibitory capacities of NSAIDs to enhance the efficacy of chemotherapy and immunotherapy.

immunology↗

bioRxiv2025

Trehalose 6-phosphate activates Target of Rapamycin in plants

Coordinating carbon availability with growth is a fundamental challenge in plants. Target of Rapamycin (TOR) promotes cell growth and is activated by sugars, but the underlying molecular mechanism has remained elusive. Here, we identify trehalose 6-phosphate (T6P), a sucrose-derived metabolite, as the key signal linking carbon to TOR activity. In Arabidopsis and Brassica napus, T6P stimulates cell growth via TOR and is required for sucrose-induced TOR activation. We show immunoprecipitates using anti-TOR antibodies contain catalytically active TOR in addition to the catalytically active SnRK1 energy sensor kinase. In vitro experiments show that, SnRK11, the catalytic subunit of SnRK1 suppresses TOR activity, and T6P reverses this inhibition in a dose-dependent manner, providing biochemical evidence that T6P activates TOR by suppressing SnRK1. This work thus establishes a direct sucrose-T6P-SnRK1-TOR signaling axis that couples carbon availability to plant growth.

plant biology↗

bioRxiv2025

Structure and evolution-guided design of minimal RNA-guided nucleases

The design of RNA-guided nucleases with properties not limited by evolution can expand programmable genome editing capabilities. However, generating diverse multi-domain proteins with robust enzymatic properties remains challenging. Here we use an artificial intelligence-driven strategy that couples structure-guided inverse protein folding with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease. High-throughput functional screening of AI-generated variants yielded editors that retained or exceeded wild-type activity in bacterial, plant and human cells. Cryo-EM-based structure determination of the most divergent active variant revealed new stabilizing contacts in the RNA/DNA interfaces across conformational states, demonstrating the design potential of this approach. Together these results establish a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space. One-sentence abstractAn evolution- and structure-conditioned model enables design of active RNA-guided nucleases with new nucleic acid contacts resolved by cryo-EM.

synthetic biology↗

bioRxiv2025

Orthosteric Molecular Glue Inhibits COP9 Signalosome with Substrate-Dependent Potency

Orthosteric inhibitors block enzyme active sites and prevent substrates from binding. Enhancing their specificity through substrate dependence seems inherently unlikely, as their mechanism hinges on direct competition rather than selective recognition. Here, we show that a molecular glue mechanism unexpectedly imparts substrate-dependent potency to CSN5i-3, an orthosteric inhibitor of the COP9 signalosome (CSN). We first confirm that CSN5i-3 inhibits CSN, which catalyzes NEDD8 deconjugation from the cullin-RING ubiquitin ligases (CRLs), by occupying the active site of its catalytic subunit, CSN5, and directly competing with the iso-peptide bond substrate. Curiously, the orthosteric inhibitor binds free CSN with only micromolar affinity, yet achieves nanomolar potency in blocking its deneddylase activity. Cryo-EM structures of the enzyme-substrate-inhibitor complex reveal that active site-engaged CSN5i-3 occludes the substrate iso-peptide linkage while simultaneously extending an NEDD8-binding exosite of CSN5, acting as a molecular glue to cement the NEDD8-CSN5 interaction. The cooperativity of this tri-molecular CSN5i-3-NEDD8-CSN5 assembly, in turn, sequesters CSN5i-3 at its binding site, conferring high potency to the orthosteric inhibitor despite its low affinity for the free enzyme. Together, our findings highlight the modest affinity requirements of molecule glues for individual target proteins and establish "orthosteric molecular glue inhibitors" as a new class of substrate-dependent enzyme antagonists.

molecular biology↗

bioRxiv2025

The 9p21.3 Coronary Artery Disease Risk Locus Modulates Vascular Cell-State Transitions via Enhancer-Driven Regulation of MTAP

The 9p21.3 locus is the strongest genetic association with coronary artery disease (CAD), yet its causal mechanisms remain unresolved. We map the regulatory architecture of 9p21.3 in disease-relevant vascular cells, identifying 12 enhancers within the CAD risk haplotype that respond dynamically to inflammatory and metabolic stress in fibroblasts and smooth muscle cells. These activated states are enriched for CAD heritability, implicating stress-responsive vascular wall cells in disease pathophysiology. Dense CRISPRi tiling integrated with fine-mapping and genomic constraint across >500,000 individuals nominates MTAP as the effector gene, with rs1537371 as a likely causal variant. Perturbation and multi-modal analyses show that MTAP loss induces pro-fibrotic and angiogenic programs and sensitizes vascular cells to TGF-{beta}-driven pathological transitions. Our findings reveal a vascular-specific enhancer network through which noncoding variation at 9p21.3 modulates CAD risk via MTAP--a previously unrecognized regulator of vascular remodeling located 269 kb from the risk haplotype. HighlightsO_LI9p21.3 CAD risk locus harbors 12 functional enhancers active in vascular wall cell types C_LIO_LICAD heritability is enriched in stressed vascular fibroblasts and smooth muscle cells C_LIO_LIHigh-resolution CRISPRi-MAC-seq maps 9p21.3 enhancer-gene and SNP-gene interactions C_LIO_LIMTAP identified as a causal effector gene regulated by 9p21.3 fine-mapped and constrained variants C_LIO_LIMTAP modulates TGF-{beta}-driven pathological vascular cell transitions C_LI

genomics↗

bioRxiv2025

The anti-retroviral therapy emtricitabine affects skeletal muscle DNA methylation and transcriptome patterns in a male HIV mouse model

BackgroundAlthough antiretroviral therapies (ART) have substantially reduced HIV-associated mortality, the increased lifespan achieved by widespread ART deployment has revealed that HIV infection is linked to an unexplained earlier onset and increased incidence of aging-associated conditions like sarcopenia. Complex syndromes, like sarcopenia, often arise from a combination of genetic and environmental factors, so in this study, we investigated effects of short-term treatment with emtricitabine (2,3-dideoxy-5-fluoro-3-thiacytidine; FTC), an FDA approved ART, on skeletal muscle DNA methylation patterns and transcriptome-wide responses in a male murine model of HIV phenotypic biology (Tg26 mice). MethodsWe treated 6 month old male Tg26 (+/-) mice or wildtype (WT) littermates on a C57BL/6 genetic background with FTC in the drinking water for one month; control groups received drinking water vehicle alone (VEH). Muscle function and body composition were measured longitudinally. Skeletal muscle methylation patterns, transcriptional changes, and histological features were quantified at sacrifice. ResultsAlthough neither gross structural nor functional muscle deficits were observed in this short-term study with ART usage, relative decreases in muscle endurance measured by hang time over the study were 2-fold more severe in the Tg26 as compared to WT mice (p=0.0453), and markers of myogenic cell maturation (Myf5, Myf6) were disrupted in the Tg26 HIV model as compared to WT littermates in a manner exacerbated by FTC treatment. Fat mass, measured by DXA, also tended (p=0.085) to be uniquely increased by FTC treatment in the Tg26 mice over the study. Differential methylation patterns and pathway enrichment data suggested that the presence of an HIV phenotype and exposure to an ART regimen altered the methylation status in skeletal muscle genes such as Camk2B, Pcolce2 and Lima1 in a manner consistent with promoting eventual functional impairment in muscle. Additionally, RNAseq revealed differential gene expression profiles and key regulatory pathways including cellular differentiation, regulation of lipid metabolism, and neuroactive ligand-receptor interactions. Lipodystrophy-related genes including LEP, ADIPOQ and PPAR involved in fat distribution and metabolism along with skeletal genes related to regulation of muscle strength were affected by the presence of an HIV phenotype and ART treatment. ConclusionsThe current study provides insights into mechanisms by which a clinically relevant ART may influence DNA methylation and transcriptome changes in skeletal muscle in the context of HIV biology. The differentially regulated pathways suggest novel targets for understanding, and eventually abrogating, the harmful effects of long-term ART use in PLWH on skeletal muscle mass and function.

cell biology↗

bioRxiv2025

From spark to wildfire: illuminating single-cell origins of virus infection spread and diversification

When a virus encounters a living cell it triggers infection, cell death, and the release of virus progeny. In lab cultures, such progeny spread to near and distant cells, creating a plaque, a visible record of virus growth and cell death. Plaque-based assays have long enabled amplification and quantification of virus particles, but the earliest infections of a plaque remain poorly characterized. Here, we used a recombinant rhinovirus expressing a fluorescent reporter protein to track the start and spread of infection across HeLa cell monolayers at single-cell resolution. We analyzed reporter expression profiles from eight plaques and over 150 cells, reviewing, testing and applying methods of time-series analysis, clustering, and dimensionality reduction. We identified primary infections based on early reporter expression in isolated cells and secondary infections among their neighbors. Primary infected cells exhibited tightly clustered gene expression profiles, while secondary infected cells showed broader heterogeneity in the timing, intensity, and duration of reporter expression, without correspondence to their associated primary cells. This heterogeneity likely reflects a combination of factors, including noisy gene expression, viral genetic changes, and variation in local cellular environments. The rapid diversification of gene expression highlights the power of single-cell imaging to shed light on infection spread.

bioengineering↗

bioRxiv2025

An antifungal with a novel mechanism of action discovered via resistance gene-guided genome mining

Invasive fungal infections claim over two million lives annually, a problem exacerbated by rising resistance to current antifungal treatments and an increasing population of immunocompromised individuals. Despite this, antifungal drug development has stagnated, with few novel agents and fewer novel targets explored in recent decades. Here, we validate acetolactate synthase (ALS), an enzyme critical for branched-chain amino acid biosynthesis and absent in humans, as a promising target for new therapeutics. Using resistance gene-guided genome mining, we discovered a biosynthetic gene cluster in Aspergillus terreus encoding HB-35018 (1), a novel spiro-cis-decalin tetramic acid that potently inhibits ALS. Biochemical and antifungal assays demonstrate that 1 surpasses existing ALS inhibitors in efficacy against Aspergillus fumigatus and other pathogenic fungi. Structural studies via cryo-electron microscopy reveal a unique covalent binding interaction between compound 1 and ALS, distinct from known inhibitors and finally, we demonstrate that ALS is essential for the virulence in a mouse model of invasive aspergillosis. These findings position ALS as a promising target for antifungal development and demonstrate the potential of resistance gene-guided genome mining for antifungal discovery.

bioengineering↗

bioRxiv2025

Transfer Learning for Survival-based Clustering of Predictors with an Application to TP53 Mutation Annotation

TP53 is the most frequently mutated gene in human cancers, and germline mutations in TP53 cause Li-Fraumeni syndrome (LFS), a hereditary predisposition to diverse cancers. Accurate annotation of TP53 mutations based on their survival effects is critical for informed LFS patient management. Motivated by this need, we develop a new approach for Survival-based Clustering of Predictors (SCP) by identifying homogeneous coefficients in Cox regression. We formulate this task as a fusionpenalized Cox regression problem and provide an efficient computational algorithm. A nonconvex distance-to-set penalty is adopted to facilitate parameter tuning and improve estimation accuracy. To overcome data limitations, we further develop TLSCP, a transfer learning extension that borrows coefficient ranking information from a source dataset under the assumption of similar ranking patterns between source and target. TL-SCP integrates ranking information through weighted rank averaging, allowing flexibility in accommodating cohort heterogeneity while maintaining model simplicity. Simulation studies demonstrate TL-SCPs superior performance over SCP in clustering recovery and coefficient estimation. In the application of TP53 mutation annotation where we utilize non-LFS germline TP53 mutation carriers as a source cohort for the target LFS cohort, TL-SCP identifies biologically meaningful TP53 mutation clusters and offers improved clinical interpretability compared to experiment-based annotations.

genetics↗

bioRxiv2025

Divergent Strategies of Mycorrhiza-Mediated Drought Adaptation in Poplar

Mycorrhizal symbiosis shapes plant growth and stress resilience. Here, we compared physiological and molecular responses of poplars colonized by Paxillus involutus (Pi) or Cenococcum geophilum (Cg) under control conditions, drought stress, and recovery. Both fungal species primed distinct local (root) and systemic (leaf) defenses compared to non-inoculated (Ni) plants. Cg-colonized poplars exhibited constitutively elevated transcripts of heat shock proteins (HSPs), galactinol synthase, and aquaporins in roots and leaves, irrespective of drought. Pi colonization enhanced growth and nitrogen-use-efficiency along with transcriptional increases of TOR/RAPTOR complex. Under severe soil moisture decline, Pi and Ni poplars showed reduced water potential, photosynthesis, growth, and leaf shedding, whereas Cg-colonized plants maintained water status, sustained photosynthesis, and retained foliage. These results reveal two contrasting mycorrhiza-mediated drought strategies in poplar: Pi fosters stress acclimation via drought-induced leaf abscission, enabling rapid recovery; Cg suppresses growth even without stress, conferring constitutive tolerance. Ectomycorrhizal species thus occupy different positions on the growth- defense trade-off spectrum. Such species-specific effects have important ecological and applied implications, enabling targeted use of EM fungi in forestry and agriculture depending on whether maximizing productivity or enhancing stress resilience is the primary goal.

plant biology↗

bioRxiv2025

Evolutionary patterns and repeated adaptive strategies of deep-sea anemones

Sea anemones occupy the full depth of the oceans, yet their evolutionary patterns and adaptive strategies to the enigmatic deep sea have remained contentious and poorly resolved. Here, we assemble genomes (n = 13) and transcriptomes for 15 species collected between 432 and 6,000 m and integrate them with all publicly available actiniarian data. Phylogenomic analyses reveal a mosaic topology among deep-sea and shallow-water clades. Using a novel framework that contrasts convergent gene-loss patterns, we show that a large number of light-associated gene families-- including the complete circadian toolkit--were independently deleted after lineages entered the aphotic realm, whereas comparable loss in shallow taxa is negligible, providing decisive support for a shallow-water origin followed by multiple descents. Intriguingly, some deep-sea lineages further streamline energy budgets by recurrent loss or pseudogenisation of key meiotic genes (e.g., Meiosin, Ythdc2, Spo11, Rad21, Mlh3), indicating a shift towards asexual reproduction. Despite this extensive genomic erosion, deep-sea anemones exhibit sophisticated molecular tuning: specific amino-acid substitutions enhance protein stability and activity under deep-sea conditions, while selective expansions of gene families related to neural excitability, membrane systems, etc., likely mitigate the suppressive environmental effects on vital physiological processes. Enzyme activity assays in the yeast system confirm that the deep-sea variants exhibit superior activity and enhanced growth at 4{degrees}C. These results define a "loss-optimization-innovation" triad that underlies bathymetric adaptations and may apply to other deep-sea fauna worldwide.

evolutionary biology↗

bioRxiv2025

BIN1 deficiency leads to DNA damage and neuronal insulin resistance through ATM dysregulation

The major neuronal isoform of the AD risk gene BIN1 is specifically reduced in patients. In the present work, we demonstrate that BIN1 is necessary for intact insulin signaling and its loss leads to cellular-level insulin resistance. Persistently activated mTORC1 feedback inhibits the insulin signaling; meanwhile, ATM-dependent DNA Damage Response decreases the expression of multiple insulin signaling pathway members. Unexpectedly, nuclear ATM activation is accompanied by autophagic degradation of the cytoplasmic ATM, rendering neurons susceptible to oxidative stress, which predisposes oxidative DNA damage, DNA strand breaks, and ATM-dependent DNA Damage Response. Treating BIN1-deficient mice with rapamycin or liraglutide to improve the insulin response, or with the natural antioxidant alpha-lipoic acid to attenuate oxidative stress, both effectively preserved the spatial cognitive ability. Lastly, we reanalyzed a single-cell transcriptomic dataset from human neurons and identified positive correlations between levels of BIN1 and the insulin signaling, as well as neuronal activity. Together, this work revealed an ATM-centered mechanism that globally damages neuronal health in BIN1-deficient pyramidal neurons, which could be a driving force in the AD disease course.

cell biology↗

bioRxiv2025

SARS-CoV-2 S protein activates the HIV latent reservoir through the mTOR pathway

During the global COVID-19 pandemic, mRNA vaccines using the S protein as antigen were widely used.Vaccine-induced S proteins can persist in vivo for weeks, triggering low-level immune activation. HIV latent reservoir maintenance is a major challenge for ART therapy, especially when immune pressure is waning. This then raises critical questions for HIV-infected patients: does prolonged exposure to S proteins affect HIV latent reservoir stability? Recent studies have pointed out that S proteins may activate the mTOR signaling pathway, which in turn affects the immune response and metabolic processes of cells. And the mTOR pathway is closely related to the maintenance and activation of HIV latent reservoir. However, how S proteins affect the HIV latent reservoir and the mechanism of activation are unclear. To explore the mechanism of how SARS-CoV-2 S proteins regulate the HIV latent reservoir and to explore whether S proteins regulate the HIV latent reservoir through the mTOR pathway, we constructed an in vitro HIV latent reservoir model for our experiments.To evaluate the potential role of S protein in HIV latent reservoir activation, relevant markers of HIV latent reservoir activation were detected using ELISA, flow cytometry, and RT-qPCR; and the relationship between S protein and mTOR was also detected by WB, CO-IP, and IFC.It was found that S proteins activated the HIV latent reservoir while increasing mTOR expression. It was further observed that mTOR inhibitors significantly inhibited S protein-induced activation of the HIV latent reservoir, and mTOR activators reversed the inhibitory effect of mTOR inhibitors on HIV latent reservoir activation. In summary, we found that S proteins activated the HIV latent reservoir through the mTOR pathway. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/670887v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@f6d87aorg.highwire.dtl.DTLVardef@1fe4cc0org.highwire.dtl.DTLVardef@60eefeorg.highwire.dtl.DTLVardef@1ea9a34_HPS_FORMAT_FIGEXP M_FIG S protein interacts with mTOR and activates the mTOR-p-p70S6K-pS6 pathway, which promotes HIV transcription C_FIG

immunology↗

bioRxiv2025

MoCETSE: A mixture-of-convolutional experts and transformer-based model for predicting Gram-negative bacterial secreted effectors

Identifying effector proteins of Gram-negative bacterial secretion systems is crucial for understanding their pathogenic mechanisms and guiding antimicrobial strategies. However, existing studies often directly rely on the outputs of protein language models for learning, which may lead to difficulties in accurately recognizing complex sequence features and long-range dependencies, thereby affecting prediction performance. In this study, we propose a deep learning model named MoCETSE to predict Gram-negative bacterial effector proteins. Specifically, MoCETSE first uses the pre-trained protein language model ESM-1b to transform raw amino acid sequences into context-aware vector representations. Then, by employing a target preprocessing network based on a mixture of convolutional experts, multiple sets of convolutional kernel "experts" process the data in parallel to separately learn local motifs and short-range dependencies as well as broader contextual information, generating more expressive sequence representations. In the transformer module, MoCETSE incorporates relative positional encoding to explicitly model the relative distances between residues, enabling the attention mechanism to precisely recognize the sequential relationships and long-range functional dependencies among amino acids, thereby achieving high-accuracy prediction of secreted effectors. MoCETSE has demonstrated outstanding predictive ability in 5-fold cross-validation and independent testing. Benchmark test shows that the performance of MoCETSE surpasses existing excellent binary and multi-class classifiers. Author SummaryGram-negative bacteria inject effector proteins into host cells via secretion systems, disrupting normal cellular functions and inducing diseases. Accurately identifying these virulent proteins is key to understanding bacterial pathogenic mechanisms and developing therapies. However, existing methods face issues like feature redundancy, inadequate capture of long-range dependent signals, and low computational efficiency. We developed MoCETSE, a novel computational method enabling end-to-end intelligent prediction of effector proteins from raw sequences. Due to the high computational cost of position-specific scoring matrix encoding, we use pre-trained protein language models to extract structural, evolutionary, and functional features from sequences, providing biologically meaningful inputs for subsequent deep learning models. Our hybrid convolutional expert network reduces dimensionality of high-dimensional embeddings and extracts multi-scale features, effectively overcoming feature redundancy and information loss, and improving model performance and efficiency. In learning secretion signal features, relative positional encoding models amino acid order, capturing critical long-range dependent signals, and enhancing the biological interpretability of predictions. MoCETSE outperforms existing tools like DeepSecE in cross-category predictions, offering a high-throughput method for effector protein prediction and clues for studying bacterial infections and developing therapies.

bioinformatics↗

bioRxiv2025

Exploring chemotaxis in spatio-temporal stoichiometric models of metabolism: Pseudomonas simiae as a case study

Summary/AbstractChemotaxis is the movement of cells or organisms in the direction of an increasing or decreasing gradient of a chemical, i.e. a chemoattractant or chemorepellent, respectively. In bacteria, this movement is typically manifested through the presence of bias in the random walk generated by run-and-tumble motility. Often, the chemoattractant is consumed by the organism, thus coupling the biophysical, directed motion with the biochemical, metabolic activity in the growing bacterial colony. In this chapter, we describe our approach to simulating chemotaxis, coupled with detailed metabolic activity, within the framework of our modeling software COMETS (Computation of Microbial Ecosystem in Time and Space). By combining genome-scale metabolic models, dynamic flux balance analysis and the newly implemented biophysical chemotaxis model, we built and qualitatively tested a chemotaxis module for COMETS. We applied this model to an automatically constructed genome-scale model of the plant commensal bacterium Pseudomonas simiae WCS417, which we hypothesized would perform chemotaxis on amino acids similar to its close relative Pseudomonas putida. COMETS simulations recapitulated the typical ring colony pattern, which is due to propagation at the colony front, indicative of bacteria growing on a chemoattractant-filled plate. By allowing for detailed examination of spatial distributions and time dynamics of the biomass, as well as concentration profiles of the metabolites involved in the growth and chemotaxis in bacterial colonies, the software method described here enables simulations of complex microbial patterns involving metabolism and directed motility. Beyond testing the appearance of the ring, future model validation could include comparisons of local growth rates and metabolic fluxes, including rates of metabolite uptake and secretion. The newly added COMETS chemotaxis capability integrates flux balance modeling with gradient-induced biomass propagation, paving the way for more realistic simulations of microbial ecosystem dynamics in complex environments, such as plant roots, where chemotaxis may play a fundamental role in microbiome-host dynamics.

systems biology↗

bioRxiv2025

Small molecule intervention of actin-binding protein profilin1 reduces tumor angiogenesis in renal cell carcinoma

Angiogenesis plays a key role in the development and progression of renal cell carcinoma (RCC). Actin-binding protein profilin-1 (Pfn1) is overexpressed in clear cell RCC predominantly in tumor-associated vascular endothelial cells (ECs). We previously demonstrated that that EC-selective (over)expression of Pfn1 accelerates RCC progression, and conversely, genetic loss of EC-Pfn1 dramatically inhibits tumor angiogenesis impeding tumor initiation and/or progression in RCC, suggesting that Pfn1 could be an actionable therapeutic target in RCC. In this study, we demonstrate that 4,4-((4-bromophenyl)methylene)bis(3,5-dimethyl-1H-pyrazole), a small molecule that we had previously identified as an inhibitor of Pfn1-actin interaction, directly binds to Pfn1 and attenuates tumor angiogenesis when directly administered into subcutaneous RCC tumors. Next, we undertook a chemical optimization approach to design and synthesize 4,4-((4-(trifluoromethyl)phenyl)methylene)bis(3,5-dimethyl-1H-pyrazole), a structural analog of our originally identified inhibitor, that exhibits improved anti-angiogenic efficacy in vitro and in vivo. Finally, we demonstrate that Pfn1 inhibitor is amenable to lipid microbubble encapsulation and release in the tumor microenvironment (TME) by ultrasound-mediated disruption of circulating microbubbles to achieve anti-angiogenic and anti-tumor benefit. In summary, our findings suggest that tumor-localized release of Pfn1 inhibitor could be a potential therapeutic strategy in RCC.

cell biology↗

bioRxiv2025

A T-cell Intrinsic Role for APOL1 Risk Alleles in Allograft Rejection

African Americans have an increased risk of kidney disease due to exonic variants in Apolipoprotein-L1 (G1 and G2). These prevalent variants have also been linked with kidney rejection, but outside of association with African ancestry, underpinning causal mechanisms are unknown. We investigated T-cell function using transgenic mice with physiologic expression of wild type (G0-), G1-, or G2-APOL1. Mice with variant APOL1 showed greater CD8+T-cell activation with expansion of a central memory (TCM) subset. Stimulated G1-CD8+T-cells showed enhanced proliferation and cytokine production, which reversed with APOL1 inhibition. In MHC-mismatched cardiac transplants, G1-mice demonstrated greater CD8+T-cell infiltration and reduced survival. Bulk transcriptome of G1-CD8+T-cells, and single-cell transcriptome of graft infiltrating TCMs, showed enrichment of canonical T-cell receptor (TCR) pathways including Ca2+-signaling. G1-CD8+T-cells demonstrated baseline ER-Ca2+ depletion followed by sustained increases in cytosolic-Ca2+ upon TCR stimulation. G1-CD8+T-cells were more sensitive to Ca2+ chelation, or store-operated Ca2+ entry inhibition, and relatively resistant to calcineurin antagonism vs. G0-CD8+T-cells. Analogously, in a kidney transplant cohort, APOL1-variant recipients developed rejection when they had elevated peripheral TCMs before transplantation and despite significantly higher tacrolimus levels vs G0/G0-AAs with rejection. In summary, we unravel an excitatory T-cell intrinsic mechanism for APOL1 exonic variants, causally linking them with kidney rejection.

immunology↗