Biology subjects

Fang, C.

Publications and source records attributed to Fang, C..

At least 19 recordsLinked to original sources

bioRxiv2026

One-Entry Golden Seamless Cloning with a Reusable Donor Streamlines Plant Gene Functional Analysis

Molecular cloning underpins functional genomics, yet current toolboxes force a trade-off. Golden Gate frameworks handle one-pot multi-fragment assembly but overcomplicate routine single-gene cloning, whereas Gibson, In-Fusion, and Gateway systems need backbone linearization, resequencing, or proprietary recombinases that leave scars. Here we present Golden Seamless (GS), a one-entry, many-destination system in which a single PCR captures a gene once into a reusable Entry-and-Expression Clone that is never re-cloned. Circle-to-circle Golden Gate moves the same validated clone into plant, yeast, or bacterial vectors without linearization, and a ccdB counter-selection with orthogonal antibiotic markers drives background near zero. Bacterial destinations embed superfolder GFP, enabling naked-eye monitoring of recombinant proteins and an antibody-free dual-modality EMSA that resolves protein and DNA channels across a >150-nm spectral gap. GS thus consolidates capture, distribution, and validation into one low-background workflow with built-in quality control, cutting the time and cost of screening many candidates across functional assays.

molecular biology↗

bioRxiv2026

A closed-loop language-model agent for target-specific multi-objective hit-to-lead optimization

Hit-to-lead optimization is a multi-objective molecular-design problem in which binding-related scores must be considered together with drug-likeness and synthetic accessibility. We developed a closed-loop language-model medicinal-chemistry agent that combines target and starting-hit context, PubMed retrieval, molecular-property tools, docking, and feedback from previously scored analogues. In a matched computational benchmark comprising six kinase targets, six methods, a 40-candidate budget, and six independent campaigns per method, the agent achieved the highest mean aggregate score under a pre-specified composite objective on four targets. Re-analysis of the same candidate sets with drug-likeness-gated docking and docking-drug-likeness hypervolume produced different target-level winners, showing that evaluation rules can change the comparative interpretation of an optimization campaign. Candidate distributions and component ablations indicated that the agent's advantage was associated primarily with retention of scored-candidate feedback and higher-QED regions rather than with docking alone. An EGFR case study illustrates a scaffold-preserving in-silico optimization trajectory from erlotinib. The study is a computational benchmark and evaluation framework; the prioritized molecules are hypotheses for subsequent experimental testing, not experimentally validated leads.

bioinformatics↗

bioRxiv2026

Speciesformer learns conserved cellular states for cross-species generative virtual cell modeling

Cells across species are governed by evolutionarily conserved biological programs, yet their molecular states and responses are reshaped by species, tissue and cellular context. A central challenge for virtual cell modeling is therefore to learn cellular states and state transitions that separate transferable biological principles from context-specific variation. Existing single-cell foundation models have advanced cellular representation learning, but most remain focused on single-species analysis, discriminative tasks or specialized forms of generation. Here we present Speciesformer, a cross-species generative single-cell foundation model that integrates evolutionary representation learning with virtual cell-state generation. Speciesformer is pretrained on SpeciesCorpus, comprising 131 million cells from 11 species, 154 tissues, and more than 923 cell types, and maps species-specific genes into a shared evolution-informed gene space. Its encoder learns transferable cell and gene representations that support biological representation probing and cross-species knowledge transfer, providing a common state space for resolving conserved and context-dependent cellular programs. Building on this shared representation, Speciesformer uses a unified generative architecture to model cellular states and state transitions under semantic and interventional conditions, enabling bidirectional generation between transcriptomic states and biological text descriptions, as well as prediction of post-perturbation transcriptomes from initial cell states and intervention descriptions, including in previously unobserved cellular contexts. By unifying evolutionary variation, biological semantics and conditional state transitions, Speciesformer extends cross-species foundation modeling toward a generative virtual cell framework for representing, describing and predicting cellular states across biological contexts.

systems biology↗

bioRxiv2026

Model Validation Protocols for Machine Learning in Small Molecule Drug Discovery

Machine learning (ML) models for molecular property prediction are increasingly deployed in drug discovery, yet their adoption in real-world scenarios requires an understanding of the conditions in which a model succeeds or fails. While standardized benchmarks are powerful instruments to measure and unlock progress in ML research, they should not be blindly treated as the end goal. Especially static and retrospective benchmarks, in which no true unknown test set is employed, limit our ability to robustly validate a model's performance. Building on the collective expertise of a cross-industry consortium, we present a model validation framework consisting of five recommendations that would enable the community to move beyond aggregate metrics toward understanding where and why molecular property prediction models fail. We connect evaluation choices to real-world applications and case studies encountered in pharmaceutical research. The framework proposes splitting strategies that mimic realistic distribution shifts and expose common failure modes. We apply the recommended framework to a recently released dataset of absorption, distribution, metabolism, and excretion (ADME) properties. Across two complementary model algorithms, our case studies reveal four distinct failure modes (extrapolation, interpolation, representation, and evaluation), showing that model errors arise not only from distribution shift but also from limitations in molecular representations. Our results show that commonly used evaluation protocols can significantly overestimate performance and may not detect important model failure modes. All software and data are released via https://github.com/srijitseal/polaris.

bioinformatics↗

bioRxiv2026

Fat body CLOCK restrains innate immunity and maintains survival under dietary stress in Drosophila

Both aging and a high-fat diet (HFD) dampen circadian gene transcription rhythms and promote chronic inflammation. How aging and HFD interact to affect peripheral molecular clocks and circadian behavior remains unclear. Using Drosophila melanogaster, we showed that aging and HFD additively dampened circadian behavior, with their adverse effects converging on the fat body (FB), a tissue that regulates systemic metabolism and innate immunity. Applying longitudinal in vivo bioluminescence recording in small, genetically defined cell populations, we found that molecular clocks in the FB were uniquely vulnerable to aging- and HFD-induced dampening of rhythm amplitude, whereas those in the clock neurons declined with age but were resistant to dietary stress. To test the consequences of this FB clock decline, we disrupted individual components of the core molecular clock specifically in the FB. We found that only CLOCK (CLK) disruption shortened lifespan on HFD, whereas disrupting its binding partner CYCLE (CYC), or the repressors PERIOD and TIMELESS, did not. Furthermore, CLK, but not CYC, disruption upregulated antimicrobial peptide expression in the FB, dampened behavioral rhythms, and suppressed locomotor activity, even though both CLK and CYC disruption comparably dampened clock gene oscillation in the FB. Together, these results indicate that FB CLK has a unique role in suppressing pro-inflammatory signals independently of CYC. Our findings provide insight into how stressors such as aging and HFD selectively disrupt the peripheral metabolic clock, and into the distinct roles of individual clock components, with implications for age-related inflammation and metabolic disease.

molecular biology↗

bioRxiv2026

Engineering tumor-homing bacteria as membrane-anchored immune checkpoint-blockade interfaces

Bacterial cancer therapies can exploit tumor tropism to localize immunomodulatory payloads, but most approaches rely on secretion or lysis-dependent release of soluble biologics that may diffuse beyond the tumor niche. Here, we engineer non-pathogenic, tumor-homing Escherichia coli strains as membrane-anchored immunotherapeutic interfaces, with individual strains displaying immune checkpoint-blocking nanobodies targeting CTLA-4 or PD-L1, either alone or in combination with a separate strain displaying murine decoy-resistant IL-18 (mDR18). By screening multiple bacterial outer-membrane proteins as scaffolds, we identified scaffold-dependent differences in display levels and target engagement, and YiaT as a functional platform for checkpoint nanobody presentation. Delivery of YiaT-displayed nanobodies in combination with OmpA-displayed mDR18 suppressed tumor growth in syngeneic mouse colon cancer and melanoma models in either local or systemic delivery. Upon systemic administration, the combined bacterial therapy preferentially accumulated in tumors, outperformed benchmark checkpoint antibody regimens combining CTLA-4 and PD-L1 under the tested conditions, and promoted tumor rejection and rechallenge resistance, without inducing broad systemic cytokine release. Further immune profiling showed that the combined treatment was associated with increased CD8 and effector-memory T-cell responses in tumors and spleens. This work establishes bacterial surface display as a modular strategy for localized cancer immunotherapy.

Synthetic Biology↗

bioRxiv2026

Perturbation of genes linked to common schizophrenia risk variants identifies cilia programs

Schizophrenia (SCZ) is a common psychiatric disorder characterized by psychosis, emotional withdrawal, and cognitive deficits. Most SCZ risk variants reside in non-coding regions of the genome and are thought to influence disease risk by modulating gene regulation. However, the target genes, biological pathways, and cell types through which these variants exert their effects remain poorly understood. To address this gap, we employed in vivo CRISPR droplet sequencing (CROP-seq) in the postnatal mouse neocortex. We perturbed 12 SCZ risk genes previously linked to functionally validated risk variants, followed by single-cell RNA sequencing. We identified 3,031 differentially expressed genes (DEGs) that recapitulate transcriptional alterations observed in postmortem SCZ brains. Integrative analysis using DEG clustering, factor analysis, and gene regulatory network inference uncovered convergent gene programs with distinct biological functions and cell type specificity. Notably, ciliary transcriptional programs consistently emerged across analytical frameworks. The primary cilium is a neurocircuit modulating signaling organelle in neurons and glia that remains understudied in SCZ. Perturbation of key contributors to the ciliary transcriptional programs led to significant alterations in ciliary structure, suggesting that SCZ genetic risk factors may influence how brain cells sense and transduce extracellular signals through synapse-independent mechanisms. Together, this study provides the first in vivo characterization of the functional consequence of common variant architecture in SCZ and implicates ciliary dysfunction as a convergent downstream mechanism.

neuroscience↗

bioRxiv2026

Discovery of ARQ-501 as a potent PafA inhibitor that elevates KatG levels to potentiate isoniazid in mycobacteria

The prokaryotic ubiquitin-like protein (Pup) conjugation system (PPS), which is essential for Mycobacterium tuberculosis (Mtb) virulence but absent in humans, presents an attractive drug target. Here, we report the discovery of ARQ-501, a quinone-based, covalent, substrate-competitive inhibitor of the Pup ligase PafA. ARQ-501 exhibited potent anti-mycobacterial activity against Mtb under host-mimicking stress conditions and within macrophages. We further identified the catalase-peroxidase KatG, essential for activation of the frontline prodrug isoniazid (INH), as a pupylation substrate. ARQ-501 inhibits KatG pupylation, causing its accumulation and creating a selective synergy with INH. This quantity over quality mechanism successfully rescued INH activation by the clinically prevalent KatG S315T mutant in enzymatic assays and enhanced INH efficacy against clinical S315T isolates to variable degrees. This work identifies a novel class of PafA inhibitors and a previously unrecognized role of pupylation in regulating KatG, offering a potential therapeutic avenue to combat drug-resistant tuberculosis.

microbiology↗

bioRxiv2026

Molecular evolution of baculovirus IE1 protein, an essential multi-functional regulator of transcription and replication

Immediate-early protein IE1 is an essential protein of baculoviruses that is involved in transcription and replication. In the present study, we provide several lines of evidence for how ancient IE1 evolved into its current version. Using progressive truncations and site-directed mutations coupled with fluorescence microscopy, surprisingly, we showed that the previously identified nuclear localization sequence (NLS), basic domain II, was essential for sequence non-specific DNA binding, but not required for IE1 nuclear import, and demonstrated that, BmNPV IE1 (BmIE1) possesses not only a unique bipartite NLS that contains a monopartite NLS but also a cryptic non-canonical NLS that is correlated with sequence non-specific DNA binding. The non-canonical NLS alone was sufficient to launch infection. We also found that N-terminally truncated IE1 can enter the nucleus through its sequence non-specific binding ability. Remarkably, the monopartite NLS, when fused to the N-terminus of EGFP, can form a novel NLS that is also functional in a mammalian cell line. Moreover, residues 58 to 151 of BmIE1 were shown to be dispensable, and residue 152 was found to be critical for launching a productive infection. To gain insight into how ancient IE1 acquired its multi-functionality, we reorganized the N-terminal 23 aa and 132 aa of BmIE1 with EGFP in a variety of manners and found that both fragments are separable and transferable. Notably, we observed that the nuclear levels of BmIE1 should reach certain thresholds to initiate infection. Additionally, we found that BmNPV could launch infection more efficiently in a BmN cell line over another BmN cell line by increasing transcription levels of immediate early genes. Collectively, these findings suggest a hypothesis where ancient IE1 might have evolved the two additional NLSs and acquired the N-terminal 132 aa through gene fusion so as to reach infection-initiating thresholds at a faster pace. Author SummaryBasic domain II was previously shown to be the NLS of AcMNPV IE1 protein. In the present study, we demonstrated that it is essential for sequence non-specific DNA binding, but not required for IE1 nuclear import, and found that BmNPV IE1 (BmIE1) possesses not only a unique bipartite NLS that contains a monopartite NLS but also a cryptic non-canonical NLS that is correlated with sequence non-specific DNA binding. We also found that N-terminally truncated BmIE1 can enter the nucleus through its sequence non-specific binding ability. Remarkably, the monopartite NLS, when fused to the N-terminus of EGFP, can form a novel NLS that is also functional in a mammalian cell line. Moreover, the domains of BmIE1 was shown to be separable and transferable. We also demonstrated that higher expression of functionally impaired BmIE1 achieved by higher MOIs or higher transfection efficiency can partially complement its compromised functions. Consistently, we found that BmNPV could launch infection more efficiently in a BmN cell line over another BmN cell line by increasing transcription levels of immediate early genes.

microbiology↗

bioRxiv2026

Genos-m: a foundation model for human-associated microbial genomes

Human-associated microbial genomes encode extensive strain-level diversity and niche-specific gene repertoires that are critical to host health. However, these complex sequence features remain difficult to capture using general-purpose DNA foundation models, highlighting the need for dedicated representation learning tailored to the human microbiome. Here, we introduce Genos-m, an open-source foundation model for human-associated microbial genome representation. Genos-m was pretrained on approximately 1.2 trillion nucleotide tokens from a curated microbial genome corpus, including human-associated prokaryotic isolates, high-quality metagenome-assembled genomes (MAGs) and bacteriophages, supplemented with GTDB species-level representative genomes to broaden prokaryotic taxonomic breadth. The model uses a sparsely activated Mixture-of-Experts (MoE) Transformer architecture, with 4.7 billion total parameters, approximately 330 million activated parameters per forward pass and a maximum context length of one million base pairs. We evaluated frozen Genos-m representations across short-sequence and gene-level tasks, biosynthetic gene cluster (BGC)-based regional sequence tasks, whole-genome strain phenotype prediction, and zero-shot transfer on prokaryote-related RNAfitness assays. Across these benchmarks, Genos-m consistently ranked among the leading comparison models, with the best performance in five of eight gene-fitness regression tasks and in BGC type classification. Using sparse autoencoders, we identified sparse features in Genos-m hidden activations that aligned with annotated ORFs, intergenic regions, and tRNA and rRNA loci. In downstream applications, Genos-m-derived genome-informed species representations in-corporated into a human microbiome self-supervised learning model improved colorectal cancer (CRC)-control classification over conventional species-abundance random forest models. Genos-m also generated stable sample-level embeddings from as few as 10,000 metagenomic reads, retaining gut microbial community structure that distinguished geographic origin and aligned with enterotypes defined from full-depth taxonomic profiles. Together, these results support Genos-m as a reusable representation model for microbial genomes and metagenomes, with conclusions bounded by the reported datasets, task definitions and evaluation protocols. Genos-m model weights, inference code, and usage documentation are publicly available on GitHub (https://github.com/BGI-HangzhouAI/Genos-m) and Hugging-Face (https://huggingface.co/BGI-HangzhouAI/Genos-m).

bioinformatics↗

bioRxiv2026

EVEE: Interpretable variant effect prediction from genomic foundation model embeddings

Scientific foundation models learn high-dimensional representations from diverse data modalities, yet what they encode and how to extract that knowledge remain open questions. Here we show that probing the internal representations of Evo 2, a 7-billion-parameter genomic foundation model, enables accurate and interpretable genetic variant effect prediction. We introduce a covariance-based probe that captures second-order structure from Evo 2 sequence embeddings to predict variant pathogenicity across variant types and functional consequences, matching or exceeding specialized predictors within their domains. To ground these predictions in known biological mechanisms, we train a complementary panel of probes on existing annotations to detect which genomic properties are disrupted by a variant. This categorized evidence is then integrated with each variants genomic context through a language model to generate variant-specific mechanistic hypotheses. Our pathogenicity predictions correlate with experimental measures of variant function, clinical penetrance, and biobank disease associations while the mechanistic hypotheses are consistent with expert reviews, known mechanism classes, and downstream molecular readouts. We release pathogenicity scores, disruption profiles, and contextualized interpretations for 4.2 million variants from the ClinVar database as an open resource through the Evo Variant Effect Explorer (EVEE). More broadly, this structured probing approach offers a general framework for interrogating foundation models across scientific disciplines and grounding their outputs in existing domain concepts.

genomics↗

bioRxiv2026

Transposable element disruption of a second thyroglobulin-like gene confers Vip3Aa resistance in Helicoverpa armigera

BackgroundThe cotton bollworm Helicoverpa armigera is a major global pest controlled by genetically engineered crops expressing Bacillus thuringiensis (Bt) toxins, including Vip3Aa. While Vip3Aa is widely deployed, the genetic basis of resistance remains poorly understood. Previous work identified disruption of a thyroglobulin-like gene (HaVipR1) as one mechanism of resistance, suggesting additional loci may be involved. ResultsUsing linkage analysis, transcriptomics, long-read sequencing, and CRISPR-Cas9 gene editing, we identify a second thyroglobulin-like gene, HaVipR2, as a novel mediator of Vip3Aa resistance. Resistance in a field-derived H. armigera line was shown to be monogenic, recessive, and autosomal, mapping to chromosome 29. Long-read sequencing revealed a [~]16 kb transposable element insertion disrupting HaVipR2, which was undetectable using standard short-read approaches. CRISPR-Cas9 knockout of HaVipR2 conferred >900-fold resistance, confirming its causal role. Comparative analyses show that HaVipR1 and HaVipR2 share conserved domain architecture, indicating that thyroglobulin-domain proteins represent a recurrent target of resistance evolution. ConclusionsOur findings establish thyroglobulin-domain proteins as a new class of Bt resistance genes in Lepidoptera and demonstrate that transposable element insertions can drive adaptive resistance while evading detection by conventional methods. These results highlight the importance of long-read sequencing and accurate genome annotation for resistance monitoring and provide new insights into the molecular basis and evolution of Vip3Aa resistance.

genomics↗

bioRxiv2026

Gut microbiome-dependent IL-1 signaling is a mediator of ACVR1R206H-driven heterotopic ossification

Inflammatory diseases cause significant morbidity and mortality, but their pathobiology is often difficult to dissect due to complex genetic-environmental interactions. Genetic forms of heterotopic ossification, such as fibrodysplasia ossificans progressiva (FOP), reduce genetic variability, allowing careful dissection of non-genetic drivers of inflammation. While >95% of FOP patients harbor the ACVR1R206H mutation, patients exhibit significant variability in disease progression, suggesting a role of environmental drivers. Here, we identify the gut microbiome as a regulator of inflammation-driven HO in FOP. Metagenomic profiling of cohabitating FOP/unaffected sibling pairs revealed a pathogenic gut microbiome profile in FOP patients (Bray-Curtis, p < 0.05). In Pdgfr-Cre/Acvr1R206H (FOP) mice, gut microbiome ablation by antibiotics reduced spontaneous HO formation (47.4% reduction, p < 0.05) and reduced plasma IL-1 pathway activity. IL-1{beta} blockade in FOP mice suppressed trauma-induced HO formation. These findings identify a gut microbiome-IL-1-HO axis with modifiable targets for developing treatments for HO and related inflammatory conditions. One Sentence SummaryAntibiotic disruption of the gut microbiome reduces HO in FOP mice via an IL-1 mediated pathway.

immunology↗

bioRxiv2026

Engineered Lactate Catabolizing Probiotics Reveal Timescale Dependent Microbiome-Host Metabolic Coupling

The exchange of lactate, a metabolic substrate and regulator, between the gut lumen and systemic circulation for use in host and microbial processes is well documented, but tools capable of uncovering whether this process influences host metabolic status across acute and chronic contexts are lacking. In our prior work, we engineered probiotic Bacillus subtilis PY79 to produce lactate oxidase (LOX) intracellularly, allowing it to rapidly convert intestinal lactate to pyruvate. Following oral administration, LOX reduced systemic lactate concentrations at rest and under challenge conditions, providing a platform for investigating lactates influence on host metabolism and microbiota. In the present work, we demonstrate that acute LOX administration effectively rewired microbiota function and host energy balance, as revealed by 16S sequencing and indirect calorimetry. In silico microbial community modeling via MICOM and metagenomic inference via PICRUSt2 suggested that acute shunting of lactate to pyruvate induced microbiota remodeling towards anabolic processes, reflected by increased flux of pyruvate, acetate, and formate, alongside moderate to large increases (Cohens d = 0.60-1.00) in pathways for fructan degradation, B-vitamin biosynthesis, and lipid synthesis. These anabolic shifts temporally aligned with transient increases in host energy expenditure ({beta} = 1.08, p<0.05) via glucose oxidation ({beta} = 0.01, p<0.05), hinting at functional coupling between microbial biosynthesis and host energy balance via lactate exchange. Of note, acute LOX administration also improved thermoregulation and survival following LPS-induced sepsis, demonstrating functional relevance of these metabolic effects during acute inflammatory challenge. To assess chronic effects, we administered LOX for 6 weeks during diet-induced obesity. LOX treatment persistently reduced blood lactate. However, this chronic lactate reduction did not curtail the progression of diet-induced obesity or induce sustained modulation of host energy expenditure. This disconnect between acute and chronic findings suggests that gut-centric lactate conversion affects energy balance through microbiome and/or host-dependent mechanisms, but cannot override homeostatic forces in the long term to produce clinical benefit during chronic disease. Our results validate LOX probiotics as a tool for acute metabolic augmentation, and highlight a clear homeostatic limit to gut-centric therapies. This platform may enable targeted design of probiotic interventions matched to therapeutic timescale and inform synbiotic formulations that overcome homeostatic compensation.

microbiology↗

bioRxiv2026

Metagenomic Evidence for Horizontal Gene Transfer and Functional Convergence in the Oral Microbiome of Cohabiting Dogs and Owners

The intimate cohabitation between humans and their pets facilitates bidirectional microbial exchange, yet the extent and functional consequences of this transfer within the oral niche remain underexplored. Here, we employed metagenomic sequencing to characterize the oral microbiome of dogs and their owners across distinct geographic regions in China, integrating taxonomic, gene-centric, and functional analyses using public databases (BacMet, CARD, eggNOG, KEGG) to assess microbe-host associations. We found that dog-owner pairs exhibited significantly higher gene-level similarity compared to unrelated individuals, indicating a strong cohabitation-driven microbial linkage. While no major taxonomic shifts were observed in the human oral microbiome associated with pet ownership, we identified a marked enrichment of antibiotic resistance genes (ARGs)--particularly those conferring resistance to peptides, fluoroquinolones, antiseptics, diaminopyrimidines, cephalosporins, and carbapenems--in cohabiting pairs. This enrichment, together with the identification of exclusively shared ARGs (e.g., mdtF, macB, RanA), suggests the potential for horizontal gene transfer (HGT) between pet- and human-associated microbiomes. Functional profiling further revealed greater similarity in microbial metabolic pathways between cohabiting pairs than between unrelated individuals, reinforcing the likelihood of HGT as a mechanism underlying functional convergence. Collectively, these findings reveal that cohabitation with dogs reshapes the human oral microbiome at the genetic and functional levels, with potential implications for antimicrobial resistance transmission. This study provides a foundational framework for assessing the health risks associated with pet-human microbial exchange in shared living environments.

microbiology↗

bioRxiv2026

A synonymous mutation in MSMEG_4729 occurs at a high frequency in spontaneous D29-resistant mutants of Mycobacterium smegmatis

Compassionate use of mycobacteriophage therapy highlights the promising potential of phage therapy as an alternative treatment option for antibiotic-resistant infections when conventional treatments fail. However, realizing the full potential of phage therapy requires addressing key challenges, including host immune responses, the limited arsenal of therapeutically-useful mycobacteriophages, and the emergence of phage resistance. Dissecting the mechanisms of phage resistance is critical for ensuring the effectiveness and sustainability of phage therapy. In this study, we demonstrate that exposure to the lytic mycobacteriophage D29 triggers diverse genetic changes in Mycobacterium smegmatis. A synonymous mutation in MSMEG_4729 arises frequently but is insufficient to confer D29 resistance on its own. Instead, we identified possible Lsr2-independent activation of the lipooligosaccharide (LOS) biosynthesis cluster in a D29-resistant mutant harboring this mutation. We have also detected the possible activity of MSMEG_3213, a type II methyltransferase associated with m6A modifications in M. smegmatis. Finally, we isolated defense escape mutants (DEMs) of D29 capable of overcoming resistance in a strain with the MSMEG_4729 synonymous mutation. This profiling of M. smegmatiss likely defensive arsenal against the therapeutically-useful mycobacteriophage D29 provides a roadmap for further investigations and rational engineering of next-generation mycobacteriophages to combat drug-resistant mycobacterial infections. Impact statementInterest in phage therapy has been gaining traction recently, which is largely due to the serious threat of antimicrobial resistance. However, the efficacy and sustainability of phage therapy is threatened by certain challenges, which includes the ever existent threat of phage resistance. In this study, we identified several likely factors involved in D29 interaction with the model mycobacterium M. smegmatis. These findings set a roadmap for future investigations that would guide rational phage engineering to expand the currently limited arsenal of therapeutically useful mycobacteriophages as well as improve the efficiency of existing ones.

microbiology↗

bioRxiv2026

The enhanced multi-tissue atlas of regulatory effects in cattle

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype-Tissue Expression (CattleGTEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

genetics↗

bioRxiv2026

Hierarchical control of cardiomyocyte maturation and ischaemia sensitivity by metabolic culture conditions

Ischaemic heart disease remains the leading cause of mortality worldwide, yet no therapies prevent cardiomyocyte death during acute ischaemia-reperfusion injury (IRI). Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a platform for modelling cardiac injury, but their immature phenotype limits the physiological fidelity of in vitro models. Here, we systematically evaluated how experimental variables used during preparation of hiPSC-CM endpoint assays influence cardiomyocyte maturation and susceptibility to IRI. Integrating literature mining, molecular profiling, statistical genetics, and functional assays, we examined the effects of replating conditions, backbone media, metabolic substrates, and signalling modulators. We define the relationship between culture conditions and metabolic supplements in determining contractile maturation and sensitivity to IRI. Notably, we show that metabolic composition of the backbone medium establishes the baseline maturation state and determines responsiveness to additional maturation cues. These findings identify metabolic environment as a dominant regulator of injury susceptibility and provide a framework for improving the physiological fidelity of hiPSC-CM models of cardiac ischaemia.

cell biology↗