Biology subjects

Zeng, T.

Publications and source records attributed to Zeng, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Systematic mapping of enhancers, silencers, and topological elements with prime editing deletion screens

Noncoding regulatory elements in the human genome can control gene expression through distinct mechanisms, including acting as enhancers, silencers, or topological elements. However, we lack tools to identify all such classes systematically and quantify their effects on gene expression in an endogenous genomic context. Here we develop Swap-seq, a method that combines pooled twin prime editing with flow-sorting to delete hundreds of endogenous regulatory sequences and measure their quantitative effects on the expression of a nearby gene. We apply Swap-seq to dissect the regulatory elements that control PPIF expression in THP-1 monocytes. We quantify the effects of distal and intronic enhancers, characterize CTCF insulators, and discover a silencer that regulates distal genes through histone deacetylase (HDAC)-mediated repression of neighboring enhancers. Hundreds of other genomic elements share its chromatin signatures and transcription factor binding sites, suggesting that this silencer represents a broader class of repressive elements. We leverage Swap-seq data to benchmark sequence-to-function models and show that they often capture the local activity of regulatory elements but fail to link them to distal target genes. Swap-seq thus provides a generalizable tool to discover regulatory elements across mechanistic classes, characterize their effects on gene expression, and generate large-scale datasets for evaluating sequence-to-function models.

genomics↗

bioRxiv2026

Nod factor signaling controlled genes in Medicago truncatula nodules

O_LILegume nodule formation is induced by rhizobia secreted Nod factors (NFs). It has been shown that NF receptors also accumulate in the apex of Medicago truncatula nodules. However, the NF signaling induced transcriptional changes in there have never been studied. C_LIO_LIHere, we studied this by using NF signaling mutant TE7, a weak allele of IPD3, blocked in rhizobial release. Nodule apices were isolated with laser microdissection and used for transcriptional analysis. C_LIO_LIWe identified 1655 NF signaling controlled genes in nodule apex. By comparing this with the transcriptome data from VAMP721d&e RNAi nodule apices, we identified a subset of 445 genes whose expression depends on NF signaling and rhizobial release. Further, we compared the set of genes controlled by NF signaling in nodule apices with that controlled in root epidermis, and these showed only a small overlap. NIN is induced by NF signaling both in the root epidermis and in the nodule. By overexpression of NIN in TE7 and knock down of NIN in wildtype nodules we showed that NF signaling controlled rhizobial release depends on NIN. C_LIO_LINF signaling controls a distinct set of genes in nodules, the function of which depends at least in part on NIN. C_LI

Developmental Biology↗

bioRxiv2026

Widespread use of invalid statistical tests in biomedical machine learning

Cross-validation is routinely used to compare performance in biomedical artificial intelligence. Standard tests ignore correlation across cross-validation folds, inflating false-positive rates. In a PRISMA-guided meta-analysis of 184 studies (impact factor [≥] 15) across 30 biomedical fields, 97% use invalid tests. Among studies with abstract-level claims supported by invalid tests, 59% rely on a spurious comparison: one that loses significance after correcting for this correlation. On average, regaining significance requires a 43% larger effect. Extending these findings to the broader literature, we estimate that spurious comparisons occur in nearly two in three studies and support abstract-level claims in nearly one in three studies. Simulations confirm false-positive rates paradoxically approach 100% when cross-validation is repeated to improve stability. We introduce SHARP, a redesign of cross-validation, which best balances false-positive control and power among 13 benchmarked tests. These results reveal widespread fragility in biomedical artificial intelligence and offer a practical route to valid comparisons.

bioinformatics↗

bioRxiv2026

Complete genome-derived metabolic interactions reveal impact of gut ecology on human health

Metabolic interactions govern gut microbiome assembly, yet functional rules remain obscured by genomic incompleteness and fragmentation. Here, we leverage 1,150 complete genomes to construct genome-scale metabolic models, demonstrating that draft genomes introduce systemic artifacts missing critical transport functions. We observe that metabolic interactions are intrinsically driven by genomic traits and niche specialization rather than random association. We stratifies strains into four ecological groups, including active players, resource predators, utilizers, and contributors, each of which exhibits distinct metabolite exchange/competition signatures. This functional architecture is strongly coupled to secondary metabolism. Applying this framework to inflammatory bowel disease revealed distinct temporal dynamics of ecological groups across disease subtypes, where group-specific dysbiosis predicted clinical phenotypes better than whole community profiles. Furthermore, integrating metabolic and co-occurrence networks to identify keystone for classifiers as features significantly improved disease diagnosis. Our study provides novel insights into gut metabolic interaction landscape, bridging the gap between genomic potential and clinical utility for precision microbiome therapeutics.

microbiology↗

bioRxiv2026

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

bioRxiv2026

The genetic repertoire of the deep sea: from sequence to structure and function

The deep sea as the largest and maybe most hostile environment on Earth is still underexplored especially regarding its genetic repertoire. Yet, previous work has revealed significant habitat-specific deep-sea biodiversity. Here, we present an integrated deep-sea genetic dataset comprising 502 million nonredundant genes from 2,138 samples and 2.4 million predicted structures, and used it to link specific protein structures with genetic variants associated with life in the deep sea and to assess their biotechnology potential. Combining global sequence analysis with biophysical and biochemical measurements revealed unprecedented sequence diversity, yet substantial structural conservation of proteins. Especially proteins involved in replication, recombination, and repair were identified to be under rapid evolution and with specialized properties. Among these, a structurally divergent helicase exhibited advantages in controlling nanopore sequencing speed. Thus, our work positions the deep sea as a unique evolutionary engine that generates and hosts genetic diversity and bridges genetic knowledge with biotechnology.

bioinformatics↗

bioRxiv2025

NanoporeDB: A Structural Resource Of Multimeric Protein Nanopores In Single-Molecule Sensing

Protein nanopores are essential molecular gateways in biology and have inspired transformative technologies in biosensing and single-molecule sequencing. While this technology has transformed genomics and biosensing, the discovery of novel nanopore scaffolds remains limited due to the scarcity of experimentally resolved pore structures. Here, we present NanoporeDB, an open-access structural resource comprising over 6,600 high-confidence multimeric models across four representative pore types. Candidate proteins were systematically mined from large-scale datasets, including the AlphaFold Protein Structure Database, UniRef90, and MGnify90, and assembled using AlphaFold-Multimer and AlphaFold3. We performed membrane embedding, pore axis annotation, and constriction profiling to enable functional interpretation. NanoporeDB features an interactive web interface with 3D visualization and quantitative metrics such as insertion depth, tilt angle, and pore geometry. This resource provides a structural foundation for advancing nanopore-based molecular sensing, precision diagnostics, and synthetic biology.

bioinformatics↗

bioRxiv2025

Single-Cell Multi-Omics Dissects Transcript Isoform and Immune Repertoire Dynamics in Human Immunosenescence

Immunosenescence, a major hallmark of systemic aging, refers to the progressive functional decline of the immune system. This decline not only compromises host defense and immunological memory but also fuels chronic inflammation and tissue degeneration (collectively known as inflammaging). While single-cell RNA sequencing (scRNA-seq) has revealed transcriptomic alterations in immune aging, analyses restricted to transcript abundance fail to capture deeper regulatory layers, such as transcript isoform diversity and the remodeling of immune receptor repertoires. To address this, we present the human peripheral immune single-cell multi-omics atlas that integrates gene expression, transcript isoforms diversity, and immune receptor repertoires. By combining single-cell full-length transcriptome sequencing (scCycloneSEQ), short-read scRNA-seq, and single-cell immune receptor sequencing (scTCR/BCR-seq), we systematically profiled peripheral blood mononuclear cells (PBMCs) from healthy young and elderly donors. Our analyses uncovered extensive age-related remodeling of immune cell composition, functional states, and TCR/BCR diversity. Notably, we identified in CD4 effector memory T cells exhibited widespread differential isoform usage (DIU), 3'UTR length variation, and a marked reshaping of cytotoxic T lymphocyte (CTL) clonotypes--all closely associated with aging-related inflammation and cellular senescence. This multi-omics atlas delineates key molecular features of immunosenescence and provides a high-resolution resource for deciphering the regulatory architecture underlying immune aging.

immunology↗

bioRxiv2025

DR5 CAR-T cells target solid tumors and suppress MDSCs with minimal toxicity

Chimeric antigen receptor (CAR) T cell therapies have poor efficacy in solid tumors due to limited target specificity and an immunosuppressive tumor microenvironment. We investigated death receptor 5 (DR5) as a CAR target based on its high expression in both solid tumors and myeloid- derived suppressor cells (MDSCs). We engineered agonistic DR5-specific CAR constructs and evaluated their activity in multiple models, demonstrating DR5-expression-dependent tumor killing, confirmed by knockout and overexpression experiments. DR5-targeting single-chain variable fragments retained their pro-apoptotic activity when expressed on non-effector cells or extracellular vesicles. Among multiple CAR designs, we identified a construct with optimized binding affinity that maintained T cell viability while preserving strong tumor and MDSC-killing potency. To assess safety and efficacy in an immunocompetent setting, we also developed a murine DR5-targeted CAR. In multiple xenograft and syngeneic mouse models, DR5 CAR-T cells reduced tumor growth, prolonged survival, and did not cause detectable toxicity. In patient- derived organoids and tissue slices, DR5 CAR-T cells infiltrated tumor tissues, reduced MDSCs, boosted CD8+ T cell activity, and inhibited tumor growth. These findings support DR5-targeted CAR-T therapy as a promising strategy for treating solid tumors, which combines direct tumor cytotoxicity with immune activation and minimizes off-target effects. TeaserDR5 CAR-T cells eliminate tumor cells and MDSCs and activate tumor-resident CD8+ T cells within the TME.

cancer biology↗

bioRxiv2025

Structural Basis for Cas9-Directed Spacer Acquisition in Type II-A CRISPR-Cas Systems

CRISPR-Cas systems confer prokaryotic adaptive immunity by integrating foreign DNA (prespacers) into host arrays. Type II-A systems employ Cas9 for protospacer adjacent motif (PAM) recognition and coordinate with Csn2 and the Cas1-Cas2 integrase during spacer acquisition, yet their structural basis remains unresolved. Here, we report cryo-EM structures of the Enterococcus faecalis Cas9-Csn2-Cas1-Cas2 supercomplex in apo and DNA-bound states. The apo-state structure (Cas92-Csn28-Cas18-Cas24) adopts a resting conformation, with Cas9 locked in a nuclease-inactive state and Cas1-Cas2 sterically blocked from prespacer loading. Upon DNA engagement, Cas9 undergoes a conformational transition, forming a prespacer catching complex that threads the DNA through Csn2s central channel. This architecture enables Cas9 to interrogate the PAM sequence while sliding along the DNA, with Cas9 and Csn2 jointly define a 30-bp DNA segment which matches the prespacer length. Subsequent dissociation of Cas9 triggers a structural reconfiguration of the Csn2-Cas1-Cas2 assembly. The PAM-proximal DNA becomes accessible, and Cas1-Cas2 relocates to bind to the exposed DNA, enabling further prespacer processing and directional integration. These findings reveal how Cas9 collaborates with Csn2 and Cas1-Cas2 to couple PAM recognition with prespacer selection, resolving the dynamic structural transitions that ensure fidelity during type II-A CRISPR adaptation.

molecular biology↗

bioRxiv2025

FEDRANN: effective overlap graph construction based on dimensionality reduction and approximate nearest neighbors

Overlap detection is a key step in de novo genome assembly pipelines based on the Overlap-Layout-Consensus (OLC) paradigm. However, existing methods for overlap detection either rely on heuristic seed-and-extension strategies or locality-sensitive hashing (LSH), both of which struggle to handle repetitive genomic regions and the computational burden of large-scale datasets. Here, we present FEDRANN, a novel strategy for overlap graph construction that integrates feature extraction, dimensionality reduction (DR), and approximate nearest neighbor (ANN) search. We find the pipeline combining inverse document frequency (IDF) transformation, sparse random projection (SRP), and NNDescent enables accurate detection of overlaps across diverse datasets. We developed an efficient open-source implementation of this pipeline named Fedrann (https://github.com/jzhang-dev/fedrann). Through systematic benchmarking on real long-read sequencing data, we demonstrate that Fedrann produces overlap graphs comparable to or better than those generated by existing state-of-the-art tools, including MECAT2, minimap2, and wtdbg2, while maintaining competitive runtime. Despite being implemented primarily in Python, Fedrann achieves performance on par with tools written in compiled languages, owing to matrix-based representations and C-accelerated numerical libraries. Our results suggest that DR and ANN techniques offer a promising new direction for scalable and accurate overlap detection in long-read assembly and broader sequence similarity search tasks.

bioinformatics↗

bioRxiv2025

Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks

Biophysical modeling provides mechanistic insights into brain function, spanning single-neuron dynamics to large-scale circuit models. These models are governed by biologically meaningful parameters, many of which can be experimentally measured. Some parameters are unknown, and optimizing them improves fit to experimental data, enhancing biological plausibility. However, existing methods require repeated, computationally expensive numerical integration of differential equations, limiting scalability to population-level datasets. Here, we introduce DELSSOME (DEep Learning for Surrogate Statistics Optimization in MEan field modeling), a framework that bypasses numerical integration by directly predicting whether parameter sets produce realistic brain dynamics. Across three large-scale circuit models, DELSSOME achieves a 1500-8000x speedup over numerical integration in predicting model realism. When embedded within an evolutionary optimization strategy, DELSSOME enables 50-100x faster parameter estimation without sacrificing agreement with numerical integration. Because of computational constraints, most studies simulate large-scale circuit models only at the group level. DELSSOME enables efficient individual-level optimization of the feedback inhibition control model. By collating 12,005 individuals across 14 datasets, we derive - for the first time - normative trajectories of cortical E/I ratio across the lifespan, revealing new insights into sex differences and network-specific patterns. This acceleration enables population-scale mechanistic modeling and unlocks new opportunities for understanding brain function.

neuroscience↗

bioRxiv2025

Somatic repetitive element insertions Define New Biomarkers in Pan-cancer genome

Repetitive elements insertions (REIs), including tandem repeat insertions (TRIs) and transposable element insertions (TEIs), constitute >90% of large-scale (>50bp) somatic insertions and are linked to diseases and cancer biomarkers. However, the genomic landscape of large-scale REIs in pan-cancer has not been well-characterized due to short-read sequencing limitations. Here, we detected somatic REIs in 325 cancer genomes across 12 cancer types using long-read whole-genome sequencing and customized algorithms. The diverse sequence patterns of somatic TRIs and the insertion mechanisms of somatic TEIs were characterized across different cancer types. We identified 152 high-frequency somatic TRIs, with 10 showing pan-cancer characteristics, including TRIs in SHROOM2, PALMD, and the enhancer of PTPRZ1. The MHC class II gene cluster exhibited the highest somatic TEI abundance, affecting [~]40% tumors. Adenocarcinomas and squamous cell carcinomas exhibited differing TEI distributions within this region. Our study highlights REIs as important but under-explored markers for personalized cancer diagnosis and immunotherapy.

genomics↗

bioRxiv2025

Themis dominates T cell exhaustion by regulation of TCR and PD-1 signaling

T cell exhaustion is important to protect the host from immunopathology during chronic viral infection, but it also impairs T cell anti-tumor immunity1-5. A fundamental unresolved question is whether and how T cell exhaustion is determined at the onset of TCR signaling6-8. Here we report an unexpected role of Themis, a TCR-proximal signaling molecule9, in T cell exhaustion. Chronic viral infection in mice usually leads to T cell exhaustion and survival of the host. Surprisingly, Themis T-cell conditional knockout mice died from severe CD8+-dependent lung immunopathology in chronic viral infection, showing Themis importance in establishing T cell exhaustion. We found that Themis-deficient CD8+ T cells were hyperactivated at the single-cell level - producing more TNF and IFN{gamma} compared to wild-type counterparts - but defective in population-level expansion. Moreover, TCF-1 and TOX expression were inhibited in Themis-deficient CD8+ T cells, thereby impairing differentiation of exhausted T cell precursors (T-pex) and maintenance of terminally exhausted T cells (T-ex), respectively. Mechanistically, Themis initially promotes TCR signaling to induce PD-1 expression and subsequently mediates PD-1 signaling. In the latter, Themis binds to PD-1 and promotes PD-1 phosphorylation and its recruitment of SHP2, thereby acting as a negative regulator to inhibit T cell effector functions. Without Themis, the orderly regulation of TCR and PD-1 signaling, and therefore exhaustion, is disrupted. Thus, our results unequivocally demonstrate that Themis-mediated early TCR signaling plays a decisive role in T cell exhaustion and provide a novel mechanism of PD-1 signaling through Themis.

immunology↗

bioRxiv2025

Causal modeling of gene effects from regulators to programs to traits: integration of genetic associations and Perturb-seq

AbstractGenetic association studies provide a unique tool for identifying causal links from genes to human traits and diseases. However, it is challenging to determine the biological mechanisms underlying most associations, and we lack genome-scale approaches for inferring causal mechanistic pathways from genes to cellular functions to traits. Here we propose new approaches to bridge this gap by combining quantitative estimates of gene-trait relationships from loss-of-function burden tests with gene-regulatory connections inferred from Perturb-seq experiments in relevant cell types. By combining these two forms of data, we aim to build causal graphs in which the directional associations of genes with a trait can be explained by their regulatory effects on biological programs or direct effects on the trait. As a proof-of-concept, we constructed a causal graph of the gene regulatory hierarchy that jointly controls three partially co-regulated blood traits. We propose that perturbation studies in trait-relevant cell types, coupled with gene-level effect sizes for traits, can bridge the gap between genetics and biology.

genetics↗

bioRxiv2025

Single cell resolved spatial immune repertoire unveils spatial heterogeneity of lymphoid aggregates in human immune disorders

Adaptive immunity, mediated by T and B cell responses, is essential for defending against infections and cancers while also being implicated in autoimmune diseases. Tracking T and B cell repertoires in situ at single-cell resolution is essential for understanding adaptive immune responses. To address the lack of tools for in situ single-cell T/BCR (XCR) sequencing, we developed Stereo-XCR-seq, an efficient strategy for retrieving and sequencing TCR and BCR from Stereo-seq cDNA libraries at subcellular resolution. Stereo-XCR-seq provides unbiased full-length XCR reads alongside spatial transcriptomics, enabling the identification of heterogeneous lymphoid aggregates with distinct clonal activities in cancers and inflammatory bowel disease (IBD). We identified plasma cell aggregates that differ from tertiary lymphoid structures (TLSs) in both transcriptomic profiles and clonal activities, with spatial positioning potentially mediating unique immune responses. Collectively, Stereo-XCR-seq enables in situ single-cell profiling of T and B cell clonal activities within tissue microenvironments, providing insights into lymphocyte adaption to environmental stimuli. This technology provides potential for advancing our understanding of tissue immunity and the development of therapeutic strategies for immune disorders.

immunology↗

bioRxiv2024

EnzymeCAGE: A Geometric Foundation Model for Enzyme Retrieval with Evolutionary Insights

Enzyme catalysis is fundamental to life, driving the chemical transformations that sustain biological processes and support industrial applications. However, unraveling the intertwined relationships between enzymes and their catalytic reactions remains a significant challenge. Here, we present EnzymeCAGE, a catalytic-specific geometric foundation model trained on approximately 1 million structure-informed enzyme-reaction pairs, spanning over 2,000 species and encompassing an extensive diversity of genomic and metabolic information. EnzymeCAGE features a geometry-aware multi-modal architecture coupled with an evolutionary information integration module, enabling it to effectively model the nuanced relationships between enzyme structure, catalytic function, and reaction specificity. EnzymeCAGE supports both experimental and predicted enzyme structures and is applicable across diverse enzyme families, accommodating a broad range of metabolites and reaction types. Extensive evaluations demonstrate EnzymeCAGEs state-of-the-art performance in enzyme function prediction, reaction de-orphaning, catalytic site identification, and biosynthetic pathway reconstruction. These results highlight its potential as a transformative foundation model for understanding enzyme catalysis and accelerating the discovery of novel biocatalysts.

synthetic biology↗

bioRxiv2024

A near-complete genome assembly of the bearded dragon Pogona vitticeps provides insights into the origin of Pogona sex chromosomes

BackgroundThe agamid dragon lizard Pogona vitticeps is one of the most popular domesticated reptiles to be kept as pets worldwide. The capacity of breeding in captivity also makes it emerging as a model species for a range of scientific research, especially for the studies of sex chromosome origin and sex determination mechanisms. ResultsBy leveraging the CycloneSEQ and DNBSEQ sequencing technologies, we conducted whole genome and long-range sequencing for a captive-bred ZZ male to construct a chromosome-scale reference genome for P. vitticeps. The new reference genome is [~]1.8 Gb in length, with a contig N50 of 202.5 Mb and all contigs anchored onto 16 chromosomes. Genome annotation assisted by long-read RNA sequencing greatly expanded the P. vitticeps lncRNA catalog. With the chromosome-scale genome, we were able to characterize the whole Z sex chromosome for the first time. We found that over 80% of the Z chromosome remains as pseudo-autosomal region (PAR) where recombination is not suppressed. The sexually differentiated region (SDR) is small and occupied mostly by transposons, yet it aggregates genes involved in male development, such as AMH, AMHR2 and BMPR1A. Finally, by tracking the evolutionary origin and developmental expression of the SDR genes, we proposed a model for the origin of P. vitticeps sex chromosomes which considered the Z-linked AMH as the master sex-determining gene. ConclusionsOur study provides novel insights into the sex chromosome origin and sex determination of this model lizard. The near-complete P. vitticeps reference genome will also benefit future study of amniote evolution and may facilitate genome-assisted breeding.

genomics↗