Biology subjects

Li, H.

Publications and source records attributed to Li, H..

At least 325 records · Page 18Linked to original sources

bioRxiv2025

Interaction of Carbamoyl-Phosphate Synthase 1 with Agmatinase in the Liver of Torpid Bats

Mammalian torpor imposes unique metabolic constraints, yet the mechanisms of nitrogen metabolism during this state remain unclear. In this study, we show that the urea cycle is selectively regulated rather than broadly suppressed in torpid bats. A significantly increased abundance of carbamoyl-phosphate synthase 1 (CPS1) maintained its functional capacity during torpor and arousal in Myotis ricketti. Proteomic analyses and confocal microscopy identified a specific association and co-localization between CPS1 and agmatinase (AGMAT), an ATP-independent enzyme involved in nitrogen metabolism. Co-localization of CPS1 and AGMAT was also observed in torpid Rhinolophus ferrumequinum, a phylogenetically distant species. Fluorescence resonance energy transfer (FRET) further supported an indirect CPS1-AGMAT interaction. Most urea cycle enzymes exhibited stable or only moderately reduced expression during bat torpor, and metabolic profiling demonstrated sustained nitrogen flux. Together, these findings reveal a conserved adaptive mechanism that maintains urea cycle function, potentially enhancing osmotic stability and energy efficiency during prolonged fasting and water scarcity.

zoology↗

bioRxiv2025

In-situ glial cell-surface proteomics identifies pro-longevity factors in Drosophila

Much focus has shifted towards understanding how glial dysfunction contributes to age-related neurodegeneration due to the critical roles glial cells play in maintaining healthy brain function. Cell-cell interactions, which are largely mediated by cell-surface proteins, control many critical aspects of development and physiology; as such, dysregulation of glial cell-surface proteins in particular is hypothesized to play an important role in age-related neurodegeneration. However, it remains technically difficult to profile glial cell-surface proteins in intact brains. Here, we applied a cell-surface proteomic profiling method to glial cells from intact brains in Drosophila, which enabled us to fully profile cell-surface proteomes in-situ, preserving native cell-cell interactions that would otherwise be omitted using traditional proteomics methods. Applying this platform to young and old flies, we investigated how glial cell-surface proteomes change during aging. We identified candidate genes predicted to be involved in brain aging, including several associated with neural development and synapse wiring molecules not previously thought to be particularly active in glia. Through a functional genetic screen, we identified one surface protein, DIP-{beta}, which is down-regulated in old flies and can increase fly lifespan when overexpressed in adult glial cells. We further performed whole-head single-nucleus RNA-seq and revealed that DIP-{beta} overexpression mainly impacts glial and fat cells. We also found that glial DIP-{beta} overexpression was associated with improved cell-cell communication, which may contribute to the observed lifespan extension. Our study is the first to apply in-situ cell-surface proteomics to glial cells in Drosophila, and to identify DIP-{beta} as a potential glial regulator of brain aging.

neuroscience↗

bioRxiv2025

Programming Microbe-Computer Interaction for Customized Life-Nonlife and Cross-Life Communication

This extension of human-computer interaction (HCI) paradigm to the non-intelligent microbe-computer interaction (MCI) is attractive for building generalized life-nonlife communication. Main challenges lie in how to construct biohybrid interface within individual MCI unit and thereafter program cross-life communication based on these MCI units. Here, we propose the design and construction of opto-interfaced MCI unit composed of engineered microbes and computer terminals, for enabling quantifiable transduction between microbial signals and digital signals. These units were able to serve as biohybrid sensors, actuators and transceivers, supporting biomonitoring, bio-actuation and microbe-centric bidirectional operations. Based on these functional units, we established programmable cross-life communication architectures capable of unicast, multicast, and logic-gate-driven communication with temporal dynamic control. The architectures were validated in biomedical scenarios including tumor hypoxia biomarking, epidermal heavy metal detoxification, and colitis intervention, demonstrating robust performance in closed-loop diagnostic-therapeutic applications. Additionally, we integrated MCI with an unmanned surface vessel for environmental monitoring, highlighting its cross-domain potential. Collectively, we provide a scalable strategy for building customized life-nonlife and cross-life communication, which is expected as an important complement to internet of things (IoT).

synthetic biology↗

bioRxiv2025

CRISPR/Cas9 screenings reveal the role of STX1A and CDK1 in Cathepsin G entering and killing colorectal cancer cells

Neutrophils are the major populations of white blood cells and have been reported to facilitate cancer metastasis. Meanwhile, emerging evidence has recently suggested the anti-cancer role of neutrophils. Our previous study revealed that CB-839 and 5-FU-treated colorectal cancer (CRC) tumors recruited neutrophils and induced neutrophil extracellular traps (NETs). Cathepsin G (CTSG), which is released during NET formation, enters CRC cells through the receptor for advanced glycation end products (RAGE) and cleaves 14-3-3{varepsilon} to promote apoptosis. However, the detailed mechanism underlying CTSGs anti-tumor function remains less studied. In this study, we report that CTSG enters CRC cells through RAGE-mediated endocytosis. Knocking out RAGE or inhibiting endocytosis blocks CTSG from entering CRC cells and attenuates CTSG-induced apoptosis. Furthermore, the clathrin coat assembly complex and SNARE proteins were enriched in an arrayed CRISPR/Cas9 screening targeting human membrane trafficking genes. Knocking out SNARE protein STX1A prevents the spread of CTSG in CRC cells and the induction of cleaved PARP. A pooled genome-wide CRISPR/Cas9 screening further identifies the role of CDK1 in the NET-induced killing of CRC cells. Inhibiting CDK1 protected CRC cells from killing by CTSG. Our study reveals novel mechanisms by which CTSG enters and kills CRC cells.

cancer biology↗

bioRxiv2025

A New Aneurysm Rupture-Prone Marfan Mouse Model with FBN1Q2467X Nonsense Mutation Reveals Adventitial Inflammation

Marfan syndrome (MFS) is a genetic disorder caused by mutations in fibrillin-1(FBN1), which encodes FBN1, a key structural component of the extracellular matrix. Mutations in FBN1 influence the severity of aortic disease and therapeutic responses, with aortic aneurysm being the leading cause of mortality in patients with MFS. To investigate the mechanisms driving aneurysm progression, we generated a mouse model (Fbn1Q2469X/+) carrying the FBN1Q2467X nonsense mutation identified in MFS patients. This mutation results in FBN1 deficiency. Although Fbn1Q2469X/+ mice appear normal, showing only mild, nonprogressive dilation of the aortic root and ascending aorta with minor reductions in blood pressure, homozygous Fbn1Q2469X/Q2469X mice develop spontaneous thoracic aortic aneurysms (TAA) that progress to rupture between 10 and 25 days of age, with 100% penetrance. Histopathology shows progressive vessel wall degeneration characterized by disorganized vascular smooth muscle cells, collagen loss, and elastic fiber fragmentation from early to late stages. RNA-seq analysis identifies inflammation as the dominant process in late-stage aneurysms. Immunofluorescence assay reveals inflammatory cells prominently localized to the adventitia near rupture sites, linking adventitial inflammation to aneurysm progression. This genetically modified Fbn1Q2469X/Q2469X mouse model consistently develops progressive aortic aneurysms and provides a reliable, cost-effective platform to investigate the molecular mechanisms of aneurysm progression and to evaluate therapeutic strategies in aneurysm diseases, including Marfan syndrome and related disorders.

genetics↗

bioRxiv2025

The co-localizing Zorya II, Druantia III, and ARMADA II defense systems on O-island 172 confer synergistic anti-phage defense in enterohemorrhagic Escherichia coli

In this study, we show that the enterohemorrhagic Escherichia coli (EHEC) strain EDL933 {Delta}stx1/2 is highly resistant to phages. The genes encoding the three phage defense systems Zorya II, Druantia III, and ARMADA II were found to co-localize on O-island 172 (OI-172) in EDL933. The three phage defense systems co-occur in 426 E. coli strains comprising 66 distinct serotypes, including 277 O157:H7 isolates and 117 diverse non-pathogenic strains. Efficiency of plating (EOP) assays were used to explore the phage spectrum and synergy of the three defense systems and their contribution to the phage resistance of strain EDL933 {Delta}stx1/2. Using {Delta}zorABE, {Delta}druHE, and {Delta}armABCD single system deletion mutants in EDL933 {Delta}stx1/2, we showed that Druantia III and ARMADA II protect to different extents against a broad spectrum of phages, including the Drexlerviridae, Siphoviridae, Demerecviridae, Vequintavirinae and Autographiviridae, but not against hypermodified Tevenvirinae. Additionally, Zorya II caused strong protection only against Autographiviridae. Furthermore, EOP assays of combined system mutants revealed strong synergistic interactions of Druantia III and ARMADA II to provide more robust immunity against a similar phage spectrum than the additive protection of the individual systems. In contrast, Druantia III and Zorya II act only weakly synergistically against a few phages. Altogether, our results revealed that Druantia III and ARMADA II are responsible for most of the phage resistance of EDL933 {Delta}stx1/2, whereas Zorya II provides additional immunity against podoviruses. Future studies are underway to elucidate the molecular basis of the synergistic interactions between the Druantia III and ARMADA II defense systems. IMPORTANCEShiga toxin-producing E. coli (STEC) O157:H7 strains cause life-threatening diseases, such as hemorrhagic colitis and the hemolytic uremic syndrome. Currently, EHEC infections can be only treated symptomatically, since antibiotics are not recommended due to induction of the Shiga toxin. While phage therapy could offer a treatment option, we show that the EHEC strain EDL933 {Delta}stx1/2 is highly resistant to many phages. EOP assays of defense mutants in the host strain revealed that the co-occurring defense systems Zorya II, Druantia III, and ARMADA II on OI-172 confer most of the phage resistance in EHEC. Moreover, our data uncovered that Druantia III and ARMADA II act synergistically in the anti-phage defense in EDL933 {Delta}stx1/2, explaining the robust immunity against a broad spectrum of phages. These results support the idea that the design of novel inhibitors against the Druantia III and ARMADA II systems could be combined with phage therapies to efficiently eradicate EHEC.

microbiology↗

bioRxiv2025

Cryo-EM structure of influenza polymerase bound to the cRNA promoter provides insights into the mechanism of virus replication

Influenza virus polymerase (FluPol) synthesizes the complementary RNA (cRNA) and the viral RNA (vRNA) using distinct de novo initiation strategies during genome replication, known as internal and terminal initiation, respectively. The de novo initiation mechanisms, especially the internal initiation process, which includes a template realignment process, is still not well understood. Here, we present a cryo-electron microscopy structure of H5N1 FluPol bound to the cRNA promoter. In combination with structural analyses and structure-guided mutagenesis studies, we identified several previously unreported structural features of FluPol essential for internal initiation. The B loop adopts an "open" conformation, allowing translocation of the 3' terminus of cRNA (3'-cRNA) template into the catalytic cavity. The dynamic of incoming 3'-cRNA template is limited by the priming and realignment loop (PR loop), which facilitates the cRNA template realignment process. An asparagine cluster above the catalytic cavity is required for polymerase activity. Our findings provide structural insights into the mechanism of replication internal initiation of FluPol.

microbiology↗

bioRxiv2025

Clonal dynamics shaped by diverse drug-tolerant persister states in melanoma resistance

Most advanced melanomas initially respond to targeted therapy but eventually relapse. Rather than acquiring new mutations, resistance is driven by drug-tolerant persister cells that enter a reversible drug-refractory state. We developed MeRLin, a high-resolution lineage tracing platform integrating cellular barcoding, single-cell transcriptomics, RNA fluorescence in situ hybridization (FISH), and computational analyses to track clonal and transcriptional dynamics in patient-derived melanoma models during prolonged therapy. Clonal dynamics revealed that persister subpopulations first responded to treatment but persisted and expanded during minimal residual disease, ultimately leading to tumor recurrence. Pre-treatment melanoma populations diversified into four conserved persister states characterized by stress-like, lipid metabolism, PI3K signaling, and extracellular matrix remodeling programs associated with adaptive resistance. Spatial transcriptomics showed the organization of these adaptive programs and a complex signaling network of autocrine and paracrine interactions among persister subpopulations. Barcoded RNA-FISH enabled spatial mapping of clonal identity and gene expression, revealing in situ co-localization of a dominant resistant clone with SLC2A1 expression. MeRLin provides a robust framework for dissecting cancer heterogeneity and identifying vulnerabilities in persister populations.

cancer biology↗

bioRxiv2025

Integrated Analysis of Glycosylation and Inflammation-Related Genes for Prognostic Risk Modeling and Immunotherapy Response Prediction in Gastric Cancer

BackgroundGastric cancer (GC) continues to be among the most commonly identified cancers worldwide. This study integrates glycosylation and inflammation-related gene features for the first time to construct a prognostic model for gastric cancer, providing new theoretical basis for revealing immune escape mechanisms and personalized treatment strategies. MethodsTranscriptomic and clinical data derived from GC samples were meticulously examined, utilizing resources from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Through differential expression analysis, we successfully identified glycosylation and inflammatory-related differentially expressed genes (GANDIRDEGs). To construct a prognostic gene signature, we applied least absolute shrinkage and selection operator (LASSO) analysis in conjunction with Cox regression analysis. Additionally, we performed somatic mutation (SM) along with copy number variation (CNV) analyses, alongside gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, we conducted gene set enrichment analysis (GSEA) along with a comprehensive evaluation of immune infiltration and drug sensitivity. ResultsWe identified and validated a six-gene (INHBA, OLR1, ROS1, EPHA5, TACR1, and IL6) signature, termed GANDIRDEGs, which showed excellent performance in distinguishing overall survival (OS) between high-risk (HR) and low-risk (LR) cohorts. Moreover, we developed a prognostic nomogram utilizing this six-gene signature that provides highly accurate predictions of GC patient outcomes.SM and CNV analyses revealed that MSR1 had the highest mutation rate among the GANDIRDEGs, with a mutation rate of 5%. GO, KEGG, and GSEA revealed significant associations of each pivotal gene with pathways, including cytokine signaling, the inflammatory response, and apoptosis mediated by CDKN1A through TP53, among various biological functions and signal transduction pathways. Our findings offer a novel gene signature, GANDIRDEGs, that correlated with prognosis, immune infiltration, and therapeutic sensitivity in patients with GC. ConclusionThis study establishes a prognostic signature integrating glycosylation and inflammatory pathways in GC, providing valuable insights into the mechanisms of immune evasion and potential personalized treatment approaches.

cell biology↗

bioRxiv2025

Insectivores exhibit superior microbial transmission efficiency and elevated zoonotic risk by 2035 relative to rodents and bats

Wild small mammals represent critical sources of zoonotic infections due to their high diversity, global distribution, and proximity to humans. Nevertheless, significant knowledge gaps persist in characterizing pan-taxonomic microbial richness and sharing dynamics, particularly regarding ecologically critical yet understudied Eulipotyphla (true insectivores). Here we take a macroecological approach to compare how microbial hosting and transmission differ across insectivores, rodents, and bats, and what ecological factors drive such disparities. We find that insectivores host comparable microbial richness to rodents and bats while exhibiting superior intra- and cross-order transmission efficiency. Urban adaptation, geographic range area, and longevity are shared drivers of microbial richness and transmission across these host orders, while greater body mass and shorter gestation time specifically are positive predictors of these outcomes within insectivores. Climate change projections identify insectivores as primary transmission hosts in new high-latitude hotspots by 2035, including parts of the US, Canada, and Russia, posing greater zoonotic threats than rodents or bats. Our findings challenge the prevailing paradigm that prioritizes rodents and bats as special zoonotic reservoirs, establishing insectivores as critical but overlooked players in disease ecology. Collective proactive surveillance of insectivores, rodents, and bats is imperative for forecasting emerging zoonotic threats and informing global risk assessment frameworks.

ecology↗

bioRxiv2025

Endocytic motif on HIV Env regulates cleavage status and antibody neutralization of cell-free and cell-to-cell infection

Antibodies inhibit human immunodeficiency virus type 1 (HIV-1) infection by targeting the envelope glycoprotein (Env). Env cleavage is a key determinant of antibody binding, as cleavage reduces Env flexibility and alters glycosylation. Given the greater abundance of uncleaved Env on the cell surface compared to virions, we investigated whether Env endocytosis, initiated through a membrane-proximal tyrosine motif in its cytoplasmic tail, regulates the abundance of cleaved Env at the cell surface. We hypothesize that such a shift would alter the cleavage and glycosylation profile of cell surface Env, affecting the sensitivity of cell-to-cell infection to neutralizing antibodies. To address this, we generated an endocytic mutant (ASPI-Env) and compared its antigenic properties to a cleavage-site mutant (SEKS-Env). Immunoprecipitation and ratiometric antibody binding studies of cell surface Env demonstrated that the ASPI mutation increases the amount of uncleaved Env on the cell surface. Consequently, ASPI-Env in cell-free infection was more sensitive to NAbs recognizing uncleaved Env. Notably, only b12, which can engage both cleaved and uncleaved Env but has a higher affinity for uncleaved Env, showed increased inhibition of ASPI-Env during cell-to-cell infection. This mirrors the enhanced neutralization of SEKS-Env during the cell-to-cell transfer assay and supports a model in which uncleaved Env participates in CD4-dependent virion transfer. Finally, the ASPI mutation altered lectin binding and differentially affected cell-to-cell and cell-free infections. Together, these findings indicate that Env endocytosis modulates the abundance of cleaved Env at the cell surface, thereby influencing antibody neutralization and lectin recognition in distinct modes of HIV-1 transmission. IMPORTANCEWe find that Env endocytosis modulates the antigenicity of Env on both the cell surface and virions. Blocking internalization increased uncleaved Env on the cell surface, thereby reshaping HIV-1 neutralization due to enhanced binding of antibodies that preferentially recognize uncleaved Env. We further show that uncleaved Env on the cell surface can initiate CD4-dependent transfer of virions across virological synapses. These findings demonstrate that Env endocytosis shapes cleavage-associated antigenicity in a manner that can differentially impact the recognition and neutralization of cells and viruses. The impact of uncleaved Env on neutralization indicates that a broader spectrum of cleaved and uncleaved Env conformations may be relevant when designing vaccines and cure strategies that must contend with a diverse antigenic landscape.

microbiology↗

bioRxiv2025

High-resolution ab initio reconstruction enables cryo-EM structure determination of small particles

Despite recent advances in data acquisition and algorithmic development, applying single particle cryogenic electron microscopy (cryoEM) to small proteins (<50kDa) remains challenging, even when high quality data are available, in part due to the lack of reliable low-resolution structural features to inform initial alignments. Here we present a workflow which effectively bypasses this step, by obtaining initial particle orientations directly from heterogeneous ab initio reconstruction in CryoSPARC solely using data at high spatial frequencies. Applying this approach, we solve the structure of a previously intractable protein in a publicly available dataset, iPKAc (EMPIAR-10252), 39 kDa, resolved at an estimated resolution of 2.7 [A] as well as a hemoglobin alpha-beta dimer (EMPIAR-10250) at 29kDa, resolved to an estimated resolution of 4 [A]. We also show that the Aca2-RNA complex (37kDa, EMPIAR-11918) can be resolved by this approach directly from a blob-picked particle stack, in a single round of heterogeneous ab initio reconstruction followed by local refinement. The map of iPKAc is of sufficient quality to autobuild 325 of 356 residues present in the original crystal structure using Modelangelo, and ordered ATP and magnesium ions can clearly be resolved. The Hb-dimer has clear secondary structural features, identifiable hemes, and visible bulky sidechains, consistent with the estimated resolution. We expect that this approach may be useful for cryo-EM analysis of other small particles near or below the theoretical size limit.

biophysics↗

bioRxiv2025

A Benchmark of Evo2 Genomic AI Models for Efficient and Practical Deployment

The rapid advancement of DNA foundation language models has brought about a transformative shift in genomics, allowing for the deciphering of intricate patterns and regulatory mechanisms embedded within DNA sequences. The genomic foundation model Evo2 demonstrates remarkable capabilities in decoding DNA functional patterns through cross-species pretraining. However, despite the great potential of Evo2 in basic genomics research, there is currently no clear and systematic guidance on its specific application scenarios, performance, and optimization directions in the field of tumor genomics, and its performance dependency on specialized hardware (such as FP8 precision on H800 GPUs) has not been empirically benchmarked. Here, we present a focused validation of Evo2 using two independent cancer genomic datasets (Bladder Urothelial Carcinoma and Ovarian Cancer), we tested the downstream tasks of Evo2, including the prediction of tumor pathogenic variants and the prediction of mutational effects, and compared its performance on A100 and H800 GPUs. The results show that critical importance of FP8 precision, enabling the H800 to achieve a 4x faster inference speed than the A100 with stable accuracy (AUC 0.88-0.95). The 7B-parameter model emerged as the top performer, whereas the 40B model experienced a severe performance drop (AUC to 0.48) on non-FP8 hardware like the A100. These findings empirically validated Evo2s hardware specifications and provided practical insights for researchers implementing the model with similar computational resources. Futhermore, our findings provide a framework for the application and optimization of downstream tasks of the DNA language model Evo2 in cancer, and can guide researchers in effectively applying it in genomic studies. Key PointsO_LIHardware Precision Impact: FP8 precision on H800 GPUs is critical for Evo 2s performance, enabling 4x faster inference than A100 (without FP8 support) while maintaining high accuracy (AUC 0.88-0.95). C_LIO_LIModel Scale Optimization: The 7B-parameter model outperformed larger variants (e.g., 40B), which suffered severe accuracy drops (AUC as low as 0.48) on non-FP8 hardware, highlighting a balance between efficiency and performance. C_LIO_LIPractical Guidelines: We provide a framework for deploying Evo 2 in cancer genomics, including hardware recommendations, dataset curation, and downstream task optimization--valuable for researchers with varied computational resources. C_LI

genomics↗

bioRxiv2025

A neuroendocrine principle: Pancreatic islets actively shape sympathetic innervation

Survival critically depends on maintaining blood glucose levels to provide essential energy, especially during emergencies such as the fight-or-flight response, when timely glucose control via neural integration is vital. However, pancreatic islets constitute only a small fraction of the pancreas and are dispersed throughout the organ, raising the fundamental question of how the nervous system coordinates synchronized control of multiple islets. Using whole-organ clearing and 3D imaging, we mapped pancreatic sympathetic innervation, revealing specialized anatomical integration between sympathetic nerves and islets. Transplanted islets intrinsically attracted sympathetic nerves independent of their native environment. Chronic islet injury disrupted sympathetic innervation and markedly impaired nerve regeneration after denervation. Sympathetic denervation markedly elevated islet-derived Reg2 and Reg3{beta}; administration of these proteins accelerated sympathetic regeneration and improved islet graft function. Our findings identify an islet-sympathetic architecture actively maintained by islets, uncovering an endocrine-driven mechanism for neural regulation, highlighting Reg2 and Reg3{beta} as therapeutic candidates for diabetes management.

neuroscience↗

bioRxiv2025

STRUMP-I: Structure-based machine learning approach to pMHC-I binding prediction using force field energy features

The adaptive immune system monitors cellular integrity by recognizing short peptides from intracellular proteins presented on Major Histocompatibility Complex class I (MHC-I) molecules, collectively termed peptide-MHC complexes (pMHC), enabling detection of foreign or mutated proteins. With the rising importance of immunotherapies targeting neoantigens in cancers, the ability to accurately predict which peptides will bind to the diverse population of MHC alleles is critically important. Current computational methods for pMHC-I prediction fall broadly into sequence-based methods, which rely heavily on large training datasets, and structure-based methods that leverage structural modeling and energetics of pMHC binding. While sequence-based methods have been popularly used, their performance is dependent on the size and quality of training data. On the other hands, while structure-based approaches can generalize better across diverse MHC alleles, they traditionally depend on identifying a single global minimum energy conformation, an assumption that often fails due to the inherent binding promiscuity of MHC-I molecules. To address these limitations, we developed a STRUMP-I (STRUcture-based pMHC Prediction (for class I)), a novel pMHC binding prediction tool that directly leverages a broad set of force-field-derived energy terms as machine-learning features. STRUMP-I achieves performance comparable to state-of-the-art sequence-based models while significantly outperforming them on MHC alleles with limited representation in training data. Furthermore, STRUMP-I demonstrates strong synergy when integrated with sequence-based methods, notably enhancing prediction precision. The robustness and generalizability of STRUMP-I were confirmed by evaluating its predictive performance on independent, previously unseen datasets, including an experimentally validated cancer neoantigen dataset. This combined approach advances our capability to reliably identify clinically relevant neoantigen targets. The source code and trained models are available at https://github.com/yoonjoolab/STRUMP-I

bioinformatics↗

bioRxiv2025

Large-language-model-based antibiotic resistance gene prediction and resistomes mining in cyanobacterial blooms

The rapid spread of antibiotic resistance genes (ARGs) in aquatic ecosystems poses a serious public health threat. Conventional ARG detection methods, including sequence-alignment and machine learning, are limited by high false-negative or false-positive rates, especially due to sequence diversity and class imbalance in metagenomic data. Moreover, few tools offer comprehensive solutions for ARG identification, classification, and functional annotation. To address these limitations, we developed ESMARG, a novel protein language model framework based on ESM1v, for accurate ARG identification, classification, and annotation. Trained with both ARG and abundant non-ARG sequences from real-world metagenomes to enhance robustness and reduce false positives, ESMARG significantly outperformed traditional alignment-based (BLAST, DIAMOND) and recent deep learning models (ARGNet, ARG-SHINE), achieving 0.998 precision, 0.939 recall, and 0.968 F1-score for ARG identification. Functional and mechanism classification modules also demonstrated high accuracy (0.986 and 0.987) and computational efficiency. We applied ESMARG to analyze 26 cyanobacterial aggregate (CA) metagenomes collected from Lake Taihu across a full annual cyanobacterial harmful algal bloom (CyanoHAB) cycle. A total of 110 ARGs, spanning 24 drug classes and multiple resistance mechanisms, were detected, with seasonal shifts in ARG abundance and composition. Strong correlations were identified between CA resistomes and microbial community structure, especially with cyanobacteria. Further, ARG abundance was shaped by both biotic factors--such as cyanobacterial dominance and bacterial functional profiles--and abiotic variables, including biochemical oxygen demand and water temperature. Our findings demonstrate the power of ESMARG for high-resolution ARG profiling and reveal complex ecological interactions between resistomes, microbiomes, and environmental factors in CyanoHAB. HighlightsO_LIDeveloped ESMARG model outperforms BLAST/other deep learning models in ARG detection C_LIO_LIARG showed seasonal dynamics in cyanobacterial metagenomes across algal bloom cycle C_LIO_LIARG was strongly correlate with microbiome structure and cyanobacteria dominance C_LIO_LIARG abundance was shaped by cyanobacteria, bacterial functions, BOD and temperature C_LI

bioinformatics↗

bioRxiv2025

High-resolution metagenome assembly for modern long reads with myloasm

Long-read metagenome assembly promises complete genomic recovery from microbiomes. However, the complexity of metagenomes poses challenges. We present myloasm, a metagenome assembler for PacBio HiFi and Oxford Nanopore Technologies (ONT) R10.4 long reads. Myloasm uses polymorphic k-mers to construct a high-resolution string graph and then leverages differential abundance for graph simplification. On real-world ONT metagenomes, myloasm assembled three times more complete circular contigs than the next-best assembler. Myloasm can make ONT and HiFi comparable for assembly: for a jointly sequenced gut metagenome, myloasm with ONT assembled more complete circular genomes than any assembler with HiFi. Myloasm recovers previously inaccessible within-species diversity; we recovered six complete Prevotella copri single-contig genomes from a gut metagenome and eight complete TM7 (Saccharibacteria) contigs with >93% similarity from an oral metagenome. With this improved resolution, we resolved two 98% similar ermF antibiotic resistance genes spreading through distinct strain-specific mobile genetic elements in a human gut.

bioinformatics↗

bioRxiv2025

Enhancers mediate euchromatin hopping at chromatin contact points

Enhancer-mediated gene activation involves the recruitment of chromatin modifiers and RNA polymerase to target promoters, but it is unknown if enhancers influence chromatin beyond their target genes. Euchromatin and heterochromatin associated histone modifications separate the genome into opposing nuclear compartments. Whereas heterochromatin marks are known to spread from one modified nucleosome to another, no such ability has been ascribed to euchromatin. Using mono-allelic enhancer deletions, native ChIP-seq, and an engineered interaction between an enhancer and transcriptionally inert DNA, we show that enhancers mediate the acquisition of euchromatin features at distal regions through chromatin looping. We term this phenomenon euchromatin hopping and found it occurring on average [~]270kb bidirectionally from enhancers, redefining our understanding of enhancer-mediated chromatin architecture with implications on enhancer identification using chromatin features. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/674255v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@12c6e9aorg.highwire.dtl.DTLVardef@1165feorg.highwire.dtl.DTLVardef@3f08c8org.highwire.dtl.DTLVardef@598bd3_HPS_FORMAT_FIGEXP M_FIG C_FIG Euchromatin hopping modelFigure showing the proposed euchromatin hopping model. TFs recognize and bind to their binding sites in an active enhancer region. Upon activation enhancers recruit coactivators and RNAPII forming a condensate that supports gene activation. After an abundance of transcriptional machinery and coactivators are recruited, adjacent TF bound sites acquire euchromatin features through physical proximity to the active compartment, we call these regions "bystanders". Upon enhancer deletion, condensate formation is lost and active euchromatin marks are not acquired at the gene promoter or other enhancer chromatin contacts. TFs are displayed in yellow, coactivators in green, RNAPII in pink, and histone modifications in red.

molecular biology↗