Biology subjects

Peng, Y.

Publications and source records attributed to Peng, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Uncovering structural determinants of peptide recognition by public and private T-cell receptors

Public T cell receptors (TCRs) recurrently emerge across individuals in response to common pathogens, yet the structural and biophysical basis distinguishing public from private clonotypes remains incompletely defined. Here, we combine epitope mapping, single-cell TCR sequencing, and single-particle cryo-electron microscopy to dissect CD8+ T cell responses to the immunodominant SARS-CoV-2 ORF3a(207-215) epitope presented by HLA-A*01:01. Among responding clonotypes, we identify a shared public TCR (TCRpub) and an individual-specific private TCR (TCRpriv) that use nearly identical TRBV5-1 {beta} chains but distinct chains. Both clonotypes exhibit comparable micromolar affinity and functional avidity, yet their structures reveal different antigen-recognition modes. We determined cryo-EM structures of the TCRpub and TCRpriv in complex with ORF3a(207-215)/ HLA-A*01:01 at [~]3 [A] resolution. Despite targeting the same epitope, the two receptors engaged the peptide-MHC complex with distinct CDR-loop orientations and contact footprints: TCRpub engages the peptide through a peptide-centric AGDL CDR3{beta} motif and focuses interactions on the MHC 2-helix, whereas TCRpriv distributes contacts across both MHC -helices via a canonical CDR3{beta} configuration. These findings illustrate how near-identical {beta} chains can yield divergent recognition strategies to recognise the same pMHC ligand through alternative -chain pairing. More broadly, this work establishes cryo-EM as a robust approach for resolving physiological-affinity TCR/pMHC complexes, providing mechanistic insight into how public TCRs emerge and persist in antiviral immunity.

immunology↗

bioRxiv2025

Single-nucleotide resolution mapping of m6A of zebrafish mRNAs in early embryonic development links m6A modifications to the maternal-to-zygotic transition

N6-methyladenosine (m6A) is the most abundant epigenetic modification on eukaryotic mRNA and has important roles in gene expression. While m6A distribution and localization have been defined in zebrafish using antibody-based methods, no research has been published on the distribution of m6A during zebrafish embryogenesis with single-base precision. Here, we present the transcriptome-wide m6A landscape at single-nucleotide resolution during zebrafish early embryonic development using m6A-selective allyl chemical labeling and sequencing (m6A-SAC-seq). We identify over 36,000 high-confidence unique m6A sites that are primarily located in the DRACH consensus motif in long internal exons, 3UTRs, and near stop codons. Our results show a >4-fold decrease in m6A levels from 256-cell to 50% epiboly, clearly linking this methylation to zebrafish maternal-to-zygotic transition. We highlight that differential methylation between developmental stages was observed in transcripts associated with mRNA metabolism, translational processing, and organ development.

genomics↗

bioRxiv2025

De Novo Hepatic Pyrimidine Synthesis Regulates Systemic Energy Homeostasis

Fasting blood uridine is increased in obesity and type 2 diabetes (T2D), but the significance of hepatic uridine biosynthesis to the etiology of both remains elusive. We found that de novo pyrimidine synthesis in the liver is reduced by fasting and diet-induced obesity, while suppression of hepatic pyrimidine synthesis promotes obesity and insulin resistance. The metabolic sequalae of hepatic pyrimidine synthesis suppression, however, is not associated with altered plasma uridine concentration. Instead, it is associated with an increased hepatic glucose production and a decreased hepatic insulin clearance, two key functions of hepatocytes in regulating systemic energy homeostasis. We found that enhanced gluconeogenesis is the primary reason for increased hepatic glucose production. Moreover, uridine, which was maintained stable in the circulation by adipose tissue and the liver, preferentially shut down pyrimidine synthesis in hepatocytes but not adipocytes at blood concentrations that occur with fasting. Remarkably, uridine, at fasting levels, increases gluconeogenesis further in hepatocytes when de novo pyrimidine synthesis is suppressed, indicating a synergistical action of uridine and its biosynthesis pathway in promoting hepatic glucose production, a mechanism highly relevant to the pathophysiology of insulin resistance in obesity. Theologically, maintenance of blood uridine within the narrow range protects mammals from high-rate spontaneous tumorigenesis. Since obesity promotes an increase in blood uridine from adipocytes, suppressing uridine synthesis in hepatocytes becomes a critical response to lower spontaneous tumorigenesis. Pyrimidine synthesis suppression in hepatocytes, however, promotes gluconeogenesis and ultimately triggers obesity and T2D. These findings suggest a new paradigm for the etiology of metabolic deterioration in diet-induced obesity, in which perturbations in uridine promotes obesity and T2D.

pathology↗

bioRxiv2025

N6-methyladenosine regulation of mRNA translation is essential for early human erythropoiesis

N6-methyladenosine (m6A) is an abundant modification of mRNA with important regulatory roles in normal and malignant hematopoiesis. We previously reported that in human erythroid leukemia (HEL) cells, m6A mRNA marking selectively regulates translation of essential erythropoiesis genes required for in vitro differentiation and human erythroid colony formation. Here, we further investigated the timing and nature of requirement for m6A-methyltransferase (MTase) activity during human erythropoiesis, using a standardized in vitro erythroid differentiation assay for hHSPCs. We identified two critical m6A regulated developmental windows in BFU-E and during the transition from CFU-E to proerythroblasts. These windows of m6A-MTase requirement coincide with rising global m6A levels, which peak in proerythroblasts. After proerythroblast formation, however, m6A -MTase activity is dispensable for differentiation, proliferation, and survival. In BFU-E, m6A-MTase promotes proliferation but is dispensable for differentiation, while, in CFU-E, both m6A -MTase and the YTHDF family of m6A readers are essential for differentiation to proerythroblasts. Mechanistically, in CFU-E, m6A MTase activity enhances translation of ribosomal and oxidative phosphorylation (OXPHOS) genes, thereby elevating global protein synthesis rates and enabling efficient erythroblast formation. We propose that this form of translational regulation by m6A emerged as an evolutionary adaptation to meet the high translational demands of human erythropoiesis.

developmental biology↗

bioRxiv2025

High-Concordance Validation of Droplet Digital PCR and Next-Generation Sequencing for EGFR Mutation Detection Across Diverse Biospecimens in a Large-scale NSCLC Cohort Study

BackgroundsNext-generation sequencing (NGS) and droplet digital PCR (ddPCR) are both established methods for detecting EGFR mutations in non-small cell lung cancer (NSCLC). However, comprehensive validation of their concordance in mutation detection and variant allele frequency (VAF) quantification across heterogeneous sample types remains limited. Inconsistent results from different sample types (e.g., cfDNA, FFPE) pose a significant challenge to clinical decisions. This is particularly critical for advanced NSCLC patients, who often rely on liquid biopsy, yet the concordance between liquid and tissue-based testing lacks validation in large-scale studies. Another issue in clinical practice is that many tumor samples are limited in quantity, making it difficult to meet testing requirements. Therefore, it is worth exploring whether pre-capture NGS libraries can serve as substitutes for original DNA. MethodsIn this study, we first developed three assays to detect EGFR L858R, exon 19 deletions (Ex19del) and T790M, respectively using ddPCR platform. Their Limit of Detection (LOD) could reach 0.01% at 100 ng of input DNA. Subsequently, we conducted a large retrospective clinical study to systematically compare the detection performance of ddPCR and NGS across three mutation types using approximately 1,000 EGFR-positive samples, including cell-free DNA (cfDNA), pre-capture NGS libraries of cfDNA (cfDNA-prePCR), FFPE-derived DNA (ffpeDNA), pre-capture NGS libraries of FFPE-derived DNA (ffpeDNA-prePCR), fresh tumor tissue DNA (ttDNA), pre-capture NGS libraries of ttDNA (ttDNA-prePCR), pleural effusion supernatants DNA (peDNA), and pre-capture NGS libraries of peDNA (peDNA-prePCR). They were analyzed for detection concordance and VAF correlation. Especially, we made comparisons of the tumor DNA, including ctDNA and tumor tissue DNA, with their paired pre-capture NGS library. ResultsKey findings demonstrated excellent overall agreement between NGS and ddPCR. The mutation detection concordance rates were 98.72% (overall), with subtype-specific rates of 98.93% (L858R), 99.23% (Ex19del), and 97.14% (T790M). VAF measurements between ddPCR and NGS showed exceptional correlation (Pearsons r = 0.975, P<0.001). Notably, pre-capture NGS libraries showed remarkable VAF concordance with their source materials (0.993 for cfDNA libraries vs cfDNA; 0.998 for tumor tissue libraries vs tumor DNA with EGFR L858R; 0.991 for tumor tissue libraries vs tumor DNA with EGFR Ex19del). ConclusionsNGS and ddPCR demonstrate high concordance in EGFR mutation detection and VAF quantification, supporting their complementary roles in clinical testing. Using pre-capture libraries as an alternative to source samples can avoid repeat biopsies and enables subsequent testing for patients with inadequate FFPE sample quantity. These findings establish an evidence base for integrated diagnostic paradigms leveraging NGSs multiplexing power and ddPCRs sensitivity.

cancer biology↗

bioRxiv2025

Cascade-Targeting Nanoparticles for Reversing Chemoresistance in Osteosarcoma

Osteosarcoma (OS) remains the most prevalent primary malignant bone tumor in adolescents, with chemotherapy resistance significantly limiting the efficacy of current treatments. To address the challenges of chemoresistance driven by DNA repair mechanisms and drug efflux, we developed a biomimetic cascade-targeting drug delivery system, TAT-mPDO@cRGD-M. This system combines a polydopamine (mPDA) core with strong photothermal and drug-loading capacities, enabling the co-delivery of cisplatin (CDDP) and olaparib (OLA). Surface functionalization with the nuclear localization peptide TAT and cloaking with osteosarcoma cell membranes modified with cRGD peptides allows for selective tumor recognition, nuclear targeting, and stimuli-responsive drug release. Upon near-infrared (NIR) irradiation, the platform enhances DNA damage, suppresses the PI3K-AKT signaling pathway, and promotes apoptosis while inhibiting epithelial-mesenchymal transition (EMT). In vitro and in vivo studies demonstrated that TAT-mPDO@cRGD-M exhibits potent antitumor activity against cisplatin-resistant osteosarcoma, maintaining strong therapeutic efficacy under low-power NIR irradiation without causing significant damage to normal tissues. This study highlights a highly specific and biocompatible therapeutic approach that offers promising potential for overcoming chemotherapy resistance in osteosarcoma and advancing clinical treatment strategies.

cancer biology↗

bioRxiv2025

The Function of Efhd1+ Telocytes in the Synovial Lymphatic System and Inflammatory-Erosive Arthritis

Resting collecting lymphatic vessels (cLVs) sense edema in distal joints and initiate contractions via unknown mechanisms. Rheumatoid arthritis (RA) patients have lymphatic drainage deficiencies from affected joints, and defects in the synovial lymphatic system exacerbate inflammatory-erosive arthritis in animal models. To understand this, we generated Efhd1-CreERT2 and Myoc-CreERT2 mice for cell-specific genetic gain and loss of function studies. These mice were crossed with tdTomato reporter (Ai9) mice, and studies showed selective tamoxifen-induced transgene expression in CD31-/CD34+ telocyte-like cells in knee and ankle synovium, and in networks physically associated with mast cells proximal to popliteal lymphatic vessels (PLVs). Consistent with the known loss of CD31-/CD34+ telocyte in RA synovium, these cells were also decreased in TNF-tg knees and partially recovered by anti-TNF treatment. Ultrastructural and gene expression studies confirmed a distinct telocyte phenotype versus closely related fibroblasts. In vivo depletion studies in tamoxifen-treated Efhd1-CreERT2 and Myoc-CreERT2 mice crossed to diphtheria toxin alpha-floxed (DTAflox) mice demonstrated telocyte requirements for physiologic lymphatic drainage and resolution of joint inflammation and focal erosions from zymosan-induced arthritis in the knee. In vitro studies demonstrated increased sensitivity to osmotic shock and decreased motility versus fibroblasts, and telocyte potential to differentiate into myofibroblasts on stiff matrix. Collectively, these findings support a model of joint homeostasis in which osmotic pressure-sensing telocyte networks extend from the synovium into mast cells proximal to joint-draining cLVs, and telocyte loss is associated with defects in the synovial lymphatic system and increased susceptibility to joint inflammation and structural damage from arthritis. TeaserThis study discovered a unique cell type (telocytes) responsible for draining inflammation from arthritic joints.

cell biology↗

bioRxiv2025

Widespread horizontal transfer and strong selection enhance microbial adaptation in Antarctic soils

Terrestrial Antarctica harbors compositionally diverse and functionally distinct microbial life. Yet the ecological and evolutionary processes enabling these communities to adapt to the polyextreme conditions of the continent remain largely unknown. Here, we address how horizontal gene transfer (HGT) and de novo mutations influence adaptation of microbial communities in 16 proglacial and mountainous Antarctic soils, from a combination of short- and long-read datasets. Phylogenetic reconciliation and mobile genetic element analysis of 676 metagenome-assembled genomes show that HGT events occur frequently within these microbial communities. While the transferred genes are distributed across diverse functional categories, those involved in energy metabolism are exchanged at relatively higher frequency. The genes for aerotrophy, i.e. the consumption of atmospheric trace gases to provide energy, carbon, and hydration, are among the most frequently and widely disseminated. Approximately a quarter of all carbon monoxide (CO) dehydrogenases and [NiFe]-hydrogenases that catalyze atmospheric CO and hydrogen (H2) oxidation are predicted to be horizontally acquired and are often closely associated with mobile genetic elements. In parallel, analysis of polymorphisms in protein-encoding genes suggests widespread purifying selection, demonstrated by a predominance of synonymous mutations. This selection is particularly intense for aerotrophy genes, providing further evidence that this process is critical for microbial survival in Antarctica. The genetic variation of hydrogenases is tightly associated with their predicted protein structures, with intense selection acting on critical sites that preserve their stability and function in Antarctic environments. Together, these findings show that previously unrecognised eco-evolutionary dynamics shape the composition and function of Antarctic desert microbial communities, and confirm aerotrophy is a strongly selected and horizontally disseminated trait.

microbiology↗

bioRxiv2025

Structural modeling reveals the mechanism of motor ATPase coordination during type IV pilus retraction

Diverse bacterial species utilize surface appendages called type IV pili (T4P) to interact with their environment. These structures are dynamically extended and retracted from the cell surface, which is critical for diverse functions. Some T4P systems rely on two distinct motor ATPases, PilT and PilU, whose combined activities are required to power forceful T4P retraction. However, the mechanism by which these motors coordinate to facilitate T4P retraction has remained unclear. Here, we utilize the competence T4P in V. cholerae as a model system to elucidate the molecular basis for PilT-PilU coordination during T4P retraction. Specifically, we modeled the interactions between PilT and PilU using AlphaFold 3 and molecular dynamics (MD) simulations. We then empirically tested these models using a combination of cytological and high-resolution genetic approaches. Our results reveal that interactions between PilT and the PilU C-terminus are critical for these motors to coordinate to drive T4P retraction. Finally, we show that PilT-PilU interactions are broadly conserved in T4P systems from diverse bacterial species, and we experimentally validate that they are required for T4P retraction in Acinetobacter baylyi. Together, this work expands our fundamental understanding of T4P dynamics, and more broadly it provides mechanistic insight into how these ATPases coordinate to assemble some of the strongest biological motors in nature. SIGNIFICANCEDiverse bacterial species use filamentous surface appendages called type IV pili (T4P) to move along surfaces, take up DNA for horizontal gene transfer, and stick to biotic and abiotic surfaces. The forceful retraction of these filaments is often required for these behaviors. In many T4P systems, the combined activity of two distinct motor ATPase proteins is required for forceful retraction; however, a detailed understanding of how these motor proteins interact to promote forceful retraction is currently lacking. Here, we use an integrated approach to uncover the molecular mechanism for motor ATPase coordination. Furthermore, we show that this mechanism is broadly conserved in diverse T4P systems.

microbiology↗

bioRxiv2025

LRP8 is a Receptor for Yellow Fever Virus

Yellow fever virus (YFV), an arbovirus causing substantial human morbidity and mortality, was the first human virus discovered over a century ago. The live-attenuated 17D vaccine is among the most successful vaccines in medicine. Despite the importance of YFV, its receptor has remained unknown. Here, we performed a barcoded, genome-wide human ORF library screen and identified LRP8 (also named APOER2) as a receptor for YFV. We show that LRP8 expression specifically boosts YFV infection in cell lines by promoting entry. AAV-mediated expression of human LRP8 in mouse liver aggravates infection and pathology. LRP8 knockdown abolishes YFV infection in brain cells, primary human hepatocytes, and notably in mosquitoes. Biochemically, LRP8 directly interacts with YFV particles via the viral envelope protein. This function of LRP8 is conserved across species, particularly in mosquitoes and primates. A soluble LRP8 decoy protein can block YFV infection in vitro and in mice, providing a potential therapeutic or prophylactic strategy. Our findings provide groundwork for understanding YFV entry, tropism, and pathogenesis, and may enable development of novel therapeutics to treat YFV infection.

microbiology↗

bioRxiv2025

Genetically Engineered Cell Membrane-Coated Nanodrug for Targeted Treatment of Thyroid Cancer

Thyroid cancer is the most common endocrine malignancy, particularly in patients with radioactive iodine-refractory differentiated thyroid cancer (RAIR-DTC), who have limited treatment options and poor clinical prognosis. In this study, doxorubicin (DOX) and sorafenib (SOR) were loaded into the photothermal conversion agent mesoporous polydopamine (mPDA), forming mPDS. Tumor cell membrane coating engineering resulted in the formation of mPDS@CAR-M, significantly improving tumor targeting. After internalization by tumor cells, the loaded drugs are rapidly released under near-infrared (NIR) laser irradiation. mPDS@CAR-M effectively inhibits tumor cell proliferation by enhancing oxidative stress, suppressing the PI3K-AKT-mTOR signaling pathway, and inducing cytotoxic autophagy. By activating harmful autophagy, mPDS@CAR-M further inhibits the epithelial-mesenchymal transition (EMT) process, reducing tumor cell migration capacity. In vivo experiments showed that mPDS@CAR-M significantly reduced tumor volume, with its therapeutic efficacy closely related to the expression level of the targeted surface antigen. Therefore, mPDS@CAR-M demonstrates significant potential in the treatment of RAIR-DTC, providing a novel direction for further clinical exploration.

cancer biology↗

bioRxiv2025

Blind Virtual Screening at Scale: A Scalable End-to-End Pipeline for Blind Docking and Affinity Prediction

Accurate and scalable prediction of protein-ligand interactions remains a central challenge in computational drug discovery, especially when the binding site is unknown (i.e., blind docking). We present a high-throughput, end-to-end algorithm for virtual screening that combines DiffDock, a diffusion-based generative model for blind docking, with UniDock Vina, an algorithm for rapid scoring. We benchmarked this approach on the CASF-2016 and DUD-E datasets, analyzing pose quality, scoring accuracy, and screening performance. We find that competitive screening power can be achieved when generating and scoring as few as three poses and without pose refinement, which facilitates scalability. Notably, our method achieves 86.78% and 82.00% for the percent of actives among the top 1% and 10% of ranked ligands, respectively, when generating as few as three poses per protein-ligand pair. The workflow is scalable, supporting blind docking and affinity prediction at a mean throughput of 0.76 seconds per protein-ligand pair when generating 40 ligand poses in batched mode parallelized to 8 NVIDIA A100 80G GPUs. These results demonstrate that accurate, large-scale blind virtual screening is feasible and offers a practical solution for screening against novel or less characterized protein targets. Code is available at: https://github.com/xinyu-dev/blind-screening-benchmark

bioinformatics↗

bioRxiv2025

PI-FC: Pre-training Individual-specific Functional Connectome through State-invariant Contrastive Learning

Functional MRI enables non-invasive mapping of brain connectivity, yet its clinical translation remains hindered by uncontrolled state-dependent variability that obscures individual-specific signatures during routine scanning. Here we introduce PI-FC -- a deep learning framework leveraging state-invariant contrastive learning to extract stable individual brain signatures across diverse arousal levels, cognitive states, and temporal scales spanning tens of seconds to hours. PI-FC achieves equivalent phenotypic prediction accuracy using substantially reduced scanning time, and eliminates state-dependent effects varying task demands and brain states. Trained on 36,119 subjects across 8 independent datasets, our model demonstrates superior cross-site generalization and outperforms traditional functional connectome (FC) in predicting neuropsychiatric conditions including schizophrenia, autism, depression, and anxiety. Furthermore, PI-FC enables zero-shot inference of brain age, biological sex, and cognitive ability without site-specific retraining. Overall, PI-FC represents a robust, clinically scalable framework that overcomes fundamental barriers to real-world deployment of precision functional neuroimaging.

neuroscience↗

bioRxiv2025

Integrated Multi-Omics Analysis for Molecular Subtyping in NSCLC: A Cohort Study

Lung cancer remains the leading cause of cancer-related morbidity and mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases. Current histopathological classification and driver gene testing provide limited prognostic and therapeutic guidance due to intra-tumoral heterogeneity and incomplete characterization of the tumor microenvironment (TME). Here, we constructed single- and multi-omics molecular classification systems for NSCLC by integrating transcriptomic, genomic, epigenomic, proteomic, and TME data from TCGA LUAD and LUSC cohorts. Single-omics analyses revealed distinct molecular patterns, including DNA methylation subtypes associated with sex and histology. Multi-omics integration identified five consensus subtypes closely corresponding to histology, with three immune-activated (CS2-CS4) and two immunosuppressive (CS1, CS5) subtypes. While overall survival did not differ significantly, progression-free survival analysis highlighted CS4 as a high-risk subtype with KRAS-driven genomic alterations. These findings provide a framework for NSCLC molecular stratification and highlight molecular and immune features that could guide future research on targeted therapies and immunotherapy.

bioinformatics↗

bioRxiv2025

scDIAGRAM: Detecting Chromatin Compartments from Individual Single-Cell Hi-C Matrix without Imputation or Reference Features

Single-cell Hi-C (scHi-C) provides unprecedented insight into 3D genome organization, but its sparse and noisy data pose challenges in accurately detecting A/B compartments, which are crucial for understanding chromatin structure and gene regulation. We presented scDIAGRAM, a data-driven method for annotating A/B compartments in single cells using direct statistical modeling and graph community detection. Unlike existing approaches, scDIAGRAM operates without relying on external information, such as the CpG density or imputation techniques, and preserves cell-to-cell heterogeneity. Accuracy and robustness of scDIAGRAM were illustrated through simulated scHi-C datasets and a human cell line. We applied scDIAGRAM to real scHi-C datasets from the mouse brain cortex, mouse embryonic development, and human acute myeloid leukemia (AML), demonstrating its ability to capture compartmental shifts associated with transcriptional variation. This robust framework offers new insights into the functional roles of chromatin compartments at single-cell resolution across various biological contexts.

bioinformatics↗

bioRxiv2025

Integrative Species Delimitation in a Speciation Continuum: Phylogenomics, Cryptic Diversity, Diversification and Historical Biogeography of Sinocyclocheilus Cavefish

The transition from structured populations to distinct species often unfolds along a speciation continuum. However, empirically dissecting this continuum poses challenges for species delimitation, particularly in rapid radiations marked by recent divergence, incomplete lineage sorting, and gene flow. The species-rich Sinocyclocheilus cavefish radiation of Southwest China, an emerging evolutionary multi-species model system, shows a notable mismatch between its high morphological diversity and the limited divergence observed in commonly used mitochondrial DNA markers. This pattern suggests that true species richness may be underestimated. Yet, comprehensive genome-wide approaches to resolve species boundaries in this group are still lacking. To address this, we combine phylogenomics, coalescent-based species delimitation, population genetics, and historical biogeography, using both genome-wide RAD-seq and multi-locus Sanger data (including nuclear and mitochondrial DNA). Our phylogenomic analyses resolve major clades and reveal substantial cryptic diversity, well beyond what was detected by earlier markers. Species delimitation based on RAD-seq genomic data identifies several cryptic evolutionary lineages. We recover a dynamic divergence history shaped by isolation and episodic connectivity. Biogeographic reconstruction supports a mid-Miocene origin following a major vicariance event, with subsequent founder-event dispersals into subterranean habitats. This long history of fragmentation is further complicated by reticulation and ancestral polymorphism, and is reflected in present-day patterns of restricted gene flow across river valleys. These results highlight the utility of integrative genomic approaches in resolving species boundaries and uncovering the evolutionary processes that underlie high diversity in large and complex radiations.

evolutionary biology↗

bioRxiv2025

Euktect: Enhanced Eukaryotic Sequence Detection and Classification in Metagenomes via the DNA Language Model

The current taxonomy classification of DNA sequences in metagenomics primarily relies on alignment against reference databases. However, the eukaryotic species in genome databases are not sufficient as there exist numerous unculturable eukaryotes inside metagenomes. These limitations hinder functional and evolutionary analyses of eukaryotes across distinct environmental samples. To overcome these limitations, we created Euktect, a deep-learning-based toolbox for reliable, alignment-free classification of eukaryotic DNA sequences across different phylogenetic levels from metagenome datasets. Euktect achieves high accuracy in extraction of eukaryotic sequences longer than 500bp from the assembled contigs of metagenomes, significantly outperforming existing methods. Furthermore, we developed an algorithm that integrates Euktects predictions with existing tools to refine metagenome-assembled genomes (MAGs), substantially increasing the yield of high-quality eukaryotic MAGs for the downstream analysis. Beyond eukaryotic detection, Euktect incorporates two specialized models: a high-precision classifier for fungal phyla, and a hierarchical classifier that accurately identifies sequences from specific fungal genera (e.g., Candida) in diverse metagenomic samples. Significantly, this framework enables prediction of host disease status (e.g., inflammatory bowel disease) by linking eukaryotic sequence identification to clinical phenotypes through machine learning models. Collectively, Euktect enables accurate reconstruction and functional annotation of eukaryotic genomes from metagenomes at large scale, thereby empowering the comprehensive utilization of sequenced eukaryotic species for downstream evolutionary and clinical research.

bioinformatics↗

bioRxiv2025

Rapid adaptation and extinction across climates in synchronized outdoor evolution experiments of Arabidopsis thaliana

Climate change is threatening species with extinction, and rapid evolutionary adaptation may be their only option for population rescue over short ecological timescales. However, direct observations of rapid genetic adaptation and population dynamics across climates are rare across species. To fill this gap, we conducted a replicated, globally synchronized evolution experiment with the plant Arabidopsis thaliana for 5 years in over 30 outdoor experimental gardens with distinct climates across Europe, the Levant, and North America. We performed whole-genome sequencing on [~]70,000 surviving reproductive individuals and directly observed rapid and repeatable adaptation across climates. Allele frequency changes over time were parallel in experimental evolution replicates within the same climates, while they diverged across contrasting climates--with some allele frequency shifts best explained by strong selection between -46% to +60%. Screening the genome for signals of rapid climate adaptation identified a polygenic architecture with both known and novel adaptive genetic variants connected to important ecological phenotypes including environmental stress responses, CAM5 and HEAT SHOCK FACTORs, and germination and spring flowering timing, CYTOCHROME P450s and TSF. We found evolutionary adaptation trends were often predictable, but variable across environments. In warm climates, high evolutionary predictability was associated with population survival up to 5 years, while erratic trends were an early warning for population extinction. Together, these results show rapid climate adaptation may be possible, but understanding its limits across species will be key for biodiversity forecasting.

evolutionary biology↗