Biology subjects

Jiao, W.

Publications and source records attributed to Jiao, W..

13 recordsLinked to original sources

bioRxiv2026

Decoding Cell-level Circadian Phase and Rhythm-state Remodeling in Single-cell Transcriptomes With scRhythmBayes

Current circadian omics analysis tools have been developed primarily for bulk time-series. However, heterogeneous single-cell datasets require analysis and interpretation of rhythmic programs across different cells, cell types, and biological conditions. In these datasets, cellular circadian phase is usually unobserved, and sample-level zeitgeber time provides temporal information but does not define the exact phase of every cell. Existing methods address only selected aspects of this problem and do not model how cell-level phase evidence informs gene-level rhythmic parameters and rhythm-state remodeling. Here we present scRhythmBayes, a new probabilistic algorithm for phase-resolved circadian analysis in heterogeneous single-cell transcriptomes. scRhythmBayes combines a seed-gene count likelihood with a stratum-aware circular prior to infer cell-level circadian phase, incorporates phase support into gene-level rhythmic modeling, and assigns posterior probabilities to interpretable rhythm-state categories, including rhythm gain, rhythm loss, amplitude remodeling and phase shifts. In heterogeneous simulations, scRhythmBayes achieved higher phase-recovery accuracy than existing phase-inference methods and maintained balanced performance across rhythmic gene detection, parameter recovery, and rhythm-state classification. Stress tests defined practical requirements for seed-gene support, zeitgeber anchoring, temporal sampling density, and cell number. In mouse liver, scRhythmBayes revealed distinct circadian phase occupancy and rhythm-state organization between periportal and pericentral hepatocytes, supporting a temporal dimension of liver zonation. It also identified cell-type-specific rhythmic markers that were largely distinct from conventional static markers, indicating that cellular identity includes temporal programs not captured by average expression. In human heart disease data, phase-coordination and phase-distribution analyses identified cell-type-selective temporal disorganization rather than uniform circadian disruption across the tissue. scRhythmBayes therefore provides a statistically grounded approach for resolving circadian organization across cells, genes, cell types and biological conditions.

bioinformatics↗

bioRxiv2026

Gut Virome Diversity and Health Status in Rescued Pangolins: Metaviromics Reveals Parvovirus as a Key Virus Associated with Disease

BackgroundPangolins are critically endangered mammals that suffer from high rates of gastrointestinal disease during captivity, yet the role of the gut virome in their health remains unexplored. This study presents the first comprehensive characterization of the gut DNA virome in Malayan (Manis javanica) and Chinese (M. pentadactyla) pangolins across different health states. ResultsMetaviromic sequencing of 16 fecal samples from healthy, diarrheal, pneumonic, free-ranging, and deceased pangolins generated 7.2-11.8 Gb clean data per sample. A total of 12 viral phyla, 26 families, 219 genera, and 1,132 species were identified. Caudovirales phages (Siphoviridae, Myoviridae, and Podoviridae) dominated the gut virome of healthy individuals, with phage content exceeding 90% in most healthy samples. However, diseased and deceased individuals exhibited a significant reduction in phage proportion (94.5% vs. 53.3%, P = 0.02), accompanied by a dramatic increase in eukaryotic viruses--particularly Parvoviridae, which accounted for 66% of the virome in deceased Malayan pangolins. Iridoviridae (38%) and Polydnaviridae (34%) dominated in deceased Chinese pangolins. SIMPER analysis identified Parvoviridae as the primary contributor to virome dissimilarity between healthy and diseased Malayan pangolins, whereas Iridoviridae and Polydnaviridae were the key contributors for Chinese pangolins. LEfSe analysis revealed 12 biomarker viruses in free-ranging pangolins (predominantly Staphylococcus and Escherichia phages), six in healthy Chinese pangolins (predominantly Streptococcus phages and Lactobacillus viruses), and six in deceased Malayan pangolins (predominantly vertebrate viruses). KEGG functional annotation revealed that genes related to DNA replication, repair, and recombination were the most abundant, suggesting frequent genomic recombination within the pangolin gut virome. ConclusionsThe gut virome of pangolins is closely associated with health status. Disease induces a shift from a phage-dominated to a eukaryotic virus-dominated virome, with Parvoviridae and Iridoviridae emerging as candidate pathogenic viruses in Malayan and Chinese pangolins, respectively. These findings provide molecular evidence for virome monitoring in pangolin conservation and highlight the need for targeted surveillance of ImportancePangolins are the most trafficked mammals in the world, and all eight species are critically endangered. During rescue and captive care, these animals suffer from high rates of gastrointestinal disease, yet the role of viruses in their gut health has never been studied. This research provides the first comprehensive map of the gut virus community in pangolins, revealing that healthy individuals carry a virus community dominated by beneficial bacterial viruses called phages, while sick and dying animals show a dramatic shift toward disease-causing viruses. Notably, parvoviruses emerge as potential pathogens in Malayan pangolins, while iridoviruses dominate in deceased Chinese pangolins. These findings offer a new tool for monitoring pangolin health in rescue centers: by tracking the balance between beneficial phages and harmful viruses, veterinarians may be able to detect illness earlier and improve survival rates. The study also highlights the importance of environmental exposure for maintaining a healthy gut virus community, supporting the creation of semi-natural enclosures for rescued pangolins. Beyond conservation, this work contributes to our understanding of how viruses move between wildlife and humans, which is critical for preventing future disease outbreaks.

microbiology↗

bioRxiv2026

Legacy Effects of Land-Use Land-Cover Change on Species Distribution Dynamics: Evidence from a landscape of diverse biogeographic crossroads

Land-use and land-cover (LULC) change is a dominant driver of biodiversity loss, yet its long-term role in restructuring species distribution remains poorly understood due to limited historical baselines and the scarcity of long-term analyses across multiple ecological transition zones. Here, we investigate nearly two centuries of land-use change across a biogeographically diverse region to evaluate how landscape transformation has reshaped vertebrate distribution range dynamics, and whether ecoregional context, habitat specialization, and taxonomic identity better explain these patterns than recent landscape change alone. Using Texas, a biogeographic crossroads with diverse ecoregional zones and a long history of intensive land-use, we quantify distributional changes in 100 native vertebrate species (mammals, birds, reptiles, and amphibians), using Vernon Baileys late nineteenth-century surveys as a historical benchmark. We integrated multi-temporal LULC datasets with spatial and multivariate analyses to assess how habitat change, species traits, and regional context relate to patterns of range expansion, contraction, and redistribution. We show that Texas has undergone non-linear landscape transformations characterized by early agricultural expansion followed by cropland abandonment, shrubland encroachment, and rapid urbanization. Range contractions were most pronounced among amphibians, reptiles, and habitat specialists, whereas generalist species and many birds exhibited greater range stability or expansion. Across taxa, primary habitat, vertebrate class, and ecoregional context emerged as the strongest predictors of distributional change, underscoring the importance of historical and environmental context over simple measures of habitat loss and fragmentation. These results indicate that while long-term LULC change establishes the underlying landscape template, species responses are structured by ecological context, including habitat affinity, taxonomic traits, and regional environmental gradients. By linking historical landscape trajectories to contemporary biodiversity patterns, this study provides a transferable framework for investigating how land-use legacies influence species distributions and community reassembly in heterogeneous human-dominated landscapes, highlighting the importance of adaptive capacity and connectivity for conservation planning.

ecology↗

bioRxiv2026

Time-resolved cryo-EM reveals conformational trajectory of allosteric activation in isocitrate lyase

Isocitrate lyase 2 (ICL2) from Mycobacterium tuberculosis undergoes dramatic conformational rearrangements upon binding to the allosteric effector acetyl-CoA. Time-resolved cryo-EM captured conformational states along the ICL2 activation trajectory, revealing how acetyl-CoA binding at the allosteric sites leads to asymmetric, half-of-site activity at the catalytic centres. These findings support a conformational selection model of allostery, whereby acetyl-CoA binding shifts the pre-existing equilibrium towards an active state of the enzyme.

biochemistry↗

bioRxiv2025

Dynamic allostery drives acetyl-CoA-mediated activation of Mycobacterium tuberculosis isocitrate lyase 2

Mycobacterium tuberculosis isocitrate lyase 2 (ICL2) is an allosterically regulated enzyme that enables the bacterium to survive on non-glycolytic substrates during infection. Previous studies showed that ICL2 is allosterically regulated by acetyl-CoA and its analogues but the molecular mechanism underpinning this regulation is unknown. Here, we use protein NMR, crystallography, molecular dynamics, and mutagenesis studies to show that two unique structural features of ICL2, its C-terminal domain and a unique helical substructure on its N-terminal catalytic domain, play important roles in the enzymes allostery. In particular, we found that the binding of acetyl-CoA promotes the dimerisation of the C-terminal domain and disrupts its interactions with the unique helical substructure on the N-terminal domain. This leads to conformational changes in the ICL2 enzyme that induces activation. Taken together, our findings reveal, for the first time, how the binding of acetyl-CoA, which is not an ICL2 substrate, induces ICL2 activation. By extension, the work also identifies a novel allosteric mechanism controlling M. tuberculosis metabolism that is amenable to therapeutic manipulation. Significance StatementMycobacterium tuberculosis isocitrate lyase 2 (ICL2) was previously shown to be activated by acetyl-CoA and propionyl-CoA - two central metabolites generated by the metabolism of sugars and fatty acids. However, it is not known how the binding of these metabolites leads to the activation of ICL2. Together with its isoform ICL1, ICL2 has been shown to be essential for the survival and pathogenesis of the bacterium. Understanding how this regulation occurs can help design novel treatments to target this protein and eradicate these bacteria, which cause the most deaths worldwide due to a single bacterial agent. This system also presents a fascinating model to examine allostery in proteins, with the techniques illustrated in this paper being applicable to other allosteric proteins.

biochemistry↗

bioRxiv2024

Identification of novel inhibitors targeting serine acetyltransferase from Neisseria gonorrhoeae

Neisseria gonorrhoeae is an obligate human pathogen and the etiological agent of the sexually transmitted infection, gonorrhoea. The rapid emergence of extensively antimicrobial-resistant strains, including those resistant to all frontline antibiotics, has led to N. gonorrhoeae being labelled a priority pathogen by the World Health Organization, highlighting the need for new antimicrobial treatments. Given its absence in humans, targeting de novo cysteine biosynthesis has been identified as a promising avenue for developing new antimicrobials against drug-resistant bacteria. The biosynthesis of cysteine is catalyzed by two enzymes; serine acetyltransferase (SAT/CysE) which catalyzes the first step and O-acetylserine sulfhydrylase (OASS/CysK) that catalyzes the second step incorporating sulfur to form L-cysteine. CysE is reported to be essential for bacterial survival in several bacterial pathogens including N. gonorrhoeae. Here, we have conducted virtual inhibitor screening of commercially available compound libraries against SAT from N. gonorrhoeae (NgSAT). We have identified a hit compound with an IC50 of 13.9 {micro}M and analyzed its interactions with the enzymes active site. This provides a platform for the identification and development of novel SAT inhibitors to combat drug-resistant bacterial pathogens.

biochemistry↗

bioRxiv2024

pnetr: An R package for the PnET family of forest ecosystem models

O_LIEcosystem models offer a rigorous way to formalize scientific theories and are critical to evaluating complex interactions among ecological and biogeochemical processes. In addition to simulation and prediction, ecosystem models are a valuable tool for testing hypotheses about mechanisms and empirical findings because they reveal critical internal processes that are difficult to observe directly. C_LIO_LIHowever, many ecosystem models are difficult to manage and apply by scientists who lack advanced computing skills due to complex model structures, lack of consistent documentation, and low-level programming implementation, which facilitates computing but reduces accessibility. C_LIO_LIHere, we present the pnetr R package, which is designed to provide an easy-to-manage ecosystem modeling framework and detailed documentation in both model structure and programming. The framework implements a family of widely used PnET (net photosynthesis, evapotranspiration) ecosystem models, which are relatively parsimonious but capture essential biogeochemical cycles of water, carbon, and nutrients. We chose the R programming language since it is familiar to many ecologists and has abundant statistical modeling resources. We showcase examples of model simulations and test the effects of phenology on carbon assimilation and wood production using data measured by the Environmental Measurement Station (EMS) eddy-covariance flux tower at Harvard Forest, MA. C_LIO_LIWe hope pnetr can facilitate further development of ecological theory and increase the accessibility of ecosystem modeling and ecological forecasting. C_LI

ecology↗

bioRxiv2024

In silico generation of synthetic cancer genomes using generative AI

Cancer originates from alterations in the genome, and understanding how these changes lead to disease is crucial for achieving the goals of precision oncology. Connecting genomic alterations to health outcomes requires extensive computational analysis using accurate algorithms. Over the years, these algorithms have become increasingly sophisticated, but a severe shortage of open access gold-standard datasets presents a fundamental challenge. Since genomic data is considered personal health information, only an extremely limited number of deeply sequenced legacy cancer genomes can be shared and redistributed. As a result, tool benchmarking is often conducted on the same small set of genomes sequenced with older technologies and uncertain ground truths. This is a major obstacle to the development of improved analytic tools. To address this issue, we have developed OncoGAN, a novel generative AI tool that uses a combination of generative adversarial networks and tabular variational autoencoders to generate realistic but entirely synthetic cancer genomes based on training sets derived from large-scale genomic projects. Our results demonstrate that this approach accurately reproduces the scale, distribution, and characteristics of somatic point mutations, copy number alterations and structural variants across multiple common cancer types, while protecting donors privacy information. OncoGAN accurately recapitulates tumor type-specific mutational signatures as well as the positional distribution of somatic mutations. To evaluate the fidelity of the simulations, we tested the synthetic genomes using DeepTumour, a software capable of identifying tumor types based on mutational patterns, and demonstrated a high level of concordance between the synthetic genome tumor type and DeepTumours prediction of the type. We also showed that augmenting real donor data with OncoGAN-generated synthetic data could be used to train a more accurate version of DeepTumour. This tool will allow the generation of an extensive and realistic set of training and testing cancer genomes whose ground truth is known exactly. This advance provides computational biologists with the ability to develop realistic cancer genome benchmarking sets and make them available to the research community for the testing, development and enhancement of cancer genome analysis tools.

bioinformatics↗

bioRxiv2022

Japanese Encephalitis Virus NS1 Protein regulates the expression and distribution of TIM-1 to promote viral infection

Japanese encephalitis virus (JEV) is a mosquito-borne Flavivirus, which may cause severe encephalitis in humans, horses, and other animals. TIM-1 has been identified to be a receptor that promotes various viruses to enter into target cells in recent years. In the present study, we found that TIM-1 protein was significantly increased in A549 cells at the late stage of JEV infection, while the transcription levels of TIM-1 remained unaltered. Interestingly, we found that NS1 protein plays a key role in increasing the expression of TIM-1 in cells infected with JEV. Further, we found that the NS1 protein also efficiently regulates TIM-1 protein to distribute in the cytoplasm in JEV-infected cells, and the amount of TIM-1 protein located on the cell membrane was reduced instead. As a consequence, NS1 protein antagonize TIM-1 mediated viral restriction for further viral infection and propagation in the late stage of infection. In molecular mechanism, the molecular weight of TIM-1 increased a bit in the present of NS1. Expression of NEU1 down-regulated TIM-1 expression and oseltamivir treatment increased the expression of TIM-1. Therefore, our data indicated that JEV NS1 protein facilitated the sialylation modification of TIM-1 to up-regulate the level of TIM-1 expression and regulate its distribution. Collectively, our study revealed that JEV NS1 protein regulates the expression and distribution of TIM-1 by facilitating its sialylation to antagonize TIM-1-mediated JEV restriction for further infection. Understanding the functional interplays between TIM-1 and NS1 proteins will offer new insights into virushost interaction. IMPORTANCET-cell immunoglobulin and mucin domain protein 1 (TIM-1) is known to promote cellular entry of various enveloped viruses. We discovered a novel phenomenon of dynamic expression and functional regulation of TIM-1 during JEV infection. Firstly, TIM-1 protein increased in the cytoplasm at the late stage of JEV infection. Furthermore, JEV NS1 protein up-regulated the intracellular expression of TIM-1 and antagonize TIM-1-mediated viral restriction for further viral infection. In molecular mechanism, JEV NS1 protein facilitated the sialylation of TIM-1 to increase the level of TIM-1 expression and cytoplasm distribution. Taken together, at the late stage of infection, JEV employs a strategy in which NS1 promotes JEV release by promoting the sialylation of TIM-1, causing it to be primarily localized in the cytoplasm. Therefore, we discovered new functions of TIM-1 and JEV NS1 during the process of JEV infection, and provide a new insight into the interactions between JEV and cell hosts.

microbiology↗

bioRxiv2022

Allosteric inhibition of Staphylococcus aureus MenD by 1,4-dihydroxy naphthoic acid: A feedback inhibition mechanism of the menaquinone biosynthesis pathway

Menaquinones (MKs) are electron carriers in bacterial respiratory chains. In Staphylococcus aureus (Sau), MKs are essential for aerobic and anaerobic respiration. As MKs are redox-active, their biosynthesis likely requires tight regulation to prevent disruption of cellular redox balance. We recently found that the Mycobacterium tuberculosis MenD, the first committed enzyme of the MK biosynthesis pathway, is allosterically inhibited by the downstream metabolite 1,4-dihydroxy-2-naphthoic acid (DHNA). To understand if this is a conserved mechanism in phylogenetically distant genera that also utilize MK, we investigated whether the Sau-MenD is allosterically inhibited by DHNA. Our results show that DHNA binds to and inhibits SEPHCHC synthase activity of Sau-MenD enzymes. We identified residues in the DHNA binding pocket that are important for catalysis (Arg98, Lys283, Lys309) and inhibition (Arg98, Lys283). Furthermore, we show that exogenous DHNA inhibits growth of Sau, an effect that can be rescued by supplementing the growth media with MK-4. Our results demonstrate that despite a lack of strict conservation of the DHNA-binding pocket between Mtb-MenD and Sau-MenD, feedback inhibition by DHNA is a conserved mechanism in Sau-MenD and hence the Sau MK biosynthesis pathway. These findings may have implications for the development of anti-staphylococcal agents targeting MK biosynthesis

biochemistry↗

bioRxiv2021

Intact Drosophila Whole Brain Cellular Quantitation reveals Sexual Dimorphism

Establishing with precision the quantity and identity of the cell types of the brain is a prerequisite for a detailed compendium of gene and protein expression in the central nervous system. Currently however, strict quantitation of cell numbers has been achieved only for the nervous system of C.elegans. Here we describe the development of a synergistic pipeline of molecular genetic, imaging, and computational technologies designed to allow high-throughput, precise quantitation with cellular resolution of reporters of gene expression in intact whole tissues with complex cellular constitutions such as the brain. We have deployed the approach to determine with exactitude the number of functional neurons and glia in the entire intact larval Drosophila central nervous system (CNS), revealing fewer neurons and more glial cells than previously predicted. We also discover an unexpected divergence between the sexes at this juvenile developmental stage, with the female CNS having significantly more neurons than that of males. Topological analysis of our data establishes that this sexual dimorphism extends to deeper features of CNS organisation. We additionally extended our analysis to quantitate the expression of voltage-gated potassium channel family genes throughout the CNS and uncover substantial differences in abundance. Our methodology enables robust and accurate quantification of the number and positioning of cells within intact organs, facilitating sophisticated analysis of cellular identity, diversity, and gene expression characteristics.

neuroscience↗

bioRxiv2019

Tumor mutational landscape is a record of the pre-malignant state

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.

genomics↗

bioRxiv2017

Accurate Discrimination of 23 Major Cancer Types via Whole Genome Somatic Mutation Patterns

The two strongest factors predicting a human cancers clinical behaviour are the primary tumours anatomic organ of origin and its histopathology. However, roughly 3% of the time a cancer presents with metastatic disease and no primary can be determined even after a thorough radiological survey. A related dilemma arises when a radiologically defined mass is sampled by cytology yielding cancerous cells, but the cytologist cannot distinguish between a primary tumour and a metastasis from elsewhere.\n\nHere we use whole genome sequencing (WGS) data from the ICGC/TCGA PanCancer Analysis of Whole Genomes (PCAWG) project to develop a machine learning classifier able to accurately distinguish among 23 major cancer types using information derived from somatic mutations alone. This demonstrates the feasibility of automated cancer type discrimination based on next-generation sequencing of clinical samples. In addition, this work opens the possibility of determining the origin of tumours detected by the emerging technology of deep sequencing of circulating cell-free DNA in blood plasma.

cancer biology↗