Biology subjects

Zhang, R.

Publications and source records attributed to Zhang, R..

At least 217 records · Page 12Linked to original sources

bioRxiv2024

De novo discovery of conserved gene clusters in microbial genomes with Spacedust

Metagenomics has revolutionized environmental and human-associated microbiome studies. However, the limited fraction of proteins with known biological process and molecular functions presents a major bottleneck. In prokaryotes and viruses, evolution favors keeping genes participating in the same biological processes co-localized as conserved gene clusters. Conversely, conservation of gene neighborhood indicates functional association. Spacedust is a tool for systematic, de novo discovery of conserved gene clusters. To find homologous protein matches it uses fast and sensitive structure comparison with Foldseek. Partially conserved clusters are detected using novel clustering and order conservation P-values. We demonstrate Spacedusts sensitivity with an all-vs-all analysis of 1 308 bacterial genomes, identifying 72 843 conserved gene clusters containing 58% of the 4.2 million genes. It recovered 95% of antiviral defense system clusters annotated by a specialized tool. Spacedusts high sensitivity and speed will facilitate the annotation of the huge numbers of sequenced bacterial, archaeal and viral genomes.

bioinformatics↗

bioRxiv2024

Enhanced bacterial chemotaxis in confined microchannels: Optimal performance in lane widths matching circular swimming radius

Understanding bacterial behavior in confined environments is helpful for elucidating microbial ecology and developing strategies to manage bacterial infections. While extensive research has focused on bacterial motility on surfaces and in porous media, chemotaxis in confined spaces remains poorly understood. Here, we investigate the chemotaxis of Escherichia coli within microfluidic lanes under a linear concentration gradient of L-aspartate. We demonstrate that E. coli exhibits significantly enhanced chemotaxis in lanes with sidewalls compared to open surfaces. We attribute this phenomenon primarily to the intrinsic chiral clockwise circular motion of surface-swimming bacteria and the subsequent alignment effect upon collision with the sidewalls. By varying lane widths, we identify that an 8 m width--approximating the radius of bacterial circular swimming on surfaces--maximizes chemotactic drift velocity. These results are supported by both experimental observations and stochastic simulations, establishing a clear proportional relationship between optimal lane width and the radius of bacterial circular swimming. Further geometric analysis provides an intuitive understanding of this phenomenon. Our results may offer insights into bacterial navigation in complex biological environments such as host tissues and biofilms, providing a preliminary step toward exploring microbial ecology in confined habitats and potential strategies for controlling bacterial infections.

biophysics↗

bioRxiv2024

Multi-Modal Large Language Model Enables All-Purpose Prediction of Drug Mechanisms and Properties

Accurately predicting the mechanisms and properties of potential drug molecules is essential for advancing drug discovery. However, traditional methods often require the development of specialized models for each specific prediction task, resulting in inefficiencies in both model training and integration into work-flows. Moreover, these approaches are typically limited to predicting pharmaceutical attributes represented as discrete categories, and struggle with predicting complex attributes that are best described in free-form texts. To address these challenges, we introduce DrugChat, a multi-modal large language model (LLM) designed to provide comprehensive predictions of molecule mechanisms and properties within a unified framework. DrugChat analyzes the structure of an input molecule along with users queries to generate comprehensive, free-form predictions on drug indications, pharmacodynamics, and mechanisms of action. Moreover, DrugChat supports multi-turn dialogues with users, facilitating interactive and in-depth exploration of the same molecule. Our extensive evaluation, including assessments by human experts, demonstrates that DrugChat significantly outperforms GPT-4 and other leading LLMs in generating accurate free-form predictions, and exceeds state-of-the-art specialized prediction models.

pharmacology and toxicology↗

bioRxiv2024

GERMIN3 plays a role in plasmodesmatal gating to regulate meristem activation related to tuberisation, tuber dormancy release and stem branching in potato

O_LIGERMIN3 has previously been identified as a target of the tuberigen activation complex suggesting a function in potato tuberisation but its role is presently unknown. C_LIO_LITo understand the role of GERMIN3 we analysed morphological, agronomic and molecular phenotypes in transgenic lines. C_LIO_LIGERMIN3 over-expressing lines of Solanum tuberosum ssp. andigena exhibited increased tuber yields under permissive conditions and enhanced tuber numbers. Post-harvest tuber sprouting exhibited reduced apical dominance with increased numbers of sprouts. Apical dominance was reduced in aerial tissues of mature plants where stem growth from axillary buds was activated. Similar results were observed in the commercial cultivar Desiree. Over-expression of GERMIN3 had no impact on the expression of SP6A, a positive regulator of tuberisation or TFL1B, a negative regulator. The GERMIN3 protein localised to the endoplasmic reticulum and transient expression in N. benthamiana leaves resulted in plasmodesmatal gating allowing intercellular transport of GFP-tagged sporamin independent of GERMIN3 oxalate oxidase activity. C_LIO_LIGERMIN3 affects tuberisation and other developmental processes by facilitating meristem activation. This identifies GERMIN3 as a novel protein associated with control of plasmodesmatal transport and supports the importance of plasmodesmatal gating in the regulation of key potato developmental processes. C_LI

plant biology↗

bioRxiv2024

Expansion in situ genome sequencing links nuclear abnormalities to hotspots of aberrant euchromatin repression

Microscopy and genomics are both used to characterize cell function, but approaches to connect the two types of information are lacking, particularly at subnuclear resolution. While emerging multiplexed imaging methods can simultaneously localize genomic regions and nuclear proteins, their ability to accurately measure DNA-protein interactions is constrained by the diffraction limit of optical microscopy. Here, we describe expansion in situ genome sequencing (ExIGS), a technology that enables sequencing of genomic DNA and superresolution localization of nuclear proteins in single cells. We applied ExIGS to fibroblast cells derived from an individual with Hutchinson-Gilford progeria syndrome to characterize how variation in nuclear morphology affects spatial chromatin organization. Using this data, we discovered that lamin abnormalities are linked to hotspots of aberrant euchromatin repression that may erode cell identity. Further, we show that lamin abnormalities heterogeneously increase the repressive environment of the nucleus in tissues and aged cells. These results demonstrate that ExIGS may serve as a generalizable platform for connecting nuclear abnormalities to changes in gene regulation across disease contexts.

genomics↗

bioRxiv2024

BTFBS: binding-prediction of bacterial transcription factors and binding sites based on deep learning

BackgroundThe binding of transcription factors (TFs) to TF-binding sites plays a vital role in the process of regulating gene expression and evolution. With the development of machine learning and deep learning, some successes have been achieved in predicting transcription factors and binding sites. Then a natural question arises: for a given transcription factor and a binding site, do they bind? This is the main motivation of this work. ResultsIn this paper, we develop a model BTFBS, which predicts whether the bacterial transcription factors and binding sites combine or not. The model takes both the amino acid sequences of bacterial transcription factors and the nucleotide sequences of binding sites as inputs, and extracts features through convolutional neural network and MultiheadAttention. For the model inputs, we use two negative sample sampling methods: RS and EE. On the test dataset of RS, the accuracy, sensitivity, specificity, F1-score and MCC of BTFBS are 0.91446, 0.89746, 0.93134, 0.91264 and 0.82946, respectively. And on the test dataset of EE, the accuracy, sensitivity, specificity, F1-score and MCC of BTFBS are 0.87868, 0.89354, 0.86394, 0.87996 and 0.75796, respectively. Meanwhile, our findings indicate that the optimal approach for obtaining negative samples in the context of bacterial research is to utilize the whole genome sequences of the corresponding bacteria, as opposed to the shuffling method. ConclusionsThe above results on the test dataset have shown that the proposed BTFBS model has a good performance in predicting the combination of bacterial transcription factors and their binding sites and provides an experimental guide. BTFBS is publicly available at https://github.com/Vceternal/BTFBS.

bioinformatics↗

bioRxiv2024

An integrated view of the structure and function of the human 4D nucleome

The dynamic three-dimensional (3D) organization of the human genome (the "4D Nucleome") is closely linked to genome function. Here, we integrate a wide variety of genomic data generated by the 4D Nucleome Project to provide a detailed view of human 3D genome organization in widely used embryonic stem cells (H1-hESCs) and immortalized fibroblasts (HFFc6). We provide extensive benchmarking of 3D genome mapping assays and integrate these diverse datasets to annotate spatial genomic features across scales. The data reveal a rich complexity of chromatin domains and their sub-nuclear positions, and over one hundred thousand structural loops and promoter-enhancer interactions. We developed 3D models of population-based and individual cell-to-cell variation in genome structure, establishing connections between chromosome folding, nuclear organization, chromatin looping, gene transcription, and DNA replication. We demonstrate the use of computational methods to predict genome folding from DNA sequence, uncovering potential effects of genetic variants on genome structure and function. Together, this comprehensive analysis contributes insights into human genome organization and enhances our understanding of connections between the regulation of genome function and 3D genome organization in general.

genomics↗

bioRxiv2024

ProtRNA: A Protein-derived RNA Language Model by Cross-Modality Transfer Learning

Protein language models (PLM), such as the highly successful ESM-2, have proven particularly effective. However, language models designed for RNA continue to face challenges. A key question is: can the information derived from PLMs be harnessed and transferred to RNA? To investigate this, a model termed ProtRNA has been developed by cross-modality transfer learning strategy for addressing the challenges posed by RNAs limited and less conserved sequences. By leveraging the evolutionary and physicochemical information encoded in protein sequences, the ESM-2 model is adapted to processing "low-resource" RNA sequence data. The results show comparable or superior performance in various RNA downstream tasks, with only 1/8 the trainable parameters and 1/6 the training data employed by the primary reference baseline RNA language model. This approach highlights the potential of cross-modality transfer learning in biological language models.

bioinformatics↗

bioRxiv2024

Genome assembly of Firmina major, an endangered savanna tree species endemic to China

The tree species Firmiana major was once dominant in the savanna vegetation of the arid hot valleys of southwest China, but was considered extinct in the wild in 1998. After eight small populations were relocated by thorough investigations between 2018 and 2020, the species was subsequently recognized as a Plant Species of Extremely Small Populations (PSESP) in China in need of urgent rescue. Moreover, due to severe human disturbance, other species in the tropical woody genus Firmiana are also endangered, and the species in this genus have almost all been listed as second-class National Protected Wild Plants in China. In order to guide future research into the conservation of this group, we present here the high-quality genome assembly of F. major. This is the first genome assembly in the genus Firmiana, and is 1.4 Gb in size. The assembly consists of 1.18 Gb repetitive sequences, 37,673 annotated genes and 31,965 coding genes.

genomics↗

bioRxiv2024

Inferring cell differentiation maps from lineage tracing data

During development, mulitpotent cells differentiate through a hierarchy of increasingly restricted progenitor cell types until they realize specialized cell types. A cell differentiation map describes this hierarchy, and inferring these maps is an active area of research spanning traditional single marker lineage studies to data-driven trajectory inference methods on single-cell RNA-seq data. Recent high-throughput lineage tracing technologies profile lineages and cell types at scale, but current methods to infer cell differentiation maps from these data rely on simple models with restrictive assumptions about the developmental process. We introduce a mathematical framework for cell differentiation maps based on the concept of potency, and develop an algorithm, Carta, that infers an optimal cell differentiation map from single-cell lineage tracing data. The key insight in Carta is to balance the trade-off between the complexity of the cell differentiation map and the number of unobserved cell type transitions on the lineage tree. We show that Carta more accurately infers cell differentiation maps on both simulated and real data compared to existing methods. In models of mammalian trunk development and mouse hematopoiesis, Carta identifies important features of development that are not revealed by other methods including convergent differentiation of specialized cell types, progenitor differentiation dynamics, and the refinement of routes of differentiation via new intermediate progenitors. Code availabilityCarta software is available at https://github.com/raphael-group/CARTA

bioinformatics↗

bioRxiv2024

Inflammation perturbs hematopoiesis by remodeling specific compartments of the bone marrow niche

Hematopoietic stem and progenitor cells (HSPC) are regulated by interactions with stromal cells in the bone marrow (BM) cavity, which can be segregated into two spatially defined central marrow (CM) and endosteal (Endo) compartments. However, the importance of this spatial compartmentalization for BM responses to inflammation and neoplasia remains largely unknown. Here, we extensively validate a combination of scRNA-seq profiling and matching flow cytometry isolation that reproducibly identifies 7 key CM and Endo populations across mouse strains and accurately surveys both niche locations. We demonstrate that different perturbations exert specific effects on different compartments, with type I interferon responses causing CM mesenchymal stromal cells to adopt an inflammatory phenotype associated with overproduction of chemokines modulating local monocyte dynamics in the surrounding microenvironment. Our results provide a comprehensive method for molecular and functional stromal characterization and highlight the importance of altered stomal cell activity in regulating hematopoietic responses to inflammatory challenges.

cell biology↗

bioRxiv2024

Development of a DNA-encoded library screening method DEL Zipper to empower the study of RNA-targeted chemical matter

To date, RNA-targeted chemical matter is under explored due to a lack of robust screening assays. In this study, we present a novel RNA-targeted small molecule screening approach using a specialized DNA-encoded library (DEL). Our findings reveal that the specialized DEL library, called "DEL Zipper", can significantly reduce single-stranded DNA-RNA region interaction signals during various kinds of RNA selection. By performing the selection against both G-quadruplex, we have identified novel hits that interact with RNA targets and the results are validated through binding. This study demonstrates that the "DEL Zipper" method is a robust screening assay that has potential for discovering small molecule ligands for diverse RNA targets.

molecular biology↗

bioRxiv2024

High-coverage, massively parallel sequencing of single-cell genomes with CAP-seq

Microbial communities are extraordinarily diverse and play crucial roles in health and disease, yet current methods lack the resolution and scalability needed to dissect their genomic and ecological complexity at the single-cell level. Here, we present CAP-seq, a high-throughput single-microbe genomics platform that combines hydrogel-based semi-permeable encapsulation with minimal microfluidics to recover thousands of single-amplified genomes (SAGs) with long reads and high completeness at low sequencing depth. We benchmarked CAP-seq using defined microbial communities, demonstrating strain-level resolution, accurate detection of rare taxa, and genome recovery exceeding 50% at [~]10x coverage. Applying CAP-seq to pediatric Clostridioides difficile infection microbiomes, we generated a high-resolution single-cell atlas comprising tens of thousands of SAGs across hundreds of species. Host-resolved profiling of the cryptic plasmid pBI143 revealed previously hidden low-abundance host associations, six new plasmid versions, and their coexistence within individuals, indicating complex plasmid evolution in situ. Longitudinal analysis during fecal microbiota transplantation and vancomycin treatment uncovered dynamic remodeling of microbial hosts, antimicrobial resistance genes, and plasmids at single-cell resolution. CAP-seq enables scalable, high-performance single-cell genomics and provides a practical, widely accessible platform for microbiome analysis, paving the way for large-scale exploration of microbial dark matter and host-microbe interactions across diverse ecosystems.

genomics↗

bioRxiv2024

Phytop: A tool for visualizing and recognizing signals of incomplete lineage sorting and hybridization using species trees output from ASTRAL

Incomplete lineage sorting (ILS) and introgression/hybridization (IH) is prevalent in nature and thus frequently result in discrepancies within phylogenetic tree topologies, leading to misinterpretation of phylogenomic data. Despite the availability of numerous tools for detecting ILS and IH among species, many of these tools are lacking effective visualization, or are time-consuming, or require prior predetermination. Here, we addressed these shortcomings by developing a fast-running, user-friendly tool called Phytop. By defining ILS and IH indices to quantify ILS and IH, this tool can detect the extent of ILS and IH among lineages with high reliability, and can visualize them based on the gene tree topology patterns constructed using ASTRAL. We tested Phytop extensively using both simulated and real data, and found that it enables users to quickly and conveniently estimate the extent of ILS and IH, thus clarifying the phylogenetic uncertainty. Phytop is available at https://github.com/zhangrengang/phytop and is expected to conveniently contribute to the intuitive inference of genetic relationships among lineages in future research.

bioinformatics↗

bioRxiv2024

Diversity and ecological roles of RNA viral communities in the cryosphere of the Tibetan Plateau

RNA viruses play crucial roles in modulating host communities, but their diversity and ecological roles in the cryosphere are poorly understood. We investigated the RNA virome from the cryosphere of the Tibetan Plateau (TPC), the largest area of the cryosphere in the mid-low latitude regions, which includes 79 metatranscriptomes from ecosystems including glaciers, proglacial lake sediments, permafrost wetland and upland soils. We obtained 8,799 RNA-dependent RNA polymerase encoding contigs, which clustered into 5,333 viral species, adding more than 4,900 new RNA viral species to the global RNA virome database. The recovered RNA viruses primarily infect prokaryotes, distinctively different from the dominance of eukaryotic RNA viruses in oceanic ecosystems. In addition to the known taxa such as Leviviricetes, we identified novel clades of putative prokaryotic RNA viruses, which greatly extended our understanding of their diversity. We further expanded the host of RNA virus by 20 additional prokaryotic phylum- or class-level taxonomic groups. Moreover, the TPC RNA viruses encoded dozens of auxiliary metabolic genes that could reprogram the metabolisms of diverse hosts, including photosynthesis in glacier eukaryotic algae and cyanobacteria, which may exert great impacts on glacier dynamics through modulating host adaptation. Furthermore, we identified potential pathogenic RNA viruses in various cryosphere environments, though their overall risks are low. This study provides the first comprehensive view of cryosphere RNA virome, highlighting their high diversity, vital ecological functions, and potential health impacts.

ecology↗

bioRxiv2024

Highly pathogenic avian influenza H5 virus exposure in goats and sheep

The recent outbreaks of highly pathogenic avian influenza A(H5N1) virus in North and South America, including widespread infection of cattle in the United States, calls for an urgent assessment of the host range of influenza A viruses, particularly for subtypes of pandemic concern. We conducted a serological survey for binding antibodies to influenza A and B viruses in goats (n=452) and sheep (n=329) in Pakistan and found high seropositive rates for the hemagglutinin (HA) of avian influenza A viruses (AIV) H5 (23.9-34.0%), H7 (13.9- 37.1%), and H9 (17.0-34.7%). In contrast, there were low levels of seropositivity against the HA of human and swine pandemic H1N1/pdm09 (0.9-1.8%) in goats and against swine H3 (0.6%) in sheep. Notably, we observed high reactivity to the neuraminidase of human H1N1/2009 (57.8-60.6%) and swine H3N2 (14.0-14.4%), likely due to cross-reactivity with the N1 and N2 proteins of H5N1 and H9N2 AIVs, respectively. Interestingly, we also detected seropositivity against influenza B HA in both goats (7.1%) and sheep (4.6%). The presence of AIV antibodies in goats and sheep suggest these species represent previously unrecognized hosts for viruses of pandemic concern, revealing extensive gaps in our current understanding of the ecology of influenza A and B viruses.

microbiology↗

bioRxiv2024

Center-surround inhibition by expectation: a neuro-computational account

Expectation is beneficial for adaptive behavior through quickly deducing plausible interpretations of information. The profile and underlying neural computations of this process, however, remain unclear. When participants expected a grating with a specific orientation, we found a center-surround inhibition profile in orientation space, which was independent from attentional modulations by task-relevance. Using computational modeling, we showed that this center-surround inhibition could be reproduced by either a sharpening of tuning curves of expected orientation or a shift of tuning curves of unexpected orientations. Intriguingly, these two computations were further supported by orientation-adjustment and orientation-discrimination experiments. Finally, the ablation studies in convolutional neural networks revealed that predictive coding feedback played a critical role in the center-surround inhibition in expectation. Altogether, our study reveals for the first time that expectation results in both enhancement and suppression, optimizing plausible interpretations during perception by enhancing expected and attenuating similar but irrelevant and potentially interfering representations.

neuroscience↗

bioRxiv2024

Structural basis of phosphate export by human XPR1

Phosphorus is an essential element for all living organisms. While inorganic phosphate (Pi) cellular import is well documented, export is poorly characterized despite the recent discovery of the inositol pyrophosphate (PP-IP)-dependent Pi exporter XPR1. In this study, we determined the cryo-EM structures of XPR1. XPR1 forms a loose dimer, with each protomer containing 10 transmembrane helices (TMs) that can be divided into a peripheral domain (TM1, 3 and 4) and a core domain (TM2 and TM5-10) structurally related to ion-translocating rhodopsins. Bound Pi is observed in a tunnel formed by the helical bundle inside the core domain at a narrowest point that separates the tunnel into an intracellular vestibule (IV) and an extracellular vestibule (EV). This narrowest point contains a cluster of Pi-coordinating basic residues, and their substitution by mutagenesis strongly impaired phosphate export. PP-Ips stimulate XPR1 activity by binding to its SPX domain. Loss of this interaction induces a conformational change of the wide open EV (conducting state) into a collapsed EV (closed state), mainly caused by structural movements of TM9 and the bulky sidechain of Trp573 right above the Pi binding site, which are essential for the Pi export activity of XPR1. Our structural and functional characterization paves the way for further in-depth studies of XPR1.

biochemistry↗