Biology subjects

Zhou, H.

Publications and source records attributed to Zhou, H..

At least 199 records · Page 11Linked to original sources

bioRxiv2024

Splenic red pulp macrophages eliminate the liver-resistant Streptococcus pneumoniae during bloodstream infection

The spleen is well-known for defense against invasive infections of encapsulated bacteria, particularly Streptococcus pneumoniae (pneumococcus). However, the precise mechanism of the splenic anti-bacterial immunity remains elusive. Here we report that red pulp (RP) macrophages execute the splenic defense against S. pneumoniae in mice, with the help of natural antibodies (nAbs) and complement system. The spleen slowly but substantially cleared encapsulated pneumococci from the bloodstream in the early phase of blood infection, especially the serotypes that resist to liver filtration. Among splenic macrophage subpopulations, only the lack of RP macrophages led to the complete loss of the splenic immunity. Intravital microscopy detected direct capture and phagocytic killing of circulating pneumococci by RP macrophages in the absence of neutrophils and inflammatory monocytes. Likewise, plasma nAbs targeting pneumococcal cell wall phosphocholine and complement protein C3 were essential for RP macrophage-mediated immune clearance. Our findings have thus uncovered the long-sought immune pathway against invasive pneumococcal infections in the spleen. Short summaryThe spleen plays a crucial role in defending against invasive infections caused by Streptococcus pneumoniae (pneumococcus) and other encapsulated bacteria in humans, but the mechanisms underlying this organ-specific immunity remain largely elusive. This study has revealed that the spleen eliminates pneumococci through a coordinated interplay among red pulp macrophages, serum nAbs targeting phosphocholine and the complement system.

microbiology↗

bioRxiv2024

MOL-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective

3D molecular representation learning has gained tremendous interest and achieved promising performance in various downstream tasks. A series of recent approaches follow a prevalent framework: an encoder-only model coupled with a coordinate denoising objective. However, through a series of analytical experiments, we prove that the encoderonly model with coordinate denoising objective exhibits inconsistency between pre-training and downstream objectives, as well as issues with disrupted atomic identifiers. To address these two issues, we propose MO_SCPLOWOLC_SCPLOW-AE for molecular representation learning, an auto-encoder model using positional encoding as atomic identifiers. We also propose a new training objective named 3D Cloze Test to make the model learn better atom spatial relationships from real molecular substructures. Empirical results demonstrate that MO_SCPLOWOLC_SCPLOW-AE achieves a large margin performance gain compared to the current state-of-the-art 3D molecular modeling approach. The source codes of MO_SCPLOWOLC_SCPLOW-AE are publicly available at https://github.com/yjwtheonly/MolAE.

bioinformatics↗

bioRxiv2024

Differential Proteomic Analysis of AML Patients at Low and Intermediate Altitudes after Chemotherapy

Chemotherapy is the primary treatment for patients with acute myeloid leukemia (AML). In addition to factors such as patient age, physical condition, and choice of medication, we have noticed that environmental factors such as altitude may also have a significant impact on post-chemotherapy bone marrow suppression in AML patients in clinical practice. The results indicate that there are differences in the proteomics of the two groups of patients during the bone marrow suppression period after chemotherapy. Differentially expressed proteins are primarily located in the cytoplasm, extracellular space, and nucleus, followed by mitochondria and membranes. These differentially expressed proteins mainly participate in biological processes such as cell and metabolism. For differential protein KEGG pathway enrichment analysis, it was found that metabolic pathways were mainly enriched in the metabolic category, while the PI3K-Akt signaling pathway, HIF-1 signaling pathway, NF-{kappa}B signaling pathway, and calcium signaling pathway were enriched in the signaling pathways.

cancer biology↗

bioRxiv2024

GGCX promotes Eurasian avian-like H1N1 swine influenza virus adaption to interspecies receptor binding

The Eurasian avian-like (EA) H1N1 swine influenza virus (SIV) possesses the capacity to instigate the next influenza pandemic, owing to its heightened affinity for the human-type -2,6 sialic acid (SA) receptor. Nevertheless, the molecular mechanisms underlying the switch in receptor binding preferences of EA H1N1 SIV remain elusive. In this study, we conducted a comprehensive genome-wide CRISPR/Cas9 knockout screen utilizing EA H1N1 SIV in porcine kidney cells. Knocking out the enzyme gamma glutamyl carboxylase (GGCX) reduced virus replication in vitro and in vivo by inhibiting the carboxylation modification of viral haemagglutinin (HA) and the adhesion of progeny viruses, ultimately impeding the replication of EA H1N1 SIV. Furthermore, GGCX was revealed to be the determinant of the D225E substitution of EA H1N1 SIV, and GGCX-medicated carboxylation modification of HA 225E contributed to the receptor binding adaption of EA H1N1 SIV to the -2,6 SA receptor. Taken together, our CRISPR screen has elucidated a novel function of GGCX in the support of EA H1N1 SIV adaption for binding to -2,6 SA receptor. Consequently, GGCX emerges as a prospective antiviral target against the infection and transmission of EA H1H1 SIV.

microbiology↗

bioRxiv2024

A general evolution landscape of language and cognition genes

The polymorphism profiles of language genes (LG) display different patterns across various ancient and modern populations, leading to the speculation that cognition gene (CG) polymorphism profiles may exhibit similar trends. However, the evolutionary processes of language gene polymorphism patterns (LGPP) and cognition gene polymorphism patterns (CGPP) are likely to demonstrate distinct characteristics. In particular, it is intriguing to determine whether there is any overlap in the timing of significant changes in CGPP and LGPP over the large timescales of evolution. The potential existence of such overlap can also be assessed by examining whether the samples carrying significant changes in LGPP and CGPP are the same. This study investigated the genetic differences at 239 SNP loci in 18 language genes (LG) and 223 SNP loci in 18 cognition genes (CG) across 170 whole genomes. Principal component analysis (PCA) was used to cluster the SNP data of the aforementioned samples, and the similarity of SNP patterns between each sample was calculated from three perspectives: LG, CG, and CGLG. The basic conclusions are as follows: (1) If different positions in the PCA analysis results can essentially represent the pattern differences in SNP polymorphisms, then both language gene polymorphism patterns and cognition gene polymorphism patterns have undergone distinct stages of evolution; (2) There were significant differences in the early manifestations of language gene polymorphism patterns and cognition gene polymorphism patterns during human evolution: Language gene polymorphism patterns could not differentiate general animals, primates, and ancient human samples in the early stages of evolution, whereas cognition gene polymorphism patterns seemed to be initially divisible into two patterns, one closely resembling a group of animals and certain ancient human samples, and the other reflected in a different set of animal and primate samples. (3) It appears that samples from all five continents can be observed at every stage of evolution, suggesting that new evolving populations have always had ample time to spread across continents. (4) A quantitative comparison of the SNP profiles of 170 samples revealed that their CG and LG plus CGLG profiles indeed have 2-3 potential significant change points, and the samples carrying these significant change points has 2 common samples, namely ge1 (Georgia) and us2 (North America), implying that the most significant changes in language or cognition gene polymorphism patterns during human evolution may have occurred in some human populations in Europe/ North America.

molecular biology↗

bioRxiv2024

Multi-Scale Protein Language Model for Unified Molecular Modeling

Protein language models have demonstrated significant potential in the field of protein engineering. However, current protein language models primarily operate at the residue scale, which limits their ability to provide information at the atom level. This limitation prevents us from fully exploiting the capabilities of protein language models for applications involving both proteins and small molecules. In this paper, we propose ESM-AA (ESM All-Atom), a novel approach that enables atom-scale and residue-scale unified molecular modeling. ESM-AA achieves this by pretraining on multi-scale code-switch protein sequences and utilizing a multi-scale position encoding to capture relationships among residues and atoms. Experimental results indicate that ESM-AA surpasses previous methods in proteinmolecule tasks, demonstrating the full utilization of protein language models. Further investigations reveal that through unified molecular modeling, ESM-AA not only gains molecular knowledge but also retains its understanding of proteins.1

bioinformatics↗

bioRxiv2024

Structural Requirements for Activity of Mind bomb1 in Notch Signaling

Mind bomb 1 (MIB1) is a RING E3 ligase that ubiquitinates Notch ligands, a necessary step for induction of Notch signaling. The structural basis for binding of the JAG1 ligand by the N-terminal region of MIB1 is known, yet how the ankyrin (ANK) and RING domains of MIB1 cooperate to catalyze ubiquitin transfer from E2[~]Ub to Notch ligands remains unclear. Here, we show that the third RING domain and adjacent coiled coil region of MIB1 (ccRING3) drives MIB1 dimerization and that ubiquitin transfer activity of MIB1 relies solely on RING3. We report x-ray crystal structures of a UbcH5B-ccRING3 complex as a fusion protein and of the ANK region. Directly tethering the N-terminal region to ccRING3 forms a minimal MIB1 protein, which is sufficient to induce a Notch response in receiver cells. Together, these studies define the functional elements of an E3 ligase needed for ligands to induce a Notch signaling response.

biochemistry↗

bioRxiv2024

Phosphate-binding pocket on cyclin B governs CDK substrate phosphorylation and mitotic timing

Cell cycle progression is governed by complexes of the cyclin-dependent kinases (CDKs) and their regulatory subunits cyclin and Cks1. CDKs phosphorylate hundreds of substrates, often at multiple sites. Multisite phosphorylation depends on Cks1, which binds initial priming phosphorylation sites to promote secondary phosphorylation at other sites. Here, we describe a similar role for a recently discovered phosphate-binding pocket (PP) on B-type cyclins. Mutation of the PP in Clb2, the major mitotic cyclin of budding yeast, alters bud morphology and delays the onset of anaphase. Mutation of the PP reduces multi-site phosphorylation of CDK substrates in vitro, including the Cdc16 and Cdc27 subunits of the anaphase-promoting complex/cyclosome and the Bud6 and Spa2 subunits of the polarisome. We conclude that the cyclin PP, like Cks1, controls the pattern of multisite phosphorylation on CDK substrates, thereby helping to establish the robust timing of cell-cycle events.

biochemistry↗

bioRxiv2024

Overcoming the "feast or famine" effect: improved interaction testing in genome-wide association studies

In genetic association analysis of complex traits, detection of interaction (either GxG or GxE) can help to elucidate the genetic architecture and biological mechanisms underlying the trait. Detection of interaction in a genome-wide interaction study (GWIS) can be methodologically challenging for various reasons, including a high burden of multiple comparisons when testing for epistasis between all possible pairs of a set of genomewide variants, as well as heteroscedasticity effects occurring in the presence of GxG or GxE interaction. In this paper, we address the problem of an even more striking phenomenon that we call the "feast or famine" effect that occurs when testing interaction in a genomewide context. We show that in any given GxE GWIS, the type 1 error of standard interaction tests performed genomewide can vary widely from the nominal level, where the actual type 1 error in any given GWIS varies as a predictable function of the observed trait and environmental values. Using standard methods, some GWISs will have systematically underinflated p-values ("feast"), and others will have systematically overinflated p-values ("famine"), which can lead to false detection of interaction, reduced power, inconsistent results across studies, and failure to replicate true signal. This startling phenomenon is specific to detection of interaction in a GWIS, and it may partly explain why such detection has often proved challenging and difficult to replicate. We show that the feast or famine effect occurs across a wide range of GxE analysis methods, including but not limited to (1) testing interaction in a linear or linear mixed model (LMM) using standard approaches such as t-tests/Wald tests, likelihood ratio tests, or score tests; (2) doing a combined interaction-association test in a linear model or LMM using standard approaches; (3) testing interaction with multiple environments or multiple SNPs, where these are modeled as random effects in a LMM using standard approaches; (4) performing tests of interaction in a GWIS where significance is assessed using permutation of the trait residuals. We show theoretically that the key cause of this phenomenon is which variables are conditioned on in the analysis. Using this insight, we have developed (i) a diagnostic ratio to detect which GWASs are subject to a strong "feast or famine" effect and (ii) the TINGA method to adjust the interaction test statistics to make their p-values approximately uniform under the null hypothesis. In simulations we show that TINGA both controls type 1 error and improves power. TINGA allows for covariates and population structure through use of a linear mixed model and accounts for heteroscedasticity. We apply TINGA to detection of epistasis in a study of flowering time in Arabidopsis thaliana. Author summaryTesting for interactions in GWAS can lead to insight into biological mechanisms, but poses greater challenges than ordinary genetic association GWAS. When testing for interaction in a GWAS setting with one fixed SNP or environmental variable, the standard test statistics may not have the expected statistical properties under the null hypothesis, which can lead to false detection of interaction, inconsistent results across studies, reduced power, and failure to replicate true signal. We propose the TINGA method to adjust the test statistics so that the null distribution of their p-values is closer to uniform. Through simulations and real data analysis, we illustrate the problems with the standard analysis and the improvement of our proposed method.

genetics↗

bioRxiv2024

Investigating 3D microbial community dynamics in the rhizosphere using complex-field and fluorescence microscopy

Microbial interactions in the rhizosphere contribute to soil health. Understanding these interactions thus has the potential to advance sustainable agriculture, ecosystem management, and environmental stewardship. Yet it is difficult to understand what we cannot see; amongst the limitations in rhizosphere imaging are challenges associated with rapidly and non-invasively imaging microbial cells over field depths relevant to plant roots. Here, we present a novel bimodal imaging technique called Complex-field and Fluorescence microscopy using the Aperture Scanning Technique (CFAST) that begins to address these limitations by integrating quantitative phase and 3D fluorescence imaging. We showcase CFASTs practicality and versatility in two ways. First, by harnessing its depth of field of more than 100 microns, we significantly reduce the number of captures required for 3D imaging of plant roots and bacteria in the rhizoplane, thereby minimizing potential photobleaching and phototoxicity. Second, by leveraging CFASTs phase sensitivity and fluorescence specificity, we track early bacterial aggregate development, bacterial competition, and gene expression under varying environmental conditions. Specifically, we resolve bacterial growth dynamics of mixed populations at the early stages of colonization without the need for genetically labeling environmental isolates. Moreover, we find that the expression of genes of interest to rhizosphere chemistry (e.g. representative genes involved in phosphorus-sensing and antibiotic production) varies spatiotemporally within microbial populations that are surface-attached and appears distinct from their expression in planktonic cultures. Together, CFASTs attributes overcome commercial imaging platform limitations and enable new insights to be gained into microbial behavioral dynamics in experimental systems of relevance to the rhizosphere.

microbiology↗

bioRxiv2024

Genomic insights into photosymbiotic evolution in Tridacna squamosa

Photosymbiosis is fundamental driving force for ecological success of benthic coral reef ecosystems, and contributing to their biodiversity and resilience. As a benchmark organism indicative of reef health, the fluted giant clam (Tridacna squamosa) forms an exemplary photosymbiotic relationship with the symbiont Symbiodiniaceae dinoflagellates, whose initiation and maturation require finely coordinated interactions. However, much of the origin and dynamics of this reciprocal interplay remains unclarified. Here, we report the first complete whole genome of T. squamosa, in conjunction with integrated multi-omics data, to illuminate the key evolutionary innovations and molecular events supporting the establishment and maintenance of photosymbiotic lifestyle in the giant clam. Programmed regulation of symbiont recognition, host immune system and GPCRs signaling activation co-contributed to dinoflagellates acquisition in T. squamosa larvae. Adaptive metabolic remodeling in the host siphonal mantle, a photosymbiotic niche, is critical to maintain the robustness of phtosymbiosis. T. squamosa has expanded light sensing gene family and evolved sophisticated signaling pathways to protect against UV photo-damage. Evidence also supports significant contribution of positive selection to host DNA-repair. Overall, our study here offers fresh mechanistic insights into the parallel evolution and molecular machinery of photosymbiosis in the giant clam-dinoflagellates duet, with implications for devising solutions to sustainable conservation.

evolutionary biology↗

bioRxiv2024

Phylogenetically and structurally diverse reductive dehalogenases link biogeochemical cycles in deep-sea cold seeps

Reductive dehalogenation is crucial for halogen cycling and environmental remediation, yet its ecological role is not completely understood, especially in deep-sea environments. To address this gap, we investigated the diversity of reductive dehalogenases (RDases) and ecophysiology of organohalide reducers in deep-sea cold seeps, which are environments rich in halogenated compounds. Through genome- resolved metagenomic analysis of 165 global cold seep sediment samples, we identified four types of RDases, namely prototypical respiratory, transmembrane respiratory, and cytosolic RDases, and one novel clade. Cold seeps were found to harbor a higher abundance of these RDase genes compared to other marine sediments, establishing them as unique hotspots for microbial reductive dehalogenation activity. These RDases are encoded by a wide range of microorganisms across four archaeal and 36 bacterial phyla, significantly expanding the known diversity of organohalide reducers. Halogen geochemistry, laboratory incubations with various halogenated compounds, metatranscriptomic data, and metabolomic profiling confirmed the presence of organohalides at concentrations of up to 18 mg/g in these sediments and demonstrated their active microbial reduction. This process is tightly linked to other biogeochemical cycles, including carbon, hydrogen, nitrogen, sulfur, and trace elements. RDases from cold seeps have diverse N-terminal structures across different gene groups, and reductive dehalogenase genes in these environments are mostly functionally constrained and conserved. These findings collectively suggest that reductive dehalogenation is a central process in deep-sea environments, mediated by a diverse array of microbes and novel enzymes.

microbiology↗

bioRxiv2023

Quantification of cell phenotype transition manifolds with information geometry

Cell phenotype transition (CPT) is crucial in development and other biological processes. Advances in single-cell sequencing reveal that CPT dynamics are confined to low-dimensional manifolds, yet current methods cannot directly quantify these manifolds. We present SCIM (single cell information manifolds), a geometry-guided approach using information geometry. SCIM embeds single-cell gene expression profiles as Gaussian distributions, defining the Fisher metric naturally in this space. We compute each cells coarse Ricci curvature, finding that low-curvature cells mark critical transitions. By further calculating each cells information velocity from RNA velocity, we find that regions with high information velocity coincide with low curvature, suggesting that geometry guides cellular dynamics on CPT manifolds. SCIM uncovers invariant features of CPT manifolds and provides a general framework for quantifying dynamics on these manifolds.

biophysics↗

bioRxiv2023

Chlamydial protease-like activating factor targets SLC7A11 for degradation to induce ferroptosis and facilitate dissemination.

Chlamydia trachomatis, the most prevalent bacterial agent of sexually transmitted infections, possesses remarkable capacities for dissemination within the host, leading to reproductive health complications. The release of progeny through the orchestrated lysis of host cells plays a crucial role in Chlamydia dissemination, but the underlying molecular mechanisms remain largely elusive. Here, we uncovered a novel mechanism by which Chlamydia induces host cells ferroptosis to facilitate its dissemination. This process involves the degradation of host protein SLC7A11 by the chlamydial protease-like activating factor (CPAF), resulting in glutathione depletion, oxidative damage, and subsequent host cell lysis characterized by lipid peroxidation. Infection with CPAF-deficient strain fails to induce host cells ferroptosis, leading to restricted progeny release. Importantly, inhibiting ferroptosis effectively limits the release of Chlamydia progeny, highlighting its potential as a therapeutic strategy for controlling Chlamydia dissemination. These findings provide insights into the chlamydial conserved dissemination strategy and enhance understanding of its pathogenesis.

microbiology↗

bioRxiv2023

Selected humanization of yeast U1 snRNP leads to global suppression of pre-mRNA splicing and mitochondrial dysfunction in the budding yeast

The recognition of 5 splice site (5 ss) is one of the earliest steps of pre-mRNA splicing. To better understand the mechanism and regulation of 5 ss recognition, we selectively humanized components of the yeast U1 snRNP to reveal the function of these components in 5 ss recognition and splicing. We targeted U1C and Luc7, two proteins that interact with and stabilize the yeast U1 (yU1) snRNA and the 5 ss RNA duplex. We replaced the Zinc-Finger (ZnF) domain of yU1C with its human counterpart, which resulted in cold-sensitive growth phenotype and moderate splicing defects. Next, we added an auxin-inducible degron to yLuc7 protein and found that Luc7-depleted yU1 snRNP resulted in the concomitant loss of PRP40 and Snu71 (two other essential yeast U1 snRNP proteins), and further biochemical analyses suggest a model of how these three proteins interact with each other in the U1 snRNP. The loss of these proteins resulted in a significant growth retardation accompanied by a global suppression of pre-mRNA splicing. The splicing suppression led to mitochondrial dysfunction as revealed by a release of Fe2+ into the growth medium and an induction of mitochondrial reactive oxygen species. Together, these observations indicate that the human U1C ZnF can substitute that of yeast, Luc7 is essential for the incorporation of the Luc7-Prp40-Snu71 trimer into yeast U1 snRNP, and splicing plays a major role in the regulation of mitochondria function in yeast.

biochemistry↗

bioRxiv2023

Small molecule inhibitor binds to NLRP3 and prevents inflammasome activation

Despite recent advances in the mechanism of oxidized DNA activating NLRP3, the molecular mechanism and consequence of oxidized DNA associating with NLRP3 remains unknown. Cytosolic NLRP3 binds oxidized DNA which has been released from the mitochondria, which subsequently triggers inflammasome activation. Human glycosylase (hOGG1) repairs oxidized DNA damage which inhibits inflammasome activation. The fold of NLRP3 pyrin domain contains amino acids and a protein fold similar to hOGG1. Amino acids that enable hOGG1 to bind and cleave oxidized DNA are conserved in NLRP3. We found NLRP3 could bind and cleave oxidized guanine within mitochondrial DNA. The binding of oxidized DNA to NLRP3 was prevented by small molecule drugs which also inhibit hOGG1. These same drugs also inhibited inflammasome activation. Elucidating this mechanism will enable design of drug memetics that treat inflammasome pathologies, illustrated herein by NLRP3 pyrin domain inhibitors which suppressed interleukin-1{beta} (IL-1{beta}) production in macrophages. One-Sentence SummaryNLRP3 cleaves oxidized DNA and small molecule drug binding inhibits inflammasome activation.

immunology↗

bioRxiv2023

Single cell discovery of m6A RNA modifications in the hippocampus

N6-methyladenosine (m6A) is a prevalent and highly regulated RNA modification essential for RNA metabolism and normal brain function. It is particularly important in the hippocampus, where m6A is implicated in neurogenesis and learning. Although extensively studied, its presence in specific cell types remain poorly understood. We investigated m6A in the hippocampus at the single cell level, revealing a comprehensive landscape of m6A modifications within individual cells. Our data also identifies transcripts which have high m6A density and are associated with brain diseases. Our data suggests that m6A containing transcripts might be of particular importance for Camk2a neurons. Overall, this work provides new insights into the molecular mechanisms underlying hippocampal physiology and lays the foundation for future studies investigating the dynamic nature of m6A RNA methylation in the healthy and diseased brain.

neuroscience↗

bioRxiv2023

MOBFinder: a tool for MOB typing for plasmid metagenomic fragments based on language model

BackgroundMOB typing is a classification scheme that classifies plasmid genomes based on their relaxase gene. The host range of plasmids of different MOB categories are diverse and MOB typing is crucial for investigating the mobilization of plasmid, especially the transmission of resistance genes and virulence factors. However, MOB typing of plasmid metagenomic data is challenging due to the highly fragmented characteristic of metagenomic contigs. ResultsWe developed MOBFinder, an 11-class classifier to classify the plasmid fragments into 10 MOB categories and a non-mobilizable category. We first performed the MOB typing for classifying complete plasmid genomes using the relaxes information, and constructed the artificial benchmark plasmid metagenomic fragments from these complete plasmid genomes whose MOB types are well annotated. Based on natural language models, we used the word vector to characterize the plasmid fragments. Several random forest classification models were trained and integrated for predicting plasmid fragments with different lengths. Evaluating the tool over the benchmark dataset, MOBFinder demonstrates higher performance compared to the existing tool, with an overall accuracy of approximately 59% higher than the MOB-suite. Moreover, the balanced accuracy, harmonic mean and F1-score could reach 99% in some MOB types. In an application focused on a T2D cohort, MOBFinder offered insights suggesting that the MOBF type might accelerate the antibiotic resistance transmission in patients suffering from T2D. ConclusionsTo the best of our knowledge, MOBFinder is the first tool for MOB tying for plasmid metagenomic fragments. MOBFinder is freely available at https://github.com/FengTaoSMU/MOBFinder.

bioinformatics↗