Biology subjects

Zhou, Z.

Publications and source records attributed to Zhou, Z..

At least 217 records · Page 12Linked to original sources

bioRxiv2024

Pandemic Vibrio parahaemolyticus wave succession by gene loss

While spontaneous mutation and gene acquisition are well-established drivers of pathogen adaptation, the role of gene loss remains underexplored. Here, we investigated the emergence and diversification of the pandemic clone (PC) of Vibrio parahaemolyticus through large-scale phylogenomic analysis of 8,684 global isolates. The PC rapidly acquired multiple marker genes and genomic islands, subsequently diverging into successive sublineages mediating independent waves of cross-country transmission, as also observed in V. cholerae. Wave succession in the last two decades was driven by loss of putrescine utilization (Puu) genes, conferring phenotypic advantages for environmental adaptation (enhanced biofilm formation) and human transmission (increased cell adhesion/intestinal colonization, reduced virulence), consistent with the virulence trade-off hypothesis. We identified Puu-gene loss in multiple bacterial genera, with effects on biofilm and adhesion replicated in V. cholerae and Escherichia coli, suggesting convergent evolution and universal phenotypic effects. Our results highlight the indispensable role of gene loss in bacterial pathogen adaptation.

microbiology↗

bioRxiv2024

Enrichment of glycoRNAs using galactose oxidase, hydrazide chemistry, and glycosidase digestion

Ribonucleic acid (RNA), essential for protein production and immune function, undergoes glycosylation, a process that attaches carbohydrates to RNA, creating unique glycoRNAs. These sugar-coated RNA molecules regulate immune responses and may be related to immune disorders. However, studying them is challenging due to RNAs fragility. Therefore, a robust method for identifying glycosylated RNA is important. To address this, we optimized methods for enriching and identifying glycoRNAs, opening doors to explore their potential interactions with immune receptors and tumor suppression. Our approach involved investigating factors such as preservation solutions, enzyme buffers, digestion temperature, and incubation time. We successfully achieved efficient digestion of both N-linked and O-linked glycoRNAs at room temperature using 25 mM ammonium bicarbonate, demonstrating the effectiveness of this method. Additionally, RNA preservation in RNAlater at -80{degrees}C allows controlled release of glycoRNAs within hours. While sequential digestion of different glycoRNA types is possible, significant degradation occurs after the first enzyme step. Thus, we recommend separate harvesting for each type of glycoRNA. These optimized protocols, utilizing SPCgRNA and TnORNA methods, pave the way for further research on N- and O-glycoRNAs in health and disease.

biochemistry↗

bioRxiv2024

Discarded diversity: Novel megaphages, auxiliary metabolic genes, and virally encoded CRISPR-Cas systems in landfills

BackgroundViruses are the most abundant microbial entity on the planet, impacting microbial community structure and ecosystem services. Despite outnumbering Bacteria and Archaea by an order of magnitude, viruses have been comparatively underrepresented in reference databases. Metagenomic examinations have illustrated that viruses of Bacteria and Archaea have been specifically understudied in engineered environments. Here we employed metagenomic and computational biology methods to examine the diversity, host interactions, and genetic systems of viruses predicted from 27 samples taken from three municipal landfills across North America. ResultsWe identified numerous viruses that are not represented in reference databases, including the third largest bacteriophage genome identified to date ([~]678 kbp), and note a cosmopolitan diversity of viruses in landfills that are distinct from viromes in other systems. Host-virus interactions were examined via host CRISPR spacer to viral protospacer mapping which captured hyper-targeted viral populations and six viral populations predicted to infect across multiple phyla. Virally-encoded auxiliary metabolic genes (AMGs) were identified with the potential to augment hosts methane, sulfur, and contaminant degradation metabolisms, including AMGs not previously reported in literature. CRISPR arrays and CRISPR-Cas systems were identified from predicted viral genomes, including the two largest bacteriophage genomes to contain these genetic features. Some virally encoded Cas effector proteins appear distinct relative to previously reported Cas systems and are interesting targets for potential genome editing tools. ConclusionsOur observations indicate landfills, as heterogeneous contaminated sites with unique selective pressures, are key locations for diverse viruses and atypical virus-host dynamics.

microbiology↗

bioRxiv2024

MARK2 regulates Golgi apparatus reorientation by phosphorylation of CAMSAP2 in directional cell migration

The reorientation of the Golgi apparatus is crucial for cell migration and is regulated by multi-polarity signals. A number of non-centrosomal microtubules anchor at the surface of the Golgi apparatus and play a vital role in the Golgi reorientation, but how the Golgi are regulated by polarity signals remains unclear. Calmodulin-regulated spectrin-associated protein 2 (CAMSAP2) is a protein that anchors microtubules to the Golgi, a cellular organelle. Our research indicates that CAMSAP2 is dynamically localized at the Golgi during its reorientation processing. Further research shows that CAMSAP2 is potentially regulated by a polarity signaling molecule called MARK2, which interacts with CAMSAP2. We used mass spectrometry to find that MARK2 phosphorylates CAMSAP2 at serine 835, which affects its interaction with the Golgi associated protein USO1 but not with CG-NAP or CLASPs. This interaction is critical for anchoring microtubules to the Golgi during cell migration, altering microtubule polarity distribution, and aiding Golgi reorientation. Our study reveals an important signaling pathway in Golgi reorientation during cell migration, which can provide insights for research in cancer cell migration, immune response, and targeted drug development.

cell biology↗

bioRxiv2024

The intestinal microbiome and Cetobacterium somerae inhibit viral infection through TLR2-type I IFN signaling axis in zebrafish

Accumulated evidences demonstrate that intestinal microbiome can inhibit viral infection. However, our knowledge of the signaling pathways and specific commensal microbes that mediate the antiviral response is limited. Here, a rhabdoviral infection model in zebrafish allows us to investigate the modes of action of microbiome-mediated antiviral effect. We observed that antibiotics-treated and germ-free zebrafish exhibited greater viral infection. Mechanistically, depletion of the intestinal microbiome alters TLR2-Myd88 signaling, and blunts neutrophil response and type I interferon (IFN) production. Moreover, a single commensal bacterium, Cetobacterium somerae, recapitulated TLR2- and type I IFN-dependent antiviral effect of the microbiome in gnotobiotic zebrafish, and C. somerae exopolysaccharides (CsEPS) was the effector molecule that engaged TLR2 to mediate antiviral function. Together, our results suggest a conserved role of intestinal microbiome in regulating type I IFN response among vertebrates, and reveal that the intestinal microbiome inhibits viral infection through a CsEPS-TLR2-type I IFN signaling axis in zebrafish.

microbiology↗

bioRxiv2024

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds

ObjectivefMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging. MethodsWe create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevel-opmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP). ResultsWe find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity. ConclusionOur model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics. SignificanceOur DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.

neuroscience↗

bioRxiv2024

LucaOne: Generalized Biological Foundation Model with Unified Nucleic Acid and Protein Language

AbstractThe language of biology, encoded in DNA, RNA, and proteins, forms the foundation of life but remains challenging to decode due to its complexity. Traditional computational methods often struggle to integrate information across these molecules, limiting a comprehensive understanding of biological systems. Advances in Natural Language Processing (NLP) with pre-trained models offer new possibilities for interpreting biological language. Here, we introduce LucaOne, a pre-trained foundation model trained on nucleic acid and protein sequences from 169,861 species. Through large-scale data integration and semisupervised learning, LucaOne demonstrates an understanding of key biological principles, such as DNA-Protein translation. Using few-shot learning, it effectively comprehends the central dogma of molecular biology and performs competitively on tasks involving DNA, RNA, or protein inputs. Our results highlight the potential of unified foundation models to address complex biological questions, providing an adaptable framework for bioinformatics research and enhancing the interpretation of lifes complexity.

bioinformatics↗

bioRxiv2024

Discovery and characterization of stereodefined PMO-gapmers targeting tau

Antisense oligonucleotides (ASOs) are an important class of therapeutics to treat genetic diseases, and expansion of this modality to neurodegenerative disorders has been an active area of research. To realize chronic administration of ASO therapeutics to treat neurogenerative diseases, new chemical modifications improving activity and safety profile are still needed. Furthermore, it is highly desirable to develop a single stereopure ASO with defined activity and safety profile to avoid any efficacy and safety concerns due to the batch-to-batch variation in the composition of diastereomers. Herein, a stereopure PMO-gapmer was developed as a new construct to improve safety and stability by installing charge-neutral PMOs at the wing region and by fully controlling phosphorus stereochemistries. The developed stereopure PMO-gapmer construct was applied to the discovery of ASO candidates for the reduction of microtubule-associated protein tau (MAPT, tau). Sequence screening targeting MAPT followed by screening of optimal phosphorus stereochemistry identified stereopure development candidates. While evaluating the stereopure PMO-gapmers, we observed a dramatic difference in safety profile among stereoisomers in which only one phosphorus stereochemistry differs. These results further highlight the benefits of developing stereopure ASOs as safe and well-characterized candidates for clinical studies.

neuroscience↗

bioRxiv2024

Ancient cyanobacterial proto-circadian clock adapted to short day-night cycles ~ 0.95 billion years ago

In the early history, the Earth rotation was much faster; however, how ancient organisms adapted to the day-night cycles of that time remains unclear. We resurrected the ancestor KaiABC (anKaiABC) genes circa 0.95 billion years (Ga) ago when the daily-night cycling period was [~] 18 h. Compared with its contemporary counterpart KaiC, the anKaiC protein shows subtle structural differences, and the activities of kinase, phosphatase activities, and adenosine triphosphatase (ATPase) of anKaiC are lower. The anKaiAB proteins are less effective in regulating KaiC/anKaiC phosphorylation status. The anKaiABC system does not sustain an endogenous oscillation but it can be entrained by an 18-h light/dark cycle. The strain expressing anKaiABC shows better adaptation under 9-h light/9-h dark cycles (LD9:9) which mimic the 18-h day-night cycles. These findings suggest that the ancient cyanobacterial proto-circadian system may not be endogenous, but it conferred the capability to adapt to daily cycles [~] 0.95 Ga ago.

evolutionary biology↗

bioRxiv2024

Peaks and Distributions of White Matter Tract-related Strains in Bicycle Helmeted Impacts: Implication for Helmet Ranking and Optimization

Traumatic brain injury (TBI) in cyclists is a growing public health problem, with helmets being the major protection gear. Finite element head models have been increasingly used to engineer safer helmets often by mitigating brain strain peaks. However, how different helmets alter the spatial distribution of brain strain remains largely unknown. Besides, existing research primarily used maximum principal strain (MPS) as the injury parameter, while white matter fiber tract-related strains, increasingly recognized as effective predictors for TBI, have rarely been used for helmet evaluation. To address these research gaps, we used an anatomically detailed head model with embedded fiber tracts to simulate fifty-one helmeted impacts, encompassing seventeen bicycle helmets under three impact locations. We assessed the helmet performance based on four tract-related strains characterizing the normal and shear strain oriented along and perpendicular to the fiber tract, as well as the prevalently used MPS. Our results showed that both the helmet model and impact location affected the strain peaks. Interestingly, we noted that helmets did not alter strain distribution, except for one helmet under one specific impact location. Moreover, our analyses revealed that helmet ranking outcome based on strain peaks was affected by the choice of injury metrics (Kendalls tau coefficient: 0.58 [~] 0.93). Significant correlations were noted between tract-related strains and angular motion-based injury metrics. This study provided new insights into computational brain biomechanics and highlighted the helmet ranking outcome was dependent on the choice of injury metrics. Our results also hinted that the performance of helmets could be augmented by mitigating the strain peak and optimizing the strain distribution with accounting the selective vulnerability of brain subregions, although more research was needed to develop region-specific injury criteria.

bioengineering↗

bioRxiv2024

pNet: A toolbox for personalized functional networks modeling

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

neuroscience↗

bioRxiv2024

JNK and PI3K signaling pathways mediate synapse formation and network spontaneous activities in primary neurons

BackgroundCellular signals orchestrating synapse formation and neuronal network function remain poorly understood. To explore the critical signaling pathways in neurons and their influence on network development, pharmacological assays were employed to inhibit multiple signaling pathways in cultured neurons. MethodsImmunofluorescence and western blotting are applied to identify the expression of synapse-related proteins within neurons. micro-electrode arrays (MEAs) are employed to study the developmental characteristics of neuronal networks. RNA sequencing is utilized to determine the gene expression profiles pertaining to multiple signaling pathways. ResultsCanonical c-jun N-terminal kinases (JNK) pathway is necessary for pre- and post-synaptic specializations, while phosphatidylinositide3-kinases (PI3K) is a key to postsynaptic specialization and affects the puncta sizes of presynaptic marker. Unexpectedly, pharmacological inhibition of JNK pathway significantly suppressed the mean firing rate (MFR), network burst frequency (NBF) and regularity of network firing after 4 weeks, but did not alter the synchrony of the network. During network development, PI3K pathway regulates the longer burst duration and lower network synchrony. Gene sets associated with neurodevelopmental processes and myelination was disturbed during restraining these signal pathways. Furthermore, inhibition of the PI3K signaling pathway obviously transformed voltage-gated ion channel activity, synaptic transmission and synaptic plasticity of neurons. ConclusionThis study reveals that JNK and PI3K signaling pathways play different roles during synapse formation, and these signaling pathways have a lasting impact on the development of neuronal networks. Thus, this study provides further insights into the intracellular signaling pathways associated with synapse formation in the development of neuronal networks.

neuroscience↗

bioRxiv2024

DeProt: A protein language model with quantizied structure and disentangled attention

Protein language models (PLMs) have shown remarkable capabilities in various protein function prediction tasks. However, while protein function is intricately tied to structure, most existing PLMs do not incorporate protein structure information. To address this issue, we introduce ProSST, a Transformer-based protein language model that seamlessly integrates both protein sequences and structures. ProSST incorporates a structure quantization module and a Transformer architecture with disentangled attention. The structure quantization module translates a 3D protein structure into a sequence of discrete tokens by first serializing the protein structure into residue-level local structures and then embeds them into dense vector space. These vectors are then quantized into discrete structure tokens by a pre-trained clustering model. These tokens serve as an effective protein structure representation. Furthermore, ProSST explicitly learns the relationship between protein residue token sequences and structure token sequences through the sequence-structure disentangled attention. We pre-train ProSST on millions of protein structures using a masked language model objective, enabling it to learn comprehensive contextual representations of proteins. To evaluate the proposed ProSST, we conduct extensive experiments on the zero-shot mutation effect prediction and several supervised downstream tasks, where ProSST achieves the state-of-the-art performance among all baselines. Our code and pretrained models are publicly available 2.

bioinformatics↗

bioRxiv2024

Macro- and Micro-Structural Alterations in the Midbrain in Early Psychosis

IntroductionEarly psychosis (EP) is a critical period in the course of psychotic disorders during which the brain is thought to undergo rapid and significant functional and structural changes 1. Growing evidence suggests that the advent of psychotic disorders is early alterations in the brains functional connectivity and structure, leading to aberrant neural network organization. The Human Connectome Project (HCP) is a global effort to map the human brains connectivity in healthy and disease populations; within HCP, there is a specific dataset that focuses on the EP subjects (i.e., those within five years of the initial psychotic episode) (HCP-EP), which is the focus of our study. Given the critically important role of the midbrain function and structure in psychotic disorders (cite), and EP in particular (cite), we specifically focused on the midbrain macro- and micro-structural alterations and their association with clinical outcomes in HCP-EP. MethodsWe examined macro- and micro-structural brain alterations in the HCP-EP sample (n=179: EP, n=123, Controls, n=56) as well as their associations with behavioral measures (i.e., symptoms severity) using a stepwise approach, incorporating a multimodal MRI analysis procedure. First, Deformation Based Morphometry (DBM) was carried out on the whole brain 3 Tesla T1w images to examine gross brain anatomy (i.e., seed-based and voxel-based volumes). Second, we extracted Fractional Anisotropy (FA), Axial Diffusivity (AD), and Mean Diffusivity (MD) indices from the Diffusion Tensor Imaging (DTI) data; a midbrain mask was created based on FreeSurfer v.6.0 atlas. Third, we employed Tract-Based Spatial Statistics (TBSS) to determine microstructural alterations in white matter tracts within the midbrain and broader regions. Finally, we conducted correlation analyses to examine associations between the DBM-, DTI- and TBSS-based outcomes and the Positive and Negative Syndrome Scale (PANSS) scores. ResultsDBM analysis showed alterations in the hippocampus, midbrain, and caudate/putamen. A DTI voxel-based analysis shows midbrain reductions in FA and AD and increases in MD; meanwhile, the hippocampus shows an increase in FA and a decrease in AD and MD. Several key brain regions also show alterations in DTI indices (e.g., insula, caudate, prefrontal cortex). A seed-based analysis centered around a midbrain region of interest obtained from freesurfer segmentation confirms the voxel-based analysis of DTI indices. TBSS successfully captured structural differences within the midbrain and complementary alterations in other main white matter tracts, such as the corticospinal tract and cingulum, suggesting early altered brain connectivity in EP. Correlations between these quantities in the EP group and behavioral scores (i.e., PANSS and CAINS tests) were explored. It was found that midbrain volume noticeably correlates with the Cognitive score of PA and all DTI metrics. FA correlates with the several dimensions of the PANSS, while AD and MD do not show many associations with PANSS or CAINS. ConclusionsOur findings contribute to understanding the midbrain-focused circuitry involvement in EP and complimentary alteration in EP. Our work provides a path for future investigations to inform specific brain-based biomarkers of EP and their relationships to clinical manifestations of the psychosis course.

neuroscience↗

bioRxiv2024

CRISPR/Cas9 gene editing in Drosophila via visual selection in a summer classroom

CRISPR/Cas9 methods are a powerful in vivo approach to edit the genome of Drosophila melanogaster. To convert existing Drosophila GAL4 lines to LexA driver lines in a secondary school classroom setting, we applied the CRISPR-based genetic approach to a collection of Gal4 driver lines. The integration of the yellow+ coat color marker into homology-assisted CRISPR knock-in (HACK) enabled visual selection of Gal4-to-LexA conversions using brightfield stereo-microscopy available in a broader set of standard classrooms. Here, we report the successful conversion of eleven Gal4 lines with expression in neuropeptide-expressing cells into corresponding, novel LexA drivers. The conversion was confirmed by LexA- and Gal4-specific GFP reporter gene expression. This curriculum was successfully implemented in a summer course running 16 hours/week for seven weeks. The modularity, flexibility, and compactness of this course should enable development of similar classes in secondary schools and undergraduate curricula, to provide opportunities for experience-based science instruction, and university-secondary school collaborations that simultaneously fulfill research needs in the community of science.

genetics↗

bioRxiv2024

The white matter fiber tract deforms most in the perpendicular direction during in vivo volunteer impacts

White matter (WM) tract-related strains are increasingly used to quantify brain mechanical responses, but their dynamics in live human brains during in vivo impact conditions remain largely unknown. Existing research primarily looked into the normal strain along the WM fiber tracts (i.e., tract-oriented normal strain), but it is rarely the case that the fiber tract only endures tract-oriented normal strain during impacts. In this study, we aim to extend the in vivo measurement of WM fiber deformation by quantifying the normal strain perpendicular to the fiber tract (i.e., tract-perpendicular normal strain) and the shear strain along and perpendicular to the fiber tract (i.e., tract-oriented shear strain and tract-perpendicular shear strain, respectively). To achieve this, we combine the three-dimensional strain tensor from the tagged magnetic resonance imaging (tMRI) with the diffusion tensor imaging (DTI) from an open-access dataset, including 44 volunteer impacts under two head loading modes, i.e., neck rotations (N = 30) and neck extensions (N = 14). The strain tensor is rotated to the coordinate system with one axis aligned with DTI-revealed fiber orientation and then four tract-related strain measures are calculated. The results show that tract-perpendicular normal strain peaks are the largest among the four strain types (p < 0.05, Friedmans test). The distribution of tract-related strains is affected by the head loading mode, of which laterally symmetric patterns with respect to the midsagittal plane are noted under neck extensions, but not under neck rotations. Our study presents a comprehensive in vivo strain quantification towards a multifaceted understanding of WM dynamics. We find the WM fiber tract deforms most in the perpendicular direction, illuminating new fundamentals of brain mechanics. The reported strain images can be used to evaluate the fidelity of computational head models, especially those intended to predict fiber deformation under non-injurious conditions.

bioengineering↗

bioRxiv2024

Multi-omics Identify Serotonin Transporter as a Promising Therapeutic Target for Essential Tremor

Essential tremor (ET) stands as one of the most prevalent cerebellar movement disorders. However, effective treatment remains elusive, largely due to a limited understanding of its molecular pathology. Harmaline-induced tremor in mouse is a well-established animal model for ET, while with enigmatic mechanism. The aim of this study was to get insight into the molecular intricacies underlying cerebellar dysfunction in harmaline-induced tremor. Combining LC-MS/MS and RNA-Seq analysis, we delved into the variation of the cerebellum between harmaline-induced tremor and the control ones. This comprehensive investigation revealed a profile of this mouse model from mRNA and protein level, highlighting 5194 correlated coding molecules, with 19 proving to be significant. Further KEGG enrichment analysis identified cerebellar serotonin transporter (SERT) as the key molecule in harmaline-induced tremor. The implications of this transcriptomic and proteomic exploration underscore the potential therapeutic value of targeting SERT as a novel treatment approach for ET. In general, our study unveils crucial insights that could pave the way for molecular target identification and effective therapeutic interventions for ET.

neuroscience↗

bioRxiv2024

Deciphering the Influence of Socioeconomic Status on Brain Structure: Insights from Mendelian Randomization

Socioeconomic status (SES) influences physical and mental health, however its relation with brain structure is less well documented. Here, we examine the role of SES on brain structure using Mendelian randomisation. First, we conduct a multivariate genome-wide association study of SES using individual, household, and area-based measures of SES, with an effective sample size of n=893,604. We identify 469 loci associated with SES and distil these loci into those that are common across measures of SES and those specific to each indicator. Second, using an independent sample of [~]35,000 we provide evidence to suggest that total brain volume is a causal factor in higher SES, and that SES is protective against white matter hyperintensities as a proportion of intracranial volume (WMHicv). Third, we find evidence that whilst differences in cognitive ability explain some of the causal effect of SES on WMHicv, differences in SES still afford a protective effect against WMHicv, independent of that made by cognitive ability.

genetics↗