Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 1,045 records · Page 58Linked to original sources

bioRxiv2021

Alkaliphilus flagellata sp. nov., Butyricicoccus intestinisimiae sp. nov., Clostridium mobile sp. nov., Clostridium simiarum sp. nov., Dysosmobacter acutus sp. nov., Paenibacillus brevis sp. nov., Peptoniphilus ovalis sp. nov., and Tissierella simiarum sp. nov., isolated from monkey feces

Non-human primates harbor diverse microbiomes in their guts. As a part of China Microbiome Initiatives, we cultivated and characterized the gut microbiome of cynomolgus monkeys (Macaca fascicularis). In this report, we communicate the characterization and taxonomy of 8 bacterial strains that were obtained from fecal samples of captive cynomolgus monkeys. The results revealed that they represented 8 novel bacterial species. The proposed names of the 8 novel species are Alkaliphilus flagellate (type strain MSJ-5T =CGMCC 1.45007T=KCTC 15974T), Butyricicoccus intestinisimiae MSJd-7T (type strain MSJd-7T =CGMCC 1.45013T =KCTC 25112T), Clostridium mobile (type strain MSJ-11T =CGMCC 1.45009T=KCTC 25065T), Clostridium simiarum (type strain MSJ-4T =CGMCC 1.45006T =KCTC 15975T), Dysosmobacter acutus (type strain MSJ-2T =CGMCC 1.32896T=KCTC 15976T), Paenibacillus brevis MSJ-6T (type strain MSJ-6T =CGMCC 1.45008T=KCTC 15973T), Peptoniphilus ovalis (type strain MSJ-1T =CGMCC 1.31770T=KCTC 15977T), and Tissierella simiarum (type strain MSJ-40T =CGMCC 1.45012T=KCTC 25071T).

microbiology↗

bioRxiv2021

Integrated de novo Gene Prediction and Peptide Assembly of Metagenomic Sequencing Data

Metagenomics is the study of all genomic content presented in given microbial communities. Metagenomic functional analysis aims to quantify protein families and reconstruct metabolic pathways from the metagenome. It plays a central role in understanding the interaction between the microbial community and its host or environment. De novo functional analysis, which allows the discovery of novel protein families, remains challenging for high-complexity communities. There are currently three main approaches for recovering novel genes or proteins: de novo nucleotide assembly, gene calling, and peptide assembly. Unfortunately, their informational connection and dependency have been overlooked, and each has been formulated as an independent problem. In this work, we develop a sophisticated workflow called integrated Metagenomic Protein Predictor (iMPP), which leverages the informational dependencies for better de novo functional analysis. iMPP contains three novel modules: a hybrid assembly graph generation module, a graph-based gene calling module, and a peptide assembly-based refinement module. iMPP significantly improved the existing gene calling sensitivity on unassembled fragmented reads, achieving a 92% - 97% recall rate at a high precision level (>90%). iMPP further allowed for more sensitive and accurate peptide assembly, recovering more reference proteins and delivering more hypothetical protein sequences. The high performance of iMPP can provide a more comprehensive and unbiased view of the microbial communities under investigation. iMPP is freely available from https://github.com/Sirisha-t/iMPP.

bioinformatics↗

bioRxiv2021

A non-bactericidal cathelicidin provides prophylactic efficacy against bacterial infection by driving phagocyte influx

The roles of bactericidal cathelicidins against bacterial infection have been extensively studied. However, the anti-bacterial property and mechanism of action of non-bactericidal cathelicidins are rarely known. Herein, a novel naturally occurring cathelicidin (PopuCATH) from tree frog (Polypedates puerensis) didnt show any direct anti-bacterial activity in vitro. Intriguingly, intraperitoneal injection of PopuCATH before bacterial inoculation significantly reduced the bacterial load in tree frogs and mice, and reduced the inflammatory response induced by bacterial inoculation in mice. PopuCATH pretreatment also increased the survival rates of septic mice induced by a lethal dose of bacterial inoculation or cecal ligation and puncture (CLP). Intraperitoneal injection of PopuCATH significantly drove the leukocyte influx in both frogs and mice. In mice, PopuCATH rapidly drove neutrophil, monocyte/macrophage influx in mouse abdominal cavity and peripheral blood with a negligible impact on T and B lymphocytes, and neutrophils, monocytes/macrophages, but not T and B lymphocytes, were required for the preventive efficacy of PopuCATH. PopuCATH did not directly act as chemoattractant for phagocytes, but PopuCATH obviously drove phagocyte migration when it was cultured with macrophages. PopuCATH significantly elicited chemokine/cytokine production in macrophages through activating p38/ERK mitogen-activated protein kinases (MAPKs) and NF-{kappa}B p65. PopuCATH markedly enhanced neutrophil phagocytosis via promoting the release of neutrophil extracellular traps (NETs). Additionally, PopuCATH showed low side effects both in vitro and in vivo. Collectively, PopuCATH acts as a host-based immune defense regulator that provides prophylactic efficacy against bacterial infection without direct antimicrobial effects. Our findings reveal a non-bactericidal cathelicidin which possesses unique anti-bacterial action, and highlight the potential of PopuCATH to prevent bacterial infection.

immunology↗

bioRxiv2021

Capturing large genomic contexts for accurately predicting enhancer-promoter interactions

Accurately identifying enhancer-promoter interactions (EPIs) is challenging because enhancers usually act on the promoters of distant target genes. Although a variety of machine learning and deep learning models have been developed, many of them are not designed to or could not be well applied to predict EPIs in cell types different from the training data. In this study, we develop the TransEPI model for EPI prediction based on datasets derived from Hi-C and ChIA-PET data. TransEPI compiles genomic features from large intervals harboring the enhancer-promoter pair and adopts a Transformer-based architecture to capture the long-range dependencies. Thus, TransEPI could achieve more accurate prediction by addressing the impact of other genomic loci that may competitively interact with the enhancer-promoter pair. We evaluate TransEPI in a challenging scenario, where the independent test samples are predicted by models trained on the data from different cell types and chromosomes. TransEPI robustly predicts cross-cell-type EPI prediction by achieving comparable performance in cross-validation and independent test. More importantly, TransEPI significantly outperforms the state-of-the-art EPI models on the independent test datasets, with the Area Under Precision-Recall Curve (auPRC) score increasing by 48.84 % on average. Hence, TransEPI is applicable for accurate EPI prediction in cell types without chromatin structure data. Moreover, we find the TransEPI framework could also be extended to identify the target gene of non-coding mutations, which may facilitate studying pathogenic non-coding mutations.

bioinformatics↗

bioRxiv2021

Extensive germline-somatic interplay drives prostate cancer through HNF1B co-option of TMPRSS2-ERG

Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression.

cancer biology↗

bioRxiv2021

Dissecting the subtropical adaptation traits and cuticle synthesis pathways via the genome of the subtropical blueberry Vaccinium darrowii

Vaccinium darrowii is a subtropical wild blueberry species, which was used to breed economically important southern highbush cultivars. The adaptation traits of V. darrowii to subtropical climate would provide valuable information for breeding blueberry and perhaps other plants, especially against the background of global warming. Here, we assembled the V. darrowii genome into 12 pseudochoromosomes using Oxford Nanopore long reads complemented with Hi-C scaffolding technologies, and predicted 41 815 genes using RNAseq evidence. Syntenic analysis across three Vaccinium species revealed a highly conserved genome structure, with the highest collinearity between V. darrowii and V. corymbosum. This conserved genome structure may explain the high fertilization during crossbreeding between V. darrowii and other blueberry cultivars. Gene expansion and tandem duplication analysis indicated possible roles of defense and flowering associated genes in adaptation of V. darrowii to the subtropics. The possible SOC1 genes in V. darrowii were identified with phylogeny and expression analysis. Blueberries are covered in a thick cuticle layer and contain anthocyanins, which confer their powdery blue color. Using RNA-sequencing, the cuticle biosynthesis pathways of Vaccinium species were delineated here in V. darrowii. This result could serve as a reference for breeding berries with customer-desired colors. The V. darrowii reference genome, together with the unique traits of this species, including diploid genome, short vegetative phase, and high compatibility in hybridization with other blueberries, make V. darrowii a potential research model for blueberry species.

plant biology↗

bioRxiv2021

Dominating Lengthscales of Zebrafish Collective Behaviour

Collective behaviour in living systems is observed across many scales, from bacteria to insects, to fish shoals. Zebrafish have emerged as a model system amenable to laboratory study. Here we report a three-dimensional study of the collective dynamics of fifty Zebrafish. We observed the emergence of collective behaviour changing between polarised to randomised, upon adaption to new environmental conditions. We quantify the spatial and temporal correlation functions of the fish and identify two length scales, the persistence length and the nearest neighbour distance, that capture the essence of the behavioural changes. The ratio of the two length scales correlates robustly with the polarisation of collective motion that we explain with a reductionist model of self-propelled particles with alignment interactions.

animal behavior and cognition↗

bioRxiv2021

AlphaFold-aware prediction of protein-DNA binding sites using graph transformer

Protein-DNA interactions play crucial roles in the biological systems, and identifying protein-DNA binding sites is the first step for mechanistic understanding of various biological activities (such as transcription and repair) and designing novel drugs. How to accurately identify DNA-binding residues from only protein sequence remains a challenging task. Currently, most existing sequence-based methods only consider contextual features of the sequential neighbors, which are limited to capture spatial information. Based on the recent breakthrough in protein structure prediction by AlphaFold2, we propose an accurate predictor, GraphSite, for identifying DNA-binding residues based on the structural models predicted by AlphaFold2. Here, we convert the binding site prediction problem into a graph node classification task and employ a transformer-based variant model to take the protein structural information into account. By leveraging predicted protein structures and graph transformer, GraphSite substantially improves over the latest sequence-based and structure-based methods. The algorithm is further confirmed on the independent test set of 181 proteins, where GraphSite surpasses the state-of-the-art structure-based method by 16.4% in AUPR and 11.2% in MCC, respectively. We provide the datasets, the predicted structures, and the source codes along with the pre-trained models of GraphSite at https://github.com/biomed-AI/GraphSite. The GraphSite web server is freely available at https://biomed.nscc-gz.cn/apps/GraphSite.

bioinformatics↗

bioRxiv2021

A universal approach for integrating super large-scale single-cell transcriptomes by exploring gene rankings

Advancement in single-cell RNA sequencing leads to exponential accumulation of single-cell expression data. However, there is still lack of tools that could integrate these unlimited accumulation of single-cell expression data. Here, we presented a universal approach iSEEEK for integrating super large-scale single-cell expression via exploring expression rankings of top-expressing genes. We developed iSEEEK with 13.7 million single-cells. We demonstrated the efficiency of iSEEEK with canonical single-cell downstream tasks on five heterogenous datasets encompassing human and mouse samples. iSEEEK achieved good clustering performance benchmarked against well-annotated cell labels. In addition, iSEEEK could transfer its knowledge learned from large-scale expression data on new dataset that was not involved in its development. iSEEEK enables identification of gene-gene interaction networks that are characteristic of specific cell types. Our study presents a simple and yet effective method to integrate super large-scale single-cell transcriptomes and would facilitate translational single-cell research from bench to bedside.

bioinformatics↗

bioRxiv2021

Spectral fiber-photometry derives hemoglobin-absorption changes for accurate measurement of fluorescent sensors

Fiber-photometry is an emerging technique for recording fluorescent sensor activity in the brain. However, significant hemoglobin-absorption artifacts in fiber-photometry data may be misinterpreted as sensor activity changes. Because hemoglobin exists in nearly every location in the brain and its concentration varies over time, such artifacts could impede the accuracy of many photometry recording results. Here we present a novel use of spectral photometry technique and propose computational methods to quantify photon absorption effects by using activity-independent fluorescence signals, which can be used to derive oxy- and deoxy-hemoglobin concentration changes. Following time-locked neuronal activation in vivo, we observed that a 20% increase in CBV contributes to about a 4% decrease in green fluorescence signal and a 2% decrease in red fluorescence signal. While these hemoglobin concentration changes are often temporally delayed than the fast-responding fluorescence spikes, we found that erroneous interpretation may occur when examining pharmacology-induced sustained activity changes, and in some cases, hemoglobin-absorption could flip the GCaMP signal polarity. We provided hemoglobin-based correction methods to restore fluorescence signals across spectra and compare our results against the commonly used regression approach. We also demonstrated the utility of spectral fiber-photometry for delineating brain regional differences in hemodynamic response functions. HighlightsO_LIHemoglobin-absorption compromises fiber-photometry recording in vivo C_LIO_LISpectral photometry allows quantification of hemoglobin concentration changes for correction C_LIO_LIThe proposed platform allows measuring regional differences in neurovascular transfer function C_LI

neuroscience↗

bioRxiv2021

DeepANIS: Predicting antibody paratope from concatenated CDR sequences by integrating bidirectional long-short-term memory and transformer neural networks

MotivationAntibodies are a type of important biomolecules in the humoral immunity system, which can bind tightly to potential antigens with high affinity and specificity. An accurate identification of the paratope, the binding sites with antigens, is crucial for antibody mechanistic research and design. Although many methods have been developed for paratope prediction, further improvement of their accuracy is necessary. ResultsIn this study, we concatenated the sequences of Complementarity Determining Regions (CDRs) within a single antibody to better capture nonlocal interactions between different CDRs and loop type-specific features for improving paratope prediction. We further integrated BiLSTM and transformer networks to gain the dependencies among the residues within the concatenated CDR sequences and to increase the interpretability of the model. The new method called DeepANIS (Antibody Interacting Site prediction) outperforms other antibody paratope prediction methods compared. AvailabilityThe DeepANIS method is freely available as a webserver at https://biomed.nscc-gz.cn:9094/apps/DeepANIS and for download at https://github.com/HideInDust/DeepANIS Contactyangyd25@mail.sysu.edu.cn or zhouyq@szbl.ac.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2021

Synaptic and mitochondrial plasticity associated with fear memory revealed by deep learning-based 3D reconstruction

Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demanding but still highly informative. We thus developed a Region-CNN-based deep learning method to identify, segment, and reconstruct synapses and mitochondria to explore the structural plasticity of synapses and mitochondria in the auditory cortex of mice subjected to fear conditioning. Upon reconstructing over 135,000 mitochondria and 160,000 synapses, we found that fear conditioning significantly increases the number of mitochondria but decreases their size, and promotes the formation of multi-contact synapses comprising a single axonal bouton and multiple postsynaptic sites from different dendrites. Modeling indicates that such multi-contact configuration increases the information storage capacity of new synapses by over 50%. With high accuracy and speed in reconstruction, our method yields structural and functional insight into cellular plasticity associated with fear learning.

neuroscience↗

bioRxiv2021

Comparative proteomic analysis of vancomycin-sensitive and vancomycin-intermediate resistant S. aureus

The extensive use of vancomycin has led to the development of MRSA (methicillin-resistant Staphylococcus aureus) strains with varying degrees of resistance to vancomycin. Accumulation of surplus cell wall material, decreased cross-linking of peptidoglycan, and/ or other cell wall alterations has been put forward to explain the VISA phenotype. To our knowledge, the protein profiles of hVISA and VISA strains are rarely analyzed via quantitative comparative proteomics. In this study, we subjected subcellular fractions isolated from two isogenic S. aureus strains (vancomycin-intermediate resistant S. aureus) to proteomic analysis, using an integrated quantitative proteomic approach assisted by bioinformatic analysis. In total,128 up-regulated proteins (mainly AhpC, Adh, ArgF et al.) were identified,21 down-regulated proteins (mainly LtaS, SdrD, MsrR, MsrB, OatA et al.) were obtained. The largest group of differentially expressed proteins is composed of enzymic proteins associated with metabolic and catalytic activity, which accounts for 50% and 51% of the total proteins, respectively.Some proteins which take an indispensable part in the regulatory networks of S. aureus with vancomycin treatment are related to Cell wall metabolism ( MurA ), Cell adhesion ( SdrC, SdrD, ClfA, ClfB ), Proteolysis ( Atl, LytM, SceD ) and Pressure response ( MsrA, MsrB, AhpC ) process.In conclusion, our proteomic study revealed regulatory proteins associated with vancomycin resistance in S. aureus, and some of these proteins are involved in the regulation of cell metabolism and function, providing protential targets for further development of drug resistance strategies.

microbiology↗

bioRxiv2021

A new single-cell level R-index for EGFR-TKI resistance and survival prediction in LUAD

EGFR-TKIs achieved excellent efficacy in EGFR-mutated patients. Unfortunately, most patients would inevitably develop progressive disease within a median of 10 to 14 months. Predicting the resistance probability remains a challenge. Therefore, we created an R-index model trained by single-cell RNA data with the OCLR algorithm. This model can be applied to estimate the level of EGFR-TKI resistance in cell line and xenograft mice models and predict prognosis in multiple cohorts. Comparing the high and the low R-index group, we found that the glycolysis pathway and KRAS up-regulation pathway were related to resistance, and MDSC was the leading cause of immunosuppression in the tumor microenvironment. These results are consistent with previous studies indicating that the R-index provides an insight into resistance status and a new way to explore resistance mechanisms and clinical treatment by the combination of Glucose metabolism-targeted or MDSC-targeted therapies. This is the first quantification method of EGFR-TKI resistance based on single-cell sequencing data solving the problem of the mixed resistance state of tumor cells and helping explore transcriptome characteristics of drug-resistant cell populations.

bioinformatics↗

bioRxiv2021

m6A-mediated Cell-cell Communication Controls Planarian Regeneration

Regeneration is the regrowth of damaged tissues or organs, a vital mechanism responding to damages from primitive organisms to higher mammals. Planarian possesses active whole-body regenerative capability owning to its vast reservoir of adult stem cells, neoblasts, thus provides an ideal model to delineate the underlying mechanisms for regeneration. N6-methyladenosine (m6A) regulates stem cell renewal and differentiation. However, how m6A controls regeneration at whole-organism level remains largely unknown. Here, we demonstrate that the depletion of m6A methyltransferase regulatory subunit wtap abolishes planarian regeneration, through regulating cell-cell communication and cell cycle. scRNA-Seq analysis unveils that the wtap knockdown induces a unique type of neural progenitor-like cells (NP-like cells), characterized by specific expression of the cell-cell communication ligand grn. Intriguingly, the depletion of m6A-modified transcripts grn/cdk9 (or cdk7) axis rescues the defective regeneration of planarian without wtap. Overall, our study reveals an indispensable role of m6A-dependent cell-cell communication essential for whole-organism regeneration.

molecular biology↗

bioRxiv2021

miR-206 inhibits estrogen-induced proliferation and invasion of ER-α36 positive gastric cancer cells

ObjectiveTo explore the biological role of miR-206 in inhibiting the proliferation and invasion of estrogen-induced ER-36 positive gastric cancer cells and its related mechanisms. MethodsMTT and tranwell assays were used to detect the proliferation and invasion of BGC-823 cells under different concentrations and time of ER stimulation. RT-PCR was used to detect the effect of ER stimulation on the content of miR-206 in gastric cancer cells. miR-206 mimics were transfected into BGC-823 cells to detect cell proliferation and invasion; luciferase reporter assay was used to determine whether miR-206 targets the 3-untranslated region of the CDK14-encoding gene (3 -UTR). ResultsWe confirmed that estrogen promoted the proliferation and invasion of BGC-823 cells; As the concentration of estrogen increases, the level of miR206 in the cell gradually rises.Overexpression of miR-206 significantly decreased the estrogen-induced BGC-823 cells. Proliferative and invasive ability; miR-206 inhibits the expression of CDK14 by directly binding to the 3-UTR of CDK14 mRNA, thereby inhibiting the proliferation and invasion of gastric cancer cells. ConclusionsOur results suggest that miR-206 inhibits estrogen-induced proliferation and invasion of ER-36-positive gastric cancer cells by inhibiting CDK14 and may be a promising therapeutic option for anticancer therapy.

cancer biology↗

bioRxiv2021

A pair of transporters controls mitochondrial Zn2+ levels to maintain mitochondrial homeostasis

Zn2+ is required for the activity of many mitochondrial proteins, which regulate mitochondrial dynamics, apoptosis and mitophagy. However, it is not understood how the proper mitochondrial Zn2+ level is achieved to maintain mitochondrial homeostasis. Using Caenorhabditis elegans, we reveal here that a pair of mitochondrion-localized transporters controls the mitochondrial level of Zn2+. We demonstrate that SLC-30A9/ZnT9 is a mitochondrial Zn2+ exporter. Loss of SLC-30A9 leads to mitochondrial Zn2+ accumulation, which damages mitochondria, impairs animal development and shortens the life span. We further identify SLC-25A25/SCaMC-2 as an important regulator of mitochondrial Zn2+ import. Loss of SLC-25A25 suppresses the abnormal mitochondrial Zn2+ accumulation and defective mitochondrial structure and functions caused by loss of SLC-30A9. Moreover, we reveal that the endoplasmic reticulum contains the Zn2+ pool from which mitochondrial Zn2+ is imported. These findings establish the molecular basis for controlling the correct mitochondrial Zn2+ levels for normal mitochondrial structure and functions. SummaryZn2+ is a trace ion essential for the function of many mitochondrial proteins. It is not known how mitochondrial Zn2+ levels are regulated. Ma at al. identify transporters that mediate mitochondrial Zn2+ export and import to maintain mitochondrial homeostasis.

cell biology↗

bioRxiv2021

E3 ubiquitin ligase SYVN1 is a key positive regulator for GSDMD-mediated pyroptosis

Gasdermin D (GSDMD) participates in activation of inflammasomes and pyroptosis. Meanwhile, ubiquitination strictly regulates inflammatory responses. However, how ubiquitination regulates Gasdermin D activity is not well understood. In this study, we show that pyroptosis triggered by Gasdermin D is regulated through ubiquitination. Specifically, SYVN1, an E3 ubiquitin ligase of gasdermin D, promotes GSDMD-mediated pyroptosis. SYVN1 deficiency inhibits pyroptosis and subsequent LDH release and PI uptake. SYVN1 directly interacts with GSDMD, and mediates K27-linked polyubiquitination of GSDMD on K203 and K204 residues, promoting GSDMD-induced pyroptotic cell death. Thus, our findings revealed the essential role of SYVN1 in GSDMD-mediated pyroptosis. Overall, GSDMD ubiquitination is a potential therapeutic module for inflammatory diseases.

immunology↗