Biology subjects

Shen, T.

Publications and source records attributed to Shen, T..

43 records · Page 3Linked to original sources

bioRxiv2019

Identification of a novel tedizolid resistance mutation in rpoB of methicillin-resistant Staphylococcus aureus

A tedizolid-resistant isolate of MRSA was selected by serial passage. Whole genome sequencing revealed only a single nucleotide variant in rpoB. Cross-resistance to linezolid, chloramphenicol, and quinupristin-dalfopristin was observed but susceptibility to other drugs including rifampin was unchanged. Models of the RNA-polymerase-ribosomal complex revealed that the mutated residue was unlikely to interact directly with the oxazolidinone binding site. This is the first time that rpoB mutation has been associated with resistance to the PhLOPSa antimicrobials.

microbiology↗

bioRxiv2019

EphB6 regulates social behavior through gut microbiota-mediated vitamin B6 metabolism and excitation/inhibition balance of medial prefrontal cortex in mice

Autism spectrum disorder (ASD) is a developmental disorder with no effective pharmacological treatments so far. Gut microbiota has been suggested to contribute to autistic symptoms. However, the key genes and the mechanisms linking gut microbiota and brain dysfunctions in ASD are still unclear. Here, we found deletion of EphB6, an ASD-associated candidate gene, induced dysregulated gut microbiota and autism-like behavior in mice. More importantly, transplanting fecal microbiota from EphB6-deficient mice resulted in disturbed gut microbiota and autism-like behavior in antibiotics-treated C57BL/6J mice. Meanwhile, transplanting fecal microbiota from wild-type mice ameliorated disturbed gut microbiota and autism-like behavior in mice with deletion of EphB6. At the metabolic levels, dysregulated gut microbiota led to vitamin B6 and dopamine defects in EphB6-deficient mice. At the cellular levels, excitation/inhibition (E/I) imbalance in medial prefrontal cortex was induced by gut microbiota-mediated defects of vitamin B6 metabolism in EphB6-deficient mice. Our study uncovers a key role for EphB6 in regulation of social behavior by gut microbiota-mediated vitamin B6 metabolism, dopamine synthesis and E/I balance, suggesting a new strategy for treatment of ASD patients.

neuroscience↗

bioRxiv2019

3D Genome Structure Variation Across Cell Types Captured by Integrating Multi-omics

Background3D genome structure contributes to the establishment or maintenance of cell identity in part by organizing genes into spatial active or inactive compartments. Less is known about how compartment switching occurs across different cell types. Rather than analyze individual A/B compartment switches between pairs of cell types, here, we seek to identify coordinated changes in groups of compartment-scale interactions across a spectrum of cell types.\n\nResultsTo characterize the impact of genome folding on cell identity, we integrated 35 Hi-C datasets with 125 DNase-seq, 244 RNA-seq, and 893 ChIP-seq datasets. We first find physical associations with the nuclear lamina inform the most dramatic changes in chromosome structure across cell types. By examining variations in chromosome structure, transcription, and chromatin accessibility, we further observe that certain sets of correlated chromosome structure contacts also co-vary in transcription and chromatin accessibility. Analyzing ChIP-seq signals, we find that sets of chromosome contacts that form and break in sync tend to share active or suppressive histone marks. Finally, we observe that similar principles appear to govern chromosome structure fluctuations across single cells as were found across cell types.\n\nConclusionOur results suggest that cells adapt their chromosome structures, guided by variable associations with the lamina and histone marks, to allocate up-regulatory or down-regulatory resources to certain regions and achieve transcription and chromatin accessibility variation. Our study shows E-PCA can identify the major variable interaction sets within populations of single cells, across broad categories of normal cell types, and between cancer and non-cancerous cell types.

bioinformatics↗

bioRxiv2019

Occurrence of cross-resistance and beta-lactam seesaw effect in glycopeptide, lipopeptide, and lipoglycopeptide-resistant MRSA correlates with membrane phosphatidylglycerol levels

Treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections is challenging and is associated with high rates of therapeutic failure. The glycopeptide (GP) vancomycin and the lipopeptide (LP) daptomycin are still relied upon to manage invasive MRSA infections; however, resistance to these antibiotics has emerged and there is evidence of cross-resistance between them. It has been observed that the susceptibility of MRSA to beta-lactams increases as susceptibility to GPs and LPs decreases, a phenomenon termed the seesaw effect. Recent efforts to understand the mechanism underlying the seesaw effect have focused on the penicillin binding proteins (PBPs). However, while daptomycin resistance is largely mediated by remodeling of membrane lipid composition, the role of membrane lipids in producing cross-resistance and the seesaw effect has not yet been investigated. Here, we evaluate the lipid profiles, cross susceptibilities, and beta-lactam susceptibilities of a collection of isogenic MRSA strains selected against daptomycin, vancomycin or dalbavancin (a lipoglycopeptide; LGP) to assess the relationship between membrane composition, cross-resistance, and the seesaw effect. We found that modification of membrane composition occurs not only in daptomycin-selected strains, but also vancomycin- and dalbavancin-selected strains. Significantly, we observed that typically the levels of short-chain phosphatidylglycerols (PGs) negatively correlate with MICs of GP/LP/LGP and positively correlate with MIC of certain beta-lactams, the latter being dependent on the primary PBP target of the particular beta-lactam. Furthermore, changes to certain PGs with long-chain fatty acids correlate well with presence of the seesaw effect. These studies demonstrate a major association between membrane remodeling and the seesaw effect.

microbiology↗

bioRxiv2019

A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium

Mouse knockouts allow studying gene functions. Often, multiple phenotypes are impacted when a gene is inactivated. The International Mouse Phenotyping Consortium (IPMC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples of 30 mouse gene knockouts and corresponding wildtype mice from IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.\n\nData SetThe dataset is available at the MetabolomicsWorkbench repository (accession ID: ST001154)\n\nData Set Licenselicense under which the data set is made available (CC0).

bioinformatics↗

bioRxiv2018

Metabolomics and proteomics analyses of grain yield reduction in rice under abrupt drought-flood alternation

HighlightAbrupt drought-flood alteration is a frequent meteorological disaster that occurs during summer in southern China and the Yangtze river basin, which often causes a large area reduction of rice yield. We previously reported abrupt drought-flood alteration effects on yield and its components, physiological characteristics, matter accumulation and translocation, rice quality of rice. However, the molecular mechanism of rice yield reduction caused by abrupt drought-flood alternation has not been reported.\n\nIn this study, four treatments were provided, no drought and no floods (control), drought without floods (duration of drought 10 d), no drought with floods (duration of floods 8 d), and abrupt drought-flood alteration (duration of drought 10 d and floods 8 d). The quantitative analysis of spike metabolites was proceeded by LC-MS (liquid chromatograph-mass spectrometry) firstly. Then the Heat-map, PCA, PLS-DA, OPLS-DA and response ranking test of OPLS-DA model methods were used to analysis the function of differential metabolites (DMs) during the rice panicle differentiation stage under abrupt drought-flood alteration. In addition, relative quantitative analysis of spike total proteins under the treatment was conducted iTRAQ (isobaric tags for relative and absolute quantification) and LC-MS. In this study, 5708 proteins were identified and 4803 proteins were quantified. The identification and analysis of DEPs function suggested that abrupt drought-flood alteration treatment can promote carbohydrate metabolic, stress response, oxidation-reduction, defense response, and energy reserve metabolic process, etc, during panicle differentiation stage. In this study relative quantitative proteomics, metabolomics and physiology data (soluble protein content, superoxide dismutase activity, hydrogen peroxidase activity, peroxidase activity, malondialdehyde content, free proline content, soluble sugar content and net photosynthetic rate) analysis were applied to explicit the response mechanism of rice panicle differentiation stage under abrupt drought-flood alteration and provides a theoretical basis for the disaster prevention and mitigation.\n\nAbstractAbrupt drought-flood alternation is a meteorological disaster that frequently occurs during summer in southern China and the Yangtze river basin, often causing a significant loss of rice production. In this study, a quantitative analysis of spike metabolites was conducted via liquid chromatograph-mass spectrometry (LC-MS), and Heat-map, PCA, PLS-DA, OPLS-DA, and a response ranking test of OPLS-DA model methods were used to analyze functions of differential metabolites (DMs) during the rice panicle differentiation stage under abrupt drought-flood alternation. The results showed that 102 DMs were identified from the rice spike between T1 (abrupt drought-flood alternation) and CK0 (control) treatment, 104 DMs were identified between T1 and CK1 (drought) treatment and 116 DMs were identified between T1 and CK2 (flood) treatment. In addition, a relative quantitative analysis of spike total proteins was conducted using isobaric tags for relative and absolute quantification (iTRAQ) and LC-MS. The identification and analysis of DEPs functions indicates that abrupt drought-flood alternation treatment can promote carbohydrate metabolic, stress response, oxidation-reduction, defense response, and energy reserve metabolic process during the panicle differentiation stage. In this study, relative quantitative metabolomics and proteomics analyses were applied to explore the response mechanism of rice panicle differentiation in response to abrupt drought-flood alternation.\n\nAbbreviations

plant biology↗

bioRxiv2018

Characterizing the 3D structure and dynamics of chromosomes and proteins in a common contact matrix framework

Any conformational ensemble of biopolymers, whether they are proteins or chromosomes, can be described using contact matrices derived from experimental or computational studies. One powerful approach to extract meaningful information from these contact matrices is to perform principal component analysis (PCA) on the covariance matrix of the contact data. Indeed, PCA on Hi-C chromosome contact matrices has revealed the spatial segregation of active and inactive chromatin. Separately, PCA on contact matrices from snapshots of protein conformations has characterized correlated fluctuations of protein domains. However, despite the similarities of these data and analyses, there has been little synergy between the PCA approaches and the comparison of resulting biological insights obtained for protein and chromosome structures. We note that, to date, different styles of analyses were applied exclusively to each biomolecule type: explicit contact correlation analysis (E-PCA) for proteins and implicit contact correlation (I-PCA) for chromosomes. In this work, we compare the results of applying both methods to both classes of biopolymers. While I-PCA reveals only average features of 3D chromosome structure, we find that applying E-PCA to an ensemble of chromosome structures from microscopy data reveals the dominant motion (concerted fluctuation) of the chromosome. Applying E-PCA to Hi-C data across the human blood cell lineage isolates the aspects of chromosome structure that most strongly differentiate cell types. Conversely, when we apply I-PCA to simulation snapshots of two protein complexes, the major component reports the consensus features of the structure, while the previously applied E-PCA characterizes correlated deviations from the mean structure.

biophysics↗