Biology subjects

Teng, X.

Publications and source records attributed to Teng, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

A peculiar evolutionary feature of monkeypox virus

From 1 Jan 2022 to 15 June 2022, more than 2,100 cases of monkeypox have been reported in 42 countries. This unusual outbreak of monkeypox has raised new concerns in academia and the public. To keep abreast of the trend of the monkeypox epidemic, it is extremely urgent and important to surveille the accumulated genomic mutations and the change of the transmission ability of the pathogen, monkeypox virus (MPXV). We report a non-canonical RNA secondary structure, G-quadruplex (RG4), that surprisingly evolved stepwise with various variants. The RG4 motif is located in the coding sequence region of MPXV C9L gene that is functional in inhibiting host innate immune response. The evolution decreases the stability of this RG4 and promotes C9L protein level in living cells. Importantly, all the reported MPXV genomes in 2022 contain the most unstable RG4 variant, which may be the reason of the increasing spread of MPXV. These findings recommend that health authorities and researchers pay attention to the genomic evolution of MPXV.

genetics↗

bioRxiv2022

Structural insights into G protein activation by D1 dopamine receptor

G protein-coupled receptors (GPCRs) comprise the largest family of membrane receptors and are the most important drug targets. An agonist-bound GPCR engages heterotrimeric G proteins and triggers the exchange of GDP with GTP to promote G proteins activation. A complete understanding of the molecular mechanisms of G proteins activation has been hindered by a lack of structural information of GPCR-G protein complex in nucleotide-bound states. Here, we present the cryoelectron microscopy (cryo-EM) structures of D1 dopamine receptor (D1R)-Gs in the nucleotide-free state, the GDP-bound state and the GTP-bound state with endogenous ligand dopamine. These structures reveal important conformational changes accounting for the release of GDP and the GTP-dependent dissociation of G from G{beta}{gamma} subunits. Combining mutagenesis functional studies, we also identified an important sequence motif in D1R that determines its G protein selectivity. Taken together, these results shed light into the molecular basis of G protein selectivity and the entire molecular signaling events of GPCR-mediated G protein activation.

molecular biology↗

bioRxiv2021

Structural insights into the ion selectivity of the MgtE channel for Mg2+ over Ca2+

MgtE is a Mg2+-selective ion channel whose orthologs are widely distributed from prokaryotes to eukaryotes, including humans, and play an important role in the maintenance of cellular Mg2+ homeostasis. Previous functional analyses showed that MgtE transports divalent cations with high selectivity for Mg2+ over Ca2+. Whereas the high-resolution structure determination of the MgtE transmembrane (TM) domain in complex with Mg2+ ions revealed a Mg2+ recognition mechanism of MgtE, the previous Ca2+-bound structure of the MgtE TM domain was determined only at moderate resolution (3.2 [A] resolution), which was insufficient to visualize the water molecules coordinated to Ca2+ ions. Thus, the structural basis of the ion selectivity of MgtE for Mg2+ over Ca2+ has remained unclear. Here, we showed that the metal-binding site of the MgtE TM domain binds to Mg2+ [~]500-fold more strongly than Ca2+. We then determined the crystal structure of the MgtE TM domain in complex with Ca2+ ions at a higher resolution (2.5 [A] resolution), allowing us to reveal hexahydrated Ca2+, which is similarly observed in the previously determined Mg2+-bound structure but with extended metal-oxygen bond lengths. Our structural, biochemical, and computational analyses provide mechanistic insights into the ion selectivity of MgtE for Mg2+ over Ca2+.

biophysics↗

bioRxiv2021

Sequential Temporal Anticipation Characterized by Neural Power Modulation and in Recurrent Neural Networks

Relevant prospective moments arise intermittently, while most of time is filled with irrelevant events, or noise, that constantly bombard our sensory systems. Thus, anticipating a few key moments necessitates disregarding what lies between the present and the future - the noise. Here, through examining how the brain and the recurrent neural networks (RNNs) anticipate a sequence of prospective moments without relying on any external timing cues, we provided a reinterpretation of temporal anticipation. We first designed a "premembering" task, where we marked three temporal locations in white noise and asked human listeners to detect a tone at one of these points. Using power modulation analyses, we investigated the memory-guided anticipatory processes in trials involving only flat noise. Our research revealed a unique neural-power modulation pattern for sequential temporal anticipation: neural power within the alpha-beta band range fluctuates over time, accurately identifying the marked locations on a sub-second scale and correlating with tone detection performance. To understand the functional roles of these neural modulations, we utilized RNNs optimized for the behavioral task. The hidden dynamics of the RNNs mirrored the neural modulations, and additional analyses and perturbations on the RNNs indicated that the neural power modulations in the alpha-beta band resulted from selective suppression of irrelevant noise periods and heightened sensitivity to anticipated temporal locations. Our behavioral, neural, and modeling findings collectively indicate that sequential temporal anticipation involves a process of dynamic gain control: anticipating a few significant moments involves actively disregarding irrelevant events that frequently occur.

neuroscience↗

bioRxiv2021

Gene-dependent yeast cell death pathway requires AP-3 vesicle trafficking leading to vacuole membrane permeabilization

Unicellular eukaryotes are suggested to undergo self-inflicted destruction. However, molecular details are sparse by comparison to the mechanisms of cell death known for human cells and animal models. Here we report a molecular pathway in Saccharomyces cerevisiae leading to vacuole/lysosome membrane permeabilization and cell death. Following exposure to heat-ramp conditions, a model of environmental stress, we observed that yeast cell death occurs over several hours, suggesting an ongoing molecular dying process. A genome-wide screen for death-promoting factors identified all subunits of the AP-3 adaptor complex. AP-3 promotes stress-induced cell death through its Arf1-GTPase-dependent vesicle trafficking function, which is required to transport and install proteins on the vacuole/lysosome membrane, including a death-promoting protein kinase Yck3. Time-lapse microscopy revealed a sequence of events where AP-3-dependent vacuole permeability occurs hours before the loss of plasma membrane integrity. An AP-3-dependent cell death pathway appears to be conserved in the human pathogen Cryptococcus neoformans.

cell biology↗

bioRxiv2021

Segmenting and Predicting Musical Phrase Structure Exploits Neural Gain Modulation and Phase Precession

Music, like language, is characterized by hierarchically organized structure that unfolds over time. Music listening therefore requires not only the tracking of notes and beats but also internally constructing high-level musical structures or phrases and anticipating incoming contents. Unlike for language, mechanistic evidence for online musical segmentation and prediction at a structural level is sparse. We recorded neurophysiological data from participants listening to music in its original forms as well as in manipulated versions with locally or globally reversed harmonic structures. We discovered a low-frequency neural component that modulated the neural rhythms of beat tracking and reliably parsed musical phrases. We next identified phrasal phase precession, suggesting that listeners established structural predictions from ongoing listening experience to track phrasal boundaries. The data point to brain mechanisms that listeners use to segment continuous music at the phrasal level and to predict abstract structural features of music.

neuroscience↗

bioRxiv2021

Identification and mechanistic analysis of an inhibitor of the CorC Mg2+ transporter

The CorC/CNNM family of Na+-dependent Mg2+ transporters is ubiquitously conserved from bacteria to humans. CorC, the bacterial member of the CorC/CNNM family of proteins, is involved in resistance to antibiotic exposure and in the survival of pathogenic microorganisms in their host environment. The CorC/CNNM family proteins possess a cytoplasmic region containing the regulatory ATP-binding site. While CorC and CNNM have attracted interest as therapeutic targets, inhibitors targeting the ir regulatory ATP-binding site have not yet been identified. Here, we performed a virtual screening of CorC by targeting its regulatory ATP-binding site, identified a chemical compound named IGN95a with inhibitory effects on both ATP binding and Mg2+ export, and determined the cytoplasmic domain structure in complex with IGN95a. Furthermore, a chemical cross-linking experiment indicated that with ATP bound to the cytoplasmic domain, the conformational equilibrium of CorC was shifted more towards the inward-facing state of the transmembrane domain. In contrast, IGN95a did not induce such a shift. Our results provide a structural basis for the further design and optimization of chemical compounds targeting the regulatory ATP-binding site of CorC as well as mechanistic insights into how ATP and chemical compounds modulate the transport activity of CorC.

biophysics↗

bioRxiv2021

Genome-wide analysis of mobile element insertions in human genomes

Mobile element insertions (MEIs) are a major class of structural variants (SVs) and have been linked to many human genetic disorders, including hemophilia, neurofibromatosis, and various cancers. However, human MEI resources from large-scale genome sequencing are still lacking compared to those for SNPs and SVs. Here, we report a comprehensive map of 36,699 non-reference MEIs constructed from 5,675 genomes, comprising 2,998 Chinese samples ([~]26.2X, NyuWa) and 2,677 samples from the 1000 Genomes Project ([~]7.4X, 1KGP). We discovered that LINE-1 insertions were highly enriched at centromere regions, implying the role of chromosome context in retroelement insertion. After functional annotation, we estimated that MEIs are responsible for about 9.3% of all protein-truncating events per genome. Finally, we built a companion database named HMEID for public use. This resource represents the latest and largest genomewide study on MEIs and will have broad utility for exploration of human MEI findings.

genomics↗

bioRxiv2021

Metabolite discovery through global annotation of untargeted metabolomics data

Liquid chromatography-high resolution mass spectrometry (LC-MS)-based metabolomics aims to identify and quantitate all metabolites, but most LC-MS peaks remain unidentified. Here, we present a global network optimization approach, NetID, to annotate untargeted LC-MS metabolomics data. The approach aims to generate, for all experimentally observed ion peaks, annotations that match the measured masses, retention times, and (when available) MS/MS fragmentation patterns. Peaks are connected based on mass differences reflecting adducting, fragmentation, isotopes, or feasible biochemical transformations. Global optimization generates a single network linking most observed ion peaks, enhances peak assignment accuracy, and produces chemically-informative peak-peak relationships, including for peaks lacking MS/MS spectra. Applying this approach to yeast and mouse data, we identified five novel metabolites (thiamine derivatives and N-glucosyl-taurine). Isotope tracer studies indicate active flux through these metabolites. Thus, NetID applies existing metabolomic knowledge and global optimization to annotate untargeted metabolomics data, revealing novel metabolites.

bioinformatics↗

bioRxiv2020

Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage

Efficient peptide and protein identification from data-independent acquisition mass spectrometric (DIA-MS) data typically rely on an experiment-specific spectral library with a suitable size. Here, we report a computational strategy for optimizing the spectral library for a specific DIA dataset based on a comprehensive spectral library, which is accomplished by a priori analysis of the DIA dataset. This strategy achieved up to 44.7% increase in peptide identification and 38.1% increase in protein identification in the test dataset of six colorectal tumor samples compared with the comprehensive pan-human library strategy. We further applied this strategy to 389 carcinoma samples from 15 tumor datasets and observed up to 39.2% increase in peptide identification and 19.0% increase in protein identification. In summary, we present a computational strategy for spectral library size optimization to achieve deeper proteome coverage of DIA-MS data.

bioinformatics↗

bioRxiv2020

The global landscape of SARS-CoV-2 genomes, variants, and haplotypes in 2019nCoVR

On 22 January 2020, the National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), created the 2019 Novel Coronavirus Resource (2019nCoVR), an open-access SARS-CoV-2 information resource. 2019nCoVR features a comprehensive integration of sequence and clinical information for all publicly available SARS-CoV-2 isolates, which are manually curated with value-added annotations and quality evaluated by our in-house automated pipeline. Of particular note, 2019nCoVR performs systematic analyses to generate a dynamic landscape of SARS-CoV-2 genomic variations at a global scale. It provides all identified variants and detailed statistics for each virus isolate, and congregates the quality score, functional annotation, and population frequency for each variant. It also generates visualization of the spatiotemporal change for each variant and yields historical viral haplotype network maps for the course of the outbreak from all complete and high-quality genomes. Moreover, 2019nCoVR provides a full collection of SARS-CoV-2 relevant literature on COVID-19 (Coronavirus Disease 2019), including published papers from PubMed as well as preprints from services such as bioRxiv and medRxiv through Europe PMC. Furthermore, by linking with relevant databases in CNCB-NGDC, 2019nCoVR offers data submission services for raw sequence reads and assembled genomes, and data sharing with National Center for Biotechnology Information. Collectively, all SARS-CoV-2 genome sequences, variants, haplotypes and literature are updated daily to provide timely information, making 2019nCoVR a valuable resource for the global research community. 2019nCoVR is accessible at https://bigd.big.ac.cn/ncov/.

genomics↗

bioRxiv2020

Compositional Variability and Mutation Spectra of Monophyletic SARS-CoV-2 Clades

COVID-19 and its causative pathogen SARS-CoV-2 have rushed the world into a staggering pandemic in a few months and a global fight against both is still going on. Here, we describe an analysis procedure where genome composition and its variables are related, through the genetic code, to molecular mechanisms based on understanding of RNA replication and its feedback loop from mutation to viral proteome sequence fraternity including effective sites on replicase-transcriptase complex. Our analysis starts with primary sequence information and identity-based phylogeny based on 22,051 SARS-CoV-2 genome sequences and evaluation of sequence variation patterns as mutation spectrum and its 12 permutations among organized clades tailored to two key mechanisms: strand-biased and function-associated mutations. Our findings include: (1) The most dominant mutation is C-to-U permutation whose abundant second-codon-position counts alter amino acid composition toward higher molecular weight and lower hydrophobicity albeit assumed most slightly deleterious. (2) The second abundance group includes: three negative-strand mutations U-to-C, A-to-G, G-to-A and a positive-strand mutation G-to-U generated through an identical mechanism as C-to-U. (3) A clade-associated and biased mutation trend is found attributable to elevated level of the negative-sense strand synthesis. (4) Within-clade permutation variation is very informative for associating non-synonymous mutations and viral proteome changes. These findings demand a bioinformatics platform where emerging mutations are mapped on to mostly subtle but fast-adjusting viral proteomes and transcriptomes to provide biological and clinical information after logical convergence for effective pharmaceutical and diagnostic applications. Such thoughts and actions are in desperate need, especially in the middle of the War against COVID-19.

microbiology↗

bioRxiv2020

Phenotype Prediction using a Tensor Representation and Deep Learning from Data Independent Acquisition Mass Spectrometry

A novel approach for phenotype prediction is developed for mass spectrometric data. First, the data-independent acquisition (DIA) mass spectrometric data is converted into a novel file format called "DIA tensor" (DIAT) which contains all the peptide precursors and fragments information and can be used for convenient DIA visualization. The DIAT format is fed directly into a deep neural network to predict phenotypes without the need to identify peptides or proteins. We applied this strategy to a collection of 102 hepatocellular carcinoma samples and achieved an accuracy of 96.8% in classifying malignant from benign samples. We further applied refined model to 492 samples of thyroid nodules to predict thyroid cancer; and achieved a predictive accuracy of 91.7% in an independent cohort of 216 test samples. In conclusion, DIA tensor enables facile 2D visualization of DIA proteomics data as well as being a new approach for phenotype prediction directly from DIA-MS data.

bioinformatics↗

bioRxiv2019

Discovery and Multi-center Verification of Prostate Cancer Protein Biomarkers using Single-shot Short Gradient Microflow SWATH and MRMHR Mass Spectrometry

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.\n\nWe applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set. We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).\n\nOverall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method. Finally, the results showed comparable ability to separate clinical groups.

cancer biology↗

bioRxiv2019

High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification

Formalin-fixed, paraffin-embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here we developed a pressure cycling technology (PCT)-SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B-cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between one to 15 years in a biobank and show a high degree of the proteome pattern similarity between two types histological region of small FFPE samples, i.e. punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of certain degree of biological variations. Applying the method to two independent DLBCL cohorts we identified myeloperoxidase (MPO), a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

biochemistry↗

bioRxiv2019

Inhibition of Osteoblast Proliferation and Migration by Exogenous and Endogenous Formaldehyde

Exogenous and endogenous formaldehyde (FA) plays an important role in cell growth and migration; however, its potential role in osteoblasts remains largely unclear. Cell counting kit-8 (CCK-8) and wound healing assays revealed that FA exposure at naturally occurring concentrations inhibited the proliferation and migration of mouse preosteoblast MC3T3-E1 cells. Moreover, RNA sequencing (RNA-seq) analysis revealed that FoxO1 signaling pathway components displayed distinct expression patterns upon FA exposure, reflected through significant enrichment of cell migration. In particular, FoxO1 Sirt1 and FA-induced related protein expression which were closely with cell proliferation and migration were confirmed by western blotting. The present results indicate that the FoxO1 pathway is involved in FA-induced inhibition of cell growth and migration.

cell biology↗

bioRxiv2019

Theta and Gamma Bands Encode Acoustic Dynamics over Wide-ranging Timescales

Natural sounds have broadband modulation spectra and contain acoustic dynamics ranging from tens to hundreds of milliseconds. How does the human auditory system encode acoustic information over wide-ranging timescales to achieve sound recognition? Previous work (Teng et al., 2017) demonstrated a temporal coding preference in the auditory system for the theta (4 - 7 Hz) and gamma (30 - 45 Hz) ranges, but it remains unclear how acoustic dynamics between these two ranges is encoded. Here we generated artificial sounds with temporal structures over timescales from ~200 ms to ~30 ms and investigated temporal coding on different timescales in the human auditory cortex. Participants discriminated sounds with temporal structures at different timescales while undergoing magnetoencephalography (MEG) recording. The data show robust neural entrainment in the theta and the gamma bands, but not in the alpha and beta bands. Classification analyses as well as stimulus reconstruction reveal that the acoustic information of all timescales can be differentiated through the theta and gamma bands, but the acoustic dynamics in the theta and gamma ranges are preferentially encoded. We replicate earlier findings of multi-time scale processing and further demonstrate that the theta and gamma bands show generality of temporal coding across all timescales with comparable capacity. The results support the hypothesis that the human auditory cortex primarily encodes auditory information employing neural processes within two discrete temporal regimes. SignificanceNatural sounds contain rich acoustic dynamics over wide-ranging timescales, but perceptually relevant regularities often occupy specific temporal ranges. For instance, speech carries phonemic information on a shorter timescale than syllabic information at ~ 200 ms. How does the brain efficiently sample continuous acoustic input to perceive temporally structured sounds? We presented sounds with temporal structures at different timescales and measured cortical entrainment using magnetoencephalography. We found, unexpectedly, that the human auditory system preserves high temporal coding precision on two non-overlapping timescales, the slower (theta) and faster (gamma) bands, to track acoustic dynamics over all timescales. The results suggest that the acoustic environment which we experience as seamless and continuous is segregated by discontinuous neural processing, or sampled.

neuroscience↗

bioRxiv2018

Speech Fine Structure Contains Critical Temporal Cues to Support Speech Segmentation

Segmenting the continuous speech stream into units for further perceptual and linguistic analyses is fundamental to speech recognition. The speech amplitude envelope (SE) has long been considered a fundamental temporal cue for segmenting speech. Does the temporal fine structure (TFS), a significant part of speech signals often considered to contain primarily spectral information, contribute to speech segmentation? Using magnetoencephalography, we show that the TFS entrains cortical oscillatory responses between 3-6 Hz and demonstrate, using mutual information analysis, that (i) the temporal information in the TFS can be reconstructed from a measure of frame-to-frame spectral change and correlates with the SE and (ii) that spectral resolution is key to the extraction of such temporal information. Furthermore, we show behavioural evidence that, when the SE is temporally distorted, the TFS provides cues for speech segmentation and aids speech recognition significantly. Our findings show that it is insufficient to investigate solely the SE to understand temporal speech segmentation, as the SE and the TFS derived from a band-filtering method convey comparable, if not inseparable, temporal information. We argue for a more synthetic view of speech segmentation - the auditory system groups speech signals coherently in both temporal and spectral domains.

neuroscience↗