Biology subjects

Zang, Y.

Publications and source records attributed to Zang, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics

Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the last decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.

bioinformatics↗

bioRxiv2024

CDHu40: a novel marker gene set of neuroendocrine prostate cancer (NEPC)

Prostate cancer (PCa) is the most prevalent cancer affecting American men. Castration-resistant prostate cancer (CRPC) can emerge during hormone therapy for PCa, manifesting with elevated serum prostate-specific antigen (PSA) levels, continued disease progression, and/or metastasis to the new sites, resulting in a poor prognosis. A subset of CRPC patients shows a neuroendocrine (NE) phenotype, signifying reduced or no reliance on androgen receptor (AR) signaling and a particularly unfavorable prognosis. In this study, we incorporated computational approaches based on both gene expression profiles and protein-protein interaction (PPI) networks. We identified 500 potential marker genes, which are significantly enriched in cell cycle and neuronal processes. The top 40 candidates, collectively named as CDHu40, demonstrated superior performance in distinguishing NE prostate cancer (NEPC) and non-NEPC samples based on gene expression profiles compared to other published marker sets. Notably, some novel marker genes in CDHu40, absent in the other marker sets, have been reported to be associated with NEPC in the literature, such as DDC, FOLH1, BEX1, MAST1, and CACNA1A. Importantly, elevated CDHu40 scores derived from our predictive model showed a robust correlation with unfavorable survival outcomes in patients, indicating the potential of the CDHu40 score as a promising indicator for predicting the survival prognosis of those patients with the NE phenotype. Motif enrichment analysis on the top candidates suggests that REST and E2F6 may serve as key regulators in the NEPC progression. Significanceour study integrates gene expression variances in multiple NEPC studies and protein-protein interaction network to pinpoint a specific set of NEPC maker genes namely CDHu40. These genes and scores based on their gene expression levels effectively distinguish NEPC samples and underscore the clinical prognostic significance and potential mechanism.

bioinformatics↗

bioRxiv2023

Characterization of proteoform post-translational modifications by top-down and bottom-up mass spectrometry in conjunction with UniProt annotations

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledgebases, such as UniProt, provide valuable information for PTM characterization and validation. Here, we present a software pipeline called PTM-TBA (PTM characterization by Top-down, Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as UniProt annotations. We identified 1,662 mass shifts from a top-down MS data set of SW480 cells, 545 (33%) of which were matched to 12 common PTMs, and 351 of which were localized. PTM-TBA validated 346 of the 1,662 mass shifts using UniProt annotations or a bottom-up MS data set of SW480 cells.

bioinformatics↗

bioRxiv2023

High-throughput screening of functional neo-antigens and their specific TCRs via the Jurkat reporter system combine with droplet microfluidics

T-cell receptor (TCR)-engineered T cells can precisely recognize a broad repertoire of targets derived from both intracellular and surface proteins of tumor cells. TCR-T adoptive cell therapy has shown safety and promising efficacy in solid tumor immunotherapy. However, antigen-specific functional TCR screening is time-consuming and expensive, which limits its application clinically. Here, we developed a novel integrated antigen-TCR screening platform based on droplet microfluidics technology, enabling high-throughput peptide-major histocompatibility complex (pMHC) library-to-TCR library screening with high sensitivity and low background signal. We introduced DNA barcoding technology to label peptide antigen candidate-loaded antigen-presenting cells (APCs) and Jurkat reporter cells to check the specificity of pMHC-TCR candidates. Coupled with the next-generation sequencing pipeline, interpretation of the DNA barcodes and the gene expression level of the Jurkat T-cell activation pathway provided a clear peptide-MHC-TCR recognition relationship. Our proof-of-principle study demonstrates that the platform could achieve unbiased pMHC-TCR library-on-library screening, which is expected to be used in the cross-reactivity and off-target testing of candidate pMHC-TCR libraries in clinical applications.

bioengineering↗

bioRxiv2022

Sodium channel slow inactivation normalizes firing in axons with uneven conductance distributions

The Na+ channels that are important for action potentials show rapid inactivation, a state in which they do not conduct, although the membrane potential remains depolarized1,2. Rapid inactivation is a determinant of millisecond scale phenomena, such as spike shape and refractory period. Na+ channels also inactivate orders of magnitude more slowly, and therefore have impacts on excitability over much longer time scales than those of a single spike or a single inter-spike interval3-9. Here, we focus on the contribution of slow inactivation to the resilience of axonal excitability10,11 when ion channels are unevenly distributed across the axonal membrane. We study models in which the voltage-gated Na+ and K+ channels are unevenly distributed along axons with different variances, capturing the heterogeneity that biological axons display12. In the absence of slow inactivation many conductance distributions result in spontaneous tonic activity. Faithful axonal propagation is achieved with the introduction of Na+ channel slow inactivation. This "normalization" effect depends on relations between the kinetics of slow inactivation and the firing frequency. Consequently, neurons with characteristically different firing frequencies will need to implement different sets of channel properties to achieve resilience. The results of this study demonstrate the importance of the intrinsic biophysical properties of ion channels in normalizing axonal function. HighlightsO_LIVariation in ion channel density in axons may compromise axonal spike propagation. C_LIO_LISlow inactivation of Na+ channels modulates their availability. C_LIO_LINa+ channel slow inactivation increases the reliability of spike propagation. C_LIO_LINormalization by slow inactivation can compensate for uneven channel distributions. C_LI

neuroscience↗

bioRxiv2022

A human DCC variant causing mirror movement disorder reveals an essential role for the Wave regulatory complex in Netrin/DCC signaling

The axon guidance cue, Netrin-1, signals through its receptor DCC to attract commissural axons to the midline. Pathogenic variants in DCC frequently lead to congenital mirror movements (CMM), but how these variants impact DCC function is largely unknown. Screening of DCC in individuals with CMM recently revealed a novel variant located in a conserved motif in the cytoplasmic tail of DCC that is predicted to bind to a central actin nucleation promoting factor, the WAVE regulatory complex (WRC). Here, we use biochemical and axon guidance assays to show that this CMM-associated DCC variant is pathogenic by disrupting the interaction between DCC and the WRC. This DCC-WRC interaction is evolutionarily conserved and is required for Netrin-1 mediated commissural axon outgrowth and guidance. Together, we identify the WRC as a pivotal component of Netrin-1/DCC signaling and further provide a molecular mechanism explaining how genetic variants in DCC may lead to CMM.

neuroscience↗

bioRxiv2022

Neuronal Morphology Enhances Robustness to Perturbations of Channel Densities

Biological neurons show significant cell-to-cell variability but have the striking ability to maintain their key firing properties in the face of unpredictable perturbations and stochastic noise. Using a population of multi-compartment models consisting of soma, neurites, and axon for the lateral pyloric (LP) neuron in the crab stomatogastric ganglion, we explored how rebound bursting is preserved when the 14 channel conductances in each model are all randomly varied. The soma-axon coupling is critical for the ability of the axon to spike during bursts and consequently determines the set of successful solutions. When the coupling deviates from a biologically realistic range, the neuronal tolerance of conductance variations is significantly lessened. Thus, the gross morphological features of these neurons enhance their robustness to perturbations of channel densities and expands the space of individual variability that can maintain a desired output pattern.

neuroscience↗

bioRxiv2022

TopFD - A Proteoform Feature Detection Tool for Top-Down Proteomics

Top-down liquid chromatography-mass spectrometry (LC-MS) analyzes intact proteoforms and generates mass spectra containing peaks of proteoforms with various isotopic compositions, charge states, and retention times. An essential step in top-down MS data analysis is proteoform feature detection, which aims to group these peaks into peak sets (features), each containing all peaks of a proteoform. Accurate protein feature detection enhances the accuracy in MS-based proteoform identification and quantification. Here we present TopFD, a software tool for top-down MS feature detection that integrates algorithms for proteoform feature detection, feature boundary refinement, and machine learning models for proteoform feature evaluation. We performed extensive benchmarking of TopFD, Promex, FlashDeconv, and Xtract using five top-down MS data sets and demonstrated that TopFD outperforms other tools in feature accuracy, reproducibility, and feature abundance reproducibility.

bioinformatics↗

bioRxiv2022

scFLUX: a web server for metabolic flux and variation prediction using transcriptomics data

Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, single cell fluxomics using laboratory approaches is currently infeasible, and none of the current flux estimation tools could achieve single cell resolution. In light of the natural associations between transcriptomic and metabolomic profiles, it remains both a feasible and urgent task to use the available single cell transcriptomics data for prediction of single cell fluxome. We present scFLUX here, which provides an online platform for prediction of metabolic fluxome and variations using transcriptomics data, on individual cell or sample level. This is in contrast to other flux estimation methods that are only able to model the fluxes for cells of pre-defined groups. The scFLUX webserver implements our in-house single cell flux estimation model, namely scFEA, which integrates a novel graph neural network architecture with a factor graph derived from the complex human metabolic network. To the best of our knowledge, scFLUX is the first and only web-based tool dedicated to predicting individual sample-/cell-metabolic fluxome and variations of metabolites using transcriptomics data. scFLUX is available at http://scflux.org/. The stand-alone tools for using scFLUX locally are available at https://github.com/changwn/scFEA.

bioinformatics↗

bioRxiv2022

Spatiotemporal landscape of SARS-CoV-2 pulmonary infection reveals Slamf9+Spp1+ macrophages promoting viral clearance and inflammation resolution

While SARS-CoV-2 pathogenesis has been intensively investigated, the host mechanisms of viral clearance and inflammation resolution are still elusive because of the ethical limitation of human studies based on COVID-19 convalescents. Here we infected Syrian hamsters by authentic SARS-CoV-2 and built an ideal model to simulate the natural recovery process of SARS-CoV-2 infection from severe pneumonia1,2. We developed and applied a spatial transcriptomic sequencing technique with subcellular resolution and tissue-scale extensibility, i.e., Stereo-seq3, together with single-cell RNA sequencing (scRNA-seq), to the entire lung lobes of 45 hamsters and obtained an elaborate map of the pulmonary spatiotemporal changes from acute infection, severe pneumonia to the late viral clearance and inflammation resolution. While SARS-CoV-2 infection caused massive damages to the hamster lungs, including naive T cell infection and deaths related to lymphopenia, we identified a group of monocyte-derived proliferating Slamf9+Spp1+ macrophages, which were SARS-CoV-2 infection-inducible and cell death-resistant, recruiting neutrophils to clear viruses together. After viral clearance, the Slamf9+Spp1+ macrophages differentiated into Trem2+ and Fbp1+ macrophages, both responsible for inflammation resolution and replenishment of alveolar macrophages. The existence of this specific macrophage subpopulation and its descendants were validated by RNAscope in hamsters, immunofluorescence in hACE2 mice, and public human autopsy scRNA-seq data of COVID-19 patients. The spatiotemporal landscape of SARS-CoV-2 infection in hamster lungs and the identification of Slamf9+Spp1+ macrophages that is pivotal to viral clearance and inflammation resolution are important to better understand the critical molecular and cellular players of COVID-19 host defense and also develop potential interventions of COVID-19 immunopathology.

immunology↗

bioRxiv2021

Host casein kinase 1-mediated phosphorylation modulates phase separation of a rhabdovirus phosphoprotein and virus infection

Liquid-liquid phase separation (LLPS) plays important roles in forming cellular membraneless organelles. However, how host factors regulate LLPS of viral proteins during negative-sense RNA (NSR) virus infections is largely unknown. Here, we used Barley yellow striate mosaic virus (BYSMV) as a model to demonstrate regulation of host casein kinase 1 in phase separation and infection of NSR viruses. We first found that the BYSMV phosphoprotein (P) formed spherical granules with liquid properties and recruited viral nucleotide (N) and polymerase (L) proteins in vivo. Moreover, the P-formed granules were tethered to the ER/actin network for trafficking and fusion. BYSMV P alone formed droplets and incorporated the N protein and genomic RNA in vitro. Interestingly, phase separation of BYSMV P was inhibited by host casein kinase 1 (CK1)-dependent phosphorylation of an intrinsically disordered P protein region. Genetic assays demonstrated that the unphosphorylated mutant of BYSMV P exhibited condensed phase, which promoted virus replication through concentrating the N, L proteins, and genome RNA into viroplasms. Whereas, the phosphorylation-mimic mutant existed in diffuse phase state leading to enhanced virus transcription. Collectively, our results demonstrate that host CK1 modulates phase separation of viral P protein and virus infection.

microbiology↗

bioRxiv2021

Evaluation of machine learning models for proteoform retention and migration time prediction in top-down mass spectrometry

Reversed-phase liquid chromatography (RPLC) and capillary zone electrophoresis (CZE) are two popular proteoform separation methods in mass spectrometry (MS)-based top-down proteomics. The prediction of proteoform retention time in RPLC and migration time in CZE provides additional information that can increase the accuracy of proteoform identification and quantification. Whereas existing methods for retention and migration time prediction are mainly focused on peptides in bottom-up MS, there is still a lack of methods for the problem in top-down MS. We systematically evaluated 6 models for proteoform retention and/or migration time prediction in top-down MS and showed that the Prosit model achieved a high accuracy (R2 > 0.91) for proteoform retention time prediction and that the Prosit model and a fully connected neural network model obtained a high accuracy (R2 > 0.94) for proteoform migration time prediction.

bioinformatics↗

bioRxiv2021

Novel pectin from crude polysaccharide of Syzygium aromaticum against SARS-CoV-2 activities by targeting 3CLpro

To date, COVID-19 is still a severe threat to public health, hence specific effective therapeutic drugs development against SARS-CoV-2 is urgent needed. 3CLpro and PLpro and RdRp are the enzymes required for the SARS-CoV-2 RNA synthesis. Therefore, binding to the enzyme may interfere the enzyme function. Before, we found that sulfated polysaccharide binding to 3CLpro might block the virus replication. Hence, we hypothesize that negative charged pectin glycan may also impede the virus replication. Here we show that 922 crude polysaccharide from Syzygium aromaticum may near completely block SARS-CoV-2 replication. The inhibition rate was 99.9% (EC50 : 0.90 M). Interestingly, 922 can associates with 3CLpro, PLpro and RdRp. We further show that the homogeneous glycan 922211 from 922 may specifically attenuate 3CL protease activity. The IC50s of 922 and 922211 against 3CLpro are 4.73 {+/-} 1.05 {micro}M and 0.18 {+/-} 0.01 {micro}M, respectively. Monosaccharide composition analysis reveals that 922211 with molecular weight of 78.7 kDa is composed of rhamnose, galacturonic acid, galactose and arabinose in the molar ratio of 8.21 : 37.81 : 3.58 : 4.49. The structure characterization demonstrated that 922211 is a homogalacturonan linked to RG-I pectin polysaccharide. The linear homogalacturonan part in the backbone may be partly methyl esterified while RG-I type part bearing 1, 4-linked -GalpA, 1, 4-linked -GalpAOMe and 1, 2, 4-linked -Rhap. There are four branches attached to C-1 or C4 position of Rhamnose glycosyl residues on the backbone. The branches are composed of 1, 3-linked {beta}-Galp, terminal (T)-linked {beta}-Galp, 1, 5-linked -Araf, T-linked -Araf, 4-linked -GalpA and/or 4-linked {beta}-GalpA. The above results suggest that 922 and 922211 might be a potential novel leading compound for anti-SARS-CoV-2 new drug development.

pharmacology and toxicology↗

bioRxiv2021

Interactions between Diameter, Myelination and the Na/K pump Affect Axonal Resilience to High Frequency Spiking

Axons reliably conduct action potentials between neurons and/or other targets. Axons have widely variable diameters and can be myelinated or unmyelinated. Although the effect of these factors on propagation speed is well studied, how they constrain axonal resilience to high frequency spiking is incompletely understood. Maximal firing frequencies range from ~ 1 Hz to > 300 Hz across neurons, but the process by which Na/K pumps counteract Na+ influx is slow, and it is unclear the extent to which slow Na+ removal is compatible with high frequency spiking. Modeling the process of Na+ removal shows that large diameter axons are more resilient to high frequency spikes than small diameter axons, because of their slow Na+ accumulation. In myelinated axons, the myelinated compartments between nodes of Ranvier act as a reservoir to slow Na+ accumulation and increase the reliability of axonal propagation. We now find that slowing the activation of K+ current can increase the Na+ influx rate, and the effect of minimizing the overlap between Na+- and K+-currents on spike propagation resilience depends on complex interactions among diameter, myelination and the Na/K pump density. Our results suggest that, in neurons with different channel gating kinetic parameters, different strategies may be required to improve the reliability of axonal propagation. Significance StatementThe reliability of spike propagation in axons is determined by complex interactions among ionic currents, ion pumps and morphological properties. We use compartment-based modeling to reveal that interactions of diameter, myelination and the Na/K pump determine the reliability of high frequency spike propagation. By acting as a reservoir of nodal Na+ influx, myelinated compartments efficiently increase propagation reliability. Although spike broadening was thought to oppose fast spiking, its effect on spike propagation is complicated, depending on the balance of Na+ channel inactivation gate recovery, Na+ influx and axial charge. Our findings suggest that slow Na+ removal influences axonal resilience to high frequency spike propagation, and that different strategies may be required to overcome this constraint in different neurons.

neuroscience↗

bioRxiv2021

Selective MAP1LC3C (LC3C) autophagy requires noncanonical initiation regulators and the paralog-specific C-terminal peptide

LC3s are canonical proteins necessary for the formation of autophagosomes. We have previously established that two paralogs, LC3B and LC3C, have opposite activities in renal cancer, with LC3B playing oncogenic role and LC3C tumor suppressing role. LC3C is an evolutionary late gene, present only in higher primates and humans. Its most distinct feature is a C-terminal 20 amino acid peptide cleaved in the process of glycine 126 lipidation. Here we investigated mechanisms of LC3C selective autophagy. LC3C autophagy requires noncanonical upstream regulatory complexes that include ULK3, UVRAG, RUBCN, PIK3C2A, and a member of ESCRT, TSG101. We established that Postdivision Midbody Rings (PDMBs) implicated in cancer stem cell regulation are direct targets of LC3C autophagy. LC3C C-terminal peptide is necessary and sufficient to mediate LC3C-dependent selective degradation of PDMBs. This work establishes a new noncanonical human-specific selective autophagic program relevant to cancer stem cells.

cancer biology↗

bioRxiv2020

A Large-Scale Structural and Functional Connectome of Social Mentalizing

Humans have a remarkable ability to infer the mind of others. This mentalizing skill relies on a distributed network of brain regions but how these regions connect and interact is not well understood. Here we leveraged large-scale multimodal neuroimaging data to elucidate the connectome-level organization and brain-wide mechanisms of mentalizing processing. Key features of the mentalizing connectome have been delineated in exquisite detail and its relationship with the default mode network has been extensively scrutinized. Our study demonstrates that mentalizing processing unfolds across functionally heterogeneous regions with highly structured fiber tracts and unique hierarchical functional architecture, which make it distinguishable from the default mode network and other social brain networks.

neuroscience↗

bioRxiv2020

SSMD: A semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data

Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different dataset scenarios. We developed a Semi-Supervised Mouse data Deconvolution (SSMD) method to study the mouse tissue microenvironment (TME). SSMD is featured by (i) a novel non-parametric method to discover data set specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (1) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment, (2) diverse experimental platforms of mouse transcriptomics data, (3) small sample size and limited training data source, and (4) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing to state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released via https://github.com/xiaoyulu95/SSMD. Key pointsO_LIWe provide a novel tissue deconvolution method, namely SSMD, which is specifically designed for mouse data to handle the variations caused by different mouse strain, genetic and phenotypic background, and experimental platforms. C_LIO_LISSMD is capable to detect data set and tissue microenvironment specific cell markers for more than 30 cell types in mouse blood, inflammatory tissue, cancer, and central nervous system. C_LIO_LISSMD achieve much improved performance in estimating relative proportion of the cell types compared with state-of-the-art methods. C_LIO_LIThe semi-supervised setting enables the application of SSMD on transcriptomics, DNA methylation and ATAC-seq data. C_LIO_LIA user friendly R package and a R shiny of SSMD based webserver are also developed. C_LI

bioinformatics↗

bioRxiv2020

Phosphoproteomics Reveals AMPK Substrate Network in Response to DNA Damage and Histone Acetylation

AMPK is a conservative energy sensor that plays roles in diverse biologic processes via direct phosphorylation on various substrates. Emerging studies have demonstrated the regulatory roles of AMPK in DNA repair, but the underlying mechanisms remain to be fully understood. Herein, using mass spectrometry-based proteomic technologies, we systematically investigate the regulatory network of AMPK in DNA damage response. Our system-wide phosphoproteome study uncovers a variety of newly-identified potential substrates involved in diverse biologic processes, whereas our system-wide histone modification analysis reveals a linkage between AMPK and histone acetylation. Together with these findings, we discover that AMPK promotes apoptosis by phosphorylating ASPP2 in irradiation-dependent way and regulates histone acetylation by phosphorylating HDAC9 in irradiation-independent way. Besides, we reveal that disturbing the histone acetylation by the bromodomain BRD4 inhibitor JQ-1 enhanced the sensitivity of AMPK-deficient cells to irradiation. Therefore, our studies provided a source to study the phosphorylation and histone acetylation underlying the regulatory network of AMPK, which could be beneficial to understand the exact role of AMPK in DNA damage response.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cell biology↗