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Biology subjects

Ning, Z.

Publications and source records attributed to Ning, Z..

At least 55 records · Page 3Linked to original sources

Elevated colonic microbiota-associated paucimannosidic and truncated N-glycans in pediatric ulcerative colitis

Pediatric ulcerative colitis (UC) is a distinct type of inflammatory bowel disease with severe disease activity and rapid progression, which can lead to detrimental life-long consequences. The pathogenesis of pediatric UC remains unclear, although dysbiosis of the gut microbiota has been considered an important factor. In this study, we used mass spectrometry-based glycomic approaches to examine the N-glycans that were associated with the intestinal mucosal-luminal interface microbiota cells of treatment-naive pediatric UC or control patients. We observed abundant paucimannosidic and other truncated N-glycans that were associated with the microbiota and found that the pediatric UC microbiota samples contained significantly higher levels of these atypical N-glycans compared to those of controls. This study indicates that intestinal N-glycans may be used as novel UC biomarker candidates and the aberrant metabolism of glycans by gut microbiota may be involved in the pathogenesis of UC in children.

systems biology↗

Amino acids 484 and 494 of SARS-CoV-2 spike are hotspots of immune evasion affecting antibody but not ACE2 binding

Understanding SARS-CoV-2 evolution and host immunity is critical to control COVID-19 pandemics. At the core is an arms-race between SARS-CoV-2 antibody and angiotensin-converting enzyme 2 (ACE2) recognition, a function of the viral protein spike. Mutations in spike impacting antibody and/or ACE2 binding are appearing worldwide, with the effect of mutation synergy still incompletely understood. We engineered 25 spike-pseudotyped lentiviruses containing individual and combined mutations, and confirmed that E484K evades antibody neutralization elicited by infection or vaccination, a capacity augmented when complemented by K417N and N501Y mutations. In silico analysis provided an explanation for E484K immune evasion. E484 frequently engages in interactions with antibodies but not with ACE2. Importantly, we identified a novel amino acid of concern, S494, which shares a similar pattern. Using the already circulating mutation S494P, we found that it reduces antibody neutralization of convalescent and post-immunization sera, particularly when combined with E484K and N501Y. Our analysis of synergic mutations provides a landscape for hotspots for immune evasion and for targets for therapies, vaccines and diagnostics. One-Sentence SummaryAmino acids in SARS-CoV-2 spike protein implicated in immune evasion are biased for binding to neutralizing antibodies but dispensable for binding the host receptor angiotensin-converting enzyme

immunology↗

MetaProClust-MS1: A tool for clustering metaproteomes using rapid MS1 profiling

Metaproteomics is used to explore the composition, dynamics and function of microbial communities. How-ever, acquiring data by tandem mass spectrometry is time consuming and resource intensive. To mediate this challenge, we present MetaProClust-MS1, a computational framework for microbiome screening developed to reduce the time required for data acquisition by mass spectrometry. In this proof-of-concept study, we tested MetaProClust-MS1 on data acquired using short 15 minute MS1-only mass spectrometry gradients and compared the results to those produced using data acquired by a traditional tandem mass spectrometry approach. MetaProClust-MS1 identified robust microbiome shifts caused by xenobiotics in both datasets. Cluster topologies were also significantly correlated. We demonstrate that MetaProClust-MS1 is able to rapidly screen microbiomes using only short MS1 profiles. This approach can be used to prioritize samples for deep metaproteomic analysis and will be especially useful in large-scale metaproteomic screens or in clinical settings where rapid results are required.

bioinformatics↗

Brain transcriptional regulatory architecture and schizophrenia etiology converge between East Asian and European ancestral populations

Understanding the genetic architecture of gene expression and splicing in human brain is critical to unlocking the mechanisms of complex neuropsychiatric disorders like schizophrenia (SCZ). Large-scale brain transcriptomic studies are based primarily on populations of European (EUR) ancestry. The uniformity of mono-racial resources may limit important insights into the disease etiology. Here, we characterized brain transcriptional regulatory architecture of East Asians (EAS; n=151), identifying 3,278 expression quantitative trait loci (eQTL) and 4,726 spliceQTL (sQTL). Comparing these to PsychENCODE/BrainGVEX confirmed our hypothesis that the transcriptional regulatory architecture in EAS and EUR brains align. Furthermore, distinctive allelic frequency and linkage disequilibrium impede QTL translation and gene-expression prediction accuracy. Integration of eQTL/sQTL with genome-wide association studies reveals common and novel SCZ risk genes. Pathway-based analyses showing shared SCZ biology point to synaptic and GTPase dysfunction as a prospective pathogenesis. This study elucidates the transcriptional landscape of the EAS brain and emphasizes an essential convergence between EAS and EUR populations.

genetics↗

Exploring the microbiome-wide lysine acetylation, succinylation and propionylation in human gut microbiota

BackgroundLysine acylations are important post-translational modifications that are present in both eukaryotes and prokaryotes, regulating diverse cellular functions. Our knowledge of the microbiome lysine acylation remains limited due to the lack of efficient analytical and bioinformatics methods for complex microbial communities. ResultsWe show that serial enrichment using motif antibodies successfully captures peptides containing lysine acetylation, propionylation and succinylation from human gut microbiome samples. A new bioinformatic workflow consisting of unrestricted database search confidently identified >60,000 acetylated, and ~20,000 propionylated and succinylated gut microbial peptides. Characterization of these identified modification-specific metaproteomes, i.e. meta-PTMomes, demonstrates that lysine acylations are differentially distributed in microbial species with different metabolic capabilities. ConclusionThis study provides an analytical framework, consisting of a serial immunoaffinity enrichment and an open database search strategy, for the study of lysine acylations in microbiome, which enables functional microbiome studies at the post-translational level.

microbiology↗

Improved estimation of phenotypic correlations using summary association statistics

Estimating the phenotypic correlations between complex traits and diseases based on their genome-wide association summary statistics has been a useful technique in genetic epidemiology and statistical genetics inference. Two state-of-the-art strategies, Z-score correlation across null-effect SNPs and LD score regression intercept, were widely applied to estimate phenotypic correlations. Here, we propose an improved Z-score correlation strategy based on SNPs with low minor allele frequencies (MAFs), and show how this simple strategy can correct the bias generated by the current methods. Comparing to LDSC, the low-MAF estimator improves phenotypic correlation estimation thus is beneficial for methods and applications using phenotypic correlations inferred from summary association statistics.

genetics↗

An Antioxidant Enzyme Therapeutic for COVID-19

The COVID-19 pandemic has taken a significant toll on people worldwide, and there are currently no specific antivirus drugs or vaccines. We report herein a therapeutic based on catalase, an antioxidant enzyme that can effectively breakdown hydrogen peroxide and minimize the downstream reactive oxygen species, which are excessively produced resulting from the infection and inflammatory process. Catalase assists to regulate production of cytokines, protect oxidative injury, and repress replication of SARS-CoV-2, as demonstrated in human leukocytes and alveolar epithelial cells, and rhesus macaques, without noticeable toxicity. Such a therapeutic can be readily manufactured at low cost as a potential treatment for COVID-19.

biochemistry↗

MealTime-MS: A Machine Learning-Guided Real-Time Mass SpectrometryAnalysis for Protein Identification and Efficient DynamicExclusion

Mass spectrometry-based proteomics technologies are the prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to identify low abundance proteins in complex samples. Characterizing such proteins is essential to provide a comprehensive understanding of the biological processes taking place in cells and tissues. Still today, most mass spectrometry-based proteomics approaches use a data-dependent acquisition strategy, which favors the collection of mass spectra from proteins of higher abundance. Since the computational identification of proteins from proteomics data is typically performed after mass spectrometry analysis, large numbers of mass spectra are typically redundantly acquired from the same abundant proteins, and little to no mass spectra are acquired for proteins of lower abundance. We therefore propose a novel supervised learning algorithm that identifies proteins in real-time as mass spectrometry data are acquired and prevents further data collection from confidently identified proteins to ultimately free mass spectrometry resources to improve the identification sensitivity of low abundance proteins. We use real-time simulations of a previously performed mass spectrometry analysis of a HEK293 cell lysate to show that our approach can identify 92.1% of the proteins detected in the experiment using 66.2% of the MS2 spectra. We also demonstrate that our approach outperforms a previously proposed method, is sufficiently fast for real-time mass spectrometry analysis, and is flexible. Finally, MealTime-MS efficient usage of mass spectrometry resources will provide a more comprehensive characterization of proteomes in complex samples.

bioinformatics↗

Aerodynamic Characteristics and RNA Concentration of SARS-CoV-2 Aerosol in Wuhan Hospitals during COVID-19 Outbreak

BackgroundThe ongoing outbreak of COVID-19 has spread rapidly and sparked global concern. While the transmission of SARS-CoV-2 through human respiratory droplets and contact with infected persons is clear, the aerosol transmission of SARS-CoV-2 has been little studied. MethodsThirty-five aerosol samples of three different types (total suspended particle, size segregated and deposition aerosol) were collected in Patient Areas (PAA) and Medical Staff Areas (MSA) of Renmin Hospital of Wuhan University (Renmin) and Wuchang Fangcang Field Hospital (Fangcang), and Public Areas (PUA) in Wuhan, China during COVID-19 outbreak. A robust droplet digital polymerase chain reaction (ddPCR) method was employed to quantitate the viral SARS-CoV-2 RNA genome and determine aerosol RNA concentration. ResultsThe ICU, CCU and general patient rooms inside Renmin, patient hall inside Fangcang had undetectable or low airborne SARS-CoV-2 concentration but deposition samples inside ICU and air sample in Fangcang patient toilet tested positive. The airborne SARS-CoV-2 in Fangcang MSA had bimodal distribution with higher concentration than those in Renmin during the outbreak but turned negative after patients number reduced and rigorous sanitization implemented. PUA had undetectable airborne SARS-CoV-2 concentration but obviously increased with accumulating crowd flow. ConclusionsRoom ventilation, open space, proper use and disinfection of toilet can effectively limit aerosol transmission of SARS-CoV-2. Gathering of crowds with asymptomatic carriers is a potential source of airborne SARS-CoV-2. The virus aerosol deposition on protective apparel or floor surface and their subsequent resuspension is a potential transmission pathway and effective sanitization is critical in minimizing aerosol transmission of SARS-CoV-2.

microbiology↗

Studying the dynamics of the gut microbiota using metabolically stable isotopic labeling and metaproteomics.

BackgroundThe gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification and quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of gut microbiome functional dynamics. ResultsFrom the stool sample of five mice that were fed with 15N hydrolysate from Ralstonia eutropha, we identified 15,297 non-redundant unlabeled peptides of which 10,839 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs). ConclusionsOur study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome. AvailabilityMetaProfiler and the bioinformatic pipeline are available at https://github.com/psmyth94/MetaProfiler.git.

microbiology↗

Metaproteomic responses of in vitro gut microbiomes to resistant starches: the role of resistant starch type and inter-individual variations

Resistant starches (RS) are dietary compounds processed by the gut microbiota into metabolites, such as butyrate, that are beneficial to the host. The production of butyrate by the microbiome appears to be affected by the plant source and type of RS as well as the individuals microbiota. In this study, we used in vitro culture and metaproteomic methods to explore the consistency and variations in individual microbiomes functional responses to three types of RS - RS2(Hi Maize 260), RS3(Novelose 330) and RS4(Fibersym RW). Results showed that RS2 and RS3 significantly altered the levels of protein expression in the individual gut microbiomes, while RS4 did not result in significant protein changes. Significantly elevated protein groups were enriched in carbohydrate metabolism and transport functions of families Eubacteriaceae, Lachnospiraceae and Ruminococcaceae. In addition, Bifidobacteriaceae was significantly increased in response to RS3. We also observed taxon-specific enrichments of starch metabolism and pentose phosphate pathways corresponding to this family. Functions related to starch utilization, ABC transporters and pyruvate metabolism pathways were consistently increased in the individual microbiomes in response to RS2 and RS3; in contrast, the downstream butyrate producing pathway response varied. Our study confirm that different types of RS have markedly variable functional effects on the human gut microbiome, and also found considerable inter-individual differences in microbiome pathway responses.

microbiology↗

Growth phase-dependent responses of an in vitro gut microbiome to metformin

In vitro gut microbiota models are often used to study drug-microbiome interaction. Similar to culturing individual microbial strains, the biomass accumulation of in vitro gut microbiota follows a logistic growth curve. Current studies on in vitro gut microbiome responses introduce drug stimulation during different growth stages, e.g. lag phase or stationary phase. However, in vitro gut microbiota in different growth phases may respond differently to same stimuli. Therefore, in this study, we used a 96-deep well plate-based culturing model (MiPro) to culture the human gut microbiota. Metformin, as the stimulus, was added at the lag, log and stationary phases of growth. Microbiome samples were collected at different time points for optical density and metaproteomic functional analysis. Results show that in vitro gut microbiota responded differently to metformin added during different growth phases, in terms of the growth curve, alterations of taxonomic and functional compositions. The addition of drugs at log phase leads to the greatest decline of bacterial growth. Metaproteomic analysis suggested that the strength of the metformin effect on the gut microbiome functional profile was ranked as lag phase > log phase > stationary phase. Our results showed that metformin added at lag phase resulted in a significantly reduced abundance of the Clostridiales order as well as an increased abundance of the Bacteroides genus, which was different from stimulation during the rest of the growth phase. Metformin also resulted in alterations of several pathways, including energy production and conversion, lipid transport and metabolism, translation, ribosomal structure and biogenesis. Our results indicate that the timing for drug stimulation should be considered when studying drug-microbiome interactions in vitro.

microbiology↗

Colorectal cancer marker identification using the aging immune system-related blood cell DNA methylome

ObjectiveThere is a body of evidence that the aging immune system is linked to cancer. Here, we hypothesized that ubiquitination might play a key gatekeeper role in immune system aging and tumorigenesis in CRC. Therefore, we will systematically study the DNA methylation of ubiquitination genes and screen candidate CRC marker that are correlated with both aging and immune cell compositions. DesignThrough aging- and immune-related DNA methylation data, we investigated the DNA methylation regulation changes in promoters with other regions of genes during aging and their association with the immune cell proportion in the circulating whole blood of healthy individuals. Then, by collecting a cohort of 100 colon cancer patients and 50 healthy individuals, we used nucleic acid mass spectrometry to test whether ubiquitination genes can be used as candidate markers for the early screening of CRC. ResultsThe biological analyses for aging- and CD4 T cell proportion-derived differential genes showed that they are associated with ubiquitination. Among them, DZIP3 was significantly associated with both aging (P-value = 3.86E-06) and CD4 T cell proportion (P-value = 1.97E-05) in circulating blood. Then, we validated that the 1st exon DNA methylation of DZIP3 could predict the onset of early stage CRC (AUC = 0.833, OR = 8.82) and all pTNM stages of CRC (AUC = 0.782, OR = 5.70). ConclusionsThe epigenetically regulated ubiquitination plays an important role in immune aging and tumorigenesis. DNA methylation characteristic of DZIP3 can be used as a promising marker of CRC early screening. Summary boxO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIThe aging immune system is associated with cancer. C_LIO_LIUbiquitination plays potent roles in regulating a variety of signals in both innate and adaptive immune cells. C_LIO_LIThe abnormalities of ubiquitination are closely related to the occurrence of various tumors. C_LIO_LIBlood cell DNA methylome analysis provides a promising tool to probe the key components of immune cell dysregulation in aging and tumorigenesis. C_LI What are the new findings?O_LIThe aging- and immune cell proportion-derived differential genes are associated with ubiquitination. C_LIO_LIThe epigenetically regulated ubiquitination plays an important role in immune aging and tumorigenesis. C_LIO_LIDNA methylation characteristic of DZIP3, an E3 ubiquitin ligase with no reports on its function in immune cells and tumorigenesis, can be used as a promising markers of CRC early screening. C_LI How might it impact on clinical practice in the foreseeable future?O_LIThe in-depth study for DNA methylome of ubiquitination will open up a new path for the study of CRC pathogenesis, diagnosis and treatment. C_LIO_LIIn addition, DZIP3-focused screening technique only needs to extract the whole blood of individuals for MassARRAY analysis; the samples are easy to obtain, and the results are objective. Therefore, this method may have important applications in clinical CRC screening. C_LI

cancer biology↗

pepFunk, a tool for peptide-centric functional analysis in metaproteomic human gut microbiome studies

Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by matching the identified peptides back to parent proteins. However, the nature of enzymatic digestion produces peptides that can be found in multiple proteins due to conservation or chance, presenting difficulties with protein and functional assignment. To combat this challenge, we developed a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with KEGG terms and a pathway enrichment analysis adapted for peptide level data. Analysis using our peptide-centric workflow is fast and identifies more enriched KEGG pathways than protein-centric analysis. Our workflow is open source and available as a web application or source code to be run locally.

bioinformatics↗

A Chemoenzymatic Method for Glycoproteomic N-glycan Type Quantitation

Glycosylation is one of the most important post-translational modifications in biological systems. Current glycoproteome methods mainly focus on qualitative identification of glycosylation sites or intact glycopeptides. However, the systematic quantitation of glycoproteins has remained largely unexplored. Here, we developed a chemoenzymatic method to quantitatively investigate N-glycoproteome based on the N-glycan types. Taking advantage of the specificity of different endoglycosidases and isotope dimethyl labeling, six N-glycan types of structures linked on each glycopeptide, including high-mannose/hybrid, bi-antennary and tri-antennary with/without core fucose, were quantified. As a proof of principle, the glycoproteomic N-glycan type quantitative (glyco-TQ) method was first used to determine the N-glycan type composition of immunoglobulin G1 (IgG1) Fc fragment. Then we applied the method to analyze the glycan type profile of proteins in the breast cancer cell line MCF7, and quantitatively revealed the N-glycan type micro-heterogeneity at both the glycopeptide and glycoprotein levels. The novel quantitative strategy to evaluate the relative intensity of the six states of N-glycan type glycosylation on each site provides a new avenue to investigate function of glycoproteins in broad areas, such as cancer biomarker research, pharmaceuticals characterization and anti-glycan vaccine development.

systems biology↗

Deep characterization of the protein lysine acetylation in human gut microbiome and its alterations in patients with Crohn’s disease

Metagenomic and metaproteomic approaches have been used to study the composition and functions of the microbiota. However, no studies have examined post-translational modifications (PTM) on human microbiome proteins at the metaproteome level, and it remains unknown whether the microbial PTM is altered or not in patient microbiome. Herein we used anti-acetyl-lysine (Kac) antibody enrichment strategy and mass spectrometry to characterize the protein lysine acetylation in human microbiome, which successfully identified 35,200 Kac peptides corresponding to 31,821 Kac sites from the microbial or host proteins in human gut microbiome samples. The gut microbial proteins exhibited Kac motifs that were distinct from those of human proteins. Functional analysis showed that microbial Kac proteins were significantly enriched in energy production and abundant in enzymes related to transferases and oxidoreductases. Applying to the analysis of pediatric Crohns disease (CD) patient microbiome identified 52 host and 136 microbial protein Kac sites that were differentially abundant in CD versus controls. Interestingly, most of the decreased Kac sites in CD were derived from Firmicutes and most of the increased sites were derived from Bacteroidetes. Forty-six out of the 52 differentially abundant human protein Kac sites were increased in CD patients, including those on calprotectin, lactotransferrin and immunoglobulins. Taken together, this study provides an efficient approach to study the lysine acetylation in microbiome and revealed taxon-specific alterations in the lysine acetylome as well as changes in host protein acetylation levels in intestinal samples during the on-set of disease in CD patients.

systems biology↗

Microbiome-wide characterization of post-translational modifications

Studying the structure and function of microbiomes is an emerging research field. Metaproteomic approaches focusing on the characterization of expressed proteins and post-translational modifications (PTMs) provide a deeper understanding of microbial communities. Previous research has highlighted the value of examining microbiome-wide protein expression in studying the roles of the microbiome in human diseases. Nevertheless, the regulation of protein functions in complex microbiomes remains under-explored. This is mainly due to the lack of efficient bioinformatics tools to identify and quantify PTMs in the microbiome. We have developed a comprehensive software termed MetaLab for the data analysis of metaproteomic datasets. Here we build an open search workflow within MetaLab for unbiased identification and quantification of PTMs from microbiome samples. This bioinformatics platform provides information about proteins, PTMs, taxa, functions, and pathways of microbial communities. The performance of the workflow was evaluated using conventional proteomics, metaproteomics from mouse and human gut microbiomes, and modification-specific enriched datasets. Superior accuracy and sensitivity were obtained simultaneously by using our method comparing with the traditional closed search strategy.

bioinformatics↗

De novo assembly of a Tibetan genome and identification of novel structural variants associated with high altitude adaptation

Structural variants (SVs) may play important roles in human adaption to extreme environments such as high altitude but have been under-investigated. Here, combining long-read sequencing with multiple scaffolding techniques, we assembled a high-quality Tibetan genome (ZF1), with a contig N50 length of 24.57 mega-base pairs (Mb) and a scaffold N50 length of 58.80 Mb. The ZF1 assembly filled 80 remaining N-gaps (0.25 Mb in total length) in the reference human genome (GRCh38). Markedly, we detected 17,900 SVs, among which the ZF1-specific SVs are enriched in GTPase activity that is required for activation of the hypoxic pathway. Further population analysis uncovered a 163-bp intronic deletion in the MKL1 gene showing large divergence between highland Tibetans and lowland Han Chinese. This deletion is significantly associated with lower systolic pulmonary arterial pressure, one of the key adaptive physiological traits in Tibetans. Moreover, with the use of the high quality de novo assembly, we observed a much higher rate of genome-wide archaic hominid (Altai Neanderthal and Denisovan) shared non-reference sequences in ZF1 (1.32%-1.53%) compared to other East Asian genomes (0.70%-0.98%), reflecting a unique genomic composition of Tibetans. One such archaic-hominid shared sequence, a 662-bp intronic insertion in the SCUBE2 gene, is enriched and associated with better lung function (the FEV1/FVC ratio) in Tibetans. Collectively, we generated the first high-resolution Tibetan reference genome, and the identified SVs may serve as valuable resources for future evolutionary and medical studies.

genomics↗