Biology subjects

Wu, P.

Publications and source records attributed to Wu, P..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Comparison of long read methods for sequencing and assembly of a plant genome

Sequencing technologies have advanced to the point where it is possible to generate high accuracy, haplotype resolved, chromosome scale assemblies. Several long read sequencing technologies are available on the market and a growing number of algorithms have been developed over the last years to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology as well as the most appropriate software for assembly and polishing. For this reason, it is important to benchmark different approaches applied to the same sample. Here, we report a comparison of three long read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION) and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of PacBio and Nanopore reads. Results obtained from combining long read technologies or short read and long read technologies are also presented. The assemblies were compared for contiguity, accuracy and completeness as well as sequencing costs and DNA material requirements. Overall, the three long read technologies produced highly contiguous and complete genome assemblies of Macadamia jansenii. At the time of sequencing, the cost associated with each method was significantly different but continuous improvements in technologies have resulted in greater accuracy, increased throughput and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies.

genomics↗

bioRxiv2019

The Calcineurin-TFEB-p62 Pathway Mediates the Activation of Cardiac Macroautophagy by Proteasomal Malfunction

RationaleThe ubiquitin-proteasome system (UPS) and the autophagic-lysosomal pathway (ALP) are pivotal to proteostasis. Targeting these pathways is emerging as an attractive strategy for treating cancer. However, a significant proportion of patients who receive a proteasome inhibitor-containing regime for example, show cardiotoxicity. Moreover, UPS and ALP defects are implicated in the pathogenesis of a large subset of heart disease. Hence, a better understanding of the cross-talk between the two catabolic pathways should help advance cardiac pathophysiology and medicine. ObjectiveSystemic pharmacological proteasome inhibition (PSMI) was shown to increase p62/SQSTM1 expression and induce myocardial macroautophagy. The present study investigates whether cardiomyocyte-restricted PSMI activates myocardial ALP and, more importantly, how proteasome malfunction activates the ALP in the heart. Methods and ResultsMyocardial macroautophagy, transcription factor EB (TFEB) expression and activity, and p62 expression were markedly increased in mice with either cardiomyocyte-restricted ablation of Psmc1 (a 19S proteasome subunit gene) or pharmacological PSMI. In cultured cardiomyocytes, PSMI-induced increases in TFEB activation and p62 expression were blunted markedly by calcineurin inhibition (cyclosporine A) and by siRNA-mediated Molcn1 silence. PSMI induced remarkable increases in myocardial autophagic flux in wild type mice but not p62 null mice. In cultured wild type, but not p62-null, mouse cardiomyocytes, PSMI induced increases in LC3-II flux and in the lysosomal removal of ubiquitinated proteins. Myocardial TFEB activation by PSMI as reflected by TFEB nuclear localization and target gene expression was strikingly less in p62 null mice compared with wild type mice. Conclusions(1) The activation of cardiac macroautophagy by proteasomal malfunction is mediated by the Mocln1-calcineurin-TFEB-p62 pathway; (2) both Mocln1 and p62 form a feed-forward loop with TFEB during TFEB activation by proteasome malfunction; and (3) targeting the Mcoln1-calcineurin-TFEB-p62 pathway may provide new means to intervene cardiac ALP activation in a proteasome malfunction setting.

cell biology↗

bioRxiv2019

The COP9 Signalosome Suppresses Cardiomyocyte Necroptosis

BackgroundLoss of cardiomyocyte (CMs) due to apoptosis and regulated necrosis contributes to heart failure. However, the molecular mechanisms governing regulated CM necrosis remain obscure. The COP9 signalosome (CSN) formed by 8 unique protein subunits (COPS1 through COPS8) functions to deneddylate Cullin-RING ligases (CRLs), thereby regulating the functioning of the CRLs. Mice with CM-restricted knockout of Cops8 (Cops8-cko) die prematurely, following reduced myocardial performance of autophagy and the ubiquitin-proteasome system (UPS) as well as massive CM necrosis. This study was aimed to determine the nature and underlying mechanisms of the CM necrosis in Cops8-cko mice. MethodsWe examined myocardial expression and activities of key proteins that reflect the status of the RIPK1-RIPK3 pathway, redox, and caspase 8 in Cops8-cko mice. Moreover, we used in vivo CM uptake of Evans blue dye (EBD) as an indicator of necrosis and performed Kaplan-Meier survival analyses to test whether treatment with a RIPK1 kinase inhibitor (necrostatin-1) or an antioxidant (N-acetyl-L-cysteine), global knockout of the RIPK3 or the Ppif gene, CM-restricted knockout of the Nrf2 gene, or cardiac HMOX1 overexpression could rescue the Cops8-cko phenotype. ResultsCompared with littermate control mice, myocardial protein levels of RIPK1, RIPK3, MLKL, the RIPK1-bound RIPK3, protein carbonyls, full-length caspase 8, Nrf2, Ser40-phosphorylated Nrf2 and BCL2, as well as histochemical staining of superoxide anions were significantly increased but the cleaved caspase 8 and the overall caspase 8 activity were markedly decreased in Cops8-cko mice, indicating that the RIPK1-RIPK3 and the Nrf2 pathways are activated and caspase 8 activation is suppressed by Cops8-cko. Continuous necrostatin-1 infusion initiated at 2 weeks of age nearly completely blocked CM necrosis at 3 weeks and markedly delayed premature death of Cops8-cko mice. RIPK3 haploinsufficiency or cardiac-specific Nrf2 heterozygous knockout discernably attenuated CM necrosis and/or delayed mouse premature death; conversely, Ppif knockout, N-acetyl-L-cysteine treatment, and cardiac overexpression of HMOX1 exacerbated CM necrosis and mouse premature death. ConclusionsCardiac Cops8/CSN malfunction causes RIPK1-RIPK3 mediated CM necroptosis in mice; sustained Nrf2 activation and reductive stress pivot cardiomyocytes to necroptosis when autophagy and the UPS are impaired; and the CSN plays an indispensable role in suppressing CM necroptosis.

cell biology↗

bioRxiv2019

hFUT1-based live cell assay to profile α1-2-fucosides enhanced influenza A virus infection

Host cell-surface glycans play critical roles in influenza A virus (IAV) infection ranging from modulation of IAV attachment to membrane fusion and host tropism. Approaches for quick and sensitive profiling of the viral avidity towards a specific type of host-cell glycan can contribute to the understanding of tropism switching among different strains of IAV. In this study, we developed a method based on chemoenzymatic glycan engineering to investigate the possible involvement of 1-2-fucosides in IAV infections. Using a truncated human fucosyltransferase 1 (hFuT1), we were able to create 1-2-linked fucosides in situ on the host cell surface to assess their influence on the host cell binding to IAV hemagglutinin and the susceptibility of host cells toward IAV induced killing. We discovered that the newly added 1-2-fucosides on host cells enhanced the infection of several human pandemic IVA subtypes. These findings suggest that glycan epitopes other than sialic aicds should be taken into consideration for assessing the human pandemic risk of this viral pathogen.

biochemistry↗

bioRxiv2019

Single-cell transcriptome profiling reveals neutrophil heterogeneity and orchestrated maturation during homeostasis and bacterial infection

The full neutrophil heterogeneity and differentiation landscape remains incompletely characterized. Here we profiled >25,000 differentiating and mature mouse neutrophils using single-cell RNA sequencing to provide a comprehensive transcriptional landscape of neutrophil maturation, function, and fate decision in their steady state and during bacterial infection. Eight neutrophil populations were defined by distinct molecular signatures. The three mature peripheral blood neutrophil subsets arise from distinct maturing bone marrow neutrophil subsets. Driven by both known and uncharacterized transcription factors, neutrophils gradually acquire microbicidal capability as they traverse the transcriptional landscape, representing an evolved mechanism for fine-tuned regulation of an effective but balanced neutrophil response. Bacterial infection reprograms the genetic architecture of neutrophil populations, alters dynamic transition between each subpopulation, and primes neutrophils for augmented functionality without affecting overall heterogeneity. In summary, these data establish a reference model and general framework for studying neutrophil-related disease mechanisms, biomarkers, and therapeutic targets at single-cell resolution.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/792200v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@18fed35org.highwire.dtl.DTLVardef@1e68b7org.highwire.dtl.DTLVardef@6cfbc8org.highwire.dtl.DTLVardef@1061a26_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA comprehensive single-cell resolution transcriptional landscape of mouse neutrophil maturation and fate decision under steady-state and bacterial infection conditions.\nC_LIO_LIThe pathogen clearance machinery in neutrophils is continuously and gradually built during neutrophil differentiation, maturation, and aging, driven by both known and uncharacterized transcription factors.\nC_LIO_LIThe three mature neutrophil subsets in peripheral blood, including a novel ISG-expressing subset, are derived from distinct bone marrow neutrophil precursors.\nC_LIO_LIBacterial infection reprograms the genetic architecture of neutrophil populations, alters dynamic transition between each subpopulation, and primes neutrophils for augmented functionality without affecting overall neutrophil heterogeneity.\nC_LIO_LIBacterial infection-induced emergency granulopoiesis is mediated by augmented proliferation of early stage neutrophil progenitors and accelerated post-mitotic maturation.\nC_LI

immunology↗

bioRxiv2019

A systematic survey of PRMT interactomes reveals the key roles of arginine methylation in the global control of RNA splicing and translation

Thousands of proteins undergo arginine methylation, a widespread post-translational modification catalyzed by various protein arginine methyltransferases (PRMTs). However, a full picture of the catalytic network for each PRMT is lacking and the global understanding of their biological roles remains limited. Here we systematically identified interacting proteins for all human PRMTs and demonstrated that they are functionally important for mRNA splicing and translation. We showed that the interactomes of human PRMTs are significantly overlapped with the known methylarginine containing proteins, and different PRMTs are functionally complementary with a high degree of overlap in their substrates and high similarities between their putative methylation motifs. Importantly, arginine methylation is significantly enriched in RNA binding proteins involved in regulating RNA splicing and translation, and inhibition of PRMTs leads to global alteration of alternative splicing and suppression of translation. In particular, ribosomal proteins are pervasively modified with methylarginine, and mutations on their methylation sites suppress ribosome assembly, translation, and eventually cell growth. Collectively, our study provides a novel global view of different PRMT networks and uncovers critical functions of arginine methylation in the regulation of mRNA splicing and translation.

molecular biology↗

bioRxiv2019

In situ Fucosylation for Modulating Wnt Signaling in Live Cells

Wnt/{beta}-catenin signaling, also known as canonical Wnt signaling, regulates critical, context-dependent transcription in numerous (patho) physiological events. Amongst the well-documented mechanisms of canonical Wnt signaling, modification of N-glycans by L-fucose (Fuc) is the newest and the least understood. Using a combination of Chinese Hamster Ovary (CHO) cell mutants with different fucosylation levels and in situ cell-surface Fuc editing (ISF), we report that (1-3)-fucosylation of N-acetylglucosamine in the LacNAc (Gal{beta}(1-4)-GlcNAc) sequences of complex N-glycans modulates Wnt signaling by regulating the endocytosis of low density lipoprotein receptor-related protein 6 (LRP6). Pulse-chase experiments reveal that increasing N-glycan LacNAc fucosylation elevates endocytosis of lipid-raft-localized LRP6, leading to the suppression of Wnt-{beta}-catenin signaling. Inhibiting endocytosis by inhibiting dynamin 1, a GTPase responsible for endocytosis in eukaryotic cells, partially rescues Wnt signaling. Remarkably, inhibition of Wnt signaling by N-glycan LacNAc fucosylation is fully rescued by the addition of free Fuc to the medium, suggesting that endocytosis of N-glycan fucosylated LRP6 may be mediated by a receptor that recognizes the bound (1-3)-Fuc. This work provides the first evidence that in situ cell-surface fucosylation can be exploited to regulate a specific signaling pathway via endocytosis, revealing a novel regulatory mechanism linking glycosylation of a cell surface receptor with its intracellular signaling.

biochemistry↗

bioRxiv2019

WikiMedMap: Expanding the Phenotyping Mapping Toolbox Using Wikipedia

Researchers utilizing phenotypic data from diverse sources require matching of phenotypes to standard clinical vocabularies. Mapping phenotypes to vocabulary can be difficult, as existing tools are often incomplete, can be difficult to access, and can be cumbersome to use, especially for non-experts. We created WikiMedMap as a simple tool that leverages Wikipedia and maps phenotype strings to standard clinical vocabularies. We assessed WikiMedMap by mapping phenotype strings from questionnaires in the UK Biobank and from Mendelian diseases in Online Mendelian Inheritance in Man (OMIM) database to eight vocabularies: International Classification of Diseases, Ninth Revision (ICD-9), ICD-10, ICD-O, Medical Subject Headings (MeSH), OMIM, Disease Database, and MedlinePlus. WikiMedMap outperformed conventional mapping tools in finding potential matches for phenotype strings. We envision WikiMedMap as a technique that complements existing and established tools to map strings to clinical vocabularies that usually do not coexist in one source.

bioinformatics↗

bioRxiv2019

Impact of rare and common genetic variants on diabetes diagnosis by hemoglobin A1c in multi-ancestry cohorts: The Trans-Omics for Precision Medicine Program.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in patients with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K/FN3KRP in Europeans and G6PD in African-Americans and Hispanics) and discovered a new African-ancestry specific low-frequency variant (rs1039215 in HBG2/HBE1, minor allele frequency (MAF)=0.03). The most associated G6PD variant (p.Val98Met, rs1050828-T, MAF=12% in African-Americans, MAF=2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693 - p.Leu353Pro, MAF=0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African-American cohorts and replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

genetics↗

bioRxiv2019

Direct Visualization of Live Zebrafish Glycan via Single-step Metabolic Labeling with Fluorophore-tagged Nucleotide Sugars

Dynamic turnover of cell-surface glycans is involved in a myriad of biological events, making this process an attractive target for in vivo molecular imaging. The metabolic glycan labeling coupled with bioorthogonal chemistry has paved the way for visulizing glycans in living organisms. However, a two-step labeling sequence is required, which is prone to tissue penetration difficulties of the imaging probes. Here, by exploring the substrate promiscuity of endogenous glycosyltransferases, we developed a single-step fluorescent glycan labeling strategy by using fluorophore-tagged analogs of nucleotide sugars directly. Injecting the fluorophore-tagged sialic acid and fucose into the yolk of zebrafish embryos at the one-cell stage enables a systematic imaging of sialylation and fucosylation in live zebrafish embryos at various developmental stages. From these studies, we obtained insights into the role of sialylated and fucosylated glycans in zebrafish hematopoiesis.

biochemistry↗

bioRxiv2019

Dean flow assisted single cell and bead encapsulation for high performance single cell expression profiling

Single-cell RNA sequencing examines the transcriptome of individual cells and reveals the inter-cell transcription heterogeneity, playing a critical role in both scientific research and clinical applications. Recently, droplet microfluidics-based platform for expression profiling has been shown as a powerful tool to capture of the transcriptional information on single cell level. Despite the breakthrough this platform brought about, it required the simultaneous encapsulation of single cell and single barcoded bead, the incidence of which was very low. Suboptimal capturing efficiency limited the throughput of the Drop-seq platform. In this work, we leveraged the advance in inertial microfluidics-based cell sorting and designed a microfluidic chip for high efficiency cell-bead co-encapsulation, increasing the capturing rate by more than four folds. Specifically, we adopted spiral and serpentine channels and ordered cells/beads before the encapsulation region. We characterized the effect of cell concentration on the capturing rate and achieved a cell-bead co-capturing rate up to 3%. We tested this platform by co-encapsulating barcoded beads and human-mouse cell mixtures. The sequencing data distinguished the majority of human and mice expressions, with the doublet rate being as low as 5.8%, indicating that the simultaneous capturing of two or more cells in one droplet was minimal even when using high cell concentration. This chip design showed great potential in improving the efficiency for future single cell expression profiling.

bioengineering↗

bioRxiv2019

Multiple splitting of droplets using multi-furcating microfluidic channels

Removing volumes from droplets is a challenging but critical step in many droplet-based applications. Geometry-mediated droplet splitting has the potential to reliably divide droplets and thus facilitate the implementation of this step. In this paper, we report the design of multi-furcating microfluidic channels for efficient droplet splitting. We studied the splitting regimes as the size of the mother droplets varied and investigated the effect of channel lengths. We further examined the droplet breakup mechanisms. This study could potentially be applied in washing steps in droplet-based biological assays or assays that require aliquot.

biophysics↗

bioRxiv2018

Developing and Evaluating Mappings of ICD-10 and ICD-10-CM codes to Phecodes

BackgroundThe PheCode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) in the electronic health record (EHR).\n\nObjectiveHere, we present our work on the development and evaluation of maps from ICD-10 and ICD-10-CM codes to PheCodes.\n\nMethodsWe mapped ICD-10 and ICD-10-CM codes to PheCodes using a number of methods and resources, such as concept relationships and explicit mappings from the Unified Medical Language System (UMLS), Observational Health Data Sciences and Informatics (OHDSI), Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT), and National Library of Medicine (NLM). We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM[->]PheCode map by investigating phenotype reproducibility and conducting a PheWAS.\n\nResultsWe mapped >75% of ICD-10-CM and ICD-10 codes to PheCodes. Of the unique codes observed in the VUMC (ICD-10-CM) and UKBB (ICD-10) cohorts, >90% were mapped to PheCodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease. A PheWAS with a lipoprotein(a) (LPA) genetic variant, rs10455872, using the ICD-9-CM and ICD-10-CM maps replicated two genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P < .001, OR = 1.60 vs. ICD-10-CM: P < .001, OR = 1.60) and with chronic ischemic heart disease (ICD-9-CM: P < .001, OR = 1.5 vs. ICD-10-CM: P < .001, OR = 1.47).\n\nConclusionsThis study introduces the initial \"beta\" versions of ICD-10 and ICD-10-CM to PheCode maps that will enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for high-throughput PheWAS in the EHR.

bioinformatics↗

bioRxiv2018

CSTDB: A Crop Stress-tolerance Gene and Protein Database Integrated by Convolutional Neural Networks

Numerous studies have shown that many genes and proteins in plants are involved in the regulation of plant resistance to abiotic and biotic stresses. The researches on the stress tolerance of crops are also the focus of many researchers. To provides a reliable platform for collecting and retrieving genetic and protein information related to stress tolerance found in crops, we constructed CSTDB(Crops Stress-tolerance Database), an integrated database that includes stress-tolerance genes and proteins for many crop species. The database was developed based on convolutional neural network technology. It is a web-accessible database that contains detailed information on the stress-tolerance genes and proteins of major crop species. Currently, the database records four major crops containing 1,371 abiotic stress-tolerance genes or proteins, and 207 genes or proteins associated with biotic stress. Each gene and protein has detailed functional information and sequence information, such as stress types, Genbank ID, Pubmed ID, Protein ID, 3D model picture and FASTA files. As a user-friendly browsing tool, this database provides search functions, BALST functions and file download functions. CSTDB can be a valuable resource, which is designed to meet the broad needs of researchers working on crops stress-tolerance experiments. Database URL: http://pcsb.ahau.edu.cn:8080/CSTDB

bioinformatics↗

bioRxiv2018

Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction

BackgroundCurrent approaches to predicting Cardiovascular disease rely on conventional risk factors and cross-sectional data. In this study, we asked whether: i) machine learning and deep learning models with longitudinal EHR information can improve the prediction of 10-year CVD risk, and ii) incorporating genetic data can add values to predictability.\n\nMethodsWe conducted two experiments. In the first experiment, we modeled longitudinal EHR data with aggregated features and temporal features. We applied logistic regression (LR), random forests (RF) and gradient boosting trees (GBT) and Convolutional Neural Networks (CNN) and Recurrent Neural Networks, using Long Short-Term Memory (LSTM) units. In the second experiment, we proposed a late-fusion framework to incorporate genetic features.\n\nResultsOur study cohort included 109, 490 individuals (9,824 were cases and 99, 666 were controls) from Vanderbilt University Medical Centers (VUMC) de-identified EHRs. American College of Cardiology and the American Heart Association (ACC/AHA) Pooled Cohort Risk Equations had areas under receiver operating characteristic curves (AUROC) of 0.732 and areas under receiver under precision and recall curves (AUPRC) of 0.187. LSTM, CNN and GBT with temporal features achieved best results, which had AUROC of 0.789, 0.790, and 0.791, and AUPRC of 0.282, 0.280 and 0.285, respectively. The late fusion approach achieved a significant improvement for the prediction performance.\n\nConclusionsMachine learning and deep learning with longitudinal features improved the 10-year CVD risk prediction. Incorporating genetic features further enhanced 10-year CVD prediction performance, underscoring the importance of integrating relevant genetic data whenever available in the context of routine care.

epidemiology↗

bioRxiv2018

Using Topic Modeling via Non-negative Matrix Factorization to Identify Relationships between Genetic Variants and Disease Phenotypes: A Case Study of Lipoprotein(a) (LPA)

Genome-wide and phenome-wide association studies are commonly used to identify important relationships between genetic variants and phenotypes. Most of these studies have treated diseases as independent variables and suffered from heavy multiple adjustment burdens due to the large number of genetic variants and disease phenotypes. In this study, we propose using topic modeling via non-negative matrix factorization (NMF) for identifying associations between disease phenotypes and genetic variants. Topic modeling is an unsupervised machine learning approach that can be used to learn the semantic patterns from electronic health record data. We chose rs10455872 in LPA as the predictor since it has been shown to be associated with increased risk of hyperlipidemia and cardiovascular diseases (CVD). Using data of 12,759 individuals from the biobank at Vanderbilt University Medical Center, we trained a topic model using NMF from 1,853 distinct phecodes extracted from the cohorts electronic health records and generated six topics. We quantified their associations with rs10455872 in LPA. Topics indicating CVD had positive correlations with rs10455872 (P < 0.001), replicating a previous finding. We also identified a negative correlation between LPA and a topic representing lung cancer (P < 0.001). Our results demonstrate the applicability of topic modeling in exploring the relationship between the genome and clinical diseases.\n\nAuthor summaryIdentifying the clinical associations of genetic variants remains crucial in understanding how the human genome modulates disease risk. Traditional phenome-wide association studies consider each disease phenotype as an independent variable, however, diseases often present as complex clusters of comorbid conditions. In this study, we propose using topic modeling to model electronic health record data as a mixture of topics (e.g., disease clusters or relevant comorbidities) and testing associations between topics and genetic variants. Our results demonstrated the feasibility of using topic modeling to replicate and discover novel associations between the human genome and clinical diseases.

genetics↗

bioRxiv2018

Bacterial Glycosyltransferase-mediated Cell-surface Chemoenzymatic Glycan Editing: Methods and Applications

AbstractChemoenzymatic glycan editing that modifies glycan structures directly on the cell surface has emerged as a complementary tool to metabolic oligosaccharide engineering. In this article, we report the discovery that three bacterial enzymes--Pasteurella multocida 2-3-sialyltransferase M144D mutant (Pm2,3ST-M144D), Photobacterium damsel 2-6-sialyltransferase (Pd2,6ST) and Helicobacter mustelae 1-2-fucosyltransferase (Hm1,2FT)--can serve as highly efficient tools for cell-surface glycan editing. Among these three enzymes, the two sialyltransferases were also found to be tolerant to large substituents introduced to the C-5 position of the cytidine monophosphate N-acetylneuraminic acid donor, including biotin and fluorescent dyes. Combining these enzymes with our previously discovered Helicobacter pylori 1-3-FT, we developed a live cell-based assay to probe host-cell glycan-mediated influenza A virus (IAV) infection including both wild-type and mutant strains of human H1N1 and H3N2 influenza subtypes. At high SiaNAc2-6-Gal levels, the ability of a viral strain to induce the host cell death is positively correlated with the SiaNAc2-6-Gal binding affinity of its haemagglutinin. Surprisingly, the creation of sLeX on the host cell surface via in situ 1-3-Fuc editing also exacerbated the killing induced by several wild-type IAV strains as well as a mutant known as HK68-MTA. Structural alignment of HAs from the wild-type HK68 and HK68-MTA revealed the formation of a putative hydrogen bond between Trp222 of HA-HK68-MTA and the C-4 hydroxyl group of the 1-3-linked fucose of sLeX. This interaction is likely to be responsible for the better binding affinity of HA-HK68-MTA to sLeX and accordingly the enhanced host-cell killing compared with the wild-type HK68.

biochemistry↗

bioRxiv2018

The Biological Evaluation of Fusidic Acid and Its Hydrogenation Derivative as Antimicrobial and Anti-inflammatory Agents

Fusidic acid (WU-FA-00) is the only commercially available antimicrobial from the fusidane family that has a narrow spectrum of activity against Gram-positive bacteria. Herein, the hydrogenation derivative (WU-FA-01) of fusidic acid was prepared, and both compounds were examined against a panel of six bacterial strains. In addition, their anti-inflammation properties were evaluated using a 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced mouse ear edema model. The results of the antimicrobial assay revealed that both WU-FA-00 and WU-FA-01 displayed a high level of antimicrobial activity against Gram-positive strains. Moreover, killing kinetic studies were performed, and the results were in accordance with the MIC and MBC results. We also demonstrated that the topical application of WU-FA-00 and WU-FA-01 effectively decreased TPA-induced ear edema in a dose-dependent manner. This inhibitory effect was associated with the inhibition of TPA-induced up-regulation of pro-inflammation cytokines IL-1{beta}, TNF- and COX-2. WU-FA-01 significantly suppressed the expression levels of p65, I{kappa}B-, and p-I{kappa}B- in the TPA-induced mouse ear model. Overall, our results showed that WU-FA-00 and WU-FA-01 not only had effective antimicrobial activities in vitro, especially to the Gram-positive bacteria, but also possessed strong anti-inflammatory effects in vivo. These results provide a scientific basis for developing fusidic acid derivatives as antimicrobial and anti-inflammatory agents.

pharmacology and toxicology↗