Project description:The metabolic model described here refers to the yeast Candida auris with the taxonomic ID 498019. Network reconstruction was performed using merlin 4.05 (Dias et al. 2015) and subsequent curation and validation were performed on OptFlux 3.0 (Rocha et al. 2010) using the IBM CPLEX 12.10 solver. Curation consisted of the editing, addition or removal of reactions so to correct previous gaps in the network using KEGG pathways, MetaCyc Database, and literature data as reference.
Project description:Flash proteotyping is a methodology for ultra-fast identification of microorganisns by tandem mass spectrometry. Here, we obtained results on five reference strains and ten new bacterial isolates. The methodology is based on direct sample infusion into the mass spectromete and an original, highly sensitive procedure for data processing and taxonomic identification.
Project description:Accompanying benchmarking sample for "TaxIt: An iterative computational pipeline for untargeted strain-level identification using MS/MS spectra from pathogenic single-organism samples": Untargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes. We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to increase the confidence in candidate taxa. For benchmarking the performance of our method, we apply our iterative workflow on several samples of bacterial and viral origin. In comparison to non-iterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted and continuously growing sequence resources such as the NCBI databases and is available under open-source BSD license at https://gitlab.com/rki_bioinformatics/TaxIt.
Project description:Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.
Project description:We report a set of rapid, efficient and low-cost methods for ATAC-seq library construction and data analysis, realized large-scale and rapid sequencing. These methods can provide a reference for the study of epigenetic regulation of gene expression.
Project description:One goal of Phase 1 of our project is to produce reference profiles of miRNAs and other small RNAs in a large and diverse set of biofluids using a systemic approach. This study contains samples associated with 10 different biofluids, and all data (sequencing data, full alignments, etc.) is openly available.
Project description:This study demonstrates the usefulness of the API by generating a baseline gut microbiota profile of a healthy population and estimating reference intervals for the functional abundance of manually selected KEGG pathways. API facilitates microbiome research by providing dynamic and customizable tools for estimating reference intervals for gut microbiota functional abundances. Through the API, researchers can rapidly generate gut microbiota functional profiles of healthy populations to use as a baseline for comparison. The API also allows users to manually select specific KEGG pathways and estimate reference intervals for the functional abundance of those pathways. By generating these customized reference intervals, researchers can better understand the expected range of gut microbiota functions in healthy individuals. API enables microbiome studies to go beyond simple taxonomic profiling and delve deeper into the functional potential of gut microbiome communities. In summary, API represents a valuable tool for microbiome researchers that enhances the ability to elucidate connections between gut microbial functions and human health.
Project description:To determine microbiota composition associated with loss of KDM5 in intestine, we carried out 16S rRNA seq analyses of dissected intestine from wildtype and kdm5 mutant. [GSM2628181-GSM2628190]. A total of 78 operational taxonomic units (OTUs) were identified in the sequence data. There were about 15 genera much less abundant in kdm5 mutant compared to wildtype. The kdm5 mutant were sensitive to pathogen. To confirm the microbiota associated with loss of KDM5 in intestine, 16S rRNA of new flies were sequenced and analyzed by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China) [GSM3243472-GSM3243481]. A total of 107 operational taxonomic units (OTUs) were identified in the sequence data. There were about 20 genera much less abundant in kdm5 mutant compared to wildtype. To confirm the microbiota associated with loss of KDM5 drosophila feeding with Lactobacillus plantarum, 16S rRNA of kdm5 mutant flies were sequenced and analyzed by Novogene Bioinformatics Technology Co., Ltd. (Tianjin, China) [GSM3263522-GSM3263527]. A total of 92 operational taxonomic units (OTUs) were identified in the sequence data. To confirm the microbiota associated with KDM5 knockdown in intestine, 16S rRNA of Myo1A-Gal4TS/+ and Myo1A-Gal4TS/+;+/kdm5RNAi flies were sequenced and analyzed by Biomarker Co. Ltd. (Beijing, China). [GSM3507915-GSM3507924]. A total of 50 operational taxonomic units (OTUs) were identified in the sequence data. There was a significant different based on the genus level between two groups.