Virome Data Explorer: A web resource to longitudinally explore respiratory viral infections, their interactions with other pathogens and host transcriptomic changes in over 100 people
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ABSTRACT:
SUBMITTER: Galanti M
PROVIDER: S-EPMC10796020 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Viral respiratory infections are an important public health concern, due to their prevalence, transmissibility, and potential to cause serious disease. Disease severity is the product of several factors beyond the presence of the infectious agent, including specific host immune responses, host genetic makeup and bacterial co-infections. To understand these interactions within natural infections we designed a longitudinal cohort study actively surveilling 18 different respiratory viruses over the course of 19 months (2016-2018) in Manhattan, New York City. The cohort includes individuals related to daycare facilities, high school students and health care workers. We retrieved weekly epidemiological and clinical data and collected over 4,000 nasal swabs for molecular characterization from 214 participants. Transcriptomic data enabled the characterization of specific markers of immune response, the identification of signatures associated with symptom severity and bacterial co-infections. We created a computational resource to facilitate access to the data and visualization of analytical results.
2023-01-30 | GSE223679 | GEO
Project description:Virome Data Explorer: A web resource to longitudinally explore respiratory viral infections, their interactions with other pathogens and host transcriptomic changes in over 100 people
| PRJNA927273 | ENA
Project description:MotivationZoonotic pathogens, such as viruses, bacteria, fungi and parasites, can be transmitted from animals to humans, causing a wide range of diseases that can vary from mild to life-threatening. These pathogens typically exhibit a broad host range, infecting domestic and/or wild animals, which serve as reservoirs of infection. Human infection can occur through direct contact with infected animals or their body fluids, consumption of contaminated food or water, or via bites from infected arthropod vectors. Understanding the epidemiological characteristics and population structure of zoonotic pathogens is of paramount importance for preventing and controlling the spread of zoonotic diseases.ResultsHere, we present ZooPathWeb, a comprehensive online resource for zoonotic pathogens. ZooPathWeb provides essential information on pathogens that are particularly relevant to public health and includes a literature collection organized by pathogen classification, such as lineage, host, country or region and publication year. Moreover, we have developed four web-based utility tools for this release: SeqNHandle, PaPhy-ML, TreeView and BLAST. These tools are specifically designed to facilitate the identification of population structure and adaptive evolution in relation to zoonotic pathogens.Availability and implementationThe ZooPathWeb website is accessed via http://lab.malab.cn/~hrs/zoopathweb/. The source code for AKINND, which is used for collecting pathogen-related literature, can be found at https://github.com/RuiSiHu/AKINND. Additionally, the source code for PaPhy-ML, utilized for phylogenetic analysis, can be found at https://github.com/RuiSiHu/PaPhy-ML.Supplementary informationSupplementary data are available at Bioinformatics Advances online.
| S-EPMC10351968 | biostudies-literature
Project description:BACKGROUND:Protein microarray is a well-established approach for characterizing activity levels of thousands of proteins in a parallel manner. Analysis of protein microarray data is complex and time-consuming, while existing solutions are either outdated or challenging to use without programming skills. The typical data analysis pipeline consists of a data preprocessing step, followed by differential expression analysis, which is then put into context via functional enrichment. Normally, biologists would need to assemble their own workflow by combining a set of unrelated tools to analyze experimental data. Provided that most of these tools are developed independently by various bioinformatics groups, making them work together could be a real challenge. RESULTS:Here we present PAWER, the online web tool dedicated solely to protein microarray analysis. PAWER enables biologists to carry out all the necessary analysis steps in one go. PAWER provides access to state-of-the-art computational methods through the user-friendly interface, resulting in publication-ready illustrations. We also provide an R package for more advanced use cases, such as bespoke analysis workflows. CONCLUSIONS:PAWER is freely available at https://biit.cs.ut.ee/pawer .
| S-EPMC7499988 | biostudies-literature
Project description:Using a spotted 65-mer oligonucleotide microarray, we have characterized the developmental expression profile from mid-gastrulation (75% epiboly) to 5 days post-fertilization (dpf) for >16,000 unique transcripts in the zebrafish genome. Microarray profiling data sets are often immense, and one challenge is validating the results and prioritizing genes for further study. The purpose of the current study was to address such issues, as well as to generate a publicly available resource for investigators to examine the developmental expression profile of any of the over 16,000 zebrafish genes on the array. On the chips, there are 16,459 printed spots corresponding to 16,288 unique transcripts and 172 beta-actin (AF025305) spots spatially distributed throughout the chip as a positive control. We have collected 55 microarray gene expression profiling results from various zebrafish laboratories and created a Perl/CGI-based software tool (http://serine.umdnj.edu/approximately ouyangmi/cgi-bin/zebrafish/profile.htm) for researchers to look for the expression patterns of their gene of interest. Users can search for their genes of interest by entering the accession numbers or the nucleotide sequences and the expression profiling will be reported in the form of expression intensities versus time-course graphical displays. In order to validate this web tool, we compared 74 genes' expression results between our web tool and the in situ hybridization results from Thisse et al. [Thisse, B., Heyer, V., Lux, A., Alunni, A., Degrave, A., Seiliez, I., Kirchner, J., Parkhill, J.-P., Thisse, C., 2004. Spatial and temporal expression of the zebrafish genome by large-scale in situ hybridization screening. Meth. Cell. Biol. 77, 505-519] as well as those reported by Mathavan et al. [Mathavan, S., Lee, S.G., mark, A., Miller, L.D., Murthy, K.R., Tong, Y., Wu, Y.L., Lam, S.H., Yang, H., Ruan, Y., Korzh, V., Gong, Z., Liu, E.T., Lufkin, T., 2005. Transcriptome analysis of zebrafish embryogenesis using microarrays. PLoS Genet. 1, 260-276]. The comparison indicates that our microarray-derived expression patterns are 80% and 75% in agreement with the in situ database (Thisse et al., 2004) and previously published microarray data (Mathavan et al., 2005), respectively. Those genes that conflict between our web tool and the in situ database either have high sequence similarity with other genes or the in situ probes are not reliable. Among those genes that disagree between our web tool and those reported by Mathavan et al. (2005), 93% of the genes are in agreement between our web tool and the in situ database, indicating our web tool results are quite reliable. Thus, this resource provides a user-friendly web based platform for researchers to determine the developmental profile of their gene of interest and to prioritize genes identified in microarray analyses by their developmental expression profile.
| S-EPMC2253684 | biostudies-literature
Project description:Post-transcriptional regulation via RNA-binding proteins plays a fundamental role in every organism, but the regulatory mechanisms lack important understanding. Nevertheless, they can be elucidated by cross-linking immunoprecipitation in combination with high-throughput sequencing (CLIP-Seq). CLIP-Seq answers questions about the functional role of an RNA-binding protein and its targets by determining binding sites on a nucleotide level and associated sequence and structural binding patterns. In recent years the amount of CLIP-Seq data skyrocketed, urging the need for an automatic data analysis that can deal with different experimental set-ups. However, noncanonical data, new protocols, and a huge variety of tools, especially for peak calling, made it difficult to define a standard. CLIP-Explorer is a flexible and reproducible data analysis pipeline for iCLIP data that supports for the first time eCLIP, FLASH, and uvCLAP data. Individual steps like peak calling can be changed to adapt to different experimental settings. We validate CLIP-Explorer on eCLIP data, finding similar or nearly identical motifs for various proteins in comparison with other databases. In addition, we detect new sequence motifs for PTBP1 and U2AF2. Finally, we optimize the peak calling with 3 different peak callers on RBFOX2 data, discuss the difficulty of the peak-calling step, and give advice for different experimental set-ups. CLIP-Explorer finally fills the demand for a flexible CLIP-Seq data analysis pipeline that is applicable to the up-to-date CLIP protocols. The article further shows the limitations of current peak-calling algorithms and the importance of a robust peak detection.
| S-EPMC7657819 | biostudies-literature
Project description:Rotavirus vaccines (RVVs) have substantially diminished mortality from severe rotavirus (RV) gastroenteritis but are significantly less effective in low- and middle-income countries (LMICs), limiting their life-saving potential. The etiology of RVV's diminished effectiveness remains incompletely understood, but the enteric microbiota has been implicated in modulating immunity to RVVs. Here, we analyze the enteric microbiota in a longitudinal cohort of 122 Ghanaian infants, evaluated over the course of 3 Rotarix vaccinations between 6 and 15 weeks of age, to assess whether bacterial and viral populations are distinct between non-seroconverted and seroconverted infants. We identify bacterial taxa including Streptococcus and a poorly classified taxon in Enterobacteriaceae as positively correlating with seroconversion. In contrast, both bacteriophage diversity and detection of Enterovirus B and multiple novel cosaviruses are negatively associated with RVV seroconversion. These findings suggest that virome-RVV interference is an underappreciated cause of poor vaccine performance in LMICs.
| S-EPMC8763403 | biostudies-literature
Project description:To better leverage the accumulated bioactivity data in the ChEMBL database, we have developed Bioactivity-explorer, a web application for interactive visualization and exploration of the large-scale bioactivity data in ChEMBL. Mining and integration of the Therapeutic Target Database disease-target mapping into the ChEMBL database has enabled Bioactivity-explorer to include 493,430 scaffolds, 31,400,000 matched molecular pairs, 1330,220 target-target interactions in terms of shared active compounds, 4526,718 target-target interactions in terms of shared active scaffolds, 97,041,700 molecule-molecule interactions and 14,974 disease-target mappings. This web tool is available at http://cadd.pharmacy.nankai.edu.cn/b17r . The source codes of the front end and back end, released under MIT license, can be found at GitHub.
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Project description:Paralogs are genes which arose via gene duplication, and when such paralogs retain overlapping or redundant function, this poses a challenge to functional genetics research. Recent technological advancements have made it possible to systematically probe gene function for redundant genes using dual or multiplex gene perturbation, and there is a need for a simple bioinformatic tool to identify putative paralogs of a gene(s) of interest. We have developed Paralog Explorer (https://www.flyrnai.org/tools/paralogs/), an online resource that allows researchers to quickly and accurately identify candidate paralogous genes in the genomes of the model organisms D. melanogaster, C. elegans, D. rerio, M. musculus, and H. sapiens. Paralog Explorer deploys an effective between-species ortholog prediction software, DIOPT, to analyze within-species paralogs. Paralog Explorer allows users to identify candidate paralogs, and to navigate relevant databases regarding gene co-expression, protein-protein and genetic interaction, as well as gene ontology and phenotype annotations. Altogether, this tool extends the value of current ortholog prediction resources by providing sophisticated features useful for identification and study of paralogous genes.
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Project description:Cognitive dysfunction due to minimal hepatic encephalopathy (MHE) adversely impacts patients with cirrhosis and more precise therapies are needed. Gut-brain axis changes are therapeutic targets, but prior studies have largely focused on bacterial changes. Our aim was to determine linkages between individual cognitive testing results and bacteria with the virome using a cross-sectional and longitudinal approach. We included cross-sectional (n = 138) and longitudinal analyses (n = 36) of patients with cirrhosis tested using three cognitive modalities, which were psychometric hepatic encephalopathy score (PHES), inhibitory control test (ICT), Stroop, and all three. Stool metagenomics with virome and bacteriome were analyzed studied cross-sectionally and in a subset followed for development/reversal of MHE repeated at 6 months (longitudinally only using PHES). Cross-sectional: We found no significant changes in α/β diversity in viruses or bacteria regardless of cognitive testing. Cognitively impaired patients were more likely to have higher relative abundance of bacteriophages linked with Streptococcus, Faecalibacterium, and Lactobacillus, which were distinct based on modality. These were also linked with cognition on correlation networks. Longitudinally, 27 patients remained stable while 9 changed their MHE status. Similar changes in phages that are linked with Streptococcus, Faecalibacterium, and Lactobacillus were seen. These phages can influence ammonia, lactate, and short-chain fatty acid generation, which are neuro-active. In conclusion, we found linkages between bacteriophages and cognitive function likely due to impact on bacteria that produce neuroactive metabolites cross-sectionally and longitudinally. These findings could help explore bacteriophages as options to influence treatment for MHE in cirrhosis.
| S-EPMC10730154 | biostudies-literature