Literature DB >> 31907101

Translating 'big data': better understanding of host-pathogen interactions to control bacterial foodborne pathogens in poultry.

Loïc Deblais1, Dipak Kathayat1, Yosra A Helmy1, Gary Closs1, Gireesh Rajashekara1.   

Abstract

Recent technological advances has led to the generation, storage, and sharing of colossal sets of information ('big data'), and the expansion of 'omics' in science. To date, genomics/metagenomics, transcriptomics, proteomics, and metabolomics are arguably the most ground breaking approaches in food and public safety. Here we review some of the recent studies of foodborne pathogens (Campylobacter spp., Salmonella spp., and Escherichia coli) in poultry using big data. Genomic/metagenomic approaches have reveal the importance of the gut microbiota in health and disease. They have also been used to identify, monitor, and understand the epidemiology of antibiotic-resistance mechanisms and provide concrete evidence about the role of poultry in human infections. Transcriptomics studies have increased our understanding of the pathophysiology and immunopathology of foodborne pathogens in poultry and have led to the identification of host-resistance mechanisms. Proteomic/metabolomic approaches have aided in identifying biomarkers and the rapid detection of low levels of foodborne pathogens. Overall, 'omics' approaches complement each other and may provide, at least in part, a solution to our current food-safety issues by facilitating the development of new rapid diagnostics, therapeutic drugs, and vaccines to control foodborne pathogens in poultry. However, at this time most 'omics' approaches still remain underutilized due to their high cost and the high level of technical skills required.

Entities:  

Keywords:  Campylobacter; Escherichia coli; Salmonella; omics; therapeutic targets

Year:  2020        PMID: 31907101     DOI: 10.1017/S1466252319000124

Source DB:  PubMed          Journal:  Anim Health Res Rev        ISSN: 1466-2523            Impact factor:   2.615


  2 in total

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Authors:  Katarzyna Kosznik-Kwaśnicka; Magdalena Podlacha; Łukasz Grabowski; Małgorzata Stasiłojć; Alicja Nowak-Zaleska; Karolina Ciemińska; Zuzanna Cyske; Aleksandra Dydecka; Lidia Gaffke; Jagoda Mantej; Dorota Myślińska; Agnieszka Necel; Karolina Pierzynowska; Ewa Piotrowska; Edyta Radzanowska-Alenowicz; Estera Rintz; Krzysztof Sitko; Gracja Topka-Bielecka; Grzegorz Węgrzyn; Alicja Węgrzyn
Journal:  Front Cell Infect Microbiol       Date:  2022-08-04       Impact factor: 6.073

2.  Database Oriented Big Data Analysis Engine Based on Deep Learning.

Authors:  Xiaoran Shang
Journal:  Comput Intell Neurosci       Date:  2022-08-31
  2 in total

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