ArticleBMC systems biology2017
Identification of natural antimicrobial peptides from bacteria through metagenomic and metatranscriptomic analysis of high-throughput transcriptome data of Taiwanese oolong teas.
Article in BMC systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- An ensemble deep learning model for predicting minimum inhibitory concentrations of antimicrobial peptides against pathogenic bacteria.iScience · 2024Article
- Article
- Perspectives in Searching Antimicrobial Peptides (AMPs) Produced by the Microbiota.Microbial ecology · 2023Review
- Article
- Computational exploration of the global microbiome for antibiotic discovery.bioRxiv : the preprint server for biology · 2023Article
- Interaction and Application of Molds and Yeasts in Chinese Fermented Foods.Frontiers in microbiology · 2021Review
- Characterization and Identification of Natural Antimicrobial Peptides on Different Organisms.International journal of molecular sciences · 2020Article
- dbAMP: an integrated resource for exploring antimicrobial peptides with functional activities and physicochemical properties on transcriptome and proteome data.Nucleic acids research · 2019Article
- Brevibacillus laterosporus strains BGSP7, BGSP9 and BGSP11 isolated from silage produce broad spectrum multi-antimicrobials.PloS one · 2019Article
- A bioinformatics potpourri.BMC genomics · 2018Article
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8 authors.
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Abstract
backgroundAnti-microbial peptides (AMPs), naturally encoded by genes and generally containing 12-100 amino acids, are crucial components of the innate immune system and can protect the host from various pathogenic bacteria and viruses. In recent years, the widespread use of antibiotics has resulted in the rapid growth of antibiotic-resistant microorganisms that often induce critical infection and pathogenesis. Recently, the advent of high-throughput technologies has led molecular biology into a data surge in both the amount and scope of data. For instance, next-generation sequencing technology has been applied to generate large-scale sequencing reads from foods, water, soil, air, and specimens to identify microbiota and their functions based on metagenomics and metatranscriptomics, respectively. In addition, oolong tea is partially fermented and is the most widely produced tea in Taiwan. Many studies have shown the benefits of oolong tea in inhibiting obesity, reducing dental plaque deposition, antagonizing allergic immune responses, and alleviating the effects of aging. However, the microbes and their functions present in oolong tea remain unknown.
resultsTo understand the relationship between Taiwanese oolong teas and bacterial communities, we designed a novel bioinformatics scheme to identify AMPs and their functional types based on metagenomics and metatranscriptomic analysis of high-throughput transcriptome data. Four types of oolong teas (Dayuling tea, Alishan tea, Jinxuan tea, and Oriental Beauty tea) were subjected to 16S ribosomal DNA and total RNA extraction and sequencing. Metagenomics analysis results revealed that Oriental Beauty tea exhibited greater bacterial diversity than other teas. The most common bacterial families across all tea types were Bacteroidaceae (21.7%), Veillonellaceae (22%), and Fusobacteriaceae (12.3%). Metatranscriptomics analysis results revealed that the dominant bacteria species across all tea types were Escherichia coli, Bacillus subtilis, and Chryseobacterium sp. StRB126, which were subjected to further functional analysis. A total of 8194 (6.5%), 26,220 (6.1%), 5703 (5.8%), and 106,183 (7.8%) reads could be mapped to AMPs.
conclusionWe found that the distribution of anti-gram-positive and anti-gram-negative AMPs is highly correlated with the distribution of gram-positive and gram-negative bacteria in Taiwanese oolong tea samples.
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