Evidence map›Paper›PMID 29322917›Full record

ArticleBMC systems biology2017

Identification of natural antimicrobial peptides from bacteria through metagenomic and metatranscriptomic analysis of high-throughput transcriptome data of Taiwanese oolong teas.

Kai-Yao Huang, Tzu-Hao Chang, Jhih-Hua Jhong, Yu-Hsiang Chi, Wen-Chi Li, Chien-Lung Chan, K Robert Lai, Tzong-Yi Lee

Abstract read
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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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0cells of the map it votes in
10citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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  10. A bioinformatics potpourri.BMC genomics · 2018
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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Kai-Yao HuangDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan.
Tzu-Hao ChangGraduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, 110, Taiwan.
Jhih-Hua JhongDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan.
Yu-Hsiang ChiDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan.
Wen-Chi LiDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan.
Chien-Lung ChanDepartment of Information Management, Yuan Ze University, Taoyuan City, 320, Taiwan.
K Robert LaiDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan.
Tzong-Yi LeeDepartment of Computer Science and Engineering, Yuan Ze University, Taoyuan City, 320, Taiwan. francis@saturn.yzu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Expression ProfilingMetagenomicsAntimicrobial Cationic PeptidesBacteriaHigh-Throughput Nucleotide SequencingRNA, Ribosomal, 16SSequence Analysis, RNATeaAntimicrobial Cationic PeptidesRNA, Ribosomal, 16STeaAmpAntimicrobial peptideMetagenomicsMetatranscriptomicsNext-generation sequencingOolong teas

Identifiers

PMID29322917
PMCPMC5763296

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.