Evidence map›Paper›PMID 30556308›Full record

ArticleMicrobial biotechnology2019

Microbial communities in swine lungs and their association with lung lesions.

Tao Huang, Mingpeng Zhang, Xinkai Tong, Jiaqi Chen, Guorong Yan, Shaoming Fang, Yuanmei Guo, Bin Yang, Shijun Xiao, Congying Chen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Microbial biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.7field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
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  6. Lung microbiota of raccoon dogs (Frontiers in microbiology · 2025
    Article
  7. Article
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  9. Article
  10. Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions-a pilot study.International microbiology : the official journal of the Spanish Society for Microbiology · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Tao HuangState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Mingpeng ZhangState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Xinkai TongState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Jiaqi ChenState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Guorong YanState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Shaoming FangState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Yuanmei GuoState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Bin YangState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Shijun XiaoState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Congying ChenState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Lusheng HuangState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
Huashui AiState Key Laboratory for Swine Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.ORCID 0000-0002-2859-8855
Jiangxi Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Under natural farming, environmental pathogenic microorganisms may invade and affect swine lungs, further resulting in lung lesions. However, few studies on swine lung microbiota and their potential relationship with lung lesions were reported. Here, we sampled 20 pigs from a hybrid herd raised under natural conditions; we recorded a lung-lesion phenotype and investigated lung microbial communities by sequencing the V3-V4 region of 16S rRNA gene for each individual. We found reduced microbial diversity but more biomass in the severe-lesion lungs. Methylotenera, Prevotella, Sphingobium and Lactobacillus were the prominent bacteria in the healthy lungs, while Mycoplasma, Ureaplasma, Sphingobium, Haemophilus and Phyllobacterium were the most abundant microbes in the severe-lesion lungs. Notably, we identified 64 lung-lesion-associated OTUs, of which two classified to Mycoplasma were positively associated with lung lesions and 62 showed negative association including thirteen classified to Prevotella and six to Ruminococcus. Cross-validation analysis showed that lung microbiota explained 23.7% phenotypic variance of lung lesions, suggesting that lung microbiota had large effects on promoting lung healthy. Furthermore, 22 KEGG pathways correlated with lung lesions were predicted. Altogether, our findings improve the knowledge about swine lung microbial communities and give insights into the relationship between lung microbiota and lung lesions.

Indexed as

MicrobiotaAnimalsCluster AnalysisDNA, BacterialDNA, RibosomalLungPhylogenyPneumonia, BacterialRNA, Ribosomal, 16SSequence Analysis, DNASwineSwine DiseasesDNA, BacterialDNA, RibosomalRNA, Ribosomal, 16S

Identifiers

PMID30556308
PMCPMC6389860
OpenAlexW2904508118

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.