Evidence map›Paper›PMID 33975559›Full record

ArticleBMC microbiology2021

Gut microbiota of homologous Chinese soft-shell turtles (Pelodiscus sinensis) in different habitats.

Benli Wu, Long Huang, Jing Chen, Ye Zhang, Jun Wang, Jixiang He

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
6.0field-weighted citation impact, top 3% 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

9 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Pathological changes of highly pathogenicThe veterinary quarterly · 2023
    Article
  7. Article
  8. Article
  9. Article
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

6 authors at 2 institutions in 1 country.

Benli WuKey Laboratory of Aquaculture & Stock Enhancement of Anhui Province, Fisheries Research Institute, Anhui Academy of Agricultural Sciences, No.40 Nongkenan Road, Luyang District, Hefei, 230031, Anhui Province, China.
Long HuangKey Laboratory of Aquaculture & Stock Enhancement of Anhui Province, Fisheries Research Institute, Anhui Academy of Agricultural Sciences, No.40 Nongkenan Road, Luyang District, Hefei, 230031, Anhui Province, China.
Jing ChenKey Laboratory of Aquaculture & Stock Enhancement of Anhui Province, Fisheries Research Institute, Anhui Academy of Agricultural Sciences, No.40 Nongkenan Road, Luyang District, Hefei, 230031, Anhui Province, China.
Ye ZhangKey Laboratory of Aquaculture & Stock Enhancement of Anhui Province, Fisheries Research Institute, Anhui Academy of Agricultural Sciences, No.40 Nongkenan Road, Luyang District, Hefei, 230031, Anhui Province, China.
Jun WangState Key Laboratory of Eco-hydraulic in Northwest Arid Region of China, Xi'an University of Technology, 710048, Xi'an, China.
Jixiang HeKey Laboratory of Aquaculture & Stock Enhancement of Anhui Province, Fisheries Research Institute, Anhui Academy of Agricultural Sciences, No.40 Nongkenan Road, Luyang District, Hefei, 230031, Anhui Province, China. hejixiangah@sina.com.
Anhui Academy of Agricultural Sciences · CNXi'an University of Technology · CN

Funding

National Key Research and Development Project of China 2018YFD0300904-4Scientific and Technological Innovation Team of Anhui Academy of Agricultural Sciences 2020YL041Young Scientists Fund 51709225
6 · The paper itself

Abstract

backgroundChinese soft-shell turtle (Pelodiscus sinensis) is an important commercial species for their high nutritional value and unique taste, but it has been a vulnerable species due to habitat loss. In this study, homologous juvenile turtles were allocated to lake, pond and paddy field to investigate the habitat effects on turtles.

resultsThe growth, morphology and gut microbial communities were monitored during the 4 months cultural period. It showed higher growth rate of turtles in paddy field and pond. The appearance, visceral coefficients, gut morphology and microbial communities in turtles were distinct among different habitats. The microbial community richness on Chao1 was obviously lower in initial turtle guts from greenhouses, whereas it was relative higher in turtle guts sampled from paddy fields than ponds and lake. Significant differences on dominant microbes were found among initial and subsequent samples from different habitats. Firmicutes was the most abundant phylum in the guts of turtles sampled from the greenhouse initially, while Proteobacteria was the most abundant phylum after cultivation in different habitats, followed by Bacteroidetes. The microbial composition were distinct in different habitats at 60d, and the appearance of dominant phyla and genera was more driven by sampling time than habitats at 120d. Both the sampling time and habitats affected the appearance of dominant phyla and genera during the cultivation. The functional predictions indicated that both habitat type and sampling time had significant effects on metabolic pathways, especially amino acid and carbohydrate metabolism.

conclusionsThe turtles could adapt to natural lakes, artificial ponds and paddy fields. The gut microbial abundance was different among the habitats and sampling time. The species of microbes were significantly more diverse in paddy field specimens than in those from ponds and lakes. Rice-turtle coculture is a potential ecological and economic farming mode that plays important roles in wild turtle protection and food security.

Indexed as

EcosystemAnimalsBiodiversityChinaGastrointestinal MicrobiomeTurtlesGut microbial variation, Diversity, Habitat, Rice-turtle coculture.

Identifiers

PMID33975559
PMCPMC8112038
OpenAlexW3184870825

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.