Evidence map›Paper›PMID 28684789›Full record

ArticleScientific reports2017

Soil bacterial quantification approaches coupling with relative abundances reflecting the changes of taxa.

Zhaojing Zhang, Yuanyuan Qu, Shuzhen Li, Kai Feng, Shang Wang, Weiwei Cai, Yuting Liang, Hui Li, Meiying Xu, Huaqun Yin and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed
–field-weighted citation impact
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

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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

54 citing papers in PubMed.

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  13. Designing and validation of specific primers for the quantitative detection of bacteria in sugarcane inoculant.Brazilian journal of microbiology : [publication of the Brazilian 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

11 authors.

Zhaojing ZhangState Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education, China), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China.
Yuanyuan QuState Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education, China), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China. qyy@dlut.edu.cn.
Shuzhen LiState Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education, China), School of Environmental Science and Technology, Dalian University of Technology, Dalian, 116024, China.
Kai FengKey Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing, 100085, China.
Shang WangKey Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing, 100085, China.
Weiwei CaiKey Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing, 100085, China.
Yuting LiangState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China.
Hui LiState Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.
Meiying XuState Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangzhou, 510070, China.
Huaqun YinSchool of Minerals Processing and Bioengineering, Central South University, Changsha, 410083, China.
Ye DengKey Laboratory of Environmental Biotechnology, Research Center for Eco-Environmental Science, Chinese Academy of Sciences, Beijing, 100085, China. yedeng@rcees.ac.cn.ORCID 0000-0002-7584-0632

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the abundance change of certain bacterial taxa is quite important for the study of soil microbiology. However, the observed differences of relative abundances by high-throughput techniques may not accurately reflect those of the actual taxon abundances. This study investigated whether soil microbial abundances coupling with microbial quantities can be more informative in describing the microbial population distribution under different locations. We analyzed relative abundances of the major species in soil microbial communities from Beijing and Tibet grasslands by using 16 S rRNA high-throughput sequencing technique, and quantified the absolute bacterial cell numbers directly or indirectly by multiple culture-independent measurements, including adenosine tri-phosphate (ATP), flow cytometry (FCM), quantitative real-time PCR (qPCR), phospholipid fatty acids (PLFA) and microbial biomass Carbon (MBC). By comparison of the relative abundance and the estimated absolute abundances (EAA) of the major components in soil microbial communities, several dominant phyla, including Actinobacteria, Bacteroidetes, Verrucomicrobia, Chloroflexi, Gemmatimonates and Planctomycetes, showed significantly different trends. These results indicated that the change in EAA might be more informative in describing the dynamics of a population in a community. Further studies of soil microbes should combine the quantification and relative abundances of the microbial communities for the comparisons among various locations.

Indexed as

Soil MicrobiologyActinobacteriaAdenosine TriphosphateBacteroidetesBiodiversityBiomassCarbonChinaChloroflexiFatty AcidsGrasslandHigh-Throughput Nucleotide SequencingMicrobial ConsortiaPhospholipidsPlanctomycetalesRNA, Ribosomal, 16SAdenosine TriphosphateCarbonFatty AcidsPhospholipidsRNA, Ribosomal, 16S

Identifiers

PMID28684789
PMCPMC5500469

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