Evidence map›Paper›PMID 35362813›Full record

ArticleArchives of microbiology2022

Identification and profiling of microbial community from industrial sludge.

Pooja Sharma, Surendra Pratap Singh

Abstract read
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In one paragraph

Article in Archives of microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Pooja SharmaDepartment of Environmental Microbiology, School for Environmental Sciences, Babasaheb Bhimrao Ambedkar (A Central) University, Lucknow, 226 025, Uttar Pradesh, India. sharmaspspooja@gmail.com.ORCID http://orcid.org/0000-0001-7513-6226
Surendra Pratap SinghPlant Molecular Biology Laboratory, Department of Botany, Dayanand Anglo-Vedic (PG) College, Chhatrapati Shahu Ji Maharaj University, Kanpur, 208 001, India. spsinghbiome@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study is to identify microbial communities in pulp and paper industry sludge and their metagenomic profiling on the basis of; phylum, class, order, family, genus and species level. Results revealed that the dominant phyla in 16S rRNA Illumina Miseq analysis inside sludge were Anaerolinea, Pseudomonas, Clostridia, Bacteriodia, Gammaproteobacteria, Spirochetia, Deltaproteobacteria, Spirochaetaceae, Prolixibacteraceae and some unknown microbial strains are also dominant. Metagenomics is a molecular biology-based technology that uses bioinformatics to evaluate huge gene sequences extracted from environmental samples to assess the composition and function of microbiota. The results of metabarcoding of the V3-V4 16S rRNA regions acquired from paired-end Illumina MiSeq sequencing were used to analyze bacterial communities and structure. The present work demonstrates the potential approach to sludge treatment in the open environment via the naturally adapted microorganism, which could be an essential addition to the disposal site. In summary, these investigations indicate that the indigenous microbial community is an acceptable bioresource for remediation or detoxification following secondary treatment. This research aims at understanding the structure of microbial communities and their diversity (%) in highly contaminated sludge to perform in situ bioremediation.

Indexed as

MicrobiotaSewageMetagenomeMetagenomicsRNA, Ribosomal, 16SRNA, Ribosomal, 16SSewageBiological treatmentEnvironmental protectionMetagenomics analysisMicrobial communityPollutants

Identifiers

PMID35362813

What OpenQuestion holds

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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.