Evidence map›Paper›PMID 37258863›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Designing Knowledge-Based Bioremediation Strategies Using Metagenomics.

Niti B Jadeja, Atya Kapley

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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. Review
  2. Review
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.

Niti B JadejaAshoka Trust for Research in Ecology and the Environment, Royal Enclave, Bengaluru, India.
Atya KapleyEnvironmental Biotechnology and Genomics Division, National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India. a_kapley@neeri.res.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional capacities for bioremediation are governed by metabolic mechanisms of inhabiting microbial communities at polluted niches. Process fluctuations lead to stress scenarios where microbes evolve continuously to adapt to sustain the harsh conditions. The biological wastewater treatment (WWT) process harbors the potential of these catabolic microbes for the degradation of organic molecules. In a typical biological WWT or soil bioremediation process, several microbial species coexist which code for enzymes that degrade complex compounds.High throughput DNA sequencing techniques for microbiome analysis in bioremediation processes have led to a powerful paradigm revealing the significance of metabolic functions and microbial diversity. The present chapter describes techniques in taxonomy and functional gene analysis for understanding bioremediation potential and novel strategies built on in silico analysis for the improvisation of existing aerobic wastewater treatment methods. Methods explaining comparative metagenomics by Metagenome Analysis server (MG-RAST) are described with successful case studies by focusing on industrial wastewaters and soil bioremediation studies.

Indexed as

MetagenomicsMicrobiotaBiodegradation, EnvironmentalMetagenomeWastewaterWastewaterActivated sludgeFunctional genomicsMetagenomics

Identifiers

What OpenQuestion holds

Textmetadata
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.