Evidence map›Paper›PMID 35015144›Full record

ArticleApplied microbiology and biotechnology2022

Predicted functional genes for the biodegradation of xenobiotics in groundwater and sediment at two contaminated naval sites.

Andrea Vera, Fernanda Paes Wilson, Alison M Cupples

Abstract read
PubMed Publisher
In one paragraph

Article in Applied microbiology and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

16 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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

3 authors at 1 institution in 1 country.

Andrea VeraDepartment of Civil and Environmental Engineering, Michigan State University, A135, 1449 Engineering Research Court, East Lansing, MI, 48824, USA.
Fernanda Paes WilsonDepartment of Civil and Environmental Engineering, Michigan State University, A135, 1449 Engineering Research Court, East Lansing, MI, 48824, USA.
Alison M CupplesDepartment of Civil and Environmental Engineering, Michigan State University, A135, 1449 Engineering Research Court, East Lansing, MI, 48824, USA. cupplesa@egr.msu.edu.ORCID http://orcid.org/0000-0003-3248-7688
Michigan State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goals of this study were to predict the genes associated with the biodegradation of organic contaminants and to examine microbial community structure in samples from two contaminated sites. The approach involved a predictive bioinformatics tool (PICRUSt2) targeting genes from twelve KEGG xenobiotic biodegradation pathways (benzoate, chloroalkane and chloroalkene, chlorocyclohexane and chlorobenzene, toluene, xylene, nitrotoluene, ethylbenzene, styrene, dioxin, naphthalene, polycyclic aromatic hydrocarbons, and metabolism of xenobiotics by cytochrome P450). Further, the predicted phylotypes associated with functional genes early in each pathway were determined. Phylogenetic analysis indicated a greater diversity in the sediment compared to the groundwater samples. The most abundant genera for sediments/microcosms included Pseudomonas, Methylotenera, Rhodococcus, Stenotrophomonas, and Brevundimonas, and the most abundant for the groundwater/microcosms included Pseudomonas, Cupriavidus, Azospira, Rhodococcus, and unclassified Burkholderiaceae. Genes from all twelve of the KEGG pathways were predicted to occur. Seven pathways contained less than twenty-five genes. The predicted genes were lowest for xenobiotics metabolism by cytochrome P450 and ethylbenzene biodegradation and highest for benzoate biodegradation. Notable trends include the occurrence of the first genes for trinitrotoluene and 2,4-dinitrotoluene degradation. Also, the complete path from toluene to benzoyl-CoA was predicted. Twenty-two of the dioxin pathway genes were predicted, including genes within the first steps. The following phylotypes were associated with the greatest number of pathways: unclassified Burkholderiaceae, Burkholderia-Caballeronia-Paraburkholderia, Pseudomonas, Rhodococcus, unclassified Betaproteobacteria, and Polaromonas. This work illustrates the value of PICRUSt2 for predicting biodegradation potential and suggests that a subset of phylotypes could be important for the breakdown of organic contaminants or their metabolites. KEY POINTS: • The approach is a low-cost alternative to shotgun sequencing. • The genes and phylotypes encoding for xenobiotic degradation were predicted. • A subset of phylotypes were associated with many pathways.

Indexed as

GroundwaterXenobioticsBiodegradation, EnvironmentalPhylogenyTolueneTolueneXenobioticsNitrotoluenePICRUSt2RDXTolueneXenobiotic

Identifiers

PMID35015144
OpenAlexW4206244075

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.