Evidence map›Paper›PMID 34991451›Full record

ArticleBMC genomic data2022

Prediction of trehalose-metabolic pathway and comparative analysis of KEGG, MetaCyc, and RAST databases based on complete genome of Variovorax sp. PAMC28711.

Prasansah Shrestha, Min-Su Kim, Ermal Elbasani, Jeong-Dong Kim, Tae-Jin Oh

Open access · goldAbstract read
In one paragraph

Article in BMC genomic data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 28 citations in OpenAlex.

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  3. Metabolic syndrome and a broken heart: trust your gut or risk your heart.American journal of physiology. Heart and circulatory physiology · 2026
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  5. Computational function prediction of bacteria and phage proteins.Microbiology and molecular biology reviews : MMBR · 2025
    Review
  6. Article
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  8. Virulence · 2022
    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

5 authors at 2 institutions in 1 country.

Prasansah Shrestha *Department of Life Science and Biochemical Engineering, Graduate School, Sun Moon University, Asan, 31460, Korea.
Min-Su Kim *Department of Life Science and Biochemical Engineering, Graduate School, Sun Moon University, Asan, 31460, Korea.
Ermal ElbasaniDepartment of Computer Science and Engineering, Sun Moon University, Asan, 31460, Korea.
Jeong-Dong KimDepartment of Computer Science and Engineering, Sun Moon University, Asan, 31460, Korea.
Tae-Jin OhDepartment of Life Science and Biochemical Engineering, Graduate School, Sun Moon University, Asan, 31460, Korea. tjoh3782@sunmoon.ac.kr.
Sun Moon University · KRAdvanced Institute of Convergence Technology · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolism including anabolism and catabolism is a prerequisite phenomenon for all living organisms. Anabolism refers to the synthesis of the entire compound needed by a species. Catabolism refers to the breakdown of molecules to obtain energy. Many metabolic pathways are undisclosed and many organism-specific enzymes involved in metabolism are misplaced. When predicting a specific metabolic pathway of a microorganism, the first and foremost steps is to explore available online databases. Among many online databases, KEGG and MetaCyc pathway databases were used to deduce trehalose metabolic network for bacteria Variovorax sp. PAMC28711. Trehalose, a disaccharide, is used by the microorganism as an alternative carbon source.

resultsWhile using KEGG and MetaCyc databases, we found that the KEGG pathway database had one missing enzyme (maltooligosyl-trehalose synthase, EC 5.4.99.15). The MetaCyc pathway database also had some enzymes. However, when we used RAST to annotate the entire genome of Variovorax sp. PAMC28711, we found that all enzymes that were missing in KEGG and MetaCyc databases were involved in the trehalose metabolic pathway.

conclusionsFindings of this study shed light on bioinformatics tools and raise awareness among researchers about the importance of conducting detailed investigation before proceeding with any further work. While such comparison for databases such as KEGG and MetaCyc has been done before, it has never been done with a specific microbial pathway. Such studies are useful for future improvement of bioinformatics tools to reduce limitations.

Indexed as

SoftwareTrehaloseBacteriaDatabases, FactualGenomeMetabolic Networks and PathwaysTrehaloseKEGGMetaCycRAST annotationTrehalose metabolismVariovorax sp. PAMC28711

Identifiers

PMID34991451
PMCPMC8734048
OpenAlexW4206444712

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.