Evidence map›Paper›PMID 31378834›Full record

ArticleFunctional & integrative genomics2020

De novo genome assembly and comparative annotation reveals metabolic versatility in cellulolytic bacteria from cropland and forest soils.

Suman Yadav, Bhaskar Reddy, Suresh Kumar Dubey

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Article in Functional & integrative genomics, 2020. 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

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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

2 citing papers in PubMed.

  1. Article
  2. Structured Framework and Genome Analysis ofJournal of fungi (Basel, Switzerland) · 2022
    Article
4 · The record

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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.

Suman YadavLaboratory of Molecular Ecology, Centre of Advanced Study in Botany, Institute of Science, Banaras Hindu University, Varanasi, 221005, India.
Bhaskar ReddyLaboratory of Molecular Ecology, Centre of Advanced Study in Botany, Institute of Science, Banaras Hindu University, Varanasi, 221005, India.
Suresh Kumar DubeyLaboratory of Molecular Ecology, Centre of Advanced Study in Botany, Institute of Science, Banaras Hindu University, Varanasi, 221005, India. skdubey@bhu.ac.in.

Funding

Council of Scientific and Industrial Research, Government of India, New Delhi 09/013(0617)/2016-EMR-I
6 · The paper itself

Abstract

Cellulose, the most abundant polysaccharide in nature, is a rich source of renewable energy and sustains soil nutrients. Among the microorganisms known to degrade cellulose, bacteria are less studied compared to fungi. In the present work, we have investigated the culturable bacteria actively involved in cellulose degradation in forest and crop field soils. Based on clear zone formation and enzyme activity assay, we identified 7 bacterial strains positive for cellulose degradation. Of these, two most efficient strains (Bacillus cereus strains BHU1 and BHU2) were selected for whole genome sequencing, annotation, and information regarding GC content, number of genes, total subsystems, starch, and cellulose degradation pathways. Average nucleotide identity (ANI) showed more than 90% similarity between both the strains (BHU1 and BHU2) and with B. cereus ATCC 14579. Both the strains have genes and enzyme families like endoglucanase and β-glucosidase as evident from whole genome sequence. Cellulase containing gene families (GH5, GH8, GH1), and many other carbohydrate-degrading enzymes, were present in both the bacterial strains. Taken together, the results suggest that the strains were efficient in cellulose degradation, and can be used for energy generation and production of value-added product.

Indexed as

Genome, BacterialAgricultureAnti-Bacterial AgentsBacillus cereusBacteriaCarbohydrate MetabolismCellulaseCelluloseForestsGenes, BacterialMolecular Sequence AnnotationSecondary MetabolismSoilWhole Genome SequencingAnti-Bacterial AgentsCellulaseCelluloseSoilBacillus cereusCellulaseCrop and forest soilsDe novo genome assemblyGH family

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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.