Evidence map›Paper›PMID 38049781›Full record

ArticleBMC biotechnology2023

Exploring the microbial diversity and characterization of cellulase and hemicellulase genes in goat rumen: a metagenomic approach.

Santosh Thapa, Suping Zhou, Joshua O'Hair, Kamal Al Nasr, Alexander Ropelewski, Hui Li

Open access · goldAbstract read
In one paragraph

Article in BMC biotechnology, 2023. 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
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

8 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Food science & nutrition · 2026
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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

6 authors at 3 institutions in 1 country.

Santosh ThapaDepartment of Agricultural and Environmental Sciences, College of Agriculture, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN, 37209, USA.
Suping ZhouDepartment of Agricultural and Environmental Sciences, College of Agriculture, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN, 37209, USA.
Joshua O'HairDepartment of Biological Sciences, College of Life & Physical Sciences, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN, 37209, USA.
Kamal Al NasrDepartment of Computer Sciences, College of Engineering, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN, 37209, USA.
Alexander RopelewskiPittsburgh Supercomputing Center, 300 S. Craig Street, Pittsburgh, PA, 15213, USA.
Hui LiDepartment of Agricultural and Environmental Sciences, College of Agriculture, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN, 37209, USA. hli@tnstate.edu.
Tennessee State University · USPittsburgh Supercomputing Center · USVanderbilt University Medical Center · US

Funding

NSF OCI 1053575USDA-NIFA 2018-38821-27737
6 · The paper itself

Abstract

backgroundGoat rumen microbial communities are perceived as one of the most potential biochemical reservoirs of multi-functional enzymes, which are applicable to enhance wide array of bioprocesses such as the hydrolysis of cellulose and hemi-cellulose into fermentable sugar for biofuel and other value-added biochemical production. Even though, the limited understanding of rumen microbial genetic diversity and the absence of effective screening culture methods have impeded the full utilization of these potential enzymes. In this study, we applied culture independent metagenomics sequencing approach to isolate, and identify microbial communities in goat rumen, meanwhile, clone and functionally characterize novel cellulase and xylanase genes in goat rumen bacterial communities.

resultsBacterial DNA samples were extracted from goat rumen fluid. Three genomic libraries were sequenced using Illumina HiSeq 2000 for paired-end 100-bp (PE100) and Illumina HiSeq 2500 for paired-end 125-bp (PE125). A total of 435gb raw reads were generated. Taxonomic analysis using Graphlan revealed that Fibrobacter, Prevotella, and Ruminococcus are the most abundant genera of bacteria in goat rumen. SPAdes assembly and prodigal annotation were performed. The contigs were also annotated using the DOE-JGI pipeline. In total, 117,502 CAZymes, comprising endoglucanases, exoglucanases, beta-glucosidases, xylosidases, and xylanases, were detected in all three samples. Two genes with predicted cellulolytic/xylanolytic activities were cloned and expressed in E. coli BL21(DE3). The endoglucanases and xylanase enzymatic activities of the recombinant proteins were confirmed using substrate plate assay and dinitrosalicylic acid (DNS) analysis. The 3D structures of endoglucanase A and endo-1,4-beta xylanase was predicted using the Swiss Model. Based on the 3D structure analysis, the two enzymes isolated from goat's rumen metagenome are unique with only 56-59% similarities to those homologous proteins in protein data bank (PDB) meanwhile, the structures of the enzymes also displayed greater stability, and higher catalytic activity.

conclusionsIn summary, this study provided the database resources of bacterial metagenomes from goat's rumen fluid, including gene sequences with annotated functions and methods for gene isolation and over-expression of cellulolytic enzymes; and a wealth of genes in the metabolic pathways affecting food and nutrition of ruminant animals.

Indexed as

CellulaseCellulasesAnimalsBacteriaCelluloseEscherichia coliGlycoside HydrolasesGoatsMetagenomeRumenCellulaseCellulasesCelluloseGlycoside HydrolaseshemicellulaseCellulolytic/ xylanolytic geneDe novo assemblyGene annotationGoat rumen bacteriaMetagenome/ shotgun sequencingRumen microbial ecology

Identifiers

PMID38049781
PMCPMC10696843
OpenAlexW4389302424

What OpenQuestion holds

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LicenceCC BY
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.