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BMC Biotechnology
Exploring themicrobial diversity
andcharacterization ofcellulase
andhemicellulase genes ingoat rumen:
ametagenomic approach
Santosh Thapa1,2, Suping Zhou1, Joshua O’Hair3, Kamal Al Nasr4, Alexander Ropelewski5 and Hui Li1*
Abstract
Background Goat 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 inde-
pendent metagenomics sequencing approach to isolate, and identify microbial communities in goat rumen, mean-
while, clone and functionally characterize novel cellulase and xylanase genes in goat rumen bacterial communities.
Results Bacterial 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 anno-
tation 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 xyla-
nase 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.
Conclusions In 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 cel-
lulolytic enzymes; and a wealth of genes in the metabolic pathways affecting food and nutrition of ruminant animals.
Keywords Goat rumen bacteria, Metagenome/ shotgun sequencing, De novo assembly, Gene annotation, Rumen
microbial ecology, Cellulolytic/ xylanolytic gene
*Correspondence:
Hui Li
hli@tnstate.edu
Full list of author information is available at the end of the article
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Page 2 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
Background
Over the past two decades, there has been an increased
global interest in the development of sustainable bio-
renewable primarily owing to the increase in green-
house gas emission, climate change and ultimately to
reduce the dependency on fossil fuels [1]. Cellulosic bio-
mass without any doubt is emerging as a sustainable raw
material for the bioeconomy. Lignocellulosic biomass
comprises mainly of polysaccharide polymers, cellulose,
hemi-cellulose, pectin, and lignin [2]. e incorporation
of enzymatic synthesis into a wide array of eco-friendly
bioprocesses such as the hydrolysis of cellulose/hemi-
cellulose has become an illustrious tool in deriving well
defined bioactive compounds and biodegradable indus-
trial products. Yet, the potential exploitation of cellulosic
biomass conversion into its oligo and monosaccharides
is particularly hindered due to the limited understand-
ing of the complex recalcitrant nature of cellulose, hemi-
cellulose and lignin, distinct biochemical functions of
the enzyme, enzymatic pathways, and the dearth of
tailor-made suitable efficient enzymes [3, 4]. is led to
the increased investigation of novel hydrolytic enzymes
from unique and extreme ecological niches. Hence, it is
of utmost significance to understand the phenomenon
behind the unexploited ecologically sustainable microbial
bioresource.
e various kinds of cellulolytic and xylanolytic
enzymes are found in microbes, plants, snails, termites,
beetles, insects dwelling in various extreme environmen-
tal niches. Microorganisms are the prime producers of
cellulolytic and xylanolytic enzymes which makes them
the most prominent players in biomass decomposition
[5]. Chen etal. reported that microbial enzymes possess
the remarkable capability to significantly expedite the
otherwise highly protracted process of biodegrading cel-
lulosic biomass [6]. Ruminant’s rumen houses dense and
complex community of symbiotic microbes that work
together to break down lignocellulose [7]. ese rumen
microbial communities are perceived as the most poten-
tial biochemical reservoir of inordinately diverse and
multi-functional cellulolytic enzymes with peculiar func-
tional adaptation to enhance green biotechnological pro-
cesses [8]. Bacterial community dominates the ruminal
environment and hence considered as the most efficient
biomass degrading enzymes in the herbivore gut micro-
biome. Despite this fact, the infancy in understanding
about the rumen microbial genetic diversity and a lack
of suitable screening culture techniques has limited the
exploitation of multiple promising enzymes. To date, less
than 5% of the microorganisms on Earth are being cul-
tivated using traditional laboratory techniques (i.e., great
plate count anomaly) [9]. Owing to this documented
disparity between cultivable and insitu diversity, a huge
biodiversity of microbial community is inevitably mis-
read. e recent advancement of metagenomics strategy
has obtained great popularity for the culture free recov-
ery of near complete microbial genomes from complex
environmental niches.
With the development of metagenomics, meta-tran-
scriptomic and metaproteomic, numerous studies of
the gut microbiome of wood feeding insects, termites,
ruminant animals (horses, cattle) have been reported
with the discovery of diverse cellulolytic enzymes [10–
15]. In 2011, Hess et.al reported that only 0.03% of the
assembled rumen metagenome had hits to sequenced
organisms [16]. Since then, thousands of bacterial
metagenomes have been sequenced and deposited into
public repositories. In 2018, Stewart etal. assembled 913
draft bacterial and archaeal Metagenome-Assembled
Genomes (MAGs) from an extensive dataset of rumen
metagenomic sequences obtained from 43 Scottish cattle
[17]. In the work conducted by Seshadri etal., they intro-
duced the Hungate1000 collection, which comprises 410
culturable archaeal and bacterial genomes. Remarkably,
their analysis revealed that 336 of these organisms were
detected in rumen metagenomic datasets [18]. In their
comprehensive analysis, Li et al. uncovered 13,825,880
non-redundant bovine rumen prokaryotic genes, nota-
bly dominated by functional species specializing in the
degradation of plant cell wall materials and methane
production [19]. Variation in diet, morphology, physi-
ology substrate availability and genetic makeup results
diversity in the GIT (gastrointestinal tract) microbi-
omes. In a recent comparative metagenomics investiga-
tion of rumen ecosystems, conducted by Glendinning
etal., a total of 391 MAGs were constructed across vari-
ous ruminant species, including cows, buffaloes, sheep,
and reindeer. is study unveiled substantial distinctions
in ruminal microbiomes, as evidenced by variations in
taxonomic composition and the presence of CAZymes
genes [20]. In a separate investigation conducted by Han
etal., the study delves into the influence of rumen degra-
dable starch (RDS) levels on gut microbiota diversity
and carbohydrate-active enzymes (CAZymes) in dairy
goats. eir findings underscore that a high RDS diet is
correlated with gastrointestinal health concerns, includ-
ing inflammation, mucosal damage, and changes in gene
expression [21]. Concurrently, investigations employ-
ing 16S rRNA analysis to investigate the phylogenetic
diversity and community structure of African rumi-
nants, yaks, deer, sheep, cattle, and reindeer have con-
sistently revealed the significant influence of both diet
and host genotype in shaping the composition and traits
of the rumen microbiome [22–25]. Even so, metagen-
omic sequences from the rumen continue to yield novel
and unique sequences that are distinct from those found
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Page 3 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
in public databases [26]. Moreover, only limited works
have reported the cloning of genes encoding glycosyl
hydrolases inhabiting goat rumen bacterial metagen-
omes and their diversity and metabolic functions with
respect to cellulosic biomass degradation. In this study,
we encompass an analysis of goat rumen bacterial diver-
sity exploiting a sequence driven metagenomic approach.
Furthermore, the potential candidate genes encoding for
cellulolytic and xylanolytic enzymes were further cloned
and expressed to perform biochemical characterization
of enzyme functionality.
Methods
Rumen sample collection andmetagenomic DNA isolation
Rumen fluid was obtained from eight 1–2-year-old male
meat goats when they were slaughtered at the goat farm
at Langston University, Oklahoma. Goats were fed on a
natural diet and hay [27]. (e rumen fluid was provided
by Dr. Puchala at Langston University; no live animals
were used in the study.) e rumen fluid was filtered
through three layers of cheese cloth. Filtrates were used
to extract genomic DNA following using the reagents
for bacterial DNA extraction in FastDNA SPIN Kit (MP
Biomedical, LLC, Solon, Ohio, USA) with modifications.
Genomic DNA was purified further using the GeneClean
Spin Kit (MP Biomedical). DNA concentrations were
quantified with NanoDrop ND-1000 spectrophotometer
(ermo-Fisher, CA, USA). e quality of DNA (integ-
rity) was confirmed by analysis on 1.0% agarose gel. e
extracted genomic DNA was stored at -20°C until fur-
ther use.
Metagenomic DNA sequencing, assembly andannotation
For DNA sequencing, approximately 0.1 µg of the
metagenomic DNA sample was used to construct the
sequencing library using Nextera DNA Sample prep kits
(Illumina, San Diego, CA). e resulting libraries had a
range of fragments from approximately 200–400bp and
were quantified using a Qubit spectrofluorometer (Inv-
itrogen, CA). ree libraries were prepared from goat
rumen metagenomics DNA samples namely Bct_789,
Bct_5121, and Bct_5122. e Bct_789 library was
sequenced on an Illumina HiSeq 2000 using TruSeq SBS
kit v3 for paired end 100bp sequencing; the Bct_5121
and Bct_5122 libraries were sequenced on an Illumina
Hiseq 2500 for paired end 125bp sequencing respectively
(Genomics Facility, Cornell University). e three librar-
ies generated a total of 435 gb reads. e raw reads were
deposited in the NCBI Sequence Read Archive (SRA)
under accession number SRX2267715 for Bct_789, and
SRX2267714 for Bct_5121, and Bct_5122.
e raw reads were processed using Cutadapt 4 pro-
gram, which include trimming, filtering (-q 15,15
–trim-n -m 31 –pair-filter = any) and removal of adapter
sequences (-b CAA GCA GAA GAC GGC ATA CGA GAT
CTA GTA CGG TCT CGT GGG CTCGG). e result-
ant high-quality reads were assembled using three kmer
sizes (-k 35, 55, 75) in SPAdes [28, 29]. Annotation of the
SPAdes assemblies was using the Prodigal gene predic-
tion programs and Diamond searches against UniProt
Bacterial sequences (only the top matching in each scaf-
fold was listed) [30, 31]. Metaphlan and Graphlan were
used to produce a phylogenetic classification across
all three datasets [32]. All the computational analysis
were completed by using pipeline from the Pittsburgh
Blacklight Supercomputer (Pittsburgh Supercomputing
Center, Pittsburgh, PA, https:// www. psc. edu/).
Phylogenetic taxonomy andfunctional gene classication
e high-quality reads from Bct_789 were also subjected
to Velvet (kmer size = 79) and SSPACE followed by CAP3
for assembly [33]. e assembled scaffolds were submit-
ted to DOE-JGI for the Metagenome Annotation Pipeline
(MAP v4) [34]. is annotation process encompasses the
prediction of various elements, including CRISPR ele-
ments, non-coding and protein-coding genes. Briefly, the
CRT and PILER-CR v1.06 tools were used for CRISPR
element identification; a combination of Hidden Markov
Models (HMMs) and ab initio gene calling algorithms
was used for protein-coding genes and non-coding RNA
genes identification; tRNAscan SE-1.3.1 was employed
for tRNA prediction; hmmsearch tool from HMMER
3.1b2 was used for ribosomal RNA genes (5S, 16S, 23S)
prediction; a consensus approach that combines the
results of four ab initio gene prediction tools prokary-
otic GeneMark.hmm (v. 2.8), MetaGeneAnnotator (v.
Aug 2008), Prodigal (v. 2.6.2), and FragGeneScan (v. 1.16)
was used for protein-coding gene prediction. Functional
annotation is performed by associating protein-coding
genes with Clusters of Orthologous Groups (COGs)
employing RPS-BLAST 2.2.31. Based on the COG clas-
sification in DOE-JGI Integrated Microbial Genomes
(IMG, https:// img. jgi. doe. gov/), the annotated genes
were classified into 26 COG functional categories. Puta-
tive endo-glucanase, exo-glucanase, and beta-glucosidase
for cellulose degradation, endo-beta xylanase, beta-
xylosidase for hemi-cellulose degradation were retrieved
from carbohydrate transport and metabolism group of
genes (279,864 gene count annotated).
Gene cloning withTOPO cloning system
e gene-specific primers for cellulase and hemi-cellulase
genes were designed using OligoPerfect TM Designer
(https:// tools. lifet echno logies. com/ conte nt. cfm? pageid=
9716, Table S1). In total, 14 cellulase and hemicellulase
genes were cloned from the goat’s rumen metagenomic
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Page 4 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
DNAs. PCR products were separated on 0.7% agarose
gels. e DNA fragments of expected sizes were excised
and purified from the gel using the QIAquick Gel Extrac-
tion Kit (Cat. No. 28704). e amplified genes were sub-
sequently ligated to pET101 vector (Invitrogen, CA) and
transformed into E. coli TOP10. Sanger sequencing was
used to confirm the sequences of cloned gene. After the
confirmation of 100% identity, these cloned sequences
were submitted to the NCBI databank (http:// www. ncbi.
nlm. nih. gov).
Recombinant protein over‑expression andcharacterization
e pET101 plasmids containing full-length open read-
ing frames of the cloned genes were transformed into
E.coli BL21 (DE3). e overnight BL21 culture was inoc-
ulated into LB with ampicillin and incubated for 2–3h at
37°C with agitation at 200rpm until the culture’s absorb-
ance OD600 = 0.6–0.8. At this point, 0.6mM IPTG was
added to induce protein expression. Following a subse-
quent 5–6h of post-induction at approximately 37°C,
the cells were harvested through centrifugation at 6,000X
g for 5min. To obtain crude protein, the cells were resus-
pended in a 100 mM HEPES buffer (pH 7.5) and sub-
jected to sonication with three 30-s bursts separated by
1-min intervals, utilizing an amplitude of 65%. Crude
protein samples were then mixed with 2X Laemmli Sam-
ple Buffer (BioRad) containing 5% β-mercaptoethanol.
e protein samples were separated on a 10–20% sodium
dodecyl sulfate polyacrylamide electrophoresis (SDS-
PAGE) gel. e molecular weight (size) of the proteins
was confirmed using Colloidal Blue Staining (Invitrogen).
To confirm the enzymatic activity of the recombinant
proteins, fresh bacterial culture was directly inoculated
into assay plates containing suitable substrates: carboxy-
methyl cellulose sodium salt (CMC) for endoglucanase
and xylan for endo-1,4-beta xylanase. en the plates
were incubated at 37°C for next 48h. After incubation,
the cellulolytic/xylanolytic activities were assayed using
the Congo Red staining method [35, 36].
To quantify the enzymatic activity, freshly grown bacte-
ria were lysed. And supernatant containing crude protein
was tested for its ability to hydrolyze CMC, and xylan oat
spelt, a substrate for the activity assay of endoglucanase
A and endo-1,4-beta xylanase respectively. e reduc-
ing sugar released upon the hydrolysis of sugar polymers
was determined using 3,5-dinitrosalicyclic acid (DNS)
method [37]. e reducing sugar content was measured
spectrophotometrically at 540nm (Milton Roy Spectro-
photometer, Model 601). One unit of enzymatic activ-
ity was defined as the amount of enzyme that liberates
1μmol of reducing sugar from the substrate per minute
under the above-mentioned assay conditions.
To determine the optimum pH, the recombinant crude
enzyme was incubated at 50°C for 45min at pH 4.0–6.0
(sodium acetate buffer), pH7.0–8.0 (sodium phosphate
buffer) and pH 9.0–10.0 (Tris–HCl buffer). e optimum
temperature for endoglucanase A was determined by
assessing enzyme activity in the range of 20–70°C using
CMC at 1% following a 45-min incubation at pH 6.0 (in a
sodium acetate buffer). e same approach was employed
for endo-1,4-beta xylanase, with the only adjustment
being the pH set to 10.0 (in a Tris–HCl buffer). e pH
stability was determined after keeping the enzymes at dif-
ferent pH at 50°C for 24h. e temperature stability was
analyzed following the pre-incubation of endoglucanse A
at pH-6.0 and endo-1,4-beta xylanase at pH-10.0 within a
temperature range of 20–70°C for 1h respectively before
further enzymatic activity test [38, 39].
Domain analysis andhomology modeling
ofendoglucanase Aandendo‑1,4‑beta xylanase
e analysis of protein domain architecture was per-
formed using SMART program (http:// smart. embl- heide
lberg. de/). For phylogenetic analysis, 26 endoglucanase
genes and 25 endo-1,4-beta xylanase genes were selected
respectively from the NCBI, CAZY, UniProt and PDB
databases [40], which cover a range of microorgan-
ism from bacteria, fungi, archaea, virus and unclassified
organisms. e hit sequences were then aligned using
neighbor-joining algorithm and P-distance model with
the bootstrap simulation in MEGA X [41]. Furthermore,
bootstrapping with resampling method of Felsenstein
and 1000 bootstrap replicates was done in order to exam-
ine the robustness of the phylogenetic tree topology [42].
Multiple sequence alignments of the target proteins
(endoglucanase A/ endo-1,4-beta xylanase) against their
selected homology proteins were performed with the
Clustal Omega software (https:// www. ebi. ac. uk/ Tools/
msa/ clust alo/). Furthermore, the sequence similari-
ties and structural information from the aligned protein
sequences were rendered through ESPript 3.0 analysis
software package (http:// espri pt. ibcp. fr/ ESPri pt/ cgi- bin/
ESPri pt. cgi).
e tertiary structures of endoglucanase A and endo-
1,4-beta xylanase was predicted using homology mod-
eling in Swiss Model (https:// swiss model. expasy. org/)
[43]. In total, 50 different template structures available in
protein data bank (PDB) were tested as template for the
3D model of endoglucanase A. e template used for the
prediction of the 3D structure of the recombinant endo-
glucanase A is the available crystal structures of ligand
bound PbGH5A (glycoside hydrolase; PDB ID: 5D9N)
from Prevotella bryantii (PbGH), which shares about 44%
amino acid sequence identity [44]. Similarly, the template
used to generate the homology model of endo-1,4-beta
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Page 5 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
xylanase is an available crystal structure of endo 1, 4
beta D-Xylanase 10B (Xyn10B) (PDB ID: 2WYS) from
Clostridium thermocellum.
To validate the predicted 3D structure from SWISS-
MODEL, Ramachandran plot was analyzed using RAM-
PAGE. e predicted structure was analyzed based on
the global model quality estimation (GMQE) score. e
accuracy of the predicted model of endoglucanase A
with GMQE score of 0.71 was evaluated by Ramachan-
dran plot using the RAMPAGE server (http:// mordr ed.
bioc. cam. ac. uk/ ~rapper/ rampa ge. php) [45]. e infor-
mation about the fitness and validation of the predicted
recombinant protein model was further confirmed using
the Verify3D (http:// servi cesn. mbi. ucla. edu/ Verif y3D/).
Meanwhile, secondary structure of the predicted model
of the enzyme was determined by using online available
server STRIDE (http:// webclu. bio. wzw. tum. de/ cgi- bin/
stride/ strid ecgi. py) [46]. e prediction of salt bridges
(distances ≤ 3.2A) was performed using visual molecular
dynamics (VMD, version 1.9.3) [47].
Results
Metagenomic DNA assembly, microbial taxonomy
andDiamond annotation
As shown in Table 1, the raw reads generated are
456,435,541*2 for Bac_5122, 176,691,539*2 for Bct_5121,
and 216,313,953*2 for Bct_789. In total, there were
1,698,882,066 raw reads generated from the sequenc-
ing libraries. e high-quality reads generated using
Cutadapt include: 439,742,222*2 in Bct_5122 sample,
174,079,701*2 in Bct_5121 sample, and 205,548,701*2 in
Bct_789 sample. ree different kmer sizes including 35,
55, and 75 were used in SPAdes assembly, and kmer = 75
results in the best assembly scaffolds. e total number
of scaffolds in Bct_5122 was 9,329,048, in Bct_5121 was
5,253,641, in Bct_789 was 4,842,139. e largest scaf-
folds were around 200,000–220,000bp, and the number
of scaffolds with length over 20,000 were around 6,000 in
all three samples.
Metaphlan and Graphlan were used to perform phy-
logenetic classification across the three datasets gener-
ated from the three libraries (Fig.1). Bacterial taxonomic
profiling indicated that at phylum level, Firmicutes, Bac-
teroidetes, and Fibrobacteres were the dominant bacteria
presenting in the goat rumen, which accounts for around
90% in total among others (Fig.1a). In total, there were
18 bacterial orders and 1 archaeal order comprised with
40 species that were detected in goat rumen samples
(Fig. 1b). At species level, Mathanobrevibacter_unclas-
sified (2.75%, Archeae) was the major Archeae species;
Butyrivibrio_unclassified (37.8%, Clostridiales), and
Prevotella ruminicola (22.7%, Bacteroidales), Fibrobacter
succinogenes (15.5%, Fibrobacterales), Butyrivibrio pro-
teoclasticus (5.8%, Clostridiales), Desulfovibrio desulfu-
ricans (5%, Desulfovibrionales), Bacteroides_unclassified
(3.5%, Bacteroidales) Ruminococcus albus (2%, Clostridi-
ales) were the predominant bacterial species present in
goat’s rumen (Supplement Table S2). Some of these bac-
terial species were also identified as the chief produc-
ers of CAZymes in goat’s rumen ecosystem for cellulose
degradation. Archaea Methanobacteria, which belong
to methane producing ruminal Methanogens were also
identified in the assembled sequences.
Diamond searching against UniProt Bacterial
sequences was performed on all the three datasets
(only the top matching in each scaffold was listed).
There were 3,334,049, 5,437,719, and 7,901,185 genes
identified in Bct_789, Bct_5121, and Bct_5122 distinc-
tively. In all three samples, a total of 19,780 glucanase
and 43,692 beta-glucosidase genes were detected,
indicating the high abundance of enzymes involved
in cellulose degradation. Similarly, 20,881 xylanase
and 18,295 xylosidase genes were identified, indi-
cating the high capability of goat rumen bacteria in
hemicellulose/xylan degradation. Additionally, 1,123
pectin methylesterase, 7,779 pectate lyase, and 5,852
polygalacturonase genes were identified, suggesting
the potential for pectin degradation (Table2). Across
all three datasets, a total of 3,327 bacterial strains
were annotated with genes involved in the degradation
of cellulosic biomass. Among these strains, a higher
proportion were detected to possess cellulase genes,
while a smaller number had genes involved in pectin
degradation. Notably, a combined total of 327 bacte-
rial strains were found to harbor functional genes for
the degradation of plant fiber (comprised with cellu-
lose, xylan, and pectin). The analysis revealed the pres-
ence of all seven enzymes (mentioned above) in eight
Table 1 Goat rumen bacterial (Bct) metagenome sequencing assembly
Datasets Size (bp) Raw reads*2 (PE) Reads after ltering Total No. of scaolds Largest Scaold No. of
scaolds > 20,000
Bct_5122 125 456,435,541 439,742,222 9,329,048 201,713 2,101
Bct_5121 125 176,691,539 174,079,701 5,253,641 222,488 1,946
Bct_789 100 216,313,953 205,548,701 4,842,139 212,207 1,951
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Page 6 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
bacterial species, namely Bacteroidals bacterium, Bac-
teroides sterorirosoris, Butyrivibrio proteoclasticus,
Butyrivibrio sp INIIa14, Butyrivibrio sp Su6, and three
species of Prevotella.
DOE_JGI annotation
e assembled scaffolds of Bct_789 were submitted to
the Integrated Microbial Genomes (IMG) for annotation
with the Img taxon object ID # 3300001425. ere were
Fig. 1 Goat rumen microbial community analysis using Metaphlan and Graphlan. a Approximately 96.6 -97.2% of fragments were assigned
to bacteria, and 2.8–3.4% belonged to Archaea. The major phylum were Firmicutes (45–48.7%), Bacteroidetes (24.5–28.5%), and Fibrobacteres
(14.1–16.5%). b The microorganisms annotated in all three datasets were combined. In total, 18 bacterial orders and 1 archaeal order comprised
with 40 species were identified
Table 2 Gene counts for genes in cellulose, hemicellulose and pectin degradation using Diamond annotation
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 7 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
10,024,714 sequences subjected to annotation analysis.
e annotation detected 748 CRISPR counts, 2,261 16s
rRNA, and 10,276,848 protein coding genes (accounts for
99.86% of annotated sequences), out of which, 3,054,241
of the genes belong to the Cluster of Orthologous Groups
(COG, 30% of annotated sequences) and 2,236,087 genes
were placed under the Pfam protein family domains
(Table3).
e 26 COG categories include general function pre-
diction (11.62% of gene count), amino acid transport
and metabolism (9.16% of gene count), carbohydrate
transport and metabolism (8.3% of gene count), repli-
cation, recombination and repair (8.48% of gene count)
and translation, ribosomal structure and biogenesis
(8.18% of gene count), and cell wall/membrane/enve-
lope biogenesis (6.98% of gene count). e total gene
count for carbohydrate transport and metabolism was
279,864, which was the database to screen CAZymes
for fiber digestion (Fig.2, Table S3).
In goat’s rumen, the degradation of plant fibers is
performed under the action of microbial enzymes.
For the cellulolytic genes, carbohydrate transport and
metabolism GO category includes 347 endo-1,4-beta-
D-glucanase genes (COG3405), 14 exo-beta-1,3-glu-
canase genes (COG5309), 1579 beta-glucosidase genes
(COG2723) and 26 cellobiase genes (COG5297) for
cellulose degradation; 3115 alpha-L-arabinofuranosi-
dase genes (COG3534), 1753 endo-1,4-beta xylanase
genes (COG3693), peptidoglycan/xylan/chitin dea-
cetylase (COG0726) and 4475 beta-xylosidase genes
(COG3664/3507) for hemicellulose degradation; and
876 pectin methylesterase genes (COG4677), 2894
polygalacturonase genes (COG5434), 478 pectate lyase
genes (COG3866) for pectin degradation.
Table 3 Statistics of the assembled sequences annotation using
DOE-JGI pipeline
Number % of Assembled
Number of sequences 10024714 100.00%
CRISPR Count 748
Genes
RNA genes 14680 0.14%
rRNA genes 8545 0.08%
16S rRNA 2261 0.02%
23S rRNA 5291 0.05%
tRNA genes 6135 0.06%
Protein coding genes 10276848 99.86%
with COG 3054241 29.68%
with Pfam 2236087 21.73%
COG Clusters 4589 99.09%
Pfam Clusters 6355 33.14%
Fig. 2 COG categories in DOE-JGI annotation
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Page 8 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
Out of 10,276,848 protein coding genes, 3,054,241
genes were identified with matching COG categories.
ose COG categories for amino acid transport and
metabolism; and carbohydrate transport and metabo-
lism; and replication, recombination and repair were
annotated with the highest number of gene counts.
Gene cloning andrecombinant enzyme characterization
e five novel cellulase/xylanase genes namely endo-
1,4-beta xylanase, endoglucanase A, beta-glucosidase
A, endo-1,6 beta-D-glucanase, and endoglucanase E
were cloned. ese genes have been deposited in the
NCBI GenBank databases under accessions KP851788,
KP851789, KP851790, KP851791, and KP851792 respec-
tively (Table S4). Two of the genes endo-1,4-beta xyla-
nase and endoglucanase A were successfully transformed
into E. coli BL21(DE3) and over-expressed with induc-
tion of IPTG. Proteins from cell lysates were separated on
SDS-PAGE gel; the protein bands matched the expected
molecular weight of the recombinant proteins, thus con-
firming the over-expression of the recombinant proteins
in the bacterial clones (Fig. S1).
e activity of the recombinant enzymes was analyzed
using the Congo red staining method. As shown in Fig.3,
the Congo red stained plates a and c (inoculated with
recombinant bacterial colonies) exhibited a clear halo
zone showing endoglucanase and endo-1,4-beta xylanase
activities; on the two control plates (b, d) which were not
inoculated with the bacterial inoculation, no substrate
degradation was seen.
e optimal enzyme activity of the crude recombinant
endoglucanase A and endo-1,4-beta xylanase was ana-
lyzed at various pH and temperature. e optimum pH
and temperature for endoglucanase A were pH 6.0 and
50°C (Fig.4a, b). e enzyme endoglucanase A displayed
a higher thermostability which retaining above 50% of
its activity at temperature 20–60°C after 1-h incubation
(Fig.4b). However, its pH stability is relatively low, the
enzyme activity at pH-4.0 and pH8.0–10.0 were severely
decreased after incubation at 50 °C for 24 h (Fig. 4a).
Within our testing range, the optimal enzymatic activity
for endo-1,4-beta xylanase was observed at pH 10 and
a temperature of 50°C. However, it’s worth noting that
enzyme activity was not evaluated at pH levels greater
than 10 (Fig.4c, d). Similarly, the enzyme endo-1,4-beta
xylanase retained over 50% activity at temperature rang-
ing from 20–60°C after 1-h incubation (Fig.4d). Moreo-
ver, it retained about over 50% of its enzymatic activity at
pH 5–10 after 24-h incubation at 50°C (Fig.4c).
Sequence andphylogenetic analysis ofendoglucanase
Aandendo‑1,4‑beta xylanase
SMART protein sequence analysis stipulated that the
putative enzyme endoglucanase A had a cellulase domain.
A total of 26 endoglucanase protein sequences from the
range of bacteria, fungi, Archaea, virus and unclassified
organism were selected for the phylogenetic analysis.
e phylogenetic analysis of endoglucanase A showed
that it is closely related with the protein sequences from
Prevotella ruminicola (WP074832387.1, Fig.5a). Multi-
ple alignments of the endoglucnase A with its homolo-
gous proteins in Prevotella ruminicola (WP074832387.1),
Bacteroidales bacterium (HBA12588.1), Bacteroides
xylanisolvens (WP117683893.1), Ruminococcaceae bac-
terium (A0A1G4QNM4) and Prevotella bryantii (PDB:
5d9M) indicated that the inferred amino acid sequence
of a GH 5 family domain and the active site of the con-
served domain (in green rectangle) with predicted cata-
lytic residue (arrow pointed) in endoglucanase A were
aligned with those of the homologous enzymes (Fig.5b).
Moreover, the protein shared less than 55.87% amino
acid sequence identity with glycoside hydrolase family
5 protein from Prevotella ruminicola and 51.26% from
Alloprevotella sp.
Fig. 3 Plate enzymatic assay of endoglucanase A and endo-1,4-beta xylanase. a-d Plate assay determination of cellulolytic and xylanolytic activity
by Congo red staining method; a and c were inoculated with BL21(DE3) harboring endoglucanase A and endo-1,4-beta xylanase respectively; b
and d are negative control with inoculation of bacterial harboring empty vector
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Page 9 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
e SMART sequence analysis indicated that the endo-
1,4-beta xylanase had a Glycosyl hydrolase-10 domain.
Similarly, a total of 25 endo-1,4-beta xylanase proteins
were selected for the neighbor-joining phylogenetic
analysis. e analysis depicts the evolutionary relation-
ship between endo-1,4-beta xylanase and associated pro-
teins, which revealed that the target enzyme from goat
rumen is closely related to the homology protein from
Ruminococcus albus (WP074961015.1) and Ruminococ-
cus flavefaciens (WP074742329.1, Fig.5c). e schematic
structure of multiple sequence alignment indicating
that the inferred amino acid sequence of a GH 10 fam-
ily domain in endo-1,4-beta xylanase was aligned with
those of selected homologous enzymes from the follow-
ing microorganisms: Clostridium thermocellum (PDB
ID: 2WYS), Ruminococcus callidus (WP_021681465.1),
Ruminococcus albus (WP_074961015.1), Rumino-
coccus flavefaciens (WP_074742329.1), Polyplastron
multivesiculatum (CAB65753.1), Ruminococcus cham-
panellensis (WP_054685651.1). Signature sequences (in
green rectangle) with detection of predicted catalytic
residue (black arrow) were well aligned among all sam-
ples (Fig.5d). Moreover, the protein shared around 59%
amino acid sequence identity with 1,4-beta xylanase gly-
cosyl hydrolase family 10 protein from Ruminococcus
albus and 57% amino acid sequence identity with 1,4-
beta xylanase family 10 protein from Ruminococcus flave-
faciens (WP074742329.1).
Homology modelling and3D structure prediction
e tertiary structures of endoglucanase A and endo-1,4-
beta xylanase are shown in Fig.6a, c. Ramachandran plot
indicates the quality and stereochemistry of the structure
that identifies the torsion angles of the residues in favored
regions, allowed regions and outliers. In the case of endo-
glucanase A, 92% of the residues had torsion angles in
favored regions, 5.9% residues were in allowed regions
and only 2.1% of the residues were the outliers (Fig.6b).
Similarly, for endo-1,4-beta xylanase, among 293 resi-
dues, 92.7% of the residues were in favored regions, 6%
Fig. 4 Enzymatic activity and stability of endoglucanase A and endo-1,4-beta xylanase. The optimized activity and stability of the recombinant
endoglucanase A and endo-1,4-beta Xylanase were determined at different temperatures and pH values. a Effects of pH on the endoglucanase
A enzyme activity at 50 °C. b Effects of temperature on the endoglucanase A activity within a temperature range of 20–70 °C, at pH 6.0. c Effects
of pH on the endo-1,4-beta xylanase enzyme activity at 50 °C. d Effects of temperature on the endo-1,4-beta xylanase activity within a temperature
range of 20–70 °C, at pH 10.0
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Page 10 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
residues were in allowed regions and only 1.3% of the res-
idues were in the disallowed regions (Fig.6d).
STRIDE results suggested most of the secondary struc-
tures as coils and turns in the predicted protein struc-
ture. However, nine α-helices, ten β-strands and four 310
helices were also present in the predicted structure of the
recombinant endoglucanase A. Similarly, the secondary
structure of endo-1,4-beta xylanase comprised of eight
α- helices, nine β-strands and three 310 helices along with
coils and turns. In addition, the predicted model of the
recombinant endoglucanase A and endo-1,4-beta xyla-
nase was observed to be constituted of nineteen and thir-
teen salt bridges respectively (distances ≤ 3.2A).
Discussion
Metagenome screening is an invaluable technique for
exploring the vast biodiversity of nature and uncover-
ing novel enzymes, as it allows for direct analysis with-
out the limitations in cultivation-based methods. e
mining of a metagenomic library has facilitated the
identification of microbial diversity and novel enzymes
(cellulase and xylanase) from a variety of environmental
samples, including soil, hot spring, termite’s gut, rumen
of dairy cow [48–51]. Earlier study identified that exper-
imental warming and the resultant decrease in soil
moisture has a significant impact on microbial biodi-
versity by reducing the richness of bacteria (9.6%). Fur-
thermore, a recent study successfully mined the camel
rumen metagenome to identify a novel alkali-thermo-
stable xylanase that could enhance the conversion of lig-
nocellulosic biomass [52].
e goat rumen is home to a diverse community of
microorganisms, including bacteria, protozoa, and fungi,
which collectively contribute to the digestion of fibrous
plant materials and the extraction of essential nutrients
[53]. ese microbes are adept at breaking down com-
plex carbohydrates, such as cellulose and hemicellulose,
into simpler sugars and short-chain fatty acids through
fermentation processes [54]. is breakdown not only
provides goats with a vital source of energy but also
aids in the absorption of nutrients, including proteins
and vitamins. Moreover, the microbial population in
the rumen helps maintain the pH balance, ensuring effi-
cient digestion and preventing conditions like acidosis
Fig. 5 Phylogenetic and multiple alignment analysis of endoglucanase A and endo-1,4-beta xylanase. a, c Neighbor-joining phylogenetic
tree of endoglucanase A and endo-1,4-beta xylanase based on protein sequences from various organisms. Scale bar corresponds to a genetic
distance of 0.10 substitution/site. b, d Multiple alignments of the endoglucnase A domain (GrE) with other homologous protein GH5 domains
and the endo-1,4-beta xylanase with other homologous protein GH10 domains
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 11 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
[55]. Bacterial population is the most abundant in the
rumen ecosystem comprising 1010 to 1011 cells/ml [56].
Studies have shown that the composition and diversity
of rumen microbes can be influenced by various fac-
tors, including diet, genetics, and environmental condi-
tions, highlighting the intricate relationship between
rumen microbiota and goat health and nutrition [57, 58].
Understanding and optimizing this microbial ecosystem
is crucial for enhancing goat productivity and overall
well-being. For this reason, there is an utmost need for
the comprehensive exploitation of goat rumen bacterial
population. e goats that were used to extract the rumi-
nant fluids in this study were on diet rich in cellulose and
xylan. Here, we utilized genome-centric metagenomics
strategy to explore diverse phylogeny, cellulose degrad-
ing potential bacterial enzymes housed in goat rumen.
Fig. 6 3D structure and overall composition analysis. Predicted 3D structure and overall composition (including alpha-helix, beta-sheet, bridge,
turn and coil and 3–10 helix) of endoglucanase A (a), and endo-1,4-beta xylanase (c). Ramachandran plot analysis demonstrates the different
residues falling in general favored (blue), general allowed (light blue), and glycine residues favored (yellow), glycine residue allowed (light yellow)
for endoglucanase A (b), and endo-1,4-beta xylanase (d)
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Page 12 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
We successfully identified 19,780 glucanase and 43,692
beta-glucosidase for cellulose degradation, 20,881 xyla-
nase and 18,295 xylosidase genes for hemicellulose/ xylan
degradation, and 1,123 pectin methylesterase, 7,779 pec-
tate lyase, and 5,852 polygalacturonase for pectin diges-
tion in 3,327 bacterial strains from goat rumen samples.
Eight bacterial strains were identified with a full spec-
trum of enzymes for cellulosic biomass digestion includ-
ing Bacteroidals bacterium, Bacteroides sterorirosoris,
Butyrivibrio proteoclasticus, Butyrivibrio sp INIIa14,
Butyrivibrio sp Su6, and three Prevotella species. Find-
ings from this study clearly confirmed the rich contain-
ment of cellulolytic genes/enzymes and microbes in the
goat’s rumen fluids. Our data concur with reports that
the rumen microbiomes of browse-feed animals contain
a high variety of glycoside hydrolases indispensable for
degrading plant cell wall materials [59–62]. In this goat
rumen sample, Butyrivibrio proteoclasticus, Prevotella
ruminicola, and Fibrobacter succinogenes were identi-
fied as the predominant bacteria in the goat’s rumen
microbiomes. ese bacterial species are known for the
ability to efficiently degrade and use cellulose as a car-
bohydrate source, which could be the primary microbes
for fiber degradation in goats as well as other ruminant
animals [63–65]. In addition, Butyrivibrio proteoclasticus
previously known as Clostridium proteoclasticum dem-
onstrated the ability to convert linoleic acid into stearic
acid in sheep rumen, suggesting its significant role in
lipid metabolism [66]. Delgado’s study explored into the
rumen microbiota and feed efficiency traits of Holstein
cattle, shedding light on the fact that cattle with high
feed efficiency had a heightened presence of Bacteroi-
detes and Prevotella. ese results emphasize the criti-
cal role played by microbiota composition in influencing
feed utilization performance [67]. In research assessing
the impact of hainanmycin (HAI) and monensin (MON)
supplementation on ruminal protein metabolism and the
populations of proteolytic bacteria in Holstein heifers, a
notable increase in the abundance of Prevotella rumini-
cola was detected. is finding underscores the signifi-
cant role these bacteria play in protein metabolism [68].
Given that the productivity of meat and milk relies heav-
ily on the microbiota’s efficiency in breaking down plant
cell walls, and conversion into protein and lipids, the rec-
ognition of key rumen microbiota assumes a pivotal role
in shaping strategies aimed at optimizing rumen fermen-
tations for enhanced animal production.
In recent years, the search for novel biocatalysts with
lignocellulose degradation functionality has gained an
utmost attention. Fueled by the recent advancement of
‘omics’ techniques, numerous microbial enzymes have
been developed and exploited for various industrial
applications. For bio-fuel production as well as other
bioconversion processes in paper, textile, food indus-
tries, where different treatments such as hot water, steam
explosion, alkaline, solvent or acidic pretreatments are
employed before or during enzyme treatment, robust
enzymes that possess multiple extremophilic traits like
thermos-alkaliphilic, thermosacidophilic, or multi-func-
tionality characteristics have the potential to be particu-
larly beneficial players. Earlier investigations by Zhang
etal. unveiled a thermostable xylanase sourced from the
salt tolerant ermobifida halotolerans strain YIM90462.
is enzyme exhibited remarkable xylanase activity at pH
9 and 70°C, making it a compelling candidate for applica-
tions in pulp and paper bioleaching [69]. Additionally, a
single fosmid harboring a cellulase enzyme, sourced from
the buffalo rumen metagenomic library, exhibited excep-
tionally high cellulase activity, with its optimal operating
conditions at pH 5.5 and 50°C. is cellulase displayed
robust stability under acidic pH conditions, indicating its
promising suitability as a potential feed supplement for
broiler chicken [70]. In a separate study, Motahar etal.
uncovered an acidic-thermostable α-amylase enzyme,
PersiAmy2, cloned from the sheep rumen metagenome.
e recombinant PersiAmy2 expressed in E. coli BL21
(DE3) exhibited remarkable stability under diverse pH,
temperature, and maintained its efficacy even in the pres-
ence of various ions, inhibitors, and surfactants, which
can be promising candidate to enhance the quality of
gluten-free bread [71]. Combining metagenome screen-
ing with PCR-based methods has resulted in the direct
cloning of numerous new genes/enzymes from environ-
mental samples. In this study, we used a sequence-based
metagenomics dataset to screen cellulolytic and xylano-
lytic enzymes from uncultured bacteria in goat rumen
fluid. We then cloned and expressed two genes encoding
for endoglucanase A and endo-1,4-beta xylanase. e
biochemical function of the two enzymes was analyzed
by using carboxymethyl cellulose and oat xylan, respec-
tively, as a sole carbon source. is process for character-
ization of various cellulases and xylanases enzymes from
bacterial metagenomes in the goat rumen environment
serves as a theoretical framework for better understand-
ing of the regulation of cellulolytic enzyme production.
Multiple alignments of the endoglucnase A from goat
rumen bacteria with its homologous proteins with a
glycoside hydrolase family 5 (GH5) family domain indi-
cated that they shared only around 51–56% amino acid
sequence identity. Likewise, the alignment of the endo-
1,4-beta xylanase to its homologous proteins containing
a glycoside hydrolase family 10 domain (GH10) showed
that they shared only around 57–59% identity similar-
ity [72–74]. Salt bridges between catalytic residues play
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Page 13 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
a vital role in facilitating intramolecular electron transfer
(IET) by promoting interactions among catalytic residues
and substrate [75]. Notably, the recombinant endoglu-
canase A gene examined in this study contains nineteen
salt bridges. e endo-1,4-beta xylanase was detected
with thirteen salt bridges. e occurrence of these salt
bridges in various essential regions of the enzyme con-
tributes to its resilience under diverse extreme phys-
icochemical conditions [76]. is revelation underscores
the novelty of the enzymes cloned in this investigation,
emphasizing that they belong to previously uncharac-
terized species, indicative of their status as entirely new
enzymes characterized by enhanced activity and ther-
mostability. As for optimum pH, and temperature, our
findings are consistent with previous studies indicating
that the ideal temperature and pH for recombinant endo-
glucanases produced by cellulolytic rumen bacteria fall
within the pH range of 5.0–7.0 and temperature range of
40–50°C [70, 77–79]. In a previous study, recombinant
expression of endoglucanase from Bacillus licheniformis
ATCC 14580 in E. coli BL21 (DE3) resulted in an activ-
ity level of 1.5 U/ml under optimized conditions, using
carboxymethylcellulose as the substrate [80]. Similarly,
another endoglucanase, EG5B, derived from Paenibacil-
lus sp. IHB B 3084, was cloned and expressed in E. coli
BL21(DE3), exhibiting the highest enzymatic activity at
1.382IU/ml [81]. In both studies, crude enzyme extracts
were utilized for enzymatic activity analysis. In contrast,
in a separate research endeavor, endoglucanase CenC
from Clostridium thermocellum was purified before
enzyme activity analysis, revealing an activity of 30 U/
mg on CMC and 9 U/mg on avicel, respectively [82].
Remarkably, the endo-1,4-beta xylanase obtained from
this study exhibited an optimum activity at temperature
around 50°C and pH 10 (within test range). Various pre-
vious studies have characterized xylanase enzymes from
different sources, including goat rumen [83], marine bac-
teria [84], camel metagenomes [85], termite gut metage-
nomes [86], and yak rumen [87]. ese xylanases exhibit
moderate thermostability and display optimal activity at
temperatures around 50–60°C. Additionally, they tend
to have an optimal pH around 8.0 and are functional in a
pH range between 5.5 and 8.0. e recombinant xylanase
investigated in our study displayed remarkable activity
over a wide pH range, making it a promising candidate
for industrial processes that demand alkaline conditions.
In previous research, the endo-xylanase xynFCB, derived
from the thermophilic bacterium ermoanaerobacte-
rium saccharolyticum NTOU1, was subjected to exog-
enous expression and purification in E. coli BL21. is
enzyme exhibited its highest activity at 91 U/mg, when
oat spelt was employed as the substrate [84]. Similarly,
in a separate study, exogenous expression of the endo-β-
1,4-xylanase XylH, originating from the gastrointestinal
bacterium Microbacterium trichothecenolyticum HY-17,
revealed optimal xylanolytic activity at a high level of
97 U/mg when oat spelt served as the substrate [88].
While the enzymatic activity analysis conducted in this
study did not yield an exceptionally high hydrolysis rate,
it’s crucial to note that the enzyme preparation process
did not incorporate a purification step. Consequently,
the crude protein extraction included a mixture of vari-
ous enzymes, potentially influencing the accuracy of the
enzymatic activity evaluation.
Conclusions
In this study, we have demonstrated the process for
investigating and utilizing metagenome resources. e
findings from this study highlight the disproportion-
ately significant role that rumen microbes in cellu-
losic biomass degradation. e in-depth analysis of the
goat rumen bacterial metagenomes along with cloning,
enrichment enzymatic assay, and invitro enzyme char-
acterization could serve as a rich resource for the bio-
technology community engaged in unearthing novel
strategy for lignocellulosic biomass conversion into CH4
rich products or other targets. We have demonstrated
the process to clone novel genes from the metagenome
and producing and characterization of recombinant cel-
lulolytic enzymes. Designing consortia with both anaero-
bic bacteria and fungi could better aid in understanding
the diverse physio-chemical parameters while offering
knowledge base to create minimal systems for the bio-
chemical conversion of lignocellulose into value added
chemicals. While the current study did not assess the rel-
ative transcription levels of the identified CAZyme genes,
it is worth noting that the microbial consortia detected
could potentially encode a substantial number of
CAZyme-associated genes that are part of enzyme-teth-
ered systems. Even so, the dataset of goat rumen-derived
genomes described in this study, along with publicly
available rumen genomes, could serve as a valuable refer-
ence for future metagenomic investigations.
Abbreviations
CAZymes Carbohydrate-Active EnZymes
CMC Carboxymethyl cellulose sodium salt
COG Cluster of orthologous groups
DNS Dinitrosalicyclic acid
GH Glycoside hydrolase
GMQE Global model quality estimation
IPTG Isopropyl β-D-1-thiogalactopyranoside
PDB Protein data bank
SDS-PAGE Sodium dodecyl sulfate polyacrylamide electrophoresis
SRA Sequence Read Archive
VMD Visual molecular dynamics
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 14 of 16
Thapaetal. BMC Biotechnology (2023) 23:51
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12896- 023- 00821-6.
Additional le1: TableS1. Primers for gene cloning from goat rumen
bacterial DNA. TableS2. Microbial community analysis using Metaphlan.
TableS3. Gene counts of CAZymes annotated by DOE-JGI pipelines.
TableS4. Cellulase and hemicellulase genes deposited into NCBI data-
base with accession number. Figure S1. SDS-PAGE analysis of the recom-
binant proteins. (+) are crude extract of IPTG induced endo 1, 4 beta
xylanase (left) around 37kD and endoglucanase A (right) around 38kDa;
(+/-) are crude extract with no IPTG induction; (-) are an IPTG induced
crude extract of an empty vector (negative control).
Acknowledgements
We would like to thank Drs Charles Lee and Theodore Thannhauser at USDA/
ARS for their guidance in performing this research project. The authors wish to
thank Dr. Ryszard Puchala at Langston University for providing goat’s rumen
fluid samples.
Authors’ contributions
SZ and ST designed the study; ST, HL performed DNA extraction, gene cloning
and enzyme characterization; ST, HL, AR and ANK conducted bioinformatics
and data analysis; ST and HL wrote original draft; SZ, JO reviewed and edited
the manuscript. All authors have read and agreed to publish the final version
of the manuscript.
Funding
This work received support from the USDA-NIFA 1890 Capacity Building Grants
Program (2018–38821-27737 and 2010–38821-21598). And the Extreme Sci-
ence and Engineering Discovery Environment (NSF grant OCI 1053575 Specifi-
cally, it used Bridges systems which are supported by NSF award numbers ACI
1445606 at the Pittsburgh Supercomputing Center.
The work also received support through the XSEDE Extended Collaborative
Support Services and the XSEDE Campus Champions program.
Availability of data and materials
The raw reads were deposited in the NCBI Sequence Read Archive (SRA) under
accession number SRX2267715 and SRX2267714. The assembled scaffolds
were deposited to the NCBI with accession number VKOM0000000000.1,
VKOL000000000.1, and VKOK000000000.1 DOJ-JGI IMG annotation data can
be retrieved from https:// img. jgi. doe. gov/ cgi- bin/m/ main. cgi? secti on= Taxon
Detai l& page= taxon Detai l& taxon_ oid= 33000 01425.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1 Department of Agricultural and Environmental Sciences, College of Agricul-
ture, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN 37209,
USA. 2 Vanderbilt University Medical Center, 2215 Garland Ave, Nashville, TN
37232, USA. 3 Department of Biological Sciences, College of Life & Physical
Sciences, Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN
37209, USA. 4 Department of Computer Sciences, College of Engineering,
Tennessee State University, 3500 John A. Merritt Blvd, Nashville, TN 37209, USA.
5 Pittsburgh Supercomputing Center, 300 S. Craig Street, Pittsburgh, PA 15213,
USA.
Received: 17 March 2023 Accepted: 20 November 2023
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