Min-Sung Kwon1, Hee Eun Jo1,2, Jieun Lee1, Kyoung-Seong Choi3, Dohyeon Yu4, Yeon-Su Oh5, Jinho Park6, Hak-Jong Choi1. 1. Research and Development Division, World Institute of Kimchi, Gwangju 61755, Korea. 2. Department of Microbiology, Chonnam National University Medical School, Gwangju 61468, Korea. 3. College of Ecology and Environmental Science, Kyungpook National University, Sangju 37224, Korea. 4. College of Veterinary Medicine, Gyeongsang National University, Jinju 52828, Korea. 5. College of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University, Chuncheon 24341, Korea. 6. College of Veterinary Medicine, Jeonbuk National University, Iksan 54596, Korea.
Coronaviruses can cause respiratory and enteric infections in humans and other
domestic animals including pigs, chickens, and cattle. Bovine coronavirus (BCoV) is
an RNA virus belonging to the Coronaviridae family, and BCoV infection results in
the development of long-lasting or severe disease [1]. BCoV infection of cattle is highly prevalent globally, and the virus
is recognized as the causative agent of neonatal calf diarrhea, winter dysentery in
adult cattle, and respiratory infections in calves and feedlot cattle [2]. BCoV infection raises serious health
problems that impede weight gain or milk production in cattle of various ages,
leading to large economic damages in the dairy and beef cattle industries worldwide
[3]. BCoV infection occur via the
respiratory or fecal–oral routes, and BCoV isolates following both routes of
infection have shown similar genotypes [4].
After enteric infection, BCoV replicates in the epithelial cells of the small and
large intestines, destroys the villi, and causes degeneration and necrosis of the
crypt epithelium and petechiae, which collectively interfere with the absorption of
electrolytes and water [5]. This process leads
to dehydration, electrolyte imbalance (usually decreased sodium level and increased
or decreased potassium level), strong ion (metabolic) acidosis, increased production
of D-lactate, and a negative energy balance (nutrient malabsorption) [6]. These symptoms induce severe and often
bloody diarrhea in calves and can be life-threatening. Treatment for diarrhea mainly
focuses on correcting dehydration, electrolyte imbalance, and acidosis through fluid
therapy [7]. Prompt and appropriate treatment
via fluid therapy is imperative for successful recovery from diarrhea associated
with BCoV infection.The commensal gut microbiota plays important roles in maintaining host homeostasis
and health [8]. This host-gut microbiota
system also impacts the control of infectious diseases. The microbiota can directly
protect against infection by competing with pathogens at mucosal entry sites or by
releasing soluble molecules that inhibit pathogenic colonization, or can provide
indirect protection by stimulating host immune responses [9]. Thus, alteration of the gut microbiota has been associated
with a decreased effectiveness of the protective barrier against infection, which
can promote host infection [10]. Although
previous studies have focused on individual pathogens that induce calf diarrhea,
recent data have suggested that the gut microbiota plays an important role in
controlling and eliminating infectious diseases. Moreover, recent studies have
demonstrated dynamic changes in the gut microbiota composition in cattle under
various growth stages and conditions [11,12].However, despite the importance of the gut microbiota in modulating host health,
little is known regarding changes in the gut microbiota and their correlations with
physiological parameters in post-weaned calves between the diarrheic state and the
recovered state. Therefore, we compared the compositional changes in the fecal
microbiota before and after treatment in post-weaned calvesinfected with BCoV and
investigated possible correlations between certain microbiota and physiological
parameters before and after recovery.
MATERIALS AND METHODS
Animals and sampling
The study was performed in a Holstein farm located in Jiri Mountain, Korea. The
experimental samples were obtained from ten female Holstein calves aged between
117 and 138 days with diarrhea for ≥ 3 days. In this study, fecal samples
from selected animals were previously tested for the presence of common
diarrhea-causing pathogens, such as Escherichia coli K99,
Salmonella spp., Cryptosporidium spp.,
BCoV, bovine rotavirus, and bovine viral diarrhea virus, and as a result, only
BCoV was positively detected [13].
Sampling was performed twice from the same animals before and after 2 months of
treatment, once in October 2019 and once in December 2019. During the 2 months,
intravenous fluid therapy was conducted to avoid electrolyte imbalance and
dehydration related diarrhea. All post-weaned calves that previously had
BCoV-associated diarrhea were not detected BCoV and were diagnosed with health
by a veterinarian after 2 months of treatment. Fecal and serum samples were
frozen at −80°C or −20°C until they were processed
and analyzed. All animal procedures were performed according to ethical
guidelines and approved by the Institutional Animal Care and Use Committee of
Jeonbuk National University (JBNU 2016-00026).
Evaluation of physiological parameters
Serum biochemistry tests were performed to evaluate eight physiological
parameters (total serum protein, albumin, blood ureanitrogen, glucose, sodium,
potassium, chloride, and phosphorus) using a Catalyst One™
chemistry analyzer (IDEXX Laboratories, Westbrook, ME, USA).
Fecal DNA extraction and 16s rRNA gene sequencing library
construction
For bacterial gene sequencing, total DNA extraction was performed from frozen
feces using a FastDNA Spin Kit (MP Biomedicals, Irvine, CA, USA) following their
instructions. NanoDrop 2000 UV-vis spectrophotometer (Thermo Fisher Scientific,
Waltham, MA, USA) was used for measuring of final DNA concentration. For
amplification of the 16S rRNA gene, the 341F/805R primer pair targeting
the V3–V4 variable region were used for the process of polymerase chain
reaction (PCR). PCR was conducted as described conditions: denaturation at
94°C for 3 min; annealing at 28 cycles of 94°C for 30 s,
53°C for 40 s, and 72°C for 1 min; and a final elongation
step at 72°C for 5 min, and then PCR products purification of each
samples was conducted with the QIAquick PCR Purification Kit (Qiagen, Hilden,
Germany). After pooling of mixed amplicons, sequencing was carried out by using
the Illumina MiSeq Sequencing system (Illumina, San Diego, CA, USA).
Analysis of 16s rRNA sequencing data
The 16S rRNA gene amplicon sequencing was processed by the open-source software
pipeline, and raw reads were subjected to quality-control analysis, where
low-quality (< Q25) reads were filtered using Trimmomatic (version 0.32).
The filtered paired-end reads were joined into single sequences using PANDAseq.
Primer sequences were then trimmed at similarity cut-off of 0.8 using an
in-house program of ChunLab. Denoising of non-redundant reads were conducted
using DUDE-Seq. The EzBioCloud database was used to obtain taxonomic assignments
and to identify chimeric reads with best-hit similarity rate below 97%. The
sequences were clustered into observed operational taxonomic units (OTUs) at a
97% similarity using CD-HIT and UCLUST. Microbial diversity was analyzed using
CLcommunity software (version 3.46, ChunLab, Seoul, Korea). Linear discriminant
analysis (LDA) effect size (LEfSe) analysis was conducted using the Galaxy
framework (https://huttenhower.sph.harvard.edu/galaxy/) to identify
significantly enriched bacterial taxa in the feces of diarrheic calves between
before and after fluidic treatment, based on a p-value of
< 0.05 and an LDA score of > 2.0.
Statistical analysis
Spearman’s correlation coefficient analysis was conducted based on the
relative abundance of genus taxa with respect to blood-parameters. Correlation
with a p-value < 0.05 were selected to construct the
network map. All statistical analyses and graphical procedures were carried out
using GraphPad Prism 8 software (GraphPad, La Jolla, CA, USA).
RESULTS
Changes in blood-parameter values in post-weaned calves between the diarrheic
and recovered states
BCoV is a respiratory and enteric virus that is frequently isolated from fecal
samples of diarrheic calves [4]. In the
present study, fecal samples collected from ten post-weaned calves with diarrhea
before fluid therapy (referred to as the pre-treatment group) were positive for
BCoV. However, after 2 months of treatment, BCoV was not detected in the fecal
samples of the post-treatment group, and the symptoms of diarrhea were also
improved (Table 1).
Data from Chae et al. with CC-BY [13].Fecal appearance - normal (0); semi-solid (1); loose (2); watery
(3).BCoV, bovine coronavirus.Since electrolyte disturbances and metabolic changes are the most significant
consequences of diarrhea in calves [14],
blood-serum parameters were analyzed to compare the physiological conditions of
calves in the diarrheic and recovered states. The levels of blood-serum
parameters, such as glucose, sodium, and phosphorous, which showed a lower
concentration in post-weaned calves with diarrhea than in those that had
recovered, were significantly enhanced, whereas the chloride concentration in
the serum was significantly reduced after 2 months of treatment. However, total
serum protein, albumin, and BUN concentrations remained unaffected (Fig. 1). These data indicate that fluid
therapy effectively altered the physiological parameters, and that these changes
were related the recovery of diarrhea caused by BCoV infection.
Fig. 1.
Principal hematological and biochemical parameters in post-weaned
calves with BCoV-related diarrhea, before and after treatment.
Serum concentrations of total protein, albumin, BUN, glucose, and
electrolytes (sodium, potassium, chloride and phosphorus) were measured
in post-weaned calves with diarrhea, before and after treatment. BCoV,
bovine coronavirus; BUN, blood urea nitrogen.
Principal hematological and biochemical parameters in post-weaned
calves with BCoV-related diarrhea, before and after treatment.
Serum concentrations of total protein, albumin, BUN, glucose, and
electrolytes (sodium, potassium, chloride and phosphorus) were measured
in post-weaned calves with diarrhea, before and after treatment. BCoV,
bovine coronavirus; BUN, blood ureanitrogen.
Comparing the 16S rRNA gene-sequencing data in post-weaned calves between the
diarrheic and recovered states
To investigate changes in the gut microbiota structure of post-weaned calves in
the diarrheic and recovered states, we analyzed their gut microbiota using 16S
rRNA gene amplicon sequencing. A total of 2,052,580 reads were generated, with
an average of 102,629 reads per calf. The Good’s coverage of fecal
samples was > 99.45%, indicating that our sample coverage was
sufficiently high to analyze microbial diversity. Alpha diversity, as determined
using the observed OTUs, and Chao1 and Shannon indices, were significantly lower
in the post-treatment group than in the pre-treatment group. However, an
increased Simpson index was observed after 2 months of fluid treatment (Fig. 2a). We next measured beta diversity
using principal coordinates analysis based on the weighted fast UniFrac distance
matrix. The results showed that the gut microbiota in calves with BCoV-mediated
diarrhea clustered separately from those in recovered calves (Fig. 2b).
Fig. 2.
Comparison of gut microbiota profiles in post-weaned calves with
BCoV-related diarrhea, before and after treatment.
(a) Alpha-diversity (observed OTUs, and Chao1, Shannon, and Simpson
indices) in each microbiota, as determined by comparing diarrheic and
recovered calves. (b) Discriminant analysis of beta diversity among
different samples. Microbial alterations between diarrheic (green) and
recovered calves (red) are illustrated by the line or circle, and
individual data are also depicted. *p < 0.05.
(c) Bar chart representing the microbiota compositions at the phylum and
genus levels in post-weaned calves with diarrhea, before and after
treatment. Mean relative abundances of the main bacterial phyla and
genera (> 2.0% of all sequences) that were distinctive between
the diarrheic and recovered calves. BCoV, bovine coronavirus; OTUs,
operational taxonomic units.
Comparison of gut microbiota profiles in post-weaned calves with
BCoV-related diarrhea, before and after treatment.
(a) Alpha-diversity (observed OTUs, and Chao1, Shannon, and Simpson
indices) in each microbiota, as determined by comparing diarrheic and
recovered calves. (b) Discriminant analysis of beta diversity among
different samples. Microbial alterations between diarrheic (green) and
recovered calves (red) are illustrated by the line or circle, and
individual data are also depicted. *p < 0.05.
(c) Bar chart representing the microbiota compositions at the phylum and
genus levels in post-weaned calves with diarrhea, before and after
treatment. Mean relative abundances of the main bacterial phyla and
genera (> 2.0% of all sequences) that were distinctive between
the diarrheic and recovered calves. BCoV, bovine coronavirus; OTUs,
operational taxonomic units.The OTUs mapped to 28 phyla, 63 classes, 131 orders, 272 families, and 798
genera. The top eight phyla (Firmicutes, Bacteroidetes, Verrucomicrobia,
Actinobacteria, Saccharibacteria_TM7, Tenericutes, Spirochaetes, and
Proteobacteria) and the top 13 genera Ruminococcaceae_uc (unclassified genus in
the Ruminococcaceae family), Sporobacter,
Paeniclostridium, Bacteroidaceae_uc, Bacteroidales_uc_g,
Turicibacter, Romboutsia,
Christensenellaceae_uc, Clostridium, Lachnospiraceae_uc,
Eubacterium, Oscillibacter, and
Alistipes are displayed in Fig. 2c. These genera accounted for 80.78% and 83.59% of the reads
in the pre- and post-treatment groups, respectively.At the phylum level, the abundances of Bacteroidetes, Verrucomicrobia,
Actinobacteria, and Proteobacteria were significantly reduced, while those of
Firmicutes, Saccharibacteria_TM7, and Spirochaetes were elevated in the
post-treatment group compared to those in the pre-treatment group
(p < 0.05). In addition, several significant
differences were also observed at the genus level. Compared with the
pre-treatment group, the abundances of Ruminococcaceae_uc,
Oscillibacter, Bacteroidaceae_uc,
Sporobacter, and Christensenellaceae_uc were significantly
lower in the post-treatment group, while those of Romboutsia,
Clostridium, Paeniclostridium, and
Turicibacter showed the opposite pattern
(p < 0.05) (Fig.
2c).
Alterations of the gut microbiome community in post-weaned calves after
recovery from diarrhea
Next, we conducted LEfSe analysis to identify the top discriminatory microbiota
at the species level between the diarrheic and recovery states. A cladogram
displaying the taxonomic hierarchical structure of the fecal microbiota (from
the phylum to genus levels) indicated significant differences in phylogenetic
distributions between the microbiota of the pre- and post-treatment groups
(Fig. 3a). Using a logarithmic LDA
score cut-off of 2.0, we identified 18 and 20 genera that were abundant in the
microbiota of the pre- and post-treatment groups, respectively (Fig. 3b). We also identified 28 genera
showing significant differences in relative abundance between the pre- and
post-treatment group. The genera Oscillibacter,
Pseudoflavonifractor, Lachnospiraceae,
Clostridium, Dorea,
Caproiciproducens, Dielma,
Phascolarctobacterium, Odoribacter,
Gallibacterium, Butyricimonas,
Acetivibrio, and Leifsonia were
significantly abundant in the pre-treatment group. However, the genera
Paeniclostridium, Turicibacter,
Clostridiaceae;Clostridium, Romboutsia,
Ruminococcus, Cellulosilyticum,
Intestinibacter,
Peptostreptococcaceae;Clostridium,
Streptococcus, Syntrophococcus,
Howardella, Ralstonia,
Paraclostridium, Kozakia,
Staphylococcus, and Turicibacter were
significantly abundant in the post-treatment group (Fig. 4). These data suggested that the composition of fecal
microbiota was significantly altered in response to 2 months of treatment in
post-weaned calves with BCoV-mediated diarrhea.
Fig. 3.
Microbiota composition in the feces of diarrheic and recovered
calves.
(a) Phylogenetic cladogram generated by performing LEfSe analysis,
depicting taxonomic associations between the microbiome communities of
the pre- and post-treatment groups. Each node represents a specific
taxonomic type. (b) The rankings of significantly different genera
(based on the LEfSe method) were reflected in the log LDA scores of both
groups. LEfSe analysis was based on the nonparametric factorial
Kruskal–Wallis rank-sum test, followed by the Wilcoxon
signed-rank test. Featured LDA scores > 2.0 are plotted
(*p < 0.05, **p <
0.01, ***p < 0.001). LEfSe, linear discriminant
analysis effect size; LDA, linear discriminant analysis.
Fig. 4.
Relative abundances of bacterial genera in the feces of diarrheic and
recovered calves.
The relative abundances of bacterial genera that averaged > 1%,
between 1% and 0.1%, between 0.1% and 0.01%, and < 0.01% of the
relative abundance observed in post-weaned calves with diarrhea, before
and after treatment. The error bars represent standard errors.
*p < 0.05, **p <
0.01, ***p < 0.001, ****p
< 0.0001.
Microbiota composition in the feces of diarrheic and recovered
calves.
(a) Phylogenetic cladogram generated by performing LEfSe analysis,
depicting taxonomic associations between the microbiome communities of
the pre- and post-treatment groups. Each node represents a specific
taxonomic type. (b) The rankings of significantly different genera
(based on the LEfSe method) were reflected in the log LDA scores of both
groups. LEfSe analysis was based on the nonparametric factorial
Kruskal–Wallis rank-sum test, followed by the Wilcoxon
signed-rank test. Featured LDA scores > 2.0 are plotted
(*p < 0.05, **p <
0.01, ***p < 0.001). LEfSe, linear discriminant
analysis effect size; LDA, linear discriminant analysis.
Relative abundances of bacterial genera in the feces of diarrheic and
recovered calves.
The relative abundances of bacterial genera that averaged > 1%,
between 1% and 0.1%, between 0.1% and 0.01%, and < 0.01% of the
relative abundance observed in post-weaned calves with diarrhea, before
and after treatment. The error bars represent standard errors.
*p < 0.05, **p <
0.01, ***p < 0.001, ****p
< 0.0001.
Correlations between gut microbiota compositions and clinical
characteristics
Based on our longitudinal gut microbiome results, we attempted to analyze the
functional correlations between differential gut microbiota compositions and
blood parameters. Spearman’s correlation coefficient (r) was computed for
nine different parameters and 38 bacterial taxa (Fig. 5). The results showed 126 statistically significant
interactions between eight blood parameters and 38 bacterial taxa
(p < 0.05). The genera
Caproiciproducens, Pseudoflavonifractor,
and Oscillibacter, which were more abundant in the post-weaned
calves with diarrhea, showed a negative correlation with blood parameters, such
as the glucose, and phosphorus levels, but it positively correlated with
chloride levels. However, the genera
Peptostreptococcaceae;Clostridium,
Intestinibacter, Cellulosilyticum,
Ruminococcus, Romboutsia,
Paeniclostridium, Clostridiaceae,
Clostridium, and Turicibacter, which were
more abundant in post-weaned calves after treatment of BCoV-mediated diarrhea,
showed positive correlation with serum glucose and phosphorus levels but
negative correlation with serum chloride levels. The increased abundance of
Dorea showed negative correlations with glucose, sodium,
and phosphorus level in pre-treatment group, while a positive correlation was
observed between those parameters and increasing abundance of
Ralstonia genus in the post-treatment group. These results
suggest that alterations of gut microbiota compositions between the pre- and
post-treatment groups are correlated with changes in their physiological
parameters.
Fig. 5.
Correlations between the gut microbiome and physiological
parameters.
Spearman’s correlation analysis was used to investigate the
relationships between fecal bacterial populations and blood parameters,
considering longitudinal results obtained with all groups. The red and
blue cells indicate positive and negative correlations, respectively.
Correction for multiple comparisons used the false discovery rate (FDR;
threshold of 0.05). *p < 0.05,
**p < 0.01, ***p <
0.001, ****p < 0.0001. BUN, blood urea nitrogen;
PHOS, phosphorus.
Correlations between the gut microbiome and physiological
parameters.
Spearman’s correlation analysis was used to investigate the
relationships between fecal bacterial populations and blood parameters,
considering longitudinal results obtained with all groups. The red and
blue cells indicate positive and negative correlations, respectively.
Correction for multiple comparisons used the false discovery rate (FDR;
threshold of 0.05). *p < 0.05,
**p < 0.01, ***p <
0.001, ****p < 0.0001. BUN, blood ureanitrogen;
PHOS, phosphorus.
DISCUSSION
Coronaviruses cause severe respiratory and enteric infectious diseases that pose
health risks to humans and domestic animals. Although previous studies have shown
changes in the gut microbiota caused by intestinal infectious diseases in cattle
[15,16], no reports have described an altered gut microbiota in calves with
diarrhea caused by BCoV. Our results showed that the gut microbiota was different
before and after diarrhea recovery and indicated a clear correlation between the
abundances of taxa (at the genus level) and the blood parameters for the first
time.We collected blood and fecal samples from the same ten post-weaned calves with
diarrhea, before and after fluid therapy. After two months of treatment, BCoV was no
longer detected in the feces, and the symptoms of diarrhea had improved. In
addition, since diarrhea leads to symptoms, such as dehydration, abnormalities in
terms of electrolytes and the acid–base balance, and nutrient malabsorption,
it is important to measure the concentrations of total protein, BUN, glucose,
electrolytes in the serum as a diagnostic index of diarrhea [17,18]. In this regard,
our results indicated that blood parameters associated with diarrheic symptoms, such
as lower levels of serum glucose, sodium, and phosphorus, were enhanced in the
post-weaned calves after treatment. Furthermore, although higher concentrations of
total serum protein, serum albumin, and BUN are generally observed in calves with
diarrhea [19,20], our results showed that these blood parameters were maintained at
low concentrations even during the diarrheic state, and no differences were found
before and after treatment. These data indicate that values of diagnostic serum
physiological parameters of calves with diarrhea vary depending on their causative
agents, suggesting that analysis of blood parameters only is inadequate as a method
for diagnosing BCoV-mediated diarrhea. Our previous study suggested that monitoring
the monocyte count and haptoglobin concentration along with clinical examination and
PCR can be used to assess the prognosis of post-weaned calves with diarrhea caused
by BCoV infection [13].Previous studies have shown that diarrhea often leads to reduced microbial diversity
in humans and animals [21-23]. In our research, alpha diversity indices
were found to be significantly lower in the post-treatment group than that in the
pre-treatment group, which implied that the diversity of the intestinal microbiota
might not be properly recovered in post-weaned calves after treatment. An
explanation for these findings would be that infectious diarrhea causes serious
damage to the intestines, accompanied by inflammation [24]. Thus, two months of fluid treatment might not be enough to
restore the gut microbial diversity, suggesting that further study on changes in the
gut microbiota after long-term treatment is necessary.In case of rotavirus-mediated diarrhea, upon comparing the main differences in
bacterial phyla between infected and uninfected calves, the abundances of Firmicutes
and Bacteroidetes were found to be reduced and that of Proteobacteria was found to
be elevated in the rotavirus diarrheic calves [16]. However, in our study, only Firmicutes increased in abundance after
recovery in calves with BCoV-related diarrhea, indicating that the alteration of the
gut microbiota may differ depending on the type of virus that induces diarrhea.We identified differences in core gut microbiota between calves in the diarrheic and
recovered states through LEfSe analysis. Then, we further investigated the
correlation between the abundances of taxa (at the genus level) and the blood
parameters. Our data showed that 14 genera were significantly correlated with three
different blood parameters simultaneously. In particular, the abundances of the
genera Caproiciproducens, Pseudoflavonifractor,
and Oscillibacter, which were more abundant in the pre-treatment
group, were found to be negatively correlated with the serum glucose and phosphorus
levels but positively correlated with the serum chloride level. Notably, only
Dorea showed negative correlations with serum glucose, sodium,
and phosphorus levels. Previous results revealed that the genus
Caproiciproducens is currently found in hens with gut dysbiosis
induced by Salmonella Typhimuriuminfection [25], and the abundance of the genus
Pseudoflavonifractor is increased in chickensinfected with
influenza A virus subtype H9N2 [26]. Besides,
though Dorea is often found in healthy individuals, its elevated
abundance is also observed in patients with multiple sclerosis and colon cancer
[27,28], indicating that this genus may play a deteriorative role in immune
regulation. In diarrheic calves, the abundances of opportunistic pathogens were
observed to be correlated with diarrhea symptoms, suggesting that changes in the gut
microbiota caused by BCoV-mediated diarrhea may lead to chronic diseases.On the contrary, the abundances of the genera
Peptostreptococcaceae;Clostridium,
Intestinibacter, Cellulosilyticum,
Ruminococcus, Romboutsia,
Paeniclostridium,
Clostridiaceae;Clostridium, and
Turicibacter increased in recovered calves, and they showed
positive correlations with the serum glucose and phosphorus levels, but negative
correlations with serum chloride level. Among these genera,
Ruminococcus has been shown to easily digest plant cellulose
and produce short-chain fatty acids, such as acetate, formate, and succinate, which
are associated with anti-inflammatory effects [29]. The genus Cellulosilyticum has been reported to be
able to break down both fiber and protein.
Peptostreptococcaceae;Clostridium was found to be predominant
in the perinatal intestinal microbiota of cattle [30]. Moreover, the genus Ralstonia was detected at
higher levels in the milk microbiomes of healthy dairy cows than those of mastitic
dairy cows [31]. Taken together, our results
demonstrate that fluidic treatment tended to increase some beneficial bacteria
associated with fiber digestion in healthy calves and reduce the opportunistic
pathogens correlated with the diarrheic symptoms in post-weaned calves with
BCoV-mediated diarrhea, suggesting that the improvement of the intestinal
dysfunction by fluid therapy might influence on the microbial changes.The data generated in this study indicated that the gut microbiota of diarrheic and
recovered calves were different. Significant differences in the microbiota structure
and composition between these two groups suggest that the microbial environment
could be changed by two months of fluid therapy, which is commonly used for calves
with diarrhea. Furthermore, these results provide new information regarding the
relationship between the gut microbiota and the physiological parameters of calves
with BCoV-mediated diarrhea.
Authors: Pallavi Singh; Tracy K Teal; Terence L Marsh; James M Tiedje; Rebekah Mosci; Katherine Jernigan; Angela Zell; Duane W Newton; Hossein Salimnia; Paul Lephart; Daniel Sundin; Walid Khalife; Robert A Britton; James T Rudrik; Shannon D Manning Journal: Microbiome Date: 2015-09-22 Impact factor: 14.650
Authors: Gregor Gorkiewicz; Gerhard G Thallinger; Slave Trajanoski; Stefan Lackner; Gernot Stocker; Thomas Hinterleitner; Christian Gülly; Christoph Högenauer Journal: PLoS One Date: 2013-02-08 Impact factor: 3.240