Functional gene arrays-based analysis of fecal microbiomes in patients with liver cirrhosis
Functional gene arrays-based analysis of fecal microbiomes in patients with liver cirrhosis
Yanfei Chen 1
Nan Qin 1
Jing Guo 1
Guirong Qian 1
Daiqiong Fang 1
Ding Shi 1
Min Xu 1
Fengling Yang 1
Zhili He 0
Joy D Van Nostrand 0
Tong Yuan 0
Ye Deng 0
Jizhong Zhou 0 2 3
Lanjuan Li 1
0 Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma , Norman, OK 73019 , USA
1 State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University , Hangzhou 310003 , PR China
2 State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University , Beijing 100084 , China
3 Earth Sciences Division, Lawrence Berkeley National Laboratory , Berkeley, CA 94720 , USA
Background: Human gut microbiota plays an important role in the pathogenesis of cirrhosis complications. Although the phylogenetic diversity of intestinal microbiota in patients with liver cirrhosis has been examined in several studies, little is known about their functional composition and structure. Results: To characterize the functional gene diversity of the gut microbiome in cirrhotic patients, we recruited a total of 42 individuals, 12 alcoholic cirrhosis patients, 18 hepatitis B virus (HBV)-related cirrhosis patients, and 12 normal controls. We determined the functional structure of these samples using a specific functional gene array, which is a combination of GeoChip for monitoring biogeochemical processes and HuMiChip specifically designed for analyzing human microbiomes. Our experimental data showed that the microbial community functional composition and structure were dramatically distinctive in the alcoholic cirrhosis. Various microbial functional genes involved in organic remediation, stress response, antibiotic resistance, metal resistance, and virulence were highly enriched in the alcoholic cirrhosis group compared to the control group and HBV-related cirrhosis group. Cirrhosis may have distinct influences on metabolic potential of fecal microbial communities. The abundance of functional genes relevant to nutrient metabolism, including amino acid metabolism, lipid metabolism, nucleotide metabolism, and isoprenoid biosynthesis, were significantly decreased in both alcoholic cirrhosis group and HBV-related cirrhosis group. Significant correlations were observed between functional gene abundances and Child-Pugh scores, such as those encoding aspartate-ammonia ligase, transaldolase, adenylosuccinate synthetase and IMP dehydrogenase. Conclusions: Functional gene array was utilized to study the gut microbiome in alcoholic and HBV-related cirrhosis patients and controls in this study. Our array data indicated that the functional composition of fecal microbiomes was heavily influenced by cirrhosis, especially by alcoholic cirrhosis. This study provides new insights into the functional potentials and activity of gut microbiota in cirrhotic patients with different etiologies.
End-stage liver disease; Intestines; Microbial communities; Alcohol; Microarray
The gastrointestinal tract harbors a complex and diverse
microbial community, which plays important roles in host
nutrition, immune function, health and disease. Increasing
evidence suggests that dysbiosis of intestinal microbiota
plays important roles in the pathogenesis of complications
of cirrhosis, such as spontaneous bacterial peritonitis, and
hepatic encephalopathy [
]. Bacterial translocation has
been postulated as the main mechanism [
intestinal bacterial overgrowth is one of the most important
factors that facilitate bacterial translocation in cirrhosis
]. Most recently, culture-independent methods including
real-time PCR and high-throughput sequencing were used
to characterize the structure of fecal microbiota in
cirrhotic patients. Compositional changes have been linked
with cirrhosis, including a significant increase of
Proteobacteria and Fusobacteria, and a corresponding decrease
of Bacteroidetes in cirrhotic patients using 454 sequencing
of 16S rDNA gene [
]. Abnormal fecal microbiota
functions in patients with hepatitis B virus (HBV) liver
cirrhosis has also been revealed using shotgun
metagenomic sequencing [
Metagenomic pyrosequencing of intestinal microbiota
have led to the discovery of novel genes from uncultivated
microorganisms, assembly of whole genomes from
community DNA sequence data and comparison of microbial
community composition under different physical
]. The human gut microbiome has significantly
enriched metabolism of carbohydrates, amino acids, and
xenobiotics, and biosynthesis of vitamins and isoprenoids,
when compared with the average content of previous
sequenced microbial genome [
]. There are a wide array of
shared microbial genes among sampled individuals,
comprising an extensive, identifiable ‘core microbiome’ at the
gene level [
]. Several studies have described changes in
the gene content of the gut microbiome across health and
Functional gene arrays (FGAs) are the microarrays
containing probes which target genes involved in a variety of
functional processes and are powerful high throughput
tools for monitoring the physiological status and
functional activities of microbial populations and communities
]. Different types of FGAs have been developed for
analyzing microbial functional community structure [
such as, GeoChip 4.0, which contains about 82,000 probes
and targets about 142,000 genes from 410 functional gene
families involved in nitrogen, carbon, sulfur and
phosphorus cycling, antibiotic resistance, virulence factors and
bacterial phage-mediated lysis (Additional file 1: Table S1),
and HuMiChip 1.0, which contains 36,082 probes
targeting ~50,000 gene coding DNA sequences from 139 key
functional genes in various metabolic pathways (e.g., the
metabolism of amino acids, carbohydrates, energy, lipids,
glycan, cofactors, vitamins, and nucleotides) (Additional
file 2: Table S2). Since human microbiomes have many
general functions which GeoChip targets, combining these
two types of FGAs would be very powerful in dissecting
the functional composition and structure of human
We hypothesized that gut dysbiosis in cirrhosis would
be related to altered microbial functional structure and
that the etiology of cirrhosis would further affect the gut
microbiome. Alcoholic and HBV are the main causes of
cirrhosis in Western country and China, respectively. In
this study, we characterized the functional structure of
fecal microbial communities in patients with alcoholic
cirrhosis and HBV-related cirrhosis compared to healthy
controls using GeoChip 4.0 + HuMiChip 1.0. We
focused on the variations of fecal microbiomes in relation
to (i) the presence of cirrhosis and (ii) the etiology of
cirrhosis, for example, chronic alcohol consumption. Our
results indicated that cirrhosis, especially alcoholic
cirrhosis, has a tremendous impact in the functional
composition of fecal microbiomes.
Overview of functional gene diversity and structure of fecal microbial communities
Based on all detected functional genes, the community
diversity was assessed by richness (number of probes
detected per sample), Shannon-Weiner (H’) and Simpson’s
(1/D) indices (Figure 1). Overall, the number of probes
detected was significantly (p < 0.01) higher in alcoholic
cirrhosis (ALC) than in HBV-related cirrhosis (HBC)
and controls (CT), while there was no significant
difference between the HBC and CT groups. Similarly, the
overall microbial functional diversity was also
significantly (p < 0.001) higher in ALC than in HBC and CT
based on Shannon-Weiner (H’) and Simpson’s (1/D)
indices, while the difference was not significant between
HBC and CT groups.
Detrended correspondence analysis (DCA) of all
detected genes was used to examine overall functional
structure changes in the microbial communities.
Resulting ordination plots showed a marked difference among
the three groups and explained 46.3% of the total
variations (Figure 2). ALC samples were clearly separated
from HBC and CT samples along DCA1 (31.2%), while
HBC and CT were distinct along DCA2 (15.1%).
The average signal intensities of functional categories
were compared among the three groups (Figure 3). The
functional categories involved in nutrient metabolism
were significantly (p < 0.05) lower in ALC and HBC than
in CT, including the functional categories of isoprenoid
biosynthesis, lipid metabolism, nucleotide metabolism,
and amino acid biosynthesis and metabolism. For glycan
biosynthesis and metabolism and cofactor biosynthesis,
the relative abundance was significantly (p < 0.05) lower
in ALC than in CT, while the difference was not
significant between HBC and CT group. Functional categories,
such as energy metabolism, organic remediation, stress
response, antibiotic resistance, metal resistance and
virulence, were significantly (p ≤ 0.001) enriched in ALC
compared to CT and HBC, while there was no
significant difference between HBC and CT.
Shifts of genes in response to cirrhosis
Cirrhosis mostly affected the abundance of functional
genes involved in nutrient metabolism. In this study, we
identified 33 genes, whose alteration was consistent
between HBC and ALC relative to controls (Figure 4).
(i) Amino acid biosynthesis and metabolism. A total of
11 genes involved in amino acid biosynthesis and
metabolism were detected significantly (p < 0.05)
reduced in both cirrhosis group, including amino acid
biosynthesis genes (2-isopropylmalate synthase gene,
cysteine synthase A gene, NADPH gene, L-threonine
aldolase gene, prephenate dehydrogenase gene, serine
(See figure on previous page.)
Figure 1 Number of probes detected and diversities of the microbial community in alcoholic cirrhosis, HBV-related cirrhosis, and
controls. Gene number (Figure 1A), Simpson Index (Figure 1B), and Shannon Index (Figure 1C) were presented as mean ± SD. Different letters
above the bar (a, b) indicated statistical difference at a P value of <0.05 among groups by one-way ANOVA and Tukey’s test. HBV-related cirrhosis
(HBC), healthy controls (CT), and alcoholic cirrhosis (ALC).
O-acetyltransferase gene, valine-pyruvate
aminotransferase gene, serine-tRNA ligase gene, and
aspartateammonia ligase gene), and amino acid metabolism
genes (glutamate decarboxylase A and B
PLPdependent gene, and lysine decarboxylase 1 gene).
(ii) Carbohydrate metabolism. Carbohydrate
metabolism is one of the most important functions the
distal gut microbiome provides for the host. The
abundance of genes involved in carbohydrate
metabolism was significantly (p < 0.05) lower in ALC
and HBC than in CT, including genes for KDPG
aldolase, transaldolase, glycogen synthase, ribokinase,
N-acetylglucosamine-6-phosphate deacetylase, and
beta-D-galactosidase. Butyrate serves as the principal
energy source for colonocytes and may fortify the
intestinal mucosal barrier by stimulating their growth [
The genes encoding butyrate kinase, which participate
in butyrate metabolism, were significantly (p < 0.001)
lower in HBC than in CT, and even lower in ALC than
(iii) Glycan biosynthesis and metabolism. The array
data demonstrated 5 genes of glycan biosynthesis and
metabolism significantly declined in both cirrhosis
groups relative to controls, including
D-alanineDalanine ligase gene, UDP-N-acetylglucosamine
acyltransferase gene, UDP-N-acetylmuramateL-alanine
ligase gene, phospho-N-acetylmuramoyl-pentapeptide
transferase gene, and
UDP-N-acetylmuramoyl-L-alanylD-glutamatemeso-diaminopimelate ligase gene
(p < 0.05).
(iv) Nucleotide metabolism. The abundance of genes
involved in nucleotide metabolism was significantly
(p < 0.05) lower in ALC and HBC than in CT, including
genes for purine metabolism (adenylosuccinate
synthetase gene, IMP dehydrogenase gene, and
purinenucleoside phosphorylase gene), and pyrimidine
metabolism (carbamoyl phosphate synthetase small subunit
glutamine amidotransferase gene, thioredoxin reductase
FAD-NADP-binding gene, and thymidine
(v) Cofactor biosynthesis and others. For cobalt
chelatase gene (encoding vitamin B12) and
pantothenate synthetase gene (encoding pantothenic
acid), the signal intensities were significantly (p < 0.001)
lower in ALC and HBC than in CT. The signal
intensities of isoprenoid biosynthesis gene encoding
4diphosphocytidyl-2C-methyl-D-erythritol synthase were
significantly (p < 0.05) lower in ALC and HBC than in
CT. Bacterial bile salt hydrolase participates in the
conversion of primary bile acids to secondary bile acids
]. The signal intensity of conjugated bile salt
hydrolase gene was found significantly (p < 0.05) lower in
HBC than in CT, and even lower in ALC than in HBC
Correlations between gene abundance and child-pugh scores
Among those genes with decreased abundances in both
cirrhosis groups, we found 7 genes negatively correlated with
the severity of liver disease, as estimated by the Child-Pugh
score, including aspartate-ammonia ligase gene (r = −0.427,
p = 0.019), serine-tRNA ligase gene (r = −0.406, p = 0.026),
and glutamate decarboxylase A and B PLP-dependent gene
(r = −0.453, p = 0.012) for amino acid metabolism,
transaldolase gene (r = −0.397, p = 0.03) for carbohydrate
metabolism, phospho-N-acetylmuramoyl-pentapeptide transferase
gene (r = −0.463, p = 0.014) for glycan metabolism,
adenylosuccinate synthetase gene (r = −0.449, p = 0.013) and IMP
dehydrogenase gene (r = −0.409, p = 0.025) for purine
metabolism (Figure 5).
Shifts of genes in response to alcohol
A comparison of ALC with HBC and CT revealed that
92 genes were uniquely altered in response to alcohol
consumption (Figure 6). Among them, 4 genes were
found significantly (p < 0.05) reduced in ALC than
in HBC and CT, including carbohydrate metabolism
gene (phosphogluconate dehydratase gene) and glycan
biosynthesis and metabolism gene
(beta-N-acetyl-Dhexosaminide N-acetylhexosaminohydrolase gene,
Nacetyl-D-galactosamine-4-sulfate 4-sulfohydrolase gene,
and N-acetylmuramoyl-L-alanine amidase gene). Most
of the over-represented genes were involved in
functional categories of organic remediation, stress response,
and antibiotic or metal resistance. The abundance of
cytochrome gene in energy metabolism was found
significantly increased in ALC than in HBC and CT.
(i) Organic degradation. A substantial number of genes
(42) involved in degradation of organic compounds were
detected with different abundances, especially those
involved in degrading aromatic carboxylic acid, BTEX
and related aromatics, chlorinated aromatics, herbicides
and pesticides related compounds, and chlorinated
solvents. Most of these genes (e.g., pimF, nagG, nmoA,
and bphA, Catechol genes, GCoADH genes) showed
significantly (p < 0.05) increased abundances in ALC than
in CT and HBC (Additional file 1: Table S1). Phthalates
within alcoholic beverages have attracted more and more
attention for their health hazards in recent years. The
abundance of phtA gene, encoding phthalate 4,
5dioxygenase, was significantly (p < 0.001) higher in ALC
than in HBC and CT.
(ii) Stress response. A total of 24 genes involved in
stress response showed significantly (p < 0.05)
increased abundances in ALC than in CT and HBC,
including oxygen stress (ahpC, ahpF, fnr, katE, and
oxyR), oxygen limitation (narH, and narJ), nitrogen
limitation (glnA), heat shock (dnaK, grpE, hrcA),
phosphate limitation (pstA, pstB, pstC and pstS), and
osmotic stress (proV).
(iii) Virulence. Functional genes associated with bacterial
virulence were found over-represented in ALC samples
compared to CT and HBC. The signal intensities of the
genes encoding the bacterial secretion system
(type_Ш_secretion), catabolite activator protein (cap),
ironregulated TonB-dependent receptor (iro), pilin protein
(pilin), and sortase family protein (srt), were significantly
(p < 0.001) higher in ALC than in HBC and CT.
(iv) Antibiotic resistance. Regarding antibiotic resistance,
5 genes were detected in significantly (p < 0.05) higher
abundance in ALC than other groups, including genes
for ABC_antibiotic_transporter, ß-lactamase_C,
MFS_antibiotic, SMR_antibiotics, and Tet genes.
(v) Metal resistance. Functional genes associated with
metal resistance were found over-represented in ALC
samples compared to CT and HBC. The signal
intensities of the genes encoding arsenite oxidase (aoxB),
arsenate reductase (ArsC), cadmium-translocating P-type
ATPase (CadA), copper-transporting P-type ATPase
(CopA), heavy metal efflux pump protein (czcA, czcD,
ZntA), RND efflux system outer membrane lipoprotein
(silC), tellurite resistence protein (TerC, TerD, TerZ),
were found singnificantly (p < 0.05) higher in ALC than
in HBC and CT.
Although several studies have reported composition
variations between cirrhotic patients and healthy controls, little
is known about bacterial gene content and their potential
functions in cirrhosis of different etiologies [
is a growing recognition of the need to study the
functional profile of fecal microbiota. Here we have presented
a functional gene array-based analysis of fecal microbiota
in patients with alcoholic cirrhosis and HBV-related
Different methods can be used to study complex
microbial populations. Recently, the development of the
newgeneration sequencing technologies challenged the use of
DNA microarrays in microbial community studies. The
main limitation of microarrays is their inability to reveal
novel species in any samples, since the arrays can only
detect those sequences for which they contain probes.
However, there are several main advantages of microarrays,
include (i) ability to profile one sample at a time, which is
useful in clinical studies and as a diagnostic tool; (ii)
quantitative nature of the acquired data allowing direct
comparison between samples; (iii) quick sample preparation and
short processing and data acquisition time (only 24 hours
from sample to data using GeoChip); (iv) currently lower
costs compared with shotgun sequencing; and (v) resistance
to contaminants of host genome, which is useful for
mucosa samples containing a large percentage of host DNA
Although a few samples overlapped, there is a trend of
separation between cirrhosis subjects and controls.
Functional categories prominent in healthy controls
were mostly related to nutrient metabolism (Figure 3).
Our results indicated that the metabolic potential of the
gut microbiota was significantly affected, analogous to a
previous study which reported a decrease in
concentration of a large number of metabolites in patients with
cirrhosis based on metabolomic analysis of feces
]. The exact reason for reduced gut microbial
metabolic potential in cirrhotic patients remains
unclear. The fact of low protein diet in the majority of
cirrhotic patients may play a role in it. Although not
recommended, patients with cirrhosis usually took low
protein diet to avoid hepatic encephalopathy [
effect of diet on gut microbiome has been verified in
several studies [
]. A controlled-feeding study of 10
subjects showed that microbiome composition changed
detectably within 24 hours of initiating a high fat/low
fiber or low fat/high fiber diet . In the current study,
the microbiome of cirrhosis had a lower relative
abundance of genes associated with the biosynthesis and
metabolism of several amino acids, including leucine
(2isopropylmalate synthase gene), serine (serine-tRNA
ligase gene and L-threonine aldolase gene), cysteine
(serine O-acetyltransferase gene and cysteine synthase
A gene), and valine (valine-pyruvate aminotransferase
gene) (Figure 3). Biosysthesis of amino acids are critical
for the growth of all microbes, but the amount and
profile of amino acids produced, and production of other
protein-containing metabolites have been reported to
vary depending on dietary composition in animal
]. Malnutrition has increasingly been
acknowledged as an important prognostic factor, which can
influence the clinical outcome of cirrhotic patients .
Alcoholic beverages, which contribute little to the
nutritional requirements of the body, are usually associated
with food deficiency due to decreased appetite [
Alcohol ingestion has been shown to decrease vitamin B12
absorption in volunteers after several weeks of intake
]. In relation to this, our data revealed that cobalt
chelatase gene was significant underrepresented in
cirrhosis groups, especially in alcoholic cirrhosis group.
Cobalt chelatase is an important pathway in vitamin B12
]. Together with diet alterations,
reduced metabolic potential of gut microbiome might
increase the risk of malnutrition in cirrhosis.
Another class of functions changed in the cirrhosis
groups was bile salt metabolism. Bile acids, drugs and
toxins undergo extensive enterohepatic circulation, which
is also called gut-liver axis [
]. Bile acids play a major role
in several hepatic and intestinal diseases. Intestinal
bacteria are known to participate in bile acid metabolism by
generating secondary bile acids (deconjugation,
]. The initial “gateway” reaction in the bacterial
metabolism of conjugated bile acids is mediated by bile
salt hydrolase [
]. In cirrhosis, decrease in intestinal
intraluminal concentrations of bile acids have been
ascribed to decrease secretion and increased deconjugation
by enteric bacteria [
]. Nevertheless, our results
demonstrated the abundance of conjugated bile salt hydrolase
gene was significantly lower in cirrhosis than in controls.
In a recent metagenomic research of patients with
HBVrelated cirrhosis using high-throughput sequencing, genes
annotated as bile salt hydrolases were also detected in
higher abundance in the normal microbiota than in the
cirrhotic microbiota [
]. In particular, cirrhotic patients
showed an altered fecal bile acid profile with a decreased
conversion of primary to secondary fecal bile acids [
is thus tempting to speculate that decrease synthesis of
bile acids in the liver contributes more importantly to
decrease in intestinal intraluminal concentrations of bile
acids in cirrhosis.
Enzyme responsible for butyrate metabolism (butyrate
kinase gene) was found in less abundant in both cirrhosis
groups, especially in alcoholic cirrhosis group (Figure 4).
Our results are in agreement with the 16S rRNA based
analysis, which shows that many of the bacterial genera
significantly less abundant in cirrhotic patients are
butyrate producers and mucin degraders, such as
Faecolibacterium and Prevotella [
]. Butyrate is known as the
principal energy source for colonocytes and may fortify the
intestinal mucosal barrier by stimulating mucin synthesis
]. Recent endoscopic studies reveal mucosal alterations
in the gastrointestinal tract including inflammatory-like
changes and vascular lesions in cirrhosis [
together these observations, a microbiota-dependent
reduction of butyrate production may possibly contribute to the
nutritional status of epithelial cell in the intestine in
cirrhosis, and potentially lead to mucosal changes, hypertensive
enteropathy and bacterial translocation indirectly.
The current results from the array analysis showed
considerable variations of the community functional structure
were observed in response to alcohol consumption. Higher
microbial richness and genetic diversity were observed in
ALC samples than in HBC or CT samples. The bacterial
genomes have been shown to be highly plastic and are
frequently reorganized through genetic rearrangements and
gene transfer, which can help them adapt to distinct
ecological conditions [
]. High level of heterogeneity and
diversity among strains were observed under stressful
ecosystem such as high ethanol content, low pH and
]. Alcohol ingested orally is transported to
the colon by blood circulation, and due to its high water
solubility, intracolonic ethanol levels are equal to those in
the blood [
]. In patients with cirrhosis, extrahepatic
ethanol metabolism, via microbial oxidation in the colon, is
responsible for a large portion of ethanol metabolism [
It was recently shown that low concentrations of alcohol
can enhance microbial activity in the human body. For
example, in Staphylococcus aureus, ethanol
supplementation stimulated the expression of genes involved in stress
response, and biofilm formation [
]. Treatment of S.
aureus with alcohol resulted in increased transcription of the
biofilm-promoting genes icaA and icaD, as well as the
antibiotic resistance gene mmpL (multidrug efflux pump),
the efflux pump gene mepA, and the sensor histidine
kinase gene vraS [
]. In relation to this, functional genes
related to stress response and antibiotic resistance were
significantly over-represented in our study.
Our results also revealed great metabolic potential in the
alcoholic cirrhosis group for xenobiotic degradation.
Numerous gut microbial genes are related to xenobiotic
degradation, including non-modified and halogenated aromatic
]. More than 700 aromatic compounds have
been isolated and identified from various wines, which
derive from by-products of yeast fermentation and additives.
Phthalates are a group of industrial chemicals that have
become ubiquitous environmental contaminants because of
their widespread usage and high persistence in the
]. Phthalates in alcoholic beverages might be from
two sources: the migration from packaging materials and
the use of diethyl phthalate as a denaturing agent for
]. The abundance of phtA genes, encoding
phthalate 4, 5-dioxygenase, was significantly higher in ALC
than in HBC or CT samples. Long-term alcohol
consumption could potentially lead to the enriched genes in
phthalates degradation. Moreover, our results revealed
metabolic potential in alcoholic cirrhosis group for
benzoate metabolism, such as bclA gene, nagG gene and 4HBH
gene (Figure 6). Benzoate could enter the tricarboxylicacid
cycle, and might constitute a potential energy source [
Aromatic compound degradation may allow for the
utilisation of a wider array of substrates that may be used for
energy harvesting in alcoholic cirrhosis.
In this study, we detected several genes which were
negatively correlated with Child-Pugh score (Figure 5).
Our results offer the possibility of using functional genes
as biomarkers to estimate the severity of liver cirrhosis.
Nevertheless, obtaining cultures of microbes is essential
for validating these hypotheses. Furthermore, since
considerable variations of the community functional structure
were observed in response to alcohol consumption,
individuals with alcohol consumption with or without liver
disease should also be compared to validate such links in
future studies. In addition, DNA-based array analysis
detects only the functional potential of microbial
communities, but not necessarily the actual functional activity. To
understand functional activities, RNA-based array analysis
is needed in future studies.
Functional gene array (GeoChip 4.0 + HuMiChip 1.0)
was utilized to study the gut microbiome in alcoholic
and HBV-related cirrhosis patients and controls in this
study. Our array data indicated that the functional
composition of fecal microbiomes was mostly
influenced by alcohol consumption, and secondly by
cirrhosis. Alcohol consumption caused significant enrichment
of functional genes including xenobiotic metabolism
and virulence, while both cirrhosis groups were
markedly depleted in the functional genes involved in
nutrient processing, such as amino acid metabolism, lipid
metabolism and nucleotide metabolism. These results
have important implications for complications of
cirrhosis (e.g., malnutrition and hypertensive enteropathy).
Therapeutic options aimed at adjusting the gut
microbiome should be a potential treatment in cirrhosis.
A total of 42 individuals were recruited for this research,
including 3 groups: (1) 12 subjects with alcoholic
cirrhosis (ALC); (2) 18 subjects with HBV-related cirrhosis
(HBC); (3) 12 subjects with normal liver function by
ultrasonographic examination and biochemical profiles
Note. 1. Age, BMI, CP, Alb, INR, TB, and Crea were expressed as mean ± SD. 2. Measure unit: Age (yr); BMI (kg/m2); TB (umol/L); PT (S); Alb (g/L); Crea (umol/L).
Abbreviations: BMI body mass index, CP Child-Pugh score, TB total bilirubin, PT prothrombin time, Alb, serum albumin, INR international normalized ratio, Crea,
(CT). The three groups were matched in terms of body
mass index, gender, and age.
Cirrhosis was diagnosed histologically in 17 out of 30
(57%) patients and on clinical and radiological grounds
in the remaining 13 (43%) patients for whom biopsy was
contraindicated by uncontrolled coagulapathy and/or
uncontrolled ascites. A diagnosis of alcoholic cirrhosis
was established if alcohol intake had been in excess of
80 g/day in men and 30 g/day in women for more than
5 years and if testing for viral, metabolic, and immune
etiologies was negative. The HBV-related cirrhotic
patients and healthy controls had no history of alcohol
abuse. Subjects with HBV-related cirrhosis had
HBVDNA detectable by PCR, and an absence of other (viral,
drug/toxin, autoimmune, or metabolic) causes of liver
disease. To avoid the influence of antibiotics or
probiotics, exclusion criteria included a history of antibiotics/
probiotics (or prebiotics) treatment within the previous
8 weeks of sample collection. Clinical characteristics of
all groups are summarized in Table 1. Detailed
characteristics of patients (e.g., hepatic encephalopathy and
ascites) are shown in Additional file 3: Table S3.
All subjects in this study provided their informed
consent in writing. The use of these subjects conformed
to the ethical guidelines of the 1975 Declaration of
Helsinki, and was approved by the First Affiliated Hospital
of Zhejiang University Institutional Review Broad.
Sampling and DNA extraction
All fecal samples were immediately frozen on collection
and stored at −70°C before analysis. Fecal DNA was
extracted with the QIAamp DNA Stool Mini Kit (Qiagen,
Valencia, CA, USA) as described previously [
quality was assessed with a ND-1000 spectrophotometer
(Nanodrop Inc., Wilmington, DE, USA). DNA
concentrations were quantified with Quant-It PicoGreen Kit
(Invitrogen Carlsbad, CA, USA) and 2 μg DNA was used
for functional gene array hybridization.
Details for labeling, hybridization, image processing and
data processing were described previously [
Probes that were detected in less than 10% of each
group were removed.
All hybridization data is available at the Institute for
Environmental Genomics, University of Oklahoma (http://
ieg.ou.edu/). Detrended correspondence analysis (DCA)
was performed by the vegan package in R 2.9.1 (R
Development Core Team 2006). Correlation between
variables was computed by Spearman Rank correlation. To
minimize false significant correlations, results were
adjusted for multiple testing within each category using
the Bonferroni correction. One way ANOVA with
Tukey’s test was used to evaluate the difference in
functional categories among the three groups. The one way
ANOVA and Spearman Rank correlation were
conducted in SPSS version 11.0 for Windows (SPSS Inc.,
Chicago, IL, USA).
Additional file 1: Table S1. Summary of probe and covered coding
sequence information of GeoChip 4 based on gene categories.
Additional file 2: Table S2. Summary of probes and covered coding
sequence information of HuMiChip 1.0 based on gene categories.
Additional file 3: Table S3. Clinical Information Summary of Patients in
HBV: Hepatitis B virus; DCA: Detrended correspondence analysis.
The authors declare that they have no competing interest.
YFC participated in the design of the study, carried out the array
hybridization, performed the statistical analysis, and write the paper. NQ, MX
and FLY recruited the patients and controls, and collected samples. JG, DQF,
DS and GRQ carried out the DNA extraction. ZH and JVN participated in the
array hybridization and helped to draft the manuscript. TY and YD
participated in the array hybridization and array analysis. LJL and JZZ
conceived of the study, and participated in its design and coordination and
helped to draft the manuscript. All authors read and approved the final
We thank Prof. Baoli Zhu in CAS Key Laboratory of Pathogenic Microbiology
& Immunology at Chinese Academy of Sciences for his contribution in study
design and data interpretation. This work was supported by the National
Program on Key Basic Research Project (973 Program) 2013CB531404, the
Major National S & T Project for Infectious Disease (11th Five Year)
2008ZX10002-007, the Science Fund for Creative Research Groups of the
National Natural Science Foundation of China (NO. 81121002), and the
Oklahoma Applied Research Support (OARS), Oklahoma Center for the
Advancement of Science and Technology (OCAST), the State of Oklahoma
through the Project AR11-035. The development of the GeoChips and
associated computational pipelines used in this study were supported by
ENIGMA (Ecosystems and Networks Integrated with Genes and Molecular
Assemblies) through the Office of Science, Office of Biological and
Environmental Research, the U. S. Department of Energy under Contract No.
DE-AC02-05CH11231, by the OBER Biological Systems Research on the Role
of Microbial Communities in Carbon Cycling Program (DE-SC0004601) and
by the U.S. National Science Foundation MacroSystems Biology program
under the contract (NSF EF-1065844).
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