Abstract
In this study we used stool profiling to identify intestinal bacteria and metabolites that are differentially represented in humans with colorectal cancer (CRC) compared to healthy controls to identify how microbial functions may influence CRC development. Stool samples were collected from healthy adults (n = 10) and colorectal cancer patients (n = 11) prior to colon resection surgery at the University of Colorado Health-Poudre Valley Hospital in Fort Collins, CO. The V4 region of the 16s rRNA gene was pyrosequenced and both short chain fatty acids and global stool metabolites were extracted and analyzed utilizing Gas Chromatography-Mass Spectrometry (GC-MS). There were no significant differences in the overall microbial community structure associated with the disease state, but several bacterial genera, particularly butyrate-producing species, were under-represented in the CRC samples, while a mucin-degrading species, Akkermansia muciniphila, was about 4-fold higher in CRC (p<0.01). Proportionately higher amounts of butyrate were seen in stool of healthy individuals while relative concentrations of acetate were higher in stools of CRC patients. GC-MS profiling revealed higher concentrations of amino acids in stool samples from CRC patients and higher poly and monounsaturated fatty acids and ursodeoxycholic acid, a conjugated bile acid in stool samples from healthy adults (p<0.01). Correlative analysis between the combined datasets revealed some potential relationships between stool metabolites and certain bacterial species. These associations could provide insight into microbial functions occurring in a cancer environment and will help direct future mechanistic studies. Using integrated “omics” approaches may prove a useful tool in identifying functional groups of gastrointestinal bacteria and their associated metabolites as novel therapeutic and chemopreventive targets.
Highlights
A healthy gastrointestinal system relies on a balanced commensal biota to regulate processes such as dietary energy harvest [1], metabolism of microbial and host derived chemicals [2], and immune modulation [3]
Stool metabolite profiles have been validated as a means of assessing gut microbial activity [20] and the current study contributes to the growing list of gut microbes in the colorectal cancer (CRC) microbiome, and utilizes a metabonomics approach to identify potential microbiome-metabolome interactions
We examined these parameters in stool samples from healthy individuals and those with CRC to see if they could be used as predictors of disease state.We observed no significant differences at the 3% genetic distance in the average diversity or evenness of stool microbial communities from healthy individuals compared to those with CRC (Table S1)
Summary
A healthy gastrointestinal system relies on a balanced commensal biota to regulate processes such as dietary energy harvest [1], metabolism of microbial and host derived chemicals [2], and immune modulation [3]. Sobhani et al [10] found that the Bacteroides/Prevotella group was over-represented in both stool and mucosa samples from individuals with colon cancer compared to their cancer-free counterparts. They found that Bifidobacterium longum, Clostridium clostridioforme, and Ruminococcus bromii were underrepresented in samples from these individuals and concluded that a lack of correlation between tumor stage/size with the over-represented populations suggested a contributory role of the bacteria in tumor development. Two additional studies, published concurrently, examined the microbiota present in the tumor mucosa and adjacent healthy tissue of individuals with colon cancer and both studies revealed an overrepresentation of Fusobacterium spp [11,12], while others have revealed an abundance of Coriobacteria and other probiotic species [13,14]. Stool metabolite profiles have been validated as a means of assessing gut microbial activity [20] and the current study contributes to the growing list of gut microbes in the CRC microbiome, and utilizes a metabonomics approach to identify potential microbiome-metabolome interactions
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