Despite a long-suspected role in the development of human colorectal cancer (CRC), the composition of gut microbiota in CRC patients has not been adequately described. In this study, fecal bacterial diversity in CRC patients (n=46) and healthy volunteers (n=56) were profiled by 454 pyrosequencing of the V3 region of the 16S ribosomal RNA gene. Both principal component analysis and UniFrac analysis showed structural segregation between the two populations. Forty-eight operational taxonomic units (OTUs) were identified by redundancy analysis as key variables significantly associated with the structural difference. One OTU closely related to Bacteroides fragilis was enriched in the gut microbiota of CRC patients, whereas three OTUs related to Bacteroides vulgatus and Bacteroides uniformis were enriched in that of healthy volunteers. A total of 11 OTUs belonging to the genera Enterococcus, Escherichia/Shigella, Klebsiella, Streptococcus and Peptostreptococcus were significantly more abundant in the gut microbiota of CRC patients, and 5 OTUs belonging to the genus Roseburia and other butyrate-producing bacteria of the family Lachnospiraceae were less abundant. Real-time quantitative PCR further validated the significant reduction of butyrate-producing bacteria in the gut microbiota of CRC patients by measuring the copy numbers of butyryl-coenzyme A CoA transferase genes (Mann–Whitney test, P<0.01). Reduction of butyrate producers and increase of opportunistic pathogens may constitute a major structural imbalance of gut microbiota in CRC patients.

Humans have evolved intimate symbiotic relationships with a consortium of gut microbes (microbiome) and individual variations in the microbiome influence host health, may be implicated in disease etiology, and affect drug metabolism, toxicity, and efficacy. However, the molecular basis of these microbe–host interactions and the roles of individual bacterial species are obscure. We now demonstrate a“transgenomic” approach to link gut microbiome and metabolic phenotype (metabotype) variation. We have used a combination of spectroscopic, microbiomic, and multivariate statistical tools to analyze fecal and urinary samples from seven Chinese individuals (sampled twice) and to model the microbial–host metabolic connectivities. At the species level, we found structural differences in the Chinese family gut microbiomes and those reported for American volunteers, which is consistent with population microbial cometabolic differences reported in epidemiological studies. We also introduce the concept of functional metagenomics, defined as “the characterization of key functional members of the microbiome that most influence host metabolism and hence health.” For example, Faecalibacterium prausnitzii population variation is associated with modulation of eight urinary metabolites of diverse structure, indicating that this species is a highly functionally active member of the microbiome, influencing numerous host pathways. Other species were identified showing different and varied metabolic interactions. Our approach for understanding the dynamic basis of host–microbiome symbiosis provides a foundation for the development of functional metagenomics as a probe of systemic effects of drugs and diet that are of relevance to personal and public health care solutions.

Hepatocellular carcinoma (HCC) is a common malignancy in the world with high morbidity and mortality rate. Identification of novel biomarkers in HCC remains impeded primarily because of the heterogeneity of the disease in clinical presentations as well as the pathophysiological variations derived from underlying conditions such as cirrhosis and steatohepatitis. The aim of this study is to search for potential metabolite biomarkers of human HCC using serum and urine metabolomics approach. Sera and urine samples were collected from patients with HCC (n = 82), benign liver tumor patients (n = 24), and healthy controls (n = 71). Metabolite profiling was performed by gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography-quadrupole time of flight mass spectrometry in conjunction with univariate and multivariate statistical analyses. Forty three serum metabolites and 31 urinary metabolites were identified in HCC patients involving several key metabolic pathways such as bile acids, free fatty acids, glycolysis, urea cycle, and methionine metabolism. Differentially expressed metabolites in HCC subjects, such as bile acids, histidine, and inosine are of great statistical significance and high fold changes, which warrant further validation as potential biomarkers for HCC. However, alterations of several bile acids seem to be affected by the condition of liver cirrhosis and hepatitis. Quantitative measurement and comparison of seven bile acids among benign liver tumor patients with liver cirrhosis and hepatitis, HCC patients with liver cirrhosis and hepatitis, HCC patients without liver cirrhosis and hepatitis, and healthy controls revealed that the abnormal levels of glycochenodeoxycholic acid, glycocholic acid, taurocholic acid, and chenodeoxycholic acid are associated with liver cirrhosis and hepatitis. HCC patients with alpha fetoprotein values lower than 20 ng/ml was successfully differentiated from healthy controls with an accuracy of 100% using a panel of metabolite markers. Our work shows that metabolomic profiling approach is a promising screening tool for the diagnosis and stratification of HCC patients.

Schizophrenia is a severe mental disorder that affects 0.5–1% of the population worldwide. Current diagnostic methods are based on psychiatric interviews, which are subjective in nature. The lack of disease biomarkers to support objective laboratory tests has been a long-standing bottleneck in the clinical diagnosis and evaluation of schizophrenia. Here we report a global metabolic profiling study involving 112 schizophrenic patients and 110 healthy subjects, who were divided into a training set and a test set, designed to identify metabolite markers. A panel of serum markers consisting of glycerate, eicosenoic acid, β-hydroxybutyrate, pyruvate and cystine was identified as an effective diagnostic tool, achieving an area under the receiver operating characteristic curve (AUC) of 0.945 in the training samples (62 patients and 62 controls) and 0.895 in the test samples (50 patients and 48 controls). Furthermore, a composite panel by the addition of urine β-hydroxybutyrate to the serum panel achieved a more satisfactory accuracy, which reached an AUC of 1 in both the training set and the test set. Multiple fatty acids and ketone bodies were found significantly (P<0.01) elevated in both the serum and urine of patients, suggesting an upregulated fatty acid catabolism, presumably resulting from an insufficiency of glucose supply in the brains of schizophrenia patients.