Yunping Qiu

Symbiotic gut microbes modulate human metabolic phenotypes

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.

Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers

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.

Serum Metabolite Profiling of Human Colorectal Cancer Using GC−TOFMS and UPLC−QTOFMS

Colorectal carcinogenesis involves the overexpression of many immediate-early response genes associated with growth and inflammation, which significantly alters downstream protein synthesis and small-molecule metabolite production. We have performed a serum metabolic analysis to test the hypothesis that the distinct metabolite profiles of malignant tumors are reflected in biofluids. In this study, we have analyzed the serum metabolites from 64 colorectal cancer (CRC) patients and 65 healthy controls using gas chromatography time-of-flight mass spectrometry (GC-TOFMS) and Acquity ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (Acquity UPLC-QTOFMS). Orthogonal partial least-squares discriminate analysis (OPLS-DA) models generated from GC-TOFMS and UPLC-QTOFMS metabolic profile data showed robust discrimination from CRC patients and healthy controls. A total of 33 differential metabolites were identified using these two analytical platforms, five of which were detected in both instruments. These metabolites potentially reveal perturbation of glycolysis, arginine and proline metabolism, fatty acid metabolism and oleamide metabolism, associated with CRC morbidity. These results suggest that serum metabolic profiling has great potential in detecting CRC and helping to understand its underlying mechanisms.

Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma

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.

Urinary metabonomic study on colorectal cancer.

After our serum metabonomic study of colorectal cancer (CRC) patients recently published in J. Proteome Res., we profiled urine metabolites from the same group of CRC patients (before and after surgical operation) and 63 age-matched healthy volunteers using gas chromatography-mass spectrometry (GC-MS) in conjunction with a multivariate statistics technique. A parallel metabonomic study on a 1,2-dimethylhydrazine (DMH)-treated Sprague-Dawley rat model was also performed to identify significantly altered metabolites associated with chemically induced precancerous colorectal lesion. The orthogonal partial least-squares-discriminant analysis (OPLS-DA) models of metabonomic results demonstrated good separations between CRC patients or DMH-induced model rats and their healthy counterparts. The significantly increased tryptophan metabolism, and disturbed tricarboxylic acid (TCA) cycle and the gut microflora metabolism were observed in both the CRC patients and the rat model. The urinary metabolite profile of postoperative CRC subjects altered significantly from that of the preoperative stage. The significantly down-regulated gut microflora metabolism and TCA cycle were observed in postoperative CRC subjects, presumably due to the colon flush involved in the surgical procedure and weakened physical conditions of the patients. The expression of 5-hydroxytryptophan significantly decreased in postsurgery samples, suggesting a recovered tryptophan metabolism toward healthy state. Abnormal histamine metabolism and glutamate metabolism were found only in the urine samples of CRC patients, and the abnormal polyamine metabolism was found only in the rat urine. This study assessed the important metabonomic variations in urine associated with CRC and, therefore, provided baseline information complementary to serum/plasma and tissue metabonomics for the complete elucidation of the underlying metabolic mechanisms of CRC.

Metabolic profiling reveals disorder of amino acid metabolism in four brain regions from a rat model of chronic unpredictable mild stress

Chronic stress is closely linked to clinical depression, which could be assessed by a chronic unpredictable mild stress (CUMS) animal model. We present here a GC/MS‐based metabolic profiling approach to investigate neurochemical changes in the cerebral cortex, hippocampus, thalamus, and remaining brain tissues. Multi‐criteria assessment for multivariate statistics could identify differential metabolites between the CUMS‐model rats versus the healthy controls. This study demonstrates that the significantly perturbed metabolites mainly involving amino acids play an indispensable role in regulating neural activity in the brain. Therefore, results obtained from such metabolic profiling strategy potentially provide a unique perspective on molecular mechanisms of chronic stress.

Potential Metabolite Markers of Schizophrenia

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.

Salivary metabolite signatures of oral cancer and leukoplakia

Oral cancer, one of the six most common human cancers with an overall 5‐year survival rate of <50%, is often not diagnosed until it has reached an advanced stage. The aim of the current study is to explore salivary metabolomics as a disease diagnostic and stratification tool for oral cancer and leukoplakia and evaluate the potential of salivary metabolome for detection of oral squamous cell carcinoma (OSCC). Saliva metabolite profiling for a group of 37 OSCC patients, 32 oral leukoplakia (OLK) patients and 34 healthy subjects was performed using ultraperformance liquid chromatography coupled with quadrupole/time‐of‐flight mass spectrometry in conjunction with multivariate statistical analysis. The OSCC, OLK and healthy control groups demonstrate characteristic salivary metabolic signatures. A panel of five salivary metabolites including γ‐aminobutyric acid, phenylalanine, valine, n‐eicosanoic acid and lactic acid were selected using OPLS‐DA model with S‐plot. The predictive power of each of the five salivary metabolites was evaluated by receiver operating characteristic curves for OSCC. Valine, lactic acid and phenylalanine in combination yielded satisfactory accuracy (0.89, 0.97), sensitivity (86.5% and 94.6%), specificity (82.4% and 84.4%) and positive predictive value (81.6% and 87.5%) in distinguishing OSCC from the controls or OLK, respectively. The utility of salivary metabolome diagnostics for oral cancer is successfully demonstrated in this study and these results suggest that metabolomics approach complements the clinical detection of OSCC and stratifies the two types of lesions, leading to an improved disease diagnosis and prognosis.

Distinct urinary metabolic profile of human colorectal cancer.

A full spectrum of metabolic aberrations that are directly linked to colorectal cancer (CRC) at early curable stages is critical for developing and deploying molecular diagnostic and therapeutic approaches that will significantly improve patient survival. We have recently reported a urinary metabonomic profiling study on CRC subjects (n = 60) and health controls (n = 63), in which a panel of urinary metabolite markers was identified. Here, we report a second urinary metabonomic study on a larger cohort of CRC (n = 101) and healthy subjects (n = 103), using gas chromatography time-of-flight mass spectrometry and ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Consistent with our previous findings, we observed a number of dysregulated metabolic pathways, such as glycolysis, TCA cycle, urea cycle, pyrimidine metabolism, tryptophan metabolism, polyamine metabolism, as well as gut microbial-host co-metabolism in CRC subjects. Our findings confirm distinct urinary metabolic footprints of CRC patients characterized by altered levels of metabolites derived from gut microbial-host co-metabolism. A panel of metabolite markers composed of citrate, hippurate, p-cresol, 2-aminobutyrate, myristate, putrescine, and kynurenate was selected, which was able to discriminate CRC subjects from their healthy counterparts. A receiver operating characteristic curve (ROC) analysis of these markers resulted in an area under the receiver operating characteristic curve (AUC) of 0.993 and 0.998 for the training set and the testing set, respectively. These potential metabolite markers provide a novel and promising molecular diagnostic approach for the early detection of CRC.

Metabonomic variations in the drug-treated type 2 diabetes mellitus patients and healthy volunteers.

The pathological development and the drug intervention of type 2 diabetes mellitus (T2DM) involve altered expression of downstream low molecular weight metabolites including lipids and amino acids, and carbohydrates such as glucose. Currently, a small number of markers used for clinical assessment of T2DM treatment may be insufficient to reflect global variations in pathophysiology. In this study, a metabonomic study was performed to determine metabolic variations associated with T2DM and the drug treatments on 74 patients who were newly diagnosed with T2DM and received a 48 week treatment of a single drug, repaglinide, metformin or rosiglitazone. Fasting overnight and 2 h postprandial blood serum of patients were collected at 24 and 48 weeks to monitor the biochemical indices (FPG, 2hPG, HbA1c, etc.). Gas chromatography/mass spectrometer coupled with multivariate statistical analysis was used to identify the alteration of global serum metabolites associated with T2DM as compared to healthy controls and responses to drug treatment. Significantly altered serum metabolites in diabetic subjects include increased valine, maltose, glutamate, urate, butanoate and long-chain fatty acid (C16:0, C18:1, C18:0, octadecanoate and arachidonate), and decreased glucuronolactone, lysine and lactate. All of the three treatments were able to down-regulate the high level of glutamate to a lower level in serum of T2DM patients, but rosiglitazone treatment was able to reverse more abnormal levels of metabolites, such as valine, lysine, glucuronolactone, C16:0, C18:1, urate, and octadecanoate, suggesting that it is more efficient to alter the metabolism of T2DM patients than the other two drugs.