Leo Lahti

Binning metagenomic contigs by coverage and composition

Shotgun sequencing enables the reconstruction of genomes from complex microbial communities, but because assembly does not reconstruct entire genomes, it is necessary to bin genome fragments. Here we present CONCOCT, a new algorithm that combines sequence composition and coverage across multiple samples, to automatically cluster contigs into genomes. We demonstrate high recall and precision on artificial as well as real human gut metagenome data sets.

Fat, fibre and cancer risk in African Americans and rural Africans

Rates of colon cancer are much higher in African Americans (65:100,000) than in rural South Africans (<5:100,000). The higher rates are associated with higher animal protein and fat and lower fiber consumption, higher colonic secondary bile acids, lower colonic short chain fatty acid quantities and higher mucosal proliferative biomarkers of cancer risk in otherwise healthy middle aged volunteers. Here we investigate further the role of fat and fiber in this association. We performed two-week food exchanges in subjects from the same populations, where African Americans were fed a high-fiber, lowfat African-style diet, and rural Africans a high-fat low-fiber western-style diet under close supervision. In comparison to their usual diets, the food changes resulted in remarkable reciprocal changes in mucosal biomarkers of cancer risk and in aspects of the microbiota and metabolome known to affect cancer risk, best illustrated by increased saccharolytic fermentation and butyrogenesis and suppressed secondary bile acid synthesis in the African Americans.

Intestinal Microbiota in Healthy Adults: Temporal Analysis Reveals Individual and Common Core and Relation to Intestinal Symptoms

Background While our knowledge of the intestinal microbiota during disease is accumulating, basic information of the microbiota in healthy subjects is still scarce. The aim of this study was to characterize the intestinal microbiota of healthy adults and specifically address its temporal stability, core microbiota and relation with intestinal symptoms. We carried out a longitudinal study by following a set of 15 healthy Finnish subjects for seven weeks and regularly assessed their intestinal bacteria and archaea with the Human Intestinal Tract (HIT)Chip, a phylogenetic microarray, in conjunction with qPCR analyses. The health perception and occurrence of intestinal symptoms was recorded by questionnaire at each sampling point. Principal Findings A high overall temporal stability of the microbiota was observed. Five subjects showed transient microbiota destabilization, which correlated not only with the intake of antibiotics but also with overseas travelling and temporary illness, expanding the hitherto known factors affecting the intestinal microbiota. We identified significant correlations between the microbiota and common intestinal symptoms, including abdominal pain and bloating. The most striking finding was the inverse correlation between Bifidobacteria and abdominal pain: subjects who experienced pain had over five-fold less Bifidobacteria compared to those without pain. Finally, a novel computational approach was used to define the common core microbiota, highlighting the role of the analysis depth in finding the phylogenetic core and estimating its size. The in-depth analysis suggested that we share a substantial number of our intestinal phylotypes but as they represent highly variable proportions of the total community, many of them often remain undetected. Conclusions/Significance A global and high-resolution microbiota analysis was carried out to determine the temporal stability, the associations with intestinal symptoms, and the individual and common core microbiota in healthy adults. The findings provide new approaches to define intestinal health and to further characterize the microbial communities inhabiting the human gut.

CDKN2A, NF2, and JUN Are Dysregulated Among Other Genes by miRNAs in Malignant Mesothelioma—A miRNA Microarray Analysis

Malignant mesothelioma (MM) is an aggressive cancer arising from mesothelial cells, mainly due to former asbestos exposure. Little is known about the microRNA (miRNA) expression of MM. miRNAs are small noncoding RNAs, which play an essential role in the regulation of gene expression. This study was carried out to analyze the miRNA expression profile of 17 MM samples using miRNA microarray. The analysis distinguished the overall miRNA expression profiles of tumor tissue and normal mesothelium. Differentially expressed miRNAs were found in tumor samples compared with normal sample. Twelve of them, let‐7b*, miR‐1228*, miR‐195*, miR‐30b*, miR‐32*, miR‐345, miR‐483‐3p, miR‐584, miR‐595, miR‐615‐3p, and miR‐885‐3p, were highly expressed whereas the remaining nine, let‐7e*, miR‐144*, miR‐203, miR‐340*, miR‐34a*, miR‐423, miR‐582, miR‐7‐1*, and miR‐9, were unexpressed or had severely reduced expression levels. Target genes for these miRNAs include the most frequently affected genes in MM such as CDKN2A, NF2, JUN, HGF, and PDGFA. Many of the miRNAs were located in chromosomal areas known to be deleted or gained in MM such as 8q24, 1p36, and 14q32. Furthermore, we could identify specific miRNAs for each histopathological subtype of MM. Regarding risk factors such as smoking status and asbestos exposure, significantly differentially expressed miRNAs were identified in smokers versus nonsmokers (miR‐379, miR‐301a, miR‐299‐3p, miR‐455‐3p, and miR‐127‐3p), but not in asbestos‐exposed patients versus nonexposed ones. This could be related to the method of assessment of asbestos exposure as asbestos remains to be the main contributor to the development of MM.

Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men

There is growing interest in understanding how diet affects the intestinal microbiota, including its possible associations with systemic diseases such as metabolic syndrome. Here we report a comprehensive and deep microbiota analysis of 14 obese males consuming fully controlled diets supplemented with resistant starch (RS) or non-starch polysaccharides (NSPs) and a weight-loss (WL) diet. We analyzed the composition, diversity and dynamics of the fecal microbiota on each dietary regime by phylogenetic microarray and quantitative PCR (qPCR) analysis. In addition, we analyzed fecal short chain fatty acids (SCFAs) as a proxy of colonic fermentation, and indices of insulin sensitivity from blood samples. The diet explained around 10% of the total variance in microbiota composition, which was substantially less than the inter-individual variance. Yet, each of the study diets induced clear and distinct changes in the microbiota. Multiple Ruminococcaceae phylotypes increased on the RS diet, whereas mostly Lachnospiraceae phylotypes increased on the NSP diet. Bifidobacteria decreased significantly on the WL diet. The RS diet decreased the diversity of the microbiota significantly. The total 16S ribosomal RNA gene signal estimated by qPCR correlated positively with the three major SCFAs, while the amount of propionate specifically correlated with the Bacteroidetes. The dietary responsiveness of the individual’s microbiota varied substantially and associated inversely with its diversity, suggesting that individuals can be stratified into responders and non-responders based on the features of their intestinal microbiota.

Metagenomics meets time series analysis: unraveling microbial community dynamics

The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the worlds oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic patterns, help to build predictive models or, on the contrary, quantify irregularities that make community behavior unpredictable. Microbial communities can change abruptly in response to small perturbations, linked to changing conditions or the presence of multiple stable states. With sufficient samples or time points, such alternative states can be detected. In addition, temporal variation of microbial interactions can be captured with time-varying networks. Here, we apply these techniques on multiple longitudinal datasets to illustrate their potential for microbiome research.

Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data

Accumulating evidence indicates that the intestinal microbiota regulates our physiology and metabolism. Bacteria marketed as probiotics confer health benefits that may arise from their ability to affect the microbiota. Here high-throughput screening of the intestinal microbiota was carried out and integrated with serum lipidomic profiling data to study the impact of probiotic intervention on the intestinal ecosystem, and to explore the associations between the intestinal bacteria and serum lipids. We performed a comprehensive intestinal microbiota analysis using a phylogenetic microarray before and after Lactobacillus rhamnosus GG intervention. While a specific increase in the L. rhamnosus-related bacteria was observed during the intervention, no other changes in the composition or stability of the microbiota were detected. After the intervention, lactobacilli returned to their initial levels. As previously reported, also the serum lipid profiles remained unaltered during the intervention. Based on a high-resolution microbiota analysis, intake of L. rhamnosus GG did not modify the composition of the intestinal ecosystem in healthy adults, indicating that probiotics confer their health effects by other mechanisms. The most prevailing association between the gut microbiota and lipid profiles was a strong positive correlation between uncultured phylotypes of Ruminococcus gnavus-group and polyunsaturated serum triglycerides of dietary origin. Moreover, a positive correlation was detected between serum cholesterol and Collinsella (Coriobacteriaceae). These associations identified with the spectrometric lipidome profiling were corroborated by enzymatically determined cholesterol and triglyceride levels. Actinomycetaceae correlated negatively with triglycerides of highly unsaturated fatty acids while a set of Proteobacteria showed negative correlation with ether phosphatidylcholines. Our results suggest that several members of the Firmicutes, Actinobacteria and Proteobacteria may be involved in the metabolism of dietary and endogenous lipids, and provide a scientific rationale for further human studies to explore the role of intestinal microbes in host lipid metabolism.

Tipping elements in the human intestinal ecosystem

The microbial communities living in the human intestine can have profound impact on our well-being and health. However, we have limited understanding of the mechanisms that control this complex ecosystem. Here, based on a deep phylogenetic analysis of the intestinal microbiota in a thousand western adults, we identify groups of bacteria that exhibit robust bistable abundance distributions. These bacteria are either abundant or nearly absent in most individuals, and exhibit decreased temporal stability at the intermediate abundance range. The abundances of these bimodally distributed bacteria vary independently, and their abundance distributions are not affected by short-term dietary interventions. However, their contrasting alternative states are associated with host factors such as ageing and overweight. We propose that the bistable groups reflect tipping elements of the intestinal microbiota, whose critical transitions may have profound health implications and diagnostic potential.

Integrative analysis of microRNA, mRNA and aCGH data reveals asbestos- and histology-related changes in lung cancer

Lung cancer has the highest mortality rate of all of the cancers in the world and asbestos‐related lung cancer is one of the leading occupational cancers. The identification of asbestos‐related molecular changes has long been a topic of increasing research interest. The aim of this study was to identify novel asbestos‐related molecular correlates by integrating miRNA expression profiling with previously obtained profiling data (aCGH and mRNA expression) from the same patient material. miRNA profiling was performed on 26 tumor and corresponding normal lung tissue samples from highly asbestos‐exposed and non‐exposed patients, and on eight control lung tissue samples. Data analyses on miRNA expression, and integration of miRNA and previously obtained mRNA data were performed using Chipster. A separate analysis was used to integrate miRNA and previously obtained aCGH data. Both known and new lung cancer‐associated miRNAs and target genes with inverse correlation were discovered. Furthermore, DNA copy number alterations (e.g., gain at 12p13.31) were correlated with the deregulated miRNAs. Specifically, thirteen novel asbestos‐related miRNAs (over‐expressed: miR‐148b, miR‐374a, miR‐24‐1*, Let‐7d, Let‐7e, miR‐199b‐5p, miR‐331‐3p, and miR‐96 and under‐expressed: miR‐939, miR‐671‐5p, miR‐605, miR‐1224‐5p and miR‐202) and inversely correlated target genes (e.g., GADD45A, LTBP1, FOSB, NCALD, CACNA2D2, MTSS1, EPB41L3) were identified. In addition, over‐expression of the well known squamous cell carcinoma‐associated miR‐205 was linked to down‐regulation of the DOK4 gene. The miRNAs/genes presented here may represent interesting targets for further investigation and could eventually have potential diagnostic implications.

MicroRNA profiling predicts survival in anti-EGFR treated chemorefractory metastatic colorectal cancer patients with wild-type KRAS and BRAF

Anti-EGFR monoclonal antibodies (anti-EGFRmAb) serve in the treatment of metastatic colorectal cancer (mCRC), but patients with a mutation in KRAS/BRAF and nearly one-half of those without the mutation fail to respond. We performed microRNA (miRNA) analysis to find miRNAs predicting anti-EGFRmAb efficacy. Of the 99 mCRC patients, we studied differential miRNA expression by microarrays from primary tumors of 33 patients who had wild-type KRAS/BRAF and third- to sixth-line anti-EGFRmAb treatment, with/without irinotecan. We tested the association of each miRNA with overall survival (OS) by the Cox proportional hazards regression model. Significant miR-31* up-regulation and miR-592 down-regulation appeared in progressive disease versus disease control. miR-31* expression and down-regulation of its target genes SLC26A3 and ATN1 were verified by quantitative reverse transcriptase polymerase chain reaction. Clustering of patients based on miRNA expression revealed a significant difference in OS between patient clusters. Members of the let-7 family showed significant up-regulation in the patient cluster with poor OS. Additionally, miR-140-5p up-regulation and miR-1224-5p down-regulation were significantly associated with poor OS in both cluster analysis and the Cox proportional hazards regression model. In mCRC patients with wild-type KRAS/BRAF, miRNA profiling can efficiently predict the benefits of anti-EGFRmAb treatment. Larger series of patients are necessary for application of these miRNAs as predictive/prognostic markers.