Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

The Intestinal Metabolome: An Intersection Between Microbiota and Host

Meta'omic Analytic Techniques for Studying the Intestinal Microbiome

Predictive functional profiling of microbial communities in fermentative hydrogen production system using PICRUSt

BackgroundAlthough high-throughput marker gene studies provide valuable insight into the diversity and relative abundance of taxa in microbial communities, they do not provide direct measures of their functional capacity. Recently, scientists have shown a general desire to predict functional profiles of microbial communities based on phylogenetic identification inferred from marker genes, and recent tools have been developed to link the two. However, to date, no large-scale examination has quantified the correlation between the marker gene based taxonomic identity and protein coding gene conservation. Here we utilize 4872 representative prokaryotic genomes from NCBI to investigate the relationship between marker gene identity and shared protein coding gene content.ResultsEven at 99–100% marker gene identity, genomes share on average less than 75% of their protein coding gene content. This occurs regardless of the marker gene(s) used: V4 region of the 16S rRNA, complete 16S rRNA, or single copy orthologs through a multi-locus sequence analysis. An important aspect related to this observation is the intra-organism variation of 16S copies from a single genome. Although the majority of 16S copies were found to have high sequence similarity (> 99%), several genomes contained copies that were highly diverged (< 97% identity).ConclusionsThis is the largest comparison between marker gene similarity and shared protein coding gene content to date. The study highlights the limitations of inferring a microbial community’s functions based on marker gene phylogeny. The data presented expands upon the results of previous studies that examined one or few bacterial species and supports the hypothesis that 16S rRNA and other marker genes cannot be directly used to fully predict the functional potential of a bacterial community.

Diet is one of the main factors that affects the composition of gut microbiota. When people move from a rural environment to urban areas, and experience improved socio-economic conditions, they are often exposed to a “globalized” Western type diet. Here, we present preliminary observations on the metagenomic scale of microbial changes in small groups of African children belonging to the same ethnicity and living in different environments, compared to children living on the urban area of Florence (Italy). We analyzed dietary habits and, by pyrosequencing of the 16S rRNA gene, gut microbiota profiles from fecal samples of children living in a rural village of Burkina Faso (n = 11), of two groups of children living in different urban settings (Nanoro town, n = 8; Ouagadougou, the capital city, n = 5) and of a group of Italian children (n = 13). We observed that when foods of animal origin, those rich in fat and simple sugars are introduced into a traditional African diet, composed of cereals, legumes and vegetables, the gut microbiota profiles changes. Microbiota of rural children retain a geographically unique bacterial reservoir (Prevotella, Treponema, and Succinivibrio), assigned to ferment fiber and polysaccharides from vegetables. Independently of geography and ethnicity, in children living in urban areas these bacterial genera were progressively outcompeted by bacteria more suited to the metabolism of animal protein, fat and sugar rich foods, similarly to Italian children, as resulted by PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a predictive functional profiling of microbial communities using 16S rRNA marker gene. Consequently, we observed a progressive reduction of SCFAs measured by gas chromatography–mass spectrometry, in urban populations, especially in Italian children, respect to rural ones. Our results even if in a limited number of individuals point out that dietary habit modifications in the course of urbanization play a role in shaping gut microbiota, and that ancient microorganisms, such as fiber-degrading bacteria, are at risk of being eliminated by the fast paced globalization of foods and by the advent of westernized lifestyle.

Two biotrickling filters were operated in continuous (BTF1) and discontinuous (BTF2) modes at a constant empty bed residence time of 60 s for 60 days. From day 60, the operation mode of each BTF was oppositely switched. Higher removal efficiencies of five aromatic pollutants were recorded with BTF1 (> 77.2%). The switch in the operation mode did not alter the removal performance of BTF1. Comparatively, BTF2 was not successfully acclimated in the discontinuous operation mode. Once the mode had been switched to continuous mode, the removal efficiencies of BTF2 on all pollutants increased drastically and finally exceeded the values observed in BTF1, with the single exception of p-xylene. Principle coordinate analysis and analysis of similarities (ANOSIM) showed that the structure of the microbial communities differed considerably between both BTFs (R = 1.000, p < 0.01) as well as before and after the switch in BTF2 (R = 0.996, p < 0.01). The random forest model demonstrated that Mycobacterium, Burkholderia, and Comamonas were the three most important bacterial genera contributing to the differences in microbial communities between the two BTFs. Metagenomics inferred by PICUSt (phylogenetic investigation of communities by reconstruction of unobserved states) indicated that BTF2 had high degradation potential for aromatic pollutants, although those genes involved in biofilm formation were less active in BTF2 than those in BTF1.

In silico analysis of soil, sediment and groundwater microbial communities to predict biodegradation potential

Obesity is a risk factor for many chronic diseases. This study aimed to investigate the effect of bariatric surgery on the gut microbiota from patients with obesity. The microbiota composition from stool samples before and after bariatric surgery were identified using bacterial 16S rRNA gene sequencing. Based on the speed of weight loss, patients were classified as the slow-loss group and fast-loss group. The ɑ- and β-diversity analysis was done to compare the species richness, evenness, and overall structure of the microbiota between different groups. Next, linear discriminant analysis effect size (LEfSe) and receiver operating characteristic (ROC) analysis were implemented to identify high-dimensional biomarkers and significantly different species of microbial taxa between different groups. Finally, the pathway analysis was inferred using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to predict the functional profiling of microbial communities. β-diversity analysis suggested that species diversity of preoperative samples of slow-loss group was significantly higher than the fast-loss group. High levels of Oscillospira and Abiotrophia in the preoperative gut microbiota may lead to poor postoperative weight loss. For patients with poor postoperative weight loss due to changes in gut microbiota, the gut microbiota is mainly composed of Lactobacillus. For patients with good postoperative results, the gut microbiota is mainly composed of Escherichia, Robinsonella, and Dialister. In addition, multiple metabolic-related pathways were significantly different between the four groups. This comparative study revealed biomarker species based on microfloral composition in patients with obesity before and after bariatric surgery.

Pineapple peel (PP) is a by-product with the potential to be used as a raw material for functional beverages. Traditional PP fermentation has so far paid little attention to the microbial community and its role in the fermentation process. As a result, the current research looked into the microbial communities and their roles during PP fermentation. A metagenomic approach based on the 16S rRNA sequencing data was used to assess the microbial communities. Subsequent analysis was performed using PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states) to analyze the microbial functions in the fermentation system. The microecology of the fermentation process in three samples was predominated by Firmicutes. Furthermore, the well-known probiotic genera Weissella, Lactobacillus, and Lactococcus were found to be predominating in the gumer, promic, and control samples, respectively. It was obvious that microenvironmental differences have an effect on the microbial composition of PP fermentation. Moreover, functional prediction revealed that carbohydrate metabolism was the most prevalent metabolic pathway during the fermentation process. Additionally, it was discovered that all of the bacteria found in the samples played significant roles in carbohydrate, amino acid, vitamin, and co-factor metabolism, which can be inferred to result in the production of beneficial metabolites.

Comparison of two bioinformatics tools used to characterize the microbial diversity and predictive functional attributes of microbial mats from Lake Obersee, Antarctica

BackgroundFor decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost-effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data.ResultsWe present a computational method called pangenome-based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU’s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome’s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8–0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed-reference OTU picking strategies against specific reference sequence databases.ConclusionsWe developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub (https://github.com/srjun/PanFP).Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1462-8) contains supplementary material, which is available to authorized users.

Heavy metal pollution is a serious environmental problem as it adversely affects crop production and human activity. In addition, the microbial community structure and composition are altered in heavy-metal-contaminated soils. In this study, using full-length 16S rRNA gene sequences obtained by a PacBio RS II system, we determined the microbial diversity and community structure in heavy-metal-contaminated soil. Furthermore, we investigated the microbial distribution, inferred their putative functional traits, and analyzed the environmental effects on the microbial compositions. The soil samples selected in this study were heavily and continuously contaminated with various heavy metals due to closed mines. We found that certain microorganisms (e.g., sulfur or iron oxidizers) play an important role in the biogeochemical cycle. Using phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) analysis, we predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) functional categories from abundances of microbial communities and revealed a high proportion belonging to transport, energy metabolism, and xenobiotic degradation in the studied sites. In addition, through full-length analysis, Conexibacter-like sequences, commonly identified by environmental metagenomics among the rare biosphere, were detected. In addition to microbial composition, we confirmed that environmental factors, including heavy metals, affect the microbial communities. Unexpectedly, among these environmental parameters, electrical conductivity (EC) might have more importance than other factors in a community description analysis.

Characterization and comparison of the temporal dynamics of ruminal bacterial microbiota colonizing rice straw and alfalfa hay within ruminants.

The use of proxies for ecosystem function in biomonitoring is desirable to move towards more holistic strategies. Next-generation sequencing of environmental DNA can clearly contribute to these advances. This research is part of a project aimed to use constructed wetlands (CWs), managed by the company Global Omnium (https://www.globalomnium.com/Group/Home/) and having the University of Valencia in charge of the scientific research, in order to improve the ecological quality of already treated wastewaters before being poured into natural environments. The rationale is that, although wastewaters treated by classical methods can meet the standards required by law, transitional constructed ecosystems, as the CWs, can promote ancillary benefits that contribute to the maintenance of the ecological health of receiving natural ecosystems. We propose that some functional traits of the microbial community can be used to outline the process of water renaturation. To assess this, the prokaryotic communities of different types of CWs were profiled by the MiSeq sequencing of the V4 region of the 16S rRNA. Using the sequences obtained, a prediction of the functional capabilities of these communities was made with the bioinformatic package PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States; https://github.com/picrust/picrust2), assuming that phylogeny and function are effectively related attributes. Predictions on the occurrence of functional marker genes, particularly those involved in the biogeochemical cycling of main nutrients (C, N, S, P), were then made. The PICRUSt2 predictions were based in the annotated genes catalog of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (https://www.genome.jp/kegg/). In general, results indicated a decline in the CWs effluents of microbial functions typical from wastewater in favor of those more suited for the receiving environment. An enhancement of aerobic metabolism was predicted to occur based on the increase of the gene encoding the cytochrome-c oxidase compared to fermentation pathways. Accordingly, both the denitrification and the dissimilatory reduction of sulfate, that are predominant in the anaerobic environments, also decreased in the effluents of the CWs to lower levels more similar to those observed in natural environments, showing a shift towards reactions at higher redox potentials. On the other hand, a development of metabolic skills for degrading plant materials (e.g., xylose, vanillin, syringate, protocatechuate) was also predicted, which was likely related to a parallel transformation of the organic matter pool in the CWs (more unreactive and natural). Additionally, increases observed in pathways for the synthesis of some cell structural compounds (e.g., mycolic acids) and coenzymes (e.g., F420 cofactor, NAD+) can be related with an enhancement of colonization and competitive potentials of the natural microbial community, as well as with changes in the actual availability of nutrients in the environment. Based on these findings, we raise the possibility of considering these functional surveys made on marker genes as a complementary strategy on the biomonitoring procedures, not only for CWs, but for the general study of freshwater ecosystem potentially affected by wastewater pollution.

Rational cropping maintains high soil fertility and a healthy ecosystem. Soil microorganism is the controller of soil fertility. Meanwhile, soil microbial communities also respond to different cropping patterns. The mechanisms by which biotic and abiotic factors were affected by different cropping sequences remain unclear in the major grain-producing regions of northeastern China. To evaluate the effects of different cropping sequences under conventional fertilization practices on soil properties, microbial communities, and crop yield, six types of plant cropping systems were performed, including soybean monoculture, wheat-soybean rotation, wheat-maize-soybean rotation, soybean-maize-maize rotation, maize-soybean-soybean rotation and maize monoculture. Our results showed that compared with the single cropping system, soybean and maize crop rotation in different combinations or sequences can increase soil total organic carbon and nutrients, and promote soybean and maize yield, especially using soybean-maize-maize and maize-soybean-soybean planting system. The 16S rRNA and internal transcribed spacer (ITS) amplicon sequencing showed that different cropping systems had different effects on bacterial and fungal communities. The bacterial and fungal communities of soybean monoculture were less diverse when compared to the other crop rotation planting system. Among the different cropping sequences, the number of observed bacterial species was greater in soybean-maize-maize planting setup and fungal species in maize-soybean-soybean planting setup. Some dominant and functional bacterial and fungal taxa in the rotation soils were observed. Network-based analysis suggests that bacterial phyla Acidobacteria and Actinobacteria while fungal phylum Ascomycota showed a positive correlation with other microbial communities. The phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) result showed the presence of various metabolic pathways. Besides, the soybean-maize-maize significantly increased the proportion of some beneficial microorganisms in the soil and reduced the soil-borne animal and plant pathogens. These results warrant further investigation into the mechanisms driving responses of beneficial microbial communities and their capacity on improving soil fertility during legume cropping. The present study extends our understanding of how different crop rotations effect soil parameters, microbial diversity, and metabolic functions, and reveals the importance of crop rotation sequences. These findings could be used to guide decision-making from the microbial perspective for annual crop planting and soil management approaches.