Characterization Of Complex Microbial Communities Research Articles

Modeling Dynamics of Human Gut Microbiota Derived from Gluten Metabolism: Obtention, Maintenance and Characterization of Complex Microbial Communities.

Western diets are rich in gluten-containing products, which are frequently poorly digested. The human large intestine harbors microorganisms able to metabolize undigested gluten fragments that have escaped digestion by human enzymatic activities. The aim of this work was obtaining and culturing complex human gut microbial communities derived from gluten metabolism to model the dynamics of healthy human large intestine microbiota associated with different gluten forms. For this purpose, stool samples from six healthy volunteers were inoculated in media containing predigested gluten or predigested gluten plus non-digested gluten. Passages were carried out every 24 h for 15 days in the same medium and community composition along time was studied via V3-V4 16S rDNA sequencing. Diverse microbial communities were successfully obtained. Moreover, communities were shown to be maintained in culture with stable composition for 14 days. Under non-digested gluten presence, communities were enriched in members of Bacillota, such as Lachnospiraceae, Clostridiaceae, Streptococcaceae, Peptoniphilaceae, Selenomonadaceae or Erysipelotrichaceae, and members of Actinomycetota, such as Bifidobacteriaceae and Eggerthellaceae. Contrarily, communities exposed to digested gluten were enriched in Pseudomonadota. Hence, this study shows a method for culture and stable maintenance of gut communities derived from gluten metabolism. This method enables the analysis of microbial metabolism of gluten in the gut from a community perspective.

Symbiont-screener: A reference-free tool to separate host sequences from symbionts for error-prone long reads

Metagenomic sequencing facilitates large-scale constitutional analysis and functional characterization of complex microbial communities without cultivation. Recent advances in long-read sequencing techniques utilize long-range information to simplify repeat-aware metagenomic assembly puzzles and complex genome binning tasks. However, it remains methodologically challenging to remove host-derived DNA sequences from the microbial community at the read resolution due to high sequencing error rates and the absence of reference genomes. We here present Symbiont-Screener (https://github.com/BGI-Qingdao/Symbiont-Screener), a reference-free approach to identifying high-confidence host’s long reads from symbionts and contaminants and overcoming the low sequencing accuracy according to a trio-based screening model. The remaining host’s sequences are then automatically grouped by unsupervised clustering. When applied to both simulated and real long-read datasets, it maintains higher precision and recall rates of identifying the host’s raw reads compared to other tools and hence promises the high-quality reconstruction of the host genome and associated metagenomes. Furthermore, we leveraged both PacBio HiFi and nanopore long reads to separate the host’s sequences on a real host-microbe system, an algal-bacterial sample, and retrieved an obvious improvement of host assembly in terms of assembly contiguity, completeness, and purity. More importantly, the residual symbiotic microbiomes illustrate improved genomic profiling and assemblies after the screening, which elucidates a solid basis of data for downstream bioinformatic analyses, thus providing a novel perspective on symbiotic research.

MIntO: A Modular and Scalable Pipeline For Microbiome Metagenomic and Metatranscriptomic Data Integration.

Omics technologies have revolutionized microbiome research allowing the characterization of complex microbial communities in different biomes without requiring their cultivation. As a consequence, there has been a great increase in the generation of omics data from metagenomes and metatranscriptomes. However, pre-processing and analysis of these data have been limited by the availability of computational resources, bioinformatics expertise and standardized computational workflows to obtain consistent results that are comparable across different studies. Here, we introduce MIntO (Microbiome Integrated meta-Omics), a highly versatile pipeline that integrates metagenomic and metatranscriptomic data in a scalable way. The distinctive feature of this pipeline is the computation of gene expression profile through integrating metagenomic and metatranscriptomic data taking into account the community turnover and gene expression variations to disentangle the mechanisms that shape the metatranscriptome across time and between conditions. The modular design of MIntO enables users to run the pipeline using three available modes based on the input data and the experimental design, including de novo assembly leading to metagenome-assembled genomes. The integrated pipeline will be relevant to provide unique biochemical insights into microbial ecology by linking functions to retrieved genomes and to examine gene expression variation. Functional characterization of community members will be crucial to increase our knowledge of the microbiome’s contribution to human health and environment. MIntO v1.0.1 is available at https://github.com/arumugamlab/MIntO.

A priori estimation of sequencing effort in complex microbial metatranscriptomes.

Metatranscriptome analysis or the analysis of the expression profiles of whole microbial communities has the additional challenge of dealing with a complex system with dozens of different organisms expressing genes simultaneously. An underlying issue for virtually all metatranscriptomic sequencing experiments is how to allocate the limited sequencing budget while guaranteeing that the libraries have sufficient depth to cover the breadth of expression of the community. Estimating the required sequencing depth to effectively sample the target metatranscriptome using RNA‐seq is an essential first step to obtain robust results in subsequent analysis and to avoid overexpansion, once the information contained in the library reaches saturation. Here, we present a method to calculate the sequencing effort using a simulated series of metatranscriptomic/metagenomic matrices. This method is based on an extrapolation rarefaction curve using a Weibull growth model to estimate the maximum number of observed genes as a function of sequencing depth. This approach allowed us to compute the effort at different confidence intervals and to obtain an approximate a priori effort based on an initial fraction of sequences. The analytical pipeline presented here may be successfully used for the in‐depth and time‐effective characterization of complex microbial communities, representing a useful tool for the microbiome research community.

PCR effects of melting temperature adjustment of individual primers in degenerate primer pools.

Deep sequencing of small subunit ribosomal RNA (SSU rRNA) gene amplicons continues to be the most common approach for characterization of complex microbial communities. PCR amplifications of conserved regions of SSU rRNA genes often employ degenerate pools of primers to enable targeting of a broad spectrum of organisms. One little noticed feature of such degenerate primer sets is the potential for a wide range of melting temperatures between the primer variants. The melting temperature variation of primers in a degenerate pool could lead to variable amplification efficiencies and PCR bias. Thus, we sought to adjust the melting temperature of each primer variant individually. Individual primer modifications were used to reduce theoretical melting temperature variation between primers, as well as to introduce inter-cluster nucleotide diversity during Illumina sequencing of primer regions. We demonstrate here the suitability of such primers for microbial community analysis. However, no substantial differences in microbial community structure were revealed when using primers with adjusted melting temperatures, though the optimal annealing temperature decreased.

MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data.

MotivationAnalysis toolkits for shotgun metagenomic data achieve strain-level characterization of complex microbial communities by capturing intra-species gene content variation. Yet, these tools are hampered by the extent of reference genomes that are far from covering all microbial variability, as many species are still not sequenced or have only few strains available. Binning co-abundant genes obtained from de novo assembly is a powerful reference-free technique to discover and reconstitute gene repertoire of microbial species. While current methods accurately identify species core parts, they miss many accessory genes or split them into small gene groups that remain unassociated to core clusters.ResultsWe introduce MSPminer, a computationally efficient software tool that reconstitutes Metagenomic Species Pan-genomes (MSPs) by binning co-abundant genes across metagenomic samples. MSPminer relies on a new robust measure of proportionality coupled with an empirical classifier to group and distinguish not only species core genes but accessory genes also. Applied to a large scale metagenomic dataset, MSPminer successfully delineates in a few hours the gene repertoires of 1661 microbial species with similar specificity and higher sensitivity than existing tools. The taxonomic annotation of MSPs reveals microorganisms hitherto unknown and brings coherence in the nomenclature of the species of the human gut microbiota. The provided MSPs can be readily used for taxonomic profiling and biomarkers discovery in human gut metagenomic samples. In addition, MSPminer can be applied on gene count tables from other ecosystems to perform similar analyses.Availability and implementationThe binary is freely available for non-commercial users at www.enterome.com/downloads.Supplementary information Supplementary data are available at Bioinformatics online.

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

BackgroundMetatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function.ResultsHere, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76 % of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions.ConclusionsThe application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-015-0146-x) contains supplementary material, which is available to authorized users.

Characterization and comparison of the bacterial microbiota in different gastrointestinal tract compartments in horses

The advance of new sequencing technologies has allowed more comprehensive characterization of complex microbial communities, including the ones inhabiting the intestinal tract. The presence of extreme environmental filters, such as low pH, digestive enzymes and anaerobic conditions along the tract, acts on the selection of unique bacteria in each compartment. The intestinal microbiota has an enormous impact on the maintenance of health. However, data about the bacteria present in the different intestinal compartments of horses are sparse. In this study, high throughput sequencing was used to characterize and compare bacterial profiles from different intestinal compartments of 11 horses scheduled for euthanasia for reasons other than gastrointestinal problems.Marked differences among compartments even at high taxonomic levels were found, with Firmicutes comprising the main bacterial phylum in all compartments. Lactobacillus spp. and Sarcina spp. predominated in the stomach and a marked increase of Streptococcus spp. occurred in the duodenum. Actinobacillus and Clostridium sensu stricto were the most abundant genera in the ileum and ‘5 genus incertae sedis’, a genus from the Subdivision 5 class of the Verrucomicrobia, was the most abundant from the large colon through feces. There was a significant increase in diversity towards the distal gut with similar profiles observed from the cecum through feces at the class level. The bacterial population comprising the equine intestinal tract varies greatly among compartments and fecal samples may be useful as representative of changes occurring in the distal compartments.

A straightforward and efficient analytical pipeline for metaproteome characterization.

BackgroundThe massive characterization of host-associated and environmental microbial communities has represented a real breakthrough in the life sciences in the last years. In this context, metaproteomics specifically enables the transition from assessing the genomic potential to actually measuring the functional expression of a microbiome. However, significant research efforts are still required to develop analysis pipelines optimized for metaproteome characterization.ResultsThis work presents an efficient analytical pipeline for shotgun metaproteomic analysis, combining bead-beating/freeze-thawing for protein extraction, filter-aided sample preparation for cleanup and digestion, and single-run liquid chromatography-tandem mass spectrometry for peptide separation and identification. The overall procedure is more time-effective and less labor-intensive when compared to state-of-the-art metaproteomic techniques. The pipeline was first evaluated using mock microbial mixtures containing different types of bacteria and yeasts, enabling the identification of up to over 15,000 non-redundant peptide sequences per run with a linear dynamic range from 104 to 108 colony-forming units. The pipeline was then applied to the mouse fecal metaproteome, leading to the overall identification of over 13,000 non-redundant microbial peptides with a false discovery rate of <1%, belonging to over 600 different microbial species and 250 functionally relevant protein families. An extensive mapping of the main microbial metabolic pathways actively functioning in the gut microbiome was also achieved.ConclusionsThe analytical pipeline presented here may be successfully used for the in-depth and time-effective characterization of complex microbial communities, such as the gut microbiome, and represents a useful tool for the microbiome research community.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-014-0049-2) contains supplementary material, which is available to authorized users.

Development of an enhanced metaproteomic approach for deepening the microbiome characterization of the human infant gut.

The establishment of early life microbiota in the human infant gut is highly variable and plays a crucial role in host nutrient availability/uptake and maturation of immunity. Although high-performance mass spectrometry (MS)-based metaproteomics is a powerful method for the functional characterization of complex microbial communities, the acquisition of comprehensive metaproteomic information in human fecal samples is inhibited by the presence of abundant human proteins. To alleviate this restriction, we have designed a novel metaproteomic strategy based on double filtering (DF) the raw samples, a method that fractionates microbial from human cells to enhance microbial protein identification and characterization in complex fecal samples from healthy premature infants. This method dramatically improved the overall depth of infant gut proteome measurement, with an increase in the number of identified low-abundance proteins and a greater than 2-fold improvement in microbial protein identification and quantification. This enhancement of proteome measurement depth enabled a more extensive microbiome comparison between infants by not only increasing the confidence of identified microbial functional categories but also revealing previously undetected categories.

A straightforward and efficient analytical pipeline for metaproteome characterization

BackgroundThe massive characterization of host-associated and environmental microbial communities has represented a real breakthrough in the life sciences in the last years. In this context, metaproteomics specifically enables the transition from assessing the genomic potential to actually measuring the functional expression of a microbiome. However, significant research efforts are still required to develop analysis pipelines optimized for metaproteome characterization.ResultsThis work presents an efficient analytical pipeline for shotgun metaproteomic analysis, combining bead-beating/freeze-thawing for protein extraction, filter-aided sample preparation for cleanup and digestion, and single-run liquid chromatography-tandem mass spectrometry for peptide separation and identification. The overall procedure is more time-effective and less labor-intensive when compared to state-of-the-art metaproteomic techniques. The pipeline was first evaluated using mock microbial mixtures containing different types of bacteria and yeasts, enabling the identification of up to over 15,000 non-redundant peptide sequences per run with a linear dynamic range from 104 to 108 colony-forming units. The pipeline was then applied to the mouse fecal metaproteome, leading to the overall identification of over 13,000 non-redundant microbial peptides with a false discovery rate of <1%, belonging to over 600 different microbial species and 250 functionally relevant protein families. An extensive mapping of the main microbial metabolic pathways actively functioning in the gut microbiome was also achieved.ConclusionsThe analytical pipeline presented here may be successfully used for the in-depth and time-effective characterization of complex microbial communities, such as the gut microbiome, and represents a useful tool for the microbiome research community.

Separation of fluorescence‐labelled terminal restriction fragment DNA on a two‐dimensional gel (T‐RFs‐2D) – an efficient approach for microbial consortium characterization

Fingerprinting techniques provide access to understanding the ecology of uncultured microbial consortia. However, the application of current techniques such as terminal restriction fragment length polymorphism (T-RFLP) and denaturing gradient gel electrophoresis (DGGE) has been hindered due to their limitations in characterizing complex microbial communities. This is due to that different populations possibly share the same terminal restriction fragments (T-RFs) and DNA fragments may co-migrate on DGGE gels. To overcome these limitations, a new approach was developed to separate terminal restriction fragments (T-RFs) of 16S rRNA genes on a two-dimensional gel (T-RFs-2D). T-RFs-2D involves restriction digestion of terminal fluorescence-labelled PCR amplified 16S rRNA gene products and their high-resolution separation via a two-dimensional (2D) gel electrophoresis based on the T-RF fragment size (1(st) D) and its sequence composition on the denaturing gradient gel (2(nd) D). The sequence information of interested T-RFs on 2D gels can be obtained through serial poly(A) tailing reaction, PCR amplification and subsequent DNA sequencing. By employing the T-RFs-2D method, bacteria with MspI digested T-RF size of 436 (±1) bp and 514 (±1) bp were identified to be a Lysobacter sp. and a Dehalococcoides sp. in a polychlorinated biphenyl (PCB) dechlorinating culture. With the high resolution of 2D separation, T-RFs-2D separated 63 DNA fragments in a complex river-sediment microbial community, while traditional DGGE detected only 41 DNA fragments in the same sample. In all, T-RFs-2D has its advantage in obtaining sequence information of interested T-RFs and also in characterization of complex microbial communities.

Target Region Selection Is a Critical Determinant of Community Fingerprints Generated by 16S Pyrosequencing

Pyrosequencing of 16S rRNA genes allows for in-depth characterization of complex microbial communities. Although it is known that primer selection can influence the profile of a community generated by sequencing, the extent and severity of this bias on deep-sequencing methodologies is not well elucidated. We tested the hypothesis that the hypervariable region targeted for sequencing and primer degeneracy play important roles in influencing the composition of 16S pyrotag communities. Subgingival plaque from deep sites of current smokers with chronic periodontitis was analyzed using Sanger sequencing and pyrosequencing using 4 primer pairs. Greater numbers of species were detected by pyrosequencing than by Sanger sequencing. Rare taxa constituted nearly 6% of each pyrotag community and less than 1% of the Sanger sequencing community. However, the different target regions selected for pyrosequencing did not demonstrate a significant difference in the number of rare and abundant taxa detected. The genera Prevotella, Fusobacterium, Streptococcus, Granulicatella, Bacteroides, Porphyromonas and Treponema were abundant when the V1–V3 region was targeted, while Streptococcus, Treponema, Prevotella, Eubacterium, Porphyromonas, Campylobacer and Enterococcus predominated in the community generated by V4–V6 primers, and the most numerous genera in the V7–V9 community were Veillonella, Streptococcus, Eubacterium, Enterococcus, Treponema, Catonella and Selenomonas. Targeting the V4–V6 region failed to detect the genus Fusobacterium, while the taxa Selenomonas, TM7 and Mycoplasma were not detected by the V7–V9 primer pairs. The communities generated by degenerate and non-degenerate primers did not demonstrate significant differences. Averaging the community fingerprints generated by V1–V3 and V7–V9 primers providesd results similar to Sanger sequencing, while allowing a significantly greater depth of coverage than is possible with Sanger sequencing. It is therefore important to use primers targeted to these two regions of the 16S rRNA gene in all deep-sequencing efforts to obtain representational characterization of complex microbial communities.

Illumina-based analysis of microbial community diversity

Microbes commonly exist in milieus of varying complexity and diversity. Although cultivation-based techniques have been unable to accurately capture the true diversity within microbial communities, these deficiencies have been overcome by applying molecular approaches that target the universally conserved 16S ribosomal RNA gene. The recent application of 454 pyrosequencing to simultaneously sequence thousands of 16S rDNA sequences (pyrotags) has revolutionized the characterization of complex microbial communities. To date, studies based on 454 pyrotags have dominated the field, but sequencing platforms that generate many more sequence reads at much lower costs have been developed. Here, we use the Illumina sequencing platform to design a strategy for 16S amplicon analysis (iTags), and assess its generality, practicality and potential complications. We fabricated and sequenced paired-end libraries of amplified hyper-variable 16S rDNA fragments from sets of samples that varied in their contents, ranging from a single bacterium to highly complex communities. We adopted an approach that allowed us to evaluate several potential sources of errors, including sequencing artifacts, amplification biases, non-corresponding paired-end reads and mistakes in taxonomic classification. By considering each source of error, we delineate ways to make biologically relevant and robust conclusions from the millions of sequencing reads that can be readily generated by this technology.

Resolution of Phenotypically Distinct Strains of Enterococcus spp. in a Complex Microbial Community Using cpn60 Universal Target Sequencing

Characterization of complex microbial communities is frequently based on the examination of polymerase chain reaction amplified sequences from a single phylogenetic marker, usually the 16S rRNA gene. However, this commonly used target often does not offer robust resolution of species or sub-species and is thus not a sufficiently informative target for understanding microbial population dynamics occurring at the strain level. We have used the cpn60 universal target sequence to characterize Enterococcus isolates from feces of growing pigs and have shown that sub-species groups, not detected using 16S rRNA sequences, can be resolved. Furthermore, groups resolved by cpn60-based phylogenetic analysis have distinct phenotypes. We report changes in the structure and function of Enterococcus communities in pig feces sampled from individual animals at three times, from suckling through to maturity. Enterococcus faecalis was largely replaced by Enterococcus hirae between suckling and 9 weeks of age, and a shift from one sub-species group of E. hirae to another was observed in all animals between 9 and 15 weeks. Conversely, E. faecalis strains remained consistent throughout the study period. Our results demonstrate that cpn60 sequences can be used to detect strain level changes in Enterococcus populations during succession in the fecal microbiota of growing pigs.

Use of ribosomal RNA-based molecular probes for characterization of complex microbial communities in anaerobic biofilms

The use of ribosomal RNA (rRNA) probe technology for the characterization of complex microbial communities is reviewed and illustrated by discussing the results of a long-term study of four anaerobic fixed-bed biofilm reactors. Two distinct approaches were used to characterize the microbial community structure in these biofilm reactors. The first used a collection of phylogenetically defined oligonucleotide rRNA probes for methanogens and sulfate-reducing bacteria (SRB) to quantify their populations. Population abundance was linked to the functional behavior of the biofilm reactor community by determining the effluent concentrations of the substrates, intermediates, and final products of microbial metabolism. This analysis indicated that the presence of SRB (especially Desulfovibrio-species) was not dependent upon the presence of sulfate. Methanobacteriales-species were the major competitors for hydrogen with these SRB in the absence of sulfate. The second approach involved selective amplification, cloning, sequencing, and whole cell hybridization to identify, visualize, and isolate a biofilm community member (strain PT-2). Subsequently, it was determined that the growth rate of strain PT-2 was significantly higher in young biofilms than in established biofilms.

Use of ribosomal RNA-based molecular probes for characterization of complex microbial communities in anaerobic biofilms

The use of ribosomal RNA (rRNA) probe technology for the characterization of complex microbial communities is reviewed and illustrated by discussing the results of a long-term study of four anaerobic fixed-bed biofilm reactors. Two distinct approaches were used to characterize the microbial community structure in these biofilm reactors. The first used a collection of phylogenetically defined oligonucleotide rRNA probes for methanogens and sulfate-reducing bacteria (SRB) to quantify their populations. Population abundance was linked to the functional behavior of the biofilm reactor community by determining the effluent concentrations of the substrates, intermediates, and final products of microbial metabolism. This analysis indicated that the presence of SRB (especially Desulfovibrio-species) was not dependent upon the presence of sulfate. Methanobacteriales-species were the major competitors for hydrogen with these SRB in the absence of sulfate. The second approach involved selective amplification, cloning, sequencing, and whole cell hybridization to identify, visualize, and isolate a biofibn community member (strain PT-2). Subsequently, it was determined that the growth rate of strain PT-2 was significantly higher in young biofilms than in established biofilms.