Parallel-META 2.0: enhanced metagenomic data analysis with functional annotation, high performance computing and advanced visualization

Metagenomic analysis revealed the potential of lactic acid bacteria in improving natural saline-alkali land

Management and improving saline-alkali land is necessary for sustainable agricultural development. We conducted a field experiment to investigate the effects of spraying lactic acid bacteria (LAB) on the cucumber and tomato plant soils. Three treatments were designed, including spraying of water, viable or sterilized LAB preparations to the soils of cucumber and tomato plants every 20 days. Spraying sterilized or viable LAB could reduce the soil pH, with a more obvious effect by using viable LAB, particularly after multiple applications. Metagenomic sequencing revealed that the soil microbiota in LAB-treated groups had higher alpha-diversity and more nitrogen-fixing bacteria compared with the water-treated groups. Both viable and sterilized LAB, but not water application, increased the complexity of the soil microbiota interactive network. The LAB-treated subgroups were enriched in some KEGG pathways compared with water or sterilized LAB subgroups, such as environmental information processing-related pathways in cucumber plant; and metabolism-related pathways in tomato plant, respectively. Redundancy analysis revealed association between some soil physico-chemical parameters (namely soil pH and total nitrogen) and bacterial biomarkers (namely Rhodocyclaceae, Pseudomonadaceae, Gemmatimonadaceae, and Nitrosomonadales). Our study demonstrated that LAB is a suitable strategy for decreasing soil pH and improving the microbial communities in saline-alkali land.

Recent Differentiation of Aquatic Bacterial Communities in a Hydrological System in the Cuatro Ciénegas Basin, After a Natural Perturbation

Pozas Rojas is a hydrological system comprising nine isolated shallow ponds and a deep lagoon, which were temporally merged in 2010 by increased rainfall due to a tropical cyclone. In this work, we assess which components, biotic interactions, or environment filtering effects, drive the assembly of microbial communities after a natural perturbation. Arsenic, pH, and temperature are among the most significant environmental variables between each pond, clustering the samples in two main groups, whereas microbial composition is diverse and unique to each site, with no core at the operational taxonomic unit level and only 150 core genera when studied at the genus level. Los Hundidos lagoon has the most differentiated community, which is highly similar to the epipelagic Mediterranean Sea communities. On the other hand, the shallow ponds at the Pozas Rojas system resemble more to epicontinental hydrological systems, such as some cold rivers of the world and the phreatic mantle from Iowa. Overall, despite being a sole of water body 2 years prior to the sampling, interspecific interactions, rather than environmental selection, seem to play a more important role in Pozas Rojas, bolstered by founder effects on each poza and subsequent isolation of each water body.

Microbial diversity in a military impacted lagoon (Vieques, Puerto Rico) and description of "Candidatus Biekeibacterium resiliens" gen. nov., sp. nov. comprising a new bacterial family

The Anones Lagoon, located in the Island Municipality of Vieques, Puerto Rico (PR), received extensive bombing by the US Navy during military exercises for decades until 2003 when military activities ceased. Here, we employed shotgun metagenomic sequencing to investigate how microbial communities responded to pollution by heavy metals and explosives at this lagoon. Sediment samples (0-5 cm) from Anones were collected in 2005 and 2014 and compared to samples from two reference lagoons, i.e., Guaniquilla, Cabo Rojo (a natural reserve) and Condado, San Juan (PR's capital city). Consistent with low anthropogenic inputs, Guaniquilla exhibited the highest degree of diversity with a lower frequency of genes related to xenobiotics metabolism between the three lagoons. Notably, a clear shift was observed in Anones, with Euryarchaeota becoming enriched (9% of total) and a concomitant increase in community diversity, by about one order of magnitude, after almost 10 years without bombing activities. In contrast, genes associated with explosives biodegradation and heavy metal transformation significantly decreased in abundance in Anones 2014 (by 91.5%). Five unique metagenome-assembled genomes (MAGs) were recovered from the Anones 2005 sample that encoded genetic determinants implicated in biodegradation of contaminants, and we propose to name one of them as "Candidatus Biekeibacterium resiliens" gen. nov., sp. nov. within the Gammaproteobacteria class. Collectively, these results provide new insights into the natural attenuation of explosive contaminants by the benthic microbial communities of the Anones lagoon and provide a reference point for assessing other similarly impacted sites and associated bioremediation efforts.

The endophytome (plant-associated microbiome): methodological approaches, biological aspects, and biotech applications

Similar to other organisms, plants establish interactions with a variety of microorganisms in their natural environment. The plant microbiome occupies the host plant's tissues, either internally or on its surfaces, showing interactions that can assist in its growth, development, and adaptation to face environmental stresses. The advance of metagenomics and metatranscriptomics approaches has strongly driven the study and recognition of plant microbiome impacts. Research in this regard provides comprehensive information about the taxonomic and functional aspects of microbial plant communities, contributing to a better understanding of their dynamics. Evidence of the plant microbiome's functional potential has boosted its exploitation to develop more ecological and sustainable agricultural practices that impact human health. Although microbial inoculants' development and use are promising to revolutionize crop production, interdisciplinary studies are needed to identify new candidates and promote effective practical applications. On the other hand, there are challenges in understanding and analyzing complex data generated within a plant microbiome project's scope. This review presents aspects about the complex structuring and assembly of the microbiome in the host plant's tissues, metagenomics, and metatranscriptomics approaches for its understanding, covering descriptions of recent studies concerning metagenomics to characterize the microbiome of non-model plants under different aspects. Studies involving bio-inoculants, isolated from plant microbial communities, capable of assisting in crops' productivity, are also reviewed.

Bacterial and Fungal Microbiome Profiling in Chilhuacle Negro Chili (Capsicum annuum L.) Associated With Fruit Rot Disease

Chilhuacle negro chili (Capsicum annuum L.) is an ancient Mexican landrace that is deeply linked to the culinary heritage of the country. Because of the high profitability and uniqueness of this crop, the Universidad Autónoma del Estado de Morelos is exploring its production in controlled environments. In the crop cycles of 2018 to 2019, the production of chilhuacle negro plants was seriously affected by an unidentified pathogen causing fruit rot, which reduced its quality, yield, and market value. Therefore, the main objective of this work was to study and characterize the fruit microbiota, which could help reveal the causal agent of this disease. Using DNA metabarcoding coupled with Illumina and nanopore sequencing technologies, we collected and analyzed both healthy and infected chili fruit, along with greenhouse bioaerosols. We also explored the bacterial and fungal microbiota by using microbiological techniques to isolate some of the culturable bacterial and fungal species. Our results suggest that the seedborne fungus Alternaria alternata is activated during the maturation stage of chilhuacle negro fruit, triggering a microbiome imbalance, which may in turn enable the establishment of other opportunistic pathogenic fungi during fruit decay, such as Mucor sp. To our knowledge, this is the first study of the chilhuacle negro chili microbiome, which can shed some light on our understanding of one of the main diseases that affect this valuable crop.

High arsenic levels increase activity rather than diversity or abundance of arsenic metabolism genes in paddy soils

Arsenic (As) metabolism genes are generally present in soils but their diversity, relative abundance, and transcriptional activity in response to different As concentrations remain unclear, limiting our understanding of the microbial activities that control the fate of an important environmental pollutant. To address this issue, we applied metagenomics and metatranscriptomics to paddy soils showing a gradient of As concentrations to investigate As resistance genes (ars) including arsR, acr3, arsB, arsC, arsM, arsI, arsP, and arsH as well as energy-generating As respiratory oxidation (aioA) and reduction (arrA) genes. Somewhat unexpectedly, the relative DNA abundances and diversity of ars, aioA, and arrA genes were not significantly different between low and high (∼10 vs ∼100 mg kg^-1) As soils. By comparison to available metagenomes from other soils, geographic distance rather than As levels drove the different compositions of microbial communities. Arsenic significantly increased ars genes abundance only when its concentration was higher than 410 mg kg^-1. In contrast, between low and high As soils, metatranscriptomics revealed a significant increase in transcription of ars and aioA genes, which are induced by arsenite, the dominant As species in paddy soils, but not arrA genes, which are induced by arsenate. These patterns appeared to be community-wide as opposed to taxon-specific. Collectively, our findings advance understanding of how microbes respond to high As levels and the diversity of As metabolism genes in paddy soils and indicated that future studies of As metabolism in soil, or other environments, should include the function (transcriptome) level. IMPORTANCE Arsenic (As) is a toxic metalloid pervasively present in the environment. Microorganisms have evolved the capacity to metabolize As, and As metabolism genes are ubiquitously present in the environment even in the absence of high concentrations of As. However, these previous studies were carried out at the DNA level and thus, the activity of the As metabolism genes detected remains essentially speculative. Here, we show that the high As levels in paddy soils increased the transcriptional activity rather than the relative DNA abundance and diversity of As metabolism genes. These findings advance our understanding of how microbes respond to and cope with high As levels and have implications for better monitoring and managing an important toxic metalloid in agricultural soils and possibly other ecosystems.

Bacterial composition and function during fermentation of Mongolia koumiss

Koumiss is a fermented mare's milk beverage that has attracted increasing attention due to its nutritional richness and important economic value. Bacteria in koumiss play a major role in pH decreasing and reducing spoilage through bacterial inhibition. The dynamic changes in nutritional content were determined firstly during fermentation, and then the metagenomics sequencing technology was applied to profile koumiss core microbiota at the species level. We also clarified the function and effect of the bacteria on the nutritional content of the final product. We also investigated active microbial function by comparing the metagenomics of representative samples collected at different time points during the fermentation process. This study dynamically revealed the bacterial composition and function of traditional koumiss during its making process. Twenty-three major functional categories related to amino acid and fat synthesis, metabolism, and so on were identified. Functional category L (represented replication-, recombination-, and repair-related functions) was one of the most important categories with the highest relative abundance in all of the 23 major functional categories. CoG category having a significant correlation with Lactococcus piscium was the most abundant. The change in metabolic activity of bacteria at different fermentation time points showed that the metabolic activity was more active in the first 24 hr and then began to stabilize. LAB play the major role in the koumiss pH decreasing and quality improvement. The functional genes of related metabolic activity of lactic acid bacteria were more active in the first 24 hr of koumiss fermentation and then began to stabilize.

Metagenomic Characterization of Soil Microbial Communities in the Luquillo Experimental Forest (Puerto Rico) and Implications for Nitrogen Cycling

The phylogenetic and functional diversities of microbial communities in tropical rainforests and how these differ from those of temperate communities remain poorly described but are directly related to the increased fluxes of greenhouse gases such as nitrous oxide (N₂O) from the tropics. Toward closing these knowledge gaps, we analyzed replicated shotgun metagenomes representing distinct life zones and an elevation gradient from four locations in the Luquillo Experimental Forest (LEF), Puerto Rico. These soils had a distinct microbial community composition and lower species diversity compared to those of temperate grasslands or agricultural soils. In contrast to the overall distinct community composition, the relative abundances and nucleotide sequences of N₂O reductases (nosZ) were highly similar between tropical forest and temperate soils. However, respiratory NO reductase (norB) was 2-fold more abundant in the tropical soils, which might be relatable to their greater N₂O emissions. Nitrogen fixation (nifH) also showed higher relative abundance in rainforest than in temperate soils, i.e., 20% versus 0.1 to 0.3% of bacterial genomes in each soil type harbored the gene, respectively. Finally, unlike temperate soils, LEF soils showed little stratification with depth in the first 0 to 30 cm, with ∼45% of community composition differences explained solely by location. Collectively, these results advance our understanding of spatial diversity and metabolic repertoire of tropical rainforest soil communities and should facilitate future ecological studies of these ecosystems. IMPORTANCE Tropical rainforests are the largest terrestrial sinks of atmospheric CO₂ and the largest natural source of N₂O emissions, two greenhouse gases that are critical for the climate. The microbial communities of rainforest soils that directly or indirectly, through affecting plant growth, contribute to these fluxes remain poorly described by cultured-independent methods. To close this knowledge gap, the present study applied shotgun metagenomics to samples selected from three distinct life zones within the Puerto Rico rainforest. The results advance our understanding of microbial community diversity in rainforest soils and should facilitate future studies of natural or manipulated perturbations of these critical ecosystems.

Diversity of Weissella confusa in Pozol and Its Carbohydrate Metabolism

The genus Weissella is composed of a group of Gram-positive facultative anaerobe bacteria with fermentative metabolism. Strains of this genus have been isolated from various ecological niches, including a wide variety of fermented cereal foods. The present study aimed to determine the relative abundance and fermentation capabilities of Weissella species isolated from pozol, a traditional maya product made of lime-cooked (nixtamalized) fermented maize. We sequenced the V3-V4 regions of 16S rDNA; Weissella was detected early in the fermentation process and reached its highest relative abundance (3.89%) after 3 h of culture. In addition, we evaluated five Weissella strains previously isolated from pozol but reported as non-amylolytic, to define alternative carbon sources such as xylan, xylooligosaccharides, and sucrose. While no growth was observed on birch xylan, growth did occur on xylooligosaccharides and sucrose. Strains WcL17 and WCP-3A were selected for genomic sequencing, as the former shows efficient growth on xylooligosaccharides and the latter displays high glycosyltransferase (GTF) activity. Genomes of both strains were assembled and recorded, with a total of 2.3 Mb in 30 contigs for WcL17 and 2.2 Mb in 45 contigs for WCP-3a. Both strains were taxonomically assigned to Weissella confusa and genomic analyses were performed to evaluate the gene products encoding active carbohydrate enzymes (CAZy). Both strains have the gene content needed to metabolize sucrose, hemicellulose, cellulose, and starch residues, all available in pozol. Our results suggest that the range of secondary enzymatic activity in Weissella confusa strains confer them with wide capabilities to participate in fermentative processes of natural products with heterogeneous carbon sources.

Starvation Alters Gut Microbiome in Black Soldier Fly (Diptera: Stratiomyidae) Larvae

Unlike for vertebrates, the impact of starvation on the gut microbiome of invertebrates is poorly studied. Deciphering shifts in metabolically active associated bacterial communities in vertebrates has led to determining the role of the associated microbiome in the sensation of hunger and discoveries of associated regulatory mechanisms. From an invertebrate perspective, such as the black soldier fly, such information could lead to enhanced processes for optimized biomass production and waste conversion. Bacteria associated with food substrates of black soldier fly are known to impact corresponding larval life-history traits (e.g., larval development); however, whether black soldier fly larval host state (i.e., starved) impacts the gut microbiome is not known. In this study, we measured microbial community structural and functional shifts due to black soldier fly larvae starvation. Data generated demonstrate such a physiological state (i.e., starvation) does in fact impact both aspects of the microbiome. At the phylum level, community diversity decreased significantly during black soldier fly larval starvation (p = 0.0025). Genus level DESeq2 analysis identified five genera with significantly different relative abundance (q < 0.05) across the 24 and 48 H post initiation of starvation: Actinomyces, Microbacterium, Enterococcus, Sphingobacterium, and Leucobacter. Finally, we inferred potential gene function and significantly predicted functional KEGG Orthology (KO) abundance. We demonstrated the metabolically active microbial community structure and function could be influenced by host-feeding status. Such perturbations, even when short in duration (e.g., 24 H) could stunt larval growth and waste conversion due to lacking a full complement of bacteria and associated functions.

Metagenomic investigation of African dust events in the Caribbean

African dust from the Sahara and Sahel regions of Northern Africa is blown intercontinental distances and is the highest portion of atmospheric dust generated each year. During the Northern Hemisphere summer months (boreal summer), these dust events travel into the Caribbean and southern United States. While viability assays, microscopy and bacterial amplicon analyses have shown that dust-associated microbes may be diverse, the specific microbial taxa that are transported intercontinental distances with these dust events remain poorly characterized. To provide new insights into these issues, five metagenomes of Saharan dust events occurring in the Caribbean, collected in the summer months of 2002 and 2008, were analyzed. The data revealed that similar microbial composition existed between three out of the five of the distinct dust events and that fungi were a prominent feature of the metagenomes compared to other environmental samples. These results have implications for better understanding of microbial transport through the atmosphere and may implicate that the dust-associated microbial load transiting the Atlantic with Saharan dust is similar from year to year.

Metagenomics as a Public Health Risk Assessment Tool in a Study of Natural Creek Sediments Influenced by Agricultural and Livestock Runoff: Potential and Limitations

Little is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens such as Shiga toxin-producing Escherichia coli (STEC) originating from these practices remains poorly quantified. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley of California was sampled over a 9-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and have functional and taxonomic diversity comparable to that observed in soils. With our sequencing effort (∼4 Gbp per library), we were unable to detect any pathogenic E. coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low abundance. Furthermore, there were no significant differences in the abundance of human- or cow-specific gut microbiome sequences in the downstream impacted sites compared to that in upstream more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, the high number of metagenomic reads carrying antibiotic resistance genes (ARGs) found in all samples was significantly higher than ARG reads in other available freshwater and soil metagenomes, suggesting that these communities may be natural reservoirs of ARGs. The work presented here should serve as a guide for sampling volumes, amount of sequencing to apply, and what bioinformatics analyses to perform when using metagenomics for public health risk studies of environmental samples such as sediments.IMPORTANCE Current agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food- and waterborne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health are assessed by culture-based tests for the intestinal bacterium Escherichia coli However, the accuracy of these traditional methods (e.g., low accuracy in quantification, and false-positive signal when PCR based) and their suitability for sediments remain unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the United States in order to assess how agricultural runoff affects the native microbial communities and if the presence of Shiga toxin-producing Escherichia coli (STEC) in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments.

Comparison of closely related, uncultivated Coxiella tick endosymbiont population genomes reveals clues about the mechanisms of symbiosis

Understanding the symbiotic interaction between Coxiella-like endosymbionts (CLE) and their tick hosts is challenging due to lack of isolates and difficulties in tick functional assays. Here we sequenced the metagenome of a CLE population from wild Rhipicephalus sanguineus ticks (CRs) and compared it to the previously published genome of its close relative, CLE of R. turanicus (CRt). The tick hosts are closely related sympatric species, and their two endosymbiont genomes are highly similar with only minor differences in gene content. Both genomes encode numerous pseudogenes, consistent with an ongoing genome reduction process. In silico flux balance metabolic analysis (FBA) revealed the excess production of L-proline for both genomes, indicating a possible proline transport from Coxiella to the tick. Additionally, both CR genomes encode multiple copies of the proline/betaine transporter, proP gene. Modelling additional Coxiellaceae members including other tick CLE, did not identify proline as an excreted metabolite. Although both CRs and CRt genomes encode intact B vitamin synthesis pathway genes, which are presumed to underlay the mechanism of CLE-tick symbiosis, the FBA analysis indicated no changes for their products. Therefore, this study provides new testable hypotheses for the symbiosis mechanism and a better understanding of CLE genome evolution and diversity.

Using QC-Blind for Quality Control and Contamination Screening of Bacteria DNA Sequencing Data Without Reference Genome

Quality control for next generation sequencing (NGS) has become increasingly important with the ever increasing importance of sequencing data for omics studies. Tools have been developed for filtering possible contaminants from species with known reference genome. Unfortunately, reference genomes for all the species involved, including the contaminants, are required for these tools to work. This precludes many real-life samples that have no information about the complete genome of the target species, and are contaminated with unknown microbial species. In this work we proposed QC-Blind, a novel quality control pipeline for removing contaminants without any use of reference genomes. The pipeline merely requires the information about a few marker genes of the target species. The entire pipeline consists of unsupervised read assembly, contig binning, read clustering, and marker gene assignment. When evaluated on in silico, ab initio and in vivo datasets, QC-Blind proved effective in removing unknown contaminants with high specificity and accuracy, while preserving most of the genomic information of the target bacterial species. Therefore, QC-Blind could serve well in situations where limited information is available for both target and contamination species.

Responses of tundra soil microbial communities to half a decade of experimental warming at two critical depths

Northern-latitude tundra soils harbor substantial carbon (C) stocks that are highly susceptible to microbial degradation with rising global temperatures. Understanding the magnitude and direction (e.g., C release or sequestration) of the microbial responses to warming is necessary to accurately model climate change. In this study, Alaskan tundra soils were subjected to experimental in situ warming by ∼1.1 °C above ambient temperature, and the microbial communities were evaluated using metagenomics after 4.5 years, at 2 depths: 15 to 25 cm (active layer at outset of the experiment) and 45 to 55 cm (transition zone at the permafrost/active layer boundary at the outset of the experiment). In contrast to small or insignificant shifts after 1.5 years of warming, 4.5 years of warming resulted in significant changes to the abundances of functional traits and the corresponding taxa relative to control plots (no warming), and microbial shifts differed qualitatively between the two soil depths. At 15 to 25 cm, increased abundances of carbohydrate utilization genes were observed that correlated with (increased) measured ecosystem carbon respiration. At the 45- to 55-cm layer, increased methanogenesis potential was observed, which corresponded with a 3-fold increase in abundance of a single archaeal clade of the Methanosarcinales order, increased annual thaw duration (45.3 vs. 79.3 days), and increased CH₄ emissions. Collectively, these data demonstrate that the microbial responses to warming in tundra soil are rapid and markedly different between the 2 critical soil layers evaluated, and identify potential biomarkers for the corresponding microbial processes that could be important in modeling.

Exploring the Human Microbiome: The Potential Future Role of Next-Generation Sequencing in Disease Diagnosis and Treatment

The interaction between the human microbiome and immune system has an effect on several human metabolic functions and impacts our well-being. Additionally, the interaction between humans and microbes can also play a key role in determining the wellness or disease status of the human body. Dysbiosis is related to a plethora of diseases, including skin, inflammatory, metabolic, and neurological disorders. A better understanding of the host-microbe interaction is essential for determining the diagnosis and appropriate treatment of these ailments. The significance of the microbiome on host health has led to the emergence of new therapeutic approaches focused on the prescribed manipulation of the host microbiome, either by removing harmful taxa or reinstating missing beneficial taxa and the functional roles they perform. Culturing large numbers of microbial taxa in the laboratory is problematic at best, if not impossible. Consequently, this makes it very difficult to comprehensively catalog the individual members comprising a specific microbiome, as well as understanding how microbial communities function and influence host-pathogen interactions. Recent advances in sequencing technologies and computational tools have allowed an increasing number of metagenomic studies to be performed. These studies have provided key insights into the human microbiome and a host of other microbial communities in other environments. In the present review, the role of the microbiome as a therapeutic agent and its significance in human health and disease is discussed. Advances in high-throughput sequencing technologies for surveying host-microbe interactions are also discussed. Additionally, the correlation between the composition of the microbiome and infectious diseases as described in previously reported studies is covered as well. Lastly, recent advances in state-of-the-art bioinformatics software, workflows, and applications for analysing metagenomic data are summarized.

Bacterial Diversity and the Geochemical Landscape in the Southwestern Gulf of Mexico

Marine sediments are an example of one of the most complex microbial habitats. These bacterial communities play an important role in several biogeochemical cycles in the marine ecosystem. In particular, the Gulf of Mexico has a ubiquitous concentration of hydrocarbons in its sediments, representing a very interesting niche to explore. Additionally, the Mexican government has opened its oil industry, offering several exploration and production blocks in shallow and deep water in the southwestern Gulf of Mexico (swGoM), from which there are no public results of conducted studies. Given the higher risk of large-scale oil spills, the design of contingency plans and mitigation activities before oil exploitation is of growing concern. Therefore, a bacterial taxonomic baseline profile is crucial to understanding the impact of any eventual oil spill. Here, we show a genus level taxonomic profile to elucidate the bacterial baseline, pointing out richness and relative abundance, as well as relationships with 79 abiotic parameters, in an area encompassing ∼150,000 km2, including a region where the exploitation of new oil wells has already been authorized. Our results describe for the first time the bacterial landscape of the swGoM, establishing a bacterial baseline "core" of 450 genera for marine sediments in this region. We can also differentiate bacterial populations from shallow and deep zones of the swGoM based on their community structure. Shallow sediments have been chronically exposed to aromatic hydrocarbons, unlike deep zones. Our results reveal that the bacterial community structure is particularly enriched with hydrocarbon-degrading bacteria in the shallow zone, where a greater aromatic hydrocarbon concentration was determined. Differences in the bacterial communities in the swGoM were also observed through a comprehensive comparative analysis relative to various marine sediment sequencing projects, including sampled sites from the Deep Water Horizon oil spill. This study in the swGoM provides clues to the bacterial population adaptation to the ubiquitous presence of hydrocarbons and reveals organisms such as Thioprofundum bacteria with potential applications in ecological surveillance. This resource will allow us to differentiate between natural conditions and alterations generated by oil extraction activities, which, in turn, enables us to assess the environmental impact of such activities.

Analysis of sequencing strategies and tools for taxonomic annotation: Defining standards for progressive metagenomics

Metagenomics research has recently thrived due to DNA sequencing technologies improvement, driving the emergence of new analysis tools and the growth of taxonomic databases. However, there is no all-purpose strategy that can guarantee the best result for a given project and there are several combinations of software, parameters and databases that can be tested. Therefore, we performed an impartial comparison, using statistical measures of classification for eight bioinformatic tools and four taxonomic databases, defining a benchmark framework to evaluate each tool in a standardized context. Using in silico simulated data for 16S rRNA amplicons and whole metagenome shotgun data, we compared the results from different software and database combinations to detect biases related to algorithms or database annotation. Using our benchmark framework, researchers can define cut-off values to evaluate the expected error rate and coverage for their results, regardless the score used by each software. A quick guide to select the best tool, all datasets and scripts to reproduce our results and benchmark any new method are available at https://github.com/Ales-ibt/Metagenomic-benchmark. Finally, we stress out the importance of gold standards, database curation and manual inspection of taxonomic profiling results, for a better and more accurate microbial diversity description.

A-GAME: improving the assembly of pooled functional metagenomics sequence data

Background

Expression screening of environmental DNA (eDNA) libraries is a popular approach for the identification and characterization of novel microbial enzymes with promising biotechnological properties. In such “functional metagenomics” experiments, inserts, selected on the basis of activity assays, are sequenced with high throughput sequencing technologies. Assembly is followed by gene prediction, annotation and identification of candidate genes that are subsequently evaluated for biotechnological applications.

Results

Here we present A-GAME (A GAlaxy suite for functional MEtagenomics), a web service incorporating state of the art tools and workflows for the analysis of eDNA sequence data. We illustrate the potential of A-GAME workflows using real functional metagenomics data, showing that they outperform alternative metagenomics assemblers. Dedicated tools available in A-GAME allow efficient analysis of pooled libraries and rapid identification of candidate genes, reducing sequencing costs and saving the need for laborious manual annotation.

Conclusion

In conclusion, we believe A-GAME will constitute a valuable resource for the functional metagenomics community.

A-GAME is publicly available at http://beaconlab.it/agame

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4369-z) contains supplementary material, which is available to authorized users.

A clinician's guide to microbiome analysis

Microbiome analysis involves determining the composition and function of a community of microorganisms in a particular location. For the gastroenterologist, this technology opens up a rapidly evolving set of challenges and opportunities for generating novel insights into the health of patients on the basis of microbiota characterizations from intestinal, hepatic or extraintestinal samples. Alterations in gut microbiota composition correlate with intestinal and extraintestinal disease and, although only a few mechanisms are known, the microbiota are still an attractive target for developing biomarkers for disease detection and management as well as potential therapeutic applications. In this Review, we summarize the major decision points confronting new entrants to the field or for those designing new projects in microbiome research. We provide recommendations based on current technology options and our experience of sequencing platform choices. We also offer perspectives on future applications of microbiome research, which we hope convey the promise of this technology for clinical applications.

Metagenome Analysis: a Powerful Tool for Enzyme Bioprospecting

Microorganisms are found throughout every corner of nature, and vast number of microorganisms is difficult to cultivate by classical microbiological techniques. The advent of metagenomics has revolutionized the field of microbial biotechnology. Metagenomics allow the recovery of genetic material directly from environmental niches without any cultivation techniques. Currently, metagenomic tools are widely employed as powerful tools to isolate and identify enzymes with novel biocatalytic activities from the uncultivable component of microbial communities. The employment of next-generation sequencing techniques for metagenomics resulted in the generation of large sequence data sets derived from various environments, such as soil, the human body and ocean water. This review article describes the state-of-the-art techniques and tools in metagenomics and discusses the potential of metagenomic approaches for the bioprospecting of industrial enzymes from various environmental samples. We also describe the unusual novel enzymes discovered via metagenomic approaches and discuss the future prospects for metagenome technologies.

Feed-additive probiotics accelerate yet antibiotics delay intestinal microbiota maturation in broiler chicken

BACKGROUND

Reducing antibiotics overuse in animal agriculture is one key in combat against the spread of antibiotic resistance. Probiotics are a potential replacement of antibiotics in animal feed; however, it is not clear whether and how probiotics and antibiotics differ in impact on physiology and microbial ecology of host animals.

RESULTS

Host phenotype and fecal microbiota of broilers with either antibiotics or probiotics as feed additive were simultaneously sampled at four time points from birth to slaughter and then compared. Probiotic feeding resulted in a lower feed conversion ratio (FCR) and induced the highest level of immunity response, suggesting greater economic benefits in broiler farming. Probiotic use but not antibiotic use recapitulated the characteristics of age-dependent development of gut microbiota in the control group. The maturation of intestinal microbiota was greatly accelerated by probiotic feeding, yet significantly retarded and eventually delayed by antibiotic feeding. LP-8 stimulated the growth of many intestinal Lactobacillus spp. and led to an altered bacterial correlation network where Lactobacillus spp. are negatively correlated with 14 genera and positively linked with none, yet from the start antibiotic feeding featured a less-organized network where such inter-genera interactions were fewer and weaker. Consistently, microbiota-encoded functions as revealed by metagenome sequencing were highly distinct between the two groups. Thus, "intestinal microbiota maturation index" was proposed to quantitatively compare impact of feed additives on animal microecology.

CONCLUSIONS

Our results reveal a tremendous potential of probiotics as antibiotics' substitute in poultry farming.

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture

BACKGROUND

Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly.

RESULTS

We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database.

CONCLUSIONS

Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.

Quantifying the Importance of the Rare Biosphere for Microbial Community Response to Organic Pollutants in a Freshwater Ecosystem

A single liter of water contains hundreds, if not thousands, of bacterial and archaeal species, each of which typically makes up a very small fraction of the total microbial community (<0.1%), the so-called "rare biosphere." How often, and via what mechanisms, e.g., clonal amplification versus horizontal gene transfer, the rare taxa and genes contribute to microbial community response to environmental perturbations represent important unanswered questions toward better understanding the value and modeling of microbial diversity. We tested whether rare species frequently responded to changing environmental conditions by establishing 20-liter planktonic mesocosms with water from Lake Lanier (Georgia, USA) and perturbing them with organic compounds that are rarely detected in the lake, including 2,4-dichlorophenoxyacetic acid (2,4-D), 4-nitrophenol (4-NP), and caffeine. The populations of the degraders of these compounds were initially below the detection limit of quantitative PCR (qPCR) or metagenomic sequencing methods, but they increased substantially in abundance after perturbation. Sequencing of several degraders (isolates) and time-series metagenomic data sets revealed distinct cooccurring alleles of degradation genes, frequently carried on transmissible plasmids, especially for the 2,4-D mesocosms, and distinct species dominating the post-enrichment microbial communities from each replicated mesocosm. This diversity of species and genes also underlies distinct degradation profiles among replicated mesocosms. Collectively, these results supported the hypothesis that the rare biosphere can serve as a genetic reservoir, which can be frequently missed by metagenomics but enables community response to changing environmental conditions caused by organic pollutants, and they provided insights into the size of the pool of rare genes and species.IMPORTANCE A single liter of water or gram of soil contains hundreds of low-abundance bacterial and archaeal species, the so called rare biosphere. The value of this astonishing biodiversity for ecosystem functioning remains poorly understood, primarily due to the fact that microbial community analysis frequently focuses on abundant organisms. Using a combination of culture-dependent and culture-independent (metagenomics) techniques, we showed that rare taxa and genes commonly contribute to the microbial community response to organic pollutants. Our findings should have implications for future studies that aim to study the role of rare species in environmental processes, including environmental bioremediation efforts of oil spills or other contaminants.

Metagenomics of Two Severe Foodborne Outbreaks Provides Diagnostic Signatures and Signs of Coinfection Not Attainable by Traditional Methods

Diagnostic testing for foodborne pathogens relies on culture-based techniques that are not rapid enough for real-time disease surveillance and do not give a quantitative picture of pathogen abundance or the response of the natural microbiome. Powerful sequence-based culture-independent approaches, such as shotgun metagenomics, could sidestep these limitations and potentially reveal a pathogen-specific signature on the microbiome that would have implications not only for diagnostics but also for better understanding disease progression and pathogen ecology. However, metagenomics have not yet been validated for foodborne pathogen detection. Toward closing these gaps, we applied shotgun metagenomics to stool samples collected from two geographically isolated (Alabama and Colorado) foodborne outbreaks, where the etiologic agents were identified by culture-dependent methods as distinct strains of Salmonella enterica subsp. enterica serovar Heidelberg. Metagenomic investigations were consistent with the culture-based findings and revealed, in addition, the in situ abundance and level of intrapopulation diversity of the pathogen, the possibility of coinfections with Staphylococcus aureus, overgrowth of commensal Escherichia coli, and significant shifts in the gut microbiome during infection relative to reference healthy samples. Additionally, we designed our bioinformatics pipeline to deal with several challenges associated with the analysis of clinical samples, such as the high frequency of coeluting human DNA sequences and assessment of the virulence potential of pathogens. Comparisons of these results to those of other studies revealed that in several, but not all, cases of diarrheal outbreaks, the disease and healthy states of the gut microbial community might be distinguishable, opening new possibilities for diagnostics.

IMPORTANCE

Diagnostic testing for enteric pathogens has relied for decades on culture-based techniques, but a total of 38.4 million cases of foodborne illness per year cannot be attributed to specific causes. This study describes new culture-independent metagenomic approaches and the associated bioinformatics pipeline to detect and type the causative agents of microbial disease with unprecedented accuracy, opening new possibilities for the future development of health technologies and diagnostics. Our tools and approaches should be applicable to other microbial diseases in addition to foodborne diarrhea.

Effect of feeding Lactobacillus plantarum P-8 on the faecal microbiota of broiler chickens exposed to lincomycin

Poultry and eggs are nutritious and healthy foods that contain high-quality proteins and low levels of fat compared with other meats. Recent studies have shown that poultry performance is closely associated with colonic health. Antibiotics are commonly used in the poultry industry to control diseases and enhance survival rates. However, antibiotic use can also result in host gut dysbiosis and immune dysregulation. Such imbalances compromise poultry health and growth performance. Thus, our study investigated the effect of Lactobacillus (L.) plantarum P-8 on the gut microbiome of chickens co-inoculated with the antibiotic lincomycin. Principal coordinate analysis showed that L. plantarum P-8 treatment shifted the faecal bacterial population structure. At the metagenomic level, the Clusters of Orthologous Groups (COGs) functional categories of P, C, N and A were overrepresented in the probiotic group. Additionally, the relative gene abundances of metabolic pathways involved in flagellar assembly, bacterial chemotaxis, nitrogen metabolism, sulfur metabolism, cofactor and vitamin biosynthesis were also higher in the probiotic group than the control; in contrast genes related to galactose degradation, carbon fixation, multiple sugar transport systems and ribosomes were underrepresented in the probiotic group. Our data suggest that feeding L. plantarum P-8 has the potential to improve metabolic activity and nutrient utilization of poultry. Furthermore, the faecal antibiotic resistomes of the two groups could be separated using principal components analysis, indicating that the probiotic treatment may modulate the intestinal antibiotic resistance gene pool by changing the population structure of the gut microbiota. This study has provided interesting insights into the application of probiotics in the poultry industry.

Parallel-META 3: Comprehensive taxonomical and functional analysis platform for efficient comparison of microbial communities

The number of metagenomes is increasing rapidly. However, current methods for metagenomic analysis are limited by their capability for in-depth data mining among a large number of microbiome each of which carries a complex community structure. Moreover, the complexity of configuring and operating computational pipeline also hinders efficient data processing for the end users. In this work we introduce Parallel-META 3, a comprehensive and fully automatic computational toolkit for rapid data mining among metagenomic datasets, with advanced features including 16S rRNA extraction for shotgun sequences, 16S rRNA copy number calibration, 16S rRNA based functional prediction, diversity statistics, bio-marker selection, interaction network construction, vector-graph-based visualization and parallel computing. Application of Parallel-META 3 on 5,337 samples with 1,117,555,208 sequences from diverse studies and platforms showed it could produce similar results as QIIME and PICRUSt with much faster speed and lower memory usage, which demonstrates its ability to unravel the taxonomical and functional dynamics patterns across large datasets and elucidate ecological links between microbiome and the environment. Parallel-META 3 is implemented in C/C++ and R, and integrated into an executive package for rapid installation and easy access under Linux and Mac OS X. Both binary and source code packages are available at http://bioinfo.single-cell.cn/parallel-meta.html.

Differential fecal microbiota are retained in broiler chicken lines divergently selected for fatness traits

Our study combined 16S rRNA-pyrosequencing and whole genome sequencing to analyze the fecal metagenomes of the divergently selected lean (LL) and fat (FL) line chickens. Significant structural differences existed in both the phylogenic and functional metagenomes between the two chicken lines. At phylum level, the FL group had significantly less Bacteroidetes. At genus level, fourteen genera of different relative abundance were identified, with some known short-chain fatty acid producers (including Subdoligranulum, Butyricicoccus, Eubacterium, Bacteroides, Blautia) and a potentially pathogenic genus (Enterococcus). Redundancy analysis identified 190 key responsive operational taxonomic units (OTUs) that accounted for the structural differences between the phylogenic metagenome of the two groups. Four Cluster of Orthologous Group (COG) categories (Amino acid transport and metabolism, E; Nucleotide transport and metabolism, F; Coenzyme transport and metabolism, H; and Lipid transport and metabolism, I) were overrepresented in LL samples. Fifteen differential metabolic pathways (Biosynthesis of amino acids, Pyruvate metabolism, Nitrotoluene degradation, Lipopolysaccharide biosynthesis, Peptidoglycan biosynthesis, Pantothenate and CoA biosynthesis, Glycosaminoglycan degradation, Thiamine metabolism, Phosphotransferase system, Two-component system, Bacterial secretion system, Flagellar assembly, Bacterial chemotaxis, Ribosome, Sulfur relay system) were identified. Our data highlighted interesting variations between the gut metagenomes of these two chicken lines.

Metagenomics and Single-Cell Omics Data Analysis for Human Microbiome Research

Microbes are ubiquitous on our planet, and it is well known that the total number of microbial cells on earth is huge. These organisms usually live in communities, and each of these communities has a different taxonomical structure. As such, microbial communities would serve as the largest reservoir of genes and genetic functions for a vast number of applications in "bio"-related disciplines, especially in biomedicine. Human microbiome is the area in which the relationships between ourselves as hosts and our microbiomes have been examined.In this chapter, we have first reviewed the researches in microbes on community, population and single-cell levels in general. Then we have focused on the effects of recent metagenomics and single-cell advances on human microbiome research, as well as their effects on translational biomedical research. We have also foreseen that with the advancement of big-data analysis techniques, deeper understanding of human microbiome, as well as its broader applications, could be realized.

Fungal Community Associated with Dactylopius (Hemiptera: Coccoidea: Dactylopiidae) and Its Role in Uric Acid Metabolism

We studied fungal species associated with the carmine cochineal Dactylopius coccus and other non-domesticated Dactylopius species using culture-dependent and -independent methods. Thirty seven fungi were isolated in various culture media from insect males and females from different developmental stages and Dactylopius species. 26S rRNA genes and ITS sequences, from cultured fungal isolates revealed different species of Cryptococcus, Rhodotorula, Debaryomyces, Trametes, and Penicillium, which are genera newly associated with Dactylopius. Uric acid (UA) and uricase activity were detected in tissues extracts from different insect developmental stages. However, accumulation of high UA levels and low uricase activities were found only after antifungal treatments, suggesting an important role of fungal species in its metabolism. Additionally, uricolytic fungal isolates were identified and characterized that presumably are involved in nitrogen recycling metabolism. After metagenomic analyses from D. coccus gut and hemolymph DNA and from two published data sets, we confirmed the presence of fungal genes involved in UA catabolism, suggesting that fungi help in the nitrogen recycling process in Dactylopius by uricolysis. All these results show the importance of fungal communities in scale insects such as Dactylopius.

Similar Microbial Consortia and Genes Are Involved in the Biodegradation of Benzalkonium Chlorides in Different Environments

Benzalkonium chlorides (BACs) are emerging pollutants. Identification of microorganisms and the genes involved in the biodegradation of BACs is crucial for better understanding the fate of BACs in the environment and developing treatment strategies. Four microbial communities degrading BACs were developed from sewage (SEW), activated sludge (AS), soil (SOIL) and sea sediment (SEA) samples. According to 16S rRNA pyrosequencing and shotgun metagenome sequencing analyses, the most abundant species represented uncharacterized members of the Pseudomonas and Achromobacter genera. BAC biotransformation rates of the enriched microbial communities were 2.8, 3.2, 17.8, and 24.3 μM hr(-1) for SEA, AS, SOIL, and SEW, respectively, and were positively correlated with the relative abundance of a particular Pseudomonas sp. strain, BIOMIG1. The strain BIOMIG1 mineralizes BACs at a rate up to 2.40 μmol hr(-1) 10(-11) cells. Genomes of four BAC degrading and nondegrading BIOMIG1 phenotypes were sequenced and differentially compared with each other. As a result, a gene cluster encoding for transporters, an integrase and a dioxygenase were involved in BAC biotransformation. Our results suggest that BIOMIG1 plays a key role on the fate of BACs in the environment and genes, other than those reported to date, are involved in BAC biotransformation in various habitats.

The Road to Metagenomics: From Microbiology to DNA Sequencing Technologies and Bioinformatics

The study of microorganisms that pervade each and every part of this planet has encountered many challenges through time such as the discovery of unknown organisms and the understanding of how they interact with their environment. The aim of this review is to take the reader along the timeline and major milestones that led us to modern metagenomics. This new and thriving area is likely to be an important contributor to solve different problems. The transition from classical microbiology to modern metagenomics studies has required the development of new branches of knowledge and specialization. Here, we will review how the availability of high-throughput sequencing technologies has transformed microbiology and bioinformatics and how to tackle the inherent computational challenges that arise from the DNA sequencing revolution. New computational methods are constantly developed to collect, process, and extract useful biological information from a variety of samples and complex datasets, but metagenomics needs the integration of several of these computational methods. Despite the level of specialization needed in bioinformatics, it is important that life-scientists have a good understanding of it for a correct experimental design, which allows them to reveal the information in a metagenome.

Environmental genes and genomes: understanding the differences and challenges in the approaches and software for their analyses

DNA-based taxonomic and functional profiling is widely used for the characterization of organismal communities across a rapidly increasing array of research areas that include the role of microbiomes in health and disease, biomonitoring, and estimation of both microbial and metazoan species richness. Two principal approaches are currently used to assign taxonomy to DNA sequences: DNA metabarcoding and metagenomics. When initially developed, each of these approaches mandated their own particular methods for data analysis; however, with the development of high-throughput sequencing (HTS) techniques they have begun to share many aspects in data set generation and processing. In this review we aim to define the current characteristics, goals and boundaries of each field, and describe the different software used for their analysis. We argue that an appreciation of the potential and limitations of each method can help underscore the improvements required by each field so as to better exploit the richness of current HTS-based data sets.

MetaBoot: a machine learning framework of taxonomical biomarker discovery for different microbial communities based on metagenomic data

As more than 90% of species in a microbial community could not be isolated and cultivated, the metagenomic methods have become one of the most important methods to analyze microbial community as a whole. With the fast accumulation of metagenomic samples and the advance of next-generation sequencing techniques, it is now possible to qualitatively and quantitatively assess all taxa (features) in a microbial community. A set of taxa with presence/absence or their different abundances could potentially be used as taxonomical biomarkers for identification of the corresponding microbial community’s phenotype. Though there exist some bioinformatics methods for metagenomic biomarker discovery, current methods are not robust, accurate and fast enough at selection of non-redundant biomarkers for prediction of microbial community’s phenotype. In this study, we have proposed a novel method, MetaBoot, that combines the techniques of mRMR (minimal redundancy maximal relevance) and bootstrapping, for discover of non-redundant biomarkers for microbial communities through mining of metagenomic data. MetaBoot has been tested and compared with other methods on well-designed simulated datasets considering normal and gamma distribution as well as publicly available metagenomic datasets. Results have shown that MetaBoot was robust across datasets of varied complexity and taxonomical distribution patterns and could also select discriminative biomarkers with quite high accuracy and biological consistency. Thus, MetaBoot is suitable for robustly and accurately discover taxonomical biomarkers for different microbial communities.

Metagenomics: tools and insights for analyzing next-generation sequencing data derived from biodiversity studies

Advances in next-generation sequencing (NGS) have allowed significant breakthroughs in microbial ecology studies. This has led to the rapid expansion of research in the field and the establishment of "metagenomics", often defined as the analysis of DNA from microbial communities in environmental samples without prior need for culturing. Many metagenomics statistical/computational tools and databases have been developed in order to allow the exploitation of the huge influx of data. In this review article, we provide an overview of the sequencing technologies and how they are uniquely suited to various types of metagenomic studies. We focus on the currently available bioinformatics techniques, tools, and methodologies for performing each individual step of a typical metagenomic dataset analysis. We also provide future trends in the field with respect to tools and technologies currently under development. Moreover, we discuss data management, distribution, and integration tools that are capable of performing comparative metagenomic analyses of multiple datasets using well-established databases, as well as commonly used annotation standards.

Assessment of quality control approaches for metagenomic data analysis

Currently there is an explosive increase of the next-generation sequencing (NGS) projects and related datasets, which have to be processed by Quality Control (QC) procedures before they could be utilized for omics analysis. QC procedure usually includes identification and filtration of sequencing artifacts such as low-quality reads and contaminating reads, which would significantly affect and sometimes mislead downstream analysis. Quality control of NGS data for microbial communities is especially challenging. In this work, we have evaluated and compared the performance and effects of various QC pipelines on different types of metagenomic NGS data and from different angles, based on which general principles of using QC pipelines were proposed. Results based on both simulated and real metagenomic datasets have shown that: firstly, QC-Chain is superior in its ability for contamination identification for metagenomic NGS datasets with different complexities with high sensitivity and specificity. Secondly, the high performance computing engine enabled QC-Chain to achieve a significant reduction in processing time compared to other pipelines based on serial computing. Thirdly, QC-Chain could outperform other tools in benefiting downstream metagenomic data analysis.

Deciphering the human microbiome using next-generation sequencing data and bioinformatics approaches

The human microbiome is one of the key factors affecting the host immune system and metabolic functions that are not encoded in the human genome. Culture-independent analysis of the human microbiome using metagenomics approach allows us to investigate the compositions and functions of the human microbiome. Computational methods analyze the microbial community by using specific marker genes or by using shotgun sequencing of the entire microbial community. Taxonomy profiling is conducted by using the reference sequences or by de novo clustering of the specific region of sequences. Functional profiling, which is mainly based on the sequence similarity, is more challenging since about half of ORFs predicted in the metagenomic data could not find homology with known protein families. This review examines computational methods that are valuable for the analysis of human microbiome, and highlights the results of several large-scale human microbiome studies. It is becoming increasingly evident that dysbiosis of the gut microbiome is strongly associated with the development of immune disorder and metabolic dysfunction.