High-throughput anaerobic screening for identifying compounds acting against gut bacteria in monocultures or communities.

The human gut microbiome is a key contributor to health, and its perturbations are linked to many diseases. Small-molecule xenobiotics such as drugs, chemical pollutants and food additives can alter the microbiota composition and are now recognized as one of the main factors underlying microbiome diversity. Mapping the effects of such compounds on the gut microbiome is challenging because of the complexity of the community, anaerobic growth requirements of individual species and the large number of interactions that need to be quantitatively assessed. High-throughput screening setups offer a promising solution for probing the direct inhibitory effects of hundreds of xenobiotics on tens of anaerobic gut bacteria. When automated, such assays enable the cost-effective investigation of a wide range of compound-microbe combinations. We have developed an experimental setup and protocol that enables testing of up to 5,000 compounds on a target gut species under strict anaerobic conditions within 5 d. In addition, with minor modifications to the protocol, drug effects can be tested on microbial communities either assembled from isolates or obtained from stool samples. Experience in working in an anaerobic chamber, especially in performing delicate work with thick chamber gloves, is required for implementing this protocol. We anticipate that this protocol will accelerate the study of interactions between small molecules and the gut microbiome and provide a deeper understanding of this microbial ecosystem, which is intimately intertwined with human health.

Obesity is the main driver of altered gut microbiome functions in the metabolically unhealthy.

Obesity (OB) and cardiometabolic disease are major public health issues linked to changes in the gut microbiome. OB and poor cardiometabolic health status (CHS) are often comorbid, which hinders efforts to identify components of the microbiome uniquely linked to either one. Here, we used a deeply phenotyped cohort of 408 adults from Colombia, including subjects with OB, unhealthy CHS, or both, to validate previously reported features of gut microbiome function and diversity independently correlated with OB or CHS using fecal metagenomes. OB was defined by body mass index, waist circumference, and body fat; CHS as healthy or unhealthy according to blood biochemistry and anthropometric data. We found that OB, more so than metabolic status, drove associations with gut microbiome structure and functions. The microbiome of obese individuals with and without co-existing unhealthy CHS was characterized by reduced metagenomic diversity, reduced fermentative potential and elevated capacity to respond to oxidative stress and produce bacterial antigens. Disease-linked features were correlated with increased host blood pressure and inflammatory markers, and were mainly contributed by members of the family Enterobacteriaceae. Our results link OB with a microbiome able to tolerate an inflammatory and oxygenated gut state, and suggest that OB is the main driver of microbiome functional differences when poor CHS is a comorbidity.

Silent recognition of flagellins from human gut commensal bacteria by Toll-like receptor 5.

Flagellin, the protein subunit of the bacterial flagellum, stimulates the innate immune receptor Toll-like receptor 5 (TLR5) after pattern recognition or evades TLR5 through lack of recognition. This binary response fails to explain the weak agonism of flagellins from commensal bacteria, raising the question of how TLR5 response is tuned. Here, we screened abundant flagellins present in metagenomes from human gut for both TLR5 recognition and activation and uncovered a class of flagellin-TLR5 interaction termed silent recognition. Silent flagellins were weak TLR5 agonists despite pattern recognition. Receptor activity was tuned by a TLR5-flagellin interaction distal to the site of pattern recognition that was present in Salmonella flagellin but absent in silent flagellins. This interaction enabled flagellin binding to preformed TLR5 dimers and increased TLR5 signaling by several orders of magnitude. Silent recognition by TLR5 occurred in human organoids and mice, and silent flagellin proteins were present in human stool. These flagellins were produced primarily by the abundant gut bacteria Lachnospiraceae and were enriched in nonindustrialized populations. Our findings provide a mechanism for the innate immune system to tolerate commensal-derived flagellins while remaining vigilant to the presence of flagellins produced by pathogens.

Incorporating genome-based phylogeny and functional similarity into diversity assessments helps to resolve a global collection of human gut metagenomes.

Tree-based diversity measures incorporate phylogenetic or functional relatedness into comparisons of microbial communities. This can improve the identification of explanatory factors compared to tree-agnostic diversity measures. However, applying tree-based diversity measures to metagenome data is more challenging than for single-locus sequencing (e.g. 16S rRNA gene). Utilizing the Genome Taxonomy Database for species-level metagenome profiling allows for functional diversity measures based on genomic content or traits inferred from it. Still, it is unclear how metagenome-based assessments of microbiome diversity benefit from incorporating phylogeny or function into measures of diversity. We assessed this by measuring phylogeny-based, function-based and tree-agnostic diversity measures from a large, global collection of human gut metagenomes composed of 30 studies and 2943 samples. We found tree-based measures to explain phenotypic variation (e.g. westernization, disease status and gender) better or equivalent to tree-agnostic measures. Ecophylogenetic and functional diversity measures provided unique insight into how microbiome diversity was partitioned by phenotype. Tree-based measures greatly improved machine learning model performance for predicting westernization, disease status and gender, relative to models trained solely on tree-agnostic measures. Our findings illustrate the usefulness of tree- and function-based measures for metagenomic assessments of microbial diversity, which is a fundamental component of microbiome science.

Reclassification of Catabacter hongkongensis as Christensenella hongkongensis comb. nov. based on whole genome analysis.

The genera Catabacter (family 'Catabacteraceae') and Christensenella (family Christensenellaceae) are close relatives within the phylum Firmicutes. Members of these genera are strictly anaerobic, non-spore-forming and short straight rods with diverse phenotypes. Phylogenetic analysis of 16S rRNA genes suggest that Catabacter splits Christensenella into a polyphyletic clade. In an effort to ensure that family/genus names represent monophyletic clades, we performed a whole-genome based analysis of the genomes available for the cultured representatives of these genera: four species of Christensenella and two strains of Catabacter hongkongensis. A concatenated alignment of 135 shared protein sequences of single-copy core genes present in the included strains indicates that C. hongkongensis is indeed nested within the Christensenella clade. Based on their evolutionary relationship, we propose the transfer of Catabacter hongkongensis to the genus Christensenella as Christensenella hongkongensis comb. nov.

Genomic Insights into Adaptations of Trimethylamine-Utilizing Methanogens to Diverse Habitats, Including the Human Gut.

Archaea of the order Methanomassiliicoccales use methylated amines such as trimethylamine as the substrates for methanogenesis. They form two large phylogenetic clades and reside in diverse environments, from soil to the human gut. Two genera, one from each clade, inhabit the human gut: Methanomassiliicoccus, which has one cultured representative, and "Candidatus Methanomethylophilus," which has none. Questions remain regarding their distribution across biomes and human populations, their association with other taxa in the gut, and whether host genetics correlate with their abundance. To gain insight into the Methanomassiliicoccales clade, particularly its human-associated members, we performed a genomic comparison of 72 Methanomassiliicoccales genomes and assessed their presence in metagenomes derived from the human gut (n = 4,472, representing 22 populations), nonhuman animal gut (n = 145), and nonhost environments (n = 160). Our analyses showed that all taxa are generalists; they were detected in animal gut and environmental samples. We confirmed two large clades, one enriched in the gut and the other enriched in the environment, with notable exceptions. Genomic adaptations to the gut include genome reduction and genes involved in the shikimate pathway and bile resistance. Genomic adaptations differed by clade, not habitat preference, indicating convergent evolution between the clades. In the human gut, the relative abundance of Methanomassiliicoccales spp. correlated with trimethylamine-producing bacteria and was unrelated to host genotype. Our results shed light on the microbial ecology of this group and may help guide Methanomassiliicoccales-based strategies for trimethylamine mitigation in cardiovascular disease.IMPORTANCE Methanomassiliicoccales are less-known members of the human gut archaeome. Members of this order use methylated amines, including trimethylamine, in methane production. This group has only one cultured representative; how its members adapted to inhabit the mammalian gut and how they interact with other microbes is largely unknown. Using bioinformatics methods applied to DNA from a wide range of samples, we profiled the abundances of these Archaea spp. in environmental and host-associated microbial communities. We observed two groups of Methanomassiliicoccales, one largely host associated and one largely found in environmental samples, with some exceptions. When host associated, these Archaea have smaller genomes and possess genes related to bile resistance and aromatic amino acid precursors. We did not detect Methanomassiliicoccales in all human populations tested, but when present, they were correlated with bacteria known to produce trimethylamine. Due to their metabolism of trimethylamine, these intriguing Archaea may form the basis of novel therapies for cardiovascular disease.

Large-Scale Metagenome Assembly Reveals Novel Animal-Associated Microbial Genomes, Biosynthetic Gene Clusters, and Other Genetic Diversity.

Large-scale metagenome assemblies of human microbiomes have produced a vast catalogue of previously unseen microbial genomes; however, comparatively few microbial genomes derive from other vertebrates. Here, we generated 5,596 metagenome-assembled genomes (MAGs) from the gut metagenomes of 180 predominantly wild animal species representing 5 classes, in addition to 14 existing animal gut metagenome data sets. The MAGs comprised 1,522 species-level genome bins (SGBs), most of which were novel at the species, genus, or family level, and the majority were enriched in host versus environment metagenomes. Many traits distinguished SGBs enriched in host or environmental biomes, including the number of antimicrobial resistance genes. We identified 1,986 diverse biosynthetic gene clusters; only 23 clustered with any MIBiG database references. Gene-based assembly revealed tremendous gene diversity, much of it host or environment specific. Our MAG and gene data sets greatly expand the microbial genome repertoire and provide a broad view of microbial adaptations to the vertebrate gut.IMPORTANCE Microbiome studies on a select few mammalian species (e.g., humans, mice, and cattle) have revealed a great deal of novel genomic diversity in the gut microbiome. However, little is known of the microbial diversity in the gut of other vertebrates. We studied the gut microbiomes of a large set of mostly wild animal species consisting of mammals, birds, reptiles, amphibians, and fish. Unfortunately, we found that existing reference databases commonly used for metagenomic analyses failed to capture the microbiome diversity among vertebrates. To increase database representation, we applied advanced metagenome assembly methods to our animal gut data and to many public gut metagenome data sets that had not been used to obtain microbial genomes. Our resulting genome and gene cluster collections comprised a great deal of novel taxonomic and genomic diversity, which we extensively characterized. Our findings substantially expand what is known of microbial genomic diversity in the vertebrate gut.

Syntrophy via Interspecies H2 Transfer between Christensenella and Methanobrevibacter Underlies Their Global Cooccurrence in the Human Gut.

Across human populations, 16S rRNA gene-based surveys of gut microbiomes have revealed that the bacterial family Christensenellaceae and the archaeal family Methanobacteriaceae cooccur and are enriched in individuals with a lean, compared to an obese, body mass index (BMI). Whether these association patterns reflect interactions between metabolic partners, as well as whether these associations play a role in the lean host phenotype with which they associate, remains to be ascertained. Here, we validated previously reported cooccurrence patterns of the two families and their association with a lean BMI with a meta-analysis of 1,821 metagenomes derived from 10 independent studies. Furthermore, we report positive associations at the genus and species levels between Christensenella spp. and Methanobrevibacter smithii, the most abundant methanogen of the human gut. By coculturing three Christensenella spp. with M. smithii, we show that Christensenella spp. efficiently support the metabolism of M. smithii via H2 production far better than Bacteroides thetaiotaomicron does. Christensenella minuta forms flocs colonized by M. smithii even when H2 is in excess. In culture with C. minuta, H2 consumption by M. smithii shifts the metabolic output of C. minuta's fermentation toward acetate rather than butyrate. Together, these results indicate that the widespread cooccurrence of these microorganisms is underpinned by both physical and metabolic interactions. Their combined metabolic activity may provide insights into their association with a lean host BMI.IMPORTANCE The human gut microbiome is made of trillions of microbial cells, most of which are Bacteria, with a subset of Archaea The bacterial family Christensenellaceae and the archaeal family Methanobacteriaceae are widespread in human guts. They correlate with each other and with a lean body type. Whether species of these two families interact and how they affect the body type are unanswered questions. Here, we show that species within these families correlate with each other across people. We also demonstrate that particular species of these two families grow together in dense flocs, wherein the bacteria provide hydrogen gas to the archaea, which then make methane. When the archaea are present, the ratio of bacterial products (which are nutrients for humans) is changed. These observations indicate that when these species grow together, their products have the potential to affect the physiology of their human host.

Gut microbiota composition explains more variance in the host cardiometabolic risk than genetic ancestry.

Cardiometabolic affections greatly contribute to the global burden of disease. The susceptibility to obesity, cardiovascular disease, and type-2 diabetes, conditions that add to the cardiometabolic syndrome (CMS), was associated with the ancestral genetic composition and gut microbiota. Studies explicitly testing associations between genetic ancestry and gut microbes are growing. We here examined whether the host genetic ancestry was associated with gut microbiota composition, and distinguished the effects of genetic ancestry and non-genetic factors on human cardiometabolic health. We performed a cross-sectional study with 441 community-dwelling Colombian mestizos from five cities spanning the Andes, Pacific, and Caribbean coasts. We characterized the host genetic ancestry by genotyping 40 ancestry informative markers; characterized gut microbiota through 16S rRNA gene sequencing; assessed diet intake, physical activity, cigarette, and medicament consumption; and measured cardiometabolic outcomes that allowed calculating a CMS risk scale. On average, each individual of our cohort was 67 ± 6% European, 21 ± 5% Native American and 12 ± 5% African. Multivariable-adjusted generalized linear models showed that individuals with higher Native American and African ancestries had increased fasting insulin, body mass index and CMS risk, as assessed by the CMS risk scale. Furthermore, we identified 21 OTUs associated to the host genetic ancestry and 20 to cardiometabolic health. While we highlight novel associations between genetic ancestry and gut microbiota, we found that the effect of intestinal microbes was more likely to explain the variance in CMS risk scale than the contributions of European, Native American and African genetic backgrounds.

Variants in genes of innate immunity, appetite control and energy metabolism are associated with host cardiometabolic health and gut microbiota composition.

Identifying the genetic and non-genetic determinants of obesity and related cardiometabolic dysfunctions is cornerstone for their prevention, treatment, and control. While genetic variants contribute to the cardiometabolic syndrome (CMS), non-genetic factors, such as the gut microbiota, also play key roles. Gut microbiota is intimately associated with CMS and its composition is heritable. However, associations between this microbial community and host genetics are understudied. We contribute filling this gap by genotyping 60 variants in 39 genes of three modules involved in CMS risk, measuring cardiometabolic risk factors, and characterizing gut microbiota in a cohort of 441 Colombians. We hypothesized that CMS risk variants were correlated with detrimental levels of clinical parameters and with the abundance of disease-associated microbes. We found several polymorphisms in genes of innate immunity, appetite control, and energy metabolism that were associated with metabolic dysregulation and microbiota composition; the associations between host genetics and cardiometabolic health were independent of the participants' gut microbiota, and those between polymorphisms and gut microbes were independent of the CMS risk. Associations were also independent of the host genetic ancestry, diet and lifestyle. Most microbes explaining genetic-microbiota associations belonged to the families Lachnospiraceae and Ruminococcaceae. Multiple CMS risk alleles were correlated with increased abundance of beneficial microbiota, suggesting that the phenotypic outcome of the evaluated variants might depend upon the genetic background of the studied population and its environmental context. Our results provide additional evidence that the gut microbiota is under the host genetic control and present pathways of host-microbe interactions.

Struo: a pipeline for building custom databases for common metagenome profilers.

SUMMARY: Taxonomic and functional information from microbial communities can be efficiently obtained by metagenome profiling, which requires databases of genes and genomes to which sequence reads are mapped. However, the databases that accompany metagenome profilers are not updated at a pace that matches the increase in available microbial genomes, and unifying database content across metagenome profiling tools can be cumbersome. To address this, we developed Struo, a modular pipeline that automatizes the acquisition of genomes from public repositories and the construction of custom databases for multiple metagenome profilers. The use of custom databases that broadly represent the known microbial diversity by incorporating novel genomes results in a substantial increase in mappability of reads in synthetic and real metagenome datasets. AVAILABILITY AND IMPLEMENTATION: Source code available for download at https://github.com/leylabmpi/Struo. Custom genome taxonomy database databases available at http://ftp.tue.mpg.de/ebio/projects/struo/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Age- and Sex-Dependent Patterns of Gut Microbial Diversity in Human Adults.

Gut microbial diversity changes throughout the human life span and is known to be associated with host sex. We investigated the association of age, sex, and gut bacterial alpha diversity in three large cohorts of adults from four geographical regions: subjects from the United States and United Kingdom in the American Gut Project (AGP) citizen-science initiative and two independent cohorts of Colombians and Chinese. In three of the four cohorts, we observed a strong positive association between age and alpha diversity in young adults that plateaued after age 40 years. We also found sex-dependent differences that were more pronounced in younger adults than in middle-aged adults, with women having higher alpha diversity than men. In contrast to the other three cohorts, no association of alpha diversity with age or sex was observed in the Chinese cohort. The association of alpha diversity with age and sex remained after adjusting for cardiometabolic parameters in the Colombian cohort and antibiotic usage in the AGP cohort. We further attempted to predict the microbiota age in individuals using a machine-learning approach for the men and women in each cohort. Consistent with our alpha-diversity-based findings, U.S. and U.K. women had a significantly higher predicted microbiota age than men, with a reduced difference being seen above age 40 years. This difference was not observed in the Colombian cohort and was observed only in middle-aged Chinese adults. Together, our results provide new insights into the influence of age and sex on the biodiversity of the human gut microbiota during adulthood while highlighting similarities and differences across diverse cohorts. IMPORTANCE Microorganisms in the human gut play a role in health and disease, and in adults higher gut biodiversity has been linked to better health. Since gut microorganisms may be pivotal in the development of microbial therapies, understanding the factors that shape gut biodiversity is of utmost interest. We performed large-scale analyses of the relationship of age and sex to gut bacterial diversity in adult cohorts from four geographic regions: the United States, the United Kingdom, Colombia, and China. In the U.S., U.K., and Colombian cohorts, bacterial biodiversity correlated positively with age in young adults but plateaued at about age 40 years, with no positive association being found in middle-aged adults. Young, but not middle-aged, adult women had higher gut bacterial diversity than men, a pattern confirmed via supervised machine learning. Interestingly, in the Chinese cohort, minimal associations were observed between gut biodiversity and age or sex. Our results highlight the patterns of adult gut biodiversity and provide a framework for future research.

Higher Fecal Short-Chain Fatty Acid Levels Are Associated with Gut Microbiome Dysbiosis, Obesity, Hypertension and Cardiometabolic Disease Risk Factors.

Fiber fermentation by gut microbiota yields short-chain fatty acids (SCFAs) that are either absorbed by the gut or excreted in feces. Studies are conflicting as to whether SCFAs are beneficial or detrimental to cardiometabolic health, and how gut microbiota associated with SCFAs is unclear. In this study of 441 community-dwelling adults, we examined associations of fecal SCFAs, gut microbiota diversity and composition, gut permeability, and cardiometabolic outcomes, including obesity and hypertension. We assessed fecal microbiota by 16S rRNA gene sequencing, and SCFA concentrations by gas chromatography/mass spectrometry. Fecal SCFA concentrations were inversely associated with microbiota diversity, and 70 unique microbial taxa were differentially associated with at least one SCFA (acetate, butyrate or propionate). Higher SCFA concentrations were associated with a measure of gut permeability, markers of metabolic dysregulation, obesity and hypertension. Microbial diversity showed association with these outcomes in the opposite direction. Associations were significant after adjusting for measured confounders. In conclusion, higher SCFA excretion was associated with evidence of gut dysbiosis, gut permeability, excess adiposity, and cardiometabolic risk factors. Studies assessing both fecal and circulating SCFAs are needed to test the hypothesis that the association of higher fecal SCFAs with obesity and cardiometabolic dysregulation is due to less efficient SCFA absorption.

Gut microbiota is associated with obesity and cardiometabolic disease in a population in the midst of Westernization.

Westernization and its accompanying epidemiological transitions are associated with changes in gut microbiota. While the extremes of this lifestyle spectrum have been compared (hunter-gatherers, industrialized countries), populations undergoing such shifts have received little attention. To fill the gap of knowledge about the microbiome evolution following broad lifestyle changes and the emergence of disease-associated dysbiosis, we performed a cross-sectional study in which we characterized the microbiota of 441 Colombian adults through 16S rRNA gene sequencing and determined its relationship with demographic, health-related and dietary parameters. We showed that in the gut microbiota of this cohort thrive taxa proper of both hunter-gatherers (Prevotella, Treponema) and citizens of industrialized countries (Bacteroides, Bifidobacterium, Barnesiella); the relative abundances of these taxa differed from those in Western and non-Western populations. We also showed that the Colombian gut microbiota is composed of five consortia of co-abundant microorganisms that are differentially associated with lifestyle, obesity and cardiometabolic disease, and highlighted metabolic pathways that might explain associations between microbiota and host health. Our results give insights into the evolution of the gut microbiota, and underscore the importance of this community to human health. Promoting the growth of specific microbial consortia could help ameliorating physiological conditions associated with Western lifestyles.

Impact of DNA extraction, sample dilution, and reagent contamination on 16S rRNA gene sequencing of human feces.

Culture-independent methods have granted the possibility to study microbial diversity in great detail, but technical issues pose a threat to the accuracy of new findings. Biases introduced during DNA extraction can result in erroneous representations of the microbial community, particularly in samples with low microbial biomass. We evaluated the DNA extraction method, initial sample biomass, and reagent contamination on the assessment of the human gut microbiota. Fecal samples of 200 mg were subjected to 1:10 serial dilutions; total DNA was obtained using two commercial kits and the microbiota assessed by 16S ribosomal RNA (rRNA) gene sequencing. In addition, we sequenced multiple technical controls. The two kits were efficient in extracting DNA from samples with as low as 2 mg of feces. However, in instances of lower biomass, only one kit performed well. The number of reads from negative controls was negligible. Both DNA extraction kits allowed inferring microbial consortia with similar membership but different abundances. Furthermore, we found differences in the taxonomic profile of the microbial community. Unexpectedly, the effect of sample dilution was moderate and did not introduce severe bias into the microbial inference. Indeed, the microbiota inferred from fecal samples was distinguishable from that of negative controls. In most cases, samples as low as 2 mg did not result in a dissimilar representation of the microbial community compared with the undiluted sample. Our results indicate that the gut microbiota inference is not much affected by contamination with laboratory reagents but largely impacted by the protocol to extract DNA.

Metformin Is Associated With Higher Relative Abundance of Mucin-Degrading Akkermansia muciniphila and Several Short-Chain Fatty Acid-Producing Microbiota in the Gut.

OBJECTIVE: Recent studies suggest the beneficial effects of metformin on glucose metabolism may be microbially mediated. We examined the association of type 2 diabetes, metformin, and gut microbiota in community-dwelling Colombian adults. On the basis of previous research, we hypothesized that metformin is associated with higher levels of short-chain fatty acid (SCFA)-producing and mucin-degrading microbiota. RESEARCH DESIGN AND METHODS: Participants were selected from a larger cohort of 459 participants. The present analyses focus on the 28 participants diagnosed with diabetes-14 taking metformin- and the 84 participants without diabetes who were matched (3-to-1) to participants with diabetes by sex, age, and BMI. We measured demographic information, anthropometry, and blood biochemical parameters and collected fecal samples from which we performed 16S rRNA gene sequencing to analyze the composition and structure of the gut microbiota. RESULTS: We found an association between diabetes and gut microbiota that was modified by metformin use. Compared with participants without diabetes, participants with diabetes taking metformin had higher relative abundance of Akkermansia muciniphila, a microbiota known for mucin degradation, and several gut microbiota known for production of SCFAs, including Butyrivibrio, Bifidobacterium bifidum, Megasphaera, and an operational taxonomic unit of Prevotella. In contrast, compared with participants without diabetes, participants with diabetes not taking metformin had higher relative abundance of Clostridiaceae 02d06 and a distinct operational taxonomic unit of Prevotella and a lower abundance of Enterococcus casseliflavus. CONCLUSIONS: Our results support the hypothesis that metformin shifts gut microbiota composition through the enrichment of mucin-degrading A. muciniphila as well as several SCFA-producing microbiota. Future studies are needed to determine if these shifts mediate metformin's glycemic and anti-inflammatory properties.

Considerations For Optimizing Microbiome Analysis Using a Marker Gene.

Next-generation sequencing technologies have found a widespread use in the study of host-microbe interactions due to the increase in their throughput and their ever-decreasing costs. The analysis of human-associated microbial communities using a marker gene, particularly the 16S rRNA, has been greatly benefited from these technologies - the human gut microbiome research being a remarkable example of such analysis that has greatly expanded our understanding of microbe-mediated human health and disease, metabolism, and food absorption. 16S studies go through a series of in vitro and in silico steps that can greatly influence their outcomes. However, the lack of a standardized workflow has led to uncertainties regarding the transparency and reproducibility of gut microbiome studies. We, here, discuss the most common challenges in the archetypical 16S rRNA workflow, including the extraction of total DNA, its use as template in PCR with primers that amplify specific hypervariable regions of the gene, amplicon sequencing, the denoising and removal of low-quality reads, the detection and removal of chimeric sequences, the clustering of high-quality sequences into operational taxonomic units, and their taxonomic classification. We recommend the essential technical information that should be conveyed in publications for reproducibility of results and encourage non-experts to include procedures and available tools that mitigate most of the problems encountered in microbiome analysis.