Piphillin predicts metagenomic composition and dynamics from DADA2-corrected 16S rDNA sequences

Characterization of the gut bacterial and viral microbiota in latent autoimmune diabetes in adults

Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by autoantibodies against insulin producing pancreatic beta cells and initial lack of need for insulin treatment. The aim of the present study was to investigate if individuals with LADA have an altered gut microbiota relative to non-diabetic control subjects, individuals with type 1 diabetes (T1D), and individuals with type 2 diabetes (T2D). Bacterial community profiling was performed with primers targeting the variable region 4 of the 16S rRNA gene and sequenced. Amplicon sequence variants (ASVs) were generated with DADA2 and annotated to the SILVA database. The gut virome was sequenced, using a viral particle enrichment and metagenomics approach, assembled, and quantified to describe the composition of the viral community. Comparison of the bacterial alpha- and beta-diversity measures revealed that the gut bacteriome of individuals with LADA resembled that of individuals with T2D. Yet, specific genera were found to differ in abundance in individuals with LADA compared with T1D and T2D, indicating that LADA has unique taxonomical features. The virome composition reflected the stability of the most dominant order Caudovirales and the families Siphoviridae, Podoviridae, and Inoviridae, and the dominant family Microviridae. Further studies are needed to confirm these findings.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Gut Microbiota Is Associated with Onset and Severity of Type 1 Diabetes in Nonobese Diabetic Mice Treated with Anti-PD-1

Our bodies are home to individual-specific microbial ecosystems that have recently been found to be modified by cancer immunotherapies. The interaction between the gut microbiome and islet autoimmunity leading to type I diabetes (T1D) is well described and highlights the microbiome contribution during the onset and T1D development in animals and humans. As cancer immunotherapies induce gut microbiome perturbations and immune-mediated adverse events in susceptible patients, we hypothesized that NOD mice can be used as a predictive tool to investigate the effects of anti-PD-1 treatment on the onset and severity of T1D, and how microbiota influences immunopathology. In this longitudinal study, we showed that anti-PD-1 accelerated T1D onset, increased glutamic acid decarboxylase-reactive T cell frequency in spleen, and precipitated destruction of β cells, triggering high glucose levels and pancreatic islet reduction. Anti-PD-1 treatment also resulted in temporal microbiota changes and lower diversity characteristic of T1D. Finally, we identified known insulin-resistance regulating bacteria that were negatively correlated with glucose levels, indicating that anti-PD-1 treatment impacts the early gut microbiota composition. Moreover, an increase of mucin-degrading Akkermansia muciniphila points to alterations of barrier function and immune system activation. These results highlight the ability of microbiota to readily respond to therapy-triggered pathophysiological changes as rescuers (Bacteroides acidifaciens and Parabacteroides goldsteinii) or potential exacerbators (A. muciniphila). Microbiome-modulating interventions may thus be promising mitigation strategies for immunotherapies with high risk of immune-mediated adverse events.

Revisiting the intrinsic mycobiome in pancreatic cancer

A growing body of literature suggests that alterations in the human microbiome are causative of disease initiation and progression. Aykut et al1 . present data supporting the argument that alterations in the gut fungal microbiome (the “mycobiome”), along with the presence of fungal elements within pancreatic tissue (specifically those of the genus Malassezia) , are associated with pancreatic oncogenesis. Upon analyzing the human sequencing data presented in the original manuscript, we found few fungal reads in pancreatic tissue samples and did not identify differences in pancreatic or gut mycobiome composition between healthy and pancreatic ductal adenocarcinoma (PDAC) patients. Our re-analysis of these data does not support an association between an intrinsic pancreatic mycobiome and the development of human PDAC, and illustrates the challenges in analyzing microbiome sequencing data from low biomass samples.

The Microbiota of a Mite Prey-Predator System on Different Host Plants Are Characterized by Dysbiosis and Potential Functional Redundancy

Microbiota has diverse roles in the life cycles of their hosts, affecting their growth, development, behavior, and reproduction. Changes in physiological conditions of the host can also impact the assemblage of host-associated microorganisms. However, little is known of the effects of host plant-prey-predatory mite interactions on mite microbiota. We compared the microbial communities of eggs and adult females of the two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae), and of adult females of the predatory mite Neoseiulus californicus (McGregor) (Acari: Phytoseiidae) on four different host plants (cotton, maize, pinto bean, and tomato) by metabarcoding sequencing of the V3-V4 region of the 16S ribosomal RNA gene (16S rRNA), using the Illumina MiSeq platform. Only the egg microbiota of T. urticae was affected by the host plant. The microbiota of the predatory mite N. californicus was very different from that of its prey, and the predator microbiota was unaffected by the different host plant-prey systems tested. Only the microbiota of the eggs of T. urticae carried Serratia as a high fidelity-biomarker, but their low abundance in T. urticae adult females suggests that the association between Serratia and T. urticae is accidental. Biomarker bacteria were also detected in the microbiota of adult females of T. urticae and N. californicus, with different biomarkers in each host plant species. The microbiota associated with eggs and adult females of T. urticae and adult females of N. californicus differed in their functional potential contributions to the host mite.

Vaginal Microbiome Metagenome Inference Accuracy: Differential Measurement Error according to Community Composition

Several studies have compared metagenome inference performance in different human body sites; however, none specifically reported on the vaginal microbiome. Findings from other body sites cannot easily be generalized to the vaginal microbiome due to unique features of vaginal microbial ecology, and investigators seeking to use metagenome inference in vaginal microbiome research are "flying blind" with respect to potential bias these methods may introduce into analyses. We compared the performance of PICRUSt2 and Tax4Fun2 using paired 16S rRNA gene amplicon sequencing and whole-metagenome sequencing data from vaginal samples from 72 pregnant individuals enrolled in the Pregnancy, Infection, and Nutrition (PIN) cohort. Participants were selected from those with known birth outcomes and adequate 16S rRNA gene amplicon sequencing data in a case-control design. Cases experienced early preterm birth (<32 weeks of gestation), and controls experienced term birth (37 to 41 weeks of gestation). PICRUSt2 and Tax4Fun2 performed modestly overall (median Spearman correlation coefficients between observed and predicted KEGG ortholog [KO] relative abundances of 0.20 and 0.22, respectively). Both methods performed best among Lactobacillus crispatus-dominated vaginal microbiotas (median Spearman correlation coefficients of 0.24 and 0.25, respectively) and worst among Lactobacillus iners-dominated microbiotas (median Spearman correlation coefficients of 0.06 and 0.11, respectively). The same pattern was observed when evaluating correlations between univariable hypothesis test P values generated with observed and predicted metagenome data. Differential metagenome inference performance across vaginal microbiota community types can be considered differential measurement error, which often causes differential misclassification. As such, metagenome inference will introduce hard-to-predict bias (toward or away from the null) in vaginal microbiome research. IMPORTANCE Compared to taxonomic composition, the functional potential within a bacterial community is more relevant to establishing mechanistic understandings and causal relationships between the microbiome and health outcomes. Metagenome inference attempts to bridge the gap between 16S rRNA gene amplicon sequencing and whole-metagenome sequencing by predicting a microbiome's gene content based on its taxonomic composition and annotated genome sequences of its members. Metagenome inference methods have been evaluated primarily among gut samples, where they appear to perform fairly well. Here, we show that metagenome inference performance is markedly worse for the vaginal microbiome and that performance varies across common vaginal microbiome community types. Because these community types are associated with sexual and reproductive outcomes, differential metagenome inference performance will bias vaginal microbiome studies, obscuring relationships of interest. Results from such studies should be interpreted with substantial caution and the understanding that they may over- or underestimate associations with metagenome content.

Microbiome analysis revealed distinct microbial communities occupying different sized nodules in field-grown peanut

Legume nodulation is the powerhouse of biological nitrogen fixation (BNF) where host-specific rhizobia dominate the nodule microbiome. However, other rhizobial or non-rhizobial inhabitants can also colonize legume nodules, and it is unclear how these bacteria interact, compete, or combinedly function in the nodule microbiome. Under such context, to test this hypothesis, we conducted 16S-rRNA based nodule microbiome sequencing to characterize microbial communities in two distinct sized nodules from field-grown peanuts inoculated with a commercial inoculum. We found that microbial communities diverged drastically in the two types of peanut nodules (big and small). Core microbial analysis revealed that the big nodules were inhabited by Bradyrhizobium, which dominated composition (>99%) throughout the plant life cycle. Surprisingly, we observed that in addition to Bradyrhizobium, the small nodules harbored a diverse set of bacteria (~31%) that were not present in big nodules. Notably, these initially less dominant bacteria gradually dominated in small nodules during the later plant growth phases, which suggested that native microbial communities competed with the commercial inoculum in the small nodules only. Conversely, negligible or no competition was observed in the big nodules. Based on the prediction of KEGG pathway analysis for N and P cycling genes and the presence of diverse genera in the small nodules, we foresee great potential of future studies of these microbial communities which may be crucial for peanut growth and development and/or protecting host plants from various biotic and abiotic stresses.

Recent advances in metagenomic analysis of different ecological niches for enhanced biodegradation of recalcitrant lignocellulosic biomass

Lignocellulose wastes stemming from agricultural residues can offer an excellent opportunity as alternative energy solutions in addition to fossil fuels. Besides, the unrestrained burning of agricultural residues can lead to the destruction of the soil microflora and associated soil sterilization. However, the difficulties associated with the biodegradation of lignocellulose biomasses remain as a formidable challenge for their sustainable management. In this respect, metagenomics can be used as an effective option to resolve such dilemma because of its potential as the next generation sequencing technology and bioinformatics tools to harness novel microbial consortia from diverse environments (e.g., soil, alpine forests, and hypersaline/acidic/hot sulfur springs). In light of the challenges associated with the bulk-scale biodegradation of lignocellulose-rich agricultural residues, this review is organized to help delineate the fundamental aspects of metagenomics towards the assessment of the microbial consortia and novel molecules (such as biocatalysts) which are otherwise unidentifiable by conventional laboratory culturing techniques. The discussion is extended further to highlight the recent advancements (e.g., from 2011 to 2022) in metagenomic approaches for the isolation and purification of lignocellulolytic microbes from different ecosystems along with the technical challenges and prospects associated with their wide implementation and scale-up. This review should thus be one of the first comprehensive reports on the metagenomics-based analysis of different environmental samples for the isolation and purification of lignocellulose degrading enzymes.

Adalimumab therapy is associated with increased faecal short chain fatty acids in hidradenitis suppurativa

Altered gut microbiota composition has been observed in individuals with hidradenitis suppurutiva (HS) and many other inflammatory diseases, including obesity, type 1 and type 2 diabetes. Here, we addressed whether adalimumab, a systemic anti-inflammatory therapy, may impact the microbiota biochemical profile, particularly on beneficial metabolites such as short-chain fatty acids (SCFAs). We conducted an observational single-arm pilot trial to assess gut microbiota composition by 16S rRNA gene sequence analysis and to detect metabolite signatures by gas chromatography in stool samples from participants with HS prior to and 12 weeks after commencing adalimumab therapy. HS individuals that better responded to adalimumab treatment showed a shift in the composition and function of the gut microbiota with significantly increased SCFA acetate and propionate compared to age, gender and BMI-matched healthy controls. A positive correlation was observed between propionate with Prevotella sp and Faecalibacterium prausnitsii. Increased SCFAs, changes in gut microbiota composition, function and metabolic profile following 12 weeks of adalimumab suggest that targeting SCFAs may be considered a potential biomarker to be evaluated as a complementary protective factor or as a diagnostically relevant signal in HS.

Resistant starch type-4 intake alters circulating bile acids in human subjects

Background

Resistant starch (RS) type 4 (RS4) is a type of RS, a class of non-digestible prebiotic dietary fibers with a range of demonstrated metabolic health benefits to the host. On the other hand, bile acids (BA) have recently emerged as an important class of metabolic function mediators that involve host-microbiota interactions. RS consumption alters fecal and cecal BA in humans and rodents, respectively. The effect of RS intake on circulating BA concentrations remains unexplored in humans.

Methods and results

Using available plasma and stool samples from our previously reported double-blind, controlled, 2-arm crossover nutrition intervention trial (Clinicaltrials.gov: NCT01887964), a liquid-chromatography/mass-spectrometry-based targeted multiple reaction monitoring, and absolute quantifications, we assessed BA changes after 12 weeks of an average 12 g/day RS4-intake. Stool BA concentrations were lower post RS4 compared to the control, the two groups consuming similar macronutrients (n = 14/group). Partial least squares-discriminant analysis revealed distinct BA signatures in stool and plasma post interventions. The increased circulating BA concentrations were further investigated using linear mixed-effect modeling that controlled for potential confounders. A higher plasma abundance of several BA species post RS4 was observed (fold increase compared to control in parenthesis): taurocholic acid (1.92), taurodeoxycholic acid (1.60), glycochenodeoxycholic acid (1.58), glycodeoxycholic acid (1.79), and deoxycholic acid (1.77) (all, p < 0.05). Distinct microbiome ortholog-signatures were observed between RS4 and control groups (95% CI), derived using the Piphillin function-prediction algorithm and principal component analysis (PCA) of pre-existing 16S rRNA gene sequences. Association of Bifidobacterium adolescentis with secondary BA such as, deoxycholic acid (rho = 0.55, p = 0.05), glycodeoxycholic acid (rho = 0.65, p = 0.02), and taurodeoxycholic acid (rho = 0.56, p = 0.04) were observed in the RS4-group, but not in the control group (all, p > 0.05).

Conclusion

Our observations indicate a previously unknown in humans- RS4-associated systemic alteration of microbiota-derived secondary BA. Follow-up investigations of BA biosynthesis in the context of RS4 may provide molecular targets to understand and manipulate microbiome-host interactions.

The Role of Feeding Characteristics in Shaping Gut Microbiota Composition and Function of Ensifera (Orthoptera)

Feeding habits were the primary factor affecting the gut bacterial communities in Ensifera. However, the interaction mechanism between the gut microbiota and feeding characteristics is not precisely understood. Here, the gut microbiota of Ensifera with diverse feeding habits was analyzed by shotgun metagenomic sequencing to further clarify the composition and function of the gut microbiota and its relationship with feeding characteristics. Our results indicate that under the influence of feeding habits, the gut microbial communities of Ensifera showed specific characteristics. Firstly, the gut microbial communities of the Ensifera with different feeding habits differed significantly, among which the gut microbial diversity of the herbivorous Mecopoda niponensis was the highest. Secondly, the functional genes related to feeding habits were in high abundance. Thirdly, the specific function of the gut microbial species in the omnivorous Gryllotalpa orientalis showed that the more diverse the feeding behavior of Ensifera, the worse the functional specificity related to the feeding characteristics of its gut microbiota. However, feeding habits were not the only factors affecting the gut microbiota of Ensifera. Some microorganisms' genes, whose functions were unrelated to feeding characteristics but were relevant to energy acquisition and nutrient absorption, were detected in high abundance. Our results were the first to report on the composition and function of the gut microbiota of Ensifera based on shotgun metagenomic sequencing and to explore the potential mechanism of the gut microbiota's association with diverse feeding habits.

Efficacy and safety of a food supplement with standardized menthol, limonene, and gingerol content in patients with irritable bowel syndrome: A double-blind, randomized, placebo-controlled trial

Background

Irritable bowel syndrome (IBS) affects 9,2% of the global population and places a considerable burden on healthcare systems. Most medications for treating IBS, including spasmolytics, laxatives, and antidiarrheals, have low efficacy. Effective and safe therapeutic treatments have yet to be developed for IBS.

Purpose

This study assessed the efficacy and safety of a food supplement containing standardized menthol, limonene, and gingerol in human participants with IBS or IBS/functional dyspepsia (FD).

Design

A double-blind, randomized, placebo-controlled trial.

Methods

We randomly assigned 56 patients with IBS or IBS/FD to an intervention group (Group 1) or control group (Group 2) that were given supplement or placebo, respectively, in addition to the standard treatment regimen for 30 d. Three outpatient visits were conducted during the study. Symptom severity was measured at each visit using a 7×7 questionnaire. Qualitative and quantitative composition of the intestinal microbiota were assessed at visits 1 and 3 based on 16S rRNA gene sequencing.

Results

At visit 1 (before treatment), the median total 7×7 questionnaire score was in the moderately ill range for both groups, with no difference between the groups (p = 0.1). At visit 2, the total 7×7 score decreased to mildly ill, with no difference between the groups (p = 0.4). At visit 3, the total score for group 1 indicated borderline illness and for group 2 remained indicated mild illness (p = 0.009). Even though we observed some variations in gut microbiota between the groups, we did not find any statistically significant changes.

Conclusion

The food supplement with standardized menthol, limonene, and gingerol content increased the efficacy of standard therapy in IBS and FD patients. The use of the supplement did not cause any obvious side effects.

Registration

ClinicalTrials.gov Identifier: NCT04484467

Species- and site-specific circulating bacterial DNA in Subantarctic sentinel mussels Aulacomya atra and Mytilus platensis

Impacts of climate changes are particularly severe in polar regions where warmer temperatures and reductions in sea-ice covers threaten the ecological integrity of marine coastal ecosystems. Because of their wide distribution and their ecological importance, mussels are currently used as sentinel organisms in monitoring programs of coastal ecosystems around the world. In the present study, we exploited the concept of liquid biopsy combined to a logistically friendly sampling method to study the hemolymphatic bacterial microbiome in two mussel species (Aulacomya atra and Mytilus platensis) in Kerguelen Islands, a remote Subantarctic volcanic archipelago. We found that the circulating microbiome signatures of both species differ significantly even though their share the same mussel beds. We also found that the microbiome differs significantly between sampling sites, often correlating with the particularity of the ecosystem. Predictive models also revealed that both species have distinct functional microbiota, and that the circulating microbiome of Aulacomya atra was more sensitive to changes induced by acute thermal stress when compared to Mytilus platensis. Taken together, our study suggests that defining circulating microbiome is a useful tool to assess the health status of marine ecosystems and to better understand the interactions between the sentinel species and their habitat.

Deciphering the influence of multiple anthropogenic inputs on taxonomic and functional profiles of the microbial communities in Yitong River, Northeast China

We conducted the analysis of physicochemical parameters, 16S rRNA amplicon sequencing and real-time quantitative polymerase chain reaction to explore the impact of human inputs on the bacterioplankton communities within a tributary of the largest river flowing through a megacity in northeast China. Agriculture largely accounted for the alteration of diversity and functions of the microbial communities. Furthermore, nitrate and total phosphorus declined at the reservoir outlet. The WWTP effluent discharge caused a decrease of the relative abundance of Actinobacteria and Cyanobacteria, while the impact on the variation of alpha diversity of river microbial community was slight. Carbon fixation and nitrogen cycle varied with the change of land use type. The rare taxa contributed with a predominant role in the response to environmental variables and NH₃-N as well as NO₃^--N were the main environmental factors that drove the shift in the bacterial community. The occurrence of the human-specific fecal indicator was mostly derived from agriculture, and its increase in relative abundance was observed in the WWTP effluent. Thus, our study provides guidance for ecological assessment and management of rivers by revealing the response pattern of river bacterioplankton to multiple types of anthropogenic stressors.

Composition and Functional Potential of the Human Mammary Microbiota Prior to and Following Breast Tumor Diagnosis

Microbiota studies have reported changes in the microbial composition of the breast upon cancer development. However, results are inconsistent and limited to the later phases of cancer development (after diagnosis). We analyzed and compared the resident bacterial taxa of histologically normal breast tissue (healthy, H, n = 49) with those of tissues donated prior to (prediagnostic, PD, n = 15) and after (adjacent normal, AN, n = 49, and tumor, T, n = 46) breast cancer diagnosis (n total = 159). DNA was isolated from tissue samples and submitted for Illumina MiSeq paired-end sequencing of the V3-V4 region of the 16S gene. To infer bacterial function in breast cancer, we predicted the functional bacteriome from the 16S sequencing data using PICRUSt2. Bacterial compositional analysis revealed an intermediary taxonomic signature in the PD tissue relative to that of the H tissue, represented by shifts in Bacillaceae, Burkholderiaceae, Corynebacteriaceae, Streptococcaceae, and Staphylococcaceae. This compositional signature was enhanced in the AN and T tissues. We also identified significant metabolic reprogramming of the microbiota of the PD, AN, and T tissue compared with the H tissue. Further, preliminary correlation analysis between host transcriptome profiling and microbial taxa and genes in H and PD tissues identified altered associations between the human host and mammary microbiota in PD tissue compared with H tissue. These findings suggest that compositional shifts in bacterial abundance and metabolic reprogramming of the breast tissue microbiota are early events in breast cancer development that are potentially linked with cancer susceptibility.

IMPORTANCE The goal of this study was to determine the role of resident breast tissue bacteria in breast cancer development. We analyzed breast tissue bacteria in healthy breast tissue and breast tissue donated prior to (precancerous) and after (postcancerous) breast cancer diagnosis. Compared to healthy tissue, the precancerous and postcancerous breast tissues demonstrated differences in the amounts of breast tissue bacteria. In addition, breast tissue bacteria exhibit different functions in pre-cancerous and post-cancerous breast tissues relative to healthy tissue. These differences in function are further emphasized by altered associations of the breast tissue bacteria with gene expression in the human host prior to cancer development. Collectively, these analyses identified shifts in bacterial abundance and metabolic function (dysbiosis) prior to breast tumor diagnosis. This dysbiosis may serve as a therapeutic target in breast cancer prevention.

Salicylic Acid-Mediated Disturbance Increases Bacterial Diversity in the Phyllosphere but Is Overcome by a Dominant Core Community

Plant microbiomes and immune responses have coevolved through history, and this applies just as much to the phyllosphere microbiome and defense phytohormone signaling. When in homeostasis, the phyllosphere microbiome confers benefits to its host. However, the phyllosphere is also dynamic and subject to stochastic events that can modulate community assembly. Investigations into the impact of defense phytohormone signaling on the microbiome have so far been limited to culture-dependent studies; or focused on the rhizosphere. In this study, the impact of the foliar phytohormone salicylic acid (SA) on the structure and composition of the phyllosphere microbiome was investigated. 16S rRNA amplicons were sequenced from aerial tissues of two Arabidopsis mutants that exhibit elevated SA signaling through different mechanisms. SA signaling was shown to increase community diversity and to result in the colonization of rare, satellite taxa in the phyllosphere. However, a stable core community remained in high abundance. Therefore, we propose that SA signaling acts as a source of intermediate disturbance in the phyllosphere. Predictive metagenomics revealed that the SA-mediated microbiome was enriched for antibiotic biosynthesis and the degradation of a diverse range of xenobiotics. Core taxa were predicted to be more motile, biofilm-forming and were enriched for traits associated with microbe-microbe communication; offering potential mechanistic explanation of their success despite SA-mediated phyllospheric disturbance.

Diet Prevents Social Stress-Induced Maladaptive Neurobehavioural and Gut Microbiota Changes in a Histamine-Dependent Manner

Exposure to repeated social stress may cause maladaptive emotional reactions that can be reduced by healthy nutritional supplementation. Histaminergic neurotransmission has a central role in orchestrating specific behavioural responses depending on the homeostatic state of a subject, but it remains to be established if it participates in the protective effects against the insults of chronic stress afforded by a healthy diet. By using C57BL/6J male mice that do not synthesize histamine (Hdc-/-) and their wild type (Hdc+/+) congeners we evaluated if the histaminergic system participates in the protective action of a diet enriched with polyunsaturated fatty acids and vitamin A on the deleterious effect of chronic stress. Behavioural tests across domains relevant to cognition and anxiety were performed. Hippocampal synaptic plasticity, cytokine expression, hippocampal fatty acids, oxylipins and microbiota composition were also assessed. Chronic stress induced social avoidance, poor recognition memory, affected hippocampal long-term potentiation, changed the microbiota profile, brain cytokines, fatty acid and oxylipins composition of both Hdc-/- and Hdc+/+ mice. Dietary enrichment counteracted stress-induced deficits only in Hdc+/+ mice as histamine deficiency prevented almost all the diet-related beneficial effects. Interpretation: Our results reveal a previously unexplored and novel role for brain histamine as a mediator of many favorable effects of the enriched diet. These data present long-reaching perspectives in the field of nutritional neuropsychopharmacology.

Perturbation on gut microbiota impedes the onset of obesity in high fat diet-induced mice

High-calorie intake has become one of the most common causes of dietary obesity, which eventually develops into type 2 diabetes mellitus (T2DM). Microbiota, along with the length of the gastrointestinal tract, is related to metabolic disorders, but its shifts and following impact on metabolic disorders due to external perturbation are still unclear. To evaluate shifts of microbiota from the proximal to the distal intestine and their impact on metabolic disorders, we profiled jejunal and colonic microbiota with the perturbation using high salt (HS) and antibiotic-induced microbiota depletion (AIMD) in diet-induced obesity (DIO) mice and analyzed the association with parameters of both obesity and blood glucose. After ten weeks of feeding DIO mice with HS intake and AIMD, they failed to develop obesity. The DIO mice with HS intake had T2DM symptoms, whereas the AIMD DIO mice showed no significant difference in blood glucose parameters. We observed that the jejunal and colonic microbiota had shifted due to settled perturbation, and jejunal microbiota within a group were more dispersed than colonic microbiota. After further analyzing jejunal microbiota using quantified amplicon sequencing, we found that the absolute abundance of Colidextribacter (R = 0.695, p = 0.001) and Faecalibaculum (R = 0.631, p = 0.005) in the jejunum was positively correlated with the changes in BW and FBG levels. The predicted pathway of glucose and metabolism of other substances significantly changed between groups (p <0.05). We demonstrated that the onset of obesity and T2DM in DIO mice is impeded when the gut microbiota is perturbed; thus, this pathogenesis depends on the gut microbiota.

Gut-associated cGMP mediates colitis and dysbiosis in a mouse model of an activating mutation in GUCY2C

Activating mutations in receptor guanylyl cyclase C (GC-C), the target of gastrointestinal peptide hormones guanylin and uroguanylin, and bacterial heat-stable enterotoxins cause early-onset diarrhea and chronic inflammatory bowel disease (IBD). GC-C regulates ion and fluid secretion in the gut via cGMP production and activation of cGMP-dependent protein kinase II. We characterize a novel mouse model harboring an activating mutation in Gucy2c equivalent to that seen in an affected Norwegian family. Mutant mice demonstrated elevated intestinal cGMP levels and enhanced fecal water and sodium content. Basal and linaclotide-mediated small intestinal transit was higher in mutant mice, and they were more susceptible to DSS-induced colitis. Fecal microbiome and gene expression analyses of colonic tissue revealed dysbiosis, up-regulation of IFN-stimulated genes, and misregulation of genes associated with human IBD and animal models of colitis. This novel mouse model thus provides molecular insights into the multiple roles of intestinal epithelial cell cGMP, which culminate in dysbiosis and the induction of inflammation in the gut.

The role of the gut microbiota in the dietary niche expansion of fishing bats

Background

Due to its central role in animal nutrition, the gut microbiota is likely a relevant factor shaping dietary niche shifts. We analysed both the impact and contribution of the gut microbiota to the dietary niche expansion of the only four bat species that have incorporated fish into their primarily arthropodophage diet.

Results

We first compared the taxonomic and functional features of the gut microbiota of the four piscivorous bats to that of 11 strictly arthropodophagous species using 16S rRNA targeted amplicon sequencing. Second, we increased the resolution of our analyses for one of the piscivorous bat species, namely Myotis capaccinii, and analysed multiple populations combining targeted approaches with shotgun sequencing. To better understand the origin of gut microorganisms, we also analysed the gut microbiota of their fish prey (Gambusia holbrooki). Our analyses showed that piscivorous bats carry a characteristic gut microbiota that differs from that of their strict arthropodophagous counterparts, in which the most relevant bacteria have been directly acquired from their fish prey. This characteristic microbiota exhibits enrichment of genes involved in vitamin biosynthesis, as well as complex carbohydrate and lipid metabolism, likely providing their hosts with an enhanced capacity to metabolise the glycosphingolipids and long-chain fatty acids that are particularly abundant in fish.

Conclusions

Our results depict the gut microbiota as a relevant element in facilitating the dietary transition from arthropodophagy to piscivory.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-021-00137-w.

Metagenomic Investigation Uncovers Presence of Probiotic-Type Microbiome in Kalparasa® (Fresh Unfermented Coconut Inflorescence Sap)

The phloem sap tapped from unopened inflorescence (spadix) of coconut palm using a novel collecting device, “coco-sap chiller,” has been branded Kalparasa^® (henceforth as Kalparasa in the text) to distinguish its properties not found in sap harvested by traditional methods. To know its hitherto unidentified microbiome profile, we employed high-throughput sequencing to uncover the bacteriome and mycobiome in fresh and 12-h fermented samples. Fresh Kalparasa had a pH of 7.2, which dropped to 4.5 after 12 h, signifying fermentation of the sap. Diversity analysis indicated fresh Kalparasa having higher bacterial species than the fermented one. Contrary to this, fresh sap had lower fungal/yeast diversity than the fermented sample. Fresh Kalparasa had relatively higher abundance of probiotic-type Leuconostoc genus followed by equal proportions of Gluconobacter, Acetobacter, and Fructobacillus. The 12-h fermented Kalparasa showed a significant increase in Gluconobacter with a sharp decrease in Leuconostoc. Mycobiome data revealed fresh Kalparasa to be preponderant in Saccharomyces and Hanseniaspora genera of yeasts while the fermented sap had higher representation of Hanseniaspora and Cortinarius and lesser Saccharomyces. This suggested that the fermentation of Kalparasa was probably driven by symbiotic culture of bacteria and yeasts (SCOBY), particularly acetic acid bacteria and non-Saccharomyces yeasts. The bacteriome-function predictions highlighted the enrichment of glycerophospholipid, ABC transporters, purine, and pyrimidine metabolisms. Based on our findings, Kalparasa containing large population of Leuconostoc mesenteroides, Fructobacillus fructosus, Saccharomyces cerevisiae, and Hanseniaspora guilliermondii can be promoted as a healthy “unfermented” plant edible food containing live probiotic-type microbiome during its consumption.

Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome

Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bacterial 16S marker gene but have not reported the metabolic function of the gut microbiome, which may mediate biological effects on the host. Here, we used the PICRUSt2 bioinformatics tool to predict the functional profiles of the gut microbiome based on 16S sequencing in two child cohorts. Both Caesarean section and perinatal antibiotics markedly influenced the functional profiles of the gut microbiome at the age of 1 year. In machine learning analysis, bacterial fatty acid, phospholipid, and biotin biosynthesis were the most important pathways that differed according to delivery mode. Proteinogenic amino acid biosynthesis, carbohydrate degradation, pyrimidine deoxyribonucleotide and biotin biosynthesis were the most important pathways differing according to antibiotic exposure. Our study shows that both Caesarean section and perinatal antibiotics markedly influence the predicted metabolic profiles of the gut microbiome at the age of 1 year.

MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data

The 16S rRNA gene amplicon sequencing is a popular technique that provides accurate characterization of microbial taxonomic abundances but does not provide any functional information. Several tools are available to predict functional profiles based on 16S rRNA gene sequence data that use different genome databases and approaches. As variable regions of partially-sequenced 16S rRNA gene cannot resolve taxonomy accurately beyond the genus level, these tools may give inflated results. Here, we developed 'MicFunPred', which uses a novel approach to derive imputed metagenomes based on a set of core genes only, thereby minimizing false-positive predictions. On simulated datasets, MicFunPred showed the lowest False Positive Rate (FPR) with mean Spearman's correlation of 0.89 (SD = 0.03), while on seven real datasets the mean correlation was 0.75 (SD = 0.08). MicFunPred was found to be faster with low computational requirements and performed better or comparable when compared with other tools.

Probiotic Yeasts and Vibrio anguillarum Infection Modify the Microbiome of Zebrafish Larvae

The host microbiome plays an essential role in health and disease. Microbiome modification by pathogens or probiotics has been poorly explored especially in the case of probiotic yeasts. Next-generation sequencing currently provides the best tools for their characterization. Debaryomyces hansenii 97 (D. hansenii 97) and Yarrowia lipolytica 242 (Y. lipolytica 242) are yeasts that protect wildtype zebrafish (Danio rerio) larvae against a Vibrio anguillarum (V. anguillarum) infection, increasing their survival rate. We investigate the effect of these microorganisms on the microbiome and neutrophil response (inflammation) in zebrafish larvae line Tg(Bacmpx:GFP)ⁱ¹¹⁴. We postulated that preinoculation of larvae with yeasts would attenuate the intestinal neutrophil response and prevent modification of the larval microbiome induced by the pathogen. Microbiome study was performed by sequencing the V3-V4 region of the 16S rRNA gene and prediction of metabolic pathways by Piphillin in conventionally raised larvae. Survival and the neutrophil response were both evaluated in conventional and germ-free conditions. V. anguillarum infection resulted in higher neutrophil number in the intestinal area compared to non-infected larvae in both conditions. In germ-free conditions, infected larvae pre-inoculated with yeasts showed fewer neutrophil numbers than infected larvae. In both conditions, only D. hansenii 97 increased the survival of infected larvae. Beta diversity of the microbiota was modified by V. anguillarum and both yeasts, compared to non-inoculated larvae. At 3 days post-infection, V. anguillarum modified the relative abundance of 10 genera, and pre-inoculation with D. hansenii 97 and Y. lipolytica 242 prevented the modification of 5 and 6 of these genera, respectively. Both yeasts prevent the increase of Ensifer and Vogesella identified as negative predictors for larval survival (accounting for 40 and 27 of the variance, respectively). In addition, yeast pre-inoculation prevents changes in some metabolic pathways altered by V. anguillarum’s infection. These results suggest that both yeasts and V. anguillarum can shape the larval microbiota configuration in the early developmental stage of D. rerio. Moreover, modulation of key taxa or metabolic pathways of the larval microbiome by yeasts can be associated with the survival of infected larvae. This study contributes to the understanding of yeast–pathogen–microbiome interactions, although further studies are needed to elucidate the mechanisms involved.

General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways

General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.

Intestinal Microbiome in Preterm Infants Influenced by Enteral Iron Dosing

OBJECTIVES

The aim of the study was to compare the intestinal microbiome in very low birth weight (VLBW) infants who received different enteral iron supplementation (EIS) doses.

STUDY DESIGN

Longitudinal stool collection in 80 VLBW infants were conducted up to 2 months postnatally in a prospective study. The 16S rRNA regions V4 was used to calculate microbiome compositions and the Piphillin software was used for bacterial functional prediction. Linear mixed effect models and Wilcoxon rank-sum tests were performed to examine the relationships between initial EIS dosage and stool microbiome and bacterial functional potential.

RESULTS

There were 105 samples collected before and 237 collected after EIS started from infants with birth gestational age and weight of 28.1 ± 2.4 weeks and 1103 ± 210 g, respectively. The average postnatal age at start of EIS was 17.9 ± 6.9 days and the average initial EIS dose was 4.8 ± 1.1 mg · kg-1 · day-1. Infants who were started on ≥6 mg · kg-1 · day-1 had higher abundances of Proteus and Bifidobacterium and a lower alpha diversity than those started on lower doses (P < 0.05). Infants given higher EIS doses had higher bacterial predicted functional potentials for ferroptosis and epithelial invasion after 2 weeks post EIS.

CONCLUSIONS

Higher EIS dosage is linked to higher abundances of Proteus and Bifidobacterium, and a less diverse microbiome and higher predicted potential of bacterial epithelial invasion. These observational findings should be further studied in a randomized study to elucidate the optimal dosage of EIS in VLBW infants.

From the Andes to the desert: 16S rRNA metabarcoding characterization of aquatic bacterial communities in the Rimac river, the main source of water for Lima, Peru

The Rimac river is the main source of water for Lima, Peru's capital megacity. The river is constantly affected by different types of contamination including mine tailings in the Andes and urban sewage in the metropolitan area. In this work, we aim to produce the first characterization of aquatic bacterial communities in the Rimac river using a 16S rRNA metabarcoding approach which would be useful to identify bacterial diversity and potential understudied pathogens. We report a lower diversity in bacterial communities from the Lower Rimac (Metropolitan zone) in comparison to other sub-basins. Samples were generally grouped according to their geographical location. Bacterial classes Alphaproteobacteria, Bacteroidia, Campylobacteria, Fusobacteriia, and Gammaproteobacteria were the most frequent along the river. Arcobacter cryaerophilus (Campylobacteria) was the most frequent species in the Lower Rimac while Flavobacterium succinicans (Bacteroidia) and Hypnocyclicus (Fusobacteriia) were the most predominant in the Upper Rimac. Predicted metabolic functions in the microbiota include bacterial motility and quorum sensing. Additional metabolomic analyses showed the presence of some insecticides and herbicides in the Parac-Upper Rimac and Santa Eulalia-Parac sub-basins. The dominance in the Metropolitan area of Arcobacter cryaerophilus, an emergent pathogen associated with fecal contamination and antibiotic multiresistance, that is not usually reported in traditional microbiological quality assessments, highlights the necessity to apply next-generation sequencing tools to improve pathogen surveillance. We believe that our study will encourage the integration of omics sciences in Peru and its application on current environmental and public health issues.

Challenges and Perspective in Integrated Multi-Omics in Gut Microbiota Studies

The advent of omic technology has made it possible to identify viable but unculturable micro-organisms in the gut. Therefore, application of multi-omic technologies in gut microbiome studies has become invaluable for unveiling a comprehensive interaction between these commensals in health and disease. Meanwhile, despite the successful identification of many microbial and host-microbial cometabolites that have been reported so far, it remains difficult to clearly identify the origin and function of some proteins and metabolites that are detected in gut samples. However, the application of single omic techniques for studying the gut microbiome comes with its own challenges which may be overcome if a number of different omics techniques are combined. In this review, we discuss our current knowledge about multi-omic techniques, their challenges and future perspective in this field of gut microbiome studies.

Metabolic Phenotypes as Potential Biomarkers for Linking Gut Microbiome With Inflammatory Bowel Diseases

The gut microbiome is of utmost importance to human health. While a healthy microbiome can be represented by a variety of structures, its functional capacity appears to be more important. Gene content of the community can be assessed by “shotgun” metagenomics, but this approach is still too expensive. High-throughput amplicon-based surveys are a method of choice for large-scale surveys of links between microbiome, diseases, and diet, but the algorithms for predicting functional composition need to be improved to achieve good precision. Here we show how feature engineering based on microbial phenotypes, an advanced method for functional prediction from 16S rRNA sequencing data, improves identification of alterations of the gut microbiome linked to the disease. We processed a large collection of published gut microbial datasets of inflammatory bowel disease (IBD) patients to derive their community phenotype indices (CPI)—high-precision semiquantitative profiles aggregating metabolic potential of the community members based on genome-wide metabolic reconstructions. The list of selected metabolic functions included metabolism of short-chain fatty acids, vitamins, and carbohydrates. The machine-learning approach based on microbial phenotypes allows us to distinguish the microbiome profiles of healthy controls from patients with Crohn's disease and from ones with ulcerative colitis. The classifiers were comparable in quality to conventional taxonomy-based classifiers but provided new findings giving insights into possible mechanisms of pathogenesis. Feature-wise partial dependence plot (PDP) analysis of contribution to the classification result revealed a diversity of patterns. These observations suggest a constructive basis for defining functional homeostasis of the healthy human gut microbiome. The developed features are promising interpretable candidate biomarkers for assessing microbiome contribution to disease risk for the purposes of personalized medicine and clinical trials.

Assessing the Relationship Between Nitrate-Reducing Capacity of the Oral Microbiome and Systemic Outcomes

The significance of the oral microbiome in the generation of the nitric oxide (NO) via the enterosalivary nitrate-nitrite-nitric oxide pathway is increasingly recognized, directly linking the oral microbiome to cardiometabolic outcomes influenced by NO. The objective of this chapter is to outline a strategy of identifying pathway-specific bacterial taxa or predicted genes of interest from 16S rRNA data, specifically in the enterosalivary pathway of nitrate reduction, and analyzing their relationship with cardiometabolic outcomes using multivariable regression models.

Differential effect of silver nanoparticles on the microbiome of adult and developing planaria

Silver nanoparticles (AgNPs) are widely incorporated in household, consumer and medical products. Their unintentional release via wastewaters raises concerns on their environmental impact, particularly for aquatic organisms and their associated bacterial communities. It is known that the microbiome plays an important role in its host's health and physiology, e.g. by producing essential nutrients and providing protection against pathogens. A thorough understanding of the effects of AgNPs on bacterial communities and on their interactions with the host is crucial to fully assess AgNP toxicity on aquatic organisms. Our results indicate that the microbiome of the invertebrate Schmidtea mediterranea, a freshwater planarian, is affected by AgNP exposure at the tested 10 μg/ml concentration. Using targeted amplification of the bacterial 16S rRNA gene V3-V4 region, two independent experiments on the microbiomes of adult worms revealed a consistent decrease in Betaproteobacteriales after AgNP exposure, mainly attributed to a decrease in Curvibacter and Undibacterium. Although developing tissues and organisms are known to be more sensitive to toxic compounds, three independent experiments in regenerating worms showed a less pronounced effect of AgNP exposure on the microbiome, possibly because underlying bacterial community changes during development mask the AgNP induced effect. The presence of a polyvinyl-pyrrolidone (PVP) coating did not significantly alter the outcome of the experiments compared to those with uncoated particles. The observed variation between the different experiments underlines the highly variable nature of microbiomes and emphasises the need to repeat microbiome experiments, within and between physiological states of the animal.

Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods

Microbiomes are integral components of diverse ecosystems, and increasingly recognized for their roles in the health of humans, animals, plants, and other hosts. Given their complexity (both in composition and function), the effective study of microbiomes (microbiomics) relies on the development, optimization, and validation of computational methods for analyzing microbial datasets, such as from marker-gene (e.g., 16S rRNA gene) and metagenome data. This review describes best practices for benchmarking and implementing computational methods (and software) for studying microbiomes, with particular focus on unique characteristics of microbiomes and microbiomics data that should be taken into account when designing and testing microbiomics methods.

Microbial function and genital inflammation in young South African women at high risk of HIV infection

BACKGROUND

Female genital tract (FGT) inflammation is an important risk factor for HIV acquisition. The FGT microbiome is closely associated with inflammatory profile; however, the relative importance of microbial activities has not been established. Since proteins are key elements representing actual microbial functions, this study utilized metaproteomics to evaluate the relationship between FGT microbial function and inflammation in 113 young and adolescent South African women at high risk of HIV infection. Women were grouped as having low, medium, or high FGT inflammation by K-means clustering according to pro-inflammatory cytokine concentrations.

RESULTS

A total of 3186 microbial and human proteins were identified in lateral vaginal wall swabs using liquid chromatography-tandem mass spectrometry, while 94 microbial taxa were included in the taxonomic analysis. Both metaproteomics and 16S rRNA gene sequencing analyses showed increased non-optimal bacteria and decreased lactobacilli in women with FGT inflammatory profiles. However, differences in the predicted relative abundance of most bacteria were observed between 16S rRNA gene sequencing and metaproteomics analyses. Bacterial protein functional annotations (gene ontology) predicted inflammatory cytokine profiles more accurately than bacterial relative abundance determined by 16S rRNA gene sequence analysis, as well as functional predictions based on 16S rRNA gene sequence data (p < 0.0001). The majority of microbial biological processes were underrepresented in women with high inflammation compared to those with low inflammation, including a Lactobacillus-associated signature of reduced cell wall organization and peptidoglycan biosynthesis. This signature remained associated with high FGT inflammation in a subset of 74 women 9 weeks later, was upheld after adjusting for Lactobacillus relative abundance, and was associated with in vitro inflammatory cytokine responses to Lactobacillus isolates from the same women. Reduced cell wall organization and peptidoglycan biosynthesis were also associated with high FGT inflammation in an independent sample of ten women.

CONCLUSIONS

Both the presence of specific microbial taxa in the FGT and their properties and activities are critical determinants of FGT inflammation. Our findings support those of previous studies suggesting that peptidoglycan is directly immunosuppressive, and identify a possible avenue for biotherapeutic development to reduce inflammation in the FGT. To facilitate further investigations of microbial activities, we have developed the FGT-DB application that is available at http://fgtdb.org/ . Video Abstract.

PUMAA: A Platform for Accessible Microbiome Analysis in the Undergraduate Classroom

Improvements in high-throughput sequencing makes targeted amplicon analysis an ideal method for the study of human and environmental microbiomes by undergraduates. Multiple bioinformatics programs are available to process and interpret raw microbial diversity datasets, and the choice of programs to use in curricula is largely determined by student learning goals. Many of the most commonly used microbiome bioinformatics platforms offer end-to-end data processing and data analysis using a command line interface (CLI), but the downside for novice microbiome researchers is the steep learning curve often required. Alternatively, some sequencing providers include processing of raw data and taxonomy assignments as part of their pipelines. This, when coupled with available web-based or graphical user interface (GUI) analysis and visualization tools, eliminates the need for students or instructors to have extensive CLI experience. However, lack of universal data formats can make integration of these tools challenging. For example, tools for upstream and downstream analyses frequently use multiple different data formats which then require writing custom scripts or hours of manual work to make the files compatible. Here, we describe a microbial ecology bioinformatics curriculum that focuses on data analysis, visualization, and statistical reasoning by taking advantage of existing web-based and GUI tools. We created the Program for Unifying Microbiome Analysis Applications (PUMAA), which solves the problem of inconsistent files by formatting the output files from several raw data processing programs to seamlessly transition to a suite of GUI programs for analysis and visualization of microbiome taxonomic and inferred functional profiles. Additionally, we created a series of tutorials to accompany each of the microbiome analysis curricular modules. From pre- and post-course surveys, students in this curriculum self-reported conceptual and confidence gains in bioinformatics and data analysis skills. Students also demonstrated gains in biologically relevant statistical reasoning based on rubric-guided evaluations of open-ended survey questions and the Statistical Reasoning in Biology Concept Inventory. The PUMAA program and associated analysis tutorials enable students and researchers with no computational experience to effectively analyze real microbiome datasets to investigate real-world research questions.