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Abstract Background Understanding the cause vs consequence relationship of gut inflammation and microbial dysbiosis in inflammatory bowel diseases (IBD) requires a reproducible mouse model of human-microbiota-driven experimental colitis. Results Our study demonstrated that human fecal microbiota transplant (FMT) transfer efficiency is an underappreciated source of experimental variability in human microbiota-associated (HMA) mice. Pooled human IBD patient fecal microbiota engrafted germ-free (GF) mice with low amplicon sequence variant (ASV)-level transfer efficiency, resulting in high recipient-to-recipient variation of microbiota composition and colitis severity in HMA Il-10 −/− mice. In contrast, mouse-to-mouse transfer of mouse-adapted human IBD patient microbiota transferred with high efficiency and low compositional variability resulting in highly consistent and reproducible colitis phenotypes in recipient Il-10 −/− mice. Engraftment of human-to-mouse FMT stochastically varied with individual transplantation events more than mouse-adapted FMT. Human-to-mouse FMT caused a population bottleneck with reassembly of microbiota composition that was host inflammatory environment specific. Mouse-adaptation in the inflamed Il-10 −/− host reassembled a more aggressive microbiota that induced more severe colitis in serial transplant to Il-10 −/− mice than the distinct microbiota reassembled in non-inflamed WT hosts. Conclusions Our findings support a model of IBD pathogenesis in which host inflammation promotes aggressive resident bacteria, which further drives a feed-forward process of dysbiosis exacerbated by gut inflammation. This model implies that effective management of IBD requires treating both the dysregulated host immune response and aggressive inflammation-driven microbiota. We propose that our mouse-adapted human microbiota model is an optimized, reproducible, and rigorous system to study human microbiome-driven disease phenotypes, which may be generalized to mouse models of other human microbiota-modulated diseases, including metabolic syndrome/obesity, diabetes, autoimmune diseases, and cancer. Video Abstract

Abstract Background Normalization, as a pre-processing step, can significantly affect the resolution of machine learning analysis for microbiome studies. There are countless options for normalization scheme selection. In this study, we examined compositionally aware algorithms including the additive log ratio (alr), the centered log ratio (clr), and a recent evolution of the isometric log ratio (ilr) in the form of balance trees made with the PhILR R package. We also looked at compositionally naïve transformations such as raw counts tables and several transformations that are based on relative abundance, such as proportions, the Hellinger transformation, and a transformation based on the logarithm of proportions (which we call “lognorm”). Results In our evaluation, we used 65 metadata variables culled from four publicly available datasets at the amplicon sequence variant (ASV) level with a random forest machine learning algorithm. We found that different common pre-processing steps in the creation of the balance trees made very little difference in overall performance. Overall, we found that the compositionally aware data transformations such as alr, clr, and ilr (PhILR) performed generally slightly worse or only as well as compositionally naïve transformations. However, relative abundance-based transformations outperformed most other transformations by a small but reliably statistically significant margin. Conclusions Our results suggest that minimizing the complexity of transformations while correcting for read depth may be a generally preferable strategy in preparing data for machine learning compared to more sophisticated, but more complex, transformations that attempt to better correct for compositionality. Video Abstract

Undernutrition in children commonly disrupts the structure and function of the small intestinal microbial community, leading to enteropathies, compromised metabolic health, and impaired growth and development. The mechanisms by which diet and microbes mediate the balance between commensal and pathogenic intestinal flora remain elusive. In a murine model of undernutrition, we investigated the direct interactions Giardia lamblia, a prevalent small intestinal pathogen, on indigenous microbiota and specifically on Lactobacillus strains known for their mucosal and growth homeostatic properties. Our research reveals that Giardia colonization shifts the balance of lactic acid bacteria, causing a relative decrease in Lactobacillus spp. and an increase in Bifidobacterium spp. This alteration corresponds with a decrease in multiple indicators of mucosal and nutritional homeostasis. Additionally, protein-deficient conditions coupled with Giardia infection exacerbate the rise of primary bile acids and susceptibility to bile acid-induced intestinal barrier damage. In epithelial cell monolayers, Lactobacillus spp. mitigated bile acid-induced permeability, showing strain-dependent protective effects. In vivo, L. plantarum, either alone or within a Lactobacillus spp consortium, facilitated growth in protein-deficient mice, an effect attenuated by Giardia, despite not inhibiting Lactobacillus colonization. These results highlight Giardia’s potential role as a disruptor of probiotic functional activity, underscoring the imperative for further research into the complex interactions between parasites and bacteria under conditions of nutritional deficiency.

Abstract Background Inflammatory bowel disease (IBD) patients experience recurrent episodes of intestinal inflammation and often follow an unpredictable disease course. Mucosal colonization with adherent-invasive Escherichia coli (AIEC) are believed to perpetuate intestinal inflammation. However, it remains unclear if the 24-year-old AIEC in vitro definition fully predicts mucosal colonization in vivo. To fill this gap, we have developed a novel molecular barcoding approach to distinguish strain variants in the gut and have integrated this approach to explore mucosal colonization of distinct patient-derived E. coli isolates in gnotobiotic mouse models of colitis. Results Germ-free inflammation-susceptible interleukin-10-deficient (Il10 −/− ) and inflammation-resistant WT mice were colonized with a consortium of AIEC and non-AIEC strains, then given a murine fecal transplant to provide niche competition. E. coli strains isolated from human intestinal tissue were each marked with a unique molecular barcode that permits identification and quantification by barcode-targeted sequencing. 16S rRNA sequencing was used to evaluate the microbiome response to E. coli colonization. Our data reveal that specific AIEC and non-AIEC strains reproducibly colonize the intestinal mucosa of WT and Il10 −/− mice. These E. coli expand in Il10 −/− mice during inflammation and induce compositional dysbiosis to the microbiome in an inflammation-dependent manner. In turn, specific microbes co-evolve in inflamed mice, potentially diversifying E. coli colonization patterns. We observed no selectivity in E. coli colonization patterns in the fecal contents, indicating minimal selective pressure in this niche from host-microbe and interbacterial interactions. Because select AIEC and non-AIEC strains colonize the mucosa, this suggests the in vitro AIEC definition may not fully predict in vivo colonization potential. Further comparison of seven E. coli genomes pinpointed unique genomic features contained only in highly colonizing strains (two AIEC and two non-AIEC). Those colonization-associated features may convey metabolic advantages (e.g., iron acquisition and carbohydrate consumption) to promote efficient mucosal colonization. Conclusions Our findings establish the in vivo mucosal colonizer, not necessarily AIEC, as a principal dysbiosis driver through crosstalk with host and associated microbes. Furthermore, we highlight the utility of high-throughput screens to decode the in vivo colonization dynamics of patient-derived bacteria in murine models. Video Abstract

Abstract Giardia lamblia (Giardia) is among the most common intestinal pathogens in children in low- and middle-income countries (LMICs). Although Giardia associates with early-life linear growth restriction, mechanistic explanations for Giardia-associated growth impairments remain elusive. Unlike other intestinal pathogens associated with constrained linear growth that cause intestinal or systemic inflammation or both, Giardia seldom associates with chronic inflammation in these children. Here we leverage the MAL-ED longitudinal birth cohort and a model of Giardia mono-association in gnotobiotic and immunodeficient mice to propose an alternative pathogenesis of this parasite. In children, Giardia results in linear growth deficits and gut permeability that are dose-dependent and independent of intestinal markers of inflammation. The estimates of these findings vary between children in different MAL-ED sites. In a representative site, where Giardia associates with growth restriction, infected children demonstrate broad amino acid deficiencies, and overproduction of specific phenolic acids, byproducts of intestinal bacterial amino acid metabolism. Gnotobiotic mice require specific nutritional and environmental conditions to recapitulate these findings, and immunodeficient mice confirm a pathway independent of chronic T/B cell inflammation. Taken together, we propose a new paradigm that Giardia-mediated growth faltering is contingent upon a convergence of this intestinal protozoa with nutritional and intestinal bacterial factors.

Obesity promotes triple-negative breast cancer (TNBC), and effective interventions are urgently needed to break the obesity-TNBC link. Epidemiologic studies indicate that bariatric surgery reduces TNBC risk, while evidence is limited or conflicted for weight loss via low-fat diet (LFD) or calorie restriction (CR). Using a murine model of obesity-driven TNBC, we compared the antitumor effects of vertical sleeve gastrectomy (VSG) with LFD, chronic CR, and intermittent CR. Each intervention generated weight and fat loss and suppressed tumor growth relative to obese mice (greatest suppression with CR). VSG and CR regimens exerted both similar and unique effects, as assessed using multiomics approaches, in reversing obesity-associated transcript, epigenetics, secretome, and microbiota changes and restoring antitumor immunity. Thus, in a murine model of TNBC, bariatric surgery and CR each reverse obesity-driven tumor growth via shared and distinct antitumor mechanisms, and CR is superior to VSG in reversing obesity’s procancer effects.

Here, the authors present ConQuR, a conditional quantile regression method that removes microbiome batch effects through non-parametric modeling of complex microbial read counts, while preserving the signals of interest.

ABSTRACT 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 (

Low-calorie sweetener (LCS) consumption in children has increased dramatically due to its widespread presence in the food environment and efforts to mitigate obesity through sugar replacement. However, mechanistic studies on the long-term impact of early-life LCS consumption on cognitive function and physiological processes are lacking. Here, we developed a rodent model to evaluate the effects of daily LCS consumption (acesulfame potassium, saccharin, or stevia) during adolescence on adult metabolic, behavioral, gut microbiome, and brain transcriptomic outcomes. Results reveal that habitual early-life LCS consumption impacts normal postoral glucose handling and impairs hippocampal-dependent memory in the absence of weight gain. Furthermore, adolescent LCS consumption yielded long-term reductions in lingual sweet taste receptor expression and brought about alterations in sugar-motivated appetitive and consummatory responses. While early-life LCS consumption did not produce robust changes in the gut microbiome, brain region–specific RNA-Seq analyses reveal LCS-induced changes in collagen- and synaptic signaling–related gene pathways in the hippocampus and nucleus accumbens, respectively, in a sex-dependent manner. Collectively, these results reveal that habitual early-life LCS consumption has long-lasting implications for glucoregulation, sugar-motivated behavior, and hippocampal-dependent memory in rats, which may be based in part on changes in nutrient transporter, sweet taste receptor, and central gene pathway expression.

The composition of the gut microbiota in patients with anorexia nervosa (AN), and the ability of this microbial community to influence the host, remains uncertain. To achieve a broader understanding of the role of the intestinal microbiota in patients with AN, we collected fecal samples before and following clinical treatment at two geographically distinct eating disorder units (Center of Excellence for Eating Disorders [UNC-CH] and ACUTE Center for Eating Disorders [Denver Health]). Gut microbiotas were characterized in patients with AN, before and after inpatient treatment, and in non-eating disorder (non-ED) controls using shotgun metagenomic sequencing. The impact of inpatient treatment on the AN gut microbiota was remarkably consistent between eating disorder units. Although weight in patients with AN showed improvements, AN microbiotas post-treatment remained distinct from non-ED controls. Additionally, AN gut microbiotas prior to treatment exhibited more fermentation pathways and a lower ability to degrade carbohydrates than non-ED controls. As the intestinal microbiota can influence nutrient metabolism, our data highlight the complex microbial communities in patients with AN as an element needing further attention post inpatient treatment. Additionally, this study defines the effects of renourishment on the AN gut microbiota and serves as a platform to develop precision nutrition approaches to potentially mitigate impediments to recovery.

Mycophenolate mofetil (MMF) is an important immunosuppressant prodrug prescribed to prevent organ transplant rejection and to treat autoimmune diseases. MMF usage, however, is limited by severe gastrointestinal toxicity that is observed in approximately 45% of MMF recipients. The active form of the drug, mycophenolic acid (MPA), undergoes extensive enterohepatic recirculation by bacterial β-glucuronidase (GUS) enzymes, which reactivate MPA from mycophenolate glucuronide (MPAG) within the gastrointestinal tract. GUS enzymes demonstrate distinct substrate preferences based on their structural features, and gut microbial GUS enzymes that reactivate MPA have not been identified. Here, we compare the fecal microbiomes of transplant recipients receiving MMF to healthy individuals using shotgun metagenomic sequencing. We find that neither microbial composition nor the presence of specific structural classes of GUS genes are sufficient to explain the differences in MPA reactivation measured between fecal samples from the two cohorts. We next employed a GUS-specific activity-based chemical probe and targeted metaproteomics to identify and quantify the GUS proteins present in the human fecal samples. The identification of specific GUS enzymes was improved by using the metagenomics data collected from the fecal samples. We found that the presence of GUS enzymes that bind the flavin mononucleotide (FMN) is significantly correlated with efficient MPA reactivation. Furthermore, structural analysis identified motifs unique to these FMN-binding GUS enzymes that provide molecular support for their ability to process this drug glucuronide. These results indicate that FMN-binding GUS enzymes may be responsible for reactivation of MPA and could be a driving force behind MPA-induced GI toxicity.

Abstract Background Identification of bacterial taxa associated with diseases, exposures, and other variables of interest offers a more comprehensive understanding of the role of microbes in many conditions. However, despite considerable research in statistical methods for association testing with microbiome data, approaches that are generally applicable remain elusive. Classical tests often do not accommodate the realities of microbiome data, leading to power loss. Approaches tailored for microbiome data depend highly upon the normalization strategies used to handle differential read depth and other data characteristics, and they often have unacceptably high false positive rates, generally due to unsatisfied distributional assumptions. On the other hand, many non-parametric tests suffer from loss of power and may also present difficulties in adjusting for potential covariates. Most extant approaches also fail in the presence of heterogeneous effects. The field needs new non-parametric approaches that are tailored to microbiome data, robust to distributional assumptions, and powerful under heterogeneous effects, while permitting adjustment for covariates. Methods As an alternative to existing approaches, we propose a zero-inflated quantile approach (ZINQ), which uses a two-part quantile regression model to accommodate the zero inflation in microbiome data. For a given taxon, ZINQ consists of a valid test in logistic regression to model the zero counts, followed by a series of quantile rank-score based tests on multiple quantiles of the non-zero part with adjustment for the zero inflation. As a regression and quantile-based approach, the method is non-parametric and robust to irregular distributions, while providing an allowance for covariate adjustment. Since no distributional assumptions are made, ZINQ can be applied to data that has been processed under any normalization strategy. Results Thorough simulations based on real data across a range of scenarios and application to real data sets show that ZINQ often has equivalent or higher power compared to existing tests even as it offers better control of false positives. Conclusions We present ZINQ, a quantile-based association test between microbiota and dichotomous or quantitative clinical variables, providing a powerful and robust alternative for the current microbiome differential abundance analysis. Video Abstract

Metabolic and bariatric surgery (MBS) is the most effective long-term treatment for Class III obesity. Reduced dietary intake is considered a behavioral driver of post-surgical weight loss, but limited data have examined this association. Therefore, this study examined prospective, longitudinal relationships between dietary intake and weight loss over 24 months following Roux-en-Y Gastric Bypass and Sleeve Gastrectomy. Relationships between weight loss and dietary intake were examined using a validated 24-h dietary recall method. Associations between total energy/macronutrient intake and weight loss outcomes were assessed at 12-, 18-, and 24-months following MBS, defining patients as “responders” and “suboptimal responders”. Consistent with previous literature, 12-month responders and suboptimal responders showed significant associations between weight loss and energy (p = 0.018), protein (p = 0.002), and total fat intake (p = 0.005). However, this study also revealed that many of these associations are no longer significant 24 months post-MBS (p > 0.05), despite consistent weight loss trends. This study suggests a short-term signal between these dietary factors and weight loss outcomes 12 months post-MBS; however, this signal does not persist beyond 12 months. These results are essential for interpreting and designing clinical studies measuring long-term post-surgical weight loss outcomes.

Abstract The gut microbiota plays an important role in human health and disease. Stool, rectal swab and rectal mucosal tissue samples have been used in individual studies to survey the microbial community but the consequences of using these different sample types are not completely understood. In this study, we report differences in stool, rectal swab and rectal mucosal tissue microbial communities with shotgun metagenome sequencing of 1397 stool, swab and mucosal tissue samples from 240 participants. The taxonomic composition of stool and swab samples was distinct, but less different to each other than mucosal tissue samples. Functional profile differences between stool and swab samples are smaller, but mucosal tissue samples remained distinct from the other two types. When the taxonomic and functional profiles were used for inference in association with host phenotypes of age, sex, body mass index (BMI), antibiotics or non-steroidal anti-inflammatory drugs (NSAIDs) use, hypothesis testing using either stool or rectal swab gave broadly significantly correlated results, but inference performed on mucosal tissue samples gave results that were generally less consistent with either stool or swab. Our study represents an important resource for determination of how inference can change for taxa and pathways depending on the choice of where to sample within the human gut.

ABSTRACT Recent rapid and large-scale urbanization has had a profound impact on human lifestyles and is associated with an increased risk of many diseases. Recent studies have revealed large differences in the human gut microbiota across populations in countries at different stages of urbanization. However, few studies have analyzed the impact of ongoing urbanization within the same geographic region. In this study, we sampled 214 participants in communities of different urbanization levels within two provinces of China and reconstructed draft prokaryotic genomes with metagenome sequences. The genomes were clustered into 447 species-level operational taxonomic units (OTUs), among which 196 did not have genomes in public reference databases according to the GTDB-Tk pipeline. The novel OTUs comprised 19.1% abundance in rural participants and 16.0% in urban participants, increasing the proportion of classified reads from 47.6% to 65.3% across all samples. Among the unknown OTUs, 26 OTUs present in rural samples were absent in urban participants, while 70 unknown OTUs were more abundant in rural than urban participants, suggesting potential loss and growth suppression of novel human symbionts during urbanization. Moreover, there were a higher number of genes, especially transporters, identified in genomes assembled from urban samples. This change in gene functionality indicates that urbanization not only altered the community structure of the human gut microbiota but also impacted its functional capacity. Taken together, these data show a dramatic change in the microbiota with urbanization and suggest the importance of cataloging microbial diversity from rural populations while these communities still exist. IMPORTANCE Previous studies have reported the differences in human gut microbiota across populations of different urbanization levels, but most of the studies focused on populations across different geographic regions. In this study, we analyzed the impact of ongoing urbanization in neighborhoods within the same geographic region. By assembling shotgun metagenome sequences, we reconstructed prokaryotic genomes from human gut microbiota and found that the novel bacterial OTUs were less abundant and less prevalent in urban participants than in rural participants, indicating potential loss and suppression of novel human symbionts during urbanization. Genes, including transporters and antibiotic resistance genes, were enriched in genomes of urban origins, suggesting change in functional potential of the microbiota. These findings suggest the significant influence of urbanization on human gut microbiota and the necessity of exploring the microbial diversity of rural populations.

ABSTRACT Previous studies have investigated the associations between the vaginal microbiome and preterm birth, with the aim of determining whether differences in community patterns meaningfully alter risk and could therefore be the target of intervention. We report on vaginal microbial analysis of a nested case-control subset of the Pregnancy, Infection, and Nutrition (PIN) Study, including 464 White women (375 term birth and 89 spontaneous preterm birth, sPTB) and 360 Black women (276 term birth and 84 sPTB). We found that the microbiome of Black women has higher alpha-diversity, higher abundance of Lactobacillus iners, and lower abundance of Lactobacillus crispatus. However, among women who douche, there were no significant differences in microbiome by race. The sPTB-associated microbiome exhibited a lower abundance of L. crispatus, while alpha diversity and L. iners were not significantly associated with sPTB. For each order of magnitude increase in the normalized relative abundance of L. crispatus, multivariable adjusted odds of sPTB decreased by approximately 20% (odds ratio, 0.81; 95% confidence interval, 0.70, 0.94). When we considered the impact of douching, associations between the microbiome and sPTB were limited to women who do not douche. We also observed strong intercorrelations between a range of maternal factors, including poverty, education, marital status, age, douching, and race, with microbiome effect sizes in the range of 1.8 to 5.2% in univariate models. Therefore, race may simply be a proxy for other socially driven factors that differentiate microbiome community structures. Future work will continue to refine reliable microbial biomarkers for preterm birth across diverse cohorts. IMPORTANCE Approximately 10% of all pregnancies in the United States end in preterm birth, and over 14% of pregnancies end in preterm birth among Black women. Knowledge on the associations between vaginal microbiome and preterm birth is important for understanding the potential cause and assessing risk of preterm birth. Our study is one of the largest studies performed to date to investigate the associations between vaginal microbiome and spontaneous preterm birth (sPTB), with stratified design for Black and White women. We found that the vaginal microbiome was different between Black and White women. The vaginal microbiome was associated with sPTB, and a lower abundance of L. crispatus increased the risk of sPTB independent of racial differences in microbial community structures. Furthermore, we also found that vaginal douching obscured the associations between vaginal microbiome, race, and preterm birth, suggesting that vaginal douching is an important factor to consider in future studies.

BACKGROUND Gut decontamination (GD) can decrease the incidence and severity of acute graft-versus-host disease (aGVHD) in murine models of allogeneic hematopoietic cell transplantation (HCT). In this pilot study, we examined the impact of GD on gut microbiome composition and the incidence of aGVHD in HCT patients.METHODS We randomized 20 patients undergoing allogeneic HCT to receive (GD) or not receive (no-GD) oral vancomycin-polymyxin B from day –5 through neutrophil engraftment. We evaluated shotgun metagenomic sequencing of serial stool samples to compare the composition and diversity of the gut microbiome between study arms. We assessed clinical outcomes in the 2 arms and performed strain-specific analyses of pathogens that caused bloodstream infections (BSI).RESULTS The 2 arms did not differ in the predefined primary outcome of Shannon diversity of the gut microbiome at 2 weeks post-HCT (genus, P = 0.8; species, P = 0.44) or aGVHD incidence (P = 0.58). Immune reconstitution of T cell and B cell subsets was similar between groups. Five patients in the no-GD arm had 8 BSI episodes versus 1 episode in the GD arm (P = 0.09). The BSI-causing pathogens were traceable to the gut in 7 of 8 BSI episodes in the no-GD arm, including Staphylococcus species.CONCLUSION While GD did not differentially affect Shannon diversity or clinical outcomes, our findings suggest that GD may protect against gut-derived BSI in HCT patients by decreasing the prevalence or abundance of gut pathogens.TRIAL REGISTRATION ClinicalTrials.gov NCT02641236.FUNDING NIH, Damon Runyon Cancer Research Foundation, V Foundation, Sloan Foundation, Emerson Collective, and Stanford Maternal & Child Health Research Institute.

Abstract Background Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition. In this study, we evaluated the performance of three commonly used metagenome prediction tools (PICRUSt, PICRUSt2, and Tax4Fun) by comparing the significance of the differential abundance of predicted functional gene profiles to those from shotgun metagenome sequencing across different environments. Results We selected 7 datasets of human, non-human animal, and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between predicted gene compositions and gene relative abundance measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the abundance of genes were permuted across samples. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of metagenome prediction tools. As an alternative, we compared the performance of genes predicted with PICRUSt, PICRUSt2, and Tax4Fun to sequenced metagenome genes in inference models associated with metadata within each dataset. With this approach, we found reasonable performance for human datasets, with the metagenome prediction tools performing better for inference on genes related to “housekeeping” functions. However, their performance degraded sharply outside of human datasets when used for inference. Conclusion We conclude that the utility of PICRUSt, PICRUSt2, and Tax4Fun for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted. Video abstract.

Iron deficiency, a common comorbidity of gastrointestinal inflammatory disorders such as inflammatory bowel diseases (IBD), is often treated with oral iron supplementation. However, the safety of oral iron supplementation remains controversial because of its association with exacerbated disease activity in a subset of IBD patients. Because iron modulates bacterial growth and function, one possible mechanism by which iron may exacerbate inflammation in susceptible hosts is by modulating the intestinal microbiota. We, therefore, investigated the impact of dietary iron on the intestinal microbiota, utilizing the conventionalization of germ-free mice as a model of a microbial community in compositional flux to recapitulate the instability of the IBD-associated intestinal microbiota. Our findings demonstrate that altering intestinal iron availability during community assembly modulated the microbiota in non-inflamed wild type (WT) and colitis-susceptible interleukin-10-deficient (Il10−/-) mice. Depletion of luminal iron availability promoted luminal compositional changes associated with dysbiotic states irrespective of host genotype, including an expansion of Enterobacteriaceae such as Escherichia coli. Mechanistic in vitro growth competitions confirmed that high-affinity iron acquisition systems in E. coli enhance its abundance over other bacteria in iron-restricted conditions, thereby enabling pathobiont iron scavenging during dietary iron restriction. In contrast, distinct luminal community assembly was observed with dietary iron supplementation in WT versus Il10−/- mice, suggesting that the effects of increased iron on the microbiota differ with host inflammation status. Taken together, shifts in dietary iron intake during community assembly modulate the ecological structure of the intestinal microbiota and is dependent on host genotype and inflammation status.

ABSTRACT 16S rRNA gene sequencing is a common and cost-effective technique for characterization of microbial communities. Recent bioinformatics methods enable high-resolution detection of sequence variants of only one nucleotide difference. In this study, we utilized a very fast HashMap-based approach to detect sequence variants in six publicly available 16S rRNA gene data sets. We then use the normal distribution combined with locally estimated scatterplot smoothing (LOESS) regression to estimate background error rates as a function of sequencing depth for individual clusters of sequences. This method is computationally efficient and produces inference that yields sets of variants that are conservative and well supported by reference databases. We argue that this approach to inference is fast, simple, and scalable to large data sets and provides a high-resolution set of sequence variants which are less likely to be the result of sequencing error. IMPORTANCE Recent bioinformatics development has enabled the detection of sequence variants with a high resolution of only one single-nucleotide difference in 16S rRNA gene sequence data. Despite this progress, there are several limitations that can be associated with variant calling pipelines, such as producing a large number of low-abundance sequence variants which need to be filtered out with arbitrary thresholds in downstream analyses or having a slow runtime. In this report, we introduce a fast and scalable algorithm which infers sequence variants based on the estimation of a normally distributed background error as a function of sequencing depth. Our pipeline has attractive performance characteristics, can be used independently or in parallel with other variant callers, and provides explicit P values for each variant evaluating the hypothesis that a variant is caused by sequencing error.

Anorexia nervosa (AN) is a psychiatric disorder that presents with profound weight dysregulation, metabolic disturbances, and an abnormal composition of gut microbial communities. As the intestinal microbiota can influence host metabolism, the impact of enteric microbial communities from patients with AN on host weight and adiposity was investigated. Germ-free (GF) mice were colonized with fecal microbiotas from either patients with AN (n = 4) prior to inpatient treatment (AN T1, n = 50 recipient mice), the same 4 patients following clinical renourishment (AN T2, n = 53 recipient mice), or age- and sex-matched non-AN controls (n = 4 human donors; non-AN, n = 50 recipient mice). Biological and fecal microbiota data were analyzed with linear mixed-effects models. Body weight did not differ significantly between AN recipient mice (T1 and T2) and non-AN recipient mice following 4 weeks of colonization. Enteric microbiotas from recipient mice colonized with AN T1 and AN T2 fecal microbiotas were more similar to each other compared with enteric microbiotas from non-AN recipient mice. Specific bacterial families in the Actinobacteria, Bacteroidetes, and Firmicutes phyla were significantly associated with body weight, fat mass, and cecum weight irrespective of the donor group. These data suggest that body weight, fat mass, and cecum weight of colonized GF mice are associated with human fecal microbes and independent of donor AN status, although additional analyses with larger cohorts are warranted.

Bariatric surgery induces significant shifts in the gut microbiota which could potentially contribute to weight loss and metabolic benefits. The aim of this study was to characterize a microbial signature following Roux-en-Y Gastric bypass (RYGB) surgery using novel and existing gut microbiota sequence data. We generated 16S rRNA gene and metagenomic sequences from fecal samples from patients undergoing RYGB surgery (n = 61 for 16S rRNA gene and n = 135 for metagenomics) at pre-surgical baseline and one, six, and twelve-month post-surgery. We compared these data with three smaller publicly available 16S rRNA gene and one metagenomic datasets from patients who also underwent RYGB surgery. Linear mixed models and machine learning approaches were used to examine the presence of a common microbial signature across studies. Comparison of our new sequences with previous longitudinal studies revealed strikingly similar profiles in both fecal microbiota composition (r = 0.41 ± 0.10; p

Marine animals represent a dynamic and complex habitat for diverse microbial communities. The microbiota associated with bottlenose dolphins (Tursiops truncatus) are believed to influence their health status, but it remains poorly understood. We therefore characterized and compared the bacterial microbiome of bottlenose dolphins from six different anatomical sites that represent four different body systems (respiratory, digestive, reproductive, and integumentary). In this study, a total of 14 free-ranging bottlenose dolphins were sampled during the 2015 Sarasota Bay Dolphin Health Assessment. Bacterial diversity and abundance were assessed by PCR amplification of the hypervariable V3–V4 regions of the bacterial 16S rRNA gene for each sample, followed by sequencing on an Illumina MiSeq platform. Analysis showed that bottlenose dolphins harbor diverse bacterial communities with a unique microbial community at each body system. Additionally, the bottlenose dolphin bacterial microbiome was clearly distinct to the aquatic microbiome from their surrounding habitat. These results are in close agreement with other cetacean microbiome studies, while our study is the first to explore what was found to be a diverse bottlenose dolphin genital microbiome. The core bacterial communities identified in this study in apparently healthy animals might be informative for future health monitoring of bottlenose dolphins.

Animal work indicates exposure to air pollutants may alter the composition of the gut microbiota. This study examined relationships between air pollutants and the gut microbiome in young adults residing in Southern California. Our results demonstrate significant associations between exposure to air pollutants and the composition of the gut microbiome using whole-genome sequencing. Higher exposure to 24-hour O3 was associated with lower Shannon diversity index, higher Bacteroides caecimuris, and multiple gene pathways, including L-ornithine de novo biosynthesis as well as pantothenate and coenzyme A biosynthesis I. Among other pollutants, higher NO2 exposure was associated with fewer taxa, including higher Firmicutes. The percent variation in gut bacterial composition that was explained by air pollution exposure was up to 11.2% for O3 concentrations, which is large compared to the effect size for many other covariates reported in healthy populations. This study provides the first evidence of significant associations between exposure to air pollutants and the compositional and functional profile of the human gut microbiome. These results identify O3 as an important pollutant that may alter the human gut microbiome. Keywords: Air pollution, Gut microbiome, Whole genome sequencing

ABSTRACT Disrupted interactions between host and intestinal bacteria are implicated in colorectal cancer (CRC) development. However, activities derived from these bacteria and their interplay with the host are unclear. Here, we examine this interplay by performing mouse and microbiota RNA sequencing on colon tissues and 16S and small RNA sequencing on stools from germfree (GF) and gnotobiotic ApcMinΔ850/+;Il10−/− mice associated with microbes from biofilm-positive human CRC tumor (BF+T) and biofilm-negative healthy (BF-bx) tissues. The bacteria in BF+T mice differentially expressed (DE) >2,900 genes, including genes related to bacterial secretion, virulence, and biofilms but affected only 62 host genes. Small RNA sequencing of stools from these cohorts revealed eight significant DE host microRNAs (miRNAs) based on biofilm status and several miRNAs that correlated with bacterial taxon abundances. Additionally, computational predictions suggest that some miRNAs preferentially target bacterial genes while others primarily target mouse genes. 16S rRNA sequencing of mice that were reassociated with mucosa-associated communities from the initial association revealed a set of 13 bacterial genera associated with cancer that were maintained regardless of whether the reassociation inoculums were initially obtained from murine proximal or distal colon tissues. Our findings suggest that complex interactions within bacterial communities affect host-derived miRNA, bacterial composition, and CRC development. IMPORTANCE Bacteria and bacterial biofilms have been implicated in colorectal cancer (CRC), but it is still unclear what genes these microbial communities express and how they influence the host. MicroRNAs regulate host gene expression and have been explored as potential biomarkers for CRC. An emerging area of research is the ability of microRNAs to impact growth and gene expression of members of the intestinal microbiota. This study examined the bacteria and bacterial transcriptome associated with microbes derived from biofilm-positive human cancers that promoted tumorigenesis in a murine model of CRC. The murine response to different microbial communities (derived from CRC patients or healthy people) was evaluated through RNA and microRNA sequencing. We identified a complex interplay between biofilm-associated bacteria and the host during CRC in mice. These findings may lead to the development of new biomarkers and therapeutics for identifying and treating biofilm-associated CRCs.

Abstract Background Urbanization is associated with an increased risk for a number of diseases, including obesity, diabetes, and cancer, which all also show associations with the microbiome. While microbial community composition has been shown to vary across continents and in traditional versus Westernized societies, few studies have examined urban-rural differences in neighboring communities within a single country undergoing rapid urbanization. In this study, we compared the gut microbiome, plasma metabolome, dietary habits, and health biomarkers of rural and urban people from a single Chinese province. Results We identified significant differences in the microbiota and microbiota-related plasma metabolites in rural versus recently urban subjects from the Hunan province of China. Microbes with higher relative abundance in Chinese urban samples have been associated with disease in other studies and were substantially more prevalent in the Human Microbiome Project cohort of American subjects. Furthermore, using whole metagenome sequencing, we found that urbanization was associated with a loss of microbial diversity and changes in the relative abundances of Viruses, Archaea, and Bacteria. Gene diversity, however, increased with urbanization, along with the proportion of reads associated with antibiotic resistance and virulence, which were strongly correlated with the presence of Escherichia and Shigella. Conclusions Our data suggest that urbanization has produced convergent evolution of the gut microbial composition in American and urban Chinese populations, resulting in similar compositional patterns of abundant microbes through similar lifestyles on different continents, including a loss of potentially beneficial bacteria and an increase in potentially harmful genes via increased relative abundance of Escherichia and Shigella.

Epidemiological studies suggest a positive association between obesity and fecal short-chain fatty acids (SCFAs) produced by microbial fermentation of dietary carbohydrates, while animal models suggest increased energy harvest through colonic SCFA production in obesity. However, there is a lack of human population-based studies with dietary intake data, plasma SCFAs, gut microbial, and anthropometric data. In 490 Chinese adults aged 30–68 years, we examined the associations between key plasma SCFAs (butyrate/isobutyrate, isovalerate, and valerate measured by non-targeted plasma metabolomics) with body mass index (BMI) using multivariable-adjusted linear regression. We then assessed whether overweight (BMI ≥ 24 kg/m2) modified the association between dietary-precursors of SCFAs (insoluble fiber, total carbohydrates, and high-fiber foods) with plasma SCFAs. In a sub-sample (n = 209) with gut metagenome data, we examined the association between gut microbial SCFA-producers with BMI. We found positive associations between butyrate/isobutyrate and BMI (p-value < 0.05). The associations between insoluble fiber and butyrate/isobutyrate differed by overweight (p-value < 0.10). There was no statistical evidence for an association between microbial SCFA-producers and BMI. In sum, plasma SCFAs were positively associated with BMI and that the colonic fermentation of fiber may differ for adults with versus without overweight.

Crohn's disease (CD) represents a chronic inflammatory disorder of the intestinal tract. Several susceptibility genes have been linked to CD, though their precise role in the pathogenesis of this disorder remains unclear. Immunity-related GTPase M (IRGM) is an established risk allele in CD. We have shown previously that conventionally raised (CV) mice lacking the IRGM ortholog, Irgm1 exhibit abnormal Paneth cells (PCs) and increased susceptibility to intestinal injury. In the present study, we sought to utilize this model system to determine if environmental conditions impact these phenotypes, as is thought to be the case in human CD. To accomplish this, wild-type and Irgm1−/− mice were rederived into specific pathogen-free (SPF) and germ-free (GF) conditions. We next assessed how these differential housing environments influenced intestinal injury patterns, and epithelial cell morphology and function in wild-type and Irgm1−/− mice. Remarkably, in contrast to CV mice, SPF Irgm1−/− mice showed only a slight increase in susceptibility to dextran sodium sulfate-induced inflammation. SPF Irgm1−/− mice also displayed minimal abnormalities in PC number and morphology, and in antimicrobial peptide expression. Goblet cell numbers and epithelial proliferation were also unaffected by Irgm1 in SPF conditions. No microbial differences were observed between wild-type and Irgm1−/− mice, but gut bacterial communities differed profoundly between CV and SPF mice. Specifically, Helicobacter sequences were significantly increased in CV mice; however, inoculating SPF Irgm1−/− mice with Helicobacter hepaticus was not sufficient to transmit a pro-inflammatory phenotype. In summary, our findings suggest the impact of Irgm1-deficiency on susceptibility to intestinal inflammation and epithelial function is critically dependent on environmental influences. This work establishes the importance of Irgm1−/− mice as a model to elucidate host-environment interactions that regulate mucosal homeostasis and intestinal inflammatory responses. Defining such interactions will be essential for developing novel preventative and therapeutic strategies for human CD.