GUT MICROBIOME DIVERSITY OF THREE RHINOCEROS SPECIES IN EUROPEAN ZOOS.

The wild rhinoceros populations have declined drastically in the past decades because the rhinoceros are heavily hunted for their horns. Zoological institutions aim to conserve rhinoceros populations in captivity, but one of the challenges of ex situ conservation is to provide food sources that resemble those available in the wild. Considering that the mammalian gut microbiota is a pivotal player in their host's health, the gut microbiota of rhinoceros may also play a role in the bioavailability of nutrients. Therefore, this study aims to characterize the fecal microbiome composition of grazing white rhinoceros (WR; Ceratotherium simum) and greater one-horned rhinoceros (GOHR; Rhinoceros unicornis) as well as the browsing black rhinoceros (BR; Diceros bicornis) kept in European zoos. Over the course of 1 yr, 166 fecal samples in total were collected from 9 BR (n = 39), 10 GOHR (n = 56), and 14 WR (n = 71) from 23 zoological institutions. The bacterial composition in the samples was determined using 16S rRNA gene Illumina sequencing. The fecal microbiomes of rhinoceros clustered by species, with BR clustering more distantly from GOHR and WR. Furthermore, the data report clustering of rhinoceros microbiota according to individual rhinoceros and institutional origin, showing that zoological institutions play a significant role in shaping the gut microbiome of rhinoceros species. In addition, BR exhibit a relatively higher microbial diversity than GOHR and WR. BR seem more susceptible to microbial gut changes and appear to have a more diverse microbiome composition among individuals than GOHR and WR. These data expand on the role of gut microbes and can provide baseline data for continued efforts in rhinoceros conservation and health status.

Screen the unforeseen: Microbiome-profiling for detection of zoonotic pathogens in wild rats.

Wild rats can host various zoonotic pathogens. Detection of these pathogens is commonly performed using molecular techniques targeting one or a few specific pathogens. However, this specific way of surveillance could lead to (emerging) zoonotic pathogens staying unnoticed. This problem may be overcome by using broader microbiome-profiling techniques, which enable broad screening of a sample's bacterial or viral composition. In this study, we investigated if 16S rRNA gene amplicon sequencing would be a suitable tool for the detection of zoonotic bacteria in wild rats. Moreover, we used virome-enriched (VirCapSeq) sequencing to detect zoonotic viruses. DNA from kidney samples of 147 wild brown rats (Rattus norvegicus) and 42 black rats (Rattus rattus) was used for 16S rRNA gene amplicon sequencing of the V3-V4 hypervariable region. Blocking primers were developed to reduce the amplification of rat host DNA. The kidney bacterial composition was studied using alpha- and beta-diversity metrics and statistically assessed using PERMANOVA and SIMPER analyses. From the sequencing data, 14 potentially zoonotic bacterial genera were identified from which the presence of zoonotic Leptospira spp. and Bartonella tribocorum was confirmed by (q)PCR or Sanger sequencing. In addition, more than 65% of all samples were dominated (>50% reads) by one of three bacterial taxa: Streptococcus (n = 59), Mycoplasma (n = 39) and Leptospira (n = 25). These taxa also showed the highest contribution to the observed differences in beta diversity. VirCapSeq sequencing in rat liver samples detected the potentially zoonotic rat hepatitis E virus in three rats. Although 16S rRNA gene amplicon sequencing was limited in its capacity for species level identifications and can be more difficult to interpret due to the influence of contaminating sequences in these low microbial biomass samples, we believe it has potential to be a suitable pre-screening method in the future to get a better overview of potentially zoonotic bacteria that are circulating in wildlife.

Development of a reproducible small intestinal microbiota model and its integration into the SHIME®-system, a dynamic in vitro gut model.

The human gastrointestinal tract consists of different regions, each characterized by a distinct physiology, anatomy, and microbial community. While the colonic microbiota has received a lot of attention in recent research projects, little is known about the small intestinal microbiota and its interactions with ingested compounds, primarily due to the inaccessibility of this region in vivo. This study therefore aimed to develop and validate a dynamic, long-term simulation of the ileal microbiota using the SHIME®-technology. Essential parameters were identified and optimized from a screening experiment testing different inoculation strategies, nutritional media, and environmental parameters over an 18-day period. Subjecting a synthetic bacterial consortium to the selected conditions resulted in a stable microbiota that was representative in terms of abundance [8.81 ± 0.12 log (cells/ml)], composition and function. Indeed, the observed community mainly consisted of the genera Streptococcus, Veillonella, Enterococcus, Lactobacillus, and Clostridium (qPCR and 16S rRNA gene targeted Illumina sequencing), while nutrient administration boosted lactate production followed by cross-feeding interactions towards acetate and propionate. Furthermore, similarly as in vivo, bile salts were only partially deconjugated and only marginally converted into secondary bile salts. After confirming reproducibility of the small intestinal microbiota model, it was integrated into the established M-SHIME® where it further increased the compositional relevance of the colonic community. This long-term in vitro model provides a representative simulation of the ileal bacterial community, facilitating research of the ileum microbiota dynamics and activity when, for example, supplemented with microbial or diet components. Furthermore, integration of this present in vitro simulation increases the biological relevance of the current M-SHIME® technology.

Anxiolytic effects of a galacto-oligosaccharides prebiotic in healthy females (18-25 years) with corresponding changes in gut bacterial composition.

Current research implicates pre- and probiotic supplementation as a potential tool for improving symptomology in physical and mental ailments, which makes it an attractive concept for clinicians and consumers alike. Here we focus on the transitional period of late adolescence and early adulthood during which effective interventions, such as nutritional supplementation to influence the gut microbiota, have the potential to offset health-related costs in later life. We examined multiple indices of mood and well-being in 64 healthy females in a 4-week double blind, placebo controlled galacto-oligosaccharides (GOS) prebiotic supplement intervention and obtained stool samples at baseline and follow-up for gut microbiota sequencing and analyses. We report effects of the GOS intervention on self-reported high trait anxiety, attentional bias, and bacterial abundance, suggesting that dietary supplementation with a GOS prebiotic may improve indices of pre-clinical anxiety. Gut microbiota research has captured the imagination of the scientific and lay community alike, yet we are now at a stage where this early enthusiasm will need to be met with rigorous research in humans. Our work makes an important contribution to this effort by combining a psychobiotic intervention in a human sample with comprehensive behavioural and gut microbiota measures.

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications.

Advances in sequencing and computational biology have drastically increased our capability to explore the taxonomic and functional compositions of microbial communities that play crucial roles in industrial processes. Correspondingly, commercial interest has risen for applications where microbial communities make important contributions. These include food production, probiotics, cosmetics, and enzyme discovery. Other commercial applications include software that takes the user's gut microbiome data as one of its inputs and outputs evidence-based, automated, and personalized diet recommendations for balanced blood sugar levels. These applications pose several bioinformatic and data science challenges that range from requiring strain-level resolution in community profiles to the integration of large datasets for predictive machine learning purposes. In this perspective, we provide our insights on such challenges by touching upon several industrial areas, and briefly discuss advances and future directions of bioinformatics and data science in microbiome research.

Novel sequencing technologies to support industrial biotechnology.

Industrial biotechnology develops and applies microorganisms for the production of bioproducts and enzymes with applications ranging from food and feed ingredients and processing to bio-based chemicals, biofuels and pharmaceutical products. Next generation DNA sequencing technologies play an increasingly important role in improving and accelerating microbial strain development for existing and novel bio-products via screening, gene and pathway discovery, metabolic engineering and additional optimization and understanding of large-scale manufacturing. In this mini-review, we describe novel DNA sequencing and analysis technologies with a focus on applications to industrial strain development, enzyme discovery and microbial community analysis.

Assessing the origin of bacteria in tap water and distribution system in an unchlorinated drinking water system by SourceTracker using microbial community fingerprints.

The general consensus is that the abundance of tap water bacteria is greatly influenced by water purification and distribution. Those bacteria that are released from biofilm in the distribution system are especially considered as the major potential risk for drinking water bio-safety. For the first time, this full-scale study has captured and identified the proportional contribution of the source water, treated water, and distribution system in shaping the tap water bacterial community based on their microbial community fingerprints using the Bayesian "SourceTracker" method. The bacterial community profiles and diversity analyses illustrated that the water purification process shaped the community of planktonic and suspended particle-associated bacteria in treated water. The bacterial communities associated with suspended particles, loose deposits, and biofilm were similar to each other, while the community of tap water planktonic bacteria varied across different locations in distribution system. The microbial source tracking results showed that there was not a detectable contribution of source water to bacterial community in the tap water and distribution system. The planktonic bacteria in the treated water was the major contributor to planktonic bacteria in the tap water (17.7-54.1%). The particle-associated bacterial community in the treated water seeded the bacterial community associated with loose deposits (24.9-32.7%) and biofilm (37.8-43.8%) in the distribution system. In return, the loose deposits and biofilm showed a significant influence on tap water planktonic and particle-associated bacteria, which were location dependent and influenced by hydraulic changes. This was revealed by the increased contribution of loose deposits to tap water planktonic bacteria (from 2.5% to 38.0%) and an increased contribution of biofilm to tap water particle-associated bacteria (from 5.9% to 19.7%) caused by possible hydraulic disturbance from proximal to distal regions. Therefore, our findings indicate that the tap water bacteria could possibly be managed by selecting and operating the purification process properly and cleaning the distribution system effectively.

The Effect of DNA Extraction Methods on Observed Microbial Communities from Fibrous and Liquid Rumen Fractions of Dairy Cows.

DNA based methods have been widely used to study the complexity of the rumen microbiota, and it is well known that the method of DNA extraction is a critical step in enabling accurate assessment of this complexity. Rumen fluid (RF) and fibrous content (FC) fractions differ substantially in terms of their physical nature and associated microorganisms. The aim of this study was therefore to assess the effect of four DNA extraction methods (RBB, PBB, FDSS, PQIAmini) differing in cell lysis and/or DNA recovery methods on the observed microbial diversity in RF and FC fractions using samples from four rumen cannulated dairy cows fed 100% grass silage (GS100), 67% GS and 33% maize silage (GS67MS33), 33% GS and 67% MS (GS33MS67), or 100% MS (MS100). An ANOVA statistical test was applied on DNA quality and yield measurements, and it was found that the DNA yield was significantly affected by extraction method (p < 0.001) and fraction (p < 0.001). The 260/280 ratio was not affected by extraction (p = 0.08) but was affected by fraction (p = 0.03). On the other hand, the 260/230 ratio was affected by extraction method (p < 0.001) but not affected by fraction (p = 0.8). However, all four extraction procedures yielded DNA suitable for further analysis of bacterial, archaeal and anaerobic fungal communities using quantitative PCR and pyrosequencing of relevant taxonomic markers. Redundancy analysis (RDA) of bacterial 16S rRNA gene sequence data at the family level showed that there was a significant effect of rumen fraction (p = 0.012), and that PBB (p = 0.012) and FDSS (p = 0.024) also significantly contributed to explaining the observed variation in bacterial community composition. Whilst the DNA extraction method affected the apparent bacterial community composition, no single extraction method could be concluded to be ineffective. No obvious effect of DNA extraction method on the anaerobic fungi or archaea was observed, although fraction effects were evident for both. In summary, the comprehensive assessment of observed communities of bacteria, archaea and anaerobic fungi described here provides insight into a rational basis for selecting an optimal methodology to obtain a representative picture of the rumen microbiota.

Diurnal Dynamics of Gaseous and Dissolved Metabolites and Microbiota Composition in the Bovine Rumen.

Diurnal patterns of ruminal fermentation metabolites and microbial communities are not commonly assessed when investigating variation in ruminal CH4 production. The aims of this study were to monitor diurnal patterns of: (i) gaseous and dissolved metabolite concentrations in the bovine rumen, (ii) H2 and CH4 emitted, and (iii) the rumen microbiota. Furthermore, the effect of dietary inclusion of linseed oil on these patterns was assessed. Four rumen cannulated multiparous cows were used in a cross-over design with two 17 days periods and two dietary treatments: a control diet and a linseed oil supplemented diet [40% maize silage, 30% grass silage, 30% concentrate on dry matter (DM) basis for both diets; fat contents of 33 vs. 56 g/kg of DM]. On day 11, rumen contents were sampled for 10 h after morning feeding to profile gaseous and dissolved metabolite concentrations and microbiota composition. H2 and CH4 emission (mass per unit of time) was measured in respiration chambers from day 13 to 17. A 100-fold increase in ruminal H2 partial pressure (contribution to the total pressure of rumen headspace gases) was observed at 0.5 h after feeding. This peak was followed by a decline to basal level. Qualitatively similar patterns after feeding were also observed for H2 and CH4 emission, ethanol and lactate concentrations, and propionate molar proportion, although the opposite pattern was seen for acetate molar proportion. Associated with these patterns, a temporal biphasic change in the microbial composition was observed as based on 16S ribosomal RNA with certain taxa specifically associated with each phase. Bacterial concentrations (log10 16S ribosomal RNA gene copies based) were affected by time, and were increased by linseed oil supplementation. Archaeal concentrations (log10 16S ribosomal RNA gene copies based) tended to be affected by time and were not affected by diet, despite linseed oil supplementation decreasing CH4 emission, tending to decrease the partial pressure of CH4, and tending to increase propionate molar proportion. Linseed oil supplementation affected microbiota composition, and was most associated with an uncultivated Bacteroidales taxon. In summary, our findings support the importance of diurnal dynamics for the understanding of VFA, H2, and CH4 production.

Effects of pectin supplementation on the fermentation patterns of different structural carbohydrates in rats.

SCOPE: We aimed to investigate and compare the effects of four types of pectins on dietary fiber (DF) fermentation, microbiota composition, and short chain fatty acid (SCFA) production throughout the large intestine in rats. METHODS AND RESULTS: Male Wistar rats were given diets supplemented with or without 3% structurally different pectins for 7 weeks. Different fermentation patterns of pectins and different location of fermentation of pectin and diet arabinoxylans (AXs) in the large intestine were observed. During cecal fermentation, sugar beet pectin significantly stimulated Lactobacillus (p < 0.01) and Lachnospiraceae (p < 0.05). The stimulating effects of sugar beet pectin on these two groups of microbes are stronger than both other pectins. In the cecum, low-methyl esterified citrus pectin and complex soy pectin increased (p < 0.05) the production of total SCFAs, propionate and butyrate, whereas high-methyl esterified pectin and sugar beet pectin did not. The fermentation patterns of cereal AXs in the cecum were significantly different upon supplementation of different pectins. These differences, however, became smaller in the colon due to an enhanced fermentation of the remaining DFs. CONCLUSION: Dietary supplementation of pectin is a potential strategy to modulate the location of fermentation of DFs, and consequently microbiota composition and SCFA production for health-promoting effects.

The small intestine microbiota, nutritional modulation and relevance for health.

The intestinal microbiota plays a profound role in human health and extensive research has been dedicated to identify microbiota aberrations that are associated with disease. Most of this work has been targeting the large intestine and fecal microbiota, while the small intestine microbiota may also have a profound impact on various aspects of the host's physiology, including immune, metabolic and endocrine functions. This review highlights the recent advances made in the study of the human small intestine microbiota. In addition, it describes recent human and animal studies that underpin the importance of this part of the intestine for health of the host organism.

T lymphocytes control microbial composition by regulating the abundance of Vibrio in the zebrafish gut.

Dysbiosis of the intestinal microbial community is considered a risk factor for development of chronic intestinal inflammation as well as other diseases such as diabetes, obesity and even cancer. Study of the innate and adaptive immune pathways controlling bacterial colonization has however proven difficult in rodents, considering the extensive cross-talk between bacteria and innate and adaptive immunity. Here, we used the zebrafish to study innate and adaptive immune processes controlling the microbial community. Zebrafish lack a functional adaptive immune system in the first weeks of life, enabling study of the innate immune system in the absence of adaptive immunity. We show that in wild type zebrafish, the initial lack of adaptive immunity associates with overgrowth of Vibrio species (a group encompassing fish and human pathogens), which is overcome upon adaptive immune development. In Rag1-deficient zebrafish (lacking adaptive immunity) Vibrio abundance remains high, suggesting that adaptive immune processes indeed control Vibrio species. Using cell transfer experiments, we confirm that adoptive transfer of T lymphocytes, but not B lymphocytes into Rag1-deficient recipients suppresses outgrowth of Vibrio. In addition, ex vivo exposure of intestinal T lymphocytes to Rag1-deficient microbiota results in increased interferon-gamma expression by these T lymphocytes, compared to exposure to wild type microbiota. In conclusion, we show that T lymphocytes control microbial composition by effectively suppressing the outgrowth of Vibrio species in the zebrafish intestine.

Immunomodulatory properties of Streptococcus and Veillonella isolates from the human small intestine microbiota.

The human small intestine is a key site for interactions between the intestinal microbiota and the mucosal immune system. Here we investigated the immunomodulatory properties of representative species of commonly dominant small-intestinal microbial communities, including six streptococcal strains (four Streptococcus salivarius, one S. equinus, one S. parasanguinis) one Veillonella parvula strain, one Enterococcus gallinarum strain, and Lactobacillus plantarum WCFS1 as a bench mark strain on human monocyte-derived dendritic cells. The different streptococci induced varying levels of the cytokines IL-8, TNF-α, and IL-12p70, while the V. parvula strain showed a strong capacity to induce IL-6. E. gallinarum strain was a potent inducer of cytokines and TLR2/6 signalling. As Streptococcus and Veillonella can potentially interact metabolically and frequently co-occur in ecosystems, immunomodulation by pair-wise combinations of strains were also tested for their combined immunomodulatory properties. Strain combinations induced cytokine responses in dendritic cells that differed from what might be expected on the basis of the results obtained with the individual strains. A combination of (some) streptococci with Veillonella appeared to negate IL-12p70 production, while augmenting IL-8, IL-6, IL-10, and TNF-α responses. This suggests that immunomodulation data obtained in vitro with individual strains are unlikely to adequately represent immune responses to mixtures of gut microbiota communities in vivo. Nevertheless, analysing the immune responses of strains representing the dominant species in the intestine may help to identify immunomodulatory mechanisms that influence immune homeostasis.

Aberrant gut microbiota composition at the onset of type 1 diabetes in young children.

AIMS/HYPOTHESIS: Recent studies indicate that an aberrant gut microbiota is associated with the development of type 1 diabetes, yet little is known about the microbiota in children who have diabetes at an early age. To this end, the microbiota of children aged 1-5 years with new-onset type 1 diabetes was compared with the microbiota of age-matched healthy controls. METHODS: A deep global analysis of the gut microbiota composition was established by phylogenetic microarray analysis using a Human Intestinal Tract Chip (HITChip). RESULTS: Principal component analyses highlighted the importance of age when comparing age-matched pairs. In pairs younger than 2.9 years, the combined abundance of the class Bacilli (notably streptococci) and the phylum Bacteroidetes was higher in diabetic children, whereas the combined abundance of members of Clostridium clusters IV and XIVa was higher in the healthy controls. Controls older than 2.9 years were characterised by a higher fraction of butyrate-producing species within Clostridium clusters IV and XIVa than was seen in the corresponding diabetic children or in children from the younger age groups, while the diabetic children older than 2.9 years could be differentiated by having an increased microbial diversity. CONCLUSIONS/INTERPRETATION: The results from both age groups suggest that non-diabetic children have a more balanced microbiota in which butyrate-producing species appear to hold a pivotal position.

Draft Genome Sequence of Veillonella parvula HSIVP1, Isolated from the Human Small Intestine.

Veillonella species are frequently encountered commensals in the human small intestine. Here, we report the draft genome sequence of the first cultured representative from this ecosystem, Veillonella parvula strain HSIVP1. The genome is predicted to encode all the necessary enzymes required for the pathway involved in the conversion of lactate to propanoate.

Draft Genome Sequence of Enterococcus sp. Strain HSIEG1, Isolated from the Human Small Intestine.

Enterococcus sp. strain HSIEG1 was isolated from the human small intestine. Its draft genome predicts a broad carbohydrate fermentation capability, which matches well with the observed physiological characteristics of this strain. This metabolic flexibility is expected to be of importance for survival and growth in the small intestinal habitat.

A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets.

BACKGROUND: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. RESULTS: The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. CONCLUSIONS: A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche.

Diversity of human small intestinal Streptococcus and Veillonella populations.

Molecular and cultivation approaches were employed to study the phylogenetic richness and temporal dynamics of Streptococcus and Veillonella populations in the small intestine. Microbial profiling of human small intestinal samples collected from four ileostomy subjects at four time points displayed abundant populations of Streptococcus spp. most affiliated with S. salivarius, S. thermophilus, and S. parasanguinis, as well as Veillonella spp. affiliated with V. atypica, V. parvula, V. dispar, and V. rogosae. Relative abundances varied per subject and time of sampling. Streptococcus and Veillonella isolates were cultured using selective media from ileostoma effluent samples collected at two time points from a single subject. The richness of the Streptococcus and Veillonella isolates was assessed at species and strain level by 16S rRNA gene sequencing and genetic fingerprinting, respectively. A total of 160 Streptococcus and 37 Veillonella isolates were obtained. Genetic fingerprinting differentiated seven Streptococcus lineages from ileostoma effluent, illustrating the strain richness within this ecosystem. The Veillonella isolates were represented by a single phylotype. Our study demonstrated that the small intestinal Streptococcus populations displayed considerable changes over time at the genetic lineage level because only representative strains of a single Streptococcus lineage could be cultivated from ileostoma effluent at both time points.

Comparative genomics analysis of Streptococcus isolates from the human small intestine reveals their adaptation to a highly dynamic ecosystem.

The human small-intestinal microbiota is characterised by relatively large and dynamic Streptococcus populations. In this study, genome sequences of small-intestinal streptococci from S. mitis, S. bovis, and S. salivarius species-groups were determined and compared with those from 58 Streptococcus strains in public databases. The Streptococcus pangenome consists of 12,403 orthologous groups of which 574 are shared among all sequenced streptococci and are defined as the Streptococcus core genome. Genome mining of the small-intestinal streptococci focused on functions playing an important role in the interaction of these streptococci in the small-intestinal ecosystem, including natural competence and nutrient-transport and metabolism. Analysis of the small-intestinal Streptococcus genomes predicts a high capacity to synthesize amino acids and various vitamins as well as substantial divergence in their carbohydrate transport and metabolic capacities, which is in agreement with observed physiological differences between these Streptococcus strains. Gene-specific PCR-strategies enabled evaluation of conservation of Streptococcus populations in intestinal samples from different human individuals, revealing that the S. salivarius strains were frequently detected in the small-intestine microbiota, supporting the representative value of the genomes provided in this study. Finally, the Streptococcus genomes allow prediction of the effect of dietary substances on Streptococcus population dynamics in the human small-intestine.

Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk.

Colon cancer is a major cause of cancer deaths in Western countries and is associated with diets high in red meat. Heme, the iron-porphyrin pigment of red meat, induces cytotoxicity of gut contents which injures surface cells leading to compensatory hyperproliferation of crypt cells. This hyperproliferation results in epithelial hyperplasia which increases the risk of colon cancer. In humans, a high red-meat diet increases Bacteroides spp in feces. Therefore, we simultaneously investigated the effects of dietary heme on colonic microbiota and on the host mucosa of mice. Whole genome microarrays showed that heme injured the colonic surface epithelium and induced hyperproliferation by changing the surface to crypt signaling. Using 16S rRNA phylogenetic microarrays, we investigated whether bacteria play a role in this changed signaling. Heme increased Bacteroidetes and decreased Firmicutes in colonic contents. This shift was most likely caused by a selective susceptibility of gram-positive bacteria to heme cytotoxic fecal water, which is not observed for gram-negative bacteria, allowing expansion of the gram-negative community. The increased amount of gram-negative bacteria most probably increased LPS exposure to colonocytes, however, there is no appreciable immune response detected in the heme-fed mice. There was no functional change in the sensing of the bacteria by the mucosa, as changes in inflammation pathways and Toll-like receptor signaling were not detected. This unaltered host-microbe cross-talk indicates that the changes in microbiota did not play a causal role in the observed hyperproliferation and hyperplasia.