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HMA mice are models that better represent human gut ecology compared to conventional laboratory mice and are commonly used to test the effects of the gut microbiome on disease or treatment response. We evaluated the fidelity of using HMA mice as avatars of ecological response to a human microbial consortium, Microbial Ecosystem Therapeutic 4. Our results show that HMA mice in our cohort and across other published studies are more similar to each other than the human donors or inoculum they are derived from and harbor a taxonomically restricted gut microbiome. These findings highlight the limitations of HMA mice in evaluating the ecological effects of complex human microbiome-targeting interventions, such as microbial consortia.

Objective Antibiotic (AB) usage strongly affects microbial intestinal metabolism and thereby impacts human health. Understanding this process and the underlying mechanisms remains a major research goal. Accordingly, we conducted the first comparative omic investigation of gut microbial communities in faecal samples taken at multiple time points from an individual subjected to β-lactam therapy. Methods The total (16S rDNA) and active (16S rRNA) microbiota, metagenome, metatranscriptome (mRNAs), metametabolome (high-performance liquid chromatography coupled to electrospray ionisation and quadrupole time-of-flight mass spectrometry) and metaproteome (ultra high performing liquid chromatography coupled to an Orbitrap MS2 instrument [UPLC-LTQ Orbitrap-MS/MS]) of a patient undergoing AB therapy for 14 days were evaluated. Results Apparently oscillatory population dynamics were observed, with an early reduction in Gram-negative organisms (day 6) and an overall collapse in diversity and possible further colonisation by ‘presumptive’ naturally resistant bacteria (day 11), followed by the re-growth of Gram-positive species (day 14). During this process, the maximum imbalance in the active microbial fraction occurred later (day 14) than the greatest change in the total microbial fraction, which reached a minimum biodiversity and richness on day 11; additionally, major metabolic changes occurred at day 6. Gut bacteria respond to ABs early by activating systems to avoid the antimicrobial effects of the drugs, while ‘presumptively’ attenuating their overall energetic metabolic status and the capacity to transport and metabolise bile acid, cholesterol, hormones and vitamins; host–microbial interactions significantly improved after treatment cessation. Conclusions This proof-of-concept study provides an extensive description of gut microbiota responses to follow-up β-lactam therapy. The results demonstrate that ABs targeting specific pathogenic infections and diseases may alter gut microbial ecology and interactions with host metabolism at a much higher level than previously assumed.

Zoonotic Campylobacter, including C. jejuni and C. coli, are among the most prevalent agents of food-borne enteritis worldwide. The immunopathological sequelae of campylobacteriosis are caused by Toll-like Receptor-4 (TLR4)-dependent host immune responses, induced by bacterial lipooligosaccharide (LOS). In order to investigate C. coli-host interactions, including the roles of the human gut microbiota and TLR4, upon infection, we applied a clinical acute campylobacteriosis model, and subjected secondary abiotic, TLR4-deficient IL10-/- mice and IL10-/- controls to fecal microbiota transplantation derived from human donors by gavage, before peroral C. coli challenge. Until day 21 post-infection, C. coli could stably colonize the gastrointestinal tract of human microbiota-associated (hma) mice of either genotype. TLR4-deficient IL10-/- mice, however, displayed less severe clinical signs of infection, that were accompanied by less distinct apoptotic epithelial cell and innate as well as adaptive immune cell responses in the colon, as compared to IL10-/- counterparts. Furthermore, C. coli infected IL10-/-, as opposed to TLR4-deficient IL10-/-, mice displayed increased pro-inflammatory cytokine concentrations in intestinal and, strikingly, systemic compartments. We conclude that pathogenic LOS might play an important role in inducing TLR4-dependent host immune responses upon C. coli infection, which needs to be further addressed in more detail.

ABSTRACT The gut microbiome plays a crucial role in maintaining intestinal homeostasis and influencing immune‐mediated diseases. Human faecal microbiota transplantation (FMT) is often employed in murine models to investigate the role of human microbes in disease regulation, but methods for effective colonisation require refinement. This study aimed to assess the colonisation efficiency of human microbiota in a murine model using FMT with human faeces, focusing particularly on the impact of gut microbiota depletion via polyethylene glycol (PEG) and comparing oral‐gastric gavage with enema administration routes. Our findings revealed that PEG‐induced depletion enhanced human microbiome colonisation in mice. Oral‐gastric gavage prolonged colonisation, while enema administration facilitated quicker resolution of dysbiosis, both inducing selective human microbial colonisation in a time‐dependent manner. Notably, genera such as Bacteroides, Blautia, Medicaternibacter and Bifidobacteria were successfully colonised, whereas Roseburia, Anaerostipes, Anaerobutyricum and Faecalibacterium failed to establish in the murine gut post‐FMT. These findings highlight the challenges of replicating human gut microbiota in murine models and underscore the importance of selecting appropriate FMT methods based on desired outcomes. This study provides valuable insights into the colonisation dynamics of human microbiota in mice, contributing to the development of more effective FMT strategies for disease treatment. We explored the efficacy of human microbiome colonisation in an animal model using FMT with human faeces. Gut microbiota depletion facilitated by PEG followed by oral administration prolonged human microbiome colonisation. In contrast, enema administration provided a more rapid correction of dysbiosis.

Cyanidin 3-glucoside (C3G) is one of the major dietary anthocyanins implicated in the prevention of chronic diseases. To evaluate the impact of human intestinal bacteria on the fate of C3G in the host, we studied the metabolism of C3G in human microbiota-associated (HMA) rats in comparison with germ-free (GF) rats. Urine and faeces of the rats were analysed for C3G and its metabolites within 48 h after the application of 92 μmol C3G/kg body weight. In addition, we tested the microbial C3G conversion in vitro by incubating C3G with human faecal slurries and selected human gut bacteria. The HMA rats excreted with faeces a three times higher percentage of unconjugated C3G products and a two times higher percentage of conjugated C3G products than the GF rats. These differences were mainly due to the increased excretion of 3,4-dihydroxybenzoic acid, 2,4,6-trihydroxybenzaldehyde and 2,4,6-trihydroxybenzoic acid. Only the urine of HMA rats contained peonidin and 3-hydroxycinnamic acid and the percentage of conjugated C3G products in the urine was decreased compared with the GF rats. Overall, the presence of intestinal microbiota resulted in a 3·7 % recovery of the C3G dose in HMA rats compared with 1·7 % in GF rats. Human intestinal bacteria rapidly degraded C3G in vitro. Most of the C3G products were also found in the absence of bacteria, but at considerably lower levels. The higher concentrations of phenolic acids observed in the presence of intestinal bacteria may contribute to the proposed beneficial health effects of C3G.

This study is to investigate the relationship between the intestinal microbiota and urine levels of the ellagic acid-derived polyphenols, the urolithins, in a cohort of subjects following a three-week walnut dietary intervention. We longitudinally collected fecal and urine samples from 39 subjects before and after walnut consumption (2 oz per day for 21 days). 16S RNA gene sequencing was performed on fecal DNA to study the association between microbiota composition and the levels of nine urolithin metabolites, which were measured using UHPLC/Q-TOF–MS/MS. Fecal microbial composition was found to be significantly different between pre- and post-walnut intervention (beta diversity, FDR- p  = 0.018; alpha diversity, p  = 0.018). Roseburia , Rothia , Parasutterella , Lachnospiraceae UCG-004, Butyricicoccus , Bilophila , Eubacterium eligens , Lachnospiraceae UCG-001, Gordonibacter , Paraprevotella , Lachnospira , Ruminococcus torques , and Sutterella were identified as the 13 most significantly enriched genera after daily intake of walnuts. We observed 26 genera that were significantly associated with 7 urolithin metabolites, with 22 genera positively correlating after walnut supplementation (FDR- p  ≤ 0.05). PICRUSt analysis showed that several inferred KEGG orthologs were associated with 4 urolithin metabolites after walnut intake. In this study, we found that walnut supplementation altered urolithin metabolites, which associates with specific changes in bacterial taxa and inferred functional contents.

Skin cancer is the most common type of cancer in the US with an increasing prevalence worldwide. While ultraviolet (UV) radiation is a well-known risk factor, there is emerging evidence that the microbiota may also contribute. In recent years, the human microbiota has become a topic of great interest, and its association with inflammatory skin diseases (i.e., atopic dermatitis, acne, rosacea) has been explored. Little is known of the role of microbiota in skin cancer, but with the recognized link between microbial dysbiosis and inflammation, and knowledge that microbiota modulates the effect of UV-induced immunosuppression, theories connecting the two have surfaced. In this paper, we provide a comprehensive review of the key literature on human microbiota, especially the skin microbiota, and skin cancer (i.e., non-melanoma skin cancer, melanoma, cutaneous T cell lymphoma). Also, mechanistic perspectives as to how our microbiota influence skin cancer development and treatment are offered.

Several studies have shown that the gut microbiota influences behavior and, in turn, changes in the immune system associated with symptoms of depression or anxiety disorder may be mirrored by corresponding changes in the gut microbiota. Although the composition/function of the intestinal microbiota appears to affect the central nervous system (CNS) activities through multiple mechanisms, accurate epidemiological evidence that clearly explains the connection between the CNS pathology and the intestinal dysbiosis is not yet available. The enteric nervous system (ENS) is a separate branch of the autonomic nervous system (ANS) and the largest part of the peripheral nervous system (PNS). It is composed of a vast and complex network of neurons which communicate via several neuromodulators and neurotransmitters, like those found in the CNS. Interestingly, despite its tight connections to both the PNS and ANS, the ENS is also capable of some independent activities. This concept, together with the suggested role played by intestinal microorganisms and the metabolome in the onset and progression of CNS neurological (neurodegenerative, autoimmune) and psychopathological (depression, anxiety disorders, autism) diseases, explains the large number of investigations exploring the functional role and the physiopathological implications of the gut microbiota/brain axis.

Abstract Defining the etiology of inflammatory bowel disease (IBD) continues to elude researchers, in part due to the possibility that there may be different triggers for a spectrum of disease phenotypes that are currently classified as either Crohn's disease (CD) or ulcerative colitis (UC). What is clear is that genetic susceptibility plays an important role in the development of IBD, and large genome-wide association studies using case-control approaches have identified more than 230 risk alleles. Many of these identified risk alleles are located in a variety of genes important in host-microbiome interactions. In spite of these major advances, the mechanisms behind the genetic influence on disease development remain unknown. In addition, the identified genetic risks have thus far failed to fully define the hereditability of IBD. Host genetics influence host interactions with the gut microbiota in maintaining health through a balance of regulated immune responses and coordinated microbial composition and function. What remains to be defined is how alterations in these interactions can lead to disease. The nature and cause of changes in the microbiota in patients with IBD are poorly understood. In spite of the large catalog of alterations in the microbiota of IBD patients, inflammation itself can alter the microbiota, leaving open the question of which is cause or effect. The composition and function of the gut microbiota are influenced by many factors, including environmental factors, dietary factors, and, as recent studies have shown, host genetic makeup. More than 200 loci have shown potential to influence the microbiota, but replication and larger studies are still required to validate these findings. It would seem reasonable to consider the combination of both host genetic makeup and the inheritance of the microbiota as interdependent heritable forces that could explain the nature of an individual's susceptibility to IBD or indeed the actual cause of IBD. In this review, we will consider the contribution of the host genetics, the microbiome, and the influence of host genetics on the microbiota to the heritability of IBD.

Recent advances in DNA sequencing technology have allowed the collection of high-dimensional data from human-associated microbial communities on an unprecedented scale. A major goal of these studies is the identification of important groups of microorganisms that vary according to physiological or disease states in the host, but the incidence of rare taxa and the large numbers of taxa observed make that goal difficult to obtain using traditional approaches. Fortunately, similar problems have been addressed by the machine learning community in other fields of study such as microarray analysis and text classification. In this review, we demonstrate that several existing supervised classifiers can be applied effectively to microbiota classification, both for selecting subsets of taxa that are highly discriminative of the type of community, and for building models that can accurately classify unlabeled data. To encourage the development of new approaches to supervised classification of microbiota, we discuss several structures inherent in microbial community data that may be available for exploitation in novel approaches, and we include as supplemental information several benchmark classification tasks for use by the community.