Altering Host Resistance to Infections through Microbial Transplantation

Host resistance to bacterial infections is thought to be dictated by host genetic factors. Infections by the natural murine enteric pathogen Citrobacter rodentium (used as a model of human enteropathogenic and enterohaemorrhagic E. coli infections) vary between mice strains, from mild self-resolving colonization in NIH Swiss mice to lethality in C3H/HeJ mice. However, no clear genetic component had been shown to be responsible for the differences observed with C. rodentium infections. Because the intestinal microbiota is important in regulating resistance to infection, and microbial composition is dependent on host genotype, it was tested whether variations in microbial composition between mouse strains contributed to differences in “host” susceptibility by transferring the microbiota of resistant mice to lethally susceptible mice prior to infection. Successful transfer of the microbiota from resistant to susceptible mice resulted in delayed pathogen colonization and mortality. Delayed mortality was associated with increased IL-22 mediated innate defense including antimicrobial peptides Reg3γ and Reg3β, and immunono-neutralization of IL-22 abrogated the beneficial effect of microbiota transfer. Conversely, depletion of the native microbiota in resistant mice by antibiotics and transfer of the susceptible mouse microbiota resulted in reduced innate defenses and greater pathology upon infection. This work demonstrates the importance of the microbiota and how it regulates mucosal immunity, providing an important factor in susceptibility to enteric infection. Transfer of resistance through microbial transplantation (bacteriotherapy) provides additional mechanisms to alter “host” resistance, and a novel means to alter enteric infection and to study host-pathogen interactions

Social interaction, noise and antibiotic-mediated switches in the intestinal microbiota

The intestinal microbiota plays important roles in digestion and resistance against entero-pathogens. As with other ecosystems, its species composition is resilient against small disturbances but strong perturbations such as antibiotics can affect the consortium dramatically. Antibiotic cessation does not necessarily restore pre-treatment conditions and disturbed microbiota are often susceptible to pathogen invasion. Here we propose a mathematical model to explain how antibiotic-mediated switches in the microbiota composition can result from simple social interactions between antibiotic-tolerant and antibiotic-sensitive bacterial groups. We build a two-species (e.g. two functional-groups) model and identify regions of domination by antibiotic-sensitive or antibiotic-tolerant bacteria, as well as a region of multistability where domination by either group is possible. Using a new framework that we derived from statistical physics, we calculate the duration of each microbiota composition state. This is shown to depend on the balance between random fluctuations in the bacterial densities and the strength of microbial interactions. The singular value decomposition of recent metagenomic data confirms our assumption of grouping microbes as antibiotic-tolerant or antibiotic-sensitive in response to a single antibiotic. Our methodology can be extended to multiple bacterial groups and thus it provides an ecological formalism to help interpret the present surge in microbiome data.Comment: 20 pages, 5 figures accepted for publication in Plos Comp Bio. Supplementary video and information availabl

Emergence of Collective Territorial Defense in Bacterial Communities: Horizontal Gene Transfer Can Stabilize Microbiomes

Multispecies bacterial communities such as the microbiota of the gastrointestinal tract can be remarkably stable and resilient even though they consist of cells and species that compete for resources and also produce a large number of antimicrobial agents. Computational modeling suggests that horizontal transfer of resistance genes may greatly contribute to the formation of stable and diverse communities capable of protecting themselves with a battery of antimicrobial agents while preserving a varied metabolic repertoire of the constituent species. In other words horizontal transfer of resistance genes makes a community compatible in terms of exoproducts and capable to maintain a varied and mature metagenome. The same property may allow microbiota to protect a host organism, or if used as a microbial therapy, to purge pathogens and restore a protective environment

Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct ‘metacommunities’, and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the ‘evidence framework’ (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community

EMQN best practice guidelines for the laboratory diagnosis of osteogenesis imperfecta

Osteogenesis imperfecta (OI) comprises a group of inherited disorders characterized by bone fragility and increased susceptibility to fractures. Historically, the laboratory confirmation of the diagnosis OI rested on cultured dermal fibroblasts to identify decreased or abnormal production of abnormal type I (pro)collagen molecules, measured by gel electrophoresis. With the discovery of COL1A1 and COL1A2 gene variants as a cause of OI, sequence analysis of these genes was added to the diagnostic process. Nowadays, OI is known to be genetically heterogeneous. About 90% of individuals with OI are heterozygous for causative variants in the COL1A1 and COL1A2 genes. The majority of remaining affected individuals have recessively inherited forms of OI with the causative variants in the more recently discovered genes CRTAP, FKBP10, LEPRE1,PLOD2, PPIB, SERPINF1, SERPINH1 and SP7, or in other yet undiscovered genes. These advances in the molecular genetic diagnosis of OI prompted us to develop new guidelines for molecular testing and reporting of results in which we take into account that testing is also used to ‘exclude' OI when there is suspicion of non-accidental injury. Diagnostic flow, methods and reporting scenarios were discussed during an international workshop with 17 clinicians and scientists from 11 countries and converged in these best practice guidelines for the laboratory diagnosis of OI

Gut microbiota trajectory in early life may predict development of celiac disease.

BACKGROUND: To investigate whether alterations in the developing intestinal microbiota and immune markers precede celiac disease (CD) onset in infants at familial risk of developing the disease. METHODS: A nested case-control study was carried out as part of a larger prospective cohort study, which included healthy full-term newborns (> 200) with at least one first relative with biopsy-verified CD. The present study includes cases of CD (n = 10) and the best-matched controls (n = 10) who did not develop the disease after 5-year follow-up. Fecal microbiota, assessed by high-throughput 16S rRNA gene amplicon sequencing, and immune parameters were profiled at 4 and 6 months of age and related to CD onset. RESULTS: The microbiota of infants who remained healthy showed an increase in bacterial diversity over time, characterized by increases in Firmicutes families, but not those who developed CD. Infants who subsequently developed CD showed a significant reduction in sIgA levels over time, while those who remained healthy showed increases in TNF-α correlated to Bifidobacterium spp. An increased relative abundance of Bifidobacterium longum was associated with control children while increased proportions of Bifidobacterium breve and Enterococcus spp. were associated with CD development. CONCLUSION: The findings suggest that alterations in the early trajectory of gut microbiota in infants at CD risk could influence the immune maturation process and predispose to CD, although larger population studies are warranted to confirm this hypothesis

Sex impacts Th1 cells, Tregs, and DCs in both intestinal and systemic immunity in a mouse strain and location-dependent manner

Background: Males and females have a different predisposition for the development of intestinal disorders, like inflammatory bowel disease (IBD). We hypothesized that sex specific differences in intestinal immune responses may underlie this bias. To test this hypothesis, we studied sex differences in immune cell populations in the Peyer's patches (PP). For comparison with systemic immunity, we studied spleen cells. Methods: Two mouse strains with different susceptibility for developing colitis (BALB/c and C57Bl/6) were used. Using flow cytometry, we measured the percentage of T cells, Th1, Th17, and Treg cells in the PP and spleen. In addition, we measured the percentages of NK cells, macrophages, myeloid, and lymphoid dendritic cells (DCs) and their expression of CD80 and CD103. Moreover, we measured percentages of monocyte subsets in the peripheral circulation. Results were tested using two-way ANOVA, p <0.05. Results: Males had a lower percentage of T cells in both PP and spleen (PP BALB/c 22.1 %, B6 13.6 %; spleen BALB/c 4.7 %, B6 19.9 %) but a higher percentage of Th1 cell in both tissues (PP BALB/c 350 %, B6 109.5 %; spleen BALB/c 48.7 %, B6 41.9 %) than females. They also had a higher percentage of Tregs in the spleen than females (BALB/c 20.5 %, B6 4.5 %). Furthermore, males had a higher percentage of CD80(+) DCs in both the PP and spleen (lymphoid DCs in PP BALB/c 104.7 %, B6 29.6 %; spleen BALB/c 72.2 %, B6 44.2 %; myeloid DCs in PP BALB/c 80.5 %, B6 93.3 %; spleen BALB/c 88.5 %, B6 50.8 %) and a higher percentage of lymphoid CD103(+) DCs in the spleen than females (BALB/c 41.5 %, B6 28.3 %). The percentage of NK cells was decreased in the spleen (BALB/c 12.5 %, B6 25.1 %) but increased in the PP (BALB/c 75.7 %, B6 78.6 %) of males as compared with females. Strain differences were also found in the PP; BALB/c mice had a higher percentage of T cells (males 58.1 %, females 75.5 %), a higher Th/Tc ratio (males 81.0 %, females 134.2 %), less FoxP3(+)CD25(-) T cells (males 14.6 %, females 30.0 %), more DCs (males 14.8 %, females 15.7 %) and macrophages (males 67.9 %, females 141.2 %), and more NK cells (males 160 %, females 164.3 %) than BALB/c mice. Conclusions: In this study, we show sex differences in intestinal and peripheral immune populations. These differences may underlie sex differences in intestinal disorders like IBD, and this information may be an important knowledge for the treatment of intestinal-related diseases

Pyrosequencing-Based Analysis of the Mucosal Microbiota in Healthy Individuals Reveals Ubiquitous Bacterial Groups and Micro-Heterogeneity

This study used 16S rRNA-based pyrosequencing to examine the microbial community that is closely associated with the colonic mucosa of five healthy individuals. Spatial heterogeneity in microbiota was measured at right colon, left colon and rectum, and between biopsy duplicates spaced 1 cm apart. The data demonstrate that mucosal-associated microbiota is comprised of Firmicutes (50.9%±21.3%), Bacteroidetes (40.2%±23.8%) and Proteobacteria (8.6%±4.7%), and that interindividual differences were apparent. Among the genera, Bacteroides, Leuconostoc and Weissella were present at high abundance (4.6% to 41.2%) in more than 90% of the studied biopsy samples. Lactococcus, Streptococcus, Acidovorax, Acinetobacter, Blautia, Faecalibacterium, Veillonella, and several unclassified bacterial groups were also ubiquitously present at an abundance <7.0% of total microbial community. With the exception of one individual, the mucosal-associated microbiota was relatively homogeneous along the colon (average 61% Bray-Curtis similarity). However, micro-heterogeneity was observed in biopsy duplicates within defined colonic sites for three of the individuals. A weak but significant Mantel correlation of 0.13 was observed between the abundance of acidomucins and mucosal-associated microbiota (P-value  =  0.04), indicating that the localized biochemical differences may contribute in part to the micro-heterogeneity. This study provided a detailed insight to the baseline mucosal microbiota along the colon, and revealed the existence of micro-heterogeneity within defined colonic sites for certain individuals

Microbial diversity and community composition of caecal microbiota in commercial and indigenous Indian chickens determined using 16s rDNA amplicon sequencing

Different alpha diversity indices for each sample of university farm data estimated using QIIME for primer pair P2 data. OTUs were clustered at > 97% similarity. (XLSX 12 kb

Differential Effects of Antibiotic Therapy on the Structure and Function of Human Gut Microbiota

The human intestinal microbiota performs many essential functions for the host. Antimicrobial agents, such as antibiotics (AB), are also known to disturb microbial community equilibrium, thereby having an impact on human physiology. While an increasing number of studies investigate the effects of AB usage on changes in human gut microbiota biodiversity, its functional effects are still poorly understood. We performed a follow-up study to explore the effect of ABs with different modes of action on human gut microbiota composition and function. Four individuals were treated with different antibiotics and samples were taken before, during and after the AB course for all of them. Changes in the total and in the active (growing) microbiota as well as the functional changes were addressed by 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. We have found that the class of antibiotic, particularly its antimicrobial effect and mode of action, played an important role in modulating the gut microbiota composition and function. Furthermore, analysis of the resistome suggested that oscillatory dynamics are not only due to antibiotic-target resistance, but also to fluctuations in the surviving bacterial community. Our results indicated that the effect of AB on the human gut microbiota relates to the interaction of several factors, principally the properties of the antimicrobial agent, and the structure, functions and resistance genes of the microbial community