Fecal Microbiota Transplantation engraftment after budesonide or placebo in patients with active ulcerative colitis using pre-selected donors: a randomized pilot study.

BACKGROUND: Fecal microbiota transplantation (FMT) shows some efficacy in treating patients with ulcerative colitis (UC), although variability has been observed among donors and treatment regimens. We investigated the effect of FMT using rationally selected donors after pretreatment with budesonide or placebo in active UC. METHODS: Patients ≥ 18 years old with mild to moderate active UC were randomly assigned to three weeks budesonide (9 mg) or placebo followed by four weekly infusions of a donor feces suspension. Two donors were selected based on microbiota composition, Treg induction and SCFA production in mice. The primary endpoint was engraftment of donor microbiota after FMT. In addition, clinical efficacy was assessed. RESULTS: In total, 24 patients were enrolled. Pretreatment with budesonide did not increase donor microbiota engraftment (p=0.56) nor clinical response, and engraftment was not associated with clinical response. At week 14, 10/24 (42%) of patients achieved (partial) remission. Remarkably, patients treated with FMT suspensions from one donor were associated with clinical response (80% of responders, p<0.05) but had lower overall engraftment of donor microbiota. Furthermore, differences in the taxonomic composition of the donors and the engraftment of certain taxa were associated with clinical response. CONCLUSION: In this small study, pretreatment with budesonide did not significantly influence engraftment or clinical response after FMT. However, clinical response appeared donor-dependent. Response to FMT may be related to transfer of specific strains instead of overall engraftment, demonstrating the need to characterize mechanisms of actions of strains that maximize therapeutic benefit in ulcerative colitis.

Heterogeneous associations of gut microbiota with Crohn's disease activity.

The multi-factorial involvement of gut microbiota with Crohn's disease (CD) necessitates robust analysis to uncover possible associations with particular microbes. CD has been linked to specific bacteria, but reported associations vary widely across studies. This inconsistency may result from heterogeneous associations across individual patients, resulting in no apparent or only weak relationships with the means of bacterial abundances. We investigated the relationship between bacterial relative abundances and disease activity in a longitudinal cohort of CD patients (n = 57) and healthy controls (n = 15). We applied quantile regression, a statistical technique that allows investigation of possible relationships outside the mean response. We found several significant and mostly negative associations with CD, especially in lower quantiles of relative abundance on family or genus level. Associations found by quantile regression deviated from the mean response in relative abundances of Coriobacteriaceae, Pasteurellaceae, Peptostreptococcaceae, Prevotellaceae, and Ruminococcaceae. For the family Streptococcaceae we found a significant elevation in relative abundance for patients experiencing an exacerbation relative to those who remained without self-reported symptoms or measurable inflammation. Our analysis suggests that specific bacterial families are related to CD and exacerbation, but associations vary between patients due to heterogeneity in disease course, medication history, therapy response, gut microbiota composition and historical contingency. Our study underscores that microbial diversity is reduced in the gut of CD patients, but suggests that the process of diversity loss is rather irregular with respect to specific taxonomic groups. This novel insight may advance our ecological understanding of this complex disease.

Edge and modular significance assessment in individual-specific networks.

Individual-specific networks, defined as networks of nodes and connecting edges that are specific to an individual, are promising tools for precision medicine. When such networks are biological, interpretation of functional modules at an individual level becomes possible. An under-investigated problem is relevance or "significance" assessment of each individual-specific network. This paper proposes novel edge and module significance assessment procedures for weighted and unweighted individual-specific networks. Specifically, we propose a modular Cook's distance using a method that involves iterative modeling of one edge versus all the others within a module. Two procedures assessing changes between using all individuals and using all individuals but leaving one individual out (LOO) are proposed as well (LOO-ISN, MultiLOO-ISN), relying on empirically derived edges. We compare our proposals to competitors, including adaptions of OPTICS, kNN, and Spoutlier methods, by an extensive simulation study, templated on real-life scenarios for gene co-expression and microbial interaction networks. Results show the advantages of performing modular versus edge-wise significance assessments for individual-specific networks. Furthermore, modular Cook's distance is among the top performers across all considered simulation settings. Finally, the identification of outlying individuals regarding their individual-specific networks, is meaningful for precision medicine purposes, as confirmed by network analysis of microbiome abundance profiles.

Capturing the dynamics of microbial interactions through individual-specific networks.

Longitudinal analysis of multivariate individual-specific microbiome profiles over time or across conditions remains dauntin. Most statistical tools and methods that are available to study microbiomes are based on cross-sectional data. Over the past few years, several attempts have been made to model the dynamics of bacterial species over time or across conditions. However, the field needs novel views on handling microbial interactions in temporal analyses. This study proposes a novel data analysis framework, MNDA, that combines representation learning and individual-specific microbial co-occurrence networks to uncover taxon neighborhood dynamics. As a use case, we consider a cohort of newborns with microbiomes available at 6 and 9 months after birth, and extraneous data available on the mode of delivery and diet changes between the considered time points. Our results show that prediction models for these extraneous outcomes based on an MNDA measure of local neighborhood dynamics for each taxon outperform traditional prediction models solely based on individual-specific microbial abundances. Furthermore, our results show that unsupervised similarity analysis of newborns in the study, again using the notion of a taxon's dynamic neighborhood derived from time-matched individual-specific microbial networks, can reveal different subpopulations of individuals, compared to standard microbiome-based clustering, with potential relevance to clinical practice. This study highlights the complementarity of microbial interactions and abundances in downstream analyses and opens new avenues to personalized prediction or stratified medicine with temporal microbiome data.

Enterobacteriaceae and Bacteroidaceae provide resistance to travel-associated intestinal colonization by multi-drug resistant Escherichia coli.

Previous studies have shown high acquisition risks of extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-E) among international travelers visiting antimicrobial resistance (AMR) hotspots. Although antibiotic use and travelers' diarrhea have shown to influence the ESBL-E acquisition risk, it remains largely unknown whether successful colonization of ESBL-E during travel is associated with the composition, functional capacity and resilience of the traveler's microbiome. The microbiome of pre- and post-travel fecal samples from 190 international travelers visiting Africa or Asia was profiled using whole metagenome shotgun sequencing. A metagenomics species concept approach was used to determine the microbial composition, population diversity and functional capacity before travel and how it is altered longitudinally. Eleven travelers were positive for ESBL-E before travel and removed from the analysis. Neither the microbial richness (Chao1), diversity (effective Shannon) and community structure (Bray-Curtis dissimilarity) in pretravel samples nor the longitudinal change of these metrics during travel were predictive for ESBL-E acquisition. A zero-inflated two-step beta-regression model was used to determine how the longitudinal change in both prevalence and abundance of each taxon was related to ESBL acquisition. There were detected increases in both the prevalence and abundance of Citrobacter freundii and two members of the genus Bacteroides, in association with remaining uncolonized by ESBL-E. These results highlight the potential of these individual microbes as a microbial consortium to prevent the acquisition of ESBL-E. The ability to alter a person's colonization resistance to a bacterium could be key to intervention strategies that aim to minimize the spread of MDR bacteria.

Cross-Sectional Analysis of the Microbiota of Human Gut and Its Direct Environment in a Household Cohort with High Background of Antibiotic Use.

Comprehensive insight into the microbiota of the gut of humans and animals, as well as their living environment, in communities with a high background of antibiotic use and antibiotic resistance genes is scarce. Here, we used 16S rRNA gene sequencing to describe the (dis)similarities in the microbiota of feces from humans (n = 107), domestic animals (n = 36), water (n = 89), and processed food (n = 74) in a cohort with individual history of antibiotic use in northern Vietnam. A significantly lower microbial diversity was observed among individuals who used antibiotics in the past 4 months (n = 44) compared to those who did not (n = 63). Fecal microbiota of humans was more diverse than nonhuman samples and shared a small part of its amplicon sequence variants (ASVs) with feces from animals (7.4% (3.2-9.9)), water (2.2% (1.2-2.8)), and food (3.1% (1.5-3.1)). Sharing of ASVs between humans and companion animals was not associated with the household. However, we did observe a correlation between an Enterobacteriaceae ASV and the presence of extended-spectrum beta-lactamase CTX-M-group-2 encoding genes in feces from humans and animals (p = 1.6 × 10-3 and p = 2.6 × 10-2, respectively), hinting toward an exchange of antimicrobial-resistant strains between reservoirs.

Destination shapes antibiotic resistance gene acquisitions, abundance increases, and diversity changes in Dutch travelers.

BACKGROUND: Antimicrobial-resistant bacteria and their antimicrobial resistance (AMR) genes can spread by hitchhiking in human guts. International travel can exacerbate this public health threat when travelers acquire AMR genes endemic to their destinations and bring them back to their home countries. Prior studies have demonstrated travel-related acquisition of specific opportunistic pathogens and AMR genes, but the extent and magnitude of travel's effects on the gut resistome remain largely unknown. METHODS: Using whole metagenomic shotgun sequencing, functional metagenomics, and Dirichlet multinomial mixture models, we investigated the abundance, diversity, function, resistome architecture, and context of AMR genes in the fecal microbiomes of 190 Dutch individuals, before and after travel to diverse international locations. RESULTS: Travel markedly increased the abundance and α-diversity of AMR genes in the travelers' gut resistome, and we determined that 56 unique AMR genes showed significant acquisition following international travel. These acquisition events were biased towards AMR genes with efflux, inactivation, and target replacement resistance mechanisms. Travel-induced shaping of the gut resistome had distinct correlations with geographical destination, so individuals returning to The Netherlands from the same destination country were more likely to have similar resistome features. Finally, we identified and detailed specific acquisition events of high-risk, mobile genetic element-associated AMR genes including qnr fluoroquinolone resistance genes, blaCTX-M family extended-spectrum ß-lactamases, and the plasmid-borne mcr-1 colistin resistance gene. CONCLUSIONS: Our results show that travel shapes the architecture of the human gut resistome and results in AMR gene acquisition against a variety of antimicrobial drug classes. These broad acquisitions highlight the putative risks that international travel poses to public health by gut resistome perturbation and the global spread of locally endemic AMR genes.

How to Count Our Microbes? The Effect of Different Quantitative Microbiome Profiling Approaches.

Next-generation sequencing (NGS) has instigated the research on the role of the microbiome in health and disease. The compositional nature of such microbiome datasets makes it however challenging to identify those microbial taxa that are truly associated with an intervention or health outcome. Quantitative microbiome profiling overcomes the compositional structure of microbiome sequencing data by integrating absolute quantification of microbial abundances into the NGS data. Both cell-based methods (e.g., flow cytometry) and molecular methods (qPCR) have been used to determine the absolute microbial abundances, but to what extent different quantification methods generate similar quantitative microbiome profiles has so far not been explored. Here we compared relative microbiome profiling (without incorporation of microbial quantification) to three variations of quantitative microbiome profiling: (1) microbial cell counting using flow cytometry (QMP), (2) counting of microbial cells using flow cytometry combined with Propidium Monoazide pre-treatment of fecal samples before metagenomics DNA isolation in order to only profile the microbial composition of intact cells (QMP-PMA), and (3) molecular based quantification of the microbial load using qPCR targeting the 16S rRNA gene. Although qPCR and flow cytometry both resulted in accurate and strongly correlated results when quantifying the bacterial abundance of a mock community of bacterial cells, the two methods resulted in highly divergent quantitative microbial profiles when analyzing the microbial composition of fecal samples from 16 healthy volunteers. These differences could not be attributed to the presence of free extracellular prokaryotic DNA in the fecal samples as sample pre-treatment with Propidium Monoazide did not improve the concordance between qPCR-based and flow cytometry-based QMP. Also lack of precision of qPCR was ruled out as a major cause of the disconcordant findings, since quantification of the fecal microbial load by the highly sensitive digital droplet PCR correlated strongly with qPCR. In conclusion, quantitative microbiome profiling is an elegant approach to bypass the compositional nature of microbiome NGS data, however it is important to realize that technical sources of variability may introduce substantial additional bias depending on the quantification method being used.

Development of the Microbiota and Associations With Birth Mode, Diet, and Atopic Disorders in a Longitudinal Analysis of Stool Samples, Collected From Infancy Through Early Childhood.

BACKGROUND & AIMS: Establishment of the gastrointestinal microbiota during infancy affects immune system development and oral tolerance induction. Perturbations in the microbiome during this period can contribute to development of immune-mediated diseases. We monitored microbiota maturation and associations with subsequent development of allergies in infants and children. METHODS: We collected 1453 stool samples, at 5, 13, 21, and 31 weeks postpartum (infants), and once at school age (6-11 years), from 440 children (49.3% girls, 24.8% born by cesarean delivery; all children except for 6 were breastfed for varying durations; median 40 weeks; interquartile range, 30-53 weeks). Microbiota were analyzed by amplicon sequencing. Children were followed through 3 years of age for development of atopic dermatitis; data on allergic sensitization and asthma were collected when children were school age. RESULTS: Diversity of fecal microbiota, assessed by Shannon index, did not differ significantly among children from 5 through 13 weeks after birth, but thereafter gradually increased to 21 and 31 weeks. Most bacteria within the Bacteroidetes and Proteobacteria phyla were already present at 5 weeks after birth, whereas many bacteria of the Firmicutes phylum were acquired at later times in infancy. At school age, many new Actinobacteria, Firmicutes, and Bacteroidetes bacterial taxa emerged. The largest increase in microbial diversity occurred after 31 weeks. Vaginal, compared with cesarean delivery, was most strongly associated with an enrichment of Bacteroides species at 5 weeks through 31 weeks. From 13 weeks onward, diet became the most important determinant of microbiota composition; cessation of breastfeeding, rather than solid food introduction, was associated with changes. For example, Bifidobacteria, staphylococci, and streptococci significantly decreased on cessation of breastfeeding, whereas bacteria within the Lachnospiraceae family (Pseudobutyrivibrio, Lachnobacterium, Roseburia, and Blautia) increased. When we adjusted for confounding factors, we found fecal microbiota composition to be associated with development of atopic dermatitis, allergic sensitization, and asthma. Members of the Lachnospiraceae family, as well as the genera Faecalibacterium and Dialister, were associated with a reduced risk of atopy. CONCLUSIONS: In a longitudinal study of fecal microbiota of children from 5 weeks through 6 to 11 years, we tracked changes in diversity and composition associated with the development of allergies and asthma.

Faecal Microbiota Dynamics and their Relation to Disease Course in Crohn's Disease.

BACKGROUND: Microbial shifts have been associated with disease activity in Crohn's disease [CD], but findings on specific taxa are inconsistent. This may be due to differences in applied methods and cross-sectional study designs. We prospectively examined the faecal microbiota in adult CD patients with changing or stable disease course over time. METHODS: Faeces were collected at two time-points from 15 healthy control individuals [HCs], 35 CD patients who were in remission and who maintained remission [RRs], and 22 CD patients during remission and also during subsequent exacerbation [RAs]. The microbial composition was assessed by 16S rRNA [V4] gene sequencing. RESULTS: Compared with HCs, patients with CD had a lower microbial richness [p = 0.0002] and diversity [p = 0.005]. Moreover, the microbial community structure of a subset of patients, clustered apart from HCs, was characterized by low microbial diversity and Faecalibacterium abundance. Patients within this cluster did not differ with respect to long-term disease course compared with patients with a 'healthy-appearing' microbiota.Over time, microbial richness and diversity did not change in RR versus RA patients. Although the microbial community structure of both RR and RA patients was less stable over time compared with that of HCs, no differences were observed between the patient groups [p = 0.17]; nor was the stability impacted by Montreal classification, medication use, or surgery. CONCLUSION: The altered microbiota composition and stability in CD was neither associated with disease activity nor long-term disease course, questioning its involvement in the development of an exacerbation. The aberrant microbiota composition in a subset of CD patients warrants further exploration of a more microbiota-driven etiology in this group.

The fecal and mucosal microbiome in acute appendicitis patients: an observational study.

AIM: We aimed to study the mucosal microbiota of the appendix in a prospective appendicitis cohort and to compare the fecal microbiota of patients and controls. We hypothesized that the microbiota may be associated with susceptibility to appendicitis. PATIENTS & METHODS: The fecal microbiota of 99 patients and 106 controls were characterized using 16S-23S intergenic spacer profiling. Richness, diversity and community structure were compared. The appendiceal microbiota from 90 patients was analyzed according to the severity of appendicitis. RESULTS: Overall fecal microbial richness and diversity were similar in patients and controls, yet richness and diversity within the group of Firmicutes, Actinobacteria, Fusobacteria and Verrucomicrobia phyla were lower in patients. Discriminant analyses could correctly classify patients and controls with fair accuracy. No differences were found according to severity in appendiceal or fecal microbiota. CONCLUSION: This study demonstrates differences in the composition of intestinal microbiota of appendicitis patients and healthy individuals.

TP53 codon 72 polymorphism affects accumulation of mtDNA damage in human cells.

Human TP53 gene is characterised by a polymorphism at codon 72 leading to an Arginine-to-Proline (R/P) substitution. The two resulting p53 isoforms have a different subcellular localisation after stress (more nuclear or more mitochondrial for the P or R isoform, respectively). p53P72 variant is more efficient than p53R72 in inducing the expression of genes involved in nuclear DNA repair. Since p53 is involved also in mitochondrial DNA (mtDNA) maintenance, we wondered whether these p53 isoforms are associated with different accumulation of mtDNA damage. We observed that cells bearing p53R72 accumulate lower amount of mtDNA damage upon rotenone stress with respect to cells bearing p53P72, and that p53R72 co-localises with polymerase gamma more than p53P72. We also analysed the in vivo accumulation of heteroplasmy in a 300 bp fragment of mtDNA D-loop of 425 aged subjects. We observed that subjects with heteroplasmy higher than 5% are significantly less than expected in the p53R72/R72 group. On the whole, these data suggest that the polymorphism of TP53 at codon 72 affects the accumulation of mtDNA mutations, likely through the different ability of the two p53 isoforms to bind to polymerase gamma, and may contribute to in vivo accumulation of mtDNA mutations.