Edge and modular significance assessment in individual-specific networks.

peer reviewedIndividual-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

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

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\u27s 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\u27 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, bla 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

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

Faecal Microbiota Transplantation Engraftment After Budesonide or Placebo in Patients With Active Ulcerative Colitis Using Pre-selected Donors:A Randomized Pilot Study

Background: Faecal 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 3 weeks of budesonide [9 mg] or placebo followed by 4-weekly infusions of a donor faeces suspension. Two donors were selected based on microbiota composition, regulatory T cell induction and short-chain fatty acid 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%] patients achieved [partial] remission. Remarkably, patients treated with FMT suspensions from one donor were associated with clinical response [80% of responders, p &lt; 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 to be 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 UC.</p

Heterogeneous associations of gut microbiota with Crohn’s disease activity

ABSTRACTThe 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

Capturing the dynamics of microbiomes using individual-specific networks

AbstractBackgroundLongitudinal analysis of multivariate individual-specific microbiome profiles over time or across conditions remains a daunting task. The vast majority of statistical tools and methods available to study the microbiota are based upon 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 how to incorporate individual-specific microbial associations in temporal analyses when the focus lies on microbial interactions.ResultsHere, we propose a novel data analysis framework, called MNDA, to uncover taxon neighbourhood dynamics that combines representation learning and individual-specific microbiome co-occurrence networks. We show that tracking local neighbourhood dynamics in microbiome interaction or co-occurrence networks can yield complementary information to standard approaches that only use microbial abundances or pairwise microbial interactions. We use cohort data on infants for whom microbiome data was available at 6 and 9 months after birth, as well as information on mode of delivery and diet changes over time. In particular, MNDA-based prediction models outperform traditional prediction models based on individual-specific abundances, and enable the detection of microbes whose neighbourhood dynamics are informative of clinical variables. We further show that similarity analyses of individuals based on microbial neighbourhood dynamics can be used to find subpopulations of individuals with potential relevance to clinical practice. The annotated source code for the MNDA framework can be downloaded from:https://github.com/H2020TranSYS/microbiome_dynamicsConclusionsMNDA extracts information from matched microbiome profiles and opens new avenues to personalized prediction or stratified medicine with temporal microbiome data

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

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