Characterization of oral and gut microbiome temporal variability in hospitalized cancer patients.

BACKGROUND: Understanding longitudinal variability of the microbiome in ill patients is critical to moving microbiome-based measurements and therapeutics into clinical practice. However, the vast majority of data regarding microbiome stability are derived from healthy subjects. Herein, we sought to determine intra-patient temporal microbiota variability, the factors driving such variability, and its clinical impact in an extensive longitudinal cohort of hospitalized cancer patients during chemotherapy. METHODS: The stool (n = 365) and oral (n = 483) samples of 59 patients with acute myeloid leukemia (AML) undergoing induction chemotherapy (IC) were sampled from initiation of chemotherapy until neutrophil recovery. Microbiome characterization was performed via analysis of 16S rRNA gene sequencing. Temporal variability was determined using coefficients of variation (CV) of the Shannon diversity index (SDI) and unweighted and weighted UniFrac distances per patient, per site. Measurements of intra-patient temporal variability and patient stability categories were analyzed for their correlations with genera abundances. Groups of patients were analyzed to determine if patients with adverse outcomes had significantly different levels of microbiome temporal variability. Potential clinical drivers of microbiome temporal instability were determined using multivariable regression analyses. RESULTS: Our cohort evidenced a high degree of intra-patient temporal instability of stool and oral microbial diversity based on SDI CV. We identified statistically significant differences in the relative abundance of multiple taxa amongst individuals with different levels of microbiota temporal stability. Increased intra-patient temporal variability of the oral SDI was correlated with increased risk of infection during IC (P = 0.02), and higher stool SDI CVs were correlated with increased risk of infection 90 days post-IC (P = 0.04). Total days on antibiotics was significantly associated with increased temporal variability of both oral microbial diversity (P = 0.03) and community structure (P = 0.002). CONCLUSIONS: These data quantify the longitudinal variability of the oral and gut microbiota in AML patients, show that increased variability was correlated with adverse clinical outcomes, and offer the possibility of using stabilizing taxa as a method of focused microbiome repletion. Furthermore, these results support the importance of longitudinal microbiome sampling and analyses, rather than one time measurements, in research and future clinical practice.

An integrative Bayesian Dirichlet-multinomial regression model for the analysis of taxonomic abundances in microbiome data.

BACKGROUND: The Human Microbiome has been variously associated with the immune-regulatory mechanisms involved in the prevention or development of many non-infectious human diseases such as autoimmunity, allergy and cancer. Integrative approaches which aim at associating the composition of the human microbiome with other available information, such as clinical covariates and environmental predictors, are paramount to develop a more complete understanding of the role of microbiome in disease development. RESULTS: In this manuscript, we propose a Bayesian Dirichlet-Multinomial regression model which uses spike-and-slab priors for the selection of significant associations between a set of available covariates and taxa from a microbiome abundance table. The approach allows straightforward incorporation of the covariates through a log-linear regression parametrization of the parameters of the Dirichlet-Multinomial likelihood. Inference is conducted through a Markov Chain Monte Carlo algorithm, and selection of the significant covariates is based upon the assessment of posterior probabilities of inclusions and the thresholding of the Bayesian false discovery rate. We design a simulation study to evaluate the performance of the proposed method, and then apply our model on a publicly available dataset obtained from the Human Microbiome Project which associates taxa abundances with KEGG orthology pathways. The method is implemented in specifically developed R code, which has been made publicly available. CONCLUSIONS: Our method compares favorably in simulations to several recently proposed approaches for similarly structured data, in terms of increased accuracy and reduced false positive as well as false negative rates. In the application to the data from the Human Microbiome Project, a close evaluation of the biological significance of our findings confirms existing associations in the literature.

The role of the gastrointestinal microbiome in infectious complications during induction chemotherapy for acute myeloid leukemia.

BACKGROUND: Despite increasing data on the impact of the microbiome on cancer, the dynamics and role of the microbiome in infection during therapy for acute myelogenous leukemia (AML) are unknown. Therefore, the authors sought to determine correlations between microbiome composition and infectious outcomes in patients with AML who were receiving induction chemotherapy (IC). METHODS: Buccal and fecal specimens (478 samples) were collected twice weekly from 34 patients with AML who were undergoing IC. Oral and stool microbiomes were characterized by 16S ribosomal RNA V4 sequencing using an Illumina MiSeq system. Microbial diversity and genera composition were associated with clinical outcomes. RESULTS: Baseline stool α-diversity was significantly lower in patients who developed infections during IC compared with those who did not (P = .047). Significant decreases in both oral and stool microbial α-diversity were observed over the course of IC, with a linear correlation between α-diversity change at the 2 sites (P = .02). Loss of both oral and stool α-diversity was associated significantly with the receipt of a carbapenem P < 0.001. Domination events by the majority of genera were transient (median duration, 1 sample), whereas the number of domination events by pathogenic genera increased significantly over the course of IC (P = .002). Moreover, patients who lost microbial diversity over the course of IC were significantly more likely to contract a microbiologically documented infection within the 90 days after IC neutrophil recovery (P = .04). CONCLUSIONS: The current data present the largest longitudinal analyses to date of oral and stool microbiomes in patients with AML and suggest that microbiome measurements could assist with the mitigation of infectious complications of AML therapy. Cancer 2016;122:2186-96. © 2016 American Cancer Society.

Characterization of the human gut microbiome during travelers' diarrhea.

Alterations in the gut microbiota are correlated with ailments such as obesity, inflammatory bowel disease, and diarrhea. Up to 60% of individuals traveling from industrialized to developing countries acquire a form of secretory diarrhea known as travelers' diarrhea (TD), and enterotoxigenic Escherichia coli (ETEC) and norovirus (NoV) are the leading causative pathogens. Presumably, TD alters the gut microbiome, however the effect of TD on gut communities has not been studied. We report the first analysis of bacterial gut populations associated with TD. We examined and compared the gut microbiomes of individuals who developed TD associated with ETEC, NoV, or mixed pathogens, and TD with no pathogen identified, to healthy travelers. We observed a signature dysbiotic gut microbiome profile of high Firmicutes:Bacteroidetes ratios in the travelers who developed diarrhea, regardless of etiologic agent or presence of a pathogen. There was no significant difference in α-diversity among travelers. The bacterial composition of the microbiota of the healthy travelers was similar to the diarrheal groups, however the ß-diversity of the healthy travelers was significantly different than any pathogen-associated TD group. Further comparison of the healthy traveler microbiota to those from healthy subjects who were part of the Human Microbiome Project also revealed a significantly higher Firmicutes:Bacteriodetes ratio in the healthy travelers and significantly different ß-diversity. Thus, the composition of the gut microbiome in healthy, diarrhea-free travelers has characteristics of a dysbiotic gut, suggesting that these alterations could be associated with factors such as travel.

Reduced transpiration response to precipitation pulses precedes mortality in a piñon-juniper woodland subject to prolonged drought.

Global climate change is predicted to alter the intensity and duration of droughts, but the effects of changing precipitation patterns on vegetation mortality are difficult to predict. Our objective was to determine whether prolonged drought or above-average precipitation altered the capacity to respond to the individual precipitation pulses that drive productivity and survival. We analyzed 5 yr of data from a rainfall manipulation experiment in piñon-juniper (Pinus edulis-Juniperus monosperma) woodland using mixed effects models of transpiration response to event size, antecedent soil moisture, and post-event vapor pressure deficit. Replicated treatments included irrigation, drought, ambient control and infrastructure control. Mortality was highest under drought, and the reduced post-pulse transpiration in the droughted trees that died was attributable to treatment effects beyond drier antecedent conditions and reduced event size. In particular, trees that died were nearly unresponsive to antecedent shallow soil moisture, suggesting reduced shallow absorbing root area. Irrigated trees showed an enhanced response to precipitation pulses. Prolonged drought initiates a downward spiral whereby trees are increasingly unable to utilize pulsed soil moisture. Thus, the additive effects of future, more frequent droughts may increase drought-related mortality.