A compositional mediation model for a binary outcome: Application to microbiome studies.

MOTIVATION: The delicate balance of the microbiome is implicated in our health and is shaped by external factors, such as diet and xenobiotics. Therefore, understanding the role of the microbiome in linking external factors and our health conditions is crucial to translate microbiome research into therapeutic and preventative applications. RESULTS: We introduced a sparse compositional mediation model for binary outcomes to estimate and test the mediation effects of the microbiome utilizing the compositional algebra defined in the simplex space and a linear zero-sum constraint on probit regression coefficients. For this model with the standard causal assumptions, we showed that both the causal direct and indirect effects are identifiable. We further developed a method for sensitivity analysis for the assumption of the no unmeasured confounding effects between the mediator and the outcome. We conducted extensive simulation studies to assess the performance of the proposed method and applied it to real microbiome data to study mediation effects of the microbiome on linking fat intake to overweight/obesity. AVAILABILITY AND IMPLEMENTATION: An R package can be downloaded from https://github.com/mbsohn/cmmb. SUPPLEMENTARY INFORMATION: Supplementary files are available at Bioinformatics online.

Predicting Treatment Response with Sensory Phenotyping in Post-Traumatic Neuropathic Pain.

OBJECTIVE: Currently available treatments for neuropathic pain are only modestly efficacious when assessed in randomized clinical trials and work for only some patients in the clinic. Induced-pain or gain-of-function phenotypes have been shown to predict response to analgesics (vs placebos) in patients with neuropathic pain. However, the predictive value of these phenotypes has never been studied in post-traumatic neuropathic pain. METHODS: Mixed-effects models for repeated measures were used to evaluate the efficacy of pregabalin vs placebo in subgroups with induced-pain phenotypes (i.e., hyperalgesia or allodynia) in data from a recent, multinational randomized clinical trial (N = 539) that identified phenotypic subgroups through the use of a structured clinical exam. RESULTS: The difference in mean pain score between the active and placebo groups (i.e., delta) after 15 weeks of treatment for the subgroup with hyperalgesia was -0.76 (P = 0.001), compared with 0.19 (P = 0.47) for the subgroup that did not have hyperalgesia. The treatment-by-phenotype interaction, which tests whether subgroups have statistically different treatment responses, was significant (P = 0.0067). The delta for the subgroup with allodynia was -0.31 (P = 0.22), compared with -0.30 (P = 0.22) for the subgroup that did not have allodynia (treatment-by-phenotype interaction P = 0.98). CONCLUSIONS: These data suggest that hyperalgesia, but not allodynia, predicts response to pregabalin in patients with chronic post-traumatic neuropathic pain. This study extends the growing data supporting the utility of induced-pain phenotypes to predict response to analgesics in post-traumatic neuropathic pain. Sensory phenotyping in large, multisite trials through the use of a structured clinical exam has the potential to accelerate the development of new analgesics and improve the generalizability of clinical trial results.

Measuring Functional Status in Huntington's Disease.

BACKGROUND: Neuropsychiatric and cognitive symptoms account for substantial morbidity in Huntington's disease (HD), but their impact on functional status may not be captured using the Total Functional Capacity (TFC) scale. The objective of this study was to assess the impact of motor, cognitive, and neuropsychiatric symptoms on functional status in persons with HD, comparing two instruments. METHODS: Multiple regression analyses assessed the relationship between neuropsychiatric, cognitive, and motor symptoms and functional status as measured using TFC and Adult Functional Adaptive Behavior (AFAB) scales. RESULTS: Greater burden of neuropsychiatric (P = 0.017), cognitive (P = 0.001), and motor (P = 0.001) symptoms was associated with greater impairments to functional status as measured by the AFAB scale. Only motor symptoms were associated with TFC scores (P = 0.002). The 3 symptom domains explained more of the variance in AFAB than TFC scores (P = 0.016). CONCLUSIONS: TFC may have limited applicability, particularly in early-stage HD patients, as a measure of functional status. The AFAB scale can be used in HD studies as a more holistic measure of functional status. © 2020 International Parkinson and Movement Disorder Society.

A robust approach for identifying differentially abundant features in metagenomic samples.

MOTIVATION: The analysis of differential abundance for features (e.g. species or genes) can provide us with a better understanding of microbial communities, thus increasing our comprehension and understanding of the behaviors of microbial communities. However, it could also mislead us about the characteristics of microbial communities if the abundances or counts of features on different scales are not properly normalized within and between communities, prior to the analysis of differential abundance. Normalization methods used in the differential analysis typically try to adjust counts on different scales to a common scale using the total sum, mean or median of representative features across all samples. These methods often yield undesirable results when the difference in total counts of differentially abundant features (DAFs) across different conditions is large. RESULTS: We develop a novel method, Ratio Approach for Identifying Differential Abundance (RAIDA), which utilizes the ratio between features in a modified zero-inflated lognormal model. RAIDA removes possible problems associated with counts on different scales within and between conditions. As a result, its performance is not affected by the amount of difference in total abundances of DAFs across different conditions. Through comprehensive simulation studies, the performance of our method is consistently powerful, and under some situations, RAIDA greatly surpasses other existing methods. We also apply RAIDA on real datasets of type II diabetes and find interesting results consistent with previous reports. AVAILABILITY AND IMPLEMENTATION: An R package for RAIDA can be accessed from http://cals.arizona.edu/%7Eanling/sbg/software.htm.

A two-stage statistical procedure for feature selection and comparison in functional analysis of metagenomes.

MOTIVATION: With the advance of new sequencing technologies producing massive short reads data, metagenomics is rapidly growing, especially in the fields of environmental biology and medical science. The metagenomic data are not only high dimensional with large number of features and limited number of samples but also complex with a large number of zeros and skewed distribution. Efficient computational and statistical tools are needed to deal with these unique characteristics of metagenomic sequencing data. In metagenomic studies, one main objective is to assess whether and how multiple microbial communities differ under various environmental conditions. RESULTS: We propose a two-stage statistical procedure for selecting informative features and identifying differentially abundant features between two or more groups of microbial communities. In the functional analysis of metagenomes, the features may refer to the pathways, subsystems, functional roles and so on. In the first stage of the proposed procedure, the informative features are selected using elastic net as reducing the dimension of metagenomic data. In the second stage, the differentially abundant features are detected using generalized linear models with a negative binomial distribution. Compared with other available methods, the proposed approach demonstrates better performance for most of the comprehensive simulation studies. The new method is also applied to two real metagenomic datasets related to human health. Our findings are consistent with those in previous reports. AVAILABILITY: R code and two example datasets are available at http://cals.arizona.edu/∼anling/software.htm. SUPPLEMENTARY INFORMATION: Supplementary file is available at Bioinformatics online.

Accurate genome relative abundance estimation for closely related species in a metagenomic sample.

BACKGROUND: Metagenomics has a great potential to discover previously unattainable information about microbial communities. An important prerequisite for such discoveries is to accurately estimate the composition of microbial communities. Most of prevalent homology-based approaches utilize solely the results of an alignment tool such as BLAST, limiting their estimation accuracy to high ranks of the taxonomy tree. RESULTS: We developed a new homology-based approach called Taxonomic Analysis by Elimination and Correction (TAEC), which utilizes the similarity in the genomic sequence in addition to the result of an alignment tool. The proposed method is comprehensively tested on various simulated benchmark datasets of diverse complexity of microbial structure. Compared with other available methods designed for estimating taxonomic composition at a relatively low taxonomic rank, TAEC demonstrates greater accuracy in quantification of genomes in a given microbial sample. We also applied TAEC on two real metagenomic datasets, oral cavity dataset and Crohn's disease dataset. Our results, while agreeing with previous findings at higher ranks of the taxonomy tree, provide accurate estimation of taxonomic compositions at the species/strain level, narrowing down which species/strains need more attention in the study of oral cavity and the Crohn's disease. CONCLUSIONS: By taking account of the similarity in the genomic sequence TAEC outperforms other available tools in estimating taxonomic composition at a very low rank, especially when closely related species/strains exist in a metagenomic sample.

Trajectories of physical well-being among adults with acute myeloid leukemia.

ABSTRACT: Patients with acute myeloid leukemia (AML) often undergo physical decline leading to negative outcomes. Identification of distinct trajectories may help guide clinical decision-making and supportive care interventions. We built group-based trajectory models (GBTM) to find trajectories of change in the Functional Assessment of Cancer Therapy Physical Well-Being (FACT-PWB) subscale (up to 5 time points over 0 to 200 days of follow-up) using data from adults with newly diagnosed AML in 4 supportive care studies. We also estimated the association of baseline characteristics (age, marital status, education, AML risk, baseline FACT-PWB, depression, and anxiety) with group membership. Among 343 patients with ≥2 FACT-PWB scores, mean age was 69.6 years (standard deviation, 12.1); most had intermediate-risk AML (n = 178 [51.8%]), received intensive treatment (n = 244 [71.1%]), and died during follow-up (n = 199 [58.0%]). The GBTM with 4 distinct trajectories showed the best fit. The largest group (n = 153 [45.0%]) showed slight improvement, whereas the smallest (n = 8 [2.4%]) experienced early decline with later improvement. Baseline FACT-PWB was the only characteristic statistically significantly associated with group membership. Adults with AML show distinct trajectories of physical well-being, and many experience some decline. Exploring trajectories of self-reported and objective physical function may inform decision-making and interventions. These trials were registered at www.ClinicalTrials.gov as #NCT02975869, #NCT03310918, and #NCT03372291.

Affective Symptoms in Pregnancy are Associated with the Vaginal Microbiome.

Composition of the vaginal microbiome in pregnancy is associated with adverse maternal, obstetric, and child health outcomes. Identifying the sources of individual differences in the vaginal microbiome is therefore of considerable clinical and public health interest. The current study tested the hypothesis that vaginal microbiome composition during pregnancy is associated with an individual's experience of affective symptoms and stress exposure. Data were based on a prospective longitudinal study of a diverse and medically healthy community sample of 275 mother-infant pairs. Affective symptoms and stress exposure and select measures of associated biomarkers (diurnal salivary cortisol, serum measures of sex hormones) were collected at each trimester; self-report, clinical, and medical records were used to collect detailed data on socio-demographic factors and health behavior, including diet and sleep. Vaginal microbiome samples were collected in the third trimester (34-40 weeks) and characterized by 16S rRNA sequencing. Identified taxa were clustered into three community state types (CST1-3) based on dissimilarity of vaginal microbiota composition. Results indicate that depressive symptoms during pregnancy were reliably associated with individual taxa and CST3 in the third trimester. Prediction of functional potential from 16S taxonomy revealed a differential abundance of metabolic pathways in CST1-3 and individual taxa, including biosynthetic pathways for the neuroactive metabolites, serotonin and dopamine. With the exception of bioavailable testosterone, no significant associations were found between symptoms- and stress-related biomarkers and CSTs. Our results provide further evidence of how prenatal psychological distress during pregnancy alters the maternal-fetal microbiome ecosystem that may be important for understanding maternal and child health outcomes.

Targeting Gut Microbiome With Prebiotic in Patients With CKD: The TarGut-CKD Study.

Introduction: Disruption of gut microbiota underpins some of the metabolic alterations observed in chronic kidney disease (CKD). Methods: In a nonrandomized, open-label, 3-phase pilot trial, with repeated measures within each phase, we examined the efficacy of oligofructose-enriched inulin (p-inulin) in changing the gut microbiome and their metabolic products in 15 patients with CKD. The stability of microbiome and metabolome was studied during the pretreatment phase (8 weeks), a p-inulin treatment phase (12 weeks), and a post treatment phase (8 weeks) of the study. Results: Study participants completed 373 of the 420 expected study visits (88.8%). Adherence to p-inulin was 83.4%. 16S rRNA sequencing was performed in 368 stool samples. A total of 1085 stool, urine, and plasma samples were subjected to untargeted metabolomic studies. p-inulin administration altered the composition of the gut microbiota significantly, with an increase in abundance of Bifidobacterium and Anaerostipes. Intersubject variations in microbiome and metabolome were larger than intrasubject variation, indicating the stability of the gut microbiome within each phase of the study. Overall metabolite compositions assessed by beta diversity in urine and stool metabolic profiles were significantly different across study phases. Several specific metabolites in stool, urine, and plasma were significant at false discovery rate (FDR) ≤ 0.1 over phase. Specifically, there was significant enrichment in microbial metabolites derived from saccharolysis. Conclusion: Results from our study highlight the stability of the gut microbiome and the expansive effect of p-inulin on microbiome and host cometabolism in patients with CKD. Findings from this study will enable rigorous design of microbiome-based intervention trials.

Associations of interleukin-6 with functional trajectories in older adults with cancer: Findings from the Health, Aging, and Body Composition Study.

BACKGROUND: Elevated markers of inflammation, such as interleukin-6 (IL-6), are associated with aging, cancer, and functional decline. We assessed the association of pre-diagnosis IL-6 levels with post-diagnosis functional trajectories among older adults with cancer. Black and White participants experience different social structures, therefore we sought to understand whether these associations differ between Black and White participants. METHODS: We conducted secondary analysis of the Health Aging, Body, and Composition (ABC) prospective longitudinal cohort study. Participants were recruited from 4/1997 to 6/1998. We included 179 participants with a new cancer diagnosis and IL-6 level measured within 2 years before diagnosis. Primary endpoint was functional measures (self-reported ability to walk 1/4, 20-meter gait speed). Nonparametric longitudinal models were used to cluster the trajectories; multinomial and logistic regressions to model associations. FINDINGS: Mean age was 74 (SD 2.9); 36 % identified as Black. For self-reported functional status, we identified 3 clusters: high stable, decline, low stable. For gait speed, we identified 2 clusters: resilient, decline. The relationship between cluster trajectory and IL-6 was different between Black and White participants (p for interaction<0.05). For gait speed, among White participants, a greater log IL-6 level was associated with greater odds of being in the decline vs. resilient cluster [Adjusted Odds Ratio (AOR): 4.31, 95 % CI: 1.43, 17.46]. Among Black participants, a greater log IL-6 levels were associated with lower odds of being in the decline vs. resilient cluster (AOR: 0.49, 95 % CI: 0.10, 2.08). Directionality was similar for self-reported ability to walk » mile (high stable vs. low stable). Among White participants, a higher log IL-6 level was associated numerically with greater odds of being in the low stable vs. high stable cluster (AOR: 1.99, 95 % CI: 0.82, 4.85). Among Black participants, a higher log IL-6 level was associated numerically with lower odds of being in the low stable cluster vs. high stable cluster (AOR: 0.78, 95 % CI: 0.30, 2.00). INTERPRETATION: The association between IL-6 levels and functional trajectories of older adults differed by race. Future analyses exploring stressors faces by other minoritized racial backgrounds are needed to determine the association between IL-6 and functional trajectories. PANEL: RESEARCH IN CONTEXT: Evidence before this study: Previous research has shown that aging is the greatest risk factor for cancer and older adults with cancer experience a higher burden of comorbidities, increasing their risk of functional decline. Race has also been shown to be associated with increased risk for functional decline. Black individuals are exposed to more chronic negative social determinants, compared to White individuals. Previous work has shown that chronic exposure to negative social determinants leads to elevated levels of inflammatory markers, such as IL-6, but studies investigating the relationship between inflammatory markers and functional decline are limited. Added value of this study: Authors of this study sought to understand the association between pre-diagnosis IL-6 levels and functional trajectories post-diagnosis in older adults with cancer, and whether these associations differed between Black and White participants with cancer. Authors decided to utilize the data from the Health, Aging and Body Composition (Health ABC) Study. The Health ACB study was a prospective longitudinal cohort study that has a high representation of Black older adults and collected inflammatory cytokines and physical function data over time. Implications of all available evidence: This work adds to the literature by providing an opportunity to study the difference in the relationships between IL-6 levels and functional trajectories between older Black and White participants with cancer. Identifying factors associated with functional decline and its trajectories may inform treatment decision making and guide development of supportive care interventions to prevent functional decline. Additionally, given the disparities in clinical outcomes for Black individuals, a better understanding of the difference in functional decline based on race will allow more equitable care to be distributed.

Exercise and epigenetic ages in older adults with myeloid malignancies.

BACKGROUND: Older adults with myeloid malignancies are susceptible to treatment-related toxicities. Accelerated DNAm age, or the difference between DNA methylation (DNAm) age and chronological age, may be used as a biomarker of biological age to predict individuals at risk. In addition, cancer treatment can also lead to accelerated DNAm age. Exercise is a promising intervention to reduce or prevent functional, psychological, and cognitive impairments in older patients with myeloid malignancies, yet there is little evidence of the effects of exercise on DNAm age. We explored (1) the associations of accelerated DNAm age with physical, psychological, and cognitive functions at baseline; (2) changes in DNAm age from baseline to post-intervention; and (3) the associations of changes in accelerated DNAm age with changes in functions from baseline to post-intervention. METHODS: We enrolled older patients with myeloid malignancies to a single-arm pilot study testing a mobile health (mHealth) exercise intervention that combines an exercise program (EXCAP©®) with a mobile application over 2 cycles of chemotherapy (8-12 weeks). Patients completed measures of physical, psychological, and cognitive functions and provided blood samples for analyses of DNAm age at baseline and post-intervention. Paired t-tests or Wilcoxon signed rank tests assessed changes in DNAm ages, and Spearman's correlation assessed the relationships between accelerated ages and functions. RESULTS: We included 20 patients (mean age: 72 years, range 62-80). Accelerated GrimAge, accelerated PhenoAge, and DunedinPACE were stable from baseline to post-intervention. At baseline, DunedinPACE was correlated with worse grip strength (r = -0.41, p = 0.08). From baseline to post-intervention, decreases in accelerated GrimAge (r = -0.50, p = 0.02), accelerated PhenoAge (r = - 0.39, p = 0.09), and DunedinPace (r = - 0.43, p = 0.06) were correlated with increases in distance walked on 6-min walk test. Decreases in accelerated GrimAge (r = - 0.49, p = 0.03), accelerated PhenoAge (r = - 0.40, p = 0.08), and DunedinPace (r = - 0.41, p = 0.07) were correlated with increases in in grip strength. CONCLUSIONS: Among older adults with myeloid malignancies receiving chemotherapy, GrimAge and PhenoAge on average are stable after a mHealth exercise intervention. Decreases in accelerated GrimAge, accelerated PhenoAge, and DunedinPACE over 8-12 weeks of exercise were correlated with increased physical performance. Future trials assessing the effects of exercise on treatment-related toxicities should evaluate DNAm age. Trial registration Clinicaltrials.gov identifier: NCT04981821.

Protocol for a pilot randomized controlled trial of a mobile health exercise intervention for older patients with myeloid neoplasms (GO-EXCAP 2).

INTRODUCTION: We have shown the Exercise for Cancer Patients (EXCAP©®) exercise program improved physical function and symptoms and reduced inflammatory markers in patients with cancer. However, adherence to exercise was lower in older adults compared to their younger counterparts. We then leveraged a mobile app to deliver EXCAP©® and adapted the intervention [Geriatric-Oncology (GO)-EXCAP] for older patients with myeloid neoplasms. In this pilot randomized trial, the primary goal is to determine effect sizes. We propose to assess the preliminary efficacy of GO-EXCAP compared to a behavioral placebo control on physical function, patient-reported outcomes (fatigue, mood, and quality of life), and inflammatory markers in 100 patients aged ≥60 years with myeloid neoplasms receiving outpatient chemotherapy. METHODS: GO-EXCAP consists of the EXCAP©® exercise prescription (daily home-based progressive aerobic walking and resistance exercises with rated perceived exercise of 5-8), EXCAP©® kit (i.e., activity tracker, resistance bands, print manual, bag), a mobile app, and an in-person or virtual session with the exercise physiologist to deliver exercise prescription. The intervention will last for three cycles of chemotherapy (approximately 12 weeks). The primary outcome measure will be physical function (Short Physical Performance Battery). Secondary outcome measures include fatigue (Brief Fatigue Inventory), mood (Center for Epidemiologic Studies Depression Scale), and quality of life (Functional Assessment of Cancer Therapy-Leukemia). Exploratory outcome measures include inflammatory markers. DISCUSSION: Older adults with myeloid neoplasms receiving outpatient chemotherapy serve as an ideal model for studying an individually tailored mobile health exercise intervention in vulnerable older patients receiving cancer treatments to prevent physical function decline and improve symptoms.

Inflammation, Attention, and Processing Speed in Patients With Breast Cancer Before and After Chemotherapy.

BACKGROUND: Inflammation may contribute to cognitive difficulties in patients with breast cancer. We tested 2 hypotheses: inflammation is elevated in patients with breast cancer vs noncancer control participants and inflammation in patients is associated with worse attention and processing speed over the course of chemotherapy. METHODS: Serum cytokines (interleukin [IL]-4, 6, 8, 10; tumor necrosis factor [TNF]-α) and soluble receptors [sTNFRI, II]) were measured in 519 females with breast cancer before and after chemotherapy and 338 females without cancer serving as control participants. Attention and processing speed were measured by Rapid Visual Processing (RVP), Backward Counting (BCT), and Trail Making-A (TMT-A) tests. Linear regression models examined patient vs control cytokines and receptor levels, adjusting for covariates. Linear regression models also examined relationships between patient cytokines and receptor levels and test performance, adjusting for age, body mass index, anxiety, depression, cognitive reserve, and chemotherapy duration. Statistical tests were 2-sided (α = .05). RESULTS: sTNFRI and sTNFRII increased over time in patients relative to controls, whereas IL-4, IL-6, and IL-10 decreased. Prechemotherapy, higher IL-8 associated with worse BCT (ß = 0.610, SE = 0.241, P = .01); higher IL-4 (ß = -1.098, SE = 0.516, P = .03) and IL-10 (ß = -0.835, SE = 0.414, P = .04) associated with better TMT-A. Postchemotherapy, higher IL-8 (ß = 0.841, SE = 0.260, P = .001), sTNFRI (ß = 6.638, SE = 2.208, P = .003), and sTNFRII (ß = 0.913, SE = 0.455, P = .045) associated with worse BCT; higher sTNFRII also associated with worse RVP (ß = -1.316, SE = 0.587, P = .03). At prechemotherapy, higher IL-4 predicted RVP improvement over time (ß = 0.820, SE = 0.336, P = .02); higher sTNFRI predicted worse BCT over time (ß = 5.566, SE = 2.367, P = .02). Longitudinally, increases in IL-4 associated with BCT improvement (ß = -0.564, SE = 0.253, P = .03). CONCLUSIONS: Generally, worse attention and processing speed were associated with higher inflammatory cytokines and receptors and lower anti-inflammatory cytokines in patients; future confirmatory studies are needed.

Machine Learning Approach Identified Multi-Platform Factors for Caries Prediction in Child-Mother Dyads.

Untreated tooth decays affect nearly one third of the world and is the most prevalent disease burden among children. The disease progression of tooth decay is multifactorial and involves a prolonged decrease in pH, resulting in the demineralization of tooth surfaces. Bacterial species that are capable of fermenting carbohydrates contribute to the demineralization process by the production of organic acids. The combined use of machine learning and 16s rRNA sequencing offers the potential to predict tooth decay by identifying the bacterial community that is present in an individual's oral cavity. A few recent studies have demonstrated machine learning predictive modeling using 16s rRNA sequencing of oral samples, but they lack consideration of the multifactorial nature of tooth decay, as well as the role of fungal species within their models. Here, the oral microbiome of mother-child dyads (both healthy and caries-active) was used in combination with demographic-environmental factors and relevant fungal information to create a multifactorial machine learning model based on the LASSO-penalized logistic regression. For the children, not only were several bacterial species found to be caries-associated (Prevotella histicola, Streptococcus mutans, and Rothia muciloginosa) but also Candida detection and lower toothbrushing frequency were also caries-associated. Mothers enrolled in this study had a higher detection of S. mutans and Candida and a higher plaque index. This proof-of-concept study demonstrates the significant impact machine learning could have in prevention and diagnostic advancements for tooth decay, as well as the importance of considering fungal and demographic-environmental factors.

Genomics of Staphylococcus aureus ocular isolates.

Staphylococcus aureus is a major cause of ocular infections, often resulting in devastating vision loss. Despite the significant morbidity associated with these infections, little is yet known regarding the specific strain types that may have a predilection for ocular tissues nor the set of virulence factors that drive its pathogenicity in this specific biological niche. Whole genome sequencing (WGS) can provide valuable insight in this regard by providing a prospective, comprehensive assessment of the strain types and virulence factors driving disease among specific subsets of clinical isolates. As such, a set of 163-member S. aureus ocular clinical strains were sequenced and assessed for both common strain types (multilocus sequence type (MLST), spa, agr) associated with ocular infections as well as the presence/absence of 235 known virulence factors in a high throughput manner. This ocular strain set was then directly compared to a fully sequenced 116-member non-ocular S. aureus strain set curated from NCBI in order to identify key differences between ocular and non-ocular S. aureus isolates. The most common sequence types found among ocular S. aureus isolates were ST5, ST8 and ST30, generally reflecting circulating non-ocular pathogenic S. aureus strains. However, importantly, ocular isolates were found to be significantly enriched for a set of enterotoxins, suggesting a potential role for this class of virulence factors in promoting ocular disease. Further genomic analysis revealed that these enterotoxins are located on mobile pathogenicity islands, thus horizontal gene transfer may promote the acquisition of enterotoxins, potentially amplifying S. aureus virulence in ocular tissues.

The Microbiome and p-Inulin in Hemodialysis: A Feasibility Study.

Background: The intestinal microbiome is an appealing target for interventions in ESKD because of its likely contribution to uremic toxicity. Before conducting clinical trials of microbiome-altering treatments, it is necessary to understand the within-person and between-person variability in the composition and function of the gut microbiome in patients with ESKD. Methods: We conducted a multicenter, nonrandomized, crossover feasibility study of patients on maintenance hemodialysis consisting of three phases: pretreatment (8 weeks); treatment, during which the prebiotic, p-inulin, was administered at a dosage of 8 g twice daily (12 weeks); and post-treatment (8 weeks). Stool samples were collected 1-2 times per week and blood was collected weekly for 28 weeks. The gut microbiome was characterized using 16S ribosomal-RNA sequencing and metabolomic profiling. Results: A total of 11 of the 13 participants completed the 28-week study. Interparticipant variability was greater than intraparticipant variability for microbiome composition (P<0.001 by UniFrac distances) and metabolomic composition (P<0.001 by Euclidean distances). p-Inulin was well tolerated by 12 of 13 participants. Adherence to the frequent sample collection and self-aliquoting of stool samples were both 96%. A change in the microbiome composition from pretreatment to post-treatment was evident by the overall shifts in weighted UniFrac distances (P=0.004) and a progressive decrease in prevalence of high intraclass correlations, indicating an increase in intraparticipant microbiome diversity during and after p-inulin treatment. An effect of p-inulin on the metabolomic profile was not evident. Conclusions: The intraparticipant stability of the gut microbiome under no-treatment conditions, the tolerability of p-inulin, the signals of increased diversity of the microbiome with p-inulin treatment, and the willingness of participants to provide stool samples all support the feasibility of a larger trial to investigate interventions targeting the gut microbiome in patients with ESKD. Whether or not p-inulin has sufficient efficacy as an intervention requires evaluation in larger studies. Clinical Trial registry name and registration number: Gut Microbiome and p-Inulin in Hemodialysis, NCT02572882.

Efficacy of a Novel Ophthalmic Antimicrobial Drug Combination Toward a Large Panel of Staphylococcus aureus Clinical Ocular Isolates From Around the World.

PURPOSE: Staphylococcus aureus is a leading cause of keratitis requiring urgent antimicrobial treatment. However, rising antibiotic resistance has rendered current ophthalmic antibiotics increasingly ineffective. First, a diverse, ocular S. aureus strain set was evaluated for resistance to 6 commonly used ophthalmic antibiotics. Next, a recently discovered antimicrobial drug combination containing polymyxin B/trimethoprim (PT) + rifampin that displayed impressive efficacy toward S. aureus in both in vitro and in vivo studies was evaluated as a potential novel keratitis therapeutic through testing this combination's efficacy against the clinical strain set. METHODS: A total of 163 S. aureus isolates were collected either commercially or from the Flaum Eye Institute, University of Rochester. The minimum inhibitory concentrations of moxifloxacin, levofloxacin, vancomycin, erythromycin, tobramycin, rifampin, and PT were determined for the entire strain set to establish the incidence of resistance to current treatment options among a contemporary clinical isolate set and compared with the performance of PT + rifampin. RESULTS: Among all 163 isolates tested, high rates of antibiotic resistance were found toward erythromycin (69% resistance), moxifloxacin (33%), levofloxacin (40%), and tobramycin (17%). Conversely, the entire strain set, including multidrug resistant isolates, was sensitive to PT + rifampin, demonstrating the potency of this combination. CONCLUSIONS: We established that antibiotic resistance is pervasive among clinical S. aureus isolates, underscoring the concern for the effectiveness of current ophthalmic antibiotics. The drug combination of PT + rifampin, however, eradicated 100% of isolates tested, demonstrating the ability to overcome existing circulating resistance factors, and as such, might represent a promising therapeutic for S. aureus keratitis.

Upper Respiratory Dysbiosis with a Facultative-dominated Ecotype in Advanced Lung Disease and Dynamic Change after Lung Transplant.

Rationale: The oropharyngeal microbiome is a primary source of lung microbiota, contributes to lower respiratory infection, and is also a driver of oral health.Objectives: We sought to understand oropharyngeal microbial communities in advanced lung disease, community dynamics after lung transplantation, and ecological features of dysbiosis.Methods: Oropharyngeal wash samples were obtained from individuals with end-stage disease awaiting transplantation (n = 22) and longitudinally from individuals at 6 weeks, 3 months, and 6 months after transplantation (n = 33), along with healthy control subjects (n = 14). Bacterial 16S and fungal internal transcribed spacer rRNA regions were deep-sequenced, and bacterial community respiratory patterns were imputed from taxonomic composition.Results: Healthy subjects' oropharyngeal microbiomes showed a gradient of community types reflecting relative enrichment of strictly anaerobic, aerobic, or facultative anaerobic bacteria. Patients with end-stage lung disease showed severe dysbiosis by both taxonomic composition and respiration phenotypes, with reduced richness and diversity, increased facultative and decreased aerobic bacteria, and absence of communities characterized by obligate aerobes. In patients at 6 weeks and 3 months post-transplant, richness and diversity were intermediate between healthy and pretransplant subjects, with near-normal distribution of community types. However, by 6 months post-transplant, oropharyngeal wash resembled the low-diversity facultative-dominated profile of pretransplant subjects. Community ecotype correlated with Candida abundance.Conclusions: End-stage lung disease is associated with marked upper respiratory tract dysbiosis involving both community structure and respiratory metabolism profiles of constituent bacteria. Dynamic changes occur after lung transplantation, with partial normalization early but later appearance of severe dysbiosis similar to pretransplant patients. Aberrant oropharyngeal communities may predispose to abnormal lung microbiota and infection risk both in advanced lung disease and after transplantation.

Molecular analysis of the endobronchial stent microbial biofilm reveals bacterial communities that associate with stent material and frequent fungal constituents.

Endobronchial stents are increasingly used to treat airway complications in multiple conditions including lung transplantation but little is known about the biofilms that form on these devices. We applied deep sequencing to profile luminal biofilms of 46 endobronchial stents removed from 20 subjects primarily with lung transplantation-associated airway compromise. Microbial communities were analyzed by bacterial 16S rRNA and fungal ITS marker gene sequencing. Corynebacterium was the most common bacterial taxa across biofilm communities. Clustering analysis revealed three bacterial biofilm types: one low diversity and dominated by Corynebacterium; another was polymicrobial and characterized by Staphylococcus; and the third was polymicrobial and associated with Pseudomonas, Streptococcus, and Prevotella. Biofilm type was significantly correlated with stent material: covered metal with the Staphylococcus-type biofilm, silicone with the Corynebacterium-dominated biofilm, and uncovered metal with the polymicrobial biofilm. Subjects with sequential stents had frequent transitions between community types. Fungal analysis found Candida was most prevalent, Aspergillus was common and highly enriched in two of three stents associated with airway anastomotic dehiscence, and fungal taxa not typically considered pathogens were highly enriched in some stents. Thus, molecular analysis revealed a complex and dynamic endobronchial stent biofilm with three bacterial types that associate with stent material, a central role for Corynebacterium, and that both expected and unexpected fungi inhabit this unique niche. The current work provides a foundation for studies to investigate the relationship between stent biofilm composition and clinical outcomes, mechanisms of biofilm establishment, and strategies for improved stent technology and use in airway compromise.