Mucus-degrading Bacteroides link carbapenems to aggravated graft-versus-host disease.

The intestinal microbiota is an important modulator of graft-versus-host disease (GVHD), which often complicates allogeneic hematopoietic stem cell transplantation (allo-HSCT). Broad-spectrum antibiotics such as carbapenems increase the risk for intestinal GVHD, but mechanisms are not well understood. In this study, we found that treatment with meropenem, a commonly used carbapenem, aggravates colonic GVHD in mice via the expansion of Bacteroides thetaiotaomicron (BT). BT has a broad ability to degrade dietary polysaccharides and host mucin glycans. BT in meropenem-treated allogeneic mice demonstrated upregulated expression of enzymes involved in the degradation of mucin glycans. These mice also had thinning of the colonic mucus layer and decreased levels of xylose in colonic luminal contents. Interestingly, oral xylose supplementation significantly prevented thinning of the colonic mucus layer in meropenem-treated mice. Specific nutritional supplementation strategies, including xylose supplementation, may combat antibiotic-mediated microbiome injury to reduce the risk for intestinal GVHD in allo-HSCT patients.

Identification of bacteria-derived HLA-bound peptides in melanoma.

A variety of species of bacteria are known to colonize human tumours1-11, proliferate within them and modulate immune function, which ultimately affects the survival of patients with cancer and their responses to treatment12-14. However, it is not known whether antigens derived from intracellular bacteria are presented by the human leukocyte antigen class I and II (HLA-I and HLA-II, respectively) molecules of tumour cells, or whether such antigens elicit a tumour-infiltrating T cell immune response. Here we used 16S rRNA gene sequencing and HLA peptidomics to identify a peptide repertoire derived from intracellular bacteria that was presented on HLA-I and HLA-II molecules in melanoma tumours. Our analysis of 17 melanoma metastases (derived from 9 patients) revealed 248 and 35 unique HLA-I and HLA-II peptides, respectively, that were derived from 41 species of bacteria. We identified recurrent bacterial peptides in tumours from different patients, as well as in different tumours from the same patient. Our study reveals that peptides derived from intracellular bacteria can be presented by tumour cells and elicit immune reactivity, and thus provides insight into a mechanism by which bacteria influence activation of the immune system and responses to therapy.

Participant Diversity in United States Randomized Controlled Trials of Antibacterials for Staphylococcus aureus Infections, 2000-2021.

BACKGROUND: Equitable representation of members from historically marginalized groups is important in clinical trials, which inform standards of care. The goal of this study was to characterize the demographics and proportional subgroup reporting and representation of participants enrolled in randomized controlled trials (RCTs) of antibacterials used to treat Staphylococcus aureus infections. METHODS: We examined randomized controlled registrational and strategy trials published from 2000 to 2021 to determine the sex, race, and ethnicity of participants. Participant to incidence ratios (PIRs) were calculated by dividing the percentage of study participants in each demographic group by the percentage of the disease population in each group. Underrepresentation was defined as a PIR < 0.8. RESULTS: Of the 87 included studies, 82 (94.2%) reported participant sex, 69 (79.3%) reported participant race, and 20 (23.0%) included ethnicity data. Only 17 (19.5%) studies enrolled American Indian/Alaskan Native participants. Median PIRs indicated that Asian and Black participants were underrepresented in RCTs compared with the incidence of methicillin-resistant S. aureus infections in these subgroups. Underrepresentation of Black participants was associated with a larger study size, international sites, industry sponsorship, and phase 2/3 trials compared with phase 4 trials (P < .05 for each). Black participants had more than 4 times the odds of being underrepresented in phase 2/3 trials compared with phase 4 trials (odds ratio, 4.57; 95% confidence interval: 1.14-18.3). CONCLUSIONS: Standardized reporting methods for race and ethnicity and efforts to increase recruitment of marginalized groups would help ensure equity, rigor, and generalizability in RCTs of antibacterial agents and reduce health inequities.

Aggressive LDL-C Lowering and the Brain: Impact on Risk for Dementia and Hemorrhagic Stroke: A Scientific Statement From the American Heart Association.

The objective of this scientific statement is to evaluate contemporary evidence that either supports or refutes the conclusion that aggressive low-density lipoprotein cholesterol lowering or lipid lowering exerts toxic effects on the brain, leading to cognitive impairment or dementia or hemorrhagic stroke. The writing group used literature reviews, references to published clinical and epidemiology studies, clinical and public health guidelines, authoritative statements, and expert opinion to summarize existing evidence and to identify gaps in current knowledge. Although some retrospective, case control, and prospective longitudinal studies suggest that statins and low-density lipoprotein cholesterol lowering are associated with cognitive impairment or dementia, the preponderance of observational studies and data from randomized trials do not support this conclusion. The risk of a hemorrhagic stroke associated with statin therapy in patients without a history of cerebrovascular disease is nonsignificant, and achieving very low levels of low-density lipoprotein cholesterol does not increase that risk. Data reflecting the risk of hemorrhagic stroke with lipid-lowering treatment among patients with a history of hemorrhagic stroke are not robust and require additional focused study.

Prognostic Significance of Nonobstructive Left Main Coronary Artery Disease in Patients With and Without Diabetes: Long-Term Outcomes From the CONFIRM Registry.

BACKGROUND: Prognostic significance of non-obstructive left main (LM) disease was recently reported. However, the influence of diabetes mellitus (DM) on event rates in patients with and without non-obstructive LM disease is not well-known. METHODS: We evaluated 27,252 patients undergoing coronary computed tomographic angiography from the COroNary CT Angiography Evaluation For Clinical Outcomes: An InteRnational Multicenter (CONFIRM) Registry. Cumulative long-term incidence of all-cause mortality (ACM) was assessed between DM and non-DM patients by normal or non-obstructive LM disease (1-49% stenosis). RESULTS: The mean age of the study population was 57.6±12.6 years. Of the 27,252 patients, 4,434 (16%) patients had DM. A total of 899 (3%) deaths occurred during the follow-up of 3.6±1.9. years. Compared to patients with normal LM, those with non-obstructive LM had more pronounced overall coronary atherosclerosis and more cardiovascular risk factors. After clinical risk factors, segment involvement score, and stenosis severity adjustment, compared to patients without DM and normal LM, patients with DM were associated with increased ACM regardless of normal (HR 1.48, 95% CI 1.22-1.78, p<0.001) or non-obstructive LM (HR 1.46, 95% CI 1.04-2.04, p=0.029), while nonobstructive LM disease was not associated with increased ACM in patients without DM (HR 0.85, 95% CI 0.67-1.07, p=0.165) and there was no significant interaction between DM and LM status (HR 1.03, 95% CI 0.69-1.54, p=0.879). CONCLUSION: From the CONFIRM registry, we demonstrated that DM was associated with increased ACM. However, the presence of non-obstructive LM was not an independent risk marker of ACM, and there was no significant interaction between DM and non-obstructive LM disease for ACM.

Alterations of the Oral Microbiome and Cumulative Carbapenem Exposure Are Associated With Stenotrophomonas maltophilia Infection in Patients With Acute Myeloid Leukemia Receiving Chemotherapy.

BACKGROUND: Stenotrophomonas maltophilia is increasingly common in patients with acute myeloid leukemia (AML). Little is known about factors that drive S. maltophilia infection. We evaluated the microbiome and cumulative antibiotic use as predictors of S. maltophilia infection in AML patients receiving remission induction chemotherapy (RIC). METHODS: Subanalysis of a prospective, observational cohort of patients with AML receiving RIC between September 2013 and August 2015 was performed. Fecal and oral microbiome samples collected from initiation of RIC until neutrophil recovery were assessed for the relative abundance of Stenotrophomonas via 16S rRNA gene quantitation. The primary outcome, microbiologically proven S. maltophilia infection, was analyzed using a time-varying Cox proportional hazards model. RESULTS: Of 90 included patients, 8 (9%) developed S. maltophilia infection (pneumonia, n = 6; skin-soft tissue, n = 2); 4/8 (50%) patients were bacteremic; and 7/8 (88%) patients with S. maltophilia infection had detectable levels of Stenotrophomonas vs 22/82 (27%) without infection (P < .01). An oral Stenotrophomonas relative abundance of 36% predicted infection (sensitivity, 96%; specificity, 93%). No association of S. maltophilia infection with fecal relative abundance was found. Cumulative meropenem exposure was associated with increased infection risk (hazard ratio, 1.17; 95% confidence interval, 1.01-1.35; P = .03). CONCLUSIONS: Here, we identify the oral microbiome as a potential source for S. maltophilia infection and highlight cumulative carbapenem use as a risk factor for S. maltophilia in leukemia patients. These data suggest that real-time monitoring of the oral cavity might identify patients at risk for S. maltophilia infection.

IS26-mediated amplification of blaOXA-1 and blaCTX-M-15 with concurrent outer membrane porin disruption associated with de novo carbapenem resistance in a recurrent bacteraemia cohort.

BACKGROUND: Approximately half of clinical carbapenem-resistant Enterobacterales (CRE) isolates lack carbapenem-hydrolysing enzymes and develop carbapenem resistance through alternative mechanisms. OBJECTIVES: To elucidate development of carbapenem resistance mechanisms from clonal, recurrent ESBL-positive Enterobacterales (ESBL-E) bacteraemia isolates in a vulnerable patient population. METHODS: This study investigated a cohort of ESBL-E bacteraemia cases in Houston, TX, USA. Oxford Nanopore Technologies long-read and Illumina short-read sequencing data were used for comparative genomic analysis. Serial passaging experiments were performed on a set of clinical ST131 Escherichia coli isolates to recapitulate in vivo observations. Quantitative PCR (qPCR) and qRT-PCR were used to determine copy number and transcript levels of ß-lactamase genes, respectively. RESULTS: Non-carbapenemase-producing CRE (non-CP-CRE) clinical isolates emerged from an ESBL-E background through a concurrence of primarily IS26-mediated amplifications of blaOXA-1 and blaCTX-M-1 group genes coupled with porin inactivation. The discrete, modular translocatable units (TUs) that carried and amplified ß-lactamase genes mobilized intracellularly from a chromosomal, IS26-bound transposon and inserted within porin genes, thereby increasing ß-lactamase gene copy number and inactivating porins concurrently. The carbapenem resistance phenotype and TU-mediated ß-lactamase gene amplification were recapitulated by passaging a clinical ESBL-E isolate in the presence of ertapenem. Clinical non-CP-CRE isolates had stable carbapenem resistance phenotypes in the absence of ertapenem exposure. CONCLUSIONS: These data demonstrate IS26-mediated mechanisms underlying ß-lactamase gene amplification with concurrent outer membrane porin disruption driving emergence of clinical non-CP-CRE. Furthermore, these amplifications were stable in the absence of antimicrobial pressure. Long-read sequencing can be utilized to identify unique mobile genetic element mechanisms that drive antimicrobial resistance.

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA). METHODS AND RESULTS: The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features. CONCLUSION: A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.

Compositional zero-inflated network estimation for microbiome data.

BACKGROUND: The estimation of microbial networks can provide important insight into the ecological relationships among the organisms that comprise the microbiome. However, there are a number of critical statistical challenges in the inference of such networks from high-throughput data. Since the abundances in each sample are constrained to have a fixed sum and there is incomplete overlap in microbial populations across subjects, the data are both compositional and zero-inflated. RESULTS: We propose the COmpositional Zero-Inflated Network Estimation (COZINE) method for inference of microbial networks which addresses these critical aspects of the data while maintaining computational scalability. COZINE relies on the multivariate Hurdle model to infer a sparse set of conditional dependencies which reflect not only relationships among the continuous values, but also among binary indicators of presence or absence and between the binary and continuous representations of the data. Our simulation results show that the proposed method is better able to capture various types of microbial relationships than existing approaches. We demonstrate the utility of the method with an application to understanding the oral microbiome network in a cohort of leukemic patients. CONCLUSIONS: Our proposed method addresses important challenges in microbiome network estimation, and can be effectively applied to discover various types of dependence relationships in microbial communities. The procedure we have developed, which we refer to as COZINE, is available online at https://github.com/MinJinHa/COZINE .

Gut Microbiome Signatures Are Predictive of Infectious Risk Following Induction Therapy for Acute Myeloid Leukemia.

BACKGROUND: The majority of studies that provide insights into the influence of the microbiome on the health of hematologic malignancy patients have concentrated on the transplant setting. Here, we sought to assess the predictive capacity of the gastrointestinal microbiome and its relationship to infectious outcomes in patients with acute myeloid leukemia (AML). METHODS: 16s rRNA-based analysis was performed on oral swabs and stool samples obtained biweekly from baseline until neutrophil recovery following induction chemotherapy (IC) in 97 AML patients. Microbiome characteristics were correlated with clinical outcomes both during and after IC completion. RESULTS: At the start of IC, higher stool Shannon diversity (hazard ratio [HR], 0.36; 95% confidence interval [CI], .18-.74) and higher relative abundance of Porphyromonadaceae (HR, 0.36; 95% CI, .18-.73) were associated with increased probability of remaining infection-free during neutropenia. A baseline stool Shannon diversity cutoff of <2 had optimal operating characteristics for predicting infectious complications during neutropenia. Although 56 patients received therapy >72 hours with a carbapenem, none of the patients had an infection with an extended spectrum ß-lactamase-producing organism. Patients who received carbapenems for >72 hours had significantly lower α-diversity at neutrophil recovery (P = .001) and were approximately 4 times more likely to have infection in the 90 days following neutrophil recovery (HR, 4.55; 95% CI, 1.73-11.93). CONCLUSIONS: Our results suggest that gut microbiome evaluation could assist with infectious risk stratification and that improved targeting of antibiotic administration during IC could decrease subsequent infectious complications in AML patients.Baseline microbiome diversity is a strong independent predictor of infection during acute myeloid leukemia induction chemotherapy (IC) among clinical and microbiome covariates. Higher baseline levels of Porphyromonadaceae appear protective against infection, while carbapenem use is associated with consequences to the microbiome and infection susceptibility post-IC.

Filament conductivity enhancement through nonlinear beam interaction.

Laser filament applications relying on filament plasma conductivity are limited by their low electron densities and corresponding short lifetimes. Filament plasma formation, an intensity-dependent process, is limited by the clamping of the filament core intensity. Consequently, increasing initial beam energy results in the breakup of the beam into multiple filaments rather than the enhancement of the electron density and conductivity of an individual filament. However, we demonstrate here the augmentation of the filament plasma density up to three times the typical value through the energy exchange between two co-propagating femtosecond beams with total powers between 1.7 and 2.2 Pfil.

Tools for Analysis of the Microbiome.

Over the past decade, it has become exceedingly clear that the microbiome is a critical factor in human health and disease and thus should be investigated to develop innovative treatment strategies. The field of metagenomics has come a long way in leveraging the advances of next-generation sequencing technologies resulting in the capability to identify and quantify all microorganisms present in human specimens. However, the field of metagenomics is still in its infancy, specifically in regard to the limitations in computational analysis, statistical assessments, standardization, and validation due to vast variability in the cohorts themselves, experimental design, and bioinformatic workflows. This review summarizes the methods, technologies, computational tools, and model systems for characterizing and studying the microbiome. We also discuss important considerations investigators must make when interrogating the involvement of the microbiome in health and disease in order to establish robust results and mechanistic insights before moving into therapeutic design and intervention.

Broadband space-time wave packets propagating 70 m.

The propagation distance of a pulsed beam in free space is ultimately limited by diffraction and space-time coupling. "Space-time" (ST) wave packets are pulsed beams endowed with tight spatio-temporal spectral correlations that render them propagation-invariant. Here we explore the limits of the propagation distance for ST wave packets. Making use of a specially designed phase plate inscribed by gray-scale lithography and having a laser-damage threshold of ∼0.5 J/cm2, we synthesize a ST light sheet of width ≈700 µm and bandwidth ∼20 nm, and confirm a propagation distance of ≈70 m.

What Are the Effects of Irreversible Electroporation on a Staphylococcus aureus Rabbit Model of Osteomyelitis?

BACKGROUND: The treatment of osteomyelitis can be challenging because of poor antibiotic penetration into the infected bone and toxicities associated with prolonged antibiotic regimens to control infection. Irreversible electroporation (IRE), a percutaneous image-guided ablation technology in which the targeted delivery of high-voltage electrical pulses permanently damages the cell membrane, has been shown to effectively control bacterial growth in various settings. However, IRE for the management of bone infections has yet to be evaluated. QUESTIONS/PURPOSES: We aimed to evaluate IRE for treating osteomyelitis by assessing (1) the efficacy of IRE to suppress the in vitro growth of a clinical isolate of S. aureus, alone or combined with cefazolin; and (2) the effects of IRE on the in vivo treatment of a rabbit model of osteomyelitis. METHODS: S. aureus strain UAMS-1 expanded in vitro to the log phase was subjected to an electric field of 2700 V/cm, which was delivered in increasing numbers of pulses. Immediately after electroporation, bacteria were plated on agar plates with or without cefazolin. The number of colony-forming units (CFUs) was scored the following day. ANOVA tests were used to analyze in vitro data. In a rabbit osteomyelitis model, we inoculated the same bacterial strain into the radius of adult male New Zealand White rabbits. Three weeks after inoculation, all animals (n = 32) underwent irrigation and débridement, as well as wound culture of the infected forelimb. Then, they were randomly assigned to one of four treatment groups (n = eight per group): untreated control, cefazolin only, IRE only, or combined IRE + cefazolin. Serial radiography was performed to assess disease progression using a semiquantitative grading scale. Bone and soft-tissue specimens from the infected and contralateral forelimbs were collected at 4 weeks after treatment for bacterial isolation and histologic assessment using a semiquantitative scale. RESULTS: The in vitro growth of S. aureus UAMS-1 was impaired by IRE in a pulse-dependent fashion; the number of CFUs/mL was different among seven pulse levels, namely 0, 10, 30, 60, 90, 120, and 150 pulses. With the number of CFUs/mL observed in untreated controls set as 100%, 10 pulses rendered a median of 50.2% (range 47.1% to 58.2%), 30 pulses rendered a median of 2.7% (range 2.5% to 2.8%), 60 pulses rendered a median of 0.014% (range 0.012% to 0.015%), 90 pulses rendered a median of 0.004% (range 0.002% to 0.004%), 120 pulses rendered a median of 0.001% (range 0.001% to 0.001%), and 150 pulses rendered a median of 0.001% (range 0.000% to 0.001%) (Kruskal-Wallis test: p = 0.003). There was an interaction between the effect of the number of pulses and the concentration of cefazolin (two-way ANOVA: F [8, 30] = 17.24; p < 0.001), indicating that combining IRE with cefazolin is more effective than either treatment alone at suppressing the growth of S. aureus UAMS-1. Likewise, the clinical response in the rabbit model (the percentage of animals without detectable residual bacteria in the bone and surrounding soft tissue after treatment) was better in the combination group than in the other groups: control, 12.5% (one of eight animals); IRE only, 12.5% (one of eight animals); cefazolin only, 25% (two of eight animals); and IRE + cefazolin, 75% (six of eight animals) (two-sided Fisher's exact test: p = 0.030). CONCLUSIONS: IRE effectively suppressed the growth of S. aureus UAMS-1 and enhanced the antibacterial effect of cefazolin in in vitro studies. When translated to a rabbit osteomyelitis model, the addition of IRE to conventional parenteral antibiotic treatment produced the strongest response, which supports the in vitro findings. CLINICAL RELEVANCE: Our results show that IRE may improve the results of standard parenteral antibiotic treatment, thus setting the stage for models with larger animals and perhaps trials in humans for validation.

Clonal Emergence of Invasive Multidrug-Resistant Staphylococcus epidermidis Deconvoluted via a Combination of Whole-Genome Sequencing and Microbiome Analyses.

Background: Pathobionts, bacteria that are typically human commensals but can cause disease, contribute significantly to antimicrobial resistance. Staphylococcus epidermidis is a prototypical pathobiont as it is a ubiquitous human commensal but also a leading cause of healthcare-associated bacteremia. We sought to determine the etiology of a recent increase in invasive S. epidermidis isolates resistant to linezolid. Methods: Whole-genome sequencing (WGS) was performed on 176 S. epidermidis bloodstream isolates collected at the MD Anderson Cancer Center in Houston, Texas, between 2013 and 2016. Molecular relationships were assessed via complementary phylogenomic approaches. Abundance of the linezolid resistance determinant cfr was determined in stool samples via reverse-transcription quantitative polymerase chain reaction. Results: Thirty-nine of the 176 strains were linezolid resistant (22%). Thirty-one of the 39 linezolid-resistant S. epidermidis infections were caused by a particular clone resistant to multiple antimicrobials that spread among leukemia patients and carried cfr on a 49-kb plasmid (herein called pMB151a). The 6 kb of pMB151a surrounding the cfr gene was nearly 100% identical to a cfr-containing plasmid isolated from livestock-associated staphylococci in China. Analysis of serial stool samples from leukemia patients revealed progressive staphylococcal domination of the intestinal microflora and an increase in cfr abundance following linezolid use. Conclusions: The combination of linezolid use plus transmission of a multidrug-resistant clone drove expansion of invasive, linezolid-resistant S. epidermidis. Our results lend support to the notion that a combination of antibiotic stewardship plus infection control measures may help to control the spread of a multidrug-resistant pathobiont.

Imaging to Assess Ischemic Heart Disease in Women.

PURPOSE OF REVIEW: Ischemic heart disease is a leading cause of morbidity and mortality for women and men around the world. However, traditional cardiovascular risk factors do not fully capture cardiac risk in women. This review summarizes sex-based differences in the clinical presentation, pathophysiology, and risk assessment of ischemic heart disease. We also examine the use of anatomic and functional imaging modalities in the diagnosis of ischemic heart disease in women. RECENT FINDINGS: Recent studies with women subjects have bolstered the predictive value of the coronary artery calcium (CAC) score in predicting atherosclerotic cardiovascular disease risk and major adverse cardiac events in a graded fashion. In addition, combined CAC scoring and coronary computed tomography (CCTA) has shown promise in excluding coronary artery disease (CAD). Using CCTA, data have suggested that increasing cardiovascular risk factors are associated with an increase in noncalcified coronary plaque in women compared with an increase in both calcified and noncalcified plaque in men with cardiac risk factors. Some data have suggested that women obtain greater prognostic benefit from CCTA than from other noninvasive tests. Fractional flow reserve obtained from a CCTA (FFRCT) is a new mathematical assessment of coronary blood flow that determines the presence of lesion-specific myocardial ischemia. Prevention and identification of ischemic heart disease remains a foundation of cardiology and public health. In women, atypical symptoms and limitations in traditional risk factor assessment lead to challenges in the identification of ischemic heart disease. With improvements in technologies such as CAC scoring, CCTA, instantaneous flow reserve (iFR), optical coherence tomography (OCT), and FFRCT, there is great promise for identification of ischemic heart disease, and the future of prevention in women. Future studies with strong female representation should investigate the role of novel imaging techniques in women.

Sequence type 1 group B Streptococcus, an emerging cause of invasive disease in adults, evolves by small genetic changes.

The molecular mechanisms underlying pathogen emergence in humans is a critical but poorly understood area of microbiologic investigation. Serotype V group B Streptococcus (GBS) was first isolated from humans in 1975, and rates of invasive serotype V GBS disease significantly increased starting in the early 1990s. We found that 210 of 229 serotype V GBS strains (92%) isolated from the bloodstream of nonpregnant adults in the United States and Canada between 1992 and 2013 were multilocus sequence type (ST) 1. Elucidation of the complete genome of a 1992 ST-1 strain revealed that this strain had the highest homology with a GBS strain causing cow mastitis and that the 1992 ST-1 strain differed from serotype V strains isolated in the late 1970s by acquisition of cell surface proteins and antimicrobial resistance determinants. Whole-genome comparison of 202 invasive ST-1 strains detected significant recombination in only eight strains. The remaining 194 strains differed by an average of 97 SNPs. Phylogenetic analysis revealed a temporally dependent mode of genetic diversification consistent with the emergence in the 1990s of ST-1 GBS as major agents of human disease. Thirty-one loci were identified as being under positive selective pressure, and mutations at loci encoding polysaccharide capsule production proteins, regulators of pilus expression, and two-component gene regulatory systems were shown to affect the bacterial phenotype. These data reveal that phenotypic diversity among ST-1 GBS is mainly driven by small genetic changes rather than extensive recombination, thereby extending knowledge into how pathogens adapt to humans.

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.