Culture-independent detection of nontuberculous mycobacteria in clinical respiratory samples

Culture-based detection of nontuberculous Mycobacteria (NTM) in respiratory samples is time consuming and can be subject to overgrowth by nonmycobacterial bacteria. We describe a single-reaction TaqMan quantitative PCR assay for the direct detection of NTM species in clinical samples that is specific, sensitive, and robust

Divergent Relationships between Fecal Microbiota and Metabolome following Distinct Antibiotic-Induced Disruptions

This is an openaccess article distributed under the terms of the Creative Commons attribution 4.0 International license.The intestinal microbiome plays an essential role in regulating many aspects of host physiology, and its disruption through antibiotic exposure has been implicated in the development of a range of serious pathologies. The complex metabolic relationships that exist between members of the intestinal microbiota and the potential redundancy in functional pathways mean that an integrative analysis of changes in both structure and function are needed to understand the impact of antibiotic exposure. We used a combination of next-generation sequencing and nuclear magnetic resonance (NMR) metabolomics to characterize the effects of two clinically important antibiotic treatments, ciprofloxacin and vancomycin-imipenem, on the intestinal microbiomes of female C57BL/6 mice. This assessment was performed longitudinally and encompassed both antibiotic challenge and subsequent microbiome reestablishment. Both antibiotic treatments significantly altered the microbiota and metabolite compositions of fecal pellets during challenge and recovery. Spearman’s correlation analysis of microbiota and NMR data revealed that, while some metabolites could be correlated with individual operational taxonomic units (OTUs), frequently multiple OTUs were associated with a significant change in a given metabolite. Furthermore, one metabolite, arginine, can be associated with increases/decreases in different sets of OTUs under differing conditions. Taken together, these findings indicate that reliance on shifts in one data set alone will generate an incomplete picture of the functional effect of antibiotic intervention. A full mechanistic understanding will require knowledge of the baseline microbiota composition, combined with both a comparison and an integration of microbiota, metabolomics, and phenotypic data

Case report: Identification of intra-laboratory blood culture contamination with Staphylococcus aureus by whole genome sequencing

© 2019 Elsevier Inc. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (February 2019) in accordance with the publisher’s archiving policyStaphylococcus aureus in blood cultures is rarely considered a contaminant. We report a case of intra-laboratory contamination between blood culture bottles which was confirmed by whole genome sequencing, highlighting the importance of molecular analysis in the clinical laboratory setting

The capacity of the fecal microbiota from Malawian infants to ferment resistant starch

In Low and Middle-Income Countries (LMIC), weaning is associated with environmentally acquired and inflammation-associated enteric disorders. Dietary intake of high amylose maize starch (HAMS) can promote commensal fermentative bacteria and drive the production of short chain fatty acids (SCFAs). By stabilizing commensal gut microbiology, and stimulating the production of anti-inflammatory metabolites, HAMS supplementation might therefore influence enteric health. However, the extent to which the gut microbiota of LMIC infants are capable of fermenting HAMS is unclear. We assessed the capacity of the fecal microbiota from pre-weaning and weaning Malawian infants to ferment HAMS and produce SCFAs using an in vitro fermentation model. Fecal microbiota from both pre-weaning and weaning infants were able to ferment HAMS, as indicated by an increase in bacterial load and total SCFA concentration, and a reduction in pH. All of these changes were more substantial in the weaning group. Acetate production was observed with both pre-weaning and weaning groups, while propionate production was only observed in the weaning group. HAMS fermentation resulted in significant alterations to the fecal microbial community in the weaning group, with significant increases in levels of Prevotella, Veillonella, and Collinsella associated with propionate production. In conclusion, fecal microbiota from Malawian infants before and during weaning has the capacity to produce acetate through HAMS fermentation, with propionate biosynthetic capability appearing only at weaning. Our results suggest that HAMS supplementation might provide benefit to infants during weaning

Inbred Mouse Populations Exhibit Intergenerational Changes in Intestinal Microbiota Composition and Function Following Introduction to a Facility

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Inbred mice are used to investigate many aspects of human physiology, including susceptibility to disease and response to therapies. Despite increasing evidence that the composition and function of the murine intestinal microbiota can substantially influence a broad range of experimental outcomes, relatively little is known about microbiome dynamics within experimental mouse populations. We investigated changes in the intestinal microbiome between C57BL/6J mice spanning six generations (assessed at generations 1, 2, 3, and 6), following their introduction to a stringently controlled facility. Fecal microbiota composition and function were assessed by 16S rRNA gene amplicon sequencing and liquid chromatography mass spectrometry, respectively. Significant divergence of the intestinal microbiota between founder and second generation mice, as well as continuing inter-generational variance, was observed. Bacterial taxa whose relative abundance changed significantly through time included Akkermansia, Turicibacter, and Bifidobacterium (p < 0.05), all of which are recognized as having the potential to substantially influence host physiology. Shifts in microbiota composition were mirrored by corresponding differences in the fecal metabolome (r = 0.57, p = 0.0001), with notable differences in levels of tryptophan pathway metabolites and amino acids, including glutamine, glutamate and aspartate. We related the magnitude of changes in the intestinal microbiota and metabolome characteristics during acclimation to those observed between populations housed in separate facilities, which differed in regards to husbandry, barrier conditions and dietary intake. The microbiome variance reported here has implications for experimental reproducibility, and as a consequence, experimental design and the interpretation of research outcomes across wide range of contexts

Burkholderia lata Infections from Intrinsically Contaminated Chlorhexidine Mouthwash, Australia, 2016

"Emerging Infectious Diseases is an open access journal in the public domain"Burkholderia lata was isolated from 8 intensive care patients at 2 tertiary hospitals in Australia. Whole-genome sequencing demonstrated that clinical and environmental isolates originated from a batch of contaminated commercial chlorhexidine mouthwash. Genomic analysis identified efflux pump–encoding genes as potential facilitators of bacterial persistence within this biocide

Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Background Asthma pathophysiology and treatment responsiveness are predicted by inflammatory phenotype. However, the relationship between airway microbiology and asthma phenotype is poorly understood. Objective We aimed to characterize the airway microbiota in patients with symptomatic stable asthma and relate composition to airway inflammatory phenotype and other phenotypic characteristics. Methods The microbial composition of induced sputum specimens collected from adult patients screened for a multicenter randomized controlled trial was determined by using 16S rRNA gene sequencing. Inflammatory phenotypes were defined by sputum neutrophil and eosinophil cell proportions. Microbiota were defined by using α- and β-diversity measures, and interphenotype differences were identified by using similarity of percentages, network analysis, and taxon fold change. Phenotypic predictors of airway microbiology were identified by using multivariate linear regression. Results Microbiota composition was determined in 167 participants and classified as eosinophilic (n = 84), neutrophilic (n = 14), paucigranulocytic (n = 60), or mixed neutrophilic-eosinophilic (n = 9) asthma phenotypes. Airway microbiology was significantly less diverse (P = .022) and more dissimilar (P = .005) in neutrophilic compared with eosinophilic participants. Sputum neutrophil proportions, but not eosinophil proportions, correlated significantly with these diversity measures (α-diversity: Spearman r = −0.374, P < .001; β-diversity: r = 0.238, P = .002). Interphenotype differences were characterized by a greater frequency of pathogenic taxa at high relative abundance and reduced Streptococcus, Gemella, and Porphyromonas taxa relative abundance in patients with neutrophilic asthma. Multivariate regression confirmed that sputum neutrophil proportion was the strongest predictor of microbiota composition. Conclusions Neutrophilic asthma is associated with airway microbiology that is significantly different from that seen in patients with other inflammatory phenotypes, particularly eosinophilic asthma. Differences in microbiota composition might influence the response to antimicrobial and steroid therapies and the risk of lung infection

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability