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Reducing bias in bacterial community analysis of lower respiratory infections.

ABSTRACT: High-throughput pyrosequencing and quantitative PCR (Q-PCR) analysis offer greatly improved accuracy and depth of characterisation of lower respiratory infections. However, such approaches suffer from an inability to distinguish between DNA derived from viable and non-viable bacteria. This discrimination represents an important step in characterising microbial communities, particularly in contexts with poor clearance of material or high antimicrobial stress, as non-viable bacteria and extracellular DNA can contribute significantly to analyses. Pre-treatment of samples with propidium monoazide (PMA) is an effective approach to non-viable cell exclusion (NVCE). However, the impact of NVCE on microbial community characteristics (abundance, diversity, composition and structure) is not known. Here, adult cystic fibrosis (CF) sputum samples were used as a paradigm. The effects of PMA treatment on CF sputum bacterial community characteristics, as analysed by pyrosequencing and enumeration by species-specific (Pseudomonas aeruginosa) and total bacterial Q-PCR, were assessed. At the local community level, abundances of both total bacteria and of P. aeruginosa were significantly lower in PMA-treated sample portions. Meta-analysis indicated no overall significant differences in diversity; however, PMA treatment resulted in a significant alteration in local community membership in all cases. In contrast, at the metacommunity level, PMA treatment resulted in an increase in community evenness, driven by an increase in diversity, predominately representing rare community members. Importantly, PMA treatment facilitated the detection of both recognised and emerging CF pathogens, significantly influencing 'core' and 'satellite' taxa group membership. Our findings suggest failure to implement NVCE may result in skewed bacterial community analyses.

SUBMITTER: Rogers GB

PROVIDER: S-EPMC3603400 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Reducing bias in bacterial community analysis of lower respiratory infections.

Rogers Geraint B GB Cuthbertson Leah L Hoffman Lucas R LR Wing Peter A C PA Pope Christopher C Hooftman Danny A P DA Lilley Andrew K AK Oliver Anna A Carroll Mary P MP Bruce Kenneth D KD van der Gast Christopher J CJ

The ISME journal 20121129 4

High-throughput pyrosequencing and quantitative PCR (Q-PCR) analysis offer greatly improved accuracy and depth of characterisation of lower respiratory infections. However, such approaches suffer from an inability to distinguish between DNA derived from viable and non-viable bacteria. This discrimination represents an important step in characterising microbial communities, particularly in contexts with poor clearance of material or high antimicrobial stress, as non-viable bacteria and extracellu ...[more]

PMID: 23190732

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Project description:IntroductionThe burden of lower respiratory tract infections (LRTIs) is a substantial public health concern. However, the epidemiology of LRTI and its bacterial aetiologies are poorly characterised, particularly in the African continent. Providing accurate data can help design cost-effective interventions to curb the burden of respiratory infections in Africa. Therefore, the aim of this systematic review and meta-analysis will be to determine the prevalence of respiratory Bacterial Aetiologies in people with low Respiratory tract Infections in Africa (BARIAFRICA) and associated factors.Methods and analysisWe will search PubMed, EMBASE, Web of Science, African Journals Online, Cumulative Index to Nursing and Allied Health Literature, and Global Index Medicus to identify studies that reported the prevalence (of enough data to compute this estimate) of respiratory bacterial infections in people with LRTIs in Africa from 1 January 2000 to 31 March 2018, without any linguistic restrictions. Study selection, data extraction and risk of bias assessment will be conducted independently by two investigators. Heterogeneity will be evaluated using the χ² test on Cochran's Q statistic and quantified with H and I² statistics. Prevalence will be pooled using a random-effect meta-analysis model. Subgroup and meta-regression analyses will be used to identify sources of heterogeneity of prevalence estimates. This study will be reported according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses.Ethics and disseminationSince this study will be based on published data, it does not require ethical approval. This systematic review and meta-analysis is intended to serve as a basis for determining the burden of LRTIs, for identifying data gaps and for guiding future investigations in Africa. The final report will be published in peer-reviewed journals, presented in conferences and submitted to relevant health policy makers.Prospero registration numberCRD42018092359.

Project description:ObjectivesVentilator-associated lower respiratory tract infections (VA-LRTIs) are associated with prolonged length of stay and increased mortality. We aimed to investigate the occurrence of bacterial VA-LRTI among mechanically ventilated COVID-19 patients and compare these findings to non-COVID-19 cohorts throughout the first and second wave of the pandemic.DesignRetrospective cohort study.SettingKarolinska University Hospital, Stockholm, Sweden.PatientsAll patients greater than or equal to 18 years treated with mechanical ventilation between January 1, 2011, and December 31, 2020.InterventionsNone.Measurements and main resultsThe cohort consisted of 20,223 ICU episodes (479 COVID-19), with a VA-LRTI incidence proportion of 30% (129/426) in COVID-19 and 18% (1,081/5,907) in non-COVID-19 among patients ventilated greater than or equal to 48 hours. The median length of ventilator treatment for COVID-19 patients was 10 days (interquartile range, 5-18 d), which was significantly longer than for all other investigated specific diagnoses. The VA-LRTI incidence rate per 1,000 ventilator days at risk was 31 (95% CI, 26-37) for COVID-19 and 34 (95% CI, 32-36) for non-COVID-19. With COVID-19 as reference, adjusted subdistribution hazard ratios for VA-LRTI was 0.29-0.50 (95% CI, < 1) for influenza, bacterial pneumonia, acute respiratory distress syndrome, and severe sepsis, but 1.38 (95% CI, 1.15-1.65) for specific noninfectious diagnoses. Compared with COVID-19 in the first wave of the pandemic, COVID-19 in the second wave had adjusted subdistribution hazard ratio of 1.85 (95% CI, 1.14-2.99). In early VA-LRTI Staphylococcus aureus was more common and Streptococcus pneumoniae, Haemophilus influenzae, and Escherichia coli less common in COVID-19 patients, while Serratia species was more often identified in late VA-LRTI.ConclusionsCOVID-19 is associated with exceptionally long durations of mechanical ventilation treatment and high VA-LRTI occurrence proportions. The incidence rate of VA-LRTI was compared with the pooled non-COVID-19 cohort, however, not increased in COVID-19. Significant differences in the incidence of VA-LRTI occurred between the first and second wave of the COVID-19 pandemic.

Project description:BackgroundLower respiratory tract infections (LRTIs) are a leading cause of childhood morbidity and mortality. Potentially pathogenic organisms are present in the respiratory tract in both symptomatic and asymptomatic children, but their presence does not necessarily indicate disease. We aimed to assess the concordance between upper and lower respiratory tract microbiota during LRTIs and the use of nasopharyngeal microbiota to discriminate LRTIs from health.MethodsFirst, we did a prospective study of children aged between 4 weeks and 5 years who were admitted to the paediatric intensive care unit (PICU) at Wilhelmina Children's Hospital (Utrecht, Netherlands) for a WHO-defined LRTI requiring mechanical ventilation. We obtained paired nasopharyngeal swabs and deep endotracheal aspirates from these participants (the so-called PICU cohort) between Sept 10, 2013, and Sept 4, 2016. We also did a matched case-control study (1:2) with the same inclusion criteria in children with LRTIs at three Dutch teaching hospitals and in age-matched, sex-matched, and time-matched healthy children recruited from the community. Nasopharyngeal samples were obtained at admission for cases and during home visits for controls. Data for child characteristics were obtained by questionnaires and from pharmacy printouts and medical charts. We used quantitative PCR and 16S rRNA-based sequencing to establish viral and bacterial microbiota profiles, respectively. We did sparse random forest classifier analyses on the bacterial data, viral data, metadata, and the combination of all three datasets to distinguish cases from controls.Findings29 patients were enrolled in the PICU cohort. Intra-individual concordance in terms of viral microbiota profiles (96% agreement [95% CI 93-99]) and bacterial microbiota profiles (58 taxa with a median Pearson's r 0·93 [IQR 0·62-0·99]; p<0·05 for all 58 taxa) was high between nasopharyngeal and endotracheal aspirate samples, supporting the use of nasopharyngeal samples as proxy for lung microbiota during LRTIs. 154 cases and 307 matched controls were prospectively recruited to our case-control cohort. Individually, bacterial microbiota (area under the curve 0·77), viral microbiota (0·70), and child characteristics (0·80) poorly distinguished health from disease. However, a classification model based on combined bacterial and viral microbiota plus child characteristics distinguished children with LRTIs from their matched controls with a high degree of accuracy (area under the curve 0·92).InterpretationOur data suggest that the nasopharyngeal microbiota can serve as a valid proxy for lower respiratory tract microbiota in childhood LRTIs, that clinical LRTIs in children result from the interplay between microbiota and host characteristics, rather than a single microorganism, and that microbiota-based diagnostics could improve future diagnostic and treatment protocols.FundingSpaarne Gasthuis, University Medical Center Utrecht, and the Netherlands Organization for Scientific Research.

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Reducing bias in bacterial community analysis of lower respiratory infections.

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Reducing bias in bacterial community analysis of lower respiratory infections.

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