ReviewPneumonia (Nathan Qld.)2018
How low can we go? The implications of low bacterial load in respiratory microbiota studies.
Review in Pneumonia (Nathan Qld.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Peripheral blood microbial signatures in current and former smokers.Scientific reports · 2021Pooled it
- Trial
- DNA sequencing for microbial surveillance in cystic fibrosis airways: advances, challenges, and clinical translation.Clinical microbiology reviews · 2026Review
- Challenges and Solutions in Low-Biomass Respiratory Microbiome Profiling: A Workflow for Bronchoalveolar Lavage Fluid Sequencing in Guinea Pigs.Physiological research · 2026Article
- Methodological bias shapes the interpretation of the urinary microbiome in low-biomass systems.Frontiers in microbiology · 2026Review
- Diagnostic value of metagenomic next-generation sequencing in the etiological diagnosis of lower respiratory tract infection.Scientific reports · 2025Article
- From Identification to Insight: Making Full Use of the Diagnostic Potential of MS/MS Proteotyping in Clinical Microbiology Using Efficient Bioinformatics.Journal of proteome research · 2025Review
- Positioning the preventive potential of microbiome treatments for cystic fibrosis in the context of current therapies.Cell reports. Medicine · 2024Review
- Recovery of microbial DNA by agar-containing solution from extremely low-biomass specimens including skin.Scientific reports · 2023Article
- A Refined, Controlled 16S rRNA Gene Sequencing Approach Reveals Limited Detection of Cerebrospinal Fluid Microbiota in Children with Bacterial Meningitis.Microbiology spectrum · 2023Article
- Realising respiratory microbiomic meta-analyses: time for a standardised framework.Microbiome · 2023Article
- Is there a placental microbiota? A critical review and re-analysis of published placental microbiota datasets.BMC microbiology · 2023Review
- The clinical application of metagenomic next-generation sequencing in sepsis of immunocompromised patients.Frontiers in cellular and infection microbiology · 2023Article
- Characterization of cerebrospinal fluid (CSF) microbiota at the time of initial surgical intervention for children with hydrocephalus.PloS one · 2023Article
- Contamination detection and microbiome exploration with GRIMER.GigaScience · 2022Article
- Compartmentalization of the host microbiome: how tumor microbiota shapes checkpoint immunotherapy outcome and offers therapeutic prospects.Journal for immunotherapy of cancer · 2022Review
- Smoking-induced microbial dysbiosis in health and disease.Clinical science (London, England : 1979) · 2022Review
- Review
- The Relationship Between Maternal and Neonatal Microbiota in Spontaneous Preterm Birth: A Pilot Study.Frontiers in pediatrics · 2022Article
- Bacterial Signatures of Paediatric Respiratory Disease: An Individual Participant Data Meta-Analysis.Frontiers in microbiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundCulture-independent sequencing methods are increasingly used to investigate the microbiota associated with human mucosal surfaces, including sites that have low bacterial load in healthy individuals (e.g. the lungs). Standard microbiota methods developed for analysis of high bacterial load specimens (e.g. stool) may require modification when bacterial load is low, as background contamination derived from sterile laboratory reagents and kits can dominate sequence data when few bacteria are present. MAIN BODY: Bacterial load in respiratory specimens may vary depending on the specimen type, specimen volume, the anatomic site sampled and clinical parameters. This review discusses methodological issues inherent to analysis of low bacterial load specimens and recommends strategies for successful respiratory microbiota studies. The range of methods currently used to process DNA from low bacterial load specimens, and the strategies used to identify and exclude background contamination are also discussed.
conclusionMicrobiota studies that include low bacterial load specimens require additional tests to ensure that background contamination does not bias the results or interpretation. Several methods are currently used to analyse the microbiota in low bacterial load respiratory specimens; however, there is scant literature comparing the effectiveness and biases of different methods. Further research is needed to define optimal methods for analysing the microbiota in low bacterial load specimens.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.