Microbial Bioactives

Microbial Bioactives | Online ISSN 2209-2161
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Microbial Bioactives

Volume 6 Number 1 2023

Article Contents

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Contents Vol 6 (1)

Unmasking Bias in Microbiome Research: A Human-Centered Introduction to Methodological Pitfalls and Meta-Analytic Insights

Most Farhana Akter 1, Md. Robiul Islam 1, Shahadat Hossain 2*

 

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Microbial Bioactives 6 (1) 1-8 https://doi.org/10.25163/microbbioacts.6110672

Submitted: 05 February 2023 Revised: 24 March 2023  Published: 08 April 2023 

Abstract

Microbiome research has transformed biological and biomedical sciences by enabling culture-independent exploration of complex microbial communities across diverse environments, from marine ecosystems to the human body. Despite these advances, microbiome studies remain highly vulnerable to systematic and random methodological biases that can substantially distort biological interpretation and limit reproducibility. This systematic review and meta-analysis synthesize evidence on how technical decisions across the microbiome research workflow influence observed microbial diversity and community structure. Specifically, it evaluates biases arising from study design, sampling strategies, DNA extraction methods, primer selection, sequencing platforms, and bioinformatic pipelines. Quantitative meta-analytic comparisons demonstrate that methodological choices frequently exert effect sizes comparable to, or greater than, true biological variables. Full-length 16S rRNA gene sequencing consistently reveals higher species richness than short-read approaches, while primer selection introduces pronounced taxon-specific dropouts, including clinically and ecologically important genera. Extraction kits display domain-dependent biases, often recovering bacterial diversity effectively while underestimating eukaryotic taxa. Case studies from marine biofilms, freshwater sediments, host-associated microbiomes, and pathogen surveillance illustrate how these biases propagate through downstream analyses, leading to underestimation of richness, misclassification of taxa, and erroneous ecological or clinical conclusions. Advances such as amplicon sequence variant inference and standardized reporting frameworks have improved resolution and transparency, yet database inconsistencies and low-biomass contamination remain persistent challenges. Collectively, the findings underscore that microbiome profiles are not neutral reflections of biological reality but products of methodological “lenses.” Addressing these biases through standardized protocols, informed methodological choices, and rigorous controls is essential for producing robust, comparable, and biologically meaningful microbiome research.

Keywords: Microbiome research; methodological bias; 16S rRNA sequencing; primer bias; DNA extraction; meta-analysis; microbial diversity; bioinformatics

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