This article provides a systematic framework for addressing contamination in microbiome studies, a critical challenge that disproportionately impacts low-biomass samples and can compromise research validity.
Low sequencing depth is a critical bottleneck that can compromise the validity of metagenomic findings, particularly for detecting rare taxa, antimicrobial resistance (AMR) genes, and strain-level variations.
This article provides a comprehensive guide to quality control for microbiome sequencing, tailored for researchers and drug development professionals.
Longitudinal microbiome studies are essential for understanding dynamic host-microbiome interactions but are particularly vulnerable to batch effects—technical variations that can obscure true biological signals and lead to spurious findings.
PCR amplification is an integral but problematic step in 16S rRNA gene sequencing, introducing significant bias that distorts microbial community profiles and threatens the validity of scientific conclusions.
Efficiently extracting high-quality DNA from Gram-positive bacteria is a critical yet challenging step in molecular diagnostics, pathogen surveillance, and drug development.
Next-generation sequencing (NGS) of low microbial biomass samples presents a significant challenge in biomedical research, where contaminating DNA can critically distort results and lead to spurious conclusions.
Metagenomic next-generation sequencing (mNGS) is revolutionizing pathogen detection and microbiome studies, but its accuracy is critically limited by high levels of host nucleic acids in clinical samples.
This article provides a foundational to advanced overview of the two predominant bioinformatics pipelines, QIIME and mothur, for 16S rRNA amplicon data analysis.
This article provides a comprehensive overview of RNA sequencing for characterizing the microbiome transcriptome, tailored for researchers and drug development professionals.