Category: Lab Notes: Microbiology

Environmental antimicrobial resistance occurs across soil, freshwater, sediments, marine ecosystems, wastewater, agricultural environments, and other microbial habitats. Learn how metagenomic sequencing is used to detect, quantify, and characterize resistance genes, resistomes, mobile genetic elements, plasmids, microbial hosts, and potential resistance pathways across interconnected environmental systems.

Antimicrobial resistance surveillance monitors resistance genes, resistant microorganisms, resistomes, and resistance patterns across human, animal, agricultural, food, wastewater, and environmental systems. Learn how metagenomics, genomic epidemiology, resistome analysis, and One Health approaches support AMR detection, monitoring, and surveillance.

Genomic epidemiology of antimicrobial resistance combines genomic sequencing with epidemiological information to investigate resistant microorganisms, resistance genes, transmission, microbial evolution, and AMR dissemination. Learn how whole-genome sequencing, metagenomics, phylogenetics, genomic context, and One Health surveillance are used to track antimicrobial resistance.

Resistance gene detection identifies genetic determinants associated with antimicrobial resistance in microbial genomes and communities. Learn how metagenomic sequencing, resistance databases, read-based and assembly-based analysis, gene prediction, abundance profiling, and genomic context are used to detect and characterize antimicrobial resistance genes.

Resistome profiling characterizes antimicrobial resistance genes within microbial communities. Learn how resistomes are detected, quantified, compared, and interpreted using metagenomic sequencing, resistance databases, abundance analysis, diversity analysis, statistical methods, and genomic context.

Resistance gene abundance analysis measures the representation of antimicrobial resistance genes within microbial communities. Learn how resistance genes are quantified using metagenomic sequencing, relative and absolute abundance methods, normalization, prevalence analysis, statistical testing, and genomic context.

Metagenomic resistome analysis examines the collection of antimicrobial resistance genes within microbial communities. Learn how resistomes are detected, profiled, quantified, compared, and interpreted using metagenomic sequencing, resistance databases, assembly, genome-resolved analysis, statistical methods, and genomic context.

Metagenomic DNA extraction is a critical step in recovering microbial DNA from complex biological and environmental samples. Learn about extraction methods, cell lysis, purification, DNA quality control, contamination, extraction bias, and sequencing requirements.

Metagenomic sample collection is one of the most important steps in a metagenomics study because the quality and representativeness of…

Amplicon sequencing is a targeted approach for studying microbial communities using selected genetic markers. Learn about 16S rRNA and ITS sequencing, PCR, bioinformatics, applications, advantages, and limitations.

Antimicrobial resistance genes enable microorganisms to survive antimicrobial exposure through mechanisms such as drug modification, target protection, reduced permeability, and active efflux. Learn how resistance genes are detected and analyzed using metagenomic sequencing, resistance gene databases, gene prediction, assembly, abundance analysis, and genomic context.

Metagenomics provides a culture-independent approach for studying antimicrobial resistance across microbial communities. Learn how resistance genes are detected and analyzed, how resistomes are characterized, and how metagenomic sequencing can investigate resistance in human, animal, agricultural, food, wastewater, and environmental systems.

Metagenomic statistical analysis helps researchers compare microbial communities, identify differentially abundant taxa and genes, analyze diversity, evaluate associations, and interpret functional and genomic patterns. Learn the key statistical methods, challenges, and best practices for reliable metagenomic analysis.

Metagenomic databases provide the reference information needed to interpret microbial DNA sequences. Explore database types, selection strategies, taxonomic and functional resources, specialized databases, applications, challenges, and best practices for reproducible metagenomic analysis.

Metagenomic functional annotation assigns potential biological functions to genes identified in microbial communities. Learn how functional annotation works, the role of databases and protein domains, metabolic pathway analysis, specialized gene annotation, applications, and limitations.