Introduction to Microbiomes and Environmental Metagenomics

Lesson 1 • Microbial Interactions and Community Dynamics

Covers symbiosis, competition, predation, and syntrophy among microbes. Prepares students to interpret community-level metagenomic data.

Lesson 2 • Biogeochemical Cycles and Microbial Function

Explains microbial roles in carbon, nitrogen, sulfur, and phosphorus cycling. Grounds functional metagenomics in ecosystem-level processes.

Lesson 3 • What Is a Microbiome?

Defines microbiome, microbiota, and metagenome with precise distinctions. Establishes vocabulary used throughout the course.

Lesson 4 • Microbial Diversity Across Domains

Surveys bacterial, archaeal, fungal, and viral diversity in environmental contexts. Connects domain-level taxonomy to ecological function.

Lesson 1 • PCR and Amplicon-Based Methods

Explains PCR principles and amplicon sequencing of marker genes such as 16S rRNA. Distinguishes amplicon approaches from shotgun metagenomics.

Lesson 2 • DNA Structure and Replication Basics

Reviews DNA double helix, base pairing, and replication fidelity. Anchors downstream understanding of sequencing chemistry.

Lesson 3 • Library Preparation and Sequencing Platforms

Describes shotgun library construction, adapter ligation, and major sequencing platforms. Prepares students to select appropriate technologies for metagenomic projects.

Lesson 4 • Gene Expression and Functional Annotation

Covers transcription, translation, and operon structure in prokaryotes. Connects gene prediction to functional annotation in metagenomes.

Lesson 1 • Experimental Design for Metagenomic Studies

Covers power analysis, controls, replication, and confounding factor management in microbiome studies. Prevents common design flaws before data collection.

Lesson 2 • Reproducible Bioinformatics Workflows

Implements workflow managers and containerization to ensure computational reproducibility. Enables others to replicate and extend analyses.

Lesson 3 • Reporting Standards and Open Science

Applies community reporting guidelines and open-access data sharing principles to metagenomic publications. Aligns student outputs with peer-review expectations.

Lesson 4 • Metadata Standards and Sample Documentation

Applies MIxS and MIMARKS metadata standards to ensure interoperability and data reuse. Links metadata quality to analytical reproducibility.

Lesson 1 • Sequence Quality Control and Denoising

Covers FASTQ format, quality scores, and denoising algorithms that produce amplicon sequence variants. Emphasizes error correction before taxonomic assignment.

Lesson 2 • Taxonomic Classification of Amplicons

Explains reference database selection and classifier algorithms for assigning taxonomy to ASVs. Addresses database bias and unclassified sequences.

Lesson 3 • Differential Abundance and Visualization

Applies statistical tests to identify taxa that differ across sample groups. Produces publication-quality visualizations of community data.

Lesson 4 • Alpha and Beta Diversity Analysis

Teaches within-sample and between-sample diversity metrics and their ecological interpretation. Connects statistical outputs to biological hypotheses.

Lesson 1 • Shotgun Metagenomics Principles

Contrasts shotgun metagenomics with amplicon approaches and outlines its advantages for functional profiling. Sets expectations for data complexity.

Lesson 2 • Taxonomic Profiling from Shotgun Reads

Applies k-mer and alignment-based tools to classify reads and estimate community composition without assembly. Complements assembly-based approaches.

Lesson 3 • Metagenomic Assembly Algorithms

Explains de Bruijn graph assembly and k-mer selection for metagenomic data. Compares assemblers suited to high-complexity communities.

Lesson 4 • Assembly Quality Assessment

Uses N50, contig length distributions, and read-mapping rates to evaluate assembly completeness. Guides decisions on downstream analysis suitability.

Lesson 1 • Principles of Metagenomic Binning

Explains tetranucleotide frequency and coverage-based binning logic. Establishes why binning is essential for organism-level analysis.

Lesson 2 • Functional Annotation of MAGs

Predicts genes and assigns functions using Prokka, KEGG, and COG databases. Links genome content to ecological roles of recovered organisms.

Lesson 3 • MAG Quality Assessment

Uses CheckM and GUNC to estimate completeness, contamination, and chimerism of MAGs. Applies minimum quality standards for downstream use.

Lesson 4 • Binning Tools and Workflows

Compares MetaBAT2, MaxBin2, and CONCOCT binning tools and introduces ensemble approaches. Guides tool selection based on dataset characteristics.

Lesson 1 • Metatranscriptomics for Active Function

Extends metagenomic analysis to RNA to capture actively expressed genes. Distinguishes gene presence from gene activity in communities.

Lesson 2 • Metabolic Pathway Reconstruction

Reconstructs metabolic pathways from annotated genes and evaluates pathway completeness. Connects gene presence to predicted metabolic capabilities.

Lesson 3 • Comparative Functional Profiling

Compares functional gene abundances across environments or treatments using statistical frameworks. Identifies enriched functions linked to ecological conditions.

Lesson 4 • Metaproteomics and Metabolomics Integration

Introduces protein and metabolite profiling as complements to metagenomics. Demonstrates multi-omics integration for holistic functional insight.

Lesson 1 • Antimicrobial Resistance in the Environment

Profiles resistome diversity in environmental samples and tracks resistance gene dissemination. Connects environmental metagenomics to public health surveillance.

Lesson 2 • Aquatic and Marine Metagenomics

Covers ocean, freshwater, and sediment microbiome studies and their global biogeochemical significance. Addresses large-scale sampling and data integration.

Lesson 3 • Soil Microbiome Research

Examines soil as the most complex microbial habitat and addresses soil-specific sampling and analysis challenges. Connects soil microbiome function to agriculture and carbon cycling.

Lesson 4 • Bioprospecting and Novel Gene Discovery

Uses functional screening and sequence-based mining to discover novel enzymes and natural products. Illustrates the biotechnological value of environmental metagenomes.