Microbiome and Genomic Analysis Lecture

Jul 12, 2024

Lecture on Microbiome and Genomic Analysis

Lecture Structure

  • Introduction to microbiome and genomic analysis with a focus on a three-day intensive workshop.
  • The workshop consists of eight different modules.

Workshop Modules Overview

  1. Module 1: Basic concepts and definitions, approach, and resources available.
  2. Module 2: Marker gene analysis based on 16S analysis to measure community diversity (alpha and beta diversity).
  3. Module 3: Piecrust tool for linking taxonomic markers to functional genes.
  4. Module 4: Shotgun metagenomic analysis covering taxonomic and functional classification.
  5. Module 5: Assembling metagenomic samples and extracting genomic sequences.
  6. Module 6: Transcriptomics and RNA-seq analysis.
  7. Module 7: Advanced statistical analysis applied to marker gene and shotgun data.
  8. Module 8: Biomarker selection from sequence analysis results for disease or environmental condition associations.

Learning Objectives

  • Define different types of metagenomic projects and process the data.
  • Hands-on usage of different tools and running standard pipelines for various datasets.
  • Discuss technical and philosophical limitations of metagenomic studies.
  • Focus areas include microbial community analysis, interpreting sequence data, and common resources for databases.

Key Concepts and Definitions

  • Microbiome: Collective genome of indigenous microbes, comprehensive genetic view of human as a life form.
  • Microbiota: Actual set of microorganisms found in a particular setting.
  • Metagenomics: Functional aspect of microbiome allowing for cloning and functional analysis of collective genomes.
  • Marker Genes: Used to characterize community without needing to culture organisms.

Importance of Metagenomics

  • Provides a way to study microbes in their communities; isolated organism studies often miss community interactions.
  • Functional analysis from metagenomics can provide insights into microbial communities and their impact on health.

Sequencing Technologies

  • Importance of advanced sequencing technologies such as Illumina, Oxford Nanopore, and PacBio.
  • Different platforms have varying error rates and throughput capabilities.

Addressing Microbiome Questions

  1. Identifying what microbes are present (taxonomic complexity).
  2. What functions are present (functional complexity).
  3. Correlation of microbiome features with environmental or host factors.
  4. Temporal dynamics of microbiome in response to treatments.

Historical Perspective

  • Evolution of metagenomic studies alongside sequencing technology advancements.
  • Significant contributions from researchers and key studies marking the development of field.

Challenges in Metagenomics

  1. Data Quality: Error rates in sequencing, chimeric reads, and metadata consistency.
  2. Reproducibility: Variability in sample types, sequencing platforms, and analysis workflows.
  3. Taxonomy and OTUs: Naming issues and resolution limitations for differentiating strains within species.
  4. Functional Annotation: Many genes remain of unknown function; hypothetical genes pose a challenge.

Common Resources and Databases

  • 16S Reference Databases: Silva, Green Genes, RDP
  • Whole Genomes: NCBI GenBank, RefSeq, HOMD
  • Functional Databases: KEGG, UniProt, CARD, Pfam, Gene Ontology
  • Project-Specific Resources: Human Microbiome Project portals, EBI, NCBI Metagenomics Archives

Summary

  • Focus on the hands-on application of tools and interpretation of microbial community data.
  • Emphasis on reproducibility, metadata standards, and addressing challenges associated with sequencing and data interpretation.