Methods for Computational Microbiome Analysis

Introduction

• Speaker: Michael Tremonti, Research Scientist
• Institution: Iowa Institute of Human Genetics, University of Iowa
• Specialization: Bioinformatics
• Topic: Computational microbiome analysis
• Format: Story of Dr. Terry Walls

Dr. Terry Walls' Story

• Profession: Clinician at the University of Iowa
• Diagnosis: Multiple sclerosis (MS) in 2000
• Condition: Wheelchair-bound by 2007
• Approach:
  • Used medical and scientific training
  • Reviewed literature, animal studies, and pharmaceutical trials
  • Developed a nutrient-rich diet strategy (Paleo diet)
  • Transitioned from supplements to nutrient-rich foods
• Outcome: Improved condition, able to walk and ride bikes
• Website: terrywalls.com

Connection to Microbiome

• Research by Dr. Ashutosh Mangalam:
  • Relationship between gut microbiome and MS
  • Isolated Prevotella histicola from a healthy individual
  • Observed regulatory CD4 T cell induction and disease suppression in MS mouse model

Importance of the Microbiome

• Interaction with disease and health
• Microbiome: Community of bacteria, viruses, archaea, fungi, and protozoa in a particular environment
• Found in diverse samples: surgical implements, soil, seawater, countertops, skin
• Genes and gene products also part of the microbiome

Microbiome Studies and Human Health

• Implications:
  • Metabolic disorders: obesity, syndromes, diabetes
  • Autoimmune diseases: IBD, Crohn’s disease
  • Neurological conditions
  • Colorectal cancer, potential link to autism
• Therapy:
  • Fecal transplant
  • Broad-spectrum antibiotics, potential impact on asthma and allergies

Conducting Microbiome Studies

• Main Questions:
  1. Who is there?
  2. What are they doing?
  3. How are they doing it?
• Community Structure:
  • Relative proportion
  • Richness and distribution
• Functional Analysis:
  • Environmental interactions
  • Enzymatic pathways

Metagenomic Sequencing

• Approaches:
  1. Amplicon Sequencing
  2. Shotgun Sequencing

Amplicon Sequencing

• Focus on ancestral ribosomal gene (e.g., 16S rRNA)
• Steps:
  1. Amplify the 16S gene
  2. Sequence using next-gen methods
  3. Quality control and clustering
  4. Generate abundance table
• Types:
  • Closed reference
  • De novo
  • Open reference

Shotgun Sequencing

• Extract all DNA in the community
• Steps:
  1. Shatter genomes into short fragments
  2. Sequence and quality control
  3. Map to a reference database
  4. Produce abundance table
• Tools: MetaFLANN, BATMAN, etc.

Properties of Microbiome Data

• Uniqueness:
  • Sparsity
  • Dynamic range
  • Compositional (proportions, not absolute abundance)

Analyzing Microbiome Data

Abundance and Prevalence

• Abundant Microbe: Highly enriched in one sample
• Prevalent Microbe: Found across all samples
• Abundant and Prevalent: Both high level and common

Alpha Diversity

• Metric: Richness and evenness within a sample

Beta Diversity

• Metric: Between-sample distance
• Analysis: Ordination plots, Bray-Curtis distance

Stratification

• Different biochemical functions across different patients

Conclusion

• Story Recap: Dr. Terry Walls’ recovery
• Research and Techniques: Metagenomic sequencing, microbiome properties, diversity metrics, stratification
• Applications: Planning interventions for disease

Thank You