🧬 1. What is a Microbiome?

A microbiome isn’t just the microbes you can name (bacteria, archaea, fungi, protists, algae). It’s the entire living and active ecosystem they form, plus their biochemical activities.

So, it includes:

• 🦠 Microbiota – the community of organisms present
• ⚙️ Activity layer – what they’re doing (metabolism, growth, signaling)
• 🧪 Macromolecules – proteins, lipids, polysaccharides they produce
• 💬 Metabolites – signaling molecules, toxins, secondary products

👉 Microbiome = microbes + what they do + what they produce

Inactive microbes contribute little. The functional state (metabolic activity) defines how much they shape the environment.

🤝 2. Holobiont Concept: You and Your Microbes Are One

A human has ~20–25k genes. But your microbes collectively add millions more genes → forming the holobiont, a super-organism consisting of host + microbiome.

Together they:

• 🔗 Co-evolve over generations
• 💬 Communicate continuously (chemically and genetically)
• ⚖️ Maintain balance: imbalance = dysbiosis, often leading to disease

💡 Example: Corals + symbiotic algae and bacteria → when heated or destabilized, both the coral and its microbiome suffer. Same logic applies to humans.

🧠 Even 37% of human genes have bacterial origins! Only ~28% are purely eukaryotic in evolutionary origin — proof of deep integration through evolution.

💪 3. The Human Microbiome and Health

The gut microbiota influences:

• 🍞 Digestion – breaking down complex food molecules
• 🧍‍♂️ Immune system – training immune cells through constant low-level exposure
• 🧠 Mental health – producing neurotransmitter precursors and signal molecules (the “gut–brain axis”)

Microbial diversity = stability. Loss of diversity → susceptibility to inflammation, obesity, autoimmune diseases, etc.

🧭 4. Microbes as Indicators of Health and Environment

Microbes dominate every ecosystem on Earth. Their composition reflects system health and can act as biological quality indicators 🧫.

This idea isn’t new:

• In the 1950s–60s: “Microbial tracking” identified fecal contamination in water via indicators like E. coli (a “lab weed” that grows easily).
• With modern molecular tools (e.g., 16S rRNA sequencing), we can now identify contamination sources (human, animal, or wildlife) much more precisely.

Today, similar logic helps identify biomarkers for human and animal diseases.

🧠 5. Two Theories of Microbiome Interpretation

🌀 Holistic Theory

• Treats the host and microbiome as one integrated system (holobiont).
• Focuses on synergy and co-evolution.

🔬 Separation Theory

• Studies each microbial group or compartment separately.
• Useful for controlled experiments, where variables must be isolated.

Most modern research uses both: a holistic framework, but with experimental reductionism for clarity.

🔍 6. Investigating Microbiomes: Methods and Tools

The lecture mentions these categories:

a. 🧫 Culturing

• The classic approach: grow microbes on media (e.g., agar).
• E. coli = key fecal contamination indicator.
• But culturing only captures a small fraction of microbial diversity.

b. 🧬 Molecular & Omics Approaches

• 16S amplicon sequencing – identifies “who’s there.”
• Shotgun metagenomics – finds genes and potential functions.
• Metatranscriptomics / metaproteomics / metabolomics – reveal what microbes are actually doing.

As you move from simple culturing → omics → metabolite profiling, you get closer to real activity instead of just presence.

c. 🔭 Imaging

• Microscopy shows spatial organization (who’s next to whom).
• Useful for visualizing biofilms, tissues, and microbial interactions.

🌐 7. Data Interpretation and Modeling

Researchers look for:

• ⏱️ Time-series effects (how microbiomes change over time)
• 🔗 Correlations between species or environmental factors
  • Positive correlation → cooperation or similar niche
  • Negative correlation → competition
• 🕸️ Network models → show strength and type of relationships (thicker lines = stronger correlation)

These correlations are later validated experimentally by isolating species or factors to test hypotheses about interactions.

🧩 8. Summary of Key Theoretical Ideas