microbiome-curation

name	microbiome-curation
description	Skill for curating microbiome-related pathophysiology in the dismech knowledge base. Use this skill when adding dysbiosis mechanisms, ecological concepts (Anna Karenina, keystone taxa, colonization resistance), SCFA/metabolite pathways, and linking microbial ecology to disease pathophysiology. Covers IBD, C. diff, obesity, and other microbiome-associated conditions.

Microbiome Curation Skill

Overview

Curate microbiome-related pathophysiology entries with ecological depth beyond simple taxa +/- lists. Focus on:

• Ecological concepts (diversity, stability, keystone taxa)
• Causal chains from dysbiosis to clinical manifestations
• Metabolic consequences (SCFA, bile acids)
• Integration with BugSigDB and primary literature

When to Use

• Adding microbiome dysbiosis entries to disorders
• Curating pathophysiology for IBD, C. diff, obesity, metabolic diseases
• Decomposing "microbiome dysbiosis" into causal graph nodes
• Adding ecological concepts (Anna Karenina, colonization resistance)
• Linking microbial metabolites to host pathophysiology

Key Principle: Graph Structure Over Monolithic Entries

DO NOT create single entries bundling all microbiome effects:

# BAD - monolithic entry
- name: Microbiome Dysbiosis
  description: >
    Reduced diversity with depletion of Firmicutes and expansion of pathobionts,
    leading to decreased SCFA and barrier dysfunction.

DO decompose into atomic nodes with downstream edges:

# GOOD - causal graph
- name: Loss of Microbial Diversity
  downstream:
  - target: Loss of Keystone SCFA Producers
  - target: Increased Microbial Community Instability

- name: Loss of Keystone SCFA Producers
  downstream:
  - target: Decreased Butyrate Production

- name: Decreased Butyrate Production
  downstream:
  - target: Impaired Colonocyte Energy Metabolism

- name: Impaired Colonocyte Energy Metabolism
  downstream:
  - target: Epithelial Barrier Dysfunction

This enables:

1. Shared nodes across disorders
2. Explicit feedback loops
3. Targeted therapeutic entry points
4. Evidence on specific causal steps

Ecological Dimensions of Dysbiosis

Beyond Taxa +/-

BugSigDB captures increased/decreased taxa, but ecology is richer:

Dimension	What it captures	Example
Taxonomic	Which species +/-	Faecalibacterium, E. coli
α-Diversity	Richness/evenness	Shannon index
β-Diversity	Inter-individual variability	Anna Karenina effect
Functional	Pathway capacity	Butyrate synthesis genes
Metabolic	Actual output	Fecal SCFA concentrations
Network	Community structure	Keystone taxa, modularity
Stability	Resilience	Alternative stable states

Anna Karenina Principle

"All healthy microbiomes are alike; each dysbiotic microbiome is dysbiotic in its own way."

Dysbiosis often manifests as increased stochasticity rather than consistent shift to specific taxa.

- name: Increased Microbial Community Instability
  description: >
    Anna Karenina effect - dysbiotic microbiomes show increased inter-individual
    variability and temporal instability. The community loses resilience and may
    occupy an alternative stable state that resists therapeutic intervention.
  notes: >
    This increased stochasticity complicates biomarker discovery and explains
    heterogeneous treatment responses.
  downstream:
  - target: Loss of Microbial Diversity
    description: Feedback loop - instability promotes further diversity loss
  evidence:
  - reference: PMID:28836573
    supports: SUPPORT
    snippet: "The result is an 'Anna Karenina principle' for animal microbiomes, in which dysbiotic individuals vary more in microbial community composition than healthy individuals."

Keystone Taxa

Low-abundance species with high network connectivity:

Taxon	Role	Loss Consequence
Faecalibacterium prausnitzii	Butyrate producer, anti-inflammatory	↓ SCFA, ↑ inflammation
Akkermansia muciniphila	Mucin degrader, cross-feeding hub	Barrier dysfunction
Clostridium scindens	7α-dehydroxylation (bai operon)	Loss of colonization resistance
Roseburia spp.	Butyrate producer	↓ SCFA

Colonization Resistance (C. diff model)

- name: Loss of Colonization Resistance
  description: >
    The healthy microbiome prevents pathogen colonization through nutrient
    competition, niche exclusion, and antimicrobial production. Antibiotic
    disruption removes these barriers.
  notes: >
    Key taxa: Lachnospiraceae, Ruminococcaceae, Collinsella. C. scindens
    provides bile acid-mediated resistance via bai operon.
  downstream:
  - target: Pathogen Germination and Expansion

- name: Loss of Secondary Bile Acid Production
  description: >
    Depletion of 7α-dehydroxylating bacteria (C. scindens, C. hylemonae)
    prevents conversion of primary to secondary bile acids. Primary bile
    acids promote pathogen germination; secondary bile acids inhibit it.
  downstream:
  - target: Pathogen Germination and Expansion

SCFA Pathway Template

Common pattern for butyrate-related mechanisms:

- name: Loss of Keystone SCFA Producers
  description: >
    Depletion of butyrate-producing Firmicutes, particularly Faecalibacterium
    prausnitzii, Roseburia spp., and Eubacterium rectale. These keystone taxa
    support community structure through cross-feeding.
  notes: >
    F. prausnitzii is anti-inflammatory; its supernatant reduces colitis in
    animal models. Primary butyrate producers use the acetyl-CoA pathway.
  downstream:
  - target: Decreased Butyrate Production

- name: Decreased Butyrate Production
  description: >
    Reduced fecal SCFA concentrations, particularly butyrate. Butyrate is
    the primary energy source for colonocytes (~70% of energy) and exerts
    anti-inflammatory effects via HDAC inhibition and GPR109A signaling.
  biological_processes:
  - preferred_term: Short-chain Fatty Acid Metabolism
    term:
      id: GO:0046459
      label: short-chain fatty acid metabolic process
  downstream:
  - target: Impaired Colonocyte Energy Metabolism

     
     
      
    
       
         
  
      

Pathobiont Expansion Template

- name: Pathobiont Expansion
  description: >
    Bloom of opportunistic pathobionts (adherent-invasive E. coli, Fusobacterium,
    Enterobacteriaceae) that exploit niches vacated by depleted commensals.
    Promote inflammation through LPS and epithelial invasion.
  downstream:
  - target: Mucosal Inflammation
    description: LPS and pro-inflammatory molecules
  - target: Epithelial Barrier Dysfunction
    description: Direct epithelial invasion and tight junction disruption
  evidence:
  - reference: PMID:26185088
    supports: SUPPORT
    snippet: "This is often characterized by an increased relative abundance of facultative anaerobic bacteria (e.g., Enterobacteriaeceae, Bacilli) and, at the same time, depletion of obligate anaerobic bacteria."

BugSigDB Integration

When to Reference BugSigDB

• Identifying which taxa are commonly reported +/- in a condition
• Validating that your keystone taxa match published signatures
• Finding PMIDs for evidence

How to Search BugSigDB

# Web interface
open "https://bugsigdb.org/w/index.php?search=ulcerative+colitis"

# R/Bioconductor
# library(bugsigdbr)
# sigs <- getSignatures(condition = "ulcerative colitis")

Adding BugSigDB Notes

- name: Loss of Colonization Resistance
  notes: >
    Metagenomics studies consistently show CDI patients have depleted Lachnospiraceae,
    Ruminococcaceae, and Collinsella spp. compared to controls. BugSigDB signatures
    confirm depletion of these protective taxa.

Key References

Ecological Concepts

Concept	PMID	Citation
Anna Karenina principle	28836573	Zaneveld et al. 2017, Nat Microbiol
Diversity/stability	22972295	Lozupone et al. 2012, Nature
Alternative stable states	[search for recent]	Microbiome journal

IBD Microbiome

Topic	PMID	Citation
F. prausnitzii	18936492	Sokol et al. 2008, PNAS
IBD meta-analysis	25307765	Walters et al. 2014, FEBS Lett
Dysbiosis patterns	26185088	Stecher 2015, Microbiol Spectr

C. diff / Colonization Resistance

Topic	PMID	Citation
bai operon	32179626	Reed et al. 2020, J Bacteriol
C. scindens	28066726	Studer et al. 2016, Front Cell Infect Microbiol
Toxin mechanism	15831824	Voth & Ballard 2005, Clin Microbiol Rev

Ontology Terms

Biological Processes (GO)

uv run runoak -i sqlite:obo:go search "short-chain fatty acid"
uv run runoak -i sqlite:obo:go search "microbiome"

Process	GO ID
SCFA metabolic process	GO:0046459
Modification by symbiont	GO:0044003
Inflammatory response	GO:0006954

Cell Types (CL)

Cell	CL ID
Colon epithelial cell	CL:0011108
Goblet cell	CL:0000160
Neutrophil	CL:0000775

Organisms (NCBITaxon)

uv run runoak -i sqlite:obo:ncbitaxon search "Faecalibacterium"

Note: Do NOT use NCBITaxon in cell_types - microbial taxa are not cell types. Include taxa in description or notes fields instead.

Validation

# Full validation
just validate kb/disorders/MyDisorder.yaml

# Check evidence snippets against the reference cache (seconds, offline)
just count-verified-snippets kb/disorders/MyDisorder.yaml

# Before opening the PR: the batched schema+terms+references sweep CI runs
just validate-disorders kb/disorders/MyDisorder.yaml

# Generate HTML to visualize causal graph
uv run python -m dismech.render kb/disorders/MyDisorder.yaml
open pages/disorders/MyDisorder.html

Common Patterns by Disorder Type

IBD (UC, Crohn's)

1. Loss of Microbial Diversity
2. Loss of Keystone SCFA Producers (F. prausnitzii)
3. Pathobiont Expansion (AIEC, Fusobacterium)
4. Decreased Butyrate → Colonocyte Energy Deficit
5. Barrier Dysfunction
6. Anna Karenina instability (feedback)

C. diff Infection

1. Antibiotic-Induced Microbial Depletion
2. Loss of Colonization Resistance
3. Loss of Secondary Bile Acid Production
4. C. difficile Germination and Expansion
5. Toxin Production → Epithelial Death + Neutrophil Recruitment
6. Pseudomembranous Colitis

Obesity / Metabolic Syndrome

1. Firmicutes/Bacteroidetes ratio shift
2. Increased Energy Harvest
3. Altered Bile Acid Metabolism
4. Gut Barrier Permeability
5. Metabolic Endotoxemia (LPS)
6. Low-grade Inflammation

Integration with Other Skills

• dismech-terms: For ontology lookups (GO, CL, UBERON)
• dismech-references: For validating PMID snippets
• cancer-curator: Some cancers have microbiome components (colorectal)