The Robogut: A Bioreactor Model of the Human Colon for Evaluation of Gut Microbial Community Ecology and Function
Bibliographic record
Abstract
The human colon is inhabited by a complex community of microbes. These microbes are integral to host health and physiology. Understanding how and when the microbiome causally influences host health will require microbiome models that can be tightly controlled and manipulated. While in vivo models are unrivalled in their ability to study host-microbial interplay, in vitro models are gaining in popularity as methods to study the ecology and function of the gut microbiota, and benefit from tight controllability and reproducibility, as well as reduced ethical constraints. In this set of protocols, we describe the Robogut, a single-stage bioreactor system designed to replicate the conditions of the distal human colon, to culture whole microbial communities derived from stool and/or colonic biopsy samples, with consideration of methods to create culture medium formulations and to build, run, and sample the bioreactor apparatus. Cleaning and maintenance of the bioreactor system are also described. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Growth medium preparation Support Protocol 1: Preparing medium supplements Basic Protocol 2: Preparing the bioreactor vessels Support Protocol 2: Making acid and base bottles Support Protocol 3: Preparing the effluent bottles Support Protocol 4: Making acid solution Support Protocol 5: Making base solution Basic Protocol 3: Preparing inoculum and inoculating bioreactors Alternate Protocol 1: Preparing inoculum less than 0.5% (w/v) of vessel volume Alternate Protocol 2: Preparing synthetic community aliquots and inoculation via the septum Alternate Protocol 3: Preparing inoculum from a tissue sample Basic Protocol 4: Sampling the bioreactor vessel Basic Protocol 5: Harvesting bioreactor vessel contents at end of experiment Support Protocol 6: Cleaning and sterilizing sampling needles Basic Protocol 6: Cleaning the bioreactor vessel Support Protocol 7: Cleaning bioreactor support bottles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".