A novel, scalable, and modular bioreactor design for dynamic simulation of the digestive tract
Bibliographic record
Abstract
In vitro gut model systems permit the growth of gut microbes outside their natural habitat and are essential to the study of gut microbiota. Systems available today are limited by a lack of scalability and flexibility in the mode of operation. Here, we describe the development of a versatile bioreactor module that can be easily adjusted for culture size and capable of sensing and controlling of environmental parameters such as pH control of culture medium, rate of influx and efflux of the culture medium, and aerobic/anaerobic atmosphere. Bioreactor modules can be operated as single units or linked in series to construct a model of a digestive tract with multiple compartments to allow the growth of microbiota in vitro. We tested the growth of synthetic and natural bacterial communities in a multicompartment continuous dynamic culture model simulation of the mammalian gut. The distal compartments of a sterile system inoculated with the synthetic bacterial community at the proximal module attained a stable bacterial density by 24 h, and all the genera present in the inoculum were firmly established in the distal modules simulating the large intestine at 5 days of continuous culture. A natural bacterial community simultaneously inoculated into the distal modules attained a stable bacterial composition at the phylum level by Day 7 of continuous culture. The findings illustrate the utility of the system to culture mixed bacterial communities which can be used to study the collective biological activities of the cultured microbiota in the absence of host influence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".