Evidence map›Paper›PMID 42420733›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Dynamic Robust Control of Microbial Communities Using Cybergenetics.

Ting An Lee, Scott B Stacey, Olivia Gallup, Harrison Steel, Kirill Sechkar

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ting An LeeDepartment of Engineering Science, University of Oxford, Oxford, UK.
Scott B StaceyDepartment of Engineering Science, University of Oxford, Oxford, UK.
Olivia GallupDepartment of Engineering Science, University of Oxford, Oxford, UK.
Harrison SteelDepartment of Engineering Science, University of Oxford, Oxford, UK. harrison.steel@eng.ox.ac.uk.
Kirill SechkarDepartment of Engineering Science, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key enabler for the engineering of complex biological systems is the co-culturing different cell strains together in a microbial community. Co-cultures can exhibit more diverse capabilities, increased robustness, and greater efficiency than a single strain engineered for a given application. However, reliable long-term control of such intricate systems is a complex task, and achieving communities that coexist stably despite potentially fluctuating cellular environments has been difficult to achieve. This challenge can be addressed by distributing signal processing between cells and computers through cybergenetics. Specifically, cellular outputs can be measured by sensors connected to a computer, which processes these signals and adjusts the cell culture conditions to achieve a desired goal; the cells then respond to this, closing the control loop. Striking a balance between computer-based and biological control implementations allows combining the strengths of the two approaches while circumventing their limitations. Here, we describe a methodology for cybergenetic control of microbial communities, considering the associated technical requirements, possible modes of interfacing between cell consortia and computers, and the resultant scope of biological and hardware design choices. This example illustrates how combining computational modeling with direct biological implementation of gene circuits leads to more robust and controllable systems with novel functionalities and applications.

Indexed as

Microbial ConsortiaCoculture TechniquesComputer SimulationModels, BiologicalBioreactorCo-cultureCompositionComposition controlContinuous cultureCybergeneticsMicrobial communityQuantitativeSynthetic biology

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.