Single strain control of microbial consortia

Fedorec, Alex J. H.; Karkaria, Behzad D.; Sulu, Michael; Barnes, C.

doi:10.1101/2019.12.23.887331

Cited by 18 publications

(28 citation statements)

References 46 publications

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“…For example, multi-agent modeling has been used to help understand how signaling and mutual cooperation can stabilize microbial communities (Kerényi et al, 2013). Furthermore, from a synthetic biology perspective many of the tools needed to engineer these systems already exist, e.g., biological parts able to implement cooperation (Shou et al, 2007), signaling (Bacchus et al, 2012), targeted death (Fedorec et al, 2019), and collective decision making (e.g., quorum sensing).…”

Section: Engineering Synthetic Ecologiesmentioning

confidence: 99%

Toward Engineering Biosystems With Emergent Collective Functions

Gorochowski

Hauert

Kreft

et al. 2020

Front. Bioeng. Biotechnol.

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Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.

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Section: Engineering Synthetic Ecologiesmentioning

confidence: 99%

Toward Engineering Biosystems With Emergent Collective Functions

Gorochowski

Hauert

Kreft

et al. 2020

Front. Bioeng. Biotechnol.

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“…Some of these bioreactor devices can be configured to measure the output of several fluorescent proteins simultaneously and control multiple inputs dynamically (Steel et al, 2019). Dilution rate has been cited several times as a critical controllable parameter; the rate of removal of molecules from the environment can produce very different population dynamics (Balagaddé et al, 2008;Weiße et al, 2015;Yurtsev et al, 2016;Fedorec et al, 2019). As such, possessing the correct tools is important for building distributed systems in liquid culture.…”

Section: Liquid and Solid State Environmentsmentioning

confidence: 99%

From Microbial Communities to Distributed Computing Systems

Karkaria¹,

Treloar²,

Barnes³

et al. 2020

Front. Bioeng. Biotechnol.

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A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

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“…Data from 10,000 cells were collected by manual gating of singlets during data collection, but for visual clarity, random samples of the data were used for dot plotting. Further data analysis was carried out using R. Singlets were selected from bulk data using the autoGate package [71] , and resultant data was plotted using R. Flow cytometry data was used primarily for method development but also with a view of using FACS sorting for selection. As such, the key measurement in many of the experiments was the proportion of cells scoring as above a 1D or 2D gate, where the gates represented a threshold value not occupied by the negative population and usable as a sorting gate during FACS.…”

Section: Assessment Of Membrane Protein Content Aliquots Of Cells Wementioning

confidence: 99%

Towards XNA molecular biology: Bacterial cell display as a robust and versatile platform for the engineering of low affinity ligands and enzymes

Csibra

Renders

Pinheiro

2020

Preprint

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Although directed evolution has been remarkably successful at expanding the chemical and functional boundaries of biology, it is limited by the robustness and flexibility of available selection platforms -traditionally designed around a single desired function with limited scope for alternative applications. We report SNAP as a quantitative reporter for bacterial cell display, which enabled fast troubleshooting and systematic development of the selection platform. In addition, we demonstrate that even weak interactions between displayed proteins and nucleic acids can be harnessed towards specific labelling of bacterial cells, allowing functional characterisation of DNA binding proteins and enzymes. Together, this establishes bacterial display as a viable route towards the systematic engineering of all ligands and enzymes required for the development of XNA molecular biology.

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Single strain control of microbial consortia

Cited by 18 publications

References 46 publications

Toward Engineering Biosystems With Emergent Collective Functions

Toward Engineering Biosystems With Emergent Collective Functions

From Microbial Communities to Distributed Computing Systems

Towards XNA molecular biology: Bacterial cell display as a robust and versatile platform for the engineering of low affinity ligands and enzymes

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