Majority sensing in synthetic microbial consortia

Alnahhas, Razan N.; Sadeghpour, Mehdi; Chen, Ye; Frey, Alexis A.; Ott, William; Josić, Krešimir; Bennett, Matthew R.

doi:10.1038/s41467-020-17475-z

Cited by 63 publications

(68 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the design, computational behaviors arise from the interactions between senders and receivers, even though the tasks performed in individual cell groups are relatively primitive. Similar themes have also been presented in other studies for majority sensing [30] and tunable population dynamics [31].…”

Section: Discussionsupporting

confidence: 75%

Synthetic neural-like computing in microbial consortia for pattern recognition

Rizik

Daniel

2020

Preprint

View full text Add to dashboard Cite

Complex biological systems in nature comprise of cells that act collectively to solve sophisticated tasks. Synthetic biological systems, in contrast, are designed for specific tasks, largely following computational principles including logic gates, analog design, and control theory. Yet such approaches cannot be easily adapted for multiple tasks in biological contexts. Alternatively, artificial neural networks (ANN), comprised of flexible interactions for processing and decision-making, are widely adopted for numerous applications and support adaptive designs. Motivated by the structural similarity between ANNs and cellular networks, here we implemented ANN-like computing in bacteria consortia for recognizing patterns. In cellular ANNs, receiver bacteria collectively interact through quorum sensing (QS) with sender bacteria for decision-making processes. Input patterns formed by chemical inducers, activate sender circuits to produce QS signaling molecules with varying levels. These levels are programmed by tuning the promoter strength acting as weights. We also developed an algorithm based on gradient descent, which is well-accepted in artificial intelligence, to optimize weights and experimentally examined them using 3x3-bit patterns.

show abstract

Section: Discussionsupporting

confidence: 75%

Synthetic neural-like computing in microbial consortia for pattern recognition

Rizik

Daniel

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The interaction between the host and gut microbiome can influence the central nervous system, modulating the brain and behavior, including mood (Muller et al, 2020 ). Synthetic biology is increasingly seeking to modulate, control and even design (Alnahhas et al, 2020 ) the microbial consortia that form microbiomes. Synthetic organisms can be used as medicines, engineered to perform metabolic functions that once ingested could treat disease (West et al, 2018 ).…”

Section: Resultsmentioning

confidence: 99%

A Systematic Review of the Criminogenic Potential of Synthetic Biology and Routes to Future Crime Prevention

Elgabry

Nesbeth

Johnson

2020

Front. Bioeng. Biotechnol.

View full text Add to dashboard Cite

Synthetic biology has the potential to positively transform society in many application areas, including medicine. In common with all revolutionary new technologies, synthetic biology can also enable crime. Like cybercrime, that emerged following the advent of the internet, biocrime can have a significant effect on society, but may also impact on peoples' health. For example, the scale of harm caused by the SARS-CoV-2 pandemic illustrates the potential impact of future biocrime and highlights the need for prevention strategies. Systematic evidence quantifying the crime opportunities posed by synthetic biology has to date been very limited. Here, we systematically reviewed forms of crime that could be facilitated by synthetic biology with a view to informing their prevention. A total of 794 articles from four databases were extracted and a three-step screening phase resulted in 15 studies that met our threshold criterion for thematic synthesis. Within those studies, 13 exploits were identified. Of these, 46% were dependent on technologies characteristic of synthetic biology. Eight potential crime types emerged from the studies: bio-discrimination, cyber-biocrime, bio-malware, biohacking, at-home drug manufacturing, illegal gene editing, genetic blackmail, and neuro-hacking. 14 offender types were identified. For the most commonly identified offenders (>3 mentions) 40% were outsider threats. These observations suggest that synthetic biology presents substantial new offending opportunities. Moreover, that more effective engagement, such as ethical hacking, is needed now to prevent a crime harvest from developing in the future. A framework to address the synthetic biology crime landscape is proposed.

show abstract

“…The signals could potentially be produced by two specific cell types, and the circuit's output could therefore report their ratio. Finally, a synthetic intercellular toggle-switch system can also function as a ratiometric sensing circuit [26] ( Figure 1F). The system is designed to switch on or off depending on which cell type is in the majority.…”

Section: Sensing Relative Population Compositionmentioning

confidence: 99%

Autonomous and Assisted Control for Synthetic Microbiology

Banderas

Bec

Cordier

et al. 2020

IJMS

View full text Add to dashboard Cite

The control of microbes and microbial consortia to achieve specific functions requires synthetic circuits that can reliably cope with internal and external perturbations. Circuits that naturally evolved to regulate biological functions are frequently robust to alterations in their parameters. As the complexity of synthetic circuits increases, synthetic biologists need to implement such robust control “by design”. This is especially true for intercellular signaling circuits for synthetic consortia, where robustness is highly desirable, but its mechanisms remain unclear. Cybergenetics, the interface between synthetic biology and control theory, offers two approaches to this challenge: external (computer-aided) and internal (autonomous) control. Here, we review natural and synthetic microbial systems with robustness, and outline experimental approaches to implement such robust control in microbial consortia through population-level cybergenetics. We propose that harnessing natural intercellular circuit topologies with robust evolved functions can help to achieve similar robust control in synthetic intercellular circuits. A “hybrid biology” approach, where robust synthetic microbes interact with natural consortia and—additionally—with external computers, could become a useful tool for health and environmental applications.

show abstract

Majority sensing in synthetic microbial consortia

Cited by 63 publications

References 51 publications

Synthetic neural-like computing in microbial consortia for pattern recognition

Synthetic neural-like computing in microbial consortia for pattern recognition

A Systematic Review of the Criminogenic Potential of Synthetic Biology and Routes to Future Crime Prevention

Autonomous and Assisted Control for Synthetic Microbiology

Contact Info

Product

Resources

About