scholarly journals Rapid screening of engineered microbial therapies in a 3-D multicellular model

2018 ◽  
Author(s):  
Tetsuhiro Harimoto ◽  
Zakary S. Singer ◽  
Oscar S. Velazquez ◽  
Joanna Zhang ◽  
Samuel Castro ◽  
...  

AbstractSynthetic biology is transforming therapeutic paradigms by engineering living cells and microbes to intelligently sense and respond to diseases including inflammation1,2, infections3-5, metabolic disorders6,7, and cancer8,9. However, the ability to rapidly engineer new therapies far outpaces the throughput of animal-based testing regimes, creating a major bottleneck for clinical translation10,11. In vitro approaches to address this challenge have been limited in scalability and broad-applicability. Here, we present a bacteria-in-spheroid co-culture (BSCC) platform that simultaneously tests host species, therapeutic payloads and synthetic gene circuits of engineered bacteria within multicellular spheroids over a timescale of weeks. Long-term monitoring of bacterial dynamics and disease progression enables quantitative comparison of critical therapeutic parameters such as efficacy and biocontainment. Specifically, we screen S. typhimurium strains expressing and delivering a library of antitumor therapeutic molecules via several synthetic gene circuits. We identify novel candidates exhibiting significant tumor reduction and demonstrate high similarity in their efficacies using a syngeneic mouse model. Lastly, we show that our platform can be expanded to dynamically profile diverse microbial species including L. monocytogenes, P. mirabilis, and E. coli in various host cell types. This high-throughput framework may serve to accelerate synthetic biology for clinical applications and understanding the host-microbe interactions in disease sites.

2019 ◽  
Vol 116 (18) ◽  
pp. 9002-9007 ◽  
Author(s):  
Tetsuhiro Harimoto ◽  
Zakary S. Singer ◽  
Oscar S. Velazquez ◽  
Joanna Zhang ◽  
Samuel Castro ◽  
...  

Synthetic biology is transforming therapeutic paradigms by engineering living cells and microbes to intelligently sense and respond to diseases including inflammation, infections, metabolic disorders, and cancer. However, the ability to rapidly engineer new therapies far outpaces the throughput of animal-based testing regimes, creating a major bottleneck for clinical translation. In vitro approaches to address this challenge have been limited in scalability and broad applicability. Here, we present a bacteria-in-spheroid coculture (BSCC) platform that simultaneously tests host species, therapeutic payloads, and synthetic gene circuits of engineered bacteria within multicellular spheroids over a timescale of weeks. Long-term monitoring of bacterial dynamics and disease progression enables quantitative comparison of critical therapeutic parameters such as efficacy and biocontainment. Specifically, we screen Salmonella typhimurium strains expressing and delivering a library of antitumor therapeutic molecules via several synthetic gene circuits. We identify candidates exhibiting significant tumor reduction and demonstrate high similarity in their efficacies, using a syngeneic mouse model. Last, we show that our platform can be expanded to dynamically profile diverse microbial species including Listeria monocytogenes, Proteus mirabilis, and Escherichia coli in various host cell types. This high-throughput framework may serve to accelerate synthetic biology for clinical applications and for understanding the host–microbe interactions in disease sites.


2020 ◽  
Author(s):  
Lei Wei ◽  
Shuailin Li ◽  
Tao Hu ◽  
Michael Q. Zhang ◽  
Zhen Xie ◽  
...  

AbstractGene expression noise plays an important role in many biological processes, such as cell differentiation and reprogramming. It can also dramatically influence the behavior of synthetic gene circuits. MicroRNAs (miRNAs) have been shown to reduce the noise of lowly expressed genes and increase the noise of highly expressed genes, but less is known about how miRNAs with different properties may regulate gene expression noise differently. Here, by quantifying gene expression noise using mathematical modeling and experimental measurements, we showed that competing RNAs and the composition of miRNA response elements (MREs) play important roles in modulating gene expression noise. We found that genes targeted by miRNAs with weak competing RNAs show lower noise than those targeted by miRNAs with strong competing RNAs. In addition, in comparison with a single MRE, repetitive MREs targeted by the same miRNA suppress the noise of lowly expressed genes but increase the noise of highly expressed genes. Additionally, MREs composed of different miRNA targets could cause similar repression levels but lower noise compared with repetitive MREs. We further observed the influence of miRNA-mediated noise modulation in synthetic gene circuits which could be applied to classify cell types using miRNAs as sensors. We found that miRNA sensors that introduce higher noise could lead to better classification performance. Our results provide a systematic and quantitative understanding of the function of miRNAs in controlling gene expression noise and how we can utilize miRNAs to modulate the behavior of synthetic gene circuits.


2021 ◽  
pp. 1-18
Author(s):  
Andrew Lezia ◽  
Arianna Miano ◽  
Jeff Hasty

Author(s):  
Barbara Jusiak ◽  
Ramiz Daniel ◽  
Fahim Farzadfard ◽  
Lior Nissim ◽  
Oliver Purcell ◽  
...  

2017 ◽  
Vol 1 (1) ◽  
pp. 30-39 ◽  
Author(s):  
Huijuan Wang ◽  
Maurice H.T. Ling ◽  
Tze Kwang Chua ◽  
Chueh Loo Poh

2019 ◽  
Author(s):  
Javier Santos-Moreno ◽  
Eve Tasiudi ◽  
Joerg Stelling ◽  
Yolanda Schaerli

AbstractGene expression control based on CRISPRi (clustered regularly interspaced short palindromic repeats interference) has emerged as a powerful tool for creating synthetic gene circuits, both in prokaryotes and in eukaryotes; yet, its lack of cooperativity has been pointed out as a potential obstacle for dynamic or multistable circuit construction. Here we use CRISPRi to build prominent synthetic gene circuits in Escherichia coli. We report the first-ever CRISPRi oscillator (“CRISPRlator”), bistable network (toggle switch) and stripe pattern-forming incoherent feed-forward loop (IFFL). Our circuit designs, conceived to feature high predictability and orthogonality, as well as low metabolic burden and context-dependency, allowed us to achieve robust circuit behaviors. Mathematical modeling suggests that unspecific binding in CRISPRi is essential to establish multistability. Our work demonstrates the wide applicability of CRISPRi in synthetic circuits and paves the way for future efforts towards engineering more complex synthetic networks, boosted by the advantages of CRISPR technology.


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