The Evolution of Cell Free Biomanufacturing

Vilkhovoy, Michael; Adhikari, Abhinav; Vadhin, Sandra; Varner, Jeffrey D.

doi:10.20944/preprints202003.0461.v1

Cited by 5 publications

(6 citation statements)

References 136 publications

(165 reference statements)

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“…It is imperative that this metabolic burden by the addition of exogenous genes be incorporated in the in vivo model description to accurately capture the expression behavior. We have recently started to explore this question by integrating effective transcription and translation models with metabolic networks in cell free reactions e.g., Vilkhovoy et al, 2018;Horvath et al, 2020, and also developing experimental tools to measure metabolite concentrations in cell free systems (Vilkhovoy et al, 2019). However, these previous transcriptional and translational models (and similar precursor models simulating eukaryotic processes, Gould et al, 2016;Tasseff et al, 2017) were less developed than those presented here.…”

Section: Discussionmentioning

confidence: 99%

Effective Biophysical Modeling of Cell Free Transcription and Translation Processes

Adhikari

Vilkhovoy

Vadhin

et al. 2020

Front. Bioeng. Biotechnol.

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Transcription and translation are at the heart of metabolism and signal transduction. In this study, we developed an effective biophysical modeling approach to simulate transcription and translation processes. The model, composed of coupled ordinary differential equations, was tested by comparing simulations of two cell free synthetic circuits with experimental measurements generated in this study. First, we considered a simple circuit in which sigma factor 70 induced the expression of green fluorescent protein. This relatively simple case was then followed by a more complex negative feedback circuit in which two control genes were coupled to the expression of a third reporter gene, green fluorescent protein. Many of the model parameters were estimated from previous biophysical studies in the literature, while the remaining unknown model parameters for each circuit were estimated by minimizing the difference between model simulations and messenger RNA (mRNA) and protein measurements generated in this study. In particular, either parameter estimates from published studies were used directly, or characteristic values found in the literature were used to establish feasible ranges for the parameter estimation problem. In order to perform a detailed analysis of the influence of individual model parameters on the expression dynamics of each circuit, global sensitivity analysis was used. Taken together, the effective biophysical modeling approach captured the expression dynamics, including the transcription dynamics, for the two synthetic cell free circuits. While, we considered only two circuits here, this approach could potentially be extended to simulate other genetic circuits in both cell free and whole cell biomolecular applications as the equations governing the regulatory control functions are modular and easily modifiable. The model code, parameters, and analysis scripts are available for download under an MIT software license from the Varnerlab GitHub repository.

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Section: Discussionmentioning

confidence: 99%

Effective Biophysical Modeling of Cell Free Transcription and Translation Processes

Adhikari

Vilkhovoy

Vadhin

et al. 2020

Front. Bioeng. Biotechnol.

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“…This has been demonstrated by a number of modeling studies of increasing sophistication (Karzbrun et al, 2011;Stögbauer et al, 2012;Tuza et al, 2015;Gyorgy and Murray, 2016;Nieß et al, 2017;Marshall and Noireaux, 2019), as well as notable examples of model-guided forward engineering of genetic circuits (Hu et al, 2015(Hu et al, , 2018Agrawal et al, 2019;Lehr et al, 2019;Westbrook et al, 2019). Recent development of integrated gene expression and metabolic models have elucidated the factors limiting CFPS (Wayman et al, 2015;Vilkhovoy et al, 2018Vilkhovoy et al, , 2019Horvath et al, 2020), suggesting that combined computational and experimental metabolomic studies are poised to contribute significantly to our understanding of CFPS in lysates.…”

Section: Model-guided Designmentioning

confidence: 98%

“…This property can be leveraged, for example, to change redox environments to promote disulphide bond formation (Matsuda et al, 2013). The kinetic progress of reactions can be followed using fluorescence from proteins and mRNA, as well as realtime metabolomic profiling, which has allowed the internal metabolism of cell-free systems to be dissected at high resolution (Bujara et al, 2011;Vilkhovoy et al, 2019). For GRN design, parameters, such as dissociation and kinetic constants between a transcription factor and promoter may be measured in situ (Geertz et al, 2012;Swank et al, 2019), and perturbations applied to the reaction composition to facilitate parameter identification and model selection (Hu et al, 2015;Moore et al, 2018).…”

Section: Accessible System: Without a Barrier Between The Reactionmentioning

confidence: 99%

Cell-Free Systems: A Proving Ground for Rational Biodesign

Laohakunakorn

2020

Front. Bioeng. Biotechnol.

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Cell-free gene expression systems present an alternative approach to synthetic biology, where biological gene expression is harnessed inside non-living, in vitro biochemical reactions. Taking advantage of a plethora of recent experimental innovations, they easily overcome certain challenges for computer-aided biological design. For instance, their open nature renders all their components directly accessible, greatly facilitating model construction and validation. At the same time, these systems present their own unique difficulties, such as limited reaction lifetimes and lack of homeostasis. In this Perspective, I propose that cell-free systems are an ideal proving ground to test rational biodesign strategies, as demonstrated by a small but growing number of examples of model-guided, forward engineered cell-free biosystems. It is likely that advances gained from this approach will contribute to our efforts to more reliably and systematically engineer both cell-free as well as living cellular systems for useful applications.

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“…CF reactions were supplemented with 11.2 mM lactose as indicated. Samples were incubated for 0, 0.5, 5, and 15 h at 29 °C and then were analyzed by LC-MS using the protocol described in Vilkhovoy et al 68 Briefly, the samples were first deproteinized by adding an equal volume of ice-cold 100% ethanol. This mixture was centrifuged at 12 000g for 15 min at 4 °C, and the supernatant fraction, which contained the metabolites, was collected and diluted 5-fold in ultrapure water to a volume of 50 μL.…”

Section: ■ Conclusionmentioning

confidence: 99%

Constructing Cell-Free Expression Systems for Low-Cost Access

et al. 2022

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Cell-free systems for gene expression have gained attention as platforms for the facile study of genetic circuits and as highly effective tools for teaching. Despite recent progress, the technology remains inaccessible for many in low- and middle-income countries due to the expensive reagents required for its manufacturing, as well as specialized equipment required for distribution and storage. To address these challenges, we deconstructed processes required for cell-free mixture preparation and developed a set of alternative low-cost strategies for easy production and sharing of extracts. First, we explored the stability of cell-free reactions dried through a low-cost device based on silica beads, as an alternative to commercial automated freeze dryers. Second, we report the positive effect of lactose as an additive for increasing protein synthesis in maltodextrin-based cell-free reactions using either circular or linear DNA templates. The modifications were used to produce active amounts of two high-value reagents: the isothermal polymerase Bst and the restriction enzyme Bsa I. Third, we demonstrated the endogenous regeneration of nucleoside triphosphates and synthesis of pyruvate in cell-free systems (CFSs) based on phosphoenol pyruvate (PEP) and maltodextrin (MDX). We exploited this novel finding to demonstrate the use of a cell-free mixture completely free of any exogenous nucleotide triphosphates (NTPs) to generate high yields of sfGFP expression. Together, these modifications can produce desiccated extracts that are 203–424-fold cheaper than commercial versions. These improvements will facilitate wider use of CFS for research and education purposes.

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The Evolution of Cell Free Biomanufacturing

Cited by 5 publications

References 136 publications

Effective Biophysical Modeling of Cell Free Transcription and Translation Processes

Effective Biophysical Modeling of Cell Free Transcription and Translation Processes

Cell-Free Systems: A Proving Ground for Rational Biodesign

Constructing Cell-Free Expression Systems for Low-Cost Access

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