Gene variant space for biosensor-based dynamic regulation

Inside a cell, protein, production and biosensor pathways can be genetically engineered within a dynamic regulation architecture that provides robustness to cell factories. Here we investigated how the selection of gene variants and their associated expression efficiency and kinetic parameters can lead to a wide diversity of dynamic responses in terms of protein or metabolite production. Results show that there is a trade-off between gene expression efficiency and pathway performance, and it can be eventually related to the evolutionary fingerprint of each gene variant. Therefore, the organism source of gene variants is a factor that needs to be considered in the design of dynamic regulation for genetic circuits.

Comparison of alternative integration sites in the chromosome and the native plasmids of the cyanobacterium Synechocystis sp. PCC 6803 in respect to expression efficiency and copy number

Background Synechocystis sp. PCC 6803 provides a well-established reference point to cyanobacterial metabolic engineering as part of basic photosynthesis research, as well as in the development of next-generation biotechnological production systems. This study focused on expanding the current knowledge on genomic integration of expression constructs in Synechocystis, targeting a range of novel sites in the chromosome and in the native plasmids, together with established loci used in literature. The key objective was to obtain quantitative information on site-specific expression in reference to replicon copy numbers, which has been speculated but never compared side by side in this host. Results An optimized sYFP2 expression cassette was successfully integrated in two novel sites in Synechocystis chromosome (slr0944; sll0058) and in all four endogenous megaplasmids (pSYSM/slr5037-slr5038; pSYSX/slr6037; pSYSA/slr7023; pSYSG/slr8030) that have not been previously evaluated for the purpose. Fluorescent analysis of the segregated strains revealed that the expression levels between the megaplasmids and chromosomal constructs were very similar, and reinforced the view that highest expression in Synechocystis can be obtained using RSF1010-derived replicative vectors or the native small plasmid pCA2.4 evaluated in comparison. Parallel replicon copy number analysis by RT-qPCR showed that the expression from the alternative loci is largely determined by the gene dosage in Synechocystis, thereby confirming the dependence formerly proposed based on literature. Conclusions This study brings together nine different integrative loci in the genome of Synechocystis to demonstrate quantitative differences between target sites in the chromosome, the native plasmids, and a RSF1010-based replicative expression vector. To date, this is the most comprehensive comparison of alternative integrative sites in Synechocystis, and provides the first direct reference between expression efficiency and replicon gene dosage in the context. In the light of existing literature, the findings support the view that the small native plasmids can be notably more difficult to target than the chromosome or the megaplasmids, and that the RSF1010-derived vectors may be surprisingly well maintained under non-selective culture conditions in this cyanobacterial host. Altogether, the work broadens our views on genomic integration and the rational use of different integrative loci versus replicative plasmids, when aiming at expressing heterologous genes in Synechocystis.

Modelling and Optimization of Processing Factors of Pumpkin Seeds Oil Extraction under Uniaxial Loading

In the present study, a Box–Behnken design of response surface methodology (RSM) was employed to optimize the processing factors (force: 100, 150, and 200 kN; speed: 3, 5, and 7 mm/min; and temperature: 40, 60, and 80 °C) for extracting pumpkin seeds oil under uniaxial compression. The design generated 15 experiments including twelve combinations of factors and three replicates at the center point. The responses: oil yield (%), oil expression efficiency (%), and energy (J) were calculated, and the regression models determined were statistically analyzed and validated. The optimum factors combination: 200 kN, 4 mm/min and 80 °C predicted the oil yield of 20.48%, oil expression efficiency of 60.90%, and energy of 848.04 J. The relaxation time of 12 min at the optimum factors increased the oil efficiency to 64.53%. The lower oil point force was determined to be 57.32 kN for estimating the maximum oil output. The tangent curve and generalized Maxwell models adequately (R2 = 0.996) described the compression and relaxation processes of pumpkin seeds oil extraction. Peroxide value increased with temperatures. The study provides detailed information useful for processing different bulk oilseeds under uniaxial loading for optimizing the mechanical oil pressing in large-scale oil production.

Investigation of Heating and Freezing Pretreatments on Mechanical, Chemical and Spectral Properties of Bulk Sunflower Seeds and Oil

The present study examined the effects of heating and freezing pretreatments on the mechanical, chemical, and spectral characteristics of sunflower seeds and oil under a linear compression process involving a universal compression-testing machine and a pressing vessel of diameter 60 mm with a plunger. The heating temperatures ranged from 40 to 80 °C and freezing temperatures from −2 to −36 °C at constant heating time of 30 min. The pretreated samples of initial height of 80 mm (22.6 × 10−5 m3) were compressed under a preset load of 100 kN and a speed of 5 mm/min. The results showed that oil expression efficiency significantly increased (p < 0.05) with increased heating temperatures but decreased with freezing temperatures. The lowest energy per volume oil of 22.55 ± 0.919 kJ/L was recorded at 80 °C compared to 26.40 ± 0.307 kJ/L noticed at −2 °C and control (25 °C) of 33.93 ± 3.866 kJ/L. The linear regression equations expressing oil expression efficiency, energy per volume oil, peroxide value, and free fatty acid, dependent on heating and freezing temperatures, were described with coefficients of determination between 0.373 and 0.908. Increased heating temperatures increased the UV absorption rate of the oil samples at a wavelength of 350 nm. The study is part of the continuing research on linear compression modeling of all processing factors, whereby the results are intended to be applied to the non-linear process dealing with a mechanical screw press to improve the oil extraction process.

Numerical optimization of microfluidic vortex shedding for genome editing human primary T cells using machine learning

Microfluidic vortex shedding (μVS) can rapidly deliver mRNA to human T cells with high yield and minimal perturbation. However, the mechanistic underpinning of μVS as an intracellular delivery method remains undefined with no optimization framework. Herein, we evaluated a series of μVS devices containing various splitter plates to attenuate vortex shedding and understand the contribution of force and frequency on expression efficiency and cell viability. We selected and applied a μVS design to knockout the expression of the endogenous T cell receptor of T cells via delivery of Cas9-RNP. 255 μVS samples were characterized across more than 150 parameters and machine learning was used to identify the 11 most predictive parameters for expression efficiency and cell viability. These results demonstrate the utility of μVS for genome editing of human T cells with CRISPR-Cas9 and provide a robust framework to optimize μVS for various constructs, cell types and protocols.

Self-organization controls expression more than abundance of molecular components of transcription and translation in confined cell-free gene expression

Cell-free gene expression using purified components or cell extracts has become an important platform for synthetic biology that is finding a growing numBer of practical applications. Unfortunately, at cell-relevant reactor volumes, cell-free expression suffers from excessive variability (noise) such that protein concentrations may vary by more than an order of magnitude across a population of identically constructed reaction chambers. Consensus opinion holds that variability in expression is due to the stochastic distribution of expression resources (DNA, RNAP, ribosomes, etc.) across the population of reaction chambers. In contrast, here we find that chamber-to-chamber variation in the expression efficiency generates the large variability in protein production. Through analysis and modeling, we show that chambers self-organize into expression centers that control expression efficiency. Chambers that organize into many centers, each having relatively few expression resources, exhibit high expression efficiency. Conversely, chambers that organize into just a few centers where each center has an abundance of resources, exhibit low expression efficiency. A particularly surprising finding is that diluting expression resources reduces the chamber-to-chamber variation in protein production. Chambers with dilute pools of expression resources exhibit higher expression efficiency and lower expression noise than those with more concentrated expression resources. In addition to demonstrating the means to tune expression noise, these results demonstrate that in cell-free systems, self-organization may exert even more influence over expression than the abundance of the molecular components of transcription and translation. These observations in cell-free platform may elucidate how self-organized, membrane-less structures emerge and function in cells.