Exploring the putative microRNAs cross-kingdom transfer in Solanum lycopersicum-Meloidogyne incognita interactions.

Introduction: Plant-pathogen interaction is an inexhaustible source of information on how to sustainably control diseases that negatively affect agricultural production. Meloidogyne incognita is a root-knot nematode (RKN), representing a pest for many crops, including tomato (Solanum lycopersicum). RKNs are a global threat to agriculture, especially under climate change, and RNA technologies offer a potential alternative to chemical nematicides. While endogenous microRNAs have been identified in both S. lycopersicum and M. incognita, and their roles have been related to the regulation of developmental changes, no study has investigated the miRNAs cross-kingdom transfer during this interaction. Methods: Here, we propose a bioinformatics pipeline to highlight potential miRNA-dependent cross-kingdom interactions between tomato and M. incognita. Results: The obtained data show that nematode miRNAs putatively targeting tomato genes are mostly related to detrimental effects on plant development and defense. Similarly, tomato miRNAs putatively targeting M. incognita biological processes have negative effects on digestion, mobility, and reproduction. To experimentally test this hypothesis, an in vitro feeding assay was carried out using sly-miRNAs selected from the bioinformatics approach. The results show that two tomato miRNAs (sly-miRNA156a, sly-miR169f) soaked by juvenile larvae (J2s) affected their ability to infect plant roots and form galls. This was also coupled with a significant downregulation of predicted target genes (Minc11367, Minc00111), as revealed by a qRT-PCR analysis. Discussions: Therefore, the current study expands the knowledge related to the cross-kingdom miRNAs involvement in host-parasite interactions and could pave the way for the application of exogenous plant miRNAs as tools to control nematode infection.

Design and Model-Driven Analysis of Synthetic Circuits with the Staphylococcus aureus Dead-Cas9 (sadCas9) as a Programmable Transcriptional Regulator in Bacteria.

Synthetic circuit design is crucial for engineering microbes that process environmental cues and provide biologically relevant outputs. To reliably scale-up circuit complexity, the availability of parts toolkits is central. Streptococcus pyogenes (sp)-derived CRISPR interference/dead-Cas9 (CRISPRi/spdCas9) is widely adopted for implementing programmable regulations in synthetic circuits, and alternative CRISPRi systems will further expand our toolkits of orthogonal components. Here, we showcase the potential of CRISPRi using the engineered dCas9 from Staphylococcus aureus (sadCas9), not previously used in bacterial circuits, that is attractive for its low size and high specificity. We designed a collection of ∼20 increasingly complex circuits and variants in Escherichia coli, including circuits with static function like one-/two-input logic gates (NOT, NAND), circuits with dynamic behavior like incoherent feedforward loops (iFFLs), and applied sadCas9 to fix a T7 polymerase-based cascade. Data demonstrated specific and efficient target repression (100-fold) and qualitatively successful functioning for all circuits. Other advantageous features included low sadCas9-borne cell load and orthogonality with spdCas9. However, different circuit variants showed quantitatively unexpected and previously unreported steady-state responses: the dynamic range, switch point, and slope of NOT/NAND gates changed for different output promoters, and a multiphasic behavior was observed in iFFLs, differing from the expected bell-shaped or sigmoidal curves. Model analysis explained the observed curves by complex interplays among components, due to reporter gene-borne cell load and regulator competition. Overall, CRISPRi/sadCas9 successfully expanded the available toolkit for bacterial engineering. Analysis of our circuit collection depicted the impact of generally neglected effects modulating the shape of component dose-response curves, to avoid drawing wrong conclusions on circuit functioning.

An In Vitro Study on the Role of Cellulases and Xylanases of Bacillus subtilis in Dairy Cattle Nutrition.

The administration of Bacilli to dairy cows exerts beneficial effects on dry matter intake, lactation performance, and milk composition, but the rationale behind their efficacy is still poorly understood. In this work, we sought to establish whether cellulases and xylanases, among the enzymes secreted by B. subtilis, are involved in the positive effect exerted by Bacilli on ruminal performance. We took advantage of two isogenic B. subtilis strains, only differing in the secretion levels of those two enzymes. A multi-factorial study was conducted in which eight feed ingredients were treated in vitro, using ruminal fluid from cannulated cows, with cultures of the two strains conveniently grown in a growth medium based on inexpensive waste. Feed degradability and gas production were assessed. Fiber degradability was 10% higher (p < 0.001) in feeds treated with the enzyme-overexpressing strain than in the untreated control, while the non-overexpressing strain provided a 5% increase. The benefit of the fibrolytic enzymes was maximal for maize silage, the most recalcitrant feed. Gas production also correlated with the amount of enzymes applied (p < 0.05). Our results revealed that B. subtilis cellulases and xylanases effectively contribute to improving forage quality, justifying the use of Bacilli as direct-fed microbials to increase animal productivity.

Design of a stable ethanologenic bacterial strain without heterologous plasmids and antibiotic resistance genes for efficient ethanol production from concentrated dairy waste.

Engineering sustainable bioprocesses that convert abundant waste into fuels is pivotal for efficient production of renewable energy. We previously engineered an Escherichia coli strain for optimized bioethanol production from lactose-rich wastewater like concentrated whey permeate (CWP), a dairy effluent obtained from whey valorization processes. Although attractive fermentation performances were reached, significant improvements are required to eliminate recombinant plasmids, antibiotic resistances and inducible promoters, and increase ethanol tolerance. Here, we report a new strain with chromosomally integrated ethanologenic pathway under the control of a constitutive promoter, without recombinant plasmids and resistance genes. The strain showed extreme stability in 1-month subculturing, with CWP fermentation performances similar to the ethanologenic plasmid-bearing strain. We then investigated conditions enabling efficient ethanol production and sugar consumption by changing inoculum size and CWP concentration, revealing toxicity- and nutritional-related bottlenecks. The joint increase of ethanol tolerance, via adaptive evolution, and supplementation of small ammonium sulphate amounts (0.05% w/v) enabled a fermentation boost with 6.6% v/v ethanol titer, 1.2 g/L/h rate, 82.5% yield, and cell viability increased by three orders of magnitude. Our strain has attractive features for industrial settings and represents a relevant improvement in the existing ethanol production biotechnologies.

Design and biofabrication of bacterial living materials with robust and multiplexed biosensing capabilities.

The intertwined adoption of synthetic biology and 3D bioprinting has the potential to improve different application fields by fabricating engineered living materials (ELMs) with unnatural genetically-encoded sense & response capabilities. However, efforts are still needed to streamline the fabrication of sensing ELMs compatible with field use and improving their functional complexity. To investigate these two unmet needs, we adopted a workflow to reproducibly construct bacterial ELMs with synthetic biosensing circuits that provide red pigmentation as visible readout in response to different proof-of-concept chemical inducers. We first fabricated single-input/single-output ELMs and we demonstrated their robust performance in terms of longevity (cell viability and evolutionary stability >15 days, and long-term storage >1 month), sensing in harsh, non-sterile or nutrient-free conditions compatible with field use (soil, water, and clinical samples, including real samples from Pseudomonas aeruginosa infected patients). Then, we fabricated ELMs including multiple spatially-separated biosensor strains to engineer: level-bar materials detecting molecule concentration ranges, multi-input/multi-output devices with multiplexed sensing and information processing capabilities, and materials with cell-cell communication enabling on-demand pattern formation. Overall, we showed successful field use and multiplexed functioning of reproducibly fabricated ELMs, paving the way to a future automation of the prototyping process and boosting applications of such devices as in-situ monitoring tools or easy-to-use sensing kits.

dCas9 regulator to neutralize competition in CRISPRi circuits.

CRISPRi-mediated gene regulation allows simultaneous control of many genes. However, highly specific sgRNA-promoter binding is, alone, insufficient to achieve independent transcriptional regulation of multiple targets. Indeed, due to competition for dCas9, the repression ability of one sgRNA changes significantly when another sgRNA becomes expressed. To solve this problem and decouple sgRNA-mediated regulatory paths, we create a dCas9 concentration regulator that implements negative feedback on dCas9 level. This allows any sgRNA to maintain an approximately constant dose-response curve, independent of other sgRNAs. We demonstrate the regulator performance on both single-stage and layered CRISPRi-based genetic circuits, zeroing competition effects of up to 15-fold changes in circuit I/O response encountered without the dCas9 regulator. The dCas9 regulator decouples sgRNA-mediated regulatory paths, enabling concurrent and independent regulation of multiple genes. This allows predictable composition of CRISPRi-based genetic modules, which is essential in the design of larger scale synthetic genetic circuits.

CRISPR Interference Modules as Low-Burden Logic Inverters in Synthetic Circuits.

CRISPR and CRISPRi systems have revolutionized our biological engineering capabilities by enabling the editing and regulation of virtually any gene, via customization of single guide RNA (sgRNA) sequences. CRISPRi modules can work as programmable logic inverters, in which the dCas9-sgRNA complex represses a target transcriptional unit. They have been successfully used in bacterial synthetic biology to engineer information processing tasks, as an alternative to the traditionally adopted transcriptional regulators. In this work, we investigated and modulated the transfer function of several model systems with specific focus on the cell load caused by the CRISPRi logic inverters. First, an optimal expression cassette for dCas9 was rationally designed to meet the low-burden high-repression trade-off. Then, a circuit collection was studied at varying levels of dCas9 and sgRNAs targeting three different promoters from the popular tet, lac and lux systems, placed at different DNA copy numbers. The CRISPRi NOT gates showed low-burden properties that were exploited to fix a high resource-consuming circuit previously exhibiting a non-functional input-output characteristic, and were also adopted to upgrade a transcriptional regulator-based NOT gate into a 2-input NOR gate. The obtained data demonstrate that CRISPRi-based modules can effectively act as low-burden components in different synthetic circuits for information processing.

Combining Millimeter-Wave Imaging, Ultrasound and Elastography in a New Multimodal Approach for Breast Cancer Detection: Initial Experimental Results.

In this paper, for the first time, a triple-mode scan using electromagnetic waves, in the shape of millimeter waves, and ultrasound waves, to obtain B-mode and quasistatic elastography images of a phantom of human breast tissues is shown. A homogeneous phantom composed of nontoxic, low-cost and easy-to-handle materials (i.e. water, oil, gelatin and dishwashing liquid) was produced, with an inclusion made of water and agar. These are intended to mimic, in terms of dielectric properties, healthy adipose tissues and neoplastic tissues, respectively. A millimeter-wave imaging prototype was used to scan the phantom, by implementing a linear synthetic array of 24 antennas with a central working frequency of 30 GHz. The phantom was then scanned using an ultrasound research system and a linear-array probe at 7 MHz, acquiring both B-mode and quasi-static elastography images. The millimeter-wave system showed an excellent ability to detect the target placed at about 1.4 cm depth. Also in the ultrasound case the inclusion was correctly detected as a hypoechoic, stiff mass. This first experimental findings show that millimeter-wave, ultrasound and elasticity imaging can be used jointly to detect tumor-like targets into phantoms mimicking healthy breast tissues. Thus, they provide promising preliminary results to further study the application of this multimodal approach in all those critical cases in which such complementary imaging techniques could be exploited for an enhanced tumor detection, based on tissues dielectric, acoustic and elastic properties.

Ethambutol disposition in humans: Challenges and limitations of whole-body physiologically-based pharmacokinetic modelling in early drug development.

Whole-body physiologically based pharmacokinetic (WB-PBPK) models have become an important tool in drug development, as they enable characterization of pharmacokinetic profiles across different organs based on physiological (systems-specific) and physicochemical (drug-specific) properties. However, it remains unclear which data are needed for accurate predictions when applying the approach to novel candidate molecules progressing into the clinic. In this work, as case study, we investigated the predictive performance of WB-PBPK models both for prospective and retrospective evaluation of the pharmacokinetics of ethambutol, considering scenarios that reflect different stages of development, including settings in which the data are limited to in vitro experiments, in vivo preclinical data, and when some clinical data are available. Overall, the accuracy of PBPK model-predicted systemic and tissue exposure was heavily dependant on prior knowledge about the eliminating organs. Whilst these findings may be specific to ethambutol, the challenges and potential limitations identified here may be relevant to a variety of drugs, raising questions about (1) the minimum requirements for prospective use of WB-PBPK models during the characterization of drug disposition and (2) implication of uncertainty for dose selection in humans.

Engineering endogenous fermentative routes in ethanologenic Escherichia coli W for bioethanol production from concentrated whey permeate.

Whey permeate (WP) is a lactose-rich waste effluent, generated during cheese manufacturing and further valorization steps, such as protein extraction. The production of ethanol by WP fermentation has been proposed to increase cost-competitiveness of dairy waste processing. In previous work, the Escherichia coli W strain was selected for its efficient growth in dairy waste and it was engineered to convert lactose into ethanol as the main fermentation product from WP and concentrated WP (CWP). To improve its performance, here the lactate dehydrogenase, fumarate reductase and pyruvate formate lyase fermentative routes were disrupted, obtaining new deletion strains. In test tubes, growth and fermentation profiles obtained in standard laboratory media and CWP showed large differences, and were affected by oxygen, medium and ethanologenic gene expression level. Among the tested strains, the one with triple deletion was superior in both high-oxygen and low-oxygen test tube fermentations, in terms of ethanol titer, rate and yield. The improved performance was due to a lower inhibition by medium acidification rather than an improved ethanol flux. The parent and triple deletion strains showed similar performance indexes in pH-controlled bioreactor experiments. However, the deletion strain showed lower base consumption and residual waste, in terms of both dry matter and chemical oxygen demand after distillation. It thus represents a step towards sustainable dairy wastewater valorization for bioenergy production by decreasing process operation costs.

A Bioinformatics Approach to Explore MicroRNAs as Tools to Bridge Pathways Between Plants and Animals. Is DNA Damage Response (DDR) a Potential Target Process?

MicroRNAs, highly-conserved small RNAs, act as key regulators of many biological functions in both plants and animals by post-transcriptionally regulating gene expression through interactions with their target mRNAs. The microRNA research is a dynamic field, in which new and unconventional aspects are emerging alongside well-established roles in development and stress adaptation. A recent hypothesis states that miRNAs can be transferred from one species to another and potentially target genes across distant species. Here, we propose to look into the trans-kingdom potential of miRNAs as a tool to bridge conserved pathways between plant and human cells. To this aim, a novel multi-faceted bioinformatic analysis pipeline was developed, enabling the investigation of common biological processes and genes targeted in plant and human transcriptome by a set of publicly available Medicago truncatula miRNAs. Multiple datasets, including miRNA, gene, transcript and protein sequences, expression profiles and genetic interactions, were used. Three different strategies were employed, namely a network-based pipeline, an alignment-based pipeline, and a M. truncatula network reconstruction approach, to study functional modules and to evaluate gene/protein similarities among miRNA targets. The results were compared in order to find common features, e.g., microRNAs targeting similar processes. Biological processes like exocytosis and response to viruses were common denominators in the investigated species. Since the involvement of miRNAs in the regulation of DNA damage response (DDR)-associated pathways is barely explored, especially in the plant kingdom, a special attention is given to this aspect. Hereby, miRNAs predicted to target genes involved in DNA repair, recombination and replication, chromatin remodeling, cell cycle and cell death were identified in both plants and humans, paving the way for future interdisciplinary advancements.

Integration of enzymatic data in Bacillus subtilis genome-scale metabolic model improves phenotype predictions and enables in silico design of poly-γ-glutamic acid production strains.

BACKGROUND: Genome-scale metabolic models (GEMs) allow predicting metabolic phenotypes from limited data on uptake and secretion fluxes by defining the space of all the feasible solutions and excluding physio-chemically and biologically unfeasible behaviors. The integration of additional biological information in genome-scale models, e.g., transcriptomic or proteomic profiles, has the potential to improve phenotype prediction accuracy. This is particularly important for metabolic engineering applications where more accurate model predictions can translate to more reliable model-based strain design. RESULTS: Here we present a GEM with Enzymatic Constraints using Kinetic and Omics data (GECKO) model of Bacillus subtilis, which uses publicly available proteomic data and enzyme kinetic parameters for central carbon (CC) metabolic reactions to constrain the flux solution space. This model allows more accurate prediction of the flux distribution and growth rate of wild-type and single-gene/operon deletion strains compared to a standard genome-scale metabolic model. The flux prediction error decreased by 43% and 36% for wild-type and mutants respectively. The model additionally increased the number of correctly predicted essential genes in CC pathways by 2.5-fold and significantly decreased flux variability in more than 80% of the reactions with variable flux. Finally, the model was used to find new gene deletion targets to optimize the flux toward the biosynthesis of poly-γ-glutamic acid (γ-PGA) polymer in engineered B. subtilis. We implemented the single-reaction deletion targets identified by the model experimentally and showed that the new strains have a twofold higher γ-PGA concentration and production rate compared to the ancestral strain. CONCLUSIONS: This work confirms that integration of enzyme constraints is a powerful tool to improve existing genome-scale models, and demonstrates the successful use of enzyme-constrained models in B. subtilis metabolic engineering. We expect that the new model can be used to guide future metabolic engineering efforts in the important industrial production host B. subtilis.

Tissue-mimicking materials for breast phantoms up to 50 GHz.

Millimeter (mm)-wave imaging has been recently proposed as a new technique for breast cancer detection, based on the significant dielectric contrast between healthy and tumor tissues. Here we propose a procedure to fabricate, electromagnetically characterize and preserve realistic breast tissue-mimicking phantoms for testing mm-wave imaging prototypes. Low-cost, non-toxic and easy-to-produce mixtures made of sunflower oil, water and gelatin were prepared and their dielectric properties were for the first time measured in the (0.5-50) GHz frequency range using a coaxial probe kit. Different oil and gelatin percentages were tested. An alternative recipe based on a waste-oil hardener was also proposed. Finally, water and sunflower oil were investigated as preservation media. The mixtures electromagnetic properties were in good agreement with those of human breast ex vivo samples. By changing the ingredient concentrations or using different solidifying agents it was possible to mimic different tissue types. Besides, we show that sunflower oil represents an effective preservation medium for the developed materials. The first breast phantom mimicking a tumor mass into healthy tissues up to 50 GHz was also successfully fabricated. Results demonstrated the potential of the designed recipes to mimic breast tissues with different biological characteristics, preserving dielectric properties over time. Thus, this study represents a fundamental step towards the development of heterogeneous breast phantoms able to mimic the electromagnetic behavior of healthy and tumor tissues for mm-wave imaging applications.

A Synthetic Close-Loop Controller Circuit for the Regulation of an Extracellular Molecule by Engineered Bacteria.

Feedback control is ubiquitous in biological systems. It can also play a crucial role in the design of synthetic circuits implementing novel functions in living systems, to achieve self-regulation of gene expression, noise reduction, rise time decrease, or adaptive pathway control. Despite in vitro, in vivo, and ex vivo implementations have been successfully reported, the design of biological close-loop systems with quantitatively predictable behavior is still a major challenge. In this work, we tested a model-based bottom-up design of a synthetic close-loop controller in engineered Escherichia coli, aimed to automatically regulate the concentration of an extracellular molecule, N-(3-oxohexanoyl)-L-homoserine lactone (HSL), by rewiring the elements of heterologous quorum sensing/quenching networks. The synthetic controller was successfully constructed and experimentally validated. Relying on mathematical model and experimental characterization of individual regulatory parts and enzymes, we evaluated the predictability of the interconnected system behavior in vivo. The culture was able to reach an HSL steady-state level of 72 nM, accurately predicted by the model, and showed superior capabilities in terms of robustness against cell density variation and disturbance rejection, compared with a corresponding open-loop circuit. This engineering-inspired design approach may be adopted for the implementation of other close-loop circuits for different applications and contribute to decreasing trial-and-error steps.

Complex Bayesian Modeling Workflows Encoding and Execution Made Easy With a Novel WinBUGS Plugin of the Drug Disease Model Resources Interoperability Framework.

The Drug Disease Model Resources (DDMoRe) Interoperability Framework (IOF) enables pharmacometric model encoding and execution via Model Description Language (MDL) and R language, through the ddmore package. Through its components and converter plugins, the IOF can execute pharmacometric tasks using different target tools, starting from a single MDL-encoded model. In this article, we present the WinBUGS plugin and show how its integration in the IOF enables an easy implementation of complex Bayesian workflows. We selected a published diabetes-linked study as a real-world example, in which two inter-related models are used to estimate insulin secretion rate in response to a glucose stimulus from intravenous glucose tolerance test (IVGTT) data. This model was implemented following different approaches to propagate uncertainty, via diverse IOF target tools (NONMEM, WinBUGS, PsN, and Xpose). The developed software supports a plethora of pharmacokinetic/pharmacodynamic (PK/PD) modeling features. It provides solutions to reproducibility and interoperability issues in Bayesian modeling, and facilitates the difficult encoding of complex PK/PD models in WinBUGS.

Re-using biological devices: a model-aided analysis of interconnected transcriptional cascades designed from the bottom-up.

BACKGROUND: The study of simplified, ad-hoc constructed model systems can help to elucidate if quantitatively characterized biological parts can be effectively re-used in composite circuits to yield predictable functions. Synthetic systems designed from the bottom-up can enable the building of complex interconnected devices via rational approach, supported by mathematical modelling. However, such process is affected by different, usually non-modelled, unpredictability sources, like cell burden. METHODS: Here, we analyzed a set of synthetic transcriptional cascades in Escherichia coli. We aimed to test the predictive power of a simple Hill function activation/repression model (no-burden model, NBM) and of a recently proposed model, including Hill functions and the modulation of proteins expression by cell load (burden model, BM). To test the bottom-up approach, the circuit collection was divided into training and test sets, used to learn individual component functions and test the predicted output of interconnected circuits, respectively. RESULTS: Among the constructed configurations, two test set circuits showed unexpected logic behaviour. Both NBM and BM were able to predict the quantitative output of interconnected devices with expected behaviour, but only the BM was also able to predict the output of one circuit with unexpected behaviour. Moreover, considering training and test set data together, the BM captures circuits output with higher accuracy than the NBM, which is unable to capture the experimental output exhibited by some of the circuits even qualitatively. Finally, resource usage parameters, estimated via BM, guided the successful construction of new corrected variants of the two circuits showing unexpected behaviour. CONCLUSIONS: Superior descriptive and predictive capabilities were achieved considering resource limitation modelling, but further efforts are needed to improve the accuracy of models for biological engineering.

Fermentation of lactose to ethanol in cheese whey permeate and concentrated permeate by engineered Escherichia coli.

BACKGROUND: Whey permeate is a lactose-rich effluent remaining after protein extraction from milk-resulting cheese whey, an abundant dairy waste. The lactose to ethanol fermentation can complete whey valorization chain by decreasing dairy waste polluting potential, due to its nutritional load, and producing a biofuel from renewable source at the same time. Wild type and engineered microorganisms have been proposed as fermentation biocatalysts. However, they present different drawbacks (e.g., nutritional supplements requirement, high transcriptional demand of recombinant genes, precise oxygen level, and substrate inhibition) which limit the industrial attractiveness of such conversion process. In this work, we aim to engineer a new bacterial biocatalyst, specific for dairy waste fermentation. RESULTS: We metabolically engineered eight Escherichia coli strains via a new expression plasmid with the pyruvate-to-ethanol conversion genes, and we carried out the selection of the best strain among the candidates, in terms of growth in permeate, lactose consumption and ethanol formation. We finally showed that the selected engineered microbe (W strain) is able to efficiently ferment permeate and concentrated permeate, without nutritional supplements, in pH-controlled bioreactor. In the conditions tested in this work, the selected biocatalyst could complete the fermentation of permeate and concentrated permeate in about 50 and 85 h on average, producing up to 17 and 40 g/l of ethanol, respectively. CONCLUSIONS: To our knowledge, this is the first report showing efficient ethanol production from the lactose contained in whey permeate with engineered E. coli. The selected strain is amenable to further metabolic optimization and represents an advance towards efficient biofuel production from industrial waste stream.

A BioBrick™-Compatible Vector for Allelic Replacement Using the XylE Gene as Selection Marker.

BACKGROUND: Circular plasmid-mediated homologous recombination is commonly used for marker-less allelic replacement, exploiting the endogenous recombination machinery of the host. Common limitations of existing methods include high false positive rates due to mutations in counter-selection genes, and limited applicability to specific strains or growth media. Finally, solutions compatible with physical standards, such as the BioBrick™, are not currently available, although they proved to be successful in the design of other replicative or integrative plasmids. FINDINGS: We illustrate pBBknock, a novel BioBrick™-compatible vector for allelic replacement in Escherichia coli. It includes a temperature-sensitive replication origin and enables marker-less genome engineering via two homologous recombination events. Chloramphenicol resistance allows positive selection of clones after the first event, whereas a colorimetric assay based on the xylE gene provides a simple way to screen clones in which the second recombination event occurs. Here we successfully use pBBknock to delete the lactate dehydrogenase gene in E. coli W, a popular host used in metabolic engineering. CONCLUSIONS: Compared with other plasmid-based solutions, pBBknock has a broader application range, not being limited to specific strains or media. We expect that pBBknock will represent a versatile solution both for practitioners, also among the iGEM competition teams, and for research laboratories that use BioBrick™-based assembly procedures.

Experimental measurements and mathematical modeling of biological noise arising from transcriptional and translational regulation of basic synthetic gene circuits.

The small number of molecules, unevenly distributed within an isogenic cell population, makes gene expression a noisy process, and strategies have evolved to deal with this variability in protein concentration and to limit its impact on cellular behaviors. As translational efficiency has a major impact on biological noise, a possible strategy to control noise is to regulate gene expression processes at the post-transcriptional level. In this study, fluctuations in the concentration of a green fluorescent protein were compared, at the single cell level, upon transformation of an isogenic bacterial cell population with synthetic gene circuits implementing either a transcriptional or a post-transcriptional control of gene expression. Experimental measurements showed that protein variability is lower under post-transcriptional control, when the same average protein concentrations are compared. This effect is well reproduced by stochastic simulations, supporting the hypothesis that noise reduction is due to the control mechanism acting on the efficiency of translation. Similar strategies are likely to play a role in noise reduction in natural systems and to be useful for controlling noise in synthetic biology applications.