Microfluidic Printing-Based Method for the Multifactorial Study of Cell-Free Protein Networks.

Protein networks can be assembled in vitro for basic biochemistry research, drug screening, and the creation of artificial cells. Two standard methodologies are used: manual pipetting and pipetting robots. Manual pipetting has limited throughput in the number of input reagents and the combination of reagents in a single sample. While pipetting robots are evident in improving pipetting efficiency and saving hands-on time, their liquid handling volume usually ranges from a few to hundreds of microliters. Microfluidic methods have been developed to minimize the reagent consumption and speed up screening but are challenging in multifactorial protein studies due to their reliance on complex structures and labeling dyes. Here, we engineered a new impact-printing-based methodology to generate printed microdroplet arrays containing water-in-oil droplets. The printed droplet volume was linearly proportional (R2 = 0.9999) to the single droplet number, and each single droplet volume was around 59.2 nL (coefficient of variation = 93.8%). Our new methodology enables the study of protein networks in both membrane-unbound and -bound states, without and with anchor lipids DGS-NTA(Ni), respectively. The methodology is demonstrated using a subnetwork of mitogen-activated protein kinase (MAPK). It takes less than 10 min to prepare 100 different droplet-based reactions, using <1 µL reaction volume at each reaction site. We validate the kinase (ATPase) activity of MEK1 (R4F)* and ERK2 WT individually and together under different concentrations, without and with the selective membrane attachment. Our new methodology provides a reagent-saving, efficient, and flexible way for protein network research and related applications.

Orthogonal tuning of gene expression noise using CRISPR-Cas.

The control of gene expression noise is important for improving drug treatment and the performance of synthetic biological systems. Previous work has tuned gene expression noise by changing the rate of transcription initiation, mRNA degradation, and mRNA translation. However, these methods are invasive: they require changes to the target genetic components. Here, we create an orthogonal system based on CRISPR-dCas9 to tune gene expression noise. Specifically, we modulate the gene expression noise of a reporter gene in Escherichia coli by incorporating CRISPR activation and repression (CRISPRar) simultaneously in a single cell. The CRISPRar uses a single dCas9 that recognizes two different single guide RNAs (sgRNA). We build a library of sgRNA variants with different expression activation and repression strengths. We find that expression noise and mean of a reporter gene can be tuned independently by CRISPRar. Our results suggest that the expression noise is tuned by the competition between two sgRNAs that modulate the binding of RNA polymerase to promoters. The CRISPRar may change how we tune expression noise at the genomic level. Our work has broad impacts on the study of gene functions, phenotypical heterogeneity, and genetic circuit control.

Stochastic ordering of complexoform protein assembly by genetic circuits.

Top-down proteomics has enabled the elucidation of heterogeneous protein complexes with different cofactors, post-translational modifications, and protein membership. This heterogeneity is believed to play a previously unknown role in cellular processes. The different molecular forms of a protein complex have come to be called "complex isoform" or "complexoform". Despite the elucidation of the complexoform, it remains unclear how and whether cellular circuits control the distribution of a complexoform. To help address this issue, we first simulate a generic three-protein complexoform to reveal the control of its distribution by the timing of gene transcription, mRNA translation, and protein transport. Overall, we ran 265 computational experiments: each averaged over 1,000 stochastic simulations. Based on the experiments, we show that genes arranged in a single operon, a cascade, or as two operons all give rise to the different protein composition of complexoform because of timing differences in protein-synthesis order. We also show that changes in the kinetics of expression, protein transport, or protein binding dramatically alter the distribution of the complexoform. Furthermore, both stochastic and transient kinetics control the assembly of the complexoform when the expression and assembly occur concurrently. We test our model against the biological cellulosome system. With biologically relevant rates, we find that the genetic circuitry controls the average final complexoform assembly and the variation in the assembly structure. Our results highlight the importance of both the genetic circuit architecture and kinetics in determining the distribution of a complexoform. Our work has a broad impact on our understanding of non-equilibrium processes in both living and synthetic biological systems.

Synthetic microbial consortia enable rapid assembly of pure translation machinery.

Assembly of recombinant multiprotein systems requires multiple culturing and purification steps that scale linearly with the number of constituent proteins. This problem is particularly pronounced in the preparation of the 34 proteins involved in transcription and translation systems, which are fundamental biochemistry tools for reconstitution of cellular pathways ex vivo. Here, we engineer synthetic microbial consortia consisting of between 15 and 34 Escherichia coli strains to assemble the 34 proteins in a single culturing, lysis, and purification procedure. The expression of these proteins is controlled by synthetic genetic modules to produce the proteins at the correct ratios. We show that the pure multiprotein system is functional and reproducible, and has low protein contaminants. We also demonstrate its application in the screening of synthetic promoters and protease inhibitors. Our work establishes a novel strategy for producing pure translation machinery, which may be extended to the production of other multiprotein systems.

Engineering approaches of smart, bio-inspired vesicles for biomedical applications.

Advances in materials engineering have allowed for the development of sophisticated and controlled drug delivery through vesicles. Smart vesicles, capable of sensing single stimulus or multiple stimuli, can be engineered to process specific environmental signals to produce a tailored response. Exhibiting multifunctionality and theranostic abilities, they are a promising platform for new therapeutic methods. Here, we discuss smartness in the context of biosensing vesicles, followed by the various components required to develop a smart vesicle and the design considerations regarding engineering approaches of each. We then focus on biomedical applications of the vesicles in disease treatment and biosensing.

Programmed Allee effect in bacteria causes a tradeoff between population spread and survival.

Dispersal is necessary for spread into new habitats, but it has also been shown to inhibit spread. Theoretical studies have suggested that the presence of a strong Allee effect may account for these counterintuitive observations. Experimental demonstration of this notion is lacking due to the difficulty in quantitative analysis of such phenomena in a natural setting. We engineered Escherichia coli to exhibit a strong Allee effect and examined how the Allee effect would affect the spread of the engineered bacteria. We showed that the Allee effect led to a biphasic dependence of bacterial spread on the dispersal rate: spread is promoted for intermediate dispersal rates but inhibited at low or high dispersal rates. The shape of this dependence is contingent upon the initial density of the source population. Moreover, the Allee effect led to a tradeoff between effectiveness of population spread and survival: increasing the number of target patches during dispersal allows more effective spread, but it simultaneously increases the risk of failing to invade or of going extinct. We also observed that total population growth is transiently maximized at an intermediate number of target patches. Finally, we demonstrate that fluctuations in cell growth may contribute to the paradoxical relationship between dispersal and spread. Our results provide direct experimental evidence that the Allee effect can explain the apparently paradoxical effects of dispersal on spread and have implications for guiding the spread of cooperative organisms.

Phenotypic signatures arising from unbalanced bacterial growth.

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify "phenotypic signatures" by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains.

Synthetic control of living cells by intracellular polymerization.

An emerging cellular engineering method creates synthetic polymer matrices inside cells. By contrast with classical genetic, enzymatic, or radioactive techniques, this materials-based approach introduces non-natural polymers inside cells, thus modifying cellular states and functionalities. Here, we cover various materials and chemistries that have been exploited to create intracellular polymer matrices. In addition, we discuss emergent cellular properties due to the intracellular polymerization, including nonreplicating but active metabolism, maintenance of membrane integrity, and resistance to environmental stressors. We also discuss past work and future opportunities for developing and applying synthetic cells that contain intracellular polymers. The materials-based approach will usher in new applications of synthetic cells for broad biotechnological applications.

Cracking the Code: Enhancing Molecular Tools for Progress in Nanobiotechnology.

Nature continually refines its processes for optimal efficiency, especially within biological systems. This article explores the collaborative efforts of researchers worldwide, aiming to mimic nature's efficiency by developing smarter and more effective nanoscale technologies and biomaterials. Recent advancements highlight progress and prospects in leveraging engineered nucleic acids and proteins for specific tasks, drawing inspiration from natural functions. The focus is developing improved methods for characterizing, understanding, and reprogramming these materials to perform user-defined functions, including personalized therapeutics, targeted drug delivery approaches, engineered scaffolds, and reconfigurable nanodevices. Contributions from academia, government agencies, biotech, and medical settings offer diverse perspectives, promising a comprehensive approach to broad nanobiotechnology objectives. Encompassing topics from mRNA vaccine design to programmable protein-based nanocomputing agents, this work provides insightful perspectives on the trajectory of nanobiotechnology toward a future of enhanced biomimicry and technological innovation.

The inoculum effect and band-pass bacterial response to periodic antibiotic treatment.

The inoculum effect (IE) refers to the decreasing efficacy of an antibiotic with increasing bacterial density. It represents a unique strategy of antibiotic tolerance and it can complicate design of effective antibiotic treatment of bacterial infections. To gain insight into this phenomenon, we have analyzed responses of a lab strain of Escherichia coli to antibiotics that target the ribosome. We show that the IE can be explained by bistable inhibition of bacterial growth. A critical requirement for this bistability is sufficiently fast degradation of ribosomes, which can result from antibiotic-induced heat-shock response. Furthermore, antibiotics that elicit the IE can lead to 'band-pass' response of bacterial growth to periodic antibiotic treatment: the treatment efficacy drastically diminishes at intermediate frequencies of treatment. Our proposed mechanism for the IE may be generally applicable to other bacterial species treated with antibiotics targeting the ribosomes.

Special Issue "Synthetic Biology for Biosensing in Health and Environmental Applications".

Biosensors are analytical devices that utilize biological sensing elements, such as enzymes, antibodies, nucleic acids, or cells, to detect a given analyte [...].

Engineering Cyborg Bacteria Through Intracellular Hydrogelation.

Natural and artificial cells are two common chassis in synthetic biology. Natural cells can perform complex tasks through synthetic genetic constructs, but their autonomous replication often causes safety concerns for biomedical applications. In contrast, artificial cells based on nonreplicating materials, albeit possessing reduced biochemical complexity, provide more defined and controllable functions. Here, for the first time, the authors create hybrid material-cell entities termed Cyborg Cells. To create Cyborg Cells, a synthetic polymer network is assembled inside each bacterium, rendering them incapable of dividing. Cyborg Cells preserve essential functions, including cellular metabolism, motility, protein synthesis, and compatibility with genetic circuits. Cyborg Cells also acquire new abilities to resist stressors that otherwise kill natural cells. Finally, the authors demonstrate the therapeutic potential by showing invasion into cancer cells. This work establishes a new paradigm in cellular bioengineering by exploiting a combination of intracellular man-made polymers and their interaction with the protein networks of living cells.

Origin of bistability underlying mammalian cell cycle entry.

Precise control of cell proliferation is fundamental to tissue homeostasis and differentiation. Mammalian cells commit to proliferation at the restriction point (R-point). It has long been recognized that the R-point is tightly regulated by the Rb-E2F signaling pathway. Our recent work has further demonstrated that this regulation is mediated by a bistable switch mechanism. Nevertheless, the essential regulatory features in the Rb-E2F pathway that create this switching property have not been defined. Here we analyzed a library of gene circuits comprising all possible link combinations in a simplified Rb-E2F network. We identified a minimal circuit that is able to generate robust, resettable bistability. This minimal circuit contains a feed-forward loop coupled with a mutual-inhibition feedback loop, which forms an AND-gate control of the E2F activation. Underscoring its importance, experimental disruption of this circuit abolishes maintenance of the activated E2F state, supporting its importance for the bistability of the Rb-E2F system. Our findings suggested basic design principles for the robust control of the bistable cell cycle entry at the R-point.

Computation of steady-state probability distributions in stochastic models of cellular networks.

Cellular processes are "noisy". In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry.

Hemifusion of giant unilamellar vesicles with planar hydrophobic surfaces: a fluorescence microscopy study.

Vesicle adhesion and fusion to interfaces are frequently used for the construction of biomimetic surfaces in biosensors and drug delivery. Ubiquitous in cell biology, vesicle fusion involves the transformation of two separate membranes into one contiguous lipid bilayer. In distinction, the deposition of vesicle membranes to hydrophobic surfaces requires the transformation of a lipidic bilayer into a monomolecular layer - a topologically distinct process termed hemifusion. Here, we used hydrophobically terminated self-assembled monolayers (SAMs) on solid surfaces to track the hemifusion of fluorescently labeled giant unilamellar vesicles (GUVs) at the single vesicle level with video time resolution (≈53 ms). We observed that a dilute monolayer, consisting of lipid extracted from the outer GUV leaflet, spreads outward across the hydrophobic surface from the vesicle adhesion site. Subsequently, bilayer hemifusion occurs by vesicle rupture near the hydrophobic surface, followed by spreading of lipid in a dense monolayer. GUV lipids thus transfer to the SAM surface in two concentric zones: an outer hemifusion zone comprises lipids drawn from the outer GUV leaflet and an inner hemifusion zone comprises lipids from both the inner and outer GUV leaflets and grows at a rate of ≈1000 µm2 s-1 (dA/dt = 970 ± 430 µm2 s-1 in n = 22 independent experiments). This growth rate is quantitatively consistent with the assumption that the spreading of the monolayer is entirely driven by the difference in surface energies of the hydrophobic and the lipid-covered SAM surfaces, which is dissipated by friction of the spreading monolayer on the SAM. Lipid transfer between the inner and outer GUV leaflets occurs via a hemifusion pore that forms early in the process near the membrane contact site. This pore also permits expulsion of water from the GUV interior as the vesicle contracts onto the contact site.

Frequency dependent growth of bacteria in living materials.

The fusion of living bacteria and man-made materials represents a new frontier in medical and biosynthetic technology. However, the principles of bacterial signal processing inside synthetic materials with three-dimensional and fluctuating environments remain elusive. Here, we study bacterial growth in a three-dimensional hydrogel. We find that bacteria expressing an antibiotic resistance module can take advantage of ambient kinetic disturbances to improve growth while encapsulated. We show that these changes in bacterial growth are specific to disturbance frequency and hydrogel density. This remarkable specificity demonstrates that periodic disturbance frequency is a new input that engineers may leverage to control bacterial growth in synthetic materials. This research provides a systematic framework for understanding and controlling bacterial information processing in three-dimensional living materials.

High-Throughput Experimentation Using Cell-Free Protein Synthesis Systems.

Cell-free protein synthesis can enable the combinatorial screening of many different components and concentrations. However, manual pipetting methods are unfit to handle many cell-free reactions. Here, we describe a microfluidic method that can generate hundreds of unique submicroliter scale reactions. The method is coupled with a high yield cell-free system that can be applied for broad protein screening assays.

Emergent bistability by a growth-modulating positive feedback circuit.

Synthetic gene circuits are often engineered by considering the host cell as an invariable 'chassis'. Circuit activation, however, may modulate host physiology, which in turn can substantially impact circuit behavior. We illustrate this point by a simple circuit consisting of mutant T7 RNA polymerase (T7 RNAP*) that activates its own expression in the bacterium Escherichia coli. Although activation by the T7 RNAP* is noncooperative, the circuit caused bistable gene expression. This counterintuitive observation can be explained by growth retardation caused by circuit activation, which resulted in nonlinear dilution of T7 RNAP* in individual bacteria. Predictions made by models accounting for such effects were verified by further experimental measurements. Our results reveal a new mechanism of generating bistability and underscore the need to account for host physiology modulation when engineering gene circuits.

Analysis of the Innovation Trend in Cell-Free Synthetic Biology.

Cell-free synthetic biology is a maturing field that aims to assemble biomolecular reactions outside cells for compelling applications in drug discovery, metabolic engineering, biomanufacturing, diagnostics, and education. Cell-free systems have several key features. They circumvent mechanisms that have evolved to facilitate species survival, bypass limitations on molecular transport across the cell wall, enable high-yielding and rapid synthesis of proteins without creating recombinant cells, and provide high tolerance towards toxic substrates or products. Here, we analyze ~750 published patents and ~2000 peer-reviewed manuscripts in the field of cell-free systems. Three hallmarks emerged. First, we found that both patent filings and manuscript publications per year are significantly increasing (five-fold and 1.5-fold over the last decade, respectively). Second, we observed that the innovation landscape has changed. Patent applications were dominated by Japan in the early 2000s before shifting to China and the USA in recent years. Finally, we discovered an increasing prevalence of biotechnology companies using cell-free systems. Our analysis has broad implications on the future development of cell-free synthetic biology for commercial and industrial applications.