Genetic toggle switch controlled by bacterial growth rate

Living Cell as a Self-Synchronized Chemical Reactor

Thermal fluctuations power all processes inside living cells. Therefore, these processes are inherently random. However, myriad multistep chemical reactions act in concerto inside a cell, finally leading to this chemical reactor's self-replication. We speculate that an underlying mechanism in nature must exist that allows all of these reactions to synchronize at multiple time and length scales, overcoming in this way the random nature of any single process in a cell. This Perspective discusses what type of research is needed to understand this undiscovered synchronization law.

Stable expression of HIV-1 MPER extended epitope on the surface of the recombinant probiotic bacteria Escherichia Coli Nissle 1917 using CRISPR/Cas9

BACKGROUND

Mucosal vaccines have the potential to induce protective immune responses at the sites of infection. Applying CRISPR/Cas9 editing, we aimed to develop a probiotic-based vaccine candidate expressing the HIV-1 envelope membrane-proximal external region (MPER) on the surface of E. coli Nissle 1917.

RESULTS

The HIV-1 MPER epitope was successfully introduced in the porin OmpF of the E. coli Nissle 1917 (EcN-MPER) and the modification was stable over 30 passages of the recombinant bacteria on the DNA and protein level. Furthermore, the introduced epitope was recognized by a human anti-HIV-1 gp41 (2F5) antibody using both live and heat-killed EcN-MPER, and this antigenicity was also retained over 30 passages. Whole-cell dot blot suggested a stronger binding of anti-HIV-1 gp41 (2F5) to heat-killed EcN-MPER than their live counterpart. An outer membrane vesicle (OMV) - rich extract from EcN-MPER culture supernatant was equally antigenic to anti-HIV-1 gp41 antibody which suggests that the MPER antigen could be harboured in EcN-MPER OMVs. Using quantitative ELISA, we determined the amount of MPER produced by the modified EcN to be 14.3 µg/108 cfu.

CONCLUSIONS

The CRISPR/Cas9 technology was an effective method for establishment of recombinant EcN-MPER bacteria that was stable over many passages. The developed EcN-MPER clone was devoid of extraneous plasmids and antibiotic resistance genes which eliminates the risk of plasmid transfer to animal hosts, should this clone be used as a vaccine. Also, the EcN-MPER clone was recognised by anti-HIV-1 gp41 (2F5) both as live and heat-killed bacteria making it suitable for pre-clinical evaluation. Expression of OmpF on bacterial surfaces and released OMVs identifies it as a compelling candidate for recombinant epitope modification, enabling surface epitope presentation on both bacteria and OMVs. By applying the methods described in this study, we present a potential platform for cost-effective and rational vaccine antigen expression and administration, offering promising prospects for further research in the field of vaccine development.

A heritable iron memory enables decision-making in Escherichia coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when Escherichia coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This "iron" memory preexists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, which tracks with its iron memory, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We demonstrate that cellular iron levels also track with biofilm formation and antibiotic tolerance, suggesting that iron memory may impact other physiologies.

Iron Memory in E. coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when E. coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This memory pre-exists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, whether low or high, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We also demonstrate that iron memory can integrate multiple stimuli, impacting other bacterial behaviors such as biofilm formation and antibiotic tolerance.

The Slowdown of Growth Rate Controls the Single-Cell Distribution of Biofilm Matrix Production via an SinI-SinR-SlrR Network

In Bacillus subtilis, master regulator Spo0A controls several cell-differentiation pathways. Under moderate starvation, phosphorylated Spo0A (Spo0A~P) induces biofilm formation by indirectly activating genes controlling matrix production in a subpopulation of cells via an SinI-SinR-SlrR network. Under severe starvation, Spo0A~P induces sporulation by directly and indirectly regulating sporulation gene expression. However, what determines the heterogeneity of individual cell fates is not fully understood. In particular, it is still unclear why, despite being controlled by a single master regulator, biofilm matrix production and sporulation seem mutually exclusive on a single-cell level. In this work, with mathematical modeling, we showed that the fluctuations in the growth rate and the intrinsic noise amplified by the bistability in the SinI-SinR-SlrR network could explain the single-cell distribution of matrix production. Moreover, we predicted an incoherent feed-forward loop; the decrease in the cellular growth rate first activates matrix production by increasing in Spo0A phosphorylation level but then represses it via changing the relative concentrations of SinR and SlrR. Experimental data provide evidence to support model predictions. In particular, we demonstrate how the degree to which matrix production and sporulation appear mutually exclusive is affected by genetic perturbations. IMPORTANCE The mechanisms of cell-fate decisions are fundamental to our understanding of multicellular organisms and bacterial communities. However, even for the best-studied model systems we still lack a complete picture of how phenotypic heterogeneity of genetically identical cells is controlled. Here, using B. subtilis as a model system, we employ a combination of mathematical modeling and experiments to explain the population-level dynamics and single-cell level heterogeneity of matrix gene expression. The results demonstrate how the two cell fates, biofilm matrix production and sporulation, can appear mutually exclusive without explicitly inhibiting one another. Such a mechanism could be used in a wide range of other biological systems.

A genome-wide association study of the occurrence of genetic variations in Edwardsiella piscicida, Vibrio harveyi, and Streptococcus parauberis under stressed environments

Bacterial mutation and genetic diversity in aquaculture have led to increasing phenotypic variances, which can weaken or invalidate strategies for controlling diseases. However, few studies have monitored the degree of mutation in fish bacterial pathogens caused by environmental pressure within a short period. In this study, transcriptomic sequences from Edwardsiella piscicida, Vibrio harveyi and Streptococcus parauberis under stressed environments were used for investigating the emergence of variants. In detail, a sub-inhibitory concentration of formalin and phenol for E. piscicida, sea water at 30°C for V. harveyi and flounder serum for S. parauberis were used as stressed environments, and significant single-nucleotide polymorphisms (SNPs) and/or mutation sites were investigated after culture in the ordinary liquid media (control) and the stressed environment through a genome-wide association study. As results, several SNPs or mutations during incubation were observed under different environments in E. piscicida and/or V. harveyi in the genes relevant to flagella, fimbria type 3 secretion systems, and outer and inner membranes that have been directly exposed to external environments. In particular, given that flagella and fimbriae are considered important factors in differentiating the serotypes in some bacterial pathogens, it can be speculated that different environmental pressures are the source of phenotypic or serotypic differentiation from the same origin. On the other hands, S. parauberis did not exhibit notable changes for 4 h when inoculated in the serum from olive flounder. The results presented in this study provide examples of possible molecular evolution in pathogens relevant to the aquaculture industry as a response to different environmental pressure.

Bacillus subtilis Histidine Kinase KinC Activates Biofilm Formation by Controlling Heterogeneity of Single-Cell Responses

In Bacillus subtilis, biofilm and sporulation pathways are both controlled by a master regulator, Spo0A, which is activated by phosphorylation via a phosphorelay-a cascade of phosphotransfer reactions commencing with autophosphorylation of histidine kinases KinA, KinB, KinC, KinD, and KinE. However, it is unclear how the kinases, despite acting via the same regulator, Spo0A, differentially regulate downstream pathways, i.e., how KinA mainly activates sporulation genes and KinC mainly activates biofilm genes. In this work, we found that KinC also downregulates sporulation genes, suggesting that KinC has a negative effect on Spo0A activity. To explain this effect, with a mathematical model of the phosphorelay, we revealed that unlike KinA, which always activates Spo0A, KinC has distinct effects on Spo0A at different growth stages: during fast growth, KinC acts as a phosphate source and activates Spo0A, whereas during slow growth, KinC becomes a phosphate sink and contributes to decreasing Spo0A activity. However, under these conditions, KinC can still increase the population-mean biofilm matrix production activity. In a population, individual cells grow at different rates, and KinC would increase the Spo0A activity in the fast-growing cells but reduce the Spo0A activity in the slow-growing cells. This mechanism reduces single-cell heterogeneity of Spo0A activity, thereby increasing the fraction of cells that activate biofilm matrix production. Thus, KinC activates biofilm formation by controlling the fraction of cells activating biofilm gene expression. IMPORTANCE In many bacterial and eukaryotic systems, multiple cell fate decisions are activated by a single master regulator. Typically, the activities of the regulators are controlled posttranslationally in response to different environmental stimuli. The mechanisms underlying the ability of these regulators to control multiple outcomes are not understood in many systems. By investigating the regulation of Bacillus subtilis master regulator Spo0A, we show that sensor kinases can use a novel mechanism to control cell fate decisions. By acting as a phosphate source or sink, kinases can interact with one another and provide accurate regulation of the phosphorylation level. Moreover, this mechanism affects the cell-to-cell heterogeneity of the transcription factor activity and eventually determines the fraction of different cell types in the population. These results demonstrate the importance of intercellular heterogeneity for understanding the effects of genetic perturbations on cell fate decisions. Such effects can be applicable to a wide range of cellular systems.

OUP accepted manuscript

Many questions remain about the interplay between adaptive and neutral processes leading to genome expansion and the evolution of cellular complexity. Genome size appears to be tightly linked to the size of the regulatory repertoire of cells (van Nimwegen E. 2003. Scaling laws in the functional content of genomes. Trends Gen. 19(9):479–484). In the context of gene regulation, we here study the interplay between adaptive and nonadaptive forces on genome and regulatory network in a computational model of cell-cycle adaptation to different environments. Starting from the well-known Caulobacter crescentus network, we report on ten replicate in silico evolution experiments where cells evolve cell-cycle control by adapting to increasingly harsh spatial habitats.

We find adaptive expansion of the regulatory repertoire of cells. Having a large genome is inherently costly, but also allows for improved cell-cycle behavior. Replicates traverse different evolutionary trajectories leading to distinct eco-evolutionary strategies. In four replicates, cells evolve a generalist strategy to cope with a variety of nutrient levels; in two replicates, different specialist cells evolve for specific nutrient levels; in the remaining four replicates, an intermediate strategy evolves. These diverse evolutionary outcomes reveal the role of contingency in a system under strong selective forces.

This study shows that functionality of cells depends on the combination of regulatory network topology and genome organization. For example, the positions of dosage-sensitive genes are exploited to signal to the regulatory network when replication is completed, forming a de novo evolved cell cycle checkpoint. Our results underline the importance of the integration of multiple organizational levels to understand complex gene regulation and the evolution thereof.

Modeling aging and its impact on cellular function and organismal behavior

Aging is a complex phenomenon of functional decay in a biological organism. Although the effects of aging are readily recognizable in a wide range of organisms, the cause(s) of aging are ill defined and poorly understood. Experimental methods on model organisms have driven significant insight into aging as a process, but have not provided a complete model of aging. Computational biology offers a unique opportunity to resolve this gap in our knowledge by generating extensive and testable models that can help us understand the fundamental nature of aging, identify the presence and characteristics of unaccounted aging factor(s), demonstrate the mechanics of particular factor(s) in driving aging, and understand the secondary effects of aging on biological function. In this review, we will address each of the above roles for computational biology in aging research. Concurrently, we will explore the different applications of computational biology to aging in single-celled versus multicellular organisms. Given the long history of computational biogerontological research on lower eukaryotes, we emphasize the key future goals of gradually integrating prior models into a holistic map of aging and translating successful models to higher-complexity organisms.

Context-Dependent Stability and Robustness of Genetic Toggle Switches with Leaky Promoters

Multistable switches are ubiquitous building blocks in both systems and synthetic biology. Given their central role, it is thus imperative to understand how their fundamental properties depend not only on the tunable biophysical properties of the switches themselves, but also on their genetic context. To this end, we reveal in this article how these factors shape the essential characteristics of toggle switches implemented using leaky promoters such as their stability and robustness to noise, both at single-cell and population levels. In particular, our results expose the roles that competition for scarce transcriptional and translational resources, promoter leakiness, and cell-to-cell heterogeneity collectively play. For instance, the interplay between protein expression from leaky promoters and the associated cost of relying on shared cellular resources can give rise to tristable dynamics even in the absence of positive feedback. Similarly, we demonstrate that while promoter leakiness always acts against multistability, resource competition can be leveraged to counteract this undesirable phenomenon. Underpinned by a mechanistic model, our results thus enable the context-aware rational design of multistable genetic switches that are directly translatable to experimental considerations, and can be further leveraged during the synthesis of large-scale genetic systems using computer-aided biodesign automation platforms.

Stability and Robustness of Unbalanced Genetic Toggle Switches in the Presence of Scarce Resources

While the vision of synthetic biology is to create complex genetic systems in a rational fashion, system-level behaviors are often perplexing due to the context-dependent dynamics of modules. One major source of context-dependence emerges due to the limited availability of shared resources, coupling the behavior of disconnected components. Motivated by the ubiquitous role of toggle switches in genetic circuits ranging from controlling cell fate differentiation to optimizing cellular performance, here we reveal how their fundamental dynamic properties are affected by competition for scarce resources. Combining a mechanistic model with nullcline-based stability analysis and potential landscape-based robustness analysis, we uncover not only the detrimental impacts of resource competition, but also how the unbalancedness of the switch further exacerbates them. While in general both of these factors undermine the performance of the switch (by pushing the dynamics toward monostability and increased sensitivity to noise), we also demonstrate that some of the unwanted effects can be alleviated by strategically optimized resource competition. Our results provide explicit guidelines for the context-aware rational design of toggle switches to mitigate our reliance on lengthy and expensive trial-and-error processes, and can be seamlessly integrated into the computer-aided synthesis of complex genetic systems.

Recent Advances in the Heterologous Biosynthesis of Natural Products from Streptomyces

Streptomyces is a significant source of natural products that are used as therapeutic antibiotics, anticancer and antitumor agents, pesticides, and dyes. Recently, with the advances in metabolite analysis, many new secondary metabolites have been characterized. Moreover, genome mining approaches demonstrate that many silent and cryptic biosynthetic gene clusters (BGCs) and many secondary metabolites are produced in very low amounts under laboratory conditions. One strain many compounds (OSMAC), overexpression/deletion of regulatory genes, ribosome engineering, and promoter replacement have been utilized to activate or enhance the production titer of target compounds. Hence, the heterologous expression of BGCs by transferring to a suitable production platform has been successfully employed for the detection, characterization, and yield quantity production of many secondary metabolites. In this review, we introduce the systematic approach for the heterologous production of secondary metabolites from Streptomyces in Streptomyces and other hosts, the genome analysis tools, the host selection, and the development of genetic control elements for heterologous expression and the production of secondary metabolites.

Tunability enhancement of gene regulatory motifs through competition for regulatory protein resources

Gene regulatory networks (GRNs) orchestrate the spatiotemporal levels of gene expression, thereby regulating various cellular functions ranging from embryonic development to tissue homeostasis. Some patterns called "motifs" recurrently appear in the GRNs. Owing to the prevalence of these motifs they have been subjected to much investigation, both in the context of understanding cellular decision making and engineering synthetic circuits. Mounting experimental evidence suggests that (1) the copy number of genes associated with these motifs varies, and (2) proteins produced from these genes bind to decoy binding sites on the genome as well as promoters driving the expression of other genes. Together, these two processes engender competition for protein resources within a cell. To unravel how competition for protein resources affects the dynamical properties of regulatory motifs, we propose a simple kinetic model that explicitly incorporates copy number variation (CNV) of genes and decoy binding of proteins. Using quasi-steady-state approximations, we theoretically investigate the transient and steady-state properties of three of the commonly found motifs: Autoregulation, toggle switch, and repressilator. While protein resource competition alters the timescales to reach the steady state for all these motifs, the dynamical properties of the toggle switch and repressilator are affected in multiple ways. For toggle switch, the basins of attraction of the known attractors are dramatically altered if one set of proteins binds to decoys more frequently than the other, an effect which gets suppressed as the copy number of the toggle switch is enhanced. For repressilators, protein sharing leads to an emergence of oscillation in regions of parameter space that were previously nonoscillatory. Intriguingly, both the amplitude and frequency of oscillation are altered in a nonlinear manner through the interplay of CNV and decoy binding. Overall, competition for protein resources within a cell provides an additional layer of regulation of gene regulatory motifs.

Stochastic models coupling gene expression and partitioning in cell division in Escherichia coli

Regulation of future RNA and protein numbers is a key process by which cells continuously best fit the environment. In bacteria, RNA and proteins exist in small numbers and their regulatory processes are stochastic. Consequently, there is cell-to-cell variability in these numbers, even between sister cells. Traditionally, the two most studied sources of this variability are gene expression and RNA and protein degradation, with evidence suggesting that the latter is subject to little regulation, when compared to the former. However, time-lapse microscopy and single molecule fluorescent tagging have produced evidence that cell division can also be a significant source of variability due to asymmetries in the partitioning of RNA and proteins. Relevantly, the impact of this noise differs from noise in production and degradation since, unlike these, it is not continuous. Rather, it occurs at specific time points, at which moment it can introduce major fluctuations. Several models have now been proposed that integrate noise from cell division, in addition to noise in gene expression, to mimic the dynamics of RNA and protein numbers of cell lineages. This is expected to be particularly relevant in genetic circuits, where significant fluctuations in one component protein, at specific time moments, are expected to perturb near-equilibrium states of the circuits, which can have long-lasting consequences. Here we review stochastic models coupling these processes in Escherichia coli, from single genes to small circuits.

Molecular-memory-driven phenotypic switching in a genetic toggle switch without cooperative binding

A genetic toggle switch would involve multistep reaction processes (e.g., complex promoter activation), creating memories between individual reaction events. Revealing the effect of this molecular memory is important for understanding intracellular processes such as cellular decision making. We propose a generalized genetic toggle switch model and use a generalized chemical master equation theory to account for the memory effect. Interestingly, we find that molecular memory can induce bimodality in this memory system although the corresponding memoryless counterpart is not bimodal. This finding implies a plausible alternative mechanism for phenotypic switching that is driven by molecular memory rather than by ultrasensitivity or cooperative binding as shown in previous studies. We also find that unbalanced memories arising from the processes by which mutually inhibiting transcription factors are produced can give rise to asymmetric bimodality without changing the positions of two peaks in the bimodal protein distribution. Given the prevalence of molecular memory in gene regulation, our findings would provide insights into cell fate decisions in growth and development.