Microbial thermogenesis is dependent on ATP concentrations and the protein kinases ArcB, GlnL, and YccC.

Organisms necessarily release heat energy in their pursuit of survival. This process is known as cellular thermogenesis and is implicated in many processes from cancer metabolism to spontaneous farm fires. However, the molecular basis for this fundamental phenomenon is yet to be elucidated. Here, we show that the major players involved in the cellular thermogenesis of Escherichia coli are the protein kinases ArcB, GlnL, and YccC. We also reveal the substrate-level control of adenosine triphosphate (ATP)-driven autophosphorylation that governs cellular thermogenesis. Specifically, through live cell microcalorimetry, we find these regulatory proteins, when knocked out in a model E. coli strain, dysregulate cellular thermogenesis. This dysregulation can be seen in an average 25% or greater increase in heat output by these cells. We also discover that both heat output and intracellular ATP levels are maximal during the late log phase of growth. Additionally, we show that microbial thermogenesis can be engineered through overexpressing glnL. Our results demonstrate a correlation between ATP concentrations in the cell and a cell's ability to generate excess heat. We expect this work to be the foundation for engineering thermogenically tuned organisms for a variety of applications.

Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia.

Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks. We developed a computational program, ssCRISPR, which designs strain-specific CRISPR guide RNA sequences with user-specified target strains, protected strains, and guide RNA properties. We experimentally verify the accuracy of the strain specificity predictions in both Escherichia coli and Pseudomonas spp. and show that up to three nucleotide mismatches are often required to ensure perfect specificity. To demonstrate the functionality of ssCRISPR, we apply computationally designed CRISPR-Cas9 guide RNAs to two applications: the purification of specific microbes through one- and two-plasmid transformation workflows and the targeted removal of specific microbes using DNA-loaded liposomes. For strain purification, we utilize gRNAs designed to target and kill all microbes in a consortium except the specific microbe to be isolated. For strain elimination, we utilize gRNAs designed to target only the unwanted microbe while protecting all other strains in the community. ssCRISPR will be of use in diverse microbiota engineering applications.

Ten simple rules for managing laboratory information.

Information is the cornerstone of research, from experimental (meta)data and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems to transform this large information load into useful scientific findings.

Duplex Structure of Double-Stranded RNA Provides Stability against Hydrolysis Relative to Single-Stranded RNA.

Phosphodiester bonds in the backbones of double-stranded (ds)RNA and single-stranded (ss)RNA are known to undergo alkaline hydrolysis. Consequently, dsRNA agents used in emerging RNA interference (RNAi) products have been assumed to exhibit low chemical persistence in solutions. However, the impact of the duplex structure of dsRNA on alkaline hydrolysis has not yet been evaluated. In this study, we demonstrated that dsRNA undergoes orders-of-magnitude slower alkaline hydrolysis than ssRNA. Furthermore, we observed that dsRNA remains intact for multiple months at neutral pH, challenging the assumption that dsRNA is chemically unstable. In systems enabling both enzymatic degradation and alkaline hydrolysis of dsRNA, we found that increasing pH effectively attenuated enzymatic degradation without inducing alkaline hydrolysis that was observed for ssRNA. Overall, our findings demonstrated, for the first time, that key degradation pathways of dsRNA significantly differ from those of ssRNA. Consideration of the unique properties of dsRNA will enable greater control of dsRNA stability during the application of emerging RNAi technology and more accurate assessment of its fate in environmental and biological systems, as well as provide insights into broader application areas including dsRNA isolation, detection and inactivation of dsRNA viruses, and prebiotic molecular evolution.

Analysis of RNA Interference (RNAi) Biopesticides: Double-Stranded RNA (dsRNA) Extraction from Agricultural Soils and Quantification by RT-qPCR.

Double-stranded RNA (dsRNA) molecules are used as a novel class of biopesticides. To enable assessments of the ecological risk associated with their release to receiving environments, we developed an approach to quantify dsRNA in agricultural soils using quantitative reverse transcription-polymerase chain reaction (RT-qPCR). To allow quantification of dsRNA adsorbed to particles, we also developed a protocol to transfer dsRNA from particles to the extraction buffer by changing particle surface charge and adding constituents to compete with dsRNA for adsorption sites. Our approach could quantify dsRNA amounts as low as 0.003 ngdsRNA/gsoil. This approach is the first available field-applicable approach able to quantify dsRNA biopesticides down to environmentally relevant concentrations. We applied this approach to investigate dsRNA dissipation (including dilution, degradation, and adsorption) in two agricultural soils. When we applied a low amount of dsRNA (1 ngdsRNA/gsoil) to the soils, we observed that a greater fraction of dsRNA was adsorbed to and extractable from soil particles in a silty clay loam soil than in a fine sandy loam soil. In both soils, dsRNA dissipated on the timescale of hours. Overall, these results demonstrate that our approach can be applied to assess the environmental fate of dsRNA biopesticides at concentrations relevant to their release to soils.

A concerted systems biology analysis of phenol metabolism in Rhodococcus opacus PD630.

Rhodococcus opacus PD630 metabolizes aromatic substrates and naturally produces branched-chain lipids, which are advantageous traits for lignin valorization. To provide insights into its lignocellulose hydrolysate utilization, we performed 13C-pathway tracing, 13C-pulse-tracing, transcriptional profiling, biomass composition analysis, and metabolite profiling in conjunction with 13C-metabolic flux analysis (13C-MFA) of phenol metabolism. We found that 1) phenol is metabolized mainly through the ortho-cleavage pathway; 2) phenol utilization requires a highly active TCA cycle; 3) NADPH is generated mainly via NADPH-dependent isocitrate dehydrogenase; 4) active cataplerotic fluxes increase plasticity in the TCA cycle; and 5) gluconeogenesis occurs partially through the reversed Entner-Doudoroff pathway (EDP). We also found that phenol-fed R. opacus PD630 generally has lower sugar phosphate concentrations (e.g., fructose 1,6-bisphosphatase) compared to metabolite pools in 13C-glucose-fed Escherichia coli (set as internal standards), while its TCA metabolites (e.g., malate, succinate, and α-ketoglutarate) accumulate intracellularly with measurable succinate secretion. In addition, we found that phenol utilization was inhibited by benzoate, while catabolite repressions by other tested carbon substrates (e.g., glucose and acetate) were absent in R. opacus PD630. Three adaptively-evolved strains display very different growth rates when fed with phenol as a sole carbon source, but they maintain a conserved flux network. These findings improve our understanding of R. opacus' metabolism for future lignin valorization.

Design rules of synthetic non-coding RNAs in bacteria.

One of the long-term goals of synthetic biology is to develop designable genetic parts with predictable behaviors that can be utilized to implement diverse cellular functions. The discovery of non-coding RNAs and their importance in cellular processing have rapidly attracted researchers' attention towards designing functional non-coding RNA molecules. These synthetic non-coding RNAs have simple design principles governed by Watson-Crick base pairing, but exhibit increasingly complex functions. Importantly, due to their specific and modular behaviors, synthetic non-coding RNAs have been widely adopted to modulate transcription and translation of target genes. In this review, we summarize various design rules and strategies employed to engineer synthetic non-coding RNAs. Specifically, we discuss how RNA molecules can be transformed into powerful regulators and utilized to control target gene expression. With the establishment of generalizable non-coding RNA design rules, the research community will shift its focus to RNA regulators from protein regulators.

Dynamics of sequestration-based gene regulatory cascades.

Gene regulatory cascades are ubiquitous in biology. Because regulatory cascades are integrated within complex networks, their quantitative analysis is challenging in native systems. Synthetic biologists have gained quantitative insights into the properties of regulatory cascades by building simple circuits, but sequestration-based regulatory cascades remain relatively unexplored. Particularly, it remains unclear how the cascade components collectively control the output dynamics. Here, we report the construction and quantitative analysis of the longest sequestration-based cascade in Escherichia coli. This cascade consists of four Pseudomonas aeruginosa protein regulators (ExsADCE) that sequester their partner. Our computational analysis showed that the output dynamics are controlled in a complex way by the concentration of the unbounded transcriptional activator ExsA. By systematically varying the cascade length and the synthesis rate of each regulator, we experimentally verified the computational prediction that ExsC plays a role in rapid circuit responses by sequestering the anti-activator ExsD, while ExsD increases response times by decreasing the free ExsA concentration. In contrast, when additional ExsD was introduced to the cascade via indirect negative feedback, the response time was significantly reduced. Sequestration-based regulatory cascades with negative feedback are often found in biology, and thus our finding provides insights into the dynamics of this recurring motif.

Multi-omic elucidation of aromatic catabolism in adaptively evolved Rhodococcus opacus.

Lignin utilization has been identified as a key factor in biorefinery profitability. However, lignin depolymerization generates heterogeneous aromatic mixtures that inhibit microbial growth and the conversion of lignocellulose to biochemicals. Rhodococcus opacus is a promising aromatic-catabolizing, oleaginous bacterium, but mechanisms for its aromatic tolerance and utilization remain undercharacterized. To better understand these mechanisms, we adaptively evolved R. opacus for improved utilization of 32 combinations of diverse aromatic compounds. Evolved R. opacus mutants showed up to 1900% growth improvement in the utilization of phenol, guaiacol, 4-hydroxybenzoate, vanillate, and benzoate compared to the wild-type strain. Whole genome sequencing revealed several redox-related genes with mutations shared across multiple adapted mutants. PVHG6, the mutant with the most improved growth on a mixture of multiple aromatic compounds, showed 56% lower superoxide dismutase activity than the wild-type strain, suggesting that redox reactions are important for aromatic tolerance and utilization. Comparative transcriptomics revealed by-product detoxification pathways and five aromatic funneling pathways that were upregulated in response to specific aromatic compounds. Gene knockout experiments confirmed the two degradation routes of the ß-ketoadipate pathway for five aromatic compounds. These results provide an improved understanding of aromatic bioconversion and facilitate development of R. opacus as a biorefinery host.

Genetic programs constructed from layered logic gates in single cells.

Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics. These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits, and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits. Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli. Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator-chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells.

Programmable control of bacterial gene expression with the combined CRISPR and antisense RNA system.

A central goal of synthetic biology is to implement diverse cellular functions by predictably controlling gene expression. Though research has focused more on protein regulators than RNA regulators, recent advances in our understanding of RNA folding and functions have motivated the use of RNA regulators. RNA regulators provide an advantage because they are easier to design and engineer than protein regulators, potentially have a lower burden on the cell and are highly orthogonal. Here, we combine the CRISPR system from Streptococcus pyogenes and synthetic antisense RNAs (asRNAs) in Escherichia coli strains to repress or derepress a target gene in a programmable manner. Specifically, we demonstrate for the first time that the gene target repressed by the CRISPR system can be derepressed by expressing an asRNA that sequesters a small guide RNA (sgRNA). Furthermore, we demonstrate that tunable levels of derepression can be achieved (up to 95%) by designing asRNAs that target different regions of a sgRNA and by altering the hybridization free energy of the sgRNA-asRNA complex. This new system, which we call the combined CRISPR and asRNA system, can be used to reversibly repress or derepress multiple target genes simultaneously, allowing for rational reprogramming of cellular functions.

Comparative transcriptomics elucidates adaptive phenol tolerance and utilization in lipid-accumulating Rhodococcus opacus PD630.

Lignin-derived (e.g. phenolic) compounds can compromise the bioconversion of lignocellulosic biomass to fuels and chemicals due to their toxicity and recalcitrance. The lipid-accumulating bacterium Rhodococcus opacus PD630 has recently emerged as a promising microbial host for lignocellulose conversion to value-added products due to its natural ability to tolerate and utilize phenolics. To gain a better understanding of its phenolic tolerance and utilization mechanisms, we adaptively evolved R. opacus over 40 passages using phenol as its sole carbon source (up to 373% growth improvement over wild-type), and extensively characterized two strains from passages 33 and 40. The two adapted strains showed higher phenol consumption rates (∼20 mg/l/h) and ∼2-fold higher lipid production from phenol than the wild-type strain. Whole-genome sequencing and comparative transcriptomics identified highly-upregulated degradation pathways and putative transporters for phenol in both adapted strains, highlighting the important linkage between mechanisms of regulated phenol uptake, utilization, and evolved tolerance. Our study shows that the R. opacus mutants are likely to use their transporters to import phenol rather than export them, suggesting a new aromatic tolerance mechanism. The identified tolerance genes and pathways are promising candidates for future metabolic engineering in R. opacus for improved lignin conversion to lipid-based products.

Synthetic Gene Regulation in Cyanobacteria.

Cyanobacteria are appealing hosts for green chemical synthesis due to their use of light and carbon dioxide. To optimize product yields and titers, specific and tunable regulation of the metabolic pathways is needed. Synthetic biology has increased and diversified the genetic tools available for biological process control. While early tool development focused on commonly used heterotrophs, there has been a recent expansion of tools for cyanobacteria. CRISPR-Cas9 has been used to edit the genome of cyanobacterial strains, while transcriptional regulation has been accomplished with CRISPR interference and RNA riboswitches. Promoter development has produced a significant number of transcriptional regulators, including those that respond to chemicals, environmental signals, and metabolic states. Trans-acting RNAs have been utilized for posttranscriptional and translational control. The regulation of translation initiation is beginning to be explored with ribosome binding sites and riboswitches, while protein degradation tags have been used to control expression levels. Devices built from multiple parts have also been developed to create more complex behaviors. These advances in development of synthetic cyanobacterial regulatory parts provide the groundwork for creation of new, even more sophisticated bioprocess control devices, bolstering the viability of cyanobacteria as sustainable biotechnology platforms.

Enabling complex genetic circuits to respond to extrinsic environmental signals.

Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc.

Physical, chemical, and metabolic state sensors expand the synthetic biology toolbox for Synechocystis sp. PCC 6803.

Many under-developed organisms possess important traits that can boost the effectiveness and sustainability of microbial biotechnology. Photoautotrophic cyanobacteria can utilize the energy captured from light to fix carbon dioxide for their metabolic needs while living in environments not suited for growing crops. Various value-added compounds have been produced by cyanobacteria in the laboratory; yet, the products' titers and yields are often not industrially relevant and lag behind what have been accomplished in heterotrophic microbes. Genetic tools for biological process control are needed to take advantage of cyanobacteria's beneficial qualities, as tool development also lags behind what has been created in common heterotrophic hosts. To address this problem, we developed a suite of sensors that regulate transcription in the model cyanobacterium Synechocystis sp. PCC 6803 in response to metabolically relevant signals, including light and the cell's nitrogen status, and a family of sensors that respond to the inexpensive chemical, l-arabinose. Increasing the number of available tools enables more complex and precise control of gene expression. Expanding the synthetic biology toolbox for this cyanobacterium also improves our ability to utilize this important under-developed organism in biotechnology. Biotechnol. Bioeng. 2017;114: 1561-1569. © 2017 Wiley Periodicals, Inc.

Cyanobacterial carbon metabolism: Fluxome plasticity and oxygen dependence.

Synechocystis sp. strain PCC 6803 has been widely used as a photo-biorefinery chassis. Based on its genome annotation, this species contains a complete TCA cycle, an Embden-Meyerhof-Parnas pathway (EMPP), an oxidative pentose phosphate pathway (OPPP), and an Entner-Doudoroff pathway (EDP). To evaluate how Synechocystis 6803 catabolizes glucose under heterotrophic conditions, we performed 13 C metabolic flux analysis, metabolite pool size analysis, gene knockouts, and heterologous expressions. The results revealed a cyclic mode of flux through the OPPP. Small, but non-zero, fluxes were observed through the TCA cycle and the malic shunt. Independent knockouts of 6-phosphogluconate dehydrogenase (gnd) and malic enzyme (me) corroborated these results, as neither mutant could grow under dark heterotrophic conditions. Our data also indicate that Synechocystis 6803 metabolism relies upon oxidative phosphorylation to generate ATP from NADPH under dark or insufficient light conditions. The pool sizes of intermediates in the TCA cycle, particularly acetyl-CoA, were found to be several fold lower in Synechocystis 6803 (compared to E. coli metabolite pool sizes), while its sugar phosphate intermediates were several-fold higher. Moreover, negligible flux was detected through the native, or heterologous, EDP in the wild type or Δgnd strains under heterotrophic conditions. Comparing photoautotrophic, photomixotrophic, and heterotrophic conditions, the Calvin cycle, OPPP, and EMPP in Synechocystis 6803 possess the ability to regulate their fluxes under various growth conditions (plastic), whereas its TCA cycle always maintains at low levels (rigid). This work also demonstrates how genetic profiles do not always reflect actual metabolic flux through native or heterologous pathways. Biotechnol. Bioeng. 2017;114: 1593-1602. © 2017 Wiley Periodicals, Inc.

De novo design of heat-repressible RNA thermosensors in E. coli.

RNA-based temperature sensing is common in bacteria that live in fluctuating environments. Most naturally-occurring RNA thermosensors are heat-inducible, have long sequences, and function by sequestering the ribosome binding site in a hairpin structure at lower temperatures. Here, we demonstrate the de novo design of short, heat-repressible RNA thermosensors. These thermosensors contain a cleavage site for RNase E, an enzyme native to Escherichia coli and many other organisms, in the 5' untranslated region of the target gene. At low temperatures, the cleavage site is sequestered in a stem-loop, and gene expression is unobstructed. At high temperatures, the stem-loop unfolds, allowing for mRNA degradation and turning off expression. We demonstrated that these thermosensors respond specifically to temperature and provided experimental support for the central role of RNase E in the mechanism. We also demonstrated the modularity of these RNA thermosensors by constructing a three-input composite circuit that utilizes transcriptional, post-transcriptional, and post-translational regulation. A thorough analysis of the 24 thermosensors allowed for the development of design guidelines for systematic construction of similar thermosensors in future applications. These short, modular RNA thermosensors can be applied to the construction of complex genetic circuits, facilitating rational reprogramming of cellular processes for synthetic biology applications.

Robust, tunable genetic memory from protein sequestration combined with positive feedback.

Natural regulatory networks contain many interacting components that allow for fine-tuning of switching and memory properties. Building simple bistable switches, synthetic biologists have learned the design principles of complex natural regulatory networks. However, most switches constructed so far are so simple (e.g. comprising two regulators) that they are functional only within a limited parameter range. Here, we report the construction of robust, tunable bistable switches in Escherichia coli using three heterologous protein regulators (ExsADC) that are sequestered into an inactive complex through a partner swapping mechanism. On the basis of mathematical modeling, we accurately predict and experimentally verify that the hysteretic region can be fine-tuned by controlling the interactions of the ExsADC regulatory cascade using the third member ExsC as a tuning knob. Additionally, we confirm that a dual-positive feedback switch can markedly increase the hysteretic region, compared to its single-positive feedback counterpart. The dual-positive feedback switch displays bistability over a 10(6)-fold range of inducer concentrations, to our knowledge, the largest range reported so far. This work demonstrates the successful interlocking of sequestration-based ultrasensitivity and positive feedback, a design principle that can be applied to the construction of robust, tunable, and predictable genetic programs to achieve increasingly sophisticated biological behaviors.