Increased triacylglycerol production in Rhodococcus opacus by overexpressing transcriptional regulators.

Lignocellulosic biomass is currently underutilized, but it offers promise as a resource for the generation of commercial end-products, such as biofuels, detergents, and other oleochemicals. Rhodococcus opacus PD630 is an oleaginous, Gram-positive bacterium with an exceptional ability to utilize recalcitrant aromatic lignin breakdown products to produce lipid molecules such as triacylglycerols (TAGs), which are an important biofuel precursor. Lipid carbon storage molecules accumulate only under growth-limiting low nitrogen conditions, representing a significant challenge toward using bacterial biorefineries for fuel precursor production. In this work, we screened overexpression of 27 native transcriptional regulators for their abilities to improve lipid accumulation under nitrogen-rich conditions, resulting in three strains that accumulate increased lipids, unconstrained by nitrogen availability when grown in phenol or glucose. Transcriptomic analyses revealed that the best strain (#13) enhanced FA production via activation of the ß-ketoadipate pathway. Gene deletion experiments confirm that lipid accumulation in nitrogen-replete conditions requires reprogramming of phenylalanine metabolism. By generating mutants decoupling carbon storage from low nitrogen environments, we move closer toward optimizing R. opacus for efficient bioproduction on lignocellulosic biomass.

Earth: Extinguishing anthropogenic risks through harmonization.

Human diseases can kill one person at a time, but the COVID-19 pandemic showed massacres could be possible. The climate crisis could be even worse, potentially leading to a bigger number of deaths of the human species and all living systems on Earth. I urge us to change our human-focused mindset to solve many problems, including the climate crisis, which humans caused to the entire ecosystems due to our arrogance: humans own this world. In this perspective article, I propose four recommendations to address climate issues through paradigm change and safe and sustainable technologies.

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.

Engineering E. coli strains using antibiotic-resistance-gene-free plasmids.

We created a generalizable pipeline for antibiotic-resistance-gene-free plasmid (ARGFP)-based cloning using a dual auxotrophic- and essential-gene-based selection strategy. We use auxotrophic selection to construct plasmids in engineered E. coli DH10B cloning strains and both auxotrophic- and essential-gene-based selection to (1) select for recombinant strains and (2) maintain a plasmid in E. coli Nissle 1917, a common chassis for engineered probiotic applications, and E. coli MG1655, the laboratory "wild-type" E. coli strain. We show that our approach has comparable efficiency to that of antibiotic-resistance-gene-based cloning. We also show that the double-knockout Nissle and MG1655 strains are simple to transform with plasmids of interest. Notably, we show that the engineered Nissle strains are amenable to long-term plasmid maintenance in repeated culturing as well as in the mouse gut, demonstrating the potential for broad applications while minimizing the risk of antibiotic resistance spread via horizontal gene transfer.

Advances in ligand-specific biosensing for structurally similar molecules.

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

EBRC: Enhancing bioeconomy through research and communication.

On September 12, 2022, President Biden issued Executive Order 14081 to enable the progress of biomanufacturing and biotechnology. This timely initiative will help overcome many challenging issues, and its potential impacts will be huge. This article discusses eight recommendations to make this US national initiative successful, encourage other nations to consider similar initiatives, and create a better world for the next generations.

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.

SynHEAL: Synthesis of Health Equity, Advancement, and Leadership.

ARPA-H recently started its operation with a great vision and potential to revolutionize the biomedical field and research. To help them shape the future biomedical field and community and to make the biotechnology community aware of this new, exciting funding agency, I share my vision after collecting many comments and opinions from researchers, policymakers, journal editors, and funding agency directors. As DARPA has made huge impacts on science, engineering, and society, ARPA-H will do so by paying attention to and implementing stakeholders' suggestions. I also suggest that the biotechnology community members, including academic researchers, people in the biotechnology industry, and policymakers, should nurture innovation and diversity.

Characterizing a Propionate Sensor in E. coli Nissle 1917.

Short-chain fatty acids (SCFAs) are commonly found in the large intestine, but generally not in the small intestine, and influence microbiome composition and host physiology. Thus, synthetic biologists are interested in developing engineered probiotics capable of in situ detection of SCFAs as biogeography or disease sensors. One SCFA, propionate, is both sensed and consumed by E. coli. Here, we utilize the E. coli transcription factor PrpR, sensitive to the propionate-derived metabolite (2S,3S)-2-methylcitrate, and its cognate promoter PprpBCDE to detect extracellular propionate with the probiotic chassis bacterium E. coli Nissle 1917. We identify that PrpR-PprpBCDE displays stationary phase leakiness and transient bimodality, and we explain these observations through evolutionary rationales and deterministic modeling, respectively. Our results will help researchers build biogeographically sensitive genetic circuits.

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism.

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2's flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Upcycling of poly(ethylene terephthalate) to produce high-value bio-products.

More than 70 million tons of poly(ethylene terephthalate) (PET) are manufactured worldwide every year. The accumulation of PET waste has become a global pollution concern, motivating the urgent development of technologies to valorize post-consumer PET. The development of chemocatalytic and enzymatic approaches for depolymerizing PET to its corresponding monomers opens up new opportunities for PET upcycling through biological transformation. Here, we identify Rhodococcus jostii strain PET (RPET) that can directly use PET hydrolysate as a sole carbon source. We also investigate the potential of RPET to upcycle PET into value-added chemicals, using lycopene as a proof-of-concept product. Through rational metabolic engineering, we improve lycopene production by more than 500-fold over that of the wild type. In addition, we demonstrate the production of approximately 1,300 µg/L lycopene from PET by cascading this strain with PET alkaline hydrolysis. This work highlights the great potential of biological conversion as a means of achieving PET upcycling.

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.

Deciphering the transcriptional regulation of the catabolism of lignin-derived aromatics in Rhodococcus opacus PD630.

Rhodococcus opacus PD630 has considerable potential as a platform for valorizing lignin due to its innate "biological funneling" pathways. However, the transcriptional regulation of the aromatic catabolic pathways and the mechanisms controlling aromatic catabolic operons in response to different aromatic mixtures are still underexplored. Here, we identified and studied the transcription factors for aromatic degradation using GFP-based sensors and comprehensive deletion analyses. Our results demonstrate that the funneling pathways for phenol, guaiacol, 4-hydroxybenzoate, and vanillate are controlled by transcriptional activators. The two different branches of the ß-ketoadipate pathway, however, are controlled by transcriptional repressors. Additionally, promoter activity assays revealed that the substrate hierarchy in R. opacus may be ascribed to the transcriptional cross-regulation of the individual aromatic funneling pathways. These results provide clues to clarify the molecule-level mechanisms underlying the complex regulation of aromatic catabolism, which facilitates the development of R. opacus as a promising chassis for valorizing lignin.

SynMADE: synthetic microbiota across diverse ecosystems.

The past two decades have witnessed rapid advances in engineering individual microbial strains to produce biochemicals and biomaterials. However, engineering microbial consortia has been relatively slow. Using systems and synthetic biology approaches, researchers have been developing tools for engineering complex microbiota. In this opinion article, I discuss future directions and visions regarding developing microbiota as a biomanufacturing host. Specifically, I propose that we can develop the soil microbial community itself as a huge bioreactor. Ultimately, researchers will provide a generalizable system that enables us to understand a microbial consortium's interaction and metabolism on diverse temporal and spatial scales to address global problems, including the climate crisis, food inequality, the issue of waste, and sustainable bioproduction.

Model-Based Design of Synthetic Antisense RNA for Predictable Gene Repression.

Our enhanced understanding of RNA folding and function has increased the use of small RNA regulators. Among these RNA regulators, synthetic antisense RNA (asRNA) is designed to contain an RNA sequence complementary to the target mRNA sequence, and the formation of double-stranded RNA (dsRNA) facilitates gene repression due to dsRNA degradation or prevention of ribosome access to the mRNA. Despite the simple complementarity rule, however, predictably tunable repression has been challenging when synthetic asRNAs are used. Here, the protocol for model-based asRNA design is described. This model can predict synthetic asRNA-mediated repression efficiency using two parameters: the change in free energy of complex formation (ΔGCF) and percent mismatch of the target binding region (TBR). The model has been experimentally validated in both Gram-positive and Gram-negative bacteria as well as for target genes in both plasmids and chromosomes. These asRNAs can be created by simply replacing the TBR sequence with one that is complementary to the target mRNA sequence of interest. In principle, this protocol can be applied to design and build asRNAs for predictable gene repression in various contexts, including multiple target genes and organisms, making asRNAs predictably tunable regulators for broad applications.