Sleeping Beauty mRNA-LNP enables stable rAAV transgene expression in mouse and NHP hepatocytes and improves vector potency.

Recombinant adeno-associated virus (rAAV) vector gene delivery systems have demonstrated great promise in clinical trials but continue to face durability and dose-related challenges. Unlike rAAV gene therapy, integrating gene addition approaches can provide curative expression in mitotically active cells and pediatric populations. We explored a novel in vivo delivery approach based on an engineered transposase, Sleeping Beauty (SB100X), delivered as an mRNA within a lipid nanoparticle (LNP), in combination with an rAAV-delivered transposable transgene. This combinatorial approach achieved correction of ornithine transcarbamylase deficiency in the neonatal Spfash mouse model following a single delivery to dividing hepatocytes in the newborn liver. Correction remained stable into adulthood, while a conventional rAAV approach resulted in a return to the disease state. In non-human primates, integration by transposition, mediated by this technology, improved gene expression 10-fold over conventional rAAV-mediated gene transfer while requiring 5-fold less vector. Additionally, integration site analysis confirmed a random profile while specifically targeting TA dinucleotides across the genome. Together, these findings demonstrate that transposable elements can improve rAAV-delivered therapies by lowering the vector dose requirement and associated toxicity while expanding target cell types.

Metabolome remodeling during the acidogenic-solventogenic transition in Clostridium acetobutylicum.

The fermentation carried out by the biofuel producer Clostridium acetobutylicum is characterized by two distinct phases. Acidogenesis occurs during exponential growth and involves the rapid production of acids (acetate and butyrate). Solventogenesis initiates as cell growth slows down and involves the production of solvents (butanol, acetone, and ethanol). Using metabolomics, isotope tracers, and quantitative flux modeling, we have mapped the metabolic changes associated with the acidogenic-solventogenic transition. We observed a remarkably ordered series of metabolite concentration changes, involving almost all of the 114 measured metabolites, as the fermentation progresses from acidogenesis to solventogenesis. The intracellular levels of highly abundant amino acids and upper glycolytic intermediates decrease sharply during this transition. NAD(P)H and nucleotide triphosphates levels also decrease during solventogenesis, while low-energy nucleotides accumulate. These changes in metabolite concentrations are accompanied by large changes in intracellular metabolic fluxes. During solventogenesis, carbon flux into amino acids, as well as flux from pyruvate (the last metabolite in glycolysis) into oxaloacetate, decreases by more than 10-fold. This redirects carbon into acetyl coenzyme A, which cascades into solventogenesis. In addition, the electron-consuming reductive tricarboxylic acid (TCA) cycle is shutdown, while the electron-producing oxidative (clockwise) right side of the TCA cycle remains active. Thus, the solventogenic transition involves global remodeling of metabolism to redirect resources (carbon and reducing power) from biomass production into solvent production.

Systems-level metabolic flux profiling elucidates a complete, bifurcated tricarboxylic acid cycle in Clostridium acetobutylicum.

Obligatory anaerobic bacteria are major contributors to the overall metabolism of soil and the human gut. The metabolic pathways of these bacteria remain, however, poorly understood. Using isotope tracers, mass spectrometry, and quantitative flux modeling, here we directly map the metabolic pathways of Clostridium acetobutylicum, a soil bacterium whose major fermentation products include the biofuels butanol and hydrogen. While genome annotation suggests the absence of most tricarboxylic acid (TCA) cycle enzymes, our results demonstrate that this bacterium has a complete, albeit bifurcated, TCA cycle; oxaloacetate flows to succinate both through citrate/alpha-ketoglutarate and via malate/fumarate. Our investigations also yielded insights into the pathways utilized for glucose catabolism and amino acid biosynthesis and revealed that the organism's one-carbon metabolism is distinct from that of model microbes, involving reversible pyruvate decarboxylation and the use of pyruvate as the one-carbon donor for biosynthetic reactions. This study represents the first in vivo characterization of the TCA cycle and central metabolism of C. acetobutylicum. Our results establish a role for the full TCA cycle in an obligatory anaerobic organism and demonstrate the importance of complementing genome annotation with isotope tracer studies for determining the metabolic pathways of diverse microbes.

Synthetic recombinase-based state machines in living cells.

State machines underlie the sophisticated functionality behind human-made and natural computing systems that perform order-dependent information processing. We developed a recombinase-based framework for building state machines in living cells by leveraging chemically controlled DNA excision and inversion operations to encode states in DNA sequences. This strategy enables convenient readout of states (by sequencing and/or polymerase chain reaction) as well as complex regulation of gene expression. We validated our framework by engineering state machines in Escherichia coli that used one, two, or three chemical inputs to control up to 16 DNA states. These state machines were capable of recording the temporal order of all inputs and performing multi-input, multi-output control of gene expression. We also developed a computational tool for the automated design of gene regulation programs using recombinase-based state machines. Our scalable framework should enable new strategies for recording and studying how combinational and temporal events regulate complex cell functions and for programming sophisticated cell behaviors.

Digital and analog gene circuits for biotechnology.

Biotechnology offers the promise of valuable chemical production via microbial processing of renewable and inexpensive substrates. Thus far, static metabolic engineering strategies have enabled this field to advance industrial applications. However, the industrial scaling of statically engineered microbes inevitably creates inefficiencies due to variable conditions present in large-scale microbial cultures. Synthetic gene circuits that dynamically sense and regulate different molecules can resolve this issue by enabling cells to continuously adapt to variable conditions. These circuits also have the potential to enable next-generation production programs capable of autonomous transitioning between steps in a bioprocess. Here, we review the design and application of two main classes of dynamic gene circuits, digital and analog, for biotechnology. Within the context of these classes, we also discuss the potential benefits of digital-analog interconversion, memory, and multi-signal integration. Though synthetic gene circuits have largely been applied for cellular computation to date, we envision that utilizing them in biotechnology will enhance the efficiency and scope of biochemical production with living cells.