Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering.

CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.

Application of functional genomics for domestication of novel non-model microbes.

With the expansion of domesticated microbes producing biomaterials and chemicals to support a growing circular bioeconomy, the variety of waste and sustainable substrates that can support microbial growth and production will also continue to expand. The diversity of these microbes also requires a range of compatible genetic tools to engineer improved robustness and economic viability. As we still do not fully understand the function of many genes in even highly studied model microbes, engineering improved microbial performance requires introducing genome-scale genetic modifications followed by screening or selecting mutants that enhance growth under prohibitive conditions encountered during production. These approaches include adaptive laboratory evolution, random or directed mutagenesis, transposon-mediated gene disruption, or CRISPR interference (CRISPRi). Although any of these approaches may be applicable for identifying engineering targets, here we focus on using CRISPRi to reduce the time required to engineer more robust microbes for industrial applications. ONE-SENTENCE SUMMARY: The development of genome scale CRISPR-based libraries in new microbes enables discovery of genetic factors linked to desired traits for engineering more robust microbial systems.

Improving growth of Cupriavidus necator H16 on formate using adaptive laboratory evolution-informed engineering.

Conversion of CO2 to value-added products presents an opportunity to reduce GHG emissions while generating revenue. Formate, which can be generated by the electrochemical reduction of CO2, has been proposed as a promising intermediate compound for microbial upgrading. Here we present progress towards improving the soil bacterium Cupriavidus necator H16, which is capable of growing on formate as its sole source of carbon and energy using the Calvin-Benson-Bassham (CBB) cycle, as a host for formate utilization. Using adaptive laboratory evolution, we generated several isolates that exhibited faster growth rates on formate. The genomes of these isolates were sequenced, and resulting mutations were systematically reintroduced by metabolic engineering, to identify those that improved growth. The metabolic impact of several mutations was investigated further using RNA-seq transcriptomics. We found that deletion of a transcriptional regulator implicated in quorum sensing, PhcA, reduced expression of several operons and led to improved growth on formate. Growth was also improved by deleting large genomic regions present on the extrachromosomal megaplasmid pHG1, particularly two hydrogenase operons and the megaplasmid CBB operon, one of two copies present in the genome. Based on these findings, we generated a rationally engineered ΔphcA and megaplasmid-deficient strain that exhibited a 24% faster maximum growth rate on formate. Moreover, this strain achieved a 7% growth rate improvement on succinate and a 19% increase on fructose, demonstrating the broad utility of microbial genome reduction. This strain has the potential to serve as an improved microbial chassis for biological conversion of formate to value-added products.

An Agrobacterium strain auxotrophic for methionine is useful for switchgrass transformation.

Auxotrophic strains of Agrobacterium tumefaciens can contribute to the development of more efficient transformation systems, especially for crops historically considered recalcitrant. Homologous recombination was used to derive methionine auxotrophs of two common A. tumefaciens strains, LBA4404 and EHA105. The EHA105 strains were more efficient for switchgrass transformation, while both the EHA105 and LBA4404 strains worked equally well for the rice control. Event quality, as measured by transgene copy number, was not affected by auxotrophy, but was higher for the LBA4404 strains than the EHA105 strains. Ultimately, the use of auxotrophs reduced bacterial overgrowth during co-cultivation and decreased the need for antibiotics.

Engineering improved ethylene production: Leveraging systems biology and adaptive laboratory evolution.

Ethylene is a small hydrocarbon gas widely used in the chemical industry. Annual worldwide production currently exceeds 150 million tons, producing considerable amounts of CO2 contributing to climate change. The need for a sustainable alternative is therefore imperative. Ethylene is natively produced by several different microorganisms, including Pseudomonas syringae pv. phaseolicola via a process catalyzed by the ethylene-forming enzyme (EFE), subsequent heterologous expression of EFE has led to ethylene production in non-native bacterial hosts including Escherichia coli and cyanobacteria. However, solubility of EFE and substrate availability remain rate-limiting steps in biological ethylene production. We employed a combination of genome-scale metabolic modelling, continuous fermentation, and protein evolution to enable the accelerated development of a high efficiency ethylene producing E. coli strain, yielding a 49-fold increase in production, the most significant improvement reported to date. Furthermore, we have clearly demonstrated that this increased yield resulted from metabolic adaptations that were uniquely linked to EFE (wild type versus mutant). Our findings provide a novel solution to deregulate metabolic bottlenecks in key pathways, which can be readily applied to address other engineering challenges.

Predicting Drug Resistance Using Deep Mutational Scanning.

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

Nanorg Microbial Factories: Light-Driven Renewable Biochemical Synthesis Using Quantum Dot-Bacteria Nanobiohybrids.

Living cells do not interface naturally with nanoscale materials, although such artificial organisms can have unprecedented multifunctional properties, like wireless activation of enzyme function using electromagnetic stimuli. Realizing such interfacing in a nanobiohybrid organism (or nanorg) requires (1) chemical coupling via affinity binding and self-assembly, (2) the energetic coupling between optoelectronic states of artificial materials with the cellular process, and (3) the design of appropriate interfaces ensuring biocompatibility. Here we show that seven different core-shell quantum dots (QDs), with excitations ranging from ultraviolet to near-infrared energies, couple with targeted enzyme sites in bacteria. When illuminated by light, these QDs drive the renewable production of different biofuels and chemicals using carbon-dioxide (CO2), water, and nitrogen (from air) as substrates. These QDs use their zinc-rich shell facets for affinity attachment to the proteins. Cysteine zwitterion ligands enable uptake through the cell, facilitating cell survival. Together, these nanorgs catalyze light-induced air-water-CO2 reduction with a high turnover number (TON) of ∼106-108 (mols of product per mol of cells) to biofuels like isopropanol (IPA), 2,3-butanediol (BDO), C11-C15 methyl ketones (MKs), and hydrogen (H2); and chemicals such as formic acid (FA), ammonia (NH3), ethylene (C2H4), and degradable bioplastics polyhydroxybutyrate (PHB). Therefore, these resting cells function as nanomicrobial factories powered by light.

Multiplex navigation of global regulatory networks (MINR) in yeast for improved ethanol tolerance and production.

Multiplex navigation of global regulatory networks (MINR) is an approach for combinatorially reprogramming gene expression to manipulate complex phenotypes. We designed, constructed, and mapped MINR libraries containing 43,020 specific mutations in 25 regulatory genes expected to perturb the yeast regulatory network. We selected growth competition experiments for library mutants conferring increased ethanol and/or glucose tolerance. We identified specific mutants that not only possessed improved ethanol and/or glucose tolerance but also produced ethanol at concentrations up to 2-fold higher than those produced by the wild-type strain. We further determined that mutations increasing ethanol tolerance were transferable to a diploid industrial yeast strain. The facile construction and mapping of 43,020 designer regulatory mutations provide a roadmap for how to access and engineer complex phenotypes in future synthetic biology and broader efforts.

Inactivation of the uptake hydrogenase in the purple non-sulfur photosynthetic bacterium Rubrivivax gelatinosus CBS enables a biological water-gas shift platform for H2 production.

Biological H2 production has potential to address energy security and environmental concerns if produced from renewable or waste sources. The purple non-sulfur photosynthetic bacterium Rubrivivax gelatinosus CBS produces H2 while oxidizing CO, a component of synthesis gas (Syngas). CO-linked H2 production is facilitated by an energy-converting hydrogenase (Ech), while a subsequent H2 oxidation reaction is catalyzed by a membrane-bound hydrogenase (MBH). Both hydrogenases contain [NiFe] active sites requiring 6 maturation factors (HypA-F) for assembly, but it is unclear which of the two annotated sets of hyp genes are required for each in R. gelatinosus CBS. Herein, we report correlated expression of hyp1 genes with Ech genes and hyp2 expression with MBH genes. Moreover, we find that while Ech H2 evolving activity is only delayed when hyp1 is deleted, hyp2 deletion completely disrupts MBH H2 uptake, providing a platform for a biologically driven water-gas shift reaction to produce H2 from CO.

Building a genome engineering toolbox in nonmodel prokaryotic microbes.

The realization of a sustainable bioeconomy requires our ability to understand and engineer complex design principles for the development of platform organisms capable of efficient conversion of cheap and sustainable feedstocks (e.g., sunlight, CO2 , and nonfood biomass) into biofuels and bioproducts at sufficient titers and costs. For model microbes, such as Escherichia coli, advances in DNA reading and writing technologies are driving the adoption of new paradigms for engineering biological systems. Unfortunately, microbes with properties of interest for the utilization of cheap and renewable feedstocks, such as photosynthesis, autotrophic growth, and cellulose degradation, have very few, if any, genetic tools for metabolic engineering. Therefore, it is important to develop "design rules" for building a genetic toolbox for novel microbes. Here, we present an overview of our current understanding of these rules for the genetic manipulation of prokaryotic microbes and the available genetic tools to expand our ability to genetically engineer nonmodel systems.

Genetic analysis of the Hox hydrogenase in the cyanobacterium Synechocystis sp. PCC 6803 reveals subunit roles in association, assembly, maturation, and function.

Hydrogenases are metalloenzymes that catalyze 2H(+) + 2e(-) ↔ H(2). A multisubunit, bidirectional [NiFe]-hydrogenase has been identified and characterized in a number of bacteria, including cyanobacteria, where it is hypothesized to function as an electron valve, balancing reductant in the cell. In cyanobacteria, this Hox hydrogenase consists of five proteins in two functional moieties: a hydrogenase moiety (HoxYH) with homology to heterodimeric [NiFe]-hydrogenases and a diaphorase moiety (HoxEFU) with homology to NuoEFG of respiratory Complex I, linking NAD(P)H ↔ NAD(P)(+) as a source/sink for electrons. Here, we present an extensive study of Hox hydrogenase in the cyanobacterium Synechocystis sp. PCC 6803. We identify the presence of HoxEFUYH, HoxFUYH, HoxEFU, HoxFU, and HoxYH subcomplexes as well as association of the immature, unprocessed large subunit (HoxH) with other Hox subunits and unidentified factors, providing a basis for understanding Hox maturation and assembly. The analysis of mutants containing individual and combined hox gene deletions in a common parental strain reveals apparent alterations in subunit abundance and highlights an essential role for HoxF and HoxU in complex/subcomplex association. In addition, analysis of individual and combined hox mutant phenotypes in a single strain background provides a clear view of the function of each subunit in hydrogenase activity and presents evidence that its physiological function is more complicated than previously reported, with no outward defects apparent in growth or photosynthesis under various growth conditions.

Establishment of a genome editing tool using CRISPR-Cas9 ribonucleoprotein complexes in the non-model plant pathogen Sphaerulina musiva.

CRISPR-Cas9 is a versatile genome editing system widely used since 2013 to introduce site-specific modifications into the genomes of model and non-model species. This technology is used in various applications, from gene knock-outs, knock-ins, and over-expressions to more precise changes, such as the introduction of nucleotides at a targeted locus. CRISPR-Cas9 has been demonstrated to be easy to establish in new species and highly efficient and specific compared to previous gene editing strategies such as Zinc finger nucleases and transcription activator-like effector nucleases. Grand challenges for emerging CRISPR-Cas9 tools in filamentous fungi are developing efficient transformation methods for non-model organisms. In this paper, we have leveraged the establishment of CRISPR-Cas9 genome editing tool that relies on Cas9/sgRNA ribonucleoprotein complexes (RNPs) in the model species Trichoderma reesei and developed the first protocol to efficiently transform the non-model species, Sphaerulina musiva. This fungal pathogen constitutes a real threat to the genus Populus, a foundational bioenergy crop used for biofuel production. Herein, we highlight the general considerations to design sgRNAs and their computational validation. We also describe the use of isolated protoplasts to deliver the CRISPR-Cas9 RNP components in both species and the screening for targeted genome editing events. The development of engineering tools in S. musiva can be used for studying genes involved in diverse processes such as secondary metabolism, establishment, and pathogenicity, among many others, but also for developing genetic mitigation approaches. The approach described here provides guidance for potential development of transformation systems in other non-model spore-bearing ascomycetes.

Highly efficient libraries design for saturation mutagenesis.

Saturation mutagenesis is a semi-rational approach for protein engineering where sites are saturated either entirely or partially to include amino acids of interest. We previously reported on a codon compression algorithm, where a set of minimal degenerate codons are selected according to user-defined parameters such as the target organism, type of saturation and usage levels. Here, we communicate an addition to our web tool that considers the distance between the wild-type codon and the library, depending on its purpose. These forms of restricted collections further reduce library size, lowering downstream screening efforts or, in turn, allowing more comprehensive saturation of multiple sites. The library design tool can be accessed via http://www.dynamcc.com/dynamcc_d/. Graphical Abstract.

Precision genome editing in plants using gene targeting and prime editing: existing and emerging strategies.

Precise modification of plant genomes, such as seamless insertion, deletion, or replacement of DNA sequences at a predefined site, is a challenging task. Gene targeting (GT) and prime editing are currently the best approaches for this purpose. However, these techniques are inefficient in plants, which limits their applications for crop breeding programs. Recently, substantial developments have been made to improve the efficiency of these techniques in plants. Several strategies, such as RNA donor templating, chemically modified donor DNA template, and tandem-repeat homology-directed repair, are aimed at improving GT. Additionally, improved prime editing gRNA design, use of engineered reverse transcriptase enzymes, and splitting prime editing components have improved the efficacy of prime editing in plants. These emerging strategies and existing technologies are reviewed along with various perspectives on their future improvement and the development of robust precision genome editing technologies for plants.

Dynamic and single cell characterization of a CRISPR-interference toolset in Pseudomonas putida KT2440 for ß-ketoadipate production from p-coumarate.

Pseudomonas putida KT2440 is a well-studied bacterium for the conversion of lignin-derived aromatic compounds to bioproducts. The development of advanced genetic tools in P. putida has reduced the turnaround time for hypothesis testing and enabled the construction of strains capable of producing various products of interest. Here, we evaluate an inducible CRISPR-interference (CRISPRi) toolset on fluorescent, essential, and metabolic targets. Nuclease-deficient Cas9 (dCas9) expressed with the arabinose (8K)-inducible promoter was shown to be tightly regulated across various media conditions and when targeting essential genes. In addition to bulk growth data, single cell time lapse microscopy was conducted, which revealed intrinsic heterogeneity in knockdown rate within an isoclonal population. The dynamics of knockdown were studied across genomic targets in exponentially-growing cells, revealing a universal 1.75 ± 0.38 h quiescent phase after induction where 1.5 ± 0.35 doublings occur before a phenotypic response is observed. To demonstrate application of this CRISPRi toolset, ß-ketoadipate, a monomer for performance-advantaged nylon, was produced at a 4.39 ± 0.5 g/L and yield of 0.76 ± 0.10 mol/mol from p-coumarate, a hydroxycinnamic acid that can be derived from grasses. These cultivation metrics were achieved by using the higher strength IPTG (1K)-inducible promoter to knockdown the pcaIJ operon in the ßKA pathway during early exponential phase. This allowed the majority of the carbon to be shunted into the desired product while eliminating the need for a supplemental carbon and energy source to support growth and maintenance.

Biological and Molecular Components for Genetically Engineering Biosensors in Plants.

Plants adapt to their changing environments by sensing and responding to physical, biological, and chemical stimuli. Due to their sessile lifestyles, plants experience a vast array of external stimuli and selectively perceive and respond to specific signals. By repurposing the logic circuitry and biological and molecular components used by plants in nature, genetically encoded plant-based biosensors (GEPBs) have been developed by directing signal recognition mechanisms into carefully assembled outcomes that are easily detected. GEPBs allow for in vivo monitoring of biological processes in plants to facilitate basic studies of plant growth and development. GEPBs are also useful for environmental monitoring, plant abiotic and biotic stress management, and accelerating design-build-test-learn cycles of plant bioengineering. With the advent of synthetic biology, biological and molecular components derived from alternate natural organisms (e.g., microbes) and/or de novo parts have been used to build GEPBs. In this review, we summarize the framework for engineering different types of GEPBs. We then highlight representative validated biological components for building plant-based biosensors, along with various applications of plant-based biosensors in basic and applied plant science research. Finally, we discuss challenges and strategies for the identification and design of biological components for plant-based biosensors.

High-Throughput Functional Genomics for Energy Production.

Functional genomics remains a foundational field for establishing genotype-phenotype relationships that enable strain engineering. High-throughput (HTP) methods accelerate the Design-Build-Test-Learn cycle that currently drives synthetic biology towards a forward engineering future. Trackable mutagenesis techniques including transposon insertion sequencing and CRISPR-Cas-mediated genome editing allow for rapid fitness profiling of a collection, or library, of mutants to discover beneficial mutations. Due to the relative speed of these experiments compared to adaptive evolution experiments, iterative rounds of mutagenesis can be implemented for next-generation metabolic engineering efforts to design complex production and tolerance phenotypes. Additionally, the expansion of these mutagenesis techniques to novel bacteria are opening up industrial microbes that show promise for establishing a bio-based economy.

Transcriptional Regulatory Networks Involved in C3-C4 Alcohol Stress Response and Tolerance in Yeast.

Alcohol toxicity significantly impacts the titer and productivity of industrially produced biofuels. To overcome this limitation, we must find and use strategies to improve stress tolerance in production strains. Previously, we developed a multiplex navigation of a global regulatory network (MINR) library that targeted 25 regulatory genes that are predicted to modify global regulation in yeast under different stress conditions. In this study, we expanded this concept to target the active sites of 47 transcriptional regulators using a saturation mutagenesis library. The 47 targeted regulators interact with more than half of all yeast genes. We then screened and selected for C3-C4 alcohol tolerance. We identified specific mutants that have resistance to isopropanol and isobutanol. Notably, the WAR1_K110N variant improved tolerance to both isopropanol and isobutanol. In addition, we investigated the mechanisms for improvement of isopropanol and isobutanol stress tolerance and found that genes related to glycolysis play a role in tolerance to isobutanol, while changes in ATP synthesis and mitochondrial respiration play a role in tolerance to both isobutanol and isopropanol. Overall, this work sheds light on basic mechanisms for isopropanol and isobutanol toxicity and demonstrates a promising strategy to improve tolerance to C3-C4 alcohols by perturbing the transcriptional regulatory network.

The Model System Saccharomyces cerevisiae Versus Emerging Non-Model Yeasts for the Production of Biofuels.

Microorganisms are effective platforms for the production of a variety of chemicals including biofuels, commodity chemicals, polymers and other natural products. However, deep cellular understanding is required for improvement of current biofuel cell factories to truly transform the Bioeconomy. Modifications in microbial metabolic pathways and increased resistance to various types of stress caused by the production of these chemicals are crucial in the generation of robust and efficient production hosts. Recent advances in systems and synthetic biology provide new tools for metabolic engineering to design strategies and construct optimal biocatalysts for the sustainable production of desired chemicals, especially in the case of ethanol and fatty acid production. Yeast is an efficient producer of bioethanol and most of the available synthetic biology tools have been developed for the industrial yeast Saccharomyces cerevisiae. Non-conventional yeast systems have several advantageous characteristics that are not easily engineered such as ethanol tolerance, low pH tolerance, thermotolerance, inhibitor tolerance, genetic diversity and so forth. Currently, synthetic biology is still in its initial steps for studies in non-conventional yeasts such as Yarrowia lipolytica, Kluyveromyces marxianus, Issatchenkia orientalis and Pichia pastoris. Therefore, the development and application of advanced synthetic engineering tools must also focus on these underexploited, non-conventional yeast species. Herein, we review the basic synthetic biology tools that can be applied to the standard S. cerevisiae model strain, as well as those that have been developed for non-conventional yeasts. In addition, we will discuss the recent advances employed to develop non-conventional yeast strains that are efficient for the production of a variety of chemicals through the use of metabolic engineering and synthetic biology.

Gene Editing Technologies for Biofuel Production in Thermophilic Microbes.

Thermophilic microbes are an attractive bioproduction platform due to their inherently lower contamination risk and their ability to perform thermostable enzymatic processes which may be required for biomass processing and other industrial applications. The engineering of microbes for industrial scale processes requires a suite of genetic engineering tools to optimize existing biological systems as well as to design and incorporate new metabolic pathways within strains. Yet, such tools are often lacking and/or inadequate for novel microbes, especially thermophiles. This chapter focuses on genetic tool development and engineering strategies, in addition to challenges, for thermophilic microbes. We provide detailed instructions and techniques for tool development for an anaerobic thermophile, Caldanaerobacter subterraneus subsp. tengcongensis, including culturing, plasmid construction, transformation, and selection. This establishes a foundation for advanced genetic tool development necessary for the metabolic engineering of this microbe and potentially other thermophilic organisms.