High-Throughput Functional Genomics for Energy Production

Reshaping Phosphatase Substrate Preference for Controlled Biosynthesis Using a "Design-Build-Test-Learn" Framework

Biosynthesis is the application of enzymes in microbial cell factories and has emerged as a promising alternative to chemical synthesis. However, natural enzymes with limited catalytic performance often need to be engineered to meet specific needs through a time-consuming trial-and-error process. This study presents a quantum mechanics (QM)-incorporated design-build-test-learn (DBTL) framework to rationally design phosphatase BT4131, an enzyme with an ambiguous substrate spectrum involved in N-acetylglucosamine (GlcNAc) biosynthesis. First, mutant M1 (L129Q) is designed using force field-based methods, resulting in a 1.4-fold increase in substrate preference (kcat/Km) toward GlcNAc-6-phosphate (GlcNAc6P). QM calculations indicate that the shift in substrate preference is caused by a 13.59 kcal mol-1 reduction in activation energy. Furthermore, an iterative computer-aided design is conducted to stabilize the transition state. As a result, mutant M4 (I49Q/L129Q/G172L) with a 9.5-fold increase in kcat-GlcNAc6P/Km-GlcNAc6P and a 59% decrease in kcat-Glc6P/Km-Glc6P is highly desirable compared to the wild type in the GlcNAc-producing chassis. The GlcNAc titer increases to 217.3 g L-1 with a yield of 0.597 g (g glucose)-1 in a 50-L bioreactor, representing the highest reported level. Collectively, this DBTL framework provides an easy yet fascinating approach to the rational design of enzymes for industrially viable biocatalysts.

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.

Light regulation of secondary metabolism in fungi

Fungi have evolved unique metabolic regulation mechanisms for adapting to the changing environments. One of the key features of fungal adaptation is the production of secondary metabolites (SMs), which are essential for survival and beneficial to the organism. Many of these SMs are produced in response to the environmental cues, such as light. In all fungal species studied, the Velvet complex transcription factor VeA is a central player of the light regulatory network. In addition to growth and development, the intensity and wavelength of light affects the formation of a broad range of secondary metabolites. Recent studies, mainly on species of the genus Aspergillus, revealed that the dimer of VeA-VelB and LaeA does not only regulate gene expression in response to light, but can also be involved in regulating production of SMs. Furthermore, the complexes have a wide regulatory effect on different types of secondary metabolites. In this review, we discussed the role of light in the regulation of fungal secondary metabolism. In addition, we reviewed the photoreceptors, transcription factors, and signaling pathways that are involved in light-dependent regulation of secondary metabolism. The effects of transcription factors on the production of secondary metabolites, as well as the potential applications of light regulation for the production of pharmaceuticals and other products were discussed. Finally, we provided an overview of the current research in this field and suggested potential areas for future research.

Multiplexed fitness profiling by RB-TnSeq elucidates pathways for lignin-related aromatic catabolism in Sphingobium sp. SYK-6

Bioconversion of lignin-related aromatic compounds relies on robust catabolic pathways in microbes. Sphingobium sp. SYK-6 (SYK-6) is a well-characterized aromatic catabolic organism that has served as a model for microbial lignin conversion, and its utility as a biocatalyst could potentially be further improved by genome-wide metabolic analyses. To this end, we generate a randomly barcoded transposon insertion mutant (RB-TnSeq) library to study gene function in SYK-6. The library is enriched under dozens of enrichment conditions to quantify gene fitness. Several known aromatic catabolic pathways are confirmed, and RB-TnSeq affords additional detail on the genome-wide effects of each enrichment condition. Selected genes are further examined in SYK-6 or Pseudomonas putida KT2440, leading to the identification of new gene functions. The findings from this study further elucidate the metabolism of SYK-6, while also providing targets for future metabolic engineering in this organism or other hosts for the biological valorization of lignin.

Dynamic and single cell characterization of a CRISPR-interference toolset in Pseudomonas putida KT2440 for β-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, β-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 βKA 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.

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Developed an inducible dCas9-based CRISPR interference toolset in Pseudomonas putida KT2440.

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Characterized single-cell dynamics of fluorescent and essential gene knockdown.

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Applied the toolset for glucose-free production of β-ketoadipate from p-coumarate.

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Produced β-ketoadipate at titer of 4.39 ± 0.5 g/L and 0.76 ± 0.10 mol/mol yield.