Metabolic Engineering Communications最新文献

Microbial synthesis of monolignols and lignans from simple substrates is a promising alternative to plant extraction. Bottlenecks and byproduct formation during heterologous production require targeted metabolomics tools for pathway optimization.

In contrast to available fractional methods, we established a comprehensive targeted metabolomics method. It enables the quantification of 17 extra- and intracellular metabolites of the monolignol and lignan pathway, ranging from amino acids to pluviatolide. Several cell disruption methods were compared. Hot water extraction was best suited regarding monolignol and lignan stability as well as extraction efficacy. The method was applied to compare enzymes for alleviating bottlenecks during heterologous monolignol and lignan production in E. coli. Variants of tyrosine ammonia-lyase had a considerable influence on titers of subsequent metabolites. The choice of multicopper oxidase greatly affected the accumulation of lignans. Metabolite titers were monitored during batch fermentation of either monolignol or lignan-producing recombinant E. coli strains, demonstrating the dynamic accumulation of metabolites.

The new method enables efficient time-resolved targeted metabolomics of monolignol- and lignan-producing E. coli. It facilitates bottleneck identification and byproduct quantification, making it a valuable tool for further pathway engineering studies. This method will benefit the bioprocess development of biotransformation or fermentation approaches for microbial lignan production.

The global regulator LaeA controls secondary metabolism in diverse Aspergillus species. Here we explored its role in regulation of itaconic acid production in Aspergillus pseudoterreus. To understand its role in regulating metabolism, we deleted and overexpressed laeA, and assessed the transcriptome, proteome, and secreted metabolome prior to and during initiation of phosphate limitation induced itaconic acid production. We found that secondary metabolite clusters, including the itaconic acid biosynthetic gene cluster, are regulated by laeA and that laeA is required for high yield production of itaconic acid. Overexpression of LaeA improves itaconic acid yield at the expense of biomass by increasing the expression of key biosynthetic pathway enzymes and attenuating the expression of genes involved in phosphate acquisition and scavenging. Increased yield was observed in optimized conditions as well as conditions containing excess nutrients that may be present in inexpensive sugar containing feedstocks such as excess phosphate or complex nutrient sources. This suggests that global regulators of metabolism may be useful targets for engineering metabolic flux that is robust to environmental heterogeneity.

Rhodotorula toruloides is a potential chassis for microbial cell factories as this yeast can metabolise different substrates into a diverse range of natural products, but the lack of efficient synthetic biology tools hinders its applicability. In this study, the modular, versatile and efficient Golden Gate DNA assembly system (RtGGA) was adapted to the first basidiomycete, an oleaginous yeast R. toruloides. R. toruloides CCT 0783 was sequenced, and used for the GGA design. The DNA fragments were assembled with predesigned 4-nt overhangs and a library of standardized parts was created containing promoters, genes, terminators, insertional regions, and resistance genes. The library was combined to create cassettes for the characterization of promoters strength and to overexpress the carotenoid production pathway. A variety of reagents, plasmids, and strategies were used and the RtGGA proved to be robust. The RtGGA was used to build three versions of the carotenoid overexpression cassette by using different promoter combinations. The cassettes were transformed into R. toruloides and the three new strains were characterized. Total carotenoid concentration increased by 41%. The dedicated GGA platform fills a gap in the advanced genome engineering toolkit for R. toruloides, enabling the efficient design of complex metabolic pathways.

In this study, a 14-gene edited Pseudomonas putida KT2440 strain for heterologous indigoidine production was examined using three distinct omic datasets. Transcriptomic data indicated that CRISPR/dCpf1-interference (CRISPRi) mediated multiplex repression caused global gene expression changes, implying potential undesirable changes in metabolic flux. ¹³C-metabolic flux analysis (¹³C-MFA) revealed that the core P. putida flux network after CRISPRi repression was conserved, with moderate reduction of TCA cycle and pyruvate shunt activity along with glyoxylate shunt activation during glucose catabolism. Metabolomic results identified a change in intracellular TCA metabolites and extracellular metabolite secretion profiles (sugars and succinate overflow) in the engineered strains. These omic analyses guided further strain engineering, with a random mutagenesis screen first identifying an optimal ribosome binding site (RBS) for Cpf1 that enabled stronger product-substrate pairing (1.6–fold increase). Then, deletion strains were constructed with excision of the PHA operon (ΔphaAZC-IID) resulting in a 2.2–fold increase in indigoidine titer over the optimized Cpf1-RBS construct at the end of the growth phase (∼6 h). The maximum indigoidine titer (at 72 h) in the ΔphaAZC-IID strain had a 1.5–fold and 1.8–fold increase compared to the optimized Cpf1-RBS construct and the original strain, respectively. Overall, this study demonstrated that integration of omic data types is essential for understanding responses to complex metabolic engineering designs and directly quantified the effect of such modifications on central metabolism.

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.

The thermotolerant yeast Kluyveromyces marxianus has gained significant attention in recent years as a promising microbial candidate for industrial biomanufacturing. Despite several contributions to the expanding molecular toolbox for gene expression and metabolic engineering of K. marxianus, there remains a need for a more efficient and versatile genome editing platform. To address this, we developed a CRISPR-based editing system that enables high efficiency marker-less gene disruptions and integrations using only 40 bp homology arms in NHEJ functional and non-functional K. marxianus strains. The use of a strong RNA polymerase II promoter allows efficient expression of gRNAs flanked by the self-cleaving RNA structures, tRNA and HDV ribozyme, from a single plasmid co-expressing a codon optimized Cas9. Implementing this system resulted in nearly 100% efficiency of gene disruptions in both NHEJ-functional and NHEJ-deficient K. marxianus strains, with donor integration efficiencies reaching 50% and 100% in the two strains, respectively. The high gRNA targeting performance also proved instrumental for selection of engineered strains with lower growth rate but improved polyketide biosynthesis by avoiding an extended outgrowth period, a common method used to enrich for edited cells but that fails to recover advantageous mutants with even slightly impaired fitness. Finally, we provide the first demonstration of simultaneous, markerless integrations at multiple loci in K. marxianus using a 2.6 kb and a 7.6 kb donor, achieving a dual integration efficiency of 25.5% in a NHEJ-deficient strain. These results highlight both the ease of use and general robustness of this system for rapid and flexible metabolic engineering in this non-conventional yeast.

Thermophilic microorganisms show high potential for use as biorefinery cell factories. Their high growth temperatures provide fast conversion rates, lower risk of contaminations, and facilitated purification of volatile products. To date, only a few thermophilic species have been utilized for microbial production purposes, and the development of production strains is impeded by the lack of metabolic engineering tools. In this study, we constructed a genome-scale metabolic model, an important part of the metabolic engineering pipeline, of the fast-growing thermophile Geobacillus sp. LC300. The model (iGEL604) contains 604 genes, 1249 reactions and 1311 metabolites, and the reaction reversibility is based on thermodynamics at the optimum growth temperature. The growth phenotype is analyzed by batch cultivations on two carbon sources, further closing balances in carbon and degree-of-reduction. The predictive ability of the model is benchmarked against experimentally determined growth characteristics and internal flux distributions, showing high similarity to experimental phenotypes.

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

The production of the biofuel, isobutanol, in E. coli faces limitations due to alcohol toxicity, product inhibition, product recovery, and long-term industrial feasibility. Here we demonstrate an approach of combining both in vivo with in vitro metabolic engineering to produce isobutanol. The in vivo production of α-ketoisovalerate (KIV) was conducted through CRISPR mediated integration of the KIV pathway in bicistronic design (BCD) in E. coli and inhibition of competitive valine pathway using CRISPRi technology. The subsequent in vitro conversion to isobutanol was carried out with engineered enzymes for 2-ketoacid decarboxylase (KIVD) and alcohol dehydrogenase (ADH). For the in vivo production of KIV and subsequent in vitro production of isobutanol, this two-step serial approach resulted in yields of 56% and 93%, productivities of 0.62 and 0.074 g L⁻¹ h⁻¹, and titers of 5.6 and 1.78 g L⁻¹, respectively. Thus, this combined biosynthetic system can be used as a modular approach for producing important metabolites, like isobutanol, without the limitations associated with in vivo production using a consolidated bioprocess.

Conditional promoters allowing both induction and silencing of gene expression are indispensable for basic and applied research. The xylP promoter (pxylP) from Penicillium chrysogenum was demonstrated to function in various mold species including Aspergillus fumigatus. pxylP allows high induction by xylan or its degradation product xylose with low basal activity in the absence of an inducer. Here we structurally characterized and engineered pxylP in A. fumigatus to optimize its application. Mutational analysis demonstrated the importance of the putative TATA-box and a pyrimidine-rich region in the core promoter, both copies of a largely duplicated 91-bp sequence (91bpDS), as well as putative binding sites for the transcription factor XlnR and a GATA motif within the 91bpDS. In agreement, pxylP activity was found to depend on XlnR, while glucose repression appeared to be indirect. Truncation of the originally used 1643-bp promoter fragment to 725 bp largely preserved the promoter activity and the regulatory pattern. Integration of a third 91bpDS significantly increased promoter activity particularly under low inducer concentrations. Truncation of pxylP to 199 bp demonstrated that the upstream region including the 91bpDSs mediates not only inducer-dependent activation but also repression in the absence of inducer. Remarkably, the 1579-bp pxylP was found to act bi-bidirectionally with a similar regulatory pattern by driving expression of the upstream-located arabinofuranosidase gene. The latter opens the possibility of dual bidirectional use of pxylP. Comparison with a doxycycline-inducible TetOn system revealed a significantly higher dynamic range of pxylP. Taken together, this study identified functional elements of pxylP and opened new methodological opportunities for its application.