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Biology subjects

Martin-Pascual, M.

Publications and source records attributed to Martin-Pascual, M..

3 recordsLinked to original sources

Systematic engineering and machine learning analysis of intrinsic terminators reveal crucial nucleotides directly upstream of the terminator hairpin.

Transcriptional termination efficiency is considered an important parameter for finetuning bacterial gene expression. Still, the design principles that determine transcription termination efficiency remain poorly understood. In this study, we aimed to investigate the impact of the 3 untranslated region (3UTR) on gene expression in Escherichia coli and other bacteria. First, 3UTR variant sequences were generated, with randomized 30 bp sequences inserted between the STOP-codon and an intrinsic terminator, consisting of a GC-rich hairpin and a downstream poly(U)-tail. Using three reporter genes, it was found that different 3UTR sequences resulted in an up to five-fold difference in protein production, independent of the upstream coding sequence. The highest protein production was achieved when an adenosine was present directly upstream of the terminator hairpin. This was consolidated by systematic substitution of key nucleotides of the terminator and assessing their effect on mRNA and protein levels. Subsequently, we developed a predictive random forest machine learning model trained on the termination efficiency of different natural and synthetic terminator sequences, revealing an important role for the nucleotides directly upstream of the terminator hairpin. Altogether, this study showed that an additional adenosine nucleotide upstream of the terminator hairpin leads to improved protein production while reducing terminator read-through. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/736697v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@d8a976org.highwire.dtl.DTLVardef@5d8269org.highwire.dtl.DTLVardef@11cc3e3org.highwire.dtl.DTLVardef@180a305_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

Computer assisted multi-level optimization of malonyl-CoA availability in Pseudomonas putida

Malonyl-CoA is the major precursor for the biosynthesis of diverse industrially valuable products such as fatty acids/alcohols, flavonoids, and polyketides. However, its intracellular availability is limited in most microbial hosts, hampering the biological synthesis of such chemicals. To address this limitation, we present a multi-level optimization workflow using modern metabolic engineer-ing technologies to systematically increase the malonyl-CoA levels in Pseudomonas putida. The workflow involves the identification of gene downregulations, chassis selection, and optimization of the acetyl-CoA carboxylase complex through ribosome binding site engineering. Computa-tional tools and high-throughput screening with a malonyl-CoA biosensor enabled the rapid eval-uation of numerous genetic targets. Combining the most beneficial targets led to a 5.8-fold en-hancement in the production titer of the valuable polyketide phloroglucinol. This study demon-strates the effective integration of computational and genetic technologies for engineering P. putida, opening new avenues for the development of industrially relevant strains and the investi-gation of fundamental biological questions.

synthetic biology↗

Model-guided metabolic engineering of curcuminoid Production in Pseudomonas putida

Production of value-added, plant-derived compounds in microbes increasingly attracts commercially interest in food and pharmaceutical industries. However, plant metabolic pathways are complex, require a robust balance of enzymes, cofactors, ATP and other metabolites, and often result in low production when transplanted to bacteria. This is exemplified by the biosynthesis of curcuminoids from the Curcuma longa plant. Here, we combine dynamic pathway modeling, systematic testing of isoenzymes, and the optimization of gene expression levels and substrate concentrations for the biosynthesis of curcuminoids in Pseudomonas putida, leading to unprecedented conversion rates of caffeic acid and tyrosine to curcumin. The development of kinetic ensemble models guided the design of production strains, emphasizing the necessity of high relative expression of c3h, curs2 and dcs and, the low relative expression of tal, comt, ccoaomt, and 4cl4. This optimization resulted in a strain that achieved a 10.8 {+/-}1.8% of the maximum theoretical yield of curcumin from tyrosine. This represents a 4.1-fold increase in production efficiency and the highest yield reported to date, demonstrating the potential of P. putida as a promising platform for curcuminoid production. Our findings highlight the effectiveness of our strategy not only in the advances in the production of curcuminoids but also in setting a framework for the biosynthesis of other complex compounds.

synthetic biology↗