Biology subjects

Menasalvas, J.

Publications and source records attributed to Menasalvas, J..

5 recordsLinked to original sources

bioRxiv2025

Biosensor-Driven Strain Engineering Reveals Key Cellular Processes for Maximizing Isoprenol Production in Pseudomonas putida

Synthetic biology tools have accelerated the generation of simple mutants, but combinatorial testing remains challenging. High-throughput methods struggle translating from proof-of-principle molecules to advanced bioproducts. We address this challenge with a biosensor-driven strategy for enhanced isoprenol production in Pseudomonas putida, a key precursor for sustainable aviation fuel and platform chemicals. This biosensor leverages P. putidas native response to short-chain alcohols via a previously uncharacterized hybrid histidine kinase signaling cascade. Refactoring the biosensor for a conditional growth-based selection enabled identification of competing cellular processes with a [~]16,500-member CRISPRi-library. An iterative combinatorial strain engineering approach yielded an integrated P. putida strain producing [~]900 mg/L isoprenol in glucose minimal medium, a 36-fold increase. Ensemble -omics analysis revealed metabolic rewiring, including amino acid accumulation as key drivers of enhanced production. Techno-economic analysis elucidated the path to economic viability and confirmed the benefits of adding amino acids outweigh the additional costs. This study establishes a robust biosensor driven approach for optimizing other heterologous pathways, accelerating microbial cell factory development. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/643695v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@533605org.highwire.dtl.DTLVardef@ff98fforg.highwire.dtl.DTLVardef@9592fdorg.highwire.dtl.DTLVardef@1e52993_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

RB-TnSeq elucidates dicarboxylic acid specific catabolism in β-proteobacteria for improved plastic monomer upcycling

Dicarboxylic acids are key components of many polymers and plastics, making them a target for both engineered microbial degradation and sustainable bioproduction. In this study, we generated a comprehensive dataset of functional evidence for the genetic basis of dicarboxylic and fatty acid metabolism using randomly-barcoded transposon sequencing (RB-TnSeq). We identified four {beta}-proteobacteria that displayed robust growth with dicarboxylic acid sole carbon sources and cultured their mutant libraries with dicarboxylic and fatty acids with carbon chain lengths from C3 to C12. The resulting fitness data suggested that dicarboxylic and fatty acid metabolisms are largely distinct, and different sets of {beta}-oxidation genes are required for catabolizing dicarboxylic versus fatty acids of the same carbon chain lengths. Additionally, we identified transcriptional regulators and transporters with strong fitness phenotypes related to dicarboxylic acid utilization. In Ralstonia sp. UNC404CL21Col (R. CL21), we deleted two transcriptional repressors to improve its utilization of short chain dicarboxylic acids. We exploited the diacid-utilizing catabolism of R. CL21 to upcycle a mock mixture of the dicarboxylic acids produced when polyethylene is oxidized. After introducing a heterologous indigoidine production pathway, this engineered Rastonia produced 0.56 {+/-} 0.02 g/L indigoidine from a mixture of dicarboxylic acids as a carbon source, demonstrating the potential of R. CL21 to upcycle plastics waste to products derived from tricarboxylic acid (TCA) cycle intermediates. ImportanceUpcycling the carbon in plastic wastes to value-added products is a promising approach to address the plastics waste and climate crises, and dicarboxylic acid metabolism is an important facet of several approaches. Improving our understanding of the genetic basis of this metabolism has the potential to uncover new enzymes and genetic parts for engineered pathways involving dicarboxylic acids. Our dataset is the most comprehensive interrogation of dicarboxylic acid catabolism to date, and this work will be of utility to researchers interested in both plastics bioproduction and upcycling applications.

microbiology↗

bioRxiv2024

Bottlenecks in the Implementation of Genome Scale Metabolic Model Based Designs for Bioproduction from Aromatic Carbon Sources

Genome scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling, pairing product formation with substrate utilization. While such approaches can improve strain performance beyond levels typically accessible using targeted strain engineering approaches, sustainable feedstocks often pose a challenge for GSMM-based methods due to incomplete underlying metabolic data. Specifically, we address a four-gene deletion design for the lignin-derived non-sugar carbon source, para-coumarate, that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product. Through omics, promoter-variation and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarate hydratase activity in the citrate cycle and required careful optimization of the final fumarate hydratase protein (PP_0897) expression to achieve growth and production. A metabolic cross-feeding experiment with the completed design strain also revealed an unanticipated nutrient requirement suggesting additional functions for the fumarate hydratase protein. A double sensitivity analysis confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. While a complete implementation of the design was achieved, this study highlights the challenge of precisely inactivating metabolic reactions encoded by under-characterized proteins especially in the context of multi-gene edits.

microbiology↗

bioRxiv2023

Ensemble and Iterative Engineering for Maximized Bioconversion to the Blue Pigment, Indigoidine from Non-Canonical Sustainable Carbon Sources

While many heterologous molecules can be produced via microbial bioconversion processes, maximizing their titers, rates, and yields from lignin-derived carbon streams remains challenging. Growth coupling can not only increase titers and yields but also shift the production period from stationary phase to growth phase. These methods for designing growth-coupling strains however require multi-gene edits for implementation which may be perceived as impractical. Here, we computationally evaluated 4,114 potential solutions for growth coupling para-coumarate to indigoidine production and prototype two cut sets in Pseudomonas putida KT2440. We used adaptive laboratory evolution (ALE) on the initial triple deletion strain to restore growth on p-CA. Using X-ray tomography on this post-ALE strain we revealed increased cell density and decreased cell volume. Proteomics identified upregulated peroxidases that mitigate reactive oxygen species formation. Nine iterative stepwise modifications further informed by model-guided and rational approaches realized a growth coupled strain that produced 7.3 g/L indigoidine at 77% MTY in para-coumarate minimal medium. These ensemble strategies provide a blueprint for producing target molecules at high product titers, rates, and yields. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/532821v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@f0754aorg.highwire.dtl.DTLVardef@a45d24org.highwire.dtl.DTLVardef@df0596org.highwire.dtl.DTLVardef@1e7e140_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2021

Optimizing a High Performing Multiplex-CRISPRi P. putida strain with Integrated Metabolomics and 13C-Metabolic Flux Analyses

Microbial cell factory development often faces bottlenecks after initial rounds of design-build-test-learn (DBTL) cycles as engineered producers respond unpredictably to further genetic modifications. Thus, deciphering metabolic flux and correcting bottlenecks are key components of DBTL cycles. Here, a 14-gene edited Pseudomonas putida KT2440 strain for heterologous indigoidine production was examined using both 13C-metabolic flux analysis (13C-MFA) and metabolite measurements. The results indicated the conservation of the cyclic Entner-Doudoroff (ED)-EMP pathway flux, downregulation of the TCA cycle and pyruvate shunt, and glyoxylate shunt activation. At the metabolite level, the CRISPR/dCpf1-interference mediated multiplex repression decreased gluconate/2-ketogluconate secretion and altered several intracellular TCA metabolite concentrations, leading to succinate overflow. Further strain engineering based on the metabolic knowledge first employed an optimal ribosome binding site (RBS) to achieve stronger product-substrate growth coupling (1.6-fold increase). Then, deletion strains were constructed using ssDNA recombineering. Of the five strains tested, deletion of the PHA operon ({Delta}phaAZC-IID) resulted in a 2.2-fold increase in growth phase production compared to the optimal RBS construct. After 72 h of batch cultivation, the {Delta}phaAZC-IID strain had 1.5-fold and 1.8-fold increases of indigoidine titer compared to the improved RBS construct and the original strain, respectively. Overall, the findings provided actionable DBTL targets as well as insights into physiological responses and flux buffering when new recombineering tools were used for engineering P. putida KT2440.

synthetic biology↗