Publications by authors named "Matthew R Incha"

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock.

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In this study, we explored the development of engineered inducible systems. Publicly available data from previous transposon sequencing assays were used to identify regulators of metabolism in KT2440. For AraC family regulators (AFRs) represented in these data, we posited AFR/promoter/inducer groupings.

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Despite advances in understanding the metabolism of Pseudomonas putida KT2440, a promising bacterial host for producing valuable chemicals from plant-derived feedstocks, a strain capable of producing free fatty acid-derived chemicals has not been developed. Guided by functional genomics, we engineered P. putida to produce medium- and long-chain free fatty acids (FFAs) to titers of up to 670 mg/L.

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Pseudomonas putida KT2440 has long been studied for its diverse and robust metabolisms, yet many genes and proteins imparting these growth capacities remain uncharacterized. Using pooled mutant fitness assays, we identified genes and proteins involved in the assimilation of 52 different nitrogen containing compounds. To assay amino acid biosynthesis, 19 amino acid drop-out conditions were also tested.

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With its ability to catabolize a wide variety of carbon sources and a growing engineering toolkit, KT2440 is emerging as an important chassis organism for metabolic engineering. Despite advances in our understanding of the organism, many gaps remain in our knowledge of the genetic basis of its metabolic capabilities. The gaps are particularly noticeable in our understanding of both fatty acid and alcohol catabolism, where many paralogs putatively coding for similar enzymes coexist, making biochemical assignment via sequence homology difficult.

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is a saprophytic bacterium with robust metabolisms and strong solvent tolerance making it an attractive host for metabolic engineering and bioremediation. Due to its diverse carbon metabolisms, its genome encodes an array of proteins and enzymes that can be readily applied to produce valuable products. In this work we sought to identify design principles and bottlenecks in the production of type III polyketide synthase (T3PKS)-derived compounds in .

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A significant bottleneck in synthetic biology involves screening large genetically encoded libraries for desirable phenotypes such as chemical production. However, transcription factor-based biosensors can be leveraged to screen thousands of genetic designs for optimal chemical production in engineered microbes. In this study we characterize two glutarate sensing transcription factors (CsiR and GcdR) from .

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Common strategies for conversion of lignocellulosic biomass to chemical products center on deconstructing biomass polymers into fermentable sugars. Here, we demonstrate an alternative strategy, a growth-coupled, high-yield bioconversion, by feeding cells a non-sugar substrate, by-passing central metabolism, and linking a key metabolic step to generation of acetyl-CoA that is required for biomass and energy generation. Specifically, we converted levulinic acid (LA), an established degradation product of lignocellulosic biomass, to butanone (a.

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In this report, we identify the relevant factors to increase production of medium chain n-alcohols through an expanded view of the reverse β-oxidation pathway. We began by creating a base strain capable of producing medium chain n-alcohols from glucose using a redox-balanced and growth-coupled metabolic engineering strategy. By dividing the heterologous enzymes in the pathway into different modules, we were able to identify and evaluate homologs of each enzyme within the pathway and identify several capable of enhancing medium chain alcohol titers and/or selectivity.

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