Biology subjects

Incha, M. R.

Publications and source records attributed to Incha, M. R..

9 recordsLinked to original sources

bioRxiv2026

Unfiltered: A rapid method for Agrobacterium-mediated transformation of Basidiomycete and Ascomycete yeasts

Agrobacterium-mediated transformation (AMT) is a critical method for genetic manipulation of non-model fungi, yet it remains a laborious and inefficient technique. When cocultured in acetosyringone-supplemented induction medium, Agrobacterium transfers DNA directly into yeast cells using its virulence machinery. Membrane filters are commonly used to support the co-culture of yeast and Agrobacterium on agar plates, however some reports demonstrate that these filters are unnecessary for specific yeast species. Here we confirm across diverse budding yeasts that membrane filters are not necessary for effective AMT. Concentrating the cells via centrifugation and "spotting" the cell pellet directly onto the induction medium proved effective. This reduces hands-on time to 15 minutes and eliminates filter cost. In the oleaginous yeast, Rhodotorula toruloides, this simplified method increases transformation efficiency by 66% to 2,500 transformants per 106 recipient cells. We further optimized the Agrobacterium:Rhodotorula cell ratio and culture resuspension volume to achieve more than 200,000 CFU per transformation representing a 2-3 fold improvement over previously implemented protocols. This spot-plating method was successfully applied to seven yeast species, including one for which genetic transformation has not previously been reported, Botryozyma nematodophila. This approach highlights the broad applicability of the spot-plating method across diverse yeast systems. Furthermore, this method could facilitate high-throughput transformation workflows that are critical for genome-scale functional studies.

microbiology↗

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↗

bioRxiv2023

Characterization and diversification of AraC/XylS family regulators guided by transposon sequencing

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 Pseudomonas putida KT2440. For the AraC-family regulators (AFRs) represented in this data, we posited AFR/promoter/inducer groupings. Eleven promoters were characterized for a response to their proposed inducers in P. putida, and the resultant data were used to create and test nine two-plasmid sensor systems in E. coli. Several of these were further developed into a palette of single-plasmid inducible systems. From these experiments, we observed an unreported inducer response from a previously characterized AFR, demonstrated that the addition of a P. putida transporter improved the sensor dynamics of an AFR in E. coli, and identified an uncharacterized AFR with a novel potential inducer specificity. Finally, targeted mutations in an AFR, informed by structural predictions, enabled further diversification of these inducible plasmids. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/550116v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@fb1ee2org.highwire.dtl.DTLVardef@a88f1dorg.highwire.dtl.DTLVardef@4bbd5borg.highwire.dtl.DTLVardef@7cdbfc_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2023

Foldy: a web application for interactive protein structure analysis

Foldy is a cloud-based application that allows non-expert scientists to easily access and utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. Built on Kubernetes, it can be deployed by universities, departments, and labs without requiring hardware resources, but can also be configured to utilize available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 3000 amino acids, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. Our manuscript describes the user interface and deployment considerations of Foldy, as well as some of our applications. By democratizing access to sophisticated AI-based tools, Foldy can facilitate life science research and promote the wider adoption of structural bioinformatics tools. Our work demonstrates that even the most advanced tools can be made accessible to a broad audience through user-friendly platforms like Foldy, and we believe it will be a valuable resource for researchers across scientific disciplines. The public structures available on the Lawrence Berkeley Labs Foldy deployment can be viewed at https://foldy.lbl.gov. Author SummaryFoldy is a cloud-based application that enables scientists to use AI-based structural biology tools such as AlphaFold and DiffDock without software expertise. Built on Kubernetes, it can be set up by universities, departments, and labs with no need for hardware resources. Foldy can predict the structure of proteins and complexes up to 3000 amino acids, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. Our public structures can be viewed at https://foldy.lbl.gov. Our manuscript highlights the user interface, deployment considerations, and product applications of Foldy. Its an accessible solution for researchers who are not software experts and can handle the traffic of thousands of users and hundreds of thousands of protein structures and docked ligands. This makes advanced AI-based tools more widely available, paving the way for accelerating life science research. By developing an easy-to-use platform, our work demonstrates that even the most sophisticated AI-based tools can be made accessible to a wide audience. Foldy enables more scientists to draw from the rapidly growing field of structural biology, making it a valuable tool for researchers across scientific disciplines. We look forward to its adoption by the scientific community.

bioinformatics↗

bioRxiv2022

Engineering Pseudomonas putida KT2440 for chain length tailored free fatty acid and oleochemical production

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, paving the road for the production of high-value oleochemicals and biofuels from cheap feedstocks, such as plant biomass, using this host. Additionally, by taking advantage of the varying substrate preferences of paralogous native fatty acyl-CoA ligases, we employed a strategy to control FFA chain length that resulted in a P. putida strain specialized in producing medium-chain FFAs. Finally, we demonstrate the production of oleochemicals in these strains by synthesizing medium-chain fatty acid methyl esters, compounds useful as biodiesel blending agents, in various media including sorghum hydrolysate at titers greater than 300 mg/L.

synthetic biology↗

bioRxiv2021

Nitrogen metabolism in Pseudomonas putida: functional analysis using random barcode transposon sequencing

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. From these 71 conditions, significant fitness phenotypes were elicited in 672 different genes including 100 transcriptional regulators and 112 transport-related proteins. We divide these conditions into 6 classes, and propose assimilatory pathways for the compounds based on this wealth of genetic data. To complement these data, we characterize the substrate range of three promiscuous aminotransferases relevant to metabolic engineering efforts in vitro. Furthermore, we examine the specificity of five transcriptional regulators, explaining some fitness data results and exploring their potential to be developed into useful synthetic biology tools. In addition, we use manifold learning to create an interactive visualization tool for interpreting our BarSeq data, which will improve the accessibility and utility of this work to other researchers. IMPORTANCEUnderstanding the genetic basis of P. putidas diverse metabolism is imperative for us to reach its full potential as a host for metabolic engineering. Many target molecules of the bioeconomy and their precursors contain nitrogen. This study provides functional evidence linking hundreds of genes to their roles in the metabolism of nitrogenous compounds, and provides an interactive tool for visualizing these data. We further characterize several aminotransferases, lactamases, and regulators--which are of particular interest for metabolic engineering.

microbiology↗

bioRxiv2019

Leveraging host metabolism for bisdemethoxycurcumin production in Pseudomonas putida

Pseudomonas putida 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 P. putida. T3PKS products are widely used as nutraceuticals and medicines and often require aromatic starter units, such as coumaroyl-CoA, which is also an intermediate in the native coumarate catabolic pathway of P. putida. Using a randomly barcoded transposon mutant (RB-TnSeq) library, we assayed gene functions for a large portion of aromatic catabolism, confirmed known pathways, and proposed new annotations for two aromatic transporters. The 1,3,6,8-tetrahydroxynapthalene synthase of Streptomyces coelicolor (RppA), a microbial T3PKS, was then used to rapidly assay growth conditions for increased T3PKS product accumulation. The feruloyl/coumaroyl CoA synthetase (Fcs) of P. putida was used to supply coumaroyl-CoA for the curcuminoid synthase (CUS) of Oryza sativa, a plant T3PKS. We identified that accumulation of coumaroyl-CoA in this pathway results in extended growth lag times in P. putida. Deletion of the second step in coumarate catabolism, the enoyl-CoA hydratase-lyase (Ech), resulted in increased production of the type III polyketide bisdemethoxycurcumin.

microbiology↗

bioRxiv2019

Identification, characterization, and application of a highly sensitive lactam biosensor from Pseudomonas putida

Caprolactam is an important polymer precursor to nylon traditionally derived from petroleum and produced on a scale of 5 million tons per year. Current biological pathways for the production of caprolactam are inefficient with titers not exceeding 2 mg/L, necessitating novel pathways for its production. As development of novel metabolic routes often require thousands of designs and result in low product titers, a highly sensitive biosensor for the final product has the potential to rapidly speed up development times. Here we report a highly sensitive biosensor for valerolactam and caprolactam from Pseudomonas putida KT2440 which is >1000x more sensitive to exogenous ligand than previously reported sensors. Manipulating the expression of the sensor oplR (PP_3516) substantially altered the sensing parameters, with various vectors showing Kd values ranging from 700 nM (79.1 g/L) to 1.2 mM (135.6 mg/L). Our most sensitive construct was able to detect in vivo production of caprolactam above background at ~6 g/L. The high sensitivity and range of OplR is a powerful tool towards the development of novel routes to the biological synthesis of caprolactam. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/700484v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@ff5b8corg.highwire.dtl.DTLVardef@d365aaorg.highwire.dtl.DTLVardef@b79b18org.highwire.dtl.DTLVardef@27732f_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2019

Glutarate metabolism in Pseudomonas putida is regulated by two distinct glutarate sensing transcription factors

Transcription factor based biosensors can be leveraged to screen thousands of genetics designs for optimal production in engineered microbes. In this study we characterize two glutarate sensing transcription factors (CsiR and GcdR) from Pseudomonas putida. The genomic contexts of CsiR homologs were analyzed and DNA binding sites were bioinformatically predicted. Both CsiR and GcdR were purified and shown to bind upstream of their coding sequencing in vitro. CsiR was shown to dissociate from DNA in vitro when exogenous glutarate was added confirming it acts as a genetic repressor. Both transcription factors were then engineered into plasmid based biosensors and their respective sensing performance features calculated. Both sensor plasmids were then reintroduced into P. putida and were evaluated for their ability to sense flux through glutarate when grown on various lysine metabolites as sole carbon sources. These findings provide information describing glutarate flux in P. putida, and potentially useful tools for future metabolic engineering and synthetic biology efforts.

microbiology↗