Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs) as key components of crucial nutrients, soaps, industrial chemicals, and fuels. However, our ability to control the composition of microbially synthesized FFAs is still limited, particularly, for producing medium‐chain fatty acids (MCFAs). This is mainly due to the lack of high‐throughput approaches for FFA analysis to engineer enzymes with desirable product specificity. Here we report a mass spectrometry (MS)‐based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. In particular, matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and a higher m/z peak ratio at 730 and 758 was used as an indication for improved MCFA production. This colony‐based method can be performed at a rate of ~2 s per sample, representing a substantial improvement over gas chromatography‐MS (typically >30 min per sample) as the gold standard method for FFA detection. To demonstrate the power of this method, we performed site‐saturation mutagenesis of the yeast fatty acid synthase and identified nine missense mutations that resulted in improved MCFA production relative to the wild‐type strain. Colony‐based MALDI‐ToF MS screening provides an effective approach for engineering microbial fatty acid compositions in a high‐throughput manner.

Pseudoperonospora cubensis, the causal agent of cucurbit downy mildew (CDM), is known to exhibit host specialization. The virulence of different isolates of the pathogen can be classified into pathotypes based on their compatibility with a differential set composed of specific cucurbit host types. However, the genetic basis of host specialization within P. cubensis is not yet known. Total genomic DNA extracted from nine isolates of P. cubensis collected from 2008 to 2013 from diverse cucurbit host types (Cucumis sativus, C. melo var. reticulatus, Cucurbita maxima, C. moschata, C. pepo, and Citrullus lanatus) in the United States were subjected to whole‐genome sequencing. Comparative analysis of these nine genomes confirmed the presence of two distinct evolutionary lineages (lineages I and II) of P. cubensis. Many fixed polymorphisms separated lineage I comprising isolates from Cucurbita pepo, C. moschata, and Citrullus lanatus from lineage II comprising isolates from Cucumis spp. and Cucurbita maxima. Phenotypic characterization showed that lineage II isolates were of the A1 mating type and belonged to pathotypes 1 and 3 that were not known to be present in the United States prior to the resurgence of CDM in 2004. The association of lineage II isolates with the new pathotypes and a lack of genetic diversity among these isolates suggest that lineage II of P. cubensis is associated with the resurgence of CDM on cucumber in the United States.

There is an omission in the Acknowledgments. The following sentence should be included in the Acknowledgments: We thank SGD Project staff for the creation of the high quality and detailed database of S. cerevisiae genes and their products and Webb Miller for helpful comments. Illumina sequencing services were performed by the Stanford Center for Genomics and Personalized Medicine.

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. The web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ∼2 s/sample.

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