Sean McIlwain

Forazoline A: Marine-Derived Polyketide with Antifungal In Vivo Efficacy†

Forazoline A, a novel antifungal polyketide with in vivo efficacy against Candida albicans, was discovered using LCMS-based metabolomics to investigate marine-invertebrate-associated bacteria. Forazoline A had a highly unusual and unprecedented skeleton. Acquisition of (13)C-(13)C gCOSY and (13)C-(15)N HMQC NMR data provided the direct carbon-carbon and carbon-nitrogen connectivity, respectively. This approach represents the first example of determining direct (13)C-(15)N connectivity for a natural product. Using yeast chemical genomics, we propose that forazoline A operated through a new mechanism of action with a phenotypic outcome of disrupting membrane integrity.

Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis

Efficiently and accurately analyzing big protein tandem mass spectrometry data sets requires robust software that incorporates state-of-the-art computational, machine learning, and statistical methods. The Crux mass spectrometry analysis software toolkit (http://cruxtoolkit.sourceforge.net) is an open source project that aims to provide users with a cross-platform suite of analysis tools for interpreting protein mass spectrometry data.

Aromatic inhibitors derived from ammonia-pretreated lignocellulose hinder bacterial ethanologenesis by activating regulatory circuits controlling inhibitor efflux and detoxification

Efficient microbial conversion of lignocellulosic hydrolysates to biofuels is a key barrier to the economically viable deployment of lignocellulosic biofuels. A chief contributor to this barrier is the impact on microbial processes and energy metabolism of lignocellulose-derived inhibitors, including phenolic carboxylates, phenolic amides (for ammonia-pretreated biomass), phenolic aldehydes, and furfurals. To understand the bacterial pathways induced by inhibitors present in ammonia-pretreated biomass hydrolysates, which are less well studied than acid-pretreated biomass hydrolysates, we developed and exploited synthetic mimics of ammonia-pretreated corn stover hydrolysate (ACSH). To determine regulatory responses to the inhibitors normally present in ACSH, we measured transcript and protein levels in an Escherichia coli ethanologen using RNA-seq and quantitative proteomics during fermentation to ethanol of synthetic hydrolysates containing or lacking the inhibitors. Our study identified four major regulators mediating these responses, the MarA/SoxS/Rob network, AaeR, FrmR, and YqhC. Induction of these regulons was correlated with a reduced rate of ethanol production, buildup of pyruvate, depletion of ATP and NAD(P)H, and an inhibition of xylose conversion. The aromatic aldehyde inhibitor 5-hydroxymethylfurfural appeared to be reduced to its alcohol form by the ethanologen during fermentation, whereas phenolic acid and amide inhibitors were not metabolized. Together, our findings establish that the major regulatory responses to lignocellulose-derived inhibitors are mediated by transcriptional rather than translational regulators, suggest that energy consumed for inhibitor efflux and detoxification may limit biofuel production, and identify a network of regulators for future synthetic biology efforts.

Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3), a component of MAP Kinase (MAPK) signaling (HOG1), a regulator of Protein Kinase A (PKA) signaling (IRA2), and a scaffolding protein for mitochondrial iron-sulfur (Fe-S) cluster biogenesis (ISU1). Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.

Prion disease diagnosis by proteomic profiling.

Definitive prion disease diagnosis is currently limited to postmortem assay for the presence of the disease-associated proteinase K-resistant prion protein. Using cerebrospinal fluid (CSF) from prion-infected hamsters, matrix-assisted laser desorption/ionization Fourier transform mass spectrometry (MALDI-FTMS), and support vector machines (SVM), we have identified peptide profiles characteristic of disease state. Using 10-fold leave-one-out cross-validation, we report a predictive accuracy of 72% with a true positive rate of 73% and a false positive rate of 27% demonstrating the suitability of using proteomic profiling and CSF for the development of multiple marker diagnostics of prion disease.

Plant-derived antifungal agent poacic acid targets β-1,3-glucan

Significance The search for new antifungal compounds is struggling to keep pace with emerging fungicide resistance. Through chemoprospecting of an untapped reservoir of inhibitory compounds, lignocellulosic hydrolysates, we have identified a previously undescribed antifungal agent, poacic acid. Using both chemical genomics and morphological analysis together for the first time, to our knowledge, we identified the cellular target of poacic acid as β-1,3-glucan. Through its action on the glucan layer of fungal cell walls, poacic acid is a natural antifungal agent against economically significant fungi and oomycete plant pathogens. This work highlights the chemical diversity within lignocellulosic hydrolysates as a source of potentially valuable chemicals. A rise in resistance to current antifungals necessitates strategies to identify alternative sources of effective fungicides. We report the discovery of poacic acid, a potent antifungal compound found in lignocellulosic hydrolysates of grasses. Chemical genomics using Saccharomyces cerevisiae showed that loss of cell wall synthesis and maintenance genes conferred increased sensitivity to poacic acid. Morphological analysis revealed that cells treated with poacic acid behaved similarly to cells treated with other cell wall-targeting drugs and mutants with deletions in genes involved in processes related to cell wall biogenesis. Poacic acid causes rapid cell lysis and is synergistic with caspofungin and fluconazole. The cellular target was identified; poacic acid localized to the cell wall and inhibited β-1,3-glucan synthesis in vivo and in vitro, apparently by directly binding β-1,3-glucan. Through its activity on the glucan layer, poacic acid inhibits growth of the fungi Sclerotinia sclerotiorum and Alternaria solani as well as the oomycete Phytophthora sojae. A single application of poacic acid to leaves infected with the broad-range fungal pathogen S. sclerotiorum substantially reduced lesion development. The discovery of poacic acid as a natural antifungal agent targeting β-1,3-glucan highlights the potential side use of products generated in the processing of renewable biomass toward biofuels as a source of valuable bioactive compounds and further clarifies the nature and mechanism of fermentation inhibitors found in lignocellulosic hydrolysates.

Chemical genomic profiling via barcode sequencing to predict compound mode of action

Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds.

Genome Sequence and Analysis of a Stress-Tolerant, Wild-Derived Strain of Saccharomyces cerevisiae Used in Biofuels Research

The genome sequences of more than 100 strains of the yeast Saccharomyces cerevisiae have been published. Unfortunately, most of these genome assemblies contain dozens to hundreds of gaps at repetitive sequences, including transposable elements, tRNAs, and subtelomeric regions, which is where novel genes generally reside. Relatively few strains have been chosen for genome sequencing based on their biofuel production potential, leaving an additional knowledge gap. Here, we describe the nearly complete genome sequence of GLBRCY22-3 (Y22-3), a strain of S. cerevisiae derived from the stress-tolerant wild strain NRRL YB-210 and subsequently engineered for xylose metabolism. After benchmarking several genome assembly approaches, we developed a pipeline to integrate Pacific Biosciences (PacBio) and Illumina sequencing data and achieved one of the highest quality genome assemblies for any S. cerevisiae strain. Specifically, the contig N50 is 693 kbp, and the sequences of most chromosomes, the mitochondrial genome, and the 2-micron plasmid are complete. Our annotation predicts 92 genes that are not present in the reference genome of the laboratory strain S288c, over 70% of which were expressed. We predicted functions for 43 of these genes, 28 of which were previously uncharacterized and unnamed. Remarkably, many of these genes are predicted to be involved in stress tolerance and carbon metabolism and are shared with a Brazilian bioethanol production strain, even though the strains differ dramatically at most genetic loci. The Y22-3 genome sequence provides an exceptionally high-quality resource for basic and applied research in bioenergy and genetics.

Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy

Mass spectrometry (MS)-based top-down proteomics is a powerful method for the comprehensive analysis of proteoforms that arise from genetic variations and post-translational modifications (PTMs). However, top-down MS analysis of high molecular weight (MW) proteins remains challenging mainly due to the exponential decay of signal-to-noise ratio with increasing MW. Size exclusion chromatography (SEC) is a favored method for size-based separation of biomacromolecules but typically suffers from low resolution. Herein, we developed a serial size exclusion chromatography (sSEC) strategy to enable high-resolution size-based fractionation of intact proteins (10-223 kDa) from complex protein mixtures. The sSEC fractions could be further separated by reverse phase chromatography (RPC) coupled online with high-resolution MS. We have shown that two-dimensional (2D) sSEC-RPC allowed for the identification of 4044 more unique proteoforms and a 15-fold increase in the detection of proteins above 60 kDa, compared to one-dimensional (1D) RPC. Notably, effective sSEC-RPC separation of proteins significantly enhanced the detection of high MW proteins up to 223 kDa and also revealed low abundance proteoforms that are post-translationally modified. This sSEC method is MS-friendly, robust, and reproducible and, thus, can be applied to both high-efficiency protein purification and large-scale proteomics analysis of cell or tissue lysate for enhanced proteome coverage, particularly for low abundance and high MW proteoforms.

Combining MALDI-FTMS and bioinformatics for rapid peptidomic comparisons.

Increasing research efforts in large-scale mass spectral analyses of peptides and proteins have led to many advances in technology and method development for collecting data and improving the quality of data. However, the resultant large data sets often pose significant challenges in extracting useful information in a high-throughput manner. Here, we describe one such method where we analyzed a large mass spectral data set collected using decapod crustacean nervous tissue extracts separated via high-performance liquid chromatography (HPLC) coupled to high-resolution matrix-assisted laser desorption/ionization Fourier transform mass spectrometry (MALDI-FTMS). Following their acquisition, the data collected from discrete LC fractions was compiled and analyzed using an in-house developed software package that deisotoped, compressed, calibrated, and matched peaks to a list of known crustacean neuropeptides. By processing these data via bioinformatics tools such as hierarchical clustering, more than 110 neuropeptides that belong to 14 peptide families were mapped in five crustacean species. Overall, we demonstrate the utility of MALDI-FTMS in combination with a bioinformatics software package for the elucidation and comparison of peptidomes of varying crustacean species. This study established an effective methodology and will provide the basis for future investigations into more comprehensive comparative peptidomics with larger collection of species and phyla in order to gain a deeper understanding of the evolution and diversification of peptide families.