Parascedosporium putredinis NO1 tailors its secretome for different lignocellulosic substrates.

Parascedosporium putredinis NO1 is a plant biomass-degrading ascomycete with a propensity to target the most recalcitrant components of lignocellulose. Here we applied proteomics and activity-based protein profiling (ABPP) to investigate the ability of P. putredinis NO1 to tailor its secretome for growth on different lignocellulosic substrates. Proteomic analysis of soluble and insoluble culture fractions following the growth of P. putredinis NO1 on six lignocellulosic substrates highlights the adaptability of the response of the P. putredinis NO1 secretome to different substrates. Differences in protein abundance profiles were maintained and observed across substrates after bioinformatic filtering of the data to remove intracellular protein contamination to identify the components of the secretome more accurately. These differences across substrates extended to carbohydrate-active enzymes (CAZymes) at both class and family levels. Investigation of abundant activities in the secretomes for each substrate revealed similar variation but also a high abundance of "unknown" proteins in all conditions investigated. Fluorescence-based and chemical proteomic ABPP of secreted cellulases, xylanases, and ß-glucosidases applied to secretomes from multiple growth substrates for the first time confirmed highly adaptive time- and substrate-dependent glycoside hydrolase production by this fungus. P. putredinis NO1 is a promising new candidate for the identification of enzymes suited to the degradation of recalcitrant lignocellulosic feedstocks. The investigation of proteomes from the biomass bound and culture supernatant fractions provides a more complete picture of a fungal lignocellulose-degrading response. An in-depth understanding of this varied response will enhance efforts toward the development of tailored enzyme systems for use in biorefining.IMPORTANCEThe ability of the lignocellulose-degrading fungus Parascedosporium putredinis NO1 to tailor its secreted enzymes to different sources of plant biomass was revealed here. Through a combination of proteomic, bioinformatic, and fluorescent labeling techniques, remarkable variation was demonstrated in the secreted enzyme response for this ascomycete when grown on multiple lignocellulosic substrates. The maintenance of this variation over time when exploring hydrolytic polysaccharide-active enzymes through fluorescent labeling, suggests that this variation results from an actively tailored secretome response based on substrate. Understanding the tailored secretomes of wood-degrading fungi, especially from underexplored and poorly represented families, will be important for the development of effective substrate-tailored treatments for the conversion and valorization of lignocellulose.

Whole genome structural predictions reveal hidden diversity in putative oxidative enzymes of the lignocellulose-degrading ascomycete Parascedosporium putredinis NO1.

IMPORTANCE: An annotated reference genome has revealed P. putredinis NO1 as a useful resource for the identification of new lignocellulose-degrading enzymes for biorefining of woody plant biomass. Utilizing a "structure-omics"-based searching strategy, we identified new potentially lignocellulose-active sequences that would have been missed by traditional sequence searching methods. These new identifications, alongside the discovery of novel enzymatic functions from this underexplored lineage with the recent discovery of a new phenol oxidase that cleaves the main structural ß-O-4 linkage in lignin from P. putredinis NO1, highlight the underexplored and poorly represented family Microascaceae as a particularly interesting candidate worthy of further exploration toward the valorization of high value biorenewable products.

A bioinformatic workflow for in silico secretome prediction with the lignocellulose degrading ascomycete fungus Parascedosporium putredinis NO1.

The increasing availability of microbial genome sequences provides a reservoir of information for the identification of new microbial enzymes. Genes encoding proteins engaged in extracellular processes are of particular interest as these mediate the interactions microbes have with their environments. However, proteomic analysis of secretomes is challenging and often captures intracellular proteins released through cell death and lysis. Secretome prediction workflows from sequence data are commonly used to filter proteins identified through proteomics but are often simplified to a single step and are not evaluated bioinformatically for their effectiveness. Here, a workflow to predict a fungal secretome was designed and applied to the coding regions of the Parascedosporium putredinis NO1 genome. This ascomycete fungus is an exceptional lignocellulose degrader from which a new lignin-degrading enzyme has previously been identified. The 'secretome isolation' workflow is based on two strategies of localisation prediction and secretion prediction each utilising multiple available tools. The workflow produced three final secretomes with increasing levels of stringency. All three secretomes showed increases in functional annotations for extracellular processes and reductions in annotations for intracellular processes. Multiple sequences isolated as part of the secretome lacked any functional annotation and made exciting candidates for novel enzyme discovery.