Genomic Analysis of the Hydrocarbon-Producing, Cellulolytic, Endophytic Fungus Ascocoryne sarcoides

The microbial conversion of solid cellulosic biomass to liquid biofuels may provide a renewable energy source for transportation fuels. Endophytes represent a promising group of organisms, as they are a mostly untapped reservoir of metabolic diversity. They are often able to degrade cellulose, and they can produce an extraordinary diversity of metabolites. The filamentous fungal endophyte Ascocoryne sarcoides was shown to produce potential-biofuel metabolites when grown on a cellulose-based medium; however, the genetic pathways needed for this production are unknown and the lack of genetic tools makes traditional reverse genetics difficult. We present the genomic characterization of A. sarcoides and use transcriptomic and metabolomic data to describe the genes involved in cellulose degradation and to provide hypotheses for the biofuel production pathways. In total, almost 80 biosynthetic clusters were identified, including several previously found only in plants. Additionally, many transcriptionally active regions outside of genes showed condition-specific expression, offering more evidence for the role of long non-coding RNA in gene regulation. This is one of the highest quality fungal genomes and, to our knowledge, the only thoroughly annotated and transcriptionally profiled fungal endophyte genome currently available. The analyses and datasets contribute to the study of cellulose degradation and biofuel production and provide the genomic foundation for the study of a model endophyte system

Compound gene co-expression profiles.

<p>Each plot shows the quantile-normalized log₂ (RPKM) for each set of genes of co-expressed with a particular compound profile (green 001, red 010, blue 100, cyan 101, purple 110, and black 111) across all 6 conditions (CB, PD4, PD14, AMM, CELL, and OAC). The first three conditions (CB, PD4, and PD14) represent the conditions where the compounds analyzed in this study were detected. The remaining conditions serve as the nulls (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002558#pgen.1002558.s030" target="_blank">Text S1f</a>or details). Within the plots, each line corresponds to a single gene.</p

Coupled transcriptomics and metabolomics to generate pathway predictions.

<p>The top panels (A–D) represent the algorithm schema and the bottom panels (E–H) represent the corresponding steps with data for an example pathway, C8 production. Cyan, green, and purple are used to denote different experimental conditions (1, 2, and 3 and CB, PD4, and PD14 for the schematic and the C8 pathway data, respectively). GC/MS total ion chromatograms (orange box, A & E) are used to generate compound co-occurrence profiles (red box, B & F). These compound co-occurrence profiles are used to group and order the compounds based on patterns of correlation and anti-correlation to build a possible biosynthetic pathway (brown box C & G). Genes for which the expression profile matches the compound profile are considered correlated and therefore likely candidates for the biosynthetic pathway of interest (gray box D & H). Retrosynthesis is then used to match correlated genes with a reaction in the pathway, represented by roman numerals denoted on pathway arrows (brown box, C&G).</p

Analysis of cellulose-related expression.

<p><i>A. sarcoides</i> transcription was profiled when grown on potato-dextrose media for 4 days (PD4), cellulose (CELL) and cellobiose (CB). (A) The total number of genes with quantile normalized log₂(RPKM) greater than 2 was computed for each condition. The venn diagram shows the overlap of these genes across the three conditions. (B) Genes were partitioned according to their homology to the four main CAZY families: Glycoside Hydrolase (GH), Glucosyl Transferase (GT), Carbohydrate Esterase (CE), Carbohydrate Binding Modules (CBM). The homologs were then filtered to include only those genes which showed a standard deviation across the three conditions greater than 0.5. Each family was separately clustered (hierarchical, Euclidean distance, single linkage). The colorbar represents the quantile normalized log₂ (RPKM) value from white (low expression) to dark blue (high expression). Note: CBM can co-occur with all families. Only those genes that had exclusively a CBM domain were clustered in the CBM matrix to avoid duplication. (C) A table of the most highly expressed genes includes genes not directly involved in degradation, such as swollenin and chitin synthase (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002558#s2" target="_blank">Results</a> for more details).</p