The carbon starvation response of Aspergillus niger during submerged cultivation: insights from the transcriptome and secretome.

Filamentous fungi are confronted with changes and limitations of their carbon source during growth in their natural habitats and during industrial applications. To survive life-threatening starvation conditions, carbon from endogenous resources becomes mobilized to fuel maintenance and self-propagation. Key to understand the underlying cellular processes is the system-wide analysis of fungal starvation responses in a temporal and spatial resolution. The knowledge deduced is important for the development of optimized industrial production processes. This study describes the physiological, morphological and genome-wide transcriptional changes caused by prolonged carbon starvation during submerged batch cultivation of the filamentous fungus Aspergillus niger. Bioreactor cultivation supported highly reproducible growth conditions and monitoring of physiological parameters. Changes in hyphal growth and morphology were analyzed at distinct cultivation phases using automated image analysis. The Affymetrix GeneChip platform was used to establish genome-wide transcriptional profiles for three selected time points during prolonged carbon starvation. Compared to the exponential growth transcriptome, about 50% (7,292) of all genes displayed differential gene expression during at least one of the starvation time points. Enrichment analysis of Gene Ontology, Pfam domain and KEGG pathway annotations uncovered autophagy and asexual reproduction as major global transcriptional trends. Induced transcription of genes encoding hydrolytic enzymes was accompanied by increased secretion of hydrolases including chitinases, glucanases, proteases and phospholipases as identified by mass spectrometry. This study is the first system-wide analysis of the carbon starvation response in a filamentous fungus. Morphological, transcriptomic and secretomic analyses identified key events important for fungal survival and their chronology. The dataset obtained forms a comprehensive framework for further elucidation of the interrelation and interplay of the individual cellular events involved.