the GeneChip Operating Software from Affymetrix, and subsequently pre-processed using the statistical language and environment R (www.R-project.org) version 2.5. The probe intensities were normalised for background noise with the robust multiarray average (RMA) method [27] using only perfect match (PM) probes. Normalisation was performed subsequently using the quantiles algorithm [28]. Gene expression values were calculated from the PM probes with the median polish summary method [27]. Statistical analysis with the limma package [29] was applied to determine differentially expressed genes. Moderated t-tests be- tween two strains grown on the same carbon sources were used for the comparison of the PHK effect on four different carbon sources. For all comparisons were empirical Bayesian statistics employed to moderate standard errors within each gene and Benjamini- Hochberg’s method [30] to adjust p-values for multi-testing. Where nothing else is stated, an adjusted cut-off value of p,0.05 was used to determine statistically significant changes. Manual annotation General function (KOG/Interpro/PFAM) was assigned by comparing PFAM predictions to a manual lookup of the bi- directional best hits in the A. niger ATCC 1015 genome sequence (http://genome.jgi-psf.org/Aspni1/Aspni1.home.html). Addition- ally was added A. nidulans genes found in the SwissProt database (Supplementary Table S8). Pathway analysis Metabolic pathway analysis was done using an adaptation of a metabolic network map for A. niger [31]. Bi-directional best blast hits were used to find A. nidulans homologues to metabolic genes. p,.05 was employed as a cut-off value for statistical significance. Reporter metabolite analysis The statistical significance of regulation around metabolites was assessed using the reporter feature algorithm with default settings [16,17]. To assign metabolite-metabolite interactions, an A. nidulans metabolic network reconstruction was used [23]. Supporting Information Table S1 File containing the measured and calculated SFL (%) of 16 fragments Found at: doi:10.1371/journal.pone.0003847.s001 (0.04 MB PDF) Table S2 File containing the modified version of the metabolic model from Pedersen et al [22] with details on the precursor calculations. Found at: doi:10.1371/journal.pone.0003847.s002 (0.19 MB PDF) Table S3 File containing the modified version of the metabolic model of David et al [23] that was used for simulation of the metabolic fluxes as well as calculations of all the metabolic fluxes. Found at: doi:10.1371/journal.pone.0003847.s003 (0.28 MB PDF) References Systems Analysis in A nidulans Table S4 Results of reporter feature algorithm for the examination of phosphoketolase over-expression on glucose. Found at: doi:10.1371/journal.pone.0003847.s004 (0.35 MB PDF) Table S5 Results of reporter feature algorithm for the examination of phosphoketolase over-expression on xylose. Found at: doi:10.1371/journal.pone.0003847.s005 (0.36 MB PDF) Table S6 Results of reporter feature algorithm for the examination of phosphoketolase over-expression on glycerol. Found at: doi:10.1371/journal.pone.0003847.s006 (0.35 MB PDF) Table S7 Results of reporter feature algorithm for the examination of phosphoketolase over-expression on ethanol Found at: doi:10.1371/journal.pone.0003847.s007 (0.35 MB PDF) Table S8 General functional (KOG/Interpro/PFAM) assign- ment and SwissProt gene names for 2805 genes from A. nidulans. Found at: doi:10.1371/journal.pone.0003847.s008 (0.38 MB PDF) Figure S1 Metabolic map of differentially regulated genes in a comparison of wild type and a phosphoketolase over-expressing (PHK) strain on glucose medium. Found at: doi:10.1371/journal.pone.0003847.s009 (0.38 MB PDF) Figure S2 Metabolic map of differentially regulated genes in a comparison of wild type and a phosphoketolase over-expressing (PHK) strain on xylose medium. Found at: doi:10.1371/journal.pone.0003847.s010 (0.38 MB PDF) Figure S3 Metabolic map of differentially regulated genes in a comparison of wild type and a phosphoketolase over-expressing (PHK) strain on glycerol medium. Found at: doi:10.1371/journal.pone.0003847.s011 (0.38 MB PDF) Figure S4 Metabolic map of differentially regulated genes in a comparison of wild type and a phosphoketolase over-expressing (PHK) strain on ethanol medium. Found at: doi:10.1371/journal.pone.0003847.s012 (0.38 MB PDF) Acknowledgments Lene Christiansen for crucial technical assistance with DNA microarray preparations. Author Contributions Conceived and designed the experiments: GP JN. Performed the experiments: GP TR GH. Analyzed the data: GP MRA TG JN. Contributed reagents/materials/analysis tools: GP LO. Wrote the paper: GP MRA TG. 1. Rohr LM, Lee SY, Cho J, Kim TY, Lee JW, et al. (2005) Global physiological understanding and metabolic engineering of microorganisms based on omics studies. Appl Microbiol Biotechnol 68: 567–579. 2. Ratledge C, Holdsworth JE (1985) Properties of a pentulose-5-phosphate phosphoketolase from yeasts grown on xylose. Appl Microbiol Biotechnol 22: 217–221. 3. Panagiotou G, Kouskoumvekaki I, Jonsdottir SO, Olsson L (2007) Monitoring novel metabolic pathways using metabolomics and machine learning: induction of the phosphoketolase pathway in Aspergillus nidulans cultivations. Metabolomics 3: 503–516. 4. Thykaer J, Nielsen J (2007) Evidence, through C13-labelling analysis, of phosphoketolase activity in fungi. Process Biochemistry 42: 1050–1055. PLoS ONE | www.plosone.org 7 December 2008 | Volume 3 | Issue 12 | e3847