Gianni Panagiotou

A trispecies Aspergillus microarray: Comparative transcriptomics of three Aspergillus species

The full-genome sequencing of the filamentous fungi Aspergillus nidulans, Aspergillus niger, and Aspergillus oryzae has opened possibilities for studying the cellular physiology of these fungi on a systemic level. As a tool to explore this, we are making available an Affymetrix GeneChip developed for transcriptome analysis of any of the three above-mentioned aspergilli. Transcriptome analysis of triplicate batch cultivations of all three aspergilli on glucose and xylose media was used to validate the performance of the microarray. Gene comparisons of all three species and cross-analysis with the expression data identified 23 genes to be a conserved response across Aspergillus sp., including the xylose transcriptional activator XlnR. A promoter analysis of the up-regulated genes in all three species indicates the conserved XlnR-binding site to be 5′-GGNTAAA-3′. The composition of the conserved gene-set suggests that xylose acts as a molecule, indicating the presence of complex carbohydrates such as hemicellulose, and triggers an array of degrading enzymes. With this case example, we present a validated tool for transcriptome analysis of three Aspergillus species and a methodology for conducting cross-species evolutionary studies within a genus using comparative transcriptomics.

Production of cellulolytic and xylanolytic enzymes by Fusarium oxysporum grown on corn stover in solid state fermentation

Corn stover is an abundant, potential fermentation substrate. Production of cellulolytic and xylanolytic enzymes by the mesophilic fungus Fusarium oxysporum under solid state culture (SSC) on corn ...

Fueling Industrial Biotechnology Growth with Bioethanol

Industrial biotechnology is the conversion of biomass via biocatalysis, microbial fermentation, or cell culture to produce chemicals, materials, and/or energy. Industrial biotechnology processes aim to be cost-competitive, environmentally favorable, and self-sustaining compared to their petrochemical equivalents. Common to all processes for the production of energy, commodity, added value, or fine chemicals is that raw materials comprise the most significant cost fraction, particularly as operating efficiencies increase through practice and improving technologies. Today, crude petroleum represents the dominant raw material for the energy and chemical sectors worldwide. Within the last 5 years petroleum prices, stability, and supply have increased, decreased, and been threatened, respectively, driving a renewed interest across academic, government, and corporate centers to utilize biomass as an alternative raw material. Specifically, bio-based ethanol as an alternative biofuel has emerged as the single largest biotechnology commodity, with close to 46 billion L produced worldwide in 2005. Bioethanol is a leading example of how systems biology tools have significantly enhanced metabolic engineering, inverse metabolic engineering, and protein and enzyme engineering strategies. This enhancement stems from method development for measurement, analysis, and data integration of functional genomics, including the transcriptome, proteome, metabolome, and fluxome. This review will show that future industrial biotechnology process development will benefit tremendously from the precedent set by bioethanol - that enabling technologies (e.g., systems biology tools) coupled with favorable economic and socio-political driving forces do yield profitable, sustainable, and environmentally responsible processes. Biofuel will continue to be the keystone of any industrial biotechnology-based economy whereby biorefineries leverage common raw materials and unit operations to integrate diverse processes to produce demand-driven product portfolios.

Probiotics modulated gut microbiota suppresses hepatocellular carcinoma growth in mice

Significance Hepatocellular carcinoma is the second most deadly cancer type globally, requiring the development of alternative or complementary therapeutic and prophylactic methods. Here, when feeding a mouse model with a novel probiotic mixture 1 wk before the tumor inoculation, we observed a reduction of the tumor weight and size by 40% compared with the control. Our results revealed that the probiotics’ beneficial effect is closely related with the abundance of certain beneficial bacteria that produce antiinflammatory metabolites, which subsequently regulate the proinflammatory immune cell population via the crosstalk between gut and tumor. We believe that our study highlights the extraordinary potential of probiotics in extraintestine cancers and can be adapted to the study of other cancers. The beneficial roles of probiotics in lowering the gastrointestinal inflammation and preventing colorectal cancer have been frequently demonstrated, but their immunomodulatory effects and mechanism in suppressing the growth of extraintestinal tumors remain unexplored. Here, we adopted a mouse model and metagenome sequencing to investigate the efficacy of probiotic feeding in controlling s.c. hepatocellular carcinoma (HCC) and the underlying mechanism suppressing the tumor progression. Our result demonstrated that Prohep, a novel probiotic mixture, slows down the tumor growth significantly and reduces the tumor size and weight by 40% compared with the control. From a mechanistic point of view the down-regulated IL-17 cytokine and its major producer Th17 cells, whose levels decreased drastically, played critical roles in tumor reduction upon probiotics feeding. Cell staining illustrated that the reduced Th17 cells in the tumor of the probiotic-treated group is mainly caused by the reduced frequency of migratory Th17 cells from the intestine and peripheral blood. In addition, shotgun-metagenome sequencing revealed the crosstalk between gut microbial metabolites and the HCC development. Probiotics shifted the gut microbial community toward certain beneficial bacteria, including Prevotella and Oscillibacter, that are known producers of antiinflammatory metabolites, which subsequently reduced the Th17 polarization and promoted the differentiation of antiinflammatory Treg/Tr1 cells in the gut. Overall, our study offers novel insights into the mechanism by which probiotic treatment modulates the microbiota and influences the regulation of the T-cell differentiation in the gut, which in turn alters the level of the proinflammatory cytokines in the extraintestinal tumor microenvironment.

Systems Analysis Unfolds the Relationship between the Phosphoketolase Pathway and Growth in Aspergillus nidulans

Background Aspergillus nidulans is an important model organism for studies on fundamental eukaryotic cell biology and on industrial processes due to its close relation to A. niger and A. oryzae. Here we identified the gene coding for a novel metabolic pathway in A. nidulans, namely the phosphoketolase pathway, and investigated the role of an increased phosphoketolase activity. Methodology/Principal Findings Over-expression of the phosphoketolase gene (phk) improved the specific growth rate on xylose, glycerol and ethanol. Transcriptome analysis showed that a total of 1,222 genes were significantly affected by over-expression of the phk, while more than half of the affected genes were carbon source specific. During growth on glucose medium, the transcriptome analysis showed that the response to phk over-expression is targeted to neutralize the effect of the over-expression by regulating the acetate metabolism and initiate a growth dampening response. Conclusions/Significance Metabolic flux analysis using 13C-labelled glucose, showed that over-expression of phosphoketolase added flexibility to the central metabolism. Our findings further suggests that A. nidulans is not optimized for growth on xylose, glycerol or ethanol as the sole carbon sources.

Linking genotype and phenotype of Saccharomyces cerevisiae strains reveals metabolic engineering targets and leads to triterpene hyper-producers

Background Metabolic engineering is an attractive approach in order to improve the microbial production of drugs. Triterpenes is a chemically diverse class of compounds and many among them are of interest from a human health perspective. A systematic experimental or computational survey of all feasible gene modifications to determine the genotype yielding the optimal triterpene production phenotype is a laborious and time-consuming process. Methodology/Principal Findings Based on the recent genome-wide sequencing of Saccharomyces cerevisiae CEN.PK 113-7D and its phenotypic differences with the S288C strain, we implemented a strategy for the construction of a β-amyrin production platform. The genes Erg8, Erg9 and HFA1 contained non-silent SNPs that were computationally analyzed to evaluate the changes that cause in the respective protein structures. Subsequently, Erg8, Erg9 and HFA1 were correlated with the increased levels of ergosterol and fatty acids in CEN.PK 113-7D and single, double, and triple gene over-expression strains were constructed. Conclusions The six out of seven gene over-expression constructs had a considerable impact on both ergosterol and β-amyrin production. In the case of β-amyrin formation the triple over-expression construct exhibited a nearly 500% increase over the control strain making our metabolic engineering strategy the most successful design of triterpene microbial producers.

Navigating the Human Metabolome for Biomarker Identification and Design of Pharmaceutical Molecules

Metabolomics is a rapidly evolving discipline that involves the systematic study of endogenous small molecules that characterize the metabolic pathways of biological systems. The study of metabolism at a global level has the potential to contribute significantly to biomedical research, clinical medical practice, as well as drug discovery. In this paper, we present the most up-to-date metabolite and metabolic pathway resources, and we summarize the statistical, and machine-learning tools used for the analysis of data from clinical metabolomics. Through specific applications on cancer, diabetes, neurological and other diseases, we demonstrate how these tools can facilitate diagnosis and identification of potential biomarkers for use within disease diagnosis. Additionally, we discuss the increasing importance of the integration of metabolomics data in drug discovery. On a case-study based on the Human Metabolome Database (HMDB) and the Chinese Natural Product Database (CNPD), we demonstrate the close relatedness of the two data sets of compounds, and we further illustrate how structural similarity with human metabolites could assist in the design of novel pharmaceuticals and the elucidation of the molecular mechanisms of medicinal plants.

Uncovering transcriptional regulation of glycerol metabolism in Aspergilli through genome-wide gene expression data analysis

Glycerol is catabolized by a wide range of microorganisms including Aspergillus species. To identify the transcriptional regulation of glycerol metabolism in Aspergillus, we analyzed data from triplicate batch fermentations of three different Aspergilli (Aspergillus nidulans, Aspergillus oryzae and Aspergillus niger) with glucose and glycerol as carbon sources. Protein comparisons and cross-analysis with gene expression data of all three species resulted in the identification of 88 genes having a conserved response across the three Aspergilli. A promoter analysis of the up-regulated genes led to the identification of a conserved binding site for a putative regulator to be 5′-TGCGGGGA-3′, a binding site that is similar to the binding site for Adr1 in yeast and humans. We show that this Adr1 consensus binding sequence was over-represented on promoter regions of several genes in A. nidulans, A. oryzae and A. niger. Our transcriptome analysis indicated that genes involved in ethanol, glycerol, fatty acid, amino acids and formate utilization are putatively regulated by Adr1 in Aspergilli as in Saccharomyces cerevisiae and this transcription factor therefore is likely to be cross-species conserved among Saccharomyces and distant Ascomycetes. Transcriptome data were further used to evaluate the high osmolarity glycerol pathway. All the components of this pathway present in yeast have orthologues in the three Aspergilli studied and its gene expression response suggested that this pathway functions as in S. cerevisiae. Our study clearly demonstrates that cross-species evolutionary comparisons among filamentous fungi, using comparative genomics and transcriptomics, are a powerful tool for uncovering regulatory systems.

Studies of the Production of Fungal Polyketides in Aspergillus nidulans by Using Systems Biology Tools

ABSTRACT Many filamentous fungi produce polyketide molecules with great significance as human pharmaceuticals; these molecules include the cholesterol-lowering compound lovastatin, which was originally isolated from Aspergillus terreus. The chemical diversity and potential uses of these compounds are virtually unlimited, and it is thus of great interest to develop a well-described microbial production platform for polyketides. Using genetic engineering tools available for the model organism Aspergillus nidulans, we constructed two recombinant strains, one expressing the Penicillium griseofulvum 6-methylsalicylic acid (6-MSA) synthase gene and one expressing the 6-MSA synthase gene and overexpressing the native xylulose-5-phosphate phosphoketolase gene (xpkA) for increasing the pool of polyketide precursor levels. The physiology of the recombinant strains and that of a reference wild-type strain were characterized on glucose, xylose, glycerol, and ethanol media in controlled bioreactors. Glucose was found to be the preferred carbon source for 6-MSA production, and 6-MSA concentrations up to 455 mg/liter were obtained for the recombinant strain harboring the 6-MSA gene. Our findings indicate that overexpression of xpkA does not directly improve 6-MSA production on glucose, but it is possible, if the metabolic flux through the lower part of glycolysis is reduced, to obtain quite high yields for conversion of sugar to 6-MSA. Systems biology tools were employed for in-depth analysis of the metabolic processes. Transcriptome analysis of 6-MSA-producing strains grown on glucose and xylose in the presence and absence of xpkA overexpression, combined with flux and physiology data, enabled us to propose an xpkA-msaS interaction model describing the competition between biomass formation and 6-MSA production for the available acetyl coenzyme A.

Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification

BackgroundIn the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produce the 6- methyl salicylic acid polyketide molecule) for application in metabolic engineering.ResultsMore than 450 metabolites were detected and subsequently used in the analysis. Our approach consists of two analytical steps of the metabolic profiling data, an initial non-linear unsupervised analysis with Self-Organizing Maps (SOM) to identify similarities and differences among the metabolic profiles of the studied strains, followed by a second, supervised analysis for training a classifier based on the selected biomarkers. Our analysis identified seven putative biomarkers that were able to cluster the samples according to their genotype. A Support Vector Machine was subsequently employed to construct a predictive model based on the seven biomarkers, capable of distinguishing correctly 14 out of the 16 samples of the different A. nidulans strains.ConclusionOur study demonstrates that it is possible to use metabolite profiling for the classification of filamentous fungi as well as for the identification of metabolic engineering targets and draws the attention towards the development of a common database for storage of metabolomics data.