Interpreting Metabolomic Profiles using Unbiased Pathway Models

Human disease is heterogeneous, with similar disease phenotypes resulting from distinct combinations of genetic and environmental factors. Small-molecule profiling can address disease heterogeneity by evaluating the underlying biologic state of individuals through non-invasive interrogation of plasma metabolite levels. We analyzed metabolite profiles from an oral glucose tolerance test (OGTT) in 50 individuals, 25 with normal (NGT) and 25 with impaired glucose tolerance (IGT). Our focus was to elucidate underlying biologic processes. Although we initially found little overlap between changed metabolites and preconceived definitions of metabolic pathways, the use of unbiased network approaches identified significant concerted changes. Specifically, we derived a metabolic network with edges drawn between reactant and product nodes in individual reactions and between all substrates of individual enzymes and transporters. We searched for “active modules”—regions of the metabolic network enriched for changes in metabolite levels. Active modules identified relationships among changed metabolites and highlighted the importance of specific solute carriers in metabolite profiles. Furthermore, hierarchical clustering and principal component analysis demonstrated that changed metabolites in OGTT naturally grouped according to the activities of the System A and L amino acid transporters, the osmolyte carrier SLC6A12, and the mitochondrial aspartate-glutamate transporter SLC25A13. Comparison between NGT and IGT groups supported blunted glucose- and/or insulin-stimulated activities in the IGT group. Using unbiased pathway models, we offer evidence supporting the important role of solute carriers in the physiologic response to glucose challenge and conclude that carrier activities are reflected in individual metabolite profiles of perturbation experiments. Given the involvement of transporters in human disease, metabolite profiling may contribute to improved disease classification via the interrogation of specific transporter activities

Threats and Conservation Strategies for Overlooked Organisms: The Case of Epiphytic Lichens

none5noIn this chapter, the main ecological factors that characterize the epiphyte environ- 7 ment and which determine the composition of epiphyte communities have been 8 described. In particular, emphasis has been made to focus on epiphytic lichens 9 which, due to their ecophysiological characteristics, represent a set of highly 10 specialized organisms that live in a delicate balance in this habitat. The main 11 threats that threaten their survival have been analysed along with the conservation 12 actions that have been undertaken to ensure the maintenance of the populations of 13 the most endangered species have been reviewed. Furthermore, some good 14 practices are suggested that can guarantee greater success of future protection 15 actions.nonePaolo Giordani, Renato Benesperi, Elisabetta Bianchi, Paola Malaspina, Juri NascimbenePaolo Giordani, Renato Benesperi, Elisabetta Bianchi, Paola Malaspina, Juri Nascimben

cDNA-Microarray Analysis as a New Tool to Predict Lymph Node Metastasis in Gastric Cancer

Background The aim of the present study was to investigate whether microarray gene expression analysis can be used to predict lymph node status in gastric cancer. Methods Twenty-nine patients undergoing gastrectomy for cancer were enrolled and subdivided according to the pathologic nodal involvement of their disease (N+ vs N0). Molecular profiling was performed by cDNA microarray on tumor tissue and healthy mucosa. Data were processed to identify differently expressed genes. Selected genes were categorized with gene ontology. Results Compared to healthy gastric mucosa, 52 genes were differently expressed in N+ patients, and 50 genes in N0 patients. Forty-five genes were similarly regulated in N+ and N0 patients, whereas 12 genes were differently expressed between N+ and N0 patients. Seven genes were exclusively expressed in N+ patients: Egr-1 was upregulated; Claudin-18, AKR1C2, Cathepsin E, CA II, TFF 1, and progastricsin were downregulated. Five genes were exclusively expressed in N0 patients: Complement C5 receptor 1, PLA2/VII, and MMP- 9 were upregulated; MAO-A and ID-4 were downregulated. Conclusions Microarray analysis could be a valuable tool to identify genes associated with lymph node metastasis in gastric cancer. This technique could improve the selection of patients with locally advanced disease who are candidates for extended lymph node dissection, multimodal treatment options, or alternative therapeutic strategies