Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (¹H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map.

Colorectal cancer is a major public health issue worldwide. Interleukin-17 (IL-17) and Th17 (T-helper cell type 17)-related molecules are involved in tumor development and in resistance to bevacizumab, an anti-vascular endothelial growth factor monoclonal antibody used in association with chemotherapy in metastatic colorectal cancer. Some studies have previously shown that IL-17A and IL-17F polymorphisms, respectively rs2275913 and rs763780, are associated with gastric or colorectal cancer risk. Here we aimed at studying the influence of IL-17A-related individual factors on overall survival and progression-free survival in patients with metastatic colorectal cancer treated with a bevacizumab-based chemotherapy. Pre-treatment serum biomarkers were retrospectively evaluated in 122 metastatic colorectal cancer patients treated by bevacizumab in combination with chemotherapy at 2-weeks intervals in a prospective cohort study (NCT00489697). The polymorphisms of IL-17A and IL-17F were analyzed by polymerase chain reaction - restriction fragment length polymorphism. Serum concentrations of Th17-related cytokines were measured by MultiPlex. The impact of individual parameters on overall survival and progression-free survival was assessed using multivariate Cox models. High baseline IL-17A serum concentrations were significantly associated with shorter progression-free survival [p = 0.043]. Other baseline serum Th17-related cytokines and polymorphisms of IL-17 were not associated with overall survival or progression-free survival. In this ancillary study, baseline serum IL-17A concentration is the only Th17/IL-17 related factor that was significantly associated with the response of patients with metastatic colorectal cancer to bevacizumab. But this main significant result is highly dependent on one case which, if left out, weakens the data. Other clinical studies are required to confirm this association. NCT00489697 . June 20, 2007.

Metabolomics has been increasingly used in animal and food sciences. Animal health is one of the most important factor that can also alter animal integrity and welfare. Some studies have already investigated the link between health and metabolic profile of dairy animals. These studies in metabolomics often consider a single type of sample using a single analytical platform (nuclear magnetic resonance or mass spectrometry). Only few studies with multi-platform approaches are also used with a single or a multi type of sample, but they mainly consider dairy cows’ metabolome although dairy goats present similar diseases, that it could be interesting to detect early to preserve animal health and milk production. This study aims to create a metabolic atlas of goat plasma, milk and feces, based on healthy animals. Our study describes a standard operating procedure for three goat matrices: blood plasma, milk, and feces using multiple platforms (NMR (¹H), UHPLC (RP)-MS and UHPLC (HILIC)-MS) that follows a unique sample preparation procedure for each sample type to be analyzed on multi-platforms basis. Our method was evaluated for its robustness and allowed a better characterization of goat metabolic profile in healthy conditions.

The transcription factor Krüppel-like factor 10 (Klf10), also known as Tieg1 for TGFβ (Inducible Early Gene-1) is known to control numerous genes in many cell types that are involved in various key biological processes (differentiation, proliferation, apoptosis, inflammation), including cell metabolism and human disease. In skeletal muscle, particularly in the soleus, deletion of the Klf10 gene (Klf10 KO) resulted in ultrastructure fiber disorganization and mitochondrial metabolism deficiencies, characterized by muscular hypertrophy. To determine the metabolic profile related to loss of Klf10 expression, we analyzed blood and soleus tissue using UHPLC-Mass Spectrometry. Metabolomics analyses on both serum and soleus revealed profound differences between wild-type (WT) and KO animals. Klf10 deficient mice exhibited alterations in metabolites associated with energetic metabolism. Additionally, chemical classes of aromatic and amino-acid compounds were disrupted, together with Krebs cycle intermediates, lipids and phospholipids. From variable importance in projection (VIP) analyses, the Warburg effect, citric acid cycle, gluconeogenesis and transfer of acetyl groups into mitochondria appeared to be possible pathways involved in the metabolic alterations observed in Klf10 KO mice. These studies have revealed essential roles for Klf10 in regulating multiple metabolic pathways whose alterations may underlie the observed skeletal muscle defects as well as other diseases.