This proposal aims to supply innovative, fast and accurate analytical methods, to avoid the delay in diagnosis in cases of Crohn¿s disease, ulcerative colitis, non-alcoholic steatohepatitis, and cryptogenic cirrhosis. In fact, the co-morbidity of the non-alcoholic fatty liver disease (NAFLD) and the inflammatory bowel disease (IBD) are important objectives to be faced and solved, since these diseases are increasingly prevalent disorders with a huge impact on the future health of citizens. At present, there is a need to overcome the methods usually adopted for the diagnosis of NAFLD and IBD, because in case of NAFLD the invasive procedure liver biopsy is applied with several unavoidable risks and complications, and also the analysis of IBD requires invasive and expensive procedures, such as ileocolonoscopy combined with cross-sectional imaging by computed tomography or magnetic resonance imaging.
In this overall scenario, the project will provide innovative and high performant analytical methods for an effective and reliable identification of biomarkers in gut microbiota, exploiting cross-cutting technologies in liquid chromatographic coupled to high resolution mass spectrometry. In detail, analytical methods based on ultra-high performance liquid chromatography (UHPLC) and nanoHPLC coupled to high resolution mass spectrometry (HRMS) and tandem mass spectrometry (MS/MS) will be employed to extend the coverage of metabolites and lipids belonging to the gut microbiota, in order to discover new biomarkers related to IBD and NAFLD.
To deliver accurate and highly sensitive analytical methods in so complex a matrix, the analytical methods developed will exploit the latest technologies available for analyte separation by liquid chromatography and analysis by MS as well as will improve untargeted metabolomics and lipidomics and targeted metabolomics combined with bioinformatics.
Due to the recent findings about a relationship between metabolite/lipid profile and IBD/NAFLD, accurate analytical methods should be developed in order to extract, analyse and identify the most relevant classes of metabolites and lipids involved in the metabolic pathways of the above mentioned diseases.
Firstly, specific sample preparation issues will be dealt with to optimize the untargeted metabolomic and lipidomic investigation. A method suitable for metabolomics study of human faecal samples will be optimized, as currently an untargeted metabolomics method by HPLC-HRMS was developed only for bovine stool [1]. Additionally, previous metabolomics works on stool involved a simple pretreatment by dilution of faecal water with an organic solvent (mainly methanol), centrifugation for the removal of proteins and filtration prior to analysis, to avoid column clogging [2]. Recent findings about the possible formation of artefacts during methanol dilution and storage will be considered [3]. Additionally, several studies have shown that sample preparation based on solid phase extraction can increase the coverage of the metabolome compared with conventional protein precipitation [4]. This issue will be considered to improve the current metabolomics coverage in gut microbiota and serum samples for the target pathological conditions. As far as the untargeted lipid analysis is concerned, recently, a method suitable for global profiling of lipid species in stool was developed [5]. Such method will be improved by dedicated bioinformatic software application.
Secondly, a comprehensive chromatographic and mass spectrometric method will be developed for an efficient separation and identification of the prepared metabolomics and lipidomics samples. Such methods will exploit recent advanced UHPLC platforms coupled to Orbitrap HRMS. Along with conventional C18 UHPLC, alternative and complementary stationary phases will be tested to increase analyte separation and identification, such as hydrophilic interaction chromatography stationary phases [6]. Alternative approaches will also be considered for separation of metabolites and lipids. In the metabolomics field, although still limited, several papers have already used nanoHPLC-nESI-MS platforms. For targeted metabolomics, these studies have highlighted that these systems may be up to 2000 fold more sensitive than conventional LC-ESI-MS and with LODs and LOQs up to 300 fold lower [4]. Thus, chromatographic methods based on nanoHPLC will be optimized to exploit the increased sensitivity of nanoHPLC systems and increase metabolite and lipid coverage.
Finally, issues related to data analysis and the identification of metabolites and lipids will be dealt with. A suspected screening approach will be followed for the identification of the metabolites and lipids related to IBD/NAFLD diseases using the available literature data to create a home-made database. The screening of detected compounds will be performed by means of dedicated software for the data pre-processing and identification (MZmine, online databases such as Chemspider, Metlin, Human Metabolome Database, LipidMaps etc.). Also, in silico fragmentation prediction tools will be used, such as Met Frag or Mass Frontier. Most importantly, metabolite and lipid coverage will be extended by the use of recent software able to identify unknows for the untargeted identification of metabolites (Metlin) [7] and lipids (Lipostar) [8]. Finally, the tentative identified compounds will be confirmed with an authentic reference standard.
The new analytical tools developed will exploit the latest technologies available for analyte separation by liquid chromatography coupled to MS analysis: moreover, the developed analytical methods will improve targeted and untargeted metabolomics and lipidomics investigations in gut microbiota in NAFLD and IBD, to address the challenge of novel biomarkers detection in gut microbiota which is a hot topic as recently reported (https://www.nature.com/subjects/microbiota).
1. N. Cesbron et al. (2017) Metabolomics 13 99
2. O. Deda et al. (2015) J Pharm Biomed Anal 113 137¿150
3. C. Sauerschnig et al. (2017) Metabolites 2018, 8(1), 1
4. A.J. Chetwynd et al. (2018) Talanta 182 380¿390
5. L. Van Meulebroek et al. (2017) Anal Chem 89(22) 12502-12510
6. D.Q. Tang et al. (2016) Mass Spectrom Rev 35(5) 574-600
7. C. Guijas et al. (2018) Anal Chem 90(5) 3156-3164
8. L. Goracci et al. (2017) Anal Chem 89(11) 6257¿6264