1. Concept of proteomics. Classic proteomics approaches. Multiomics Landscape: transcriptomics, proteomics, glycomics, metabolomics to final phenotype. - structural vs functional proteomics. Bottom-up vs top-down strategies. - Examples: Proteomic approach for biomarker discovery.
2. Sample preparation (the key to the success of the experiment)
3. Mass spectrometric platforms for the detection of peptides and proteins
3.1. Proteins identification by peptide mapping. Mass spectometers: Ionization / mass separation / ion collection - A century of developments in MS. (from first MS Thomson 1987 to ESI of biomolècules Fenn et al. 2002). Nobel prize 2002: Tanaka MALDI, Fenn ESI. Main parts in MS (ion source, mass analyser, detector) • Inlet: sample plate, target, HPLC, EC, GC, solid probe • Ion source: MALDI, API, ESI, FAB, LSIMS, EI, CI • Mass separation: TOF, Quadrupole, Ion Trap (orbitrap), magnètic sector, FTMS, • Detector: microchannel plate, electron multiplier, hybrid... • Data System. High vacuum System (ionization, mass filter, detector) / turbo pumps. - MALDI-TOF MS: matrix selection (CHCA, SA, Ferrulic acid, DHB, HPA, etc...) - pros and cons. Reflector mode. Delayed extraction. Calibration. MS spectra interpretation.
4. MALDI-TOF MS applications and Proteomics bioinformatics basics
4.1. Important concepts: mass resolution, accuracy, resolution, peak width at half height... - Nominal mass, monoisotopic mass, most abundant mass, average mass - Useful interpretation tools: isotopic resolution, fractional mass - Mass spectra interpretation: MALDI TOF (mainly monocharged) vs ESI (multi-charged ions) explain deconvolution - Real case bottom-up proteomics: proteins, 2DE, excise protein bands, destaining, in gel reduction, alkylation, protease digestion, identification MALDI peptide mass fingerprint. - Spectra processing, calibration, - Purging MS data (trypsin auto-proteolysis, keratin, artefactual peaks) peakErazor.exe software - Peptide mass fingerprint: MASCOT (real examples) - Uniprot, SwissProt databases for theoretical mass (in silico digestions)
5. LC-MS-MS and Quantitative proteomics
5.1. LC-ESI-QQQ - Chromatogram OD vs ionogram TIC - Modes of data acquisiton: SCAN and SIM. Product Ion Scan, Precursor Scan, Neutral Loss Scan, Multiple Reaction Mode. Exemples. - QQQ pros and cons. LC-ESI-QQQ, LC-ESI-Q-TOF (Q-star polsar) , MALDI-TOF-TOF, QIT - Mass spectra interpretation: aa masses, isobaric aa, peptide fragmentation, fragment ion nomenclature (a,b,c Nter vs x,y,z Cter). - Tandem MS: de novo sequencing (spectra interpretation) - Quantitation experimental paradigm (labelling): SILAC- metabolic labelling, ICAT - isotope coded affinity tag, iTRAQ - isobaric tags AQUA – absolute quantification (calibration-response curve)
La Qualificació final serà “Apte” o “no-Apte”.
- Per a obtenir una qualificació “Apte”:
• Caldrà assistir a un 80% o més de les classes (es registrarà l’assistència)
• Caldrà realitzar uns exercicis que consistiran en fer la digestió "in silico" d'una proteïna per obtenir el pèptids teòrics i també identificar una proteïna a partir de perfils experimentals de peptide mapping. Per considerar superat la part d'exercicis caldrà obtenir una qualificació mínima de 5.0.
The final Qualification will be “Pass” or “non-Pass”.
- To obtain an “Pass” qualification:
• You will be required to attend at least 80% of the lectures (attendance will be registered)
• You will need to do some exercises that will consist of the "in silico" digestion of a protein to obtain the theoretical peptides and also to identify a protein from experimental peptide mapping profiles. To pass the exercise part, you will need to have a grade of 5.0 or higher.
Criteris específics de la nota «No Presentat»:
Una falta d'assistència superior al 20% de les sessions presencials i/o no presentar els exercicis es considerarà No Presentat.
It is mandatory the attendance at a minimum of 80% of the lectures to pass the course. A NOT PRESENTED student implies that he/she has not done the written work or has attended less than the 80% of the lectures.
In case of single evaluation, A NOT PRESENTED STUDENT implies that he/she has not done the single final exam and/or has not attended a minimum of 80% of the lectures.
Avaluació única:
• Caldrà assistir a un 80% o més de les classes (es registrarà l’assistència)
• Caldrà realitzar un examen final amb exercicis treballats a classe i obtenir una qualificació mínima de 5.0.
Students should attend a minimum of 80% of the lectures to get the option for this single evaluation.
Students that can opt for a single evaluation will perform a final exam of the whole content of the course. This exam will account for the 100% of the final grade obtained by the student and if failed may be repeated only once.
Requisits mínims per aprovar:
- Per a obtenir una qualificació “Apte”:
• Caldrà assistir a un 80% o més de les classes (es registrarà l’assistència)
• Caldrà realitzar uns exercicis que consistiran en fer la digestió "in silico" d'una proteïna per obtenir el pèptids teòrics i també identificar una proteïna a partir de perfils experimentals de peptide mapping. Per considerar superat la part d'exercicis caldrà obtenir una qualificació mínima de 5.0.
- To obtain an “Pass” qualification:
• You will be required to attend at least 80% of the lectures (attendance will be registered)
• You will need to do some exercises that will consist of the "in silico" digestion of a protein to obtain the theoretical peptides and also to identify a protein from experimental peptide mapping profiles. To pass the exercise part, you will need to have a grade of 5.0 or higher.