The ?Dark Side? of Food Stuff Proteomics: The CPLL-Marshals Investigate

The present review deals with analysis of the proteome of animal and plant-derived food stuff, as well as of non-alcoholic and alcoholic beverages. The survey is limited to those system investigated with the help of combinatorial peptide ligand libraries, a most powerful technique allowing access to low- to very-low-abundance proteins, i.e. to those proteins that might characterize univocally a given biological system and, in the case of commercial food preparations, attest their genuineness or adulteration. Among animal foods the analysis of cow’s and donkey’s milk is reported, together with the proteomic composition of egg white and yolk, as well as of honey, considered as a hybrid between floral and animal origin. In terms of plant and fruits, a survey is offered of spinach, artichoke, banana, avocado, mango and lemon proteomics, considered as recalcitrant tissues in that small amounts of proteins are dispersed into a large body of plant polymers and metabolites. As examples of non-alcoholic beverages, ginger ale, coconut milk, a kola drink, almond milk and orgeat syrup are analyzed. Finally, the trace proteome of white and red wines, beer and aperitifs is reported, with the aim of tracing the industrial manipulations and herbal usage prior to their commercialization. The review ends with a comparison between mammalian and plant proteomics highlighting the difficulties besieging analysis of any vegetable proteome

In taberna quando sumus: od biblijskog opijanja do proteomike vina

Analysis of white and red wine trace proteomes via capture with combinatorial peptide ligand libraries (CPLL) is reported here. Most of the alcoholic beverages tested (all of Italian origin) were found to contain only traces of casein (on average from 20 to 60 µg/L, with a detectability of as low as 1 µg/L) and not any grape protein any longer, as they had been fined with bovine casein (surprisingly also red wines for which the typical fining agent is egg albumin). However, analysis of untreated white wine (Recioto, from Garganega grapes in the Veneto region) via CPLL capture indeed permitted to detect close to 100 unique gene products from the grapes, suggesting the possibility of proteotyping grand crus, i.e. those aged, high quality wines that should not be treated with fining agents. Thus the CPLL technique could become a formidable tool for traceability of beverages in particular and of foodstuff in general. For trace protein analysis, a new, most powerful CPLL methodology emerges: capture at pH=2.2 in 0.1 % trifluoroacetic acid (TFA) under the conditions mimicking reversed-phase mechanisms of adsorption.U radu su prikazani rezultati analize proteina u tragovima u crnim i bijelim vinima i uspoređeni pomoću datoteka rekombiniranih peptidnih liganada (CPLL). Ispitana su vina talijanskog podrijetla. U većini je uzoraka pronađen kazein u tragovima (prosječno od 20 do 60 µg/L, s pragom detekcije već od 1 µg/L), ali ni jedan protein iz grožđa, jer su sva vina bila pročišćena goveđim kazeinom, uključujući i crna vina koja se obično pročišćuju albuminom iz jaja. Međutim, analizom netretiranog bijelog vina (Recioto iz grožđa sorte Garganega, regija Veneto) pomoću datoteka rekombiniranih peptidnih liganada opaženo je gotovo 100 jedinstvenih produkata gena iz grožđa, što omogućava karakterizaciju proteoma vina grand cru, visokokvalitetnih odležanih vina koja inače ne treba pročišćavati. Stoga bi datoteke rekombiniranih peptidnih liganada mogle poslužiti kao odličan alat za otkrivanje proteina u tragovima u hrani i piću. Novom metodom CPLL pri pH=2,2 u prisutnosti 0,1 % trifluorooctene kiseline omogućena je analiza proteina u uvjetima koji oponašaju mehanizme njihove adsorpcije pri kromatografiji obrnutih faza

Low-Abundance Protein Enrichment for Medical Applications: The Involvement of Combinatorial Peptide Library Technique

The discovery of low- and very low-abundance proteins in medical applications is considered a key success factor in various important domains. To reach this category of proteins, it is essential to adopt procedures consisting of the selective enrichment of species that are present at extremely low concentrations. In the past few years pathways towards this objective have been proposed. In this review, a general landscape of the enrichment technology situation is made first with the presentation and the use of combinatorial peptide libraries. Then, a description of this peculiar technology for the identification of early-stage biomarkers for well-known pathologies with concrete examples is given. In another field of medical applications, the determination of host cell protein traces potentially present in recombinant therapeutic proteins, such as antibodies, is discussed along with their potentially deleterious effects on the health of patients on the one hand, and on the stability of these biodrugs on the other hand. Various additional applications of medical interest are disclosed for biological fluids investigations where the target proteins are present at very low concentrations (e.g., protein allergens)

In taberna quando sumus: A Drunkard’s Cakewalk Through Wine Proteomics

Analysis of white and red wine trace proteomes via capture with combinatorial peptide ligand libraries (CPLL) is reported here. Most of the alcoholic beverages tested (all of Italian origin) were found to contain only traces of casein (on average from 20 to 60 µg/L, with a detectability of as low as 1 µg/L) and not any grape protein any longer, as they had been fined with bovine casein (surprisingly also red wines for which the typical fining agent is egg albumin). However, analysis of untreated white wine (Recioto, from Garganega grapes in the Veneto region) via CPLL capture indeed permitted to detect close to 100 unique gene products from the grapes, suggesting the possibility of proteotyping grand crus, i.e. those aged, high quality wines that should not be treated with fining agents. Thus the CPLL technique could become a formidable tool for traceability of beverages in particular and of foodstuff in general. For trace protein analysis, a new, most powerful CPLL methodology emerges: capture at pH=2.2 in 0.1 % trifluoroacetic acid (TFA) under the conditions mimicking reversed-phase mechanisms of adsorption

Purification par voie chromatographique des anticorps monoclonaux produits par des hybridomes cultives dans un milieu pauvre en proteines

SIGLECNRS AR 12919 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

In-depth Exploration of Cerebrospinal Fluid by Combining Peptide Ligand Library Treatment and Label-free Protein Quantification*

Cerebrospinal fluid (CSF) is the biological fluid in closest contact with the brain and thus contains proteins of neural cell origin. Hence, CSF is a biochemical window into the brain and is particularly attractive for the search for biomarkers of neurological diseases. However, as in the case of other biological fluids, one of the main analytical challenges in proteomic characterization of the CSF is the very wide concentration range of proteins, largely exceeding the dynamic range of current analytical approaches. Here, we used the combinatorial peptide ligand library technology (ProteoMiner) to reduce the dynamic range of protein concentration in CSF and unmask previously undetected proteins by nano-LC-MS/MS analysis on an LTQ-Orbitrap mass spectrometer. This method was first applied on a large pool of CSF from different sources with the aim to better characterize the protein content of this fluid, especially for the low abundance components. We were able to identify 1212 proteins in CSF, and among these, 745 were only detected after peptide library treatment. However, additional difficulties for clinical studies of CSF are the low protein concentration of this fluid and the low volumes typically obtained after lumbar puncture, precluding the conventional use of ProteoMiner with large volume columns for treatment of patient samples. The method has thus been optimized to be compatible with low volume samples. We could show that the treatment is still efficient with this miniaturized protocol and that the dynamic range of protein concentration is actually reduced even with small amounts of beads, leading to an increase of more than 100% of the number of identified proteins in one LC-MS/MS run. Moreover, using a dedicated bioinformatics analytical work flow, we found that the method is reproducible and applicable for label-free quantification of series of samples processed in parallel