Proteomic fingerprinting of mistletoe (Viscum album L.) via combinatorial peptide ligand libraries and mass spectrometry analysis

Publication date: Available online 29 May 2017
Source:Journal of Proteomics
Author(s): María Vergara-Barberán, María Jesús Lerma-García, Maria Nicoletti, Ernesto Francisco Simó-Alfonso, José Manuel Herrero-Martínez, Elisa Fasoli, Pier Giorgio Righetti
Combinatorial peptide ligand libraries (CPLLs), coupled to mass spectrometry (MS) analysis, have been used to investigate in depth the proteome of Viscum album L. (VA), commonly named European mistletoe, in order to provide a first proteomic fingerprinting. For this purpose, the proteins were captured via CPLLs at two different pH values (acidic and neutral). A total of 648 non-redundant proteins were identified by using two different databases. The two pH values, chosen for bead incubations, have contributed to increment the capture ability: 56% and 31% of CPLLs species were respectively recognized at pH7.2 and at pH2.2. Finally the biological function of identified proteins was evaluated in order to understand their role on human health and the potential benefits of mistletoe extracts in medicine.SignificanceViscum album L. (VA) extracts are recently used as supporting medicine for cancer therapy, improving patients' survival and increasing their quality of life in medicine. These anticancer effects are investigated and they are probably due to mistletoe's capability to favor tumor cell's death and to modulate the immune system. Although the increasing interest in VA medical benefits, the role of its components in human health remains unclear. In order to exploit this aspect, it is important to comprehensively study proteins present in Viscum album L. (VA) extracts. Nevertheless, since plant proteomics analysis is in most cases handicapped by the presence of high-abundance proteins masking the detection of the low-abundance ones, it is important to overcome this challenge. In this sense, combinatorial peptide ligand libraries (CPLLs) have been used to reduce the dynamic protein concentration range to enable the identification of a higher amount of proteins than employing conventional methods. In this work, a total of 648 non-redundant proteins were identified: 56% and 31% of CPLLs species were respectively recognized at pH7.2 and at pH2.2. This deep proteome identification was useful to investigate the biological functions of proteins in order to evaluate their potential role in human health.

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