Weronika Ząbek
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Interests
Weronika Ząbek has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Eliza Matuszewska
Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-806 Poznan, Poland
1 shared publication - Elżbieta Hołderna-Kędzia
Institute of Natural Fibers and Medicinal Plants National Research Institute, Wojska Polskiego 71B, 60-630 Poznan, Poland
1 shared publication - Grzegorz Rosiński
Department of Animal Physiology and Developmental Biology, Faculty of Biology, Adam Mickiewicz University in Poznań, Poznań, Poland
1 shared publication - Jan Matysiak
Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Poznan University of Medical Sciences, 61-614 Poznan, Poland
1 shared publication - Jarosław Zawadziński
Department of Physiotherapy, Poznan University of Medical Sciences, 61-701 Poznan, Poland
1 shared publication - Joanna Matysiak
Faculty of Health Sciences, University of Kalisz, Kalisz, Poland
1 shared publication
Latest Publications
- Open Access
Mining the Royal Jelly Proteins: Combinatorial Hexapeptide Ligand Library Significantly Improves the MS-Based Proteomic Identification in Complex Biological Samples
Royal jelly (RJ) is a complex, creamy secretion produced by the glands of worker bees. Due to its health-promoting properties, it is used by humans as a dietary supplement. However, RJ compounds are not fully characterized yet. Hence, in this research, we aimed to broaden the knowledge of the proteomic composition of fresh RJ. Water extracts of the samples were pre-treated using combinatorial hexapeptide ligand libraries (ProteoMinerTM kit), trypsin-digested, and analyzed by a nanoLC-MALDI-TOF/TOF MS system. To check the ProteoMinerTM performance in the MS-based protein identification, we also examined RJ extracts that were not prepared with the ProteoMinerTM kit. We identified a total of 86 proteins taxonomically classified to Apis spp. (bees). Among them, 74 proteins were detected in RJ extracts pre-treated with ProteoMinerTM kit, and only 50 proteins were found in extracts non-enriched with this technique. Ten of the identified features were hypothetical proteins whose existence has been predicted, but any experimental evidence proves their in vivo expression. Additionally, we detected four uncharacterized proteins of unknown functions. The results of this research indicate that the ProteoMinerTM strategy improves proteomic identification in complex biological samples. Broadening the knowledge of RJ composition may contribute to the development of standards and regulations, enhancing the quality of RJ, and consequently, the safety of its supplementation.
Open AccessMining the Royal Jelly Proteins: Combinatorial Hexapeptide Ligand Library Significantly Improves the MS-Based Proteomic Identification in Complex Biological Samples
Royal jelly (RJ) is a complex, creamy secretion produced by the glands of worker bees. Due to its health-promoting properties, it is used by humans as a dietary supplement. However, RJ compounds are not fully characterized yet. Hence, in this research, we aimed to broaden the knowledge of the proteomic composition of fresh RJ. Water extracts of the samples were pre-treated using combinatorial hexapeptide ligand libraries (ProteoMinerTM kit), trypsin-digested, and analyzed by a nanoLC-MALDI-TOF/TOF MS system. To check the ProteoMinerTM performance in the MS-based protein identification, we also examined RJ extracts that were not prepared with the ProteoMinerTM kit. We identified a total of 86 proteins taxonomically classified to Apis spp. (bees). Among them, 74 proteins were detected in RJ extracts pre-treated with ProteoMinerTM kit, and only 50 proteins were found in extracts non-enriched with this technique. Ten of the identified features were hypothetical proteins whose existence has been predicted, but any experimental evidence proves their in vivo expression. Additionally, we detected four uncharacterized proteins of unknown functions. The results of this research indicate that the ProteoMinerTM strategy improves proteomic identification in complex biological samples. Broadening the knowledge of RJ composition may contribute to the development of standards and regulations, enhancing the quality of RJ, and consequently, the safety of its supplementation.