Prevalence of Listeria species in some foods and their rapid identification

Purpose: To investigate the occurrence of Listeria spp., (particularly L. monocytogenes ), in different foods and to compare diagnostic tools for their identification at species level. Methods: Samples of high protein foods such as raw meats and meat products and including beef products, chicken, fish and camel milk were analysed for the presence of Listeria spp. The isolates were characterised by morphological and cultural analyses, and confirmed isolates were identified by protein profiling and verified using API Listeria system. Protein profiling by SDS-PAGE was also used to identify Listeria spp. Results: Out of 40 meat samples, 14 (35 %) samples were contaminated with Listeria spp., with the highest incidence (50 %) occurring in raw beef products and raw chicken. Protein profiling by SDSPAGE was used to identify Listeria spp. The results were verified with API Listeria system. Approximately 25 % of the identified isolates were Listeria seeligeri , Listeria welshimeri , and Listeria grayi (three positive samples), while 16.66 % of the isolates were Listeria monocytogenes (two positive samples); 16.6 % of the isolates were Listeria innocua (two positive samples), while 8.3 % of the isolates were Listeria ivanovii (one positive sample). Conclusion: High protein foods contain different types of Listeria species; whole-cell protein profiles and API Listeria system can help in the identification of Listeria at the species level.

Proteomic profile of acute myeloid leukaemia: A review update

Proteome analysis is a complex and dynamic process that encompasses several analytical platforms that include protein sequencing, structural or expression proteomics, protein modification, sub-cellular protein localization, protein-protein interaction and biological functional proteomics. In fact, expression proteomics is extensively applied in a majority of biomarker detection studies because it provides a detailed overview of differentially expressed proteins in cellular pathways and disease processes. Proteomics are also effective and dynamic in protein-protein interactions and cross-talks between interacting molecules of the cell. Proteomics has evolved into a crucial tool used to investigate the biochemical changes that possibly lead to development of cancer biomarkers. This review draws attention to the progress and advancements in cancer proteomics technology with the aim of simplifying the understanding of the mechanisms underlying the disease and to contribute to detection of biomarkers in addition to the development of novel treatments. Given that proteome is a dynamic entity of cellular functions in health and disease, it is capable of reflecting the immediate environmental state of cells and tissues as shown in this review. The review shows the possibility of elucidating the pathophysiology of acute myeloid leukaemia (AML) through proteome expressions, thus confirming the viability of proteome analysis in profiling AML.