Comparative database search engine analysis on massive tandem mass spectra of pork-based food products for halal proteomics

Mass spectrometry-based proteomics relies on dedicated software for peptide and protein identification. These software include open-source or commercial-based search engines; wherein, they employ different algorithms to establish their scoring and identified proteins. Although previous comparative studies have differentiated the proteomics results from different software, there are still yet studies specifically been conducted to compare and evaluate the search engine in the field of halal analysis. This is important because the halal analysis is often using commercial meat samples that have been subjected to various processing, further complicating its analysis. Thus, this study aimed to assess three open-source search engines (Comet, X! Tandem, and ProteinProspector) and a commercial-based search engine (ProteinPilot™) against 135 raw tandem mass spectrometry data files from 15 types of pork-based food products for halal analysis. Each database search engine contained high false-discovery rate (FDR); however, a post-searching algorithm called PeptideProphet managed to reduce the FDR, except for ProteinProspector and ProteinPilot™. From this study, the combined database search engine (executed by iProphet) reveals a thorough protein list for pork-based food products; wherein the most abundant proteins are myofibrillar proteins. Thus, this proteomics study will aid the identification of potential peptide and protein biomarkers for future precision halal analysis. SIGNIFICANCE: A critical challenge of halal proteomics is the availability of a database to confirm the inferential peptides as well as proteins. Currently, the established database such as UniProtKB is related to animal proteome; however, the halal proteomics is related to the highly processed meat-based food products. This study highlights the use of different database search engines (Comet, X! Tandem, ProteinProspector, and ProteinPilot™) and their respective algorithms to analyse 135 raw tandem mass spectrometry data files from 15 types of pork-based food products. This is the first attempt that has compared different database search engines in the context of halal proteomics to ensure the effectiveness of controlling the FDR. Previous studies were just focused on the advantages of a certain algorithm over another. Moreover, other previous studies also have mainly reported the use of mass spectrometry-based shotgun proteomics for meat authentication (the most similar field to halal analysis), but none of the studies were reported on halal aspects that used samples originated from highly processed food products. Hence, a systematic comparative study is duly needed for a more comprehensive and thorough proteomics analysis for such samples. In this study, our combinatorial approach for halal proteomics results from the different search engines used (Comet, X! Tandem, and ProteinProspector) has successfully generated a comprehensive spectral library for the pork-based meat products. This combined spectral library is freely available at https://data.mendeley.com/datasets/6dmm8659rm/3. Thus far, this is the first and new attempt at establishing a spectral library for halal proteomics. We also believe this study is a pioneer for halal proteomics that aimed at non-conventional and non-model organism proteomics, protein analytics, protein bioinformatics, and potential biomarker discovery.