Updated on 2021/10/25

写真a

 
AMR ELGUOSHY ABD ELDAYEM SHALABY
 
Organization
Graduate School of Medical and Dental Sciences Specially Appointed Assistant Professor
Title
Specially Appointed Assistant Professor
External link

Degree

  • 博士(学術) ( 2019.3   新潟大学 )

Research History

  • Niigata University   Graduate School of Medical and Dental Sciences   Specially Appointed Assistant Professor

    2019.4

 

Papers

  • Utilization of the Proteome Data Deposited in SRMAtlas for Validating the Existence of the Human Missing Proteins in GPM. International journal

    Amr Elguoshy, Yoshitoshi Hirao, Keiko Yamamoto, Bo Xu, Naohiko Kinoshita, Toshiaki Mitsui, Tadashi Yamamoto

    Journal of proteome research   18 ( 12 )   4197 - 4205   2019.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    The Human Proteome Project (HPP) has made great efforts to clarify the existing evidence of human proteins since 2012. However, according to the recent release of neXtProt (2019-1), approximately 10% of all human genes still have inadequate or no experimental evidence of their translation at the protein level. They were categorized as missing proteins (PE2-PE4). To further the goal of HPP, we developed a two-step bioinformatic strategy addressing the utilization of the SRMAtlas synthetic peptides corresponding to the missing proteins as an exclusive reference in order to explore their natural counterparts within GPM. In the first step, we searched the GPM for the non-nested SRMAtlas peptides corresponding to the missing proteins, taking under consideration only those detected via ≥2 non-nested unitypic/proteotypic peptides "Stranded peptides" with length ≥9 amino acids in the same proteomic study. As a result, 51 missing proteins were newly detected in 35 different proteomic studies. In the second step, we validated these newly detected missing proteins based on matching the spectra of their synthetic and natural peptides in SRMAtlas and GPM, respectively. The results showed that 23 of the missing proteins with ≥2 non-nested peptides were validated by careful spectral matching.

    DOI: 10.1021/acs.jproteome.9b00355

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  • The Optimized Workflow for Sample Preparation in LC-MS/MS-Based Urine Proteomics

    Suguru Saito, Yoshitoshi Hirao, Ali F. Quadery, Bo Xu, Amr Elguoshy, Hidehiko Fujinaka, Shohei Koma, Keiko Yamamoto, Tadashi Yamamoto

    Methods and Protocols   2 ( 2 )   46 - 46   2019.6

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    Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    The sample condition is an important factor in urine proteomics with stability and accuracy. However, a general protocol of urine protein preparation in mass spectrometry analysis has not yet been established. Here, we proposed a workflow for optimized sample preparation based on methanol/chloroform (M/C) precipitation and in-solution trypsin digestion in LC-MS/MS-based urine proteomics. The urine proteins prepared by M/C precipitation showed around 80% of the protein recovery rate. The samples showed the largest number of identified proteins, which were over 1000 on average compared with other precipitation methods in LC-MS/MS-based urine proteomics. For further improvement of the workflow, the essences were arranged in protein dissolving and trypsin digestion step for the extraction of urine proteins. Addition of Ethylene diamine tetraacetic acid (EDTA) dramatically enhanced the dissolution of protein and promoted the trypsin activity in the digestion step because the treatment increased the number of identified proteins with less missed cleavage sites. Eventually, an optimized workflow was established by a well-organized strategy for daily use in the LC-MS/MS-based urine proteomics. The workflow will be of great help for several aims based on urine proteomics approaches, such as diagnosis and biomarker discovery.

    DOI: 10.3390/mps2020046

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  • Proteomics Analysis of Urine to Examine Physical Effects of Warm Nano Mist Sauna Bathing. International journal

    Yoshitoshi Hirao, Naohiko Kinoshita, Bo Xu, Suguru Saito, Ali F Quadery, Amr Elguoshy, Keiko Yamamoto, Tadashi Yamamoto

    Healthcare (Basel, Switzerland)   7 ( 2 )   2019.5

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    Language:English   Publishing type:Research paper (scientific journal)  

    Conventional sauna bathing may have some health benefits as it facilitates relaxing, detoxing and promoting metabolism. However, conventional sauna bathing at a high temperature may be harmful for the body by increasing the risk of heart failure. The nano-mist sauna has been developed to provide nano-size water particles at a lower temperature. Hence, nano-mist sauna bathing is expected to be useful for health without the risks that arise at high temperatures. In this study, we performed a comprehensive proteomics analysis of urine samples obtained from healthy volunteers before and after they had taken a sauna bath with nano-mist (n = 10) or with conventional mist (n = 10) daily for two weeks (4 groups). The average numbers of urine proteins identified by liquid chromatography-linked mass chromatography in each group varied from 678 to 753. Interestingly, the protein number was increased after sauna bathing both with nano-mist or with conventional mist. Quantitative analysis indicated that considerable numbers of proteins were obviously up-regulated, with more than two-folds in urine samples after the nano-mist sauna bathing. The KEGG pathway analysis showed significant stimulation of the lysosome pathway (p = 5.89E-6) after the nano-mist bathing, which may indicate the nano-mist sauna bathing promotes metabolism related to the lysosome pathway more efficiently than conventional mist sauna bathing and may provide more health benefits.

    DOI: 10.3390/healthcare7020071

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  • Proteome Profiling of Diabetic Mellitus Patient Urine for Discovery of Biomarkers by Comprehensive MS-Based Proteomics. International journal

    Yoshitoshi Hirao, Suguru Saito, Hidehiko Fujinaka, Shigeru Miyazaki, Bo Xu, Ali F Quadery, Amr Elguoshy, Keiko Yamamoto, Tadashi Yamamoto

    Proteomes   6 ( 1 )   2018.2

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    Language:English   Publishing type:Research paper (scientific journal)  

    Diabetic mellitus (DM) is a disease that affects glucose homeostasis and causes complications, such as diabetic nephropathy (DN). For early diagnosis of DN, microalbuminuria is currently one of the most frequently used biomarkers. However, more early diagnostic biomarkers are desired in addition to microalbuminuria. In this study, we performed comprehensive proteomics analysis of urine proteomes of diabetic mellitus patients without microalbuminuria and healthy volunteers to compare the protein profiles by mass spectrometry. With high confidence criteria, 942 proteins in healthy volunteer urine and 645 proteins in the DM patient urine were identified with label-free semi-quantitation, respectively. Gene ontology and pathway analysis were performed with the proteins, which were up- or down-regulated in the DM patient urine to elucidate significant changes in pathways. The discovery of a useful biomarker for early DN discovery is expected.

    DOI: 10.3390/proteomes6010009

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  • Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining Strategy. International journal

    Amr Elguoshy, Yoshitoshi Hirao, Bo Xu, Suguru Saito, Ali F Quadery, Keiko Yamamoto, Toshiaki Mitsui, Tadashi Yamamoto

    Journal of proteome research   16 ( 12 )   4403 - 4414   2017.12

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    In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10-4)% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.

    DOI: 10.1021/acs.jproteome.7b00423

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  • Why are they missing? : Bioinformatics characterization of missing human proteins. International journal

    Amr Elguoshy, Sameh Magdeldin, Bo Xu, Yoshitoshi Hirao, Ying Zhang, Naohiko Kinoshita, Yusuke Takisawa, Masaaki Nameta, Keiko Yamamoto, Ali El-Refy, Fawzy El-Fiky, Tadashi Yamamoto

    Journal of proteomics   149   7 - 14   2016.10

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    NeXtProt is a web-based protein knowledge platform that supports research on human proteins. NeXtProt (release 2015-04-28) lists 20,060 proteins, among them, 3373 canonical proteins (16.8%) lack credible experimental evidence at protein level (PE2:PE5). Therefore, they are considered as "missing proteins". A comprehensive bioinformatic workflow has been proposed to analyze these "missing" proteins. The aims of current study were to analyze physicochemical properties, existence and distribution of the tryptic cleavage sites, and to pinpoint the signature peptides of the missing proteins. Our findings showed that 23.7% of missing proteins were hydrophobic proteins possessing transmembrane domains (TMD). Also, forty missing entries generate tryptic peptides were either out of mass detection range (>30aa) or mapped to different proteins (<9aa). Additionally, 21% of missing entries didn't generate any unique tryptic peptides. In silico endopeptidase combination strategy increased the possibility of missing proteins identification. Coherently, using both mature protein database and signal peptidome database could be a promising option to identify some missing proteins by targeting their unique N-terminal tryptic peptide from mature protein database and or C-terminus tryptic peptide from signal peptidome database. In conclusion, Identification of missing protein requires additional consideration during sample preparation, extraction, digestion and data analysis to increase its incidence of identification.

    DOI: 10.1016/j.jprot.2016.08.005

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  • A proteomic glimpse into human ureter proteome. International journal

    Sameh Magdeldin, Yoshitoshi Hirao, Amr Elguoshy, Bo Xu, Ying Zhang, Hidehiko Fujinaka, Keiko Yamamoto, John R Yates 3rd, Tadashi Yamamoto

    Proteomics   16 ( 1 )   80 - 4   2016.1

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    Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 (http://proteomecentral.proteomexchange.org/dataset/PXD002620).

    DOI: 10.1002/pmic.201500214

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  • Complementary protein and peptide OFFGEL fractionation for high-throughput proteomic analysis. International journal

    Sameh Magdeldin, Amr Elguoshy, Yutaka Yoshida, Yoshitoshi Hirao, Bo Xu, Ying Zhang, Keiko Yamamoto, Hiroki Takimoto, Hidehiko Fujinaka, Naohiko Kinoshita, Tadashi Yamamoto

    Analytical chemistry   87 ( 16 )   8481 - 8   2015.8

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    OFFGEL fractionation of mouse kidney protein lysate and its tryptic peptide digest has been examined in this study for better understanding the differences between protein and peptide fractionation methods and attaining maximum recruitment of this modern methodology for in-depth proteomic analysis. With the same initial protein/peptide load for both fractionation methods, protein OFFGEL fractionation showed a preponderance in terms of protein identification, fractionation efficiency, and focusing resolution, while peptide OFFGEL was better in recovery, number of peptide matches, and protein coverage. This result suggests that the protein fractionation method is more suitable for shotgun analysis while peptide fractionation suits well quantitative peptide analysis [isobaric tags for relative and absolute quantitation (iTRAQ) or tandem mass tags (TMT)]. Taken together, utilization of the advantages of both fractionation approaches could be attained by coupling both methods to be applied on complex biological tissue. A typical result is shown in this article by identification of 8262 confident proteins of whole mouse kidney under stringent condition. We therefore consider OFFGEL fractionation as an effective and efficient addition to both label-free and quantitative label proteomics workflow.

    DOI: 10.1021/acs.analchem.5b01911

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