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Arie Admon

Publications and source records attributed to Arie Admon.

16 recordsLinked to original sources

Innovative CRISPR/Cas9-Based Strategy for Allele-Specific HLA Peptidome Analysis Using a Pan-HLA Antibody.

Human leukocyte antigen (HLA) immunopeptidomics is restricted by the limited availability of allele-specific antibodies and by potential artifacts introduced by HLA overexpression systems. To address these challenges, we developed a CRISPR/Cas9-based strategy that selectively deletes undesired classical class I alleles while preserving a single endogenous allele, thereby enabling allele-resolved peptidome profiling with a pan-HLA class I antibody. As a proof of concept, we edited JY cells to eliminate HLA-B∗07:02 and HLA-C∗07:02 while retaining HLA-A∗02:01 (ΔBC clones). Peptide-HLA complexes were immunoprecipitated from WT and ΔBC clones using either the pan-HLA class I antibody W6/32 or the A∗02:01-specific antibody PA2.1, followed by nanoLC-MS/MS and computational HLA assignment. Deletion of HLA-B and HLA-C alleles caused an expected ∼55% reduction in total class I surface expression. Despite this, W6/32 immunoprecipitation from ΔBC clones recovered a comparable peptide yield to PA2.1 in WT cells. Binding predictions showed that most peptides identified in ΔBC clones using W6/32 were assigned to HLA-A∗02:01, with near-complete loss of HLA-B∗07:02- and HLA-C∗07:02-derived peptides. Sequence logo analysis confirmed the canonical A∗02:01 motif across conditions. The ΔBC W6/32 immunopeptidome exhibited a high degree of overlap (∼88%) with the WT PA2.1 repertoire, supporting the specificity and fidelity of the approach. These findings establish CRISPR-based editing of HLA alleles as a viable strategy for allele-specific immunopeptidome analysis using pan-HLA antibodies, supporting its potential application beyond this proof-of-concept system, reducing reliance on allele-specific reagents and facilitating the study of underrepresented HLA alleles.

Humans↗

Antibodies as oncogenes: a hypothesis.

We would like to put forward the hypothesis that cancer patients may produce autoantibodies that promote uncontrolled cell growth and thereby function as oncogenes. Dying cells release proteins that stimulate the production of autoantibodies, an event also known to occur during the earliest stages of tumor growth. If some of these autoantibodies are directed against cell surface hormone receptors, they could oligomerize the receptors and inadvertently transmit growth signals. The abnormal signals could result in uncontrolled cell proliferation and, eventually, oncogenesis. Thus, some specific autoantibodies from among the large repertoires of autoantibodies present in the sera of cancer patients are, in reality, oncogenes. If such oncogenic autoantibodies are indeed present and can be identified, inhibition of their molecular action may be an effective therapeutic modality.

Autoantibodies↗

Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals.

BACKGROUND: The ability of an oocyte to develop into a viable embryo depends on the accumulation of specific maternal information and molecules, such as RNAs and proteins. A serial analysis of gene expression (SAGE) was carried out in parallel with proteomic analysis on fully-grown ovarian follicles from zebrafish (Danio rerio). The data obtained were compared with ovary/follicle/egg molecular phenotypes of other animals, published or available in public sequence databases. RESULTS: Sequencing of 27,486 SAGE tags identified 11,399 different ones, including 3,329 tags with an occurrence superior to one. Fifty-eight genes were expressed at over 0.15% of the total population and represented 17.34% of the mRNA population identified. The three most expressed transcripts were a rhamnose-binding lectin, beta-actin 2, and a transcribed locus similar to the H2B histone family. Comparison with the large-scale expressed sequence tags sequencing approach revealed highly expressed transcripts that were not previously known to be expressed at high levels in fish ovaries, like the short-sized polarized metallothionein 2 transcript. A higher sensitivity for the detection of transcripts with a characterized maternal genetic contribution was also demonstrated compared to large-scale sequencing of cDNA libraries. Ferritin heavy polypeptide 1, heat shock protein 90-beta, lactate dehydrogenase B4, beta-actin isoforms, tubulin beta 2, ATP synthase subunit 9, together with 40 S ribosomal protein S27a, were common highly-expressed transcripts of vertebrate ovary/unfertilized egg. Comparison of transcriptome and proteome data revealed that transcript levels provide little predictive value with respect to the extent of protein abundance. All the proteins identified by proteomic analysis of fully-grown zebrafish follicles had at least one transcript counterpart, with two exceptions: eosinophil chemotactic cytokine and nothepsin. CONCLUSION: This study provides a complete sequence data set of maternal mRNA stored in zebrafish germ cells at the end of oogenesis. This catalogue contains highly-expressed transcripts that are part of a vertebrate ovarian expressed gene signature. Comparison of transcriptome and proteome data identified downregulated transcripts or proteins potentially incorporated in the oocyte by endocytosis. The molecular phenotype described provides groundwork for future experimental approaches aimed at identifying functionally important stored maternal transcripts and proteins involved in oogenesis and early stages of embryo development.

Animals↗

The turnover kinetics of major histocompatibility complex peptides of human cancer cells.

Peptides presented by the major histocompatibility complex (MHC) are derived from the degradation of cellular proteins. Thus, the repertoire of these peptides (the MHC peptidome) should correlate better with the cellular protein degradation scheme (the degradome) than with the cellular proteome. To test the validity of this statement and to determine whether the majority of MHC peptides are derived from short lived proteins, from defective ribosome products, or from regular long lived cellular proteins we analyzed in parallel the turnover kinetics of both MHC peptides and cellular proteins in the same cancer cells. The analysis was performed by pulse-chase experiments based on stable isotope labeling in tissue culture followed by capillary chromatography and tandem mass spectrometry. Indeed only a limited correlation was observed between the proteome and the MHC peptidome observed in the same cells. Moreover a detailed analysis of the turnover kinetics of the MHC peptides helped to assign their origin to normal, to short lived or long lived proteins, or to the defective ribosome products. Furthermore the analysis of the MHC peptides turnover kinetics helped to direct attention to abnormalities in the degradation schemes of their source proteins. These observations can be extended to search for cancer-related abnormalities in protein degradation, including those that lead to loss of tumor suppressors and cell cycle regulatory proteins.

Amino Acid Sequence↗

Evaluation of prefractionation methods as a preparatory step for multidimensional based chromatography of serum proteins.

Prefractionations of proteins prior to their proteolysis, chromatography, and MS/MS analyses help reduce complexity and increase the yield of protein identifications. A number of methods were evaluated here for prefractionating serum samples distributed to the participating laboratories as part of the human Plasma Proteome Project. These methods include strong cation exchange (SCX) chromatography, slicing of SDS-PAGE gel bands, and liquid-phase IEF of the proteins. The fractionated proteins were trypsinized and the resulting peptides were resolved and analyzed by multidimensional protein identification technology coupled to IT MS/MS. The MS/MS spectra were clustered, combined, and searched against the IPI protein databank using Pep-Miner. The identification results were evaluated for the efficacy of the different prefractionation methodologies to identify larger numbers of proteins at higher confidence and to achieve the best coverage of the proteins with the identified peptides. Prefractionation based on SCX resulted in the largest number of identified proteins, followed by gel slices and then the liquid-phase IEF. An important observation was that each of the methods revealed a set of unique proteins, some identified with high confidence. Therefore, for comprehensive identification of the serum proteins, several different prefractionation approaches should be used in parallel.

Blood Proteins↗

Centralized data analysis of a large interlaboratory proteomics project: a feasibility study.

The human Plasma Proteome Project (PPP) is a large-scale collaboration between many laboratories. One of the most demanding tasks in the PPP involved the analysis of very large amounts of raw MS/MS data produced by the participants. The main approach for managing this task was letting the participants analyze their own data and submit the results to the central PPP repository as lists of identified proteins and peptides. To complement this distributed approach, we also performed centralized analysis of the raw MS/MS data provided by the participants. Due to the data redundancy inherent in such a project, centralized analysis has the potential to reduce the computational effort by reducing redundancy before the analysis. Centralized analysis can also unify the process and take advantage of data sharing among laboratories to improve protein identification and validation. The process we employed included removing low-quality spectra, clustering spectra by mutual similarity, and applying uniform peptide and protein identification procedures. To demonstrate the process, we analyzed 5.28 million MS/MS spectra derived by eight laboratories from tryptic peptides of serum and plasma proteins.

Blood Proteins↗

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Algorithms↗

Proteomics in cancer vaccine development.

Proteomics is a new scientific field aimed at the large-scale characterization of the protein constituents of biologic systems. It facilitates comparisons between different protein preparations by searching for minute differences in their protein expression repertoires and the patterns of their post-translational modifications. These attributes make proteomics perfectly suited for searching for proteins and peptides expressed exclusively or preferentially in cancer cells as candidates for cancer vaccines. The main proteomics technologies include 2D polyacrylamide gel electrophoresis, multidimensional high-performance liquid chromatography, mass spectrometry and protein arrays. Proteomics technologies used to analyze cancer culture cells, fresh tumor specimens, human leukocyte antigen peptides, serum and serum antibodies (serologic proteomics) have successfully identified tumor markers. Turning the potential vaccine candidates identified by proteomics technologies into clinical treatments awaits demonstration.

Animals↗

A novel DNA methyltransferase I-derived peptide eluted from soluble HLA-A*0201 induces peptide-specific, tumor-directed cytotoxic T cells.

MHC peptides derived from tumor-associated antigens (TAAs) can serve as the basis for the development of immunotherapeutics to treat human malignancies. Previously, we identified novel HLA-A*0201 (HLA-A2)-restricted peptides recovered from soluble HLA molecules secreted by human tumor cell lines, transfected with truncated genes of HLA-A2 and HLA-B7. Here, 4 candidate peptides eluted from soluble HLA-A2 were selected on the basis of their precursor proteins being TAAs. Peptide p1028 (GLIEKNIEL), derived from DNA methyltransferase I (DNMT-1), which is overexpressed in various human tumors, showed the highest affinity to HLA-A2 and was relatively abundant in the sMHC/peptide complexes of all transfected breast, ovarian and prostate cancer cell lines. Peptide p1028-specific CTLs were generated in vitro and shown to efficiently lyse not only target cells pulsed with the peptide but also HLA-A2-positive breast cancer cell lines MDA-231 and MCF-7. The peptide induced IFN-gamma production in CTLs, which were selectively stained by a p1028 tetramer. Since DNMT-1 is a widely expressed tumor-associated enzyme, the novel DNMT-1-derived, HLA-A2-restricted peptide GLIEKNIEL identified here may provide a suitable candidate for a therapeutic cancer vaccine.

Breast Neoplasms↗

Improving large-scale proteomics by clustering of mass spectrometry data.

Tandem mass spectrometry (MS/MS), coupled with liquid chromatography (LC), is a powerful tool for the analysis and comparison of complex protein and peptide mixtures. However, the extremely large amounts of data that result from the process are very complex and difficult to analyze. We show how the clustering of similar spectra from multiple LC-MS/MS runs can help in data management and improve the analysis of complex peptide mixtures. The major effect of spectrum clustering is the reduction of the huge amounts of data to a manageable size. As a result, analysis time is shorter and more data can be stored for further analysis. Furthermore, spectrum quality improvement allows the identification of more peptides with greater confidence, the comparison of complex peptide mixtures is facilitated, and the entire proteomics project is presented in concise form. Pep-Miner is an advanced software tool that implements these clustering-based applications. It proved useful in several comparative proteomics projects involving lung cancer cells and various other cell types. In one of these projects, Pep-Miner reduced 517 000 spectra to 20 900 clusters and identified 2518 peptides derived from 830 proteins. Clustering and identification lasted less than two hours on an IBM Thinkpad T23 computer (laptop). Pep-Miner's unique properties make it a very useful tool for large-scale shotgun proteomics projects.

Algorithms↗

MHC-bound antigens and proteomics for novel target discovery.

The MHC molecules present normal as well as disease-related and pathogen-derived peptides to T cells as a way of alerting the immune system of the health status of a cell. Proteomic technologies involving immunoaffinity purification are now extensively used to separate MHC complexes from their peptide cargo, and then the peptides are sequenced by tandem mass spectrometry. The identified peptides are tested as vaccine candidates for viral diseases, immunostimulants for treating cancer, and immune-tolerance-inducing agents for autoimmune disorders. One of the challenges in devising novel HLA-peptide-based immunotherapies is to decipher whether a therapeutic window exists between the induction of tumor immunity and the onset of autoimmunity, which can have dangerous sequelae. This review will cover these topics with an overview of the vast possibilities emerging in the field of proteomic analyses of MHC-bound antigens as novel targets for immunotherapy.

Animals↗

Tumor antigens and proteomics from the point of view of the major histocompatibility complex peptides.

The major histocompatibility complex (MHC) peptide repertoire of cancer cells serves both as a source for new tumor antigens for development of cancer immunotherapy and as a rich information resource about the protein content of the cancer cells (their proteome). Thousands of different MHC peptides are normally displayed by each cell, where most of them are derived from different proteins and thus represent most of the cellular proteome. However, in contrast to standard proteomics, which surveys the cellular protein contents, analyses of the MHC peptide repertoire correspond more to the rapidly degrading proteins in the cells (i.e. the transient proteome). MHC peptides can be efficiently purified by affinity chromatography from membranal MHC molecules, or preferably following transfection of vectors for expression of recombinant soluble MHC molecules. The purified peptides are resolved and analyzed by capillary high-pressure liquid chromatography-electrospray ionization-tandem mass spectrometry, and the data are deciphered with new software tools enabling the creation of large databanks of MHC peptides displayed by different cell types and by different MHC haplotypes. These lists of identified MHC peptides can now be used for searching new tumor antigens, and for identification of proteins whose rapid degradation is significant to cancer progression and metastasis. These lists can also be used for identification of new proteins of yet unknown function that are not detected by standard proteomics approaches. This review focuses on the presentation, identification and analysis of MHC peptides significant for cancer immunotherapy. It is also concerned with the aspects of human proteomics observed through large-scale analyses of MHC peptides.

Antigens, Neoplasm↗

Recombinant human antibodies against the reverse transcriptase of human immunodeficiency virus type-1.

Inhibitory antibodies to the reverse transcriptase (RT) of human immunodeficiency virus type-1 (HIV-1) can be used to block the life cycle of the virus. We have isolated five different human single chain Fv (ScFv) antibodies specific for HIV-1 RT from an antibody phage display library. Three of these antibodies inhibited the RNA-dependent DNA polymerase (RDDP) activity of RT and one of the three (F-6) inhibited also its DNA-dependent DNA polymerase (DDDP) activity. Unexpectedly, F-6 binds to the carboxyl terminus of the large subunit of RT, which contains the ribonuclease H (RNase H) domain, and not the polymerase domain of the protein. Moreover, this binding did not inhibit the RNase H enzymatic activity. To further characterize F-6 antibody, two cyclic synthetic peptides based on the amino acids sequences of the CDR3 of F-6 were synthesized. Peptide F-6CDRH3, with the sequence of CDR3 of the heavy chain, inhibited the RDDP activity of RT while peptide F-6CDRL3, with the sequence of CDR3 of the light chain, had no effect on this activity of RT. These results indicate that some of the effects of F-6 are mediated by the CDR3 of the heavy chain. The antibodies identified here will be further tested as intrabodies for their capacity to protect human cells from HIV-1 infection.

Amino Acid Sequence↗

Large-scale analysis of HLA peptides presented by HLA-Cw4.

A large number of HLA-Cw4 (Cw *0402) peptides were purified, sequenced, and identified from breast and ovarian carcinoma cell lines. HLA-Cw4 molecules were expressed in these cells as soluble, secreted HLA (sHLA) and recovered from the growth medium. The peptides were separated by capillary reversed-phase HPLC and analyzed by tandem mass-spectrometry. The resulting peptides fit to some extent, but not completely, the known consensus of the Cw4 peptide-binding motif. Among the identified peptides, there are a few that originate from proteins of possible interest for cancer immunotherapy or diagnostics, including mucin-5B, ART-1, fatty acid synthase, putative prostate cancer tumor suppressor, DNA topoisomerase-1, and Rac1. This work demonstrates that large-scale identification of HLA peptides recovered from sHLA is an advantageous approach for establishing the HLA peptide consensus of different haplotypes and the identification of useful peptides for treatment of diseases such as cancer, viral, and autoimmune diseases.

HLA-C Antigens↗

Analysis of endogenous peptides bound by soluble MHC class I molecules: a novel approach for identifying tumor-specific antigens.

The Human MHC Project aims at comprehensive cataloging of peptides presented within the context of different human leukocyte antigens (HLA) expressed by cells of various tissue origins, both in health and in disease. Of major interest are peptides presented on cancer cells, which include peptides derived from tumor antigens that are of interest for immunotherapy. Here, HLA-restricted tumor-specific antigens were identified by transfecting human breast, ovarian and prostate tumor cell lines with truncated genes of HLA-A2 and HLA-B7. Soluble HLA secreted by these cell lines were purified by affinity chromatography and analyzed by nano-capillary electrospray ionization-tandem mass spectrometry. Typically, a large peptide pool was recovered and sequenced including peptides derived from MAGE-B2 and mucin and other new tumor-derived antigens that may serve as potential candidates for immunotherapy.

Animals↗