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1,695 results on '"Kelleher, Neil L."'

1. Bioactivity-driven fungal metabologenomics identifies antiproliferative stemphone analogs and their biosynthetic gene cluster

Author

Ayon, Navid J., Earp, Cody E., Gupta, Raveena, Butun, Fatma A., Clements, Ashley E., Lee, Alexa G., Dainko, David, Robey, Matthew T., Khin, Manead, Mardiana, Lina, Longcake, Alexandra, Rangel-Grimaldo, Manuel, Hall, Michael J., Probert, Michael R., Burdette, Joanna E., Keller, Nancy P., Raja, Huzefa A., Oberlies, Nicholas H., Kelleher, Neil L., and Caesar, Lindsay K.

Published
2024
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2. Author Correction: Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Author

Jain, Sanjay, Pei, Liming, Spraggins, Jeffrey M., Angelo, Michael, Carson, James P., Gehlenborg, Nils, Ginty, Fiona, Gonçalves, Joana P., Hagood, James S., Hickey, John W., Kelleher, Neil L., Laurent, Louise C., Lin, Shin, Lin, Yiing, Liu, Huiping, Naba, Alexandra, Nakayasu, Ernesto S., Qian, Wei-Jun, Radtke, Andrea, Robson, Paul, Stockwell, Brent R., Van de Plas, Raf, Vlachos, Ioannis S., Zhou, Mowei, Börner, Katy, and Snyder, Michael P.

Published
2024
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3. Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

Author

Jain, Sanjay, Pei, Liming, Spraggins, Jeffrey M., Angelo, Michael, Carson, James P., Gehlenborg, Nils, Ginty, Fiona, Gonçalves, Joana P., Hagood, James S., Hickey, John W., Kelleher, Neil L., Laurent, Louise C., Lin, Shin, Lin, Yiing, Liu, Huiping, Naba, Alexandra, Nakayasu, Ernesto S., Qian, Wei-Jun, Radtke, Andrea, Robson, Paul, Stockwell, Brent R., Van de Plas, Raf, Vlachos, Ioannis S., Zhou, Mowei, Börner, Katy, and Snyder, Michael P.

Published
2023
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4. Proteomics Standards Initiatives ProForma 2.0 Unifying the encoding of Proteoforms and Peptidoforms

Author

LeDuc, Richard D., Deutsch, Eric W., Binz, Pierre-Alain, Fellers, Ryan T., Cesnik, Anthony J., Klein, Joshua A., Bossche, Tim Van Den, Gabriels, Ralf, Yalavarthi, Arshika, Perez-Riverol, Yasset, Carver, Jeremy, Bittremieux, Wout, Kawano, Shin, Pullman, Benjamin, Bandeira, Nuno, Kelleher, Neil L., Thomas, Paul M., and Vizcaíno, Juan Antonio

Subjects
Quantitative Biology - Biomolecules
Abstract

There is the need to represent in a standard manner all the possible variations of a protein or peptide primary sequence, including both artefactual and post-translational modifications of peptides and proteins. With that overall aim, here, the Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has developed a notation, called ProForma 2.0, which is a substantial extension of the original ProForma notation, developed by the Consortium for Top-Down Proteomics (CTDP). ProForma 2.0 aims to unify the representation of proteoforms and peptidoforms. Therefore, this notation supports use cases needed for bottom-up and middle/topdown proteomics approaches and allows the encoding of highly modified proteins and peptides using a human and machine-readable string. ProForma 2.0 covers encoding protein modification names and accessions, cross-linking reagents including disulfides, glycans, modifications encoded using mass shifts and/or via chemical formulas, labile and C or N-terminal modifications, ambiguity in the modification position and representation of atomic isotopes, among other use cases. Notational conventions are based on public controlled vocabularies and ontologies. Detailed information about the notation and existing implementations are available at http://www.psidev.info/proforma and at the corresponding GitHub repository (https://github.com/HUPO-PSI/proforma).

Published
2021

5. New views of old proteins: clarifying the enigmatic proteome

Author

Functional, Participants in a NIH Workshop on, Proteomics, Integrative, Johnson, Kristin E. Burnum, Conrads, Thomas P., Drake, Richard R., Herr, Amy E., Iyengar, Ravi, Kelly, Ryan T., Lundberg, Emma, MacCoss, Michael J., Naba, Alexandra, Nolan, Garry P., Pevzner, Pavel A., Rodland, Karin D., Sechi, Salvatore, Slavov, Nikolai, Spraggins, Jeffrey M., Van Eyk, Jennifer E., Vidal, Marc, Vogel, Christine, Walt, David R., and Kelleher, Neil L.

Subjects
Quantitative Biology - Biomolecules
Abstract

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide provocative projections for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we offer potential futures for a next generation of disruptive approaches to define, quantify and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade., Comment: Submitted to Nature. 22 Pages. 6 Figures. Corresponding author Neil L. Kelleher

Published
2021

8. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Author

Hickey, John W., Neumann, Elizabeth K., Radtke, Andrea J., Camarillo, Jeannie M., Beuschel, Rebecca T., Albanese, Alexandre, McDonough, Elizabeth, Hatler, Julia, Wiblin, Anne E., Fisher, Jeremy, Croteau, Josh, Small, Eliza C., Sood, Anup, Caprioli, Richard M., Angelo, R. Michael, Nolan, Garry P., Chung, Kwanghun, Hewitt, Stephen M., Germain, Ronald N., Spraggins, Jeffrey M., Lundberg, Emma, Snyder, Michael P., Kelleher, Neil L., and Saka, Sinem K.

Subjects
Quantitative Biology - Tissues and Organs
Abstract

Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells are largely based on transcriptomic single-cell approaches that lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient coverage depth, several multiplexed protein imaging methods have recently been developed. Though these antibody-based technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this perspective, we provide essential resources and key considerations for obtaining robust and reproducible multiplexed antibody-based imaging data compiling specialized knowledge from domain experts and technology developers., Comment: {\ddag}authors contributed equally to this work

Published
2021

10. The Human Proteoform Project: Defining the human proteome

Author

Smith, Lloyd M, Agar, Jeffrey N, Chamot-Rooke, Julia, Danis, Paul O, Ge, Ying, Loo, Joseph A, Paša-Tolić, Ljiljana, Tsybin, Yury O, and Kelleher, Neil L

Subjects
Genetics, Human Genome, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Consortium for Top-Down Proteomics
Abstract

Proteins are the primary effectors of function in biology, and thus, complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants, and posttranslational modifications. This knowledge is foundational for the biological complexes and networks that control biology yet remains largely unknown. We propose here an ambitious initiative to define the human proteome, that is, to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented along with a call for improved technologies in a two-pronged strategy to the Human Proteoform Project.

Published
2021

11. Elevated N-Linked Glycosylation of IgG V Regions in Myasthenia Gravis Disease Subtypes.

Author

Mandel-Brehm, Caleigh, Fichtner, Miriam L, Jiang, Ruoyi, Winton, Valerie J, Vazquez, Sara E, Pham, Minh C, Hoehn, Kenneth B, Kelleher, Neil L, Nowak, Richard J, Kleinstein, Steven H, Wilson, Michael R, DeRisi, Joseph L, and O'Connor, Kevin C

Subjects
Myasthenia Gravis, Clinical Research, Autoimmune Disease, Neurosciences, Rare Diseases, Adult, Aged, Autoantibodies, B-Lymphocytes, Female, Glycosylation, Humans, Immunoglobulin G, Immunoglobulin Variable Region, Male, Middle Aged, Phenotype, Receptors, Antigen, B-Cell, Young Adult, Immunology
Abstract

Elevated N-linked glycosylation of IgG V regions (IgG-VN-Glyc) is an emerging molecular phenotype associated with autoimmune disorders. To test the broader specificity of elevated IgG-VN-Glyc, we studied patients with distinct subtypes of myasthenia gravis (MG), a B cell-mediated autoimmune disease. Our experimental design focused on examining the B cell repertoire and total IgG. It specifically included adaptive immune receptor repertoire sequencing to quantify and characterize N-linked glycosylation sites in the circulating BCR repertoire, proteomics to examine glycosylation patterns of the total circulating IgG, and an exploration of human-derived recombinant autoantibodies, which were studied with mass spectrometry and Ag binding assays to respectively confirm occupation of glycosylation sites and determine whether they alter binding. We found that the frequency of IgG-VN-Glyc motifs was increased in the total BCR repertoire of patients with MG when compared with healthy donors. The elevated frequency was attributed to both biased V gene segment usage and somatic hypermutation. IgG-VN-Glyc could be observed in the total circulating IgG in a subset of patients with MG. Autoantigen binding, by four patient-derived MG autoantigen-specific mAbs with experimentally confirmed presence of IgG-VN-Glyc, was not altered by the glycosylation. Our findings extend prior work on patterns of Ig V region N-linked glycosylation in autoimmunity to MG subtypes.

Published
2021

12. A community resource for paired genomic and metabolomic data mining

Author

Schorn, Michelle A, Verhoeven, Stefan, Ridder, Lars, Huber, Florian, Acharya, Deepa D, Aksenov, Alexander A, Aleti, Gajender, Moghaddam, Jamshid Amiri, Aron, Allegra T, Aziz, Saefuddin, Bauermeister, Anelize, Bauman, Katherine D, Baunach, Martin, Beemelmanns, Christine, Beman, J Michael, Berlanga-Clavero, María Victoria, Blacutt, Alex A, Bode, Helge B, Boullie, Anne, Brejnrod, Asker, Bugni, Tim S, Calteau, Alexandra, Cao, Liu, Carrión, Víctor J, Castelo-Branco, Raquel, Chanana, Shaurya, Chase, Alexander B, Chevrette, Marc G, Costa-Lotufo, Leticia V, Crawford, Jason M, Currie, Cameron R, Cuypers, Bart, Dang, Tam, de Rond, Tristan, Demko, Alyssa M, Dittmann, Elke, Du, Chao, Drozd, Christopher, Dujardin, Jean-Claude, Dutton, Rachel J, Edlund, Anna, Fewer, David P, Garg, Neha, Gauglitz, Julia M, Gentry, Emily C, Gerwick, Lena, Glukhov, Evgenia, Gross, Harald, Gugger, Muriel, Guillén Matus, Dulce G, Helfrich, Eric JN, Hempel, Benjamin-Florian, Hur, Jae-Seoun, Iorio, Marianna, Jensen, Paul R, Kang, Kyo Bin, Kaysser, Leonard, Kelleher, Neil L, Kim, Chung Sub, Kim, Ki Hyun, Koester, Irina, König, Gabriele M, Leao, Tiago, Lee, Seoung Rak, Lee, Yi-Yuan, Li, Xuanji, Little, Jessica C, Maloney, Katherine N, Männle, Daniel, Martin H., Christian, McAvoy, Andrew C, Metcalf, Willam W, Mohimani, Hosein, Molina-Santiago, Carlos, Moore, Bradley S, Mullowney, Michael W, Muskat, Mitchell, Nothias, Louis-Félix, O’Neill, Ellis C, Parkinson, Elizabeth I, Petras, Daniel, Piel, Jörn, Pierce, Emily C, Pires, Karine, Reher, Raphael, Romero, Diego, Roper, M Caroline, Rust, Michael, Saad, Hamada, Saenz, Carmen, Sanchez, Laura M, Sørensen, Søren Johannes, Sosio, Margherita, Süssmuth, Roderich D, Sweeney, Douglas, Tahlan, Kapil, Thomson, Regan J, Tobias, Nicholas J, Trindade-Silva, Amaro E, and van Wezel, Gilles P

Subjects
Human Genome, Genetics, Biotechnology, Generic health relevance, Data Mining, Databases, Factual, Genomics, Metabolomics, Medicinal and Biomolecular Chemistry, Biochemistry and Cell Biology, Biochemistry & Molecular Biology
Abstract

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.

Published
2021

13. Interlaboratory Study for Characterizing Monoclonal Antibodies by Top-Down and Middle-Down Mass Spectrometry

Author

Srzentić, Kristina, Fornelli, Luca, Tsybin, Yury O, Loo, Joseph A, Seckler, Henrique, Agar, Jeffrey N, Anderson, Lissa C, Bai, Dina L, Beck, Alain, Brodbelt, Jennifer S, van der Burgt, Yuri EM, Chamot-Rooke, Julia, Chatterjee, Sneha, Chen, Yunqiu, Clarke, David J, Danis, Paul O, Diedrich, Jolene K, D’Ippolito, Robert A, Dupré, Mathieu, Gasilova, Natalia, Ge, Ying, Goo, Young Ah, Goodlett, David R, Greer, Sylvester, Haselmann, Kim F, He, Lidong, Hendrickson, Christopher L, Hinkle, Joshua D, Holt, Matthew V, Hughes, Sam, Hunt, Donald F, Kelleher, Neil L, Kozhinov, Anton N, Lin, Ziqing, Malosse, Christian, Marshall, Alan G, Menin, Laure, Millikin, Robert J, Nagornov, Konstantin O, Nicolardi, Simone, Paša-Tolić, Ljiljana, Pengelley, Stuart, Quebbemann, Neil R, Resemann, Anja, Sandoval, Wendy, Sarin, Richa, Schmitt, Nicholas D, Shabanowitz, Jeffrey, Shaw, Jared B, Shortreed, Michael R, Smith, Lloyd M, Sobott, Frank, Suckau, Detlev, Toby, Timothy, Weisbrod, Chad R, Wildburger, Norelle C, Yates, John R, Yoon, Sung Hwan, Young, Nicolas L, and Zhou, Mowei

Subjects
Analytical Chemistry, Chemical Sciences, Biotechnology, Animals, Antibodies, Monoclonal, Complementarity Determining Regions, Humans, Mass Spectrometry, Mice, Proteomics, Therapeutic protein, glycoform, intact mass measurement, tandem mass spectrometry, MS/MS, Fourier transform mass spectrometry, FTMS, Medicinal and Biomolecular Chemistry, Physical Chemistry (incl. Structural), Analytical chemistry
Abstract

The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.

Published
2020

14. Proteomanalyse

Author

Lottspeich, Friedrich, Jooß, Kevin, Kelleher, Neil L., Götze, Michael, Friedrich, Betty, Aebersold, Ruedi, Kurreck, Jens, editor, Engels, Joachim W., editor, and Lottspeich, Friedrich, editor

Published
2022
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17. Top-down mass spectrometry of native proteoforms and their complexes: a community study

Author

Habeck, Tanja, primary, Brown, Kyle A., additional, Des Soye, Benjamin, additional, Lantz, Carter, additional, Zhou, Mowei, additional, Alam, Novera, additional, Hossain, Md Amin, additional, Jung, Wonhyeuk, additional, Keener, James E., additional, Volny, Michael, additional, Wilson, Jesse W., additional, Ying, Yujia, additional, Agar, Jeffrey N., additional, Danis, Paul O., additional, Ge, Ying, additional, Kelleher, Neil L., additional, Li, Huilin, additional, Loo, Joseph A., additional, Marty, Michael T., additional, Paša-Tolić, Ljiljana, additional, Sandoval, Wendy, additional, and Lermyte, Frederik, additional

Published
2024
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18. Bulk IgG glycosylation predicts COVID-19 severity and vaccine antibody response

Author

Ash, Michelle K., Bhimalli, Pavan P., Cho, Byoung-Kyu, Mattamana, Basil Baby, Gambut, Stéphanie, Tarhoni, Imad, Fhied, Cristina L., Reyes, Anjelica F., Welninski, Samantha J., Arivalagan, Jaison, Negrão, Fernanda, Goel, Renu, Beck, Todd L., Hope, Thomas J., Sha, Beverly E., Goo, Young Ah, Al-Harthi, Lena, Mamede, João I., Borgia, Jeffrey A., Kelleher, Neil L., and Schneider, Jeffrey R.

Published
2022
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19. Best practices and benchmarks for intact protein analysis for top-down mass spectrometry

Author

Donnelly, Daniel P, Rawlins, Catherine M, DeHart, Caroline J, Fornelli, Luca, Schachner, Luis F, Lin, Ziqing, Lippens, Jennifer L, Aluri, Krishna C, Sarin, Richa, Chen, Bifan, Lantz, Carter, Jung, Wonhyeuk, Johnson, Kendall R, Koller, Antonius, Wolff, Jeremy J, Campuzano, Iain DG, Auclair, Jared R, Ivanov, Alexander R, Whitelegge, Julian P, Paša-Tolić, Ljiljana, Chamot-Rooke, Julia, Danis, Paul O, Smith, Lloyd M, Tsybin, Yury O, Loo, Joseph A, Ge, Ying, Kelleher, Neil L, and Agar, Jeffrey N

Subjects
Biological Sciences, Biotechnology, Prevention, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Benchmarking, Mass Spectrometry, Protein Denaturation, Protein Processing, Post-Translational, Proteins, Proteomics, Technology, Medical and Health Sciences, Developmental Biology, Biological sciences
Abstract

One gene can give rise to many functionally distinct proteoforms, each of which has a characteristic molecular mass. Top-down mass spectrometry enables the analysis of intact proteins and proteoforms. Here members of the Consortium for Top-Down Proteomics provide a decision tree that guides researchers to robust protocols for mass analysis of intact proteins (antibodies, membrane proteins and others) from mixtures of varying complexity. We also present cross-platform analytical benchmarks using a protein standard sample, to allow users to gauge their proficiency.

Published
2019

21. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging

Author

Hickey, John W., Neumann, Elizabeth K., Radtke, Andrea J., Camarillo, Jeannie M., Beuschel, Rebecca T., Albanese, Alexandre, McDonough, Elizabeth, Hatler, Julia, Wiblin, Anne E., Fisher, Jeremy, Croteau, Josh, Small, Eliza C., Sood, Anup, Caprioli, Richard M., Angelo, R. Michael, Nolan, Garry P., Chung, Kwanghun, Hewitt, Stephen M., Germain, Ronald N., Spraggins, Jeffrey M., Lundberg, Emma, Snyder, Michael P., Kelleher, Neil L., and Saka, Sinem K.

Published
2022
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24. ProForma: A Standard Proteoform Notation

Author

LeDuc, Richard D, Schwämmle, Veit, Shortreed, Michael R, Cesnik, Anthony J, Solntsev, Stefan K, Shaw, Jared B, Martin, Maria J, Vizcaino, Juan A, Alpi, Emanuele, Danis, Paul, Kelleher, Neil L, Smith, Lloyd M, Ge, Ying, Agar, Jeffrey N, Chamot-Rooke, Julia, Loo, Joseph A, Pasa-Tolic, Ljiljana, and Tsybin, Yury O

Subjects
Amino Acid Sequence, Computational Biology, Databases, Protein, Humans, Information Dissemination, International Cooperation, Molecular Sequence Annotation, Protein Processing, Post-Translational, Proteome, Proteomics, Reproducibility of Results, Software, Tandem Mass Spectrometry, standard, proteoform, human readable, machine readable, Chemical Sciences, Biological Sciences, Biochemistry & Molecular Biology
Abstract

The Consortium for Top-Down Proteomics (CTDP) proposes a standardized notation, ProForma, for writing the sequence of fully characterized proteoforms. ProForma provides a means to communicate any proteoform by writing the amino acid sequence using standard one-letter notation and specifying modifications or unidentified mass shifts within brackets following certain amino acids. The notation is unambiguous, human-readable, and can easily be parsed and written by bioinformatic tools. This system uses seven rules and supports a wide range of possible use cases, ensuring compatibility and reproducibility of proteoform annotations. Standardizing proteoform sequences will simplify storage, comparison, and reanalysis of proteomic studies, and the Consortium welcomes input and contributions from the research community on the continued design and maintenance of this standard.

Published
2018

25. How many human proteoforms are there?

Author

Aebersold, Ruedi, Agar, Jeffrey N, Amster, I Jonathan, Baker, Mark S, Bertozzi, Carolyn R, Boja, Emily S, Costello, Catherine E, Cravatt, Benjamin F, Fenselau, Catherine, Garcia, Benjamin A, Ge, Ying, Gunawardena, Jeremy, Hendrickson, Ronald C, Hergenrother, Paul J, Huber, Christian G, Ivanov, Alexander R, Jensen, Ole N, Jewett, Michael C, Kelleher, Neil L, Kiessling, Laura L, Krogan, Nevan J, Larsen, Martin R, Loo, Joseph A, Ogorzalek Loo, Rachel R, Lundberg, Emma, MacCoss, Michael J, Mallick, Parag, Mootha, Vamsi K, Mrksich, Milan, Muir, Tom W, Patrie, Steven M, Pesavento, James J, Pitteri, Sharon J, Rodriguez, Henry, Saghatelian, Alan, Sandoval, Wendy, Schlüter, Hartmut, Sechi, Salvatore, Slavoff, Sarah A, Smith, Lloyd M, Snyder, Michael P, Thomas, Paul M, Uhlén, Mathias, Van Eyk, Jennifer E, Vidal, Marc, Walt, David R, White, Forest M, Williams, Evan R, Wohlschlager, Therese, Wysocki, Vicki H, Yates, Nathan A, Young, Nicolas L, and Zhang, Bing

Subjects
Humans, Proteins, Protein Isoforms, Proteome, Ubiquitin, Proteomics, Protein Biosynthesis, Protein Processing, Post-Translational, Phenotype, Genome, Human, Databases, Protein, Mass Spectrometry, Genetics, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Medicinal and Biomolecular Chemistry, Biochemistry and Cell Biology, Biochemistry & Molecular Biology
Abstract

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

Published
2018

26. Design, Synthesis, and Mechanistic Studies of (R)-3-Amino-5,5-difluorocyclohex-1-ene-1-carboxylic Acid as an Inactivator of Human Ornithine Aminotransferase

Author

Devitt, Allison N., primary, Vargas, Abigail L., additional, Zhu, Wei, additional, Des Soye, Benjamin James, additional, Butun, Fatma Ayaloglu, additional, Alt, Tyler, additional, Kaley, Nicholas, additional, Ferreira, Glaucio M., additional, Moran, Graham, additional, Kelleher, Neil L., additional, Liu, Dali, additional, and Silverman, Richard B., additional

Published
2024
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27. Single Cell Analysis of Proteoforms

Author

Su, Pei, primary, Hollas, Michael A. R., additional, Butun, Fatma Ayaloglu, additional, Kanchustambham, Vijaya Lakshmi, additional, Rubakhin, Stanislav, additional, Ramani, Namrata, additional, Greer, Joseph B., additional, Early, Bryan P., additional, Fellers, Ryan T., additional, Caldwell, Michael A., additional, Sweedler, Jonathan V., additional, Kafader, Jared O., additional, and Kelleher, Neil L., additional

Published
2024
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29. Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring

Author

Huang, Che-Fan, primary, Kline, Jake T., additional, Negrão, Fernanda, additional, Robey, Matthew T., additional, Toby, Timothy K., additional, Durbin, Kenneth R., additional, Fellers, Ryan T., additional, Friedewald, John J., additional, Levitsky, Josh, additional, Abecassis, Michael M. I., additional, Melani, Rafael D., additional, Kelleher, Neil L., additional, and Fornelli, Luca, additional

Published
2024
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31. Proteomanalyse

Author

Lottspeich, Friedrich, primary, Jooß, Kevin, additional, Kelleher, Neil L., additional, Götze, Michael, additional, Friedrich, Betty, additional, and Aebersold, Ruedi, additional

Published
2021
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32. The emerging landscape of single-molecule protein sequencing technologies

Author

Alfaro, Javier Antonio, Bohländer, Peggy, Dai, Mingjie, Filius, Mike, Howard, Cecil J., van Kooten, Xander F., Ohayon, Shilo, Pomorski, Adam, Schmid, Sonja, Aksimentiev, Aleksei, Anslyn, Eric V., Bedran, Georges, Cao, Chan, Chinappi, Mauro, Coyaud, Etienne, Dekker, Cees, Dittmar, Gunnar, Drachman, Nicholas, Eelkema, Rienk, Goodlett, David, Hentz, Sébastien, Kalathiya, Umesh, Kelleher, Neil L., Kelly, Ryan T., Kelman, Zvi, Kim, Sung Hyun, Kuster, Bernhard, Rodriguez-Larrea, David, Lindsay, Stuart, Maglia, Giovanni, Marcotte, Edward M., Marino, John P., Masselon, Christophe, Mayer, Michael, Samaras, Patroklos, Sarthak, Kumar, Sepiashvili, Lusia, Stein, Derek, Wanunu, Meni, Wilhelm, Mathias, Yin, Peng, Meller, Amit, and Joo, Chirlmin

Published
2021
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34. A multi-iron enzyme installs copper-binding oxazolone/thioamide pairs on a nontypeable Haemophilus influenzae virulence factor.

Author

Manley, Olivia M., Shriver, Tucker J., Tian Xu, Melendrez, Isaac A., Palacios, Philip, Robson, Scott A., Yisong Guo, Kelleher, Neil L., Ziarek, Joshua J., and Rosenzweig, Amy C.

Subjects
HAEMOPHILUS influenzae, OXAZOLONE, PEPTIDES, TANDEM mass spectrometry, MOSSBAUER spectroscopy
Abstract

The multinuclear nonheme iron-dependent oxidases (MNIOs) are a rapidly growing family of enzymes involved in the biosynthesis of ribosomally synthesized, posttranslationally modified peptide natural products (RiPPs). Recently, a secreted virulence factor from nontypeable Haemophilus influenzae (NTHi) was found to be expressed from an operon, which we designate the hvf operon, that also encodes an MNIO. Here, we show by Mössbauer spectroscopy that the MNIO HvfB contains a triiron cofactor. We demonstrate that HvfB works together with HvfC [a RiPP recognition element (RRE)-containing partner protein] to perform six posttranslational modifications of cysteine residues on the virulence factor precursor peptide HvfA. Structural characterization by tandem mass spectrometry and NMR shows that these six cysteine residues are converted to oxazolone and thioamide pairs, similar to those found in the RiPP methanobactin. Like methanobactin, the mature virulence factor, which we name oxazolin, uses these modified residues to coordinate Cu(I) ions. Considering the necessity of oxazolin for host cell invasion by NTHi, these findings point to a key role for copper during NTHi infection. Furthermore, oxazolin and its biosynthetic pathway represent a potential therapeutic target for NTHi. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Histone H1 loss drives lymphoma by disrupting 3D chromatin architecture

Author

Yusufova, Nevin, Kloetgen, Andreas, Teater, Matt, Osunsade, Adewola, Camarillo, Jeannie M., Chin, Christopher R., Doane, Ashley S., Venters, Bryan J., Portillo-Ledesma, Stephanie, Conway, Joseph, Phillip, Jude M., Elemento, Olivier, Scott, David W., Béguelin, Wendy, Licht, Jonathan D., Kelleher, Neil L., Staudt, Louis M., Skoultchi, Arthur I., Keogh, Michael-Christopher, Apostolou, Effie, Mason, Christopher E., Imielinski, Marcin, Schlick, Tamar, David, Yael, Tsirigos, Aristotelis, Allis, C. David, Soshnev, Alexey A., Cesarman, Ethel, and Melnick, Ari M.

Published
2021
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43. The serine hydroxymethyltransferase-2 (SHMT2) initiates lymphoma development through epigenetic tumor suppressor silencing

Author

Parsa, Sara, Ortega-Molina, Ana, Ying, Hsia-Yuan, Jiang, Man, Teater, Matt, Wang, Jiahui, Zhao, Chunying, Reznik, Ed, Pasion, Joyce P., Kuo, David, Mohan, Prathibha, Wang, Shenqiu, Camarillo, Jeannie M., Thomas, Paul M., Jain, Neeraj, Garcia-Bermudez, Javier, Cho, Byoung-kyu, Tam, Wayne, Kelleher, Neil L., Socci, Nicholas, Dogan, Ahmet, De Stanchina, Elisa, Ciriello, Giovanni, Green, Michael R., Li, Sheng, Birsoy, Kivanc, Melnick, Ari M., and Wendel, Hans-Guido

Published
2020
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45. A computational framework to explore large-scale biosynthetic diversity

Author

Navarro-Muñoz, Jorge C., Selem-Mojica, Nelly, Mullowney, Michael W., Kautsar, Satria A., Tryon, James H., Parkinson, Elizabeth I., De Los Santos, Emmanuel L. C., Yeong, Marley, Cruz-Morales, Pablo, Abubucker, Sahar, Roeters, Arne, Lokhorst, Wouter, Fernandez-Guerra, Antonio, Cappelini, Luciana Teresa Dias, Goering, Anthony W., Thomson, Regan J., Metcalf, William W., Kelleher, Neil L., Barona-Gomez, Francisco, and Medema, Marnix H.

Published
2020
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