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Wang Y, Mai G, Zou M, Long H, Chen YQ, Sun L, Tian D, Zhao Y, Jiang G, Cao Z, Du X. Heavy chain sequence-based classifier for the specificity of human antibodies. Brief Bioinform 2021; 23:6483065. [PMID: 34953464 DOI: 10.1093/bib/bbab516] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 10/07/2021] [Accepted: 11/12/2021] [Indexed: 11/13/2022] Open
Abstract
Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnostics. High-throughput sequencing technologies have promoted comprehensive profiling of the immune repertoire, which has resulted in large amounts of antibody sequences that remain to be further analyzed. In this study, antibodies were downloaded from IMGT/LIGM-DB and Sequence Read Archive databases. Contributing features from antibody heavy chains were formulated as numerical inputs and fed into an ensemble machine learning classifier to classify the antigen specificity of six classes of antibodies, namely anti-HIV-1, anti-influenza virus, anti-pneumococcal polysaccharide, anti-citrullinated protein, anti-tetanus toxoid and anti-hepatitis B virus. The classifier was validated using cross-validation and a testing dataset. The ensemble classifier achieved a macro-average area under the receiver operating characteristic curve (AUC) of 0.9246 from the 10-fold cross-validation, and 0.9264 for the testing dataset. Among the contributing features, the contribution of the complementarity-determining regions was 53.1% and that of framework regions was 46.9%, and the amino acid mutation rates occupied the first and second ranks among the top five contributing features. The classifier and insights provided in this study could promote the mechanistic study, isolation and utilization of potential therapeutic antibodies.
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Affiliation(s)
- Yaqi Wang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Guoqin Mai
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Min Zou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Haoyu Long
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Yao-Qing Chen
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Litao Sun
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Dechao Tian
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Yang Zhao
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Zicheng Cao
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, P.R. China.,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou 510275, P.R. China.,Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, 510030, P.R. China
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2
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Aizik L, Dror Y, Taussig D, Barzel A, Carmi Y, Wine Y. Antibody Repertoire Analysis of Tumor-Infiltrating B Cells Reveals Distinct Signatures and Distributions Across Tissues. Front Immunol 2021; 12:705381. [PMID: 34349765 PMCID: PMC8327180 DOI: 10.3389/fimmu.2021.705381] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 06/29/2021] [Indexed: 12/12/2022] Open
Abstract
The role of B cells in the tumor microenvironment (TME) has largely been under investigated, and data regarding the antibody repertoire encoded by B cells in the TME and the adjacent lymphoid organs are scarce. Here, we utilized B cell receptor high-throughput sequencing (BCR-Seq) to profile the antibody repertoire signature of tumor-infiltrating lymphocyte B cells (TIL−Bs) in comparison to B cells from three anatomic compartments in a mouse model of triple-negative breast cancer. We found that TIL-Bs exhibit distinct antibody repertoire measures, including high clonal polarization and elevated somatic hypermutation rates, suggesting a local antigen-driven B-cell response. Importantly, TIL-Bs were highly mutated but non-class switched, suggesting that class-switch recombination may be inhibited in the TME. Tracing the distribution of TIL-B clones across various compartments indicated that they migrate to and from the TME. The data thus suggests that antibody repertoire signatures can serve as indicators for identifying tumor-reactive B cells.
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Affiliation(s)
- Ligal Aizik
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yael Dror
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - David Taussig
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Adi Barzel
- The School of Neurobiology, Biochemistry and Biophysics, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaron Carmi
- Department of Pathology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yariv Wine
- The Shmunis School of Biomedicine and Cancer Research, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
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3
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Avram O, Kigel A, Vaisman-Mentesh A, Kligsberg S, Rosenstein S, Dror Y, Pupko T, Wine Y. PASA: Proteomic analysis of serum antibodies web server. PLoS Comput Biol 2021; 17:e1008607. [PMID: 33493161 PMCID: PMC7861515 DOI: 10.1371/journal.pcbi.1008607] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 02/04/2021] [Accepted: 12/06/2020] [Indexed: 01/17/2023] Open
Abstract
MOTIVATION A comprehensive characterization of the humoral response towards a specific antigen requires quantification of the B-cell receptor repertoire by next-generation sequencing (BCR-Seq), as well as the analysis of serum antibodies against this antigen, using proteomics. The proteomic analysis is challenging since it necessitates the mapping of antigen-specific peptides to individual B-cell clones. RESULTS The PASA web server provides a robust computational platform for the analysis and integration of data obtained from proteomics of serum antibodies. PASA maps peptides derived from antibodies raised against a specific antigen to corresponding antibody sequences. It then analyzes and integrates proteomics and BCR-Seq data, thus providing a comprehensive characterization of the humoral response. The PASA web server is freely available at https://pasa.tau.ac.il and open to all users without a login requirement.
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Affiliation(s)
- Oren Avram
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Aya Kigel
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Anna Vaisman-Mentesh
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Sharon Kligsberg
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Shai Rosenstein
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yael Dror
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Tal Pupko
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yariv Wine
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
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4
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Teraguchi S, Saputri DS, Llamas-Covarrubias MA, Davila A, Diez D, Nazlica SA, Rozewicki J, Ismanto HS, Wilamowski J, Xie J, Xu Z, Loza-Lopez MDJ, van Eerden FJ, Li S, Standley DM. Methods for sequence and structural analysis of B and T cell receptor repertoires. Comput Struct Biotechnol J 2020; 18:2000-2011. [PMID: 32802272 PMCID: PMC7366105 DOI: 10.1016/j.csbj.2020.07.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 07/08/2020] [Accepted: 07/08/2020] [Indexed: 02/07/2023] Open
Abstract
B cell receptors (BCRs) and T cell receptors (TCRs) make up an essential network of defense molecules that, collectively, can distinguish self from non-self and facilitate destruction of antigen-bearing cells such as pathogens or tumors. The analysis of BCR and TCR repertoires plays an important role in both basic immunology as well as in biotechnology. Because the repertoires are highly diverse, specialized software methods are needed to extract meaningful information from BCR and TCR sequence data. Here, we review recent developments in bioinformatics tools for analysis of BCR and TCR repertoires, with an emphasis on those that incorporate structural features. After describing the recent sequencing technologies for immune receptor repertoires, we survey structural modeling methods for BCR and TCRs, along with methods for clustering such models. We review downstream analyses, including BCR and TCR epitope prediction, antibody-antigen docking and TCR-peptide-MHC Modeling. We also briefly discuss molecular dynamics in this context.
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Affiliation(s)
- Shunsuke Teraguchi
- Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Japan
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Dianita S. Saputri
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Mara Anais Llamas-Covarrubias
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
- Departamento de Biología Molecular y Genómica, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Mexico
| | - Ana Davila
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Diego Diez
- Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Sedat Aybars Nazlica
- Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - John Rozewicki
- Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Japan
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Hendra S. Ismanto
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Jan Wilamowski
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Jiaqi Xie
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Zichang Xu
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | | | - Floris J. van Eerden
- Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Songling Li
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
| | - Daron M. Standley
- Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita, Japan
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Japan
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5
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Prechl J. Network Organization of Antibody Interactions in Sequence and Structure Space: the RADARS Model. Antibodies (Basel) 2020; 9:antib9020013. [PMID: 32384800 PMCID: PMC7345901 DOI: 10.3390/antib9020013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/09/2020] [Accepted: 04/15/2020] [Indexed: 02/06/2023] Open
Abstract
Adaptive immunity in vertebrates is a complex self-organizing network of molecular interactions. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function. In this paper, a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RAdial ADjustment of System Resolution (RADARS), is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction corresponding to particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power law distribution of antibody-free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees, and B1 cells function as nodes with minimal degree. Overall, the RADARS model implies that a finite number of antibody structures can interact with an infinite number of antigens by immunologically controlled adjustment of interaction energy distribution. Understanding quantitative network properties of the system should help the organization of sequence-derived predicted structural data.
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Affiliation(s)
- József Prechl
- Diagnosticum Zrt., 126. Attila u., 1047 Budapest, Hungary
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6
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Vaisman-Mentesh A, Rosenstein S, Yavzori M, Dror Y, Fudim E, Ungar B, Kopylov U, Picard O, Kigel A, Ben-Horin S, Benhar I, Wine Y. Molecular Landscape of Anti-Drug Antibodies Reveals the Mechanism of the Immune Response Following Treatment With TNFα Antagonists. Front Immunol 2019; 10:2921. [PMID: 31921180 PMCID: PMC6930160 DOI: 10.3389/fimmu.2019.02921] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 11/28/2019] [Indexed: 12/25/2022] Open
Abstract
Drugs formulated from monoclonal antibodies (mAbs) are clinically effective in various diseases. Repeated administration of mAbs, however, elicits an immune response in the form of anti-drug-antibodies (ADA), thereby reducing the drug's efficacy. Notwithstanding their importance, the molecular landscape of ADA and the mechanisms involved in their formation are not fully understood. Using a newly developed quantitative bio-immunoassay, we found that ADA concentrations specific to TNFα antagonists can exceed extreme concentrations of 1 mg/ml with a wide range of neutralization capacity. Our data further suggest a preferential use of the λ light chain in a subset of neutralizing ADA. Moreover, we show that administration of TNFα antagonists result in a vaccine-like response whereby ADA formation is governed by the extrafollicular T cell-independent immune response. Our bio-immunoassay coupled with insights on the nature of the immune response can be leveraged to improve mAb immunogenicity assessment and facilitate improvement in therapeutic intervention strategies.
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Affiliation(s)
- Anna Vaisman-Mentesh
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Shai Rosenstein
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Miri Yavzori
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Yael Dror
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Ella Fudim
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Bella Ungar
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Uri Kopylov
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Orit Picard
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Aya Kigel
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Shomron Ben-Horin
- Gastroenterology Department, Sheba Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel Aviv-Yafo, Israel
| | - Itai Benhar
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
| | - Yariv Wine
- George S. Wise Faculty of Life Sciences, School of Molecular Cell Biology and Biotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel
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7
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Olson BJ, Moghimi P, Schramm CA, Obraztsova A, Ralph D, Vander Heiden JA, Shugay M, Shepherd AJ, Lees W, Matsen FA. sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation. Front Immunol 2019; 10:2533. [PMID: 31736960 PMCID: PMC6838214 DOI: 10.3389/fimmu.2019.02533] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 10/11/2019] [Indexed: 12/28/2022] Open
Abstract
The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.
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Affiliation(s)
- Branden J Olson
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States.,Department of Statistics, University of Washington, Seattle, WA, United States
| | - Pejvak Moghimi
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
| | - Chaim A Schramm
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Anna Obraztsova
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Duncan Ralph
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Jason A Vander Heiden
- Department of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, CA, United States
| | - Mikhail Shugay
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Adrian J Shepherd
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
| | - William Lees
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
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8
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Abstract
Antibodies are considered the hallmark of the adaptive immune system in that they mediate various key biological functions, such as direct neutralization and recruitment of effector immune cells to eliminate invading pathogens. Antibodies exhibit several unique properties, including high diversity (enabling binding to a wide range of targets), high specificity and structural integrity. These properties and the understanding that antibodies can be utilized in a wide range of applications have motivated the scientific community to develop new approaches for antibody repertoire analysis and rapid monoclonal antibody discovery. Today, antibodies are key modules in the pharmaceutical and diagnostic industries. By virtue of their high affinity and specificity to their targets and the availability of technologies to engineer different antibodies to a wide range of targets, antibodies have become the most promising natural biological molecules in a range of biotechnological applications, such as: highly specific and sensitive nanobiosensors for the diagnostics of different biomarkers; nanoparticle-based targeted drug delivery systems to certain cells or tissues; and nanomachines, which are nanoscale mechanical devices that enable energy conversion into precise mechanical motions in response to specific molecular inputs. In this review, we start by describing the unique properties of antibodies, how antibody diversity is generated, and the available technologies for antibody repertoire analysis and antibody discovery. Thereafter, we provide an overview of some antibody-based nanotechnologies and discuss novel and promising approaches for the application of antibodies in the nanotechnology field. Overall, we aim to bridge the knowledge gap between the nanotechnology and antibody engineering disciplines by demonstrating how technological advances in the antibody field can be leveraged to develop and/or enhance new technological approaches in the nanotechnology field.
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Affiliation(s)
- Yaron Hillman
- School of Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel
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