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Petersen BM, Kirby MB, Chrispens KM, Irvin OM, Strawn IK, Haas CM, Walker AM, Baumer ZT, Ulmer SA, Ayala E, Rhodes ER, Guthmiller JJ, Steiner PJ, Whitehead TA. An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries. Nat Commun 2024; 15:3974. [PMID: 38730230 PMCID: PMC11087541 DOI: 10.1038/s41467-024-48072-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 04/19/2024] [Indexed: 05/12/2024] Open
Abstract
Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of nine different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.
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Affiliation(s)
- Brian M Petersen
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Monica B Kirby
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Karson M Chrispens
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Olivia M Irvin
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Isabell K Strawn
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Cyrus M Haas
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Alexis M Walker
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Zachary T Baumer
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Sophia A Ulmer
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Edgardo Ayala
- Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Emily R Rhodes
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Jenna J Guthmiller
- Department of Immunology and Microbiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Paul J Steiner
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Timothy A Whitehead
- Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA.
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Radojković M, Ubbink M. Positive epistasis drives clavulanic acid resistance in double mutant libraries of BlaC β-lactamase. Commun Biol 2024; 7:197. [PMID: 38368480 PMCID: PMC10874438 DOI: 10.1038/s42003-024-05868-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 01/26/2024] [Indexed: 02/19/2024] Open
Abstract
Phenotypic effects of mutations are highly dependent on the genetic backgrounds in which they occur, due to epistatic effects. To test how easily the loss of enzyme activity can be compensated for, we screen mutant libraries of BlaC, a β-lactamase from Mycobacterium tuberculosis, for fitness in the presence of carbenicillin and the inhibitor clavulanic acid. Using a semi-rational approach and deep sequencing, we prepare four double-site saturation libraries and determine the relative fitness effect for 1534/1540 (99.6%) of the unique library members at two temperatures. Each library comprises variants of a residue known to be relevant for clavulanic acid resistance as well as residue 105, which regulates access to the active site. Variants with greatly improved fitness were identified within each library, demonstrating that compensatory mutations for loss of activity can be readily found. In most cases, the fittest variants are a result of positive epistasis, indicating strong synergistic effects between the chosen residue pairs. Our study sheds light on a role of epistasis in the evolution of functional residues and underlines the highly adaptive potential of BlaC.
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Affiliation(s)
- Marko Radojković
- Leiden Institute of Chemistry, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Marcellus Ubbink
- Leiden Institute of Chemistry, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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McConnell A, Hackel BJ. Protein engineering via sequence-performance mapping. Cell Syst 2023; 14:656-666. [PMID: 37494931 PMCID: PMC10527434 DOI: 10.1016/j.cels.2023.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 05/10/2023] [Accepted: 06/21/2023] [Indexed: 07/28/2023]
Abstract
Discovery and evolution of new and improved proteins has empowered molecular therapeutics, diagnostics, and industrial biotechnology. Discovery and evolution both require efficient screens and effective libraries, although they differ in their challenges because of the absence or presence, respectively, of an initial protein variant with the desired function. A host of high-throughput technologies-experimental and computational-enable efficient screens to identify performant protein variants. In partnership, an informed search of sequence space is needed to overcome the immensity, sparsity, and complexity of the sequence-performance landscape. Early in the historical trajectory of protein engineering, these elements aligned with distinct approaches to identify the most performant sequence: selection from large, randomized combinatorial libraries versus rational computational design. Substantial advances have now emerged from the synergy of these perspectives. Rational design of combinatorial libraries aids the experimental search of sequence space, and high-throughput, high-integrity experimental data inform computational design. At the core of the collaborative interface, efficient protein characterization (rather than mere selection of optimal variants) maps sequence-performance landscapes. Such quantitative maps elucidate the complex relationships between protein sequence and performance-e.g., binding, catalytic efficiency, biological activity, and developability-thereby advancing fundamental protein science and facilitating protein discovery and evolution.
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Affiliation(s)
- Adam McConnell
- Department of Biomedical Engineering, University of Minnesota - Twin Cities, 421 Washington Avenue SE, Minneapolis, MN 55455, USA
| | - Benjamin J Hackel
- Department of Biomedical Engineering, University of Minnesota - Twin Cities, 421 Washington Avenue SE, Minneapolis, MN 55455, USA; Department of Chemical Engineering and Materials Science, University of Minnesota - Twin Cities, 421 Washington Avenue SE, Minneapolis, MN 55455, USA.
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4
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Mighell TL, Toledano I, Lehner B. SUNi mutagenesis: Scalable and uniform nicking for efficient generation of variant libraries. PLoS One 2023; 18:e0288158. [PMID: 37418460 DOI: 10.1371/journal.pone.0288158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 06/20/2023] [Indexed: 07/09/2023] Open
Abstract
Multiplexed assays of variant effects (MAVEs) have made possible the functional assessment of all possible mutations to genes and regulatory sequences. A core pillar of the approach is generation of variant libraries, but current methods are either difficult to scale or not uniform enough to enable MAVEs at the scale of gene families or beyond. We present an improved method called Scalable and Uniform Nicking (SUNi) mutagenesis that combines massive scalability with high uniformity to enable cost-effective MAVEs of gene families and eventually genomes.
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Affiliation(s)
- Taylor L Mighell
- The Barcelona Institute of Science and Technology, Center for Genomic Regulation (CRG), Barcelona, Spain
| | - Ignasi Toledano
- The Barcelona Institute of Science and Technology, Center for Genomic Regulation (CRG), Barcelona, Spain
| | - Ben Lehner
- The Barcelona Institute of Science and Technology, Center for Genomic Regulation (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
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Leonard AC, Weinstein JJ, Steiner PJ, Erbse AH, Fleishman SJ, Whitehead TA. Stabilization of the SARS-CoV-2 receptor binding domain by protein core redesign and deep mutational scanning. Protein Eng Des Sel 2022; 35:6553331. [PMID: 35325236 PMCID: PMC9077414 DOI: 10.1093/protein/gzac002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/21/2022] [Accepted: 02/16/2022] [Indexed: 11/12/2022] Open
Abstract
Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen-specific antibodies at multiple distinct epitopes. This is a challenge, as stability enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study, we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L receptor binding domain mutations, maintains recognition by the receptor ACE2 and a panel of different anti-receptor binding domain monoclonal antibodies, is between 1 and 2°C more thermally stable than the original receptor binding domain using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original receptor binding domain. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes. We envision that this strategy may be particularly powerful for cases when there are multiple or unknown binding sites.
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Affiliation(s)
- Alison C Leonard
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80303, USA
| | - Jonathan J Weinstein
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Paul J Steiner
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO 80303, USA
| | - Annette H Erbse
- Department of Biochemistry, University of Colorado, Boulder, CO 80303, USA
| | - Sarel J Fleishman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
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Kirby MB, Whitehead TA. Facile Assembly of Combinatorial Mutagenesis Libraries Using Nicking Mutagenesis. Methods Mol Biol 2022; 2461:85-109. [PMID: 35727445 PMCID: PMC9730894 DOI: 10.1007/978-1-0716-2152-3_6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Combinatorial mutagenesis is a method where multiple user-defined mutations are encoded at defined positions in a sequence. Combinatorial mutagenic libraries can be used in a variety of applications including evaluating fundamental questions about molecular evolution, directed evolution workflows for enzyme engineering, and in better understanding of biological processes like antibody affinity maturation. Here, we show a method of combinatorial mutagenesis utilizing the template-based nicking mutagenesis with several modifications. We show an example for generating a combinatorial library with 14 mutated positions, a total of 16,384 library variants, and a protocol for the generation of large, user-defined combinatorial libraries. The reader can use this protocol to create such libraries in 2 days.
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Affiliation(s)
- Monica B Kirby
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, USA
| | - Timothy A Whitehead
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, USA.
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Kuiper BP, Prins RC, Billerbeck S. Oligo Pools as an Affordable Source of Synthetic DNA for Cost-Effective Library Construction in Protein- and Metabolic Pathway Engineering. Chembiochem 2021; 23:e202100507. [PMID: 34817110 PMCID: PMC9300125 DOI: 10.1002/cbic.202100507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/23/2021] [Indexed: 11/11/2022]
Abstract
The construction of custom libraries is critical for rational protein engineering and directed evolution. Array‐synthesized oligo pools of thousands of user‐defined sequences (up to ∼350 bases in length) have emerged as a low‐cost commercially available source of DNA. These pools cost ≤10 % (depending on error rate and length) of other commercial sources of custom DNA, and this significant cost difference can determine whether an enzyme engineering project can be realized on a given research budget. However, while being cheap, oligo pools do suffer from a low concentration of individual oligos and relatively high error rates. Several powerful techniques that specifically make use of oligo pools have been developed and proven valuable or even essential for next‐generation protein and pathway engineering strategies, such as sequence‐function mapping, enzyme minimization, or de‐novo design. Here we consolidate the knowledge on these techniques and their applications to facilitate the use of oligo pools within the protein engineering community.
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Affiliation(s)
- Bastiaan P Kuiper
- Molecular Microbiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands
| | - Rianne C Prins
- Molecular Microbiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands
| | - Sonja Billerbeck
- Molecular Microbiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands
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