1
|
d'Oelsnitz S, Diaz DJ, Kim W, Acosta DJ, Dangerfield TL, Schechter MW, Minus MB, Howard JR, Do H, Loy JM, Alper HS, Zhang YJ, Ellington AD. Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme. Nat Commun 2024; 15:2084. [PMID: 38453941 PMCID: PMC10920890 DOI: 10.1038/s41467-024-46356-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 02/22/2024] [Indexed: 03/09/2024] Open
Abstract
A major challenge to achieving industry-scale biomanufacturing of therapeutic alkaloids is the slow process of biocatalyst engineering. Amaryllidaceae alkaloids, such as the Alzheimer's medication galantamine, are complex plant secondary metabolites with recognized therapeutic value. Due to their difficult synthesis they are regularly sourced by extraction and purification from the low-yielding daffodil Narcissus pseudonarcissus. Here, we propose an efficient biosensor-machine learning technology stack for biocatalyst development, which we apply to engineer an Amaryllidaceae enzyme in Escherichia coli. Directed evolution is used to develop a highly sensitive (EC50 = 20 μM) and specific biosensor for the key Amaryllidaceae alkaloid branchpoint 4'-O-methylnorbelladine. A structure-based residual neural network (MutComputeX) is subsequently developed and used to generate activity-enriched variants of a plant methyltransferase, which are rapidly screened with the biosensor. Functional enzyme variants are identified that yield a 60% improvement in product titer, 2-fold higher catalytic activity, and 3-fold lower off-product regioisomer formation. A solved crystal structure elucidates the mechanism behind key beneficial mutations.
Collapse
Affiliation(s)
- Simon d'Oelsnitz
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA.
- Synthetic Biology HIVE, Department of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA.
| | - Daniel J Diaz
- Department of Chemistry, University of Texas at Austin, Austin, TX, 78712, USA
- Institute for Foundations of Machine Learning, University of Texas at Austin, Austin, TX, 78712, USA
| | - Wantae Kim
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Daniel J Acosta
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| | - Tyler L Dangerfield
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| | - Mason W Schechter
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| | - Matthew B Minus
- Department of Chemistry, Prairie View A&M University, 100 University Dr, Prairie View, TX, 77446, USA
| | - James R Howard
- Department of Chemistry, University of Texas at Austin, Austin, TX, 78712, USA
| | - Hannah Do
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| | - James M Loy
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| | - Hal S Alper
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Y Jessie Zhang
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| | - Andrew D Ellington
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, 78712, USA
| |
Collapse
|
2
|
Loveless TB, Grotts JH, Schechter MW, Forouzmand E, Carlson CK, Agahi BS, Liang G, Ficht M, Liu B, Xie X, Liu CC. Lineage tracing and analog recording in mammalian cells by single-site DNA writing. Nat Chem Biol 2021; 17:739-747. [PMID: 33753928 PMCID: PMC8891441 DOI: 10.1038/s41589-021-00769-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 02/09/2021] [Indexed: 01/31/2023]
Abstract
Studying cellular and developmental processes in complex multicellular organisms can require the non-destructive observation of thousands to billions of cells deep within an animal. DNA recorders address the staggering difficulty of this task by converting transient cellular experiences into mutations at defined genomic sites that can be sequenced later in high throughput. However, existing recorders act primarily by erasing DNA. This is problematic because, in the limit of progressive erasure, no record remains. We present a DNA recorder called CHYRON (Cell History Recording by Ordered Insertion) that acts primarily by writing new DNA through the repeated insertion of random nucleotides at a single locus in temporal order. To achieve in vivo DNA writing, CHYRON combines Cas9, a homing guide RNA and the template-independent DNA polymerase terminal deoxynucleotidyl transferase. We successfully applied CHYRON as an evolving lineage tracer and as a recorder of user-selected cellular stimuli.
Collapse
Affiliation(s)
- Theresa B Loveless
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
- NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine, CA, USA
| | - Joseph H Grotts
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Mason W Schechter
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Elmira Forouzmand
- Department of Computer Science, University of California, Irvine, Irvine, CA, USA
| | - Courtney K Carlson
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Bijan S Agahi
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Guohao Liang
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Michelle Ficht
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Beide Liu
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA
| | - Xiaohui Xie
- Department of Computer Science, University of California, Irvine, Irvine, CA, USA
| | - Chang C Liu
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, USA.
- NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine, CA, USA.
- Department of Chemistry, University of California, Irvine, Irvine, CA, USA.
- Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, USA.
- Center for Complex Biological Systems, University of California, Irvine, Irvine, CA, USA.
| |
Collapse
|