1
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Flynn J, Samant N, Schneider-Nachum G, Tenzin T, Bolon DNA. Mutational fitness landscape and drug resistance. Curr Opin Struct Biol 2023; 78:102525. [PMID: 36621152 PMCID: PMC10243218 DOI: 10.1016/j.sbi.2022.102525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/29/2022] [Accepted: 12/06/2022] [Indexed: 01/08/2023]
Abstract
Robust technology has been developed to systematically quantify fitness landscapes that provide valuable opportunities to improve our understanding of drug resistance and define new avenues to develop drugs with reduced resistance susceptibility. We outline the critical importance of drug resistance studies and the potential for fitness landscape approaches to contribute to this effort. We describe the major technical advancements in mutational scanning, which is the primary approach used to quantify protein fitness landscapes. There are many complex steps to consider in planning and executing mutational scanning projects including developing a selection scheme, generating mutant libraries, tracking the frequency of variants using next-generation sequencing, and processing and interpreting the data. Key experimental parameters impacting each of these steps are discussed to aid in planning fitness landscape studies. There is a strong need for improved understanding of drug resistance, and fitness landscapes provide a promising new approach.
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Affiliation(s)
- Julia Flynn
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Neha Samant
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Gily Schneider-Nachum
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Tsepal Tenzin
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Daniel N A Bolon
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.
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2
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Liu W, Tang S, Peng J, Zhu Y, Pan L, Wang J, Peng X, Cheng H, Chen Z, Wang Y, Zhou H. Enhancing lactose recognition of a key enzyme in 2'-fucosyllactose synthesis: α-1,2-fucosyltransferase. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:1303-1314. [PMID: 36116126 DOI: 10.1002/jsfa.12224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/12/2022] [Accepted: 09/18/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND 2'-Fucosyllactose, a representative oligosaccharide in human milk, is an emerging and promising food and pharmaceutical ingredient due to its powerful health benefits, such as participating in immune regulation, regulation of intestinal flora, etc. To enable economically viable production of 2'-fucosyllactose, different biosynthesis strategies using precursors and pathway enzymes have been developed. The α-1,2-fucosyltransferases are an essential part involved in these strategies, but their strict substrate selectivity and unsatisfactory substrate tolerance are one of the key roadblocks limiting biosynthesis. RESULTS To tackle this issue, a semi-rational manipulation combining computer-aided designing and screening with biochemical experiments were adopted. The mutant had a 100-fold increase in catalytic efficiency compared to the wild-type. The highest 2'-fucosyllactose yield was up to 0.65 mol mol-1 lactose with a productivity of 2.56 g mL-1 h-1 performed by enzymatic catalysis in vitro. Further analysis revealed that the interactions between the mutant and substrates were reduced. The crucial contributions of wild-type and mutant to substrate recognition ability were closely related to their distinct phylotypes in terms of amino acid preference. CONCLUSION It is envisioned that the engineered α-1,2-fucosyltransferase could be harnessed to relieve constraints imposed on the bioproduction of 2'-fucosyllactose and lay a theoretical foundation for elucidating the substrate recognition mechanisms of fucosyltransferases. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Wenxian Liu
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
| | - Shizhe Tang
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
| | - Jing Peng
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
| | - Yuling Zhu
- Changsha Yunkang Biotechnology Co Ltd, Changsha, P. R. China
| | - Lina Pan
- Ausnutria Institute Food & Nutrition, Ausnutria Dairy China Co Ltd, Changsha, P. R. China
| | - Jiaqi Wang
- Ausnutria Institute Food & Nutrition, Ausnutria Dairy China Co Ltd, Changsha, P. R. China
| | - Xiaoyu Peng
- Ausnutria Institute Food & Nutrition, Ausnutria Dairy China Co Ltd, Changsha, P. R. China
| | - Haina Cheng
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
- Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha, P. R. China
| | - Zhu Chen
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
- Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha, P. R. China
| | - Yuguang Wang
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
- Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha, P. R. China
| | - Hongbo Zhou
- School of Minerals Processing and Bioengineering, Central South University, Changsha, P. R. China
- Key Laboratory of Biometallurgy of Ministry of Education, Central South University, Changsha, P. R. China
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3
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Azbukina N, Zharikova A, Ramensky V. Intragenic compensation through the lens of deep mutational scanning. Biophys Rev 2022; 14:1161-1182. [PMID: 36345285 PMCID: PMC9636336 DOI: 10.1007/s12551-022-01005-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 09/26/2022] [Indexed: 12/20/2022] Open
Abstract
A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them. Supplementary Information The online version contains supplementary material available at 10.1007/s12551-022-01005-w.
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Affiliation(s)
- Nadezhda Azbukina
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskie Gory, 119991 Moscow, Russia
| | - Anastasia Zharikova
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskie Gory, 119991 Moscow, Russia
- National Medical Research Center for Therapy and Preventive Medicine, Petroverigsky per., 10, Bld.3, 101000 Moscow, Russia
| | - Vasily Ramensky
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 1-73, Leninskie Gory, 119991 Moscow, Russia
- National Medical Research Center for Therapy and Preventive Medicine, Petroverigsky per., 10, Bld.3, 101000 Moscow, Russia
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4
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Abstract
One core goal of genetics is to systematically understand the mapping between the DNA sequence of an organism (genotype) and its measurable characteristics (phenotype). Understanding this mapping is often challenging because of interactions between mutations, where the result of combining several different mutations can be very different than the sum of their individual effects. Here we provide a statistical framework for modeling complex genetic interactions of this type. The key idea is to ask how fast the effects of mutations change when introducing the same mutation in increasingly distant genetic backgrounds. We then propose a model for phenotypic prediction that takes into account this tendency for the effects of mutations to be more similar in nearby genetic backgrounds. Contemporary high-throughput mutagenesis experiments are providing an increasingly detailed view of the complex patterns of genetic interaction that occur between multiple mutations within a single protein or regulatory element. By simultaneously measuring the effects of thousands of combinations of mutations, these experiments have revealed that the genotype–phenotype relationship typically reflects not only genetic interactions between pairs of sites but also higher-order interactions among larger numbers of sites. However, modeling and understanding these higher-order interactions remains challenging. Here we present a method for reconstructing sequence-to-function mappings from partially observed data that can accommodate all orders of genetic interaction. The main idea is to make predictions for unobserved genotypes that match the type and extent of epistasis found in the observed data. This information on the type and extent of epistasis can be extracted by considering how phenotypic correlations change as a function of mutational distance, which is equivalent to estimating the fraction of phenotypic variance due to each order of genetic interaction (additive, pairwise, three-way, etc.). Using these estimated variance components, we then define an empirical Bayes prior that in expectation matches the observed pattern of epistasis and reconstruct the genotype–phenotype mapping by conducting Gaussian process regression under this prior. To demonstrate the power of this approach, we present an application to the antibody-binding domain GB1 and also provide a detailed exploration of a dataset consisting of high-throughput measurements for the splicing efficiency of human pre-mRNA 5′ splice sites, for which we also validate our model predictions via additional low-throughput experiments.
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5
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Safari M, Jayaraman B, Yang S, Smith C, Fernandes JD, Frankel AD. Functional and structural segregation of overlapping helices in HIV-1. eLife 2022; 11:72482. [PMID: 35511220 PMCID: PMC9119678 DOI: 10.7554/elife.72482] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Overlapping coding regions balance selective forces between multiple genes. One possible division of nucleotide sequence is that the predominant selective force on a particular nucleotide can be attributed to just one gene. While this arrangement has been observed in regions in which one gene is structured and the other is disordered, we sought to explore how overlapping genes balance constraints when both protein products are structured over the same sequence. We use a combination of sequence analysis, functional assays, and selection experiments to examine an overlapped region in HIV-1 that encodes helical regions in both Env and Rev. We find that functional segregation occurs even in this overlap, with each protein spacing its functional residues in a manner that allows a mutable non-binding face of one helix to encode important functional residues on a charged face in the other helix. Additionally, our experiments reveal novel and critical functional residues in Env and have implications for the therapeutic targeting of HIV-1.
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Affiliation(s)
- Maliheh Safari
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
| | - Bhargavi Jayaraman
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
| | - Shumin Yang
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States.,School of Medicine, Tsinghua University, Beijing, China
| | - Cynthia Smith
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
| | - Jason D Fernandes
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
| | - Alan D Frankel
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
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6
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Gonzalez Somermeyer L, Fleiss A, Mishin AS, Bozhanova NG, Igolkina AA, Meiler J, Alaball Pujol ME, Putintseva EV, Sarkisyan KS, Kondrashov FA. Heterogeneity of the GFP fitness landscape and data-driven protein design. eLife 2022; 11:75842. [PMID: 35510622 PMCID: PMC9119679 DOI: 10.7554/elife.75842] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 03/25/2022] [Indexed: 11/24/2022] Open
Abstract
Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design - instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.
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Affiliation(s)
| | - Aubin Fleiss
- Synthetic Biology Group, MRC London Institute of Medical SciencesLondonUnited Kingdom,Institute of Clinical Sciences, Faculty of Medicine and Imperial College Centre for Synthetic Biology, Imperial College LondonLondonUnited Kingdom
| | - Alexander S Mishin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of SciencesMoscowRussian Federation
| | - Nina G Bozhanova
- Department of Chemistry, Center for Structural Biology, Vanderbilt UniversityNashvilleUnited States
| | - Anna A Igolkina
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna BioCenterViennaAustria
| | - Jens Meiler
- Department of Chemistry, Center for Structural Biology, Vanderbilt UniversityNashvilleUnited States,Institute for Drug Discovery, Medical School, Leipzig UniversityLeipzigGermany
| | - Maria-Elisenda Alaball Pujol
- Synthetic Biology Group, MRC London Institute of Medical SciencesLondonUnited Kingdom,Institute of Clinical Sciences, Faculty of Medicine and Imperial College Centre for Synthetic Biology, Imperial College LondonLondonUnited Kingdom
| | | | - Karen S Sarkisyan
- Synthetic Biology Group, MRC London Institute of Medical SciencesLondonUnited Kingdom,Institute of Clinical Sciences, Faculty of Medicine and Imperial College Centre for Synthetic Biology, Imperial College LondonLondonUnited Kingdom,Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of SciencesMoscowRussian Federation
| | - Fyodor A Kondrashov
- Institute of Science and Technology AustriaKlosterneuburgAustria,Evolutionary and Synthetic Biology Unit, Okinawa Institute of Science and Technology Graduate UniversityOkinawaJapan
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7
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Relation Between the Number of Peaks and the Number of Reciprocal Sign Epistatic Interactions. Bull Math Biol 2022; 84:74. [PMID: 35713756 PMCID: PMC9205815 DOI: 10.1007/s11538-022-01029-z] [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: 02/18/2022] [Accepted: 05/15/2022] [Indexed: 01/25/2023]
Abstract
Empirical essays of fitness landscapes suggest that they may be rugged, that is having multiple fitness peaks. Such fitness landscapes, those that have multiple peaks, necessarily have special local structures, called reciprocal sign epistasis (Poelwijk et al. in J Theor Biol 272:141-144, 2011). Here, we investigate the quantitative relationship between the number of fitness peaks and the number of reciprocal sign epistatic interactions. Previously, it has been shown (Poelwijk et al. in J Theor Biol 272:141-144, 2011) that pairwise reciprocal sign epistasis is a necessary but not sufficient condition for the existence of multiple peaks. Applying discrete Morse theory, which to our knowledge has never been used in this context, we extend this result by giving the minimal number of reciprocal sign epistatic interactions required to create a given number of peaks.
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8
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Schneider-Nachum G, Flynn J, Mavor D, Schiffer CA, Bolon DNA. Analyses of HIV proteases variants at the threshold of viability reveals relationships between processing efficiency and fitness. Virus Evol 2021; 7:veab103. [PMID: 35299788 PMCID: PMC8923237 DOI: 10.1093/ve/veab103] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/17/2021] [Accepted: 12/13/2021] [Indexed: 12/13/2022] Open
Abstract
Investigating the relationships between protein function and fitness provides keys for understanding biochemical mechanisms that underly evolution. Mutations with partial fitness defects can delineate the threshold of biochemical function required for viability. We utilized a previous deep mutational scan of HIV-1 protease (PR) to identify variants with 15–45 per cent defects in replication and analysed the biochemical function of eight variants (L10M, L10S, V32C, V32I, A71V, A71S, Q92I, Q92N). We purified each variant and assessed the efficiency of peptide cleavage for three cut sites (MA-CA, TF-PR, and PR-RT) as well as gel-based analyses of processing of purified Gag. The cutting activity of at least one site was perturbed relative to WT protease for all variants, consistent with cutting activity being a primary determinant of fitness effects. We examined the correlation of fitness defects with cutting activity of different sites. MA-CA showed the weakest correlation (R2 = 0.02) with fitness, suggesting relatively weak coupling with viral replication. In contrast, cutting of the TF-PR site showed the strongest correlation with fitness (R2 = 0.53). Cutting at the TF-PR site creates a new PR protein with a free N-terminus that is critical for activity. Our findings indicate that increasing the pool of active PR is rate limiting for viral replication, making this an ideal step to target with inhibitors.
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Affiliation(s)
- Gily Schneider-Nachum
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St, Worcester, MA 01605, USA
| | - Julia Flynn
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St, Worcester, MA 01605, USA
| | - David Mavor
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St, Worcester, MA 01605, USA
| | - Celia A Schiffer
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St, Worcester, MA 01605, USA
| | - Daniel N A Bolon
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, 364 Plantation St, Worcester, MA 01605, USA
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9
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Heyne M, Shirian J, Cohen I, Peleg Y, Radisky ES, Papo N, Shifman JM. Climbing Up and Down Binding Landscapes through Deep Mutational Scanning of Three Homologous Protein-Protein Complexes. J Am Chem Soc 2021; 143:17261-17275. [PMID: 34609866 PMCID: PMC8532158 DOI: 10.1021/jacs.1c08707] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Protein-protein interactions (PPIs) have evolved to display binding affinities that can support their function. As such, cognate and noncognate PPIs could be highly similar structurally but exhibit huge differences in binding affinities. To understand this phenomenon, we study three homologous protease-inhibitor PPIs that span 9 orders of magnitude in binding affinity. Using state-of-the-art methodology that combines protein randomization, affinity sorting, deep sequencing, and data normalization, we report quantitative binding landscapes consisting of ΔΔGbind values for the three PPIs, gleaned from tens of thousands of single and double mutations. We show that binding landscapes of the three complexes are strikingly different and depend on the PPI evolutionary optimality. We observe different patterns of couplings between mutations for the three PPIs with negative and positive epistasis appearing most frequently at hot-spot and cold-spot positions, respectively. The evolutionary trends observed here are likely to be universal to other biological complexes in the cell.
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Affiliation(s)
- Michael Heyne
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel.,Avram and Stella Goldstein-Goren Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel
| | - Jason Shirian
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Itay Cohen
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel
| | - Yoav Peleg
- Life Sciences Core Facilities (LSCF) Structural Proteomics Unit (SPU), Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Evette S Radisky
- Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Jacksonville, Florida 32224, United States
| | - Niv Papo
- Avram and Stella Goldstein-Goren Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel
| | - Julia M Shifman
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
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10
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Miton CM, Buda K, Tokuriki N. Epistasis and intramolecular networks in protein evolution. Curr Opin Struct Biol 2021; 69:160-168. [PMID: 34077895 DOI: 10.1016/j.sbi.2021.04.007] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/01/2021] [Accepted: 04/21/2021] [Indexed: 12/01/2022]
Abstract
Proteins are molecular machines composed of complex, highly connected amino acid networks. Their functional optimization requires the reorganization of these intramolecular networks by evolution. In this review, we discuss the mechanisms by which epistasis, that is, the dependence of the effect of a mutation on the genetic background, rewires intramolecular interactions to alter protein function. Deciphering the biophysical basis of epistasis is crucial to our understanding of evolutionary dynamics and the elucidation of sequence-structure-function relationships. We featured recent studies that provide insights into the molecular mechanisms giving rise to epistasis, particularly at the structural level. These studies illustrate the convoluted and fascinating nature of the intramolecular networks co-opted by epistasis during the evolution of protein function.
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Affiliation(s)
- Charlotte M Miton
- Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada
| | - Karol Buda
- Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada
| | - Nobuhiko Tokuriki
- Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada.
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11
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Burton TD, Eyre NS. Applications of Deep Mutational Scanning in Virology. Viruses 2021; 13:1020. [PMID: 34071591 PMCID: PMC8227372 DOI: 10.3390/v13061020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 05/26/2021] [Accepted: 05/26/2021] [Indexed: 12/20/2022] Open
Abstract
Several recently developed high-throughput techniques have changed the field of molecular virology. For example, proteomics studies reveal complete interactomes of a viral protein, genome-wide CRISPR knockout and activation screens probe the importance of every single human gene in aiding or fighting a virus, and ChIP-seq experiments reveal genome-wide epigenetic changes in response to infection. Deep mutational scanning is a relatively novel form of protein science which allows the in-depth functional analysis of every nucleotide within a viral gene or genome, revealing regions of importance, flexibility, and mutational potential. In this review, we discuss the application of this technique to RNA viruses including members of the Flaviviridae family, Influenza A Virus and Severe Acute Respiratory Syndrome Coronavirus 2. We also briefly discuss the reverse genetics systems which allow for analysis of viral replication cycles, next-generation sequencing technologies and the bioinformatics tools that facilitate this research.
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Affiliation(s)
| | - Nicholas S. Eyre
- College of Medicine and Public Health, Flinders University, Bedford Park, SA 5042, Australia;
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12
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Routh S, Acharyya A, Dhar R. A two-step PCR assembly for construction of gene variants across large mutational distances. Biol Methods Protoc 2021; 6:bpab007. [PMID: 33928191 PMCID: PMC8062255 DOI: 10.1093/biomethods/bpab007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/09/2021] [Accepted: 04/01/2021] [Indexed: 11/14/2022] Open
Abstract
Construction of empirical fitness landscapes has transformed our understanding of genotype–phenotype relationships across genes. However, most empirical fitness landscapes have been constrained to the local genotype neighbourhood of a gene primarily due to our limited ability to systematically construct genotypes that differ by a large number of mutations. Although a few methods have been proposed in the literature, these techniques are complex owing to several steps of construction or contain a large number of amplification cycles that increase chances of non-specific mutations. A few other described methods require amplification of the whole vector, thereby increasing the chances of vector backbone mutations that can have unintended consequences for study of fitness landscapes. Thus, this has substantially constrained us from traversing large mutational distances in the genotype network, thereby limiting our understanding of the interactions between multiple mutations and the role these interactions play in evolution of novel phenotypes. In the current work, we present a simple but powerful approach that allows us to systematically and accurately construct gene variants at large mutational distances. Our approach relies on building-up small fragments containing targeted mutations in the first step followed by assembly of these fragments into the complete gene fragment by polymerase chain reaction (PCR). We demonstrate the utility of our approach by constructing variants that differ by up to 11 mutations in a model gene. Our work thus provides an accurate method for construction of multi-mutant variants of genes and therefore will transform the studies of empirical fitness landscapes by enabling exploration of genotypes that are far away from a starting genotype.
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Affiliation(s)
- Shreya Routh
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
| | - Anamika Acharyya
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
| | - Riddhiman Dhar
- Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India
- Correspondence address. Department of Biotechnology, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India. Tel. +91-3222-304562; E-mail:
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13
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Aharon L, Aharoni SL, Radisky ES, Papo N. Quantitative mapping of binding specificity landscapes for homologous targets by using a high-throughput method. Biochem J 2020; 477:1701-1719. [PMID: 32296833 PMCID: PMC7376575 DOI: 10.1042/bcj20200188] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/11/2020] [Accepted: 04/14/2020] [Indexed: 01/08/2023]
Abstract
To facilitate investigations of protein-protein interactions (PPIs), we developed a novel platform for quantitative mapping of protein binding specificity landscapes, which combines the multi-target screening of a mutagenesis library into high- and low-affinity populations with sophisticated next-generation sequencing analysis. Importantly, this method generates accurate models to predict affinity and specificity values for any mutation within a protein complex, and requires only a few experimental binding affinity measurements using purified proteins for calibration. We demonstrated the utility of the approach by mapping quantitative landscapes for interactions between the N-terminal domain of the tissue inhibitor of metalloproteinase 2 (N-TIMP2) and three matrix metalloproteinases (MMPs) having homologous structures but different affinities (MMP-1, MMP-3, and MMP-14). The binding landscapes for N-TIMP2/MMP-1 and N-TIMP2/MMP-3 showed the PPIs to be almost fully optimized, with most single mutations giving a loss of affinity. In contrast, the non-optimized PPI for N-TIMP2/MMP-14 was reflected in a wide range of binding affinities, where single mutations exhibited a far more attenuated effect on the PPI. Our new platform reliably and comprehensively identified not only hot- and cold-spot residues, but also specificity-switch mutations that shape target affinity and specificity. Thus, our approach provides a methodology giving an unprecedentedly rich quantitative analysis of the binding specificity landscape, which will broaden the understanding of the mechanisms and evolutionary origins of specific PPIs and facilitate the rational design of specific inhibitors for structurally similar target proteins.
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Affiliation(s)
- Lidan Aharon
- Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Shay-Lee Aharoni
- Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| | - Evette S. Radisky
- Department of Cancer Biology, Mayo Clinic Comprehensive Cancer Center, Jacksonville 32224, Florida, USA
| | - Niv Papo
- Department of Biotechnology Engineering and the National Institute of Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
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14
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Abstract
Knowledge of the distribution of fitness effects (DFE) of mutations is critical to the understanding of protein evolution. Here, we describe methods for large-scale, systematic measurements of the DFE using growth competition and deep mutational scanning. We discuss techniques for producing comprehensive libraries of gene variants as well as provide necessary considerations for designing these experiments. Using these methods, we have constructed libraries containing over 18,000 variants, measured fitness effects of these mutations by deep mutational scanning, and verified the presence of fitness effects in individual variants. Our methods provide a high-throughput protocol for measuring biological fitness effects of mutations and the dependence of fitness effects on the environment.
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15
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Minimum epistasis interpolation for sequence-function relationships. Nat Commun 2020; 11:1782. [PMID: 32286265 PMCID: PMC7156698 DOI: 10.1038/s41467-020-15512-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 03/12/2020] [Indexed: 12/17/2022] Open
Abstract
Massively parallel phenotyping assays have provided unprecedented insight into how multiple mutations combine to determine biological function. While such assays can measure phenotypes for thousands to millions of genotypes in a single experiment, in practice these measurements are not exhaustive, so that there is a need for techniques to impute values for genotypes whose phenotypes have not been directly assayed. Here, we present an imputation method based on inferring the least epistatic possible sequence-function relationship compatible with the data. In particular, we infer the reconstruction where mutational effects change as little as possible across adjacent genetic backgrounds. The resulting models can capture complex higher-order genetic interactions near the data, but approach additivity where data is sparse or absent. We apply the method to high-throughput transcription factor binding assays and use it to explore a fitness landscape for protein G.
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16
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Liberles DA, Chang B, Geiler-Samerotte K, Goldman A, Hey J, Kaçar B, Meyer M, Murphy W, Posada D, Storfer A. Emerging Frontiers in the Study of Molecular Evolution. J Mol Evol 2020; 88:211-226. [PMID: 32060574 PMCID: PMC7386396 DOI: 10.1007/s00239-020-09932-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
A collection of the editors of Journal of Molecular Evolution have gotten together to pose a set of key challenges and future directions for the field of molecular evolution. Topics include challenges and new directions in prebiotic chemistry and the RNA world, reconstruction of early cellular genomes and proteins, macromolecular and functional evolution, evolutionary cell biology, genome evolution, molecular evolutionary ecology, viral phylodynamics, theoretical population genomics, somatic cell molecular evolution, and directed evolution. While our effort is not meant to be exhaustive, it reflects research questions and problems in the field of molecular evolution that are exciting to our editors.
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Affiliation(s)
- David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA.
| | - Belinda Chang
- Department of Ecology and Evolutionary Biology and Department of Cell and Systems Biology, University of Toronto, 25 Harbord Street, Toronto, ON, M5S 3G5, Canada
| | - Kerry Geiler-Samerotte
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA
| | - Aaron Goldman
- Department of Biology, Oberlin College and Conservatory, K123 Science Center, 119 Woodland Street, Oberlin, OH, 44074, USA
| | - Jody Hey
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA
| | - Betül Kaçar
- Department of Molecular and Cell Biology, University of Arizona, Tucson, AZ, 85721, USA
| | - Michelle Meyer
- Department of Biology, Boston College, Chestnut Hill, MA, 02467, USA
| | - William Murphy
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA
| | - David Posada
- Biomedical Research Center (CINBIO), University of Vigo, Vigo, Spain
| | - Andrew Storfer
- School of Biological Sciences, Washington State University, Pullman, WA, 99164, USA
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17
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Flynn JM, Rossouw A, Cote-Hammarlof P, Fragata I, Mavor D, Hollins C, Bank C, Bolon DN. Comprehensive fitness maps of Hsp90 show widespread environmental dependence. eLife 2020; 9:53810. [PMID: 32129763 PMCID: PMC7069724 DOI: 10.7554/elife.53810] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 03/03/2020] [Indexed: 12/29/2022] Open
Abstract
Gene-environment interactions have long been theorized to influence molecular evolution. However, the environmental dependence of most mutations remains unknown. Using deep mutational scanning, we engineered yeast with all 44,604 single codon changes encoding 14,160 amino acid variants in Hsp90 and quantified growth effects under standard conditions and under five stress conditions. To our knowledge, these are the largest determined comprehensive fitness maps of point mutants. The growth of many variants differed between conditions, indicating that environment can have a large impact on Hsp90 evolution. Multiple variants provided growth advantages under individual conditions; however, these variants tended to exhibit growth defects in other environments. The diversity of Hsp90 sequences observed in extant eukaryotes preferentially contains variants that supported robust growth under all tested conditions. Rather than favoring substitutions in individual conditions, the long-term selective pressure on Hsp90 may have been that of fluctuating environments, leading to robustness under a variety of conditions.
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Affiliation(s)
- Julia M Flynn
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
| | - Ammeret Rossouw
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
| | - Pamela Cote-Hammarlof
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
| | - Inês Fragata
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - David Mavor
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
| | - Carl Hollins
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
| | - Claudia Bank
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Daniel Na Bolon
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
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18
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Mayorov A, Dal Peraro M, Abriata LA. Active Site-Induced Evolutionary Constraints Follow Fold Polarity Principles in Soluble Globular Enzymes. Mol Biol Evol 2020; 36:1728-1733. [PMID: 31004173 DOI: 10.1093/molbev/msz096] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
A recent analysis of evolutionary rates in >500 globular soluble enzymes revealed pervasive conservation gradients toward catalytic residues. By looking at amino acid preference profiles rather than evolutionary rates in the same data set, we quantified the effects of active sites on site-specific constraints for physicochemical traits. We found that conservation gradients respond to constraints for polarity, hydrophobicity, flexibility, rigidity and structure in ways consistent with fold polarity principles; while sites far from active sites seem to experience no physicochemical constraint, rather being highly variable and favoring amino acids of low metabolic cost. Globally, our results highlight that amino acid variation contains finer information about protein structure than usually regarded in evolutionary models, and that this information is retrievable automatically with simple fits. We propose that analyses of the kind presented here incorporated into models of protein evolution should allow for better description of the physical chemistry that underlies molecular evolution.
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Affiliation(s)
- Alexander Mayorov
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Matteo Dal Peraro
- Laboratory for Biomolecular Modeling, École Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Luciano A Abriata
- Laboratory for Biomolecular Modeling, École Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Protein Production and Structure Core Facility, École Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics, Lausanne, Switzerland
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19
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Higher-order epistasis shapes the fitness landscape of a xenobiotic-degrading enzyme. Nat Chem Biol 2019; 15:1120-1128. [DOI: 10.1038/s41589-019-0386-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 09/06/2019] [Indexed: 12/31/2022]
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20
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Klein SA, Majumdar A, Barrick D. A Second Backbone: The Contribution of a Buried Asparagine Ladder to the Global and Local Stability of a Leucine-Rich Repeat Protein. Biochemistry 2019; 58:3480-3493. [PMID: 31347358 PMCID: PMC7184636 DOI: 10.1021/acs.biochem.9b00355] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Parallel β-sheet-containing repeat proteins often display a structural motif in which conserved asparagines form a continuous ladder buried within the hydrophobic core. In such "asparagine ladders", the asparagine side-chain amides form a repetitive pattern of hydrogen bonds with neighboring main-chain NH and CO groups. Although asparagine ladders have been thought to be important for stability, there is little experimental evidence to support such speculation. Here we test the contribution of a minimal asparagine ladder from the leucine-rich repeat protein pp32 to stability and investigate lattice rigidity and hydrogen bond character using solution nuclear magnetic resonance (NMR) spectroscopy. Point substitutions of the two ladder asparagines of pp32 are strongly destabilizing and decrease the cooperativity of unfolding. The chemical shifts of the ladder side-chain HZ protons are shifted significantly downfield in the NMR spectrum and have low temperature coefficients, indicative of strong hydrogen bonding. In contrast, the HE protons are shifted upfield and have temperature coefficients close to zero, suggesting an asymmetry in hydrogen bond strength along the ladder. Ladder NH2 groups have weak 1H-15N cross-peak intensities; 1H-15N nuclear Overhauser effect and 15N CPMG experiments show this to be the result of high rigidity. Hydrogen exchange measurements demonstrate that the ladder NH2 groups exchange very slowly, with rates approaching the global exchange limit. Overall, these results show that the asparagine side chains are held in a very rigid, nondynamic structure, making a significant contribution to the overall stability. In this regard, buried asparagine ladders can be considered "second backbones" within the cores of their elongated β-sheet host proteins.
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Affiliation(s)
- Sean A. Klein
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218 USA
| | - Ananya Majumdar
- The Johns Hopkins University Biomolecular NMR Center, Johns Hopkins University, Baltimore, Maryland, 21218
| | - Doug Barrick
- T.C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218 USA
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21
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Abstract
For nearly a century adaptive landscapes have provided overviews of the evolutionary process and yet they remain metaphors. We redefine adaptive landscapes in terms of biological processes rather than descriptive phenomenology. We focus on the underlying mechanisms that generate emergent properties such as epistasis, dominance, trade-offs and adaptive peaks. We illustrate the utility of landscapes in predicting the course of adaptation and the distribution of fitness effects. We abandon aged arguments concerning landscape ruggedness in favor of empirically determining landscape architecture. In so doing, we transform the landscape metaphor into a scientific framework within which causal hypotheses can be tested.
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Affiliation(s)
- Xiao Yi
- BioTechnology Institute, University of Minnesota, St. Paul, MN
| | - Antony M Dean
- BioTechnology Institute, University of Minnesota, St. Paul, MN.,Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN
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22
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Boucher JI, Whitfield TW, Dauphin A, Nachum G, Hollins C, Zeldovich KB, Swanstrom R, Schiffer CA, Luban J, Bolon DNA. Constrained Mutational Sampling of Amino Acids in HIV-1 Protease Evolution. Mol Biol Evol 2019; 36:798-810. [PMID: 30721995 DOI: 10.1093/molbev/msz022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The evolution of HIV-1 protein sequences should be governed by a combination of factors including nucleotide mutational probabilities, the genetic code, and fitness. The impact of these factors on protein sequence evolution is interdependent, making it challenging to infer the individual contribution of each factor from phylogenetic analyses alone. We investigated the protein sequence evolution of HIV-1 by determining an experimental fitness landscape of all individual amino acid changes in protease. We compared our experimental results to the frequency of protease variants in a publicly available data set of 32,163 sequenced isolates from drug-naïve individuals. The most common amino acids in sequenced isolates supported robust experimental fitness, indicating that the experimental fitness landscape captured key features of selection acting on protease during viral infections of hosts. Amino acid changes requiring multiple mutations from the likely ancestor were slightly less likely to support robust experimental fitness than single mutations, consistent with the genetic code favoring chemically conservative amino acid changes. Amino acids that were common in sequenced isolates were predominantly accessible by single mutations from the likely protease ancestor. Multiple mutations commonly observed in isolates were accessible by mutational walks with highly fit single mutation intermediates. Our results indicate that the prevalence of multiple-base mutations in HIV-1 protease is strongly influenced by mutational sampling.
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Affiliation(s)
- Jeffrey I Boucher
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA
| | - Troy W Whitfield
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA.,Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA
| | - Ann Dauphin
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA
| | - Gily Nachum
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA
| | - Carl Hollins
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA
| | - Konstantin B Zeldovich
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA
| | - Ronald Swanstrom
- Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, NC
| | - Celia A Schiffer
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA
| | - Jeremy Luban
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA.,Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA
| | - Daniel N A Bolon
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA
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