1
|
Phylogenetic inference of changes in amino acid propensities with single-position resolution. PLoS Comput Biol 2022; 18:e1009878. [PMID: 35180226 PMCID: PMC9106220 DOI: 10.1371/journal.pcbi.1009878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 05/13/2022] [Accepted: 01/28/2022] [Indexed: 11/19/2022] Open
Abstract
Fitness conferred by the same allele may differ between genotypes and environments, and these differences shape variation and evolution. Changes in amino acid propensities at protein sites over the course of evolution have been inferred from sequence alignments statistically, but the existing methods are data-intensive and aggregate multiple sites. Here, we develop an approach to detect individual amino acids that confer different fitness in different groups of species from combined sequence and phylogenetic data. Using the fact that the probability of a substitution to an amino acid depends on its fitness, our method looks for amino acids such that substitutions to them occur more frequently in one group of lineages than in another. We validate our method using simulated evolution of a protein site under different scenarios and show that it has high specificity for a wide range of assumptions regarding the underlying changes in selection, while its sensitivity differs between scenarios. We apply our method to the env gene of two HIV-1 subtypes, A and B, and to the HA gene of two influenza A subtypes, H1 and H3, and show that the inferred fitness changes are consistent with the fitness differences observed in deep mutational scanning experiments. We find that changes in relative fitness of different amino acid variants within a site do not always trigger episodes of positive selection and therefore may not result in an overall increase in the frequency of substitutions, but can still be detected from changes in relative frequencies of different substitutions.
Collapse
|
2
|
Klink GV, O'Keefe H, Gogna A, Bazykin GA, Elson JL. A broad comparative genomics approach to understanding the pathogenicity of Complex I mutations. Sci Rep 2021; 11:19578. [PMID: 34599203 PMCID: PMC8486755 DOI: 10.1038/s41598-021-98360-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 09/01/2021] [Indexed: 12/29/2022] Open
Abstract
Disease caused by mutations of mitochondrial DNA (mtDNA) are highly variable in both presentation and penetrance. Over the last 30 years, clinical recognition of this group of diseases has increased. It has been suggested that haplogroup background could influence the penetrance and presentation of disease-causing mutations; however, to date there is only one well-established example of such an effect: the increased penetrance of two Complex I Leber's hereditary optic neuropathy mutations on a haplogroup J background. This paper conducts the most extensive investigation to date into the importance of haplogroup context in the pathogenicity of mtDNA mutations in Complex I. We searched for proven human point mutations across more than 900 metazoans finding human disease-causing mutations and potential masking variants. We found more than a half of human pathogenic variants as compensated pathogenic deviations (CPD) in at least in one animal species from our multiple sequence alignments. Some variants were found in many species, and some were even the most prevalent amino acids across our dataset. Variants were also found in other primates, and in such cases, we looked for non-human amino acids in sites with high probability to interact with the CPD in folded protein. Using this "local interactions" approach allowed us to find potential masking substitutions in other amino acid sites. We suggest that the masking variants might arise in humans, resulting in variability of mutation effect in our species.
Collapse
Affiliation(s)
- Galya V Klink
- Sector of Molecular Evolution, Institute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, Moscow, Russian Federation
| | - Hannah O'Keefe
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Amrita Gogna
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Georgii A Bazykin
- Sector of Molecular Evolution, Institute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, Moscow, Russian Federation.
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Skolkovo, Russian Federation.
| | - Joanna L Elson
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK.
- Human Metabolomics, North-West University, Potchefstroom, South Africa.
| |
Collapse
|
3
|
Fouks B, Brand P, Nguyen HN, Herman J, Camara F, Ence D, Hagen DE, Hoff KJ, Nachweide S, Romoth L, Walden KKO, Guigo R, Stanke M, Narzisi G, Yandell M, Robertson HM, Koeniger N, Chantawannakul P, Schatz MC, Worley KC, Robinson GE, Elsik CG, Rueppell O. The genomic basis of evolutionary differentiation among honey bees. Genome Res 2021; 31:1203-1215. [PMID: 33947700 PMCID: PMC8256857 DOI: 10.1101/gr.272310.120] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 04/22/2021] [Indexed: 02/06/2023]
Abstract
In contrast to the western honey bee, Apis mellifera, other honey bee species have been largely neglected despite their importance and diversity. The genetic basis of the evolutionary diversification of honey bees remains largely unknown. Here, we provide a genome-wide comparison of three honey bee species, each representing one of the three subgenera of honey bees, namely the dwarf (Apis florea), giant (A. dorsata), and cavity-nesting (A. mellifera) honey bees with bumblebees as an outgroup. Our analyses resolve the phylogeny of honey bees with the dwarf honey bees diverging first. We find that evolution of increased eusocial complexity in Apis proceeds via increases in the complexity of gene regulation, which is in agreement with previous studies. However, this process seems to be related to pathways other than transcriptional control. Positive selection patterns across Apis reveal a trade-off between maintaining genome stability and generating genetic diversity, with a rapidly evolving piRNA pathway leading to genomes depleted of transposable elements, and a rapidly evolving DNA repair pathway associated with high recombination rates in all Apis species. Diversification within Apis is accompanied by positive selection in several genes whose putative functions present candidate mechanisms for lineage-specific adaptations, such as migration, immunity, and nesting behavior.
Collapse
Affiliation(s)
- Bertrand Fouks
- Department of Biology, University of North Carolina at Greensboro, Greensboro, North Carolina 27403, USA
- Institute for Evolution and Biodiversity, Molecular Evolution and Bioinformatics, Westfälische Wilhelms-Universität, 48149 Münster, Germany
| | - Philipp Brand
- Department of Evolution and Ecology, Center for Population Biology, University of California, Davis, Davis, California 95161, USA
- Laboratory of Neurophysiology and Behavior, The Rockefeller University, New York, New York 10065, USA
| | - Hung N Nguyen
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
| | - Jacob Herman
- Department of Biology, University of North Carolina at Greensboro, Greensboro, North Carolina 27403, USA
| | - Francisco Camara
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08036 Barcelona, Spain
| | - Daniel Ence
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
- Department of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA
| | - Darren E Hagen
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, Oklahoma 74078, USA
| | - Katharina J Hoff
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
- University of Greifswald, Center for Functional Genomics of Microbes, 17489 Greifswald, Germany
| | - Stefanie Nachweide
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
| | - Lars Romoth
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
| | - Kimberly K O Walden
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Roderic Guigo
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08036 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
| | - Mario Stanke
- University of Greifswald, Institute for Mathematics and Computer Science, Bioinformatics Group, 17489 Greifswald, Germany
- University of Greifswald, Center for Functional Genomics of Microbes, 17489 Greifswald, Germany
| | | | - Mark Yandell
- Department of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA
- Utah Center for Genetic Discovery, University of Utah, Salt Lake City, Utah 84112, USA
| | - Hugh M Robertson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Nikolaus Koeniger
- Department of Behavioral Physiology and Sociobiology (Zoology II), University of Würzburg, 97074 Würzburg, Germany
| | - Panuwan Chantawannakul
- Environmental Science Research Center (ESRC) and Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Michael C Schatz
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Kim C Worley
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Gene E Robinson
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Christine G Elsik
- MU Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA
- Division of Animal Sciences, University of Missouri, Columbia, Missouri 65211, USA
- Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211, USA
| | - Olav Rueppell
- Department of Biology, University of North Carolina at Greensboro, Greensboro, North Carolina 27403, USA
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada
| |
Collapse
|
4
|
Swamy KBS, Schuyler SC, Leu JY. Protein Complexes Form a Basis for Complex Hybrid Incompatibility. Front Genet 2021; 12:609766. [PMID: 33633780 PMCID: PMC7900514 DOI: 10.3389/fgene.2021.609766] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 01/20/2021] [Indexed: 12/20/2022] Open
Abstract
Proteins are the workhorses of the cell and execute many of their functions by interacting with other proteins forming protein complexes. Multi-protein complexes are an admixture of subunits, change their interaction partners, and modulate their functions and cellular physiology in response to environmental changes. When two species mate, the hybrid offspring are usually inviable or sterile because of large-scale differences in the genetic makeup between the two parents causing incompatible genetic interactions. Such reciprocal-sign epistasis between inter-specific alleles is not limited to incompatible interactions between just one gene pair; and, usually involves multiple genes. Many of these multi-locus incompatibilities show visible defects, only in the presence of all the interactions, making it hard to characterize. Understanding the dynamics of protein-protein interactions (PPIs) leading to multi-protein complexes is better suited to characterize multi-locus incompatibilities, compared to studying them with traditional approaches of genetics and molecular biology. The advances in omics technologies, which includes genomics, transcriptomics, and proteomics can help achieve this end. This is especially relevant when studying non-model organisms. Here, we discuss the recent progress in the understanding of hybrid genetic incompatibility; omics technologies, and how together they have helped in characterizing protein complexes and in turn multi-locus incompatibilities. We also review advances in bioinformatic techniques suitable for this purpose and propose directions for leveraging the knowledge gained from model-organisms to identify genetic incompatibilities in non-model organisms.
Collapse
Affiliation(s)
- Krishna B. S. Swamy
- Division of Biological and Life Sciences, School of Arts and Sciences, Ahmedabad University, Ahmedabad, India
| | - Scott C. Schuyler
- Department of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Division of Head and Neck Surgery, Department of Otolaryngology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Jun-Yi Leu
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| |
Collapse
|
5
|
Neverov AD, Popova AV, Fedonin GG, Cheremukhin EA, Klink GV, Bazykin GA. Episodic evolution of coadapted sets of amino acid sites in mitochondrial proteins. PLoS Genet 2021; 17:e1008711. [PMID: 33493156 PMCID: PMC7861529 DOI: 10.1371/journal.pgen.1008711] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 02/04/2021] [Accepted: 12/07/2020] [Indexed: 11/19/2022] Open
Abstract
The rate of evolution differs between protein sites and changes with time. However, the link between these two phenomena remains poorly understood. Here, we design a phylogenetic approach for distinguishing pairs of amino acid sites that evolve concordantly, i.e., such that substitutions at one site trigger subsequent substitutions at the other; and also pairs of sites that evolve discordantly, so that substitutions at one site impede subsequent substitutions at the other. We distinguish groups of amino acid sites that undergo coordinated evolution and evolve discordantly from other such groups. In mitochondrion-encoded proteins of metazoans and fungi, we show that concordantly evolving sites are clustered in protein structures. By analysing the phylogenetic patterns of substitutions at concordantly and discordantly evolving site pairs, we find that concordant evolution has two distinct causes: epistatic interactions between amino acid substitutions and episodes of selection independently affecting substitutions at different sites. The rate of substitutions at concordantly evolving groups of protein sites changes in the course of evolution, indicating episodes of selection limited to some of the lineages. The phylogenetic positions of these changes are consistent between proteins, suggesting common selective forces underlying them. The mode and rate of evolution of a protein site depends on the effect of its mutations on protein fitness. The fitness effect of a mutation itself can change in the course of evolution for at least two reasons. First, it can be modulated by substitutions occurring at other sites, a phenomenon called epistasis. Second, changes in selection can be non-epistatic, affecting sites independently of one another. Here, we analyse substitutions accumulated by the evolving lineages of the five proteins encoded by the mitochondrial genomes of thousands of species of metazoans and fungi. We show that substitutions at different amino acid sites occur in a coordinated fashion, and this coordination is caused both by epistasis and by episodes of selection affecting groups of sites. We partition each protein into several groups of concordantly evolving sites such that evolution of sites from different groups is discordant, and show that the proteins encoded by the mitochondrial genome consist of coevolving structural blocks. Some of these blocks have a clear functional specialization, e.g. are associated with interfaces between proteins composing respiratory complexes. Together, our results reveal a previously unrecognized complexity in the causes of variation in evolutionary rates between protein sites.
Collapse
Affiliation(s)
- Alexey D. Neverov
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, Russia
- * E-mail:
| | - Anfisa V. Popova
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, Russia
| | - Gennady G. Fedonin
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, Russia
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, Moscow region, Russia
| | | | - Galya V. Klink
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
| | - Georgii A. Bazykin
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
- Skolkovo Institute of Science and Technology, Skolkovo, Russia
| |
Collapse
|
6
|
Stolyarova AV, Nabieva E, Ptushenko VV, Favorov AV, Popova AV, Neverov AD, Bazykin GA. Senescence and entrenchment in evolution of amino acid sites. Nat Commun 2020; 11:4603. [PMID: 32929079 PMCID: PMC7490271 DOI: 10.1038/s41467-020-18366-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 08/20/2020] [Indexed: 01/01/2023] Open
Abstract
Amino acid propensities at a site change in the course of protein evolution. This may happen for two reasons. Changes may be triggered by substitutions at epistatically interacting sites elsewhere in the genome. Alternatively, they may arise due to environmental changes that are external to the genome. Here, we design a framework for distinguishing between these alternatives. Using analytical modelling and simulations, we show that they cause opposite dynamics of the fitness of the allele currently occupying the site: it tends to increase with the time since its origin due to epistasis ("entrenchment"), but to decrease due to random environmental fluctuations ("senescence"). By analysing the genomes of vertebrates and insects, we show that the amino acids originating at negatively selected sites experience strong entrenchment. By contrast, the amino acids originating at positively selected sites experience senescence. We propose that senescence of the current allele is a cause of adaptive evolution.
Collapse
Affiliation(s)
- A V Stolyarova
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Skolkovo, 143028, Russia.
| | - E Nabieva
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Skolkovo, 143028, Russia
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, 127051, Russia
| | - V V Ptushenko
- Department of Photochemistry and Photobiology, N. M. Emanuel Institute of Biochemical Physics of Russian Academy of Sciences, Moscow, 119334, Russia
- A. N. Belozersky Institute of Physical-Chemical Biology, M. V. Lomonosov Moscow State University, Moscow, 119992, Russia
| | - A V Favorov
- Division of Biostatistics and Bioinformatics, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Laboratory of System Biology and Computational Genetics, Vavilov Institute of General Genetics, Moscow, 119991, Russia
| | - A V Popova
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, 111123, Russia
| | - A D Neverov
- Department of Molecular Diagnostics, Central Research Institute for Epidemiology, Moscow, 111123, Russia
| | - G A Bazykin
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Skolkovo, 143028, Russia
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, 127051, Russia
| |
Collapse
|
7
|
Burskaia V, Naumenko S, Schelkunov M, Bedulina D, Neretina T, Kondrashov A, Yampolsky L, Bazykin GA. Excessive Parallelism in Protein Evolution of Lake Baikal Amphipod Species Flock. Genome Biol Evol 2020; 12:1493-1503. [PMID: 32653919 DOI: 10.1093/gbe/evaa138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2020] [Indexed: 11/12/2022] Open
Abstract
Repeated emergence of similar adaptations is often explained by parallel evolution of underlying genes. However, evidence of parallel evolution at amino acid level is limited. When the analyzed species are highly divergent, this can be due to epistatic interactions underlying the dynamic nature of the amino acid preferences: The same amino acid substitution may have different phenotypic effects on different genetic backgrounds. Distantly related species also often inhabit radically different environments, which makes the emergence of parallel adaptations less likely. Here, we hypothesize that parallel molecular adaptations are more prevalent between closely related species. We analyze the rate of parallel evolution in genome-size sets of orthologous genes in three groups of species with widely ranging levels of divergence: 46 species of the relatively recent lake Baikal amphipod radiation, a species flock of very closely related cichlids, and a set of significantly more divergent vertebrates. Strikingly, in genes of amphipods, the rate of parallel substitutions at nonsynonymous sites exceeded that at synonymous sites, suggesting rampant selection driving parallel adaptation. At sites of parallel substitutions, the intraspecies polymorphism is low, suggesting that parallelism has been driven by positive selection and is therefore adaptive. By contrast, in cichlids, the rate of nonsynonymous parallel evolution was similar to that at synonymous sites, whereas in vertebrates, this rate was lower than that at synonymous sites, indicating that in these groups of species, parallel substitutions are mainly fixed by drift.
Collapse
Affiliation(s)
- Valentina Burskaia
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Moscow Oblast, Russia
| | - Sergey Naumenko
- Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevitch Institute), Moscow, Russia
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Mikhail Schelkunov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Moscow Oblast, Russia
- Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevitch Institute), Moscow, Russia
| | - Daria Bedulina
- Institute of Biology, Irkutsk State University, Russia
- Baikal Research Centre, Irkutsk, Russia
| | - Tatyana Neretina
- Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevitch Institute), Moscow, Russia
- N.A. Pertsov White Sea Biological Station, Lomonosov Moscow State University, Primorskiy, Russia
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Russia
| | - Alexey Kondrashov
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Russia
- Department of Ecology and Evolutionary Biology, University of Michigan
| | - Lev Yampolsky
- Department of Biological Sciences, East Tennessee State University
| | - Georgii A Bazykin
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Moscow Oblast, Russia
- Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevitch Institute), Moscow, Russia
| |
Collapse
|
8
|
Haddox HK, Dingens AS, Hilton SK, Overbaugh J, Bloom JD. Mapping mutational effects along the evolutionary landscape of HIV envelope. eLife 2018; 7:34420. [PMID: 29590010 PMCID: PMC5910023 DOI: 10.7554/elife.34420] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 03/15/2018] [Indexed: 01/04/2023] Open
Abstract
The immediate evolutionary space accessible to HIV is largely determined by how single amino acid mutations affect fitness. These mutational effects can shift as the virus evolves. However, the prevalence of such shifts in mutational effects remains unclear. Here, we quantify the effects on viral growth of all amino acid mutations to two HIV envelope (Env) proteins that differ at >100 residues. Most mutations similarly affect both Envs, but the amino acid preferences of a minority of sites have clearly shifted. These shifted sites usually prefer a specific amino acid in one Env, but tolerate many amino acids in the other. Surprisingly, shifts are only slightly enriched at sites that have substituted between the Envs—and many occur at residues that do not even contact substitutions. Therefore, long-range epistasis can unpredictably shift Env’s mutational tolerance during HIV evolution, although the amino acid preferences of most sites are conserved between moderately diverged viral strains. The virus that causes AIDS, or HIV, has a protein called Env on its surface, which is essential for the virus to infect cells. Env can also be recognized by the immune system, which then targets the virus for destruction or blocks it from infecting cells. Unfortunately, Env evolves very quickly, which means that HIV can evade our defenses. However, there are limits to how much this protein can change, since it still needs to perform its essential role in helping viruses enter cells. In the century since HIV first appeared in human populations, the virus has evolved considerably. There are now many HIV strains that infect people, and they bear Env proteins with substantially different sequences. However, it is not clear if these changes in sequence have resulted in Envs from distinct strains being able to tolerate different mutations. To examine this question, Haddox et al. compared how the Envs from two strains of HIV react to modifications in their sequences. They created all possible individual mutations in the proteins, and the resulting collections of mutated viruses were then tested for their ability to infect cells in the laboratory. Most mutations had similar effects in both Env proteins. This allowed Haddox et al. to identify portions of the protein that easily accommodate changes, and portions that must remain unchanged for viruses to remain infectious—at least in the laboratory. Some of these mutations are under different types of pressures when the virus faces the immune system, and those were identified using computational approaches. However, some mutations were tolerated differently by the two Env proteins. Therefore, viral strains differ in how their Env proteins can evolve. The parts of Env that showed differences in mutational tolerance between the strains were not necessarily the parts that differ in sequence. This shows that changes in sequence in one part of the protein can modify how other portions evolve. It remains to be determined whether changes in tolerance to mutations translate into differences in how the virus can escape immunity. This is an important question given that the rapid evolution of Env is a major obstacle to creating a vaccine for HIV.
Collapse
Affiliation(s)
- Hugh K Haddox
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, United States.,Molecular and Cellular Biology PhD program, University of Washington, Seattle, United States
| | - Adam S Dingens
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, United States.,Molecular and Cellular Biology PhD program, University of Washington, Seattle, United States
| | - Sarah K Hilton
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, United States.,Department of Genome Sciences, University of Washington, Seattle, United States
| | - Julie Overbaugh
- Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, United States.,Epidemiology Program, Fred Hutchinson Cancer Research Center, Seattle, United States
| | - Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, United States.,Department of Genome Sciences, University of Washington, Seattle, United States
| |
Collapse
|
9
|
Klink GV, Golovin AV, Bazykin GA. Substitutions into amino acids that are pathogenic in human mitochondrial proteins are more frequent in lineages closely related to human than in distant lineages. PeerJ 2017; 5:e4143. [PMID: 29250469 PMCID: PMC5731343 DOI: 10.7717/peerj.4143] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Accepted: 11/16/2017] [Indexed: 11/23/2022] Open
Abstract
Propensities for different amino acids within a protein site change in the course of evolution, so that an amino acid deleterious in a particular species may be acceptable at the same site in a different species. Here, we study the amino acid-changing variants in human mitochondrial genes, and analyze their occurrence in non-human species. We show that substitutions giving rise to such variants tend to occur in lineages closely related to human more frequently than in more distantly related lineages, indicating that a human variant is more likely to be deleterious in more distant species. Unexpectedly, substitutions giving rise to amino acids that correspond to alleles pathogenic in humans also more frequently occur in more closely related lineages. Therefore, a pathogenic variant still tends to be more acceptable in human mitochondria than a variant that may only be fit after a substantial perturbation of the protein structure.
Collapse
Affiliation(s)
- Galya V. Klink
- Sector of Molecular Evolution, Institute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, Moscow, Russian Federation
| | - Andrey V. Golovin
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Georgii A. Bazykin
- Sector of Molecular Evolution, Institute for Information Transmission Problems (Kharkevich Institute) of the Russian Academy of Sciences, Moscow, Russian Federation
- Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Skolkovo, Russian Federation
| |
Collapse
|