Mutagenesis provides insight into proteins, but only recently have assays that couple genotype to phenotype been used to assess the activities of as many as 1 million mutant versions of a protein in a single experiment. This approach-'deep mutational scanning'-yields large-scale data sets that can reveal intrinsic protein properties, protein behavior within cells and the consequences of human genetic variation. Deep mutational scanning is transforming the study of proteins, but many challenges must be tackled for it to fulfill its promise.

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Deep mutational scanning: a new style of protein science

A central topic in biology concerns how genotypes determine phenotypes and functions of organisms that affect their evolutionary fitness. This Review discusses recent advances in the development of empirical fitness landscapes and their contribution to theoretical analyses of the predictability of evolution. The genotype–fitness map (that is, the fitness landscape) is a key determinant of evolution, yet it has mostly been used as a superficial metaphor because we know little about its structure. This is now changing, as real fitness landscapes are being analysed by constructing genotypes with all possible combinations of small sets of mutations observed in phylogenies or in evolution experiments. In turn, these first glimpses of empirical fitness landscapes inspire theoretical analyses of the predictability of evolution. Here, we review these recent empirical and theoretical developments, identify methodological issues and organizing principles, and discuss possibilities to develop more realistic fitness landscape models.

Empirical fitness landscapes and the predictability of evolution

https://www.cell.com/trends/genetics/pdf/S0168-9525(11)00077-1.pdf

Molecular mechanisms of epistasis within and between genes

Why some individuals develop AIDS rapidly whereas others remain healthy without treatment for many years remains a central question of HIV research. An evolutionary perspective reveals an apparent conflict between two levels of selection on the virus. On the one hand, there is rapid evolution of the virus in the host, and on the other, new observations indicate the existence of virus factors that affect the virulence of infection whose influence persists over years in infected individuals and across transmission events. Here, we review recent evidence that shows that viral genetic factors play a larger role in modulating disease severity than anticipated. We propose conceptual models that reconcile adaptive evolution at both levels of selection. Evolutionary analysis provides new insight into HIV pathogenesis.

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Virulence and pathogenesis of HIV-1 infection: an evolutionary perspective.

Many microbial populations rapidly adapt to changing environments with multiple variants competing for survival. To quantify such complex evolutionary dynamics in vivo, time resolved and genome wide data including rare variants are essential. We performed whole-genome deep sequencing of HIV-1 populations in 9 untreated patients, with 6-12 longitudinal samples per patient spanning 5-8 years of infection. The data can be accessed and explored via an interactive web application. We show that patterns of minor diversity are reproducible between patients and mirror global HIV-1 diversity, suggesting a universal landscape of fitness costs that control diversity. Reversions towards the ancestral HIV-1 sequence are observed throughout infection and account for almost one third of all sequence changes. Reversion rates depend strongly on conservation. Frequent recombination limits linkage disequilibrium to about 100 bp in most of the genome, but strong hitch-hiking due to short range linkage limits diversity.

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Population genomics of intrapatient HIV-1 evolution

The development of a quantitative understanding of viral evolution and the fitness landscape in HIV-1 drug resistance is a formidable challenge given the large number of available drugs and drug resistance mutations. We analyzed a dataset measuring the in vitro fitness of 70,081 virus samples isolated from HIV-1 subtype B infected individuals undergoing routine drug resistance testing. We assayed virus samples for in vitro replicative capacity in the absence of drugs as well as in the presence of 15 individual drugs. We employed a generalized kernel ridge regression to estimate main fitness effects and epistatic interactions of 1,859 single amino acid variants found within the HIV-1 protease and reverse transcriptase sequences. Models including epistatic interactions predict an average of 54.8% of the variance in replicative capacity across the 16 different environments and substantially outperform models based on main fitness effects only. We find that the fitness landscape of HIV-1 protease and reverse transcriptase is characterized by strong epistasis.

A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase.

Principal component analysis of general patterns of HIV-1 replicative fitness in different drug environments

Background The Swiss National Science Foundation (SNSF) supports fundamental and use-inspired research in all disciplines. Peer reviewers assess the proposals submitted to the SNSF. We examined whether the gender of applicants and reviewers and other factors influenced the summary scores awarded.
 Methods We analysed 38,250 reports on 12,294 grant applications across all disciplines 2006 to 2016. Proposals were rated on a scale from 1 (=worst) to 6 (=best) by 26,836 reviewers. We used linear mixed effects regression models adjusted for research topic, applicant's age, nationality, affiliation and calendar period to examine associations, and interactions between gender of the applicant and other variables.
 Results In univariable analysis, male applicants received more favourable evaluation scores than female applicants (+0.19 points; 95% CI 0.14-0.23), and male reviewers awarded higher scores than female reviewers (+0.12; 95% CI 0.08-0.15). Applicant-nominated reviewers awarded higher scores than reviewers nominated by the SNSF (+0.53; 95% CI 0.50-0.56), and reviewers affiliated with research institutions outside of Switzerland more favourable scores than reviewers affiliated with Swiss institutions (+0.53; 95% CI 0.49-0.56). In multivariable analysis, differences between male and female applicants were attenuated (to +0.08; 95% CI 0.04-0.13) whereas results changed little for source of nomination and affiliation of reviewers. There was an interaction between gender of applicant and reviewer, and between gender of applicant and calendar period. Male reviewers gave higher scores than female reviewers, with a greater difference for male than for female applicants (P=0.037 from test of interaction). The gender difference increased after September 2011, when new evaluation forms were introduced (P=0.033 from test of interaction).
 Conclusions Our study showed that peer review of grant applications at SNSF might be prone to biases stemming from different applicant and reviewer characteristics. The SNSF abandoned the nomination of peer reviewers by applicants, and made members of panels aware of the other systematic differences in scores. The new form introduced in 2011 may inadvertently have given more emphasis to the applicant’s track record, and a revision is now under discussion. We encourage other funders to conduct similar studies, in order to improve the evidence base for rational and fair research funding.

Gender and other potential biases in peer review: Analysis of 38,250 external peer review reports

Potential bias in peer review of grant applications at the Swiss National Science Foundation

One of the aims of systems biology is to decode genetic sequences in terms of biological activity and phenotypic expression. In particular, to describe evolutionary processes, it is important to characterize the fitness of organisms as a function of the genetic space they can explore. In other words, it is important to characterize the fitness landscape on which evolution takes place. Many theoretical studies in evolutionary biology have assumed simplistic fitness functions to be able to study the evolutionary process. This thesis however, explores and describes a fitness landscape based on real invitro fitness of HIV experimental data. Background knowledge about the data is presented in chapter 1. In addition, this chapter also introduces two individual mutation-based models of the fitness landscape used in chapters 2 and 3. One, the main effects (ME) model, includes the estimates of the fitness effects of individual amino acid variants; whereas the other, the main and epistatic effects (MEEP) model, also accommodates the estimates of the pairwise epistatic interactions. The details of the fitting and the performance of the models are presented in the appendix A. Most importantly, the two individual mutation-based models of the fitness landscape are a great tool to investigate the roles of epistasis and pleiotropy. Chapter 2 explores three complementary visual representations of the fitness landscape. One provides a polynomial surface fitting of the experimental fitness values of the viral sequences, represented by points in a plane and placed such that the information about the number of amino acid mutations between the sequences is maximally conserved. The second representation renders the fitness landscape as a network where edges link neighboring sequences and the size of the nodes accounts for fitness. The third representation uses the MEEP model to generate a three dimensional fitness surface based on a grid of 1-mutation neighboring sequences incorporating the most frequent individual mutations. All three representations indicate a high level of local ruggedness and support Kauffman’s massif central hypothesis which states that high fitness genotypes tend to be close to each other. Most importantly, they show that low-dimensional fitness maps can still capture important features of complex fitness landscapes. Chapter 3 uses the ME and the MEEP fitness landscape models to simulate the evolution of HIV populations and study the maintenance of genetic recombination, one of the most intriguing problems of evolutionary biology. On the basis of simplistic models of fitness landscapes, it has been shown that the interaction between genetic drift and natural selection favors recombination independent of epistatic interactions. The ME and the MEEP

/pdf/the-exploration-of-hiv-fitness-landscapes-14mwcw8v2t.pdf

João Martins

Papers

A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase.

Principal component analysis of general patterns of HIV-1 replicative fitness in different drug environments

Gender and other potential biases in peer review: Analysis of 38,250 external peer review reports

Potential bias in peer review of grant applications at the Swiss National Science Foundation

The exploration of HIV fitness landscapes