The human immuno-deficiency virus sub-type 1 (HIV-1) is evolving to keep up with a changing fitness landscape, due to the various drugs introduced to stop the virus's replication. As the virus adapts, the information the virus encodes about its environment must change, and this change is reflected in the amino-acid composition of proteins, as well as changes in viral RNAs, binding sites, and splice sites. Information can also be encoded in the interaction between residues in a single protein as well as across proteins, leading to a change in the epistatic patterns that can affect how the virus can change in the future. Measuring epistasis usually requires fitness measurements that are difficult to obtain in high-throughput . Here we show that epistasis can be inferred from the pair-wise information between residues, and study how epistasis and information have changed over the long-term. Using HIV-1 protease sequence data from public databases covering the years 1998-2006 (from both treated and untreated subjects), we show that drug treatment has increased the protease's per-site entropies on average. At the same time, the sum of mutual entropies across all pairs of residues within the protease shows a significant increase over the years, indicating an increase in epistasis in response to treatment, a trend not seen within sequences from untreated subjects. Our findings suggest that information theory can be an important tool to study long-term trends in the evolution of macromolecules.
Epistatic interactions between residues in a protein determine its adaptability as well the shape of its evolutionary trajectory. While several studies have shown that strong selection pressures enrich epistatic interactions in an evolving protein, little is known about how epistatic interactions themselves change over time when selection pressures are not constant. Obtaining fitness data to measure epistasis in a protein over significant and evolutionarily relevant time scales is a daunting task, rendering a study of the long-term evolution of epistasis in a protein currently infeasible . Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using genomic sequences collected for almost a decade from treated and untreated patients, to understand how proteins adapt to a changing environment of treatment over time. We show that mutual information between pairs of residues is a necessary (but not sufficient) condition for epistasis, allowing us to use information as a proxy for epistasis. We analyze the "fossils" of the evolutionary trajectories of a protein contained in the sequence data, and show that epistatic interactions continue to enrich in the HIV-1 protease as more potent drugs enter the market. While initially epistatic interactions are likely to constrain the evolvability of a protein, we find no evidence that the HIV-1 protease has reached its potential for adaptation after 9 years of adapting to a changing drug environment. The protein is able to encode information about novel and more potent drugs using epistatic interactions, while maintaining sufficient diversity and thermostability. We propose that this mechanism is central to protein evolution not just in HIV-1 protease, but for any protein adapting to rapidly changing conditions
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The human immuno-deficiency virus sub-type 1 (HIV-1) is evolving to keep up with a changing fitness landscape, due to the various drugs introduced to stop the virus's replication. As the virus adapts, the information the virus encodes about its environment must change, and this change is reflected in the amino-acid composition of proteins, as well as changes in viral RNAs, binding sites, and splice sites. Information can also be encoded in the interaction
Epistatic interactions
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single protein as well as across proteins, leading to a change in the epistatic patterns that can affect how the virus can change in the future. Measuring epistasis usually requires fitness measurements that are difficult to obtain in high-throughput
protein determine its adaptability as well the shape of its evolutionary trajectory. While several studies have shown that strong selection pressures enrich epistatic interactions in an evolving protein, little is known about how epistatic interactions themselves change over time when selection pressures are not constant. Obtaining fitness data to measure epistasis in a protein over significant and evolutionarily relevant time scales is a daunting task, rendering a study of the long-term evolution of epistasis in a protein currently infeasible
R
show that epistasis can be inferred from the pair-wise information between residues, and study how epistasis and information have changed over the long-term. Using HIV-1 protease sequence data from public databases covering the years 1998-2006 (from both
analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using genomic sequences collected for almost a decade from
R
subjects), we show that drug treatment has increased the protease's per-site entropies on average. At the same time, the sum of mutual entropies across all
patients, to understand how proteins adapt to a changing environment of treatment over time. We show that mutual information between
R
within the protease shows a significant increase over the years, indicating an increase in epistasis in response to treatment, a trend not seen within sequences from untreated subjects. Our findings suggest that information theory can be an important tool to study long-term trends in the evolution of macromolecules.
is a necessary (but not sufficient) condition for epistasis, allowing us to use information as a proxy for epistasis. We analyze the "fossils" of the evolutionary trajectories of a protein contained in the sequence data, and show that epistatic interactions continue to enrich in the HIV-1 protease as more potent drugs enter the market. While initially epistatic interactions are likely to constrain the evolvability of a protein, we find no evidence that the HIV-1 protease has reached its potential for adaptation after 9 years of adapting to a changing drug environment. The protein is able to encode information about novel and more potent drugs using epistatic interactions, while maintaining sufficient diversity and thermostability. We propose that this mechanism is central to protein evolution not just in HIV-1 protease, but for any protein adapting to rapidly changing conditions