Limits to detecting epistasis in the fitness landscape of HIV

Abstract

The rapid evolution of HIV is constrained by interactions between mutations which affect viral fitness. In this work, we explore the role of epistasis in determining the mutational fitness landscape of HIV for multiple drug target proteins, including Protease, Reverse Transcriptase, and Integrase. Epistatic interactions between residues modulate the mutation patterns involved in drug resistance, with unambiguous signatures of epistasis best seen in the comparison of the Potts model predicted and experimental HIV sequence “prevalences” expressed as higher-order marginals (beyond triplets) of the sequence probability distribution. In contrast, experimental measures of fitness such as viral replicative capacities generally probe fitness effects of point mutations in a single background, providing weak evidence for epistasis in viral systems. The detectable effects of epistasis are obscured by higher evolutionary conservation at sites. While double mutant cycles in principle, provide one of the best ways to probe epistatic interactions experimentally without reference to a particular background, we show that the analysis is complicated by the small dynamic range of measurements. Overall, we show that global pairwise interaction Potts models are necessary for predicting the mutational landscape of viral proteins.

Mechanisms of HIV-1 Integrase Resistance to Dolutegravir and Potent Inhibition of Drug Resistant Variants

“…The Potts statistical energy models probe the underlying relationships between protein structure, function, and fitness and, here, they are used to provide insights into the coupled nature of the effects of primary and compensatory residue pairs (see Supplementary Note 1). For a more detailed description of the Potts model in protein biophysics, we refer the reader to references (52)(53)(54)(55)(56), and for applications of the Potts model to HIV including description of data processing and model inference to references (38,42,43,(57)(58)(59)(60).…”

Mechanisms of HIV-1 integrase resistance to dolutegravir and potent inhibition of drug-resistant variants

“…The Potts statistical energy models probe the underlying relationships between protein structure, function, and fitness, and here, they are used to provide insights into the coupled nature of the effects of primary and compensatory residue pairs (see note S1). For a more detailed description of the Potts model in protein biophysics, we refer the reader to (53)(54)(55)(56)(57) and, for applications of the Potts model to HIV including description of data processing and model inference, to (39,43,44,(58)(59)(60)(61).…”

Emergence of functional information from multivariate correlations

“…However, each sequence is also a pattern, so it should be possible in principle to relate the individual pattern in the sequence to its function. Indeed, methods of this sort have been developed before: they use sophisticated techniques to link the patterns to function, either by regression [16,17] or by using a multiplesequence alignment (MSA) to train a probabilistic model (usually called 'Potts' or 'Ising' model) [18][19][20][21].…”