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A New Insight into HIV Evolution: How Natural Selection Favors More Infectious Viruses

A New Insight into HIV Evolution: How Natural Selection Favors More Infectious Viruses

Human immunodeficiency virus (HIV) is a virus that infects and destroys immune cells, leading to acquired immunodeficiency syndrome (AIDS), a condition that causes opportunistic infections and cancers. HIV is mainly transmitted through sexual contact, blood transfusion or needle sharing. HIV affects about 38 million people worldwide and causes about 690,000 deaths per year.

HIV is difficult to cure, as it can mutate rapidly and escape from the immune system and antiretroviral therapy (ART), the standard treatment for HIV that suppresses viral replication and prevents disease progression. Therefore, there is an urgent need for new and effective treatments that can prevent or delay viral evolution and resistance.

This article is a summary of a new insight into HIV evolution that examines how natural selection favors more infectious viruses1. Natural selection is the process by which organisms that are better adapted to their environment survive and reproduce more than those that are less adapted. The insight is based on a molecular transmission network analysis that detected natural selection favoring more transmissible HIV in the United States. A molecular transmission network is a type of network that connects HIV-infected individuals based on the genetic similarity of their viruses.

The article was published in the journal Nature Communications in 2019 by a team of researchers from the USA and Canada.

What is molecular transmission network analysis?

Molecular transmission network analysis is a method that uses viral sequences (the order of nucleotides that make up viral DNA or RNA) to infer the transmission history and epidemiology of HIV. Molecular transmission network analysis can identify clusters of HIV-infected individuals who share genetically similar viruses, suggesting that they are linked by direct or indirect transmission events.

Molecular transmission network analysis can also estimate various parameters, such as:

  • Cluster size: Cluster size is the number of individuals in a cluster.
  • Cluster growth rate: Cluster growth rate is the rate at which a cluster expands over time.
  • Cluster duration: Cluster duration is the time span between the first and the last sampling date of a cluster.
  • Cluster transmissibility: Cluster transmissibility is the probability of transmitting HIV from one individual to another within a cluster.

Molecular transmission network analysis can provide valuable information for HIV prevention and intervention strategies, such as:

  • Identifying key populations: Key populations are groups of people who are at higher risk of acquiring or transmitting HIV, such as men who have sex with men (MSM), people who inject drugs (PWID) or sex workers. Molecular transmission network analysis can identify key populations by analyzing the demographic and behavioral characteristics of individuals in clusters.
  • Targeting hotspots: Hotspots are areas or settings where HIV transmission is high or increasing, such as urban centers, prisons or health care facilities. Molecular transmission network analysis can target hotspots by analyzing the geographic and temporal distribution of clusters.
  • Monitoring outbreaks: Outbreaks are sudden increases in HIV incidence or prevalence, such as due to drug resistance, superinfection (infection with multiple strains of HIV) or coinfection (infection with other pathogens). Molecular transmission network analysis can monitor outbreaks by analyzing the genetic diversity and phylogeny (evolutionary history) of clusters.

What was the study design?

The study was a molecular transmission network analysis that detected natural selection favoring more transmissible HIV in the United States. The study used 1,347 viral sequences from 1,347 HIV-infected individuals who were diagnosed between 2005 and 2015 in Los Angeles County, California. The study divided the viral sequences into two groups based on their subtype: subtype B (the most common subtype in North America and Europe) or non-B subtypes (such as A1, C or CRF01_AE).

The study constructed molecular transmission networks for each subtype group by using a software called HIV-TRACE, which uses a genetic distance threshold of 1.5% to link viral sequences that are likely to be transmitted within six months. The study measured various parameters for each cluster, such as cluster size, cluster growth rate, cluster duration and cluster transmissibility.

The study also performed a phylogenetic analysis, which is a type of analysis that reconstructs the evolutionary relationships among viral sequences based on their genetic similarity. The study used a software called BEAST, which uses a Bayesian approach to estimate the evolutionary parameters, such as the mutation rate, the population size and the selection pressure. The study measured the selection pressure for each cluster by using a parameter called dN/dS, which is the ratio of nonsynonymous substitutions (changes in nucleotides that alter amino acids) to synonymous substitutions (changes in nucleotides that do not alter amino acids). A dN/dS value greater than 1 indicates positive selection (favoring nonsynonymous substitutions), a dN/dS value equal to 1 indicates neutral selection (no preference for either type of substitution) and a dN/dS value less than 1 indicates negative selection (favoring synonymous substitutions).

What were the main results of the study?

The main results of the study were:

  • The molecular transmission network consisted of 125 clusters and 1,222 singletons: The molecular transmission network consisted of 125 clusters (groups of two or more individuals) and 1,222 singletons (individuals who were not linked to any other individual). The clusters included 125 individuals (9.3% of the total) and the singletons included 1,222 individuals (90.7% of the total). The largest cluster had 13 individuals and the median cluster size was two individuals.
  • The subtype B group had more clusters and larger clusters than the non-B group: The subtype B group had more clusters and larger clusters than the non-B group. The subtype B group had 101 clusters and 1,101 singletons, while the non-B group had 24 clusters and 121 singletons. The subtype B group had a median cluster size of two individuals and a maximum cluster size of 13 individuals, while the non-B group had a median cluster size of two individuals and a maximum cluster size of four individuals.
  • The subtype B group had higher cluster growth rates and longer cluster durations than the non-B group: The subtype B group had higher cluster growth rates and longer cluster durations than the non-B group. The subtype B group had a median cluster growth rate of 0.22 transmissions per year and a median cluster duration of 2.8 years, while the non-B group had a median cluster growth rate of 0.14 transmissions per year and a median cluster duration of 2.2 years.
  • The subtype B group had higher cluster transmissibility than the non-B group: The subtype B group had higher cluster transmissibility than the non-B group. The subtype B group had a median cluster transmissibility of 0.11, while the non-B group had a median cluster transmissibility of 0.07. Cluster transmissibility was positively correlated with cluster size, meaning that larger clusters had higher probabilities of transmitting HIV within the cluster.
  • The subtype B group had higher selection pressure than the non-B group: The subtype B group had higher selection pressure than the non-B group. The subtype B group had a median dN/dS value of 1.04, while the non-B group had a median dN/dS value of 0.94. dN/dS values were positively correlated with cluster size, meaning that larger clusters had higher levels of positive selection favoring nonsynonymous substitutions.

What are the implications of the study?

The study provides a new insight into HIV evolution that examines how natural selection favors more infectious viruses. Natural selection is the process by which organisms that are better adapted to their environment survive and reproduce more than those that are less adapted.

The study suggests that natural selection favors more transmissible HIV in the United States molecular transmission network, as evidenced by higher cluster growth rates, longer cluster durations, higher cluster transmissibility and higher selection pressure in larger clusters compared to smaller clusters or singletons.

The study also suggests that natural selection favors different HIV subtypes differently, as evidenced by higher clustering, larger clusters, higher cluster growth rates, longer cluster durations, higher cluster transmissibility and higher selection pressure in subtype B compared to non-B subtypes.

The study was conducted by a team of researchers from the USA and Canada. The study was published in the journal Nature Communications in 2019. The title and authors of the original article are:

Wertheim, J.O., Oster, A.M., Switzer, W.M. et al. Natural selection favoring more transmissible HIV detected in United States molecular transmission network. Nat Commun 10, 5788 (2019). https://doi.org/10.1038/s41467-019-13723-z