Scale bar indicates number of substitutions. A cluster is defined by nodes with a posterior probability of 1. Letters indicate the six largest clusters phylogenetically defined. Cluster G seven individuals included one female and one injection drug user. Thus, the clustering identified in this study reflects the epidemiology of HIV transmission by sexual contact among MSM. Clusters A—E and H, comprising 88 patients in all, were selected for further analysis on an individual basis using phylogenetic methods incorporating a relaxed molecular clock the other clusters were not large enough for this analysis.
For each cluster, an exponential model of population growth was significantly favoured over a constant population size data not shown. Substitution rates at third-base positions vary nearly 3-fold among clusters Figure S1 , but the differences are not significant. The coefficient of variation in substitution rate was 0. Each of the clusters reveals some degree of internal structure, particularly the two largest clusters, A and B. In these it can be seen that there are two subclades in cluster A comprising sequences that are much more closely related to each other than they are to those of the other.
Time-scaled phylogenies were generated using the partitioned SRD06 model. B Terminal branches removed with scale in calendar years to show timing of transmission events. It is important to know whether the structure of the transmission network has influenced the transmission of drug-resistant virus. We have identified all patient samples with resistance-associated mutations in the six clusters by coloured circles at the tips Figure 5 A. In one case in cluster A and a second in cluster E, two patients who were nearest neighbours in the phylogeny both had resistance-associated mutations.
However, the mutations are either entirely cluster A or substantially cluster E different in the patient pairs Figure S3 , so there is no clear evidence of transmission of drug resistance in any of these clusters. Each viral sequence in the time-scaled phylogenies represents a different patient. Therefore, for any two sequences, the branches connecting them through their most recent common ancestor MRCA include at least one transmission event.
Consequently, the distance between the MRCA and the previous node estimates the upper bound of time between transmission events. Figure 5 B shows the structure of the time-dated phylogenies with tips removed, revealing the variation in internode distances.
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This representation is scaled by calendar year, from which we can infer the periods over which these clustered transmissions occurred. For clusters A and E this spans much of the s, from to , while the transmissions that link cluster B occurred earlier in the decade, up to Most transmissions in the remaining clusters C, D, and H occurred in the latter part of the decade. As expected, these are always narrowest for the most recent nodes and become much shallower as the time between the node and the dated samples increases. It is very likely that not all members of any transmission cluster have been sampled, so the average time between transmissions will almost certainly be overestimated.
Median branch length was We have made use of sequence data obtained for resistance genotyping for the largest clinical centre treating patients with HIV in London to reconstruct the transmission network in this population. New HIV diagnoses among MSM have risen steadily in the United Kingdom for almost 10 years, and are now approaching twice the number recorded annually in the mid to late s [ 32 ]. Efforts to characterize the changes in this population that have been responsible, including the National Survey of Sexual Attitudes and Lifestyles NATSAL; [ 33 ] , have provided substantial amounts of information on current risk behaviour of this population.
There was also a notable and significant increase in prevalence of risk activities between the and NATSAL surveys [ 36 ]. We have used a database of HIV sequences collected in the course of routine clinical treatment from 2, patients to characterize the relationships between viruses infecting different individuals attending a large clinic in London.
The depth of sampling meant this study was much more informative about the transmission patterns than previous studies [ 15 ].
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We identified individuals whose virus had a close relationship with at least one other, and using two different approaches showed that almost 90 of these individuals could be linked in clusters of 10 or more individuals. The tightness of clustering is striking, with most of the linked transmissions occurring within periods of at most 3—4 y. The closeness of these events is inevitably underestimated as a result of incomplete data i.
Extrapolation of the conclusions from this clinic population more widely depends on the degree to which patients attending the Chelsea and Westminster clinic reflect the UK MSM population with HIV as a whole. While the location of its primary catchment area within central London suggested it would be likely to be representative, we have recently been able to extend these studies to the entire UK CHIC patient population. Preliminary analysis of HIV genotypes from 8, patients that have been investigated for clustering using the genetic distance approach revealed 2, individuals with a link to at least one other patient.
Among these, several large clusters have been observed, with Chelsea and Westminster patients distributed among patients from other clinics data not shown. Other possible limitations of the study should be recognised. Although the use of a phylogenetic definition of clusters avoids the necessity to select an arbitrary distance value, there are clear restrictions on what can be concluded from the phylogeny.
The similarity between many of the sequences within these clusters is frequently so high that there is little power to estimate the internal order of transmissions with any confidence. Neither is it possible, from the phylogeny alone, to determine direction of transmission, or how many individuals in the cluster were transmitters.
Thus, cluster E Figure 5 could have been generated by transmissions from a minimum of three individuals transmitting to six, one, and two others, respectively; or alternatively, from a maximum of seven, where one transmits to three others and all others transmit once. The former situation would be expected under a more skewed distribution of partner numbers, which has been suggested by several studies [ 8 , 33 , 34 , 38 ].
These results therefore complement rather than replace studies that would define parameters such as partner number. One of the possible consequences of rapid transmission within clusters is a local increase in the transmission of drug-resistant strains [ 39 , 40 ]. Whether this had occurred was examined by maximum likelihood reconstruction of ancestral states at all sites associated with drug resistance in the six large clusters.
In no case was a drug-resistant virus identified at the root of these clusters unpublished data , which may have reflected the time at which these particular events were occurring Figure 5 B. The distribution of mutations at the tips of the trees also do not suggest extensive transmission of resistance-associated mutations.
There were only two cases where nearest-neighbour patients both had mutations, and the mutations differed between the pair in each case, suggesting they were all examples of secondary rather than primary resistance. As the time-dependent phylogenies are calibrated in calendar years, we are able to estimate when most of the transmissions in each cluster occurred. For cluster A, the largest cluster comprising 30 individuals, most of the transmissions between them occurred within about 6 y preceding Figure 5 B ; for cluster C, the transmissions were tightly restricted to —, with many estimated to have occurred in ; for cluster B, however, the transmissions mostly occurred between and Many of the transmission intervals with the exception of cluster B lie within or closely precede the period during which HIV diagnoses have been increasing.
Given an expected delay from infection to diagnosis of 3—5 y, we could infer that these clustered transmissions contributed to the increase in prevalence that occurred in London and the United Kingdom in that time [ 32 ]. From these results we can also say that many of these transmission clusters were initiated relatively early in the highly active antiretroviral therapy HAART era and before transmitted ARV resistance became a significant problem in the UK [ 40 ].
As epidemiological models become increasingly complex, incorporating variable mixing patterns [ 41 ], quantitative data on the transmission network structure and the dynamics of transmission will be vital to ensure appropriate parameterization. The level of epidemiologically relevant information yielded by the time-dated phylogeny with respect to the structure and dynamics of the HIV transmission network in this population represents a substantial increase in our depth of knowledge on which interventions can be based.
BEAST analysis is based on a summary of a large number of phylogenetic trees where individual trees may have a slightly different topology depending on the degree of support for the existence of each node. To indicate support for an estimated node date, it is possible to estimate the marginal distribution of TMRCA for all taxa that are found within below each node of the maximum clade credibility tree.
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For each node within each cluster tree, the distribution of the TMRCA was calculated from the same tree sample used to produce the trees. Numbers of analyzed samples where patient had been receiving ARV before sample was taken, by year. Average difference between 1, subtype B sequences and proportion of polymorphic sites. Numbers of resistance-associated mutations observed in each cluster according to coding region and in total.
We are very grateful to Esther Fearnhill and Dr. Sergei Kosakovsky Pond for his assistance with the analysis in the early stages of this work; and to Dr. Simon Frost for discussions. GJH analyzed the data and prepared the results for publication. ALP recruited study subjects and supervised clinical care. All authors contributed to writing the paper. Abstract Background The structure of sexual contact networks plays a key role in the epidemiology of sexually transmitted infections, and their reconstruction from interview data has provided valuable insights into the spread of infection.
Methods and Findings Sequences of the protease and reverse transcriptase coding regions from 2, patients, predominantly MSM, from London were compared: of these showed a close match to at least one other subtype B sequence. Conclusions Reconstruction of the HIV transmission network using a dated phylogeny approach has revealed the HIV epidemic among MSM in London to have been episodic, with evidence of multiple clusters of transmissions dating to the late s, a period when HIV prevalence is known to have doubled in this population. Editors' Summary Background.
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Why Was This Study Done? What Did the Researchers Do and Find? What Do These Findings Mean? Additional Information. Introduction Sexually transmitted infections spread through an often complex network of sexual contacts [ 1 ]. Methods Dataset Our base dataset comprised 2, anonymised HIV-1 nucleotide sequences concatenated full-length protease [PR] and partial reverse transcriptase [RT] coding sequences, 1, nucleotides in length from patients attending HIV clinics at the Chelsea and Westminster Hospital, London, during the period — Identification of Transmission Clusters In order to remove the influence of convergent evolution at antiretroviral drug resistance mutations on the phylogenetic analysis, two versions of the dataset were analyzed: i third-base positions only for analyses of exact and exact plus ambiguous differences; sites and ii a codon-stripped dataset from which 37 codons associated with major resistance in PR 30, 32, 33, 46, 47, 48, 50, 54, 76, 82, 84, 88, and 90 and RT 41, 62, 65, 67, 69, 70, 74, 75, 77, , , , , , , , , , , , , , , , and were stripped from the alignment leaving 1, nt.
Ancestral State Reconstruction The ancestral state of amino acids for each cluster group was determined using MrBayes. Download: PPT. Figure 1. Epidemiological and Phylogenetic Structure of the Transmission Network In order to identify patterns of transmission among the subtype B sequences, two complementary approaches were adopted.
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Figure 2. Figure 3. Figure 4. Detailed Phylogenies of Clusters Clusters A—E and H, comprising 88 patients in all, were selected for further analysis on an individual basis using phylogenetic methods incorporating a relaxed molecular clock the other clusters were not large enough for this analysis. Figure 5.
Distribution of ARV Resistance—Associated Mutations It is important to know whether the structure of the transmission network has influenced the transmission of drug-resistant virus.
Background
Dating Transmission Events Each viral sequence in the time-scaled phylogenies represents a different patient. Figure 6. Discussion We have made use of sequence data obtained for resistance genotyping for the largest clinical centre treating patients with HIV in London to reconstruct the transmission network in this population. Supporting Information. Figure S1. Figure S2. Figure S3. Figure S4. Dated Phylogenies with Marginal Distributions for TMRCAs BEAST analysis is based on a summary of a large number of phylogenetic trees where individual trees may have a slightly different topology depending on the degree of support for the existence of each node.
Table S1. Table S2. Table S3. Details of Resistance Mutations Detected Within Clusters Numbers of resistance-associated mutations observed in each cluster according to coding region and in total. Acknowledgments We are very grateful to Esther Fearnhill and Dr. References 1.
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