Rapid intrahost evolution of human cytomegalovirus is shaped by demography and positive selection

Abstract

Populations of human cytomegalovirus (HCMV), a large DNA virus, are highly polymorphic in patient samples, which may allow for rapid evolution within human hosts. To understand HCMV evolution, longitudinally sampled genomic populations from the urine and plasma of 5 infants with symptomatic congenital HCMV infection were analyzed. Temporal and compartmental variability of viral populations were quantified using high throughput sequencing and population genetics approaches. HCMV populations were generally stable over time, with ~88% of SNPs displaying similar frequencies. However, samples collected from plasma and urine of the same patient at the same time were highly differentiated with approximately 1700 consensus sequence SNPs (1.2% of the genome) identified between compartments. This inter-compartment differentiation was comparable to the differentiation observed in unrelated hosts. Models of demography (i.e., changes in population size and structure) and positive selection were evaluated to explain the observed patterns of variation. Evidence for strong bottlenecks (>90% reduction in viral population size) was consistent among all patients. From the timing of the bottlenecks, we conclude that fetal infection occurred between 13-18 weeks gestational age in patients analyzed, while colonization of the urine compartment followed roughly 2 months later. The timing of these bottlenecks is consistent with the clinical histories of congenital HCMV infections. We next inferred that positive selection plays a small but measurable role in viral evolution within a single compartment. However, positive selection appears to be a strong and pervasive driver of evolution associated with compartmentalization, affecting ≥ 34 of the 167 open reading frames (~20%) of the genome. This work offers the most detailed map of HCMV in vivo evolution to date and provides evidence that viral populations can be stable or rapidly differentiate, depending on host environment. The application of population genetic methods to these data provides clinically useful information, such as the timing of infection and compartment colonization.

Figure 1. HCMV population diversity is correlated with host compartment.

Box and whisker plots of the nucleotide diversity of HCMV populations sampled from the urine and plasma compartments. The boxes mark the interquartile values and the whiskers show the minimum and maximum values. The distributions are significantly different (P = 0.046, Mann-Whitney U, denoted by *), with urine populations exhibiting lower diversity values than plasma populations.

Figure 2. HCMV populations show patterns of both stability and differentiation.

Host-matched specimens were paired either across time or compartments. The frequency of SNPs was tracked across the pairings. The trajectories show that HCMV populations can be stable, with the majority of SNPs remaining at nearly the same frequencies over time. A minority of SNPs rapidly change frequencies during the course of sampling, which is most apparent in panels C and G. Panels A–D: trajectories of all SNPs in the populations. Panels E–H: trajectories of only the consensus sequence SNPs identified between the pairings. Panels A and E: B103 longitudinal urine populations. Panels B and F: B103 longitudinal plasma populations. Panels C and G: B103 one week plasma and urine populations. Panels D and H: MS1 longitudinal urine populations. See supplemental Figure 2 for a complete representation of all pairings used in this study.

Figure 3. HCMV populations are highly differentiated across compartments.

High throughput sequence data was generated on HCMV populations collected from 5 infants from either the urine or plasma compartment or both compartments (patient B103). Panel A: Consensus sequences were generated from the population data of each sample and maximum likelihood phylogenetic trees were constructed from whole genome alignments. Sequences longitudinally sampled from the same compartment of the same host clustered together. In contrast, B103 sequences sampled from the urine and plasma at the same time were highly differentiated and clustered more closely with sequences from other hosts. Intriguingly, plasma sequences from two hosts appeared (M103 and B103) to form a single clade, a result consistent with convergent evolution acting on plasma populations. Node labels represent bootstrap values from 100 replicates and the tree was rooted with the HCMV reference sequence (Strain Merlin, Ref Seq ID: NC_006273). Panel B: Population differentiation between the populations was measured by estimating the summary statistic F_ST for the specimen pairings. Higher values of F_ST indicate higher levels of population differentiation. HCMV populations are relatively stable across time when measuring populations collected from the same compartment of a single host or between monozygotic, monochorionic twins (MS1 and MS2). B103 populations sampled from different compartments at a single timepoint showed elevated F_ST values, indicative of higher levels of population differentiation. The level of differentiation observed between compartments in a single patient is comparable to that observed between populations collected from unrelated patients. Error bars represent 95% confidence intervals. ANOVA analysis: P = 6.7×10⁻¹³.

Figure 4. Demographic histories of HCMV clinical isolates show evidence of bottlenecks and expansions.

The demographic histories of the viral populations were inferred from the high throughput sequence data. In the models, time increases from left to right and the width of the various shapes is proportional to the size of the viral populations. All population sizes and timespans are drawn to scale. A tabular representation of parameter values of the model can be found in Table S2. See the text for a complete discussion of the models. Panel A: Model of B103 sampled population histories. (The populations within the urine compartment of B103 are drawn to 1∶8 scale [as compared to the B103 plasma compartment] for the sake of clarity.) Panel B: Model of B101 sampled population histories. Panel C: Model of M103 sampled population histories. Panel D: Model of MS1 and MS2 sampled population histories Panel E: Expansion of early timepoints of MS1 and MS2 model. Arrows drawn between populations (Panels A and D) represent migration rates and are scaled relative to each other and not population sizes to improve visibility of the arrows.

Figure 5. Positive selection plays a variable role in HCMV in vivo evolution.

The population branch statistic (PBS) was used to identify putative targets of positive selection within the HCMV viral populations collected from congenitally infected infants. Higher PBS values identify loci that have a higher likelihood of being targets of postive selection. The red line indicates the 5% significance threshold, above which values are considered significant. This threshold was determined through simulations using the demographic parameters inferred from the data, as depicted in Figure 4 and Table S2. See Tables S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14 for tabular presentations of these data. Panel A: longitudinal B103 urine populations. Panel B: B103 longitudinal plasma populations. Panel C: B103 1 week plasma and urine populations. For the results of all PBS analyses, see Figure S3.

Figure 6. Pre-existing and new SNPs contribute to varying degrees to HCMV evolution.

Panel A: Consensus sequence SNPs between populations were classified as either pre-existing (detected in the ancestral and derived populations) or new (only detected in the derived population). Plotted are the occurrence of these two classes of SNPs in the various patient specimens. Panel B: A tabular representation of the data presented in Panel A.