Biology subjects

Romero, E. V.

Publications and source records attributed to Romero, E. V..

3 recordsLinked to original sources

bioRxiv2026

Haplotype and diversity signatures of ultra-soft selective sweeps in HIV-1

Many urgent medical and agricultural challenges are driven by resistance evolution via soft selective sweeps of multiple simultaneous mutations. Standard approaches to detect these mutations involve genome scans for regions with reduced diversity and increased haplotype lengths. However, it is unknown the extent to which those signatures persist as the number of mutations driving resistance grows. Here, we analyzed longitudinal linkage-resolved data from 10 intra-host HIV populations treated with broadly neutralizing antibody 10-1074. We found that HIV escapes 10-1074 with minimal perturbations to diversity and haplotype homozygosity in the region surrounding the sweep in the majority (8/10) of treated individuals. We matched these in vivo escape trajectories to forward simulations and found that adaptive mutations conferring escape must have been present on 20 or more genetic backgrounds to generate these signatures. These "ultra-soft" sweep signatures more closely resemble genetic patterns in a treatment non-responder without an adaptive response to 10-1074 than those of two other trial participants where adaptation occurred via harder selective sweeps. Our results demonstrate that HIV can adapt to a broadly neutralizing antibody treatment while retaining nearly all of its standing genetic diversity and that selection scans dependent on regional diversity and haplotype homozygosity signatures fail in this "ultra-soft" regime.

evolutionary biology↗

bioRxiv2025

Distinct modes of evolution drive HIV escape from two broadly neutralizing antibodies.

Broadly neutralizing antibodies (bNAbs) show promise for HIV treatment and prevention, but are vulnerable to resistance evolution. Comprehensively understanding in vivo viral escape from individual bNAbs is necessary to design bNAb combinations that will provide durable responses. We characterize viral escape from two such bNAbs, 10-1074 and 3BNC117, using deep, longitudinal sequencing of full length HIV envelope (env) genes from study participants treated with bNAb monotherapy. Improved sequencing depth and computational evolutionary analyses permit us to identify in vivo routes and parallelism underlying HIV escape from each bNAb, providing new insights into this evolutionary process. We find that 10-1074 escape is restricted to a small number of previously documented pathways seen across participants, but these escape mutations 1) emerge via extensively recurrent mutation, 2) are not equally preferred, and 3) can pre-exist at low frequency in intra-host viral populations before therapy, although their detection does not predict rebound timing. In contrast, 3BNC117 escape follows background-specific patterns in which specific escape mutations present in one intra-host population rarely emerge or spread in other populations, except among highly related viruses. Despite this, 3BNC117 escape mutations often still emerge recurrently within their host. Our findings map longitudinal in vivo antibody escape across 20 diverse clade B HIV intra-host populations and reveal clinically relevant resistance dynamics that highlight how combination bNAb therapies will need to contend with extensively recurring escape mutations and dependence on genetic background. Significance StatementUsing recently developed techniques that capture viral genetic diversity and associations between mutations at depth, we deeply sequenced HIV from two clinical trials of broadly neutralizing antibody (bNAb) monotherapies, 3BNC117 and 10-1074. We computationally characterized HIV populations longitudinally with unprecedented resolution as they escaped these therapies in people living with HIV. Intra-host tracking of individual HIV genetic backgrounds reveals extensively recurrent mutations driving escape and suggests that HIV escape routes from certain bNAbs can depend sensitively on the genetic background of the virus. Our findings highlight the difficulties in evaluating pre-treatment resistance, provide an analysis blueprint for future trials, and inform the design of emerging combination antibody therapies to maximize the likelihood of durable efficacy.

molecular biology↗

bioRxiv2023

Elevated HIV viral load is associated with higher recombination rate in vivo.

HIVs exceptionally high recombination rate drives its intra-host diversification, enabling immune escape and multi-drug resistance within people living with HIV. While we know that HIVs recombination rate varies by genomic position, we have little understanding of how recombination varies throughout infection or between individuals as a function of the rate of cellular coinfection. We hypothesize that denser intra-host populations may have higher rates of coinfection and therefore recombination. To test this hypothesis, we develop a new approach (Recombination Analysis via Time Series Linkage Decay, or RATS-LD) to quantify recombination using autocorrelation of linkage between mutations across time points. We validate RATS-LD on simulated data under short read sequencing conditions and then apply it to longitudinal, high-throughput intra-host viral sequencing data, stratifying populations by viral load (a proxy for density). Among sampled viral populations with the lowest viral loads (< 26,800 copies/mL), we estimate a recombination rate of 1.5x10-5 events/bp/generation (95% CI: 7x10-6-2.9x10-5), similar to existing estimates. However, among samples with the highest viral loads (> 82,000 copies/mL), our median estimate is approximately 6 times higher. In addition to co-varying across individuals, we also find that recombination rate and viral load are associated within single individuals across different time points. Our findings suggest that rather than acting as a constant, uniform force, recombination can vary dynamically and drastically across intra-host viral populations and within them over time. More broadly, we hypothesize that this phenomenon may affect other facultatively asexual populations where spatial co-localization varies.

evolutionary biology↗