The researchers reconstructed the evolutionary and geographic history of CRF01_AE using viral sequences and Bayesian phylogeographic methods. Their analysis indicates that, after entering Thailand in the early 1980s, CRF01_AE spread across Southeast Asia and into China. Repeated movement across national borders was central to this continental expansion.

The reconstructed history also shows that many lineages circulated for years before detection, revealing substantial cryptic transmission before surveillance recognized them. Once established, transmission clusters persisted for decades and sustained local epidemics long after their initial introduction. These findings demonstrate that the regional spread of CRF01_AE unfolded over many years rather than through a single detectable event.

By showing that viral lineages remained undetected for years and that transmission clusters continued for decades, the study provides a historical context for the emergence of CRF01_AE across Asia. The authors identify early molecular surveillance and coordinated regional strategies as important for detecting emerging lineages and interrupting cross-border transmission.

Subject of Research: Evolutionary and geographic spread of HIV-1 CRF01_AE from Central Africa across Asia

Article Title: Global spread and evolutionary trajectories of HIV-1 CRF01_AE: Insights from phylogenetic analysis

Article References: Li, X., Jorgensen, D., Liu, H., Nie, Q., Bates, C., & Gu, Q. (2026). Global spread and evolutionary trajectories of HIV-1 CRF01_AE: Insights from phylogenetic analysis. PLOS One, 21(10), e0360404. https://doi.org/10.1371/journal.pone.0360404

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360404

Keywords: HIV-1, CRF01_AE, phylogenetics, Bayesian reconstruction, viral evolution, genome sequencing, molecular surveillance, cross-border transmission, Southeast Asia, China, Thailand, Central Africa

Poxviruses are large double-stranded DNA viruses, and recombination has long been recognized as a fundamental engine of their evolution. Laboratory studies dating back to the late 1980s demonstrated high levels of genetic exchange among poxvirus DNAs in infected cells, and comparative genomics of variola, the smallpox virus, revealed signatures of past recombination events in its evolutionary history. Recombination requires co-infection of a single cell by two genetically distinct viruses, after which the cellular and viral machinery can copy alternating templates, stitching together segments from each parent. In principle, mpox viruses from different clades could recombine wherever their transmission chains overlap — in a co-infected individual or, more plausibly given the epidemiology, in an animal reservoir host where viruses from distinct phylogeographic lineages might meet.

The Indian case came to light through the country’s mpox diagnostic network, which the Indian Council of Medical Research has been strengthening since the global outbreak of clade IIb virus began in 2022. The patient, who acquired the infection through travel, was managed clinically while specimens were forwarded for molecular testing and whole-genome sequencing. Initial real-time PCR screening could not have distinguished this virus from any other mpox infection, since standard assays target conserved genes shared across clades. Only when the researchers assembled the complete genome did the mosaic structure become apparent: stretches of sequence unambiguously derived from clade Ib, the lineage that emerged in Central Africa and spread internationally in 2024, alternating with stretches characteristic of clade IIb, the West African lineage behind the 2022 worldwide epidemic.

Detailed comparative analysis showed that the recombinant genome carries clade-defining mutations from both parental lineages. Clade-defining mutations are the fixed single-nucleotide changes that distinguish the major mpox clades Ia, Ib, IIa and IIb from one another; their simultaneous presence in a single genome, arranged in a block-like pattern along the chromosome, is the molecular fingerprint of recombination rather than convergent mutation. The team mapped 34 recombinant tracts — continuous segments of the genome inherited from one or the other parental clade — and identified 21 mutations that define the recombinant lineage itself. This pattern mirrors that of the UK recombinant virus, which likewise displayed 34 recombinant tracts and 21 recombinant lineage-associated mutations, a coincidence of architecture that points to a shared ancestry.

Phylogenetic analysis reinforced that conclusion. When individual recombinant tracts were extracted and placed on separate phylogenetic trees, each tract clustered with reference genomes from its parental clade, alternating between Ib and IIb positions depending on the segment examined. When whole recombinant genomes were compared with representative sequences from all four clades, the Indian and UK viruses formed a distinct group positioned intermediate between clades Ib and IIb. A phylogenetic network constructed with SplitsTree placed the recombinants in a characteristic box-like structure, a visual signature of reticulate evolution that arises when sequence relationships cannot be explained by a single branching tree. Statistical testing supported the inference of recombination among these viruses.

Beyond the phylogenetics, the team went a step further than most surveillance studies by isolating live virus. Clinical material was propagated in Vero CCL-81 cells, and cytopathic effects were observed by the third day after infection at the second passage, with the experiment repeated three times with consistent results. Virus isolation matters because it confirms that the recombinant genome was not an artefact of mixed sequencing reads from a co-infected patient but a viable, replicating virus. It also provides reagents for phenotypic characterization — growth kinetics, drug susceptibility, antigenicity — that sequence data alone cannot deliver. Both the clinical sample sequence and the isolate sequence were deposited publicly in the Pathoplexus database and the International Nucleotide Sequence Database Collaboration, under accession numbers that allow any laboratory to verify or extend the analysis.

The practical consequences for diagnostics are among the most important implications of the work. Several multiplex real-time PCR assays have been developed to differentiate mpox clades, exploiting clade-specific mutations to classify infections rapidly, and targeted assays exist specifically to detect the novel clade Ib lineage. A recombinant virus that combines genetic material from two clades can scramble such classifications: depending on which primer and probe sets are used, a single specimen might be typed as Ib, as IIb, or yield discordant results across targets. In the worst case, a diagnostic algorithm keyed to a clade Ib-specific mutation that falls inside a clade IIb-derived tract of the recombinant genome could produce a false negative for clade Ib classification. The authors outline a diagnostic workflow for the preliminary identification of suspected recombinant MPXV isolates, emphasizing that clade-typing assays should be interpreted alongside whole-genome sequencing whenever results are discordant or epidemiologically unexpected.

The broader epidemiological question raised by the finding is where and how these recombination events occurred. The Indian virus was imported through travel, and the UK virus was likewise detected in a traveller returning from Asia, yet both genomes cluster together, implying a common recombinant ancestor rather than two independent recombination events. That places the origin of this lineage in a location where clade Ib and clade IIb viruses circulate in proximity — a region where the 2024 clade Ib outbreak overlapped geographically with lingering clade IIb transmission. If such co-circulation is sustained, further recombinants can be expected. The properties of any recombinant cannot be assumed in advance: recombination can combine, dilute, or disrupt adaptive mutations affecting transmissibility, immune evasion, or antiviral susceptibility, and only phenotypic study of isolated viruses will resolve those questions.

For surveillance programmes, the lesson is that clade-labelled snapshots are no longer sufficient. The 2022 global mpox epidemic demonstrated how quickly a localized zoonotic spillover can become an international epidemic once a virus adapts to sustained human transmission, and the emergence of clade Ib in 2024 with higher reported severity underscored the cost of delayed recognition. Recombination adds a third dimension of unpredictability on top of mutation and geographic spread. Wastewater surveillance, which has successfully detected mpox in environmental samples, offers one complementary channel for tracking viral diversity at the population level, but it too depends on downstream sequencing to reveal recombinant structure. What the Indian and UK detections prove is that the global sequencing network, when properly resourced and connected to rapid data-sharing platforms such as Pathoplexus, can catch these events and alert the international community within the timeframe that matters for public health response.

The Indian study also illustrates the value of linking clinical care, laboratory diagnostics and research sequencing under a single coordinated response. State health authorities in Kerala coordinated disease control activities, clinical teams managed the patient, and the virology team at ICMR–NIV Pune performed molecular testing, genome sequencing, phylogenetic analysis and virus isolation as an integrated pipeline, supported by intramural funding and by the Department of Health Research’s programme to expand the national mpox laboratory network. The result is a complete characterization of a rare viral entity within weeks of detection — from bedside to genome to viable isolate to publicly shared sequence data. As mpox continues to circulate in humans and presumably in animal reservoirs, recombinant lineages such as this Ib/IIb mosaic will serve as markers of where distinct viral populations meet, and continued genomic surveillance, backed by standardized diagnostics capable of recognizing their mosaic genomes, will determine whether the world spots the next such virus before it spreads.

Subject of Research: Recombinant Clade Ib and IIb monkeypox virus identified in an imported mpox case in India

Article Title: Genomic surveillance of an imported recombinant Clade Ib and IIb monkeypox virus case in India

Article References: Sahay, R. R., Khurana, J., Moorkoth, A. P., PP, B., Shete, A. M., Yadav, S., Majumdar, T., Rani, S., Vijay, N., Mali, D., Kamble, S., Gavari, S., Gawande, P., Marathe, H., Acharya, A. K., Gupta, N., & Yadav, P. D. (2026). Genomic surveillance of an imported recombinant Clade Ib and IIb monkeypox virus case in India. Nature Microbiology. https://doi.org/10.1038/s41564-026-02508-y

Image Credits: AI Generated

DOI: 10.1038/s41564-026-02508-y

Keywords: mpox, monkeypox virus, recombination, Clade Ib, Clade IIb, genomic surveillance, whole-genome sequencing, phylogenetics, virus isolation, diagnostics, India, public health

The central insight of the work is that vaccination and natural infection are not independent processes acting on a static target. When a large fraction of a population carries antibodies against the currently dominant viral variant, the virus experiences strong selection favoring any mutant that can evade those antibodies. Vaccination, by expanding the pool of immune individuals, increases this selective pressure. In the language of evolutionary biology, vaccination raises the herd immunity threshold that the virus must climb, and in doing so it can speed up the very evolutionary race it is meant to end. The model shows that this acceleration is not a marginal effect; depending on parameter choices informed by real influenza data, vaccination can measurably shorten the time it takes for an escape variant to emerge and spread, and in some regimes it may even increase the incidence of infection rather than reduce it.

To reach this conclusion, Rouzine built a framework that links two traditionally separate layers of description. The first layer is an epidemiological model of a population infected with a continuously evolving virus, tracking how susceptible, infected, and immune individuals change over time as the virus drifts antigenically. The second layer is a model of evolution at multiple genetic loci, capturing the fact that antibody escape in influenza typically requires not a single mutation but a coordinated combination of changes across several sites in the viral genome. The two layers feed into each other: the epidemiological state of the population determines how strongly each escape mutation is selected, while the evolving viral variant determines who is susceptible and who is protected. This coupling is what allows the model to ask about vaccination in a dynamically meaningful way, rather than treating the virus as a fixed adversary.

The parameters of the coupled model were chosen to reflect empirical data on influenza virus, including the characteristic rates of mutation, the strength of antibody selection, and the epidemiological turnover of the virus in human populations. This grounding matters because the qualitative behavior of such models can change dramatically with parameter values. A model calibrated to arbitrary numbers might predict almost anything; a model anchored to measured influenza biology is constrained to explore the regime in which real vaccine campaigns actually operate. Within that regime, the study examined how the outcome of a vaccination program depends on the properties of the antibodies that the vaccine elicits and on the timing and positioning of the vaccine strain relative to the circulating virus.

A key structural distinction in the analysis concerns whether the protective effects of consecutive vaccinations overlap or do not overlap. In the overlapping case, antibodies elicited by successive vaccine formulations recognize overlapping sets of viral variants, so that a person vaccinated in consecutive seasons accumulates a broader shield of immunity. In the non-overlapping case, each vaccination generates antibodies against a distinct set of variants, and the protection from one campaign does not reinforce the protection from the next. The model treats these scenarios separately because they lead to different evolutionary dynamics. When effects overlap, the immune pressure on the virus is more coherent and sustained; when they do not, the virus faces a more fragmented landscape of selection, which changes both the pace of escape and the composition of escape mutations that succeed.

The most striking predictions concern two scenarios in which vaccination avoids backfiring. The first is that antibodies elicited by the vaccine are more broadly neutralizing than the antibodies generated by natural infection. If the vaccine induces a wider repertoire of recognition, targeting conserved features or a broader panel of antigenic variants, then the immune pressure it adds is not so easily escaped by a small number of mutations, and the evolutionary race slows in favor of the population. The second scenario is that the vaccine vector lies slightly ahead of the dominant viral variant along the evolutionary trajectory of the virus. In other words, if the vaccine anticipates the next step of viral evolution rather than chasing the variant that is already circulating, vaccination pre-arms the population against the variant that selection is about to favor, and the anticipated escape loses its advantage.

Both scenarios are demanding, and the model is candid about what happens when neither is met. A vaccine that elicits antibodies no broader than those from natural infection, and that targets a strain already dominant or already receding, adds immune pressure against variants the virus is abandoning while leaving the emerging escape path open. The result can be a net acceleration of viral evolution, with the ironic possibility that vaccination increases infection incidence by hastening the arrival of variants that evade existing immunity in the population. This does not mean that vaccination is futile; it means that the design and timing of vaccination matter in ways that a static view of immunity cannot capture. The value of a vaccine against a rapidly evolving virus depends on where it sits in the evolutionary race, not merely on how many people receive it.

These findings carry a constructive message for vaccine development. The study suggests that the probabilistic prognosis of virus evolution, meaning the forecasting of which variants are likely to arise and spread under current immune conditions, represents a promising strategy for improving vaccines, complementing the ongoing search for broadly neutralizing vaccines. Broadly neutralizing antibodies remain the gold standard, because they collapse the evolutionary escape routes available to the virus. But developing such vaccines for influenza has proved difficult, and the model indicates that a second, complementary path exists: using evolutionary models to place conventional vaccine strains slightly ahead of the dominant circulating variant, so that the immunity induced by vaccination intercepts the virus where it is going rather than where it has been. In this framing, vaccine selection becomes a forecasting problem, and the quality of the forecast directly determines whether vaccination helps or hinders the population.

The work also illustrates a broader principle in the study of rapidly evolving pathogens: epidemiology and evolution cannot be fully understood in isolation. The composition of the immune population shapes which mutations are beneficial to the virus, and the mutations that succeed reshape the epidemiology of the following season. Models that couple these processes, as the present study does, can capture feedback loops that simpler approaches miss, including the counterintuitive result that increasing immunity in a population can, under some conditions, increase the speed at which immune escape occurs. For influenza, where antigenic drift forces annual reformulation of vaccines and where prediction of the coming season’s strains remains an imperfect science, such coupled models offer a quantitative language for discussing why some vaccine campaigns perform better than others.

As with any theoretical study, the predictions rest on model assumptions and on the parameter values drawn from influenza data, and translating them into practice will require empirical validation and careful integration with surveillance systems that track viral evolution in near real time. Nevertheless, the conclusions sharpen the agenda for the field. Vaccination against a rapidly evolving respiratory virus is not a static intervention but a move in an ongoing evolutionary game, and the model identifies the conditions under which that move wins: either antibodies broader than nature’s own, or a vaccine strain positioned just ahead of the virus on its evolutionary path. Failing both, the race continues, and the virus may run faster for having been pushed. The study thus reframes vaccine improvement as a problem in evolutionary forecasting, one in which predicting the probabilistic future of the virus becomes as important as measuring its present.

Subject of Research: Modeling how vaccination influences the evolutionary race between influenza virus antigenic escape and collective immunity

Article Title: Vaccination accelerates the race of influenza virus against collective immunity

Article References: Rouzine, I. M. (2026). Vaccination accelerates the race of influenza virus against collective immunity. PLOS Pathogens, 22(10), e1014311. https://doi.org/10.1371/journal.ppat.1014311

Image Credits: AI Generated

DOI: 10.1371/journal.ppat.1014311

Keywords: influenza, vaccination, viral evolution, antigenic drift, herd immunity, antibody escape, epidemiological model, multilocus evolution, broadly neutralizing antibodies, vaccine design, PLOS Pathogens, evolutionary forecasting

A research team led by Carolyn Williamson of the University of Cape Town, together with Penny L. Moore of the University of the Witwatersrand and James I. Mullins of the University of Washington, set out to answer a question that therapeutic trials cannot cleanly address: what happens to viral evolution when a broadly neutralizing antibody is already circulating in the blood at the moment of transmission? In chronic infection, resistance can emerge from archived reservoir viruses that carry pre-existing mutations, muddying any interpretation of cause and effect. In the AMP setting, by contrast, participants acquired HIV while receiving either VRC01 or placebo, and the virus that founded each infection was typically a single, genetically homogeneous lineage. That low diversity at transmission creates a high theoretical barrier to escape, because the virus must generate and select new mutations from a very narrow starting point. The trials therefore offered a uniquely clean window on de novo escape under defined antibody pressure.

The team focused on 47 participants who had acquired single-lineage infections with viruses that were sensitive or only intermediately resistant to VRC01, defined by an IC80 neutralization titre of 3 micrograms per millilitre or less. Twenty-three came from the Africa trial and 24 from the Americas trial, distributed across 21 placebo recipients, 15 low-dose recipients and 11 high-dose recipients. From each participant, the researchers analysed envelope sequences from two early timepoints, the first a median of just 18 days after the estimated date of acquisition. In total, 11,730 previously generated env sequences were examined, with a median of 108 sequences per participant per timepoint, generated using a Pacific Biosciences single-molecule real-time platform with unique molecular identifiers to ensure accuracy. This depth matters enormously: variants circulating at frequencies of one percent or lower would be invisible to conventional sequencing with around 20 reads, yet such low-frequency mutants are precisely where resistance begins.

To detect escape, the investigators tracked amino acid changes over time at 34 positions within the VRC01 epitope, using two complementary approaches. Escape logograms compared the amino acid composition at the second timepoint against the consensus of the founder lineage at the first, while maximum-likelihood phylogenetic trees paired with highlighter plots visualized which sequences had diverged and which mutations travelled together. Variant sites appeared in 18 of the 47 participants, and the pattern was strikingly asymmetric. Eleven variant sites were observed exclusively in VRC01 recipients and only one exclusively in placebo recipients, while three appeared in both groups. In the Africa trial, variant sites were significantly more common among treated participants, appearing in 9 of 13 VRC01 recipients versus 2 of 10 placebo recipients, and when the rate of change in variant frequency per day was pooled across trials, the high-dose group showed a significantly faster rate than placebo.

Identifying a variant site, however, is not the same as proving escape. To establish causality, the team used site-directed mutagenesis to introduce each observed amino acid change into a pseudovirus clone carrying the participant’s own transmitted founder envelope, then measured neutralization sensitivity in the standard TZM-bl assay. A change was classified as an escape mutation if it shifted the IC80 by more than threefold. The verdict was unambiguous: escape mutations emerged in 8 of 26 VRC01-treated participants, or 31 percent, compared with none of the 21 placebo recipients, a difference that held up statistically with a P value of 0.006. Notably, all eight escape cases were diagnosed within eight weeks of the last infusion, and no escape was seen in participants diagnosed after the trial endpoint, consistent with the idea that circulating drug levels were the selective force. Escape was also more frequent in the Africa trial, where all infections were subtype C, than in the Americas trial, where all were subtype B.

Structurally, the escape pathways converged on a familiar neighbourhood. The Loop D region of gp120 was the dominant hot spot, with mutations at residues 276, 279 and 280 detected in all eight participants, most often at positions 279 and 280. Additional mutations appeared in the N197 glycan motif and in the beta23 and V5 regions, including G458E, G459D and K460N. In two participants the virus appeared to toggle between alternative amino acids at the same residue, a pattern previously recognized as a signature of positive selection. Structural modelling onto a crystal structure of VRC01 bound to a subtype C gp120 offered a mechanistic explanation for several of these changes: the N280D substitution introduces a negative charge that electrostatically repels a negatively charged residue on the antibody light chain, while G458E and G459D insert bulky, charged side chains into a constrained binding interface. In contrast, D279A and D279G likely escape by shortening side chains and removing a negative charge, reshaping the contact surface in the opposite direction.

Perhaps the most clinically consequential finding concerns cross-resistance. The researchers tested 17 pseudovirus mutants against a panel of ten broadly neutralizing antibodies, including VRC01-class antibodies such as 3BNC117, VRC_CH31, VRC01.23LS and VRC07-523LS, as well as non-VRC01-class CD4 binding site antibodies N6, 1-18 and CH235.12, with PG9 and 10E8v4 as outgroup controls targeting the V2 apex and membrane-proximal external region. Pairwise correlations computed with random-effects generalized linear models showed that most VRC01-class antibodies clustered tightly with VRC01, meaning that escape from one largely compromised the others. Yet two antibodies stood apart. N6, whose distinct binding angle likely explains its resilience, was only moderately correlated with VRC01, and the highly potent antibody 1-18 was the most robust of all, retaining IC80 values below 1 microgram per millilitre against 75 percent of the VRC01 escape mutants and a median IC80 below 0.1 micrograms per millilitre overall. Intriguingly, some Loop D mutations actually increased sensitivity to CH235.12, by as much as 44-fold, illustrating that escape from one antibody can come at the cost of vulnerability to another.

Double mutations told an equally instructive story about how resistance compounds. In one participant, the N197T/K460N combination conferred more than tenfold greater resistance than either single mutation alone, pushing the IC80 above 25 micrograms per millilitre. In another, the double mutants N280D/G459D and D279A/G459D produced 42-fold to 76-fold increases in resistance relative to the single mutants. The effects were also strongly context dependent: the same N280D mutation conferred resistance to six of eight antibodies in one viral backbone, four of eight in another, and only one of eight in a third, underscoring that the genetic background in which a mutation arises shapes its antigenic consequence. One participant also carried an A318T substitution that co-evolved with the G458E escape mutation, possibly compensating for the fitness cost of inserting a charged, bulky residue into the CD4 binding interface.

That fitness cost is the study’s most reassuring thread. When the team searched 8,452 group M HIV-1 sequences from the Los Alamos National Laboratory database, every escape amino acid except K460N was present at a frequency below one percent of circulating viruses, and the K460N change was simply a reversion from one uncommon residue to a more common one. The rarity of these mutations in the wild suggests they impose a replicative penalty on the virus, which may explain why they have not spread despite the antibody’s clinical use. Whether resistant variants could persist and transmit if VRC01 exposure were more sustained remains an open question, and the authors argue that long-term surveillance of these variants in treatment and prevention cohorts should be a priority.

The broader implications reach directly into the design of next-generation prevention. Because 40 percent of the escape mutations detected here were present at frequencies of two percent or lower, standard sequencing approaches would have missed most of them, a gap the authors say argues for incorporating deep sequencing into resistance screening for prevention and cure trials. More strategically, the findings demonstrate that antibody-mediated pre-exposure prophylaxis, like antiretroviral-based PrEP before it, can select for viral escape after infection, and that escape pathways are common, convergent and predictable. As newer broadly neutralizing antibodies with greater potency, broader coverage and longer half-lives enter clinical evaluation, the map of VRC01’s vulnerabilities provides a blueprint: antibodies such as N6 and 1-18, which shrugged off these escape mutations, point toward combinations that could raise the evolutionary barrier and keep HIV’s adaptability in check.

Subject of Research: Viral escape from the broadly neutralizing antibody VRC01 during HIV prevention trials

Article Title: Prophylactic treatment with broadly neutralizing antibody VRC01 selects for escape mutants after infection in Antibody-Mediated Prevention trials

Article References: Williamson, C., Curry, L., Mkhize, N. N., Giorgi, E. E., Magaret, C. A., Lambson, B. E., Bhebhe, S., Kaldine, H., Moyo-Gwete, T., Rolland, M., Rossenkhan, R., Garcia, N. M. G., Moodley, C., Yssel, A., Huang, Y., Marsden, A. A., Reeves, D. B., Mayer, B. T., Bumgarner, R. E., … Mullins, J. I. (2026). Prophylactic treatment with broadly neutralizing antibody VRC01 selects for escape mutants after infection in Antibody-Mediated Prevention trials. Nature Microbiology. https://doi.org/10.1038/s41564-026-02467-4

Image Credits: AI Generated

DOI: 10.1038/s41564-026-02467-4

Keywords: HIV, VRC01, broadly neutralizing antibodies, viral escape, AMP trials, HIV prevention, CD4 binding site, Loop D, deep sequencing, viral evolution, antibody-mediated prophylaxis, Nature Microbiology

The scale of the challenge is staggering. More than 17 million SARS-CoV-2 genome sequences have been publicly shared since the pandemic began, a figure that dwarfs anything virologists had previously contemplated. Before 2020, few researchers would have predicted that a single virus would accumulate even 100,000 genomes. When Rambaut and colleagues proposed the Pango system early in the pandemic, they anticipated that roughly 200 active lineages would suffice, warning that more would obscure rather than clarify discussion. In practice, between 200 and 1,000 distinct lineages circulated in any given month for much of the pandemic. That the system survived this explosion of data owes much to community curation and to tools such as Pangolin, Nextclade, UShER and Taxonium, which made assigning new genomes to lineages a routine computational task.

The core logic of a Pango lineage system is deceptively simple. A lineage is defined as a set of virus sequences forming an epidemiologically relevant cluster on a phylogenetic tree—specifically, all sequences descending from the most recent common ancestor of a curated set of designated reference genomes. The framework distinguishes between designation, in which high-quality sequences are formally assigned to define a lineage, and assignment, in which new genomes are classified against those definitions using phylogenetic placement, defining mutations or machine-learning classifiers. Designation is a deliberate, curated act; assignment is inferential and carries some uncertainty, which the authors argue must be acknowledged when results are interpreted, particularly for lower-quality or incomplete sequences.

What makes a cluster worthy of a name? The new framework lays out a set of signals that can justify designation, tailored to the biology and public health context of each virus. These include introduction into a new region with evidence of onward transmission, a change in phenotype, a notable constellation of mutations with possible functional relevance, recombination or reassortment, or evidence of rapid growth relative to other lineages. For SARS-CoV-2, early lineage definitions leaned heavily on geographical clustering while travel restrictions limited human movement; as global travel resumed, the criteria shifted toward growth advantage, recombination and mutations associated with immune escape. Any new lineage must also be genetically distinct from its ancestor by one or more mutations, show evidence of onward community transmission, and be supported by enough high-quality genomes to evaluate these criteria—though the exact thresholds are deliberately left flexible, to be set per virus and revised as circumstances change.

The architecture of lineage names encodes ancestry directly. Founding lineages are labelled with single letters at an initial time point chosen to capture the diversity relevant to public health; descendant sublineages append dot-separated numbers, so the 75th sublineage of BA.2 becomes BA.2.75. To keep names readable as diversity accumulates, an alias is introduced at a defined hierarchical level—after three levels for SARS-CoV-2, after two for mpox virus—replacing the prefix with the next available letter while the full ancestry is preserved in metadata. Circulating recombinants receive X-prefixed codes, as with SARS-CoV-2 lineage XBB, a recombinant of BJ.1 and BA.2.75, and designation can proceed even when the parental lineages remain uncertain. For reassorting viruses with segmented genomes, the system can be anchored to a single representative segment, typically the fastest-evolving one most relevant to transmission or antigenicity, with reassortment events in other segments capable of triggering new designations.

Critically, the authors stress that Pango is not a universal taxonomy and should not replace existing schemes. The International Committee on Taxonomy of Viruses classifies viruses down to the species rank, and below that level the field has long used a patchwork of terms—type, subtype, genotype, group and clade—each with its own conventions. A Pango system occupies an intermediate granularity: finer than persistent clade nomenclatures suited to long-term evolutionary patterns such as antigenic turnover, and coarser than phylotypes, a dot-separated notation encoding every node in a phylogeny for fine-scale local investigations such as hospital outbreaks. For endemic pathogens whose diversity is deep and largely historic, the authors caution that a fine-scale dynamic system may add complexity without public health benefit. Yet it becomes valuable when new selective pressures are expected—following vaccine or antiviral introduction, for instance—or when eradication programmes demand close tracking of contemporary transmission, as with poliovirus or measles virus.

The framework is also explicit about when it should not be used at all. Pathogens must be ‘measurably evolving’—accumulating detectable genetic diversity over the timescale of interest—for a lineage system to be informative. Many RNA viruses meet this bar, but double-stranded DNA viruses generally evolve too slowly unless host-mediated processes such as APOBEC3 editing elevate their mutation rates, as has occurred in mpox virus. Zoonotic outbreaks driven by repeated independent spillovers, such as the 2018 Lassa fever outbreak in Nigeria or re-emergences of yellow fever virus in Brazil, do not warrant lineage systems, nor do self-limiting, geographically confined transmission chains. Dynamic nomenclatures are most valuable for sustained human-to-human outbreaks spreading across multiple regions, exemplified by the global clade IIb mpox outbreak of 2022, where Pango-style lineages complemented existing clade labels. Independent spillovers giving rise to separate sustained outbreaks would each warrant their own lineage system.

To demonstrate the framework on a virus with a long history of human circulation, the team built a Pango lineage system for chikungunya virus, a mosquito-borne alphavirus first identified in 1952 and since reported in 114 countries. Working from roughly 3,300 publicly available near-full-length genomes, they filtered the data to sequences sampled from 2016 onwards and designated 21 lineages across eight founding lineages, labelled A through H. The conventional three-clade geography-based system maps onto this scheme: the West African clade corresponds to lineages A and B, the Asian clade to lineage C, and the East/Central/South African clade to lineages D through H, with twelve hierarchical sublineages defined across the founding lineages. The authors argue that geography-based labels have become misleading as phylogeographic patterns shift, and that naming conventions for chikungunya have lacked standardization. Sequences predating 2016 fall outside the system under the designation O, but can be incorporated as new founding lineages if they reappear in contemporary transmission—a flexibility illustrated by a 2021 mosquito sample from China that falls outside all current lineages.

Lessons from the pandemic loom over the entire enterprise. Pango labels proved poorly suited to public communication, which is why the World Health Organization introduced Greek-letter names for variants of concern such as Alpha and Omicron; yet after Omicron no further Greek letters were assigned, and the WHO has continued to rely on Pango lineages for tracking variants of interest and concern. The pandemic also revealed structural vulnerabilities. Global sequencing capacity remains deeply unequal, with high-income countries overrepresented in public databases while epidemiologically important regions contribute few sequences. The authors argue that designation systems must compensate by applying stricter thresholds in well-sampled countries and giving greater weight to data from underrepresented regions, and that the people closest to the data must be empowered to propose and flag new lineages through transparent public forums such as GitHub.

Perhaps the most sobering recommendation concerns sustainability. The Pango system was conceived as dynamic and time-limited, expected to be most useful for the duration of the pandemic, and the authors argue that such systems should exist only as long as they retain clear utility and support. When an epidemic pathogen transitions to endemicity, a more stable, persistent nomenclature with lower maintenance burden may serve better. Yet no organization currently exists to fund the establishment and maintenance of lineage systems, even as public health agencies, universities and industry all benefit from them. The authors propose a model that leverages distributed expertise across public health laboratories and academia, coordinated through central governance and modelled on established surveillance networks. As viral genomic data continue to shape outbreak control, they conclude, coherent and accessible nomenclature will be essential for translating complex genomic information into public health action—and the principles of utility, scalability, transparency and equity laid out here offer a foundation for building it.

Subject of Research: Generalization of the Pango viral lineage nomenclature system for genomic epidemiology and surveillance

Article Title: A generalized lineage nomenclature for viral genomic epidemiology

Article References: Colquhoun, R., Hinrichs, A. S., Hill, V., Ruis, C., Roemer, C., Pybus, O. G., Rambaut, A., & O’Toole, Á. (2026). A generalized lineage nomenclature for viral genomic epidemiology. Nature Microbiology. https://doi.org/10.1038/s41564-026-02468-3

Image Credits: AI Generated

DOI: 10.1038/s41564-026-02468-3

Keywords: Pango lineages, viral genomics, genomic epidemiology, SARS-CoV-2, chikungunya virus, phylogenetics, nomenclature, outbreak surveillance, mpox virus, viral evolution, public health, recombination

The motivation behind the work lies in the limitations of the current diagnostic toolkit. Next-generation sequencing is the gold standard for decoding viral genomes and tracking mutations, but it is a complex, multi-step process that can take weeks and may occasionally miss or misinterpret variants. Reverse transcription polymerase chain reaction, by contrast, is fast and widely deployed from bench to bedside, yet it can only detect sequences that are already known: if mutations arise in the primer-binding regions, the assay may fail entirely, and designing new primers for an emerging variant can take nearly as long as full sequencing. Raman spectroscopy offers a third path — one that does not read the base sequence at all, but instead captures the structural consequences of sequence variation as they are written into the RNA molecule’s vibrational behavior.

In the study, viral variants were propagated in VeroE6/TMPRSS2 cells, and RNA was extracted from culture supernatants using a commercial kit. Raman spectra were collected with a confocal LabRAM HR800 spectrometer excited at 532 nanometers, achieving spectral resolution better than one wavenumber with an internal neon lamp reference for calibration. Ten spectra were averaged for each RNA sample across an area of roughly two square millimeters, and the resulting spectra were baseline-corrected and deconvoluted into Gaussian-Lorentzian sub-band components using an automatic solver built on machine learning algorithms. Crucially, the optimization preserved the spectral positions and bandwidths of elementary molecular components while treating relative intensities as structure-dependent variables, a constrained approach that dramatically reduces the risk of overfitting in spectrally congested regions.

The spectra, recorded between 400 and 1800 wavenumbers, were morphologically similar across all 20 strains but differed in telling details. Ring-breathing markers for the four RNA bases appeared at characteristic positions: about 724 wavenumbers for adenine, 778 for cytosine, 672 for guanine and 791 for uracil. Backbone signals included the O-P-O stretching modes near 807 and 824 wavenumbers and a C3′-O-P bending band at 432 wavenumbers, while ribofuranose sugar rings contributed a strong C-O/C-C stretching signal at roughly 1045 wavenumbers. When the researchers compared the fractional intensities of the base signals with the actual base fractions computed from genomic data, the two disagreed substantially — pyrimidine signals systematically overestimated their base fractions and purine signals underestimated them. These mismatches could not be explained by base composition, which is nearly homogeneous across strains, but instead arise from differences in Raman cross-sections and from hyperchromic and hypochromic effects tied to RNA secondary structure.

That structural sensitivity is precisely what makes the approach powerful. Single-stranded viral RNA folds into stems, hairpin loops, pseudoknots, bulge loops, internal loops and multibranched junctions, and each motif modulates the Raman spectrum in its own way. Double-stranded stems enhance base stacking and hydrogen bonding, sharpening and intensifying purine ring signals; hairpin loops bend the phosphodiester backbone and alter its vibrational response; bulges and internal loops distort local geometry and reduce stacking-related intensity. To rationalize these effects, the team predicted the secondary structures of all 20 genomes with the ViennaRNA package using sequences from the GISAID database, computing positional descriptors including base-pairing probability, cumulative minimum-free-energy nesting depth, Shannon entropy and a custom composite “strain score” flagging nucleotides that are structurally engaged yet conformationally unstable.

Several quantitative relationships emerged. The ribofuranose ring signal at 1045 wavenumbers showed a clean linear dependence on genome length — the longer the RNA chain, the stronger the signal — because the sugar ring’s two additional dihedral angles affect only the pucker conformation and are not directly strained by backbone bending. Phosphodiester backbone signals, by contrast, scattered far more widely, since the six backbone dihedral angles are directly perturbed by kinks introduced through non-canonical base pairing. Searches for AUUCU repeats and kink-turn motifs, known sources of backbone deformation, found that their counts varied only marginally among the strains and could not alone account for the observed scatter. More strikingly, the 432-wavenumber C3′-O-P bending signal displayed an exponential hyperchromic dependence on the number of hairpin loops, with the ancestral strain — which had the most hairpins, 592 — showing the strongest intensity. The researchers interpret this as evidence that RNA backbone vibrations become more Raman-active as secondary-structure complexity increases, likely because tight structural constraints reduce vibrational energy dissipation and make the bending mode more cooperative.

A second key marker appeared near 1460 wavenumbers, a composite band dominated by C=N and C=C stretching in guanine and adenine together with C-H and N-H bending. Its relative intensity rose linearly with average stem length, tracking the increased base stacking and hydrogen bonding of longer double-stranded regions. Neither of these trends could be reproduced for neighboring bands of similar origin, underscoring the unique sensitivity of the 1460-wavenumber signal to base-stacking effects. Because hairpins and stems regulate viral infectivity — stabilizing the genome against host nucleases, enabling translation initiation of the ORF1a/ORF1ab replicase polyproteins through conserved stem-loop structures in the 5′ untranslated region, and hiding immunostimulatory double-stranded motifs from innate immune sensors such as RIG-I, MDA5, PKR and the OAS family — the two Raman markers can be read as proxies for replication efficiency and immune evasion, respectively.

Plotted as a rescaled intensity timeline across the 20 strains, these markers tell an evolutionary story. The ancestral variant scored highest on both functions. Successive variants showed a general decline in the translation/replication indicator, with the Theta variant as a notable exception, its secondary structure scoring closest to the ancestor’s — consistent with reports of concerning spike mutations in that lineage. From the Mu variant onward, the immune-evasion indicator climbed sharply through the first wave of Omicron subvariants, in agreement with the known immune-escape character of Omicron, and a further, smaller spike appeared in a later Omicron subvariant. The authors note that such trade-offs between immune escape and replication fitness are well documented in HIV, influenza and hepatitis C, and that Omicron’s emergence indeed traded replication efficiency for immune evasion.

Classification posed its own challenge. Principal component analysis, a standard chemometric tool in biomedical spectroscopy, succeeded in separating only a minority of the 20 RNA samples, a partial failure the researchers attribute to the extreme complexity of RNA secondary structure. Instead, they converted each deconvoluted spectrum into a Raman barcode, assigning to each sub-band a line whose thickness and spacing encode the band’s width and area. Every one of the 20 barcodes proved unique, univocally locating the molecular structure of each sample, including the spectroscopic imprint of its secondary structure. Compared with DNA barcoding initiatives that require sequencing short genetic markers, the Raman approach skips sequence analysis altogether, potentially enabling on-site pathogen identification in a time dictated solely by RNA extraction, once a comprehensive spectral library and standardized deconvolution protocols are in place.

The authors are careful to frame the work as a proof of concept with clear limitations. The study used purified viral RNA from controlled cell cultures rather than clinical specimens containing host RNA, proteins and debris; it cannot identify individual nucleotide substitutions or determine primary sequence, and should be regarded as complementary to genomic sequencing rather than a replacement; and the barcode algorithm will require inter-laboratory validation, standardized acquisition protocols and expanded spectral libraries before clinical translation. Its ability to resolve newly emerging variants differing by only a few mutations remains to be systematically tested. Nevertheless, the study establishes that Raman spectroscopy captures structural information encoded within viral RNA that conventional compositional analyses cannot reach — amplified spectral differences arising from small genomic ones — and demonstrates that a Raman library of viral RNA barcodes could one day give virologists a rapid, low-cost route to variant identification in emergency and critical-care settings, precisely where timely classification of emerging strains matters most.

Subject of Research: Raman spectroscopic fingerprinting of SARS-CoV-2 viral RNA secondary structure for variant classification

Article Title: Raman Analysis of RNA Nucleotide Strands From SARS‐CoV‐2 Variants and Subvariants: A Step Forward in the Definition of “Raman Genome”

Article References: Pezzotti, G., Yasukochi, Y., Angiola, G., Ueno, T., Ikegami, S., Okawa, R., Adachi, T., Zhu, W., Mazda, O., Grillo, A., Higasa, K., & Okuma, K. (2026). Raman Analysis of RNA Nucleotide Strands From SARS‐CoV‐2 Variants and Subvariants: A Step Forward in the Definition of “Raman Genome”. Advanced Science, Article e77679. https://doi.org/10.1002/advs.77679

Image Credits: AI Generated

DOI: 10.1002/advs.77679

Keywords: SARS-CoV-2, Raman spectroscopy, viral RNA, Raman genome, variants and subvariants, RNA secondary structure, Raman barcode, molecular diagnostics, machine learning, ViennaRNA, immune evasion, viral evolution

The research team focused on five large double-stranded DNA viruses: vaccinia virus, the type species of mammal-infecting poxviruses, and four human herpesviruses, namely herpes simplex virus 1, Epstein–Barr virus, human cytomegalovirus and Kaposi’s sarcoma-associated herpesvirus. These viruses are known to encode numerous host-like domains acquired through horizontal gene transfer during their long evolutionary history. To find them systematically, the researchers predicted the three-dimensional structures of 540 viral proteins using AlphaFold2 and then employed Foldseek, a fast structural homology search tool, to identify viral domains that structurally resemble human proteins. After a series of filtering steps designed to eliminate spurious matches between low-complexity folds and partially homologous structures, the pipeline yielded 7,593 human–viral structural homolog pairs derived from 144 distinct viral proteins.

The scale of this mimicry is striking. In herpes simplex virus 1, structurally host-like domains account for roughly 11 percent of the encoded proteome, while in vaccinia virus the figure rises to 31 percent. Notably, despite their structural resemblance, the sequence similarity between viral mimics and their human counterparts is often low, averaging just 28.4 percent within the homologous region and 6.3 percent across full-length proteins. This makes them imperfect mimics: similar enough in fold to bind the same partners, yet different enough in sequence that the interacting surfaces are not identical. The researchers then asked which of these structural homologs actually function in a similar way, defining functional similarity as the sharing of at least one common human interaction partner, which they termed a mutual host target.

By overlaying experimentally characterized human–virus protein interaction networks from databases such as HVIDB with within-human interaction maps from STRING, the team identified 645 triads consisting of a viral mimicking protein, a host-mimicked protein and a mutual host target. These triads involve 229 functionally mimicked human proteins, 40 viral mimicking proteins and 118 mutual host targets. One illustrative example is the KSHV protein ORF72, which structurally resembles the human cyclin CCNO, with both proteins predicted to interact with the human kinase CDK3 through a similar binding region. The set of functionally mimicked proteins, those with direct evidence of shared interactions, became the focus of the subsequent evolutionary analysis.

To measure evolutionary pressure, the researchers computed dN/dS, the ratio of nonsynonymous to synonymous substitutions, for more than 9,000 human genes across ten primate species, including chimpanzee, gorilla, orangutan, macaques and mouse lemur. The results were unambiguous. Human proteins known to bind viral proteins are significantly more conserved than the proteome at large, confirming earlier findings. But the proteins entangled in mimicry are conserved to an even greater degree. Mutual host targets, the human proteins contacted by both the viral mimic and the host-mimicked protein, were the most conserved viral-binding group tested, and functionally mimicked proteins were significantly more conserved than the broader set of structural homologs. When the team searched for signatures of pervasive positive selection using codon-based models in PAML, the picture was equally striking: proteins targeted by mimics showed virtually no positively selected genes at most statistical thresholds, in sharp contrast to the modest but detectable positive selection seen among viral-binding proteins in general.

What explains this exceptional conservation? The researchers found that mimicry-related host proteins sit at crowded hubs of the cellular interaction network. Mutual targets and functionally mimicked proteins have significantly more interaction partners than average human proteins, and targets of mimicry are also more highly expressed across tissues than other viral-binding proteins. Gene ontology analysis showed that these proteins are enriched in antiviral pathways such as cell death, cytokine response and inflammatory signaling, as well as in processes frequently manipulated by viruses, including Golgi regulation, the G1/S cell cycle transition and signal transduction. Within these shared functional categories, mimicked and target proteins were more conserved than their non-mimicked counterparts in the majority of cases, 75.6 percent for mimicked proteins and 63.2 percent for targets. The implication is that essential cellular roles constrain these proteins, leaving the host little room to mutate away from viral mimics without damaging its own interactome.

The analysis then zoomed in to the level of individual amino acids. Using AlphaFold-Multimer to predict complexes between mimicked and target proteins, the team identified interface residues and compared their evolutionary rates with those of buried core residues and exposed surface residues. As expected, interfaces and cores evolved more slowly than surfaces. More revealing was the comparison between two kinds of interface: mimicry interfaces, the residues that physically contact the mutual target, and general interfaces, predicted binding sites for unrelated proteins using the deep learning tool ScanNet and the SVM-based method ISPRED4. In both mimicked and target proteins, mimicry interfaces were significantly more conserved than general interfaces, indicating that the residues exploited by viral mimics are under especially strong purifying selection.

Because viral mimics are imperfect copies, their binding surfaces on the host target are not identical to those of the host-mimicked protein. The researchers therefore subdivided target interfaces into residues contacted by the host-mimicked protein, residues contacted only by the viral mimic, and residues contacted by both. The mutual residues were the most conserved, while residues exclusively touched by the viral protein evolved significantly faster. This pattern hints at a possible escape route: host surfaces used only by the virus, and not required for essential cellular interactions, may tolerate more change, potentially allowing the host to weaken viral interactions selectively. Yet even these faster-evolving regions showed no enrichment for positively selected residues, so the authors caution that this remains a hypothesis rather than demonstrated host escape. The team also compared perfect and imperfect mimicry, examining short linear motifs in disordered viral regions that exactly copy host motifs. Host proteins targeted by these perfect motif mimics, 89 in total, were the most conserved group in the entire study, more constrained even than targets of imperfect domain mimicry, consistent with the idea that perfect mimicry leaves the host no way to discriminate foe from friend.

On the viral side, the picture was more complex. Comparing orthologs across orthopoxviruses, simplexviruses, cytomegaloviruses and rhadinoviruses, the researchers found no consistent difference in evolutionary rate between mimicking and non-mimicking viral proteins, a result they attribute to technical limitations such as small protein sets and limited rate ranges, as well as biological factors including the multifunctional nature of viral proteins. Crucially, however, viral mimics were not enriched for positively selected genes; if anything, the fraction of such genes was lower in mimics than in other viral proteins across all four lineages. In the few mimicking–target complexes that could be modeled with high confidence, interface residues of viral mimics were more conserved than surface residues, mirroring the host-side pattern. The single positively selected residue detected in a viral mimic, asparagine 15 in the vaccinia Bcl-2-like protein OPG035, sits far from the interface with its human target, pointing away from any adaptive remodeling of the binding surface.

The overall message is a reframing of how host–virus conflict plays out at the molecular level. While arms races do occur, particularly in immune and restriction factors, the interactions mediated by mimicry appear governed by constraint rather than escalation. Viruses have exploited the host’s inability to escape: by targeting highly connected, highly expressed, functionally essential proteins through surfaces the host must preserve, mimics anchor themselves to interaction networks that evolution cannot easily redeploy. The conserved nature of these interfaces may also carry practical value, the authors suggest, since stable binding regions could serve as targets for antiviral drugs designed to disrupt mimicry-mediated interactions. And because these principles govern the conservation and evolvability of host–virus interaction networks, they may help predict which viruses can switch hosts and which barriers stand in the way of zoonotic emergence. The study’s data and code are openly available, offering a resource for the growing field of structural virology.

Subject of Research: Evolutionary dynamics of viral molecular mimicry and host protein interactions in large DNA viruses

Article Title: The evolutionary dynamics between viral mimics and host proteins

Article References: Fuchs, R., Schor, O., Naim, B., Tussia-Cohen, D., Mozzi, A., Forni, D., Friedman, S., Haggai, Z., Sironi, M., & Hagai, T. (2026). The evolutionary dynamics between viral mimics and host proteins. Molecular Systems Biology, 22(6), 902-927. https://doi.org/10.1038/s44320-026-00200-1

Image Credits: AI Generated

DOI: 10.1038/s44320-026-00200-1

Keywords: molecular mimicry, virus-host interactions, viral evolution, protein-protein interactions, AlphaFold, dN/dS, positive selection, herpesvirus, poxvirus, structural biology, host-pathogen coevolution, protein interfaces

The research, led by Tianxiong Yu and Zhiping Weng of the University of Massachusetts Chan Medical School together with William E. Theurkauf, and conducted in collaboration with Michaela D. J. Blyton and Keith Chappell of the University of Queensland along with Birgit S. Koppetsch, Milky Abajorga and Jeremy Luban, rests on an unusually broad genomic survey. The team analyzed whole-genome sequencing data from 405 wild koalas, a sample set that spans nearly the entire range of the species. From these genomes they catalogued germline insertions of KoRV-A, the sites where the virus has stitched itself into koala chromosomes in cells that give rise to sperm and eggs, allowing the insertions to be passed down through generations.

Endogenous retroviruses occupy a special place in virology and genome biology. When a retrovirus infects a germ cell, the DNA copy it makes of its RNA genome can be permanently fixed into the host genome. From that moment the insertion behaves like any other genetic marker, inherited according to Mendelian rules. Older endogenous retroviruses accumulate in the genomes of virtually all vertebrates, but KoRV-A is remarkable because its endogenization appears to be geologically recent. Previous studies had estimated that KoRV-A first integrated into the koala genome roughly 300,000 years ago, a blink in evolutionary time for a process that in most lineages concluded tens of millions of years ago. That recency means koalas are living through a rare, observable transition: the conversion of an active infectious retrovirus into inherited genetic cargo.

By mapping where shared KoRV-A insertions occur across the range of sampled animals, the researchers could infer the geography of the virus’s expansion. Insertions that are shared by many koalas across broad areas are older, having had more time to spread, while insertions found in single individuals or narrow localities are younger. Tracing this gradient of sharedness and diversity, the analysis converged on a starting point near Coffs Harbour in New South Wales. From that mid-range epicenter, the virus appears to have radiated outward, generating the mosaic of insertion patterns that now distinguishes koala populations across the continent.

The study also documents how the virus diversified as it spread. As KoRV-A moved through wild populations, certain subtypes emerged and rose to prevalence, each carrying characteristic sequence variation in the long terminal repeats and coding regions that define retroviral strains. Two of these successful subtypes did something biologically striking: they recombined with an ancient endogenous retrovirus already resident in the koala genome, known as PhER. These recombination events produced distinct recombinant variants, termed recKoRV variants, and the analysis found that different recombinant forms characterize the northern and southern koala populations. Recombination between a young, active retrovirus and a deeply ancient endogenous element is a vivid illustration of how the koala genome functions as an arena in which viral lineages interact, exchange genetic material, and generate new variants.

Geography, as much as virology, shaped the resulting distribution. The researchers identified a barrier north of Sydney that appears to have slowed the southward spread of KoRV-A into Sydney and regions beyond. Such barriers to viral dispersal are critical to understanding the current and future burden of retroviral disease in koalas. KoRV infection is associated with serious health consequences in wild populations, including immune suppression and increased susceptibility to infections and cancers, so the pace and pattern of the virus’s southward march has direct implications for conservation. A population that has carried endogenous KoRV-A for longer may have evolved some degree of accommodation to the virus, while populations only recently exposed may face harsher impacts.

The technical foundation of the study is the systematic detection of insertion sites from short-read whole-genome sequencing data. At each candidate insertion, reads that span the junction between viral sequence and flanking koala DNA provide evidence for the insertion’s presence, and the number of supporting reads yields an estimate of the allele frequency, indicating how many chromosomes in the population carry that particular insertion. Insertions with high allele frequencies across many individuals represent ancient, deeply shared events, while those at low frequency in restricted localities mark recent integrations. The team supplemented this with analysis of the 5-prime long terminal repeat sequences of each insertion, which allowed them to assign insertions to KoRV-A subtypes and to track how subtype composition shifts across geography. Down-sampling analyses confirmed that these patterns were robust to variation in sequencing depth and sample density.

What makes the koala system scientifically valuable is that it compresses into a single living species a process that is usually visible only through deep evolutionary time. In mice, humans, and most other mammals, endogenous retroviruses are fossils, long-defanged remnants of infections that occurred before those species existed. In koalas, the endogenization process is young enough that both the infectious virus circulating between individuals and the fixed germline insertions inherited from ancestors can be studied side by side. The 405-genome dataset effectively turns the koala range into a natural time series, with geographic distance from the inferred origin at Coffs Harbour serving as a proxy for time since the virus arrived.

The evolutionary trajectory proposed by the authors therefore reads as a narrative with a defined beginning, a set of diversification events, and a partially constrained spread. The story begins with the initial integration of KoRV-A into the koala germline near Coffs Harbour, around the middle of the species’ range, consistent with a rough timescale of hundreds of thousands of years. As the virus dispersed, subtypes arose and became regionally dominant, and two of them captured sequence from the ancient PhER retrovirus, yielding recombinant variants that now mark the northern and southern populations respectively. Along the way, a barrier north of Sydney slowed the southern expansion, leaving populations south of that line with a different retroviral landscape than those to the north.

For conservation biologists, the practical value of this work lies in its detailed map of retroviral diversity across koala populations. Knowing where the virus began, which subtypes and recombinant variants prevail in which regions, and where natural barriers have limited spread provides a baseline for monitoring the ongoing epidemic and for anticipating how KoRV-A may continue to move through vulnerable southern populations. For virologists and genome biologists, the study offers a rare, range-wide portrait of endogenization in action, showing how a retrovirus spreads, diversifies, recombines with ancient residents of the host genome, and is gradually absorbed into the hereditary fabric of a species. The koala, an iconic and threatened marsupial, is thus also a living laboratory of viral evolution, and the trajectory reconstructed from these 405 genomes gives science its clearest view yet of where that story began.

Subject of Research: Evolutionary origins and spread of the koala retrovirus KoRV-A in the koala germline genome

Article Title: The trajectory of KoRV-A evolution suggests initial integration into the koala germline genome near Coffs Harbour in New South Wales

Article References: Yu, T., Blyton, M. D. J., Koppetsch, B. S., Abajorga, M., Luban, J., Chappell, K., Theurkauf, W. E., & Weng, Z. (2026). The trajectory of KoRV-A evolution suggests initial integration into the koala germline genome near Coffs Harbour in New South Wales. Genome Biology. https://doi.org/10.1186/s13059-026-04258-w

Image Credits: AI Generated

DOI: 10.1186/s13059-026-04258-w

Keywords: koala retrovirus, KoRV-A, endogenous retrovirus, koala genome, germline integration, viral evolution, genome biology, Coffs Harbour, recombination, PhER, New South Wales, whole-genome sequencing

The research team collected RSV-positive upper respiratory tract samples from patients who tested positive between October 2023 and March 2025, spanning two consecutive seasons that straddled the deployment of nirsevimab. Whole viral genomes were recovered using an amplicon-based sequencing protocol carried out on Illumina platforms, with assemblies generated through a consensus-building pipeline known as vcf-consensus-builder. This approach allowed the investigators to capture near-complete genomes from a substantial fraction of positive samples, providing the resolution needed to place each virus within a fine-grained phylogenetic framework and to examine amino acid variation in the proteins most relevant to prevention and treatment.

In total, the study retrieved 302 RSV genome sequences, with 129 derived from the 2023–2024 season and 173 from the 2024–2025 season. The clinical composition of the cohort reflects the burden of RSV disease in the region: most infections occurred in infants aged one year or younger, who accounted for 56.0 percent of cases, and males made up 57.3 percent of the sampled population. Lower respiratory tract infections were documented in 72.7 percent of cases, 67.2 percent of patients required hospitalization, and 15.0 percent were admitted to an intensive care unit. Notably, the dataset included 17 nirsevimab breakthrough infections, cases in which infants who had received the monoclonal antibody nonetheless developed symptomatic RSV disease.

Phylogenetic analysis using maximum-likelihood methods implemented in IQ-TREE, with a GTR plus F, invariant sites, and gamma model of substitution, assigned the circulating viruses to established clades within the two major RSV subgroups. The most frequently detected clades were A.D.3, representing 26.8 percent of sequences, and B.D.E.1, representing 20.2 percent, followed by A.D.1.2 at 17.5 percent and A.D.5.2 at 14.2 percent. This distribution confirms that multiple lineages of both RSV-A and RSV-B co-circulated in Lombardy throughout the study period, with no single clade achieving complete dominance across the two seasons.

Beyond clade assignment, the researchers applied Bayesian coalescent methods under a constant population size prior and a strict molecular clock to define what they termed large phylogenetic clusters, or LPCs. These were groups of more than ten sequences supported by a posterior probability of one, indicating tightly linked transmission chains or rapidly expanding lineages. Four such clusters were identified, and two of them proved particularly striking: a cluster of 56 A.D.3 strains and another of 17 A.D.1.2 strains were detected exclusively in the 2024–2025 season, the first season of routine nirsevimab use. The emergence of season-specific clusters suggests that new viral lineages established themselves in the population after the prophylaxis program began.

A central concern of the study was the monitoring of mutations associated with resistance to the preventive and therapeutic agents now deployed against RSV. The fusion protein, or F, is the target of the monoclonal antibodies palivizumab, nirsevimab, and clesrovimab, while the nucleoprotein, or N, is the target of the small-molecule inhibitor zelicapavir. Resistance-associated mutations were identified in two samples from the 2023–2024 season and two from the 2024–2025 season. These included K272E in an A.D.5.3 strain and N262Y in an A.D.3 strain, both associated with reduced susceptibility to palivizumab, and N208D in a B.D.E.1 strain as well as the combination of K68I and L204S in a B.D.E.1 nirsevimab breakthrough infection, mutations linked to nirsevimab resistance.

Among the 17 nirsevimab breakthrough infections, the investigators also detected the S213R substitution at antigenic site Ø of the F protein in an A.D.1.2 sample. Site Ø is the principal binding site for nirsevimab, and changes at this region can diminish antibody binding. By contrast, no mutations conferring resistance to clesrovimab, a newer monoclonal antibody that binds a different region of F, were detected during the study. However, four substitutions were observed at the clesrovimab binding site: K433R in a B.D.4.1.1 strain, C439R in an A.D.1.2 strain, N437S in an A.D.5.2 strain, and N444S in an A.D.3 strain, with three of the four appearing during the 2024–2025 season. These variants were not classified as resistance mutations, but their presence at a pharmacologically critical epitope warrants continued attention.

The nucleoprotein analysis likewise revealed signals relevant to antiviral therapy. The I129M substitution in the N protein, which is associated with resistance to zelicapavir, was detected in a B.D.E.1 sample from the 2024–2025 season at an intrapatient relative abundance of 0.05, indicating that the variant existed as a minor species within the quasispecies of that infection rather than as the dominant viral population. Such low-frequency variants are typically invisible to conventional diagnostic assays but can be resolved by deep sequencing, and their detection underscores the value of high-resolution genomic surveillance in identifying resistance determinants before they become established at the population level.

Multivariable analysis comparing the two seasons revealed several statistically significant differences associated with the 2024–2025 period. That season was characterized by an increased number of sequences belonging to large phylogenetic clusters, greater amino acid variability at antigenic site Ø of the F protein, and higher Ct values on diagnostic testing, which correspond to lower viral loads in respiratory samples. Hospital intensive care unit admissions were also fewer in the second season. While the observational design of the study precludes drawing direct causal links between nirsevimab deployment and these shifts, the concurrence of prophylaxis introduction with reduced disease severity, altered viral population structure, and expanded F protein variability provides a compelling rationale for sustained monitoring.

The overall message from the Lombardy surveillance program is one of cautious reassurance combined with vigilance. Nirsevimab breakthrough infections remained rare relative to the scale of the prophylaxis campaign, and bona fide resistance mutations were detected in only a handful of samples across two seasons. At the same time, the virus is demonstrably diversifying, with season-specific phylogenetic clusters and accumulating variation at antibody binding sites on the F protein. As monoclonal antibodies and vaccines become mainstays of RSV prevention worldwide, the Lombardy experience illustrates how whole-genome sequencing, phylogenetic clustering, and mutation-level analysis can be woven into routine public health practice, ensuring that shifts in viral evolution are detected early enough to inform and adjust prophylaxis strategies before they compromise protection of the most vulnerable patients.

Subject of Research: Genomic evolution and monoclonal antibody resistance of respiratory syncytial virus in Lombardy before and after nirsevimab introduction

Article Title: Genomic characterization of circulating respiratory syncytial virus strains in Lombardy before and after the introduction of nirsevimab prophylaxis

Article References: Uceda Renteria, S., Galli, C., Ferrari, G., Cossu, M. V., Lombardi, A., Tagliabue, C., Galli, G., Parisi, A., Pellegrinelli, L., Romano, G., Bono, P., Pitrolo, A. M. G., Salpini, R., Salvini, F., Svicher, V., Bosis, S., Callegaro, A., Gori, A., Baldanti, F., … Alteri, C. (2026). Genomic characterization of circulating respiratory syncytial virus strains in Lombardy before and after the introduction of nirsevimab prophylaxis. Genome Medicine. https://doi.org/10.1186/s13073-026-01768-x

Image Credits: AI Generated

DOI: 10.1186/s13073-026-01768-x

Keywords: respiratory syncytial virus, nirsevimab, genomic surveillance, viral evolution, monoclonal antibodies, fusion protein, phylogenetics, whole-genome sequencing, antiviral resistance, breakthrough infections, Lombardy, public health

The investigation was led by Reem M. Aljowaie, Ibrahim M. Aziz, Mohamed A. Farrag, Noorah A. Alkubaisi, Asma N. Alsaleh and Fahad N. Almajhdi of the Department of Botany and Microbiology at King Saud University. Between 2014 and 2020, the team collected 311 respiratory specimens from patients presenting with influenza-like illness in Riyadh. Each sample was screened by reverse transcription polymerase chain reaction, a molecular technique capable of detecting viral RNA with high sensitivity. Of the 311 specimens, 88, or 28.3 percent, tested positive for influenza A, while only six samples, representing 1.9 percent, were positive for influenza B virus. Although the number of influenza B detections was modest, the researchers sequenced the complete hemagglutinin and neuraminidase genes of these viruses, providing the full-length genetic data needed for rigorous evolutionary analysis.

Hemagglutinin and neuraminidase are the two surface proteins that define the antigenic identity of influenza viruses. Hemagglutinin mediates entry into host cells and is the principal target of neutralizing antibodies, while neuraminidase facilitates the release of newly formed viral particles. Mutations accumulating in these proteins can alter antigenic properties and, by extension, the degree of protection conferred by vaccination. The Riyadh team recorded mutations at both the nucleotide and amino acid levels, mapped N-linked glycosylation sites, and compared their sequences against WHO vaccine reference strains. They also generated six influenza B isolates from the 2014 to 2020 specimens and incorporated 31 previously published Riyadh sequences covering 2010 through 2025, allowing the analysis to extend across a decade and a half of local viral evolution.

The phylogenetic results revealed a clear lineage replacement event. Viruses belonging to the B/Yamagata lineage were detected in Riyadh in 2015, whereas samples from 2020 belonged exclusively to the B/Victoria lineage. Influenza B viruses are divided into these two genetically and antigenically distinct lineages, which co-circulated globally for decades before the B/Yamagata lineage dramatically declined after the COVID-19 pandemic. The Riyadh dataset mirrors this global pattern: among the sequenced isolates available for the full 2010 to 2025 period, no B/Yamagata-lineage viruses were detected in recent years, and sustained B/Victoria predominance was observed throughout the later portion of the surveillance window.

Within the B/Victoria lineage, the analysis showed that recent isolates from 2023 to 2025 carried the characteristic deletion of amino acids at positions 164 and 165 in the hemagglutinin protein. This deletion, located in or near antigenic regions of the protein, first emerged in globally circulating Victoria-lineage viruses and has become a defining feature of newer subclades. The Riyadh sequences from 2021 to 2025 all belonged to the V1A.3a.2 subclade, which has become the globally dominant form of B/Victoria. Earlier viruses in the dataset fell within subclades V1A.3 and related groups, illustrating the stepwise genetic drift that has characterized the lineage over the surveillance period.

Despite this ongoing evolution, the study found that the hemagglutinin and neuraminidase proteins of the circulating viruses were highly conserved relative to the WHO vaccine strains. Substitutions were identified in the major antigenic regions of hemagglutinin, including the 120-loop, the 150-loop, the 160-loop and the 190-helix, structural elements that antibodies recognize when they neutralize the virus. However, these changes were limited in number and did not translate into substantial genetic distance from the vaccine components. The B/Yamagata viruses from earlier years displayed lineage-specific glycosylation patterns, while the Victoria-lineage viruses maintained largely conserved N-linked glycosylation profiles, with one notable exception: some isolates showed a gain or loss of a glycosylation site at hemagglutinin position 197, a change that could potentially influence antigenicity and deserves continued monitoring.

Perhaps the most reassuring finding from a public health standpoint concerns vaccine compatibility. The researchers compared recent Riyadh isolates with the WHO-recommended vaccine strains B/Austria/1,359,417/2021 and B/Tokyo/EIS13-175/2025 and found that the local viruses remained genetically close to both, exhibiting only limited amino acid substitutions. This suggests that the influenza B component of seasonal vaccines has continued to match the viruses circulating in Riyadh, supporting the effectiveness of current vaccination strategies in the region. Because influenza B vaccine mismatch has historically contributed to reduced vaccine effectiveness in some seasons, this genetic concordance is a meaningful indicator for Saudi immunization planning.

The study also underscores the practical challenges of influenza B surveillance. With only 1.9 percent of the collected specimens testing positive for influenza B, the virus circulates at low levels in Riyadh compared with influenza A, and the number of sequences available for any given season is small. The authors are careful to frame their lineage replacement conclusion as reflecting the available surveillance dataset rather than an absolute claim of global or even national disappearance of B/Yamagata. Nevertheless, the finding aligns with international observations that B/Yamagata has not been robustly detected since around 2020, raising questions about whether the lineage may have gone extinct and whether quadrivalent vaccines, which include both B lineages, will continue to be necessary or whether trivalent formulations lacking B/Yamagata will become standard.

The research was approved by the Research Ethics Committee at King Saud University under Institutional Review Board number 14/4463/IRB 03/IRB, approved on December 3, 2014, and conducted in accordance with the Declaration of Helsinki, with informed consent obtained from all participants. The work was funded by the Ongoing Research Funding Program of King Saud University under grant ORF-2026-198. The authors declare no competing interests, and the article is published open access under a Creative Commons license.

For Saudi Arabia and the wider Middle East region, where long-term influenza B sequence data have historically been sparse, this fifteen-year record fills an important gap in the global map of influenza B evolution. The authors conclude that the predominance of B/Victoria and the non-detection of B/Yamagata within the available dataset underscore the need for continuous molecular surveillance to monitor viral evolution, assess vaccine strain compatibility, and support influenza prevention efforts in the kingdom. As influenza B continues its slow but steady genetic drift, sustained sequencing efforts in underrepresented regions such as Saudi Arabia will remain essential for ensuring that vaccine recommendations rest on a genuinely global picture of viral diversity.

Subject of Research: Long-term molecular epidemiology and genetic evolution of influenza B virus in Riyadh, Saudi Arabia, from 2010 to 2025

Article Title: Long-term molecular surveillance of influenza B virus in Riyadh, Saudi Arabia (2010–2025): lineage replacement, genetic evolution, and vaccine strain compatibility

Article References: Aljowaie, R. M., Aziz, I. M., Farrag, M. A., Alkubaisi, N. A., Alsaleh, A. N., & Almajhdi, F. N. (2026). Long-term molecular surveillance of influenza B virus in Riyadh, Saudi Arabia (2010–2025): lineage replacement, genetic evolution, and vaccine strain compatibility. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14442-9

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14442-9

Keywords: influenza B virus, B/Victoria lineage, B/Yamagata lineage, hemagglutinin, vaccine effectiveness, phylogenetic analysis, molecular epidemiology, lineage replacement, glycosylation, Saudi Arabia, viral evolution, surveillance