The research team, led by Mmabatho Mashapo and Thendo Mafuna of the University of Johannesburg together with colleagues at the University of South Africa and the Agricultural Research Council’s Onderstepoort Veterinary Research, analysed 23 isolates obtained from beef and pork samples purchased at retail outlets. After quality filtering, 18 high-quality whole genomes were retained. These were then placed alongside 356 publicly available food-associated genomes in a comparative framework, allowing the South African isolates to be situated within the global population structure of the species for the first time.

The methodological backbone of the study was core genome multilocus sequence typing, or cgMLST, a technique that compares the sequences of hundreds to thousands of genes shared by all strains in a species. By tallying the differences at these core loci, cgMLST produces a fine-grained measure of genetic relatedness that can reveal transmission chains, geographic clusters and evolutionary lineages with a resolution that older fingerprinting methods cannot match. In this analysis, the combined dataset resolved into four major lineages, and the South African isolates fell predominantly within a clade designated HC1490_10, a group that is widely distributed internationally.

Traditional multilocus sequence typing, which examines a smaller set of housekeeping genes and assigns each strain a sequence type or ST, added another layer of detail. The local isolates represented 11 distinct sequence types, including several that are potentially uncommon in the published literature: ST661, ST329, ST173 and ST352. At the same time, the researchers detected ST3, ST18 and ST178 among the South African samples, sequence types that belong to lineages known to be prevalent and widely distributed around the world. This mix of locally distinctive and globally shared types suggests that the meat supply carries both endemic diversity and strains with international connections.

Beyond relatedness, the team explored the pan-genome, the total complement of genes found across all strains of the species. Bacteria typically split their gene pool into a core of universally conserved genes and a vast accessory genome of genes present in only some strains. Yersinia enterocolitica showed what geneticists call an open pan-genome: as more genomes are added, new genes keep appearing, a pattern driven by a high proportion of accessory and so-called cloud genes, particularly in the global dataset. Open pan-genomes are signatures of substantial genomic plasticity, indicating that the species readily gains and loses DNA through horizontal gene transfer, the exchange of genetic material between organisms that reshapes bacterial populations over ecological timescales.

One of the most consequential questions for any foodborne pathogen survey is antimicrobial resistance. Here the study delivered a nuanced result. Profiling of the resistome, the full set of resistance-associated genes, revealed a conserved intrinsic resistome dominated by beta-lactamase genes, notably blaA and ampC, along with efflux-associated determinants that pump antibiotics out of the cell. These intrinsic genes are part of the species’ normal genetic makeup and are not typically associated with clinical treatment failure. By contrast, acquired resistance genes, which bacteria pick up from other organisms and which often confer clinically relevant drug resistance, were detected only at low frequencies, and intriguingly, they were confined to isolates belonging to the HC1490_10 clade.

The mobile genetic element analysis shed light on how this plasticity is achieved. The researchers identified a diverse array of plasmids, the small circular DNA molecules that bacteria exchange readily, and prophages, viral genomes integrated into the bacterial chromosome. Both play major roles in horizontal gene transfer and genome plasticity. Encouragingly, however, no plasmid-associated antimicrobial resistance genes were detected in the isolates studied, suggesting that the mobile elements circulating in these meat-associated populations are not currently ferrying clinically important resistance determinants between strains.

Virulence, not resistance, is the other half of the public health equation, and it was here that the study produced its most reassuring finding. The South African isolates lacked the plasmid-associated pathogenicity determinants that define dangerous strains, including the genes encoding the Type III secretion system, a molecular syringe that pathogenic yersiniae use to inject effector proteins into host cells and subvert the immune response. The local isolates were consequently classified as non-pathogenic biotype 1A. In stark contrast, the pathogenic lineage represented in the global dataset, designated HC1490_2, harboured both chromosomal and plasmid-encoded virulence factors, the full toolkit required to cause disease in humans.

These results place South African retail meat in a comparatively favourable light but come with important caveats. The dominance of non-pathogenic biotype 1A strains suggests a currently low virulence risk from the meat samples examined. Yet the presence of globally distributed lineages, including the clade in which acquired resistance genes were concentrated, underscores the potential for pathogenic variants to emerge or be introduced. Food production systems are dynamic, and the same open pan-genome that makes Yersinia enterocolitica so genomically flexible means that virulence and resistance traits can, in principle, move between lineages when conditions allow.

The authors argue that their findings make a direct case for integrating whole-genome sequencing into food safety and One Health surveillance frameworks, an approach that connects human, animal and environmental health into a single monitoring system. Genomic surveillance of this kind can trace contamination routes, flag the arrival of pathogenic clones, and detect emerging resistance before it becomes a clinical problem. For a country whose meat industry feeds millions and exports internationally, the message is clear: the bacteria on the supermarket shelf carry a genomic record of where they came from, and reading that record routinely could help keep one of food safety’s quieter threats from ever getting louder.

Subject of Research: Genomic epidemiology and antimicrobial resistance of Yersinia enterocolitica in South African meat and global populations

Article Title: Whole-genome sequencing reveals the genomic epidemiology of Yersinia enterocolitica in South African meat and global populations

Article References: Mashapo, M., Matle, I., Seakamela, E., & Mafuna, T. (2026). Whole-genome sequencing reveals the genomic epidemiology of Yersinia enterocolitica in South African meat and global populations. BMC Genomics. https://doi.org/10.1186/s12864-026-13409-z

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13409-z

Keywords: Yersinia enterocolitica, whole-genome sequencing, genomic epidemiology, antimicrobial resistance, virulence factors, pan-genome, cgMLST, food safety, meat contamination, South Africa, One Health, biotype 1A

The research team began with a large and clinically grounded collection: 373 Enterobacteriaceae isolates that had been recovered from routine diagnostic specimens and found to be resistant to third-generation cephalosporins. Because these isolates came from the clinical microbiology laboratory rather than from a targeted screening program, they represent the resistant organisms that clinicians actually encountered in practice. Every isolate was subjected to antimicrobial susceptibility testing and to polymerase chain reaction confirmation of bla_CTX-M-65, a deliberate step that guards against the false positives that can arise when sequence reads are assigned to closely related CTX-M alleles. Whole-genome sequencing followed, allowing the investigators to place each confirmed isolate within its species phylogeny, to characterize its full resistome and to extract and compare the plasmids carrying the resistance gene.

The headline finding from the local collection was one of relative rarity paired with striking breadth. Only 20 of the 373 isolates, or 5.4 percent, carried bla_CTX-M-65, confirming that this allele is a minority player among cephalosporin-resistant Enterobacteriaceae. Yet those 20 isolates were distributed across three distinct species: 14 Escherichia coli, 5 Salmonella enterica serovar Typhimurium and a single Klebsiella pneumoniae. That spread across genera is itself informative, because it suggests that bla_CTX-M-65 is not locked into a single bacterial lineage. Instead, the gene appears able to establish itself in genetically very different hosts, consistent with the idea that horizontal gene transfer, rather than clonal expansion alone, drives its dissemination.

The resistance phenotypes of these isolates added a sobering clinical dimension. All 20 were resistant to cefuroxime, an expected consequence of possessing an extended-spectrum beta-lactamase, but the co-resistance extended well beyond the beta-lactam class. Seventy percent were resistant to levofloxacin, a fluoroquinolone that is frequently used when cephalosporin therapy fails or when oral treatment is preferred. Multidrug resistance of this kind narrows therapeutic options significantly, particularly for pathogens such as Salmonella Typhimurium, where fluoroquinolones are a mainstay for invasive disease. The combination of a cephalosporin-hydrolyzing enzyme and fluoroquinolone resistance on the same bacterial background is a recurring pattern in Enterobacteriaceae, and this study confirms that bla_CTX-M-65-positive isolates fit squarely within it.

Phylogenetic analysis of the sequenced genomes revealed two episodes of likely within-hospital transmission hiding inside the otherwise diverse collection. Among the E. coli isolates, a pair belonging to sequence type ST155 differed by only 9 single nucleotide polymorphisms across their core genomes, despite having been recovered from different hospital departments. In genomic epidemiology, core-genome differences of that magnitude are generally interpreted as evidence of a very recent common ancestor, pointing to direct or indirect transmission of a single clone between wards. Similarly, the five Salmonella Typhimurium isolates formed a tight cluster belonging to ST34, with fewer than 20 core-genome SNPs separating members of the group, and the affected patients included children treated in pediatrics. Together these findings illustrate how genomic resolution can uncover transmission chains that routine susceptibility testing would never flag.

Perhaps the most clinically alarming single isolate was the K. pneumoniae strain, which belonged to ST11 and carried both bla_CTX-M-65 and bla_KPC-2. The ST11 lineage is already notorious as one of the principal vehicles for carbapenem resistance in K. pneumoniae worldwide, and bla_KPC-2 encodes a carbapenemase that inactivates the last-line beta-lactam antibiotics used against multidrug-resistant Gram-negative infections. The co-occurrence of a carbapenemase and an extended-spectrum cephalosporinase in the same genome means the organism carries enzymatic firepower against nearly the entire beta-lactam arsenal. Whether the two genes reside on the same plasmid or on separate elements was not the central question of the study, but their coexistence in a single ST11 background underscores how resistance determinants accumulate on successful lineages, creating organisms that are progressively harder to treat.

To place these local findings in a global context, the investigators compiled and analyzed 1,421 bla_CTX-M-65-positive plasmids from public sequence databases. This comparative step is where the study’s architecture becomes most distinctive. Rather than treating the plasmid as an accessory detail, the team asked which replicon types dominate the plasmids that carry this particular gene and how conserved their backbones are across geography and time. The answer was a small set of recurrent architectures. IncHI2 plasmids, large low-copy-number elements with a well-documented role in carrying multiple resistance genes, were prevalent, as were members of the IncF family, specifically IncFIA/IB combinations and IncFII/R plasmids. The prominence of IncF-type plasmids aligns with their established reputation as the workhorses of CTX-M dissemination in E. coli, while the frequent appearance of IncHI2 elements highlights that versatile, broad-host-range plasmids also serve as major carriers of this allele.

Backbone comparison delivered the study’s most geographically expansive insight. Representative plasmids sequenced in this study showed high backbone similarity to bla_CTX-M-65-carrying plasmids previously reported from China and South Korea, indicating that the same underlying plasmid frameworks, rather than merely the same gene, are circulating across the region. In other words, the dissemination of CTX-M-65 appears to follow a two-track model: diverse bacterial clones pick up the gene, but they pick it up on a limited set of shared plasmid scaffolds. This pattern matters for surveillance, because tracking the plasmid backbones, and not just the bacterial lineages, can reveal importation events and cross-border spread that host-based analysis alone would miss. It also matters mechanistically, since a conserved backbone implies conserved fitness properties, copy number and transfer machinery that may explain why these particular plasmids succeed.

The analysis of the DNA immediately surrounding bla_CTX-M-65 added a third layer to the picture. Insertion sequences are short mobile DNA elements that can shuttle genes between chromosomes and plasmids, and certain ones are known accomplices of CTX-M genes. ISEcp1 in particular is famous for its role in mobilizing bla_CTX-M alleles by providing promoter sequences and acting as a transposition vehicle, and IS26 has become synonymous with the assembly of multidrug-resistance regions through a replicative transposition mechanism. In this study, ISEcp1, IS26 and IS903 were the mobile elements most commonly identified within the bla_CTX-M-65-associated genetic contexts, painting a consistent picture of a gene that has been repeatedly captured, re-packaged and redeployed by the standard genetic toolkit of the Enterobacteriaceae resistome.

Taken together, the study delivers a message that is more nuanced than a simple alarm. On one hand, bla_CTX-M-65 is uncommon, appearing in only 5.4 percent of cephalosporin-resistant isolates in this collection, and its detection should not overshadow the dominant CTX-M lineages. On the other hand, its behavior is instructive: it colonizes multiple species, rides on a small number of successful plasmid backbones that span international boundaries, hitches its mobility to well-known insertion sequences and occasionally lands in the most dangerous possible hosts, such as carbapenemase-producing ST11 K. pneumoniae. The identification of a clonally related E. coli pair spanning hospital departments and an ST34 Salmonella cluster within pediatrics demonstrates that genomic surveillance can catch transmission events that conventional methods overlook. The authors’ conclusion, that the diversity of bacterial hosts combined with related plasmid backbones demands continued genomic monitoring, is a fitting one. As sequencing becomes cheaper and databases grow, the ability to distinguish a gene hitchhiking on a shared plasmid from an independently acquired allele will increasingly determine how effectively hospitals and public health agencies can interrupt the silent traffic in resistance genes that moves between wards, species and countries.

Subject of Research: Genomic epidemiology of CTX-M-65-producing multidrug-resistant Enterobacteriaceae and the plasmid backbones carrying the resistance gene

Article Title: Genomic epidemiology of blaCTX−M−65-positive clinical Enterobacteriaceae reveals clonal diversity and shared plasmid backbones

Article References: Chen, X., Zhang, X., Song, J., Zeng, S., Huang, Y., & Li, X. (2026). Genomic epidemiology of blaCTX−M−65-positive clinical Enterobacteriaceae reveals clonal diversity and shared plasmid backbones. BMC Genomics. https://doi.org/10.1186/s12864-026-13446-8

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13446-8

Keywords: CTX-M-65, Enterobacteriaceae, antimicrobial resistance, extended-spectrum beta-lactamases, plasmids, whole-genome sequencing, Escherichia coli, Salmonella, Klebsiella pneumoniae, genomic epidemiology, mobile genetic elements, hospital transmission

The team began by resolving the population structure of Lineage 3 using phylogenetic reconstruction and hierarchical Bayesian clustering. This analysis showed that the dominant clade, known as L3.1.1, accounts for more than 95 percent of all Lineage 3 isolates and can be subdivided into six distinct monophyletic sublineages, designated L3.1.1.1 through L3.1.1.6. Each of these sublineages displays its own geographic distribution and demographic trajectory, meaning that what has historically been treated as a relatively uniform lineage is in fact a collection of genetically coherent populations with separate evolutionary histories. The researchers also compiled diagnostic SNP markers for each sublineage, providing a practical toolkit that other laboratories can use to classify isolates without needing to reconstruct full phylogenies for every new sample.

Phylogeographic reconstruction pointed to South Asia as the probable origin of most of the six sublineages, from which multiple intercontinental dispersal events radiated outward. This pattern fits the broader picture of tuberculosis spreading along historical human migration routes, and the study found that many European isolates were indeed associated with migration into the continent. However, the story did not end there. Using genomic clustering, terminal branch lengths, and a metric called time-scaled haplotypic density, the researchers assessed whether isolates found outside endemic regions reflected imported cases or sustained local transmission. Strikingly, they identified 1,399 isolates consistent with potential local transmission, demonstrating that Lineage 3 is not merely hitching rides with migrating populations but is, in some places, establishing self-sustaining transmission chains far from its historical range.

One of the most technically interesting aspects of the study is its use of time-scaled haplotypic density, or THD, a measure that captures how densely related genomes cluster through time and can signal recent, rapid transmission even when classical clustering criteria are ambiguous. Combined with terminal branch length analysis, which flags isolates sitting on short phylogenetic branches as likely products of recent transmission, these methods allowed the team to distinguish between the passive movement of bacteria across borders and their active amplification within new host populations. Phylodynamic modeling of effective population size through time revealed recent expansion in three sublineages in particular: L3.1.1.1, L3.1.1.5, and L3.1.1.6. These demographic signals suggest that certain branches of Lineage 3 are not just surviving outside their ancestral homelands but growing.

The drug-resistance findings are perhaps the most clinically urgent part of the work. Across the dataset, 29.8 percent of Lineage 3 isolates carried mutations associated with resistance to anti-tuberculosis drugs, a substantial burden that varies dramatically between sublineages. The highest burden was concentrated in L3.1.1.6, where 45.4 percent of isolates carried resistance-associated mutations, and where the researchers documented a marked enrichment for pre-extensively drug-resistant strains. Pre-extensively drug-resistant tuberculosis sits one step below the most intractable form of the disease, typically combining multidrug resistance with additional resistance to fluoroquinolones, and its concentration within a single expanding sublineage is a warning sign that genomic surveillance programs cannot afford to ignore.

Why should highly resistant bacteria be able to spread at all? Resistance mutations often impose a fitness cost, slowing bacterial growth and reducing transmissibility. The study offers a potential answer in the form of compensatory evolution. Within L3.1.1.6, the researchers found that compensatory mutations in the rpoA and rpoC genes, which encode subunits of the RNA polymerase complex, were associated with elevated time-scaled haplotypic density. These genes are the classic site of fitness-restoring mutations in rifampicin-resistant tuberculosis, because they can offset the cost of resistance mutations in rpoB, the primary target of the drug. The association between rpoA and rpoC compensatory mutations and higher THD values indicates that these secondary changes may be restoring the transmissibility of highly resistant clones, effectively allowing them to compete with drug-susceptible strains and facilitating their spread through populations.

Genome-wide scans for positive selection added another layer to the adaptive story. By comparing gene-wise pN/pS profiles, a measure of nonsynonymous to synonymous polymorphism that flags genes under diversifying selection, across the sublineages of Lineage 3 and against Lineages 2 and 4, the team identified signatures of adaptation that differed between geographically defined clusters. Notably, sublineage-resolved selection analyses highlighted the gene Rv1500 as consistently enriched in European local transmission clusters, suggesting that specific genetic changes may be helping the bacterium adapt to transmission in new host populations and environments. The country-specific distributions of positively selected mutations in places such as Tanzania, Norway, and Sudan further underscore how local conditions can shape the evolutionary trajectory of distinct bacterial populations.

The comparative framing of the study also matters. Lineage 2, which includes the Beijing family, and Lineage 4, the globally dominant Euro-American lineage, have been the focus of most genomic epidemiology of tuberculosis. By systematically comparing terminal branch lengths, ancestral mutation profiles, and pN/pS patterns across Lineages 2, 3, and 4, the researchers were able to place Lineage 3’s evolution in context, showing that its sublineages exhibit heterogeneous trajectories rather than a single uniform pattern of spread. This heterogeneity is the central message of the work: global dissemination of Lineage 3 is largely driven by migration, but certain sublineages show clear evidence of local amplification and expansion beyond their historical range, a distinction that only sublineage-resolved analysis can reveal.

For public health, the implications are concrete. If surveillance systems classify Lineage 3 isolates only at the lineage level, they risk missing the emergence of locally transmitting, drug-resistant clones such as those in L3.1.1.6. The diagnostic SNP markers published with this study offer a low-cost way to integrate sublineage typing into routine workflows, and the demonstration that compensatory mutations correlate with transmission potential suggests that monitoring for rpoA and rpoC changes could help prioritize which resistant clusters warrant the most aggressive public health response. As drug-resistant tuberculosis continues to challenge control efforts worldwide, studies like this one show that the fine-grained evolutionary history of bacterial populations is not an academic curiosity but a practical map of where the next outbreaks are most likely to ignite.

Subject of Research: Genomic epidemiology and evolutionary dynamics of drug-resistant Mycobacterium tuberculosis Lineage 3

Article Title: Emergence of locally transmitting and drug-resistant clones shapes global expansion of Mycobacterium tuberculosis Lineage 3

Article References: Zhu, C., Ni, M., Mo, M., Wu, Z., Nadire, A., Huang, Z., & Li, W. (2026). Emergence of locally transmitting and drug-resistant clones shapes global expansion of Mycobacterium tuberculosis Lineage 3. Genome Medicine. https://doi.org/10.1186/s13073-026-01789-6

Image Credits: AI Generated

DOI: 10.1186/s13073-026-01789-6

Keywords: Mycobacterium tuberculosis, Lineage 3, genomic epidemiology, drug resistance, phylogenetics, transmission dynamics, phylogeography, compensatory evolution, pre-extensively drug-resistant tuberculosis, rpoA, rpoC, genomic surveillance

Hand, foot and mouth disease is a common childhood illness caused by several enteroviruses, most notably enterovirus A71 and coxsackievirus A16. While most infections resolve with mild fever, mouth ulcers and a characteristic rash on the hands, feet and buttocks, enterovirus A71 is notorious for its capacity to invade the central nervous system. Infected children can develop brainstem encephalitis, acute flaccid paralysis, pulmonary edema and cardiogenic shock, complications that can progress from first symptoms to death within hours. Vietnam has experienced repeated waves of severe hand, foot and mouth disease over the past two decades, and the 2023 outbreak raised urgent questions about which viral lineage was responsible and why the population appeared so vulnerable.

The investigation centered on enterovirus A71 subgenogroup B5, a variant that had been circulating elsewhere in the Asia-Pacific region before its appearance in Vietnam. Genomic analysis of viruses recovered from patients during the 2023 outbreak revealed a striking pattern: the Vietnamese B5 sequences were tightly clustered, indicating that the entire outbreak descended from a single introduction event rather than from multiple independent importations. This observation has important implications for outbreak preparedness, because it suggests that a single crossing of a border by one infected individual can be sufficient to seed a nationwide epidemic when the conditions are right.

One of the most intriguing questions the researchers addressed was whether subgenogroup B5 had evolved the ability to evade immunity generated by earlier enterovirus A71 strains. Vietnam had previously experienced outbreaks caused by other subgenogroups, including B5 viruses that circulated as far back as 2014. If the 2022 and 2023 viruses had drifted antigenically away from their predecessors, previously acquired immunity would offer little protection, explaining the severity of the new epidemic. To test this hypothesis, the team collected convalescent plasma from patients infected with subgenogroup B5 in both 2014 and 2023 and measured how effectively the antibodies in these samples could neutralize contemporary viruses in the laboratory.

The results were clear and, in a sense, reassuring. Plasma from patients infected in 2014 neutralized the 2023 viruses with titers comparable to those achieved by plasma from patients infected in 2023, and the same held true in the reverse direction. In other words, the antigenic properties of the virus had not appreciably changed over the nine-year interval, and there was no evidence of immune evasion. The severity of the 2023 outbreak therefore could not be attributed to a viral escape from pre-existing immunity. Instead, the explanation lay in the age structure of susceptibility within the population, particularly among the youngest children who had never encountered any enterovirus A71 strain.

Serological surveys conducted in Ho Chi Minh City revealed the scale of this vulnerability. At one month before the start of the outbreak, only 6.7 percent of children aged zero to under three years carried neutralizing antibodies against enterovirus A71. Even at six months before the outbreak began, the figure was similarly low. This meant that the vast majority of infants and toddlers in the city, the group at highest risk of severe disease, had no immunological defense against the incoming virus. When subgenogroup B5 arrived, it found an almost entirely susceptible cohort in the exact age bracket where infection is most likely to turn dangerous.

The study did not stop at documenting susceptibility before the outbreak. The researchers repeated their serological measurements as the epidemic unfolded, and the results traced the arc of the outbreak in real time. As the proportion of young children with neutralizing antibodies rose, the number of enterovirus A71 infected patients residing in Ho Chi Minh City fell. This inverse relationship, in which increasing population immunity coincided with declining transmission, suggests that the outbreak burned through the susceptible pool until so many children had been infected and immunized that the virus could no longer spread efficiently. It also demonstrates that serosurveillance, the systematic measurement of antibody levels in the population, can serve as a practical early warning tool.

The implications of this serosurveillance-based approach extend well beyond a single outbreak. Traditional disease surveillance relies on detecting clinical cases, which by definition identifies an outbreak only after substantial transmission has already occurred. Measuring the fraction of the population that lacks neutralizing antibodies, by contrast, can quantify the size of the susceptible reservoir before any cases appear. In the case of enterovirus A71, the Vietnamese data show that a seroprevalence of under seven percent in children under three years of age signaled an acute risk of severe epidemic emergence. Health authorities monitoring antibody levels in young children could, in principle, identify comparable windows of vulnerability in advance and intensify clinical preparedness, public communication and, where available, vaccination efforts accordingly.

Enterovirus A71 remains an active public health threat concentrated in the Asia-Pacific region, where periodic outbreaks of severe hand, foot and mouth disease continue to burden pediatric health systems. Vaccines against the virus have been developed and licensed in China, but coverage across the wider region remains incomplete, and no vaccine is universally deployed. The Vietnamese experience underscores how quickly a single imported lineage can exploit gaps in population immunity, and how the cyclical nature of enterovirus transmission creates recurring cohorts of susceptible infants between epidemic waves. The authors note that the virus has a high potential to become a global problem, and that it should therefore be closely monitored beyond its current geographic range.

Collectively, the study offers a model for investigating the emergence of any pathogen that causes severe disease in a defined age group. By integrating viral genomics, antigenic characterization and longitudinal serology, the researchers were able to rule out immune evasion, pinpoint the timing and origin of the introduction, quantify the susceptibility of the at-risk population and connect rising immunity to declining transmission. These insights into the epidemiological factors driving enterovirus A71 emergence are intended to inform outbreak preparedness and response, and to support the development of serosurveillance-based risk assessment frameworks that could be applied to enteroviruses and other emerging infectious threats alike.

Subject of Research: Virological and epidemiological investigation of a severe enterovirus A71 hand, foot and mouth disease outbreak in Vietnam in 2023

Article Title: Virological and epidemiological investigations of a severe hand foot and mouth disease outbreak, Vietnam, 2023

Article References: Nguyet, L. A., Anh, N. T., Quy, D. T., Hong, N. T. T., Minh, N. N. Q., Nguyen, P. N. T., Quang, P. V., Han, D. D. K., Ny, N. T. H., Nhu, L. N. T., Truc, T. H. C., Thuy, C. T., Hoang, N. N., Thien, T. B., Thanh, L. K., Hung, N. T., Khanh, T. H., Hiep, C. M., Ngoc, N. M., … Tan, L. V. (2026). Virological and epidemiological investigations of a severe hand foot and mouth disease outbreak, Vietnam, 2023. PLOS Neglected Tropical Diseases, 20(10), e0014789. https://doi.org/10.1371/journal.pntd.0014789

Image Credits: AI Generated

DOI: 10.1371/journal.pntd.0014789

Keywords: enterovirus A71, hand foot and mouth disease, subgenogroup B5, Vietnam, serosurveillance, neutralizing antibodies, outbreak, pediatric infectious disease, genomic epidemiology, immune evasion, public health, Asia-Pacific

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 research team, led by Abdulwasid Abubakari and Charity Ahiabor of Accra Technical University in Ghana, together with George Osei-Adjei and corresponding author Hizbullah Khan of Guangdong Medical University in China, assembled and analyzed 467 high-quality P. aeruginosa genome assemblies. Every genome included in the analysis met a strict quality threshold of greater than 95 percent completeness, and the collection spanned 17 African countries over a remarkable 26-year window, from 1998 to 2024. All of the data were drawn from publicly available assemblies in the NCBI database, meaning the study required no new sampling or ethics approvals, but its systematic reanalysis with standardized tools allowed comparisons that had previously been impossible across such a geographically and temporally scattered dataset.

The methodological backbone of the study was a pangenome analysis, an approach that partitions the collective gene repertoire of a bacterial species into the core genome shared by all isolates and the accessory genome carried by only some. The researchers used iterative pangenome clustering across seven amino acid identity thresholds ranging from 50 to 98 percent, a strategy that captures gene families at different levels of evolutionary relatedness. They complemented this with exploratory core-genome single nucleotide polymorphism phylogenetics to reconstruct the evolutionary relationships among isolates, and with pangenome-wide association studies, or Pan-GWAS, to detect accessory genes whose presence correlates with specific geographic regions.

The results revealed an exceptionally “open” pangenome architecture, quantified by a scaling exponent of gamma equal to 0.23. In pangenome mathematics, a low gamma value signals that each newly sequenced genome is likely to bring a substantial number of previously unseen genes into the catalogue, indicating enormous genetic diversity and extensive gene acquisition. Across the African population, the analysis catalogued 25,501 distinct gene families, a figure that underscores how genetically versatile this pathogen is on the continent. An open pangenome also has practical implications for surveillance: it suggests that local African isolates may carry functional repertoires that global reference-based analyses routinely miss, and that continued sampling will keep yielding new genetic material rather than approaching a saturation point.

Phylogenomic reconstruction resolved 466 unique core genome SNP profiles, and the resulting tree was characterized by strong regional clustering. In other words, isolates from the same part of the continent tended to be more closely related to each other than to isolates from distant regions, a pattern consistent with largely local transmission and evolution rather than a single continental epidemic lineage sweeping across borders. This regional structure matters for public health planning, because it implies that resistance control strategies may need to be tailored to regional population dynamics rather than applied as one uniform continental blueprint.

Perhaps the most striking finding is what the authors describe as an “African Clonal Inversion.” Globally, the sequence type known as ST235 is regarded as the archetypal P. aeruginosa super-clone, a multidrug-resistant lineage that has spread through hospitals worldwide and dominates high-risk clone surveys on other continents. In the African dataset, however, the picture is reversed. Among the 71 isolates identified as belonging to high-risk clones, ST111 accounted for 46.5 percent, or 33 of 71 isolates, outnumbering ST235, which represented 14.1 percent or 10 of 71, by more than three-fold. This inversion suggests that the forces shaping P. aeruginosa success in African healthcare settings differ from those driving the global spread of ST235, and it raises the possibility that ST111 possesses ecological or resistance advantages that are particularly effective in African hospital environments.

The study also mapped the resistome, the complete set of antimicrobial resistance genes carried by the isolates, and found it to be geographically stratified in a way that has direct clinical consequences. The gene blaNDM-1, which encodes the New Delhi metallo-beta-lactamase and confers resistance to some of the most powerful last-line carbapenem antibiotics, dominated in Northern and Eastern African country subsets. Meanwhile, blaVIM-2, another metallo-beta-lactamase gene but from a distinct enzymatic family, was concentrated in Southern Africa. Because both genes threaten the carbapenem class that clinicians rely on when treating severe P. aeruginosa infections, their uneven continental distribution means that empirical treatment guidelines and diagnostic panels may need to account for which resistance determinants are actually circulating in a given region rather than assuming a homogeneous African resistance landscape.

Beyond resistance genes, the Pan-GWAS analysis uncovered regional associations in the accessory genome that hint at how local P. aeruginosa populations differ in their broader functional biology. The researchers found enrichment of a Type VI Secretion System component, the tla3 gene, in North African isolates. The Type VI Secretion System is a molecular spear-like apparatus that bacteria use to inject effector proteins into competing microbes and host cells, playing a major role in interbacterial competition and virulence. In West Africa, the analysis identified enrichment of phenazine biosynthesis clusters, including the phzA2 gene. Phenazines are redox-active secondary metabolites that contribute to P. aeruginosa’s survival, biofilm formation and pathogenicity. These regional functional signatures suggest that different African populations may have evolved distinct ecological strategies, potentially shaped by local hospital conditions, antibiotic prescribing practices, microbial competition and environmental reservoirs.

To make these findings actionable rather than merely archival, the team integrated the entire dataset into a live interactive dashboard hosted on Microreact, a widely used platform for visualizing genomic epidemiology. This means that researchers, public health officials and clinicians across Africa and beyond can explore the phylogenetic trees, geographic distributions and resistance gene patterns themselves, updating the picture as new genomes are deposited. Such open infrastructure is particularly valuable on a continent where surveillance capacity varies widely between countries, because it lowers the technical barrier for local laboratories to place their own isolates in continental and global context.

The study’s authors are careful to frame their work as a foundation rather than a finished map. The dataset, while the largest of its kind for the continent, still reflects the uneven distribution of sequencing capacity and data deposition across Africa, and the researchers themselves categorized some countries with limited sampling as yielding only exploratory Pan-GWAS results. Nevertheless, by demonstrating that African P. aeruginosa populations have their own clonal hierarchy, their own resistance geography and their own accessory gene signatures, the analysis makes a compelling case that the continent can no longer be treated as a footnote in global pathogen genomics. As antimicrobial resistance continues to escalate worldwide, understanding how Priority 1 pathogens evolve in undermapped regions is not just an African concern but a global one, and this study provides both the evidence and the tools to begin that work in earnest.

Subject of Research: Pan-African genomic population structure and antimicrobial resistance distribution of Pseudomonas aeruginosa

Article Title: Pan-African genomics of Pseudomonas aeruginosa highlights regional population structure and AMR stratification

Article References: Abubakari, A., Ahiabor, C., Osei-Adjei, G., & Khan, H. (2026). Pan-African genomics of Pseudomonas aeruginosa highlights regional population structure and AMR stratification. BMC Genomics. https://doi.org/10.1186/s12864-026-13365-8

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13365-8

Keywords: Pseudomonas aeruginosa, pangenomics, antimicrobial resistance, Africa, genomic epidemiology, high-risk clones, resistome, ST111, ST235, Pan-GWAS, MLST, BMC Genomics

Salmonella Typhimurium is among the leading causes of foodborne gastroenteritis worldwide, and its monophasic variant—distinguished serologically by the absence of one of its two flagellar phases—has surged in prevalence across Europe, the Americas and Asia over recent decades. The lineage, which belongs to sequence type 34 and typically displays the antigenic formula 4,[5],12:i:-, has repeatedly been implicated in outbreaks linked to pork, poultry and processed foods. Yet despite its clear epidemiological importance, the genetic determinants that allowed this clone to outcompete its biphasic ancestor, the previously prevalent ST19 lineage, had remained uncertain. The new study set out to resolve that question at unprecedented scale.

The team’s comparative analysis of tens of thousands of genomes revealed a striking pattern: the expanding ST34 clone carried a frameshift mutation in dinB, the gene encoding a translesion DNA synthesis polymerase also known as DNA polymerase IV. The mutation, a deletion of a single thymine residue within a homopolymeric tract of seven thymidines near the 5′ end of the gene, introduces a premature stop codon that truncates the 39.7-kilodalton DinB protein to a nonfunctional fragment of roughly 1.9 kilodaltons. Because DinB is normally involved in bypassing damaged DNA templates and in generating genetic diversity under stress, its loss initially appears counterintuitive for a pathogen on the rise.

Functional experiments, however, demonstrated that the crippled polymerase has far-reaching downstream consequences. Transcriptomic profiling showed that the frameshift dinB mutation rewires the expression of flagellar genes, altering the balance between the two phase-one and phase-two flagellin systems that Salmonella uses to evade host immune detection. Specifically, the mutation led to transcriptional changes that favored retention of fliC, which encodes phase-one flagellin, and set the stage for the subsequent loss of fljB, the gene encoding phase-two flagellin. Western blot analyses confirmed that dinB-mutant strains displayed an increased proportion of cells expressing FliC, while in vitro motility assays showed that swimming ability was preserved despite the underlying genetic upheaval.

The physiological consequence of this reprogramming became apparent in infection models. Using transposon insertion sequencing and in vivo competition experiments in mice, the researchers found that the requirements for successful gut colonization shifted once fljB was lost. Genes that were dispensable, or even costly, in the ancestral background became essential or advantageous in the mutant context, and vice versa. The frameshift dinB strain carrying the fljB deletion outcompeted the previously prevalent biphasic ST19 lineage in the intestine, indicating that the combination of the polymerase defect and flagellin loss conferred a measurable competitive advantage within the host environment.

To move beyond correlation, the authors built a temporal evolutionary model that simulated the dynamics of four competing lineages: biphasic ST19, biphasic ST34, ST34 carrying the frameshift dinB, and monophasic ST34 carrying both the frameshift and the fljB deletion. The modeling demonstrated that the chronological order of the events matters critically. The dinB mutation had to precede the loss of fljB for the monophasic clone to expand as observed, and the simulated selection coefficients derived from the model were quantitatively consistent with selection estimates computed from real-world changes in genotype frequencies among human clinical isolates. Sensitivity analyses confirmed that the conclusion held regardless of the initial frequency of ST34, the presence or absence of spatial population structure, or the precise metric used to quantify selection.

This ordered dependency is what the researchers describe as a stepwise pathoadaptation model: a sequence of gene-loss events in which each deletion reshapes the genetic background so that the next loss becomes beneficial rather than deleterious. The concept echoes a growing recognition in microbial evolution that genome reduction can be a creative force. Recent work on Vibrio parahaemolyticus, for example, showed that wave succession within a pandemic clone was likewise driven by gene loss, and earlier studies documented how monophasic Salmonella Typhimurium microevolved during a prolonged epidemic in the United Kingdom. The new study, however, is notable for linking the ecological success of a zoonotic lineage to a specific, mechanistically validated chain of molecular events.

The broader implications extend to public health forecasting. If the emergence of major bacterial clones can depend on relatively simple, ordered mutational steps, then surveillance systems that monitor homopolymeric tracts and other mutation-prone loci may gain predictive power over which lineages are poised to expand. The study’s data resources—including genomic data deposited at the China National GeneBank Database, Enterobase and NCBI, transcriptomic data under accession GSE280131, proteomic data via PRIDE, and transposon-sequencing reads under BioProject PRJNA1347559—provide a substantial foundation for such efforts. The mathematical model code has also been made publicly available on GitHub, enabling other groups to test the generality of the sequential gene-loss framework in other pathogens.

At the same time, the work underscores how little of bacterial adaptation is driven by gene acquisition alone. Monophasic ST34 also carries traits such as copper resistance and heavy-metal tolerance that have been implicated in its persistence in livestock production environments, and antimicrobial resistance remains a defining feature of many circulating clones. But the new analysis places gene loss at the center of the lineage’s rise, reframing flagellar phase variation—a long-studied quirk of Salmonella biology—as a decisive axis of clonal competition. As the authors note, understanding the genetic factors facilitating the emergence of infectious diseases is critical, and this study delivers a concrete mechanistic answer for one of the most consequential zoonotic pathogens of the modern food system. The lesson is uncomfortable but clarifying: for bacteria, sometimes less is more, and the road to pandemic status can be paved by the genes a pathogen leaves behind.

Subject of Research: Stepwise gene loss driving the clonal expansion of monophasic Salmonella Typhimurium ST34

Article Title: Sequential gene loss promotes expansion of monophasic Salmonella Typhimurium ST34

Article References: Wu, X., Wang, T., Jia, C., Zhou, H., Li, Y., Baker, S., & Yue, M. (2026). Sequential gene loss promotes expansion of monophasic Salmonella Typhimurium ST34. Nature Microbiology. https://doi.org/10.1038/s41564-026-02483-4

Image Credits: AI Generated

DOI: 10.1038/s41564-026-02483-4

Keywords: Salmonella Typhimurium, monophasic ST34, gene loss, dinB, flagellin, fljB, pathoadaptation, bacterial evolution, genomic epidemiology, foodborne pathogen, zoonotic disease, Nature Microbiology

A new study published in Nature introduces Delphy, a scalable Bayesian phylogenetics platform designed from the ground up for near-real-time analysis of outbreak-scale datasets. The work addresses a bottleneck that has frustrated the genomics community since 2020: how to preserve the statistical rigor of Bayesian inference while making it fast enough to run continuously on datasets containing hundreds of thousands of genomes. The authors demonstrate that Delphy can produce dated, uncertainty-aware phylogenies from massive SARS-CoV-2 datasets on timescales of hours rather than days or weeks, opening the door to a style of genomic epidemiology in which phylogenetic estimates are refreshed as routinely as case counts.

The core challenge Delphy tackles is one of combinatorial explosion. Bayesian phylogenetic inference requires exploring an astronomically large space of possible trees, branch lengths, and substitution model parameters, typically via Markov chain Monte Carlo (MCMC) sampling. Each step of an MCMC chain proposes a small change to the current state of the tree and evaluates how well the resulting configuration explains the sequence data, a calculation whose cost scales with both the number of taxa and the length of the genome alignment. With a few hundred genomes, a desktop workstation can handle the workload. With hundreds of thousands, the likelihood evaluations become prohibitively expensive, and the mixing of the chain—the efficiency with which it explores the space of trees—deteriorates because the vast majority of proposed moves are rejected. Traditional implementations such as BEAST, which has served the field admirably for years, were architected for datasets orders of magnitude smaller than those generated during the pandemic.

Delphy’s designers approached the problem by rethinking the inference engine rather than simply optimizing existing code. The platform restructures the likelihood computation to take advantage of modern hardware accelerators, particularly graphics processing units (GPUs), which excel at the kind of massively parallel arithmetic that underlies phylogenetic likelihood calculations. In a phylogenetic likelihood evaluation, the probability of observing the sequence data at each site of the genome must be computed for every node of the tree, and these computations are largely independent of one another. By mapping them onto thousands of parallel processing cores, Delphy amortizes the cost of each likelihood evaluation across hardware that consumer laptops and cloud instances now routinely carry. The result is a dramatic speedup in the inner loop of Bayesian inference, the very component that dominated runtime in earlier tools.

Hardware alone, however, would not have been sufficient. The study also describes algorithmic innovations in how the chain explores tree space and how the analysis is partitioned. Rather than requiring the entire dataset to be re-analyzed from scratch each time new genomes arrive, Delphy is built to support incremental updates, in which an existing posterior sample of trees is extended and refined as additional sequences become available. This design mirrors the operational rhythm of outbreak response, where sequencing data arrive in a continuous stream and analysts need updated estimates on a daily or even hourly cadence. The ability to warm-start an analysis from a previous posterior, rather than beginning each run cold, converts what was historically a batch process into something closer to a living model of an epidemic.

Another distinguishing feature of the platform is its treatment of time. During the COVID-19 pandemic, the field converged on the value of time-calibrated phylogenies, in which branch lengths are expressed in units of calendar time using sampling dates as calibration points. These dated trees allow epidemiologists to estimate when lineages diverged, when a variant likely entered a region, and how quickly lineages were growing or declining in frequency. Delphy incorporates temporal structure directly into its Bayesian model, jointly estimating the evolutionary rate and the timing of divergence events alongside the tree topology. Crucially, it retains full posterior distributions over these quantities, so that an analyst can report not just a point estimate of when a lineage emerged but a credible interval that honestly reflects the limits of the data. In fast-moving outbreak situations, where decisions about border measures, vaccine updates, and public communications hinge on timing estimates, that quantified uncertainty is not a luxury; it is the difference between a defensible inference and an overconfident one.

The authors validate the platform on datasets drawn from the SARS-CoV-2 pandemic, the largest real-world stress test genomic epidemiology has ever faced. Global repositories accumulated many millions of viral genomes during that outbreak, and even curated subsets routinely exceeded the practical limits of legacy Bayesian tools. Delphy’s benchmarks show that analyses on datasets of this scale, which would have been effectively impossible with prior software, complete in hours on appropriate hardware, with posterior estimates that are consistent with those obtained by slower reference methods on smaller subsets. This kind of cross-validation matters: speed is worthless if the fast answer is wrong. By demonstrating agreement between its accelerated inference and established approaches on tractable data, the study builds the case that Delphy’s approximations and engineering choices preserve the statistical integrity that Bayesian methods are meant to guarantee.

The implications for public health practice extend well beyond coronaviruses. The same architecture applies to any rapidly evolving pathogen for which dense genomic sampling is available, including influenza, respiratory syncytial virus, dengue, mpox, and foodborne bacterial outbreaks. In each of these settings, the operational question is similar: can a public health laboratory turn a week’s worth of new genomes into an updated picture of transmission before the picture changes again? A tool that delivers dated phylogenies with quantified uncertainty on a near-real-time cadence shifts genomic epidemiology from retrospective analysis toward genuine situational awareness. It also lowers the barrier for smaller laboratories and public health agencies in low-resource settings, since the computational demands, while substantial, are within reach of cloud computing budgets that are far smaller than the supercomputing clusters previously imagined necessary for pandemic-scale Bayesian work.

The study also speaks to a broader lesson about scientific software. The pandemic exposed a gap between the methods developed in academic statistics and systematics communities and the operational needs of public health. Tools that were exemplary for studies of dozens or hundreds of taxa could not simply be scaled by throwing more processors at them; they required rethinking data structures, sampling strategies, and the software engineering practices needed for continuous, reliable operation. Delphy represents the kind of ground-up redesign that gap demands, combining modern statistical machinery with the performance engineering of contemporary high-performance computing. Its open availability means that the wider community can scrutinize, extend, and build upon the platform, which is essential if it is to become trusted infrastructure rather than a one-off demonstration.

Challenges remain, of course. Bayesian inference on enormous datasets still requires careful attention to model adequacy, because a fast and precise answer to a poorly specified model is of limited value. Recombination, which is substantial in coronaviruses, complicates the strictly tree-based assumptions underlying most phylogenetic software, and integrating recombination-aware inference at pandemic scale remains an open problem. Sampling bias—where genomes are sequenced unevenly across geography, time, and severity of illness—continues to shape what any phylogenetic method can honestly conclude. None of these caveats diminishes the significance of the advance, but they frame the work realistically: Delphy removes a computational barrier that has constrained the field for years, leaving the scientific community freer to focus on the biological and epidemiological subtleties that no amount of computing power can resolve on its own.

If the trajectory of genomic surveillance continues, the coming years will see sequencing embedded ever more deeply in routine public health, from wastewater monitoring to hospital diagnostics. In that world, the demand for phylogenetic analyses that are simultaneously rigorous, current, and scalable will only grow. Delphy’s demonstration that Bayesian phylogenetics can operate at near-real-time speed on outbreak-scale data marks a turning point in that trajectory, promising that the statistical rigor that made phylogenetics indispensable to evolutionary biology can finally be delivered at the tempo at which epidemics actually unfold.

Subject of Research: Scalable near-real-time Bayesian phylogenetic inference for infectious disease outbreak genomics

Article Title: Scalable near-real-time Bayesian phylogenetics for outbreaks with Delphy

Article References: Varilly, P., Schifferli, M., Yang, K., Cronan, P., Specht, I., Burcham, T., Glennon, O., Jacks, O., Laning, E., Marrs, L., Oba, K., Yeung, S., Zhao, K. W., Parker, E., Omah, I., Pekar, J. E., Luebbert, L., Andersen, K. G., Park, D. J., … Sabeti, P. C. (2026). Scalable near-real-time Bayesian phylogenetics for outbreaks with Delphy. Nature. https://doi.org/10.1038/s41586-026-11012-6

Image Credits: AI Generated

DOI: 10.1038/s41586-026-11012-6

Keywords: Bayesian phylogenetics, Delphy, outbreak genomics, viral evolution, SARS-CoV-2, genomic epidemiology, GPU computing, Markov chain Monte Carlo, phylodynamics, public health surveillance, time-calibrated phylogenies, real-time inference

The history of dual therapy with ceftriaxone and azithromycin illustrates how quickly the situation can change. The combination was introduced as a strategic response to concerns about ceftriaxone monotherapy failure, and it carried the added benefit of activity against Chlamydia trachomatis and Mycoplasma genitalium, which frequently co-occur with gonorrhea. In its early years the strategy worked in many settings, because most ceftriaxone-resistant gonococcal strains were still susceptible to azithromycin, and the dual approach helped slow the international spread of ceftriaxone resistance. Over the past five years, however, azithromycin resistance has risen disturbingly across the globe, undermining the drug’s value within dual therapy and threatening the efficacy of current treatment protocols. Contributing factors include extensive and often inappropriate antibiotic use, suboptimal diagnostic practices, limited surveillance systems, and delayed updates to clinical guidelines.

The future therapeutic landscape appears increasingly precarious. Two novel antimicrobials, zoliflodacin and gepotidacin, have recently been approved for uncomplicated gonorrhea, yet few additional agents are in clinical development. At the same time, resistance to ceftriaxone itself continues to climb in many regions, and strains with concurrent resistance to both ceftriaxone and azithromycin have now been reported in several WHO regions. High treatment costs further restrict access in resource-limited settings, where surveillance and control measures are often weakest, compounding the risk that resistance emerges and spreads undetected. Without new therapeutic strategies, enhanced global surveillance and robust research investment, gonorrhea could become progressively harder to treat, with rising morbidity, complications and treatment failures.

Azithromycin is an oral macrolide long used against chlamydial and mycoplasmal infections, and it once demonstrated good efficacy against gonococci as well. Its widespread availability, particularly where antibiotics can be obtained without prescription or regulation, has contributed significantly to the development of resistance. Over the past decade, azithromycin resistance has steadily increased in both high- and low-income countries, with marked geographic variability shaped by local treatment practices, surveillance infrastructure and antibiotic consumption patterns. Although azithromycin is no longer routinely recommended for gonorrhea in many settings, rising resistance limits its remaining utility and underscores why continued antimicrobial resistance surveillance matters.

The numbers tell a sobering story. A retrospective genomic surveillance study by Daniel Golparian and colleagues, published in The Lancet Microbe, examined N. gonorrhoeae isolates collected across 21 European Economic Area countries in 2020 through the European Gonococcal Antimicrobial Surveillance Programme. It found that azithromycin resistance, defined by the EUCAST epidemiological cut-off of MIC greater than 1 mg/L, had risen to 9.4 percent of isolates, up from 8.0 percent in 2018. In the United States, resistance climbed from 0.01 percent in 1992 to 0.4 percent by 2012, then surged fourfold from 0.6 percent in 2013 to 2.5 percent in 2014, reaching 4.6 percent in 2018 and 5.9 percent by 2019 among isolates with elevated MICs. Globally, the WHO Gonococcal Antimicrobial Surveillance Programme reported that 46 of 53 countries, or 87 percent, detected azithromycin-resistant isolates in 2022, and 36 countries reported resistance in at least 5 percent of isolates.

Regional heterogeneity is striking. In the WHO Western Pacific region, seven of eight reporting countries detected resistant isolates in 2022, with Brunei, Cambodia, China, Japan and Singapore each reporting resistance in at least 5 percent of isolates, while Australia and New Zealand recorded lower levels. China’s Gonococcal Resistance Surveillance Program documented azithromycin resistance reaching 16.9 percent in 2022, a substantial increase over the preceding five years, whereas all isolates reported from the Philippines remained susceptible. Surveillance itself faces structural challenges: while high-income countries maintain robust systems, reporting is inconsistent in low- and middle-income countries due to constraints in laboratory capacity, funding and infrastructure. Only 77 countries and territories reported gonococcal resistance data to WHO GASP during 2019 to 2022, and the absence of data from parts of Africa and Southeast Asia means the true global extent of resistance, and of dual-therapy treatment failures, may be significantly underreported.

Understanding the molecular machinery behind resistance clarifies why surveillance is difficult. Azithromycin inhibits bacterial protein synthesis by binding the peptidyltransferase region of domain V of the 23S rRNA in the 50S ribosomal subunit, blocking peptide exit. Resistance arises through several mechanisms: mutations in the 23S rRNA itself, particularly A2059G and C2611T, alter the drug-binding site; the A2059G transition in all four rRNA alleles produces extraordinarily high MICs of 256 to 4096 mg/L, while C2611T yields moderate resistance of 2 to 32 mg/L. Acquired erm genes encoding rRNA methylases can modify the target, though they have become rare in recent isolates. Mutations in rplD and rplV, encoding ribosomal proteins L4 and L22, moderately raise MICs, and efflux pump overexpression adds another layer of resistance.

Efflux is now central to the story. The MtrCDE pump, the best-characterized system, expels macrolides when its regulator MtrR is disabled by mutations such as G45D, or when promoter mutations, including a single-nucleotide deletion in a 13-base-pair inverted repeat, increase pump transcription. Mosaic mtr alleles, acquired through recombination with sequences from Neisseria meningitidis or Neisseria lactamica, substantially raise azithromycin MICs by altering both the pump and its regulation. The MacAB and mef-encoded efflux systems may also contribute, though they remain less studied in gonococci. Collectively, these mechanisms reveal a complex and geographically variable genetic architecture of resistance.

That variability is precisely what undermines molecular diagnostics. Historically, 23S rRNA mutations were the predominant, best-characterized determinants, and systematic reviews confirm that assays targeting A2059G accurately detect high-level resistance while C2611T assays identify moderate resistance. But the European genomic surveillance revealed a decisive shift: only 10.5 percent of azithromycin-resistant isolates in 2020 carried 23S rRNA mutations, down from 24.1 percent in 2018, while roughly 89 percent instead carried mtrD/mtrR promoter mosaic 2 or semi-mosaic mtrD variants. The authors attribute the resistance surge to the expansion of specific NG-STAR clonal complexes, notably CC63, CC168 and CC213 harboring the mosaic promoter, plus the emergence of novel CC1031 carrying a semi-mosaic mtrD variant. An assay built for the old targets would miss the dominant circulating resistance genotypes.

The implications for public health are clear. The WHO advocates molecular assays that detect resistance markers to guide therapy and support stewardship, but their validity, accuracy and specificity falter when marker distributions differ across regions; in areas dominated by mtrD mosaic variants, a 23S rRNA-focused assay would yield a very low positive predictive value. Tailoring molecular targets to local genetic epidemiology is therefore essential. In low- and middle-income countries where routine whole-genome sequencing is impractical, a pragmatic sentinel-site strategy, with representative laboratories performing susceptibility testing and periodically referring isolates to regional reference centers for genomic characterization, offers a feasible alternative. A standardized minimum dataset reported to WHO GASP, covering susceptibility results, specimen source, geography, collection year and resistance determinants, would enable continuous refinement of regionally calibrated assays. The shift from dual therapy toward ceftriaxone monotherapy may also reshape selection pressure on azithromycin resistance, though the magnitude and direction of that effect remain uncertain, since macrolide use for other infections, fitness effects and lineage dynamics all play a role. Sustained phenotypic and genomic surveillance, novel antimicrobials and combination therapies, and collaboration among researchers, clinicians and public health stakeholders will determine whether gonorrhea remains treatable in the decade ahead.

Subject of Research: Heterogeneity of azithromycin resistance markers in Neisseria gonorrhoeae and the challenges of implementing molecular assays for routine antimicrobial resistance surveillance

Article Title: Heterogeneity of azithromycin resistance markers in Neisseria gonorrhoeae and challenges in implementing molecular assays for routine surveillance

Article References: Yuan, Q., Xiu, L., & Peng, J. (2026). Heterogeneity of azithromycin resistance markers in Neisseria gonorrhoeae and challenges in implementing molecular assays for routine surveillance. New Microbes and New Infections, 73, Article 101838. https://doi.org/10.1016/j.nmni.2026.101838

Image Credits: AI Generated

DOI: 10.1016/j.nmni.2026.101838

Keywords: Neisseria gonorrhoeae, azithromycin resistance, antimicrobial resistance, molecular surveillance, 23S rRNA mutations, mtr mosaic variants, efflux pumps, WHO GASP, ceftriaxone, gonorrhea treatment, genomic epidemiology, molecular diagnostics

The analysis, covering publications from 2000 to 2025, drew on the Scopus database and followed a PRISMA-adapted screening workflow to construct a final analytical corpus of 1,746 articles and reviews spanning 432 journals and involving 11,277 unique authors. The field has expanded at a compound annual growth rate of 17.10%, accumulating 42,075 citations with an average of 24.10 citations per document. Growth accelerated sharply after 2018: annual output rose from 84 publications in 2018 to 259 in 2025, a trajectory the study attributes to increasing prioritization of antimicrobial resistance on the global research agenda and a post-pandemic surge in translational diagnostic research.

To frame the analysis, the study anchored itself in the World Health Organization’s bacterial priority pathogen lists. The WHO’s 2017 framework classified resistant bacteria into critical, high, and medium priority categories, and its 2024 update expanded the list to 24 pathogens across 15 bacterial families using multicriteria decision analysis that weighed mortality, incidence, resistance trends, transmissibility, preventability, treatability, and the state of the drug development pipeline. The critical tier now includes carbapenem-resistant Acinetobacter baumannii, carbapenem-resistant and third-generation cephalosporin-resistant Enterobacterales, and rifampicin-resistant Mycobacterium tuberculosis, while carbapenem-resistant Pseudomonas aeruginosa was moved from critical to high priority based on regional resistance trends and comparatively lower transmission capacity.

Against this backdrop, the bibliometric results reveal a field organized around distinct pathogen axes. Staphylococcus aureus dominated the corpus with 730 publications and 21,945 total citations, followed by Mycobacterium tuberculosis with 439 publications, Enterobacterales with 389, Pseudomonas aeruginosa with 309, Acinetobacter baumannii with 279, and Enterococcus faecium with 250. Growth over the past five years was strongest for Streptococcus pneumoniae at 27.79%, Pseudomonas aeruginosa at 26.35%, and Enterobacterales at 22.81%, signaling a decisive shift in research attention toward Gram-negative carbapenem resistance as the most urgent clinical frontier.

At the platform level, conventional PCR and nucleic acid amplification testing appeared in 61.51% of publications, while whole-genome sequencing featured in 55.44%, making these two technologies the twin pillars of the literature. Because platform categories were not mutually exclusive, many publications combined both approaches. Multiplex PCR stood out for impact, averaging 42.57 citations per article, reflecting the foundational role of early target-specific resistance detection. Emerging technologies, including nanopore sequencing, metagenomic sequencing, and CRISPR-based diagnostics, appeared at low frequencies but formed distinct and growing clusters, suggesting they represent innovation fronts that have not yet reached routine clinical integration.

Resistance marker analysis identified mecA/mecC, rpoB, blaNDM, katG, and vanA/vanB as the most frequently studied molecular targets. Methicillin resistance in staphylococci, epitomized by the mecA gene and its newer variant mecC, anchored the Gram-positive research tradition, while the tuberculosis markers rpoB, katG, and inhA defined a mature and specialized diagnostic axis. Carbapenemase genes, including blaKPC, blaNDM, and blaOXA-48, together with the mobile colistin resistance gene mcr and the fluoroquinolone targets gyrA and parC, showed the strongest recent growth, with gyrA and parC expanding at compound annual rates of 44.28% and 49.53% respectively over the last five years.

Thematic mapping of keyword co-occurrence networks revealed that the literature is structured around six interpretable clusters. Two emerged as mature core themes: PCR-based rapid antimicrobial resistance detection, organized around MRSA, multiplex PCR, and the mecA/mecC and vanA/vanB markers, and a whole-genome sequencing and genomic epidemiology theme spanning multiple pathogen groups. The tuberculosis resistance marker axis formed a strong but specialized mature theme, while the carbapenemase and Gram-negative resistance gene cluster, the metagenomic and nanopore clinical diagnostics cluster, and a general cross-pathogen antimicrobial resistance cluster were identified as emerging or niche research fronts.

Thematic evolution analysis across three time windows documented a clear conceptual restructuring. The early period from 2000 to 2010 centered on target-specific markers such as mecA, vancomycin resistance, and real-time PCR, reflecting an era of single-gene rapid tests. The middle period from 2011 to 2020 brought whole-genome sequencing, tuberculosis, multiplex PCR, and the Enterobacterales-carbapenemase axis to prominence. The recent period from 2021 to 2025 represents a more integrated antimicrobial resistance framework in which WGS, Staphylococcus aureus, and antibiotic resistance concepts dominate, demonstrating the field’s transition from individual marker detection to genomically integrated, translationally oriented diagnostics.

The study’s methodological rigor included a validation exercise in which 150 randomly selected records were blindly reassessed to test the rule-based text-matching system used to classify pathogens, platforms, markers, and clinical contexts. Concordance rates reached 100% for platform and resistance-marker labels, 91.3% for pathogen labels, and 86.7% for clinical-context labels, yielding an overall average agreement of 94.5%. The analysis also mapped the geography of the field: China led production with 263 publications, followed by the United States with 252, the United Kingdom with 130, and Germany with 127, though the United Kingdom and France showed higher rates of international collaboration and network centrality, revealing a divide between volume-based productivity and collaboration-intensive influence.

The findings carry important implications for clinical practice. Prior evidence shows that rapid diagnostic tests, when deployed alongside antimicrobial stewardship programs, reduce mortality in bloodstream infections compared with blood culture alone. The bibliometric structure documented here confirms that molecular diagnostics has evolved beyond answering whether a pathogen is present, into a multilayered data-generating enterprise that supports resistance prediction, monitoring of clonal spread, and clinical and public health decision-making. At the same time, the study acknowledges limitations: PCR panels and WGS report genetic content rather than physiological state, meaning phenomena such as bacterial persistence and tolerance fall largely outside the field’s marker-centered vocabulary, and future work integrating phenotypic, genomic, and virulence-layer data will be essential to close the gap between resistance prediction and treatment outcome.

Subject of Research: Bibliometric mapping of molecular diagnostic platforms and resistance markers for WHO priority bacterial pathogens

Article Title: Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends

Article References: Ünlü, S. (2026). Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends. MicrobiologyOpen, 15(5), Article e70394. https://doi.org/10.1002/mbo3.70394

Image Credits: AI Generated

DOI: 10.1002/mbo3.70394

Keywords: antimicrobial resistance, molecular diagnostics, WHO priority pathogens, whole-genome sequencing, PCR, bibliometric analysis, MRSA, carbapenemase genes, Mycobacterium tuberculosis, Enterobacterales, CRISPR diagnostics, genomic epidemiology