Biology subjects

Gambaro, F.

Publications and source records attributed to Gambaro, F..

11 recordsLinked to original sources

bioRxiv2026

Intra-host IRES heterogeneity shapes hepatitis C virus translation through epistatic and population-level effects

Hepatitis C virus (HCV) circulates within each patient as a diverse population of closely related genomes, yet RNA functional properties are commonly inferred from a single consensus or dominant genome. The contribution of non-coding intra-host variability, particularly within the internal ribosome entry site (IRES), to translational efficiency remains poorly defined. Here we investigated how naturally occurring HCV IRES variation influences viral RNA translation. Complete IRES sequences from chronically infected patients were analyzed using molecular cloning, bicistronic reporters, full-length replication-deficient viral RNAs and reconstructed intra-host populations. We found that natural IRES mutations displayed context-dependent effects, and combinations of mutations produced translational phenotypes that could not be predicted from the corresponding single mutations, consistent with intragenic epistasis. Moreover, several variants behaved differently in bicistronic reporters and full-length viral RNAs, demonstrating that both genomic and cellular context shape IRES function. Reconstructed genotype 1a populations largely reproduced the activity of their dominant haplotypes. In contrast, reconstructed genotype 3a populations translated substantially more efficiently than their corresponding dominant sequences, showing that low-frequency variants can collectively modulate translation at the population level. These findings demonstrate that the translational phenotype of HCV cannot always be inferred from the dominant sequence alone and identify epistasis, genomic context, and intra-host population composition as interacting determinants of viral RNA translation. ImportanceHepatitis C virus (HCV) exists within each infected person as a diverse population of closely related viruses rather than as a single genetic sequence. This study shows that natural variation in a key RNA region controlling viral protein production can alter how efficiently the virus functions, and that these effects depend on combinations of mutations rather than on individual changes alone. By analyzing complete viral RNAs in addition to widely used reporter systems, we demonstrate that the full viral genome can substantially influence the activity of this regulatory region, providing a more realistic view of how translation occurs during natural infection. Our findings also reveal that rare viral variants can collectively shape the behavior of the viral population, challenging the common practice of relying on a single dominant sequence to represent an infection. These results provide new insight into how genetic diversity drives HCV evolution and adaptation.

molecular biology↗

bioRxiv2026

Breeding pig transport drives the dispersal of swine influenza A virus across Europe

Pigs serve as reservoirs of former human influenza A virus (IAV) H1N1 and H3N2 lineages and act as mixing vessels for diverse strains, facilitating the emergence of novel IAVs. Understanding the spread and evolution of swine IAVs (swIAVs) is therefore crucial to assess the risk of strains with zoonotic potential emerging. This study uses a phylogeographic framework to investigate the predictors of swIAV dispersal across Europe. All publicly available swIAV genomic sequences were retrieved and subsampled for the ten largest European pig-producing countries. Discrete phylogeographic reconstructions were conducted for H1, H3, N1, N2 encoding genes and all internal gene segments. Our analyses indicate that viral dispersal predominantly occurred from north-western to southern and eastern Europe, with frequent long-distance transitions between non-adjacent countries. We also extended the discrete phylogeographical analyses with generalized linear models to test the association between viral movement and potential predictors, such as live pig trade, pork trade, pig densities, farm sizes, or the geographic distance between key pig production zones. We find that breeding pig trade is the only consistently well-supported predictor of between-country transition events, whereas pork trade and geographic distance were not supported. This highlights that farms importing breeding pigs from multiple countries could act as hotspots for reassortment of diverse swIAV strains. Strengthening external biosecurity on farms with emphasis on quarantining breeding pigs, limiting long-distance transport, and implementing a One Health surveillance system for earlier detection of emerging strains, could help curb the rapid spread and evolution of swIAV in Europe. Author summaryInfluenza A viruses that originally came from humans are now circulating in pigs. This is a public health concern because these viruses continue to evolve in pigs and may eventually return to humans in new forms that could cause more severe disease. To better prevent this risk, we need to understand the dispersal dynamics of influenza viruses infecting pigs. For this purpose, we retrieved all publicly available European swine influenza A virus genomic sequences. Using this genomic dataset, we reconstructed how the virus has spread across Europe and investigated the external factors that may have driven the spread. Our results indicate that swine influenza A viruses frequently spread between European countries, in particular from north-western to southern and eastern Europe, and that the trade of pigs intended for breeding is strongly associated with these patterns of spread. Consequently, measures such as quarantining of breeding pigs, could help preventing swine influenza variants from spreading between and becoming established in new regions. We also find major gaps in available genomic data from several European countries. We therefore recommend stronger European surveillance programs that include monitoring influenza viruses in both animals and humans to improve early detection of new emerging viral variants.

genomics↗

bioRxiv2026

Evolutionary history of Jamestown Canyon virus disentangles complex multi-vector ecology

Jamestown Canyon virus (JCV) is a re-emerging mosquito-borne virus of increasing concern in North America. It has been historically understudied, leading to significant gaps in our understanding of its evolutionary history, ecological maintenance, and transmission dynamics. Here, we generated 658 whole-genome JCV sequences from the Northeast United States, including 84% (500/597) of all JCV-positive mosquitoes detected in Connecticut from 1997-2022. Then we applied phylodynamic methods to demonstrate how mosquito phenology and host interaction structure the persistence and spread of JCV. Our phylogenetic analyses estimate that JCV was introduced in the Northeast by at least the early 1700s and the primary introductions of lineages A and B into Connecticut occurred during the mid-1800s to mid-1900s. Further, we estimate that JCV evolves at a rate of [~]3 x 10-5 s/s/y, making it one of the slowest evolving known RNA viruses, because the virus spends [~]10 months per year in evolutionary stasis while over-wintering in mosquito eggs. To investigate ecological drivers of JCV spread in Connecticut, we paired discrete trait and continuous phylogeographic reconstructions with mosquito surveillance data. We estimate that JCV has a low diffusion rate of [~]30-60 km2/year, which is more similar to slow-moving tick-borne viruses than other mosquito-borne viruses. We found that univoltine Aedes mosquitoes were likely to maintain the virus across years through overwintering in eggs, accounting for its slow evolution and dispersal, while multivoltine mosquitoes contribute to periodic bursts of spatial diffusion and amplification within seasons. By characterizing seasonal dynamics of JCV, we demonstrate the utility of dense sequencing and phylodynamics to disentangle complex transmission cycles, offering a framework to rapidly advance our evolutionary and ecological knowledge of understudied viruses.

ecology↗

bioRxiv2025

Escalating human exposure to tropical mosquito-borne viruses in Europe

Human-induced climate change has multiple public health impacts, including the expansion of the geographical range of vector-borne diseases. Pathogens such as dengue, chikungunya and Zika viruses, transmitted by Aedes mosquitos, can cause severe health outcomes ranging from acute febrile illness, chronic joint pain, to birth defects and even death. Evaluating the future risk of human population exposure is therefore crucial as large outbreaks could overwhelm healthcare systems. Europe, one of the fastest warming regions globally, harbours the competent mosquito vector Aedes albopictus in over 20 countries, making tropical Aedes-borne viruses an increasing threat to the continent, which has already experienced local outbreaks over the past two decades. Here we use an ecological niche modelling approach to assess past, present, and future risk of human population exposure to dengue, chikungunya, and Zika viruses in Europe. Our results show that recent climate change has already increased the potential exposure to these viruses, particularly across the Mediterranean basin, which is a current hotspot for local outbreaks. Major metropolitan areas in Spain, France, Italy, and Croatia are by now located in at-risk areas, and this risk is projected to intensify and expand northward by mid-century. Under a high greenhouse gas emissions scenario, European areas ecologically suitable for Aedes-borne virus circulation could increase by up to [~]70%, leading to an additional [~]50 million people living in areas at risk by the end of the century. These findings underscore the urgent need for strengthened vector and epidemiological surveillance, as well as preparedness strategies across newly suitable regions to anticipate future public health threats associated with these arboviral diseases.

ecology↗

bioRxiv2025

Navigating sampling bias in discrete phylogeographic analysis: assessing the performance of an adjusted Bayes factor

Bayesian phylogeographic inference is widely used in molecular epidemiological studies to reconstruct the dispersal history of pathogens. Discrete phylogeographic analysis treats geographic locations as discrete traits and infers lineage transition events among them, and is typically followed by a Bayes factor (BF) test to assess the statistical support. In the standard BF (BFstd) test, the relative abundance of the involved trait states is not considered, which can be problematic in the case of unbalanced sampling. Existing methods to correct sampling bias in discrete phylogeographic analyses using continuous-time Markov chain (CTMC) model, often require additional epidemiological information to balance the sampling effort among locations. As such data is not necessarily available, alternative approaches that rely solely on available genomic data are needed. In this perspective, we assess the performance of a modification of the BFstd, the adjusted Bayes factor (BFadj), which incorporates information on the relative abundance of samples by location when inferring support for transition events and root location inference without requiring additional data. Using a simulation framework, we assess the statistical performance of BFstd and BFadj under varying levels of sampling bias, estimating their type I and type II error rates. Our results show that BFadj complements the BFstd by reducing type I errors at the cost increasing type II errors for inferred transition events, while improving type I and type II errors in root location inference. Our findings provide guidelines for implementing the complementary BFadj to detect and mitigate sampling bias in discrete phylogeographic inference using CTMC modelling.

evolutionary biology↗

bioRxiv2025

Comparative performance of novel viral landscape phylogeography approaches

The fast rate of evolution in RNA viruses implies that their evolutionary and ecological processes occur on the same time scale. Genome sequences of these pathogens can therefore contain information about the processes that govern their transmission and dispersal. In particular, landscape phylogeographic approaches use phylogeographic reconstructions to investigate the impact of environmental factors and variables on the spatial spread of viruses. Here, we extend and improve existing approaches and develop three novel landscape phylogeographic methods that can test the impact of continuous environmental factors on the diffusion velocity of viral lineages. In order to evaluate the different methods, we also implemented two simulation frameworks to test and compare their statistical performance. The results enable us to formulate clear guidelines for the use of three complementary landscape phylogeographic approaches that have sufficient statistical power and low rates of false positives. Our open-source methods are available to the scientific community and can be used to investigate the drivers of viral spread, with potential benefits for understanding virus epidemiology and designing tailored intervention strategies.

evolutionary biology↗

bioRxiv2021

The B1.351 and P.1 variants extend SARS-CoV-2 host range to mice

Receptor recognition is a major determinant of viral host range, infectivity and pathogenesis. Emergences have been associated with serendipitous events of adaptation upon encounters with novel hosts, and the high mutation rate of RNA viruses may explain their frequent host shifts. SARS-CoV-2 extensive circulation in humans results in the emergence of variants, including variants of concern (VOCs) with diverse mutations notably in the spike, and increased transmissibility or immune escape. Here we show that, unlike the initial and Delta variants, the three VOCs bearing the N501Y mutation can infect common laboratory mice. Contact transmission occurred from infected to naive mice through two passages. This host range expansion likely results from an increased binding of the spike to the mouse ACE2. Together with the observed contact transmission, it raises the possibility of wild rodent secondary reservoirs enabling the emergence of new variants.

microbiology↗

bioRxiv2021

A novel SARS-CoV-2 related coronavirus in bats from Cambodia

Knowledge of the origin and reservoir of the coronavirus responsible for the ongoing COVID-19 pandemic is still fragmentary. To date, the closest relatives to SARS-CoV-2 have been detected in Rhinolophus bats sampled in the Yunnan province, China. Here we describe the identification of SARS-CoV-2 related coronaviruses in two Rhinolophus shameli bats sampled in Cambodia in 2010. Metagenomic sequencing identified nearly identical viruses sharing 92.6% nucleotide identity with SARS-CoV-2. Most genomic regions are closely related to SARS-CoV-2, with the exception of a small region corresponding to the spike N terminal domain. The discovery of these viruses in a bat species not found in China indicates that SARS-CoV-2 related viruses have a much wider geographic distribution than previously understood, and suggests that Southeast Asia represents a key area to consider in the ongoing search for the origins of SARS-CoV-2, and in future surveillance for coronaviruses.

microbiology↗

bioRxiv2020

High transmissibility and fetal pathogenicity of recent Zika virus strains from the African lineage

The global emergence of Zika virus (ZIKV) in the last decade revealed the unprecedented ability for a mosquito-borne virus to cause congenital birth defects such as microcephaly. A puzzling aspect of ZIKV emergence is that all human outbreaks and birth defects to date have been exclusively associated with the Asian ZIKV lineage, despite a growing body of laboratory evidence pointing towards higher transmissibility and pathogenicity of the African ZIKV lineage. Whether this apparent paradox reflects the use of relatively old African ZIKV strains in most laboratory studies is unclear. Here, we experimentally compared the transmissibility and pathogenicity of seven low-passage ZIKV strains representing the recently circulating viral genetic diversity. We found that recent African ZIKV strains largely outperformed their Asian counterparts in mosquito transmission kinetics experiments, which translated into a markedly higher epidemic potential in outbreak computer simulations. In addition, African ZIKV strains were significantly more lethal than Asian ZIKV strains in immunocompromised adult mice. Finally, prenatal infection of immunocompetent mouse embryos with an African ZIKV strain resulted in embryonic death whereas it caused microcephaly with Asian ZIKV strains. Together, our results demonstrate the high epidemic potential and pathogenicity of recent ZIKV strains from Africa. Importantly, they also imply that the African ZIKV lineage could more easily go unnoticed by public health surveillance systems than the Asian ZIKV lineage due to its propensity to cause fetal loss rather than birth defects.

microbiology↗

bioRxiv2020

Introductions and early spread of SARS-CoV-2 in France

Following the emergence of coronavirus disease (COVID-19) in Wuhan, China in December 2019, specific COVID-19 surveillance was launched in France on January 10, 2020. Two weeks later, the first three imported cases of COVID-19 into Europe were diagnosed in France. We sequenced 97 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from samples collected between January 24 and March 24, 2020 from infected patients in France. Phylogenetic analysis identified several early independent SARS-CoV-2 introductions without local transmission, highlighting the efficacy of the measures taken to prevent virus spread from symptomatic cases. In parallel, our genomic data reveals the later predominant circulation of a major clade in many French regions, and implies local circulation of the virus in undocumented infections prior to the wave of COVID-19 cases. This study emphasizes the importance of continuous and geographically broad genomic sequencing and calls for further efforts with inclusion of asymptomatic infections.

genomics↗

bioRxiv2020

Fragmentation of extracellular ribosomes and tRNAs shapes the extracellular RNAome

A major proportion of extracellular RNAs (exRNAs) do not co-isolate with extracellular vesicles (EVs) and remain in ultracentrifugation supernatants of cell-conditioned medium or mammalian blood serum. However, little is known about exRNAs beyond EVs. We have previously shown that the composition of the nonvesicular exRNA fraction is highly biased toward specific tRNA-derived fragments capable of forming RNase-protecting dimers. To solve the problem of stability in exRNA analysis, we developed RI-SEC-seq: a method based on sequencing the size exclusion chromatography (SEC) fractions of nonvesicular extracellular samples treated with RNase inhibitors (RI). This method revealed dramatic compositional changes in exRNA population when enzymatic RNA degradation was inhibited. We demonstrated the presence of ribosomes and full-length tRNAs in cell-conditioned medium of a variety of mammalian cell lines. Their fragmentation generates some small RNAs that are highly resistant to degradation. The extracellular biogenesis of some of the most abundant exRNAs demonstrates that extracellular abundance is not a reliable input to estimate RNA secretion rates. Finally, we showed that chromatographic fractions containing extracellular ribosomes can be sensed by dendritic cells. Extracellular ribosomes and/or tRNAs could therefore be decoded as damage-associated molecular patterns.

cell biology↗