In the search for natural reservoirs of hepatitis C virus (HCV), a broad diversity of non-human viruses within the Hepacivirus genus has been uncovered. However, the evolutionary dynamics that shaped the diversity and timescale of hepaciviruses evolution remain elusive. To gain further insights into the origins and evolution of this genus, we screened a large dataset of wild mammal samples (n = 1,672) from Africa and Asia, and generated 34 full-length hepacivirus genomes. Phylogenetic analysis of these data together with publicly available genomes emphasizes the importance of rodents as hepacivirus hosts and we identify 13 rodent species and 3 rodent genera (in Cricetidae and Muridae families) as novel hosts of hepaciviruses. Through co-phylogenetic analyses, we demonstrate that hepacivirus diversity has been affected by cross-species transmission events against the backdrop of detectable signal of virus-host co-divergence in the deep evolutionary history. Using a Bayesian phylogenetic multidimensional scaling approach, we explore the extent to which host relatedness and geographic distances have structured present-day hepacivirus diversity. Our results provide evidence for a substantial structuring of mammalian hepacivirus diversity by host as well as geography, with a somewhat more irregular diffusion process in geographic space. Finally, using a mechanistic model that accounts for substitution saturation, we provide the first formal estimates of the timescale of hepacivirus evolution and estimate the origin of the genus to be about 22 million years ago. Our results offer a comprehensive overview of the micro- and macroevolutionary processes that have shaped hepacivirus diversity and enhance our understanding of the long-term evolution of the Hepacivirus genus.
Unmyelinated non-peptidergic nociceptors (NP afferents) arborise in lamina II of the spinal cord and receive GABAergic axoaxonic synapses, which mediate presynaptic inhibition. However, until now the source of this axoaxonic synaptic input was not known. Here we provide evidence that it originates from a population of inhibitory calretinin-expressing interneurons (iCRs), which correspond to lamina II islet cells. The NP afferents can be assigned to 3 functionally distinct classes (NP1-3). NP1 afferents have been implicated in pathological pain states, while NP2 and NP3 afferents also function as pruritoceptors. Our findings suggest that all 3 of these afferent types innervate iCRs and receive axoaxonic synapses from them, providing feedback inhibition of NP input. The iCRs also form axodendritic synapses, and their targets include cells that are themselves innervated by the NP afferents, thus allowing for feedforward inhibition. The iCRs are therefore ideally placed to control the input from non-peptidergic nociceptors and pruritoceptors to other dorsal horn neurons, and thus represent a potential therapeutic target for the treatment of chronic pain and itch.
Parasitic helminths influence the composition of the gut microbiome. However, the microbiomes of individuals living in helminth-endemic regions are understudied. The Orang Asli, an indigenous population in Malaysia with high burdens of the helminth Trichuris trichiura, displayed microbiotas enriched in Clostridiales, an order of spore-forming obligate anaerobes previously shown to have immunogenic properties. We previously isolated novel Clostridiales that were enriched in these individuals and found that a subset promoted the Trichuris life cycle. Here, we further characterized the functional properties of these bacteria. Enzymatic and metabolomic profiling revealed a range of activities associated with metabolism and host response. Consistent with this finding, monocolonization of mice with individual isolates identified bacteria that were potent inducers of regulatory T cell (Treg) differentiation in the colon. Comparisons between variables revealed by these studies identified enzymatic properties correlated with Treg induction and Trichuris egg hatching. These results provide functional insights into the microbiotas of an understudied population.
Recently, species clustering within Dickeya zeae has been identified as complex, encompassing validly published names, including D. oryzae and D. parazeae, with some strains potentially delineating new species. In this study, genomes of strains isolated from a bacterial heart rot outbreak in pineapple (Ananas comosus var. comosus) on Oahu, Hawaii, along with two strains from pineapple in Malaysia, were sequenced. Orthologous average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values among the sequenced genomes ranged from 98.93-99.9% and 91.8-99.9%, respectively, supporting the classification of seven strains within the same species. Comparisons of ANI and dDDH values between these seven strains and type strains of D. zeae, D. parazeae, and D. oryzae ranged from 94.4-95.9% and 57.2-66.5%, respectively. These values fall below the proposed boundaries for new species designation, supporting the delineation of a novel species. Phylogenetic analyses, including 16S rRNA, gapA, multi-locus sequence analysis (MLSA) of 10 housekeeping genes, whole-genome, and pangenome analyses, were concordant and revealed a distinct monophyletic clade, separating these strains from other members of the D. zeae complex, with D. oryzae as the closest relative. Notably, a nitrogen fixation gene cluster comprising 28 genes, similar to the Klebsiella spp. nitrogenase gene cluster, was found in the genome of the seven pineapple strains. Based on polyphasic approaches, including ANI, dDDH, biochemical, physiological, and phylogenomic analyses, we propose the reclassification in a new species of the five pineapple strains from Hawaii A5391, A5410T, A5611, A6136, and A6137, together with the two pineapple strains from Malaysia CFBP 1272 and CFBP 1278, previously classified as D. zeae. We propose the name Dickeya ananae sp. nov. for this taxon, represented by the type strain A5410T (= ICMP 25020T = LMG 33197T).
Recent reports from Thailand reveal a substantial surge in Plasmodium knowlesi cases over the past decade, with a more than eightfold increase in incidence by 2023 compared to 2018. This study investigates temporal changes in genetic polymorphism associated with the escalating transmission of P. knowlesi malaria in Thailand over the past two decades. Twenty-five P. knowlesi samples collected in 2018-2023 were sequenced for the 42-kDa region of pkmsp1 and compared with 24 samples collected in 2000-2009, focusing on nucleotide diversity, natural selection, recombination rate, and population differentiation. Seven unique haplotypes were identified in recent samples, compared to 15 in earlier samples. Nucleotide and haplotype diversities were lower in recent samples (π = 0.016, Hd = 0.817) than in earlier samples (π = 0.018, Hd = 0.942). Significantly higher synonymous substitution rates were observed in both sample sets (dS - dN = 2.77 and 2.43, p < 0.05), indicating purifying selection and reduced genetic diversity over time. Additionally, 8 out of 17 mutation points were located on B-cell epitopes, suggesting an adaptive response by the parasites to evade immune recognition. Population differentiation analysis using the fixation index (Fst) revealed high genetic differentiation between parasite populations in central and southern Thailand or Malaysia. Conversely, the relatively lower Fst value between southern Thailand and Malaysia suggests a closer genetic relationship, possibly reflecting historical gene flow. In conclusion, our findings highlight a decline in genetic diversity and evidence of purifying selection associated with the recently increased incidence of P. knowlesi malaria in Thailand. The minor genetic differentiation between P. knowlesi populations from southern Thailand and Malaysia suggests a shared recent ancestry of these parasites and underscores the need for coordinated efforts between the two countries for the elimination of P. knowlesi.
Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is of significant importance in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates the efficient prioritization of samples for subsequent, costly analyses such as short-read and long-read whole genome sequencing. We focus on five genes-Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), alpha-Synuclein (SNCA), and Amyloid Beta Precursor Protein (APP)-which may be relevant to neurological diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinson's Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finder's interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using both short-read and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied sparsity, noise, and size. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.
Apicomplexa are single-celled eukaryotes that can infect humans and include the mosquito-borne parasite Plasmodium, the cause of malaria. Increasing rates of drug resistance in human-only Plasmodium species are reducing the efficacy of control efforts and antimalarial treatments. There are also rising cases of P. knowlesi, the only zoonotic Plasmodium species that causes severe disease and death in humans. Thus, there is a need to develop additional innovative strategies to combat malaria. Viruses that infect non-Plasmodium spp. Disease-causing protozoa have been shown to affect pathogen life cycle and disease outcomes. However, only one virus (Matryoshka RNA virus 1) has been identified in Plasmodium, and none have been identified in zoonotic Plasmodium species. The rapid expansion of the known RNA virosphere using structure- and artificial intelligence-based methods suggests that this dearth is due to the divergent nature of RNA viruses that infect protozoa. We leveraged these newly uncovered data sets to explore the virome of human-infecting Plasmodium species collected in Sabah, east (Borneo) Malaysia. We identified a highly divergent RNA virus in two human-infecting P. knowlesi isolates that is related to the unclassified group 'ormycoviruses'. By characterising fifteen additional ormycoviruses identified in the transcriptomes of arthropods we show that this group of viruses exhibits a complex ecology at the arthropod-mammal interface. Through the application of artificial intelligence methods, we then demonstrate that the ormycoviruses are part of a diverse and unclassified viral taxon. This is the first observation of an RNA virus in a zoonotic Plasmodium species. By linking small-scale experimental data to large-scale virus discovery advances, we characterise the diversity and genomic architecture of an unclassified viral taxon. This approach should be used to further explore the virome of disease-causing Apicomplexa and better understand how protozoa-infecting viruses may affect parasite fitness, pathobiology, and treatment outcomes.
Museum collections harbor millions of samples, largely unutilized for long-read sequencing. Here, we use ethanol-preserved samples containing kilobase-sized DNA to show that amplification-free protocols can yield contiguous genome assemblies. Additionally, using a modified amplification-based protocol, employing an alternative polymerase to overcome PCR bias, we assembled the 3.1 Gb maned sloth genome, surpassing the previous 500 Mb protocol size limit. Our protocol also improves assemblies of other difficult-to-sequence molluscs and arthropods, including millimeter-sized organisms. By highlighting collections as valuable sample resources and facilitating genome assembly of tiny and challenging organisms, our study advances efforts to obtain reference genomes of all eukaryotes.
Fusobacterium nucleatum is an oral bacterium known to colonize colorectal tumors, where it is thought to play an important role in cancer progression. Recent advances in sequencing and phenotyping of F. nucleatum have revealed important differences at the subspecies level, but whether these differences impact the overall tumor ecology, and tumorigenesis itself, remain poorly understood. In this study, we sought to characterize Fusobacteria in the tumor microbiome of a cohort of individuals with CRC through a combination of molecular, spatial, and microbiologic analyses. We assessed for relative abundance of F. nucleatum in tumors compared to paired normal tissue, and correlated abundance with clinical and pathological features. We demonstrate striking enrichment of F. nucleatum and the recently discovered subspecies animalis clade 2 (Fna C2) specifically in colon tumors that have biofilms, highlighting the importance of complex community partnerships in the pathogenesis of this important organism.
Understanding how life is adapting to urban environments represents an important challenge in evolutionary biology. Here we investigate a widely cited example of urban adaptation, Culex pipiens form molestus, also known as the London Underground Mosquito. Population genomic analysis of ~350 contemporary and historical samples counter the popular hypothesis that molestus originated belowground in London less than 200 years ago. Instead, we show that molestus first adapted to human environments aboveground in the Middle East over the course of >1000 years, likely in concert with the rise of agricultural civilizations. Our results highlight the role of early human society in priming taxa for contemporary urban evolution and have important implications for understanding arbovirus transmission.
Frugivory is essential for the maintenance of tropical forests, influencing seed movement, spatial structure, and ecosystem functioning. Although frugivory interactions are well documented at local scales, we still know relatively little about how network structure varies across biogeographic regions, particularly in equatorial lowland forests. In this study, we compare frugivory networks in lowland forests in the Guiana Shield (South America), Malaysia (Southeast Asia), and Central Africa (Gabon and Cameroon). Because these sites occur at similar latitudes, they provide a useful setting to examine how evolutionary history and biogeographic context, rather than climate alone, might shape the structure of the network. We analyze patterns across regions, focusing on implications for frugivory interactions and, ultimately, seed dispersal. Guided by the Integrative Hypothesis of Specialization (IHS), we focus on the role of megafauna and other large-bodied frugivores, which are important consumers of large fruits and dispersers of large seeds, and have experienced different historical trajectories in each continent. We also considered whether smaller frugivores, such as rodents, might partially compensate for the loss of Megafauna in the Americas through seed handling and caching behavior. The pantropical comparison revealed structural and functional differences between the studied frugivory networks. In the Guianas, lacking megafauna, the frugivory network showed strong modularity with nestedness within modules, forming a marked compound topology. Alternatively, in Central Africa, with elephants and great apes, the network showed intermediate modularity and nestedness, reflecting a balance between local compartmentalization and regional integration. Finally, in Malaysia, the network was predominantly nested, with a few highly connected species, especially figs and flying foxes, that linked most of the partners. Across continents, frugivory networks tend toward a compound topology, but the relative influence of modular and nested components shifts with biogeography, evolution, and ecology.