Small mammals harbor a diverse array of zoonotic pathogens. To date, however, metagenomic surveys of these species have primarily focused on viral diversity, with limited attention paid to bacteria and eukaryotic pathogens. Additionally, the ecological determinants of pathogen diversity within these mammals have not been systematically examined. Herein, we employed a metatranscriptomics approach to survey the pathogen infectome of 2,408 individual samples, representing lung, liver, and gut tissues from 858 animals collected throughout Guangdong province, China, with a study design that accounted for host species, tissue, season, and geographic location. We identified 76 pathogen species, including 29 RNA viruses, 12 DNA viruses, 5 bacteria, and 30 eukaryotic pathogens, 33 of which were newly discovered. Tissue distribution analysis revealed distinct organotropisms, suggesting varied transmission routes, while host distribution analysis showed that each animal carried an average of one pathogen, with 10 pathogens widely distributed among mammalian orders. Our characterization of the geographic and seasonal patterns revealed that pathogen richness was primarily influenced by region, host species, and season, while pathogen composition was largely shaped by host genetic distance. Collectively, these data provide the first comprehensive insight into the dynamics of the pathogen infectome in these key mammalian disease reservoirs, highlighting the major factors driving pathogen diversity and transmission. ### Competing Interest Statement The authors have declared no competing interest.

Bats are natural reservoirs for a wide range of microorganisms, including many notable zoonotic pathogens. However, the infectome of bat kidneys remains poorly understood. To address this gap, we performed meta-transcriptomic sequencing on kidney tissues from 142 bats, spanning ten species sampled at five locations in Yunnan province, China. This analysis identified 22 viral species, including 20 novel viruses, two of which represented newly discovered henipaviruses closely related to the highly pathogenic Hendra and Nipah viruses. These henipaviruses were found in the kidneys of bats inhabiting an orchard near villages, raising concerns about potential fruit contamination via bat urine and transmission risks to livestock or humans. Additionally, we identified a novel protozoan parasite, tentatively named Klossiella yunnanensis, along with two highly abundant bacterial species, one of which is a newly discovered species, Flavobacterium yunnanensis. These findings broaden our understanding of the bat kidney infectome, underscore critical zoonotic threats, and highlight the need for comprehensive, full-spectrum microbial analyses of previously understudied organs to better assess spillover risks from bat populations. ### Competing Interest Statement The authors have declared no competing interest.

Understanding wildlife-pathogen interactions is crucial for mitigating zoonotic risk. Through meta-transcriptomic sequencing we profiled the infectomes of 1,922 samples from 67 mammalian species across China, uncovering a remarkable diversity of viral, bacterial, fungal, and parasitic pathogens. Of the 195 pathogens identified, 62 were novel, including a bi-segmented coronavirus in diseased lesser pandas, which we propose represents a new genus - Zetacoronavirus. The orders Carnivora and Rodentia exhibited the highest pathogen diversity and were implicated in numerous host-jumping events. Comparative analysis of diseased versus healthy animals revealed a trend of higher pathogen loads in the former, with possible differences in tissue tropisms. In total, 48 zoonotic and 17 epizootic pathogens were identified, with frequent cross-species transmission, emphasizing the potential for emerging public health threats. This study highlights the urgent need for wildlife pathogen surveillance to inform proactive disease management strategies. ### Competing Interest Statement The authors have declared no competing interest.

Current metagenomic tools can fail to identify highly divergent RNA viruses. We developed a deep learning algorithm, termed LucaProt, to discover highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 metatranscriptomes generated from diverse global ecosystems. LucaProt integrates both sequence and predicted structural information, enabling the accurate detection of RdRP sequences. Using this approach, we identified 161,979 potential RNA virus species and 180 RNA virus supergroups, including many previously poorly studied groups, as well as RNA virus genomes of exceptional length (up to 47,250 nucleotides) and genomic complexity. A subset of these novel RNA viruses was confirmed by RT-PCR and RNA/DNA sequencing. Newly discovered RNA viruses were present in diverse environments, including air, hot springs, and hydrothermal vents, with virus diversity and abundance varying substantially among ecosystems. This study advances virus discovery, highlights the scale of the virosphere, and provides computational tools to better document the global RNA virome.

Yunnan province in China shares its borders with three neighboring countries: Myanmar, Vietnam, and Laos. The region is characterized by a diverse climate and is known to be a suitable habitat for various arthropods, including midges which are notorious for transmitting diseases which pose significant health burdens affecting both human and animal health. A total of 431,100 midges were collected from 15 different locations in the border region of Yunnan province from 2015 to 2020. These midges were divided into 37 groups according to the collection year and sampling site. These 37 groups of midges were then homogenized to extract nucleic acid. Metatranscriptomics were used to analyze their viromes. Based on the obtained cytochrome C oxidase I gene (COI) sequences, three genera were identified, including one species of Forcipomyia, one species of Dasyhelea, and twenty-five species of Culicoides. We identified a total of 3199 viruses in five orders and 12 families, including 1305 single-stranded positive-stranded RNA viruses (+ssRNA) in two orders and seven families, 175 single-stranded negative-stranded RNA viruses (−ssRNA) in two orders and one family, and 1719 double-stranded RNA viruses in five families. Six arboviruses of economic importance were identified, namely Banna virus (BAV), Japanese encephalitis virus (JEV), Akabane virus (AKV), Bluetongue virus (BTV), Tibetan circovirus (TIBOV), and Epizootic hemorrhagic disease virus (EHDV), all of which are capable, to varying extents, of causing disease in humans and/or animals. The survey sites in this study basically covered the current distribution area of midges in Yunnan province, which helps to predict the geographic expansion of midge species. The complexity and diversity of the viral spectrum carried by midges identified in the study calls for more in-depth research, which can be utilized to monitor arthropod vectors and to predict the emergence and spread of zoonoses and animal epidemics, which is of great significance for the control of vector-borne diseases.

RNA viruses exhibit vast phylogenetic diversity and can significantly impact public health and agriculture. However, current bioinformatics tools for viral discovery from metagenomic data frequently generate false positive virus results, overestimate viral diversity, and misclassify virus sequences. Additionally, current tools often fail to determine virus-host associations, which hampers investigation of the potential threat posed by a newly detected virus. To address these issues we developed VirID, a software tool specifically designed for the discovery and characterization of RNA viruses from metagenomic data. The basis of VirID is a comprehensive RNA-dependent RNA polymerase database to enhance a workflow that includes RNA virus discovery, phylogenetic analysis, and phylogeny-based virus characterization. Benchmark tests on a simulated data set demonstrated that VirID had high accuracy in profiling viruses and estimating viral richness. In evaluations with real-world samples, VirID was able to identify RNA viruses of all types, but also provided accurate estimations of viral genetic diversity and virus classification, as well as comprehensive insights into virus associations with humans, animals, and plants. VirID therefore offers a robust tool for virus discovery and serves as a valuable resource in basic virological studies, pathogen surveillance, and early warning systems for infectious disease outbreaks.

Seoul orthohantavirus (SEOV) has been identified as one of the main causative agents of hemorrhagic fever with renal syndrome (HFRS) in China. The virus was found circulating in rodent populations in almost all provinces of the country, reflecting the wide distribution of HFRS. Here, using the direct immunofluorescence assay (DFA) and real-time quantitative reverse transcription PCR (qRT-PCR) approach, we performed screening in 1784 small mammals belonging to 14 species of three orders captured in the main areas of HFRS endemicity in Yunnan province (southwestern China) and identified 37 SEOV-positive rats (36 Rattus norvegicus and 1 Rattus tanezumi). A 3-year surveillance of HFRS epidemics and dynamics of rodent reservoir density and virus prevalence implied a potential correlation between them. The subsequent meta-transcriptomic sequencing and phylogenetic analyses revealed three SEOV variants, among which two are completely novel. The ancestral character state reconstruction (ACSR) analysis based on both novel variants and documented strains from 5 continents demonstrated that SEOV appeared to originate near the southwestern area (Yunnan-Kweichow Plateau) of China, then could spread to other regions and countries by their rodent carriers, resulting in a global distribution today. In summary, these data furthered the understanding regards genetic diversity and the potential origin for SEOV. However, the expanding endemic foci in the province suggest that the virus is spreading over a wider region and is much more diverse than previous depicted, which means that increased sampling is necessary.

Companion animals such as cats and dogs harbor diverse microbial communities that can potentially impact human health due to close and frequent contact. To better characterize their total infectomes and assess zoonotic risks, we characterized the overall infectomes of companion animals (cats and dogs) and evaluated their potential zoonotic risks. Meta-transcriptomic analyses were performed on 239 samples from cats and dogs collected across China, identifying 24 viral species, 270 bacterial genera, and two fungal genera. Differences in the overall microbiome and infectome composition were compared across different animal species (cats or dogs), sampling sites (rectal or oropharyngeal), and health status (healthy or diseased). Diversity analyses revealed that viral abundance was generally higher in diseased animals compared to healthy ones, while differences in microbial composition were mainly driven by sampling site, followed by animal species and health status. Disease association analyses validated the pathogenicity of known pathogens and suggested potential pathogenic roles of previously undescribed bacteria and newly discovered viruses. Cross-species transmission analyses identified seven pathogens shared between cats and dogs, such as alphacoronavirus 1, which was detected in both oropharyngeal and rectal swabs albeit with differential pathogenicity. Further analyses showed that some viruses, like alphacoronavirus 1, harbored multiple lineages exhibiting distinct pathogenicity, tissue, or host preferences. Ultimately, a systematic evolutionary screening identified 27 potential zoonotic pathogens in this sample set, with far more bacterial than viral species, implying potential health threats to humans. Overall, our meta-transcriptomic analysis reveals a landscape of actively transcribing microorganisms in major companion animals, highlighting key pathogens, those with the potential for cross-species transmission, and possible zoonotic threats. IMPORTANCE:This study provides a comprehensive characterization of the entire community of infectious microbes (viruses, bacteria, and fungi) in companion animals like cats and dogs, termed the "infectome." By analyzing hundreds of samples from across China, the researchers identified numerous known and novel pathogens, including 27 potential zoonotic agents that could pose health risks to both animals and humans. Notably, some of these zoonotic pathogens were detected even in apparently healthy pets, highlighting the importance of surveillance. The study also revealed key microbial factors associated with respiratory and gastrointestinal diseases in pets, as well as potential cross-species transmission events between cats and dogs. Overall, this work sheds light on the complex microbial landscapes of companion animals and their potential impacts on animal and human health, underscoring the need for monitoring and management of these infectious agents.

Metagenomic sequencing has transformed our understanding of viral diversity in wildlife and its threat to human health. Despite this progress, many studies have lacked systematic and ecologically informed sampling, which has left numerous potentially emergent viruses undiscovered, and the drivers of their ecology and evolution poorly understood. We conducted an extensive analysis of viruses in the lung, spleen, and gut of 1,688 animals from 38 mammalian species across 428 sites in Yunnan, China—a hotspot for zoonotic diseases. We identified 162 mammalian viral species, including 102 novel species and 24 posing potential risks to humans due to their relationships with known pathogens associated with serious diseases and their ability to cross major host species barriers. Our findings offer an in-depth view of virus organotropism, cross-species transmission, host sharing patterns, and the ecological factors influencing viral evolution, all of which are critical for anticipating and mitigating future zoonotic outbreaks. ### Competing Interest Statement The authors have declared no competing interest.

Mosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Here, using a meta-transcriptomic approach, we determined the viromes of 2,438 individual mosquitoes (81 species), spanning similar to 4,000 km along latitudes and longitudes in China. From these data we identified 393 viral species associated with mosquitoes, including 7 (putative) species of arthropod-borne viruses (that is, arboviruses). We identified potential mosquito species and geographic hotspots of viral diversity and arbovirus occurrence, and demonstrated that the composition of individual mosquito viromes was strongly associated with host phylogeny. Our data revealed a large number of viruses shared among mosquito species or genera, enhancing our understanding of the host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, perhaps reflecting long-distance mosquito dispersal. Together, these results greatly expand the known mosquito virome, linked viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the biogeography and diversity of viruses in insect vectors.

Metagenomic sequencing has transformed the understanding of viral diversity in wildlife and the potential threats these viruses pose to human health.Despite this progress,such sequencing studies often have lacked systematic and ecologically informed sampling,thereby likely missing many potential human pathogens and the drivers behind their ecology,evolution and emergence.We conducted an extensive search for viruses in the lungs,spleens and guts of 1688 mammals from 38 species across 428 sites in Yunnan Province,China-a hotspot for zoonoses emergence.We identified 162 mammalian viruses,including 102 new ones and 24 posing potential risks to humans due to their relationships with known human pathogens associated with serious diseases or their ability to cross major host species barriers.Our findings offer an in-depth view of virus organotropism,cross-host associations,host sharing patterns,and the ecological factors influencing viral evolution,all of which are critical for anticipating and mitigating future zoonotic outbreaks.

ObjectivesThe respiratory tract is the portal of entry for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a variety of respiratory pathogens other than SARS-CoV-2 have been associated with severe cases of COVID-19 disease, the dynamics of the upper respiratory microbiota during disease the course of disease, and how they impact disease manifestation, remain uncertain.MethodsWe collected 349 longitudinal upper respiratory samples from a cohort of 65 COVID-19 patients (cohort 1), 28 samples from 28 recovered COVID-19 patients (cohort 2), and 59 samples from 59 healthy controls (cohort 3). All COVID-19 patients originated from the earliest stage of the epidemic in Wuhan. Based on a modified clinical scale, the disease course was divided into five clinical disease phases (pseudotimes): “Healthy” (pseudotime 0), “Incremental” (pseudotime 1), “Critical” (pseudotime 2), “Complicated” (pseudotime 3), “Convalescent” (pseudotime 4), and “Long-term follow-up” (pseudotime 5). Using meta-transcriptomics, we investigated the features and dynamics of transcriptionally active microbes in the upper respiratory tract (URT) over the course of COVID-19 disease, as well as its association with disease progression and clinical outcomes.ResultsOur results revealed that the URT microbiome exhibits substantial heterogeneity during disease course. Two clusters of microbial communities characterized by low alpha diversity and enrichment for multiple pathogens or potential pathobionts (including Acinetobacter and Candida) were associated with disease progression and a worse clinical outcome. We also identified a series of microbial indicators that classified disease progression into more severe stages. Longitudinal analysis revealed that although the microbiome exhibited complex and changing patterns during COVID-19, a restoration of URT microbiomes from early dysbiosis toward more diverse status in later disease stages was observed in most patients. In addition, a group of potential pathobionts were strongly associated with the concentration of inflammatory indicators and mortality.ConclusionThis study revealed strong links between URT microbiome dynamics and disease progression and clinical outcomes in COVID-19, implying that the treatment of severe disease should consider the full spectrum of microbial pathogens present.

Between 7 December 2022 and 28 February 2023, China experienced a new wave of COVID-19 that swept across the entire country and resulted in an increasing amount of respiratory infections and hospitalizations. The purpose of this study is to reveal the intensity and composition of coinfecting microbial agents. In total, 196 inpatients were recruited from The Third People’s Hospital of Shenzhen, and 169 respiratory and 73 blood samples were collected for metagenomic next-generation sequencing. The total “Infectome” was characterized and compared across different groups defined by the SARS-CoV-2 detection status, age groups, and severity of disease. Our results revealed a total of 22 species of pathogenic microbes (4 viruses, 13 bacteria, and 5 fungi), and more were discovered in the respiratory tract than in blood. The diversity of the total infectome was highly distinguished between respiratory and blood samples, and it was generally higher in patients that were SARS-CoV-2-positive, older in age, and with more severe disease. At the individual pathogen level, HSV-1 seemed to be the major contributor to these differences observed in the overall comparisons. Collectively, this study reveals the highly complex respiratory infectome and high-intensity coinfection in patients admitted to the hospital during the period of the 2023 COVID-19 pandemic in China.

A series of C21 steroidal glycosides were isolated from the root bark of Periploca sepium, including a new compound, perisepiumoside A1 (1), and six known compounds (2-7). Their structures were elucidated by analysis of HR-ESI-MS, and 1D and 2D NMR spectroscopic data. All these compounds were tested for their NO production inhibitory activity in LPS-stimulated RAW 264.7 cells. Results showed that these C21 steroidal glycosides could remarkably inhibit NO production, particularly 1 and 2 with IC50 values of 30.81 ± 0.18 μM and 44.39 ± 0.21 μM, respectively. In addition, the cytotoxicity of these compounds was measured on A549, MCF-7, and HeLa cancer cell lines. Among them, compounds 1 and 7 displayed cytotoxicity against the A549 cell line with IC50 values of 28.41 ± 0.12 μM and 39.06 ± 0.05 μM, respectively.

Mosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Using a meta-transcriptomic approach, we analysed the virome of 2,438 individual mosquitos (79 species), spanning ~4000 km along latitudes and longitudes in China. From these data we identified 393 core viral species associated with mosquitos, including seven (putative) arbovirus species. We identified potential species and geographic hotspots of viral richness and arbovirus occurrence, and demonstrated that host phylogeny had a strong impact on the composition of individual mosquito viromes. Our data revealed a large number of viruses shared among mosquito species or genera, expanding our knowledge of host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, possibly facilitated by long-distance mosquito migrations. Together, our results greatly expand the known mosquito virome, linked the viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the ecology of viruses of insect vectors.

ABSTRACTMosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Using a meta-transcriptomic approach, we analysed the virome of 2,438 individual mosquitos (79 species), spanning ∼4000 km along latitudes and longitudes in China. From these data we identified 393 core viral species associated with mosquitos, including seven (putative) arbovirus species. We identified potential species and geographic hotspots of viral richness and arbovirus occurrence, and demonstrated that host phylogeny had a strong impact on the composition of individual mosquito viromes. Our data revealed a large number of viruses shared among mosquito species or genera, expanding our knowledge of host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, possibly facilitated by long-distance mosquito migrations. Together, our results greatly expand the known mosquito virome, linked the viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the ecology of viruses of insect vectors.

Bats are the reservoir of many viral pathogens with strong pathogenicity, including NBVs. Nevertheless, it is unclear whether arthropod vectors are involved in transmitting NBVs.

Since 2018, the outbreaks of genotype II African swine fever virus (ASFV) in China and several eastern Asian countries have caused a huge impact on the local swine industry, resulting in huge economic losses. However, little is known about the origin, genomic diversity, evolutionary features, and epidemiological history of the genotype II ASFV. Here, 14 high-quality complete genomes of ASFVs were generated via sequencing of samples collected from China over the course of 3 years, followed by phylogenetic and phylodynamic analyses. The strains identified were relatively homogeneous, with a total of 52 SNPs and 11 indels compared with the prototype strain HLJ/2018, among which there were four exceptionally large deletions (620-18,023 nt). Evolutionary analyses revealed that ASFV strains distributed in eastern Asia formed a monophyly and a 'star-like' structure centered around the prototype strain, suggesting a single origin. Additionally, phylogenetic network analysis and ancestral reconstruction of geographic state indicated that genotype II ASFV strains in eastern Asia likely originated from Western Europe. Overall, these results contribute to the understanding of the history and current status of genotype II ASFV strains in eastern Asian, which could be of considerable importance in disease control and prevention.

Cats harbor many important viral pathogens, and the knowledge of their diversity has been greatly expanded thanks to increasingly popular molecular sequencing techniques. While the diversity is mostly described in numerous regionally defined studies, there lacks a global overview of the diversity for the majority of cat viruses, and therefore our understanding of the evolution and epidemiology of these viruses was generally inadequate. In this study, we analyzed 12,377 genetic sequences from 25 cat virus species and conducted comprehensive phylodynamic analyses. It revealed, for the first time, the global diversity for all cat viruses known to date, taking into account highly virulent strains and vaccine strains. From there, we further characterized and compared the geographic expansion patterns, temporal dynamics and recombination frequencies of these viruses. While respiratory pathogens such as feline calicivirus showed some degree of geographical panmixes, the other viral species are more geographically defined. Furthermore, recombination rates were much higher in feline parvovirus, feline coronavirus, feline calicivirus and feline foamy virus than the other feline virus species. Collectively, our findings deepen the understanding of the evolutionary and epidemiological features of cat viruses, which in turn provide important insight into the prevention and control of cat pathogens.

RNA viruses are diverse components of global ecosystems. The metagenomic identification of RNA viruses is currently limited to those with sequence similarity to known viruses, such that highly divergent viruses that comprise the “dark matter” of the virosphere remain challenging to detect. We developed a deep learning algorithm – LucaProt – to search for highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 global meta- transcriptomes. LucaProt integrates both sequence and structural information to accurately and efficiently detect RdRP sequences. With this approach we identified 180,571 RNA viral species and 180 superclades (viral phyla/classes). This is the broadest diversity of RNA viruses described to date, including many viruses undetectable using BLAST or HMM approaches. The newly identified RNA viruses were present in diverse ecological niches, including the air, hot springs and hydrothermal vents, and both virus diversity and abundance varied substantially among ecological types. We also identified the longest RNA virus genome (nido-like) observed so far, at 47,250 nucleotides, and expanded the diversity of RNA bacteriophage to more than ten phyla/classes. This study marks the beginning of a new era of virus discovery, with the potential to redefine our understanding of the global virosphere and reshape our understanding of virus evolutionary history.