Apis mellifera) and invasive Argentine ants (Linepithema humile), for virus presence and replication. We tested for the black queen cell virus (BQCV), deformed wing virus (DWV), and Kashmir bee virus (KBV) that were initially detected in bees, and the two recently discovered Linepithema humile bunya-like virus 1 (LhuBLV1) and Moku virus (MKV). DWV, KBV, and MKV were detected and replicated in a wide range of hosts and commonly co-infected hymenopterans. Secondly, we placed KBV and DWV in a global phylogeny with sequences from various countries and hosts to determine the association of geographic origin and host with shared ancestry. Both phylogenies showed strong geographic rather than host-specific clustering, suggesting frequent inter-species virus transmission. Transmission routes between hosts are largely unknown. Nonetheless, avoiding the introduction of non-native species and diseased pollinators appears important to limit spill overs and disease emergence.Emerging viruses have caused concerns about pollinator population declines, as multi-host RNA viruses may pose a health threat to pollinators and associated arthropods. In order to understand the ecology and impact these viruses have, we studied their host range and determined to what extent host and spatial variation affect strain diversity. Firstly, we used RT-PCR to screen pollinators and associates, including honey bees ( Pollinator communities worldwide are declining at an alarming rate ,2,3. EmeApis mellifera) because a number of RNA viruses that are circulating within bee populations have been associated with reduced health and reports of colony collapses [Viral infections have been extensively studied in the European honey bee  has been hypothesized to form such a reservoir for honey bee viruses [Species introduction can alter virus communities through the introduction of new pathogens and though introduced hosts providing reservoirs for existing pathogens . For insney bees  but alsoney bees ,30. Invaney bees . In New  viruses . Three b viruses ,32 and f viruses  may faciLinepithema humile bunya-like virus 1 (LhuBLV1). Limited knowledge about the host range of these viruses, particularly hosts of ‘bee viruses’ outside bees, makes identifying hosts and potential reservoirs an important step in understanding virus emergence. Secondly, we quantified to what degree the host species and geographic origin of DWV and KBV strains correlate with shared ancestry. We used phylogenetic analysis and phylogeny–trait correlation of our sequences supplemented with viral sequences retrieved from GenBank from various hosts all over the world. Phylogenies separated by geographic regions with hosts interspersed within these can provide evidence for inter-specific transmission. Alternatively, clustering within hosts species could indicate a high degree of host specificity.In this study, we tested the hypothesis that a range of pollinators and associated arthropods, including honey bees and Argentine ants, are infected by the same viral pathogens. Furthermore, we hypothesised that frequent inter-species viral transmission results in viral phylogenies that are predominantly associated with geographic origin instead of being associated with host species. Firstly, we screened pollinators and associated arthropods for five RNA viruses and tested for virus replication. Most bee-affecting viruses are positive sense single-stranded RNA (+ssRNA) viruses ,35, inclA. mellifera) and Argentine ants (L. humile) as two focal species for this study and sampled these species more frequently than other arthropod species. Adult workers were directly collected from ant nests (n = 32) and beehives (n = 51) using mouth aspirators or collections jars, respectively. Samples of pollinators and associated arthropods (n = 66) were collected using sweep nets or jars when directly collected from abandoned beehives. Collection sites consisted of a mix of agricultural fields, beach edge vegetation strips, and urban areas in the Northland region of New Zealand (n = 135) and January 2019 (n = 14), some in apiaries, some near Argentine ant nests, and others without an apiary or ant nest nearby  before reverse transcription to cDNA using qScript  following the manufacturer’s instructions. PCR was carried out with MyTaq™ Mix and MyTaq™ Red Mix . Here, 15-µL reaction mixes consisted of 1 µL of template (1:20 diluted cDNA) and 0.4 µM of each primer. PCR cycling conditions were 1 min at 95 °C, followed by 35 cycles (38 for KBV) of 15 s of 95 °C, 15 s 55 °C, 30 s 72 °C, and a final 7 min of 72 °C. Positive and negative controls were run alongside every PCR. Primer sequences used in this study can be found in the www.ncbi.nlm.nih.gov/Blast) against the NCBI nucleotide collection and were submitted to GenBank under the accession numbers MT068447 to MT068476.RT-PCR products were visualised on a 2% agarose gel (1.5% for DWV) stained with SYBR™ Safe DNA stain  and run alongside a TrackIt 100-bp DNA ladder . A subset of positive samples were cleaned using ExoSAP-IT™  following the manufacturer’s instructions and sent for Sanger sequencing to Macrogen Inc . This subset included at least one virus positive sample for every arthropod species for each virus. Sequences were confirmed using a BLASTn search  indicates active replication and parasitism of host cells by the virus ,40. SimiReverse transcription (RT) reactions were carried out in the presence of a tagged primer that contains a non-viral sequence (tag) at the 5′ end of the virus-specific primer . The nonepiR package [prop.test function within R , we teswww.ncbi.nlm.nih.gov/genbank/). We used the same genomic regions that were used in the virus detection assay to conduct the phylogenetic analyses, which were a fragment of the RNA-dependent RNA polymerase (RdRp) for DWV and the major capsid protein vp3 for KBV. Through a BLASTn search, we retrieved 160 sequences that matched the DWV RdRp fragment. Only DWV-A was included in the analysis because all DWV sequences from our sample in New Zealand matched the DWV-A group. For KBV, 11 sequences matching the vp3 fragment were found and added to the sequences from this study. Most DWV and KBV sequences available on GenBank are from A. mellifera hosts; therefore, we tested an additional 34 Argentine ant samples obtained by Felden et al. (2019) from Argentina, California, and France , out of which 97% (95% CI: 92%–99%) were infected with at least one and many with multiple  viruses. One individual had as many as four viruses. Outside the order Hymenoptera (n = 46), 51% (95% CI: 37%–65%) of samples were found positive for at least one virus but only 6% (95% CI: 2%–17%) for multiple (two) viruses.We collected arthropods from eight different orders. Virus-positive species were found in all except the Odonata , but we L. humile specific. Interestingly, all ants that tested positive for DWV were sampled from a nest in an apiary , KBV was more prevalent in ants than in bees , and MKV infections were not significantly different between the two species   . MKV wasPolistes and Vespula species tested  and Vespula pensylvanica from Hawaii (KU645789). LhuBLV1 most closely matched the putative RdRp complex gene of the only available LhuBLV1 sequences on GenBank (MH213237) from Argentine ants from Spain .Using BLAST searches, we confirmed the virus identity and identified locations and hosts infected with viral strains most similar to those observed in our samples. BLAST searches showed that BQCV most closely matched the polyprotein of BQCV found in a honey bee in Lithuania (KP223790) . The MKV sequences from 10 different species showed little sequence variation; all sequences derived in this study closely matched  the MKV polyprotein found in A. mellifera from New Zealand (MF623172) and Vespa carbo from Italy (KY909333) (posterior probability (pp) = 0.539, The phylogenetic analysis showed that DWV sequences found in New Zealand in this study clustered within the DWV-A clade and formed a monophyletic group with a sequence from V. vulgaris, however, closely matched samples from the USA   for a number of host states that included Apis, Varroa, bee associates, non-Apis bees, and L. humile  and parsimony score (PS), p < 0.01, vp3 region (n = 24), samples from a geographic location were often sourced from the same host, and vice versa. KBV sequences significantly clustered within New Zealand, Europe, and Australia  but also within bumble bees (MC: p < 0.01)  . The 10 Apis hosts. To our knowledge, this work represents the first study to confirm active LhuBLV1 and MKV infections in arthropod hosts by detecting the positive and negative viral strand intermediate, respectively. Virus replication in novel hosts is a key contributor in disease emergence; nevertheless, even hosts without active virus replication may show active virus replication at a different time [Our study shows that multiple RNA viruses that were initially detected in honey bees or Argentine ants infect a range of pollinators and associated arthropods. We have added to the growing body of evidence of bee viruses infecting and replicating in non-ent time  or can bent time . The artent time , yet theent time  and DWV-ent time ,57. To went time .Bobilla) and in New Zealand native Hymenoptera , Coleoptera (Scolopterus penicillatus), and Blattodea (Maoriblatta).DWV appears to be the most prevalent honey bee pathogen, occurring in approximately 55% of colonies worldwide . We founV. pensylvanica may represent an MKV reservoir on Hawaii [Apis mellifera Bunyavirus 1 and 2 in honey bees [In case of the more recently discovered viruses, such as MKV and LhuBLV1, the knowledge of disease symptoms, dynamics, or host range is very limited ,37. Studn Hawaii ,36. We cney bees . We deteVarroa-mediated high DWV titres in bees may cause spill overs and promote virus spread to associates and other pollinators [Pathogen transmission may potentially alter competition among multiple host species so that spatial interactions are important when regarding transmission networks . RNA virlinators . The prelinators  and speclinators ,13,64. Wlinators , and thelinators .Coinfections and interactions between viral species within the host can play a key factor in the epidemiology and evolution of viruses . Many inSingle-stranded RNA viruses have been considered to be the most likely type of pathogen to jump between species and cause disease outbreaks  that couPolistes wasps and bumble bees. Some cockroaches, crickets, wasps, and ants that tested positive for virus replication were found in close proximity to beehives and are species known to scavenge or prey on honey bees [Varroa mites that exclusively feed on honey bee tissue [Myrmica rubra are found positive for the negative strand of DWV for up to 13 weeks after consuming infected honey bees [We confirmed DWV, KBV, and MKV replication in a number of species, indicating that these species possibly act as biological vectors that facilitate disease emergence. However, with pollinators and associates collected in the field, we cannot exclude the possibility of detecting viruses and negative strand intermediates in the gut contents that come from other infected insects. KBV and MKV replication was confirmed in species not typically known to eat bees, such as ney bees ,33. Recee tissue  and vecte tissue ,77. Yet,e tissue . Neverthney bees , which iney bees  or aid iney bees  remains Varroa in 2001 [A. mellifera populations but that the virus shows little host specificity [To understand the current epidemic of bee viruses, it is key to determine the role of the host species and geographic distribution ,65. By p in 2001 , all Newcificity . AlthougMany emerging viruses infect and actively replicate within a wide range of pollinators and associated Arthropod species. Our results and others indicate that the host species can affect the association with shared ancestry, which indicates virus transmission, but that these effects are weaker than the geographic location . Overall


Kitaviridae includes a small number of positive-stranded RNA plant viruses. Interestingly, this family name is not derived from the name of the type virus member, as usually, but from the family name of Dr. Elliot Watanabe Kitajima, a prominent virologist participating in kitavirus studies  virus particles and have multipartite genomes composed of two, three, or four RNAs for cile-, higre- and bluner-viruses, respectively. In addition to common particle morphology, most viruses share some important biological peculiarities, such as lack of systemic movement , as all viruses in this family are rod-shaped] followed by those of the family Bromoviridae  domain or concatenated sequences of methyl transferase (MT), replicative RNA helicase (HEL), and RdRp unambiguously showed that kitaviruses are most closely related to members of family Martellivirales, show genome similarity to arthropod tombus-like viruses  and Wuhan heteroptera virus 1 (NC_033461) each encode in their monopartite genomes three proteins distantly related to SP24 among seven non-replicative proteins  among nege-like viruses, proteins  .It is currently assumed that multiple inter-kingdom jumps between hosts created the modern plant and insect positive-stranded RNA virus diversity, which started its expansion from arthropod hosts as a primary reservoir  strongly argues in favor of quite recent horizontal virus transfer between plant and arthropod hosts. This RNA virus—Gentian Kobu-sho-associated virus (GKaV)—is discovered in a hyperplastic (tumorous disorder-affected) Japanese gentians, possesses a very large genomic RNA (22 Kb) and codes for a polyprotein of more than 810 kDa with prominent sequence similarity to proteins encoded by flaviviruses  (accession GGDV01007611) (data not shown).Outside nege-kitavirus representatives, identification of a unique plant virus in gentian  having a similarity to blunervirus RNAs. Three of these P. tomentosa VLRAs exhibit a gene arrangement quite similar to that in RNAs 1, 2, and 3 of blunerviruses  , barley aphid RNA negev-like virus 4 and “jiviviruses”  encodes an RdRp domain also showing relationship to closteroviruses and negev-like viruses  encode SF1 helicases. Most probably, at least one of the blunervirus SF1 helicases represents a replicative protein. Particularly, RNA1-encoded helicase is a part of protein combining MT and HEL domains similarly to the replicative RNA1-encoded protein in the members of elicases . Strikinviruses” , which iviruses” . “Jivivi viruses . However viruses . Most st viruses  (Supplem viruses . Thus, tBased on these results and those presented in our previous papers (Morozov and Solovyev, SM collected and analyzed the data and authored drafts of the paper. EL prepared figure and reviewed the final draft. AS authored drafts of the paper, prepared figure, and reviewed the final draft. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Tomato spotted wilt orthotospovirus (TSWV) was the most common virus, with a detection rate of about 20.0% followed by Pepper vein yellows virus . This survey revealed for the first time that pepper is a natural host of Tobacco vein distorting virus (TVDV) worldwide and tomato is a natural host of Potato leafroll virus (PLRV) in China. PeVYV, Tobacco mild green mosaic virus (TMGMV) and Wild tomato mosaic virus (WTMV) were first time found in pepper and Tomato mottle mosaic virus (ToMMV) and Chilli veinal mottle virus (ChiVMV) were first time found in tomato in Yunnan Province. Finally, the virus incidences were higher in Kunming, Yuxi, Chuxiong, and Honghe region than other regions.During pepper and tomato production seasons in 2013–2017, large-scale virus disease surveys were conducted in different regions of Yunnan Province, China. A total of 1,267 pepper and tomato samples with various virus-like symptoms were collected and analyzed for virus infections through dot enzyme-linked immunosorbent assay (dot-ELISA), polymerase chain reaction (PCR), and reverse-transcription (RT)-PCR. The detection results showed that 19 different viruses were present in about 50.9% of the assayed samples, and among these viruses, seven viruses were found in both pepper and tomato samples. Mixed infections with two to three of the 15 identified mixed infection types were found in the pepper samples and 10 identified mixed infection types were found in the tomato samples. Among the infected samples,  Capsicum annuum) and tomato (Solanum lycopersicum) are two economically important solanaceous vegetable crops in China and many other countries. With the rapid increase of production areas and growth of new cultivars in the recent years, outbreaks of virus disease have become common in solanaceous crops, leading to serious yield losses. Approximately 76 and 136 viruses have been reported for pepper and tomato plants throughout the world, respectively (Cucumber mosaic virus (CMV) and Tobacco mosaic virus (TMV) were the most predominant viruses in both pepper and tomato fields in China , harvested, and then stored separately in plastic sampling bags till use. This survey focused on pepper and tomato crops in 38 counties belonging to 12 different cities or autonomous regions from April to October in 2013, 2014, 2015, and 2016 and April in 2017. More tissue samples were collected from the surveyed fields with higher disease incidences and severer disease symptoms, while fewer samples were collected from the fields with lower disease incidences and milder disease symptoms . The col2HPO4, 0.001 M KH2PO4, pH 7.4), the tube was placed at −80°C for 5 min, and then ground using a high-throughput tissue homogenizer  set at 60 Hz for 2 × 90 s (twice). The tube was centrifuged at 8,000 × g and 4°C for 5 min, and the supernatant in each tube was blotted onto a nitrocellulose membrane  followed by air-drying. The membrane was incubated for 30 min in 10 ml PBST buffer  supplemented with 5% skim milk powder and then probed with a diluted monoclonal antibody for 1 h at 37°C. Monoclonal antibodies specific for Broad bean wilt virus 2 (BBWV2), Cucumber green mottle mosaic virus (CGMMV), CMV, TMV, Tomato spotted wilt orthotospovirus (TSWV), or Turnip mosaic virus (TuMV) were kindly provided by Prof. Xueping Zhou, Zhejiang University, Hangzhou, China. After four washes in the PBST solution, the membrane was incubated again in 10 ml 10,000 times diluted alkaline phosphatase (AP)-conjugated goat anti-mouse IgG  in PBST for 1 h at 37°C. After five washes in PBST, the membrane was incubated in 5 ml AP substrate solution  as instructed for color development at room temperature for 10–25 min. The reaction was terminated after the positive control dots developed a purple color, whereas the negative control dots remained a light green color. A sample was considered infected if all three dots developed the purple color. Positive control samples representing BBWV2, CMV, TMV, TSWV, or TuMV were maintained in our laboratory, and the CGMMV-infected control sample was kindly provided by Dr. Zhaobang Cheng, Jiangsu Academy of Agricultural Science, Nanjing, China.Serological tests were done using the dot enzyme-linked immunosorbent assay (dot-ELISA) as described  with sli–) Kit . Each RT reaction contained about 200 ng of total RNA (2 μl), 1 μl of Random Oligo-dT (N6) primer  or a specific reverse primer (10 μM), and 3 μl nuclease-free ddH2O. The mixture was incubated at 70°C for 10 min and then chilled immediately on ice for 3 min. After addition of 2 μl of 5 × M-MLV buffer, 0.5 μl of dNTP mixture (10 mM each), 0.5 μl of RTase M-MLV (RNase H–), and 1 μl of nuclease-free H2O, the reaction mixture was incubated at 42°C for 1 h followed by 70°C for 15 min. Each PCR reaction was 10 μl , 0.2 μl each primer (10 μM each), 1 μl cDNA (RT-PCR) or total nucleic acid (PCR), and 3.6 μl nuclease-free H2O), and the reaction condition was initial denaturation at 94°C for 5 min, 35 cycles (for reactions using specific primers) or 40 cycles (for reactions using degenerated primers) of 94°C for 30 s, 40–55°C for 30 s, and 72°C for 1 min, followed by the final extension at 72°C for 7 min. The PCR or RT-PCR products were visualized in 1% agarose gels through electrophoresis in 0.5 × TBE buffer. The resulting agarose gels were stained with 5 μl Gold View as instructed  and examined under an UV illumination GenoSens1850 system.Total nucleic acid was extracted from tissue samples using a modified CTAB method . Degener1. The results were then confirmed by both dot-ELISA and RT-PCR for RNA viruses or PCR for DNA viruses.PCR products were recovered using a Universal DNA Purification Kit  and then cloned into the pMD19-T Vector . At least three clones representing a single PCR product were sequenced by the Beijing Genomics Institute . The resulting sequences were used to BLAST search the sequence database at the National Center for Biotechnology InformationPepper and tomato fields in 38 counties, belonging to 12 different cities or autonomous regions (refer to as regions thereafter) were surveyed for virus diseases in 2013, 2014, 2015, 2016, and 2017 . A totalChilli veinal mottle virus (ChiVMV), CMV, Pepper mild mottle virus (PMMoV), Tobacco bushy top virus (TBTV), Tomato mosaic virus (ToMV), Tomato mottle mosaic virus (ToMMV), and TSWV were detected in both pepper and tomato samples (Pepper vein yellows virus (PeVYV) and CMV  . Among t samples . The vir and CMV . Further and CMV . For ins and CMV .To determine the geographical distributions of these viruses in Yunnan Province, we analyzed the field survey and virus detection data. The result showed that the virus detection rates in Kunming, Yuxi, Honghe, and Chuxiong regions were higher, ranging from 49.3 to 69.6% , and alsTobacco vein distorting virus (TVDV), PMMoV, ToMMV, TMV, Tobacco mild green mosaic virus (TMGMV), BBWV2, TBTV, and Wild tomato mosaic virus (WTMV) (MN889854). In addition, PeVYV (GenBank accession no. MN889851), TMGMV (GenBank accession no. MN889852), and WTMV (GenBank accession no. MN889853) were first time found in the pepper fields in Yunnan Province. Among the 49 pepper-infecting CMV isolates, 48 were CMV I subgroup isolates and one was CMV II subgroup isolate.A total of 13 RNA viruses were detected in 429 of the 821 assayed pepper samples, namely: TSWV, PeVYV, CMV, ChiVMV, ToMV, s (WTMV) . Among ts (WTMV) . In thisOf the 429 infected pepper samples, 51 samples were co-infected with two or three different viruses  . Among tTSWV was the most common virus in Kunming, Yuxi, and Chuxiong regions, while PeVYV was the most dominant virus in Honghe, Dehong, Baoshan, and Wenshan regions . In DaliTomato chlorosis virus (ToCV), Tomato zonate spot orthotospovirus (TZSV), CMV, ToMV, TBTV, ToMMV, ChiVMV, PMMoV, and Potato leafroll virus (PLRV), and the identified DNA viruses were Tomato yellow leaf curl virus (TYLCV), Tomato yellow leaf curl Thailand virus (TYLCTHV), and Papaya leaf curl China virus (PaLCuCNV). Among these viruses, TSWV and TYLCV were most common viruses found in the tomato samples. In this survey, PLRV (GenBank accession no. MN894826) was first time found in the infected tomato samples in China, while ToMMV (GenBank accession no. MN894824) and ChiVMV (GenBank accession no. MN894825) were first time found in the tomato samples in Yunnan Province. It is noteworthy that all the CMV isolates detected in the tomato samples belonged to the CMV II subgroup.A total of 10 RNA viruses and three DNA viruses were detected in 216 of the 446 assayed tomato samples . The ideAmong the 216 infected tomato samples, 38 were co-infected with two or three viruses  . Among tThe dominant tomato-infecting viruses in different regions varied. For instance, TSWV was the most common tomato-infecting virus in Kunming region from 2013 to 2016, whereas CMV and TYLCV were the most common viruses in Yuxi and Chuxiong regions, respectively . In 2013In this study, the most common disease symptoms observed on the infected pepper and tomato plants were leaf mottling or mosaic, distortion, necrosis and yellowing, and plant stunting. To investigate the potential correlations between disease symptoms and the 19 identified viruses, we compared disease symptom and the virus identification data obtained in this study. The result indicated that the correlations were complex. Same virus often caused different disease symptoms in these two host plants of different varieties at different growth stages and in different infection seasons. In contrast, some different viruses caused similar disease symptoms in different infected pepper or tomato plants of the same variety. Furthermore, disease symptoms caused by different combinations of viruses in the pepper and tomato plants also varied and were influenced by the environmental conditions. Therefore, disease symptoms shown on infected plants cannot be directly linked to the causal virus(es). However, disease symptoms caused by a single certain virus in a particular host plant were similar, including blistering and ring spots in the TSWV-infected leaves or leaf distortion  in CMV-infected leaves. Disease symptoms caused by viruses belonging to the same genus  were similar .In this study, we surveyed pepper and tomato fields in different regions in Yunnan Province, China . The resvia different ways, management strategies for different regions should also vary accordingly. For example, applications of insect pesticides and resistant pepper and tomato varieties should be used in Kunming, Dehong, Honghe, Dali, and Baoshan regions because most dominant viruses in these regions are transmitted by insect vectors , and TYLCV were the major viruses in pepper and tomato fields in different provinces of China . The resTBTV and TVDV were known to infect tobacco to cause bushy top disease , it may In this survey, no virus was detected in some samples with virus-like symptoms. It is possible that these virus-like symptoms were induced by other factors, including fungi, insects, abiotic stresses, environmental conditions, and/or pesticides. It is also possible that the causal virus(es) were not covered by the detection methods. As the sample sizes from some locations were small, the disease incidence in these locations needs further validation. Nevertheless, the information presented here should allow a better management of virus diseases in Yunnan Province.We have conducted a comprehensive survey of virus diseases in the pepper and tomato fields in Yunnan Province, one of the main vegetable production provinces in China. Our result indicates that the virus population structure in the pepper fields is more complex than that in the tomato fields. This information is useful for a better management of virus diseases in these two vegetable fields in this region.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/YLi, GT, and FL conceived and designed the experiments. YLi, LX, and WZ performed the experiments. YLi and GT collected the samples and analyzed the data. PL, XC, and YLiu contributed reagents, materials, and analysis tools. YLi, RL, and FL wrote the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Respiratory syncytial virus , Human Rhinovirus , Influenza A virus  and Human Bocavirus . RSV infections peaked in July to October, were relatively more common in children <1 year and in the northernmost hospital. IAV infections peaked in December to February and were relatively more common in patients >5 years in the central region. Coinfection with IAV or RSV was associated with increased disease severity compared with patients only infected with HBoV or HRV. Over a hundred genomes belonging to 13 families and 24 genera were obtained via metagenomic sequencing, including novel viruses and viruses less commonly associated with ARIs. Phylogenetic and phylogeographic analyses further indicated that neighboring countries were the most likely source of many virus lineages causing ARIs in Vietnam and estimated the period that specific lineages have been circulating. Our study illustrates the value of applying the state-of-the-art virus diagnostic methods (multiplex RT-PCR and metagenomic sequencing) and phylodynamic analyses at a national level to generate an integrated picture of viral ARI epidemiology.Acute respiratory infections (ARIs) impose a major public health burden on fragile healthcare systems of developing Southeast Asian countries such as Vietnam. The epidemiology, genetic diversity and transmission patterns of respiratory viral pathogens that circulate in this region are not well characterized. We used RT-PCR to screen for 14 common respiratory viruses in nasal/throat samples from 4326 ARI patients from 5 sites in Vietnam during 2012–2016. 64% of patients tested positive for viruses; 14% tested positive multiple co-infecting viruses. The most frequently detected viruses were  Acute respiratory infections are the leading cause of morbidity and mortality in young children under 5 years, accounting for over 16% of deaths worldwide, which mainly occur in Southeast Asia , includiHuman metapneumovirus (HPMV)], although such knowledge may aid studies of the circulation and spread of the viruses at both regional and global scales. Metagenomic sequencing technology and bioinformatics analyses are promising strategies for identifying pathogens in clinical and public health settings, which not only allow the characterization of different known and novel pathogens simultaneously, but also provided better understanding of the transmission dynamics of infectious diseases with the supplement of epidemiological information  have allowed the identification of new pathogens as causes of respiratory diseases . Howeverormation .In this study, we explored the characteristics of multiple viral pathogens co-circulating in patients with ARIs in five regions of Vietnam over a 4 year period. Specifically, we examined the differences in the relative abundance of respiratory virus infections by geographic location, patient age, and season/time, compared the severity of infections and tested for an impact of coinfections on severity. We also assessed the genetic diversity of respiratory viral pathogens in Vietnam and compared the molecular epidemiology of viruses co-circulating in the same region using full genome sequences. In addition, we used genome sequence data to look for the presence of less well-studied virus species from the virome in respiratory samples, some of which may be associated with ARIs.The Vietnam Initiative on Zoonotic InfectiONS (VIZIONS) was a multidisciplinary Vietnam-based project established to increase the understanding of the origins, risks and emergence of zoonotic infections . In thisHuman parainfluenza virus (HPIV group 1–4), HBoV, EV, HRV , Coronavirus (CoV), HAdV, and Human parechovirus (HPeV)  ; whereass (HPeV) . Note thn = 559) and then put through a metagenomic sequencing process which has been previously described  to measure root-to-tip divergence for ML trees.We conducted phylogenetic analyses to further explore the evolution and transmission of current circulating respiratory viral pathogens in Vietnam using whole genome sequence data. Reference sequences for related genus were obtained from GenBank up to 16/06/2017, and aligned with sequences retrieved in this study using Muscle . For pat8 steps and sampled every 104 steps. Two independent runs were used in each segment to confirm the convergence and then combined. For major respiratory pathogens which have adequate numbers of Vietnamese sequences, we estimated the spatial diffusion dynamics between Vietnam and other locations (use continent and country as traits for discrete states). We considered the possible influence of unbalanced sampling and subsampled sequences from the same locations and isolation time. We used an asymmetric model and incorporated BSSVS to identify a sparse set of transmission rates that identify the statistically supported connectivity . Different substitution models, clock models and tree models were evaluated for each segment by using the stepping stone method . A generectivity . We alsoectivity .e-transformed response variables  were used to compare length of time spent in hospital by patients infected with different viruses, patients positive and negative for virus infection, as well as patients with and without coinfections, including gender, age, and hospital site as potential confounding variables. We used an ANOVA-based model selection procedure to assess the importance of explanatory variables in explaining variation in the response variable. Each explanatory variable was tested for significance using likelihood ratio tests (LRTs) by removing each variable from the full model individually and using an LRT to compare models including and excluding that variable. To examine the effect of specific coinfection combinations on disease severity, we used a linear mixed model  comparing Los of patients who single-infected with major viruses with patients who coinfections with other viral pathogens. All analyses were implemented in R version 3.4.4.Fisher’s exact tests were used to examine whether there was an association between types of viruses and location/gender/patient age/seasonality. Generalized linear models (GLMs) with logn = 3394, 79%) were children aged 1 month to 5 years old; 844 (20%) were between 5 and 65 years; 88 (2%) were older than 65 years old. Of the 4326 enrolled patients, 4323 were tested for 14 viral pathogens using RT-PCR at hospitals in BaVi/Hanoi (n = 601), Hue (n = 561), Dak Lak (n = 1444), Khanh Hoa (n = 1058) and Dong Thap (n = 659)  . There an = 659) .n = 980) of tested patients, followed by HRV , IAV  and HBoV (7.3% n = 331). In addition, we found that the proportion of patients with ARIs who were positive for a specific viral pathogen varied significantly across hospital sites (Fisher’s exact test: p < 0.001)  . For exa213 = 456.2, p < 0.001, n = 3523; n = 747), group 2 is 1 to 5 years old (n = 2647), group 3 is 6 to 65 years old (n = 844), group 4 is >65 years old (n = 88)  . The perp < 0.001). The percentages of HRV in group 1 and 2 (20 and 20%) were significantly greater than in group 3 and 4 (12 and 9%) (Fisher’s exact test: p < 0.001). HBoV showed a similar pattern  as HRV (Fisher’s exact test: p < 0.001). In contrast, the percentage of IAV was higher in groups 3 and 4 (53 and 45%) and lower in groups 1 and 2 (6 and 15%) (Fisher’s exact test: p < 0.001).Regarding specific viruses, the percentages of RSV were significantly greater in group 1 (61% of detected viruses) compared with the other three age groups  . For specific viruses, the detection of RSV peaked during May to October and IAV was most frequently detected from December to February; whereas no consistent seasonal pattern was observed for HRV and HBoV  of patients as a proxy for disease severity as there were no fatalities in this study. The LoS (days) varied significantly between patients who tested positive for different virus species . For exaEnterovirus (EV) (25%). Among all HBoV cases with coinfections, the most frequently co-detected viruses were HRV 29%, HAdV 24% and RSV 23%. We further tested whether co-infections with specific viruses increased the LoS but found that coinfections did not significantly affect the LoS of patients with RSV, HRV, IAV, or HBoV infections  had a single viral pathogen and 625 (23%) had multiple viral pathogens. Overall, the length of stay in hospital for patients infected with a single virus was not significantly different from those infected with multiple viruses . The profections . Howevern = 1576), who may have bacterial infections, undetected virus infections, post-viremic virus infections or non-infectious respiratory conditions. We found patients without any virus detected spent significantly less time in hospital , we further tested whether the trends of seasonality, coinfection rate and their Los are differed among sites and age groups , S3. TheAnelloviridae  were further investigated using metagenomic sequencing. If multiple contigs from a sample generated hits to the same reference genome in the BLAST alignment, one representative contig was selected. In total, 218 unique full genomes/partial virus genomes (out of 1363 contigs) were resolved from 167 unique patients. These virus sequences belonged to 13 families and 24 genera . Around oviridae . These mn = 54) were significantly higher than those samples in which a virus was detected by both methods    and Herpesviridae , plus smaller numbers of HPyV, MeV, Picobirnavirus, Gammapapillomavirus, Cardiovirus, ICV, and Circovirus (n = 1 to 8) viruses . In contrast, more than half of patients who tested positive for Alphatorquevirus (n = 20), Cytomegalovirus (n = 15) and Lymphocryptovirus (n = 2) were co-infected with one or more of the common respiratory viruses and those who tested positive for Betatorquevirus, HPyV, unclassified Anellovirus, Gammapapillomavirus and Gammatorquevirus were always co-infected with common respiratory viruses. The specific co-infection combinations between common respiratory and other viruses retrieved from the same patient (n = 40) are shown in We compared the results of metagenomic sequencing and RT-PCR . First, < 0.001) , indicat< 0.001) , metagen viruses . Specifin = 109) were obtained, including virus species or subtypes reported for the first time in Vietnam: HAdV, HMPV, Human coronavirus , HRV, EV (type B), ICV, Cardiovirus, HPyV and Anellovirus (Anellovirus), maximum likelihood trees were generated  (We retrieved 21 RSV complete genome sequences. These genomes were isolated from young children (0 to 3 years old). Twelve genomes (with nucleotide genome sequence identities between 98.6 and 99.9%) belonged to subtype A and 9 genomes (with nucleotide genome sequence identities between 99.0 and 99.7%) belonged to subtype B. There were no significant differences between the two subtypes in terms of patients’ age, gender, admission date to hospital and length of stay in hospital (Mann-Whitney p > 0.5) . BayesiaWe found that all RSV-A Vietnamese isolates in this study belonged to genotype ON1 . These iU Test, with p > 0.5). Strong temporal clustering was apparent in both SwH1N1 and H3N2 phylogenies, and sequences co-circulating in the same location in Vietnam and the same year were subdivided into multiple subgroups (four for both SwH1N1 and H3N2) (Nineteen IAV sequences (9 H3N2 and 10 SwH1N1) with nearly full genome lengths were obtained. These IAV sequences were obtained from patients with a wide age range (0 to 35 years old) . Similarnd H3N2) . Each sund H3N2) . Specifind H3N2)  and H3N2nd H3N2) . In addind H3N2) . The geond H3N2) . With cund H3N2) .In total, 7 HBoV genomes were obtained, all from young children (1–2 years old). These genomes all belonged to HBoV type 1 (HBoV-1). Phylogenetic analysis of Vp1 genes showed that the co-circulating Vietnamese HBoV sequences formed two separate subgroups: three of them fell into one subgroup emerged around 2006, which were grouped together with strains isolated in HCMC in 2014 , as wellTen HRV genomes were obtained in this study. Except for one isolated from a 58-year-old patient, all HRV genomes were from children under 5 years . The 10 Here we present the results of a large-scale, prospective study to explore the virus diversity in patients with ARIs in Vietnam. Using multiplex PCR, we found 14 respiratory viruses in patients at different proportions at 5 hospital sites during the study period. RSV was the most frequently detected virus, followed by HRV, IAV, and HBoV, although the proportions fluctuated by patient age, location and time. These findings are in good agreement with many previous studies on hospitalized ARIs .Consistent with previous work , we founWe found that RSV type A and B co-occurred throughout the 3 year study period. However, the proportions of these two types differed year by year . In North China, subgroup B was found to be dominant in the 2012/2013 season and in the 2013/2014 the subgroup of dominance shifted from B to A , which dWe also identified different spatial transmission patterns for RSV and IAV in Vietnam. We found a strong phylogeographic linkage of the RSV clusters from Vietnam with sequences within Asia and frequent transmissions of RSV from China to Vietnam . In comparison, IAVs from Vietnam were likely transmitted from the sequences prevalent both within Asia and other continents . The results were consistent with the complex global circulation patterns of seasonal IAV . For theCytomegalovirus, Lymphocryptovirus, and Herpes simplex virus, often found as co-infections in the respiratory tract or lung, mainly in patients with suppressed immune systems  (No. 157-12) in the United Kingdom. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.LL and MW designed the study. GR and LL performed the statistical analyses. JA, AI, and LL performed the metagenomics analyses. LL performed the phylogenetic analyses and wrote the manuscript. All authors reviewed, commented on and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Many neurodegenerative diseases are associated with chronic inflammation in the brain and periphery giving rise to a continuous imbalance of immune processes. Next to inflammation markers, activation of transposable elements, including long intrespersed nuclear elements (LINE) elements and endogenous retroviruses (ERVs), has been identified during neurodegenerative disease progression and even correlated with the clinical severity of the disease. ERVs are remnants of viral infections in the human genome acquired during evolution. Upon activation, they produce transcripts and the phylogenetically youngest ones are still able to produce viral-like particles. In addition, ERVs can bind transcription factors and modulate immune response. Being between own and foreign, ERVs are reviewed in the context of viral infections of the central nervous system, in aging and neurodegenerative diseases. Moreover, this review tests the hypothesis that viral infection may be a trigger at the onset of neuroinflammation and that ERVs sustain the inflammatory imbalance by summarizing existing data of neurodegenerative diseases associated with viruses and/or ERVs. Viruses have long been linked with diseases of the nervous system. Several viruses, including human α-herpesvirus types 1, 2, and 3 , human cytomegalovirus (CMV), human immunodeficiency virus (HIV), Epstein–Barr virus (EBV), Ebola virus, and rabies virus are capable of reaching the central nervous system (CNS) . Often, More recent research has shown that viruses, such as HIV, EBV, CMV, influenza, herpesviruses, and HTLV-1 can activate viral sequences originating from retroviral infections in the distant past of human evolution that have been incorporated into the human genome . While tThis review highlights the interplay between endogenous viruses and retroelements, on the one hand, and exogenous viruses, on the other hand, and aims at revealing underlying mechanisms in aging, and neurodegenerative and neuroinflammatory diseases summarizing recent advances in this field.The central nervous system (CNS) is not a common target organ for viruses. It is neither easily accessible nor as advantageous in terms of contagiousness and successful viral transmission to new hosts as the respiratory or gastrointestinal tract. Shielded by the meninges, CSF, and blood brain barrier (BBB), the CNS is immunologically unique and privileged . AlthougOnce in the CNS, acute infections present with encephalitis, myelitis, or viral meningitis. Generally, virus-triggered immune reaction is limited in time and ends with the virus being combated; however, certain neurotropic viruses can continue to elicit progressive damage on brain structure, function, and cognition long after the clearance of virus from the peripheral blood. In addition to this type of chronic infections, viruses can enter a latent (dormant) phase, interrupted by occasional full awakening of the virus. Sometimes, the same virus can contribute to both. This is the case for the HIV , measlesExogenous retroviruses from which ERVs originate, like other retroviruses, contain single-stranded (ss) anti-sense RNA and RNA reverse polymerase to generate double-stranded DNA (dsDNA). With the help of the retroviral integrase, this DNA copy may become endogenized into the host genome, essentially when infecting gametes (germ cells) with chromosomal insertion sites that will allow the birth of viable offspring over generations. Over the evolution, this type of infections and endogenizations of retroviruses have occurred multiple times . GradualLong interspersed nuclear elements (LINEs) are a group of non-LTR  retroelements that compose up to 21% of the human genome . LINE-1 Alu family is the most common member of the short interspersed nuclear elements (SINEs) and accounts for about 13% of the human genome . Alu eleHERVs, LINEs, and Alus regulate gene expression networks at multiple levels, providing a rich pool for RNA diversification , functioInherent ERVs and exogenous viruses, being distant relatives, share common mechanisms but can also be opponents. When viruses first try to enter a cell, HERV, coming from inside the host genome, can provide protection by blocking the cellular receptors relevant for the exogenous retrovirus entry . ERVs caActivated innate and adaptive immune system cells both can stimulate ERV transcription . Generaltrans-activation can take place where transcription of one virus is initiated by factors produced by the other virus. When ERVs provide envelope glycoproteins to exogenous retroviruses, these could establish a new host cell repertoire and circumvent immune system response  affecting multiple systems in the body. One of the complications of HIV infection is the HIV-associated neurodegenerative disorder (HAND) , which cNeurodegeneration characteristic to HAND emanates from chronic inflammation, sustained by activated monocytes, macrophages and astrocytes, and neurotoxic HIV viral proteins . These iFurther augmentation of neurodegeneration and neuroinflammation in HAND comes from HIV and infection-induced cytokines’  ability to dynamically activate HERVs, such as HERV-W  and HERVOf note, incidence of HIV-associated dementia has reduced threefold after the combination antiretroviral therapy became available . New medAlzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by gradual cognitive decline. AD can start even decades before the appearance of clinical symptoms . AD is aGrowing evidence points to the role of pathogens, such as HHV-1, HHV-6A, HHV-7 , EBV, anHERV-H, HERV-K, HERV-L, and HERV-W are transcriptionally active in the brains of AD patients . This acMultiple sclerosis (MS) is a neurodegenerative and neuroinflammatory CNS disease characterized by multifocal demyelinating lesions in the brain and spinal cord leading to progressive physical and cognitive disabilities. Development of MS has been associated with viral infections and activation of HERVs .Among viruses, higher transcription levels of HHV-3 and HHV-6 have been found in the CSF of individuals suffering from MS . Also, cHERV-W is also the main HERV associated with MS pathology. Further, the expression level of HERV-W in the brain of MS patients correlates positively with the severity of disability and disease progression . HERV-W Mechanistically, HERV-W env protein has been shown to induce microglial polarization and closely associate with myelinated axons in MS lesions ultimately leading to structural damage of these axons . HERV-W ClinicalTrials.gov identifier: NCT02782858).The central role of HERV-W env in MS neurodegeneration has led to the development of a specific monoclonal antibody, Temelimab (GNbAC1) , an agenAmyotrophic lateral sclerosis (ALS) is a neurodegenerative disease, characterized by progressive loss of cortical and spinal motor neurons. While majority of ALS cases are sporadic, mutations in certain genes, such as trans-activation responsive (TAR) DNA-binding protein 43 (TDP-43), have been associated with ALS development .That ALS might be linked with viral infections, comes from finding HIV and HTLV-1 presence in the brains of ALS patients . FurtherSchizophrenia is a neuropsychiatric and neurodevelopmental disorder characterized by episodes of psychosis, hallucinations, and delusions. Disease typically starts in young adulthood and is strongly affected by genetic background and environmental factors . The neuThe likelihood of developing schizophrenia is increased by infections (most significantly evidenced with studies on HHV-2) , subclinIn addition to LINE-1, expression of several HERV families, such as HERV-K, HERV-W, and HERV-H, has been shown to be dysregulated in the brains, cerebrospinal fluid, and blood of schizophrenia patients . This coHighly pathogenic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a single-stranded RNA virus from the coronavirus’s family .SARS-CoV-2 enters host via its immunogenic spike glycoprotein binding to ACE2 receptor on endothelial and smooth muscle cells . ResultaSARS-CoV-2 viral proteins interact with human proteins that regulate cellular longevity and aging, and are involved in stress response, vesicle trafficking, lipid metabolism, production of reactive oxygen species, RNA regulation, ubiquitin ligases, and mitochondrial activity . ImpaireUp to one third of COVID-19 patients develop neurological symptoms beyond the acute stage of the disease, mainly manifesting with chronic fatigue syndrome and myalgic encephalomyelitis . That seAging is a progressive deterioration of physiological functions at the cellular, organ, and organism levels eventually leading to senescence. Aging disrupts the balance between the nervous and the immune system and increases risk for various neurodegenerative and neuroinflammatory diseases .Aging increases genomic instability  by graduAging can determine the outcome of interplay between endogenous and exogenous viruses. Interaction of the endogenous murine leukemia virus with the generally non-pathogenic murine togavirus lactate dehydrogenase-elevating virus leads to a fatal and progressive neurological disease in up to 100% of aged mice. This suggests convergence of age-related, genetic, immunological, and viral factors in the development of a neurological disease resembling ALS in humans .This review brings together studies that have described a role for exogenous viruses and (H)ERVs in CNS pathologies and thereby highlights the interplay between the inherent and the foreign. A contribution of exogenous and endogenous viruses, separately and together, is increasingly evident in common forms of dementia in young (HAND) and elderly population (AD), MS, ALS, and also schizophrenia. In other neurological complications of viral origin, such as SARS-CoV-2, it remains to be seen if and how HERV, LINE-1, and Alu expression may be involved. Viral CNS infections can be early triggers of neuroinflammation; however, if viruses are successfully combated or entered in a latent state, a central role might be attributed to endogenous retroviruses. ERV activation during infections seems to be a common  mechanism that the host may not be able to control at some point. ERVs can become continuously activated and sustain the inflammatory imbalance. The crosstalk with IFN seems to play an important role here. Facilitating factors that are associated with continuous ERV activation such as aging, stress, and other comorbidities as well as re-awakening of a latent virus, cumulative or opportunistic infections, as seen in immune-deprived conditions, contribute to the progressive neurodegeneration or delayed CNS pathologies. We are only beginning to understand how exogenous viruses in connection with HERVs and other retroelements affect normal aging and development of neurodegenerative diseases and other neuropathologies. The central role of HERV-W in MS pathology has led to its targeting in clinical trials. It remains to be seen, whether other HERVs could provide key targets in other neurodegenerative diseases, such as HERV-K in ALS, to which there is currently no cure.CR designed the manuscript idea, performed literature search, and wrote the manuscript.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Viruses are ubiquitous biological entities, estimated to be the largest reservoirs of unexplored genetic diversity on Earth. Full functional characterization and annotation of newly discovered viruses requires tools to enable taxonomic assignment, the range of hosts, and biological properties of the virus. Here we focus on prokaryotic viruses, which include phages and archaeal viruses, and for which identifying the viral host is an essential step in characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus, which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts, which needs improvements at both accuracy and usability. Here we develop a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods.k-mer frequencies between viral and host genomic sequences as features. PHP gave a host prediction accuracy of 34% (genus level) on the VirHostMatcher benchmark dataset and a host prediction accuracy of 35% (genus level) on a new dataset containing 671 viruses and 60,105 prokaryotic genomes. The prediction accuracy exceeded that of two alignment-free methods . PHP also outperformed these two alignment-free methods much  when predicting hosts for prokaryotic viruses which cannot be predicted by the BLAST-based or the CRISPR-spacer-based methods alone. Requiring a minimal score for making predictions (thresholding) and taking the consensus of the top 30 predictions further improved the host prediction accuracy of PHP.We present here Prokaryotic virus Host Predictor (PHP), a software tool using a Gaussian model, to predict hosts for prokaryotic viruses using the differences of The Prokaryotic virus Host Predictor software tool provides an intuitive and user-friendly API for the Gaussian model described herein. This work will facilitate the rapid identification of hosts for newly identified prokaryotic viruses in metagenomic studies. Prokaryotic viruses which include phages and archaeal viruses play an important role in balancing the global ecosystem by regulating the composition of bacteria and archaea in water and soil. Identifying the viral host is essential for characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts which needs improvements at both accuracy and usability. This study developed a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. It will contribute to the rapid identification of hosts for prokaryotic viruses in metagenomic studies, and will extend our knowledge of virus-host interactions.31 viral particles at any given time on earth [Viruses are ubiquitous biological entities, with an estimate of 10on earth –5. For hon earth  and Crohon earth . Intereson earth , 9, espeViruses are estimated to be the largest reservoirs of unexplored genetic diversity on earth . Novel vIdentifying the viral host is essential for characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is to culture the virus, which is low-throughput, time-consuming, and expensive . Even woSeveral computational approaches have been introduced to predict hosts of viruses based on viral genomic sequences. They can be largely classified into two groups according to their dependence on alignment: alignment-based methods and alignment-free methods. The alignment-based methods rely on sequence similarity searches between a query virus and candidate host genomes because viruses and their hosts sometimes share genes and/or short nucleotide sequences , 17. Suck-mers to other phages with known hosts [2* for measuring the similarity of oligonucleotide frequency between viruses and hosts, and predicts the one with the lowest distance to the virus as the viral host. VHM achieved a host prediction accuracy of 33% at the genus level. WIsH predicts viral hosts by training a homogeneous Markov model for each potential host genome, then calculating the likelihood of a contig under each of the trained Markov models, and finally predicting the host whose model yields the highest likelihood. WIsH has achieved 63% mean accuracy at the genus level on their benchmark dataset of 3 kbp phage contigs and is currently the best tool for predicting phage hosts based on short phage contigs.The alignment-free methods predict the host of viruses based on co-occurring wn hosts , or sequwn hosts  and WIsHwn hosts  have achk-mer frequencies between viral and host genomic sequences. A standalone tool and a web-based tool was implemented to run the GM. The GM not only outperformed previous alignment-free methods, but also shaped a complement to the alignment-based methods in predicting hosts for prokaryotic viruses. The GM should facilitate the prediction of virus host in metagenomic studies.In this study, a Gaussian model (GM) for predicting hosts of prokaryotic viruses was developed based on the differences of The prokaryotic viruses were referred to as viruses hereinafter unless otherwise specified. Two datasets were used to build and test computational models for predicting virus hosts. The first was the VirHostMatcher (VHM) benchmark dataset obtained from Ahlgren’s study . The taxThe second dataset was the test dataset to assess the computational models of predicting virus hosts. Contrary to the VHM dataset that contains virus-host interactions compiled from the NCBI RefSeq database  before Mk-mer frequencies between virus and prokaryotic genomic sequences as features, and outputs a score  for the prokaryote. The k-mers of 4 nucleotides were selected  for all prokaryotic genomes available in the dataset. For example, in the test dataset, each of the 60,105 prokaryotic genomes would be assigned a score  by the GM. The prokaryotic species with the highest score was considered as the predicted host of the virus. The predicted host was compared to the actual host at different taxonomic levels. If the predicted host belonged to the same taxonomic unit such as genus with the actual host, the prediction was considered as correct at the level. The accuracy of virus host prediction at a certain taxonomic level was defined as the ratio of correctly predicted host at this taxonomic level.VHM and WIsH were the best alignment-free methods for predicting phage hosts according to previous studies , 19. ForPrevious studies by Edwards et al.  showed tTo predict the virus host based on BLAST, the genome sequence of each virus was queried against the prokaryotic genomes in the test dataset using blastn (version 2.6.0+) . The proTo predict the virus host based on CRISPR spacer sequences, firstly, the CRISPR spacer sequences in all prokaryote genomes of the test dataset were extracted by the CRISPR Recognition Tool (CRT) . Then, tL bp  randomly subsampled from viral genomes were built, and the models were evaluated by the ten-fold cross-validations on the K-means clustering of the VHM dataset.Metagenomic assembly often yields partial genomes, so the prediction of the virus host based on contigs of varying lengths was important. To test the GM in prediction of virus hosts in metagenomics, the GMs based on simulated viral contigs of length k-mer frequencies between viral and host genomic sequences  was developed in this study to predict the hosts based on the differences of ces see “”. To evaces see “. Firstlyk-mers and the number of components  used in the model. The virus host prediction accuracy of the GM increased as the length of k-mers increased from 1 to 5, and then decreased with k-mers of six nucleotides  may result in over-estimate of the performance of the GM in the test dataset. Therefore, when predicting a target virus-host interaction in the test dataset, the GM was re-built based on the training dataset from which the virus-host interactions that shared the same viral and host genus with the target virus-host interactions were removed. This resulted in a compromised performance of the GM on the test dataset  hosts with the highest score. When 30 predicted hosts were considered, the prediction accuracy at the genus level improved significantly using this consensus approach for GM and VHM, achieving an accuracy of 0.45 and 0.39, respectively  to provide a user-friendly interface for the GM algorithm. PHP is freely available either as a standalone version  or in thk-mer frequencies in viral and prokaryotic genomes, and model training, while the process of model building of WIsH took 27 min  and the number of components in the Gaussian mixture model(B). Figure S3. The comparison between GM and other common machine learning algorithms on host prediction accuracy. All models took the k-mer frequency (k = 4) as features, and were trained with the default parameters. Negative samples are needed for building computational models with these machine-learning algorithms, and were obtained as follows: for each virus, a non-host prokaryote was randomly selected, which resulted in the same number of negative samples as the positive samples, i.e., virus-host interactions. The testing strategy mentioned in Fig. n_estimators) and the number of features to consider when looking for the best split (max_features), have a key impact on the performance of the RF algorithm. Besides, the length of k-mers used in the modeling may also have an influence on the performance of the RF algorithm. Therefore, the n_estimators, max_features, and the length of k-mers were further tuned to improve the RF algorithm. The RF algorithm with the “n_estimators” set to be 2000, “max_features” set to be “auto”, and k-mer length set to be 6 was found to perform best (see “Random forest with best parameters” in the figure). The modeling with these machine-learning algorithms was computed with the “scikit-learn” package in python. Figure S4. The distribution of k-mer frequency differences between virus and hosts genomes (blue), and those between virus and non-host prokaryotic genomes (orange). (A-H) represents the randomly selected k-mers of AGTT, AAAA,TTGC, CACG, AATT, TAGA, CGGG, TTCT, respectively. Figure S5. The taxonomic distribution of viruses in the VHM dataset.


Morbidity and mortality due to pregnancy and childbearing are high in developing countries. This study aims to estimate patient and health system costs of managing pregnancy and birth-related complications in sub-Saharan Africa.A systematic review of the literature was conducted to identify costing studies published and unpublished, from January 2000 to May 2019. The search was done in Pubmed, EMBASE, Cinahl, and Web of Science databases and grey literature. The study was registered in PROSPERO with registration No. CRD42019119316. All costs were converted to 2018 US dollars using relevant Consumer Price Indices.Out of 1652 studies identified, 48 fulfilled the inclusion criteria. The included studies were of moderate to high quality. Spontaneous vaginal delivery cost patients and health systems between USD 6–52 and USD 8–73, but cesarean section costs between USD 56–377 and USD 80–562, respectively. Patient and health system costs of abortion range between USD 11–66 and USD 40–298, while post-abortion care costs between USD 21–158 and USD 46–151, respectively. The patient and health system costs for managing a case of eclampsia range between USD 52–231 and USD 123–186, while for maternal hemorrhage they range between USD 65–196 and USD 30–127, respectively. Patient cost for caring low-birth weight babies ranges between USD 38–489 while the health system cost was estimated to be USD 514.This is the first systematic review to compile comprehensive up-to-date patient and health system costs of managing pregnancy and birth-related complications in sub-Saharan Africa. It indicates that these costs are relatively high in this region and that patient costs were largely catastrophic relative to a 10 % of average national per capita income. An estimated 303,000 preventable deaths occurred during pregnancy and childbirth globally in 2015, mostly as a result of pregnancy and birth-related complications. Most of these maternal deaths occurred in low-income countries, particularly in sub-Saharan Africa. About three-quarters of these complications include unsafe abortions, hypertensive disorders in pregnancy i.e. pre-eclampsia and eclampsia, sepsis, severe bleeding, and complications arising at the time of delivery .The United Nations Development Fund reports that the prevalence of adolescent pregnancy has decreased globally, but remained relatively unchanged in sub-Saharan Africa . By 2030This study aims to assess patient and health system costs associated with the management of pregnancy and birth-related complications in sub-Saharan Africa. The results will feed into a cost-benefit analysis study comparing two adolescent pregnancy prevention strategies in Zambia to help policymakers to choose the strategy with the greatest potential for return on investment . The stuWe used the PRISMA checklist that is recommended for reporting a systematic review and meta-analysis of clinical trials , with slThe search of the literature was conducted by ATM in Pubmed, EMBASE, Cinahl, and Web of Science databases using combinations of the following search terms: cost, costs, cost of illness, economic burden, cost analysis, healthcare costs, health care costs, preterm birth, low birth weight, preeclampsia, eclampsia, abortion, post-abortion complication, cesarean section, and individual names of sub-Saharan African countries. An example of a search code used to search in Pubmed is shown in Table We included costing studies that i) were conducted in sub-Saharan Africa ii) published from January 2000 to 13th May 2019 iii) targeted normal delivery as well as pregnancy and birth-related complications including pre-eclampsia, eclampsia, pre-term birth, low birth weight babies, small for gestational age babies, unsafe abortion and post-abortion complications. The search was limited to humans and the English language. Review papers and reports were excluded because we were only interested in primary cost data, but they were instead used to identify other relevant studies. Two reviewers (ATM and PB) independently screened the titles and abstracts of all the articles to assess eligibility and the qualifying ones were subjected to further screening for eligibility by the two reviewers by reading the full text.Quality assessment was conducted independently by ATM and PH. To the best of our knowledge, there is no quality assessment guideline for cost studies: hence, we developed an 8-item checklist from Drummond et al. , Liers eWe extracted information about the name of the primary author, year of publication, year in which the data was collected, study design, the country in which data was collected, costing perspective used, the currency used, cost information, disease condition, target population from which data was collected and the level of the healthcare facility.Costs were categorized as health system costs if they were borne by the healthcare facility and patient costs if they were borne by the patient or caregiver. Health system costs could further be categorized as recurrent if spent on items that are used up in the course of the year such as salaries, supplies, and utilities or capital costs if spent on items that last more than a year such as buildings, furniture, and equipment. Patient costs included both direct costs and indirect costs. Direct costs were those paid in the process of seeking/accessing care and included out-of-pocket payment for treatment , transport to and from the healthcare facility, food, and other related expenses. Indirect costs were those that resulted from the loss of income as a result of not being able to engage in economically productive activities due to illness. When costs were reported separately for public, private, or non-governmental organizations, etc., we computed a simple average.Base year costs in local currencies were first converted to US dollars (USD) using the existing exchange rate for the base years of the individual studies, before adjustment to 2018 USD using relevant US Consumer Price Indices (CPI) . Annual In total 1652 studies were identified from the systematic literature search, of which 373 studies were duplicates. The remaining 1279 unique studies were subjected to first stage screening for eligibility by reading the titles and abstracts, and as a result, 1201 studies were excluded because they were not relevant, and 6 articles were not available as full texts. The full-text screening was done for the remaining 72 articles, of which 48 were included  for normal delivery range from USD 5.6–52.4 and the health system cost (n = 6) range from USD 8.4–72.8. However, only five of the thirteen studies reported both direct and indirect patient costs and four of the six studies reported both recurrent and capital health system costs. The patient cost (n = 11) for C-section ranges from USD 55.8–377.3 but only three of the eleven studies reported both direct and indirect patient costs. The health system cost (n = 9) for C-section ranges from USD 79.7–561.8 but only seven of the nine studies reported both recurrent and capital health system costs.Table n = 8) and health system costs for abortion care services (n = 4) range from USD 11.2–65.7 and USD 40.3–298.3, respectively. Only two of the eight studies reported direct and indirect patient costs while three of the four studies reported both recurrent and capital health system costs. For PAC services the reported patient cost (n = 6) ranges from USD 20.8–158.4 and all studies reported direct costs only. The health system costs for PAC (n = 8) were in the range between USD 46.1–151.1, and three of the eight studies reported both recurrent and capital costs.Table n = 5) range between USD 51.6–230.5, and two of the five studies reported both direct and indirect costs. The health system costs for eclampsia (n = 2) range from USD 122.7–186.4 and no capital cost was measured. For care of low-birth weight babies, the patient cost (n = 3) ranged between USD 38.2–486.7, and two studies contained both direct and indirect costs, while only one study by Sicuri et al. (2011) from Mozambique reported an average health system cost of about USD 514 for caring such babies. For the management of maternal hemorrhage, patient cost (n = 4) ranges between USD 65.1–196.2, and half of the studies reported both direct and indirect costs. The health system cost for maternal hemorrhage range between USD 30.3–127.4 and all the studies reported recurrent health system cost only.Table Figures This review shows that pregnancy and childbearing expose women and their families to a lot of out-of-pocket (OOP) payments, particularly in the presence of complications. For normal spontaneous vaginal deliveries, women pay between USD 5.6–52.4 and for C-section they pay between USD 55.8–377.3, meaning on average it costs seven times more to deliver by C-section. The OOP payments usually constitute costs of drugs and medical supplies like cotton wools, syringes, transportation to and from the health facilities, food, drinks and unofficial payments to health workers. Mean OOP payments were either very close to or exceeded 10 % of an average national per capita income for some countries, thus most likely exposing patients and their families to substantial financial burden.Results from the included studies show that catastrophic health expenditures were common among the study participants , 31, 59.Our study indicates that pregnancy and childbearing complications are also relatively expensive to the healthcare systems in sub-Saharan Africa. Health systems use between USD 8–73 per patient for normal deliveries, but a staggering USD 80–562 for C-section, USD 40–300 for medical abortion, USD 40–150 for post-abortion care, USD 120–190 to care for eclampsia, USD 30–130 to treat hemorrhage and about USD 500 to care for low-birth weight babies. In 2009 it was estimated that the annual cost to treat unsafe abortion complications in sub-Saharan Africa ranged from USD 68–76 million  and in 2This study has several limitations, which requires care in its interpretation. Firstly, the included studies were methodologically very heterogeneous in terms of range patient and health system costs included making it hard to fully disaggregate the costs. Secondly, costs are very context-specific especially for non-traded goods and services such as wages and salaries, which are usually one of the main cost drivers. Thus, in countries where salaries and prices of commodities are high always tend to skew the average costs. Also, there could be a lot of variations in the structure and complexity of the healthcare system and services available for managing pregnancy and birth-related complications between countries, hence resource requirements and costs could infinitely vary from one place to another. For this reason, we could not aggregate the costs into meaningful means or medians.Our findings regarding the costs of maternal health care have several policy implications despite the limitations. First, it is well documented that adolescent pregnancy and childbearing are associated with elevated risks of complications , 69, whiThis is the first systematic literature review to compile comprehensive up-to-date patient and health system costs of managing pregnancy and birth-related complications in sub-Saharan Africa. It indicates that these costs are relatively high. It further shows that patient costs were largely catastrophic relative to a 10 % of average national per capita income, thus exposing families to immense financial burden and impoverishment, in particularly poor families that live under one USD per day. Hence health policies that advocate for free maternal health services and universal health coverage on maternal and newborn care should be encouraged and prioritized on both national, regional, and international agenda. Otherwise, the high costs will continue to hinder access to maternal health services in sub-Saharan Africa, thus negating the efforts to reduce infant and maternal mortality rates which are relatively high in this region. Although the study found a relatively large number of studies, the evidence base on the costs of maternal care is nevertheless still scarce; hence, more studies are needed to fill the gaps.