Unveiling the unknown viral world in groundwater.

Viruses as the prevailing biological entities are poorly understood in underground realms. Here, we establish the first metagenomic Groundwater Virome Catalogue (GWVC) comprising 280,420 viral species ( ≥ 5 kb) detected from 607 monitored wells in seven geo-environmental zones throughout China. In expanding ~10-fold the global portfolio of known groundwater viruses, we uncover over 99% novel viruses and about 95% novel viral clusters. By linking viruses to hosts from 119 prokaryotic phyla, we double the number of microbial phyla known to be virus-infected in groundwater. As keystone ultrasmall symbionts in aquifers, CPR bacteria and DPANN archaea are susceptible to virulent viruses. Certain complete CPR viruses even likely infect non-CPR bacteria, while partial CPR/DPANN viruses harbor cell-surface modification genes that assist symbiont cell adhesion to free-living microbes. This study reveals the unknown viral world and auxiliary metabolism associated with methane, nitrogen, sulfur, and phosphorus cycling in groundwater, and highlights the importance of subsurface virosphere in viral ecology.

Global diversity and ecological functions of viruses inhabiting oil reservoirs.

Oil reservoirs, being one of the significant subsurface repositories of energy and carbon, host diverse microbial communities affecting energy production and carbon emissions. Viruses play crucial roles in the ecology of microbiomes, however, their distribution and ecological significance in oil reservoirs remain undetermined. Here, we assemble a catalogue encompassing viral and prokaryotic genomes sourced from oil reservoirs. The catalogue comprises 7229 prokaryotic genomes and 3,886 viral Operational Taxonomic Units (vOTUs) from 182 oil reservoir metagenomes. The results show that viruses are widely distributed in oil reservoirs, and 85% vOTUs in oil reservoir are detected in less than 10% of the samples, highlighting the heterogeneous nature of viral communities within oil reservoirs. Through combined microcosm enrichment experiments and bioinformatics analysis, we validate the ecological roles of viruses in regulating the community structure of sulfate reducing microorganisms, primarily through a virulent lifestyle. Taken together, this study uncovers a rich diversity of viruses and their ecological functions within oil reservoirs, offering a comprehensive understanding of the role of viral communities in the biogeochemical cycles of the deep biosphere.

Use of strips of rapid diagnostic tests as a source of ribonucleic acid for genomic surveillance of viruses: an example of SARS-CoV-2.

BACKGROUND: This study aimed to demonstrate that the genomic material of SARS-CoV-2 can be isolated from strips of COVID-19 rapid diagnostic test cassettes. METHOD: It was a prospective cross-sectional study involving patients admitted to treatment centers and sampling sites in the city of Conakry, Guinea. A total of 121 patients were double sampled, and 9 more patients were tested only for RDT. PCR was conducted according to the protocol of the RunMei kit. Sequencing was performed by using the illumina COVIDSeq protocol. Nine COVID-19 RDTs without nasopharyngeal swabs were in addition tested. RESULT: Among the 130 COVID-19 RDTs, forty-seven were macroscopically positive, whereas seventy-two were positive according to PCR using RDT strip, while among the 121 VTM swabs, sixty-four were positive. Among eighty-three negative COVID-19 RDTs, twenty-seven were positive by PCR using RDT strip with a geometric mean Ct value of 32.49 cycles. Compared to those of PCR using VTM, the sensitivity and specificity of PCR using RDT strip were estimated to be 100% and 85.96%, respectively, with 93.39% test accuracy. Among the fifteen COVID-19 RDT extracts eligible for sequencing, eleven had sequences identical to those obtained via the standard method, with coverage between 75 and 99.6%. CONCLUSION: These results show that COVID-19 RDTs can be used as biological material for the genomic surveillance of SARS-CoV-2.

Genome composition-based deep learning predicts oncogenic potential of HPVs.

Human papillomaviruses (HPVs) account for more than 30% of cancer cases, with definite identification of the oncogenic role of viral E6 and E7 genes. However, the identification of high-risk HPV genotypes has largely relied on lagged biological exploration and clinical observation, with types unclassified and oncogenicity unknown for many HPVs. In the present study, we retrieved and cleaned HPV sequence records with high quality and analyzed their genomic compositional traits of dinucleotide (DNT) and DNT representation (DCR) to overview the distribution difference among various types of HPVs. Then, a deep learning model was built to predict the oncogenic potential of all HPVs based on E6 and E7 genes. Our results showed that the main three groups of Alpha, Beta, and Gamma HPVs were clearly separated between/among types in the DCR trait for either E6 or E7 coding sequence (CDS) and were clustered within the same group. Moreover, the DCR data of either E6 or E7 were learnable with a convolutional neural network (CNN) model. Either CNN classifier predicted accurately the oncogenicity label of high and low oncogenic HPVs. In summary, the compositional traits of HPV oncogenicity-related genes E6 and E7 were much different between the high and low oncogenic HPVs, and the compositional trait of the DCR-based deep learning classifier predicted the oncogenic phenotype accurately of HPVs. The trained predictor in this study will facilitate the identification of HPV oncogenicity, particularly for those HPVs without clear genotype or phenotype.

Detection of lumpy skin disease virus reads in the human upper respiratory tract microbiome requires further investigation.

Lumpy skin disease virus (LSDV), a double-stranded DNA virus from the Capripoxvirus genus, primarily affects Bos indicus, Bos taurus breeds, and water buffalo. Arthropod vectors, including mosquitoes and biting flies, are the main LSDV transmitters. Although LSDV is not zoonotic, this study unexpectedly detected LSDV reads in the upper respiratory tract microbiome of humans from rural and urban areas in Maharashtra, India. Nasopharyngeal and oropharyngeal swab samples collected for SARS-CoV-2 surveillance underwent whole-genome metagenomics sequencing, revealing LSDV reads in 25% of samples. Split kmer analysis provided insights into sample relatedness despite the low coverage of LSDV reads with the reference genome. Our findings, which include the detection of LSDV contigs aligning to specific locations on the reference genome, suggest a common source for LSDV reads, potentially shared water sources, or milk/milk products. Further investigation is needed to ascertain the mode of transmission and reason for the detection of LSDV reads in human upper respiratory tract.

Recombination and selection trajectory of the monkeypox virus during its adaptation in the human population.

Monkeypox, caused by the monkeypox virus (MPXV), was historically confined to West and Central Africa but has now spread globally. Recombination and selection play crucial roles in the evolutionary adaptation of MPXV; however, the evolution of MPXV and its relationship with the recent, ground-breaking monkeypox epidemic remains poorly understood. To gain insights into the evolutionary dynamics of MPXV, comprehensive in silico recombination and selection analyses were conducted based on MPXV whole genome sequence data. Three types of recombination were identified: five ancestor-sharing interspecies recombination events, six specific interspecies recombination events and four intraspecies recombination events. The results highlight the prevalent occurrence of recombination in MPXV, with 73.3% occurring in variable regions of the genome. Selection analysis was performed from three dimensions: proteins around recombination regions, proteins from recombinant ancestors and MPXV branches, and whole-genome gene analysis. Results revealed 2 and 7 proteins under positive selection in the first two dimensions, respectively. These proteins are mainly involved in infection immunity, apoptosis regulation and viral virulence. Whole-genome analysis detected 25 genes under positive selection, mainly associated with immune response and viral regulation. Understanding their evolutionary patterns will help predict and prevent cross-species transmission, zoonotic outbreaks and potential human epidemics.

Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens.

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer mismatches overlapping with primers and predicted PCR byproducts. We also compare Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluate Olivar on real wastewater samples and found that Olivar has up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available online as a web application at https://olivar.rice.edu  and can be installed locally as a command line tool with Bioconda. Source code, installation guide, and usage are available at https://github.com/treangenlab/Olivar .

Phylogeny and disease associations of a widespread and ancient intestinal bacteriophage lineage.

Viruses are core components of the human microbiome, impacting health through interactions with gut bacteria and the immune system. Most human microbiome viruses are bacteriophages, which exclusively infect bacteria. Until recently, most gut virome studies focused on low taxonomic resolution (e.g., viral operational taxonomic units), hampering population-level analyses. We previously identified an expansive and widespread bacteriophage lineage in inhabitants of Amsterdam, the Netherlands. Here, we study their biodiversity and evolution in various human populations. Based on a phylogeny using sequences from six viral genome databases, we propose the Candidatus order Heliusvirales. We identify heliusviruses in 82% of 5441 individuals across 39 studies, and in nine metagenomes from humans that lived in Europe and North America between 1000 and 5000 years ago. We show that a large lineage started to diversify when Homo sapiens first appeared some 300,000 years ago. Ancient peoples and modern hunter-gatherers have distinct Ca. Heliusvirales populations with lower richness than modern urbanized people. Urbanized people suffering from type 1 and type 2 diabetes, as well as inflammatory bowel disease, have higher Ca. Heliusvirales richness than healthy controls. We thus conclude that these ancient core members of the human gut virome have thrived with increasingly westernized lifestyles.

Unraveling the habitat preferences, ecological drivers, potential hosts, and auxiliary metabolism of soil giant viruses across China.

BACKGROUND: Soil giant viruses are increasingly believed to have profound effects on ecological functioning by infecting diverse eukaryotes. However, their biogeography and ecology remain poorly understood. RESULTS: In this study, we analyzed 333 soil metagenomes from 5 habitat types (farmland, forest, grassland, Gobi desert, and mine wasteland) across China and identified 533 distinct giant virus phylotypes affiliated with nine families, thereby greatly expanding the diversity of soil giant viruses. Among the nine families, Pithoviridae were the most diverse. The majority of phylotypes exhibited a heterogeneous distribution among habitat types, with a remarkably high proportion of unique phylotypes in mine wasteland. The abundances of phylotypes were negatively correlated with their environmental ranges. A total of 76 phylotypes recovered in this study were detectable in a published global topsoil metagenome dataset. Among climatic, geographical, edaphic, and biotic characteristics, soil eukaryotes were identified as the most important driver of beta-diversity of giant viral communities across habitat types. Moreover, co-occurrence network analysis revealed some pairings between giant viral phylotypes and eukaryotes (protozoa, fungi, and algae). Analysis of 44 medium- to high-quality giant virus genomes recovered from our metagenomes uncovered not only their highly shared functions but also their novel auxiliary metabolic genes related to carbon, sulfur, and phosphorus cycling. CONCLUSIONS: These findings extend our knowledge of diversity, habitat preferences, ecological drivers, potential hosts, and auxiliary metabolism of soil giant viruses. Video Abstract.

In field use of water samples for genomic surveillance of infectious spleen and kidney necrosis virus (ISKNV) infecting tilapia fish in Lake Volta, Ghana.

Viral outbreaks are a constant threat to aquaculture, limiting production for better global food security. A lack of diagnostic testing and monitoring in resource-limited areas hinders the capacity to respond rapidly to disease outbreaks and to prevent viral pathogens becoming endemic in fisheries productive waters. Recent developments in diagnostic testing for emerging viruses, however, offers a solution for rapid in situ monitoring of viral outbreaks. Genomic epidemiology has furthermore proven highly effective in detecting viral mutations involved in pathogenesis and assisting in resolving chains of transmission. Here, we demonstrate the application of an in-field epidemiological tool kit to track viral outbreaks in aquaculture on farms with reduced access to diagnostic labs, and with non-destructive sampling. Inspired by the "lab in a suitcase" approach used for genomic surveillance of human viral pathogens and wastewater monitoring of COVID19, we evaluated the feasibility of real-time genome sequencing surveillance of the fish pathogen, Infectious spleen and kidney necrosis virus (ISKNV) in Lake Volta. Viral fractions from water samples collected from cages holding Nile tilapia (Oreochromis niloticus) with suspected ongoing ISKNV infections were concentrated and used as a template for whole genome sequencing, using a previously developed tiled PCR method for ISKNV. Mutations in ISKNV in samples collected from the water surrounding the cages matched those collected from infected caged fish, illustrating that water samples can be used for detecting predominant ISKNV variants in an ongoing outbreak. This approach allows for the detection of ISKNV and tracking of the dynamics of variant frequencies, and may thus assist in guiding control measures for the rapid isolation and quarantine of infected farms and facilities.

Complete genome sequence of a novel amalgavirus in sponge gourd, Luffa cylindrica.

A novel monopartite dsRNA virus, tentatively named "sponge gourd amalgavirus 1" (SGAV1), was discovered by high-throughput sequencing in sponge gourd (Luffa cylindrica) displaying mosaic symptoms in Jiashan County, Zhejiang Province, China. The genome of SGAV1 is 3,447 nucleotides in length and contains partially overlapping open reading frames (ORFs) encoding a putative replication factory matrix-like protein and a fusion protein, respectively. The fusion protein of SGAV1 shares 57.07% identity with the homologous protein of salvia miltiorrhiza amalgavirus 1 (accession no. DAZ91057.1). Phylogenetic analysis based on the RNA-dependent RNA polymerase (RdRp) protein suggests that SGAV1 belongs to the genus Amalgavirus of the family Amalgaviridae. Moreover, analysis of SGAV1-derived small interfering RNAs indicated that SGAV1 was actively replicating in the host plant. Semi-quantitative RT-PCR showed higher levels of SGAV1 expression in leaves than in flowers and fruits. This is the first report of a novel amalgavirus found in sponge gourd in China.

Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family.

PURPOSE: In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is achieved through a deep neural network model that relies on convolutional neural networks (CNNs). Since viruses within the same family share similar genetic and structural characteristics, the classification process becomes more challenging, necessitating more robust models. With the rapid evolution of viral genomes and the increasing need for timely classification, we aimed to provide a robust and efficient tool that could increase the accuracy of viral identification and classification processes. Contribute to advancing research in viral genomics and assist in surveilling emerging viral strains. METHODS: Based on a one-dimensional deep CNN, the proposed tool is capable of training and testing on the Coronaviridae family, including SARS-CoV-2. Our model's performance was assessed using various metrics, including F1-score and AUROC. Additionally, artificial mutation tests were conducted to evaluate the model's generalization ability across sequence variations. We also used the BLAST algorithm and conducted comprehensive processing time analyses for comparison. RESULTS: DeepVirusClassifier demonstrated exceptional performance across several evaluation metrics in the training and testing phases. Indicating its robust learning capacity. Notably, during testing on more than 10,000 viral sequences, the model exhibited a more than 99% sensitivity for sequences with fewer than 2000 mutations. The tool achieves superior accuracy and significantly reduced processing times compared to the Basic Local Alignment Search Tool algorithm. Furthermore, the results appear more reliable than the work discussed in the text, indicating that the tool has great potential to revolutionize viral genomic research. CONCLUSION: DeepVirusClassifier is a powerful tool for accurately classifying viral sequences, specifically focusing on SARS-CoV-2 and other subtypes within the Coronaviridae family. The superiority of our model becomes evident through rigorous evaluation and comparison with existing methods. Introducing artificial mutations into the sequences demonstrates the tool's ability to identify variations and significantly contributes to viral classification and genomic research. As viral surveillance becomes increasingly critical, our model holds promise in aiding rapid and accurate identification of emerging viral strains.

A novel betapartitivirus isolated from Cordyceps militaris, an edible-medicinal mushroom.

In this study, we identified a novel partitivirus, named "Cordyceps militaris partitivirus 1" (CmPV1), in Cordyceps militaris strain RCEF7506. The complete genome of CmPV1 comprises two segments, dsRNA1 and dsRNA2, each encoding a single protein. dsRNA1 (2,206 bp) encodes an RNA-dependent RNA polymerase (RdRp), and dsRNA2 (2,256 bp) encodes a coat protein (CP). Sequence analysis revealed that dsRNA1 has the highest similarity to that of Bipolaris maydis partitivirus 2 (BmPV2), whereas dsRNA2 shows the highest similarity to human blood-associated partitivirus (HuBPV). Phylogenetic analysis based on RdRp sequences suggests that CmPV1 is a new member of the genus Betapartitivirus of the family Partitiviridae. This is the first documentation of a betapartitivirus infecting the entomopathogenic fungus C. militaris.

A new geminialphasatellite associated with wheat dwarf virus identified in winter barley in France.

Using a high-throughput sequencing (HTS) approach, we report the discovery of a new alphasatellite identified in a winter barley plant collected in France in 2022 that was also infected by wheat dwarf virus (WDV). The presence of the satellite and of WDV was confirmed by several independent PCR assays, and the complete genome sequence was determined. The circular satellite genome is 1424 nt long and shows typical hallmarks of members of the subfamily Geminialphasatellitinae, including a replication-associated hairpin with a CAGTATTAC sequence and a Rep-encoding open reading frame (ORF). It also possesses a second ORF, embedded in a different frame within the Rep ORF, which is also observed in clecrusatellites and a few other members of the family Alphasatellitidae. Pairwise sequence comparisons and phylogenetic analysis showed that this satellite represents a novel species. Its closest relatives are in the genus Colecusatellite, but it likely represents a new genus given its divergence from other genera of the subfamily Geminialphasatellitinae. Given that WDV was the only virus observed in coinfection with the satellite, the name "wheat dwarf virus-associated alphasatellite" is proposed for this novel agent.

Genotypic characterization of novel S-DEL variants of porcine epidemic diarrhea virus identified in South Korea.

The highly pathogenic genotype 2b (HP-G2b) of porcine epidemic diarrhea virus (PEDV), which caused a pandemic in 2013-2014, evolved in South Korea and became endemic, affecting the domestic pig industry. This study describes the genotypic traits of novel HP-G2b PEDV strains identified on affected farms experiencing low disease severity with < 10% neonatal mortality. Nucleotide sequencing revealed common deletion patterns, termed S-DEL2, resulting in a two-amino-acid deletion at positions 60 and 61, 61 and 62, or 63 and 64 in the N-terminal domain of the spike (S) protein of all isolates. The S barcode profiles of S-DEL2 variants differed from each other and shared 96.0-99.4% and 98.5-99.6% nt sequence identity with other South Korean HP-G2b PEDV strains in the S gene and in the complete genome sequence, respectively. Genetic and phylogenetic analysis showed that the S-DEL2 strains belonged to diverse domestic clades: CK, CK.1, CK.2, or NC. The emergence of novel S-DEL2 strains suggests that continuous evolution of PEDV occurs under endemic circumstances, resulting in genetic diversity and distinct clinical presentations. This study advances our knowledge regarding the genetic and pathogenic heterogeneity of PEDV and emphasizes the importance of active monitoring and surveillance to identify novel variants and determine their genotypic and phenotypic characteristics.

A safe, effective and adaptable live-attenuated SARS-CoV-2 vaccine to reduce disease and transmission using one-to-stop genome modifications.

Approved vaccines are effective against severe COVID-19, but broader immunity is needed against new variants and transmission. Therefore, we developed genome-modified live-attenuated vaccines (LAV) by recoding the SARS-CoV-2 genome, including 'one-to-stop' (OTS) codons, disabling Nsp1 translational repression and removing ORF6, 7ab and 8 to boost host immune responses, as well as the spike polybasic cleavage site to optimize the safety profile. The resulting OTS-modified SARS-CoV-2 LAVs, designated as OTS-206 and OTS-228, are genetically stable and can be intranasally administered, while being adjustable and sustainable regarding the level of attenuation. OTS-228 exhibits an optimal safety profile in preclinical animal models, with no side effects or detectable transmission. A single-dose vaccination induces a sterilizing immunity in vivo against homologous WT SARS-CoV-2 challenge infection and a broad protection against Omicron BA.2, BA.5 and XBB.1.5, with reduced transmission. Finally, this promising LAV approach could be applicable to other emerging viruses.

Exploring Barmah Forest virus pathogenesis: molecular tools to investigate non-structural protein 3 nuclear localization and viral genomic determinants of replication.

Barmah Forest virus (BFV) is a mosquito-borne virus that causes arthralgia with accompanying rash, fever, and myalgia in humans. The virus is mainly found in Australia and has caused outbreaks associated with significant health concerns. As the sole representative of the Barmah Forest complex within the genus Alphavirus, BFV is not closely related genetically to other alphaviruses. Notably, basic knowledge of BFV molecular virology has not been well studied due to a lack of critical investigative tools such as an infectious clone. Here we describe the construction of an infectious BFV cDNA clone based on Genbank sequence and demonstrate that the clone-derived virus has in vitro and in vivo properties similar to naturally occurring virus, BFV field isolate 2193 (BFV2193-FI). A substitution in nsP4, V1911D, which was identified in the Genbank reference sequence, was found to inhibit virus rescue and replication. T1325P substitution in nsP2 selected during virus passaging was shown to be an adaptive mutation, compensating for the inhibitory effect of nsP4-V1911D. The two mutations were associated with changes in viral non-structural polyprotein processing and type I interferon (IFN) induction. Interestingly, a nuclear localization signal, active in mammalian but not mosquito cells, was identified in nsP3. A point mutation abolishing nsP3 nuclear localization attenuated BFV replication. This effect was more prominent in the presence of type I interferon signaling, suggesting nsP3 nuclear localization might be associated with IFN antagonism. Furthermore, abolishing nsP3 nuclear localization reduced virus replication in mice but did not significantly affect disease.IMPORTANCEBarmah Forest virus (BFV) is Australia's second most prevalent arbovirus, with approximately 1,000 cases reported annually. The clinical symptoms of BFV infection include rash, polyarthritis, arthralgia, and myalgia. As BFV is not closely related to other pathogenic alphaviruses or well-studied model viruses, our understanding of its molecular virology and mechanisms of pathogenesis is limited. There is also a lack of molecular tools essential for corresponding studies. Here we describe the construction of an infectious clone of BFV, variants harboring point mutations, and sequences encoding marker protein. In infected mammalian cells, nsP3 of BFV was located in the nuclei. This finding extends our understanding of the diverse mechanisms used by alphavirus replicase proteins to interact with host cells. Our novel observations highlight the complex synergy through which the viral replication machinery evolves to correct mutation errors within the viral genome.

Targeted whole-genome recovery of single viral species in a complex environmental sample.

Characterizing unknown viruses is essential for understanding viral ecology and preparing against viral outbreaks. Recovering complete genome sequences from environmental samples remains computationally challenging using metagenomics, especially for low-abundance species with uneven coverage. We present an experimental method for reliably recovering complete viral genomes from complex environmental samples. Individual genomes are encapsulated into droplets and amplified using multiple displacement amplification. A unique gene detection assay, which employs an RNA-based probe and an exonuclease, selectively identifies droplets containing the target viral genome. Labeled droplets are sorted using a microfluidic sorter, and genomes are extracted for sequencing. We demonstrate this method's efficacy by spiking two known viral genomes, Simian virus 40 (SV40, 5,243 bp) and Human Adenovirus 5 (HAd5, 35,938 bp), into a sewage sample with a final abundance in the droplets of around 0.1% and 0.015%, respectively. We achieve 100% recovery of the complete sequence of the spiked-in SV40 genome with uniform coverage distribution. For the larger HAd5 genome, we cover approximately 99.4% of its sequence. Notably, genome recovery is achieved with as few as one sorted droplet, which enables the recovery of any desired genomes in complex environmental samples, regardless of their abundance. This method enables single-genome whole-genome amplification and targeting characterizations of rare viral species and will facilitate our ability to access the mutational profile in single-virus genomes and contribute to an improved understanding of viral ecology.

Predicting symptom severity in PSTVd-infected tomato plants using the PSTVd genome sequence.

Viroids, one of the smallest known infectious agents, induce symptoms of varying severity, ranging from latent to severe, based on the combination of viroid isolates and host plant species. Because viroids are transmissible between plant species, asymptomatic viroid-infected plants may serve as latent sources of infection for other species that could exhibit severe symptoms, occasionally leading to agricultural and economic losses. Therefore, predicting the symptoms induced by viroids in host plants without biological experiments could remarkably enhance control measures against viroid damage. Here, we developed an algorithm using unsupervised machine learning to predict the severity of disease symptoms caused by viroids (e.g., potato spindle tuber viroid; PSTVd) in host plants (e.g., tomato). This algorithm, mimicking the RNA silencing mechanism thought to be linked to viroid pathogenicity, requires only the genome sequences of the viroids and host plants. It involves three steps: alignment of synthetic short sequences of the viroids to the host plant genome, calculation of the alignment coverage, and clustering of the viroids based on coverage using UMAP and DBSCAN. Validation through inoculation experiments confirmed the effectiveness of the algorithm in predicting the severity of disease symptoms induced by viroids. As the algorithm only requires the genome sequence data, it may be applied to any viroid and plant combination. These findings underscore a correlation between viroid pathogenicity and the genome sequences of viroid isolates and host plants, potentially aiding in the prevention of viroid outbreaks and the breeding of viroid-resistant crops.

HIV-1 subtype A1, D, and recombinant proviral genome landscapes during long-term suppressive therapy.

The primary obstacle to curing HIV-1 is a reservoir of CD4+ cells that contain stably integrated provirus. Previous studies characterizing the proviral landscape, which have been predominantly conducted in males in the United States and Europe living with HIV-1 subtype B, have revealed that most proviruses that persist during antiretroviral therapy (ART) are defective. In contrast, less is known about proviral landscapes in females with non-B subtypes, which represents the largest group of individuals living with HIV-1. Here, we analyze genomic DNA from resting CD4+ T-cells from 16 female and seven male Ugandans with HIV-1 receiving suppressive ART (n = 23). We perform near-full-length proviral sequencing at limiting dilution to examine the proviral genetic landscape, yielding 607 HIV-1 subtype A1, D, and recombinant proviral sequences (mean 26/person). We observe that intact genomes are relatively rare and clonal expansion occurs in both intact and defective genomes. Our modification of the primers and probes of the Intact Proviral DNA Assay (IPDA), developed for subtype B, rescues intact provirus detection in Ugandan samples for which the original IPDA fails. This work will facilitate research on HIV-1 persistence and cure strategies in Africa, where the burden of HIV-1 is heaviest.