viruSITE-integrated database for viral genomics

The Discovery of Phages in the Substantia Nigra and Its Implication for Parkinson's Disease

Background: A century ago, a mystery between a virus and Parkinson's disease (PD) was described. Owing to the limitation of human brain biopsy and the challenge of electron microscopy in observing virions in human brain tissue, it has been difficult to study the viral etiology of PD. Recent discovery of virobiota reveals that viruses coexist with humans as symbionts. Newly developed transcriptomic sequencing and novel bioinformatic approaches for mining the encrypted virome in human transcriptome make it possible to study the relationship between symbiotic viruses and PD. Nevertheless, whether viruses exist in the human substantia nigra (SN) and whether symbiotic viruses underlie PD pathogenesis remain unknown. Methods: We collected current worldwide human SN transcriptomic datasets from the United States, the United Kingdom, the Netherlands, and Switzerland. We used bioinformatic approaches including viruSITE and the Viral-Track to identify the existence of viruses in the SN of patients. The comprehensive RNA sequencing-based virome analysis pipeline was used to characterize the virobiota in the SN. The Pearson's correlation analysis was used to examine the association between the viral RNA fragment counts (VRFCs) and PD-related human gene sequencing reads in the SN. The differentially expressed genes (DEGs) in the SN between PD patients and non-PD individuals were used to examine the molecular signatures of PD and also evaluate the impact of symbiotic viruses on the SN. Findings: We observed the existence of viruses in the human SN. A dysbiosis of virobiota was found in the SN of PD patients. A marked correlation between VRFC and PD-related human gene expression was detected in the SN of PD patients. These PD-related human genes correlated to VRFC were named as the virus-correlated PD-related genes (VPGs). We identified 3 bacteriophages (phages), including the Proteus phage VB_PmiS-Isfahan, the Escherichia phage phiX174, and the Lactobacillus phage Sha1, that might impair the gene expression of neural cells in the SN of PD patients. The Proteus phage VB_PmiS-Isfahan was a common virus in the SN of patients from the United Kingdom, the Netherlands, and Switzerland. VPGs and DEGs together highlighted that the phages might dampen dopamine biosynthesis and weaken the cGAS-STING function. Interpretation: This is the first study to discover the involvement of phages in PD pathogenesis. A lifelong low symbiotic viral load in the SN may be a contributor to PD pathogenesis. Our findings unlocked the black box between brain virobiota and PD, providing a novel insight into PD etiology from the perspective of phage-human symbiosis.

Altered immune landscape of cervical lymph nodes reveals Epstein-Barr virus signature in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system, and Epstein-Barr virus (EBV) infection is a prerequisite for developing the disease. However, the pathogenic mechanisms that lead to MS remain to be determined. Here, we characterized the immune landscape of deep cervical lymph nodes (dcLNs) in newly diagnosed untreated patients with MS (pwMS) using fine-needle aspirations. By combining single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing, we observed increased memory B cells and reduced germinal center B cells with decreased clonality in pwMS. Double-negative memory B cells were increased in pwMS that transcriptionally resembled B cells with a lytic EBV infection. Moreover, EBV-targeting memory CD8 T cells were detected in a subset of pwMS. We also detected increased EBV DNA in dcLNs and elevated viral loads in patient saliva. These findings suggest that EBV-driven B cell dysregulation is a critical mechanism in MS pathogenesis.

Gene expression and chromatin conformation of microglia in virally suppressed people with HIV

The presence of HIV in sequestered reservoirs is a central impediment to a functional cure, allowing HIV to persist despite life-long antiretroviral therapy (ART), and driving a variety of comorbid conditions. Our understanding of the latent HIV reservoir in the central nervous system is incomplete, because of difficulties in accessing human central nervous system tissues. Microglia contribute to HIV reservoirs, but the molecular phenotype of HIV-infected microglia is poorly understood. We leveraged the unique "Last Gift" rapid autopsy program, in which people with HIV are closely followed until days or even hours before death. Microglial populations were heterogeneous regarding their gene expression profiles but showed similar chromatin accessibility landscapes. Despite ART, we detected occasional microglia containing cell-associated HIV RNA and HIV DNA integrated into open regions of the host's genome (∼0.005%). Microglia with detectable HIV RNA showed an inflammatory phenotype. These results demonstrate a distinct myeloid cell reservoir in the brains of people with HIV despite suppressive ART. Strategies for curing HIV and neurocognitive impairment will need to consider the myeloid compartment to be successful.

Hot Spots of Site-Specific Integration into the Sinorhizobium meliloti Chromosome

The diversity of phage-related sequences (PRSs) and their site-specific integration into the genomes of nonpathogenic, agriculturally valuable, nitrogen-fixing root nodule bacteria, such as Sinorhizobium meliloti, were evaluated in this study. A total of 314 PRSs, ranging in size from 3.24 kb to 88.98 kb, were identified in the genomes of 27 S. meliloti strains. The amount of genetic information foreign to S. meliloti accumulated in all identified PRSs was 6.30 Mb. However, more than 53% of this information was contained in prophages (Phs) and genomic islands (GIs) integrated into genes encoding tRNAs (tRNA genes) located on the chromosomes of the rhizobial strains studied. It was found that phiLM21-like Phs were predominantly abundant in the genomes of S. meliloti strains of distant geographical origin, whereas RR1-A- and 16-3-like Phs were much less common. In addition, GIs predominantly contained fragments of phages infecting bacteria of distant taxa, while rhizobiophage-like sequences were unique. A site-specific integration analysis revealed that not all tRNA genes in S. meliloti are integration sites, but among those in which integration occurred, there were "hot spots" of integration into which either Phs or GIs were predominantly inserted. For the first time, it is shown that at these integration "hot spots", not only is the homology of attP and attB strictly preserved, but integrases in PRSs similar to those of phages infecting the Proteobacteria genera Azospirillum or Pseudomonas are also present. The data presented greatly expand the understanding of the fate of phage-related sequences in host bacterial genomes and also raise new questions about the role of phages in bacterial-phage coevolution.

Unraveling the intricacies of host-pathogen interaction through single-cell genomics

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions.

Comparative genomics of the carmine cochineal symbiont Candidatus Dactylopiibacterium carminicum reveals possible protection to the host against viruses via CRISPR/Cas

We present new genomes from the bacterial symbiont Candidatus Dactylopiibacterium carminicum obtained from non-domesticated carmine cochineals belonging to the scale insect Dactylopius (Hemiptera: Coccoidea: Dactylopiidae). As Dactylopiibacterium has not yet been cultured in the laboratory, metagenomes and metatranscriptomics have been key in revealing putative symbiont functions. Dactylopiibacterium is a nitrogen-fixing beta-proteobacterium that may be vertically transmitted and shows differential gene expression inside the cochineal depending on the tissue colonized. Here we found that all cochineal species tested had Dactylopiibacterium carminicum which has a highly conserved genome. All Dactylopiibacterium genomes analyzed had genes involved in nitrogen fixation and plant polymer degradation. Dactylopiibacterium genomes resemble those from free-living plant bacteria, some found as endophytes. Notably, we found here a new putative novel function where the bacteria may protect the insect from viruses, since all Dactylopiibacterium genomes contain CRISPRs with a spacer matching nucleopolyhedrovirus that affects insects.

Single cell RNA-seq: a novel tool to unravel virus-host interplay

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

Vulture: cloud-enabled scalable mining of microbial reads in public scRNA-seq data

The rapidly growing collection of public single-cell sequencing data has become a valuable resource for molecular, cellular, and microbial discovery. Previous studies mostly overlooked detecting pathogens in human single-cell sequencing data. Moreover, existing bioinformatics tools lack the scalability to deal with big public data. We introduce Vulture, a scalable cloud-based pipeline that performs microbial calling for single-cell RNA sequencing (scRNA-seq) data, enabling meta-analysis of host-microbial studies from the public domain. In our benchmarking experiments, Vulture is 66% to 88% faster than local tools (PathogenTrack and Venus) and 41% faster than the state-of-the-art cloud-based tool Cumulus, while achieving comparable microbial read identification. In terms of the cost on cloud computing systems, Vulture also shows a cost reduction of 83% ($12 vs. ${\$}$70). We applied Vulture to 2 coronavirus disease 2019, 3 hepatocellular carcinoma (HCC), and 2 gastric cancer human patient cohorts with public sequencing reads data from scRNA-seq experiments and discovered cell type-specific enrichment of severe acute respiratory syndrome coronavirus 2, hepatitis B virus (HBV), and Helicobacter pylori-positive cells, respectively. In the HCC analysis, all cohorts showed hepatocyte-only enrichment of HBV, with cell subtype-associated HBV enrichment based on inferred copy number variations. In summary, Vulture presents a scalable and economical framework to mine unknown host-microbial interactions from large-scale public scRNA-seq data. Vulture is available via an open-source license at https://github.com/holab-hku/Vulture.

Efficacy of antiviral therapy and host-virus interactions visualised using serial liver sampling with fine-needle aspirates

Background & Aims

Novel therapies for chronic hepatitis B (CHB), such as RNA interference, target all viral RNAs for degradation, whereas nucleoside analogues are thought to block reverse transcription with minimal impact on viral transcripts. However, limitations in technology and sampling frequency have been obstacles to measuring actual changes in HBV transcription in the liver of patients starting therapy.

Methods

We used elective liver sampling with fine-needle aspirates (FNAs) to investigate the impact of treatment on viral replication in patients with CHB. Liver FNAs were collected from patients with CHB at baseline and 12 and 24 weeks after starting tenofovir alafenamide treatment. Liver FNAs were subjected to single-cell RNA sequencing and analysed using the Viral-Track method.

Results

HBV was the only viral genome detected and was enriched within hepatocytes. The 5' sequencing technology identified protein-specific HBV transcripts and showed that tenofovir alafenamide therapy specifically reduced pre-genomic RNA transcripts with little impact on HBsAg or HBx transcripts. Infected hepatocytes displayed unique gene signatures associated with an immunological response to viral infection.

Conclusions

Longitudinal liver sampling, combined with single-cell RNA sequencing, captured the dynamic impact of antiviral therapy on the replication status of HBV and revealed host-pathogen interactions at the transcriptional level in infected hepatocytes. This sequencing-based approach is applicable to early-stage clinical studies, enabling mechanistic studies of immunopathology and the effect of novel therapeutic interventions.

Impact and Implications

Infection-dependent transcriptional changes and the impact of antiviral therapy on viral replication can be measured in longitudinal human liver biopsies using single-cell RNA sequencing data.

Going through phages: a computational approach to revealing the role of prophage in Staphylococcus aureus

Prophages have important roles in virulence, antibiotic resistance, and genome evolution in Staphylococcus aureus . Rapid growth in the number of sequenced S. aureus genomes allows for an investigation of prophage sequences at an unprecedented scale. We developed a novel computational pipeline for phage discovery and annotation. We combined PhiSpy, a phage discovery tool, with VGAS and PROKKA, genome annotation tools to detect and analyse prophage sequences in nearly 10 011  S . aureus genomes, discovering thousands of putative prophage sequences with genes encoding virulence factors and antibiotic resistance. To our knowledge, this is the first large-scale application of PhiSpy on a large-scale set of genomes (10 011  S . aureus ). Determining the presence of virulence and resistance encoding genes in prophage has implications for the potential transfer of these genes/functions to other bacteria via transduction and thus can provide insight into the evolution and spread of these genes/functions between bacterial strains. While the phage we have identified may be known, these phages were not necessarily known or characterized in S. aureus and the clustering and comparison we did for phage based on their gene content is novel. Moreover, the reporting of these genes with the S. aureus genomes is novel.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

Single-cell RNA-seq methods to interrogate virus-host interactions

The twenty-first century has seen the emergence of many epidemic and pandemic viruses, with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate intracellular parasites, viruses rely on host cells to replicate and produce progeny, resulting in complex virus and host dynamics during an infection. Single-cell RNA sequencing (scRNA-seq), by enabling broad and simultaneous profiling of both host and virus transcripts, represents a powerful technology to unravel the delicate balance between host and virus. In this review, we summarize technological and methodological advances in scRNA-seq and their applications to antiviral immunity. We highlight key scRNA-seq applications that have enabled the understanding of viral genomic and host response heterogeneity, differential responses of infected versus bystander cells, and intercellular communication networks. We expect further development of scRNA-seq technologies and analytical methods, combined with measurements of additional multi-omic modalities and increased availability of publicly accessible scRNA-seq datasets, to enable a better understanding of viral pathogenesis and enhance the development of antiviral therapeutics strategies.

Development of Single-Cell Transcriptomics and Its Application in COVID-19

Over the last three years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related health crisis has claimed over six million lives and caused USD 12 trillion losses to the global economy. SARS-CoV-2 continuously mutates and evolves with a high basic reproduction number (R0), resulting in a variety of clinical manifestations ranging from asymptomatic infection to acute respiratory distress syndrome (ARDS) and even death. To gain a better understanding of coronavirus disease 2019 (COVID-19), it is critical to investigate the components that cause various clinical manifestations. Single-cell sequencing has substantial advantages in terms of identifying differentially expressed genes among individual cells, which can provide a better understanding of the various physiological and pathological processes. This article reviewed the use of single-cell transcriptomics in COVID-19 research, examined the immune response disparities generated by SARS-CoV-2, and offered insights regarding how to improve COVID-19 diagnosis and treatment plans.

Post-genomic platform for development of oligonucleotide vaccines against RNA viruses: diamond cuts diamond

The coronavirus pandemic has starkly demonstrated the need to create highly effective vaccines against various viral diseases. The emerging new platforms for vaccine creation (adenovirus vectors and mRNA vaccines) have shown their worth in the fight against the prevention of coronavirus infection. However, adenovirus vectors and mRNA vaccines have a serious disadvantage: as a rule, only the S protein of the coronavirus is presented as an antigen. This tactic for preventing infection allows the ever-mutating virus to escape quickly from the immunity protection provided by such vaccines. Today, viral genomic databases are well-developed, which makes it possible to create new vaccines on a fundamentally new post-genomic platform. In addition, the technology for the synthesis of nucleic acids is currently experiencing an upsurge in demand in various fields of molecular biology. The accumulated experience suggests that the unique genomic sequences of viruses can act as antigens that trigger powerful humoral and cellular immunity. To achieve this effect, the following conditions must be created: the structure of the nucleic acid must be single-stranded, have a permanent 3D nanostructure, and have a unique sequence absent in the vaccinated organism. Oligonucleotide vaccines are able to resist the rapidly changing genomic sequences of RNA viruses by using conserved regions of their genomes to generate a long-term immune response, acting according to the adage that a diamond cuts a diamond. In addition, oligonucleotide vaccines will not contribute to antibody-dependent enhanced infection, since the nucleic acid of the coronavirus is inside the viral particle. It is obvious that new epidemics and pandemics caused by RNA viruses will continue to arise periodically in the human population. The creation of new, safe, and effective platforms for the production of vaccines that can flexibly change and adapt to new subtypes of viruses is very urgent and at this moment should be considered as a strategically necessary task.

Virus finding tools: current solutions and limitations

MOTIVATION

The study of the Human Virome remains challenging nowadays. Viral metagenomics, through high-throughput sequencing data, is the best choice for virus discovery. The metagenomics approach is culture-independent and sequence-independent, helping search for either known or novel viruses. Though it is estimated that more than 40% of the viruses found in metagenomics analysis are not recognizable, we decided to analyze several tools to identify and discover viruses in RNA-seq samples.

RESULTS

We have analyzed eight Virus Tools for the identification of viruses in RNA-seq data. These tools were compared using a synthetic dataset of 30 viruses and a real one. Our analysis shows that no tool succeeds in recognizing all the viruses in the datasets. So we can conclude that each of these tools has pros and cons, and their choice depends on the application domain.

AVAILABILITY

Synthetic data used through the review and raw results of their analysis can be found at https://zenodo.org/record/6426147. FASTQ files of real data can be found in GEO (https://www.ncbi.nlm.nih.gov/gds) or ENA (https://www.ebi.ac.uk/ena/browser/home). Raw results of their analysis can be downloaded from https://zenodo.org/record/6425917.

MeShClust v3.0: high-quality clustering of DNA sequences using the mean shift algorithm and alignment-free identity scores

Background

Tools for accurately clustering biological sequences are among the most important tools in computational biology. Two pioneering tools for clustering sequences are CD-HIT and UCLUST, both of which are fast and consume reasonable amounts of memory; however, there is a big room for improvement in terms of cluster quality. Motivated by this opportunity for improving cluster quality, we applied the mean shift algorithm in MeShClust v1.0. The mean shift algorithm is an instance of unsupervised learning. Its strong theoretical foundation guarantees the convergence to the true cluster centers. Our implementation of the mean shift algorithm in MeShClust v1.0 was a step forward. In this work, we scale up the algorithm by adapting an out-of-core strategy while utilizing alignment-free identity scores in a new tool: MeShClust v3.0.

Results

We evaluated CD-HIT, MeShClust v1.0, MeShClust v3.0, and UCLUST on 22 synthetic sets and five real sets. These data sets were designed or selected for testing the tools in terms of scalability and different similarity levels among sequences comprising clusters. On the synthetic data sets, MeShClust v3.0 outperformed the related tools on all sets in terms of cluster quality. On two real data sets obtained from human microbiome and maize transposons, MeShClust v3.0 outperformed the related tools by wide margins, achieving 55%–300% improvement in cluster quality. On another set that includes degenerate viral sequences, MeShClust v3.0 came third. On two bacterial sets, MeShClust v3.0 was the only applicable tool because of the long sequences in these sets. MeShClust v3.0 requires more time and memory than the related tools; almost all personal computers at the time of this writing can accommodate such requirements. MeShClust v3.0 can estimate an important parameter that controls cluster membership with high accuracy.

Conclusions

These results demonstrate the high quality of clusters produced by MeShClust v3.0 and its ability to apply the mean shift algorithm to large data sets and long sequences. Because clustering tools are utilized in many studies, providing high-quality clusters will help with deriving accurate biological knowledge.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08619-0).

Individual-based model highlights the importance of trade-offs for virus-host population dynamics and long-term co-existence

Viruses play diverse and important roles in ecosystems. In recent years, trade-offs between host and virus traits have gained increasing attention in viral ecology and evolution. However, microbial organism traits, and viral population parameters in particular, are challenging to monitor. Mathematical and individual-based models are useful tools for predicting virus-host dynamics. We have developed an individual-based evolutionary model to study ecological interactions and evolution between bacteria and viruses, with emphasis on the impacts of trade-offs between competitive and defensive host traits on bacteria-phage population dynamics and trait diversification. Host dynamics are validated with lab results for different initial virus to host ratios (VHR). We show that trade-off based, as opposed to random bacteria-virus interactions, result in biologically plausible evolutionary outcomes, thus highlighting the importance of trade-offs in shaping biodiversity. The effects of nutrient concentration and other environmental and organismal parameters on the virus-host dynamics are also investigated. Despite its simplicity, our model serves as a powerful tool to study bacteria-phage interactions and mechanisms for evolutionary diversification under various environmental conditions.

Clustering biological sequences with dynamic sequence similarity threshold

BACKGROUND

Biological sequence clustering is a complicated data clustering problem owing to the high computation costs incurred for pairwise sequence distance calculations through sequence alignments, as well as difficulties in determining parameters for deriving robust clusters. While current approaches are successful in reducing the number of sequence alignments performed, the generated clusters are based on a single sequence identity threshold applied to every cluster. Poor choices of this identity threshold would thus lead to low quality clusters. There is however little support provided to users in selecting thresholds that are well matched with the input sequences.

RESULTS

We present a novel sequence clustering approach called ALFATClust that exploits rapid pairwise alignment-free sequence distance calculations and community detection in graph for clusters generation. Instead of a single threshold applied to every generated cluster, ALFATClust is capable of dynamically determining the cut-off threshold for each individual cluster by considering both cluster separation and intra-cluster sequence similarity. Benchmarking analysis shows that ALFATClust generally outperforms existing approaches by simultaneously maintaining cluster robustness and substantial cluster separation for the benchmark datasets. The software also provides an evaluation report for verifying the quality of the non-singleton clusters obtained.

CONCLUSIONS

ALFATClust is able to generate sequence clusters having high intra-cluster sequence similarity and substantial separation between clusters without having users to decide precise similarity cut-off thresholds.

Maternal-fetal immune responses in pregnant women infected with SARS-CoV-2

Pregnant women represent a high-risk population for severe/critical COVID-19 and mortality. However, the maternal-fetal immune responses initiated by SARS-CoV-2 infection, and whether this virus is detectable in the placenta, are still under investigation. Here we show that SARS-CoV-2 infection during pregnancy primarily induces unique inflammatory responses at the maternal-fetal interface, which are largely governed by maternal T cells and fetal stromal cells. SARS-CoV-2 infection during pregnancy is also associated with humoral and cellular immune responses in the maternal blood, as well as with a mild cytokine response in the neonatal circulation (i.e., umbilical cord blood), without compromising the T-cell repertoire or initiating IgM responses. Importantly, SARS-CoV-2 is not detected in the placental tissues, nor is the sterility of the placenta compromised by maternal viral infection. This study provides insight into the maternal-fetal immune responses triggered by SARS-CoV-2 and emphasizes the rarity of placental infection.

Dysregulation of brain and choroid plexus cell types in severe COVID-19

Although SARS-CoV-2 primarily targets the respiratory system, patients with and survivors of COVID-19 can suffer neurological symptoms1-3. However, an unbiased understanding of the cellular and molecular processes that are affected in the brains of patients with COVID-19 is missing. Here we profile 65,309 single-nucleus transcriptomes from 30 frontal cortex and choroid plexus samples across 14 control individuals (including 1 patient with terminal influenza) and 8 patients with COVID-19. Although our systematic analysis yields no molecular traces of SARS-CoV-2 in the brain, we observe broad cellular perturbations indicating that barrier cells of the choroid plexus sense and relay peripheral inflammation into the brain and show that peripheral T cells infiltrate the parenchyma. We discover microglia and astrocyte subpopulations associated with COVID-19 that share features with pathological cell states that have previously been reported in human neurodegenerative disease4-6. Synaptic signalling of upper-layer excitatory neurons-which are evolutionarily expanded in humans7 and linked to cognitive function8-is preferentially affected in COVID-19. Across cell types, perturbations associated with COVID-19 overlap with those found in chronic brain disorders and reside in genetic variants associated with cognition, schizophrenia and depression. Our findings and public dataset provide a molecular framework to understand current observations of COVID-19-related neurological disease, and any such disease that may emerge at a later date.

Maternal-Fetal Immune Responses in Pregnant Women Infected with SARS-CoV-2

Pregnant women are a high-risk population for severe/critical COVID-19 and mortality. However, the maternal-fetal immune responses initiated by SARS-CoV-2 infection, and whether this virus is detectable in the placenta, are still under investigation. Herein, we report that SARS-CoV-2 infection during pregnancy primarily induced specific maternal inflammatory responses in the circulation and at the maternal-fetal interface, the latter being governed by T cells and macrophages. SARS-CoV-2 infection during pregnancy was also associated with a cytokine response in the fetal circulation (i.e. umbilical cord blood) without compromising the cellular immune repertoire. Moreover, SARS-CoV-2 infection neither altered fetal cellular immune responses in the placenta nor induced elevated cord blood levels of IgM. Importantly, SARS-CoV-2 was not detected in the placental tissues, nor was the sterility of the placenta compromised by maternal viral infection. This study provides insight into the maternal-fetal immune responses triggered by SARS-CoV-2 and further emphasizes the rarity of placental infection.

Identity: rapid alignment-free prediction of sequence alignment identity scores using self-supervised general linear models

Pairwise global alignment is a fundamental step in sequence analysis. Optimal alignment algorithms are quadratic-slow especially on long sequences. In many applications that involve large sequence datasets, all what is needed is calculating the identity scores (percentage of identical nucleotides in an optimal alignment-including gaps-of two sequences); there is no need for visualizing how every two sequences are aligned. For these applications, we propose Identity, which produces global identity scores for a large number of pairs of DNA sequences using alignment-free methods and self-supervised general linear models. For the first time, the new tool can predict pairwise identity scores in linear time and space. On two large-scale sequence databases, Identity provided the best compromise between sensitivity and precision while being faster than BLAST, Mash, MUMmer4 and USEARCH by 2-80 times. Identity was the best performing tool when searching for low-identity matches. While constructing phylogenetic trees from about 6000 transcripts, the tree due to the scores reported by Identity was the closest to the reference tree (in contrast to andi, FSWM and Mash). Identity is capable of producing pairwise identity scores of millions-of-nucleotides-long bacterial genomes; this task cannot be accomplished by any global-alignment-based tool. Availability: https://github.com/BioinformaticsToolsmith/Identity.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Virosaurus A Reference to Explore and Capture Virus Genetic Diversity

The huge genetic diversity of circulating viruses is a challenge for diagnostic assays for emerging or rare viral diseases. High-throughput technology offers a new opportunity to explore the global virome of patients without preconception about the culpable pathogens. It requires a solid reference dataset to be accurate. Virosaurus has been designed to offer a non-biased, automatized and annotated database for clinical metagenomics studies and diagnosis. Raw viral sequences have been extracted from GenBank, and cleaned up to remove potentially erroneous sequences. Complete sequences have been identified for all genera infecting vertebrates, plants and other eukaryotes (insect, fungus, etc.). To facilitate the analysis of clinically relevant viruses, we have annotated all sequences with official and common virus names, acronym, genotypes, and genomic features (linear, circular, DNA, RNA, etc.). Sequences have been clustered to remove redundancy at 90% or 98% identity. The analysis of clustering results reveals the state of the virus genetic landscape knowledge. Because herpes and poxviruses were under-represented in complete genomes considering their potential diversity in nature, we used genes instead of complete genomes for those in Virosaurus.

Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.

Propagation and Molecular Characterization of Fowl Adenovirus Serotype 8b Isolates in Chicken Embryo Liver Cells Adapted on Cytodex™ 1 Microcarrier Using Stirred Tank Bioreactor

Large volume production of vaccine virus is essential for prevention and control of viral diseases. The objectives of this study were to propagate Fowl adenovirus (FAdV) isolate (UPM08136) in chicken embryo liver (CEL) cells adapted to Cytodex™ 1 microcarriers using stirred tank bioreactor (STB) and molecularly characterize the virus. CEL cells were prepared and seeded onto prepared Cytodex™ 1 microcarriers and incubated first in stationary phase for 3 h and in STB at 37 °C, 5% CO2, and 20 rpm for 24 h. The CEL cells were infected with FAdV isolate (UPM08136) passage 5 (UPM08136CELP5) or passage 20 (UPM08136CELP20) and monitored until cell detachment. Immunofluorescence, TCID50, sequencing, alignment of hexon and fiber genes, and phylogenetic analysis were carried out. CEL cells were adapted well to Cytodex™ 1 microcarriers and successfully propagated the FAdV isolates in STB with virus titer of 107.5 (UPM08136CELP5B1) and 106.5 (UPM08136CELP20B1) TCID50/mL. These isolates clustered with the reference FAdV serotype 8b in the same evolutionary clade. The molecular characteristics remained unchanged, except for a point substitution at position 4 of the hexon gene of UPM08136CELP20B1, suggesting that propagation of the FAdV isolate in STB is stable and suitable for large volume production and could be a breakthrough in the scale-up process.

Viral diversity in oral cavity from Sapajus nigritus by metagenomic analyses

Sapajus nigritus are non-human primates which are widespread in South America. They are omnivores and live in troops of up to 40 individuals. The oral cavity is one of the main entry routes for microorganisms, including viruses. Our study proposed the identification of viral sequences from oral swabs collected in a group of capuchin monkeys (n = 5) living in a public park in a fragment of Mata Atlantica in South Brazil. Samples were submitted to nucleic acid extraction and enrichment, which was followed by the construction of libraries. After high-throughput sequencing and contig assembly, we used a pipeline to identify 11 viral families, which are Herpesviridae, Parvoviridae, Papillomaviridae, Polyomaviridae, Caulimoviridae, Iridoviridae, Astroviridae, Poxviridae, and Baculoviridae, in addition to two complete viral genomes of Anelloviridae and Genomoviridae. Some of these viruses were closely related to known viruses, while other fragments are more distantly related, with 50% of identity or less to the currently available virus sequences in databases. In addition to host-related viruses, insect and small vertebrate-related viruses were also found, as well as plant-related viruses, bringing insights about their diet. In conclusion, this viral metagenomic analysis reveals, for the first time, the profile of viruses in the oral cavity of wild, free ranging capuchin monkeys.

Energetics and IC50 based epitope screening in SARS CoV-2 (COVID 19) spike protein by immunoinformatic analysis implicating for a suitable vaccine development

BACKGROUND

The recent outbreak by SARS-CoV-2 has generated a chaos in global health and economy and claimed/infected a large number of lives. Closely resembling with SARS CoV, the present strain has manifested exceptionally higher degree of spreadability, virulence and stability possibly due to some unidentified mutations. The viral spike glycoprotein is very likely to interact with host Angiotensin-Converting Enzyme 2 (ACE2) and transmits its genetic materials and hijacks host machinery with extreme fidelity for self propagation. Few attempts have been made to develop a suitable vaccine or ACE2 blocker or virus-receptor inhibitor within this short period of time.

METHODS

Here, attempt was taken to develop some therapeutic and vaccination strategies with a comparison of spike glycoproteins among SARS-CoV, MERS-CoV and the SARS-CoV-2. We verified their structure quality (SWISS-MODEL, Phyre2, and Pymol) topology (ProFunc), motifs (MEME Suite, GLAM2Scan), gene ontology based conserved domain (InterPro database) and screened several epitopes (SVMTrip) of SARS CoV-2 based on their energetics, IC50 and antigenicity with regard to their possible glycosylation and MHC/paratope binding (Vaxigen v2.0, HawkDock, ZDOCK Server) effects.

RESULTS

We screened here few pairs of spike protein epitopic regions and selected their energetic, Inhibitory Concentration50 (IC50), MHC II reactivity and found some of those to be very good target for vaccination. A possible role of glycosylation on epitopic region showed profound effects on epitopic recognition.

CONCLUSION

The present work might be helpful for the urgent development of a suitable vaccination regimen against SARS CoV-2.

Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

Viruses are a constant threat to global health as highlighted by the current COVID-19 pandemic. Currently, lack of data underlying how the human host interacts with viruses, including the SARS-CoV-2 virus, limits effective therapeutic intervention. We introduce Viral-Track, a computational method that globally scans unmapped single-cell RNA sequencing (scRNA-seq) data for the presence of viral RNA, enabling transcriptional cell sorting of infected versus bystander cells. We demonstrate the sensitivity and specificity of Viral-Track to systematically detect viruses from multiple models of infection, including hepatitis B virus, in an unsupervised manner. Applying Viral-Track to bronchoalveloar-lavage samples from severe and mild COVID-19 patients reveals a dramatic impact of the virus on the immune system of severe patients compared to mild cases. Viral-Track detects an unexpected co-infection of the human metapneumovirus, present mainly in monocytes perturbed in type-I interferon (IFN)-signaling. Viral-Track provides a robust technology for dissecting the mechanisms of viral-infection and pathology.

Current Trends in Diagnostics of Viral Infections of Unknown Etiology

Viruses are evolving at an alarming rate, spreading and inconspicuously adapting to cutting-edge therapies. Therefore, the search for rapid, informative and reliable diagnostic methods is becoming urgent as ever. Conventional clinical tests (PCR, serology, etc.) are being continually optimized, yet provide very limited data. Could high throughput sequencing (HTS) become the future gold standard in molecular diagnostics of viral infections? Compared to conventional clinical tests, HTS is universal and more precise at profiling pathogens. Nevertheless, it has not yet been widely accepted as a diagnostic tool, owing primarily to its high cost and the complexity of sample preparation and data analysis. Those obstacles must be tackled to integrate HTS into daily clinical practice. For this, three objectives are to be achieved: (1) designing and assessing universal protocols for library preparation, (2) assembling purpose-specific pipelines, and (3) building computational infrastructure to suit the needs and financial abilities of modern healthcare centers. Data harvested with HTS could not only augment diagnostics and help to choose the correct therapy, but also facilitate research in epidemiology, genetics and virology. This information, in turn, could significantly aid clinicians in battling viral infections.

Next generation sequencing and proteomics in plant virology: how is Colombia doing?

Crop production and trade are two of the most economically important activities in Colombia, and viral diseases cause a high negative impact to agricultural sector. Therefore, the detection, diagnosis, control, and management of viral diseases are crucial. Currently, Next-Generation Sequencing (NGS) and ‘Omic’ technologies constitute a right-hand tool for the discovery of novel viruses and for studying virus-plant interactions. This knowledge allows the development of new viral diagnostic methods and the discovery of key components of infectious processes, which could be used to generate plants resistant to viral infections. Globally, crop sciences are advancing in this direction. In this review, advancements in ‘omic’ technologies and their different applications in plant virology in Colombia are discussed. In addition, bioinformatics pipelines and resources for omics data analyses are presented. Due to their decreasing prices, NGS technologies are becoming an affordable and promising means to explore many phytopathologies affecting a wide variety of Colombian crops so as to improve their trade potential.

MeShClust: an intelligent tool for clustering DNA sequences

Sequence clustering is a fundamental step in analyzing DNA sequences. Widely-used software tools for sequence clustering utilize greedy approaches that are not guaranteed to produce the best results. These tools are sensitive to one parameter that determines the similarity among sequences in a cluster. Often times, a biologist may not know the exact sequence similarity. Therefore, clusters produced by these tools do not likely match the real clusters comprising the data if the provided parameter is inaccurate. To overcome this limitation, we adapted the mean shift algorithm, an unsupervised machine-learning algorithm, which has been used successfully thousands of times in fields such as image processing and computer vision. The theory behind the mean shift algorithm, unlike the greedy approaches, guarantees convergence to the modes, e.g. cluster centers. Here we describe the first application of the mean shift algorithm to clustering DNA sequences. MeShClust is one of few applications of the mean shift algorithm in bioinformatics. Further, we applied supervised machine learning to predict the identity score produced by global alignment using alignment-free methods. We demonstrate MeShClust's ability to cluster DNA sequences with high accuracy even when the sequence similarity parameter provided by the user is not very accurate.

Viral Long-Term Evolutionary Strategies Favor Stability over Proliferation

Viruses are known to have some of the highest and most diverse mutation rates found in any biological replicator, with single-stranded (ss) RNA viruses evolving the fastest, and double-stranded (ds) DNA viruses having rates approaching those of bacteria. As mutation rates are tightly and negatively correlated with genome size, selection is a clear driver of viral evolution. However, the role of intragenomic interactions as drivers of viral evolution is still unclear. To understand how these two processes affect the long-term evolution of viruses infecting humans, we comprehensively analyzed ssRNA, ssDNA, dsRNA, and dsDNA viruses, to find which virus types and which functions show evidence for episodic diversifying selection and correlated evolution. We show that selection mostly affects single stranded viruses, that correlated evolution is more prevalent in DNA viruses, and that both processes, taken independently, mostly affect viral replication. However, the genes that are jointly affected by both processes are involved in key aspects of their life cycle, favoring viral stability over proliferation. We further show that both evolutionary processes are intimately linked at the amino acid level, which suggests that it is the joint action of selection and correlated evolution, and not just selection, that shapes the evolutionary trajectories of viruses—and possibly of their epidemiological potential.

Detection and Molecular Characterization of Novel dsRNA Viruses Related to the Totiviridae Family in Umbelopsis ramanniana

Umbelopsis ramanniana is an oleaginous fungus belonging to the Mucoromycotina subphylum. Our group had previously detected four double-stranded RNA (dsRNA) bands in the U. ramanniana NRRL 1296 strain by gel electrophoresis. Here we describe the molecular characterization of its dsRNA elements as well as the discovery of four novel dsRNA viruses: Umbelopsis ramanniana virus 1 (UrV1), Umbelopsis ramanniana virus 2 (UrV2), Umbelopsis ramanniana virus 3 (UrV3), and Umbelopsis ramanniana virus 4 (UrV4). Full genomes of UrV1, UrV3, and UrV4 were determined using the full-length amplification of cDNAs (FLAC) technique; they contain two open reading frames (ORF), which putatively encode the coat protein (CP) and the RNA dependent RNA polymerase (RdRp), respectively. In case of UrV2, a partial ORF encoding a partial RdRp gene could be determined. Based on the phylogeny inferred from the RdRp sequences, UrV1 and UrV4 belong to the genus Totivirus, while UrV2 may belong to the genus Victorivirus. UrV3 nested to a novel, unclassified group of Totiviridae, which is related to the genus Totivirus. Hybridization analysis revealed that the dsRNA molecules of UrV1 and UrV4 correspond to the same 5.0-kbp electrophoretic band, whilst the probe for the UrV3 hybridized to the largest, 5.3-kbp and the 3.0-kbp bands of the dsRNA pattern of U. ramanniana. Interestingly, the probe for the UrV2 sequence did not hybridized to any dsRNA bands, but it could be amplified from the isolated 3.0-kbp fragment. By transmission electron microscopy, two different isometric virus particles with about 50 and 35 nm in diameter were detected in U. ramanniana NRRL 1296 indicating that this strain harbor multiple viruses. Beside U. ramanniana, dsRNA elements were also detected in other Umbelopsis isolates with different patterns consisting of 2 to 4 discrete and different sized (0.7–5.3-kbp) dsRNA molecules. Based on a hybridization analysis with UrV1 CP and RdRp probes, the bands with the size of around 5.0-kbp, which were present in all tested Umbelopsis strains, are presumed as possible full mycovirus genomes.

Relationship Between G-Quadruplex Sequence Composition in Viruses and Their Hosts

A subset of guanine-rich nucleic acid sequences has the potential to fold into G-quadruplex (G4) secondary structures, which are functionally important for several biological processes, including genome stability and regulation of gene expression. Putative quadruplex sequences (PQSs) G₃₊N_1-7G₃₊N_1-7G₃₊N_1-7G₃₊ are widely found in eukaryotic and prokaryotic genomes, but the base composition of the N_1-7 loops is biased across species. Since the viruses partially hijack their hosts' cellular machinery for proliferation, we examined the PQS motif size, loop length, and nucleotide compositions of 7370 viral genome assemblies and compared viral and host PQS motifs. We studied seven viral taxa infecting five distant eukaryotic hosts and created a resource providing a comprehensive view of the viral quadruplex motifs. Overall, short-looped PQSs are predominant and with a similar composition across viral taxonomic groups, albeit subtle trends emerge upon classification by hosts. Specifically, there is a higher frequency of pyrimidine loops in viruses infecting animals irrespective of the viruses' genome type. This observation is confirmed by an in-depth analysis of the Herpesviridae family of viruses, which showed a distinctive accumulation of thermally stable C-looped quadruplexes in viruses infecting high-order vertebrates. The occurrence of viral C-looped G4s, which carry binding sites for host transcription factors, as well as the high prevalence of viral TTA-looped G4s, which are identical to vertebrate telomeric motifs, provide concrete examples of how PQSs may help viruses impinge upon, and benefit from, host functions. More generally, these observations suggest a co-evolution of virus and host PQSs, thus underscoring the potential functional significance of G4s.

Giant Viruses-Big Surprises

Viruses are the most prevalent infectious agents, populating almost every ecosystem on earth. Most viruses carry only a handful of genes supporting their replication and the production of capsids. It came as a great surprise in 2003 when the first giant virus was discovered and found to have a >1 Mbp genome encoding almost a thousand proteins. Following this first discovery, dozens of giant virus strains across several viral families have been reported. Here, we provide an updated quantitative and qualitative view on giant viruses and elaborate on their shared and variable features. We review the complexity of giant viral proteomes, which include functions traditionally associated only with cellular organisms. These unprecedented functions include components of the translation machinery, DNA maintenance, and metabolic enzymes. We discuss the possible underlying evolutionary processes and mechanisms that might have shaped the diversity of giant viruses and their genomes, highlighting their remarkable capacity to hijack genes and genomic sequences from their hosts and environments. This leads us to examine prominent theories regarding the origin of giant viruses. Finally, we present the emerging ecological view of giant viruses, found across widespread habitats and ecological systems, with respect to the environment and human health.

A metagenomic study of DNA viruses from samples of local varieties of common bean in Kenya

Common bean (Phaseolus vulgaris L.) is the primary source of protein and nutrients in the majority of households in sub-Saharan Africa. However, pests and viral diseases are key drivers in the reduction of bean production. To date, the majority of viruses reported in beans have been RNA viruses. In this study, we carried out a viral metagenomic analysis on virus symptomatic bean plants. Our virus detection pipeline identified three viral fragments of the double-stranded DNA virus Pelargonium vein banding virus (PVBV) (family, Caulimoviridae, genus Badnavirus). This is the first report of the dsDNA virus and specifically PVBV in legumes to our knowledge. In addition two previously reported +ssRNA viruses the bean common mosaic necrosis virus (BCMNVA) (Potyviridae) and aphid lethal paralysis virus (ALPV) (Dicistroviridae) were identified. Bayesian phylogenetic analysis of the Badnavirus (PVBV) using amino acid sequences of the RT/RNA-dependent DNA polymerase region showed the Kenyan sequence (SRF019_MK014483) was closely matched with two Badnavirus viruses: Dracaena mottle virus (DrMV) (YP_610965) and Lucky bamboo bacilliform virus (ABR01170). Phylogenetic analysis of BCMNVA was based on amino acid sequences of the Nib region. The BCMNVA phylogenetic tree resolved two clades identified as clade (I and II). Sequence from this study SRF35_MK014482, clustered within clade I with other Kenyan sequences. Conversely, Bayesian phylogenetic analysis of ALPV was based on nucleotide sequences of the hypothetical protein gene 1 and 2. Three main clades were resolved and identified as clades I-III. The Kenyan sequence from this study (SRF35_MK014481) clustered within clade II, and nested within a sub-clade; comprising of sequences from China and an earlier ALPV sequences from Kenya isolated from maize (MF458892). Our findings support the use of viral metagenomics to reveal the nascent viruses, their viral diversity and evolutionary history of these viruses. The detection of ALPV and PVBV indicate that these viruses have likely been underreported due to the unavailability of diagnostic tools.

Unexpected invasion of miniature inverted-repeat transposable elements in viral genomes

Background

Transposable elements (TEs) are common and often present with high copy numbers in cellular genomes. Unlike in cellular organisms, TEs were previously thought to be either rare or absent in viruses. Almost all reported TEs display only one or two copies per viral genome. In addition, the discovery of pandoraviruses with genomes up to 2.5-Mb emphasizes the need for biologists to rethink the fundamental nature of the relationship between viruses and cellular life.

Results

Herein, we performed the first comprehensive analysis of miniature inverted-repeat transposable elements (MITEs) in the 5170 viral genomes for which sequences are currently available. Four hundred and fifty one copies of ten miniature inverted-repeat transposable elements (MITEs) were found and each MITE had reached relatively large copy numbers (some up to 90) in viruses. Eight MITEs belonging to two DNA superfamilies (hobo/Activator/Tam3 and Chapaev-Mirage-CACTA) were for the first time identified in viruses, further expanding the organismal range of these two superfamilies. TEs may play important roles in shaping the evolution of pandoravirus genomes, which were here found to be very rich in MITEs. We also show that putative autonomous partners of seven MITEs are present in the genomes of viral hosts, suggesting that viruses may borrow the transpositional machinery of their cellular hosts' autonomous elements to spread MITEs and colonize their own genomes. The presence of seven similar MITEs in viral hosts, suggesting horizontal transfers (HTs) as the major mechanism for MITEs propagation.

Conclusions

Our discovery highlights that TEs contribute to shape genome evolution of pandoraviruses. We concluded that as for cellular organisms, TEs are part of the pandoraviruses' diverse mobilome.