Using artificial intelligence to document the hidden RNA virosphere.

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

VirID: Beyond Virus Discovery - An Integrated Platform for Comprehensive RNA Virus Characterization.

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

Total infectome characterization of respiratory infections in pre-COVID-19 Wuhan, China.

At the end of 2019 Wuhan witnessed an outbreak of "atypical pneumonia" that later developed into a global pandemic. Metagenomic sequencing rapidly revealed the causative agent of this outbreak to be a novel coronavirus denoted SARS-CoV-2. To provide a snapshot of the pathogens in pneumonia-associated respiratory samples from Wuhan prior to the emergence of SARS-CoV-2, we collected bronchoalveolar lavage fluid samples from 408 patients presenting with pneumonia and acute respiratory infections at the Central Hospital of Wuhan between 2016 and 2017. Unbiased total RNA sequencing was performed to reveal their "total infectome", including viruses, bacteria and fungi. We identified 35 pathogen species, comprising 13 RNA viruses, 3 DNA viruses, 16 bacteria and 3 fungi, often at high abundance and including multiple co-infections (13.5%). SARS-CoV-2 was not present. These data depict a stable core infectome comprising common respiratory pathogens such as rhinoviruses and influenza viruses, an atypical respiratory virus (EV-D68), and a single case of a sporadic zoonotic pathogen-Chlamydia psittaci. Samples from patients experiencing respiratory disease on average had higher pathogen abundance than healthy controls. Phylogenetic analyses of individual pathogens revealed multiple origins and global transmission histories, highlighting the connectedness of the Wuhan population. This study provides a comprehensive overview of the pathogens associated with acute respiratory infections and pneumonia, which were more diverse and complex than obtained using targeted PCR or qPCR approaches. These data also suggest that SARS-CoV-2 or closely related viruses were absent from Wuhan in 2016-2017.

Probing biological nanotopology via diffusion of weakly constrained plasmonic nanorods with optical coherence tomography.

Biological materials exhibit complex nanotopology, i.e., a composite liquid and solid phase structure that is heterogeneous on the nanoscale. The diffusion of nanoparticles in nanotopological environments can elucidate biophysical changes associated with pathogenesis and disease progression. However, there is a lack of methods that characterize nanoprobe diffusion and translate easily to in vivo studies. Here, we demonstrate a method based on optical coherence tomography (OCT) to depth-resolve diffusion of plasmon-resonant gold nanorods (GNRs) that are weakly constrained by the biological tissue. By using GNRs that are on the size scale of the polymeric mesh, their Brownian motion is minimally hindered by intermittent collisions with local macromolecules. OCT depth-resolves the particle-averaged translational diffusion coefficient (DT) of GNRs within each coherence volume, which is separable from the nonequilibrium motile activities of cells based on the unique polarized light-scattering properties of GNRs. We show how this enables minimally invasive imaging and monitoring of nanotopological changes in a variety of biological models, including extracellular matrix (ECM) remodeling as relevant to carcinogenesis, and dehydration of pulmonary mucus as relevant to cystic fibrosis. In 3D ECM models, DT of GNRs decreases with both increasing collagen concentration and cell density. Similarly, DT of GNRs is sensitive to human bronchial-epithelial mucus concentration over a physiologically relevant range. This novel method comprises a broad-based platform for studying heterogeneous nanotopology, as distinct from bulk viscoelasticity, in biological milieu.

Characterizing Autism Spectrum Disorder Through Fusion of Local Cortical Activation and Global Functional Connectivity Using Game-Based Stimuli and a Mobile EEG System.

The deficit in social interaction skills among individuals with autism spectrum disorder (ASD) is strongly influenced by personal experiences and social environments. Neuroimaging studies have previously highlighted the link between social impairment and brain activity in ASD. This study aims to develop a method for assessing and identifying ASD using a social cognitive game-based paradigm combined with electroencephalo-graphy (EEG) signaling features. Typically developing (TD) participants and autistic preadolescents and teenagers were recruited to participate in a social game while 12-channel EEG signals were recorded. The EEG signals underwent preprocessing to analyze local brain activities, including event-related potentials (ERPs) and time-frequency features. Additionally, the global brain network's functional connectivity between brain regions was evaluated using phase-lag indices (PLIs). Subsequently, machine learning models were employed to assess the neurophysiological features. Results indicated pronounced ERP components, particularly the late positive potential (LPP), in parietal regions during social training. Autistic preadolescents and teenagers exhibited lower LPP amplitudes and larger P200 amplitudes compared to TD participants. Reduced theta synchronization was also observed in the ASD group. Aberrant functional connectivity within certain time intervals was noted in the ASD group. Machine learning analysis revealed that support-vector machines achieved a sensitivity of 100%, specificity of 91.7%, and accuracy of 95.8% as part of the performance evaluation when utilizing ERP and brain oscillation features for ASD characterization. These findings suggest that social interaction difficulties in autism are linked to specific brain activation patterns. Traditional behavioral assessments face challenges of subjectivity and accuracy, indicating the potential use of social training interfaces and EEG features for cognitive assessment in ASD.

Total Infectome Characterization of Respiratory Infections during the 2022-23 COVID-19 Outbreak in China Revealed Extensive Coinfections with Links to SARS-CoV-2 Status, Age, and Disease Severity.

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

Meta-transcriptomic analysis of companion animal infectomes reveals their diversity and potential roles in animal and human disease.

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

The clinical outcome of COVID-19 is strongly associated with microbiome dynamics in the upper respiratory tract.

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

Metagenomic analysis of individual mosquito viromes reveals the geographical patterns and drivers of viral diversity.

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

Motility-, autocorrelation-, and polarization-sensitive optical coherence tomography discriminates cells and gold nanorods within 3D tissue cultures.

We propose a method for differentiating classes of light scatterers based upon their temporal and polarization properties computed from time series of polarization-sensitive optical coherence tomography (PS-OCT) images. The amplitude (motility) and time scale (autocorrelation decay time) of the speckle fluctuations are combined with the cross-polarization pixel-wise to render Motility-, autocorrelation-, and polarization-sensitive (MAPS) OCT contrast images. This combination of metrics provides high specificity for discriminating diffusive gold nanorods and mammary epithelial cell spheroids within 3D tissue culture, based on their unique MAPS signature. This has implications toward highly specific contrast in molecular (nanoparticle-based) and functional (cellular activity) imaging using standard PS-OCT hardware.

Genetic Diversity and Evolution of Viruses Infecting Felis catus: A Global Perspective.

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

Individual bat virome analysis reveals co-infection and spillover among bats and virus zoonotic potential.

Bats are reservoir hosts for many zoonotic viruses. Despite this, relatively little is known about the diversity and abundance of viruses within individual bats, and hence the frequency of virus co-infection and spillover among them. We characterize the mammal-associated viruses in 149 individual bats sampled from Yunnan province, China, using an unbiased meta-transcriptomics approach. This reveals a high frequency of virus co-infection (simultaneous infection of bat individuals by multiple viral species) and spillover among the animals studied, which may in turn facilitate virus recombination and reassortment. Of note, we identify five viral species that are likely to be pathogenic to humans or livestock, based on phylogenetic relatedness to known pathogens or in vitro receptor binding assays. This includes a novel recombinant SARS-like coronavirus that is closely related to both SARS-CoV and SARS-CoV-2. In vitro assays indicate that this recombinant virus can utilize the human ACE2 receptor such that it is likely to be of increased emergence risk. Our study highlights the common occurrence of co-infection and spillover of bat viruses and their implications for virus emergence.

Metagenomic analysis of individual mosquitos reveals the ecology of insect viruses.

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

A time-series meta-transcriptomic analysis reveals the seasonal, host, and gender structure of mosquito viromes.

Although metagenomic sequencing has revealed high numbers of viruses in mosquitoes sampled globally, our understanding of how their diversity and abundance varies in time and space as well as by host species and gender remains unclear. To address this, we collected 23,109 mosquitoes over the course of 12 months from a bat-dwelling cave and a nearby village in Yunnan province, China. These samples were organized by mosquito species, mosquito gender, and sampling time for meta-transcriptomic sequencing. A total of 162 eukaryotic virus species were identified, of which 101 were novel, including representatives of seventeen RNA virus multi-family supergroups and four species of DNA virus from the families Parvoviridae, Circoviridae, and Nudiviridae. In addition, two known vector-borne viruses-Japanese encephalitis virus and Banna virus-were found. Analyses of the entire virome revealed strikingly different viral compositions and abundance levels in warmer compared to colder months, a strong host structure at the level of mosquito species, and no substantial differences between those viruses harbored by male and female mosquitoes. At the scale of individual viruses, some were found to be ubiquitous throughout the year and across four mosquito species, while most of the other viruses were season and/or host specific. Collectively, this study reveals the diversity, dynamics, and evolution of the mosquito virome at a single location and sheds new lights on the ecology of these important vector animals.

Design of a Vaccine Passport Validation System Using Blockchain-based Architecture: Development Study.

BACKGROUND: COVID-19 is an ongoing global pandemic caused by SARS-CoV-2. As of June 2021, 5 emergency vaccines were available for COVID-19 prevention, and with the improvement of vaccination rates and the resumption of activities in each country, verification of vaccination has become an important issue. Currently, in most areas, vaccination and reverse transcription polymerase chain reaction (RT-PCR) test results are certified and validated on paper. This leads to the problem of counterfeit documents. Therefore, a global vaccination record is needed. OBJECTIVE: The main objective of this study is to design a vaccine passport (VP) validation system based on a general blockchain architecture for international use in a simulated environment. With decentralized characteristics, the system is expected to have the advantages of low cost, high interoperability, effectiveness, security, and verifiability through blockchain architecture. METHODS: The blockchain decentralized mechanism was used to build an open and anticounterfeiting information platform for VPs. The contents of a vaccination card are recorded according to international Fast Healthcare Interoperability Resource (FHIR) standards, and blockchain smart contracts (SCs) are used for authorization and authentication to achieve hierarchical management of various international hospitals and people receiving injections. The blockchain stores an encrypted vaccination path managed by the user who manages the private key. The blockchain uses the proof-of-authority (PoA) public chain and can access all information through the specified chain. This will achieve the goal of keeping development costs low and streamlining vaccine transit management so that countries in different economies can use them. RESULTS: The openness of the blockchain helps to create transparency and data accuracy. This blockchain architecture contains a total of 3 entities. All approvals are published on Open Ledger. Smart certificates enable authorization and authentication, and encryption and decryption mechanisms guarantee data protection. This proof of concept demonstrates the design of blockchain architecture, which can achieve accurate global VP verification at an affordable price. In this study, an actual VP case was established and demonstrated. An open blockchain, an individually approved certification mechanism, and an international standard vaccination record were introduced. CONCLUSIONS: Blockchain architecture can be used to build a viable international VP authentication process with the advantages of low cost, high interoperability, effectiveness, security, and verifiability.

NAMPT Inhibitor and P73 Activator Represses P53 R175H Mutated HNSCC Cell Proliferation in a Synergistic Manner.

The p53 family has the following three members: p53, p63 and p73. p53 is a tumor suppressor gene that frequently exhibits mutation in head and neck cancer. Most p53 mutants are loss-of-function (LoF) mutants, but some acquire some oncogenic function, such as gain of function (GoF). It is known that the aggregation of mutant p53 can induce p53 GoF. The p73 activators RETRA and NSC59984 have an anti-cancer effect in p53 mutation cells, but we found that p73 activators were not effective in all head and neck squamous cell carcinoma (HNSCC) cell lines, with different p53 mutants. A comparison of the gene expression profiles of several regulator(s) in mutant HNSCC cells with or without aggregation of p53 revealed that nicotinamide phosphoribosyltransferase (NAMPT) is a key regulator of mutant p53 aggregation. An NAMPT inhibitor, to reduce abnormal aggregation of mutant p53, used in combination with a p73 activator, was able to effectively repress growth in HNSCC cells with p53 GoF mutants. This study, therefore, suggests a potential combination therapy approach for HNSCC with a p53 GoF mutation.

Individual bat viromes reveal the co-infection, spillover and emergence risk of potential zoonotic viruses.

Bats are reservoir hosts for many zoonotic viruses. Despite this, relatively little is known about the diversity and abundance of viruses within bats at the level of individual animals, and hence the frequency of virus co-infection and inter-species transmission. Using an unbiased meta-transcriptomics approach we characterised the mammalian associated viruses present in 149 individual bats sampled from Yunnan province, China. This revealed a high frequency of virus co-infection and species spillover among the animals studied, with 12 viruses shared among different bat species, which in turn facilitates virus recombination and reassortment. Of note, we identified five viral species that are likely to be pathogenic to humans or livestock, including a novel recombinant SARS-like coronavirus that is closely related to both SARS-CoV-2 and SARS-CoV, with only five amino acid differences between its receptor-binding domain sequence and that of the earliest sequences of SARS-CoV-2. Functional analysis predicts that this recombinant coronavirus can utilize the human ACE2 receptor such that it is likely to be of high zoonotic risk. Our study highlights the common occurrence of inter-species transmission and co-infection of bat viruses, as well as their implications for virus emergence.

Trafficked Malayan pangolins contain viral pathogens of humans.

Pangolins are the most trafficked wild animal in the world according to the World Wildlife Fund. The discovery of SARS-CoV-2-related coronaviruses in Malayan pangolins has piqued interest in the viromes of these wild, scaly-skinned mammals. We sequenced the viromes of 161 pangolins that were smuggled into China and assembled 28 vertebrate-associated viruses, 21 of which have not been previously reported in vertebrates. We named 16 members of Hunnivirus, Pestivirus and Copiparvovirus pangolin-associated viruses. We report that the L-protein has been lost from all hunniviruses identified in pangolins. Sequences of four human-associated viruses were detected in pangolin viromes, including respiratory syncytial virus, Orthopneumovirus, Rotavirus A and Mammalian orthoreovirus. The genomic sequences of five mammal-associated and three tick-associated viruses were also present. Notably, a coronavirus related to HKU4-CoV, which was originally found in bats, was identified. The presence of these viruses in smuggled pangolins identifies these mammals as a potential source of emergent pathogenic viruses.

Long-range alignment of gold nanorods in electrospun polymer nano/microfibers.

In this study, a scalable fabrication technique for controlling and maintaining the nanoscale orientation of gold nanorods (GNRs) with long-range macroscale order has been achieved through electrospinning. The volume fraction of GNRs with an average aspect ratio of 3.1 is varied from 0.006 to 0.045 in aqueous poly(ethylene oxide) solutions to generate electrospun fibers possessing different GNR concentrations and measuring 40-3000 nm in diameter. The GNRs within these fibers exhibit excellent alignment with their longitudinal axis parallel to the fiber axis n. According to microscopy analysis, the average deviant angle between the GNR axis and n increases modestly from 3.8 to 13.3° as the fiber diameter increases. Complementary electron diffraction measurements confirm preferred orientation of the {100} GNR planes. Optical absorbance spectroscopy measurements reveal that the longitudinal surface plasmon resonance bands of the aligned GNRs depend on the polarization angle and that maximum extinction occurs when the polarization is parallel to n.

Discovery and Characterization of Actively Replicating DNA and Retro-Transcribing Viruses in Lower Vertebrate Hosts Based on RNA Sequencing.

In a previous study, a metatranscriptomics survey of RNA viruses in several important lower vertebrate host groups revealed huge viral diversity, transforming the understanding of the evolution of vertebrate-associated RNA virus groups. However, the diversity of the DNA and retro-transcribing viruses in these host groups was left uncharacterized. Given that RNA sequencing is capable of revealing viruses undergoing active transcription and replication, we collected previously generated datasets associated with lower vertebrate hosts, and searched them for DNA and retro-transcribing viruses. Our results revealed the complete genome, or "core gene sets", of 18 vertebrate-associated DNA and retro-transcribing viruses in cartilaginous fishes, ray-finned fishes, and amphibians, many of which had high abundance levels, and some of which showed systemic infections in multiple organs, suggesting active transcription or acute infection within the host. Furthermore, these new findings recharacterized the evolutionary history in the families Hepadnaviridae, Papillomaviridae, and Alloherpesviridae, confirming long-term virus-host codivergence relationships for these virus groups. Collectively, our results revealed reliable and sufficient information within metatranscriptomics sequencing to characterize not only RNA viruses, but also DNA and retro-transcribing viruses, and therefore established a key methodology that will help us to understand the composition and evolution of the total "infectome" within a diverse range of vertebrate hosts.