Loss to gain: pseudogenes in microorganisms, focusing on eubacteria, and their biological significance.

Pseudogenes are defined as "non-functional" copies of corresponding parent genes. The cognition of pseudogenes continues to be refreshed through accumulating and updating research findings. Previous studies have predominantly focused on mammals, but pseudogenes have received relatively less attention in the field of microbiology. Given the increasing recognition on the importance of pseudogenes, in this review, we focus on several aspects of microorganism pseudogenes, including their classification and characteristics, their generation and fate, their identification, their abundance and distribution, their impact on virulence, their ability to recombine with functional genes, the extent to which some pseudogenes are transcribed and translated, and the relationship between pseudogenes and viruses. By summarizing and organizing the latest research progress, this review will provide a comprehensive perspective and improved understanding on pseudogenes in microorganisms. KEY POINTS: • Concept, classification and characteristics, identification and databases, content, and distribution of microbial pseudogenes are presented. • How pseudogenization contribute to pathogen virulence is highlighted. • Pseudogenes with potential functions in microorganisms are discussed.

Viruses contribute to microbial diversification in the rumen ecosystem and are associated with certain animal production traits.

BACKGROUND: The rumen microbiome enables ruminants to digest otherwise indigestible feedstuffs, thereby facilitating the production of high-quality protein, albeit with suboptimal efficiency and producing methane. Despite extensive research delineating associations between the rumen microbiome and ruminant production traits, the functional roles of the pervasive and diverse rumen virome remain to be determined. RESULTS: Leveraging a recent comprehensive rumen virome database, this study analyzes virus-microbe linkages, at both species and strain levels, across 551 rumen metagenomes, elucidating patterns of microbial and viral diversity, co-occurrence, and virus-microbe interactions. Additionally, this study assesses the potential role of rumen viruses in microbial diversification by analyzing prophages found in rumen metagenome-assembled genomes. Employing CRISPR-Cas spacer-based matching and virus-microbe co-occurrence network analysis, this study suggests that the viruses in the rumen may regulate microbes at strain and community levels through both antagonistic and mutualistic interactions. Moreover, this study establishes that the rumen virome demonstrates responsiveness to dietary shifts and associations with key animal production traits, including feed efficiency, lactation performance, weight gain, and methane emissions. CONCLUSIONS: These findings provide a substantive framework for further investigations to unravel the functional roles of the virome in the rumen in shaping the microbiome and influencing overall animal production performance. Video Abstract.

Prevalence of Respiratory Viruses in Children With Acute Respiratory Infections in Shanghai, China, From 2013 to 2022.

BACKGROUND: A variety of viruses can cause acute respiratory infections (ARIs), resulting in a high disease burden worldwide. To explore the dominant viruses and their prevalence characteristics in children with ARIs, comprehensive surveillance was carried out in the Pudong New Area of Shanghai. METHODS: Between January 2013 and December 2022, the basic and clinical information, and respiratory tract specimens of 0-14 years old children with ARIs were collected in five sentinel hospitals in Shanghai Pudong. Each specimen was tested for eight respiratory viruses, and the positive rates of different age groups, case types (inpatient or outpatient) were analyzed. RESULTS: In our study, 30.67% (1294/4219) children with ARIs were positive for at least one virus. Influenza virus (IFV) was the most commonly detected respiratory virus (349/4219, 8.27%), followed by respiratory syncytial virus (RSV) (217/4219, 5.14%), para-influenza virus (PIV) (215/4219, 5.10%), and human coronavirus (HCoV, including 229E, OC43, NL63, and HKU1) (184/4219, 4.36%). IFV was the leading respiratory virus in outpatients aged 5-14 years (201/1673, 12.01%); RSV was the most prevalent respiratory virus in both inpatients (61/238, 25.63%) and outpatients (4/50, 8.00%) for ARI patients aged <6 months old. For PIV, HMPV, HCoV, and HRV, the risk of infection usually was higher among young children. Co-infection with more than two viruses was seen in 3.25% (137/4219). CONCLUSIONS: IFV and RSV played important roles in ARIs among children, but the risk populations were different. There are needs for targeted diagnosis and treatment and necessary immunization and non-pharmaceutical interventions.

A stochastic approach for co-evolution process of virus and human immune system.

Infectious diseases have long been a shaping force in human history, necessitating a comprehensive understanding of their dynamics. This study introduces a co-evolution model that integrates both epidemiological and evolutionary dynamics. Utilizing a system of differential equations, the model represents the interactions among susceptible, infected, and recovered populations for both ancestral and evolved viral strains. Methodologically rigorous, the model's existence and uniqueness have been verified, and it accommodates both deterministic and stochastic cases. A myriad of graphical techniques have been employed to elucidate the model's dynamics. Beyond its theoretical contributions, this model serves as a critical instrument for public health strategy, particularly predicting future outbreaks in scenarios where viral mutations compromise existing interventions.

Limited availability of methods for the detection of xenotransplantation-relevant viruses in veterinary laboratories.

BACKGROUND: The German Xenotransplantation Consortium is in the process to prepare a clinical trial application (CTA) on xenotransplantation of genetically modified pig hearts. In the CTA documents to the central and national regulatory authorities, that is, the European Medicines Agency (EMA) and the Paul Ehrlich Institute (PEI), respectively, it is required to list the potential zoonotic or xenozoonotic porcine microorganisms including porcine viruses as well as to describe methods of detection in order to prevent their transmission. The donor animals should be tested using highly sensitive detection systems. I would like to define a detection system as the complex including the actual detection methods, either PCR-based, cell-based, or immunological methods and their sensitivity, as well as sample generation, sample preparation, sample origin, time of sampling, and the necessary negative and positive controls. Lessons learned from the identification of porcine cytomegalovirus/porcine roseolovirus (PCMV/PRV) in the xenotransplanted heart in the recipient in the Baltimore study underline how important such systems are. The question is whether veterinary laboratories can supply such assays. METHODS: A total of 35 veterinary laboratories in Germany were surveyed for their ability to test for selected xenotransplantation-relevant viruses, including PCMV/PRV, hepatitis E virus, and porcine endogenous retrovirus-C (PERV-C). As comparison, data from Swiss laboratories and a laboratory in the USA were analyzed. Furthermore, we assessed which viruses were screened for in clinical and preclinical trials performed until now and during screening of pig populations. RESULTS: Of the nine laboratories that provided viral diagnostics, none of these included all potential viruses of concern, indeed, the most important assays confirmed in recent human trials, antibody detection of PCMV/PRV and screening for PERV-C were not available at all. The situation was similar in Swiss and US laboratories. Different viruses have been tested for in first clinical and preclinical trials performed in various countries. CONCLUSION: Based on these results it is necessary to establish special virological laboratories able to test for all xenotransplantation-relevant viruses using validated assays, optimally in the xenotransplantation centers.

A two-stage computational framework for identifying antiviral peptides and their functional types based on contrastive learning and multi-feature fusion strategy.

Antiviral peptides (AVPs) have shown potential in inhibiting viral attachment, preventing viral fusion with host cells and disrupting viral replication due to their unique action mechanisms. They have now become a broad-spectrum, promising antiviral therapy. However, identifying effective AVPs is traditionally slow and costly. This study proposed a new two-stage computational framework for AVP identification. The first stage identifies AVPs from a wide range of peptides, and the second stage recognizes AVPs targeting specific families or viruses. This method integrates contrastive learning and multi-feature fusion strategy, focusing on sequence information and peptide characteristics, significantly enhancing predictive ability and interpretability. The evaluation results of the model show excellent performance, with accuracy of 0.9240 and Matthews correlation coefficient (MCC) score of 0.8482 on the non-AVP independent dataset, and accuracy of 0.9934 and MCC score of 0.9869 on the non-AMP independent dataset. Furthermore, our model can predict antiviral activities of AVPs against six key viral families (Coronaviridae, Retroviridae, Herpesviridae, Paramyxoviridae, Orthomyxoviridae, Flaviviridae) and eight viruses (FIV, HCV, HIV, HPIV3, HSV1, INFVA, RSV, SARS-CoV). Finally, to facilitate user accessibility, we built a user-friendly web interface deployed at https://awi.cuhk.edu.cn/∼dbAMP/AVP/.

Epidemiology and Clinical impact of single and multi-viral respiratory infections in post-pandemic era.

Acute respiratory tract infections (ARI) are common diseases in children and adults and could cause severe infections in high-risk patients, like the immunocompromised and elderly, and are the leading cause of morbidity, hospitalization and mortality. This study aimed to explore the prevalence of respiratory viruses and the clinical impact of single- and multi-infection among hospitalized patients in various age groups. 3578 nasopharyngeal swabs (NPS) were analyzed for pathogen detection of acute respiratory tract infections. 930 out of 3578 NPS were diagnosed positive for at least one respiratory virus. The distribution of viral infections, prevalence and pathogen, differed significantly among age groups. Most RTI are observed in the age group over 65 years (50.6%) with a high SARS-CoV2 prevalence, following by group <5 years (25.6%), where the most frequently detected viruses were RSV, Rhinovirus, FluA-H3, MPV, and AdV. The co-infection rate also varies according to age and, in some cases, especially in older adults, could have severe clinical impact. This study emphasizes that it is important to know and analyze, in all age groups of hospitalized patients, the epidemiology of respiratory viruses, the prevalence of coinfections, and the clinical impact of various pathogens. Furthermore, in a clinical setting, the rapid diagnosis of respiratory infections by means of molecular tests is crucial not only to avoid hospital outbreaks, but also to allow early and optimal treatment to reduce morbidity and mortality.

Epidemiology and molecular characterization of respiratory viruses at the end of COVID-19 pandemic in Lombardy, Northern Italy.

The COVID-19 pandemic forced the adoption of non-pharmaceutical interventions (NPIs) which influenced the circulation of other respiratory pathogens, such as Influenza virus (FLU), Parainfluenza virus (PIV), Respiratory Syncytial virus (RSV), Rhinovirus (RV), Enterovirus (EV), Adenovirus (AdV), Human Metapneumovirus (hMPV), and Human Coronavirus (CoV). The aim of the current study was to investigate how, with the end of the pandemic, the withdrawal of the NPIs impacted on the circulation and distribution of common respiratory viruses. The analyzed samples were collected from June 2021 to March 2023 (post-pandemic period) and compared to ones from the pandemic period. Nucleic acid detection of all respiratory viruses was performed by multiplex real time Polymerase Chain Reaction (PCR) and sequencing was conducted by Next Generation Sequencing (NGS) technique. Our analysis shows that the NPIs adopted against SARS-CoV-2 were also effective in controlling the spread of other respiratory viruses. Moreover, we documented how RV/EVs were the most commonly identified species, with the more abundant strains represented by Coxsackievirus (CV)-A/B and RV-A/C. RV/EVs were also detected in some co-infection cases; in particular, the majority of co-infections concerned CV-B/RV-A, CV-B/ECHO. Given the pandemic potential of respiratory viruses, accurate molecular screening is essential for a proper surveillance and prevention strategy.

A novel approach to exploring the dark genome and its application to mapping of the vertebrate virus fossil record.

BACKGROUND: Genomic regions that remain poorly understood, often referred to as the dark genome, contain a variety of functionally relevant and biologically informative features. These include endogenous viral elements (EVEs)-virus-derived sequences that can dramatically impact host biology and serve as a virus fossil record. In this study, we introduce a database-integrated genome screening (DIGS) approach to investigate the dark genome in silico, focusing on EVEs found within vertebrate genomes. RESULTS: Using DIGS on 874 vertebrate genomes, we uncover approximately 1.1 million EVE sequences, with over 99% originating from endogenous retroviruses or transposable elements that contain EVE DNA. We show that the remaining 6038 sequences represent over a thousand distinct horizontal gene transfer events across 10 virus families, including some that have not previously been reported as EVEs. We explore the genomic and phylogenetic characteristics of non-retroviral EVEs and determine their rates of acquisition during vertebrate evolution. Our study uncovers novel virus diversity, broadens knowledge of virus distribution among vertebrate hosts, and provides new insights into the ecology and evolution of vertebrate viruses. CONCLUSIONS: We comprehensively catalog and analyze EVEs within 874 vertebrate genomes, shedding light on the distribution, diversity, and long-term evolution of viruses and reveal their extensive impact on vertebrate genome evolution. Our results demonstrate the power of linking a relational database management system to a similarity search-based screening pipeline for in silico exploration of the dark genome.

Evaluation of the Impact of Concentration and Extraction Methods on the Targeted Sequencing of Human Viruses from Wastewater.

Sequencing human viruses in wastewater is challenging due to their low abundance compared to the total microbial background. This study compared the impact of four virus concentration/extraction methods (Innovaprep, Nanotrap, Promega, and Solids extraction) on probe-capture enrichment for human viruses followed by sequencing. Different concentration/extraction methods yielded distinct virus profiles. Innovaprep ultrafiltration (following solids removal) had the highest sequencing sensitivity and richness, resulting in the successful assembly of several near-complete human virus genomes. However, it was less sensitive in detecting SARS-CoV-2 by digital polymerase chain reaction (dPCR) compared to Promega and Nanotrap. Across all preparation methods, astroviruses and polyomaviruses were the most highly abundant human viruses, and SARS-CoV-2 was rare. These findings suggest that sequencing success can be increased using methods that reduce nontarget nucleic acids in the extract, though the absolute concentration of total extracted nucleic acid, as indicated by Qubit, and targeted viruses, as indicated by dPCR, may not be directly related to targeted sequencing performance. Further, using broadly targeted sequencing panels may capture viral diversity but risks losing signals for specific low-abundance viruses. Overall, this study highlights the importance of aligning wet lab and bioinformatic methods with specific goals when employing probe-capture enrichment for human virus sequencing from wastewater.

Considerations and Opportunities for Probe Capture Enrichment Sequencing of Emerging Viruses from Wastewater.

Until recently, wastewater-based monitoring for pathogens of public health concern primarily used PCR-based quantification methods and targeted sequencing for specific pathogens (e.g., SARS-CoV-2). In the past three years, researchers have expanded sequencing to monitor a broad range of pathogens, applying probe capture enrichment to wastewater. The goals of those studies included (1) monitoring and expanding fundamental knowledge of disease dynamics for known pathogens and (2) evaluating the potential for early detection of emerging diseases resulting from zoonotic spillover or novel viral variants. Several studies using off-the-shelf probe panels designed for clinical and environmental surveillance reported that enrichment increased virus relative abundance but did not recover complete genomes for most nonenteric viruses. Based on our experience and recent results reported by others using these panels for wastewater, clinical, and synthetic samples, we discuss challenges and technical factors that affect the rates of false positive and false negative results. We identify trade-offs and opportunities throughout the workflow, including in wastewater sample processing, probe panel design, and bioinformatic analysis. We suggest tailored methods of virus concentration and background removal, carefully designed probe panels, and multithresholded bioinformatics analysis.

Inactivation of microorganisms on fabrics using plasma-activated nebulized mist driven by different plasma gases.

The disinfection of fabrics is crucial in preventing the spread of infectious diseases caused by pathogenic microorganisms to maintain public health. A previous study proved that plasma-activated nebulized mist (PANM) could effectively inactivate microorganisms both in aerosol and attached to the surface. In this study, the PANM driven by different plasma gases were employed to inactivate microorganisms on diverse fabrics. The PANM could efficiently inactivate a variety of microorganisms, including bacteria, fungi, and viruses, contaminating different fabrics, and even across covering layers of different fabrics. The mites residing on the cotton fabrics both uncovered and covered with various types of fabrics were also effectively inactivated by the PANM. After 30 times repeated treatments of the PANM, notable changes were observed in the color of several fabrics while the structural integrity and mechanical strength of the fabrics were unaffected and maintained similarly to the untreated fabrics with slight changes in elemental composition. Additionally, only trace amounts of nitrate remained in the fabrics after the PANM treatment. Therefore, the PANM treatment supplied an efficient, broad-spectrum, and environmentally friendly strategy for industrial and household disinfection of fabrics.

Epidemiological and etiological characteristics of 1266 patients with severe acute respiratory infection in central China, 2018-2020: a retrospective survey.

BACKGROUND: Severe acute respiratory infection (SARI), a significant global health concern, imposes a substantial disease burden. In China, there is inadequate data concerning the monitoring of respiratory pathogens, particularly bacteria, among patients with SARI. Therefore, this study aims to delineate the demographic, epidemiological, and aetiological characteristics of hospitalised SARI patients in Central China between 2018 and 2020. METHODS: Eligible patients with SARI admitted to the First Affiliated Hospital of Zhengzhou University between 1 January 2018 and 31 December 2020 were included in this retrospective study. Within the first 24 h of admission, respiratory (including sputum, nasal/throat swabs, bronchoalveolar lavage fluid, thoracocentesis fluid, etc.), urine, and peripheral blood specimens were collected for viral and bacterial testing. A multiplex real-time polymerase chain reaction (PCR) diagnostic approach was used to identify human influenza virus, respiratory syncytial virus, parainfluenza virus, adenovirus, human bocavirus, human coronavirus, human metapneumovirus, and rhinovirus. Bacterial cultures of respiratory specimens were performed with a particular focus on pathogenic microorganisms, including S. pneumoniae, S. aureus, K. pneumoniae, P. aeruginosa, Strep A, H. influenzae, A. baumannii, and E. coli. In cases where bacterial culture results were negative, nucleic acid extraction was performed for PCR to assay for the above-mentioned eight bacteria, as well as L. pneumophila and M. pneumoniae. Additionally, urine specimens were exclusively used to detect Legionella antigens. Furthermore, epidemiological, demographic, and clinical data were obtained from electronic medical records. RESULTS: The study encompassed 1266 patients, with a mean age of 54 years, among whom 61.6% (780/1266) were males, 61.4% (778/1266) were farmers, and 88.8% (1124/1266) sought medical treatment in 2020. Moreover, 80.3% (1017/1266) were housed in general wards. The most common respiratory symptoms included fever (86.8%, 1122/1266) and cough (77.8%, 986/1266). Chest imaging anomalies were detected in 62.6% (792/1266) of cases, and 58.1% (736/1266) exhibited at least one respiratory pathogen, with 28.5% (361/1266) having multiple infections. Additionally, 95.7% (1212/1266) of the patients were from Henan Province, with the highest proportion (38.3%, 486/1266) falling in the 61-80 years age bracket, predominantly (79.8%, 1010/1266) seeking medical aid in summer and autumn. Bacterial detection rate (39.0%, 495/1266) was higher than viral detection rate (36.9%, 468/1266), with the primary pathogens being influenza virus (13.8%, 175/1266), K. pneumoniae (10.0%, 127/1266), S. pneumoniae (10.0%, 127/1266), adenovirus (8.2%, 105/1266), P. aeruginosa (8.2%, 105/1266), M. pneumoniae (7.8%, 100/1266), and respiratory syncytial virus (7.7%, 98/1266). During spring and winter, there was a significant prevalence of influenza virus and human coronavirus, contrasting with the dominance of parainfluenza viruses in summer and autumn. Respiratory syncytial virus and rhinovirus exhibited higher prevalence across spring, summer, and winter. P. aeruginosa, K. pneumoniae, and M. pneumoniae were identified at similar rates throughout all seasons without distinct spikes in prevalence. However, S. pneumoniae showed a distinctive pattern with a prevalence that doubled during summer and winter. Moreover, the positive detection rates of various other viruses and bacteria were lower, displaying a comparatively erratic prevalence trend. Among patients admitted to the intensive care unit, the predominant nosocomial bacteria were K. pneumoniae (17.2%, 43/249), A. baumannii (13.6%, 34/249), and P. aeruginosa (12.4%, 31/249). Conversely, in patients from general wards, predominant pathogens included influenza virus (14.8%, 151/1017), S. pneumoniae (10.4%, 106/1017), and adenovirus (9.3%, 95/1017). Additionally, paediatric patients exhibited significantly higher positive detection rates for influenza virus (23.9%, 11/46) and M. pneumoniae (32.6%, 15/46) compared to adults and the elderly. Furthermore, adenovirus (10.0%, 67/669) and rhinovirus (6.4%, 43/669) were the primary pathogens in adults, while K. pneumoniae (11.8%, 65/551) and A. baumannii (7.1%, 39/551) prevailed among the elderly, indicating significant differences among the three age groups. DISCUSSION: In Central China, among patients with SARI, the prevailing viruses included influenza virus, adenovirus, and respiratory syncytial virus. Among bacteria, K. pneumoniae, S. pneumoniae, P. aeruginosa, and M. pneumoniae were frequently identified, with multiple infections being very common. Additionally, there were substantial variations in the pathogen spectrum compositions concerning wards and age groups among patients. Consequently, this study holds promise in offering insights to the government for developing strategies aimed at preventing and managing respiratory infectious diseases effectively.

Therapeutic bacteria and viruses to combat cancer: double-edged sword in cancer therapy: new insights for future.

Cancer, ranked as the second leading cause of mortality worldwide, leads to the death of approximately seven million people annually, establishing itself as one of the most significant health challenges globally. The discovery and identification of new anti-cancer drugs that kill or inactivate cancer cells without harming normal and healthy cells and reduce adverse effects on the immune system is a potential challenge in medicine and a fundamental goal in Many studies. Therapeutic bacteria and viruses have become a dual-faceted instrument in cancer therapy. They provide a promising avenue for cancer treatment, but at the same time, they also create significant obstacles and complications that contribute to cancer growth and development. This review article explores the role of bacteria and viruses in cancer treatment, examining their potential benefits and drawbacks. By amalgamating established knowledge and perspectives, this review offers an in-depth examination of the present research landscape within this domain and identifies avenues for future investigation.

Nanopore and Illumina sequencing reveal different viral populations from human gut samples.

The advent of viral metagenomics, or viromics, has improved our knowledge and understanding of global viral diversity. High-throughput sequencing technologies enable explorations of the ecological roles, contributions to host metabolism, and the influence of viruses in various environments, including the human intestinal microbiome. However, bacterial metagenomic studies frequently have the advantage. The adoption of advanced technologies like long-read sequencing has the potential to be transformative in refining viromics and metagenomics. Here, we examined the effectiveness of long-read and hybrid sequencing by comparing Illumina short-read and Oxford Nanopore Technology (ONT) long-read sequencing technologies and different assembly strategies on recovering viral genomes from human faecal samples. Our findings showed that if a single sequencing technology is to be chosen for virome analysis, Illumina is preferable due to its superior ability to recover fully resolved viral genomes and minimise erroneous genomes. While ONT assemblies were effective in recovering viral diversity, the challenges related to input requirements and the necessity for amplification made it less ideal as a standalone solution. However, using a combined, hybrid approach enabled a more authentic representation of viral diversity to be obtained within samples.

Virus-Induced Epilepsy vs. Epilepsy Patients Acquiring Viral Infection: Unravelling the Complex Relationship for Precision Treatment.

The intricate relationship between viruses and epilepsy involves a bidirectional interaction. Certain viruses can induce epilepsy by infecting the brain, leading to inflammation, damage, or abnormal electrical activity. Conversely, epilepsy patients may be more susceptible to viral infections due to factors, such as compromised immune systems, anticonvulsant drugs, or surgical interventions. Neuroinflammation, a common factor in both scenarios, exhibits onset, duration, intensity, and consequence variations. It can modulate epileptogenesis, increase seizure susceptibility, and impact anticonvulsant drug pharmacokinetics, immune system function, and brain physiology. Viral infections significantly impact the clinical management of epilepsy patients, necessitating a multidisciplinary approach encompassing diagnosis, prevention, and treatment of both conditions. We delved into the dual dynamics of viruses inducing epilepsy and epilepsy patients acquiring viruses, examining the unique features of each case. For virus-induced epilepsy, we specify virus types, elucidate mechanisms of epilepsy induction, emphasize neuroinflammation's impact, and analyze its effects on anticonvulsant drug pharmacokinetics. Conversely, in epilepsy patients acquiring viruses, we detail the acquired virus, its interaction with existing epilepsy, neuroinflammation effects, and changes in anticonvulsant drug pharmacokinetics. Understanding this interplay advances precision therapies for epilepsy during viral infections, providing mechanistic insights, identifying biomarkers and therapeutic targets, and supporting optimized dosing regimens. However, further studies are crucial to validate tools, discover new biomarkers and therapeutic targets, and evaluate targeted therapy safety and efficacy in diverse epilepsy and viral infection scenarios.

CNS Viral Infections-What to Consider for Improving Drug Treatment: A Plea for Using Mathematical Modeling Approaches.

Neurotropic viruses may cause meningitis, myelitis, encephalitis, or meningoencephalitis. These inflammatory conditions of the central nervous system (CNS) may have serious and devastating consequences if not treated adequately. In this review, we first summarize how neurotropic viruses can enter the CNS by (1) crossing the blood-brain barrier or blood-cerebrospinal fluid barrier; (2) invading the nose via the olfactory route; or (3) invading the peripheral nervous system. Neurotropic viruses may then enter the intracellular space of brain cells via endocytosis and/or membrane fusion. Antiviral drugs are currently used for different viral CNS infections, even though their use and dosing regimens within the CNS, with the exception of acyclovir, are minimally supported by clinical evidence. We therefore provide considerations to optimize drug treatment(s) for these neurotropic viruses. Antiviral drugs should cross the blood-brain barrier/blood cerebrospinal fluid barrier and pass the brain cellular membrane to inhibit these viruses inside the brain cells. Some antiviral drugs may also require intracellular conversion into their active metabolite(s). This illustrates the need to better understand these mechanisms because these processes dictate drug exposure within the CNS that ultimately determine the success of antiviral drugs for CNS infections. Finally, we discuss mathematical model-based approaches for optimizing antiviral treatments. Thereby emphasizing the potential of CNS physiologically based pharmacokinetic models because direct measurement of brain intracellular exposure in living humans faces ethical restrictions. Existing physiologically based pharmacokinetic models combined with in vitro pharmacokinetic/pharmacodynamic information can be used to predict drug exposure and evaluate efficacy of antiviral drugs within the CNS, to ultimately optimize the treatments of CNS viral infections.

Advances in rapid point-of-care virus testing.

Outbreaks of viral diseases seriously jeopardize people's health and cause huge economic losses. At the same time, virology provides a new perspective for biology, molecular biology and cancer research, and it is important to study the discovered viruses with potential applications. Therefore, the development of immediate and rapid viral detection methods for the prevention and treatment of viral diseases as well as the study of viruses has attracted extensive attention from scientists. With the continuous progress of science and technology, especially in the field of bioanalysis, a series of new detection techniques have been applied to the on-site rapid detection of viruses, which has become a powerful approach for human beings to fight against viruses. In this paper, the latest research progress of rapid point-of-care detection of viral nucleic acids, antigens and antibodies is presented. In addition, the advantages and disadvantages of these technologies are discussed from the perspective of practical application requirements. Finally, the problems and challenges faced by rapid viral detection methods and their development prospects are discussed.

VirusPredictor: XGBoost-based software to predict virus-related sequences in human data.

MOTIVATION: Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data. RESULTS: We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150-350 (Illumina short reads), 850-950 (Sanger sequencing data), and 2000-5000 bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to >0.98 when query sequences increased from 150-350 to >850 bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. ∼1000 bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients' unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions. AVAILABILITY AND IMPLEMENTATION: www.dllab.org/software/VirusPredictor.html.