Neurotropic pathogens, notably, herpesviruses, have been associated with significant neuropsychiatric effects. As a group, these pathogens can exploit molecular mimicry mechanisms to manipulate the host central nervous system to their advantage. Here, we present a systematic computational approach that may ultimately be used to unravel protein-protein interactions and molecular mimicry processes that have not yet been solved experimentally. Toward this end, we validate this approach by replicating a set of pre-existing experimental findings that document the structural and functional similarities shared by the human cytomegalovirus-encoded UL144 glycoprotein and human tumor necrosis factor receptor superfamily member 14 (TNFRSF14). We began with a thorough exploration of the Homo sapiens protein database using the Basic Local Alignment Search Tool (BLASTx) to identify proteins sharing sequence homology with UL144. Subsequently, we used AlphaFold2 to predict the independent three-dimensional structures of UL144 and TNFRSF14. This was followed by a comprehensive structural comparison facilitated by Distance-Matrix Alignment and Foldseek. Finally, we used AlphaFold-multimer and PPIscreenML to elucidate potential protein complexes and confirm the predicted binding activities of both UL144 and TNFRSF14. We then used our in silico approach to replicate the experimental finding that revealed TNFRSF14 binding to both B- and T-lymphocyte attenuator (BTLA) and glycoprotein domain and UL144 binding to BTLA alone. This computational framework offers promise in identifying structural similarities and interactions between pathogen-encoded proteins and their host counterparts. This information will provide valuable insights into the cognitive mechanisms underlying the neuropsychiatric effects of viral infections.
- MeSH
- Cognition physiology MeSH
- Humans MeSH
- Molecular Mimicry * MeSH
- Models, Molecular MeSH
- Amino Acid Sequence MeSH
- Protein Binding MeSH
- Viral Proteins metabolism chemistry MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Metagenomics is gradually being implemented for diagnosing infectious diseases. However, in-depth protocol comparisons for viral detection have been limited to individual sets of experimental workflows and laboratories. In this study, we present a benchmark of metagenomics protocols used in clinical diagnostic laboratories initiated by the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS). A mock viral reference panel was designed to mimic low biomass clinical specimens. The panel was used to assess the performance of twelve metagenomic wet lab protocols currently in use in the diagnostic laboratories of participating ENNGS member institutions. Both Illumina and Nanopore, shotgun and targeted capture probe protocols were included. Performance metrics sensitivity, specificity, and quantitative potential were assessed using a central bioinformatics pipeline. Overall, viral pathogens with loads down to 104 copies/ml (corresponding to CT values of 31 in our PCR assays) were detected by all the evaluated metagenomic wet lab protocols. In contrast, lower abundant mixed viruses of CT values of 35 and higher were detected only by a minority of the protocols. Considering the reference panel as the gold standard, optimal thresholds to define a positive result were determined per protocol, based on the horizontal genome coverage. Implementing these thresholds, sensitivity and specificity of the protocols ranged from 67 to 100 % and 87 to 100 %, respectively. A variety of metagenomic protocols are currently in use in clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implying the need for standardization of metagenomic analysis for use in clinical settings.
- MeSH
- Benchmarking * MeSH
- Humans MeSH
- Metagenomics * methods standards MeSH
- Sensitivity and Specificity * MeSH
- Virus Diseases diagnosis virology MeSH
- Viruses * genetics classification isolation & purification MeSH
- Computational Biology methods MeSH
- High-Throughput Nucleotide Sequencing methods standards MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
The volume of nucleic acid sequence data has exploded recently, amplifying the challenge of transforming data into meaningful information. Processing data can require an increasingly complex ecosystem of customized tools, which increases difficulty in communicating analyses in an understandable way yet is of sufficient detail to enable informed decisions or repeats. This can be of particular interest to institutions and companies communicating computations in a regulatory environment. BioCompute Objects (BCOs; an instance of pipeline documentation that conforms to the IEEE 2791-2020 standard) were developed as a standardized mechanism for analysis reporting. A suite of BCOs is presented, representing interconnected elements of a computation modeled after those that might be found in a regulatory submission but are shared publicly - in this case a pipeline designed to identify viral contaminants in biological manufacturing, such as for vaccines.
- MeSH
- Workflow MeSH
- Vaccines * MeSH
- Computational Biology * MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Publication type
- Journal Article MeSH
The eukaryotic phylum Parabasalia is composed primarily of anaerobic, endobiotic organisms such as the veterinary parasite Tritrichomonas foetus and the human parasite Trichomonas vaginalis, the latter causing the most prevalent, non-viral, sexually transmitted disease world-wide. Although a parasitic lifestyle is generally associated with a reduction in cell biology, T. vaginalis provides a striking counter-example. The 2007 T. vaginalis genome paper reported a massive and selective expansion of encoded proteins involved in vesicle trafficking, particularly those implicated in the late secretory and endocytic systems. Chief amongst these were the hetero-tetrameric adaptor proteins or 'adaptins', with T. vaginalis encoding ∼3.5 times more such proteins than do humans. The provenance of such a complement, and how it relates to the transition from a free-living or endobiotic state to parasitism, remains unclear. In this study, we performed a comprehensive bioinformatic and molecular evolutionary investigation of the heterotetrameric cargo adaptor-derived coats, comparing the molecular complement and evolution of these proteins between T. vaginalis, T. foetus and the available diversity of endobiotic parabasalids. Notably, with the recent discovery of Anaeramoeba spp. as the free-living sister lineage to all parabasalids, we were able to delve back to time points earlier in the lineage's history than ever before. We found that, although T. vaginalis still encodes the most HTAC subunits amongst parabasalids, the duplications giving rise to the complement took place more deeply and at various stages across the lineage. While some duplications appear to have convergently shaped the parasitic lineages, the largest jump is in the transition from free-living to endobiotic lifestyle with both gains and losses shaping the encoded complement. This work details the evolution of a cellular system across an important lineage of parasites and provides insight into the evolutionary dynamics of an example of expansion of protein machinery, counter to the more common trends observed in many parasitic systems.
Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.
- MeSH
- Humans MeSH
- Pandemics MeSH
- Virus Diseases * drug therapy genetics MeSH
- Computational Biology * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Throughout the last few decades, humans have been fascinated by technological innovation. To solve the universal healthcare challenges, tech companies provided a torrent of innovation. The new coronavirus has established a significant foothold on the world, which is being combated via digital interventions across infected geographical borders and territories. COVID-19 reactions can be coordinated using digital technology in a cascade that spans from the healthcare care facility to the pending viral epicenter’s exterior. As evidence, there are incidents of medical robotics, surveillance drones, as well as the internet - of - things. COVID-19 diagnostics are based on PCR tests and medical imaging. At a clinical accuracy of percent, computed tomography assisted in correcting the accuracy variance of PCR testing. COVID-19 reactions can be independent thanks to artificial intelligence. When properly sourced, technology may be a never-ending system of invention and potential. Scientists can use technology to address global issues, pushing the boundaries of concrete possibility. Digital interventions have improved COVID-19 responses, emphasised the need of medical imaging throughout the outbreak, and exposed healthcare personnel to the possibility of contactless treatment.
Spontaneous preterm birth is a serious medical condition responsible for substantial perinatal morbidity and mortality. Its phenotypic characteristics, preterm labor with intact membranes (PTL) and preterm premature rupture of the membranes (PPROM), are associated with significantly increased risks of neurological and behavioral alterations in childhood and later life. Recognizing the inflammatory milieu associated with PTL and PPROM, here, we examined expression signatures of placental tryptophan metabolism, an important pathway in prenatal brain development and immunotolerance. The study was performed in a well-characterized clinical cohort of healthy term pregnancies (n = 39) and 167 preterm deliveries (PTL, n = 38 and PPROM, n = 129). Within the preterm group, we then investigated potential mechanistic links between differential placental tryptophan pathway expression, preterm birth and both intra-amniotic markers (such as amniotic fluid interleukin-6) and maternal inflammatory markers (such as maternal serum C-reactive protein and white blood cell count). We show that preterm birth is associated with significant changes in placental tryptophan metabolism. Multifactorial analysis revealed similarities in expression patterns associated with multiple phenotypes of preterm delivery. Subsequent correlation computations and mediation analyses identified links between intra-amniotic and maternal inflammatory markers and placental serotonin and kynurenine pathways of tryptophan catabolism. Collectively, the findings suggest that a hostile inflammatory environment associated with preterm delivery underlies the mechanisms affecting placental endocrine/transport functions and may contribute to disruption of developmental programming of the fetal brain.
- MeSH
- Biomarkers MeSH
- Humans MeSH
- Metabolic Networks and Pathways MeSH
- Disease Susceptibility MeSH
- Placenta metabolism MeSH
- Premature Birth diagnosis etiology metabolism MeSH
- Gene Expression Regulation MeSH
- Risk Factors MeSH
- Gene Expression Profiling MeSH
- Pregnancy MeSH
- Transcriptome * MeSH
- Tryptophan metabolism MeSH
- Computational Biology methods MeSH
- Pregnancy Outcome MeSH
- Inflammation complications etiology MeSH
- Check Tag
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Rabies is also known as Rhabdoviruses. It is a preventable viral disease transmitted through the bite of a rabid animal. It belongs to the family Rhabdoviridae order mononegavirals. Rabies infects the CNS of mammals, ultimately causing disease in the brain and death. Rhabdoviruse is approximately 180nm long, 70nm wide and 400 trimeric spikes which are tightly arranged on the surface of the virus. The genome encodes 5 proteins designated as nucleoprotein(N), phosphoprotein(P), matrix protein(M), glycoprotein(G) and a viral RNA polymerase protein(L). The clinical course of rabies occurs in five stages. Stage 1 is the incubation period, stage 2 is the prodromal period, stage 3 is the neurological period, stage 4 is coma stage 5 occurs infrequently is recovery. The current study determines the biological process of a virus against(Homosapiens). Here we retrieved an interaction network of rabies virus-host(homosapiens) from astring virus database. This network was further be analyzed and the resulted network was clustered. By performing gene ontology analysis for the clustered proteins we, therefore, identified proteins which has a highly effective role in cellular processes and viral infection mechanisms. Hence this study helps to understand the various proteins that can be targeted for further development in drug discovery and also in the prevention of this disease.
Influenza A virus (IAV) infection is a serious public health problem all over the world. This virus belongs to the family Orthomyxoviridae and this is the only species of the virus occurring in the genus Alphainfluenzavirus. IAV consists of ss negative sense RNA as its genetic material and its genome comprises eight segments of viral RNA and each segment is complexed with trimeric viral polymerase proteins and nucleoprotein. IAV causes zoonotic infections in birds and severe respiratory infections in humans. The current study determines the various proteins in the biological processes of Influenza A virus in the host (Homosapiens). In this experiment, we retrieved a protein interaction network of Influenza A virus with Homosapiens. To this network cluster analysis was performed which resulted in 6 clusters. Further, gene enrichment analysis was performed for the clustered proteins using the Panther GO database and we, therefore, identified proteins that have a highly effective role in cellular processes and viral infection mechanisms. Hence this study helps to understand the various proteins that can be targeted for further development in drug discovery and also in the prevention of this disease
BACKGROUND: Rhinosinusitis is an inflammation of the sinonasal cavity which affects roughly one in seven people per year. Acute rhinosinusitis (ARS) is mostly, apart from allergic etiology, caused by a viral infection and, in some cases (30-50%), by a bacterial superinfection. Antibiotics, indicated only in rare cases according to EPOS guidelines, are nevertheless prescribed in more than 80% of ARS cases, which increases the resistant bacterial strains in the population. METHODS: We have designed a clinical decision support system (CDSS), RHINA, based on a web application created in HTML 5, using JavaScript, jQuery, CCS3 and PHP scripting language. The presented CDSS RHINA helps general physicians to decide whether or not to prescribe antibiotics in patients with rhinosinusitis. RESULTS: In a retrospective study of a total of 1465 patients with rhinosinusitis, the CDSS RHINA presented a 90.2% consistency with the diagnosis and treatment made by the ENT specialist. CONCLUSION: Patients assessed with the assistance of our CDSS RHINA would decrease the over-prescription of antibiotics, which in turn would help to reduce the bacterial resistance to the most commonly prescribed antibiotics.
- MeSH
- Chronic Disease MeSH
- Humans MeSH
- Retrospective Studies MeSH
- Rhinitis * diagnosis drug therapy MeSH
- Sinusitis * diagnosis drug therapy MeSH
- Decision Support Systems, Clinical * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
