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.

• Keywords
• Bioinformatics, Cognition, Mitochondria, Psychiatry, Virus,
• 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
• Names of Substances
• Viral Proteins 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.

• Keywords
• Benchmark, Clinical viral metagenomics, Wet lab protocols,
• 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
• Research Support, Non-U.S. Gov't 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.

• Keywords
• BioCompute, HTS, adventitious virus detection, metagenomics, next generation sequencing, vaccine,
• MeSH
• Workflow MeSH
• Vaccines * MeSH
• Computational Biology * MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Vaccines * MeSH

Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.

• Keywords
• Bioinformatic, Genomic, Plant, Variant, Virus,
• MeSH
• Genome, Viral genetics   MeSH
• Polymorphism, Single Nucleotide * genetics   MeSH
• Humans MeSH
• Computational Biology MeSH
• High-Throughput Nucleotide Sequencing * MeSH
• Knowledge MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't 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.

• Keywords
• COPI, Clathrin, Evolutionary cell biology, Membrane trafficking, Metamonada, Trichomonas vaginalis,
• MeSH
• Humans MeSH
• Parabasalidea * MeSH
• Parasites * MeSH
• Trichomonas vaginalis * genetics   MeSH
• Tritrichomonas foetus * genetics   MeSH
• Computational Biology MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

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.

• Keywords
• artificial intelligence, drug discovery, vaccine development, viral informatics, viral pandemic,
• 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

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
• Names of Substances
• Biomarkers MeSH
• Tryptophan MeSH

The holistic characterisation of the human internal chemical exposome using high-resolution mass spectrometry (HRMS) would be a step forward to investigate the environmental ætiology of chronic diseases with an unprecedented precision. HRMS-based methods are currently operational to reproducibly profile thousands of endogenous metabolites as well as externally-derived chemicals and their biotransformation products in a large number of biological samples from human cohorts. These approaches provide a solid ground for the discovery of unrecognised biomarkers of exposure and metabolic effects associated with many chronic diseases. Nevertheless, some limitations remain and have to be overcome so that chemical exposomics can provide unbiased detection of chemical exposures affecting disease susceptibility in epidemiological studies. Some of these limitations include (i) the lack of versatility of analytical techniques to capture the wide diversity of chemicals; (ii) the lack of analytical sensitivity that prevents the detection of exogenous (and endogenous) chemicals occurring at (ultra) trace levels from restricted sample amounts, and (iii) the lack of automation of the annotation/identification process. In this article, we discuss a number of technological and methodological limitations hindering applications of HRMS-based methods and propose initial steps to push towards a more comprehensive characterisation of the internal chemical exposome. We also discuss other challenges including the need for harmonisation and the difficulty inherent in assessing the dynamic nature of the internal chemical exposome, as well as the need for establishing a strong international collaboration, high level networking, and sustainable research infrastructure. A great amount of research, technological development and innovative bio-informatics tools are still needed to profile and characterise the "invisible" (not profiled), "hidden" (not detected) and "dark" (not annotated) components of the internal chemical exposome and concerted efforts across numerous research fields are paramount.

• Keywords
• EWAS, Exposome, High-Resolution Mass Spectrometry, Internal chemical exposome, Non-targeted analysis, Suspect screening,
• MeSH
• Biomarkers MeSH
• Exposome * MeSH
• Mass Spectrometry MeSH
• Humans MeSH
• Environmental Exposure analysis   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Biomarkers MeSH

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.

• Keywords
• Antibiotic resistance, Clinical decision support system, EPOS, Rhinosinusitis,
• 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

Marine oomycetes have recently been shown to be concurrently infected by (-)ssRNA viruses of the order Bunyavirales. In this work, even higher virus variability was found in a single isolate of Phytophthora condilina, a recently described member of Phytophthora phylogenetic Clade 6a, which was isolated from brackish estuarine waters in southern Portugal. Using total and small RNA-seq the full RdRp of 13 different potential novel bunya-like viruses and two complete toti-like viruses were detected. All these viruses were successfully confirmed by reverse transcription polymerase chain reaction (RT-PCR) using total RNA as template, but complementarily one of the toti-like and five of the bunya-like viruses were confirmed when dsRNA was purified for RT-PCR. In our study, total RNA-seq was by far more efficient for de novo assembling of the virus sequencing but small RNA-seq showed higher read numbers for most viruses. Two main populations of small RNAs (21 nts and 25 nts-long) were identified, which were in accordance with other Phytophthora species. To the best of our knowledge, this is the first study using small RNA sequencing to identify viruses in Phytophthora spp.

• Keywords
• Bunyavirales, RdRp, Totiviridae, dsRNA, estuaries, mycovirus, oomycete,
• MeSH
• Phylogeny MeSH
• Genome, Viral MeSH
• RNA, Small Untranslated genetics   MeSH
• Open Reading Frames MeSH
• Phytophthora virology   MeSH
• RNA, Viral genetics   MeSH
• RNA Viruses classification   genetics   isolation & purification   MeSH
• Sequence Analysis, DNA MeSH
• Sequence Analysis, RNA * MeSH
• RNA-Seq MeSH
• Virus Diseases virology   MeSH
• Computational Biology MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Portugal MeSH
• Names of Substances
• RNA, Small Untranslated MeSH
• RNA, Viral MeSH