Disease X Testing: The results of an international external quality assessment exercise

The United Nations Secretary-General Mechanism (UNSGM) for investigation of the alleged use of chemical and biological weapons is the only established international mechanism of this type under the UN. The UNGSM may launch an international investigation, relying on a roster of expert consultants, qualified experts, and analytical laboratories nominated by the member states. Under the framework of the UNSGM, we organized an external quality assurance exercise for nominated laboratories, named the Disease X Test, to improve the ability to discover and identify new pathogens that may cause possible epidemics and to determine their animal origin. The "what-if" scenario was to identify the etiological agent responsible for an outbreak that has tested negative for many known pathogens, including viruses and bacteria. Three microbes were added to the samples, Dabie bandavirus, Mammarenavirus, and Gemella spp., of which the last two have not been taxonomically named or published. The animal samples were from Rattus norvegicus, Marmota himalayana, New Zealand white rabbit, and the tick Haemaphysalis longicornis. Of the 11 international laboratories that participated in this activity, six accurately identified pathogen X as a new Mammarenavirus, and five correctly identified the animal origin as R. norvegicus. These results showed that many laboratories under the UNSGM have the capacity and ability to identify a new virus during a possible international investigation of a suspected biological event. The technical details are discussed in this report.Copyright © 2022

First isolation and characterization of the prototype strain of the SARSCoV-2 virus at the beginning of the COVID-19 pandemic in Peru

Introduction: Currently, isolated from SARS-CoV-2 virus exceed 600 million cases in the world. Objective(s): Isolation and characterization of the SARS-CoV-2 virus causing COVID-19 at the beginning of the pandemic in Peru. Method(s): Twenty nasal and pharyngeal swab samples were isolated from SARS-CoV-2 using two cell lines, Vero ATCC CCL-81 and Vero E-6;virus identification was performed by RT-PCR and the onset of cytopathic effect (CPE) was evaluated by indirect immunofluorescence and subsequent identification by genomic sequencing. One of the most widely circulating isolates were selected and named the prototype strain (PE/B.1.1/28549/2020). Then 10 successive passages were performed on Vero ATCC CCL-81 cells to assess mutation dynamics. Result(s): Results detected 11 virus isolates by cytopathic effect, and subsequently confirmed by RT-PCR and indirect immunofluorescence. Of these, six were sequenced and identified as the lineages B.1, B.1.1, B.1.1.1, and B.1.205 according to the Pango lineage nomenclature. The prototype strain corresponded to lineage B.1.1. The analysis of the strains from the successive passages showed mutations mainly at in the spike (S) protein of the virus without variation in the identity of the lineage. Conclusion(s): Four lineages were isolated in the Vero ATCC CCL-81 cell line. Subcultures in the same cell line showed mutations in the spike protein indicating greater adaptability to the host cell and variation in pathogenicity in vitro, a behavior that allows it to have more survival success.Copyright © 2023 Anales de la Facultad de Medicina. All rights reserved.

Procalcitonin combined to point of care molecular respiratory panel testing for antibiotic stewardship in the emergency room: the PROARRAY study

Introduction: Molecular syndromic respiratory panel (RP) or procalcitonin (PCT)-driven algorithms have reported conflicting efficacy for antibiotic ATB) stewardship in LRTI. We hypothesized that combining real-time PCT measurement and virus identification would reduce ATB exposition in LRTI suspicions presenting to the emergency department (ED). Method(s): PROARRAY study is a prospective, randomized interventional trial, conducted in the adult ED of an academic 1600-bed hospital. Patients attending the ED with a suspicion of LRTI were randomized into the intervention arm (systematic PCT measurement and point of care BIOFIRE RP2plus (then 2.1) testing, with the recommendation to withhold or withdraw ATB if PCT < 0.25 mug/L and/or identification of a virus) or a standard of care (SOC) arm. The primary endpoint was the duration of antibiotic exposure in the first 28 days. Result(s): 451 patients were randomized (intervention: 225, SOC: 226), mean age 62.5 +/- 19.4 years, hospitalization rate 59.9%, mean length of stay 7.4 +/- 8.4 days. Main diagnoses were CAP (n = 129), COVID-19 (n = 91), AECOPD (n = 31). The BIOFIRE RP2.1plus identified at least one viral species in 112 patients (49.8%). The duration of ATB exposition in ITT population was 6.00 [0.00;9.00] and 5.00 [0.00-9.00] days in the SOC and interventional arm respectively (p = 0.71). ATB was started in 31.3% and 34.1% respectively (p = 0.54). ATB exposure was below 6 days in 100 (47.2%) and 108 patients (50.59%) respectively (p = 0.58). Conclusion(s): Displaying real-time PCT and RP results failed to significantly reduce the ATB exposition in LRTI suspicions. However, the ATB duration and rate of initiation were already low in SOC arm, which comprised PCT measurement in routine in our ED. Routine PCT measurement probably participated to the lower median ATB duration (6.0 days) than hypothesized (9.0 days) and argues for the main contribution of PCT in ATB stewardship. Moreover, as the intervention was done at ED's level, we did not control for ATB stewardship in wards for inpatients.

Proteome2virus: Shotgun mass spectrometry data analysis pipeline for virus identification

Objectives: Shotgun proteomics is a generic method enabling detection of multiple viral species in one assay. The reliable and accurate identification of these viral species by analyzing peptides from MS-spectra is a challenging task. The aim of this study was to develop an easy accessible proteome analysis approach for the identification of viruses that cause respiratory and gastrointestinal infections. Method(s): For this purpose, a shotgun proteomics based method and a web application, 'proteome2virus', were developed. Identified peptides were searched in a database comprising proteomic data of 46 viruses known to be infectious to humans. Result(s): The method was successfully tested for cultured viruses and eight fecal samples consisting of ten different viral species from seven different virus families, including SARS-CoV-2. The samples were prepared with two different sample preparation methods and were measured with two different mass spectrometers. Conclusion(s): The results demonstrate that the developed web application is applicable to different MS data sets, generated from two different instruments, and that with this approach a high variety of clinically relevant viral species can be identified. This emphasizes the potential and feasibility for the diagnosis of a wide range of viruses in clinical samples with a single shotgun proteomics analysis.Copyright © 2023

Association between HLA and SARSCOV- 2 infection in Mexican Mestizos

The Acute Respiratory Syndrome caused by the new coronavirus described in Wuhan, China in 2019 is a viral, respiratory multifactorial infectious disease, which presents different stages depending on genetic and environmental factors that influence severity. As December 19, 2022, 653,192,573 COVID-19 cases worldwide and over six million deaths;330,795 occurred in Mexico, were reported. Our aim was to analyze the contribution of HLA in Mexican patients infected with COVID-19, categorized in different clinical subgroups. A total of 114 COVID-19 patients and 164 healthy controls, all of them Mexican Mestizos from the highlands, were included in the study;RNA columns were used for extraction, and real-time PCR method was performed for the virus identification. DNA was isolated with the Maxwell16 system and 11 HLA loci were typed using NGS (CareDx, Immucor, and One Lambda). The subjects included: 22 asymptomatic, 86 symptomatic and 109 who were previously vaccinated. We compared controls versus positive patients;versus symptomatic;vaccinated negative versus vaccinated positive;controls versus asymptomatic;asymptomatic versus symptomatic individuals. The significant high risk alleles were A*29:02 (OR = 3.95), B*45:01 (OR = 6.92), C*03:04 (OR = 2.24). DPB1*03:01(OR = 3.17) is a susceptibility marker in vaccinated and unvaccinated patients. The latter is prevalent in Hispanics, Russia, Finland, Spain and the United Kingdom. DQA1*02:01 (p = 0.009, OR = 1.96;DQB1*02:02 (p = 0.009, OR = 2.13) was a susceptibility marker in infected patients who were vaccinated. This is prevalent in Argentina, Brazil, Algeria, Australia, Canada, and China, while high-risk B*45:01 and C*03:04 are prevalent in India, Israel, Eastern Europe, and Mediterranean countries. Protective alleles where DRB1*04:01, A*02:01, DQB1*03:01 and DPB1*02:01. These data are relevant to prioritize vaccination, according to the HLA profile in Mexicans, therefore these data are relevant for the epidemiology of COVID-19.

Development of a validated molecular analytical method to determine the viral safety of F(AB´)2 products: A novel application for a well-known technique.

The immunotherapy agents derived from horses are biological products that allow the neutralization of clinically relevant immunogens, such as the SARS-CoV-2 virus that causes COVID-19, or the neutralization of toxins present in the venoms of snakes, spiders, and other poisonous animals. Due to their importance, detecting adventitious viruses in equine hyperimmune serum (raw material in industrial processes) is a critical step to support the safety of products for human use, and, in consequence, it is a requirement for commercialization and distribution. The safety of the finished product is based on three complementary approaches: (i) testing of the source material (horse serum) donations, (ii) release of the starting material (i.e., pool of horse serum) based on non-reactivity for a range of human infectious or pathogenic viruses, and (iii) validate (selected) steps of the manufacturing process for their capacity to inactivate and/or remove a wide range of viruses potentially present in the starting material. Orthogonal approaches to reduce viral contamination risk include implementing a reliable and validated system for detecting adventitious viruses. Thus, it is necessary to establish trustworthy and sufficiently sensitive analytical methods to evidence the lack of viruses to assure the safety of the therapeutic product. Therefore, in this research, an analytical method based on end-point Reverse Transcription Polymerase Chain Reaction (RT-PCR) was developed, implemented, and validated in hyperimmune equine serum samples to detect Venezuelan equine encephalitis virus, West Nile virus, and Rabies virus.

Intelligent Surface-Enhanced Raman Scattering Sensor System for Virus Identification

COVID-19 has devastated the entire world for the past couple of years. Timely and efficient detection and identification of a virus are crucial in preventing the wider virus spread. By using intelligent sensors based on Surface-Enhanced Raman Scattering (SERS), it is possible to detect and identify virus automatically. In this study, we successfully applied the XGBoost Algorithm (Supervised Machine Learning) to classify the type of the virus using the SERS sensor data. The supervised approach has a limitation when a new type of virus arises, whose shape is different from the previously known samples. To tackle this problem, we investigated the unsupervised learning approaches that can cluster the virus data into different groups without labeled data. The unsupervised approach presented in this paper is called k-Shape Clustering. This technique compares the cross-correlation between different samples and then clusters them into similar or different groups. If a subvariant of a virus emerges, it would be clustered into the existing virus groups;if a new type of virus is found, it would be clustered into a new group. Both of the approaches have shown very promising results based on extensive evaluations. © 2022 IEEE.

Oral manifestations in patients with COVID- 19 disease

The aim is to determine oral manifestations in patients with COVID-19 disease and in the postcovid period. Methods: A special survey (questionnaire) was made in 424 people who had COVID-19 confirmed by RT-PCR, ELISA for specific IgM and IgG antibodies and Chest CT scan (168 people). 123 people had complaints and clinical symptoms in the oral cavity 2-6 months after the illness and they came to the University dental clinic. Laboratory tests have been performed (clinical blood test, blood immunogram, virus and fungal identification). Results: Survey results showed that 16,0% participants had asymptomatic COVID-19, 23,6% - mild and 48,1% moderate disease. 12,3% with severe COVID-19 were treated in a hospital with oxygen support. In the first 2 weeks 44,3% indicated xerostomia, dysgeusia (21,7%), muscle pain during chewing (11,3%), pain during swallowing (30,2%), burning and painful tongue (1,9%), tongue swelling (30,2%), catharal stomatitis (16,0%), gingival bleeding (22,6%), painful ulcers (aphthae) (8,5%) and signs of candidiasis - white plaque in the tongue (12,3%). After illness (3-6 months), patients indicated dry mouth (12,3%), progressing of gingivitis (20,7%) and periodontitis (11,3%). In patients who applied to the clinic we identified such diagnoses: desquamative glossitis - 16 cases, glossodynia (11), herpes labialis and recurrent herpetic gingivostomatitis (27), hairy leukoplakia (1), recurrent aphthous stomatitis (22), aphthosis Sutton (4), necrotising ulcerative gingivitis (13), oral candidiasis (14), erythema multiforme (8), Stevens-Johnson syndrome (2), oral squamous cell papillomas on the gingiva (4) and the lower lip (1). According to laboratory studies, virus reactivation (HSV, VZV, EBV, CMV, Papilloma viruces) was noted in 52 patients (42,3%), immunodeficiency in 96 people (78,0%), immunoregulation disorders (allergic and autoimmune reactions) in 24 people (19,5%). Conclusions: Lack of oral hygiene, hyposalivation, vascular compromise, stress, immunodeficiency and reactivation of persistent viral and fungal infections in patients with COVID-19 disease are risk factors for progression of periodontal and oral mucosal diseases.

Accurate virus identification with interpretable Raman signatures by machine learning.

Rapid identification of newly emerging or circulating viruses is an important first step toward managing the public health response to potential outbreaks. A portable virus capture device, coupled with label-free Raman spectroscopy, holds the promise of fast detection by rapidly obtaining the Raman signature of a virus followed by a machine learning (ML) approach applied to recognize the virus based on its Raman spectrum, which is used as a fingerprint. We present such an ML approach for analyzing Raman spectra of human and avian viruses. A convolutional neural network (CNN) classifier specifically designed for spectral data achieves very high accuracy for a variety of virus type or subtype identification tasks. In particular, it achieves 99% accuracy for classifying influenza virus type A versus type B, 96% accuracy for classifying four subtypes of influenza A, 95% accuracy for differentiating enveloped and nonenveloped viruses, and 99% accuracy for differentiating avian coronavirus (infectious bronchitis virus [IBV]) from other avian viruses. Furthermore, interpretation of neural net responses in the trained CNN model using a full-gradient algorithm highlights Raman spectral ranges that are most important to virus identification. By correlating ML-selected salient Raman ranges with the signature ranges of known biomolecules and chemical functional groups­for example, amide, amino acid, and carboxylic acid­we verify that our ML model effectively recognizes the Raman signatures of proteins, lipids, and other vital functional groups present in different viruses and uses a weighted combination of these signatures to identify viruses.

The International Virus Bioinformatics Meeting 2022.

The International Virus Bioinformatics Meeting 2022 took place online, on 23-25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus-host interactions, viral sequence analysis, virus identification and annotation, phages, and viral diversity. This report summarizes the main research findings and highlights presented at the meeting.

Viral Metagenomic Data Analyses of Five New World Bat Species from Argentina: Identification of 35 Novel DNA Viruses.

Bats are natural reservoirs of a variety of zoonotic viruses, many of which cause severe human diseases. Characterizing viruses of bats inhabiting different geographical regions is important for understanding their viral diversity and for detecting viral spillovers between animal species. Herein, the diversity of DNA viruses of five arthropodophagous bat species from Argentina was investigated using metagenomics. Fecal samples of 29 individuals from five species (Tadarida brasiliensis, Molossus molossus, Eumops bonariensis, Eumops patagonicus, and Eptesicus diminutus) living at two different geographical locations, were investigated. Enriched viral DNA was sequenced using Illumina MiSeq, and the reads were trimmed and filtered using several bioinformatic approaches. The resulting nucleotide sequences were subjected to viral taxonomic classification. In total, 4,520,370 read pairs were sequestered by sequencing, and 21.1% of them mapped to viral taxa. Circoviridae and Genomoviridae were the most prevalent among vertebrate viral families in all bat species included in this study. Samples from the T. brasiliensis colony exhibited lower viral diversity than samples from other species of New World bats. We characterized 35 complete genome sequences of novel viruses. These findings provide new insights into the global diversity of bat viruses in poorly studied species, contributing to prevention of emerging zoonotic diseases and to conservation policies for endangered species.

Single virus inductively coupled plasma mass spectroscopy analysis: A comprehensive study.

The characterisation of individual nanoparticles by single particle ICP-MS (SP-ICP-MS) has paved the way for the analysis of smallest biological systems. This study suggests to adapting this method for single viruses (SV) identification and counting. With high resolution multi-channel sector field (MC SF) ICP-MS records in SV detection mode, the counting of master and key ions can allow analysis and identification of single viruses. The counting of 2-500 virial units can be performed in 20 s. Analyses are proposed to be carried out in Ar torch for master ions: 12C+, 13C+, 14N+, 15N+, and key ions 31P+, 32S+, 33S+ and 34S+. All interferences are discussed in detail. The use of high resolution SF ICP-MS is recommended while options with anaerobic/aerobic atmospheres are explored to upgrade the analysis when using quadrupole ICP-MS. Application for two virus types (SARS-COV2 and bacteriophage T5) is investigated using time scan and fixed mass analysis for the selected virus ions allowing characterisation of the species using the N/C, P/C and S/C molar ratio's and quantification of their number concentration.