Laboratory detection methods for the human coronaviruses.
Ontology highlight
ABSTRACT:
SUBMITTER: Shabani E
PROVIDER: S-EPMC7520381 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
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Project description:The ongoing crisis due to the global pandemic caused by a highly contagious coronavirus (Coronavirus disease - 2019; COVID-19) and the lack of either proven effective therapy or a vaccine has made diagnostic a valuable tool in disease tracking and prevention. The complex nature of this newly emerging virus calls for scientists' attention to find the most reliable, highly sensitive, and selective detection techniques for better control or spread of the disease. Reverse transcriptase-polymerase chain reaction (RT-PCR) and serology-based tests are currently being used. However, the speed and accuracy of these tests may not meet the current demand; thus, alternative technology platforms are being developed. Nano biosensor technology platforms have been established as a promising diagnostic tool for rapid and accurate detection of viruses as well as other life-threatening diseases even in resource-limited settings. This review aims to provide a short overview of recent advancements in molecular and biosensor-based diagnosis of viruses, including the human coronaviruses, and highlight the challenges and future perspectives of these detection technologies.
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Project description:Porcine enteric coronaviruses (CoVs) cause highly contagious enteric diarrhea in suckling piglets. These COV infections are characterized by clinical signs of vomiting, watery diarrhea, dehydration, and high morbidity and mortality, resulting in significant economic losses and tremendous threats to the pig farming industry worldwide. Because the clinical manifestations of pigs infected by different CoVs are similar, it is difficult to differentiate between the specific pathogens. Effective high-throughput detection methods are powerful tools used in the prevention and control of diseases. The immune system of piglets is not well developed, so serological methods to detect antibodies against these viruses are not suitable for rapid and early detection. This paper reviews various PCR-based methods used for the rapid and efficient detection of these pathogenic CoVs in swine intestines. KEY POINTS: 1. Swine enteric coronaviruses (CoVs) emerged and reemerged in past years. 2. Enteric CoVs infect pigs at all ages with high mortality rate in suckling pigs. 3. Rapid and efficient detection methods are needed and critical for diagnosis.
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Project description:Human coronaviruses HCoV-OC43, HCoV-229E, HCoV-NL63 and HCoV-HKU1 are common respiratory viruses associated with acute respiratory infection. They have a global distribution. Rapid and accurate diagnosis of HCoV infection is important for the management and treatment of hospitalized patients with HCoV infection. Here, we developed a melting curve-based multiplex RT-qPCR assay for simultaneous detection of the four HCoVs. In the assay, SYTO 9 was used to replace SYBR Green I as the fluorescent dye, and GC-modified primers were designed to improve the melting temperature (Tm) of the specific amplicon. The four HCoVs were clearly distinguished by characteristic melting peaks in melting curve analysis. The detection sensitivity of the assay was 3 × 10² copies for HCoV-OC43, and 3 × 10¹ copies for HCoV-NL63, HCoV-229E and HCoV-HKU1 per 30 ?L reaction. Clinical evaluation and sequencing confirmation demonstrated that the assay was specific and reliable. The assay represents a sensitive and reliable method for diagnosis of HCoV infection in clinical samples.
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Project description:In an epidemiological study of ferret coronaviruses (FRCoVs), novel FRCoV strains (Saitama-1 and Aichi-1) were detected by reverse transcription-polymerase chain reaction (RT-PCR) and nucleotide sequence analysis of partial RNA-dependent RNA polymerase (RdRp) genes. Phylogenetic analysis indicated that these strains belonged to different clusters from other FRCoV strains. Next, the nucleotide sequence of the 3'-terminal region of Saitama-1 (8271 bases) strain was determined and compared with those of the other FRCoVs, indicating that the Saitama-1 strain differed from the previously reported MSU-1 and MSU-2 strains in the regions encoding spike (S) protein, nucleocapsid, and open reading frame 7b. Furthermore, the results of SimPlot analysis indicated that FRCoV (MSU-2 strain) emerged via a recombination event of S protein between the MSU-1 and Saitama-1 strains. This mechanism is similar to that responsible for the emergence of type II feline coronavirus. This information will be useful for understanding the pathogenesis of FRCoV in ferrets.
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2022-05-11 | GSE196416 | GEO
Project description:BackgroundPsittacosis outbreak investigations require rapid identification of cases in order to trace possible sources and perform public health risk assessments. In recent outbreaks in the Netherlands, such investigations were hampered by the non-specificity of laboratory testing methods to identify human Chlamydia psittaci infections.MethodA systematic search of PubMed and Scopus databases of literature published between 01 January, 1986 and 03 July, 2017 was done to find best practices of laboratory-testing methods used in psittacosis outbreaks of two or more human cases. Reference lists of included articles were hand searched to identify additional articles.ResultsThirty-seven eligible articles were identified, describing 44 human psittacosis outbreaks in 12 countries. Laboratory tests performed were PCR (with various targets), serologic tests (complement binding reactions, ELISA's, immunofluorescence tests and immuno-peroxidase tests) and culture, in various combinations. The literature provided no 'gold standard' laboratory testing strategy to identify recent human C. psittaci infections. In most psittacosis outbreaks, for a considerable number of cases (or tested individuals in an exposed cohort), C. psittaci infection could not be confirmed, nor excluded as causative pathogen. None of the testing strategies was found to be suitable for (nearly) full case finding.ConclusionPCR enables rapid identification of human psittacosis patients and helps source finding by genotyping but has the disadvantage that sensitivity is high only in the acute phase. In outbreak situations, there is often a time delay and therefore, there is a need for new serologic testing methods next to PCR, with good specificity and sensitivity. Moreover, serum is easier to collect than the preferred diagnostic materials for PCR. A serologic test that can reliably confirm infection status without the necessity of convalescent serum sampling would enhance case finding, source tracing, identification of risk factors and assessment of burden of disease in various settings.
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Project description:Most coronaviruses infecting humans cause mild diseases, whereas severe acute respiratory syndrome (SARS)-associated coronavirus is an extremely dangerous pathogen. Here, we report the development of a serologic assay for detection of antibodies to human coronaviruses (HCoVs) based on recombinant nucleocapsid (N) proteins of all known pathogenic strains (229E, NL63, OC43, HKU1, SARS). The novel immunoassay is highly useful for epidemiologic surveys, where use of nucleic acid diagnostics often is limited. Purified recombinant antigens were immobilized on nitrocellulose membranes and applied in a line immunoassay, which allows rapid detection of antibodies to 5 different HCoVs in a single experiment. For assay evaluation, serum samples from persons infected with 229E or OC43 (acute/convalescent), recovered SARS patients and healthy donors were analyzed. Screening for nucleocapsid (N)-specific immunoglobulin G (IgG) in convalescent sera reached 100% sensitivity. With this new technique, we found that recently identified NL63 and HKU1 contribute significantly to the overall spectrum of coronavirus infections. Possibly, cross-reactive antibody responses were observed using 229E and OC43 serum pairs. However, the potential of this assay could clearly be demonstrated employing SARS-positive serum samples, where nonspecific binding to nucleocapsids of other HCoVs was not observed. This coronavirus strain-specific line immunoassay represents a powerful tool for serologic diagnostics.
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Project description:Immunoglobulin G (IgG) purification is a critical process for evaluating its role in autoimmune diseases, which are defined by the occurrence of autoantibodies. Affinity chromatography with protein G is widely considered the optimal technique for laboratory-scale purification. However, this technique has some limitations, including the exposure of IgG to low pH, which can compromise the quality of the purified IgG. Here, we show that alternative methods for IgG purification are possible, while maintaining the quality of IgG. Different techniques for IgG purification from serum were evaluated and compared with protein G-based approaches: MelonTM Gel, caprylic acid-ammonium sulfate (CA-AS) precipitation, anion exchange chromatography with diethylaminoethyl (DEAE) following AS precipitation, and AS precipitation alone. The results demonstrated that the purification yield of these techniques surpassed that of protein G. However, differences in the purity of IgG were observed using GeLC-MS/MS. The avidity of purified IgG against selected targets (SARS-CoV-2 and topoisomerase-I) was similar between purified IgG obtained using all techniques and unpurified sera. Our work provides valuable insights for future studies of IgG function by recommending alternative purification methods that offer advantages in terms of yield, time efficiency, cost-effectiveness, and milder pH conditions than protein G.
2024-09-02 | PXD050732 | Pride
Project description:Accurate and precise detection of anthropogenic impacts on stream ecosystems using macroinvertebrates as biological indicators depends on the use of appropriate field and laboratory methods. We assessed the responsiveness to anthropogenic disturbances of assemblage metrics and composition by comparing commonly employed alternative combinations of field sampling and individuals counting methods. Four datasets were derived by, in the field 1) conducting multihabitat sampling (MH) or 2) targeting samples in leaf packs (single-habitat sampling - SH) and, in the laboratory A) counting all individuals of the samples, or B) simulating subsampling of 300 individuals per sample. We collected our data from 39 headwater stream sites in a drainage basin located in the Brazilian Cerrado. We used a previously published quantitative integrated disturbance index (IDI), based on both local and catchment disturbance measurements, to characterize the intensity of anthropogenic alterations at each site. Family richness and % Ephemeroptera, Plecoptera and Trichoptera (% EPT) individuals obtained from each dataset were tested against the IDI through simple linear regressions, and the differences in assemblage composition between least- and most-disturbed sites was tested using Permutational Multivariate Analysis of Variance (PERMANOVA). When counting all individuals, differences in taxonomic richness and assemblage composition of macroinvertebrate assemblages between least- and most-disturbed sites were more pronounced in the MH than in the SH sampling method. Leaf packs seemed to concentrate high abundance and diversity of macroinvertebrates in highly disturbed sites, acting as 'biodiversity hotbeds' in these situations, which likely reduced the response of the assemblages to the disturbance gradient when this substrate was targeted. However, MH sampling produced weaker results than SH when subsampling was performed. The % EPT individuals responded better to the disturbance gradient when SH was employed, and its efficiency was not affected by the subsampling procedure. We conclude that no single method was the best in all situations, and the efficiency of a sampling protocol depends on the combination of field and laboratory methods being used. Although the total count of individuals with multihabitat sampling obtained the best results for most of the evaluated variables, the decision of which procedures to use depends on the amount of time and resources available, on the variables of interest, on the availability of habitat types in the sites sampled, and on the other methods being employed in the sampling protocol.
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