A reliable and quick method for screening alternative splicing variants for low-abundance genes.

Alternative splicing (AS) is a universal phenomenon in eukaryotes, and it is still challenging to identify AS events. Several methods have been developed to identify AS events, such as expressed sequence tags (EST), microarrays and RNA-seq. However, EST has limitations in identifying low-abundance genes, while microarray and RNA-seq are high-throughput technologies, and PCR-based technology is needed for validation. To overcome the limitations of EST and shortcomings of high-throughput technologies, we established a method to identify AS events, especially for low-abundance genes, by reverse transcription (RT) PCR with gene-specific primers (GSPs) followed by nested PCR. This process includes two major steps: 1) the use of GSPs to amplify as long as the specific gene segment and 2) multiple rounds of nested PCR to screen the AS and confirm the unknown splicing variants. With this method, we successfully identified three new splicing variants, namely, GenBank Accession No. HM623886 for the bdnf gene (GenBank GeneID: 12064), GenBank Accession No. JF417977 for the trkc gene (GenBank GeneID: 18213) and GenBank Accession No. HM623888 for the glb-18 gene (GenBank GeneID: 172485). In addition to its reliability and simplicity, the method is also cost-effective and labor-intensive. In conclusion, we developed an RT-nested PCR method using gene-specific primers to efficiently identify known and novel AS variants. This approach overcomes the limitations of existing methods for detecting rare transcripts. By enabling the discovery of new isoforms, especially for low-abundance genes, this technique can aid research into aberrant splicing in disease. Future studies can apply this method to uncover AS variants involved in cancer, neurodegeneration, and other splicing-related disorders.

A Literature Review on the Relative Diagnostic Accuracy of Chest CT Scans versus RT-PCR Testing for COVID-19 Diagnosis.

BACKGROUND: Reverse transcription polymerase chain reaction (RT-PCR) is the main technique used to identify COVID-19 from respiratory samples. It has been suggested in several articles that chest CTs could offer a possible alternate diagnostic tool for COVID-19; however, no professional medical body recommends using chest CTs as an early COVID-19 detection modality. This literature review examines the use of CT scans as a diagnostic tool for COVID-19. METHOD: A comprehensive search of research works published in peer-reviewed journals was carried out utilizing precisely stated criteria. The search was limited to English-language publications, and studies of COVID-19-positive patients diagnosed using both chest CT scans and RT-PCR tests were sought. For this review, four databases were consulted: these were the Cochrane and ScienceDirect catalogs, and the CINAHL and Medline databases made available by EBSCOhost. FINDINGS: In total, 285 possibly pertinent studies were found during an initial search. After applying inclusion and exclusion criteria, six studies remained for analysis. According to the included studies, chest CT scans were shown to have a 44 to 98% sensitivity and 25 to 96% specificity in terms of COVID-19 diagnosis. However, methodological limitations were identified in all studies included in this review. CONCLUSION: RT-PCR is still the suggested first-line diagnostic technique for COVID-19; while chest CT is adequate for use in symptomatic patients, it is not a sufficiently robust diagnostic tool for the primary screening of COVID-19.

ExonSurfer: a web-tool to design primers at exon-exon junctions.

BACKGROUND: Reverse transcription quantitative PCR (RT-qPCR) with intercalating dyes is one of the main techniques to assess gene expression levels used in basic and applied research as well as in diagnostics. However, primer design for RT-qPCR can be complex due to the high demands on primer quality. Primers are best placed on exon junctions, should avoid polymorphic regions, be specific to the target transcripts and also prevent genomic amplification accurately, among others. Current software tools manage to meet all the necessary criteria only insufficiently. Here, we present ExonSurfer, a novel, user-friendly web-tool for qPCR primer design. RESULTS: ExonSurfer combines the different steps of the primer design process, encompassing target selection, specificity and self-complementarity assessment, and the avoidance of issues arising from polymorphisms. Amplification of potentially contaminating genomic DNA is avoided by designing primers on exon-exon junctions, moreover, a genomic alignment is performed to filter the primers accordingly and inform the user of any predicted interaction. In order to test the whole performance of the application, we designed primer pairs for 26 targets and checked both primer efficiency, amplicon melting temperature and length and confirmed the targeted amplicon by Sanger sequencing. Most of the tested primers accurately and selectively amplified the corresponding targets. CONCLUSION: ExonSurfer offers a comprehensive end-to-end primer design, guaranteeing transcript-specific amplification. The user interface is intuitive, providing essential specificity and amplicon details. The tool can also be used by command line and the source code is available. Overall, we expect ExonSurfer to facilitate RT-qPCR set-up for researchers in many fields.

Evaluation of self-collected nasal, urine, and saliva samples for molecular detection of SARS-CoV-2 using an EUA approved RT-PCR assay and a laboratory developed LAMP SARS-CoV-2 test.

As the SARS-CoV-2 virus spread throughout the world, millions of positive cases of COVID-19 were registered and, even though there are millions of people already vaccinated against SARS-CoV-2, a large part of the global population remains vulnerable to contracting the virus. Massive nasopharyngeal sample collection in Puerto Rico at the beginning of the pandemic was limited by the scarcity of trained personnel and testing sites. To increase SARS-CoV-2 molecular testing availability, we evaluated the diagnostic accuracy of self-collected nasal, saliva, and urine samples using the TaqPath reverse transcription polymerase chain reaction (RT-PCR) COVID-19 kit to detect SARS-CoV-2. We also created a colorimetric loop-mediated isothermal amplification (LAMP) laboratory developed test (LDT) to detect SARS-CoV-2, as another strategy to increase the availability of molecular testing in community-based laboratories. Automated RNA extraction was performed in the KingFisher Flex instrument, followed by PCR quantification of SARS-CoV-2 on the 7500 Fast Dx RT-PCR using the TaqPath RT-PCR COVID-19 molecular test. Data was interpreted by the COVID-19 Interpretive Software from Applied Biosystems and statistically analyzed with Cohen's kappa coefficient (k). Cohen's kappa coefficient (k) for paired nasal and saliva samples showed moderate agreement (0.52). Saliva samples exhibited a higher viral load. We also observed 90% concordance between LifeGene-Biomarks' SARS-CoV-2 Rapid Colorimetric LAMP LDT and the TaqPath RT-PCR COVID-19 test. Our results suggest that self-collected saliva is superior to nasal and urine samples for COVID-19 testing. The results also suggest that the colorimetric LAMP LDT is a rapid alternative to RT-PCR tests for the detection of SARS-CoV-2. This test can be easily implemented in clinics, hospitals, the workplace, and at home; optimizing the surveillance and collection process, which helps mitigate global public health and socioeconomic upheaval caused by airborne pandemics.

Detection of Foodborne RNA Viruses by Reverse Transcriptase Droplet Digital PCR.

Foodborne viruses remain the largest cause of human gastroenteritis and one of the largest contributors to foodborne illnesses worldwide. Currently, quantitative reverse transcription PCR (qRT-PCR) or real-time qPCR are the detection methods commonly used for quantification of foodborne viruses, but those methods have several disadvantages, such as relying on standard curves for quantification and the background noise from a bulk reaction. ddPCR uses an oil-water emulsion to form multiple droplets that partition small amounts of viral genetic material (DNA or RNA) into each of the droplets. These droplets then undergo amplification cycles and are analyzed using Poisson distributions. This allows for absolute quantification without the need for a standard curve, which makes ddPCR a precise tool in surveillance of foodborne viruses. Herein, we describe the process of detecting foodborne viruses using RNA isolated from various matrices. Up to 96 samples including the positive and negative controls can be analyzed on a single plate by ddPCR.

Establishment of dual reverse transcriptase-polymerase chain reaction for detection system for Areca palm velarivirus 1.

Areca palm velarivirus 1 (APV1) is one of the main pathogen causing yellow leaf disease, and leading to considerable losses in the Areca palm industry. The detection methods for APV1 are primarily based on phenotype determination and molecular techniques, such as polymerase chain reaction (PCR). However, a single PCR has limitations in accuracy and sensitivity. Therefore, in the present study, we established a dual RT-PCR APV1-detection system with enhanced accuracy and sensitivity using two pairs of specific primers, YLDV2-F/YLDV2-R and YLDV4-F/YLDV4-R. Moreover, two cDNA fragments covering different regions of the viral genome were simultaneously amplified, with PCR amplicon of 311 and 499 bp, respectively. The dual RT-PCR detection system successfully amplified the two target regions of the APV1, demonstrating high specificity and sensitivity and compensating for the limitations of single-primer detection methods. We tested 60 Areca palm samples from different geographical regions, highlighting its advantages in that the dual RT-PCR system efficiently and accurately detected APV1 in samples across diverse areas. The dual RT-PCR APV1 detection system provides a rapid, accurate, and sensitive method for detecting the virus and offers valuable technical support for research in preventing and managing yellow leaf diseases caused by APV1 in Areca palms. Moreover, the findings of this study can serve as a reference for establishing similar plants viral detection systems in the future.

Qualitative detection of E. coli in distributed drinking water using real-time reverse transcription PCR targeting 16S rRNA: Validation and practical experiences.

Escherichia coli (E. coli) plays a central role as an indicator for fecal contamination to predict the possible presence of microbial pathogens in drinking water. Current detection methods for E. coli are based on time-consuming culture-based techniques. There is a strong need for methods to detect fecal contamination rapidly in distributed drinking water to prevent outbreaks of waterborne disease and support water utilities to efficiently manage their operations like actions to repair or maintain distribution pipes, to minimize impact on consumers. This study describes the validation and application of a qualitative real time reverse transcription PCR (RT-PCR) method targeting 16S ribosomal RNA (rRNA) for rapid detection of E. coli in distributed drinking water. The RT-PCR assay targets 16S rRNA, a highly abundant RNA in viable cells, enabling robust detection at the required sensitivity of 1 CFU/100 ml. The validation was performed by comparing the RT-PCR method with the culture-based chromogenic reference method (CCA) using the protocol and criteria described in ISO 16,140-2:2016. The validation demonstrated that this RT-PCR method can be used to specifically detect E. coli in a broad range of drinking water samples with at least the same limit of detection as the culture method (Relative Limit Of Detection = 0.75, range 0.43-1.43). The inclusivity study showed that the RT-PCR method was able to detect a broad range of E. coli strains derived from different sources and geographic areas, including pathogenic serotype O157 strains that are not detected with the culture method. The exclusivity study determined that other bacterial genera are not detected with this RT-PCR. However, Escherichia fergusonii was detected and, based on "in silico" analysis, it is expected that also E. albertii and E. marmotae and Shigella species will be detectable using this RT-PCR. An interlaboratory study confirmed that the RT-PCR and culture method have comparable sensitivities when tested by different participants at different laboratories. The application of RT-PCR to confirm the hygienic quality of distributed drinking water after actions to repair or maintain distribution pipes was compared with the culture method on 8076 routine samples, analyzed by the drinking water laboratories in the Netherlands. This comparison study showed a 96.4 % agreement between RT-PCR and culture. In 3.3 % of the samples E. coli was detected with RT-PCR and not with the culture method and in 0.1 % of the samples E. coli was only detected by culture confirming either a higher sensitivity for RT-PCR or the detection of RNA from uncultivable cells. Finally, the application of RT-PCR was highlighted during a contamination event in Belgium where we demonstrate the potency of RT-PCR as a tool to rapidly monitor the spread of microbial contamination and to monitor the effect of measures to remove the contamination This is the first fully validated rapid nucleic based method for detection of E. coli in distributed drinking water. These results demonstrate that this RT-PCR method can be used as a rapid alternative to the culture method to monitor E. coli in distributed drinking water. However, it should be emphasized that nucleic acid based detection methods rely on highly different detection principles (detection of captured nucleic acids present in a sample) than culture base methods (presence of cells cultivable on a selective medium) resulting in occasional different analysis results. Varying treatment and disinfection steps (UV, chlorine, monochloramine, Ozone) or environmental factors (decay) can influence the results and cause differences between RT-PCR and culture methods.

A Method to Quantitatively Examine Heat Stress-Induced Alternative Splicing in Plants by RNA-Seq and RT-PCR.

Alternative splicing (AS) of pre-mRNAs is a type of post-transcriptional regulation in eukaryotes that expands the number of mRNA isoforms. Intron retention is the primary form of AS in plants and occurs more frequently when plants are exposed to environmental stresses. Several wet-lab and bioinformatics techniques are used to detect AS events, but these techniques are technically challenging or unsuitable for studying AS in plants. Here, we report a method that combines RNA-sequencing and reverse transcription PCR for visualizing and validating heat stress-induced AS events in plants, using Arabidopsis thaliana and HEAT SHOCK PROTEIN21 (HSP21) as examples.

Development of a multiplex real-time quantitative reverse-transcription polymerase chain reaction for the detection of four bee viruses.

Viruses in the families Dicistroviridae and Iflaviridae are among the main threats to western honey bees (Apis mellifera) and native bee species. Polymerase chain reaction (PCR) is the gold standard for pathogen detection in bees. However, high throughput screening for bee virus infections in singleplex PCR reactions is cumbersome and limited by the high quantities of sample RNA required. Thus, the development of a sensitive and specific multiplex PCR detection method for screening for multiple viruses simultaneously is necessary. Here, we report the development of a one-step multiplex reverse-transcription quantitative polymerase chain reaction (RT-qPCR) assay to detect four viruses commonly encountered in pollinator species. The optimized multiplex RT-qPCR protocol described in this study allows simultaneous detection of two dicistroviruses (Israeli acute paralysis virus and Black queen cell virus) and two iflaviruses (Sacbrood virus and Deformed wing virus) with high efficiency and specificity comparable to singleplex detection assays. This assay provides a broad range of detection and quantification, and the results of virus quantification in this study are similar to those performed in other studies using singleplex detection assays. This method will be particularly useful for data generation from small-bodied insect species that yield low amounts of RNA.

Validation of one-step reverse transcription digital PCR assays for Norovirus GI.

Regular monitoring of Norovirus presence in environmental and food samples is crucial due to its high transmission rates and outbreak potential. For detecting Norovirus GI, reverse transcription qPCR method is commonly used, but its sensitivity can be affected by assay performance. This study shows significantly reduced assay performance in digital PCR or qPCR when using primers targeting Norovirus GI genome 5291-5319 (NC_001959), located on the hairpin of the predicted RNA structure. It is highly recommended to avoid this region in commercial kit development or diagnosis to minimizing potential risk of false negatives.

Evaluation of different molecular systems for detection and quantification of SARS-CoV-2 RNA from wastewater samples.

Wastewater-based epidemiology has proved to be a suitable approach for tracking the spread of epidemic agents including SARS-CoV-2 RNA. Different protocols have been developed for quantitative detection of SARS-CoV-2 RNA from wastewater samples, but little is known on their performance. In this study we compared three protocols based on Reverse Transcription Real Time-PCR (RT-PCR) and one based on Droplet Digital PCR (ddPCR) for SARS-CoV-2 RNA detection from 35 wastewater samples. Overall, SARS-CoV-2 RNA was detected by at least one method in 85.7 % of samples, while 51.4 %, 22.8 % and 8.6 % resulted positive with two, three or all four methods, respectively. Protocols based on commercial RT-PCR assays and on Droplet Digital PCR showed an overall higher sensitivity vs. an in-house assay. The use of more than one system, targeting different genes, could be helpful to increase detection sensitivity.

Real-time reverse transcription recombinase polymerase amplification (RT-RPA) assay for detection of cassava brown streak viruses.

Cassava brown streak disease (CBSD) caused by Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) is the most economically important viral disease of cassava. As cassava is a vegetatively propagated crop, the development of rapid and sensitive diagnostics would aid in the identification of virus-free planting material and development of effective management strategies. In this study, a rapid, specific and sensitive real-time reverse transcription recombinase polymerase amplification (RT-RPA) assay was developed for real-time detection of CBSV and UCBSV. The RT-RPA was able to detect as little as 2 pg/µl of purified RNA obtained from infected cassava leaves, a sensitivity equivalent to that obtained by quantitative real-time reverse transcription PCR (qRT-PCR), within 20 min at 37 °C. Further, the RT-RPA detected each target virus directly from crude leaf and stem extracts, avoiding the tedious and costly isolation of high-quality RNA. The developed RT-RPA assay provides a valuable diagnostic tool that can be adopted by cassava seed certification and virus resistance breeding programs to ensure distribution of virus-free cassava planting materials to farmers. This is the first report on the development and validation of crude sap-based RT-RPA assay for the detection of cassava brown streak viruses (UCBSV and CBSV) infection in cassava plants.

Analytical validation of a semi-automated methodology for quantitative measurement of SARS-CoV-2 RNA in wastewater collected in northern New England.

Wastewater-based epidemiology (WBE) can be used to monitor the community presence of infectious disease pathogens of public health concern such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Viral nucleic acid has been detected in the stool of SARS-CoV-2-infected individuals. Asymptomatic SARS-CoV-2 infections make community monitoring difficult without extensive and continuous population screening. In this study, we validated a procedure that includes manual pre-processing, automated SARS-CoV-2 RNA extraction and detection workflows using both reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR) and reverse transcriptase droplet digital PCR (RT-ddPCR). Genomic RNA and calibration materials were used to create known concentrations of viral material to determine the linearity, accuracy, and precision of the wastewater extraction and SARS-CoV-2 RNA detection. Both RT-qPCR and RT-ddPCR perform similarly in all the validation experiments, with a limit of detection of 50 copies/mL. A wastewater sample from a care facility with a known outbreak was assessed for viral content in replicate, and we showed consistent results across both assays. Finally, in a 2-week survey of two New Hampshire cities, we assessed the suitability of our methods for daily surveillance. This paper describes the technical validation of a molecular assay that can be used for long-term monitoring of SARS-CoV-2 in wastewater as a potential tool for community surveillance to assist with public health efforts.IMPORTANCEThis paper describes the technical validation of a molecular assay that can be used for the long-term monitoring of SARS-CoV-2 in wastewater as a potential tool for community surveillance to assist with public health efforts.

Droplet Digital RT-PCR (dd RT-PCR) Detection of SARS-CoV-2 in Honey Bees and Honey Collected in Apiaries across the Campania Region.

Coronaviruses (CoVs), a subfamily of Orthocoronavirinae, are viruses that sometimes present a zoonotic character. Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for the recent outbreak of COVID-19, which, since its outbreak in 2019, has caused about 774,593,066 confirmed cases and 7,028,881 deaths. Aereosols are the main route of transmission among people; however, viral droplets can contaminate surfaces and fomites as well as particulate matter (PM) in suspensions of natural and human origin. Honey bees are well known bioindicators of the presence of pollutants and PMs in the environment as they can collect a great variety of substances during their foraging activities. The aim of this study was to evaluate the possible role of honey bees as bioindicators of the prevalence SARS-CoV-2. In this regard, 91 samples of honey bees and 6 of honey were collected from different apiaries of Campania region (Southern Italy) in four time periods from September 2020 to June 2022 and were analyzed with Droplet Digital RT-PCR for SARS-CoV-2 target genes Orf1b and N. The screening revealed the presence of SARS-CoV-2 in 12/91 in honey bee samples and in 2/6 honey samples. These results suggest that honey bees could also be used as indicators of outbreaks of airborne pathogens such as SARS-CoV-2.

Prevalence of viral agents causing swine reproductive failure in Korea and the development of multiplex real-time PCR and RT-PCR assays.

This study aimed to investigate the prevalence of viral agents causing reproductive failure in pigs in Korea. In addition, two types of multiplex real-time PCR (mqPCR) were developed for the simultaneous detection of Aujeszky's disease virus (ADV) and porcine parvovirus (PPV) in mqPCR and encephalomyocarditis virus (EMCV) and Japanese encephalitis virus (JEV) in reverse transcription mqPCR (mRT-qPCR). A total of 150 aborted fetus samples collected from 2020 to 2022 were analyzed. Porcine reproductive and respiratory syndrome virus was the most prevalent (49/150 32.7%), followed by porcine circovirus type 2 (31/150, 20.7%), and PPV1 (7/150, 4.7%), whereas ADV, EMCV, and JEV were not detected. The newly developed mqPCR and mRT-qPCR could simultaneously detect and differentiate with high sensitivities and specificities. When applied to aborted fetuses, the newly developed mqPCR for PPV was 33.3% more sensitivities than the previously established diagnostic method. Amino acid analysis of the VP2 sequences of PPV isolates revealed considerable similarity to the highly pathogenic Kresse strain. This study successfully evaluated the prevalence of viral agents causing reproductive failure among swine in Korea, the developed mqPCR and mRT-qPCR methods could be utilized as effective and accurate diagnostic methods for the epidemiological surveillance of ADV, PPV, EMCV, and JEV.

Novel approach for detecting classical swine fever virus from swabs of wild boar cut tails using nested real-time PCR.

We devised a method to detect the classical swine fever virus (CSFV) in tail-wiped swabs from wild boars. The CSFV gene in swabs was detected with high sensitivity using nested real-time polymerase chain reaction (PCR), which is a combination of reverse transcription-PCR (RT-PCR) and real-time PCR. We compared CSFV gene detection from boar tissue using the conventional and our tail-wiped swab method. The tail-wiped swab method showed sensitivity and specificity of 100% (26/26) and 98.8% (172/174), respectively compared to the conventional method. Thus, the swab-based CSFV detection method was considered to have detection sensitivity comparable to that of conventional methods. Additionally, we conducted surveillance for CSFV in wild boars on Awaji Island. CSFV was detected in 10.7% (45/420) of samples.

Comparison of 4 laboratory tests for the detection of bovine rabies viral infection in Paraguay: fluorescent antibody test, rapid detection test, histologic lesions, and RT-PCR.

Rabies virus (RABV; Lyssavirus rabies) is a neurotropic virus that can be transmitted to mammals by the hematophagous bat Desmodus rotundus. An accurate, accessible method for the detection of RABV in cattle is necessary in Paraguay; thus, we evaluated the detection of RABV using 4 techniques: fluorescent antibody test (FAT), immunochromatography rapid detection test (RDT; Anigen Rapid Rabies Ag test kit; Bionote), a reverse-transcription PCR (RT-PCR) assay, and histologic lesions in different portions of the CNS of 49 Paraguayan cattle to determine the most sensitive and specific technique. By FAT and RDT, 15 of 49 (31%) samples were positive. By RT-PCR amplification of N and G genes, 13 of 49 (27%) and 12 of 49 (25%) were positive, respectively. RDT had high agreement with FAT (kappa = 1); sensitivity was 100% (95% CI: 97-100%) and specificity was 100% (95% CI: 99-100%). The amplification of the N and G genes resulted in substantial agreement (kappa of 0.9 and 0.8, respectively) compared with FAT, and the sensitivity and specificity of the N gene were 87% (95% CI: 66-100%) and 100% (95% CI: 98-100%), respectively, and those of the G gene were 80% (95% CI: 56-100%) and 100% (95% CI: 98-100%), respectively. Histologic lesions observed were lymphoplasmacytic meningoencephalitis, gliosis, and neuronophagia. The agreement observed between the FAT and RDT tests suggests that RDT is an accurate tool for the detection of RABV. Histopathology can be used to confirm lesions caused by RABV and to rule out other conditions; the RT-PCR assay is useful for molecular epidemiology studies.

Comparative evaluation of RT-PCR and antigen-based rapid diagnostic tests (Ag-RDTs) for SARS-CoV-2 detection: performance, variant specificity, and clinical implications.

The COVID-19 pandemic has highlighted the critical need for accurate and efficient diagnostic tools for detecting severe acute respiratory coronavirus 2 (SARS-CoV-2) infections. This study presents a comparison of two diagnostic tests: RT-PCR and antigen detection rapid diagnostic tests (Ag-RDTs). This study focused on their performance, variant specificity, and their clinical implications. A simultaneous testing of 268 samples was carried out for SARS-CoV-2 using RT-PCR and Ag-RDTs [flourescence immunoassay (FIA) and lateral flow immunoassay (LFIA)]. Viral load was quantified, and variant identification was performed using a PCR-based assay. The prevalence was found to be 30.2% using reverse transcription PCR (RT-PCR), 26.5% using FIA, and 25% using LFIA. When comparing the FIA and LFIA, the overall diagnostic performance was found to be 80.25% vs 76.54%, 96.79% vs 97.33%, 91.55% vs 90.51%, and 91.88% vs 92.56% for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), respectively. Both Ag-RDTs showed a strong agreement with RT-PCR (κ = 0.78-0.80). The overall accuracies of the FIA and LFIA were 92.41% and 92.13%, respectively. The FIA showed higher sensitivity (73.68%) and PPV (92.08%) than the LFIA (65.79% and 90.56%, respectively) in asymptomatic patients. At low Ct values (<25), both Ag-RDTs had 100% sensitivity, but the sensitivity reduced to 31.82% for FIA and 27.27% for LFIA at Ct values > 30. The diagnostic sensitivity of FIA compared to LFIA for detecting the Alpha variant was 78.85% vs. 69.23% and 72.22% vs. 83.33% for the Delta variant. Both Ag-RDTs had 100% sensitivity for detecting Omicron. Both Ag-RDTs performed well in patients with high viral loads and Omicron variant infections compared to those infected with Alpha and Delta variants. This study confirms the comparable performance of RT-PCR and Ag-RDTs, specifically FIA and LFIA, for SARS-CoV-2 detection. The FIA showed higher sensitivity and PPV in asymptomatic cases, while both Ag-RDTs exhibited strong agreement with RT-PCR results. Notably, Ag-RDTs, particularly FIA, proved effective in detecting the Omicron variant and cases with high viral loads, highlighting their potential clinical utility in managing the COVID-19 pandemic.IMPORTANCEThis study is of utmost importance in providing effective responses to manage the COVID-19 pandemic. It rigorously compares the diagnostic accuracy, variant specificity, and practical considerations of reverse transcription PCR (RT-PCR) and antigen detection rapid diagnostic tests (Ag-RDTs) for severe acute respiratory coronavirus 2 (SARS-CoV-2), answering critical questions. The results of this study will help healthcare professionals choose the appropriate testing methods, allocate resources effectively, and enhance public health strategies. Given the evolution of the virus, understanding the performance of these diagnostic tools is crucial to adapting to emerging variants. Additionally, the study provides insights into logistical challenges and accessibility issues, which will contribute to refining testing workflows, particularly in resource-limited settings. Ultimately, the study's impact extends to global healthcare, providing valuable information for policymakers, clinicians, and public health officials as they work together for mitigating the impact of the pandemic.

Evaluation of different genomic regions of rotavirus B and rotavirus C for development of real-time RT‒PCR assays.

BACKGROUND: The causative agents of diarrhea, rotavirus B (RVB) and rotavirus C (RVC) are common in adults and patients of all age groups, respectively. Due to the Rotavirus A (RVA) vaccination program, a significant decrease in the number of gastroenteritis cases has been observed globally. The replacement of RVA infections with RVB, RVC, or other related serogroups is suspected due to the possibility of reducing natural selective constraints due to RVA infections. The data available on RVB and RVC incidence are scant due to the lack of cheap and rapid commercial diagnostic assays and the focus on RVA infections. The present study aimed to develop real-time RT‒PCR assays using the data from all genomic RNA segments of human RVB and RVC strains available in the Gene Bank. RESULTS: Among the 11 gene segments, NSP3 and NSP5 of RVB and the VP6 gene of RVC were found to be suitable for real-time RT‒PCR (qRT‒PCR) assays. Fecal specimens collected from diarrheal patients were tested simultaneously for the presence of RVB (n = 192) and RVC (n = 188) using the respective conventional RT‒PCR and newly developed qRT‒PCR assays. All RVB- and RVC-positive specimens were reactive in their respective qRT‒PCR assays and had Ct values ranging between 23.69 and 41.97 and 11.49 and 36.05, respectively. All known positive and negative specimens for other viral agents were nonreactive, and comparative analysis showed 100% concordance with conventional RT‒PCR assays. CONCLUSIONS: The suitability of the NSP5 gene of RVB and the VP6 gene of RVC was verified via qRT‒PCR assays, which showed 100% sensitivity and specificity. The rapid qRT‒PCR assays developed will be useful diagnostic tools, especially during diarrheal outbreaks for testing non-RVA rotaviral agents and reducing the unnecessary use of antibiotics.

Developing an interpretation model for body fluid identification.

Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenarios, alternative molecular methods are required. An example of this is the detection of menstrual fluid and vaginal material, which are not able to be identified using conventional techniques. Endpoint reverse-transcription PCR (RT-PCR) is currently used for this purpose to amplify body fluid specific messenger RNA (mRNA) transcripts in forensic casework. Real-time quantitative reverse-transcription PCR (RT-qPCR) is a similar method but utilises fluorescent markers to generate quantitative results in the form of threshold cycle (Cq) values. Despite the uncertainty surrounding body fluid identification, most interpretation guidelines utilise categorical statements. Probabilistic modelling is more realistic as it reflects biological variation as well as the known performance of the method. This research describes the application of various machine learning models to single-source mRNA profiles obtained by RT-qPCR and assesses their performance. Multinomial logistic regression (MLR), Naïve Bayes (NB), and linear discriminant analysis (LDA) were used to discriminate between the following body fluid categories: saliva, circulatory blood, menstrual fluid, vaginal material, and semen. We identified that the performance of MLR was somewhat improved when the quantitative dataset of the original Cq values was used (overall accuracy of approximately 0.95) rather than presence/absence coded data (overall accuracy of approximately 0.94). This indicates that the quantitative information obtained by RT-qPCR amplification is useful in assigning body fluid class. Of the three classification methods, MLR performed the best. When we utilised receiver operating characteristic curves to observe performance by body fluid class, it was clear that all methods found difficulty in classifying menstrual blood samples. Future work will involve the modelling of body fluid mixtures, which are common in samples analysed as part of sexual assault investigations.