The Drift in Molecular Testing for Influenza: Mutations Affecting Assay Performance

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time

With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first real-time, reagent-free, portable analysis platform for viral detection in liquid saliva, using COVID-19 as a proof-of-concept. We show that vibrational molecular spectroscopy and machine learning (ML) detect biomolecular changes consistent with the presence of viral infection. Saliva samples were collected from 470 individuals, including 65 that were infected with COVID-19 (28 from hospitalized patients and 37 from a walk-in testing clinic) and 251 that had a negative polymerase chain reaction (PCR) test. A further 154 were collected from healthy volunteers. Saliva measurements were achieved in 6 minutes or less and led to machine learning models predicting COVID-19 infection with sensitivity and specificity reaching 90%, depending on volunteer symptoms and disease severity. Machine learning models were based on linear support vector machines (SVM). This platform could be deployed to manage future pandemics using the same hardware but using a tunable machine learning model that could be rapidly updated as new viral strains emerge.

Key performance evaluation of commercialized multiplex rRT-PCR kits for respiratory viruses: implications for application and optimization

Respiratory tract infections (RTIs) caused by viruses are prevalent and significant conditions in clinical settings. Accurate and effective detection is of paramount importance in the diagnosis, treatment, and prevention of viral RTIs. With technological advancements, multiplex real-time reverse transcription polymerase chain reaction (rRT-PCR) assays have been developed and extensively adopted for the diagnosis of viral RTIs. Given the potential challenges in the detection performance of multiplex assays, this study evaluated the analytical sensitivity and competitive interference of the six most commonly used multiplex rRT-PCR kits for detection of respiratory viruses in China. The results revealed that the limits of detection were variable across the viruses and kits. Most of the evaluated multiplex kits demonstrated comparable or enhanced analytical sensitivity compared with singleplex kits for clinically significant viruses, including human adenovirus (HAdV)-3, HAdV-7, Omicron BA.5, H1N1pdm09, H3N2, B/Victoria, respiratory syncytial virus subtype A, and respiratory syncytial virus subtype B, whereas multiplex kits showed relatively less analytical sensitivity for human rhinovirus-B72, human metapneumovirus-A2, parainfluenza virus (PIV)-1, and PIV-3. In addition, most multiplex kits successfully identified co-infections when one analyte was present at a low concentration and another analyte was present at a high concentration.

IMPORTANCE

The complexity and severity of viral respiratory tract infections (RTIs) emphasize the pivotal role of precise diagnosis for viral RTIs in guiding effective public health responses and ensuring appropriate medical interventions, given the substantial population at risk. This study highlights the necessity and importance of evaluating the analytical validity of multiplex real-time reverse transcription polymerase chain reaction assays, offering valuable insights into their optimization and application.

Protocol for the creation and characterization of SARS-CoV-2 variant testing panels using remnant clinical samples for diagnostic assay testing

The emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Alpha variant in 2020 demonstrated the need for reanalysis of diagnostic tests to ensure detection of emerging variants. Here, we present a protocol for creating and characterizing SARS-CoV-2 variant testing panels using remnant clinical samples for diagnostic assay testing. We describe steps for characterizing SARS-CoV-2 remnant clinical samples and preparing them into pools and their use in preparing varying quantities of virus. We then detail procedures for verifying variant detection using the resulting sample panel. For complete details on the use and execution of this protocol, please refer to Rao et al.1,2.

Global genomic diversity and conservation of SARS-CoV-2 since the COVID-19 outbreak

IMPORTANCE

Our results indicate that most severe acute respiratory syndrome coronavirus 2 genomes sampled from patients had a mutation rate ≤1.07 ‰ and genome-tail proteins (including S protein) were the main sources of genetic polymorphism. The analysis of the virus-host interaction network of genome-tail proteins showed that they shared some antiviral signaling pathways, especially the intracellular protein transport pathway.

Nano-based techniques: A revolutionary approach to prevent covid-19 and enhancing human awareness

In every century of history, there are many new diseases emerged, which are not even cured by many developed countries. Today, despite of scientific development, new deadly pandemic diseases are caused by microorganisms. Hygiene is considered to be one of the best methods of avoiding such communicable diseases, especially viral diseases. Illness caused by SARS-CoV-2 was termed COVID-19 by the WHO, the acronym derived from "coronavirus disease 2019. The globe is living in the worst epidemic era, with the highest infection and mortality rate owing to COVID-19 reaching 6.89% (data up to March 2023). In recent years, nano biotechnology has become a promising and visible field of nanotechnology. Interestingly, nanotechnology is being used to cure many ailments and it has revolutionized many aspects of our lives. Several COVID-19 diagnostic approaches based on nanomaterial have been developed. The various metal NPs, it is highly anticipated that could be viable and economical alternatives for treating drug resistant in many deadly pandemic diseases in near future. This review focuses on an overview of nanotechnology's increasing involvement in the diagnosis, prevention, and therapy of COVID-19, also this review provides readers with an awareness and knowledge of importance of hygiene.

Enhanced Arbovirus Surveillance with High-Throughput Metatranscriptomic Processing of Field-Collected Mosquitoes

Surveillance programs are essential for the prevention and control of mosquito-borne arboviruses that cause serious human and animal diseases. Viral metatranscriptomic sequencing can enhance surveillance by enabling untargeted, high-throughput arbovirus detection. We used metatranscriptomic sequencing to screen field-collected mosquitoes for arboviruses to better understand how metatranscriptomics can be utilised in routine surveillance. Following a significant flood event in 2016, more than 56,000 mosquitoes were collected over seven weeks from field traps set up in Victoria, Australia. The traps were split into samples of 1000 mosquitoes or less and sequenced on the Illumina HiSeq. Five arboviruses relevant to public health (Ross River virus, Sindbis virus, Trubanaman virus, Umatilla virus, and Wongorr virus) were detected a total of 33 times in the metatranscriptomic data, with 94% confirmed using reverse transcription quantitative PCR (RT-qPCR). Analysis of metatranscriptomic cytochrome oxidase I (COI) sequences enabled the detection of 12 mosquito and two biting midge species. Screening of the same traps by an established public health arbovirus surveillance program corroborated the metatranscriptomic arbovirus and mosquito species detections. Assembly of genome sequences from the metatranscriptomic data also led to the detection of 51 insect-specific viruses, both known and previously undescribed, and allowed phylogenetic comparison to past strains. We have demonstrated how metatranscriptomics can enhance surveillance by enabling untargeted arbovirus detection, providing genomic epidemiological data, and simultaneously identifying vector species from large, unsorted mosquito traps.

Multiplex Target-Redundant RT-LAMP for Robust Detection of SARS-CoV-2 Using Fluorescent Universal Displacement Probes

The increasing prevalence of variant lineages during the COVID-19 pandemic has the potential to disrupt molecular diagnostics due to mismatches between primers and variant templates. Point-of-care molecular diagnostics, which often lack the complete functionality of their high-throughput laboratory counterparts, are particularly susceptible to this type of disruption, which can result in false-negative results. To address this challenge, we have developed a robust Loop Mediated Isothermal Amplification assay with single tube multiplexed multitarget redundancy and an internal amplification control. A convenient and cost-effective target-specific fluorescence detection system allows amplifications to be grouped by signal using adaptable probes for pooled reporting of SARS-CoV-2 target amplifications or differentiation of the Internal Amplification Control. Over the course of the pandemic, primer coverage of viral lineages by the three redundant sub-assays has varied from assay to assay as they have diverged from the Wuhan-Hu-1 isolate sequence, but aggregate coverage has remained high for all variant sequences analyzed, with a minimum of 97.4% (Variant of Interest: Eta). In three instances (Delta, Gamma, Eta), a high-frequency mismatch with one of the three sub-assays was observed, but overall coverage remained high due to multitarget redundancy. When challenged with extracted human samples the multiplex assay showed 87% or better sensitivity (of 30 positive samples), with 100% sensitivity for samples containing greater than 30 copies of viral RNA per reaction (of 21 positive samples), and 100% specificity (of 60 negative samples). These results are further evidence that conventional laboratory methodologies can be leveraged at the point of care for robust performance and diagnostic stability over time. IMPORTANCE The COVID-19 pandemic has had tremendous impact, and the ability to perform molecular diagnostics in resource limited settings has emerged as a key resource for mitigating spread of the disease. One challenge in COVID-19 diagnosis, as well as other viruses, is ongoing mutation that can allow viruses to evade detection by diagnostic tests. We developed a test that detects multiple parts of the virus genome in a single test to reduce the chance of missing a virus due to mutation, and it is designed to be simpler and faster than typical laboratory tests while maintaining high sensitivity. This capability is enabled by a novel fluorescent probe technology that works with a simple constant temperature reaction condition.

Designing sensitive viral diagnostics with machine learning

Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome's conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants. Toward that goal, we screen 19,209 diagnostic-target pairs, concentrated on CRISPR-based diagnostics, and train a deep neural network to accurately predict diagnostic readout. We join this model with combinatorial optimization to maximize sensitivity over the full spectrum of a virus's genomic variation. We introduce Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT), a system for automated design, and use it to design diagnostics for 1,933 vertebrate-infecting viral species within 2 hours for most species and within 24 hours for all but three. We experimentally show that ADAPT's designs are sensitive and specific to the lineage level and permit lower limits of detection, across a virus's variation, than the outputs of standard design techniques. Our strategy could facilitate a proactive resource of assays for detecting pathogens.

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

SIGNIFICANCE

The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus.

AIM

We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents.

APPROACH

We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique-Raman spectroscopy-to detect changes in the molecular profile of saliva associated with COVID-19 infection.

RESULTS

We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%.

CONCLUSION

These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases.

Respiratory viral infections in pragmatically selected adults in intensive care units

Respiratory viruses can be detected in 18.3 to 48.9% of critically ill adults with severe respiratory tract infections (RTIs). The present study aims to assess the clinical significance of respiratory viruses in pragmatically selected adults in medical intensive care unit patients and to identify factors associated with viral respiratory viral tract infections (VRTIs). We conducted a prospective study on critically ill adults with suspected RTIs without recognized respiratory pathogens. Viral cultures with monoclonal antibody identification, in-house real-time polymerase chain reaction (PCR) for influenza virus, and FilmArray respiratory panel were used to detect viral pathogens. Multivariable logistic regression was applied to identify factors associated with VRTIs. Sixty-four (40.5%) of the included 158 critically ill adults had respiratory viruses detected in their respiratory specimens. The commonly detected viruses included influenza virus (20), followed by human rhinovirus/enterovirus (11), respiratory syncitial virus (9), human metapneumovirus (9), human parainfluenza viruses (8), human adenovirus (7), and human coronaviruses (2). The FilmArray respiratory panel detected respiratory viruses in 54 (34.6%) patients, but showed negative results for seven of 13 patients with influenza A/H3 infection. In the multivariable logistic regression model, patient characters associated with VRTIs included those aged < 65 years, household contact with individuals with upper RTI, the presence of fever, cough with sputum production, and sore throat. Respiratory viruses were not uncommonly detected in the pragmatically selected adults with critical illness. The application of multiplex PCR testing for respiratory viruses in selected patient population is a practical strategy, and the viral detection rate could be further improved by the patient characters recognized in this study.

Investigating the sequence variation in the influenza A matrix genes during the 2017-2018 and 2018-2019 seasons in samples from a local population in London

Recent publications have highlighted the emergence of mutations in the M1 gene of both influenza A H1N1pdm09 and H3N2 subtypes affecting the performance of commercial RT-PCR assays. Respiratory samples from the 2018/2019 season positive by our in-house RT-PCR for influenza A were analysed for the prevalence and impact of any M1 gene mutations. Sequence information was used to re-design primers for our routine assay and their performance assessed. Forty-five samples, consisting of 11 H1N1pdm09 and 34 H3N2 subtypes, together with the NIBSC H1N1 control were sequenced. All samples displayed the core mutations for H1N1 M1(C154T; G174A and G238A) and for H3N2 M1(C153T; C163T and G189T); three of the H1N1pdm09 viruses also showed a small number of point mutations. None of the mutations appeared to affect either the sensitivity or efficiency of the RT-PCR when compared to the re-designed primers. Although the mutations we found agreed with those in the publications cited we did not encounter any problems with our routine diagnostic assay and no improvements were found when the primers were modified to suit those mutations. However, it is likely that the influenza A virus M1 gene will accumulate further mutations that could impact RT-PCR assays and, therefore, it would be prudent to implement routine sequencing of samples during the influenza seasons to ensure no loss in assay performance.

Bridging the gaps in test interpretation of SARS-CoV-2 through Bayesian network modelling

In the absence of an established gold standard, an understanding of the testing cycle from individual exposure to test outcome report is required to guide the correct interpretation of severe acute respiratory syndrome-coronavirus-2 reverse transcriptase real-time polymerase chain reaction (RT-PCR) results and optimise the testing processes. Bayesian network models have been used within healthcare to bring clarity to complex problems. We use this modelling approach to construct a comprehensive framework for understanding the real-world predictive value of individual RT-PCR results.

We elicited knowledge from domain experts to describe the test process through a facilitated group workshop. A preliminary model was derived based on the elicited knowledge, then subsequently refined, parameterised and validated with a second workshop and one-on-one discussions.

Causal relationships elicited describe the interactions of pre-testing, specimen collection and laboratory procedures and RT-PCR platform factors, and their impact on the presence and quantity of virus and thus the test result and its interpretation. By setting the input variables as ‘evidence’ for a given subject and preliminary parameterisation, four scenarios were simulated to demonstrate potential uses of the model.

The core value of this model is a deep understanding of the total testing cycle, bridging the gap between a person's true infection status and their test outcome. This model can be adapted to different settings, testing modalities and pathogens, adding much needed nuance to the interpretations of results.

A brief review of influenza virus infection

Influenza is an acute viral respiratory infection that affects all age groups and is associated with high mortality during pandemics, epidemics, and sporadic outbreaks. Nearly 10% of the world's population is affected by influenza annually, with about half a million deaths each year. Influenza vaccination is the most effective method for preventing influenza infection and its complications. The influenza vaccine's efficacy varies each season based on the circulating influenza strains and vaccine uptake rates. Currently, three antiviral drugs targeting the influenza virus surface glycoprotein neuraminidase are available for treatment and prophylaxis of disease. Given the significant burden of influenza infection globally, this review is focused on the latest findings in the etiology, epidemiology, transmission, clinical manifestation, diagnosis, prevention, and treatment of influenza.

PANDAA intentionally violates conventional qPCR design to enable durable, mismatch-agnostic detection of highly polymorphic pathogens

Sensitive and reproducible diagnostics are fundamental to containing the spread of existing and emerging pathogens. Despite the reliance of clinical virology on qPCR, technical challenges persist that compromise their reliability for sustainable epidemic containment as sequence instability in probe-binding regions produces false-negative results. We systematically violated canonical qPCR design principles to develop a Pan-Degenerate Amplification and Adaptation (PANDAA), a point mutation assay that mitigates the impact of sequence variation on probe-based qPCR performance. Using HIV-1 as a model system, we optimized and validated PANDAA to detect HIV drug resistance mutations (DRMs). Ultra-degenerate primers with 3' termini overlapping the probe-binding site adapt the target through site-directed mutagenesis during qPCR to replace DRM-proximal sequence variation. PANDAA-quantified DRMs present at frequency ≥5% (2 h from nucleic acid to result) with a sensitivity and specificity of 96.9% and 97.5%, respectively. PANDAA is an innovative advancement with applicability to any pathogen where target-proximal genetic variability hinders diagnostic development.

Trends and Innovations in Biosensors for COVID-19 Mass Testing

Fast and widespread diagnosis is crucial to fighting against the outbreak of COVID-19. This work surveys the landscape of available and emerging biosensor technologies for COVID-19 testing. Molecular diagnostic assays based on quantitative reverse transcription polymerase chain reaction are used in most clinical laboratories. However, the COVID-19 pandemic has overwhelmed testing capacity and motivated the development of fast point-of-care tests and the adoption of isothermal DNA amplification. Antigenic and serological rapid tests based on lateral-flow immunoassays suffer from low sensitivity. Advanced digital systems enhance performance at the expense of speed and the need for large equipment. Emerging technologies, including CRISPR gene-editing tools, benefit from high sensitivity and specificity of molecular diagnostics and the easy use of lateral-flow assays. DNA sequencing and sample pooling strategies are highlighted to bring out the full capacity of the available biosensor technologies and accelerate mass testing.

Analysis of RNA sequences of 3636 SARS-CoV-2 collected from 55 countries reveals selective sweep of one virus type

BACKGROUND & OBJECTIVES

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus-2) is evolving with the progression of the pandemic. This study was aimed to investigate the diversity and evolution of the coronavirus SARS-CoV-2 with progression of the pandemic over time and to identify similarities and differences of viral diversity and evolution across geographical regions (countries).

METHODS

Publicly available data on type definitions based on whole-genome sequences of the SARS-CoV-2 sampled during December and March 2020 from 3636 infected patients spread over 55 countries were collected. Phylodynamic analyses were performed and the temporal and spatial evolution of the virus was examined.

RESULTS

It was found that (i) temporal variation in frequencies of types of the coronavirus was significant; ancestral viruses of type O were replaced by evolved viruses belonging to type A2a; (ii) spatial variation was not significant; with the spread of SARS-CoV-2, the dominant virus was the A2a type virus in every geographical region; (iii) within a geographical region, there was significant micro-level variation in the frequencies of the different viral types, and (iv) the evolved coronavirus of type A2a swept rapidly across all continents.

INTERPRETATION & CONCLUSIONS

SARS-CoV-2 belonging to the A2a type possesses a non-synomymous variant (D614G) that possibly eases the entry of the virus into the lung cells of the host. This may be the reason why the A2a type has an advantage to infect and survive and as a result has rapidly swept all geographical regions. Therefore, large-scale sequencing of coronavirus genomes and, as required, of host genomes should be undertaken in India to identify regional and ethnic variation in viral composition and its interaction with host genomes. Further, careful collection of clinical and immunological data of the host can provide deep learning in relation to infection and transmission of the types of coronavirus genomes.

Nanopore Sequencing Reveals Novel Targets for Detection and Surveillance of Human and Avian Influenza A Viruses

Accurate detection of influenza A virus (IAV) is crucial for patient management, infection control, and epidemiological surveillance. The World Health Organization and the Centers for Disease Control and Prevention have recommended using the M gene as the diagnostic gene target for reverse-transcription-PCR (RT-PCR). However, M gene RT-PCR has reduced sensitivity for recent IAV due to novel gene mutations. Here, we sought to identify novel diagnostic targets for the molecular detection of IAV using long-read third-generation sequencing. Direct nanopore sequencing from 18 nasopharyngeal specimens and one saliva specimen showed that the 5' and 3' ends of the PB2 gene and the entire NS gene were highly abundant. Primers selected for PB2 and NS genes were well matched with seasonal or avian IAV gene sequences. Our novel PB2 and NS gene real-time RT-PCR assays showed limits of detection similar to or lower than that of M gene RT-PCR and achieved 100% sensitivity and specificity in the detection of A(H1N1), A(H3N2), and A(H7N9) in nasopharyngeal and saliva specimens. For 10 patients with IAV detected by M gene RT-PCR conversion in sequentially collected specimens, NS and/or PB2 gene RT-PCR was positive in 2 (20%) of the initial specimens that were missed by M gene RT-PCR. In conclusion, we have shown that PB2 or NS gene RT-PCRs are suitable alternatives to the recommended M gene RT-PCR for diagnosis of IAV. Long-read nanopore sequencing facilitates the identification of novel diagnostic targets.

Panther Fusion® Respiratory Virus Assays for the detection of influenza and other respiratory viruses

BACKGROUND

Nucleic acid amplification tests (NAATs), such as PCR, are preferred for respiratory virus testing, due to superior diagnostic accuracy and faster turnaround time. Panther Fusion® Respiratory Assays (Fusion), which includes FluA/B/RSV (FFABR), Paraflu and AdV/hMPV/RV, offers a modular approach to syndromic testing on a fully automated platform while improving gene targets and expanding the test menu.

OBJECTIVES AND STUDY DESIGN

We evaluated Fusion using 275 consecutive nasopharyngeal specimens previously used in an analysis of five PCRs, as well as 225 archived specimens.

RESULTS

Of the combined 500 specimens, 134 were positive for influenza A (FluA), 54 for FluB, 65 for RSV, 64 for parainfluenza (PIV), 24 for adenovirus (AdV), 21 for humanmetapneumovirus (hMPV), and 40 for rhinovirus (RV) with Fusion. Of the positive samples Fusion correlated with historical results for all but one, despite multiple freeze-thaws cycles of this collection. Fusion was positive for an additional 33 samples, including 11 FluAs, 7 RSVs, 3 PIV3s, 3 AdV, 6 hMPV and 3 RVs. These samples were retested with corresponding Prodesse (Pro) assays using quadruple sample volume. This resolver test confirmed Fusion results for an additional 4 FluAs, 4 RSVs, 1 PIV3 and 3 AdVs. The sensitivity and specificity ranges of Fusion were 99-100% and 98-100%. Limit of detection (LOD) analyses were performed on a variety of Flu isolates. The LODs ranged from 2.69 to 2.99 log copies/ml and demonstrated superior LOD as compared to previously published data for some assays or to concurrent analyses with two new commercial tests.

New Subgenotyping and Consensus Real-Time Reverse Transcription-PCR Assays for Hepatitis A Outbreak Surveillance

Laboratory surveillance plays an important role in the detection and control of hepatitis A outbreaks and requires the application of rapid and accurate molecular diagnostic tools for hepatitis A virus (HAV) RNA detection, subgenotype identification, and sequence-based genotyping. We describe the development and validation of a triplex real-time, reverse transcription-PCR (triplex rRT-PCR) assay for the identification and discrimination of HAV subgenotypes IA, IB, and IIIA and a singleplex rRT-PCR assay designed to detect all HAV genotypes infecting humans. Overall, the accuracy, sensitivity, and specificity of the new assays were >97% for serum and plasma specimens collected during unrelated outbreaks of HAV in California and Michigan compared to a nested RT-PCR genotyping assay and the ISO 15216-1 rRT-PCR method for HAV detection. The new assays will permit the rapid detection of HAV RNA and discrimination among subgenotypes IA, IB, and IIIA in serum and plasma specimens, which will strengthen public health surveillance efforts for HAV outbreak detection and response.

Analytical and clinical evaluation of a point-of-care molecular diagnostic system and its influenza A/B assay for rapid molecular detection of the influenza virus

Recently, rapid molecular detection systems have been used for point-of-care testing for the diagnosis of influenza worldwide. Here, we evaluated the performance of the cobas Liat system and the cobas Influenza A/B assay (Liat) using fresh nasopharyngeal samples collected from a Japanese population between December 2017 and February 2018. The performance of the examination was compared with that of antigen testing and a conventional polymerase chain reaction (nested-PCR) method. A total of 159 patients were included in this study, and 77 tested positive using Liat. The concordance rate between Liat and nested PCR was 97.5%. The median time between the ordering of testing and completion of molecular analyses using Liat was 30 min (interquartile range: 28-35 min). The overall sensitivity and specificity of antigen testing were 57.1% and 100%, respectively. The duration from symptom onset to examination did not alter antigen testing sensitivity. The current study demonstrates the high performance of Liat for the rapid molecular identification of the influenza virus.

A novel PCR-based point-of-care method facilitates rapid, efficient, and sensitive diagnosis of influenza virus infection

OBJECTIVE

The aim of this single-centre study was the comparative analysis of the GeneXpert (Cepheid Inc.) and the LIAT (Roche) system for the rapid polymerase chain reaction (PCR)-based detection of influenza A (IA) and influenza B (IB) viruses.

PATIENTS AND METHODS

During the 2017-2018 flu season, 651 prospectively collected samples (throat and nasal swabs) of patients with symptoms of influenza-like illness or acute respiratory infection were tested for the presence of IA and IB viruses using the GeneXpert and LIAT systems. To evaluate the usefulness for near-patient testing, a LIAT system was installed at the Department of Emergency Medicine, and sample testing was performed on site. Reference testing of all samples was performed with the Xpert Flu assay and for 313 samples in addition with the Xpert Xpress Flu/RSV (respiratory syncytial virus) assay at the central laboratory. Analysis of all samples was carried out within 24 hr after collection.

RESULTS

Overall, 267 of the 651 samples analysed were positive for influenza viruses in at least one of the three assays investigated (IA, 88; IB, 179). The overall rates of agreement between the LIAT assay and the Xpert Flu assay was 96.0% for the detection of IA and IB viruses. The sensitivity and specificity of the LIAT assay compared to the Xpert Flu assay for the detection of IA was 98.80% (95% confidence interval (CI) 93.47-99.97%) and 99.12% (95% CI, 97.96% to 99.71%) and for the detection of IB 98.76% (95% CI 95.58-99.85%), and 96.33% (95% CI 94.26-97.81%), respectively. The LIAT assay showed a statistically significant higher detection rate of IB virus than the Xpert Flu assay (p <0.01). No significant difference was found between the detection rate of the LIAT assay and the Xpert Xpress Flu/RSV assay. The mean time to the availability of a definite test result was significantly shorter with the on-site LIAT system than the GeneXpert system (mean 59 min saving time; p <0.01).

CONCLUSION

The LIAT system represents a robust and highly sensitive point-of-care device for the rapid PCR-based detection of influenza A and influenza B viruses.

History of matrix genes mutations within PCR target regions among circulating influenza H3N2 clades over ten-plus-years

BACKGROUND

Emerging influenza A/H3N2 clades have been associated with M1 gene mutations which affect the performance of commercial PCR assays.

OBJECTIVES AND STUDY DESIGN

The evolution and prevalence of problematic M1 mutations, and their associated viral clades, were investigated. All European and USA isolates from the GISAID database with both HA and M1 sequences available, collected during the respiratory seasons from the Fall of 2007 through January of 2018, were analyzed.

RESULTS

Five M1 target region patterns, designated A-E, were observed in more than 10% of the isolates during a season, with patterns that appeared sequentially, each having one additional mutation. The C153T mutation was universal. Pattern A, which only had the single mutation, predominated between 2007/08 and 2009/10. Dual- and triple-mutation patterns (B and C) emerged in 2010/11 and 2011/12 respectively, and pattern C predominated for one season (2012/13). In 2012/13, the problematic quadruple-mutation containing C163T first appeared in 3C.2 viruses. Seasons 2013/14 and 14/15 were associated with significant viral diversity with five clades and four M1 patterns co-circulating, with different rates in Europe and the USA. Since 2014, clade 3C.2a with M1 pattern D has emerged as the predominant type. During 2016/17 season, a new quintuplet mutation pattern (E) emerged in cluster 3C.2a1 isolates.

CONCLUSIONS

M1 target region mutations have been prevalent for more than ten years, with the number of mutations continually increasing. Often population inferences of M1 mutations can be made based on viral clade. However, gene segment reassortment can affect predictive abilities.