A targeted LC-MRM3 proteomic approach for the diagnosis of SARS-CoV-2 infection in nasopharyngeal swabs.

Since its first appearance, SARS-CoV-2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein (NCAP). A highly selective multiple reaction monitoring MRM3 strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM3 approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral NCAP peptides from nasopharyngeal swabs samples presenting a cycle threshold (Ct) value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immuno-purification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with Ct-values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted mass spectrometry.

Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples.

Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples. IMPORTANCE: Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.

A multicenter evaluation of the QIAstat-Dx meningitis-encephalitis syndromic test kit as compared to the conventional diagnostic microbiology workflow.

PURPOSE: Rapid diagnosis and treatment of infectious meningitis and encephalitis (ME) is critical to minimize morbidity and mortality. Recently, Qiagen introduced the CE-IVD QIAstat-Dx ME panel (QS-ME) for syndromic diagnostic testing of meningitis and encephalitis. Some data on the performance of the QS-ME in comparison to the BioFire FilmArray ME panel are available. In this study, the performance of the QS-ME is compared to the current diagnostic workflow in two academic medical centers in the Netherlands. METHODS: A total of 110 cerebrospinal fluid samples were retrospectively tested with the QS-ME. The results obtained were compared to the results of laboratory-developed real-time PCR assays (LDTs), IS-pro, bacterial culture, and cryptococcal antigen (CrAg) testing. In addition, the accuracy of the QS-ME was also investigated using an external quality assessment (EQA) panel consisting of ten samples. RESULTS: Four of the 110 samples tested failed to produce a valid QS-ME result. In the remaining 106 samples, the QS-ME detected 53/53 viral targets, 38/40 bacterial targets, and 7/13 Cryptococcus neoformans targets. The discrepant bacterial results consisted of two samples that were previously tested positive for Listeria monocytogenes (CT 35.8) and Streptococcus pneumoniae (CT 40), respectively. The QS-ME detected one additional result, consisting of a varicella-zoster virus signal (CT 35.9), in a sample in which both techniques detected Streptococcus pyogenes. Finally, 100% concordance was achieved in testing a blinded bacterial ME EQA panel. CONCLUSION: The QS-ME is a relevant addition to the syndromic testing landscape to assist in diagnosing infectious ME.

A core-genome multilocus sequence typing scheme for the detection of genetically related Streptococcus pyogenes clusters.

The recently observed increase in invasive Streptococcus pyogenes infections causes concern in Europe. However, conventional molecular typing methods lack discriminatory power to aid investigations of outbreaks caused by S. pyogenes. Therefore, there is an urgent need for high-resolution molecular typing methods to assess genetic relatedness between S. pyogenes isolates. In the current study, we aimed to develop a novel high-resolution core-genome multilocus sequence typing (cgMLST) scheme for S. pyogenes and compared its discriminatory power to conventional molecular typing methods. The cgMLST scheme was designed with the commercial Ridom SeqSphere+ software package. To define a cluster threshold, the scheme was evaluated using publicly available data from nine defined S. pyogenes outbreaks in the United Kingdom. The cgMLST scheme was then applied to 23 isolates from a suspected S. pyogenes outbreak and 117 S. pyogenes surveillance isolates both from the Netherlands. MLST and emm-typing results were used for comparison to cgMLST results. The allelic differences between isolates from defined outbreaks ranged between 6 and 31 for isolates with the same emm-type, resulting in a proposed cluster threshold of <5 allelic differences out of 1,095 target loci. Seven out of twenty-three (30%) isolates from the suspected outbreak had an allelic difference of <2, thereby identifying a potential cluster that could not be linked to other isolates. The proposed cgMLST scheme shows a higher discriminatory ability when compared to conventional typing methods. The rapid and simple analysis workflow allows for extended detection of clusters of potential outbreak isolates and surveillance and may facilitate the sharing of sequencing results between (inter)national laboratories.

A comparison of five Illumina, Ion Torrent, and nanopore sequencing technology-based approaches for whole genome sequencing of SARS-CoV-2.

Rapid identification of the rise and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern remains critical for monitoring of the efficacy of diagnostics, therapeutics, vaccines, and control strategies. A wide range of SARS-CoV-2 next-generation sequencing (NGS) methods have been developed over the last years, but cross-sequence technology benchmarking studies have been scarce. In the current study, 26 clinical samples were sequenced using five protocols: AmpliSeq SARS-CoV-2 (Illumina), EasySeq RC-PCR SARS-CoV-2 (Illumina/NimaGen), Ion AmpliSeq SARS-CoV-2 (Thermo Fisher), custom primer sets (Oxford Nanopore Technologies (ONT)), and capture probe-based viral metagenomics (Roche/Illumina). Studied parameters included genome coverage, depth of coverage, amplicon distribution, and variant calling. The median SARS-CoV-2 genome coverage of samples with cycle threshold (Ct) values of 30 and lower ranged from 81.6 to 99.8% for, respectively, the ONT protocol and Illumina AmpliSeq protocol. Correlation of coverage with PCR Ct values varied per protocol. Amplicon distribution signatures differed across the methods, with peak differences of up to 4 log10 at disbalanced positions in samples with high viral loads (Ct values ≤ 23). Phylogenetic analyses of consensus sequences showed clustering independent of the workflow used. The proportion of SARS-CoV-2 reads in relation to background sequences, as a (cost-)efficiency metric, was the highest for the EasySeq protocol. The hands-on time was the lowest when using EasySeq and ONT protocols, with the latter additionally having the shortest sequence runtime. In conclusion, the studied protocols differed on a variety of the studied metrics. This study provides data that assist laboratories when selecting protocols for their specific setting.

External Quality Assessment of SARS-CoV-2 Sequencing: an ESGMD-SSM Pilot Trial across 15 European Laboratories.

This first pilot trial on external quality assessment (EQA) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whole-genome sequencing, initiated by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Genomic and Molecular Diagnostics (ESGMD) and the Swiss Society for Microbiology (SSM), aims to build a framework between laboratories in order to improve pathogen surveillance sequencing. Ten samples with various viral loads were sent out to 15 clinical laboratories that had free choice of sequencing methods and bioinformatic analyses. The key aspects on which the individual centers were compared were the identification of (i) single nucleotide polymorphisms (SNPs) and indels, (ii) Pango lineages, and (iii) clusters between samples. The participating laboratories used a wide array of methods and analysis pipelines. Most were able to generate whole genomes for all samples. Genomes were sequenced to various depths (up to a 100-fold difference across centers). There was a very good consensus regarding the majority of reporting criteria, but there were a few discrepancies in lineage and cluster assignments. Additionally, there were inconsistencies in variant calling. The main reasons for discrepancies were missing data, bioinformatic choices, and interpretation of data. The pilot EQA was overall a success. It was able to show the high quality of participating laboratories and provide valuable feedback in cases where problems occurred, thereby improving the sequencing setup of laboratories. A larger follow-up EQA should, however, improve on defining the variables and format of the report. Additionally, contamination and/or minority variants should be a further aspect of assessment.

Evaluation of the Genmark ePlex® and QIAstat-Dx® respiratory pathogen panels in detecting bacterial targets in lower respiratory tract specimens.

BACKGROUND: The ePlex® and QIAstat-Dx® respiratory pathogen panels detect multiple respiratory pathogens, mainly viruses but also Legionella pneumophila, Mycoplasma pneumoniae and Bordetella pertussis. The assays have been marketed for use in nasopharyngeal swab specimens. For diagnosing bacterial pneumonia, lower respiratory tract (LRT) specimens are indicated. Aim of this study was to evaluate the performance of these syndromic panels for these three bacterial targets in samples from the LRT. Fifty-six specimens were collected from our repositories, five negative samples and fifty-one samples which had been previously tested positive with the routine diagnostic real-time PCR assays for Legionella spp. (N = 20), Bordetella spp. (N = 16) or M. pneumoniae (N = 15). RESULTS: The QIAstat-Dx Respiratory Panel V2 (RP) assay detected all of the L. pneumophila and B. pertussis positive samples but only 11/15 (73.3 %) of the M. pneumoniae targets. The ePlex Respiratory Pathogen Panel (RPP) assay detected 10/14 (71.4 %) of the L. pneumophila targets, 8/12 (66.7 %) of the B. pertussis positive samples and 13/15 (86.7 %) of the M. pneumoniae targets. CONCLUSIONS: No false-positive results were reported for all three bacterial pathogens by both assays. The clinical performance of both assays depended highly on the bacterial load in the sample and the type of specimen under investigation.

Performance of the QIAstat-Dx Gastrointestinal Panel for Diagnosing Infectious Gastroenteritis.

Detection and identification of enteropathogens that cause infectious gastroenteritis are essential steps for appropriate patient treatment and effective isolation precautions. Several syndrome-based tests have recently become available, with the gastrointestinal panel (GIP) assay on the QIAstat-Dx as the most recent addition to the syndromic testing landscape. The QIAstat-Dx GIP assay offers simultaneous testing for 24 bacterial, viral, and parasitic enteropathogens using a single test that reports the results in 70 min. In this study, we compared the performance of the GIP assay to laboratory-developed real-time PCR assays (LDTs), using 172 prospectively and retrospectively collected fecal samples from patients suspected to have infectious gastroenteritis. The GIP assay detected 97/107 enteropathogens (91%) that were detected by LDTs, and the overall agreement of results increased to 95% when excluding discrepant results with cycle threshold (CT ) values of >35. Further, the GIP assay detected 42 additional enteropathogens that were not detected, or tested, by LDTs. These included 35 diarrheagenic Escherichia coli targets for which the clinical relevance is unclear for most. The main advantage of the QIAstat-Dx system compared to other syndromic testing systems is the ability to generate CT values that could help with the interpretation of results. However, compared to LDTs, the GIP assay is limited by flexibility and high-throughput testing. In conclusion, the GIP assay offers an easy, sample-to-answer workflow with a rapid detection of the most common enteropathogens and therefore has the potential to direct appropriate therapy and infection control precautions.

Multicenter Evaluation of QIAstat-Dx Respiratory Panel V2 for Detection of Viral and Bacterial Respiratory Pathogens.

QIAstat-Dx Respiratory Panel V2 (RP) is a novel molecular-method-based syndromic test for the simultaneous and rapid (∼70-min) detection of 18 viral and 3 bacterial pathogens causing respiratory infections. This report describes the first multicenter retrospective comparison of the performance of the QIAstat-Dx RP assay to the established ePlex Respiratory Pathogen Panel (RPP) assay, for which we used 287 respiratory samples from patients suspected with respiratory infections. The QIAstat-Dx RP assay detected 312 (92%) of the 338 respiratory targets that were detected by the ePlex RPP assay. Most of the discrepant results have been observed in the low-pathogen-load samples. In addition, the QIAstat-Dx RP assay detected 19 additional targets in 19 respiratory samples that were not detected by the ePlex RPP assay. Nine of these discordant targets were considered to represent true positives after discrepancy testing by a third method. The main advantage of the QIAstat-Dx system compared to other syndromic testing systems, including the ePlex RPP assay, is the ability to generate cycle threshold (CT ) values, which could help with the interpretation of results. Taking the data together, this study showed good performance of the QIAstat-Dx RP assay in comparison to the ePlex RPP assay for the detection of respiratory pathogens. The QIAstat-Dx RP assay offers a new, rapid, and accurate sample-to-answer multiplex panel for the detection of the most common viral and bacterial respiratory pathogens and therefore has the potential to direct appropriate therapy and infection control precautions.

Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory.

Recent advancements in next-generation sequencing (NGS) have provided the foundation for modern studies into the composition of microbial communities. The use of these NGS methods allows for the detection and identification of ('difficult-to-culture') microorganisms using a culture-independent strategy. In the field of routine clinical diagnostics however, the application of NGS is currently limited to microbial strain typing for epidemiological purposes only, even though the implementation of NGS for microbial community analysis may yield clinically important information. This lack of NGS implementation is due to many different factors, including issues relating to NGS method standardization and result reproducibility. In this review article, the authors provide a general introduction to the most widely used NGS methods currently available (i.e., targeted amplicon sequencing and shotgun metagenomics) and the strengths and weaknesses of each method is discussed. The focus of the publication then shifts toward 16S rRNA gene NGS methods, which are currently the most cost-effective and widely used NGS methods for research purposes, and are therefore more likely to be successfully implemented into routine clinical diagnostics in the short term. In this respect, the experimental pitfalls and biases created at each step of the 16S rRNA gene NGS workflow are explained, as well as their potential solutions. Finally, a novel diagnostic microbiota profiling platform ('MYcrobiota') is introduced, which was developed by the authors by taking into consideration the pitfalls, biases, and solutions explained in this article. The development of the MYcrobiota, and future NGS methodologies, will help pave the way toward the successful implementation of NGS methodologies into routine clinical diagnostics.

Development and evaluation of a culture-free microbiota profiling platform (MYcrobiota) for clinical diagnostics.

Microbiota profiling has the potential to greatly impact on routine clinical diagnostics by detecting DNA derived from live, fastidious, and dead bacterial cells present within clinical samples. Such results could potentially be used to benefit patients by influencing antibiotic prescribing practices or to generate new classical-based diagnostic methods, e.g., culture or PCR. However, technical flaws in 16S rRNA gene next-generation sequencing (NGS) protocols, together with the requirement for access to bioinformatics, currently hinder the introduction of microbiota analysis into clinical diagnostics. Here, we report on the development and evaluation of an "end-to-end" microbiota profiling platform (MYcrobiota), which combines our previously validated micelle PCR/NGS (micPCR/NGS) methodology with an easy-to-use, dedicated bioinformatics pipeline. The newly designed bioinformatics pipeline processes micPCR/NGS data automatically and summarizes the results in interactive, but simple web reports. In order to explore the utility of MYcrobiota in clinical diagnostics, 47 clinical samples (40 "damaged skin" samples and 7 synovial fluids) were investigated using routine bacterial culture as comparator. MYcrobiota confirmed the presence of bacterial DNA in 37/37 culture-positive samples and detected bacterial taxa in 2/10 culture-negative samples. Moreover, 36/38 potentially relevant aerobic bacterial taxa and 3/3 mixtures of anaerobic bacteria were identified using culture and MYcrobiota, with the sensitivity and specificity being 95%. Interestingly, the majority of the 448 bacterial taxa identified using MYcrobiota were not identified using culture, which could potentially have an impact on clinical decision-making. Taken together, the development of MYcrobiota is a promising step towards the introduction of microbiota analysis into clinical diagnostic laboratories.

Characterization of the nasopharyngeal and middle ear microbiota in gastroesophageal reflux-prone versus gastroesophageal reflux non-prone children.

Otitis media (OM) is one of the most common pediatric infections worldwide, but the complex microbiology associated with OM is poorly understood. Previous studies have shown an association between OM and gastroesophageal reflux (GER) in children. Therefore, in order to bridge the gap in our current understanding of the interaction between GER and OM, we investigated the nasopharyngeal and middle ear microbiota of children suffering from GER-associated OM and OM only, using culture-independent 16S rRNA gene sequencing. Middle ear fluid, nasopharyngeal swabs, and clinical data were collected as part of a prospective pilot study conducted at the Department of Otorhinolaryngology of the Erasmus MC-Sophia Children's Hospital, Rotterdam, the Netherlands. A total of 30 children up to 12 years of age who suffered from recurrent acute otitis media (AOM) (5), chronic otitis media with effusion (OME) (23), or both (2), and who were listed for tympanostomy tube placement, were included in the study. Nine children were included in the GER-associated OM cohort and 21 in the OM-only cohort. We found no obvious effect of GER on the nasopharyngeal and middle ear microbiota between the two groups of children. However, our results highlight the need to assess the true role of Alloiococcus spp. and Turicella spp. in children presenting with a high prevalence of recurrent AOM and chronic OME.

Automating the Illumina DNA library preparation kit for whole genome sequencing applications on the flowbot ONE liquid handler robot.

Whole-genome sequencing (WGS) is currently making its transition from research tool into routine (clinical) diagnostic practice. The workflow for WGS includes the highly labor-intensive library preparations (LP), one of the most critical steps in the WGS procedure. Here, we describe the automation of the LP on the flowbot ONE robot to minimize the risk of human error and reduce hands-on time (HOT). For this, the robot was equipped, programmed, and optimized to perform the Illumina DNA Prep automatically. Results obtained from 16 LP that were performed both manually and automatically showed comparable library DNA yields (median of 1.5-fold difference), similar assembly quality values, and 100% concordance on the final core genome multilocus sequence typing results. In addition, reproducibility of results was confirmed by re-processing eight of the 16 LPs using the automated workflow. With the automated workflow, the HOT was reduced to 25 min compared to the 125 min needed when performing eight LPs using the manual workflow. The turn-around time was 170 and 200 min for the automated and manual workflow, respectively. In summary, the automated workflow on the flowbot ONE generates consistent results in terms of reliability and reproducibility, while significantly reducing HOT as compared to manual LP.

Multicenter benchmarking of short and long read wet lab protocols for clinical viral metagenomics.

Metagenomics is gradually being implemented for diagnosing infectious diseases. However, in-depth protocol comparisons for viral detection have been limited to individual sets of experimental workflows and laboratories. In this study, we present a benchmark of metagenomics protocols used in clinical diagnostic laboratories initiated by the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS). A mock viral reference panel was designed to mimic low biomass clinical specimens. The panel was used to assess the performance of twelve metagenomic wet lab protocols currently in use in the diagnostic laboratories of participating ENNGS member institutions. Both Illumina and Nanopore, shotgun and targeted capture probe protocols were included. Performance metrics sensitivity, specificity, and quantitative potential were assessed using a central bioinformatics pipeline. Overall, viral pathogens with loads down to 104 copies/ml (corresponding to CT values of 31 in our PCR assays) were detected by all the evaluated metagenomic wet lab protocols. In contrast, lower abundant mixed viruses of CT values of 35 and higher were detected only by a minority of the protocols. Considering the reference panel as the gold standard, optimal thresholds to define a positive result were determined per protocol, based on the horizontal genome coverage. Implementing these thresholds, sensitivity and specificity of the protocols ranged from 67 to 100 % and 87 to 100 %, respectively. A variety of metagenomic protocols are currently in use in clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implying the need for standardization of metagenomic analysis for use in clinical settings.

Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 3,960,704 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of March 2023, viewable at https://viridian.taxonium.org. Each genome was constructed using a novel assembly tool called Viridian (https://github.com/iqbal-lab-org/viridian), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. Phase 2 of our project will address the fact that the data in the public archives is heavily geographically biased towards the Global North. We therefore have contributed new raw data to ENA/SRA from many countries including Ghana, Thailand, Laos, Sri Lanka, India, Argentina and Singapore. We will incorporate these, along with all public raw data submitted between March 2023 and the current day, into an updated set of assemblies, and phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

Improved Diagnostics in Bacterial Neonatal Meningitis Using a Next-Generation Sequencing Platform.

INTRODUCTION: Bacterial meningitis in infants is an infrequent but life-threatening condition. Empiric therapy should begin as soon as meningitis is thought likely. Consequently, the causative microorganisms may not always be detected using culturing techniques, as cerebrospinal fluid (CSF) cultures are influenced by antibiotics. Nucleic acid amplification tests, such as polymerase chain reaction (PCR) (multiplex panels), may overcome this limitation but require a priori knowledge of the likely pathogen present within the sample. With this in mind, we investigated to what extent a culture-free, broad-range 16S rRNA gene next-generation sequencing (NGS) platform (MYcrobiota) could add to the microbiological diagnosis of meningitis. METHODS: Retrospective cohort study at level III neonatal intensive care unit. Included were all infants with suspected meningitis admitted between 10 November 2017 and 31 December 2020. A comparison was made of the bacterial pathogen detection rate between MYcrobiota and conventional bacterial culture. RESULTS: In a 3-year period, 37 CSF samples (diagnostic and follow-up) from 35 infants with proven or possible meningitis were available for MYcrobiota testing. MYcrobiota detected the presence of bacterial pathogens in 11 samples (30%), in contrast with the conventional CSF culture, which detected bacteria in 2 of 36 samples (5.6%). CONCLUSION: Addition of 16S rRNA sequencing to conventional culturing greatly improved the identification of the aetiology of bacterial meningitis compared to culturing of CSF samples alone.

The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections.

BACKGROUND: The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. RESULTS: Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). CONCLUSIONS: We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections.

Convalescent Plasma in a Patient with Protracted COVID-19 and Secondary Hypogammaglobulinemia Due to Chronic Lymphocytic Leukemia: Buying Time to Develop Immunity?

It is not exactly clear yet which type of immune response prevails to accomplish viral clearance in coronavirus disease 2019 (COVID-19). Studying a patient with chronic lymphocytic leukemia and hypogammaglobulinemia who suffered from COVID-19 provided insight in the immunological responses after treatment with COVID-19 convalescent plasma (CCP). Treatment consisted of oxygen, repeated glucocorticosteroids and multiple dosages of CCP guided by antibody levels. Retrospectively performed humoral and cellular immunity analysis made clear that not every serological test for COVID-19 is appropriate for follow-up of sufficient neutralizing antibodies after CCP. In retrospect, we think that CCP merely bought time for this patient to develop an adequate cellular immune response which led to viral clearance and ultimately clinical recovery.

Increasing diagnostic possibilities using the geneLEAD VIII platform for detection of SARS-CoV-2.

At the time SARS-CoV-2 was identified as the cause of coronavirus disease 2019 (COVID-19) no in vitro diagnostic (IVD) tests were available since it was a new virus. Very shortly after the release of the genomic sequence of SARS-CoV-2, laboratory-developed tests (LDTs) were developed, made available and implemented in several laboratories in the Netherlands and globally. In this study, the performance of an E-gene Sarbeco specific real-time reverse-transcriptase PCR (RT-PCR) was verified on the open modus of the geneLEAD VIII sample-to-answer platform. The results obtained from 134 clinical samples, of which 63 had been tested positive, showed almost complete concordance compared to the same PCR on the routine diagnostic systems and that was validated according to the national reference standard. The only discordant sample tested positive using the routine diagnostic workflow with a cycle threshold (CT) value of 37.7, while the sample tested negative using the geneLEAD VIII workflow. In addition, good performance was achieved in analyzing a blinded SARS-CoV-2 external quality assurance (EQA) panel. Implementation of the geneLEAD VIII platform as routine diagnostic tool resulted in testing 871 clinical samples with 115 positive results. In conclusion, the geneLEAD VIII SARS-CoV-2 workflow presented in this study showed excellent diagnostic performance and with a rapid turnaround time of approximately two hours it proved a valuable option for STAT SARS-CoV-2 testing in the absence of (rapid, CE-IVD) point-of-care testing platforms.