Comparison of SARS-CoV-2 N gene real-time RT-PCR targets and commercially available mastermixes.

BACKGROUND: This study aimed to evaluate the impact of four different reverse transcription quantitative PCR (RT-qPCR) master mixes on the performance of SARS-CoV-2 diagnostic PCRs using three primer/probe assays targeting the N gene (A, B and C). The dynamic range and lowest detected quantity was determined using a SARS-CoV-2 partial N gene RNA transcript dilution series (100,000-1 copy/µl) and verified using 72 nose and throat swabs, 29 of which tested positive for SARS-CoV-2 RNA. RESULTS: Assay C consistently detected the lowest quantity of partial N gene RNA transcript with all mastermixes. The Takara One Step PrimeScript™ III RT-PCR Kit mastermix enabled all primer pairs to detect the entire dynamic range evaluated, with the Qiagen Quantifast and Thermofisher TaqPath 1-Step kits also performing well. Sequences from all three primer/probe sets tested in this study (assay A, B and C) have 100 % homology to ≥97 % of the of SARS-CoV-2 sequences available up to 31st December 2020 (n = 291,483 sequences). CONCLUSIONS: This work demonstrates that specific assays (in this case assay C) can perform well in terms of dynamic range and lowest detected quantity regardless of the mastermix used. However we also show that, by choosing the most appropriate mastermix, poorer performing primer pairs are also able to detect all of the template dilutions investigated. This work increases the potential options when choosing assays for SARS-CoV-2 diagnosis and provides solutions to enable them to work with optimal analytical sensitivity.

Single base mutations in the nucleocapsid gene of SARS-CoV-2 affects amplification efficiency of sequence variants and may lead to assay failure.

Reverse transcriptase quantitative PCR (RT-qPCR) is the main diagnostic assay used to detect SARS-CoV-2 RNA in respiratory samples. RT-qPCR is performed by specifically targeting the viral genome using complementary oligonucleotides called primers and probes. This approach relies on prior knowledge of the genetic sequence of the target. Viral genetic variants with changes to the primer/probe binding region may reduce the performance of PCR assays and have the potential to cause assay failure. In this work we demonstrate how two single nucleotide variants (SNVs) altered the amplification curve of a diagnostic PCR targeting the Nucleocapsid (N) gene and illustrate how threshold setting can lead to false-negative results even where the variant sequence is amplified. We also describe how in silico analysis of SARS-CoV-2 genome sequences available in the COVID-19 Genomics UK Consortium (COG-UK) and GISAID databases was performed to predict the impact of sequence variation on the performance of 22 published PCR assays. The vast majority of published primer and probe sequences contain sequence mismatches with at least one SARS-CoV-2 lineage. We recommend that visual observation of amplification curves is included as part of laboratory quality procedures, even in high throughput settings where thresholds are set automatically and that in silico analysis is used to monitor the potential impact of new variants on established assays. Ideally comprehensive in silico analysis should be applied to guide selection of highly conserved genomic regions to target with future SARS-CoV-2 PCR assays.

Boron Doped Diamond as a Low Biofouling Material in Aquatic Environments: Assessment of Pseudomonas aeruginosa Biofilm Formation.

Boron doped diamond (BDD), given the robustness of the material, is becoming an electrode of choice for applications which require long-term electrochemical monitoring of analytes in aqueous environments. However, despite the extensive work in this area, there are no studies which directly assess the biofilm formation (biofouling) capabilities of the material, which is an essential consideration because biofouling often causes deterioration in the sensor performance. Pseudomonas aeruginosa is one of the most prevalent bacterial pathogens linked to water-related diseases, with a strong capacity for forming biofilms on surfaces that are exposed to aquatic environments. In this study, we comparatively evaluate the biofouling capabilities of oxygen-terminated (O-)BDD against materials commonly employed as either the packaging or sensing element in water quality sensors, with an aim to identify factors which control biofilm formation on BDD. We assess the monospecies biofilm formation of P. aeruginosa in two different growth media, Luria-Bertani, a high nutrient source and drinking water, a low nutrient source, at two different temperatures (20 and 37 °C). Multispecies biofilm formation is also investigated. The performance of O-BDD, when tested against all other materials, promotes the lowest extent of P. aeruginosa monospecies biofilm formation, even with corrections made for total surface area (roughness). Importantly, O-BDD shows the lowest water contact angle of all materials tested, that is, greatest hydrophilicity, strongly suggesting that for these bacterial species, the factors controlling the hydrophilicity of the surface are important in reducing bacterial adhesion. This was further proven by keeping the surface topography fixed and changing surface termination to hydrogen (H-), to produce a strongly hydrophobic surface. A noticeable increase in biofilm formation was found. Doping with boron also results in changes in hydrophobicity/hydrophilicity compared to the undoped counterpart, which in turn affects the bacterial growth. For practical electrochemical sensing applications in aquatic environments, this study highlights the extremely beneficial effects of employing smooth, O-terminated (hydrophilic) BDD electrodes.

Pseudomonas-Specific NGS Assay Provides Insight Into Abundance and Dynamics of Pseudomonas Species Including P. aeruginosa in a Cooling Tower.

Pseudomonas species are frequent inhabitants of freshwater environments and colonizers of water supply networks via bioadhesion and biofilm formation. P. aeruginosa is the species most commonly associated with human disease, causing a wide variety of infections with links to its presence in freshwater systems. Though several other Pseudomonas species are of ecological and public health importance, little knowledge exists regarding environmental abundances of these species. In the present study, an Illumina-based next-generation sequencing (NGS) approach using Pseudomonas-specific primers targeting the 16S rRNA gene was evaluated and applied to a set of freshwater samples from different environments including a cooling tower sampled monthly during 2 years. Our approach showed high in situ specificity and accuracy. NGS read counts revealed a precise quantification of P. aeruginosa and a good correlation with the absolute number of Pseudomonas genome copies in a validated genus-specific qPCR assay, demonstrating the ability of the NGS approach to determine both relative and absolute abundances of Pseudomonas species and P. aeruginosa. The characterization of Pseudomonas communities in cooling tower water allowed us to identify 43 phylotypes, with P. aeruginosa being the most abundant. A shift existed within each year from a community dominated by phylotypes belonging to P. fluorescens and P. oleovorans phylogenetic groups to a community where P. aeruginosa was highly abundant. Co-occurrence was observed between P. aeruginosa and other phylotypes of P. aeruginosa group as well as the potentially pathogenic species P. stutzeri, but not with phylotypes of the P. fluorescens group, indicating the need to further investigate the metabolic networks and ecological traits of Pseudomonas species. This study demonstrates the potential of deep sequencing as a valuable tool in environmental diagnostics and surveillance of health-related pathogens in freshwater environments.

Bacterial community dynamics in a cooling tower with emphasis on pathogenic bacteria and Legionella species using universal and genus-specific deep sequencing.

Cooling towers are the major source of outbreaks of legionellosis in Europe and worldwide. These outbreaks are mostly associated with Legionella species, primarily L. pneumophila, and its surveillance in cooling tower environments is of high relevance to public health. In this study, a combined NGS-based approach was used to study the whole bacterial community, specific waterborne and water-based bacterial pathogens, especially Legionella species, targeting the 16S rRNA gene. This approach was applied to water from a cooling tower obtained by monthly sampling during two years. The studied cooling tower was an open circuit cooling tower with lamellar cooling situated in Braunschweig, Germany. A highly diverse bacterial community was observed with 808 genera including 25 potentially pathogenic taxa using universal 16S rRNA primers. Sphingomonas and Legionella were the most abundant pathogenic genera. By applying genus-specific primers for Legionella, a diverse community with 85 phylotypes, and a representative core community with substantial temporal heterogeneity was observed. A high percentage of sequences (65%) could not be affiliated to an acknowledged species. L. pneumophila was part of the core community and the most abundant Legionella species reinforcing the importance of cooling towers as its environmental reservoir. Major temperature shifts (>10 °C) were the key environmental factor triggering the reduction or dominance of the Legionella species in the Legionella community dynamics. In addition, interventions by chlorine dioxide had a strong impact on the Legionella community composition but not on the whole bacterial community. Overall, the presented results demonstrated the value of a combined NGS approach for the molecular monitoring and surveillance of health related pathogens in man-made freshwater systems.

Development of a genus-specific next generation sequencing approach for sensitive and quantitative determination of the Legionella microbiome in freshwater systems.

BACKGROUND: Next Generation Sequencing (NGS) has revolutionized the analysis of natural and man-made microbial communities by using universal primers for bacteria in a PCR based approach targeting the 16S rRNA gene. In our study we narrowed primer specificity to a single, monophyletic genus because for many questions in microbiology only a specific part of the whole microbiome is of interest. We have chosen the genus Legionella, comprising more than 20 pathogenic species, due to its high relevance for water-based respiratory infections. METHODS: A new NGS-based approach was designed by sequencing 16S rRNA gene amplicons specific for the genus Legionella using the Illumina MiSeq technology. This approach was validated and applied to a set of representative freshwater samples. RESULTS: Our results revealed that the generated libraries presented a low average raw error rate per base (<0.5%); and substantiated the use of high-fidelity enzymes, such as KAPA HiFi, for increased sequence accuracy and quality. The approach also showed high in situ specificity (>95%) and very good repeatability. Only in samples in which the gammabacterial clade SAR86 was present more than 1% non-Legionella sequences were observed. Next-generation sequencing read counts did not reveal considerable amplification/sequencing biases and showed a sensitive as well as precise quantification of L. pneumophila along a dilution range using a spiked-in, certified genome standard. The genome standard and a mock community consisting of six different Legionella species demonstrated that the developed NGS approach was quantitative and specific at the level of individual species, including L. pneumophila. The sensitivity of our genus-specific approach was at least one order of magnitude higher compared to the universal NGS approach. Comparison of quantification by real-time PCR showed consistency with the NGS data. Overall, our NGS approach can determine the quantitative abundances of Legionella species, i. e. the complete Legionella microbiome, without the need for species-specific primers. CONCLUSIONS: The developed NGS approach provides a new molecular surveillance tool to monitor all Legionella species in qualitative and quantitative terms if a spiked-in genome standard is used to calibrate the method. Overall, the genus-specific NGS approach opens up a new avenue to massive parallel diagnostics in a quantitative, specific and sensitive way.

Recurrence due to relapse or reinfection with Mycobacterium tuberculosis: a whole-genome sequencing approach in a large, population-based cohort with a high HIV infection prevalence and active follow-up.

BACKGROUND: Recurrent tuberculosis is a major health burden and may be due to relapse with the original strain or reinfection with a new strain. METHODS: In a population-based study in northern Malawi, patients with tuberculosis diagnosed from 1996 to 2010 were actively followed after the end of treatment. Whole-genome sequencing with approximately 100-fold coverage was performed on all available cultures. Results of IS6110 restriction fragment-length polymorphism analyses were available for cultures performed up to 2008. RESULTS: Based on our data, a difference of ≤10 single-nucleotide polymorphisms (SNPs) was used to define relapse, and a difference of >100 SNPs was used to define reinfection. There was no evidence of mixed infections among those classified as reinfections. Of 1471 patients, 139 had laboratory-confirmed recurrences: 55 had relapse, and 20 had reinfection; for 64 type of recurrence was unclassified. Almost all relapses occurred in the first 2 years. Human immunodeficiency virus infection was associated with reinfection but not relapse. Relapses were associated with isoniazid resistance, treatment before 2007, and lineage-3 strains. We identified several gene variants associated with relapse. Lineage-2 (Beijing) was overrepresented and lineage-1 underrepresented among the reinfecting strains (P = .004). CONCLUSIONS: While some of the factors determining recurrence depend on the patient and their treatment, differences in the Mycobacterium tuberculosis genome appear to have a role in both relapse and reinfection.