Evaluation of the pilot wastewater surveillance for SARS-CoV-2 in Norway, June 2022 - March 2023.

BACKGROUND: During the COVID-19 pandemic, wastewater-based surveillance gained great international interest as an additional tool to monitor SARS-CoV-2. In autumn 2021, the Norwegian Institute of Public Health decided to pilot a national wastewater surveillance (WWS) system for SARS-CoV-2 and its variants between June 2022 and March 2023. We evaluated the system to assess if it met its objectives and its attribute-based performance. METHODS: We adapted the available guidelines for evaluation of surveillance systems. The evaluation was carried out as a descriptive analysis and consisted of the following three steps: (i) description of the WWS system, (ii) identification of users and stakeholders, and (iii) analysis of the system's attributes and performance including sensitivity, specificity, timeliness, usefulness, representativeness, simplicity, flexibility, stability, and communication. Cross-correlation analysis was performed to assess the system's ability to provide early warning signal of new wave of infections. RESULTS: The pilot WWS system was a national surveillance system using existing wastewater infrastructures from the largest Norwegian municipalities. We found that the system was sensitive, timely, useful, representative, simple, flexible, acceptable, and stable to follow the general trend of infection. Preliminary results indicate that the system could provide an early signal of changes in variant distribution. However, challenges may arise with: (i) specificity due to temporary fluctuations of RNA levels in wastewater, (ii) representativeness when downscaling, and (iii) flexibility and acceptability when upscaling the system due to limited resources and/or capacity. CONCLUSIONS: Our results showed that the pilot WWS system met most of its surveillance objectives. The system was able to provide an early warning signal of 1-2 weeks, and the system was useful to monitor infections at population level and complement routine surveillance when individual testing activity was low. However, temporary fluctuations of WWS values need to be carefully interpreted. To improve quality and efficiency, we recommend to standardise and validate methods for assessing trends of new waves of infection and variants, evaluate the WWS system using a longer operational period particularly for new variants, and conduct prevalence studies in the population to calibrate the system and improve data interpretation.

Ablation of the Cß2 subunit of PKA in immune cells leads to increased susceptibility to systemic inflammation in mice.

Protein kinase A (PKA) is a holoenzyme composed of a regulatory subunit dimer and two catalytic subunits and regulates numerous cellular functions including immune cell activity. There are two major catalytic subunit genes, PRKACA and PRKACB encoding the catalytic subunits Cα and Cß. The PRKACB gene encodes several splice variants including Cß2, which is enriched in T-, B- and natural killer cells. Cß2 is significantly larger (46 kDa) than any other C splice variant. In this study we characterized mice ablated for the Cß2 protein demonstrating a significantly reduced cAMP-induced catalytic activity of PKA in the spleenocytes, lymphocytes and thymocytes. We also observed a significantly increased number of CD62L-expressing CD4+ and CD8+ T cells in LNs, accompanied by increased susceptibility to systemic inflammation by the Cß2 ablated mice. The latter was reflected in an elevated sensitivity to collagen-induced arthritis (CIA), as well as higher concentration of TNF-α and lower concentration of IL-10 in response to LPS challenges. We suggest a role of Cß2 in regulating innate as well as adaptive immune sensitivity in vivo.

The Mycobacterium tuberculosis transcriptional landscape under genotoxic stress.

BACKGROUND: As an intracellular human pathogen, Mycobacterium tuberculosis (Mtb) is facing multiple stressful stimuli inside the macrophage and the granuloma. Understanding Mtb responses to stress is essential to identify new virulence factors and pathways that play a role in the survival of the tubercle bacillus. The main goal of this study was to map the regulatory networks of differentially expressed (DE) transcripts in Mtb upon various forms of genotoxic stress. We exposed Mtb cells to oxidative (H2O2 or paraquat), nitrosative (DETA/NO), or alkylation (MNNG) stress or mitomycin C, inducing double-strand breaks in the DNA. Total RNA was isolated from treated and untreated cells and subjected to high-throughput deep sequencing. The data generated was analysed to identify DE genes encoding mRNAs, non-coding RNAs (ncRNAs), and the genes potentially targeted by ncRNAs. RESULTS: The most significant transcriptomic alteration with more than 700 DE genes was seen under nitrosative stress. In addition to genes that belong to the replication, recombination and repair (3R) group, mainly found under mitomycin C stress, we identified DE genes important for bacterial virulence and survival, such as genes of the type VII secretion system (T7SS) and the proline-glutamic acid/proline-proline-glutamic acid (PE/PPE) family. By predicting the structures of hypothetical proteins (HPs) encoded by DE genes, we found that some of these HPs might be involved in mycobacterial genome maintenance. We also applied a state-of-the-art method to predict potential target genes of the identified ncRNAs and found that some of these could regulate several genes that might be directly involved in the response to genotoxic stress. CONCLUSIONS: Our study reflects the complexity of the response of Mtb in handling genotoxic stress. In addition to genes involved in genome maintenance, other potential key players, such as the members of the T7SS and PE/PPE gene family, were identified. This plethora of responses is detected not only at the level of DE genes encoding mRNAs but also at the level of ncRNAs and their potential targets.

Night work, season and alertness as occupational safety hazards in the Arctic: protocol for the Noralert observational crossover study among Norwegian process operators.

INTRODUCTION: The objective of this study is to determine the effects of night work, Arctic seasonal factors and cold working environments on human functions relevant to safety. The study aims to quantify the contribution of (1) several consecutive night shifts, (2) seasonal variation on sleepiness, alertness and circadian rhythm and (3) whether a computational model of sleep, circadian rhythms and cognitive performance can accurately predict the observed sleepiness and alertness. METHODS AND ANALYSIS: In an observational crossover study of outdoor and indoor workers (n=120) on a three-shift schedule from an industrial plant in Norway (70 °N), measurements will be conducted during the summer and winter. Sleep duration and quality will be measured daily by smartphone questionnaire, aided by actigraphy and heart rate measurements. Sleepiness and alertness will be assessed at regular intervals by the Karolinska Sleepiness Scale and the psychomotor vigilance test, respectively. Saliva samples will assess melatonin levels, and a blood sample will measure circadian time. Thermal exposures and responses will be measured by sensors and by thermography. ETHICS AND DISSEMINATION: All participants will give written informed consent to participate in the study, which will be conducted in accordance with the Declaration of Helsinki. The Norwegian Regional Committee for Medical Research Ethics South-East D waivered the need for ethics approval (reference 495816). Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers.

Molecular Epidemiology of the Norwegian SARS-CoV-2 Delta Lineage AY.63.

Extensive genomic surveillance has given great insights into the evolution of the SARS-CoV-2 virus and emerging variants. During the summer months of 2021, Norway was dominated by the Pango lineage AY.63 which is a sub-lineage of the highly transmissible Delta variant. Strikingly, AY.63 did not spread in other countries to any significant extent. AY.63 carried a key mutation, A222V, in the spike protein, as well as the deletion of three residues in nsp1. Although these mutations are close to functionally important areas, we did not find any evidence that they induced higher fitness compared to other Delta lineages. This variant was introduced to Norway at a time when there were low levels of SARS-CoV-2 and contact-reducing measures were relaxed, which probably explains why the lineage rose so quickly. Furthermore, we found that the lack of imports of AY.63 from other countries probably led to the eventual demise of the lineage in Norway.

The impact of global lineage dynamics, border restrictions, and emergence of the B.1.1.7 lineage on the SARS-CoV-2 epidemic in Norway.

As the COVID-19 pandemic swept through an immunologically naïve human population, academics and public health professionals scrambled to establish methods and platforms for genomic surveillance and data sharing. This offered a rare opportunity to study the ecology and evolution of SARS-CoV-2 over the course of the ongoing pandemic. Here, we use population genetic and phylogenetic methodology to characterize the population dynamics of SARS-CoV-2 and reconstruct patterns of virus introductions and local transmission in Norway against this backdrop. The analyses demonstrated that the epidemic in Norway was largely import driven and characterized by the repeated introduction, establishment, and suppression of new transmission lineages. This pattern changed with the arrival of the B.1.1.7 lineage, which was able to establish a stable presence concomitant with the imposition of severe border restrictions.

Performance evaluation of a new custom, multi-component DNA isolation method optimized for use in shotgun metagenomic sequencing-based aerosol microbiome research.

BACKGROUND: Aerosol microbiome research advances our understanding of bioaerosols, including how airborne microorganisms affect our health and surrounding environment. Traditional microbiological/molecular methods are commonly used to study bioaerosols, but do not allow for generic, unbiased microbiome profiling. Recent studies have adopted shotgun metagenomic sequencing (SMS) to address this issue. However, SMS requires relatively large DNA inputs, which are challenging when studying low biomass air environments, and puts high requirements on air sampling, sample processing and DNA isolation protocols. Previous SMS studies have consequently adopted various mitigation strategies, including long-duration sampling, sample pooling, and whole genome amplification, each associated with some inherent drawbacks/limitations. RESULTS: Here, we demonstrate a new custom, multi-component DNA isolation method optimized for SMS-based aerosol microbiome research. The method achieves improved DNA yields from filter-collected air samples by isolating DNA from the entire filter extract, and ensures a more comprehensive microbiome representation by combining chemical, enzymatic and mechanical lysis. Benchmarking against two state-of-the-art DNA isolation methods was performed with a mock microbial community and real-world air samples. All methods demonstrated similar performance regarding DNA yield and community representation with the mock community. However, with subway samples, the new method obtained drastically improved DNA yields, while SMS revealed that the new method reported higher diversity. The new method involves intermediate filter extract separation into a pellet and supernatant fraction. Using subway samples, we demonstrate that supernatant inclusion results in improved DNA yields. Furthermore, SMS of pellet and supernatant fractions revealed overall similar taxonomic composition but also identified differences that could bias the microbiome profile, emphasizing the importance of processing the entire filter extract. CONCLUSIONS: By demonstrating and benchmarking a new DNA isolation method optimized for SMS-based aerosol microbiome research with both a mock microbial community and real-world air samples, this study contributes to improved selection, harmonization, and standardization of DNA isolation methods. Our findings highlight the importance of ensuring end-to-end sample integrity and using methods with well-defined performance characteristics. Taken together, the demonstrated performance characteristics suggest the new method could be used to improve the quality of SMS-based aerosol microbiome research in low biomass air environments.

The subway microbiome: seasonal dynamics and direct comparison of air and surface bacterial communities.

BACKGROUND: Mass transit environments, such as subways, are uniquely important for transmission of microbes among humans and built environments, and for their ability to spread pathogens and impact large numbers of people. In order to gain a deeper understanding of microbiome dynamics in subways, we must identify variables that affect microbial composition and those microorganisms that are unique to specific habitats. METHODS: We performed high-throughput 16S rRNA gene sequencing of air and surface samples from 16 subway stations in Oslo, Norway, across all four seasons. Distinguishing features across seasons and between air and surface were identified using random forest classification analyses, followed by in-depth diversity analyses. RESULTS: There were significant differences between the air and surface bacterial communities, and across seasons. Highly abundant groups were generally ubiquitous; however, a large number of taxa with low prevalence and abundance were exclusively present in only one sample matrix or one season. Among the highly abundant families and genera, we found that some were uniquely so in air samples. In surface samples, all highly abundant groups were also well represented in air samples. This is congruent with a pattern observed for the entire dataset, namely that air samples had significantly higher within-sample diversity. We also observed a seasonal pattern: diversity was higher during spring and summer. Temperature had a strong effect on diversity in air but not on surface diversity. Among-sample diversity was also significantly associated with air/surface, season, and temperature. CONCLUSIONS: The results presented here provide the first direct comparison of air and surface bacterial microbiomes, and the first assessment of seasonal variation in subways using culture-independent methods. While there were strong similarities between air and surface and across seasons, we found both diversity and the abundances of certain taxa to differ. This constitutes a significant step towards understanding the composition and dynamics of bacterial communities in subways, a highly important environment in our increasingly urbanized and interconnect world. Video abstract.

Evolution of the cAMP-dependent protein kinase (PKA) catalytic subunit isoforms.

The 3',5'-cyclic adenosine monophosphate (cAMP)-dependent protein kinase, or protein kinase A (PKA), pathway is one of the most versatile and best studied signaling pathways in eukaryotic cells. The two paralogous PKA catalytic subunits Cα and Cß, encoded by the genes PRKACA and PRKACB, respectively, are among the best understood model kinases in signal transduction research. In this work, we explore and elucidate the evolution of the alternative 5' exons and the splicing pattern giving rise to the numerous PKA catalytic subunit isoforms. In addition to the universally conserved Cα1/Cß1 isoforms, we find kinase variants with short N-termini in all main vertebrate classes, including the sperm-specific Cα2 isoform found to be conserved in all mammals. We also describe, for the first time, a PKA Cα isoform with a long N-terminus, paralogous to the PKA Cß2 N-terminus. An analysis of isoform-specific variation highlights residues and motifs that are likely to be of functional importance.

Observed correlation between the expression levels of catalytic subunit, Cß2, of cyclic adenosine monophosphate-dependent protein kinase and prostate cancer aggressiveness.

BACKGROUND: Today overtreatment of indolent prostate cancers and undertreatment of aggressive prostate cancer are a major concern for patients, their families, and the health care system. New biomarkers distinguishing indolent and aggressive prostate cancer are needed to improve precision medicine. In prostate cancer, protein kinase A (PKA) is known to activate the androgen receptor and published data indicate that PKA subunits can act as predictive markers for response to radiation and chemotherapy. We have previously shown that the catalytic subunit, Cß2, of PKA is up-regulated in prostate cancer and we would in this study investigate the potential of Cß2 to become a prognostic biomarker in prostate cancer. METHODS: Data were sampled from a total of 241 patients from 3 independent cohorts. We measured and compared Cß2 messenger RNA (mRNA) levels in prostate tumor and nontumor samples (n = 22), and exon levels in a cohort of 50 tumor samples, as well as acquiring mRNA data from the publicly available database The cancer genome atlas (n = 169). RESULTS: Cß2 mRNA was up-regulated in prostate cancer in all 3 cohorts, measured by 3 different methods. Furthermore, the relative Cß2 mRNA expression levels were lower in prostate cancer samples with Gleason score 8 to 10 compared with samples with Gleason score<8 (P = 0.004). Finally, low expression of Cß2 mRNA in prostate cancer biopsies correlated with poor survival (hazard ratio = 0.20; 95% CI: 0.048-0.86; P = 0.031), adjusted for risk group and age. CONCLUSIONS: We suggest that Cß2 mRNA expression may be used as a biomarker together with established prognostic markers to more precisely predict aggressiveness in patients diagnosed with prostate cancer.