Comparison of analytical sensitivity and efficiency for SARS-CoV-2 primer sets by TaqMan-based and SYBR Green-based RT-qPCR.

The pandemic of coronavirus disease 2019 (COVID-19) continues to threaten public health. For developing countries where vaccines are still in shortage, cheaper alternative molecular methods for SARS-CoV-2 identification can be crucial to prevent the next wave. Therefore, 14 primer sets recommended by the World Health Organization (WHO) was evaluated on testing both clinical patient and environmental samples with the gold standard diagnosis method, TaqMan-based RT-qPCR, and a cheaper alternative method, SYBR Green-based RT-qPCR. Using suitable primer sets, such as ORF1ab, 2019_nCoV_N1 and 2019_nCoV_N3, the performance of the SYBR Green approach was comparable or better than the TaqMan approach, even when considering the newly dominating or emerging variants, including Delta, Eta, Kappa, Lambda, Mu, and Omicron. ORF1ab and 2019_nCoV_N3 were the best combination for sensitive and reliable SARS-CoV-2 molecular diagnostics due to their high sensitivity, specificity, and broad accessibility. KEY POINTS: • With suitable primer sets, the SYBR Green method performs better than the TaqMan one. • With suitable primer sets, both methods should still detect the new variants well. • ORF1ab and 2019_nCoV_N3 were the best combination for SARS-CoV-2 detection.

Light intensity and spectral distribution affect chytrid infection of cyanobacteria via modulation of host fitness.

Light gradients are an inherent feature in aquatic ecosystems and play a key role in shaping the biology of phytoplankton. Parasitism by chytrid fungi is gaining increasing attention as a major control agent of phytoplankton due to its previously overlooked ubiquity, and profound ecological and evolutionary consequences. Despite this interest, if and how light conditions modulate phytoplankton chytridiomycosis remains poorly studied. We investigated life-history traits of a chytrid parasite, Rhizophydium megarrhizum, under different light intensities and spectral compositions when infecting two closely related planktonic cyanobacteria with different light-harvesting strategies: Planktothrix rubescens and P. agardhii. In general, parasite transmission was highest under light conditions (both intensity and quality) that maximized growth rates for uninfected cyanobacteria. Chytrid encystment on hosts was significantly affected by light intensity and host strain identity. This likely resulted from higher irradiances stimulating the increased discharge of photosynthetic by-products, which drive parasite chemotaxis, and from strain-specific differences at the cell-surface. Comparisons of parasite transmission and host growth rates under different light conditions suggest the potential for epidemic development at higher irradiances, whereas host and parasite could coexist without epidemic outbreaks at lower light levels. These results illustrate the close relationship between parasite transmission and host fitness, which is ultimately modulated by the external environment.

Direct Quantitation of SARS-CoV-2 Virus in Urban Ambient Air via a Continuous-Flow Electrochemical Bioassay.

Airborne SARS-CoV-2 virus surveillance faces challenges in complicated biomarker enrichment, interferences from various non-specific matters and extremely low viral load in the urban ambient air, leading to difficulties in detecting SARS-CoV-2 bioaerosols. This work reports a highly specific bioanalysis platform, with an exceptionally low limit-of-detection (≤1 copy m-3 ) and good analytical accordance with RT-qPCR, relying on surface-mediated electrochemical signaling and enzyme-assisted signal amplification, enabling gene and signal amplification for accurate identification and quantitation of low doses human coronavirus 229E (HCoV-229E) and SARS-CoV-2 viruses in urban ambient air. This work provides a laboratory test using cultivated coronavirus to simulate the airborne spread of SARS-CoV-2, and validate that the platform could reliably detect airborne coronavirus and reveal the transmission characteristics. This bioassay conducts the quantitation of real-world HCoV-229E and SARS-CoV-2 in airborne particulate matters collected from road-side and residential areas in Bern and Zurich (Switzerland) and Wuhan (China), with resultant concentrations verified by RT-qPCR.

SARS-CoV-2 and other airborne respiratory viruses in outdoor aerosols in three Swiss cities before and during the first wave of the COVID-19 pandemic.

Caused by the SARS-CoV-2 virus, Coronavirus disease 2019 (COVID-19) has been affecting the world since the end of 2019. While virus-laden particles have been commonly detected and studied in the aerosol samples from indoor healthcare settings, studies are scarce on air surveillance of the virus in outdoor non-healthcare environments, including the correlations between SARS-CoV-2 and other respiratory viruses, between viruses and environmental factors, and between viruses and human behavior changes due to the public health measures against COVID-19. Therefore, in this study, we collected airborne particulate matter (PM) samples from November 2019 to April 2020 in Bern, Lugano, and Zurich. Among 14 detected viruses, influenza A, HCoV-NL63, HCoV-HKU1, and HCoV-229E were abundant in air. SARS-CoV-2 and enterovirus were moderately common, while the remaining viruses occurred only in low concentrations. SARS-CoV-2 was detected in PM10 (PM below 10 µm) samples of Bern and Zurich, and PM2.5 (PM below 2.5 µm) samples of Bern which exhibited a concentration positively correlated with the local COVID-19 case number. The concentration was also correlated with the concentration of enterovirus which raised the concern of coinfection. The estimated COVID-19 infection risks of an hour exposure at these two sites were generally low but still cannot be neglected. Our study demonstrated the potential functionality of outdoor air surveillance of airborne respiratory viruses, especially at transportation hubs and traffic arteries.

On-Site Quantification and Infection Risk Assessment of Airborne SARS-CoV-2 Virus Via a Nanoplasmonic Bioaerosol Sensing System in Healthcare Settings.

On-site quantification and early-stage infection risk assessment of airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high spatiotemporal resolution is a promising approach for mitigating the spread of coronavirus disease 2019 (COVID-19) pandemic and informing life-saving decisions. Here, a condensation (hygroscopic growth)-assisted bioaerosol collection and plasmonic photothermal sensing (CAPS) system for on-site quantitative risk analysis of SARS-CoV-2 virus-laden aerosols is presented. The CAPS system provided rapid thermoplasmonic biosensing results after an aerosol-to-hydrosol sampling process in COVID-19-related environments including a hospital and a nursing home. The detection limit reached 0.25 copies/µL in the complex aerosol background without further purification. More importantly, the CAPS system enabled direct measurement of the SARS-CoV-2 virus exposures with high spatiotemporal resolution. Measurement and feedback of the results to healthcare workers and patients via a QR-code are completed within two hours. Based on a dose-responseµ model, it is used the plasmonic biosensing signal to calculate probabilities of SARS-CoV-2 infection risk and estimate maximum exposure durations to an acceptable risk threshold in different environmental settings.

Abundance and diversity of antibiotic resistance genes possibly released to ambient air by experiments in biology laboratories.

Antibiotic resistance genes (ARG) have been considered as a global emerging threat to public health systems. As special locations where both antibiotics and ARGs are directly used, biology laboratories are poorly studied but potential important emission sources where not only the environmental stress is strong but also obtaining resistance is much easier comparing to other well studied hot spots including farms, hospitals, wastewater treatment plants and landfills where antibiotics but not ARGs are used or discharged. Therefore, in this study, 11 Swiss biology laboratories working on different fields and located in the city center, suburb and rural area were studied to reveal the abundance and diversity of airborne ARGs in them and their surrounding areas with Colony-forming units (CFU) cultivation and quantitative Polymerase Chain Reaction (qPCR). Most biology laboratories did not discharge significant amounts or varieties of ARGs and cultivable bacteria via air. No correlation was found between the number of CFUs and the abundance of 16S rRNA, but two clusters of correlated airborne ARGs, the animal husbandry related cluster, and city and hospital related cluster were identified in this study. Although most biology laboratories may not be the emission sources of a wide variety of airborne ARGs, the ARGs in the animal husbandry related cluster which are abundant in the animal laboratories and aadA1 which is abundant in the laboratories working on other eukaryocytes need to be furtherly studied to make sure if they are potential health risks for the researchers.

Nitrogen-cycling gene pool shrunk by species interactions among denser bacterial and archaeal community stimulated by excess organic matter and total nitrogen in a eutrophic bay.

Microbial densities, functional genes, and their responses to environment factors have been studied for years, but still a lot remains unknown about their interactions with each other. In this study, the abundances of 7 nitrogen cycling genes in the sediments from Hangzhou Bay were analyzed along with bacterial and archaeal 16S rRNA abundances as the biomarkers of their densities. The amount of organic matter (OM) and total nitrogen (TN) strongly positively correlated with each other and microbial densities, while total phosphate (TP) and ammonia-nitrogen (NH3-N) did not. Most studied genes were density suppressed, while nirS was density stable, and nosZ and hzo were density irrelevant. This suggests eutrophication could limit inorganic nitrogen cycle pathways and the removal of nitrogen in the sediment and emit more greenhouse gases. This study provides a new insight of microbial community structures, functions and their interactions in the sediments of eutrophic bays.

Dual-Functional Plasmonic Photothermal Biosensors for Highly Accurate Severe Acute Respiratory Syndrome Coronavirus 2 Detection.

The ongoing outbreak of the novel coronavirus disease (COVID-19) has spread globally and poses a threat to public health in more than 200 countries. Reliable laboratory diagnosis of the disease has been one of the foremost priorities for promoting public health interventions. The routinely used reverse transcription polymerase chain reaction (RT-PCR) is currently the reference method for COVID-19 diagnosis. However, it also reported a number of false-positive or -negative cases, especially in the early stages of the novel virus outbreak. In this work, a dual-functional plasmonic biosensor combining the plasmonic photothermal (PPT) effect and localized surface plasmon resonance (LSPR) sensing transduction provides an alternative and promising solution for the clinical COVID-19 diagnosis. The two-dimensional gold nanoislands (AuNIs) functionalized with complementary DNA receptors can perform a sensitive detection of the selected sequences from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through nucleic acid hybridization. For better sensing performance, the thermoplasmonic heat is generated on the same AuNIs chip when illuminated at their plasmonic resonance frequency. The localized PPT heat is capable to elevate the in situ hybridization temperature and facilitate the accurate discrimination of two similar gene sequences. Our dual-functional LSPR biosensor exhibits a high sensitivity toward the selected SARS-CoV-2 sequences with a lower detection limit down to the concentration of 0.22 pM and allows precise detection of the specific target in a multigene mixture. This study gains insight into the thermoplasmonic enhancement and its applicability in the nucleic acid tests and viral disease diagnosis.

Sediment bacterial community structures and their predicted functions implied the impacts from natural processes and anthropogenic activities in coastal area.

Coastal ecosystem structures and functions are changing under natural and anthropogenic influences. In this study, surface sediment samples were collected from disturbed zone (DZ), near estuary zone (NEZ), and far estuary zone (FEZ) of Hangzhou Bay, one of the most seriously polluted bays in China. The bacterial community structures and predicted functions varied significantly in different zones. Firmicutes were found most abundantly in DZ, highlighting the impacts of anthropogenic activities. Sediment total phosphorus was most influential on the bacterial community structures. Predicted by PICRUSt analysis, DZ significantly exceeded FEZ and NEZ in the subcategory of Xenobiotics Biodegradation and Metabolism; and DZ enriched all the nitrate reduction related genes, except nrfA gene. Seawater salinity and inorganic nitrogen, respectively as the representative natural and anthropogenic factor, performed exact-oppositely in nitrogen metabolism functions. The changes of bacterial community compositions and predicted functions provide a new insight into human-induced pollution impacts on coastal ecosystem.

Occurrence and distribution of antibiotic resistance genes in the sediments of drinking water sources, urban rivers, and coastal areas in Zhuhai, China.

Antibiotic resistance genes (ARGs) are regarded as emerging contaminants related with human activities. Aquatic environments of an urban city are apt for the persistence and prevalence of ARGs. In this study, we investigated the occurrence and distribution of ARGs and integrase genes in the sediment samples collected from drinking water sources, urban rivers, and coastal areas of Zhuhai, China, in the dry and wet seasons of 2016. The results show that sulfonamide resistance gene of sulII was present at the highest detection frequency (85.71%); and its average concentrations were also the highest in both dry and wet seasons (3.78 × 107 and 9.04 × 107 copies/g sediment, respectively), followed by tetC, tetO, tetA, ermB, dfrA1, and blaPSE-1. Temporally, the concentrations of total ARGs in the wet season were likely higher than those in the dry season; and spatially, the concentrations of total ARGs in the drinking water sources were substantially lower than those in the urban rivers and nearby coastal areas, indicating the different degrees of anthropogenic impact and consequent health risks. Positive correlations were found between intI1 and each quantitative ARG in all wet season samples rather than dry season samples, which suggested higher temperature and more rain in summer might have positive influences on ARG dissemination, especially that mediated by intI1 gene and class I integrons.

The impact of wastewater treatment effluent on microbial biomasses and diversities in coastal sediment microcosms of Hangzhou Bay.

Disposal of wastewater treatment plant (WWTP) effluent into sea, a typical anthropogenic disturbance, may influence many environmental factors and change the coastal microbial community structure. In this study, by setting up coastal sediment microcosms perturbed by WWTP effluent, the changes of microbial community structure under different degree of disturbances were investigated. Quantitative PCR (qPCR) and terminal restriction fragment length polymorphism (T-RFLP) were used to analyzed the biomass and biodiversity. High throughput sequencing analysis was used to identify the classification of the microorganisms. Our study suggested that low ratio of WWTP effluent may stimulate dominant species, which increase the biomass but decrease the biodiversity; while high ratio of WWTP effluent may depress all species, which decrease the biomass but increase the biodiversity. In other words, the impact was dose-dependent. The changes of microbial community structure may provide a metric for water environmental assessment and pollution control.

Identifying the key taxonomic categories that characterize microbial community diversity using full-scale classification: a case study of microbial communities in the sediments of Hangzhou Bay.

Coastal areas are land-sea transitional zones with complex natural and anthropogenic disturbances. Microorganisms in coastal sediments adapt to such disturbances both individually and as a community. The microbial community structure changes spatially and temporally under environmental stress. In this study, we investigated the microbial community structure in the sediments of Hangzhou Bay, a seriously polluted bay in China. In order to identify the roles and contribution of all microbial taxa, we set thresholds as 0.1% for rare taxa and 1% for abundant taxa, and classified all operational taxonomic units into six exclusive categories based on their abundance. The results showed that the key taxa in differentiating the communities are abundant taxa (AT), conditionally abundant taxa (CAT), and conditionally rare or abundant taxa (CRAT). A large population in conditionally rare taxa (CRT) made this category collectively significant in differentiating the communities. Both bacteria and archaea demonstrated a distance decay pattern of community similarity in the bay, and this pattern was strengthened by rare taxa, CRT and CRAT, but weakened by AT and CAT. This implied that the low abundance taxa were more deterministically distributed, while the high abundance taxa were more ubiquitously distributed.

Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space.

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.