•Cyanobacterial bloom frequency was analyzed for satellite pixels in 2,196 US lakes.•Pixel-scale cyanobacterial frequencies were summarized for each lake and state.•Spatial clusters of high and low ...annual frequencies were identified across the US.•Results could assist in prioritizing local and national resources and monitoring.
Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.
Severe SARS-CoV-2 infection is associated with strong inflammation and autoantibody production against diverse self-antigens, suggesting a system-wide defect in B cell tolerance. BND cells are a B ...cell subset in healthy individuals harboring autoreactive but anergic B lymphocytes. In vitro evidence suggests inflammatory stimuli can breach peripheral B cell tolerance in this subset. We asked whether SARS-CoV-2-associated inflammation impairs BND cell peripheral tolerance. To address this, PBMCs and plasma were collected from healthy controls, individuals immunized against SARS-CoV-2, or subjects with convalescent or severe SARS-CoV-2 infection. We demonstrate that BND cells from severely infected individuals are significantly activated, display reduced inhibitory receptor expression, and restored BCR signaling, indicative of a breach in anergy during viral infection, supported by increased levels of autoreactive antibodies. The phenotypic and functional BND cell alterations significantly correlate with increased inflammation in severe SARS-CoV-2 infection. Thus, autoreactive BND cells are released from peripheral tolerance with SARS-CoV-2 infection, likely as a consequence of robust systemic inflammation.
Double negative (DN) B cells (CD27-IgD-) comprise a heterogenous population of DN1, DN2, and the recently described DN3 and DN4 subsets. In autoimmune disease, DN2 cells are reported to be precursors ...to autoreactive antibody secreting cells and expansion of DN2 cells is linked to elevated interferon levels. Severe SARS-CoV-2 infection is characterized by elevated systemic levels of pro-inflammatory cytokines and serum autoantibodies and expansion of the DN2 subset in severe SARS-CoV-2 infection has been reported. However, the activation status, functional capacity and contribution to virally-induced autoantibody production by DN subsets is not established. Here, we validate the finding that severe SARS-CoV-2 infection is associated with a reduction in the frequency of DN1 cells coinciding with an increase in the frequency of DN2 and DN3 cells. We further demonstrate that with severe viral infection DN subsets are at a heightened level of activation, display changes in immunoglobulin class isotype frequency and have functional BCR signaling. Increases in overall systemic inflammation (CRP), as well as specific pro-inflammatory cytokines (TNFα, IL-6, IFNγ, IL-1β), significantly correlate with the skewing of DN1, DN2 and DN3 subsets during severe SARS-CoV-2 infection. Importantly, the reduction in DN1 cell frequency and expansion of the DN3 population during severe infection significantly correlates with increased levels of serum autoantibodies. Thus, systemic inflammation during SARS-CoV-2 infection drives changes in Double Negative subset frequency, likely impacting their contribution to generation of autoreactive antibodies.
Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional ...in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll a, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms—the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)—were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll a measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (ρt), Rayleigh-corrected reflectances (ρs), and remote sensing reflectances (Rrs). MCI slightly outperformed NDCI across all reflectance products. MCI using ρt showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll a to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-a conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales.
•Satellite-derived cyanobacteria and qualitative sampler responses had 94% agreement.•685 drinking water sources are observable with 300-m satellite imagery.•2019 temporal frequency of blooms ...averaged 2% across source waters, peaking at 100%.•Effect size of 10 years needed for observed trends to outweigh residual variability.•Only 5 source waters have sufficient data for a sustained trend from 2016 to 2020.
This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency's Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses (n = 84) submitted as part of the U.S. Environmental Protection Agency's fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016 through 2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.
The rapid worldwide spread of SARS-CoV-2 has accelerated research and development for controlling the COVID-19 pandemic. A multi-coronavirus protein microarray was created containing full-length ...proteins, overlapping protein fragments of various lengths, and peptide libraries from SARS-CoV-2 and four other human coronaviruses. Sera from confirmed COVID-19 patients as well as unexposed individuals were applied to multicoronavirus arrays to identify specific antibody reactivity. High-level IgG, IgM, and IgA reactivity to structural proteins S, M, and N of SARS-CoV-2, as well as accessory proteins such as ORF3a and ORF7a, were observed that were specific to COVID-19 patients. Antibody reactivity against overlapping 100-, 50-, and 30-amino acid fragments of SARS-CoV-2 proteins was used to identify antigenic regions. Numerous proteins of SARS-CoV, Middle East respiratory syndrome coronavirus (MERS-CoV), and the endemic human coronaviruses HCoV-NL63 and HCoV-OC43 were also more reactive with IgG, IgM, and IgA in COVID-19 patient sera than in unexposed control sera, providing further evidence of immunologic cross-reactivity between these viruses. Whereas unexposed individuals had minimal reactivity against SARS-CoV-2 proteins that poorly correlated with reactivity against HCoV-NL63 and HCoV-OC43 S2 and N proteins, COVID-19 patient sera had higher correlation between SARS-CoV-2 and HCoV responses, suggesting that de novo antibodies against SARS-CoV-2 cross-react with HCoV epitopes. Array responses were compared with validated spike protein-specific IgG enzyme-linked immunosorbent assays (ELISAs), showing agreement between orthologous methods. SARS-CoV-2 microneutralization titers were low in the COVID-19 patient sera but correlated with array responses against S and N proteins. The multi-coronavirus protein microarray is a useful tool for mapping antibody reactivity in COVID-19 patients. IMPORTANCE With novel mutant SARS-CoV-2 variants of concern on the rise, knowledge of immune specificities against SARS-CoV-2 proteins is increasingly important for understanding the impact of structural changes in antibody-reactive protein epitopes on naturally acquired and vaccine-induced immunity, as well as broader topics of cross-reactivity and viral evolution. A multi-coronavirus protein microarray used to map the binding of COVID-19 patient antibodies to SARS-CoV-2 proteins and protein fragments as well as to the proteins of four other coronaviruses that infect humans has shown specific regions of SARS-CoV-2 proteins that are highly reactive with patient antibodies and revealed cross-reactivity of these antibodies with other human coronaviruses. These data and the multi-coronavirus protein microarray tool will help guide further studies of the antibody response to COVID-19 and to vaccination against this worldwide pandemic.
A prerequisite for the design of an HIV vaccine that elicits protective antibodies is understanding the developmental pathways that result in desirable antibody features. The development of ...antibodies that mediate antibody-dependent cellular cytotoxicity (ADCC) is particularly relevant because such antibodies have been associated with HIV protection in humans. We reconstructed the developmental pathways of six human HIV-specific ADCC antibodies using longitudinal antibody sequencing data. Most of the inferred naive antibodies did not mediate detectable ADCC. Gain of antigen binding and ADCC function typically required mutations in complementarity determining regions of one or both chains. Enhancement of ADCC potency often required additional mutations in framework regions. Antigen binding affinity and ADCC activity were correlated, but affinity alone was not sufficient to predict ADCC potency. Thus, elicitation of broadly active ADCC antibodies may require mutations that enable high-affinity antigen recognition along with mutations that optimize factors contributing to functional ADCC activity.
There are limited data describing SARS-CoV-2-specific immune responses and their durability following infection and vaccination in nursing home residents. We conducted a prospective longitudinal ...evaluation of 11 consenting SARS-CoV-2-positive nursing home residents to evaluate the quantitative titers and durability of binding antibodies detected after SARS-CoV-2 infection and subsequent COVID-19 vaccination. The evaluation included nine visits over 150 days from October 25, 2020, through April 1, 2021. Visits included questionnaire administration, blood collection for serology, and paired anterior nasal specimen collection for testing by BinaxNOW.sup.TM COVID-19 Ag Card (BinaxNOW), reverse transcription polymerase chain reaction (RT-PCR), and viral culture. We evaluated quantitative titers of binding SARS-CoV-2 antibodies post-infection and post-vaccination (beginning after the first dose of the primary series). The median age among participants was 74 years; one participant was immunocompromised. Of 10 participants with post-infection serology results, 9 (90%) had detectable Pan-Ig, IgG, and IgA antibodies, and 8 (80%) had detectable IgM antibodies. At first antibody detection post-infection, two-thirds (6/9, 67%) of participants were RT-PCR-positive, but none were culture- positive. Ten participants received vaccination; all had detectable Pan-Ig, IgG, and IgA antibodies through their final observation less than or equal to90 days post-first dose. Post-vaccination geometric means of IgG titers were 10-200-fold higher than post-infection. Nursing home residents in this cohort mounted robust immune responses to SARS-CoV-2 post-infection and post-vaccination. The augmented antibody responses post-vaccination are potential indicators of enhanced protection that vaccination may confer on previously infected nursing home residents.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To characterize and compare severe acute respiratory coronavirus virus 2 (SARS-CoV-2)-specific immune responses in plasma and gingival crevicular fluid (GCF) from nursing home residents during and ...after natural infection.
Prospective cohort.
Nursing home.
SARS-CoV-2-infected nursing home residents.
A convenience sample of 14 SARS-CoV-2-infected nursing home residents, enrolled 4-13 days after real-time reverse transcription polymerase chain reaction diagnosis, were followed for 42 days. After diagnosis, plasma SARS-CoV-2-specific pan-Immunoglobulin (Ig), IgG, IgA, IgM, and neutralizing antibodies were measured at 5 time points, and GCF SARS-CoV-2-specific IgG and IgA were measured at 4 time points.
All participants demonstrated immune responses to SARS-CoV-2 infection. Among 12 phlebotomized participants, plasma was positive for pan-Ig and IgG in all 12 participants. Neutralizing antibodies were positive in 11 participants; IgM was positive in 10 participants, and IgA was positive in 9 participants. Among 14 participants with GCF specimens, GCF was positive for IgG in 13 participants and for IgA in 12 participants. Immunoglobulin responses in plasma and GCF had similar kinetics; median times to peak antibody response were similar across specimen types (4 weeks for IgG; 3 weeks for IgA). Participants with pan-Ig, IgG, and IgA detected in plasma and GCF IgG remained positive throughout this evaluation, 46-55 days after diagnosis. All participants were viral-culture negative by the first detection of antibodies.
Nursing home residents had detectable SARS-CoV-2 antibodies in plasma and GCF after infection. Kinetics of antibodies detected in GCF mirrored those from plasma. Noninvasive GCF may be useful for detecting and monitoring immunologic responses in populations unable or unwilling to be phlebotomized.
Abstract
We compared paired serum specimens from household contacts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases with detectable SARS-CoV-2 seroconversion with contacts who ...remained seronegative. No protection from SARS-CoV-2 infection was associated with human coronavirus antibodies; however, an increase in common betacoronavirus antibodies was associated with seroconversion to SARS-CoV-2 in mild to moderately ill cases.
PDF
