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Castelletti N, Paunovic I, Rubio-Acero R, Beyerl J, Plank M, Reinkemeyer C, Kroidl I, Noreña I, Winter S, Olbrich L, Janke C, Hoelscher M, Wieser A. A Dried Blood Spot protocol for high-throughput quantitative analysis of SARS-CoV-2 RBD serology based on the Roche Elecsys system. Microbiol Spectr 2024; 12:e0288523. [PMID: 38426747 DOI: 10.1128/spectrum.02885-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/15/2023] [Indexed: 03/02/2024] Open
Abstract
SARS-CoV-2 spreads pandemically since 2020; in 2021, effective vaccinations became available and vaccination campaigns commenced. Still, it is hard to track the spread of the infection or to assess vaccination success in the broader population. Measuring specific anti-SARS-CoV-2 antibodies is the most effective tool to track the spread of the infection or successful vaccinations. The need for venous-blood sampling however poses a significant barrier for large studies. Dried-blood-spots on filter-cards (DBS) have been used for SARS-CoV-2 serology in our laboratory, but so far not to follow quantitative SARS-CoV-2 anti-spike reactivity in a longitudinal cohort. We developed a semi-automated protocol or quantitative SARS-CoV-2 anti-spike serology from self-sampled DBS, validating it in a cohort of matched DBS and venous-blood samples (n = 825). We investigated chromatographic effects, reproducibility, and carry-over effects and calculated a positivity threshold as well as a conversion formula to determine the quantitative binding units in the DBS with confidence intervals. Sensitivity and specificity reached 96.63% and 97.81%, respectively, compared to the same test performed in paired venous samples. Between a signal of 0.018 and 250 U/mL, we calculated a correction formula. Measuring longitudinal samples during vaccinations, we demonstrated relative changes in titers over time in several individuals and in a longitudinal cohort over four follow-ups. DBS sampling has proven itself for anti-nucleocapsid serosurveys in our laboratory. Similarly, anti-spike high-throughput DBS serology is feasible as a complementary assay. Quantitative measurements are accurate enough to follow titer dynamics in populations also after vaccination campaigns. This work was supported by the Bavarian State Ministry of Science and the Arts; LMU University Hospital, LMU Munich; Helmholtz Center Munich; University of Bonn; University of Bielefeld; German Ministry for Education and Research (proj. nr.: 01KI20271 and others) and the Medical Biodefense Research Program of the Bundeswehr Medical Service. Roche Diagnostics provided kits and machines for analyses at discounted rates. The project is funded also by the European-wide Consortium ORCHESTRA. The ORCHESTRA project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 101016167. The views expressed in this publication are the sole responsibility of the author, and the Commission is not responsible for any use that may be made of the information it contains.IMPORTANCESARS-CoV-2 has been spreading globally as a pandemic since 2020. To determine the prevalence of SARS-CoV-2 antibodies among populations, the most effective public health tool is measuring specific anti-SARS-CoV-2 antibodies induced by infection or vaccination. However, conducting large-scale studies that involve venous-blood sampling is challenging due to the associated feasibility and cost issues. A more cost-efficient and less invasive method for SARS-CoV-2 serological testing is using Dried-Blood-Spots on filter cards (DBS). In this paper, we have developed a semi-automated protocol for quantifying SARS-CoV-2 anti-spike antibodies from self-collected DBS. Our laboratory has previously successfully used DBS sampling for anti-nucleocapsid antibody surveys. Likewise, conducting high-throughput DBS serology for anti-spike antibodies is feasible as an additional test that can be performed using the same sample preparation as the anti-nucleocapsid analysis. The quantitative measurements obtained are accurate enough to track the dynamics of antibody levels in populations, even after vaccination campaigns.
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Affiliation(s)
- Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Institute of Radiation Medicine, Helmholtz Zentrum München, Neuherberg, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
| | - Michael Plank
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Christina Reinkemeyer
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
| | - Ivan Noreña
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
| | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
| | - Christian Janke
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
- Center for International Health (CIH), University Hospital, LMU Munich, Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
- Max-von-Pettenkofer Institute, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
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Hintze S, Möhl BS, Beyerl J, Wulff K, Wieser A, Bork K, Meinke P. Mutant plasminogen in hereditary angioedema is bypassing FXII/kallikrein to generate bradykinin. Front Physiol 2023; 13:1090732. [PMID: 36685169 PMCID: PMC9849239 DOI: 10.3389/fphys.2022.1090732] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023] Open
Abstract
Hereditary angioedema (HAE) is characterized by recurrent localized edema in various organs, which can be potentially fatal. There are different types of hereditary angioedema, which include genetic deficiency of C1 inhibitor (C1-INH) and hereditary angioedema with normal C1-INH (HAEnCI). In HAEnCI patients mutations have been identified in the F12, PLG, KNG1, ANGPT1, MYOF, and HS3ST6 genes. The release of bradykinin from kininogen via the kallikrein-kinin system (KKS) has been shown to be the main mediator in HAE-FXII, but for HAE-PLG there are only first indications how the PLG mutations can result in bradykinin release. Here we identified in a multi-generation HAE-PLG family an additional F12 mutation, resulting in the loss of one F12 allele. There were no differences in the clinical presentation between HAE-PLG patients with and without the additional F12 mutation, thus we concluded that the kallikrein-kinin system is bypassed in HAE-PLG. Structural modeling and in vitro assays using purified proteins confirmed the PLG mutation c.988A>G; p.K330E to be a gain of function mutation resulting in an increased bradykinin release by direct cleavage of high molecular weight kininogen (HMWK). Thus, we can provide clinical and experimental evidence that mutant plasminogen in HAE-PLG is bypassing FXII/kallikrein to generate bradykinin.
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Affiliation(s)
- Stefan Hintze
- Friedrich-Baur-Institute at the Department of Neurology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany,Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany
| | - Britta S. Möhl
- Institute of Virology, School of Medicine, Technical University of Munich/Helmholtz Zentrum München, Munich, Germany
| | - Jessica Beyerl
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany,Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany,Max-von-Pettenkofer Institute, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Karin Wulff
- University Medicine, University of Greifswald, Greifswald, Germany
| | - Andreas Wieser
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection and Pandemic Research, Munich, Germany,Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany,Max-von-Pettenkofer Institute, Ludwig-Maximilians-University Munich, Munich, Germany,DZIF: German Centre for infection research (DZIF), Partner Site Munich, Munich, Germany
| | - Konrad Bork
- Department of Dermatology, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Peter Meinke
- Friedrich-Baur-Institute at the Department of Neurology, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany,*Correspondence: Peter Meinke,
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Puchinger K, Castelletti N, Rubio-Acero R, Geldmacher C, Eser TM, Deák F, Paunovic I, Bakuli A, Saathoff E, von Meyer A, Markgraf A, Falk P, Reich J, Riess F, Girl P, Müller K, Radon K, Guggenbuehl Noller JM, Wölfel R, Hoelscher M, Kroidl I, Wieser A, Olbrich L, Alamoudi E, Anderson J, Baumann M, Behlen M, Beyerl J, Böhnlein R, Brauer A, Britz V, Bruger J, Caroli F, Contento L, Diekmannshemke J, Do A, Dobler G, Eberle U, Eckstein J, Frese J, Forster F, Frahnow T, Fröschl G, Geisenberger O, Gillig K, Heiber A, Hinske C, Hoefflin J, Hofberger T, Höfinger M, Hofmann L, Horn S, Huber K, Janke C, Kappl U, Kiani C, Kroidl A, Laxy M, Leidl R, Lindner F, Mayrhofer R, Mekota AM, Müller H, Metaxa D, Pattard L, Pletschette M, Prückner S, Pusl K, Raimúndez E, Rothe C, Schäfer N, Schandelmaier P, Schneider L, Schultz S, Schunk M, Schwettmann L, Seibold H, Sothmann P, Stapor P, Theis F, Thiel V, Thiesbrummel S, Thur N, Waibel J, Wallrauch C, Winter S, Wolff J, Wullinger P, Yaqine H, Zange S, Zeggini E, Zimmermann T, Zielke A, Ibraheem M, Ahmed M, Becker M, Diepers P, Schälte Y, Garí M, Pütz P, Pritsch M, Fingerle V, Le Gleut R, Gilberg L, Brand I, Diefenbach M, Eser T, Weinauer F, Martin S, Quenzel EM, Durner J, Girl P, Müller K, Radon K, Fuchs C, Hasenauer J. The interplay of viral loads, clinical presentation, and serological responses in SARS-CoV-2 – Results from a prospective cohort of outpatient COVID-19 cases. Virology 2022; 569:37-43. [PMID: 35245784 PMCID: PMC8855229 DOI: 10.1016/j.virol.2022.02.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 02/15/2022] [Accepted: 02/15/2022] [Indexed: 11/24/2022]
Abstract
Risk factors for disease progression and severity of SARS-CoV-2 infections require an understanding of acute and long-term virological and immunological dynamics. Fifty-one RT-PCR positive COVID-19 outpatients were recruited between May and December 2020 in Munich, Germany, and followed up at multiple defined timepoints for up to one year. RT-PCR and viral culture were performed and seroresponses measured. Participants were classified applying the WHO clinical progression scale. Short symptom to test time (median 5.0 days; p = 0.0016) and high viral loads (VL; median maximum VL: 3∙108 copies/mL; p = 0.0015) were indicative for viral culture positivity. Participants with WHO grade 3 at baseline had significantly higher VLs compared to those with WHO 1 and 2 (p = 0.01). VLs dropped fast within 1 week of symptom onset. Maximum VLs were positively correlated with the magnitude of Ro-N-Ig seroresponse (p = 0.022). Our results describe the dynamics of VLs and antibodies to SARS-CoV-2 in mild to moderate cases that can support public health measures during the ongoing global pandemic.
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Rubio-Acero R, Beyerl J, Muenchhoff M, Roth MS, Castelletti N, Paunovic I, Radon K, Springer B, Nagel C, Boehm B, Böhmer MM, Graf A, Blum H, Krebs S, Keppler OT, Osterman A, Khan ZN, Hoelscher M, Wieser A. Spatially resolved qualified sewage spot sampling to track SARS-CoV-2 dynamics in Munich - One year of experience. Sci Total Environ 2021; 797:149031. [PMID: 34346361 PMCID: PMC8294104 DOI: 10.1016/j.scitotenv.2021.149031] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/23/2021] [Accepted: 07/09/2021] [Indexed: 05/03/2023]
Abstract
Wastewater-based epidemiology (WBE) is a tool now increasingly proposed to monitor the SARS-CoV-2 burden in populations without the need for individual mass testing. It is especially interesting in metropolitan areas where spread can be very fast, and proper sewage systems are available for sampling with short flow times and thus little decay of the virus. We started in March 2020 to set up a once-a-week qualified spot sampling protocol in six different locations in Munich carefully chosen to contain primarily wastewater of permanent residential areas, rather than industry or hospitals. We used RT-PCR and sequencing to track the spread of SARS-CoV-2 in the Munich population with temporo-spatial resolution. The study became fully operational in mid-April 2020 and has been tracking SARS-CoV-2 RNA load weekly for one year. Sequencing of the isolated viral RNA was performed to obtain information about the presence and abundance of variants of concern in the Munich area over time. We demonstrate that the evolution of SARS-CoV-2 RNA loads (between <7.5 and 3874/ml) in these different areas within Munich correlates well with official seven day incidence notification data (between 0.0 and 327 per 100,000) obtained from the authorities within the respective region. Wastewater viral loads predicted the dynamic of SARS-CoV-2 local incidence about 3 weeks in advance of data based on respiratory swab analyses. Aligning with multiple different point-mutations characteristic for certain variants of concern, we could demonstrate the gradual increase of variant of concern B.1.1.7 in the Munich population beginning in January 2021, weeks before it became apparent in sequencing results of swabs samples taken from patients living in Munich. Overall, the study highlights the potential of WBE to monitor the SARS-CoV-2 pandemic, including the introduction of variants of concern in a local population.
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Affiliation(s)
- Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Maximilian Muenchhoff
- Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, 80336 Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany.
| | | | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336 Munich, Germany; Center for International Health, Ludwig-Maximilians-University, Munich, Germany.
| | - Bernd Springer
- Fire Department, Disaster Control, City of Munich, Germany.
| | | | | | - Merle M Böhmer
- Taskforce Infectiology, Department for Infectious Disease Epidemiology (TFI 2), Bavarian Health and Food Safety Authority, Oberschleissheim, Germany; Institute of Social Medicine and Health Systems Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University of Munich, Munich, Germany.
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University of Munich, Munich, Germany.
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis, Gene Center, Ludwig Maximilians University of Munich, Munich, Germany.
| | - Oliver T Keppler
- German Center for Infection Research (DZIF), partner site Munich, Germany; Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, 80336 Munich, Germany.
| | - Andreas Osterman
- German Center for Infection Research (DZIF), partner site Munich, Germany; Max von Pettenkofer Institute & Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, 80336 Munich, Germany.
| | - Zohaib Nisar Khan
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany.
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany; Center for International Health, Ludwig-Maximilians-University, Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany.
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, 80802 Munich, Germany; German Center for Infection Research (DZIF), partner site Munich, Germany.
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5
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Radon K, Bakuli A, Pütz P, Le Gleut R, Guggenbuehl Noller JM, Olbrich L, Saathoff E, Garí M, Schälte Y, Frahnow T, Wölfel R, Pritsch M, Rothe C, Pletschette M, Rubio-Acero R, Beyerl J, Metaxa D, Forster F, Thiel V, Castelletti N, Rieß F, Diefenbach MN, Fröschl G, Bruger J, Winter S, Frese J, Puchinger K, Brand I, Kroidl I, Wieser A, Hoelscher M, Hasenauer J, Fuchs C. From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany). BMC Infect Dis 2021; 21:925. [PMID: 34493217 PMCID: PMC8423599 DOI: 10.1186/s12879-021-06589-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 08/19/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND In the 2nd year of the COVID-19 pandemic, knowledge about the dynamics of the infection in the general population is still limited. Such information is essential for health planners, as many of those infected show no or only mild symptoms and thus, escape the surveillance system. We therefore aimed to describe the course of the pandemic in the Munich general population living in private households from April 2020 to January 2021. METHODS The KoCo19 baseline study took place from April to June 2020 including 5313 participants (age 14 years and above). From November 2020 to January 2021, we could again measure SARS-CoV-2 antibody status in 4433 of the baseline participants (response 83%). Participants were offered a self-sampling kit to take a capillary blood sample (dry blood spot; DBS). Blood was analysed using the Elecsys® Anti-SARS-CoV-2 assay (Roche). Questionnaire information on socio-demographics and potential risk factors assessed at baseline was available for all participants. In addition, follow-up information on health-risk taking behaviour and number of personal contacts outside the household (N = 2768) as well as leisure time activities (N = 1263) were collected in summer 2020. RESULTS Weighted and adjusted (for specificity and sensitivity) SARS-CoV-2 sero-prevalence at follow-up was 3.6% (95% CI 2.9-4.3%) as compared to 1.8% (95% CI 1.3-3.4%) at baseline. 91% of those tested positive at baseline were also antibody-positive at follow-up. While sero-prevalence increased from early November 2020 to January 2021, no indication of geospatial clustering across the city of Munich was found, although cases clustered within households. Taking baseline result and time to follow-up into account, men and participants in the age group 20-34 years were at the highest risk of sero-positivity. In the sensitivity analyses, differences in health-risk taking behaviour, number of personal contacts and leisure time activities partly explained these differences. CONCLUSION The number of citizens in Munich with SARS-CoV-2 antibodies was still below 5% during the 2nd wave of the pandemic. Antibodies remained present in the majority of SARS-CoV-2 sero-positive baseline participants. Besides age and sex, potentially confounded by differences in behaviour, no major risk factors could be identified. Non-pharmaceutical public health measures are thus still important.
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Affiliation(s)
- Katja Radon
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336, Munich, Germany.
- Center for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany.
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 89337, Munich, Germany.
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Peter Pütz
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
| | - Ronan Le Gleut
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | | | - Laura Olbrich
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Elmar Saathoff
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Mercè Garí
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Yannik Schälte
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
| | - Turid Frahnow
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
| | - Roman Wölfel
- German Center for Infection Research (DZIF), partner site, Munich, Germany
- Bundeswehr Institute of Microbiology, 80937, Munich, Germany
| | - Michael Pritsch
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Camilla Rothe
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Michel Pletschette
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Dafni Metaxa
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Felix Forster
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, 80336, Munich, Germany
- Comprehensive Pneumology Center (CPC) Munich, German Center for Lung Research (DZL), 89337, Munich, Germany
| | - Verena Thiel
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Friedrich Rieß
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Maximilian N Diefenbach
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Günter Fröschl
- Center for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jan Bruger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Simon Winter
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Jonathan Frese
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Kerstin Puchinger
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Isabel Brand
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Michael Hoelscher
- Center for International Health (CIH), University Hospital, LMU Munich, 80336, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, 80802, Munich, Germany
- German Center for Infection Research (DZIF), partner site, Munich, Germany
| | - Jan Hasenauer
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
- Interdisciplinary Research Unit Mathematics and Life Sciences, University of Bonn, 53113, Bonn, Germany
| | - Christiane Fuchs
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Faculty of Business Administration and Economics, Bielefeld University, 33615, Bielefeld, Germany
- Core Facility Statistical Consulting, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Center for Mathematics, Technische Universität München, 85748, Garching, Germany
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Beyerl J, Rubio-Acero R, Castelletti N, Paunovic I, Kroidl I, Khan ZN, Bakuli A, Tautz A, Oft J, Hoelscher M, Wieser A. A dried blood spot protocol for high throughput analysis of SARS-CoV-2 serology based on the Roche Elecsys anti-N assay. EBioMedicine 2021; 70:103502. [PMID: 34333234 PMCID: PMC8320407 DOI: 10.1016/j.ebiom.2021.103502] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/12/2021] [Accepted: 07/12/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Since 2020 SARS-CoV-2 spreads pandemically, infecting more than 119 million people, causing >2·6 million fatalities. Symptoms of SARS-CoV-2 infection vary greatly, ranging from asymptomatic to fatal. Different populations react differently to the disease, making it very hard to track the spread of the infection in a population. Measuring specific anti-SARS-CoV-2 antibodies is an important tool to assess the spread of the infection or successful vaccinations. To achieve sufficient sample numbers, alternatives to venous blood sampling are needed not requiring medical personnel or cold-chains. Dried-blood-spots (DBS) on filter-cards have been used for different studies, but not routinely for serology. METHODS We developed a semi-automated protocol using self-sampled DBS for SARS-CoV-2 serology. It was validated in a cohort of matched DBS and venous-blood samples (n = 1710). Feasibility is demonstrated with two large serosurveys with 10247 company employees and a population cohort of 4465 participants. FINDINGS Sensitivity and specificity reached 99·20% and 98·65%, respectively. Providing written instructions and video tutorials, 99·87% (4465/4471) of the unsupervised home sampling DBS cards could be analysed. INTERPRETATION DBS-sampling is a valid and highly reliable tool for large scale serosurveys. We demonstrate feasibility and accuracy with a large validation cohort including unsupervised home sampling. This protocol might be of big importance for surveillance in resource-limited settings, providing low-cost highly accurate serology data. FUNDING Provided by Bavarian State Ministry of Science and the Arts, LMU University-Hospital; Helmholtz-Centre-Munich, German Ministry for Education and Research (project01KI20271); University of Bonn; University of Bielefeld; the Medical Biodefense Research Program of Bundeswehr-Medical-Service; Euroimmun, RocheDiagnostics provided discounted kits and machines.
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Affiliation(s)
- Jessica Beyerl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Noemi Castelletti
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Inge Kroidl
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Zohaib N Khan
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Abhishek Bakuli
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany
| | - Andreas Tautz
- Corporate Health Management / Department Occupational Health; DPDHL Group, Bonn 53113, Germany
| | - Judith Oft
- Center for International Health (CIH), University Hospital, LMU Munich, Munich 80336, Germany
| | - Michael Hoelscher
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany; Center for International Health (CIH), University Hospital, LMU Munich, Munich 80336, Germany
| | - Andreas Wieser
- Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig-Maximilians-Universität (LMU) Munich, Munich 80802, Germany; German Center for Infection Research (DZIF), Partner Site Munich, Germany.
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Wimmer A, Beyerl J, Schuster M. Copper Drinking Water Pipes as a Previously Undocumented Source of Silver-Based Nanoparticles. Environ Sci Technol 2019; 53:13293-13301. [PMID: 31593441 DOI: 10.1021/acs.est.9b04271] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Wastewater streams are widely known to release silver-based nanoparticles (Ag-b-NPs) into the environment with a plethora of unknown consequences. Until recently, studies have commonly associated Ag-b-NP sources with products that contain these NPs for antimicrobial reasons, such as fabrics, cosmetics, and medical products. However, our study reveals that there is a thus far completely undocumented source of Ag-b-NPs: copper drinking water pipes. We applied cloud point extraction hyphenated to electrothermal atomic absorption spectrometry or single-particle inductively coupled plasma mass spectrometry to analyze the concentration and perform size-selective quantification of Ag-b-NPs in tap water passing through copper pipes. Up to 83 ng of total silver and 25 ng of Ag-b-NPs were present in tap water samples per liter, which resulted in an NP proportion of approximately 30% of total silver. In total, 96% of the measurable particle sizes ranged from 10 to 36 nm. Additionally, 53 μg of copper was released per liter tap water on average. The measurements included tap water from different sampling days and from four different buildings with varying ages, whereas Ag-b-NPs could be detected in the tap water of two buildings. Silver traces in the copper pipe material of 27.5 ± 4.4 μg g-1 were found to be responsible for the release of nanoparticulate silver into the tap water.
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Affiliation(s)
- Andreas Wimmer
- Division of Analytical Chemistry, Department of Chemistry , Technical University of Munich , Garching 85748 , Germany
| | - Jessica Beyerl
- Division of Analytical Chemistry, Department of Chemistry , Technical University of Munich , Garching 85748 , Germany
| | - Michael Schuster
- Division of Analytical Chemistry, Department of Chemistry , Technical University of Munich , Garching 85748 , Germany
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