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Nadeau S, Devaux AJ, Bagutti C, Alt M, Ilg Hampe E, Kraus M, Würfel E, Koch KN, Fuchs S, Tschudin-Sutter S, Holschneider A, Ort C, Chen C, Huisman JS, Julian TR, Stadler T. Influenza transmission dynamics quantified from RNA in wastewater in Switzerland. Swiss Med Wkly 2024; 154:3503. [PMID: 38579316 DOI: 10.57187/s.3503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2024] Open
Abstract
INTRODUCTION Influenza infections are challenging to monitor at the population level due to many mild and asymptomatic cases and similar symptoms to other common circulating respiratory diseases, including COVID-19. Methods for tracking cases outside of typical reporting infrastructure could improve monitoring of influenza transmission dynamics. Influenza shedding into wastewater represents a promising source of information where quantification is unbiased by testing or treatment-seeking behaviours. METHODS We quantified influenza A and B virus loads from influent at Switzerland's three largest wastewater treatment plants, serving about 14% of the Swiss population (1.2 million individuals). We estimated trends in infection incidence and the effective reproductive number (Re) in these catchments during a 2021/22 epidemic and compared our estimates to typical influenza surveillance data. RESULTS Wastewater data captured the same overall trends in infection incidence as laboratory-confirmed case data at the catchment level. However, the wastewater data were more sensitive in capturing a transient peak in incidence in December 2021 than the case data. The Re estimated from the wastewater data was roughly at or below the epidemic threshold of 1 during work-from-home measures in December 2021 but increased to at or above the epidemic threshold in two of the three catchments after the relaxation of these measures. The third catchment yielded qualitatively the same results but with wider confidence intervals. The confirmed case data at the catchment level yielded comparatively less precise R_e estimates before and during the work-from-home period, with confidence intervals that included one before and during the work-from-home period. DISCUSSION Overall, we show that influenza RNA in wastewater can help monitor nationwide influenza transmission dynamics. Based on this research, we developed an online dashboard for ongoing wastewater-based influenza surveillance in Switzerland.
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Affiliation(s)
- Sarah Nadeau
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | | | - Monica Alt
- State Laboratory of Basel-Stadt, Basel, Switzerland
| | | | - Melanie Kraus
- Department of Health, Canton of Basel-Stadt, Basel, Switzerland
| | - Eva Würfel
- Department of Health, Canton of Basel-Stadt, Basel, Switzerland
| | - Katrin N Koch
- Cantonal Office of Public Health, Department of Economics and Health, Canton of Basel-Landschaft, Liestal, Switzerland
| | - Simon Fuchs
- Department of Health, Canton of Basel-Stadt, Basel, Switzerland
| | - Sarah Tschudin-Sutter
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel and University of Basel, Basel, Switzerland
| | | | - Christoph Ort
- Department of Environmental Microbiology, EAWAG, Dübendorf, Switzerland
| | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Jana S Huisman
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Timothy R Julian
- Department of Environmental Microbiology, EAWAG, Dübendorf, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
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Jahn K, Dreifuss D, Topolsky I, Kull A, Ganesanandamoorthy P, Fernandez-Cassi X, Bänziger C, Devaux AJ, Stachler E, Caduff L, Cariti F, Corzón AT, Fuhrmann L, Chen C, Jablonski KP, Nadeau S, Feldkamp M, Beisel C, Aquino C, Stadler T, Ort C, Kohn T, Julian TR, Beerenwinkel N. Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC. Nat Microbiol 2022. [PMID: 35851854 DOI: 10.1101/2021.01.08.21249379] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.
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Affiliation(s)
- Katharina Jahn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - David Dreifuss
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Anina Kull
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | | | - Xavier Fernandez-Cassi
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carola Bänziger
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Alexander J Devaux
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Elyse Stachler
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Lea Caduff
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Federica Cariti
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Alex Tuñas Corzón
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Lara Fuhrmann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Kim Philipp Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sarah Nadeau
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Mirjam Feldkamp
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Catharine Aquino
- Functional Genomics Center Zurich, ETH Zurich, Zurich, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Christoph Ort
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Tamar Kohn
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Timothy R Julian
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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Caduff L, Dreifuss D, Schindler T, Devaux AJ, Ganesanandamoorthy P, Kull A, Stachler E, Fernandez-Cassi X, Beerenwinkel N, Kohn T, Ort C, Julian TR. Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021. Euro Surveill 2022; 27:2100806. [PMID: 35272748 PMCID: PMC8915404 DOI: 10.2807/1560-7917.es.2022.27.10.2100806] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023] Open
Abstract
BackgroundThroughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches.AimHere, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater.MethodsWe developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69-70 and ORF1a Δ3675-3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC.ResultsBased on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69-70 was 0.34 (95% confidence interval (CI): 0.30-0.39) and based on ORF1a Δ3675-3677 was 0.53 (95% CI: 0.49-0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38-0.61).ConclusionDigital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing.
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Affiliation(s)
- Lea Caduff
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - David Dreifuss
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tobias Schindler
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Alexander J Devaux
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | | | - Anina Kull
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Elyse Stachler
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Xavier Fernandez-Cassi
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tamar Kohn
- Laboratory of Environmental Chemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Christoph Ort
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
| | - Timothy R Julian
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
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Held NA, Sutherland KM, Webb EA, McIlvin MR, Cohen NR, Devaux AJ, Hutchins DA, Waterbury JB, Hansel CM, Saito MA. Mechanisms and heterogeneity of in situ mineral processing by the marine nitrogen fixer Trichodesmium revealed by single-colony metaproteomics. ISME Commun 2021; 1:35. [PMID: 36739337 PMCID: PMC9723768 DOI: 10.1038/s43705-021-00034-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 06/10/2021] [Accepted: 06/18/2021] [Indexed: 02/06/2023]
Abstract
The keystone marine nitrogen fixer Trichodesmium thrives in high-dust environments. While laboratory investigations have observed that Trichodesmium colonies can access the essential nutrient iron from dust particles, less clear are the biochemical strategies underlying particle-colony interactions in nature. Here we demonstrate that Trichodesmium colonies engage with mineral particles in the wild with distinct molecular responses. We encountered particle-laden Trichodesmium colonies at a sampling location in the Southern Caribbean Sea; microscopy and synchrotron-based imaging then demonstrated heterogeneous associations with iron oxide and iron-silicate minerals. Metaproteomic analysis of individual colonies by a new low-biomass approach revealed responses in biogeochemically relevant proteins including photosynthesis proteins and metalloproteins containing iron, nickel, copper, and zinc. The iron-storage protein ferritin was particularly enriched implying accumulation of mineral-derived iron, and multiple iron acquisition pathways including Fe(II), Fe(III), and Fe-siderophore transporters were engaged. While the particles provided key trace metals such as iron and nickel, there was also evidence that Trichodesmium was altering its strategy to confront increased superoxide production and metal exposure. Chemotaxis regulators also responded to mineral presence suggesting involvement in particle entrainment. These molecular responses are fundamental to Trichodesmium's ecological success and global biogeochemical impact, and may contribute to the leaching of particulate trace metals with implications for global iron and carbon cycling.
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Affiliation(s)
- Noelle A Held
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
| | - Kevin M Sutherland
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
| | - Eric A Webb
- Marine and Environmental Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Matthew R McIlvin
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Natalie R Cohen
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Alexander J Devaux
- Department of Microbiology, Boston University School of Medicine, Boston, MA, USA
| | - David A Hutchins
- Marine and Environmental Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - John B Waterbury
- Department of Biology, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Colleen M Hansel
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Mak A Saito
- Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA.
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Yurdakul C, Avci O, Matlock A, Devaux AJ, Quintero MV, Ozbay E, Davey RA, Connor JH, Karl WC, Tian L, Ünlü MS. High-Throughput, High-Resolution Interferometric Light Microscopy of Biological Nanoparticles. ACS Nano 2020; 14:2002-2013. [PMID: 32003974 DOI: 10.1021/acsnano.9b08512] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Label-free, visible light microscopy is an indispensable tool for studying biological nanoparticles (BNPs). However, conventional imaging techniques have two major challenges: (i) weak contrast due to low-refractive-index difference with the surrounding medium and exceptionally small size and (ii) limited spatial resolution. Advances in interferometric microscopy have overcome the weak contrast limitation and enabled direct detection of BNPs, yet lateral resolution remains as a challenge in studying BNP morphology. Here, we introduce a wide-field interferometric microscopy technique augmented by computational imaging to demonstrate a 2-fold lateral resolution improvement over a large field-of-view (>100 × 100 μm2), enabling simultaneous imaging of more than 104 BNPs at a resolution of ∼150 nm without any labels or sample preparation. We present a rigorous vectorial-optics-based forward model establishing the relationship between the intensity images captured under partially coherent asymmetric illumination and the complex permittivity distribution of nanoparticles. We demonstrate high-throughput morphological visualization of a diverse population of Ebola virus-like particles and a structurally distinct Ebola vaccine candidate. Our approach offers a low-cost and robust label-free imaging platform for high-throughput and high-resolution characterization of a broad size range of BNPs.
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Affiliation(s)
- Celalettin Yurdakul
- Department of Electrical and Computer Engineering , Boston University , Boston , Massachusetts 02215 , United States
| | - Oguzhan Avci
- Department of Electrical and Computer Engineering , Boston University , Boston , Massachusetts 02215 , United States
| | - Alex Matlock
- Department of Electrical and Computer Engineering , Boston University , Boston , Massachusetts 02215 , United States
| | - Alexander J Devaux
- Department of Microbiology and National Infectious Diseases Laboratories , Boston University School of Medicine , Boston , Massachusetts 02118 , United States
| | - Maritza V Quintero
- Department of Biochemistry and Structural Biology , University of Texas Health San Antonio , San Antonio , Texas 78229 , United States
| | - Ekmel Ozbay
- Department of Electrical and Electronics Engineering , Bilkent University , 06800 Ankara , Turkey
| | - Robert A Davey
- Department of Microbiology and National Infectious Diseases Laboratories , Boston University School of Medicine , Boston , Massachusetts 02118 , United States
| | - John H Connor
- Department of Microbiology and National Infectious Diseases Laboratories , Boston University School of Medicine , Boston , Massachusetts 02118 , United States
| | - W Clem Karl
- Department of Electrical and Computer Engineering , Boston University , Boston , Massachusetts 02215 , United States
| | - Lei Tian
- Department of Electrical and Computer Engineering , Boston University , Boston , Massachusetts 02215 , United States
| | - M Selim Ünlü
- Department of Electrical and Computer Engineering , Boston University , Boston , Massachusetts 02215 , United States
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