Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.Andre Franke and David Ellinghaus were supported by a grant from the German Federal Ministry of Education and Research (01KI20197), Andre Franke, David Ellinghaus and Frauke Degenhardt were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). David Ellinghaus was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). David Ellinghaus, Karina Banasik and Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German Research Foundation (DFG) through the Research Training Group 1743, "Genes, Environment and Inflammation". This project was supported by a Covid-19 grant from the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197). Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL – strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by a MIUR grant to the Department of Medical Sciences, under the program "Dipartimenti di Eccellenza 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de hacer Europa").Beatriz Cortes is supported by national grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), “A way to build Europe”). Additional data included in this study was obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio Julià and Sara Marsal were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). Antonio Julià was also supported the by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. Mario Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón's team is supported by CIBER of Epidemiology and Public Health (CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from Research Council of Norway grant no 312780 during the conduct of the study. Dr. Solligård: reports grants from Research Council of Norway grant no 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF).Oliver A. Cornely is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – CECAD, EXC 2030 – 390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping was performed by the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. Kerstin U. Ludwig is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme – Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). Christoph Lange and Jan Heyckendorf are supported by the German Center for Infection Research (DZIF). Thorsen Brenner, Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung Universitätsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).N

Relevance of Stanniocalcin 2 in human Neuroblastoma

Das humane Neuroblastom (NB) ist die häufigste extrakraniale Tumorerkrankung im Kindesalter. Diese Krebsform zeichnet sich besonders durch ihre Heterogenität aus, bei der aggressive Progression und Metastasierung im extremen Gegensatz zur häufig auftretenden Spontanregression und Differenzierung stehen. Die Erforschung des genetischen Hintergrunds der Tumoren ist ausschlaggebend für die Suche nach neuen prognostischen Markern und damit der Möglichkeit individueller Therapiestratifizierung bei den betroffenen Säuglingen und Kleinkindern. Für meine Untersuchungen habe ich das sezernierte Glykoprotein Stanniocalcin 2 (STC2) ausgewählt, das bislang noch nicht näher im Zusammenhang mit dem NB untersucht wurde. Beim Menschen konnte dem Protein noch keine eindeutige Funktion zugeordnet werden und bei der Progression von Tumoren wird STC2 widersprüchlich beschrieben. Das Ziel meiner Arbeit war es, die Funktion von STC2 im humanen Neuroblastom zu untersuchen und zu prüfen, ob STC2, wie es sich in Vorversuchen angedeutet hatte, mit einer günstigen Prognose korreliert. Die STC2-Expression wurde in NB-Zelllinien und Primärtumoren bestimmt und es konnte gezeigt werden, dass das Molekül mit metastasierenden Tumorstadien und der Amplifikation des MYCN-Onkogens positiv korreliert. Außerdem konnte die Expression von zwei STC2-mRNAs nachgewiesen werden, die vermutlich aufgrund alternativer Transkript-Polyadenylierung entstehen. Die funktionelle Analyse transfizierter NB-Zellen zeigte, dass die Überexpression von STC2 die Apoptoseneigung der Zellen erhöht und dadurch einen wachstumsmindernden Effekt vermittelt. Gleichzeitig konnte in vitro bei den STC2-transfizierten Zellen eine deutliche Steigerung der Invasivität und eine erhöhte Aktivität der Matrixmetalloproteinase 2 nachgewiesen werden. In vivo bildeten die STC2-exprimierenden Zellen Tumoren, die im Vergleich zu den Tumoren der Kontrollzellen weniger solide waren und in ihrer Erscheinung blutgefüllten Zysten glichen. In ihrem Inneren konnten neben den wenigen Tumorzellen, die sich im Randbereich befanden, Gefäßtrümmer, aber keine intakten Gefäße nachgewiesen werden. Diese Arrosion von Gefäßen war auch bei Untersuchungen mit gereinigtem Protein zu beobachten. Rekombinantes STC2-Protein war in der Lage, Blutungen und die Bildung von Granulationsgewebe in der Chorioallantoismembran von Hühnerembryonen zu induzieren. Die im Zuge dieser Arbeit generierten Daten weisen auf eine duale Funktion von STC2 bei der Progression des NB hin. STC2 hat eine wachstumshemmende Wirkung auf NB-Zellen, scheint aber gleichzeitig invasives Verhalten und Tumormetastasierung zu fördern. Somit muss die Hypothese, dass STC2 mit einer günstigen Prognose korreliert, abgelehnt werden. Ob die Korrelation von STC2 mit ungünstigem Tumorverhalten zukünftig als prognostischer Marker für die Risikostratifizierung beim humanen NB eingesetzt werden kann, muss in weiteren Studien geprüft werden

Genetic evidence for a novel competence inhibitor in the industrially important Bacillus licheniformis

Abstract Natural genetic competence renders bacteria able to take up and, in case there is sufficient homology to the recipient’s chromosome, integrate exogenously supplied DNA. Well studied in Bacillus subtilis, genetic competence is—in several aspects—known to be differently regulated in Bacillus licheniformis. We now report on the identification of a novel, chromosomally encoded homolog of a competence inhibitor in B. licheniformis (ComI) that has hitherto only been described as a plasmid borne trait in the ancestral B. subtilis NCIB3610. Bioinformatical analysis that included 80 Bacillus strains covering 20 different species revealed a ComI encoding gene in all of the examined B. licheniformis representatives, and was identified in few among the other species investigated. The predicted ComI of B. licheniformis is a highly conserved peptide consisting of 28 amino acids. Since deletion of comI in B. licheniformis DSM13 resulted in twofold increased transformation efficiency by genetic competence and overexpression resulted in threefold decreased transformability, the function as a competence inhibitor became evident

Complete Genome Sequences of the Chemolithoautotrophic Oligotropha carboxidovorans Strains OM4 and OM5

We report on genome sequencing of Oligotropha carboxidovorans strain OM4 and resequencing of strain OM5. The genomes of both are composed of one chromosome and two plasmids. The presence of two plasmids in the OM5 genome is inconsistent with the previously published sequence, for which only one plasmid was described (D. Paul, S. Bridges, S. Burgess, Y. Dandass, and M. Lawrence, BMC Genomics 11:511, 2010)

MOESM1 of Genetic evidence for a novel competence inhibitor in the industrially important Bacillus licheniformis

Additional file 1: Table S1. Oligonucleotides used in this study. Table S2. GeneBank accession numbers

Oligonucleotides used in this study.

<p>*Restriction sites within the oligonucleotide sequences are printed in bold.</p><p>Oligonucleotides used in this study.</p

Results of the signal to noise ratio determination.

<p>The table shows the average base coverage and signal to noise ratios for mappings of NGS experiments of phage DNA isolated from <i>B</i>. <i>licheniformis</i> DSM13 and MW3, and the mutant strains <i>B</i>. <i>licheniformis</i> ΔPBSX and ΔPBSX_ΔBLi_Pp3. The average base coverage in prophage regions (signal) and in non-prophage regions (noise) were calculated by counting the number of reads and dividing them by the respective region size. The signal to noise ratio (signal divided by noise) was calculated to compare experiments with different reads numbers. The relative noise (%) gives a percent value for the noise in relation to the signal (set 100%).</p><p>Results of the signal to noise ratio determination.</p

Phage activity graphs on the genome of <i>B</i>. <i>licheniformis</i> DSM13.

<p><i>B</i>. <i>licheniformis</i> phage DNA was sequenced by next generation sequencing (NGS) and sequences were mapped on the genome of <i>B</i>. <i>licheniformis</i> DSM13. The results are displayed in NPKM values calculated by TraV [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0120759#pone.0120759.ref026" target="_blank">26</a>]. Prophage regions BLi_Pp1 – BLi_Pp7 are marked with grey bars. A: The phage DNA read mapping of <i>B</i>. <i>licheniformis</i> DSM13 shows a even distribution of reads over the whole genome as well as read accumulations around the origin of replication and also in some further regions, especially in BLi_Pp3. B: The <i>B</i>. <i>licheniformis</i> ΔPBSX phage DNA read mapping (green graph) shows a strong read accumulation in the region BLi_Pp3 compared to the <i>B</i>. <i>licheniformis</i> DSM13 read mapping (red graph), and a slight read accumulation in region BLi_Pp6. The <i>B</i>. <i>licheniformis</i> ΔPBSX-ΔBLi_Pp3 phage DNA read mapping (blue graph, result of the first experiment is shown) exhibits a distinct read accumulation in BLi_Pp6.</p

Genome-Based Identification of Active Prophage Regions by Next Generation Sequencing in <i>Bacillus licheniformis</i> DSM13

<div><p>Prophages are viruses, which have integrated their genomes into the genome of a bacterial host. The status of the prophage genome can vary from fully intact with the potential to form infective particles to a remnant state where only a few phage genes persist. Prophages have impact on the properties of their host and are therefore of great interest for genomic research and strain design. Here we present a genome- and next generation sequencing (NGS)-based approach for identification and activity evaluation of prophage regions. Seven prophage or prophage-like regions were identified in the genome of <i>Bacillus licheniformis</i> DSM13. Six of these regions show similarity to members of the <i>Siphoviridae</i> phage family. The remaining region encodes the <i>B</i>. <i>licheniformis</i> orthologue of the PBSX prophage from <i>Bacillus subtilis</i>. Analysis of isolated phage particles (induced by mitomycin C) from the wild-type strain and prophage deletion mutant strains revealed activity of the prophage regions BLi_Pp2 (PBSX-like), BLi_Pp3 and BLi_Pp6. In contrast to BLi_Pp2 and BLi_Pp3, neither phage DNA nor phage particles of BLi_Pp6 could be visualized. However, the ability of prophage BLi_Pp6 to generate particles could be confirmed by sequencing of particle-protected DNA mapping to prophage locus BLi_Pp6. The introduced NGS-based approach allows the investigation of prophage regions and their ability to form particles. Our results show that this approach increases the sensitivity of prophage activity analysis and can complement more conventional approaches such as transmission electron microscopy (TEM).</p></div