Suchergebnisse

[Abstract] Acinetobacter baumannii is a multidrug-resistant pathogen that represents a serious threat to global health. A. baumannii possesses a wide range of virulence factors that contribute to the bacterial pathogenicity. Among them, the siderophore acinetobactin is one of the most important, being essential for the development of the infection. In this study we performed an in-depth analysis of the acinetobactin cluster in the strain A. baumannii ATCC 17978. For this purpose, nineteen individual isogenic mutant strains were generated, and further phenotypical analysis were performed. Individual mutants lacking the biosynthetic genes entA, basG, basC, basD, and basB showed a significant loss in virulence, due to the disruption in the acinetobactin production. Similarly, the gene bauA, coding for the acinetobactin receptor, was also found to be crucial for the bacterial pathogenesis. In addition, the analysis of the ΔbasJ/ΔfbsB double mutant strain demonstrated the high level of genetic redundancy between siderophores where the role of specific genes of the acinetobactin cluster can be fulfilled by their fimsbactin redundant genes. Overall, this study highlights the essential role of entA, basG, basC, basD, basB and bauA in the pathogenicity of A. baumannii and provides potential therapeutic targets for the design of new antivirulence agents against this microorganism. ; This work was funded by Projects PI15/00860 awarded to GB and PI17/01482 to AB and MP, all within in the National Plan for Scientific Research, Development and Technological Innovation 2013–2016 and funded by the ISCIII – General Subdirection of Assessment and Promotion of the Research-European Regional Development Fund (FEDER) "A way of making Europe." The study was also funded by project IN607A 2016/22 (GAIN- Agencia Gallega de Innovación – Consellería de Economía, Emprego e Industria) awarded to GB. This work was also supported by Planes Nacionales de I + D + i 2008–2011/2013–2016 and Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministerio de Economía y Competitividad, Spanish Network for Research in Infectious Diseases (REIPI RD16/0016/006) co-financed by European Development Regional Fund "A way to achieve Europe" and operative program Intelligent Growth 2014–2020. This work was also supported by Grant RTI2018-093634-B-C22 (AEI/FEDER, EU) from the State Agency for Research (AEI) of Spain, co-funded by the FEDER Programme from the European Union and Xunta de Galicia for the support of Grant ED431E 2018/03 for CICA-INIBIC strategic and the initiative "Seed Projects 2019–2020." JV-U was financially supported by the ISCIII project FI18/00315, LÁ-F by the ISCIII project PI14/00059 and the IN606B-2018/011, MM-G was financially supported by the Grant Clara Roy (SEIMC, Spanish Society of Clinical Microbiology and Infectious Diseases), KC-P by IN607A 2016/22 and AECC (Asociación Española Contra el Cáncer) predoctoral fellowship and LA by Xunta de Galicia co-funded with the European Social Fund (FSE) of the European Union (ED481A-2019/081) ; Xunta de Galicia; IN607A 2016/22 ; Xunta de Galicia; ED431E 2018/03 ; Xunta de Galicia; IN606B-2018/011 ; Xunta de Galicia; IN607A 2016/22 ; Xunta de Galicia; ED481A-2019/081

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG ; [Abstract] The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID–19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW Spain), where wastewater from a treatment plant was analyzed to track the epidemic dynamics in a population of 369,098 inhabitants. Viral load detected in the wastewater and the epidemiological data from A Coruña health system served as main sources for statistical models developing. Regression models described here allowed us to estimate the number of infected people (R2 = 0.9), including symptomatic and asymptomatic individuals. These models have helped to understand the real magnitude of the epidemic in a population at any given time and have been used as an effective early warning tool for predicting outbreaks in A Coruña municipality. The methodology of the present work could be used to develop a similar wastewater-based epidemiological model to track the evolution of the COVID–19 epidemic anywhere in the world where centralized water-based sanitation systems exist. ; This work was supported by EDAR Bens S.A., A Coruña, Spain [grant references INV04020, INV12120 and INV05921 to MP], the National Plan for Scientific Research, Development and Technological Innovation 2013-2016 funded by the ISCIII, Spain - General Subdirection of Assessment and Promotion of the Research-European Regional Development Fund (FEDER) "A way of making Europe" [grant numbers PI15/00860 to GB, PI17/01482 and PI20/00413 to MP], the GAIN, Xunta de Galicia, Spain [grant number IN607A 2016/22 to GB, ED431C-2016/015 and ED431C-2020/14 to RC, ED431C 2017/58 to SL, ED431G 2019/01 to RC and SL, and ED431C 2017/66 to MCV], MINECO, Spain [grant number MTM2017-82724-R to RC], Ministerio de Ciencia e Innovación, Spain [grant number PID2020-113578RB-100 to RC], and the Spanish Network for Research in Infectious Diseases [REIPI RD16/0016/006 to GB]. The work was also supported by the European Virus Archive Global (EVA-GLOBAL) project that has received funding from the European Union's Horizon 2020 - Research and Innovation Framework Programme under grant agreement no 871029. SR-F was financially supported by REIPI RD16/0016/006, KC-P by IN607A 2016/22 and the Spanish Association against Cancer (AECC) and JAV by IN607A 2016/22. Funding for open access charge: Universidade da Coruña/CISUG ; EDAR Bens S.A.; INV04020 ; EDAR Bens S.A.; INV12120 ; EDAR Bens S.A.; INV05921 ; Xunta de Galicia; IN607A 2016/22 ; Xunta de Galicia; ED431C-2016/015 ; Xunta de Galicia; ED431C-2020/14 ; Xunta de Galicia; ED431C 2017/58 ; Xunta de Galicia; ED431G 2019/01 ; Xunta de Galicia; ED431C 2017/66

Abstract
Wastewater-based epidemiology has been widely used as a cost-effective method for tracking the COVID-19 pandemic at the community level. Here we describe COVIDBENS, a wastewater surveillance program running from June 2020 to March 2022 in the wastewater treatment plant of Bens in A Coruña (Spain). The main goal of this work was to provide an effective early warning tool based in wastewater epidemiology to help in decision-making at both the social and public health levels. RT-qPCR procedures and Illumina sequencing were used to weekly monitor the viral load and to detect SARS-CoV-2 mutations in wastewater, respectively. In addition, own statistical models were applied to estimate the real number of infected people and the frequency of each emerging variant circulating in the community, which considerable improved the surveillance strategy. Our analysis detected 6 viral load waves in A Coruña with concentrations between 103 and 106 SARS-CoV-2 RNA copies/L. Our system was able to anticipate community outbreaks during the pandemic with 8–36 days in advance with respect to clinical reports and, to detect the emergence of new SARS-CoV-2 variants in A Coruña such as Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529 and BA.2) in wastewater with 42, 30, and 27 days, respectively, before the health system did. Data generated here helped local authorities and health managers to give a faster and more efficient response to the pandemic situation, and also allowed important industrial companies to adapt their production to each situation. The wastewater-based epidemiology program developed in our metropolitan area of A Coruña (Spain) during the SARS-CoV-2 pandemic served as a powerful early warning system combining statistical models with mutations and viral load monitoring in wastewater over time.

The presence of SARS-CoV-2 RNA in wastewater was first reported in March 2020. Over the subsequent months, the potential for wastewater surveillance to contribute to COVID-19 mitigation programmes has been the focus of intense national and international research activities, gaining the attention of policy makers and the public. As a new application of an established methodology, focused collaboration between public health practitioners and wastewater researchers is essential to developing a common understanding on how, when and where the outputs of this non-invasive community-level approach can deliver actionable outcomes for public health authorities. Within this context, the NORMAN SCORE "SARS-CoV-2 in sewage" database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date. Through offering direct access to underpinning meta-data sets (and describing its use in data interpretation), the NORMAN SCORE database is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance. It is also a tool to engage public health practitioners in discussions on use of the approach, providing an opportunity to build mutual understanding of the demand and supply for data and facilitate the translation of this promising research application into public health practice. ; All authors wish to thank the WWTP operators for providing samples. LL, AH and MV would like to acknowledge the VINNOVA (Swedish Governmental Agency for Innovation Systems) DRIZZLE – Centre for Stormwater Management (Grant no. 2016-05176) and the technical expertise provided by the Stormwater&Sewers network, Nireas-International Water Research Center of the University of Cyprus would like to thank the Sewerage Board of Limassol-Amathus (SBLA), the Sewerage Board of Nicosia (SBN) and the Paralimni Sewerage Board (PSB) for the provision of influent samples, for the purpose of performing this work. MPD wishes to thank COVIDBENS Inv04020 financed by EDAR Bens S.A, A Coruña, FYL wishes to thank Z Cetecioglu Gurol (KTH) and P Haglund (Umeå University) and TM would like to acknowledge financial support from APVV-19-0250, PP-COVID-20-0019, ASS8 and VIR-SCAN. Authors from the Univ Jaume LB, FH, MB and RdL acknowledge the financial support from Dirección General del Agua, Generalitat Valenciana, to develop the project "Covid_Wastewater", as well as the help E. Santateresa and N. Zamorano from FACSA, for the invaluable support in performing this work. RdL. was funded through a Beatriz Galindo Fellowship of the Ministerio de Educación y Formación Profesional, Spanish Government (BEAGAL18/00042). TM wishes to thank the generous support of the Operational Program Integrated Infrastructure for the project "Strategic research in the field of SMART monitoring, treatment and preventive protection against coronavirus (SARS-CoV-2) ", Project no. 313011ASS8 (co-financed by the European Regional Development Fund) and the project VIR-SCAN - Wastewater monitoring data as an early warning tool to alert COVID-19 in the population (EOSCsecretariat.eu has received funding from the European Union's Horizon Program call H2020-INFRAEOSC- 05-2018-2019, grant Agreement number 831644). SK (IBISS) acknowledges the financial support from Ministry of Education, Science and Technological Development of Republic of Serbia grant No 451-03-9/2021-14/ 200007.