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      Synthetic gene-regulatory networks in the opportunistic human pathogen Streptococcus pneumoniae

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          Significance

          Streptococcus pneumoniae is a major human pathogen responsible for enormous global morbidity and mortality. Despite this, the pneumococcus makes up part of the commensal nasopharyngeal flora. How the pneumococcus switches from this commensal to pathogenic state and causes disease is unclear and very likely involves variability in expression of its virulence factors. Here, we used synthetic biology approaches to generate complex gene-regulatory networks such as logic gates and toggle switches. We show that these networks are functional in vivo to control capsule production in an influenza-superinfection model. This opens the field of systematically testing the role of phenotypic variation in pneumococcal virulence. The approaches used here may serve as an example for synthetic biology projects in unrelated organisms.

          Abstract

          Streptococcus pneumoniae can cause disease in various human tissues and organs, including the ear, the brain, the blood, and the lung, and thus in highly diverse and dynamic environments. It is challenging to study how pneumococci control virulence factor expression, because cues of natural environments and the presence of an immune system are difficult to simulate in vitro. Here, we apply synthetic biology methods to reverse-engineer gene expression control in S. pneumoniae. A selection platform is described that allows for straightforward identification of transcriptional regulatory elements out of combinatorial libraries. We present TetR- and LacI-regulated promoters that show expression ranges of four orders of magnitude. Based on these promoters, regulatory networks of higher complexity are assembled, such as logic AND gates and IMPLY gates. We demonstrate single-copy genome-integrated toggle switches that give rise to bimodal population distributions. The tools described here can be used to mimic complex expression patterns, such as the ones found for pneumococcal virulence factors. Indeed, we were able to rewire gene expression of the capsule operon, the main pneumococcal virulence factor, to be externally inducible (YES gate) or to act as an IMPLY gate (only expressed in absence of inducer). Importantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza A virus superinfection murine model of pneumonia, paving the way for in vivo investigations of the importance of gene expression control on the pathogenicity of S. pneumoniae.

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          Most cited references73

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            Enzymatic assembly of DNA molecules up to several hundred kilobases.

            We describe an isothermal, single-reaction method for assembling multiple overlapping DNA molecules by the concerted action of a 5' exonuclease, a DNA polymerase and a DNA ligase. First we recessed DNA fragments, yielding single-stranded DNA overhangs that specifically annealed, and then covalently joined them. This assembly method can be used to seamlessly construct synthetic and natural genes, genetic pathways and entire genomes, and could be a useful molecular engineering tool.
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              Tn-seq; high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms

              Biological pathways are structured in complex networks of interacting genes. Solving the architecture of such networks may provide valuable information, such as how microorganisms cause disease. Here we present a method (Tn-seq) for accurately determining quantitative genetic interactions on a genome-wide scale in microorganisms. Tn-seq is based on the assembly of a saturated Mariner transposon insertion library. After library selection, changes in frequency of each insertion mutant are determined by sequencing of the flanking regions en masse. These changes are used to calculate each mutant’s fitness. Fitness was determined for each gene of the gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis. A genome-wide screen for genetic interactions identified both alleviating and aggravating interactions that could be further divided into seven distinct categories. Due to the wide activity of the Mariner transposon, Tn-seq has the potential to contribute to the exploration of complex pathways across many different species.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                3 November 2020
                21 October 2020
                21 October 2020
                : 117
                : 44
                : 27608-27619
                Affiliations
                [1] aMolecular Genetics Group, Groningen Biomolecular Sciences and Biotechnology Institute, Centre for Synthetic Biology, University of Groningen , 9747 AG, Groningen, The Netherlands;
                [2] bDepartment of Fundamental Microbiology, Faculty of Biology and Medicine, University of Lausanne , CH-1015 Lausanne, Switzerland;
                [3] cUniversité de Lille, CNRS, Inserm, Centre Hospitalier Universitaire de Lille, Institut Pasteur Lille , U1019–UMR 9017–CIIL–Center for Infection and Immunity of Lille, F-59000 Lille, France
                Author notes
                3To whom correspondence may be addressed. Email: jan-willem.veening@ 123456unil.ch .

                Edited by Ralph R. Isberg, Tufts University School of Medicine, Boston, MA, and approved September 21, 2020 (received for review November 15, 2019)

                Author contributions: R.A.S., C.G., and J.-W.V. designed research; R.A.S., C.G., L.V.M., and J.-C.S. performed research; R.A.S., C.G., L.V.M., and J.-C.S. analyzed data; and R.A.S. and J.-W.V. wrote the paper.

                1Present address: Genencor International, DuPont Nutrition & Biosciences, Willem Einthovenstraat 4, 2342 BH Oegstgeest, The Netherlands.

                2R.A.S. and C.G. contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-6296-8928
                http://orcid.org/0000-0001-9854-4652
                http://orcid.org/0000-0002-3162-6634
                Article
                201920015
                10.1073/pnas.1920015117
                7959565
                33087560
                c1df18d7-8794-4570-ad20-0230084d2956
                Copyright © 2020 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                Page count
                Pages: 12
                Funding
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNF) 501100001711
                Award ID: 31003A_172861
                Award Recipient : Jan-Willem Veening
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNF) 501100001711
                Award ID: 40AR40_185533
                Award Recipient : Jan-Willem Veening
                Funded by: EC | H2020 | H2020 Priority Excellent Science | H2020 European Research Council (ERC) 100010663
                Award ID: 771534-PneumoCaTChER
                Award Recipient : Jan-Willem Veening
                Funded by: European Commission (EC) 501100000780
                Award ID: 847786
                Award Recipient : Jean-Claude Sirard
                Categories
                Biological Sciences
                Microbiology

                pneumococcus,toggle switch,synthetic biology,superinfection,counterselection

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