4
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Multistep diversification in spatiotemporal bacterial-phage coevolution

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The evolutionary arms race between phages and bacteria, where bacteria evolve resistance to phages and phages retaliate with resistance-countering mutations, is a major driving force of molecular innovation and genetic diversification. Yet attempting to reproduce such ongoing retaliation dynamics in the lab has been challenging; laboratory coevolution experiments of phage and bacteria are typically performed in well-mixed environments and often lead to rapid stagnation with little genetic variability. Here, co-culturing motile E. coli with the lytic bacteriophage T7 on swimming plates, we observe complex spatiotemporal dynamics with multiple genetically diversifying adaptive cycles. Systematically quantifying over 10,000 resistance-infectivity phenotypes between evolved bacteria and phage isolates, we observe diversification into multiple coexisting ecotypes showing a complex interaction network with both host-range expansion and host-switch tradeoffs. Whole-genome sequencing of these evolved phage and bacterial isolates revealed a rich set of adaptive mutations in multiple genetic pathways including in genes not previously linked with phage-bacteria interactions. Synthetically reconstructing these new mutations, we discover phage-general and phage-specific resistance phenotypes as well as a strong synergy with the more classically known phage-resistance mutations. These results highlight the importance of spatial structure and migration for driving phage-bacteria coevolution, providing a concrete system for revealing new molecular mechanisms across diverse phage-bacterial systems.

          Abstract

          Bacteria and their viruses coexist and coevolve in nature, but maintaining them together in the lab is challenging. Here, a spatially structured environment allowed prolonged coevolution, with bacteria and phage diversifying into multiple ecotypes, uncovering gene mechanisms affecting phage-bacteria interactions.

          Related collections

          Most cited references81

          • Record: found
          • Abstract: not found
          • Article: not found

          Regression Shrinkage and Selection Via the Lasso

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq.

            Next-generation DNA sequencing (NGS) can be used to reconstruct eco-evolutionary population dynamics and to identify the genetic basis of adaptation in laboratory evolution experiments. Here, we describe how to run the open-source breseq computational pipeline to identify and annotate genetic differences found in whole-genome and whole-population NGS data from haploid microbes where a high-quality reference genome is available. These methods can also be used to analyze mutants isolated in genetic screens and to detect unintended mutations that may occur during strain construction and genome editing.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Programming cells by multiplex genome engineering and accelerated evolution.

              The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales. Although in vitro and directed evolution methods have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-D-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.
                Bookmark

                Author and article information

                Contributors
                rkishony@technion.ac.il
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                28 December 2022
                28 December 2022
                2022
                : 13
                : 7971
                Affiliations
                [1 ]GRID grid.6451.6, ISNI 0000000121102151, Faculty of Biology, , Technion–Israel Institute of Technology, ; Haifa, Israel
                [2 ]GRID grid.6451.6, ISNI 0000000121102151, Faculty of Computer Science, , Technion–Israel Institute of Technology, ; Haifa, Israel
                [3 ]GRID grid.6451.6, ISNI 0000000121102151, Faculty of Biomedical Engineering, , Technion–Israel Institute of Technology, ; Haifa, Israel
                Author information
                http://orcid.org/0000-0001-8693-7176
                http://orcid.org/0000-0002-5013-5072
                Article
                35351
                10.1038/s41467-022-35351-w
                9797572
                36577749
                9fa4b2a1-0e29-41e3-9815-c67a0ac8d4b0
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 April 2022
                : 29 November 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003977, Israel Science Foundation (ISF);
                Award ID: 455/19
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100001201, Kavli Foundation;
                Funded by: ISRAEL SCIENCE FOUNDATION – BROAD INSTITUTE Joint Program, grant No. 2790/19
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                coevolution,bacteriophages,bacterial genetics,experimental evolution
                Uncategorized
                coevolution, bacteriophages, bacterial genetics, experimental evolution

                Comments

                Comment on this article