34
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A call for caution in analysing mammalian co-transfection experiments and implications of resource competition in data misinterpretation

      brief-report

      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

          Transient transfections are routinely used in basic and synthetic biology studies to unravel pathway regulation and to probe and characterise circuit designs. As each experiment has a component of intrinsic variability, reporter gene expression is usually normalized with co-delivered genes that act as transfection controls. Recent reports in mammalian cells highlight how resource competition for gene expression leads to biases in data interpretation, with a direct impact on co-transfection experiments. Here we define the connection between resource competition and transient transfection experiments and discuss possible alternatives. Our aim is to raise awareness within the community and stimulate discussion to include such considerations in future experimental designs, for the development of better transfection controls.

          Related collections

          Most cited references38

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

          Growth rate-dependent global effects on gene expression in bacteria.

          Bacterial gene expression depends not only on specific regulatory mechanisms, but also on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding of these global effects is necessary for a quantitative understanding of gene regulation and for the design of synthetic genetic circuits. We find that the observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependencies for genetic circuits involving activators, repressors, and feedback control were analyzed and verified experimentally with synthetic circuits. Additional results suggest a feedback mechanism mediated by general growth-dependent effects that does not require explicit gene regulation if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence). Copyright 2009 Elsevier Inc. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Interdependence of cell growth and gene expression: origins and consequences.

            In bacteria, the rate of cell proliferation and the level of gene expression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and gene expression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on gene expression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Genetic circuit design automation.

              Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits forEscherichia coli(880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decision-making, control, sensing, or spatial organization.
                Bookmark

                Author and article information

                Contributors
                f.ceroni@imperial.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                5 May 2021
                5 May 2021
                2021
                : 12
                : 2545
                Affiliations
                [1 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Department of Chemical Engineering, , Imperial College London, South Kensington Campus, ; London, UK
                [2 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Imperial College Centre for Synthetic Biology, South Kensington Campus, ; London, UK
                [3 ]GRID grid.25786.3e, ISNI 0000 0004 1764 2907, Synthetic and Systems Biology lab for Biomedicine, , Istituto Italiano di Tecnologia-IIT, Largo Barsanti e Matteucci, ; Naples (ITA), Italy
                Author information
                http://orcid.org/0000-0002-6563-2792
                http://orcid.org/0000-0001-8045-4843
                http://orcid.org/0000-0001-7734-9153
                http://orcid.org/0000-0001-5435-2667
                http://orcid.org/0000-0001-7237-4982
                Article
                22795
                10.1038/s41467-021-22795-9
                8099865
                33953169
                392ef71d-d10e-43f2-9570-8f70ea5c81eb
                © The Author(s) 2021

                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
                : 20 November 2020
                : 29 March 2021
                Categories
                Comment
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                synthetic biology,biomedical engineering
                Uncategorized
                synthetic biology, biomedical engineering

                Comments

                Comment on this article