Molecular Systems Biology 9; Article number 702; doi:10.1038/msb.2013.58 Citation: Molecular Systems Biology 9:702 www.molecularsystemsbiology.com
Design of orthogonal genetic switches based on a crosstalk map of rs, anti-rs, and promoters Virgil A Rhodius1,6, Thomas H Segall-Shapiro2,6, Brian D Sharon3, Amar Ghodasara2, Ekaterina Orlova1, Hannah Tabakh1, David H Burkhardt3, Kevin Clancy4, Todd C Peterson4, Carol A Gross1,5,* and Christopher A Voigt2,* 1 Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA, USA, 2 Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA, 3 Graduate Group in Biophysics, University of California San Francisco, San Francisco, CA, USA, 4 Synthetic Biology Research and Development, Life Technologies, Carlsbad, CA, USA and 5 Department of Cell and Tissue Biology, University of California San Francisco, San Francisco, CA, USA 6 These authors contributed equally to this work * Corresponding author. CA Gross, Department of Microbiology and Immunology, University of California San Francisco, 600 16th Street, San Francisco, CA 94158, USA. Tel.: þ 1 415 476 4161; Fax: þ 1 415 514 4080; E-mail:
[email protected] or CA Voigt, Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, 500 Technology Square NE47-277, Cambridge, MA 02139, USA. Tel.: þ 1 617 324 4851; E-mail:
[email protected]
Received 6.5.13; accepted 26.9.13
Cells react to their environment through gene regulatory networks. Network integrity requires minimization of undesired crosstalk between their biomolecules. Similar constraints also limit the use of regulators when building synthetic circuits for engineering applications. Here, we mapped the promoter specificities of extracytoplasmic function (ECF) rs as well as the specificity of their interaction with anti-rs. DNA synthesis was used to build 86 ECF rs (two from every subgroup), their promoters, and 62 anti-rs identified from the genomes of diverse bacteria. A subset of 20 rs and promoters were found to be highly orthogonal to each other. This set can be increased by combining the 35 and 10 binding domains from different subgroups to build chimeras that target sequences unrepresented in any subgroup. The orthogonal rs, anti-rs, and promoters were used to build synthetic genetic switches in Escherichia coli. This represents a genome-scale resource of the properties of ECF rs and a resource for synthetic biology, where this set of well-characterized regulatory parts will enable the construction of sophisticated gene expression programs. Molecular Systems Biology 9: 702; published online 29 October 2013; doi:10.1038/msb.2013.58 Subject Categories: metabolic and regulatory networks; synthetic biology Keywords: compiler; genetic circuit; part mining; synthetic biology; systems biology
Introduction Bacterial sigma factors (ss), the promoter recognition subunits of RNA polymerase (RNAP), are modular proteins with domains that recognize DNA sequences in the 10 and 35 regions of their target promoters (Hook-Barnard and Hinton, 2007). In addition to the housekeeping ss (e.g., s70 in E. coli) that recognize the thousands of canonical promoters essential for growth, bacteria have a variable number of stressactivated alternative ss that direct RNAP to distinct promoter sequences. This enables cells to express multiple genes associated with a particular developmental state or stress response (Gruber and Gross, 2003) and to execute complex gene expression dynamics that implement temporal control and serve as developmental checkpoints (Chater, 2001). For example, spore formation in B. subtilis requires a cascade of five ss (sH-sF-sE-sG-sK) (Stragier and Losick, 1990). ss can be embedded in complex webs of partner swapping networks, including anti-ss, which physically block ss from interacting with RNAP (Helmann, 1999; Campbell et al, 2008; Staron´ et al, 2009), and anti-anti-ss. Such feedback loops and protein–protein interactions generate more complex dynamics & 2013 EMBO and Macmillan Publishers Limited
for integrating many environmental and cellular signals (Marles-Wright and Lewis, 2007). Extracytoplasmic function (ECF) ss are the smallest and simplest alternative ss, as well as the most abundant and phylogenetically diverse (Helmann, 2002; Staron´ et al, 2009). Possessing just the two domains that bind the promoter 10 and 35 regions (Gruber and Gross, 2003) (Figure 1A), they provide cells with a highly modular means to react to their environment (Lonetto et al, 1994; Staron´ et al, 2009), often responding to a signal through the action of an anti-s. ECF ss usually autoregulate their own expression and that of their anti-s (Rouvie`re et al, 1995; Rhodius et al, 2005). This organization can lead to diverse dynamical phenomena, including ultrasensitive bistable switches and pulse generators (Voigt et al, 2005; Locke et al, 2011; Tiwari et al, 2011). Moreover, promoters of an ECF s are highly conserved, facilitating identification, modeling, and rational design (Staron´ et al, 2009; Rhodius and Mutalik, 2010). Promoter specificity also results in a large dynamic range of output, where the OFF state is very low in the absence of the s and the ON state produces a high level of expression. Molecular Systems Biology 2013 1
Crosstalk between ECF ss, anti-ss, and promoters VA Rhodius et al
RNA polymerase
Sigma
Anti-sigma
GCAGGAACCGGTTGCGCTTAAACGCCACTCAG CCGGGGAACCCATCCTTTTCTGCGTCCACACAG GATGGAACCGCCTGGTCGGTCTTGCCACACAG CAGGGAACCGATGCGTCAATCGCACCACACAA TTGGGAACCGGAGCATAAAACACGCCACATAT AAGGGAACTGATCCGGGCCGTGACCCACTCAG TCAGGAACCCGATGGTGGTTTGCGCCACTCAT AAGGGAACTGAACCGACCAACGACCCACTCAG
–35 –10
Bits
2 1 0
UP –35–10
Arrange ECF operons from genome databases into subgroups
Transcription
Promoter
Identify predicted autoregulatory promoters within subgroups
GGAACCG
G A
T
C
A TC GTC G
TG TCGA G CC
A
CCAC CA
TCGCG A TA A
A A CC G C C A GT A CGA GGTTT T A TTG
T
Extract promoter motifs proteobacteria actinobacteria
UP element
A T GCG GA T A TT
Sigma binding boxes
Select orthogonal promoters, add UP elements
cyanobacteria chlorobi
firmicutes bacteriodetes
Sigma ECF38_1322*< ECF38_1442* ECF39_2973* ECF39_1438 ECF17_1691*< ECF17_1458* ECF27_4265*< ECF27_1331* ECF20_992*< ECF20_2913* ECF11_3726* ECF11_987*< ECF35_3582* ECF35_1119 ECF33_375* ECF33_423*< ECF34_3302* ECF14_3200* ECF14_1324*< ECF26_4464*< ECF26_837* ECF15_436*< ECF15_524* ECF12_807* ECF12_808* ECF29_371* ECF29_2688 ECF25_1645* ECF25_1643* ECF02_2817*< ECF02_915* ECF03_1198*< ECF03_1244* ECF04_1609* ECF04_1617* ECF36_3196 ECF36_1595 ECF19_3197 ECF19_1315 ECF18_4451 ECF18_4438 ECF34_1384*< ECF21_1280 ECF21_2825 ECF01_4085 ECF31_2963* ECF01_3473* ECF40_3198* ECF40_1380* ECF16_3622*< ECF16_973* ECF30_35* ECF32_1122*< ECF32_3724* ECF09_3581* ECF09_1009* ECF07_980* ECF07_1134* ECF08_3580* ECF08_3627 ECF06_3576 ECF06_853 ECF05_965 ECF05_1054 ECF31_34*< ECF28_1088*< ECF28_1040* ECF24_1034 ECF24_69 ECF10_3486 ECF10_2914 ECF30_83* ECF37_3390* ECF37_2513*< ECF13_1146 ECF13_1025 ECF23_231 ECF23_1851* ECF22_4450*< ECF22_1147* ECF43_4437 ECF43_3477 ECF41_491*< ECF41_1141 ECF42_3583 ECF42_4454*< Anti-sigma AS38_1322*< AS38_1442
AS39_1438 AS17_1691 AS17_1458 AS27_4265*< AS27_1331* AS20_992*
