Using targeted chromatin regulators to engineer combinatorial and spatial transcriptional regulation - PubMed (original) (raw)

Using targeted chromatin regulators to engineer combinatorial and spatial transcriptional regulation

Albert J Keung et al. Cell. 2014.

Abstract

The transcription of genomic information in eukaryotes is regulated in large part by chromatin. How a diverse array of chromatin regulator (CR) proteins with different functions and genomic localization patterns coordinates chromatin activity to control transcription remains unclear. Here, we take a synthetic biology approach to decipher the complexity of chromatin regulation by studying emergent transcriptional behaviors from engineered combinatorial, spatial, and temporal patterns of individual CRs. We fuse 223 yeast CRs to programmable zinc finger proteins. Site-specific and combinatorial recruitment of CRs to distinct intralocus locations reveals a range of transcriptional logic and behaviors, including synergistic activation, long-range and spatial regulation, and gene expression memory. Comparing these transcriptional behaviors with annotated CR complex and function terms provides design principles for the engineering of transcriptional regulation. This work presents a bottom-up approach to investigating chromatin-mediated transcriptional regulation and introduces chromatin-based components and systems for synthetic biology and cellular engineering.

Copyright © 2014 Elsevier Inc. All rights reserved.

PubMed Disclaimer

Figures

Figure 1

Figure 1. A synthetic biology approach to engineering chromatin-based transcriptional regulation

Eukaryotic gene transcription is regulated by diverse chromatin-regulating complexes and networks (top right). The complexes were decomposed into a library of subunit chromatin regulator (CR) proteins (top left). These subunits were fused to engineered zinc finger (ZF) proteins to enable site-specific spatial and combinatorial targeting to designed gene loci (bottom). This modular framework allows the direct functional characterization of individual CRs as transcriptional regulators, and for designing locus architectures that recruit different combinations of CRs to explore and engineer complex spatial and combinatorial transcriptional regulation.

Figure 2

Figure 2. Identifying transcriptional regulators by direct recruitment of a library of 223 CRs

(A, top) 223 CR proteins were fused to an engineered ZF protein (or non-targeting ZF) and placed under the control of an inducible GAL1 promoter. Each fusion protein was individually recruited to operators placed upstream of a minimal CYC1 promoter driving the expression of GFP. NLS, nuclear localization signal. (A, bottom) Fold change in GFP expression induced by VP16 activation and Mig1 repression domains fused to targeting or non-targeting ZF proteins. (B) Fold change in GFP expression for the library of 223 ZF-CR fusions (normalized to uninduced levels). Repressors (blue bars) were classified as having < 0.7 fold change, while activators (red bars) have > 2 fold change. (C) CRs grouped by complex and plotted according to the percentage of activators and repressors in each complex. Dot colors correspond to the general activities of each complex. Error bars are standard deviations of three isogenic strains. See also Figures S1 and S2.

Figure 3

Figure 3. Combinatorial recruitment reveals distinct classes of regulators for engineering transcriptional logic

(A) An engineered two-input system enabling the co-recruitment of CRs and VP16 transactivating domain (ZF 43-8, grey; ZF 97-4, blue) (Khalil et al., 2012). (B) Representative transcriptional logic outputs of the two-input system divide CRs into six distinct classes (top to bottom): VP16-independent dominant repressors, repressors, CRs with no effect, VP16 enhancers, additive activators (purple), and synergistic activators (red). (C) Activating CRs clustered by complex and plotted by level of transcriptional synergy. Transcription/preinitiation complex regulators generated weak synergy, while chromatin assembly/remodeling, chromatin-modifying, and transcription-elongating regulators generated strong synergy. Synergy is the “cooperation” of factors to produce a total output, and here is defined as the fraction of total output not accounted for by summing the outputs from the individual components. Synergy = [(A – 1) – (B – 1) – (C – 1)]/(A – 1) where A = CR and VP16, B = CR only, and C = VP16 only. (D) Activators clustered by gene ontology function terms and plotted as percentage of CRs in each term group with “strong synergy” (greater than the average synergy of 0.2). Error bars are standard deviations of three isogenic strains. See also S3.

Figure 4

Figure 4. Engineering spatial regulation by targeting CRs upstream and downstream of a gene

A gene locus was engineered to recruit 223 CR fusions to operators either upstream or downstream (downstream of a CYC1 terminator) of a reporter gene. CRs were grouped according to their upstream- and downstream-targeted regulatory profiles. Gene ontology function terms unique to each group are listed along with the number of CRs in the group associated with each term. See also Figure S4.

Figure 5

Figure 5. Simultaneous and distinct regulation of two genes by individual CRs

(A) Schematic of the engineered, dual-gene reporter locus (CYC1 promoters and terminators used throughout) (top). Fold change in GFP (green bars) and mCherry (red bars) expression for six targeted CR fusions (bottom). (B) Swapping operator locations results in inversion of transcriptional outputs. (C) Schematic of the same locus architecture as in (A) but containing two different promoters and terminators (BIO2 promoter and ADH1 terminator in purple). Error bars are standard deviations of three isogenic strains. See also Figure S5.

Figure 6

Figure 6. Long-range and multi-gene regulation by targeted CRs

(A) Schematic of the engineered, multi-gene reporter locus. The 27 strongest repressors and 48 strongest activators identified from the full ZF-CR library as well as all CRs with histone-modifying catalytic domains were targeted upstream of the first gene. (B) Heat map of the fold change in fluorescence for GFP, mCherry, and BFP, revealing classes of CRs that regulate only the proximal gene (left and middle) or that repress all three genes in the locus (right). See also Figure S6.

Figure 7

Figure 7. Epigenetic repression and insulation

(A) Time courses of induction/wash-out experiments for three CRs. CR fusions were expressed at t = 0 hr by the addition of the small molecule ATc, which was subsequently washed out at t = 12 hr (grey bars). Med16 and Isw2 show reversible activation and repression of GFP, respectively. Sir2 maintains full repressive memory of the proximal gene and partial repressive memory of the downstream gene. (B) Nucleosome-disfavoring sequences inserted between the GFP and mCherry genes as putative barrier or insulator elements. (C) Fold change in fluorescence for GFP, mCherry, and BFP induced by targeting (top) or non-targeting (bottom) multi-gene repressors (Sir2, Rph1, Sum1 fusions). The (CCGNN)32 sequence robustly insulates only the middle gene (mCherry) from repression by the CRs. (D) Schematic of the multi-gene regulatory circuit. Error bars are standard deviations of three isogenic strains. See also Figure S7.

Comment in

Similar articles

Cited by

References

    1. Atkinson MR, Savageau MA, Myers JT, Ninfa AJ. Development of genetic circuitry exhibiting toggle switch or oscillatory behavior in Escherichia coli. Cell. 2003;113:597–607. - PubMed
    1. Bi X, Yu Q, Sandmeier JJ, Zou Y. Formation of Boundaries of Transcriptionally Silent Chromatin by Nucleosome-Excluding Structures. Molecular and Cellular Biology. 2004;24:2118–2131. - PMC - PubMed
    1. Blount BA, Weenink T, Vasylechko S, Ellis T. Rational diversification of a promoter providing fine-tuned expression and orthogonal regulation for synthetic biology. PLoS One. 2012;7:e33279. - PMC - PubMed
    1. Cherry JM, Hong EL, Amundsen C, Balakrishnan R, Binkley G, Chan ET, Christie KR, Costanzo MC, Dwight SS, Engel SR, et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Research. 2012;40:D700–705. - PMC - PubMed
    1. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, Hsu PD, Wu X, Jiang W, Marraffini LA, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. 2013;339:819–823. - PMC - PubMed

Publication types

MeSH terms

Substances

LinkOut - more resources