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Engineering stringent genetic biocontainment of yeast with a protein stability switch

ABSTRACT: Synthetic biology holds immense promise to tackle key problems we are facing, for instance in resource use, environmental health, and human health care. However, comprehensive safety measures are needed to deploy genetically engineered microorganisms in open-environment applications. Intrinsic, genetically encoded biocontainment systems, which control cell survival based on environmental cues, can solve this issue. Here, we describe a genetic biocontainment system based on conditional stability of essential proteins. We used a yeast-adapted destabilizing domain degron, which can be stabilized by estradiol addition (ERdd). Leveraging the yeast GFP collection and lab automation platforms, we ERdd-tagged 775 essential genes and screened for strains with estradiol dependent growth. Three genes, SPC110, DIS3 and RRP46, were found to be particularly suitable targets. Respective strains showed no growth defect in the presence of estradiol and strong growth inhibition in its absence. SPC110-ERdd offered the most stringent containment, with an escape frequency of 7.0x10-8, and full growth restoration at 100 nM estradiol. By systematically analyzing the containment escapees, we identified the non-essential C-terminal region of SPC110 as target for escape mutations. Its removal decreased the escape frequency with a single ERdd tag further to 4.9x10-9. Combining SPC110-ERdd with a second ERdd tag on either DIS3 or RRP46 resulted in escape frequencies below the detection limit of the used assay (<2x10-10). Being based on conditional protein stability, this approach is mechanistically orthogonal to previously reported intrinsic biocontainment systems. It thus can be readily combined with other systems, for instance ones based on transcriptional or translational control of essential gene expression, to achieve multiplexed, extremely stringent control over the survival of engineered organisms.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Stefan Hoffmann

LAB HEAD: Yizhi Cai

PROVIDER: PXD042326 | Pride | 2024-02-05

REPOSITORIES: Pride

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			Action	DRS
	20221118_6pm_Std_GTU_13-15.pdf	Pdf
	20221118_6pm_Std_GTU_13.raw	Raw
	20221118_6pm_Std_GTU_14.raw	Raw
	20221118_6pm_Std_GTU_15.raw	Raw
	20221118_6pm_Std_GTU_16-18.pdf	Pdf

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Project description:Primordial follicle assembly is the process by which ovarian primordial follicles are formed. During follicle assembly oocyte nests break down and a layer of pre-granulosa cells surrounds individual oocytes to form primordial follicles. The pool of primordial follicles formed is the source of oocytes for ovulation during a femaleM-bM-^@M-^Ys reproductive life. Complex networks of cellular signaling and gene expression are essential for any biological process. A systems biology experimental approach provides a global view of these gene relationships in a particular developmental process. The current study utilized a systems approach to detect all genes that are differentially expressed in response to seven different growth factor and hormone treatments known to influence primordial follicle assembly in a neonatal rat ovary culture system. One novel growth factor, basic fibroblast growth factor (FGF2), was experimentally determined to inhibit follicle assembly. The different growth factor and hormone treatments were all found to affect the same physiological pathways, but each treatment affected a unique set of differentially expressed genes (signature gene set). A gene bionetwork analysis identified gene modules of coordinately expressed interconnected genes and it was found that different gene modules appear to accomplish distinct tasks during primordial follicle assembly. Unique gene networks were identified for a number of the modules and signature gene sets. Predictions of physiological pathways important to follicle assembly were validated using ovary culture experiments in which ERK1/2 (MAPK1) activity was increased. A number of the highly interconnected genes in these gene networks have previously been linked to primary ovarian insufficiency (POI) and polycystic ovarian disease syndrome (PCOS). Observations have identified novel factors and gene networks that regulate primordial follicle assembly. This systems approach has helped elucidate the molecular control of primordial follicle assembly and provided potential therapeutic targets for the treatment of ovarian disease. We used microarrays to determine genes expressed differentially between control and P0 ovaries treated with 7 growth factors: AMH, CTGF, estradiol (E2), Activin-a, FGF2, progesterone (P4), and TNFa. RNA samples from 7 control samples are compared to 3 growth factor treated ovary samples for each AMH (human Anti-MM-CM-<lerian hormone), CTGF (connective tissue growth factor ), estradiol (E2), TNF (tumor necrosis factor ), FGF2 (fibroblast growth factor 2), Inhba (inhibin, beta A), and 2 samples for progesterone (P4).

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Engineering stringent genetic biocontainment of yeast with a protein stability switch

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