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Review
. 2018 Mar;10(2):10.1002/wsbm.1405.
doi: 10.1002/wsbm.1405. Epub 2017 Sep 28.

Small molecule signaling, regulation, and potential applications in cellular therapeutics

Affiliations
Review

Small molecule signaling, regulation, and potential applications in cellular therapeutics

Monica P McNerney et al. Wiley Interdiscip Rev Syst Biol Med. 2018 Mar.

Abstract

Small molecules have many important roles across the tree of life: they regulate processes from metabolism to transcription, they enable signaling within and between species, and they serve as the biochemical building blocks for cells. They also represent valuable phenotypic endpoints that are promising for use as biomarkers of disease states. In the context of engineering cell-based therapeutics, they hold particularly great promise for enabling finer control over the therapeutic cells and allowing them to be responsive to extracellular cues. The natural signaling and regulatory functions of small molecules can be harnessed and rewired to control cell activity and delivery of therapeutic payloads, potentially increasing efficacy while decreasing toxicity. To that end, this review considers small molecule-mediated regulation and signaling in bacteria. We first discuss some of the most prominent applications and aspirations for responsive cell-based therapeutics. We then describe the transport, signaling, and regulation associated with three classes of molecules that may be exploited in the engineering of therapeutic bacteria: amino acids, fatty acids, and quorum-sensing signaling molecules. We also present examples of existing engineering efforts to generate cells that sense and respond to levels of different small molecules. Finally, we discuss future directions for how small molecule-mediated regulation could be harnessed for therapeutic applications, as well as some critical considerations for the ultimate success of such endeavors. WIREs Syst Biol Med 2018, 10:e1405. doi: 10.1002/wsbm.1405 This article is categorized under: Biological Mechanisms > Cell Signaling Biological Mechanisms > Metabolism Translational, Genomic, and Systems Medicine > Therapeutic Methods.

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Conflict of interest statement

Monica P. McNerney, No conflicts of interest

Mark P. Styczynski, No conflicts of interest

Figures

Figure 1
Figure 1
Overview of the ways that metabolite signals can be harnessed to create cellular therapeutics. Extracellular metabolites, including amino acids, fatty acids, and quorum sensing molecules, can trigger changes in cellular activity. Some metabolites enter the cytoplasm directly through the membrane or through specific transporters, and other metabolites bind to proteins either extracellularly or in the periplasm and trigger signaling cascades. Metabolites can effect changes in cells by changing the conformation of enzymes, mRNA, or transcription factors. Ultimately, to create effective cellular therapeutics, cells will have to sense and respond to multiple metabolite markers by enacting layered logic gates to tightly and specifically control the production of therapeutic proteins or metabolites. Finally, the therapeutic molecules must be released so that they can have the desired effect on the target cells.
Figure 2
Figure 2
Control of tryptophan biosynthesis genes in E. coli. Tryptophan biosynthesis is controlled through both transcriptional repression and transcriptional attenuation. (A) In the presence of tryptophan, the transcription factor TrpR binds to tryptophan, changes its conformation, and binds to the trp operator site to prevent binding of RNA polymerase (RNAP) to the promoter (Ptrp) and transcription of the trp operon. (B) Transcriptional attenuation is another layer of control in preventing unnecessary expression of tryptophan biosynthesis genes. If transcription is initiated in the presence of tryptophan, while translating the leader peptide TrpL, a transcriptional terminator is transcribed that causes RNAP dissociation from the DNA and prevents transcription of the trp operon. (C) In the absence of tryptophan, TrpR cannot bind to the trp operator site, and transcription of the trp operon proceeds. (D) In limited tryptophan, the ribosome stalls on tryptophan codons in the leader peptide because of a shortage of tryptophan-charged charged transfer RNAs. This stall alters messenger RNA (mRNA) folding kinetics such that an antiterminator forms, transcription continues, and tryptophan biosynthesis proteins are synthesized.
Figure 3
Figure 3
Examples of ways that metabolite signaling and regulation has been harnessed for metabolic engineering and therapeutic applications. (A) Tryptophan regulation of cell output. The genes of the tna operon, which naturally degrade tryptophan, were replaced with either GFP or the vioABCDE genes, which produce the purple pigment violacein from tryptophan. In the presence of tryptophan, tryoptophan binds to the ribosome to prevent premature transcriptional termination. Replacement of the naturally occurring genes with either reporter genes or metabolic pathways created a biosensor that reported on intracellular tryptophan levels and a dynamically controlled metabolic pathway that upregulated violacein synthesis in the presence of excess tryptophan. Adapted from Fang, et. al. (B) Dynamic regulation of fatty acid production to improve fatty acids yields. In the absence of malonyl-CoA (a precursor to fatty acids), the transcription factor FapR turns on the malonyl-CoA synthesis pathway and represses synthesis of fatty acids. When sufficient malonyl-CoA has accumulated, malonyl-CoA binds to FapR, and the FapR-malonyl-CoA complex then activates the fatty acid synthesis pathway. Adapted from Xu, et. al. (C) Cell-density dependent metabolite production. Target genes are expressed from a T7 promoter, which is only transcribed in the presence of T7 RNA polymerase (T7 RNAP). In low cell density, the transcription factor LsrR represses production of T7 RNAP, and the target genes are not expressed. Once the culture reaches a threshold cell density, phosphorylated autoinducer binds to LsrR, and LsrR no longer represses transcription of T7 RNAP. T7 RNAP then transcribes the target gene. Adapted from Tsao, et. al. (D) Cell-density dependent drug delivery. Genes for an anti-cancer drug and a lytic protein were placed under control of LuxR regulated promoters. In low cell density, these genes are not activated. Once the cells reach a threshold cell density, autoinducer binds to LuxR, turning on production of the drug and lytic protein. Synchronized lysis of cells delivers the drug to the surrounding environment, and a few unlysed bacteria enable reseeding and pulsatile treatment. Adapted from Din, et. al.
Figure 4
Figure 4
Fatty acid transport, signaling, and regulation in E. coli. The outer membrane protein FadL recognizes and transports long chain fatty acids (LCFA) into the periplasm. The slight acidity of the periplasm causes the carboxyl group of the LCFA to become protonated, which triggers it to “flip” to the cytoplasmic face of the inner membrane. The acyl-CoA synthetase FadD then localizes to the inner membrane, where it cleaves the charged fatty acid to yield a long chain acyl-CoA. The transcription factor FadR binds the LC Acyl-CoA, which makes FadR unable to bind to its operator site. Fatty acid degradation pathways are upregulated and fatty acid synthesis pathways are downregulated. Figure adapted from Dirusso and Black.
Figure 5
Figure 5
Quorum sensing signaling and regulation. (A) AHL-mediated quorum-sensing networks. LuxI is an AHL synthase that produces acyl-homoserine lactones (AHLs) that can freely diffuse through the membrane. When the AHL concentration reaches a critical threshold, LuxR family proteins bind AHL to alter the transcription of target genes. (B) The AI-2 mediated quorum sensing network in E. coli. LuxS produces the quorum sensing molecule AI-2. The transporter YdgG facilitates AI-2 export. When the AI-2 concentration has reached a threshold level, the ABC transporter LsrACDB imports AI-2 into the cytoplasm, where it is phosphorylated by LsrK. The phosphorylated AI-2 molecule binds to LsrR, prompting derepression of target genes. Figure adapted from (A) Miller & Bassler and (B) Li et al..

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