Directly light-regulated binding of RGS-LOV photoreceptors to anionic membrane phospholipids.

We report natural light-oxygen-voltage (LOV) photoreceptors with a blue light-switched, high-affinity (KD ∼ 10-7 M), and direct electrostatic interaction with anionic phospholipids. Membrane localization of one such photoreceptor, BcLOV4 from Botrytis cinerea, is directly coupled to its flavin photocycle, and is mediated by a polybasic amphipathic helix in the linker region between the LOV sensor and its C-terminal domain of unknown function (DUF), as revealed through a combination of bioinformatics, computational protein modeling, structure-function studies, and optogenetic assays in yeast and mammalian cell line expression systems. In model systems, BcLOV4 rapidly translocates from the cytosol to plasma membrane (∼1 second). The reversible electrostatic interaction is nonselective among anionic phospholipids, exhibiting binding strengths dependent on the total anionic content of the membrane without preference for a specific headgroup. The in vitro and cellular responses were also observed with a BcLOV4 homolog and thus are likely to be general across the dikarya LOV class, whose members are associated with regulator of G-protein signaling (RGS) domains. Natural photoreceptors are not previously known to directly associate with membrane phospholipids in a light-dependent manner, and thus this work establishes both a photosensory signal transmission mode and a single-component optogenetic tool with rapid membrane localization kinetics that approaches the diffusion limit.

The Effect of Different Ester Chain Modifications of Two Guaianolides for Inhibition of Colorectal Cancer Cell Growth.

Several sesquiterpene lactones (STLs) have been tested as lead drugs in cancer clinical trials. Salograviolide-A (Sal-A) and salograviolide-B (Sal-B) are two STLs that have been isolated from Centaurea ainetensis, an indigenous medicinal plant of the Middle Eastern region. The parent compounds Sal-A and Sal-B were modified and successfully prepared into eight novel guaianolide-type STLs (compounds 1-8) bearing ester groups of different geometries. Sal-A, Sal-B, and compounds 1-8 were tested against a human colorectal cancer cell line model with differing p53 status; HCT116 with wild-type p53 and HCT116 p53-/- null for p53, and the normal-like human colon mucosa cells with wild-type p53, NCM460. IC50 values indicated that derivatization of Sal-A and Sal-B resulted in potentiation of HCT116 cell growth inhibition by 97% and 66%, respectively. The effects of the different molecules on cancer cell growth were independent of p53 status. Interestingly, the derivatization of Sal-A and Sal-B molecules enhanced their anti-growth properties versus 5-Fluorouracil (5-FU), which is the drug of choice in colorectal cancer. Structure-activity analysis revealed that the enhanced molecule potencies were mainly attributed to the position and number of the hydroxy groups, the lipophilicity, and the superiority of ester groups over hydroxy substituents in terms of their branching and chain lengths. The favorable cytotoxicity and selectivity of the potent molecules, to cancer cells versus their normal counterparts, pointed them out as promising leads for anti-cancer drug design.

Designing Single-Component Optogenetic Membrane Recruitment Systems: The Rho-Family GTPase Signaling Toolbox.

We describe the efficient creation of single-component optogenetic tools for membrane recruitment-based signaling perturbation using BcLOV4 technology. The workflow requires two plasmids to create six different domain arrangements of the dynamic membrane binder BcLOV4, a fluorescent reporter, and the fused signaling protein of interest. Screening of this limited set of genetic constructs for expression characteristics and dynamic translocation in response to one pulse of light is sufficient to identify viable signaling control tools. The reliability of this streamlined approach is demonstrated by the creation of an optogenetic Cdc42 GTPase and Rac1-activating Tiam1 GEF protein, which together with our other recently reported technologies, completes a toolbox for spatiotemporally precise induction of Rho-family GTPase signaling at the GEF or GTPase level, for driving filopodial protrusions, lamellipodial protrusions, and cell contractility, respectively mediated by Cdc42, Rac1, and RhoA.

Application of Systems Biology to Neuroproteomics: The Path to Enhanced Theranostics in Traumatic Brain Injury.

The application of systems biology tools in analyzing heterogeneous data from multiple sources has become a necessity, especially in biomarker discovery. Such tools were developed with several approaches to address different types of research questions and hypotheses. In the field of neurotrauma and traumatic brain injury (TBI), three distinct approaches have been used so far as systems biology tools, namely functional group categorization, pathway analysis, and protein-protein interaction (PPI) networks. The databases allow for query of the system to identify candidate targets which can be further studied to elucidate potential downstream biomarkers indicative of disease progression, severity, and improvement. The various systems biology tools, databases, and strategies that can be implemented on available TBI data in neuroproteomic studies are discussed in this chapter.

Role of Systems Biology in Brain Injury Biomarker Discovery: Neuroproteomics Application.

Years of research in the field of neurotrauma have led to the concept of applying systems biology as a tool for biomarker discovery in traumatic brain injury (TBI). Biomarkers may lead to understanding mechanisms of injury and recovery in TBI and can be potential targets for wound healing, recovery, and increased survival with enhanced quality of life. The literature available on neurotrauma studies from both animal and clinical studies has provided rich insight on the molecular pathways and complex networks of TBI, elucidating the proteomics of this disease for the discovery of biomarkers. With such a plethora of information available, the data from the studies require databases with tools to analyze and infer new patterns and associations. The role of different systems biology tools and their use in biomarker discovery in TBI are discussed in this chapter.