Interaction of Fluorescent Probes with Sirtuin Proteins

Sirtuins are a class of proteins belonging to the Sir2 (Silencing information regulator 2) family of NAD+ dependent protein lysine deacylases. Different Isoforms (SIRT1-SIRT7) differ in their specific deacylase activity and cellular location. They have roles in DNA repair, glucose metabolism, and cellular proliferation which make them highly desirable targets for carcinoma therapeutics. We previously used 1-aminoanthracene’s (AMA) fluorescent properties when bound with SIRT2 (Kd of 37 μM) to develop a high-throughput screen to identify novel ligands that inhibit SIRT2’s enzymatic activities. We hope to reveal other potential probes for future high-throughput screening with all the sirtuin isotopes. 1-AMA’s fluorescence along with fluorescent labeled peptides “Cy3-PEG4-H4K16(myr)” and “FAM-PEG4-H4K16(myr)” were used in binding assays to determine their affinities with SIRT2, SIRT3, and SIRT6. Further, we determined 1-AMA’s ability to bind sirtuin isoforms when they were equilibrated with 100 μM of various acyl-peptides. 1-AMA displays weak binding to SIRT3 and SIRT6 when compared to SIRT2. FAM-PEG4-H4K16(myr) binds SIRT2 with a Kd of 7nM which is much higher than its interaction with SIRT3 and SIRT6 (Kd of 6 μM and 2 μM, respectively). Cy3-PEG4-H4K16(myr) binds as expected SIRT2,3,6 although its affinity for SIRT6 changes minimally with the addition of ADP-ribose, which suggests Cy3 may facilitate binding in the absence of SIRT6’s co-factor. Future work will test additional probes with the other sirtuin proteins and establish their competency to be utilized for high-throughput screening

Replication Protein A (RPA) Targeting of Uracil DNA Glycosylase (UNG2)

Replication Protein A (RPA) is a single stranded DNA binding protein which stabilizes ssDNA for replication and repair. One function of RPA is to bind the DNA repair enzyme uracil DNA glycosylase (UNG2) and direct its activity towards ssDNA dsDNA junctions. UNG2 removes uracil bases from DNA which can appear through dUMP misincorporation or through cytosine deamination. If uracil is present instead of a cytosine, then the original GC pair becomes a GU pair. The uracil will then base pair to adenine in the replicated daughter strand. This results in a GC → AT mutation that could contribute to cancer formation. RPA is known to target UNG2 towards individual uracil bases. We hypothesize that RPA will target UNG2 to uracil bases in DNA regardless of the number of uracils in the DNA strand

Effect of Uracil DNA Glycosylase Activity on the Efficacy of Thymidylate Synthase Inhibitor/HDAC Inhibitor Combination Therapies in Colon Cancer

Human uracil DNA glycosylase (UNG2) is responsible for removing uracil bases from DNA and initiates base excision repair pathways. Accumulation of uracil or its fluorinated analogs in DNA is one of the killing mechanisms of thymidylate synthase (TS) inhibitors in cancer cells, and depletion of UNG2 often enhances the toxicity of these anticancer drugs. We tested the effect of UNG2 KO on the efficacy of multiple TS inhibitors (5-fluorouracil, fluorodeoxyuridine, and pemetrexed) and we determined that, except for 5-fluorouracil, all other TS inhibitors were significantly more potent in UNG2 KO cells compared to wild-type HT29 cells. Interestingly, UNG2 protein levels can also be depleted by the HDAC inhibitors SAHA and MS275, providing a pharmacologic strategy to reduce UNG2 activity in cells. Unexpectedly, the HDAC inhibitors synergized with 5-fluorouracil but not fluorodeoxyuridine in both wild-type and UNG2-knockout cells. Similarly, HDAC inhibitors synergized with pemetrexed in wild-type HT29 but not UNG2-knockout cells. This suggested that HDAC inhibitors sensitized cells to 5-fluorouracil through an UNG2-independent mechanism. Interestingly, SAHA depleted the UNG2 level, whereas TS inhibitors alone and their combination with SAHA upregulated the level of UNG2 at 24 hours. This suggests HDAC inhibitors deplete UNG2 but, when combined with TS inhibitors, it did not affect UNG2, at least at a concentration of 100nM. Our future aim is to study these pharmacological drug combinations targeting UNG2 activity in cells and elucidate exact mechanisms of cell death

UNG2 and RPA Activity on ssDNA-dsDNA Junctions

Uracil DNA glycosylase, or UNG2, is an enzyme that is involved in DNA repair. Its primary job is to eliminate harmful uracil bases from DNA strands. To do this, the enzyme is assisted by replication protein A (RPA). RPA helps UNG2 in the identification of uracil bases by targeting UNG2 activity near ssDNA-dsDNA junctions (1-3). The results from assays presented here agree with published findings that showed UNG2 is heavily targeted by RPA to uracil bases that are close to ssDNA-dsDNA junctions (for example, uracil located 9 bps from the junction as opposed to 33 bps) (1,2). However, these previous experiments were performed in the absence of a macromolecular crowding agent. Inert compounds such as PEG8K can be used experimentally to better represent the physiologic environment inside a cell, which is very crowded with proteins and other small molecules and differs from dilute conditions often used in enzyme assays. In the presence of a crowding agent (PEG8K), we found that RPA balances UNG2’s selectivity for uracil sites near ssDNA-dsDNA junctions that contain a 5’ ssDNA section. In other words, UNG2 becomes less targeted to uracils that are very close to the junction (i.e., U9). Interestingly, this effect was not seen when we examined RPA effects on UNG2 activity using ssDNA-dsDNA junctions substrates that contain a 3’ ssDNA section

Substrate-Dependent Modulation of SIRT2 by a Fluorescent Probe, 1-Aminoanthracene

Sirtuin isoform 2 (SIRT2) is an enzyme that catalyzes the removal of acyl groups from lysine residues. SIRT2’s catalytic domain has a hydrophobic tunnel where its substrate acyl groups bind. Here, we report that the fluorescent probe 1-aminoanthracene (AMA) binds within SIRT2’s hydrophobic tunnel in a substrate-dependent manner. AMA’s interaction with SIRT2 was characterized by its enhanced fluorescence upon protein binding (\u3e10-fold). AMA interacted weakly with SIRT2 alone in solution (Kd = 37 μM). However, when SIRT2 was equilibrated with a decanoylated peptide substrate, AMA’s affinity for SIRT2 was enhanced ∼10-fold (Kd = 4μM). The peptide’s decanoyl chain and AMA co-occupied SIRT2’s hydrophobic tunnel when bound to the protein. In contrast, binding of AMA to SIRT2 was competitive with a myristoylated substrate whose longer acyl chain occluded the entire tunnel. AMA competitively inhibited SIRT2 demyristoylase activity with an IC50 of 21 μM, which was significantly more potent than its inhibition of other deacylase activities. Finally, binding and structural analysis suggests that the AMA binding site in SIRT2’s hydrophobic tunnel was structurally stabilized when SIRT2 interacted with a decanoylated or 4-oxononanoylated substrate, but AMA’s binding site was less stable when SIRT2 was bound to an acetylated substrate. Our use of AMA to explore changes in SIRT2’s hydrophobic tunnel that are induced by interactions with specific has implications for developing ligands that modulate SIRT2’s substrate specificity

Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison of Brain- Cousens and Cedergreen Models for a Biochemical Dataset

Biphasic, non-sigmoidal dose-response relationships are frequently observed in biochemistry and pharmacology, but they are not always analyzed with appropriate statistical methods. Here, we examine curve fitting methods for “hormetic” dose-response relationships where low and high doses of an effector produce opposite responses. We provide the full dataset used for modeling, and we provide the code for analyzing the dataset in SAS using two established mathematical models of hormesis, the Brain-Cousens model and the Cedergreen model. We show how to obtain and interpret curve parameters such as the ED50 that arise from modeling, and we discuss how curve parameters might change in a predictable manner when the conditions of the dose-response assay are altered. In addition to modeling the raw dataset that we provide, we also model the dataset after applying common normalization techniques, and we indicate how this affects the parameters that are associated with the fit curves. The Brain-Cousens and Cedergreen models that we used for curve fitting were similarly effective at capturing quantitative information about the biphasic dose-response relationships

Modeling Biphasic, Non-Sigmoidal Dose-Response Relationships: Comparison of Brain-Cousens and Cedergreen Models for a Biochemical Dataset

Biphasic, non-sigmoidal dose-response relationships are frequently observed in biochemistry and pharmacology, but they are not always analyzed with appropriate statistical methods. Here, we examine curve fitting methods for "hormetic" dose-response relationships where low and high doses of an effector produce opposite responses. We provide the full dataset used for modeling, and we provide the code for analyzing the dataset in SAS using two established mathematical models of hormesis, the Brain-Cousens model and the Cedergreen model. We show how to obtain and interpret curve parameters such as the ED50 that arise from modeling, and we discuss how curve parameters might change in a predictable manner when the conditions of the dose-response assay are altered. In addition to modeling the raw dataset that we provide, we also model the dataset after applying common normalization techniques, and we indicate how this affects the parameters that are associated with the fit curves. The Brain-Cousens and Cedergreen models that we used for curve fitting were similarly effective at capturing quantitative information about the biphasic dose-response relationships

A Conserved Mechanism for Hormesis in Molecular Systems

Hormesis refers to dose-response phenomena where low dose treatments elicit a response that is opposite the response observed at higher doses. Hormetic dose-response relationships have been observed throughout all of biology, but the underlying determinants of many reported hormetic dose-responses have not been identified. In this report, we describe a conserved mechanism for hormesis on the molecular level where low dose treatments enhance a response that becomes reduced at higher doses. The hormetic mechanism relies on the ability of protein homo-multimers to simultaneously interact with a substrate and a competitor on different subunits at low doses of competitor. In this case, hormesis can be observed if simultaneous binding of substrate and competitor enhances a response of the homo-multimer. We characterized this mechanism of hormesis in binding experiments that analyzed the interaction of homotrimeric proliferating cell nuclear antigen (PCNA) with uracil DNA glycosylase (UNG2) and a fluorescein-labeled peptide. Additionally, the basic features of this molecular mechanism appear to be conserved with at least two enzymes that are stimulated by low doses of inhibitor: dimeric BRAF and octameric glutamine synthetase 2 (GS2). Identifying such molecular mechanisms of hormesis may help explain specific hormetic responses of cells and organisms treated with exogenous compounds

Substrate-specific Effect on Sirtuin Conformation and Oligomerization

Human sirtuins are a family of nicotinamide adenine dinucleotide (NAD +)-dependent enzymes that are responsible for removing acyl modifications from lysine residues. Sirtuins are involved in the formation and proliferation of cancers and are thought to regulate the progression of neurodegenerative diseases. Although sirtuins can be pharmacologically targeted by small molecules, it is not easy to modulate the substrate selectivity of sirtuins despite the chemical diversity of their substrates. Here, we report substrate-specific effects on sirtuin conformation and oligomerization that regulate enzyme deacylase activity. We used fluorescent acyl peptide probes to study substrate interactions with two sirtuin isoforms: SIRT2 and SIRT6. We observed that some of the fluorescent acyl peptides bind sirtuins and change their conformation, whereas other probes bind sirtuins without causing such structural changes. Our fluorescent probes also revealed that SIRT2 forms a dimer at relevant cellular concentrations (~100 nM) in contrast to SIRT6, which is exclusively monomeric. SIRT2 undergoes a conformational transition from dimer to monomer when bound to myristoyl-substrate which slows its demyristoylase reaction, but SIRT2 remains dimeric when performing its deacetylase reaction. Our fluorescent peptide probes will continue to be used to examine substrate specific effects on sirtuin structure and function in order to understand how to pharmacologically modulate sirtuin substrate selectivity

A rapid research needs appraisal methodology to identify evidence gaps to inform clinical research priorities in response to outbreaks-results from the Lassa fever pilot

Abstract Background: Infectious disease epidemics are a constant threat, and while we can strengthen preparedness in advance, inevitably, we will sometimes be caught unaware by novel outbreaks. To address the challenge of rapidly identifying clinical research priorities in those circumstances, we developed and piloted a protocol for carrying out a systematic, rapid research needs appraisal (RRNA) of existing evidence within 5 days in response to outbreaks globally, with the aim to inform clinical research prioritization. Methods: The protocol was derived from rapid review methodologies and optimized through effective use of predefined templates and global time zones. It was piloted using a Lassa fever (LF) outbreak scenario. Databases were searched from 1969 to July 2017. Systematic reviewers based in Canada, the UK, and the Philippines screened and extracted data using a systematic review software. The pilot was evaluated through internal analysis and by comparing the research priorities identified from the data, with those identified by an external LF expert panel. Results: The RRNA pilot was completed within 5 days. To accommodate the high number of articles identified, data extraction was prioritized by study design and year, and the clinical research prioritization done post-day 5. Of 118 potentially eligible articles, 52 met the data extraction criteria, of which 46 were extracted within the 5-day time frame. The RRNA team identified 19 clinical research priorities; the expert panel independently identified 21, of which 11 priorities overlapped. Each method identified a unique set of priorities, showing that combining both methods for clinical research prioritization is more robust than using either method alone. Conclusions: This pilot study shows that it is feasible to carry out a systematic RRNA within 5 days in response to a (re-) emerging outbreak to identify gaps in existing evidence, as long as sufficient resources are identified, and reviewers are experienced and trained in advance. Use of an online systematic review software and global time zones effectively optimized resources. Another 3 to 5 days are recommended for review of the extracted data and to formulate clinical research priorities. The RRNA can be used for a “Disease X” scenario and should optimally be combined with an expert panel to ensure breadth and depth of coverage of clinical research priorities. Keywords: Emerging infectious diseases, Clinical research priorities, Outbreak response, Lassa fever, Rapid research needs appraisal methodolog