Water-soluble Azobenzene Photoswitches for Controlling Biological Systems

Photoswitches are small molecules that reversibly change their shape and properties upon irradiation with light of different colors. Since these molecules can be manipulated with nonharmful light from the outside at any given location and time, photoswitches are a powerful tool to study different biological targets and for the development of novel light-responsive therapeutics. The major challenges for the application of photoswitches in biological settingare their insolubility in water as well as the fact that the aqueous environment often has a negative impact on the properties of the photoswitch. In addition, many known photoswitches respond to UV light which is damaging to tissue. Those challenges have inspired great efforts to redesign the photoswitch molecules to fully respond to exclusively visible light while also featuring water solubility. In my thesis I focused on developing water-soluble photoswitchesand applying them to manipulate biological systems. The synthesized photoswitches were used to harness the cell-destroying activity of a biological toxin resulting, in a system which could destroy cancer cells upon illumination with light of a specific color. Furthermore, a photoswitch was incorporated into a peptide known to play a crucial role in neurodegenerative diseases, such as Huntington’s disease, to shed light on the mechanism of the disease. Furthermore, this thesis reports several photoswitches which are both watersoluble and completely responsive to visible light thus bringing them one step closer towards applications in living organisms

Molecular photoswitches in aqueous environments

Molecular photoswitches enable dynamic control of processes with high spatiotemporal precision, using light as external stimulus, and hence are ideal tools for different research areas spanning from chemical biology to smart materials. Photoswitches are typically organic molecules that feature extended aromatic systems to make them responsive to (visible) light. However, this renders them inherently lipophilic, while water-solubility is of crucial importance to apply photoswitchable organic molecules in biological systems, like in the rapidly emerging field of photopharmacology. Several strategies for solubilizing organic molecules in water are known, but there are not yet clear rules for applying them to photoswitchable molecules. Importantly, rendering photoswitches water-soluble has a serious impact on both their photophysical and biological properties, which must be taken into consideration when designing new systems. Altogether, these aspects pose considerable challenges for successfully applying molecular photoswitches in aqueous systems, and in particular in biologically relevant media. In this review, we focus on fully water-soluble photoswitches, such as those used in biological environments, in both in vitro and in vivo studies. We discuss the design principles and prospects for water-soluble photoswitches to inspire and enable their future applications

Reversible Photocontrolled Nanopore Assembly

Self-assembly is a fundamental feature of biological systems, and control of such processes offers fascinating opportunities to regulate function. Fragaceatoxin C (FraC) is a toxin that upon binding to the surface of sphingomyelin-rich cells undergoes a structural metamorphosis, leading to the assembly of nanopores at the cell membrane and causing cell death. In this study we attached photoswitchable azobenzene pendants to various locations near the sphingomyelin binding pocket of FraC with the aim of remote controlling the nanopore assembly using light. We found several constructs in which the affinity of the toxin for biological membranes could be activated or deactivated by irradiation, thus enabling reversible photocontrol of pore formation. Notably, one construct was completely inactive in the thermally adapted state; it however induced full lysis of cultured cancer cells upon light irradiation. Selective irradiation also allowed isolation of individual nanopores in artificial lipid membranes. Photocontrolled FraC might find applications in photopharmacology for cancer therapeutics and has potential to be used for the fabrication of nanopore arrays in nanopore sensing devices, where the reconstitution, with high spatiotemporal precision, of single nanopores must be controlled

Design and Synthesis of Visible-Light-Responsive Azobenzene Building Blocks for Chemical Biology

Tetra-ortho-fluoro-azobenzenes are a class of photoswitches useful for the construction of visible-light-controlled molecular systems. They can be used to achieve spatio-temporal control over the properties of a chosen bioactive molecule. However, the introduction of different substituents to the tetra-fluoro-azobenzene core can significantly affect the photochemical properties of the switch and compromise biocompatibility. Herein, we explored the effect of useful substituents, such as functionalization points, attachment handles, and water-solubilizing groups, on the photochemical properties of this photochromic system. In general, all the tested fluorinated azobenzenes exhibited favorable photochemical properties, such as high photostationary state distribution and long half-lives, both in organic solvents and in water. One of the azobenzene building blocks was functionalized with a trehalose group to enable the uptake of the photoswitch into mycobacteria. Following metabolic uptake and incorporation of the trehalose-based azobenzene in the mycobacterial cell wall, we demonstrated photoswitching of the azobenzene in the isolated total lipid extract

Photoswitchable, Water-Soluble Bisazobenzene Cross-Linkers with Enhanced Properties for Biological Applications

Photoswitchable cross-linkers are light-responsive molecules that can be attached at two locations to a target biomolecule to modulate its activity. Under irradiation, the cross-linker changes the distance between the residues it spans, affecting the structure and function of the labeled target. Efficient photocontrol is enabled especially by cross-linkers with large end-to-end length change upon switching. The design of water-soluble azobenzene-based cross-linkers for applications in chemical biology remains challenging due to major issues regarding synthesis and purification. Furthermore, the solubility and photochemical properties of the reported systems are frequently not suitable in aqueous media. Herein we report two water-soluble bisazobenzene cross-linkers with extended half-lives and high photostationary state isomer distributions that can be achieved upon irradiation. We present molecules that enable cross-linking of biomolecular residues within one target, or are bridging two proteins to allow the study of protein–protein interactions, which paves the way for light-based manipulation of under-explored biological targets

ZDHHC_lipidomics_2023.zip

Lipidomics Methods Lipid extraction: HEK293T cells were seeded in 6-well plates, grown to 70% confluency and treated with bumped fatty acid probes (15 µM) for 4 h. Cells were dislodged into their growth media by pipetting and pelleted by centrifugation (500 x g, 5 min). The cell pellet was washed 2X with ice-cold PBS and pelleting by centrifugation. Subsequently, the cells were resuspended in 500 µL of ice-cold 150 mM ammonium bicarbonate. An aliquot (10%) was kept aside for protein concentration determination and the remaining sample snap-frozen in liquid nitrogen and stored at -80°C until further processing. For protein concentration determination, cells were lysed in M-PER™ Mammalian Protein Extraction Reagent (Thermo Fisher, 78501) and protein content determined using the Pierce™ BCA Protein Assay Kit (Thermo Fisher, 23227) as per the manufacturer’s instructions. An aliquot equivalent to 100 µg protein per sample were used for lipid extraction. Lipid were extracted by the methyl-tert-butyl ether (MTBE) method with minor modifications62. Extractions were performed in glass vials fitted with Teflon-lined caps using MS-grade solvents and water. Glass pipettes were used to handle any MTBE-containing solutions or lipid extracts. Methanol (1.5 mL) was added and the protein sample vortexed. MTBE (5 mL) was added and the mixture was incubated for 1 h at RT on a shaker. Phase separation was induced by the addition of water (1.25 mL) followed by incubation for 10 min at room temperature. The sample was centrifuged (1,000 x g, 10 min) and the upper organic phase collected. The lower aqueous phase was re-extracted by addition of 1.67 mL of solvent mixture comprising MTBE/methanol (10:3, v/v) and 0.32 mL water. The samples were vortexed, incubated for 10 min and centrifuged (1000 x g, 10 min). The upper phase was recovered, and the combined organic phases were evaporated at 37°C under a stream of nitrogen and stored at -20°C. Lipid extracts were reconstituted in 100 µL loading buffer (isopropanol/water/acetonitrile, 2:1:1, v/v/v). Blank control extraction was performed on a 200 µL aliquot of 150 mM ammonium bicarbonate solution. Quality control (QC) samples were prepared by pooling a small aliquot of all experimental samples after resuspension in loading buffer. Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS): Analysis was performed on a 1290 Infinity II UHPLC system coupled to a 6550 iFunnel quadrupole time-of-flight (QTOF) mass spectrometer (Agilent Technologies). The reversed-phase chromatography protocol was optimized with minor modifications from Cajka and Fiehn63. Extracted lipids were separated on an Acquity UPLC CSH C18 column (130 Å, 1.7 μm, 2.1 x 100 mm) fitted with an Acquity UPLC CSH C18 VanGuard pre-column (130 Å, 1.7 µm, 2.1 mm x 5 mm) (both Waters). The column was maintained at 65°C at a flowrate of 0.6 mL/min. The mobile phases used were 60:40 (v:v) acetonitrile/H2O (solvent A) and 10:90 (v:v) acetonitrile/isopropanol (solvent B). Solvent A and B were supplemented with 10 mM ammonium formate and 0.1% formic acid for ESI positive mode and with 10 mM ammonium acetate for ESI negative mode analysis. UHPLC gradient elution was carried out as follows: 0−2 min 15-30% B; 2-2.5 min 30-48% B; 2.5−11 min 48-82% B; 11-11.5 min 82-99% B; 11.5-14.50 min 99% B. The gradient was returned to initial conditions over 0.5 min and the column equilibrated for 3 min before subsequent runs. Between injections a 100% isopropanol needle wash was performed. For negative mode 5 µL (MS mode) or 10 µL (MS/MS mode) of sample and for positive mode 4 µL (MS mode) or 8 µL (MS/MS mode) of sample were injected. Samples were injected in randomized order, with QC sample injections added to the start, middle and end of each sample sequence to ensure consistency and reproducibility of all acquisition parameters. Samples were loaded in a random order by blinded selection from pooled anonymously labelled samples. Electrospray parameters were set as follows: gas and sheath gas temperature, 200°C; drying gas flow, 14 L/min; sheath gas flow, 11 L/min; sheath gas temperature, 350°C; nebulizer pressure, 35 psig; capillary voltage, 3,000 V; nozzle voltage, 1,000 V. MS-TOF fragmentor and Oct 1 RF Vpp radio voltage were set to 350 and 750 V respectively. The QTOF was calibrated and operated in the extended dynamic range mode (∼2 GHz) in the mass range 50 to 1700 m/z. Spectra were acquired in centroid mode with an acquisition rate of 2 spectra/s for MS mode acquisition. Data was acquired in MS mode for quantitative analysis of the natural lipidome, and MS/MS mode to obtain data for lipid structure assignment. MS/MS data was acquired in auto-MS/MS mode (data-dependent). Spectra were acquired in centroid mode with an acquisition rate of 1 and 5 spectra/s for MS and MS/MS acquisition, respectively. Collision energy was adjusted to -35 eV and 30 eV for negative and positive modes, respectively. Mass range for precursor selection was 300-1650 m/z (negative) and 250-1680 m/z (positive). Fragmentation was triggered if the precursor reached 5000 (negative) or 2000 (positive) counts and maximum precursors per cycle was set to 5. MS/MS isolation width for precursors was selected as narrow (1.3 m/z). Active exclusion was enabled, set to exclude after 3 spectra and release after 0.1 min. To improve precursor selection, background ions were added to an exclusion list. For structure determination of probe-derived lipids, a list of preferred precursor ions was generated for each probe to improve MS/MS coverage of features originating from probe metabolism. MS/MS analysis of DMSO control samples were used to confirm assignment of natural lipids. Quantitative analysis of natural lipidome: Lipid annotations and quantifications were performed following the guidelines of the Lipidomics Standard Initiative (https://lipidomics-standards-initiative.org/). Feature extraction was carried out in Mass Hunter Profinder (v. 10.0, Agilent Technologies) using the “Batch Targeted Feature Extraction” option. Features were matched to an in-house library containing mass and retention time information of lipid species including glycerophospholipids, sphingolipids, fatty acids and glycolipids. All lipids in the database were previously assigned from MS/MS data using MS-DIAL64 followed by manual curation. H+, Na+ and NH4+ adducts were selected for positive mode and H−, C2H3O2− and CHO2− adducts were selected for negative mode data. Both mass and retention time were required for feature matching. Match tolerance was set to 5 ppm for mass and 0.15 min for retention time. The EIC extraction range was limited to +/- 0.3 min of the expected retention time. An overall score of >70 was required for feature matching, with the contribution to overall score set as follows: Mass score 100, Isotope abundance score 60, Isotope spacing score 50, Retention time score 100. Features over 20% of saturation limit were excluded from the dataset. Matched features were manually inspected and re-integrated where required and checked for correct adduct pattern for the relevant lipid class. Data were exported as .csv files containing the identity, peak area and the retention time of each lipid species. Further data analysis and data representation was performed in Excel and GraphPad Prism. The relative abundance of each lipid species within a class was calculated as a percentage of the summed peak areas of all species identified within the class. TG species were quantified from data acquired in positive mode while all other species were quantified from data acquired in negative mode. n=5 for each experimental condition. Assignment of probe-derived lipids: Feature extraction of data acquired in MS mode was carried out in Mass Hunter Profinder (v. 10.0, Agilent Technologies) using the “Batch Recursive Feature Extraction (small molecule/peptide)” option. Samples were grouped according to experimental condition. All parameters except those detailed below were used as pre-set by the program. Peak heights were set to a minimum of 3000 counts. H+, Na+ and NH4+ adducts were selected for positive mode and H−, C2H3O2− and CHO2− adducts were selected for negative mode. For compound binning and alignment, retention time tolerance was set to (+/- 0% + 0.15 min) and mass tolerance to (+/- 5 ppm + 2 mDa). A MFE score of at least 70 was required in at least 4 of 6 samples per group. For match tolerance, the mass was set to +/- 10 ppm and retention time to +/- 0.15 min. The EIC extraction range was limited to +/- 0.15 min of the expected retention time. An overall score of >75 was required for feature matching, with the contribution to overall score set as follows: Mass score 100, Isotope abundance score 60, Isotope spacing score 50, Retention time score 100. Features over 20% of saturation limit were excluded from the dataset. Post-processing filters were set to require a score (Tgt) of at least 50 in 4 out of 6 samples per experimental group. Manual filtering was performed to remove features present in the blank extraction samples. To create a list of features originating from probe metabolism, only features unique to each probe condition were selected. All features present in DMSO control samples were discarded. Features were manually inspected and re-integrated where required. The feature lists were used to create inclusion lists for MS/MS analysis and peak lists for lipid annotations as described below. </p