This work was supported by NIH-NEI grants (EY030889 and 3R01EY030889-03S1) and in part by the University of Minnesota start-up funds to G.P.L. We would also like to thank the National Eye Institute for providing us with the 11-cis-retinal standard used in this manuscript.

NOTE: All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Minnesota (protocol # 2312-41637A) and performed in compliance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. Perform all extractions in the dark, under a dim red light for illumination. Be aware of residual light emitted by instrument displays and accessory LEDs.
1. Spectrophotometric retinoid standard generation and external standard curve generation
NOTE: Prepare a dry ice container for temporary storage of retinoids before analysis with the HPLC.
<ol>
	<li>Weigh an arbitrary but appropriate quantity of retinoids and dissolve them in an appropriate solvent for quantification through spectrophotometry. 
	NOTE: The solvent of choice used in this study is ethanol, and the molar absorptivity values of retinoids dissolved in ethanol are detailed in Table 1. Anhydrous, HPLC-grade ethanol must be used to dissolve standards and samples. Ethanol purified solely through distillation forms an azeotropic mixture with water, containing approximately 4% water by volume. Water is immiscible with the hexanoic mobile phase and will result in the hydration of the silica stationary phase, leading to eventual degradation of the column.</li>
	<li>Utilizing the Beer-Lambert Law and the molar absorptivity of the pertinent retinoid, quantify the concentration of the generated standard (Table 1). 
	Absorbance = Molar Absorbtivitty (&#949;)&#160;&#215; Molar Concentration&#160;&#215; Path Length</li>
	<li>Perform serial dilutions to create concentrations that can generate a standard curve within the range of quantitation for the desired tissue. 
	NOTE: Be aware of the fundamental limitations of the Beer-Lambert Law, such as its lack of validity with high concentrations of analyte. To avoid this issue, the diluted retinoid standards should avoid generating absorbance values greater than 1. For our applications in retinol and retinaldehyde quantification in murine organs, we found that a calibration curve with a range of 1-10 ng was able to cover the typical quantities found. For retinyl palmitate quantification from murine liver, we found that a calibration curve with a range of 20-80 &#181;g was able to cover the typical quantities found.</li>
	<li>By incrementally altering the injection volume from the previously created stock solution, thereby incrementally altering the injected amount of retinoid, integrate the peaks to generate an external standard curve suitable for retinoid quantification where peak integration is directly proportional to the amount of retinoid injected.</li>
</ol>
2. Tissue harvest and sample collection
NOTE: Prepare a dry ice container for temporary storage of tissue before tissue homogenization and retinoid extraction. Recommended tissue harvest amounts are detailed in Table 2. To account for retinoid variations due to variations in blood content for each tissue, tissue extraction should be done on fully perfused mice, and blood extraction should be completed on separate mice.
<ol>
	<li>Euthanize the mice following the guidelines set forth by the Institutional Animal Care and Use Committee (IACUC) dictated protocol (CO2 asphyxiation here).</li>
	<li>Blood: Immediately following euthanasia, decapitate the mice with a pair of scissors, and drain the blood from the main trunk of the mice into a 1.5 mL tube.</li>
	<li>Eye: Using a pair of forceps, remove the eyes from the decapitated head.</li>
	<li>Brain: Using a pair of small scissors, cut into the decapitated head and remove the brain using a pair of forceps.</li>
	<li>Kidney, liver, spleen, heart, and lung: Using a pair of small scissors, make an incision into the abdomen, cut in the superior direction along the midline, and cut through the sternum and ribcage. Remove the exposed tissue using a pair of forceps.</li>
</ol>
3. Tissue homogenization
NOTE: If analysis of smaller partitions of organs is desired, such as in larger organs (e.g., liver or lung tissue), the whole organ should be homogenized to avoid differences in retinoid content in different parts of the tissue. Instead, partition the homogenate if smaller quantities of tissue are desired. A schematic for the protocol is detailed in Figure 2. This modified protocol was adapted from Kane and Napoli44.
<ol>
	<li>Place the tissue in the tissue grinder tube, along with 50% ice-cold saline (0.9%) and 50% methanol. See Table 2 for the volume used for each tissue type.</li>
	<li>Place the pestle into the grinder tube, slowly and gently perform five full rotations with the pestle to obtain a homogenate.</li>
	<li>Transfer samples into 15 mL tubes immediately after homogenization.</li>
	<li>Add 2 mL of methanol and let sit for 15 min at room temperature. 
	NOTE: If analysis of retinaldehyde oxime derivatives is desired, add 1 mL of 0.1 M hydroxylamine hydrochloride in 0.1 M HEPES (pH 6.5) (Figure 1).</li>
</ol>
4. Retinoid extraction
CAUTION: Hexane is highly flammable, highly volatile, and highly toxic. National Institute for Occupational Safety and Health (NIOSH)-approved respirators, eye protection, butyl gloves, and a fume hood must be used when handling hexane. When evaporating hexane from samples, some form of enhanced air circulation apparatus is recommended to prevent solvent fume buildup, for example, a snorkel suction apparatus.
<ol>
	<li>Add 10 mL of hexane to the homogenate and vortex mix the tube horizontally for at least 10 s. 
	NOTE: It is critical that the phases mix fully.</li>
	<li>Centrifuge the homogenate/hexane mixture for 3 min at 1,000 &#215; g to facilitate phase separation.</li>
	<li>Conduct the extraction 2x to ensure total extraction of retinoids from the homogenate. Repeat steps 4.1 and 4.2.</li>
	<li>Draw off the hexane layer using a pipette and place the hexane layer into a separate set of glass 15 mL tubes for vacuum evaporation. 
	NOTE: For evaporation, use GLASS 15 mL tubes to avoid adhesion of retinoids to the walls of the tube.</li>
	<li>Using a vacuum centrifuge, completely evaporate the hexane.</li>
</ol>
5. Resuspension and HPLC analysis
NOTE: Since the HPLC system used in this manuscript was a binary pump system, the four-component mobile phase was premixed into a singular bottle prior to operation.
CAUTION: All four organic solvents used in this method are highly flammable, highly volatile, and highly toxic. 1,4-dioxane is susceptible to explosive peroxide formation upon exposure to oxygen. Keep all vessels containing 1,4-dioxane closed when not in use. National Institute for Occupational Safety and Health (NIOSH)-approved respirators, eye protection, butyl gloves, and a fume hood must be used when handling these solvents. While running these solvents in an HPLC, some form of enhanced air circulation apparatus is recommended to prevent solvent fume buildup, for example, a snorkel suction apparatus.
<ol>
	<li>Resuspend the dried 15 mL tube with 100 &#181;L of hexane; vortex well to make sure all retinoids are dissolved.</li>
	<li>Pipette all 100 &#181;L of hexane into a single glass insert for HPLC analysis.</li>
	<li>Set up the HPLC run (adapted from Landers and Olson45): mobile phase: 85.4% hexane (v/v), 11.2% ethyl acetate (v/v), 2% dioxane (v/v), 1.4% 1-octanol (v/v); column: two 4.6 mm ID x 250 nm, 5 &#181;m columns, connected in series; a multicolumn Thermostat Temperature: 25 &#176;C; injection volume: 100 &#181;L; flow rate: 1 mL/min; run time: 40 min. Use UV spectrum absorbance detection; keep the option checked in to acquire UV spectrum from 200 nm to 400 nm.</li>
</ol>
6. Peak Identification and Integration
<ol>
	<li>Identify peaks using retention time and UV spectra of each retinoid of interest as observed from analysis of retinoid standards (Figure 3, Table 3, and Table 4).</li>
	<li>Using the chromatographic data system of the chosen HPLC system, integrate the identified peaks. The integration, or area under the curve is directly proportional to the amount of analyte. Reference the external standard curve generated in step 1 to quantify the analyte.
	<ol>
		<li>For analysis of chromatograms generated from biological tissue, use manual integration over automatic integration offered by typical chromatographic data systems, since variabilities in parameters such as retention time are often observed in such samples.</li>
		<li>Ensure that chromatograms do not exhibit irregularities that might indicate issues during the run, such as noisy baselines or non-Gaussian peaks. These issues indicate contaminants in the HPLC or wear on columns and should be rectified for valid analysis.</li>
	</ol>
	</li>
</ol>

Vitamin A Metabolite Analysis in Murine Tissue for Rhodopsin Function Studies

The authors declare no conflict of interest.

In this method, normal-phase HPLC is used to detect and quantify relevant retinoids, including retinyl esters, retinaldehydes, and retinols. Given the importance of 11-cis-retinal as the critical chromophore in the activation of the rhodopsin GPCR, a method that can detect the metabolites that is related to the production of 11-cis-retinal is critical to the study of overall visual function. The main advantage of this method is that all relevant isomers of both retinaldehydes and retinols can be simulta...

G protein-coupled receptors (GPCRs) are one of the most studied and characterized superfamily of proteins known. In its most well-known function, GPCRs serve as a cell surface receptor in signal transduction, initializing intracellular responses upon binding with a specific ligand. GPCRs are characterized by seven transmembrane (TM) helical domains and six total loop domains. Of the six loops, three loops are oriented extracellularly to facilitate ligand binding, while the other three intracellular loops are coupled to a heterotrimeric G protein consisting of the G&#945;, G&#946;, and G&#947; subunits1,2.
GPCRs are classified into several classes, including Class A Rhodopsin-Like, Class B Secretin Receptor family, Class C Glutamate, Class D Fungal Mating Pheromone Receptors, Class E Cyclic AMP receptors, and Class F Frizzled/Smoothened3,4. As its name suggests, the GPCR rhodopsin-like Class A subclass includes rhodopsin, the critical GPCR responsible for phototransduction and visual function. Rhodopsin contains all the pertinent key characteristics and structural elements that are found in the canonical model of GPCRs, including the previously mentioned seven TM helical domains, the six extracellular and intracellular loops, and association with a heterotrimeric G protein, also known as transducin (Gt) in photoreceptors1,5,6,7. Within the binding pocket of rhodopsin, 11-cis-retinal, the light-sensitive chromophore ligand, binds to rhodopsin on lysine 296 through a covalent Schiff base linkage, thus forming 11-cis-retinylidene1,8. Upon absorption of a photon, 11-cis-retinylidene photoisomerizes into all-trans-retinylidene, inducing a conformational change within rhodopsin. Therefore, the 11-cis-retinal ligand is critical to the function of the rhodopsin GPCR, and a robust and efficient supply of 11-cis-retinal must be continuously maintained to overcome the high turnover rate within photoreceptors.
Retinaldehydes such as 11-cis-retinal belong to a group of molecules collectively called retinoids, and biologically relevant retinoids are more widely referred to as vitamin A. Retinoids are characterized by a cyclic end group connected to a conjugated polyene chain, with a polar end group at the other end. Retinaldehydes and associated vitamers of vitamin A are no exception to this characterization, which contain the &#946;-ionone ring as the cyclic end group, a diterpene polyene chain, and a differing polar end group depending on the vitamer, that is, aldehyde group for retinaldehydes, hydroxyl group for retinols, carboxyl group for retinoic acids, ester bond for retinyl esters, etc (Figure 1)9,10.
Mammals cannot synthesize vitamin A de novo, but plants can; therefore, all retinoids within mammalian systems must originate from the diet of plant-based producers to the consumers in the food chain. In the canonical model of vitamin A metabolism, &#946;-carotene, the archetypal plant provitamin A, is absorbed into the intestinal enterocyte through the scavenger receptor class B, member 1 (SCARB1), cleaved into two molecules of all-trans-retinal by &#946;-carotene oxygenase 1 (BCO1/BCMO1), which binds to retinaldehyde binding protein 2 (RBP2) and is reduced to all-trans-retinol by retinol dehydrogenases (RDH), converted into retinyl esters by lecithin retinol acyltransferase (LRAT), and then sent to the bloodstream in chylomicrons11,12,13,14. Retinyl esters, such as retinyl palmitate, on the other hand, serve as the predominant provitamin A from animal sources. Retinyl palmitate from the intestinal lumen is hydrolyzed into all-trans-retinol by carboxylesterase 1 (CES1) and diffuses into the intestinal enterocyte15. The liver is the primary storage and homeostatic organ for vitamin A homeostasis, which absorbs the retinyl esters within these chylomicrons, which are hydrolyzed into all-trans-retinol bound to cellular retinol-binding protein 1 (CRBP1) by retinyl ester hydrolases, enters hepatic stellate cells and is converted back into retinyl esters by LRAT for storage13,16,17. To maintain a homeostatic level of vitamin A in the organism, the liver releases vitamin A in the form of all-trans-retinol bound to a serum transport complex, consisting of retinol-binding protein 4 (RBP4) and transthyretin (TTR)15,18,19. This complex will be referred to as holo-RBP4 in this manuscript.
To use this systemic vitamin A supply in the blood, systemic tissues, including ocular tissue where a robust source of vitamin A is maintained, must have a method to absorb holo-RBP4 into tissue. Within the photoreceptor-rich retina in ocular tissue, the membrane receptor stimulated by retinoic acid 6 (STRA6) is the transporter implicated in this function. In mechanistic studies, STRA6 has been shown to be capable of facilitating the intake of extracellular all-trans-retinol from holo-RBP4 into the RPE20. This imported all-trans-retinol will then enter the visual cycle, which is the process by which all-trans-retinol is converted into 11-cis-retinal within the RPE and the photoreceptor outer segment, thereby facilitating visual function when bound to rhodopsin9,21.
Once all-trans-retinol from circulatory holo-RBP4 crosses the blood-retina barrier into the RPE within ocular tissue through STRA6, all-trans-retinol in the RPE is first esterified into retinyl esters by LRAT, then hydrolyzed into 11-cis-retinol by retinal pigment epithelium-specific 65 kDa protein (RPE65). 11-cis-retinol is then converted into 11-cis-retinal by the retinol dehydrogenase 5. This 11-cis-retinal is then carried into the photoreceptor&#39;s outer segment (OS) by the interphotoreceptor retinoid-binding protein (IRBP)9,21. Within the endoplasmic reticulum that surrounds the photoreceptor nucleus within the outer nuclear layer (ONL), the opsin GPCRs are synthesized and transported across the connecting cilium (CC). The motor proteins that are involved in this transport across the CC are contentious, but current hypotheses implicate kinesin and dynein-based intraflagellar transport (IFT) or myosin-based transport as being likely facilitators of this process14,22,23,24,25,26. Once these two components meet within the membranous disks within the OS, 11-cis-retinal and opsin form 11-cis-retinylidene through a Schiff base covalent linkage at lysine 196 on rhodopsin, ready for phototransduction8.
While the expression of STRA6 within the RPE of the retina helps facilitate the intake of all-trans-retinol from holo-RBP4, STRA6 was not found to be expressed in the liver, despite its role as the main homeostatic organ for vitamin A and exhibiting capabilities in intaking all-trans-retinol from holo-RBP415,19,27,28,29,30,31. Eventually, an analogous receptor called retinol-binding protein 4 receptor 2 (RBPR2) was discovered, exhibiting the capability to intake all-trans-retinol from holo-RBP4, much like STRA6, but is expressed in hepatic tissue32.
Therefore, a complete understanding of the role of rhodopsin in visual function necessitates an understanding of the biological processes that culminate in the regeneration of the visual pigment. This is, in turn, intimately related to the previously described processes, including the metabolism of provitamin A precursors, storage within the liver, release of holo-RBP4 by the liver, and eventual uptake of holo-RBP4 through STRA6 and RBPR2 membrane receptors. As mentioned above, animal models such as mice remain one of the premier models in the study of such processes. Hence, we would like to present an extraction method for retinoids in murine tissue, as well as a normal-phase high-performance liquid chromatography (HPLC) method that can detect and quantify these retinoids. Using these methods, the important retinoids described above, such as the 11-cis-retinal rhodopsin ligand or the main transport retinoid all-trans-retinol, can be analyzed in ocular, hepatic, and systemic organs. By assessing retinoid supply in murine tissue, our understanding of the disease states and pathologies related to the logistical supply of retinoids can be further advanced.
Besides functioning as a chromophore in visual function through association with opsin GPCRs, retinoids also play a major role in mammalian cell signaling through retinoic acid signaling, facilitated by two families of nuclear receptors, retinoic acid receptors (RARs) and retinoid X receptors (RXRs), that bind directly to DNA and regulated gene transcription33. These two families or receptors both utilize retinoids in the form of retinoic acids as the ligand. RARs have been shown to have affinity for both all-trans-retinoic acid and 9-cis-retinoic acid, whereas RXRs express affinity for only 9-cis-retinoic acid34,35. Retinoic acids in uncontrolled quantities are teratogenic, and retinoic acid signaling must be extremely tightly controlled36. Production of retinoic acids for signaling must occur locally and at very specific time points for the proper development of tissues, such as in hindbrain and limb development, but countless other examples utilize retinoic acid signaling37,38. Within cells participating in retinoic acid signaling, retinoic acids are synthesized by two groups of enzymes, alcohol/retinol dehydrogenases (ADHs/RDHs) that facilitate the oxidation of retinols taken in by STRA6 or RBPR2 to retinaldehydes, and retinaldehyde dehydrogenases (RALDHs) that facilitate oxidation of retinaldehydes to retinoic acids39. While not participating in GPCR signaling per se, retinoic acids nonetheless present as a crucial retinoid that also functions as a ligand for signaling receptors.
While not described in detail here, we would like to acknowledge the previously established methods for retinoid detection using HPLC across various contexts, such as in food research and the study of microbial rhodopsin. These methods employ different goals and approaches to retinoid detection, including the use of reverse-phase techniques that require less volatile and hazardous mobile phases40,41,42, the detection of retinoic acids and their associated isomers40,41, and purification and extraction from different biological sources43. Our method focuses specifically on the detection of retinyl palmitate, retinaldehyde isomers, and retinol isomers from mammalian tissue. Different protocols should be considered if the intended use case differs from this specific application.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>1-Octanol, suitable for HPLC, &#8805;99.5%</td>
			<td>Sigma-Aldrich, Millipore Sigma</td>
			<td>203-917-6</td>
			<td></td>
		</tr>
		<tr>
			<td>1,4-Dioxane, suitable for HPLC, &#8805;99.5%</td>
			<td>Sigma-Aldrich, Millipore Sigma</td>
			<td>204-661-8</td>
			<td></td>
		</tr>
		<tr>
			<td>11-cis-retinal</td>
			<td>National Eye Institute</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>11-cis-Retinol</td>
			<td>Toronto Research Chemicals</td>
			<td>TRC-R252105</td>
			<td></td>
		</tr>
		<tr>
			<td>13-cis-retinal</td>
			<td>Toronto Research Chemicals</td>
			<td>TRC-R239900</td>
			<td></td>
		</tr>
		<tr>
			<td>13-cis-retinol</td>
			<td>Toronto Research Chemicals</td>
			<td>TRC-R252110</td>
			<td></td>
		</tr>
		<tr>
			<td>All-trans-Retinal</td>
			<td>Toronto Research Chemicals</td>
			<td>TRC-R240000</td>
			<td></td>
		</tr>
		<tr>
			<td>All-trans-Retinol</td>
			<td>Toronto Research Chemicals</td>
			<td>TRC-R252002</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethyl Acetate, suitable for HPLC, &#8805;99.7%</td>
			<td>Sigma-Aldrich, Millipore Sigma</td>
			<td>205-500-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Hexane, HPLC Grade</td>
			<td>Fisher Scientific, Spectrum Chemical</td>
			<td>18-610-808</td>
			<td></td>
		</tr>
		<tr>
			<td>Methanol (HPLC)</td>
			<td>Fisher Scienctific</td>
			<td>A452SK-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Retinyl Palmitate</td>
			<td>Toronto Research Chemicals</td>
			<td>TRC-R275450</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Chloride (Crystalline/Certified ACS)</td>
			<td>Fisher Scientific</td>
			<td>S271-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Instruments</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>1260 Infinity II Analytical Fraction Collector</td>
			<td>Agilent</td>
			<td>G1364F</td>
			<td></td>
		</tr>
		<tr>
			<td>1260 Infinity II Binary Pump</td>
			<td>Agilent</td>
			<td>G7112B</td>
			<td></td>
		</tr>
		<tr>
			<td>1260 Infinity II Diode Array Detector</td>
			<td>Agilent</td>
			<td>G7115A</td>
			<td></td>
		</tr>
		<tr>
			<td>1260 Infinity II Multicolumn Thermostat</td>
			<td>Agilent</td>
			<td>G7116A</td>
			<td></td>
		</tr>
		<tr>
			<td>1260 Infinity II Vialsampler</td>
			<td>Agilent</td>
			<td>G7129A</td>
			<td></td>
		</tr>
		<tr>
			<td>ST40R Refrigerated Centrifuge</td>
			<td>Thermo Scientific</td>
			<td>TSST40R</td>
			<td></td>
		</tr>
		<tr>
			<td>Vacufuge Plus Centrifuge Concentrator</td>
			<td>Eppendorf</td>
			<td>22820168</td>
			<td></td>
		</tr>
		<tr>
			<td>Consumables</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>2 mL Amber Screw Top Vials</td>
			<td>Agilent</td>
			<td>5188-6535</td>
			<td></td>
		</tr>
		<tr>
			<td>Crimp Cap with PTFE/red rubber septa, 11 mm</td>
			<td>Agilent</td>
			<td>5183-4498</td>
			<td></td>
		</tr>
		<tr>
			<td>Disposable Glass Conical Centrifuge Tubes</td>
			<td>Millipore Sigma</td>
			<td>CLS9950215</td>
			<td></td>
		</tr>
		<tr>
			<td>Screw cap tube, 15 mL</td>
			<td>Sarstedt</td>
			<td>62.554.502</td>
			<td></td>
		</tr>
		<tr>
			<td>Vial insert, 150 &#181;L, glass with polymer feet</td>
			<td>Agilent</td>
			<td>5183-2088</td>
			<td></td>
		</tr>
	</tbody>
</table>

quantitative analysis of dietary vitamin a metabolites in murine ocular and non-ocular tissues using high-performance liquid chromatography

G protein-coupled receptors (GPCRs) are a superfamily of transmembrane proteins that initiate signaling cascades through activation of its G protein upon association with its ligand. In all mammalian vision, rhodopsin is the GPCR responsible for the initiation of the phototransduction cascade. Within photoreceptors, rhodopsin is bound to its chromophore 11-cis-retinal and is activated through the light-sensitive isomerization of 11-cis-retinal to all-trans-retinal, which activates the transducin G protein, resulting in the phototransduction cascade. 
While phototransduction is well understood, the processes that are involved in the supply of dietary vitamin A precursors for 11-cis-retinal generation in the eye, as well as diseases resulting in disruption of this supply, are not yet fully understood. Once vitamin A precursors are absorbed into the intestine, they are stored in the liver as retinyl esters and released into the bloodstream as all-trans-retinol bound to retinol-binding protein 4 (RBP4). This circulatory RBP4-retinol will be absorbed by systemic organs, such as the liver, lungs, kidney, and eye. Hence, a method for the quantification of the various metabolites of dietary vitamin A in the eye and systemic organs is critical to the study of proper rhodopsin GPCR function. 
In this method, we present a comprehensive extraction and analytical method for vitamin A analysis in murine tissue. Through normal-phase, high-performance liquid chromatography analysis, all relevant isomers of retinaldehydes, retinols, and retinyl esters can be detected simultaneously through a single run, which allows for the efficient use of experimental samples and increases internal reliability across different vitamin A metabolites within the same sample. With this comprehensive method, investigators will be able to better assess systemic vitamin A supply in rhodopsin GPCR function.

Here, we utilized the method described above to detect and quantify retinoids in murine ocular and systemic tissue and generated representative chromatograms. We will additionally give a summary of the typical retinoids that can be detected in these tissues.
At 6 months of age, mice were euthanized through CO2 asphyxiation. To maintain ocular retinoid content, mice were dark-adapted for 2 days prior to euthanization and extraction. Two eyes, 0.2 g of liver, and 75 &#956;L of blood w...

Author Spotlight: Investigating Physiological Functions of Vitamin A Transporters Using HPLC-Based Vitamin A Profiling

Here, a normal-phase, high-performance liquid chromatography method is described to detect and quantify critical retinoids involved in the facilitation of visual function in both ocular and systemic tissue, in the context of the systemic vitamin A supply to generate the essential photosensitive rhodopsin chromophore 11-cis-retinal.

Quantitative Analysis of Dietary Vitamin A Metabolites in Murine Ocular and Non-Ocular Tissues Using High-Performance Liquid Chromatography

G protein-coupled receptors (GPCRs) are a superfamily of transmembrane proteins that initiate signaling cascades through activation of its G protein upon ...

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600 Views.  University of Minnesota. Here, a normal-phase, high-performance liquid chromatography method is described to detect and quantify critical retinoids involved in the facilitation of visual function in both ocular and systemic tissue, in the context of the systemic vitamin A supply to generate the essential photosensitive rhodopsin chromophore 11-cis-retinal.

Video: Author Spotlight: Investigating Physiological Functions of Vitamin A Transporters Using HPLC-Based Vitamin A Profiling

A Tandem Liquid Chromatography&#8211;Mass Spectrometry-based Approach for Metabolite Analysis of Staphylococcus aureus

In an effort to thwart bacterial pathogens, hosts often limit the availability of nutrients at the site of infection. This limitation can alter the abundances of key metabolites to which regulatory factors respond, adjusting cellular metabolism. In recent years, a number of proteins and RNA have emerged as important regulators of virulence gene expression. For example, the CodY protein responds to levels of branched-chain amino acids and GTP and is widely conserved in low G+C Gram-positive bacteria. As a global regulator in Staphylococcus aureus, CodY controls the expression of dozens of virulence and metabolic genes. We hypothesize that S. aureus uses CodY, in part, to alter its metabolic state in an effort to adapt to nutrient-limiting conditions potentially encountered in the host environment. This manuscript describes a method for extracting and analyzing metabolites from S. aureus using liquid chromatography coupled with mass spectrometry, a protocol that was developed to test this hypothesis. The method also highlights best practices that will ensure rigor and reproducibility, such as maintaining biological steady state and constant aeration without the use of continuous chemostat cultures. Relative to the USA200 methicillin-susceptible S. aureus isolate UAMS-1 parental strain, the isogenic codY mutant exhibited significant increases in amino acids derived from aspartate (e.g., threonine and isoleucine) and decreases in their precursors (e.g., aspartate and O-acetylhomoserine). These findings correlate well with transcriptional data obtained with RNA-seq analysis: genes in these pathways were up-regulated between 10- and 800-fold in the codY null mutant. Coupling global analyses of the transcriptome and the metabolome can reveal how bacteria alter their metabolism when faced with environmental or nutritional stress, providing potential insight into the physiological changes associated with nutrient depletion experienced during infection. Such discoveries may pave the way for the development of novel anti-infectives and therapeutics.

Here we describe a protocol for the extraction of metabolites from Staphylococcus aureus and their subsequent analysis via liquid chromatography and mass spectrometry.

In an effort to thwart bacterial pathogens, hosts often limit the availability of nutrients at the site of infection. This limitation can alter the ...

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures.

A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually ...

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

Leaf Spray Mass Spectrometry: A Rapid Ambient Ionization Technique to Directly Assess Metabolites from Plant Tissues

Plants produce thousands of small molecules that are diverse in their chemical properties. Mass spectrometry (MS) is a powerful technique for analyzing plant metabolites because it provides molecular weights with high sensitivity and specificity. Leaf spray MS is an ambient ionization technique where plant tissue is used for direct chemical analysis via electrospray, eliminating chromatography from the process. This approach to sampling metabolites allows for a wide range of chemical classes to be detected simultaneously from intact plant tissues, minimizing the amount of sample preparation needed. When used with a high-resolution, accurate mass MS, leaf spray MS facilitates the rapid detection of metabolites of interest. It is also possible to collect tandem mass fragmentation data with this technique to facilitate a compound identification. The combination of accurate mass measurements and fragmentation is beneficial in confirming compound identities. The leaf spray MS technique requires only minor modifications to a nanospray ionization source and is a useful tool to further expand the capabilities of a mass spectrometer. Here, fresh leaf tissue from Sceletium tortuosum (Aizoaceae), a traditional medicinal plant from South Africa, is analyzed; numerous mesembrine alkaloids are detected with leaf spray MS.

Leaf spray mass spectrometry is a direct chemical analysis technique that minimizes the sample preparation and eliminates chromatography, allowing for the rapid detection of small molecules from plant tissues.

Plants produce thousands of small molecules that are diverse in their chemical properties. Mass spectrometry (MS) is a powerful technique for analyzing ...

Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting

Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances in both basic and clinical research. However, as with many similar experimental techniques, the outcome of Western blot analyses is easily influenced by choices made in the design and execution of the experiment. Specific housekeeping proteins have traditionally been used to normalize protein levels for quantification, however, these have a number of limitations and have therefore been increasingly criticized over the past few years. Here, we describe a detailed protocol that we have developed to allow us to undertake complex comparisons of protein expression variation across different tissues, mouse models (including disease models), and developmental timepoints. By using a fluorescent total protein stain and introducing the use of an internal loading standard, it is possible to overcome existing limitations in the number of samples that can be compared within experiments and systematically compare protein levels across a range of experimental conditions. This approach expands the use of traditional western blot techniques, thereby allowing researchers to better explore protein expression across different tissues and samples.

This method describes a robust and reproducible approach for the comparison of protein levels in different tissues and at different developmental timepoints using a standardized quantitative western blotting approach.

Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances ...

Quantification of Coenzyme A in Cells and Tissues

Emerging research has revealed that the cellular coenzyme A (CoA) supply can become limiting with a detrimental impact on growth, metabolism and survival. Measurement of cellular CoA is a challenge due to its relatively low abundance and the dynamic conversion of free CoA to CoA thioesters that, in turn, participate in numerous metabolic reactions. A method is described that navigates through potential pitfalls during sample preparation to yield an assay with a broad linear range of detection that is suitable for use in many biomedical laboratories.

This method describes sample preparation from cultured cells and animal tissues, extraction and derivatization of coenzyme A in the samples, followed by high pressure liquid chromatography for purification and quantification of the derivatized coenzyme A by absorbance or fluorescence detection.

Emerging research has revealed that the cellular coenzyme A (CoA) supply can become limiting with a detrimental impact on growth, metabolism and survival. ...

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of biological membranes, energy storage and production, cellular signaling, vesicular transport of proteins, organelle biogenesis, and regulated cell death. Because the budding yeast Saccharomyces cerevisiae is a unicellular eukaryote amenable to thorough molecular analyses, its use as a model organism helped uncover mechanisms linking lipid metabolism and intracellular transport to complex biological processes within eukaryotic cells. The availability of a versatile analytical method for the robust, sensitive, and accurate quantitative assessment of major classes of lipids within a yeast cell is crucial for getting deep insights into these mechanisms. Here we present a protocol to use liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for the quantitative analysis of major cellular lipids of S. cerevisiae. The LC-MS/MS method described is versatile and robust. It enables the identification and quantification of numerous species (including different isobaric or isomeric forms) within each of the 10 lipid classes. This method is sensitive and allows identification and quantitation of some lipid species at concentrations as low as 0.2 pmol/&#181;L. The method has been successfully applied to assessing lipidomes of whole yeast cells and their purified organelles. The use of alternative mobile phase additives for electrospray ionization mass spectrometry in this method can increase the efficiency of ionization for some lipid species and can be therefore used to improve their identification and quantitation.

Quantitative Analysis of the Cellular Lipidome of Saccharomyces Cerevisiae Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

We present a protocol using liquid chromatography coupled with tandem mass spectrometry to identify and quantify major cellular lipids in Saccharomyces cerevisiae. The described method for a quantitative assessment of major lipid classes within a yeast cell is versatile, robust, and sensitive.

Lipids are structurally diverse amphipathic molecules that are insoluble in water. Lipids are essential contributors to the organization and function of ...

Ubiquitin Chain Analysis by Parallel Reaction Monitoring

Assessment of the global profile of ubiquitin chain topologies within a proteome is of interest to answer a wide range of biological questions. The protocol outlined here takes advantage of the di-glycine (-GG) modification left after the tryptic digestion of ubiquitin incorporated in a chain. By quantifying these topology-characteristic peptides the relative abundance of each ubiquitin chain topology can be determined. The steps required to quantify these peptides by a parallel reaction monitoring experiment are reported taking into consideration the stabilization of ubiquitin chains. Preparation of heavy controls, cell lysis, and digestion are described along with the appropriate mass spectrometer setup and data analysis workflow. An example data set with perturbations in ubiquitin topology is presented, accompanied by examples of how optimization of the protocol can affect results. By following the steps outlined, a user will be able to perform a global assessment of the ubiquitin topology landscape within their biological context.

This method describes the assessment of global changes in ubiquitin chain topology. The assessment is performed by the application of a mass spectrometry-based targeted proteomics approach.

Assessment of the global profile of ubiquitin chain topologies within a proteome is of interest to answer a wide range of biological questions. The ...

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Understanding the interactions between genes, the environment and management in agricultural practice could allow more accurate prediction and management of product yield and quality. Metabolomics data provides a read-out of these interactions at a given moment in time and is informative of an organism&#39;s biochemical status. Further, individual metabolites or panels of metabolites can be used as precise biomarkers for yield and quality prediction and management. The plant metabolome is predicted to contain thousands of small molecules with varied physicochemical properties that provide an opportunity for a biochemical insight into physiological traits and biomarker discovery. To exploit this, a key aim for metabolomics researchers is to capture as much of the physicochemical diversity as possible within a single analysis. Here we present a liquid chromatography-mass spectrometry-based untargeted metabolomics method for the analysis of field-grown wheat grain. The method uses the liquid chromatograph quaternary solvent manager to introduce a third mobile phase and combines a traditional reversed-phase gradient with a lipid-amenable gradient. Grain preparation, metabolite extraction, instrumental analysis and data processing workflows are described in detail. Good mass accuracy and signal reproducibility were observed, and the method yielded approximately 500 biologically relevant features per ionization mode. Further, significantly different metabolite and lipid feature signals between wheat varieties were determined.

A method for the untargeted analysis of wheat grain metabolites and lipids is presented. The protocol includes an acetonitrile metabolite extraction method and reversed phase liquid chromatography-mass spectrometry methodology, with acquisition in positive and negative electrospray ionization modes.

Understanding the interactions between genes, the environment and management in agricultural practice could allow more accurate prediction and management ...

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics

Peptidoglycan is an important component of bacterial cell walls and a common cellular target for antimicrobials. Although aspects of peptidoglycan structure are fairly conserved across all bacteria, there is also considerable variation between Gram-positives/negatives and between species. In addition, there are numerous known variations, modifications, or adaptations to the peptidoglycan that can occur within a bacterial species in response to growth phase and/or environmental stimuli. These variations produce a highly dynamic structure that is known to participate in many cellular functions, including growth/division, antibiotic resistance, and host defense avoidance. To understand the variation within peptidoglycan, the overall structure must be broken down into its constitutive parts (known as muropeptides) and assessed for overall cellular composition. Peptidoglycomics uses advanced mass spectrometry combined with high-powered bioinformatic data analysis to examine peptidoglycan composition in fine detail. The following protocol describes the purification of peptidoglycan from bacterial cultures, the acquisition of muropeptide intensity data through a liquid chromatograph&#8212;mass spectrometer, and the differential analysis of peptidoglycan composition using bioinformatics.

This protocol covers a detailed analysis of peptidoglycan composition using liquid chromatography mass spectrometry coupled with advanced feature extraction and bioinformatic analysis software.