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Ionization Properties of Phospholipids Determined by Zeta Potential Measurements
通过ζ电位测量测定磷脂双分子层的膜电位   

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Abstract

Biological membranes are vital for diverse cellular functions such as maintaining cell and organelle structure, selective permeability, active transport, and signaling. The surface charge of the membrane bilayer plays a critical role in these myriad processes. For most biomembranes, the surface charge of anionic phospholipids contributes to the negative surface charge density within the interfacial region of the bilayer. To quantify surface charge, it is essential to understand the proton dissociation behavior of the titratable headgroups within such lipids. We describe a protocol that uses model membranes for electrokinetic zeta potential measurements coupled with data analysis using Gouy-Chapman-Stern formalism to determine the pKa value of the component lipids. A detailed example is provided for homogeneous bilayers composed of the monoanionic lipid phosphatidylglycerol. This approach can be adapted for the measurement of bilayers with a heterogeneous lipid combination, as well as for lipids with multiple titratable sites in the headgroup (e.g., cardiolipin).

Background

Phospholipids are central building blocks of biological membranes (Figure 1). As amphipathic molecules, each contains a hydrophobic region consisting of acyl chains and a hydrophilic region consisting of a polar headgroup (Figure 1A). Some phospholipid headgroups are zwitterionic, containing both positively and negatively charged functional groups at physiological pH (Figure 1B), whereas others are acidic, bearing an overall formal negative charge (Figure 1C). Lipids within biomembranes exist stably as a lamellar assembly, forming bilayers in which the acyl chains of two leaflets interact to form a hydrophobic core and two interfacial regions consisting of the polar headgroups (Figure 1D). Most naturally occurring biomembranes contain a certain percentage of acidic phospholipids; therefore, their lipid composition imparts a net negative charge to the interfacial region (Gennis, 1989; Marsh, 2013). Bilayer surface charge is a key factor in many membrane-level processes including interactions with proteins and solution ions as well as membrane morphology, fusion and phase changes. Because the formal charge of lipid headgroups is a primary determinant of this surface charge, it is critical to have accurate measurements of the proton dissociation behavior (quantified as pKa values) of the constituent functional groups.


Figure 1. Phospholipid structure and the lamellar lipid bilayer. A. General structure of a glycerophospholipid. A common phospholipid is based on a scaffold of a central glycerol molecule (thickened line), with the constituent carbons designated by stereospecific numbering (sn-1, sn-2 and sn-3, as indicated). The hydrophobic domain consists of hydrocarbon tails esterified at the sn-1 and sn-2 positions. The polar headgroup contains a negatively charged phosphate group attached to the sn-3 position, which may be modified by an R group to render specific headgroup identity. B. Structure of phosphatidylcholine (R = choline) with a saturated 16 carbon aliphatic tail at the sn-1 position and an unsaturated 18 carbon tail at the sn-2 position. The zwitterionic nature of the headgroup is shown as the negative phosphate and the positive tertiary amine. C. Structure of phosphatidylglycerol (R = glycerol) with acyl chains identical to those shown above. The anionic nature of the headgroup is shown by the uncompensated negative charge on the phosphate. D. The lamellar lipid bilayer, showing the hydrocarbon core composed of the aliphatic lipid tails and the solvent-exposed interfacial regions.


The electric field that is established by charged headgroups results in a complex profile of electric potential in the aqueous region (Figure 2) (McLaughlin, 1977). Models for the electric potential profile are based on the physical chemistry of phase boundary interfaces, here representing a solid surface in contact with an aqueous phase (Oshima, 2010). Membrane surface electrostatics can be quantitatively modeled using Gouy-Chapman-Stern theory, which relates the density of charges on the membrane surface (σ, C m-2) and the electric potential (ψ, V), as described in the data analysis section. In a simplified model, the surface charge is comprised of charges that are fixed to the solid body as well as solution ions that are adsorbed tightly to the surface by chemical interactions. For lipid bilayers, the fixed charges can be considered to be the titratable acidic (phosphate) and basic (primary anime) functional groups of lipid headgroups, whereas the adsorbed ions are solution electrolytes that specifically bind headgroup sites with nonzero association constants (Tocanne and Teissie, 1990). This layer of charges is collectively defined as the Stern layer, but may be subdivided into other layers with increasing complexity. Adjacent to this region is a layer in which solvated solution ions are more diffusely distributed. In this region, termed the Gouy-Chapman layer, the distribution of counterions (those with charges opposite to the dominant surface charge) and coions (those with charges identical to the surface charge) arises from electrostatic attraction (counterions) or repulsion (coions) balanced with the entropic tendency of ions to diffuse away from the surface. Because counterions are highly enriched in this region due to electrostatic attraction to the surface, they act to screen the surface charge, thereby attenuating the electric field. Taken as a whole, this distribution of charges sets up the ‘diffuse electrical double layer’ of biomembranes.

Here we describe a methodology to determine the pKa of lipid headgroups using measurements of the electrostatic potentials of model membranes. This approach is based on the electrophoresis of lipid bilayer vesicles (liposomes), which we used in a recent publication to measure the proton dissociation behavior of the dimeric phospholipid cardiolipin (Sathappa and Alder, 2016). In the presence of an applied electric field, charged colloidal particles will migrate relative to the suspending liquid toward the electrode of opposing charge (Delgado et al., 2007). As the charged particle surface flows tangentially along the bulk fluid, there exists a thin layer of solution, termed the hydrodynamically stagnant layer, which moves with the particle. This layer extends into the diffuse region to a so-called slipping plane or shear plane. The electric potential at this layer that separates the hydrodynamically immobile layer from the bulk is termed the zeta potential (ζ) (Figure 2). The speed of migration depends on the electrophoretic mobility (μ, m2.V-1.s-1) of the particle, defined by the Helmholtz-Smoluchowski equation as the particle velocity per unit electric field:

Where, εr is the relative permittivity, ε0 is the permittivity of free space, and η is the viscosity of the solution (Aveyard and Haydon, 1973). As Eq. 1 shows, the mobility of charged particles in an external electric field is directly related to the magnitude of ζ. Hence, in an electrolyte solution of a given pH, liposomes with greater surface charge will have a higher ζ and therefore move with higher velocity in a given electric field.
   Whereas optical electrophoresis measurements provide an unambiguous measure of electrokinetic mobility and zeta potential, translating these measurements into information on proton dissociation characteristics of titratable groups requires more detailed evaluation. This protocol explains the preparation of suitable model membranes, measurements of zeta potential using optical electrophoresis, and data analysis using Gouy-Chapman-Stern formalism to obtain lipid pKa values.


Figure 2. The electrostatic profile of the diffuse double layer. A liposome is a model membrane that consists of a vesicular lipid bilayer (left), whose surface and interfacial region in the aqueous phase can be modeled as an electrical double layer (right). In this model, a bilayer surface containing anionic phospholipids is modeled as a planar surface (gray) with uniformly distributed negative charges, from which an electric field originates (red shading). The distribution of solution electrolytes is shown for counterions (in this case, cations shown in blue) and coions (in this case, anions shown in red). Within the Stern layer, counterions are firmly bound to the bilayer surface. Within the Gouy-Chapman layer, solution ions are more disperse, reflecting a balance between Coulombic attraction (cations) or repulsion (anions) and thermal motion. The titratable charged lipid headgroups and adsorbed counterions together define the surface charge density (σ). The electric potential (ψ) assumes a maximum magnitude at the interface surface (ψ0) and attenuates toward the bulk solution (ψbulk) in a manner that is dependent on the ionic characteristics of the bathing solution. The electric potential at the slip plane, termed the zeta potential (ζ) is the measured parameter in this protocol.

Materials and Reagents

  1. Kimble Corex tubes (30 ml) (Thermo Fisher Scientific, Fisher Scientific, catalog number: 0950037 )
  2. Hamilton gas-tight syringe (Avanti Lipids Polar, catalog number: 610017 )
  3. Polycarbonate membrane filters, 0.4 µm (Avanti Lipids Polar, catalog number: 610007 )
  4. Wide-range pH test paper (Thermo Fisher Scientific, Fisher Scientific, catalog number: 14-850-1 )
  5. Glass tube
  6. 4 ml semi-micro cuvettes (SARSTEDT, catalog number: 67.745 )
  7. Hellma Suprasil quartz cuvette (Sigma-Aldrich, catalog number: Z802433 )
  8. Glass vials
  9. N2
  10. 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1’-rac-glycerol) (POPG) (Avanti Lipids Polar, catalog number: 840457C ) (Note 1)
  11. Chloroform (Thermo Fisher Scientific, Fisher Scientific, catalog number: C298 )
  12. Sodium chloride (NaCl) (Sigma-Aldrich, catalog number: S9888 )
  13. Teflon-lined closures (Avanti Lipids Polar, catalog number: 600460 )
  14. 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) (Avanti Lipids Polar, catalog number: 850457C )
  15. 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphethanolamine (POPE) (Avanti Lipids Polar, catalog number: 850757C )
  16. Ethanol
  17. Potassium chloride (KCl)
  18. Citric acid monohydrate (C6H8O7·H2O) (Sigma-Aldrich, catalog number: C1909 )
  19. Sodium phosphate dibasic (Na2HPO4) (Sigma-Aldrich, catalog number: S7907 )
  20. 2-amino-2-methyl-1,3-propanediol (AMPD) (Sigma-Aldrich, catalog number: A9754 )
  21. Iron (III) chloride hexahydrate (FeCl3·6H2O) (Sigma-Aldrich, catalog number: 236489 )
  22. Millipore filter sterilized water (ddH2O) (EMD Millipore, catalog number: Milli-Q Advantage A10 water purification system )
  23. Ammonium thiocyanate (NH4SCN) (Sigma-Aldrich, catalog number: 221988 )
  24. Citrate-phosphate buffers (see Recipes)
  25. AMPD buffer (see Recipes)
  26. Ammonium ferrothiocyanate solution (see Recipes)

Equipment

  1. Nitrogen tank
  2. Fume hood
  3. Vacuum desiccator (Eppendorf, model: Vacufuge Plus )
  4. Nanoparticle size analyzer (Malvern Instruments, model: Zetasizer Nano S90 ) (Zetasizer Nano Series Technical Note, Malvern Instruments: https://caliscc.org/images/presentations/Morante_Zeta_Potential.pdf)
  5. NanosphereTM polymer microsphere size standards, size 60 ± 2.7 nm (Thermo Fisher Scientific, Thermo ScientificTM, catalog number: 3060A )
  6. Pasteur pipette
  7. Vortexer (Bio-Rad Laboratories, model: BR 2000 )
  8. Filter supports (Avanti Lipids Polar, catalog number: 610014 )
  9. AccumetTM pH meter (Thermo Fisher Scientific, Fisher ScientificTM, catalog number: AB15 Plus )
  10. Avanti Mini Extruder Kit (Avanti Lipids Polar, catalog number: 610023 )
  11. Spectrophotometer (Thermo Fisher Scientific, Fisher Scientific, model: Ultrospec 2100 Pro )
  12. Zeta potential analyzer (Brookhaven Instruments, model: ZetaPlus Zeta Potential Analyzer )
  13. Zeta potential reference material (Brookhaven Instruments, catalog number: BI-ZR5 )

Software

  1. Zetasizer software
  2. Microsoft Excel

Procedure

  1. Liposome preparation
    1. Aliquot the desired lipid volumes into Kimble Corex tubes using a gas-tight syringe. For the illustrated protocol, add 200 μl of 25 mg/ml POPG chloroform stock into the tube. (Notes 2 and 3)
    2. The lipids are dried under a gentle N2 steam in a fume hood for approximately 30 min (Note 4).
    3. To remove residual chloroform, the lipids are further dried overnight under a vacuum in the desiccator.
    4. The dried lipids are hydrated and resuspended by vigorous vortexing in 1 ml of respective phosphate citrate buffer (pH 2.0 to 8.0) or AMPD buffer (pH 8.0 to 10.0) (see Recipes) and incubated for an additional 30 min (Note 5).
    5. The hydrated lipids are extruded each set 19 times through a 0.4 μm membrane maintained at proper temperature (Note 6).

  2. Quality control and liposome sizing
    1. The resulting liposomes are analyzed by dynamic light scattering in a Zetasizer Nano S90 to confirm the homogeneity and the accurate size of the samples prepared as shown in Figure 3A.
      1. Size measurements are performed using 90° scattering optics with the following measurement parameters. Temperature: 25 ± 1 °C; Dispersant: phosphate buffered saline; Refractive index: 1.332; Viscosity: 0.9128 cP; Equilibration time: 1 min; Measurement: automatic; Analysis model: general purpose (normal resolution). Instrument calibration is conducted using NanosphereTM size standards.
      2. 60 μl of each sample is placed in a quartz cuvette and measured with three successive runs at 1 min intervals.
      3. The scattering data are analyzed by Zetasizer software as shown in Figures 3B and 3C.
    2. The pH of the liposomes after extrusion is verified by using a pH paper as shown in Figure 3D.
    3. Measurement of the lipid concentration of vesicle samples is conducted using established colorimetric assay that measures the phospholipid-ammonium ferrothiocyanate complex (Marom and Abdussalam, 2013).
      1. Calibration curves are produced as follows:
        1. Add 40 μl POPG (25 mg/ml) to 9.96 ml of chloroform in a glass tube to prepare a stock solution of 0.1 mg/ml POPG.
        2. Make 11 samples of POPG in a glass tube as shown in Table 1.
        3. Vortex the samples for 1 min each after the addition of ammonium ferrothiocyanate and chloroform.
        4. Two separate phases will become evident. Using a Pasteur pipette, carefully remove the upper phase and discard it.
        5. Transfer the lower phase to a suitable cuvette and measure the absorbance at 488 nm using a spectrophotometer. The sample without POPG is used as blank.
        6. The graph of absorbance at 488 nm versus lipid concentration (mg/ml) serves as the calibration curve (Figure 3E).

          Table 1. The reaction mixture for plotting the calibration curve



          Figure 3. Liposome characterization. A. Representative intensity distribution trace for liposomes prepared from 100 mol% POPG by dynamic light scattering indicating a homogenous population. B. Mean diameters (Z-average values) of 100 mol% POPG liposomes. C. Polydispersity indices of 100 mol% POPG liposomes. D. The respective pH of liposomes after hydration and extrusion in various pH buffers verified using a pH paper. E. Representative phospholipid calibration curve.

      2. The lipid concentration of liposome samples is measured as follows:
        1. Add 10 μl of prepared liposomes into a glass tube. Add 2 ml ammonium ferrothiocyanate and vortex for 1 min.
        2. Add 1.99 ml of chloroform and vortex for 1 min.
        3. The lower phase is taken and the absorbance is measured at 488 nm.
        4. The respective lipid concentration is calculated by using the calibration curve, making sure to multiply the measured concentration by 200 to get the final concentration (1:200 dilution).
        5. Liposomes are diluted to a concentration of 1 mg/ml in the respective buffer.

  3. Zeta potential measurements are conducted using a ZetaPlus Zeta Potential Analyzer (see Reference 10)
    1. Add 1.6 ml of 1 mg/ml liposomes sample in 4 ml-semi micro cuvettes.
    2. Open the ZetaPlus software and change the appropriate conditions in the ‘Parameters’ Dialogue box. The measurement parameters are as follows. Electric field: 14.86 V/cm; Current 21.37 mA; Conductance: 3936 μS; Viscosity: 0.890 cP; Refractive index: 1.330; Dielectric constant: 78.54; Temperature: 25 °C. The electrodes used are ZetaPlus, SR-516 type electrode (Note 7).
    3. The measurements are made for three runs with ten cycles (Note 8).

Data analysis

The protocol presented above allows for the acquisition of zeta potential values for POPG-containing liposomes under a range of pH values. The goal of the data analysis is to evaluate the pKa value of the component lipids based on these data. In this section, we first give a brief overview of the theoretical and mathematical considerations involved in this analysis. We then present a stepwise process for thoroughly evaluating the data.

  1. Theory and modeling
    1. The electrostatic profile of the diffuse double layer perpendicular to the plane of the bilayer (Figure 2) is modeled using Gouy-Chapman-Stern formalism. In this concise theoretical overview, we present the relevant equations in this analysis; for further information on theory and mathematical derivation, the reader is referred to several background resources (McLaughlin, 1977; Oshima, 2010; Aveyard and Haydon, 1973) and to our recent publication (Sathappa and Alder, 2016) upon which this analysis is based.
    2. There are several simplifying assumptions of the Gouy-Chapman-Stern model, including: (i) that the membrane can be considered an infinite planar surface with bound charges uniformly smeared at x = 0; (ii) that the dielectric constant of the solution is constant at all x > 0; and (iii) that solution ions can be treated as point charges. In this model, the variable x represents the distance from the bilayer surface (see Figure 2).
    3. The bilayer surface charge originates from the titratable functional groups on the lipids and the adsorbed ions from solution. The maximal intrinsic surface charge from lipid groups (σmax j) is defined by the molar fraction-weighted maximal surface charge density of each lipid species j

      Where,
      e is either the total formal charge or the elementary charge (± 1.6022 x 10-19 C) on the ionized titratable group,
      χj is the molar fraction of species j,
      Aj is the cross-sectional area of species j.
      We assume for this analysis that Aj of a typical phospholipid is 70 Å2 and does not change with protonation state or complexation with ions. Note that σmax j is a constant for a given lipid system (Note 9).
    4. The effective charge density of lipid headgroups (σ) under different conditions is modeled as a Langmuir adsorption isotherm that accounts for both the protonation state of the headgroup (depending on the surface pH) and on specific binding of solution counterions (depending on the surface concentration of ions). For the example given here, we need only account for the headgroup phosphate as the acidic ionizable headgroup charge and the presence of monovalent counterions; hence, the equation for σ takes the form:

      Where,
      [H+]0 and [C+]0 are the surface concentrations of protons and monovalent cations, respectively (each in units of molarity, M),
      Ka (M) is the acid dissociation (ionization) constant,
      KC (M-1) is the association constant for 1:1 binding of the mononvalent cation to the headgroup. The distribution of ions in the direction normal to the membrane surface is determined by Boltzmann statistics. Thus, the surface concentrations [H+]0 and [C+]0 can be defined from concentrations in the bulk, [H+] and [C+] as follows:

      Where,
      z is the valence of the relevant species,
      F is the Faraday constant (9.649 x 104 C mol-1),
      R is the universal gas constant (8.314 J mol-1 K-1),
      T is the absolute temperature (K),
      ψ0 (V) is the electric potential at the surface (relative to the bulk, ψ).
      Note that the work (in J mol-1) required to bring an ion from infinity to a position with electric potential ψ is quantified as zF ψ. Therefore, based on the Boltzmann distribution, there will be an accumulation of protons and cations (z = +1) and a decrease in anions (z = -1) at distances approaching the negatively charged bilayer surface.
    5. The Gouy-Chapman equation, based on the Poisson-Boltzmann relationship, relates surface potential (ψ0) and surface charge density (σ):

      Where,
      C is the bulk concentration of ion of valence z.
      Values of ψ0, σ and Ka can be determined by the simultaneous evaluation of Eq. 3-5.
    6. Finally, the electrostatic profile in the direction normal to the bilayer surface is used to determine σ0 from measurements of ζ (see Figure 2). To quantify ψ as a function of distance from the surface, we first consider the Debye constant, κ (m-1), quantified as

      The value, κ-1 (m), is called the Debye length, which represents a measure of the thickness of the diffuse double layer. As shown in Eq. 6, the Debye length depends on the concentration and valence of electrolyte in the solution near the solid-aqueous interface. The higher the ionic strength (and higher valence of component ions), the more effectively solution ions will screen the electric field from the surface, thereby more rapidly attenuating the electric potential and reducing the extent of the double layer.
    7. The distance-dependent decay of the electric potential from the membrane surface is quantified by the following relationship:

      Where,
      x (m) is the distance from the membrane plane,
      ψx is the electric potential at that distance. To calculate ψ0 from measurements of ζ based on these relationships, we must make an assumption about the distance at which the shear plane exists such that for each measured value of zeta potential, we can assume that ζ = ψx.

  2. Data analysis
    In the presented methodology, ζ measurements over a range of solution pH values are analyzed to evaluate the pKa of the component lipid. The quantitative analysis described here is delineated into three steps, each one described below with reference to the theoretical considerations from the previous section. In our previous work (Sathappa and Alder, 2016), we primarily used Wolfram Mathematica 10 for quantitative evaluation. But for the present analysis, we have adapted this as a more simplified approach for use with Microsoft Excel. A representative Excel worksheet is presented in Figure 4, which explicitly shows all three stages of analysis along with the way in which each cell should be populated. The spreadsheet represents a mock data set in which POPG liposomes were subjected to zeta potential measurements in the presence of 10 mM monovalent electrolyte over a range of pH values (pH 1-9) (Note 10). The input values of ζ in this example are as follows:
         pH 1, ζ = -6.899 mV; pH 2, ζ = -27.273 mV;   pH 3, ζ = -57.717 mV 
         pH 4, ζ = -88.171 mV;   pH 5, ζ = -110.527 mV;   pH 6, ζ = -118.836 mV 
         pH 7, ζ = -120.118 mV;   pH 8, ζ = -120.255 mV;   pH 9, ζ = -120.268 mV 
    1. Step 1: Enter experiment parameters
      1. The first column relates to characteristics of the model lipid system:
        1. Cell C4 (data input): This is the formal charge per ionized lipid headgroup. POPG is an anionic lipid with a maximum of one negative charge per lipid; therefore, a value of -1 is input here.
        2. Cell C5 (data input): This is the mol% anionic lipid in the model system. In this example, liposomes are pure POPG (χPOPG = 1.0); therefore, a value of 100 is entered here.
        3. Cell C6 (formula input): This calculation of surface charge density is a form of Eq. 2 that quantifies σ in terms of total charge per Å2.
        4. Cell C7 (formula input): This recasts σ in terms of C m-2 for use in the adsorption isotherm for direct comparison with the Gouy-Chapman equation.
      2. The second column relates to the ionic characteristics of the bathing solution:
        1. Cell H3 (data input): This is the molar concentration of monovalent electrolyte in the solution. In this example, the solution contains 10 mM NaCl; therefore, a value of 0.01 is entered here.
        2. Cell H4 (formula input): This is the formula input for the Debye constant κ (Eq. 6), given that |z| = 1 and assuming that εr = 80 and T = 298K.
        3. Cell H5 (formula input): This is the calculated value of the Debye length, 1/κ, in terms of m.
        4. Cell H6 (formula input): This recasts 1/κ in terms of Å.
        5. Cell H7 (data input): This is the assumed distance x of the slip plane from the surface of the bilayer (correlating with the point at which ψx = ζ). Based on previous work [Sathappa and Alder (2016) and references therein], a value of 2 Å should be input here.
        6. Cell H8 (formula input): This is the product of κ and x, which is used in Eq. 7.
    2. Step 2: Calculate surface potential
      1. For each pH-specific value of ζ, the corresponding value of ψ0 is calculated.
        1. Cells A13-A21 (data input): The values of bulk pH for each reading.
        2. Cells B13-B21 (formula input): This converts bulk pH to bulk [H+] in units of molarity.
        3. Cells C13-C21 (data input): The values of ζ (V) for each pH condition are entered.
        4. Cells D13-D21 (formula input): This is a rearrangement of Eq. 7 that is used as the objective cell in the Solver protocol to calculate ψ0.
        5. Cells E13-E21 (calculated values): These are the variable cells in the Solver protocol. For consistency, set each cell equal to -0.00001 prior to running Solver.
      2. To calculate ψ0 for each given ζ using Solver, open Solver (from the Excel ‘Tools’ dropdown menu) and perform the following for each data point:
        1. Set objective for the relevant ‘Eq. 7’ cell (e.g., D13 for the ‘pH 1’ point) to a value of 0.
        2. Assign the variable cell as the relevant ‘ψ0 (V)’ cell (e.g., E13 for the ‘pH 1’ point).
        3. Make sure that unconstrained variables can be negative.
        4. Click Solve
    3. Step 3: Calculate surface charge density and pKa
      1. First, the Gouy-Chapman equation (Eq. 5) is used to calculate the effective surface charge density. Second, this value is equated with the adsorption isotherm (Eq. 3) to solve for the measurement-specific Ka value.
        1. Cells G13-G21 (formula input): This is the Gouy-Chapman equation, which calculates σ based on the known concentration of electrolytes in solution and the calculated values of ψ0.
        2. Cells H13-H21 (formula input): This is the calculation of the surface H+ concentration based on the Boltzmann distribution (Eq. 4a).
        3. Cells I13-I21 (formula input): This is the calculation of the surface cation concentration based on the Boltzmann distribution (Eq. 4b).
        4. Cells J13-J21 (formula input): This is an algebraic manipulation of Eq. 3, which solves for Ka assuming that the association constant of cation adsorption to the POPG headgroup is 0.6 M-1.
        5. Cell J22 (formula input): This takes the average Ka value for all measurements and converts it to a pKa value.


          Figure 4. Excel sheet workup for data analysis. A. Data entry cells, subdivided into steps 1-3. Cells in green are those used for direct data input. Non-shaded cells are those either containing formulas or calculated values. See text for detailed explanation. B. Input for formula cells, along with corresponding equations from the text. Cells and variables highlighted in blue are those that are copied from rows 13 to 21 within each column.

Notes

  1. All lipid stocks in chloroform should be stored in glass vials with Teflon-lined closures at -20 °C.
  2. The lipid stocks are thawed to room temperature under a fume hood for 15 min before aliquoting into Kimble Corex tubes. It is essential that plastic does not come into contact with lipid stocks in chlorofom, as this solvent will leach impurities from the plastic. Hamilton gas-tight syringes should be used to transfer lipid stocks in organic solvents.
  3. It is also possible to prepare liposomes with a heterogeneous composition of synthetic lipids by preparing a blend of lipids at this stage. For example, the phospholipids 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC); 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphethanolamine (POPE); and POPG can be used to prepare liposomes composed of POPC:POPE:POPG (40:40:20 mol%) by mixing 85 μl of 25 mg/ml POPC, 81 μl of 25 mg/ml POPE and 43 μl of 25 mg/ml POPG prior to drying down the lipids.
  4. Lipid drying times under the nitrogen stream will vary. In general, once the first white residue begins to appear, drying is continued for an additional 10-15 min. When dried, the lipids will develop a thin film at the bottom of the glass tube. Avoid excessive drying, as this will make hydration and resuspension of the lipid film difficult.
  5. Make sure the temperature of the hydration buffer and extruder are above the phase transition temperature (Tm) of the lipid being used (or the Tm of the lowest-melting lipid in a heterogeneous blend). If the target Tm is above room temperature, all buffers should be brought above the Tm in a temperature-controlled incubator and the extruder heating block assembly should be equilibrated to the desired temperature atop an adjustable hot plate prior to extrusion. Note that the Tm of POPG is -2 °C; therefore, the illustrated protocol can be carried out at room temperature.
  6. The extruder is assembled in accordance with manufacturer’s instructions (https://avantilipids.com/tech-support/liposome-preparation/luvet/). To reduce the dead volume during extrusion, pre-wet all extruder parts by passing the appropriate buffer through the assembled extruder, then discarding the buffer. The final extrusion should be taken from the opposite syringe used to load the sample to reduce contamination. During extrusion, lipid samples generally go from being hazy to more transparent. Between sample preparations, wash the extrusion parts thoroughly with water, ethanol, then allow to air dry to reduce contamination.
  7. The instrument parameters must be modified in accordance with the buffer, pH and temperature of each run. Instrument calibration is conducted using BI-ZR5 zeta potential reference material in 1 mM KCl at -49 mV ± 4 mV.
  8. After each run, the liposomes in the cuvettes should be mixed well, to avoid settling of liposomes to the bottom of the cuvette.
  9. For information on modeling multicomponent systems containing different lipids with differing pKa values, refer to our recent publication (Sathappa and Alder, 2016).
  10. In practice, a smaller pH range will be required to maintain stability of the liposome samples. The wide pH range (1-9) given in this theoretical example is for illustrative purposes only to allow the reader to understand the conceptual basis of the analysis.

Recipes

  1. Citrate-phosphate buffers (100 ml each, pH 2-8, each with 10 mM NaCl)
    1. Prepare 0.1 M solution of citric acid solution by dissolving 0.58 g NaCl and 21.01 g of citric acid monohydrate in 1 L of ddH2O.
    2. Prepare 0.2 M solution of phosphate solution by dissolving 0.58 g NaCl and 28.40 g of dibasic sodium phosphate in 1 L of ddH2O.
    3. Mix citric acid and phosphate at the following volumes to obtain buffered solutions of the following pH values (Table 2):

      Table 2. Phosphate citrate buffer recipe


  2. AMPD buffer (100 ml, each with 10 mM NaCl)
    1. Prepare 0.2 M solution of AMPD by dissolving 0.058 g NaCl and 21.03 g of AMPD in 90 ml of ddH2O.
    2. Set solution to desired pH using 6 N NaOH (initial pH will be approximately 7.6).
    3. Adjust final volume to 100 ml with ddH2O.
  3. Ammonium ferrothiocyanate solution
    Dissolve 27.3 g FeCl3·6H2O and 30.4 g ammonium thiocyanate in 1 L ddH2O.

Acknowledgments

This protocol was adapted from our recent published work (Sathappa and Alder, 2016). Research in the Alder Group is supported by National Institutes of Health Grant 1R01GM113092, National Science Foundation Grant MCB-1330693, and a Barth Syndrome Foundation Research Grant (to N.N.A.).

References

  1. Aveyard, R. and Haydon, D. A. (1973). An introduction of the principles of surface chemistry. Cambridge University Press.
  2. Delgado, A. V., Gonzalez-Caballero, F., Hunter, R. J., Koopal, L. K., Lyklema, J., International Union of, P., Applied Chemistry, P. and Biophysical Chemistry Division, I. T. R. (2007). Measurement and interpretation of electrokinetic phenomena. J Colloid Interface Sci 309(2): 194-224.
  3. Gennis, R. B. (1989). Biomembranes molecular structure and function. Springer.
  4. Marom, M. and Abdussalam, A. (2013). The use of cardiolipin-containing liposomes as a model system to study the interaction between proteins and the inner mitochondrial membrane. Methods Mol Biol 1033: 147-155.
  5. Marsh, D. (2013). Handbook of lipid bilayers, Second Edition. CRC Press.
  6. McLaughlin, S. (1977). Electrostatic potentials at membrane-solution interfaces. Curr Top Membr Transp 9: 71-144.
  7. Oshima, H. (2010). Biophysical chemistry of biointerfaces. Wiley.
  8. Sathappa, M. and Alder, N. N. (2016). The ionization properties of cardiolipin and its variants in model bilayers. Biochim Biophys Acta 1858(6): 1362-1372.
  9. Tocanne, J. F. and Teissie, J. (1990). Ionization of phospholipids and phospholipid-supported interfacial lateral diffusion of protons in membrane model systems. Biochim Biophys Acta 1031(1): 111-142.

简介

生物膜对于多种细胞功能如维持细胞和细胞器结构,选择性渗透性,主动转运和信号传导至关重要。膜双层的表面电荷在这些无数过程中起关键作用。对于大多数生物膜,阴离子磷脂的表面电荷有助于在双层的界面区域内的负表面电荷密度。为了量化表面电荷,必须理解可滴定头基在这种脂质内的质子解离行为。我们描述了使用模型膜用于电动ζ电位测量以及使用Gouy-Chapman-Stern形式的数据分析以确定组分脂质的p a 值的方案。提供了由单阴离子脂质磷脂酰甘油组成的均匀双层的详细实施例。这种方法可以适用于测量具有异质脂质组合的双层,以及用于在头部组中具有多个可滴定位点的脂质(例如,心磷脂)。

[背景] 磷脂是生物膜的中心结构单元(图1)。作为两亲性分子,每个包含由酰基链组成的疏水区和由极性头基组成的亲水区(图1A)。一些磷脂头基是两性离子的,在生理pH下含有带正电和带负电的官能团(图1B),而其它磷脂头基是酸性的,带有整体形式的负电荷(图1C)。生物膜内的脂质作为层状组件稳定存在,形成双层,其中两个叶的酰基链相互作用形成疏水核和由极性头基组成的两个界面区域(图1D)。大多数天然存在的生物膜含有一定百分比的酸性磷脂;因此,它们的脂质组成赋予界面区域净负电荷(Gennis,1989; Marsh,2013)。双层表面电荷是许多膜级过程中的关键因素,包括与蛋白质和溶液离子的相互作用以及膜形态,融合和相变。因为脂质头基的形式电荷是这种表面电荷的主要决定因素,所以具有质子解离行为的精确测量(定量为p a 值)是关键的,的组成功能组别。


图1.磷脂结构和层状脂质双层 。 A.甘油磷脂的一般结构。常见的磷脂基于中心甘油分子(加厚线)的支架,其中组成碳由立体特异性编号( sn -1, sn em> sn -3,如图所示)。疏水域由在 sn -1和 sn -2位置酯化的烃尾组成。极性头部基团包含连接到sn - 3位置的带负电的磷酸基团,其可以被R基团修饰以赋予特定的头基同一性。 B.磷脂酰胆碱(R =胆碱)的结构,在sn -1位置具有饱和的16碳脂肪族尾部,在sn -2位置具有不饱和的18碳尾部。头基的两性离子性质显示为负性磷酸盐和正性叔胺。 C.具有与上述相同的酰基链的磷脂酰甘油(R =甘油)的结构。头基的阴离子性质通过磷酸盐上未补偿的负电荷显示。 D.层状脂质双层,显示由脂肪族脂质尾部和溶剂暴露的界面区域组成的烃核心。

 由充电的头基产生的电场导致水域中电位的复杂分布(图2)(McLaughlin,1977)。电势分布的模型基于相界面界面的物理化学,这里表示与水相接触的固体表面(Oshima,2010)。膜表面静电可以使用Gouy-Chapman-Stern理论定量建模,其涉及膜表面上的电荷密度(σem,C m -2 )和电荷电位(ψ,V),如数据分析部分所述。在简化的模型中,表面电荷由固定到固体上的电荷以及通过化学相互作用紧密吸附到表面的溶液离子组成。对于脂质双层,固定电荷可以被认为是脂质头基的可滴定酸性(磷酸盐)和碱性(主要芳香胺)官能团,而吸附的离子是特异性地

材料和试剂

  1. Kimble Corex管(30ml)(Thermo Fisher Scientific,Fisher Scientific,目录号:0950037)
  2. Hamilton气密注射器(Avanti Lipids Polar,目录号:610017)
  3. 聚碳酸酯膜过滤器,0.4μm(Avanti Lipids Polar,目录号:610007)
  4. 宽范围pH试纸(Thermo Fisher Scientific,Fisher Scientific,目录号:14-850-1)
  5. 玻璃管
  6. 4ml半微量比色皿(SARSTEDT,目录号:67.745)
  7. Hellma Suprasil石英比色皿(Sigma-Aldrich,目录号:Z802433)
  8. 玻璃小瓶
  9. N 2
  10. 1-棕榈酰-2-油酰-sn-甘油-3-磷酸 - (1'-外消旋 - 甘油)(POPG)(Avanti Lipids Polar,目录号:840457C )(注1)
  11. 氯仿(Thermo Fisher Scientific,Fisher Scientific,目录号:C298)
  12. 氯化钠(NaCl)(Sigma-Aldrich,目录号:S9888)
  13. 特氟隆衬里密封件(Avanti Lipids Polar,目录号:600460)
  14. 1-棕榈酰-2-油酰-sn-甘油-3-磷酸胆碱(POPC)(Avanti Lipids Polar,目录号:850457C)
  15. 1-棕榈酰-2-油酰-sn-甘油-3-磷酸乙醇胺(POPE)(Avanti Lipids Polar,目录号:850757C)
  16. 乙醇
  17. 氯化钾(KCl)
  18. 柠檬酸一水合物(C 6 H 8 O 7 O 7·H 2 O)(Sigma-Aldrich,目录号:C1909)
  19. 磷酸氢二钠(Na 2 HPO 4)(Sigma-Aldrich,目录号:S7907)
  20. 2-氨基-2-甲基-1,3-丙二醇(AMPD)(Sigma-Aldrich,目录号:A9754)
  21. 氯化铁(III)六水合物(FeCl 3·6H 2 O)(Sigma-Aldrich,目录号:236489)
  22. 微孔过滤灭菌水(ddH 2 O)(EMD Millipore,目录号:Milli-Q Advantage A10水纯化系统)
  23. 硫氰酸铵(NH 4 SCN)(Sigma-Aldrich,目录号:221988)
  24. 柠檬酸盐 - 磷酸盐缓冲液(参见配方)
  25. AMPD缓冲区(请参阅配方)
  26. 硫氰酸铵溶液(参见配方)

设备

  1. 氮气罐
  2. 通风橱
  3. 真空干燥器(Eppendorf,型号:Vacufuge Plus)
  4. 纳米粒度分析仪(Malvern Instruments,型号:Zetasizer Nano S90)(Zetasizer Nano Series Technical Note,Malvern Instruments: https://caliscc.org/images/presentations/Morante_Zeta_Potential.pdf
  5. Nanosphere TM 聚合物微球尺寸标准,尺寸为60±2.7nm(Thermo Fisher Scientific,Thermo Scientific TM ,目录号:3060A)
  6. 巴斯德移液器
  7. Vortexer(Bio-Rad Laboratories,型号:BR 2000)
  8. 过滤器支架(Avanti Lipids Polar,目录号:610014)
  9. Accumet pH计(Thermo Fisher Scientific,Fisher Scientific TM ,目录号:AB15 Plus)
  10. Avanti Mini Extruder Kit(Avanti Lipids Polar,目录号:610023)
  11. 分光光度计(Thermo Fisher Scientific,Fisher Scientific,型号:Ultrospec 2100 Pro)
  12. Zeta电位分析仪(Brookhaven Instruments,型号:ZetaPlus Zeta电位分析仪)
  13. ζ电位参考材料(Brookhaven Instruments,目录号:BI-ZR5)

软件

  1. Zetasizer软件
  2. Microsoft Excel

程序

  1. 脂质体制备
    1. 使用气密注射器等分所需的脂质体积到Kimble Corex管中。对于说明的协议,添加200微升25毫克/毫升POPG氯仿储备管中。 (注2和3)
    2. 将脂质在通风橱中在温和的N 2蒸汽下干燥约30分钟(注释4)。
    3. 为了除去残留的氯仿,将脂质在干燥器中在真空下进一步干燥过夜
    4. 将干燥的脂质水合并通过在1ml相应的磷酸盐柠檬酸盐缓冲液(pH 2.0至8.0)或AMPD缓冲液(pH 8.0至10.0)(参见Recipes)中剧烈涡旋再悬浮并再温育30分钟(注释5) br />
    5. 将水合脂质通过保持在适当温度的0.4μm膜(注6)挤出19次
  2. 质量控制和脂质体大小
    1. 在Zetasizer Nano S90中通过动态光散射分析所得脂质体以确认如图3A所示制备的样品的均匀性和准确尺寸。
      1. 使用具有以下测量参数的90°散射光学器件进行尺寸测量。温度:25±1℃;分散剂:磷酸盐缓冲盐水;折射率:1.332;粘度:0.9128cP;平衡时间:1分钟;测量:自动;分析模型:通用(正常分辨率)。仪器校准使用Nanosphere TM 尺寸标准进行
      2. 将每个样品60μl置于石英比色皿中,并以1分钟间隔连续三次测量
      3. 通过Zetasizer软件分析散射数据,如图3B和3C所示。
    2. 挤出后的脂质体的pH通过使用如图3D所示的pH纸来验证
    3. 囊泡样品的脂质浓度的测量使用测量磷脂 - 铵亚铁氰化物络合物的已建立的比色测定法进行(Marom和Abdussalam,2013)。
      1. 校准曲线如下产生:
        1. 在玻璃管中加入40μlPOPG(25mg/ml)到9.96ml氯仿中,制备0.1mg/ml POPG的储备溶液。
        2. 在表1所示的玻璃管中制备11个POPG样品
        3. 在加入亚硫氰酸铵和氯仿后,涡旋样品各1分钟
        4. 两个单独的阶段将变得明显。使用巴斯德吸管,小心地取出上层相并丢弃
        5. 将下层转移到合适的试管中,使用分光光度计测量488nm处的吸光度。不含POPG的样品用作空白。
        6. 488nm处的吸光度对脂质浓度(mg/ml)的曲线图用作校准曲线(图3E)。

          表1.用于绘制校准曲线的反应混合物



          图3.脂质体表征 A.通过动态光散射表示均匀群体的由100mol%POPG制备的脂质体的代表性强度分布图。 B.100mol%POPG脂质体的平均直径(Z-平均值)。 C.100mol%POPG脂质体的多分散指数。 D.在使用pH试纸验证的各种pH缓冲液中水合和挤出后脂质体的各自的pH。 E.代表性磷脂校准曲线。

      2. 脂质体样品的脂质浓度如下测量:
        1. 加入10微升准备的脂质体到玻璃管。加入2ml亚硫氰酸铵并涡旋1分钟
        2. 加入1.99ml氯仿并涡旋1分钟
        3. 将脂质体在各自的缓冲液中稀释至1mg/ml的浓度。

  3. ζ电位测量使用ZetaPlus Zeta电位分析仪(参见参考文献10)进行
    1. 加入1.6毫升1毫克/毫升脂质体样品在4毫升半微量比色皿。
    2. 打开ZetaPlus软件,并在"参数"对话框中更改相应的条件。测量参数如下。电场:14.86V/cm;电流21.37 mA;电导:3936μS;粘度:0.890cP;折射率:1.330;介电常数:78.54;温度:25℃。使用的电极是ZetaPlus,SR-516型电极(注7)
    3. 测量进行三次,10次循环(注8)

数据分析

上述方案允许在pH值范围内获得含POPG的脂质体的ζ电位值。数据分析的目的是基于这些数据评价组分脂质的p a 值。在本节中,我们首先简要概述本分析中涉及的理论和数学考虑。然后,我们提出一个逐步的过程,以彻底评估数据。

  1. 理论与建模
    1. 垂直于双层平面的扩散双层的静电曲线(图2)使用Gouy-Chapman-Stern形式来建模。在这个简明的理论概述中,我们在本分析中提出相关方程;对于理论和数学推导的进一步信息,读者参考几个背景资源(McLaughlin,1977; Oshima,2010; Aveyard和Haydon,1973)和我们最近的出版物(Sathappa和Alder, 。
    2. 有几个简化的Gouy-Chapman-Stern模型的假设,包括:(i)膜可以被认为是无限平面表面,在x = 0处具有均匀污染的带电荷; (ii)溶液的介电常数在所有x> 0;和(iii)溶液离子可以作为点电荷处理。在该模型中,变量x表示与双层表面的距离(见图2)
    3. 双层表面电荷源自脂质上的可滴定官能团和来自溶液的吸附离子。通过每种脂质的摩尔分数加权的最大表面电荷密度来定义来自脂质基团的最大内在表面电荷(σem max j j

      在哪里,
      是电离可滴定组上的总形式电荷或基本电荷(±1.6022×10 <-19
      C),
      是 j 种的摩尔分数,
      是 j 种的横截面。
      对于该分析,我们假设典型磷脂的 是 70 Å
      在哪里,
      分别是质子和单价阳离子的表面浓度[H sup + 1/sup]和[C sup + 1/sup] (每个以摩尔浓度为单位, M ),
      ( M )是酸解离(电离)常数,
      -1 )是单价阳离子与头基。离子在垂直于膜表面的方向上的分布由玻尔兹曼统计学确定。因此,表面浓度[H sup + O] O和[C sup + O] O sub可以从批量,[H + ] 和[C + ]

      在哪里,
      z 是相关物种的价,
      是法拉第常数(9.649×10 4 C mol -1 ),
      是通用气体常数(8.314 J mol -1 K -1 ),
      T 是绝对温度(K),
      (V)是表面处的电势(相对于体积,ψ )。
      注意,将离子从无穷远带到具有电势ψ的位置所需的功(以J mol -1 )被定量为zF ψ。因此,基于玻尔兹曼分布,在距离处将存在质子和阳离子的积累( z = +1)和阴离子的减少( z = -1)接近带负电荷的双层表面
    4. 基于泊松 - 波尔兹曼关系的Gouy-Chapman方程式涉及表面电势(θem)和表面电荷密度(σem):

      在哪里,
      C 是价态的离子的本体浓度 z 。
      值s 和 的 K 可以通过等式的同时评估来确定。 3-5。
    5. 最后,在垂直于双层表面的方向上的静电分布用于根据ζ的测量确定(参见图2)的σ 0。为了量化作为距离表面的距离的函数的Θe/em,我们首先考虑德拜常数κ(m -1 ), br />
      值e em,κ -1 (m)被称为德拜长度,其代表漫射双层的厚度的量度。如公式如图6所示,德拜长度取决于固体 - 水性界面附近的溶液中的电解质的浓度和化合价。离子强度越高(和组分离子的价态越高),溶解离子越能有效地屏蔽来自表面的电场,从而更快地衰减电位并减小双层的范围。
    6. 来自膜表面的电位的距离依赖性衰减通过以下关系来量化:

      在哪里,
      x(m)是离膜平面的距离,
      x 是该距离处的电位。为了基于这些关系从ζ的测量计算ψ,我们必须假设剪切面存在的距离,使得对于ζ电势的每个测量值,我们可以假定ζ =ψ
    7. 步骤1:输入实验参数
      1. 第一列涉及模型脂质系统的特征:
        1. 细胞C4(数据输入):这是每个电离脂质头基团的形式电荷。 POPG是每个脂质具有最多一个负电荷的阴离子脂质;因此,此处输入值-1。
        2. 细胞C5(数据输入):这是模型系统中的mol%阴离子脂质。在该实施例中,脂质体是纯的POPG(χ POPG = 1.0);因此,此处输入值100。
        3. 单元C6(公式输入):表面电荷密度的这种计算是公式2,其以每个 2 的总电荷量化σ。
        4. 电池C7(公式输入):这在用于吸附等温线的C m -2 方面重写σ以与Gouy-Chapman方程直接比较。
      2. 第二列涉及洗液的离子特性:
        1. 细胞H3(数据输入):这是溶液中单价电解质的摩尔浓度。在该实施例中,溶液含有10mM NaCl;因此,此处输入0.01的值。
        2. 单元H4(公式输入):这是德拜常数κ(公式6)的公式输入,假设| z | = 1并假设ε r = 80和T = 298K。
        3. 单元H5(公式输入):这是以米为单位的德拜长度1 /κ的计算值。
        4. 细胞H6(公式输入):这重新表示1 /κ。
        5. 单元H7(数据输入):这是滑移面距双层表面的假定距离x(与其中ψ x <= x> ζ)。基于以前的工作[Sathappa和Alder(2016)及其中的参考文献],此处应输入2的值。
        6. 单元H8(公式输入):这是κ和x的乘积,其在等式1中使用。 7。
    8. 步骤2:计算表面电位
      1. 对于每个pH特异性值ζ,ψψ 0
        1. 单元格A13-A21(数据输入):每个读数的体积pH值
        2. 细胞B13-B21(配方输入):以摩尔浓度单位将批量pH转换为批量[H + ]。
        3. 细胞C13-C21(数据输入):输入每种pH条件下的ζ(V)值。
        4. 单元D13-D21(公式输入):这是等式1的重新排列。 7,其用作求解器协议中的目标单元以计算 0
        5. 单元格E13-E21(计算值):这些是Solver协议中的可变单元格。为了一致性,在运行Solver之前将每个单元格设置为-0.00001。
      2. 为了使用Solver,open Solver(来自Excel的"工具"下拉菜单)为每个给定的ζi计算ψ 数据点:
        1. 设置相关的"方程"的目标。 7'单元格(例如。,"pH 1"点的D13)设置为0.
        2. 将变量单元格指定为相关的ψ 0 em>例如。,E13为'pH 1'点)。
        3. 确保不受约束的变量可以为负数。
        4. 单击解决
    9. 步骤3:计算表面电荷密度和p a
      1. 首先,使用Gouy-Chapman方程(式5)计算有效表面电荷密度。第二,该值等于吸附等温线(方程式3)以求出测量特异性的 值。
        1. 细胞G13-G21(公式输入):这是Gouy-Chapman方程,其基于溶液中已知的电解质浓度和计算的ψ值计算 sub> 0 。
        2. 单元H13-H21(公式输入):这是基于波尔兹曼分布(公式4a)的表面H + 浓度的计算。
        3. 电池I13-I21(公式输入):这是基于玻尔兹曼分布计算表面阳离子浓度(公式4b)。
        4. 单元J13-J21(公式输入):这是等式的代数操作。 3,其假设阳离子吸附到POPG头基的缔合常数为0.6M -1 ,其解决了
        5. 单元J22(公式输入):这取得所有测量的平均值 Ka ,并将其转换为p K a 值。

          图4.用于数据分析的Excel表单处理。A.数据输入单元格,细分为步骤1-3。绿色单元格是用于直接数据输入的单元格。非阴影单元格是包含公式或计算值的单元格。有关详细说明,请参阅文本。 B.公式单元的输入,以及来自文本的对应方程。以蓝色突出显示的单元格和变量是从列中第13行到第21行复制的单元格和变量。

笔记

  1. 氯仿中的所有脂质储备液应储存在带有特氟隆衬里的玻璃小瓶中,温度为-20°C
  2. 将脂质储备液在通风橱下解冻至室温15分钟,然后等分到Kimble Corex管中。重要的是塑料不会与氯仿中的脂质原料接触,因为这种溶剂会从塑料中浸出杂质。应使用Hamilton气密注射器在有机溶剂中转移脂质原液。
  3. 也可以通过在该阶段制备脂质的混合物来制备具有合成脂质的多相组合物的脂质体。例如,磷脂1-棕榈酰基-2-油酰基-sn-甘油-3-磷酸胆碱(POPC); 1-棕榈酰-2-油酰-sn-甘油-3-磷脂酰乙醇胺(POPE);和POPG可以用于通过混合85μl的25mg/ml POPC,81μl的25mg/ml的POPE和43μl的25mg/ml的POPE组成的POPC:POPE:POPG(40:40:20mol% ml POPG,然后干燥脂质
  4. 在氮气流下的脂质干燥时间将变化。通常,一旦第一白色残余物开始出现,再继续干燥10-15分钟。当干燥时,脂质将在玻璃管的底部形成薄膜。避免过度干燥,因为这将使水性和脂质膜的再悬浮困难
  5. 确保水合缓冲液和挤出机的温度高于所用脂质的相变温度(T m)(或最低熔点脂质的T m)在多相共混物中)。如果目标T sub高于室温,则所有缓冲液应在温度控制的培养箱中升至T m以上,并且挤出机加热块组件应当平衡至在挤出之前在可调热板上的期望温度。注意,POPG的T m1是-2℃;因此,所示的方案可以在室温下进行
  6. 挤出机根据制造商的说明进行组装( https://avantilipids.com/tech-support/liposome-preparation/luvet/)。为了减少挤出期间的死体积,通过使合适的缓冲液通过组装的挤出机预先润湿所有挤出机部件,然后丢弃缓冲液。最后挤出应从用于装载样品的相对的注射器中取出,以减少污染。在挤出期间,脂质样品通常从模糊到更透明。在样品制备之间,用水,乙醇彻底冲洗挤出部件,然后风干,以减少污染
  7. 仪器参数必须根据每次运行的缓冲液,pH和温度进行修改。使用BI-ZR5ζ电位参比物质在1mM KCl中在-49mV±4mV下进行仪器校准。
  8. 每次运行后,比色杯中的脂质体应该充分混合,以避免脂质体沉降到比色皿的底部。
  9. 有关建模包含具有不同p k a 值的不同脂质的多组分系统的信息,请参阅我们最近的出版物(Sathappa和Alder,2016)。
  10. 在实践中,将需要较小的pH范围以维持脂质体样品的稳定性。本理论实例中给出的宽pH范围(1-9)仅用于说明目的,以使读者能够理解分析的概念基础。

食谱

  1. 柠檬酸盐 - 磷酸盐缓冲液(各100ml,pH 2-8,各自具有10mM NaCl)
    1. 通过将0.58g NaCl和21.01g柠檬酸一水合物溶解在1L ddH 2 O中制备0.1M柠檬酸溶液。
    2. 通过将0.58g NaCl和28.40g磷酸氢二钠溶解在1L ddH 2 O中制备0.2M磷酸盐溶液。
    3. 以下列体积混合柠檬酸和磷酸盐,得到下列pH值的缓冲溶液(表2):

      表2.磷酸盐柠檬酸盐缓冲液配方


  2. AMPD缓冲液(100ml,各自含有10mM NaCl)
    1. 通过将0.058g NaCl和21.03g AMPD溶解在90ml ddH 2 O中制备0.2M AMPD溶液。
    2. 使用6N NaOH将溶液设定为所需的pH(初始pH为约7.6)
    3. 用ddH 2 O调节终体积至100ml。
  3. 硫氰酸铵溶液
    在1L ddH 2 O中溶解27.3g FeCl 3·6H 2 O和30.4g硫氰酸铵。

致谢

这个协议改编自我们最近出版的工作(Sathappa和Alder,2016)。阿尔德集团的研究由国立卫生研究院资助1R01GM113092,国家科学基金会资助MCB-1330693和巴特综合征基金会研究资助(到N.N.A.)支持。

参考文献

  1. Aveyard,R。和Haydon,DA(1973)。  表面化学原理的介绍 <剑桥大学出版社。
  2. Delgado,AV,Gonzalez-Caballero,F.,Hunter,RJ,Koopal,LK,Lyklema,J.,International Union of,P.,Applied Chemistry,P.and Biophysical Chemistry Division,ITR(2007)。< a class ="ke-insertfile"href ="http://www.ncbi.nlm.nih.gov/pubmed/17368660"target ="_ blank">电动现象的测量和解释 J胶体Interface Sci 309(2):194-224。
  3. Gennis,RB(1989)。  Biomembranes分子结构和功能。/a> Springer 。
  4. Marom,M.和Abdussalam,A。(2013)。  1033:147-155。
  5. Marsh,D。(2013)。  Handbook of lipid bilayers,Second Edition。 CRC Press 。
  6. McLaughlin,S。(1977)。  膜上静电电位 - 溶液界面。 Curr Top Membr Transp 9:71-144。
  7. Oshima,H。(2010)。  生物物理化学
  8. Sathappa,M。和Alder,NN(2016)。  心肌磷脂及其变体在模型双层中的电离性质。 生物化学生物物理学 1858(6):1362-1372。
  9. Tocanne,JF和Teissie,J。(1990)。  在膜模型系统中,磷脂和磷脂支持的质子的界面侧向扩散的离子化。 Biochim Biophys Acta 1031(1):111-142。
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Copyright: © 2016 The Authors; exclusive licensee Bio-protocol LLC.
引用:Sathappa, M. and Alder, N. N. (2016). Ionization Properties of Phospholipids Determined by Zeta Potential Measurements. Bio-protocol 6(22): e2030. DOI: 10.21769/BioProtoc.2030.
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