Protein Quantitation Methods

Protein Quantitation

  • Overview of Current Methods

    • Protein quantitation techniques include:

    • Amino Acid Analysis

      • Most accurate but requires sophisticated instruments.

    • UV Spectrophotometry

    • Colorimetric Methods

    • Mass Spectrometry

UV Spectrophotometry

  • Principle: Measures absorbance of aromatic amino acids at 280 nm to quantify protein concentration.

  • Amino Acids Used:

    • Tryptophan

    • Tyrosine

    • Cysteine

  • Advantages:

    • Simple method that requires small sample volume.

    • No standard curve needed if molar absorption coefficient is known.

  • Disadvantages:

    • Requires pure proteins and is incompatible with contaminants like nucleic acids with similar absorption spectrum.

    • Absorption coefficient must be pre-determined.

Colorimetric Assays

  • Function: Determines protein concentration in solutions through optical density measurement.

  • Common Assays (Dye-binding):

    • Lowry Assay

    • BCA Assay (Bicinchoninic Acid)

    • Bradford Assay

  • Process:

    • Uses a standard curve of a reference protein (e.g., BSA) to determine concentration.

Beer-Lambert Law

  • Relates optical density (A) to concentration (c) using the equation:

  • A (optical density) = εlc

    • Where:

    • E = Absorption coefficient

    • c = Concentration of the compound

    • l = Optical path length

Proteins for Standard Curves

  • Pure proteins

  • Known concentration measured by an independent method

  • Broad linear dynamic range

  • Fitting linear or nonlinear regression models to the quantitative data

Principles of Standard Curve Assays

  • Identically treated samples = directly comparable. Protein quantity = only cause for difference in final absorbance/fluorescence

  • Validation: If unknown and standard samples have the same absorbance, they contain the same concentration.

  • Concentration results expressed in the same units as standards to make standard curve (e.g., mg/mL).

  • Dilution factor is considered post-measurement.

Densitometry Analysis

  • Usage: Useful when proteins have low UV response, or purity is unclear. Some colorimetric assays have low sensitivity and require a lot of sample.

  • Measuring Intensity: Optical density: intensity of staining of bands in gel/degree of darkness of X-ray film

  • Measures degree of darkness as a fcuntion of light transmission.

  • Equation: OD = Log_{10} (1/Transmittance) = E*c*l

    • Transmittance: fraction of light not absorbed by sample

    • Requires a reference standard curve for quantitation.

Benefits of Quantification after Electrophoresis

  • Allows evaluation of purity and yield of individual proteins in complex mixtures.

  • Quantification can be relative, particularly if compared to a standard curve based on a different protein.

Standard Curves in Electrophoresis

  • Created by plotting optical density of protein standards across increasing concentrations.

  • Data can fit models such as linear, hyperbolic, quadratic, or polynomial for smooth curves.

Imaging Systems

  • Several systems for capturing signals post-gel electrophoresis exist, including:

    • Chemiluminescence (after Western blotting)

    • Transmitted visible light through gel staining

  • Detection: Converts photon energy to electrical signals using PMT or CCD arrays.

Digitalization of Images

  • Converts the continuous analog signal to a digital signal.

  • Predetermined discrete intensity levels.

  • Number of intensity levels defines digital resolution; greater levels improve sensitivity.

Image Depth and Bit Depth

  • Image depth refers to pixel intensity values; defined by bits = describe total number of gray shades visible.

  • Example:

    • 8 bits: 256 shades (2^8)

    • 16 bits: 65536 shades (2^16)

    • Human eye perceives 6 bits.

  • Chip with more bits = distinguish smaller differences in intensities

Dynamic Range

  • Dynamic range: range of band intensities measurable in one instance relating to system noise.

  • A wide dynamic range = high sensitivity (detection of faint bands) without signal saturation (strong signal bands)

  • Linear Dynamic Range: Signal intensities are directly related to the source amount.

CCD Camera-Based Systems

  • Composed of illumination and lens assembly to focus images on a CCD array.

  • Sensitive to light, temperature, high energy radiation.

  • Noise from dark current from thermal energy can have strong effect on performance

  • Designed for single field imaging but may require cooling (very $$$) to reduce noise —> improve sensitivity and dynamic range.

  • Limitations: CCD chips are small (~1cm²), image much larger —> long optical path is required to rpoject entire image area onto chip. = decrease light collection efficiency, requires long integration times to collect sufficient signal

Digital Image Scanners

  • Maximize light collection to increase sensitivity: sensor of scanner very close to image —> increase light collection 100-400 fold in a very short time.

  • Shorter exposure times reduce dark noise, and usable at room temperature with cost-efficient sensors.

Summary of Signal Intensity and Source Proximity

  • The closer the light source to the sensor, the higher the signal intensity collected (Inverse Square Law).

  • Example:

    • C-DiGit Blot Scanner (~1mm source) vs. CCD (~500mm).

  • The intensity collected decreases with the square of distance from the source.