20.109(S08):Protein-level analysis (Day6)

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20.109(S08): Laboratory Fundamentals of Biological Engineering

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Contents

Introduction

As you have seen in 20.109 and in the scientific literature, imaging technologies can provide valuable insight into biological systems. Each different imaging method has a particular set of associated advantages and drawbacks. For example, fluorescence microscopy can provide high-resolution images, but the penetration depth at which samples can be viewed is limited (though improved by recent developments such as multiphoton microscopy). Magnetic resonance imaging (MRI) has just the opposite characteristics, and its potential for large-area and deep tissue imaging makes it quite useful in medicine.

Sample image of live cells for analysis
Sample image of live cells for analysis
Sample cell counting result for image above
Sample cell counting result for image above

Whatever the imaging modality, the resulting plethora of imaging information, especially if at the single-cell level or through multiple sections of a 3D-tissue, requires potent and efficient analysis tools. Many image analysis software packages are commercially available, with varying degrees of user-friendliness, algorithm efficiency, etc. Today, you’ll use an open source analysis package from NIH called ImageJ.

Basic image processing includes noise reduction, enhancement of brightness and contrast, thresholding images based on intensity (e.g., everything below a certain intensity value is considered background), and colorizing. For cells, typical analyses include measurement of surface area (i.e., how spread is the cell morphology?), tracking individual cell intensities (as you know from Module 2, these may reflect content of calcium or other molecules of interest), and counting cell populations. In general, analyses that require tracking cells over time are more complicated than static analyses. For example, tracking cell migration typically involves setting thresholds with respect to both intensity and size, then running an algorithm that calculates the centroid of each cell at each time-point and from those centroids the cell’s path and velocity. Fully automated tracking can be challenged by cells dropping in and out of the plane of view, crossing paths with other similar-looking cells, or just moving very quickly. On the other hand, fully manual tracking – which utilizes the power the human eye to avoid mistracking cells – is tedious and time-consuming, not to mention that it will still have a non-zero error rate. Thankfully, your focus today will be on static measurements!

Now, let’s return to thinking about the structure of cartilage for a bit, as promised on Day 4. Our work in this module has focused on chondrocytes themselves (viability and morphology) and on the ECM protein collagen. While collagen makes up ~50-60% of the dry weight of cartilage tissue, another key feature is a high proteoglycan content of ~ 15-30%. In fact, you may have noticed that many of the papers we looked at on Day 1 assayed proteoglycan content to assess the degree of cartilage formation in a tissue engineered construct. Usually this was done by DMMB (dimethylmethylene blue) staining; several similar compounds, called cationic dyes, bind to negatively charged moieties, a key feature of proteoglycans.

Proteoglycans are proteins carrying glycosaminoglycan (GAG) chains, which commonly include keratan and chondroitin sulfates. Aggrecan is the major proteoglycan in cartilage tissue, and many aggrecan monomers attach to a single hyaluronic acid chain to form large aggregates – hence the name. The many negative side chains of proteoglycans (primarily sulfates and carboxylic acids) repel each other, and contribute to the osmotic swelling properties of cartilage tissue. Proteoglycans are trapped within the collagen matrix, the former being primarily responsible for compressive strength (due to changes in osmotic swelling) and the latter for tensile strength. Proteoglycans also contribute to joint lubrication and response to shearing forces.

Osteoarthritis, the primary disease that cartilage tissue engineering aims to treat, is associated with a loss of proteoglycan content. This in turn reduces the swelling and elasticity of cartilage tissue, and its ability to respond to compressive loads. This leads to collagen degradation, joint inflammation, and cartilage tissue destruction. Thus, a physiological proteoglycan content is of essential importance for an engineered cartilage tissue. For our purposes of tracking basic phenotypic maintenance or de-differentiation of chondrocytes, collagen will serve just as well; however, keep in mind that it tells only part of the story.

Protocols

Part 1: Day 2 of ELISA

  1. Begin by washing your samples. (Check the protocol on Day 5 for a refresher.) This time do four washes instead of only two - you don’t want to amplify the signal from any primary antibody that isn’t firmly bound to your samples.
  2. When you are ready, ask the teaching faculty for some alkaline-phosphatase labeled secondary antibody (this should be diluted at the last minute). Add 100 μL of diluted antibody per well. Incubate for 90 min (at room temperature), and work on Part 2 of today's protocol.
  3. Your final wash step should be very thorough because it again precedes an amplification step. To reduce non-specific binding and improve your signal-to-noise ratio, do four careful washes. In the next step, we are adding the substrate for the alkaline phosphatase enzyme.
  4. Ask the teaching faculty for development buffer and a pNPP (p-nitrophenyl phosphate) pellet. Vortex until the pellet is fully dissolved in the buffer, then add 100 μL of development solution to each well. Cover your plate with aluminum foil now!
  5. Every few minutes, check if the samples are becoming yellow. This will most likely take 10-15 minutes, but may happen sooner or later.
    • The top 1-3 samples in the standards may become bright yellow, while the bottom 1-2 samples may appear very pale yellow. Once again, we have a signal:noise issue. If you wait too long, more samples will become saturated (bright), and the results will be meaningless. If you don’t wait long enough, you may miss a positive but low result.
    • Use your best judgment! Ideally, look for a couple of your samples (not just the standards) to have developed some colour. However, note that some sample may not have measurable protein content (particularly supernatants). Feel free to ask the teaching faculty for advice.
  6. When your samples are ready, add 100 μL of Stop Solution (0.4 M NaOH). A member of the teaching faculty will take the plates to BPEC and read them in the absorbance plate reader at 420 nm.
  7. You can hang around and analyze your data today (see Part 1 of the Day 7 protocol), or wait until next time.

Part 2: Continue ImageJ analysis (optional)

Today you can finish any analysis that you did not get to on Day 5.

Prepare the following figures and paste them in your notebook: live/dead sample pictures; live/dead cell count table; RT-PCR image; RT-PCR intensity table; ELISA graphs; ELISA results table. There is no need to write formal captions, just brief (handwritten or typed) descriptions. (You probably will not have the ELISA data ready and analyzed until Day 7, depending on how long your plates take to develop.)

You should also write up a paragraph on today's talk page summarizing your results (morphology, viability, transcript, and protein analyses), highlighting both similarities and differences between results obtained for different culture conditions. This can help guide future iterations of this module.

Update: A lot of folks finished all their analysis on Day 5. If this is the case for you, and you and your partner already have a pretty solid idea that you have committed to for your presentation, you may want to have the Day 7 Part 2 cross-group discussion today instead.

For next time

  1. Your oral presentations of your research proposals will be given one week from today. Reconsult the specific directions for what you'll need as well as the more general guidelines for all oral presentations. You may find it helpful to prepare an outline of your presentation prior to filling in the slides and working out exactly what you will say: Recall that you will need to present
    • a brief project overview (1 slide)
    • sufficient background information for everyone to understand your proposal (1-3 slides)
    • a statement of the research problem and goals (1 slide)
    • project details and methods (3-5 slides)
    • predicted outcomes if everything goes according to plan and if nothing does (3-5 slides)
    • needed resources to complete the work (1 slide)
    • societal impact if all goes well (1 slide)

Suggested numbers of slides are listed here but the number may vary depending on the particulars of your proposal. You will have time to work on the presentation and ask questions about your work in lab next time.

Reagent List

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