Choosing a Topic and Writing a Proposal

Your should try to design an experiment that will provide insight into some issue involving transport through a cell membrane. The topic could be

biological: For example, you could test if putting a cell in a hypotonic solution kills the cell.
physical: For example, you could test if osmotic flow of water through a cell membrane is truly colligative.
engineering: For example, you could develop software to automatically measure the diameters of cells from video images in real time.

Good projects balance risk and reward. The problem should be easy enough that you are likely to get good results. But it should also be challenging enough that something interesting (i.e., unexpected) is likely to occur. A good way to achieve this balance is to propose a relatively straightforward experiment but then keep your eyes open. Results are rarely exactly what one expects. So if you don't notice something interesting about your results, you probably aren't looking at the results very critically.

Projects can involve any of the topics discussed above or a topic of your own creation. A well thought-out project, whether based on one of the ones above or not, will usually promote better data collection, better report writing, and ultimately a better grade. If you create a novel project, you must obtain any supplies or equipment that is not part of the standard laboratory setup described in Methods. For example, studying the diffusivity of some large biological molecule like a drug molecule might be an interesting project. However, you are responsible for obtaining the biological molecule and determining a method to measure its concentration.

When you choose your topic, remember that your experiment should take only a few hours to complete. Think through how many measurements you will need to make and how long it will take to make each measurement.

One common way to develop a well-defined proposal is to formulate a specific and testable hypothesis, and center your project on that hypothesis (so-called hypothesis-driven projects). Avoid vague hypotheses, such as: "I would like to understand how concentration affects the diffusivity of dyes." Instead choose a more narrrowly focused hypothesis, such as: "Increasing the concentration of dye to near saturation values will decrease the diffusivity of the dye." This more-focused hypothesis is testable: it can be true or false. If you form a clear hypothesis, you will be able to plan a logical set of measurements to test the hypothesis, and you will be able to come to a clear conclusion when you write your report.

Alternatively, you can focus your project on developing a new way of measuring interesting phenomena, or finding ways to analyze data much more efficiently, or seeking out ways to enhance the accuracy of measurement. These are often called as technology-development projects, and you usually start with an idea (instead of hypothesis) and you experimentally verify that your idea on a certain measurement / analysis technique is better than common ones.

When you do your experiment, you may get unexpected results. For example, you may have planned to measure effects of glucose on the diffusivity of a dye. However, you may find that the added glucose affects the velocity of flow in the chambers. You should explore unexpected results and try to understand their bases. Your aim should be not simply to reject or accept your hypothesis, but to develop insight into the phenomena. For example, perhaps changes in velocity result from changes in viscosity and changes in viscosity of the medium affect your estimate of diffusivity. If so, the unanticipated changes in velocity could be the key to understanding the measured changes in diffusivity.

Keep in mind that this is an experimental, open-ended project. It is highly possible for a group to get started based on a certain hypothesis, then to discover some unexpected results which could lead to proving another hypothesis, not the original one. Or they might realize / discover a new, better way of analyzing the same data, and the project could turn into a technology-development. Or they could discover that one can achieve more accurate measurement by controlling an often-overlooked experimental variable. Your goal is to make self-consistent measurements and provide a rational explanation for those measurements, not to validate or refute a particular theoretical model. Theoretical analyses may support your experimental findings. However, your grade will be based primarily on the reliability of your data and the plausibility of your explanations.

Example Topics

This section lists several topics that you could explore as your project. You may choose one of these or you can construct an entirely new one. The descriptions given here are incomplete, and really just serve as starting points. Your plan should be more complete, by adding detailed plan of work. Keep it simple so that you can complete the work, including some preliminary plotting of results and thinking about interpretation within a several-hour lab session. You may also want time to check your interpretation by taking additional measurements.

Population measurements do not accurately reflect osmotic behavior. Here we will track individual cells as they migrate down the channel and are subjected to a DI water shock. We will take volume measurements on the cells at the beginning and end of the channel, and repeat for at least 20 cells. Then we will analyze the data either on a cell-by-cell basis or by grouping the data into "before" and "after" populations.
Increasing solution density will increase cell velocity. Here we will mix the cell solution with a solution of higher density in the channel. As the two solutions interdiffuse, the solution density will increase and the cells will be levitated off the ground. This will cause them to migrate faster down the channel. By measuring the migration velocity as a function of distance down the channel, we will be able to calculate the cell density.
Larger cells roll faster Here we will record the velocity of rolling cells as a function of cell size. Larger cells, since their centers are further from the substrate, should feel a stronger flow drag and roll faster.
Cells at the middle of channel move at the centerline velocity Here we will use a density-balanced solution to prevent cells from settling onto the substrate. We will then measure the velocity of the cells along the centerline of the channel, and compare that with the centerline flow velocity measured using neutrally buoyant beads.
"Hypothesis-driven" projects
Osmotic pressure vs. osmolar concentration difference
Motivation: The osmotic pressure will depend on the difference in salt concentration of the two streams. Therefore, the speed of cell morphology changes induced by an osmotic 'shock' will be proportional to the concentration difference.
Hypothesis: A cell will change it shape faster when the magnitude of the osmotic shock is increased.
Experiment: Compare the size of the cells at a certain location from the merging point, as a function of salt concentration difference.
Is osmosis truly colligative?
Motivation: The osmotic pressure will depend only on the difference in solute concentration of the two streams. It should not matter which kind of molecules (solutes) are used, as long as their osmolar concentrations are the same.
Hypothesis: Osmotic pressure induced changes of cells should not depend on the species of solute.
Experiment: Pick a number of solutes that are quite different in size and other properties (such as BSA and salt). Measure and compare the osmosis-induced cell shape changes to confirm or disapprove the colligative nature of osmosis.
Is osmotic response of cells the same for live and dead cells?
Motivation: One of the cell functions is homeostasis, which means cells want to maintain their status as much as possible. Therefore, dead cells will have different osmotic response compared with live cells.
Hypothesis: Live cells will have smaller osmotic response compared with dead cells.
Experiment: Prepare two populations of cells (live and dead) by heating. Give them the same osmotic shock in the microfluidic device. Compare the response induced in live cells with that of dead cells.
Will the osmotic response of a cell be the same independent for fast diffusing substances such as alcohol?
Motivation: Alcohols are known to be dissolved well in lipid. Therefore, diffusive transport might occur as well as osmotic response when a cell is given a osmotic shock caused by alcohols.
Hypothesis: When alcohols are used as a solute, osmotic response of a cell would be small than the case of using other, fat-insoluble solutes.
Experiment: Give cells the same osmotic shock (with same osmolarity) in the microfluidic device, but with two different solute (alcohol and KCl, for example) Compare the response induced in two cases.
Cells may be able to expand well, but might not be able to shrink.
Motivation: It is known that there are intracellular matrix which holds the cell membrane to a 3D structure, maintaining the cell shapes. If so, cell might be able to swell rather freely, but might not be able to shrink that much even under the osmotic shock.
Hypothesis: Osmotic response of cells are not following Van't Hoff's law when cells are allowed to shrink, not swell.
Experiment: Give cells the osmotic shock with higher and lower osmolarity compared with cell's natural salinity. Compare the osmotic responses in both cases with the prediction of Vant Hoff's law.
Analysis of cell size
Motivation: A typical osmotic swelling experiment can generate a large amount of video data with many cells moving. How should one analyze these data to get the most information out?
Idea : By (automated) image processing, one could develop a procedure for data analysis for osmosis experiment that is much faster and more accurate.
Method: Develop a procedure of data analysis by comparing successive images in video data, and compare the effectiveness of data analysis with the conventional counting methods.