Many factors affect light emission in bioluminescence imaging (BLI), which is why creating a kinetic curve is so important for experimental accuracy and reproducibility. But what is a kinetic curve? What factors impact your signal? How do you generate a kinetic curve? Keep reading to find all your answers here, or use the content list to navigate to exactly what information you’re looking for.


In This Article:

What is an enzymatic kinetic curve?

Michaelis-Menten equation and general enzymatic kinetic curve.

What is a kinetic curve in bioluminescence imaging?

Why a kinetic curve is essential for bioluminescence imaging

What factors impact bioluminescent signaling?

How to generate a kinetic curve for bioluminescence imaging

1.For IP or SQ Injection:

2.For IV Injection:

3.Image your subject

4.Choose your time point

References


What is an enzymatic kinetic curve?

An enzymatic kinetic curve is a way of studying the rate of an enzymatic reaction given changes in components of a reaction. Usually those changes have to do with substrate concentration.

The values use the Michaelis-Menten equation and are plotted on a chart where the Y-axis represents the velocity of the reaction and the X-axis represents substrate reaction (Atkins Lab, n.d.).


Michaelis-Menten equation and general enzymatic kinetic curve


Michaelis-Menten equation and general enzymatic kinetic curve - the equation for an enzymatic reaction kinetic curve


Vmax is the maximum velocity of the system when the substrate is at maximum concentration. [S] is substrate concentration. Km is substrate concentration when the velocity of the enzyme reaction is at ½ of Vmax.


Michaelis-Menten enzymatic kinetic curve illustrated example showing substrate concentration on the X axis and reaction velocity on the Y axis.


What is a kinetic curve in bioluminescence imaging?

A kinetic curve for luciferase activity within your experimental model is used to identify the time point at which peak emission and signal plateau occurs. You can consider the kinetic curve of luciferin-luciferase as a “time-signal intensity curve (Yang et al., 2016).” Data from a kinetic curve help researchers determine the best time point, after substrate injection, to image their subject.

In bioluminescence imaging, the kinetic curve is generated by taking a series of measurements that measure signal intensity. These measurements occur over the course of multiple time points, plotting intensity in relation to time after injection.

While the luciferin-luciferase reaction is an enzymatic reaction, the kinetic curve used for bioluminescence imaging looks different from the plot generated by the Michaelis-Menten equation.

Rather than plotting reaction velocity and substrate concentration, the curve for light emission kinetics in bioluminescence imaging plots light emission, in terms of relative light units, on the Y-axis and time, in minutes, on the X-axis.


Bioluminescent kinetic curve illustrated example showing relative light units on the Y axis and time after injection on the X axis. Bioluminscent kinetic curve ensure experimental reproducibilty by finding the best time point to image a sample


Some imaging acquisition software programs may plot kinetics based on percentage of light intensity versus time, where light intensity is represented on the Y-axis.

Ultimately, kinetic curves for bioluminescence imaging provides a way to visually identify the period after substrate injection where peak emission and plateau occurs. This insight informs researchers about the most optimal time point to image their subjects after substrate injection.


Why a kinetic curve is essential for bioluminescence imaging

So many factors can affect the kinetics of a bioluminescent signal. Because each experiment has its own unique setup (tumor location, size, experimental application, model used, etc.), it is critical for reproducibility and accuracy to identify peak signaling time.


What factors impact bioluminescent signaling?

Many factors influence bioluminescent emissions. Below are listed some considerations. But don’t let this intimidate you during your experiment. Taking it one step at a time, and conducting a kinetic curve when anything changes will ensure optimization, reproducibility and overall BLI success (Sim, Bibee, Wickline, & Sept, 2011), (Sadikot & Blackwell, 2005).

  • Tumor location – for instance emission could take longer if you’re imaging a tumor in the brain.
  • Tumor size
  • Cell lines used in the xenograft
  • Luciferin delivery method
  • Specific animal model
  • Therapeutic intervention
  • Tissue depth
  • Substrate used (modified)
  • Scar tissue
  • Tumor geometry


How to generate a kinetic curve for bioluminescence imaging

Generating your kinetic curve depends a lot on the system you’re using for image acquisition as well as the software you’re using for analysis.

Some instruments have sequence programs that can be set in order to generate images for a kinetic curve, which can be further analyzed using imaging software.

Our In Vivo Luciferin Handbook details methods for determining a kinetic curve along with a lot of other helpful information and protocols for in vivo imaging. However, we will provide those instructions here as well.

To generate a kinetic curve for luciferase activity in your model:

Inject luciferin via one of the proposed methods listed below (Intraperitoneal, Intravenous, or Subcutaneous). If you need to sedate the animals before injection, be aware that it may slightly extend the kinetics (peak luciferase expression time). The biodistribution of luciferin may also be different depending on the route of administration.


1. For IP or SQ Injection:

  • If you are able to inject into animals that are still awake, wait three minutes, then sedate by your method of choice (gas or injectable anesthesia). See Appendix for anesthesia/analgesia drugs and dosages in rats and mice.
  • Place sedated animals in imaging chamber and take the first image approximately five minutes post luciferin injection.


2. For IV Injection:

  • Place sedated animals in imaging chamber and take the first image within first two minutes post luciferin injection.


3. Image your subject

Continue to take images every 5-10 minutes up to about 40-60 minutes for IP or SQ injected models (for IV injected models: image every 1-5 minutes up to 20-30 minutes) to generate a kinetic curve for luciferase expression in your model. (Most injectable anesthesia will last 20-30 minutes and might require an additional dose for a full kinetic curve study!)


4. Choose your time point

Choose the best time point to image your model from your kinetic curve. Many models reach their peak signal time approximately 10-20 minutes post IP or SQ luciferin injection and 2-5 minutes post IV luciferin injection.



References

Atkins Lab. (n.d.). Michaelis-Menten Kinetics and Briggs-Haldane Kinetics. Retrieved September 24, 2020, from https://depts.washington.edu/wmatkins/kinetics/mic...

Baert, A. (Ed.). (1970, January 01). Time‐signal Intensity Curve (TIC). Retrieved September 24, 2020, from https://link.springer.com/referenceworkentry/10.10...

Burgos, J., Rosol, M., Moats, R., Khankaldyyan, V., Kohn, D., Nelson, M., & Laug, W. (2003, June). Time course of bioluminescent signal in orthotopic and heterotopic brain tumors in nude mice. Retrieved September 24, 2020, from https://www.ncbi.nlm.nih.gov/pubmed/12813886

Dai, Y., Chen, D., Wang, G., Yin, J., Zhan, Y., Wu, K., . . . Chen, X. (2020, February). Kinetic modeling and analysis of dynamic bioluminescence imaging of substrates administered by intraperitoneal injection. Retrieved September 24, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC70632...

Inoue, Y., Kiryu, S., Watanabe, M., Tojo, A., & Ohtomo, K. (2010). Timing of imaging after d-luciferin injection affects the longitudinal assessment of tumor growth using in vivo bioluminescence imaging. Retrieved September 24, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC29104...

Sadikot, R., & Blackwell, T. (2005). Bioluminescence imaging. Retrieved September 21, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC27133...

Sim, H., Bibee, K., Wickline, S., & Sept, D. (2011, February 1). Pharmacokinetic modeling of tumor bioluminescence implicates efflux, and not influx, as the bigger hurdle in cancer drug therapy. Retrieved September 24, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC30737...

Yang, S., Li, F., Chen, J., Zhang, G., Liao, Y., & Huang, T. (2016, April 7). Kinetic Curve Type Assessment for Classification of Breast Lesions Using Dynamic Contrast-Enhanced MR Imaging. Retrieved September 24, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC48244...