The most complex problem I have ever worked on has been my research effort to answer a seemingly simple question; how much metabolic energy (ATP) does a cell expend during cell migration (motility/crawling). Many tissues in our body are inherently motile. Cells can flow like a liquid, crawl through blood vessels, and even migrate together like a flock of birds. This process, known as collective cell migration, is vital to our understanding of how cells from a primary-tumor metastasize to a distant location in the body, among other pathological conditions found in the lung and during embryonic development. I sought to develop a project which measures the amount of metabolic energy a cell uses during this cell migration.
Answering this question involves integrating procedures in molecular biology to measure the cell metabolic state (using various biomarkers) together with techniques in experimental biophysics to measure cell mechanics and migration (such as traction stresses, morphology/shape analysis, and cell tracking/dynamics). The state-of-art techniques precluded measuring all of these biological and physical properties simultaneously and in such a manner that spatial correlations could be used to answer the question. As such, my task was to develop, troubleshoot, and execute experimental techniques that concurrently allow all of these biophysical quantities to be measured with spatial resolution (mapping), and to produce a multi-dimensional dataset to correlate cell metabolism with cell mechanics.
To act on this task, I approached the project by breaking it into piecemeal components consisting of major topical research areas such as integrating and proving efficacy of cell metabolic biomarkers, conducting cell force measurements, optical imaging for cell tracking, and final data analysis pipelines for each data-type. The complexity of this project was in concurrently developing the solutions for each of the major topical areas such that they could be integrated into a single format. To broach this complexity, I designed overarching experimental requirements to apply to each topical area such as the parameters of the assay timeline, design features/format of the integrated experimental device, spectral requirements for multi-channel imaging, biological constraints dictated by cell health and viability, and data format requirements. The overarching principles guided the development of each research area and ensured that solutions to each topical area would conform with the overall project goals and result in successful integration of each major experimental component. This project management technique required a broad-view of the overall project goals, cross-contextual awareness during decision making, and down-in-the-weeds details.
In addition to the cross-discipline technical complexity, this project also required management of multiple personnel who were responsible for accomplishing sub-project aims such as biomarker transfection, coding cell tracking image analysis, and fabricating experimental devices. As such, I gained experience in multiple management styles as needed for each of the personnel I worked with, such as utilizing visionary management, servant-leadership style, or directive management. This team approach ensured that each piece of the complex project moved toward completion in lock-step.
Finally, this complex project resulted in the generation of the largest biophysical dataset ever measured, which includes simultaneous tracking of cell mechanical, dynamical, morphological, and metabolic information for millions of cells. We discovered that during collective cell migration, cell metabolism increases, and cells switch to an inefficient form of metabolism called glycolysis. These results are basic knowledge regarding cell mechano-bioenergetics and may guide further development of therapeutics that target cell migratory processes. This project has yielded a high-impact result that has been accepted for publication in Scientific Reports. Furthermore, this project was a collaborative effort that integrated developers, mathematicians, physicists, biologists, and medical doctors, including advancing the career of multiple undergraduate researchers. Nothing has been more gratifying than seeing the hard work from our team effort result in such terrific scientific findings. I am proud to have led this project and am excited to work on research and development opportunities of similar or greater complexity!