Collaborative Research: EAGER: Exploring beyond visualization: Data sonification of bacterial chemotaxis patterns

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

In this Era of Big Data an unprecedented amount of information is being collected at rates that are overwhelming researchers' capacity to process data in meaningful ways. Converting streams of numbers into graphical representations has proven to be useful over the past three decades to identify trends in complex data sets such as weather patterns, stock market fluctuations, and flu epidemics. While visualization is a powerful approach to data analysis, not all data are amenable to visualization. Sonification, the mapping of information to sound, is an alternative method for extracting useful information from visually chaotic data. One familiar example of data sonification is a Geiger counter that converts invisible gamma radiation to an audible frequency of clicks. This project demonstrates the utility of sonification in a study of how microbes swim toward nutrients that are critical for their survival. The goal is to promote more widespread use of sonification to analyze big data within the biological research community. Sonification of data can also increase public scientific literacy and public engagement with science and technology. As demonstrated by the catchy Higgs Boson tune, sonified data made the discovery of subatomic particles more accessible to the public. Sound and music are used in this project to provide a medium through which to engage elementary school-age children in a welcoming manner about the excitement of science. Another notable aspect is that data sonification provides a convenient platform to engage sight-impaired individuals in research. The project brings together expertise in biological systems engineering and digital music composition that provide diverse perspectives for cross-training student research assistants. In this project sonification is used to detect changes in the swimming patterns of microorganisms upon exposure to a chemical stimulus (i.e. chemotaxis). When examining a population of swimming microbes through a microscope the movement appears chaotic, making subtle changes in the paths of individual organisms impossible to discern in real time. By mapping visual images to the frequency domain in real-time one can transform the chaotic visual motion to discernible differences in auditory sounds. The specific project objectives are to: (1) identify the features of bacterial swimming motion that are detected in sonified data; (2) optimize video microscopy settings and video filters to enhance the signal-to-noise ratio of the data collected; (3) sonify data in real time to allow simultaneous audio and visual input to an observer; (4) evaluate the robustness of data sonification algorithms for bacteria that have different swimming behaviors; and (5) screen microbes for chemotaxis beyond the training set to evaluate the success of the sonification process. One outcome of this work will be a platform to generate sonified data in real-time that is synchronous with visual observations to allow high-throughput screening of chemotactic responses for various species to different chemoeffectors over a range of concentrations. Another, and perhaps more impactful outcome, will be to significantly expand the tools that biological scientists have at their disposal to identify patterns in complex data that they collect. This award is jointly funded by the Systems and Synthetic Biology Cluster and the Cellular and Dynamics Cluster in the Division of Molecular and Cellular Biology. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.