Technology developed at the Buck unravels cellular mechanisms behind diseases and natural aging

An analysis tool developed during a professor’s graduate studies in ‘98 now serves as the foundation for transformative projects at The Buck.

In 1998, while a graduate student in Budapest, Buck Institute Associate Research Professor Akos Gerencser, MD, PhD, began development of computer software to measure properties of mitochondria. Today, Dr. Gerencser and other Buck professors continue to use this state-of-the-art technology, coined Image Analyst, to unravel cellular changes that take place during both aging and disease progression.  This mechanistic understanding can guide development of targeted therapies to reverse morbidities associated with aging and disease.

As the head of the Morphology and Imaging Core, Dr. Gerencser oversees a team focused on automating and streamlining data analysis at the Buck. Dr. Gerencser’s team uses Image Analyst and other technologies to provide microscopic imaging and bioenergetic analyses—which inform on how a cell uses energy—to Buck researchers and external users at UCSF and Stanford. Revolutionizing analysis in the age-related disease field and beyond, Dr. Gerencser has been cited in over 7,000 publications, having published and made his technologies commercially available.

Dr. Gerencser’s Image Analyst technology has a unique ability to track changes in cell function during disease and aging,  while interrogating the cellular components contributing to cell function. To illustrate, imagine a normally functioning cell as an orchestra, where each instrument represents a different biological component that works in harmony to create a symphony. Disease and aging cause disruptions to cell components, similar to instruments playing out of tune. These small disruptions accumulate, altering the function of the cell, as an off-tune instrument similarly disturbs the harmony of a song. 

Similar to a conductor monitoring the key of individual instruments to understand the source of an off-tune performance, Image Analyst analyzes properties of cell components to understand how they disturb normal cellular function, while measuring cellular function. This is done through real-time live cell imaging and quantitative analysis. Importantly, machine learning analyzes images to discover minute details which would not be possible by the human eye. 

Dr. Gerencser’s research focuses on using Image Analyst to study the mechanisms behind irregular insulin secretion from pancreatic beta cells in type II diabetes. He investigates mitochondrial activity as a key indicator of cellular function, since mitochondria, the cell’s "powerhouses”, supply the energy to fuel all cellular functions. Mitochondrial dysfunction is common in chronic diseases, including diabetes, and studying mitochondrial activity provides insight on pancreatic beta cell function and mechanisms causing type II diabetes. 

With Image Analyst, Dr. Gerencser became the first to test human-donated pancreatic beta cell function through mitochondrial activity measurement. Unlike other assays that produce difficult-to-interpret results, Image Analyst uses a mathematical model to provide clear measurements of mitochondrial activity. In 2015, leveraging this technology, Dr. Gerencser discovered mitochondria’s intricate role in insulin secretion and identified malfunctioning mitochondria as a cause of irregular insulin secretion in type II diabetes.

Currently, Dr. Gerencser studies transcriptomics – the analysis of which genes are turned on or off – in malfunctioning pancreatic beta cells to uncover the causes of mitochondrial dysfunction and irregular cell function in type II diabetes. With further mechanistic understanding of why cells behave differently in type II diabetes, therapeutics can be developed to reverse irregular insulin secretion in type II diabetes.

With the support of a grant from the Hevolution Foundation awarded to the Buck last year, Dr. Gerencser is also using Image Analyst technology to define an aging phenotype, or observable property, characteristic to all cells as they age. This research is some of the first of its kind, where Image Analyst and new machinery funded by the grant allow for high throughput screening—or rapid testing of thousands of samples—of observable characteristics of cells as they age. With further understanding of what happens to cells as they age, therapeutics can be developed to target aging.

Dr. Gerencser finds satisfaction in his continuously-evolving research, and finds his work exciting since, “new projects are constantly coming up, and we can work on whatever is on the cutting edge.” The manifold applications of Image Analyst allow Dr. Gerencser to engage in first-of-their-kind projects, with applications spanning from type II diabetes to aging.