The human body is a key subject of research by scientists worldwide. A biomedical engineering research team led by Professor Kevin Tsia, programme director of the Biomedical Engineering Programme under the Faculty of Engineering of the University of Hong Kong (HKU), has created an all-in-one large-scale computational framework - StaVia- to unlock the vast information hidden in human cells.
Professor Tsia's team collaborated with Professor Joshua Ho and Professor Yuanhua Huang , both from School of Biomedical Sciences at the Li Ka Shing Faculty of Medicine of HKU (HKUMed). They successfully apply the tool in analysing the development process of zebrafish embryos – tracking the growth and development from a single cell into a complete organism. This study aids in understanding cellular growth and diseases. Despite the apparent differences between humans and zebrafish, a surprising number of similarities exist. In fact, 70% of human genes can also be found in zebrafish.
"StaVia's findings are significant because they allowed us to explore the entire development of zebrafish embryos, from 10 hour to 10 days fertilization, in detail for the first time. This includes previously overlooked cell types, providing new insights into how different cells form and develop, which could lead to better understanding of growth and development in other organisms, too. For examples, how does embryo develop its the nervous system (including the brain and spinal cord), the skin, and sensory organs (e.g., Eye, ears, and olfactory organ) It's a one-of-its-kind method allowing us to map out the timeline of development at high resolution," said Professor Kevin Tsia from the Department of Electrical and Electronic Engineering, who is also the Programme Director of the Faculty of Engineering's Biomedical Engineering Programme.
Significance in developmental biology research
The key developer of StaVia, Dr. Shobana V Stassen, explained, "Another important and unique feature of StaVia is that it represents a new frontier in the field called "spatiotemporal omics" from which we can analyze spatial information of physical tissue structure, omics data of cells therein and their time evolution all simultaneously. In StaVia, we could craft an intuitive "metro-map" for us to analyze the temporal trajectory and spatial habitats of cells in tissues or organs."
Comprising rich information of single cells at high precision, omics data are crucial for probing the properties of cells, and tracking their transformation to gauge the disease progression. The immense value of measuring omics data of cells has been driving a number of global research initiatives (including US, Europe and Asia) to create "cell atlases" of different parts of the human body. These detailed maps help scientists in studying tissues and organs in extraordinary detail - transforming the understanding of how cells develop and function. However, as the data size and diversity of these atlases increase, analysing them becomes more challenging. The complexity and size make it difficult to clearly track how different cell types form and change over time, and even visualising this information is also a struggle
"StaVia synergises multi-faceted single-cell omics data, regardless its complexity, to maps the intricate paths the cells take as they develop and change in different biological processes, including embryo development. Our tool works very well with large-scale cell atlases, maintaining all the intricate details embedded in omics data, making it easy and intuitive for scientists to understand complex cell behaviours over time and space," said Professor Tsia.
"It can discover elusive cell lineages and rare cell fates in a variety of biological processes that can hardly be discovered by other methods, providing hints on how diseases evolve."
His team's latest achievement has been published in an article entitled "StaVia: spatially and temporally aware cartography with higher-order random walks for cell atlases" in the open-access journal, Genome Biology.
Advancing fundamental biological discovery
Professor Tsia's colleagues at HKUMed have already adopted StaVia in their cell-related research. "Cells matter because they are the fundamental unit of life. When you are sick, your cells are the source of the problem, and that's how I became interested in studying cells. If you want to know more about something, you should start with the root cause," said Professor Tsia.
Research groups around the world are trying to understand how human health and disease evolve at the cell level. "It may sound simple, seem like information carried in textbooks. But in fact, all along no one has had a clear understanding of the matter," said Professor Tsia.
With vast unknowns about the cell atlases in the human body, StaVia can be applied in basic biological or fundamental research, generating new insights and knowledge for biologists or biomedical scientists. Pertinent discoveries could help address global issues such as ageing.
"Brain disease is another hot topic. There is research focusing on how human brain cells and their omics changed over time, say from 50 to 80 years old. The overall goal is to identify signature and key drivers of aging, and eventually to develop drugs that could treat aging-related brain diseases," said Professor Tsia, whose team is also involved in joint projects on similar topics with the universities in US.
He describes StaVia as the third generation of the computational tool he and his team, including doctoral students and post-docs, had developed. "We began jumping into the area of omics back in 2019," he recalled.
Currently he is continuing collaborations with HKUMed on studying the progress of cancer using StaVia, tracking the evolution of cells from the early stage to the late stage of the disease.
For details about the research article, please visit:
https://genomebiology.biomedcentral.com/articles/10.1186/s13059-024-03347-y
About Professor Kevin Tsia
Kevin Tsia is currently a Professor in the Department of Electrical and Electronic Engineering and the Programme Director of the Biomedical Engineering Program at The University of Hong Kong. His research interest covers a broad range of subject matters including ultra-fast optical imaging for imaging flow cytometry and high-speed in-vivo brain imaging, bioinformatics approaches for single-cell analysis. He is SPIE Fellow, and the HK Research Grants Council (RGC) Research Fellow (2020). He received Early Career Award 2012-2013 by RGC in Hong Kong. He also received the Outstanding Young Research Award 2015 at HKU as well as 14th Chinese Science and Technology Award for Young Scientists in 2016. He holds 11 granted and pending US patents on ultrafast optical imaging technologies. He is a co-founder of start-up company commercializing the high-speed microscopy technology for cancer screening and treatment monitoring applications. It was among the top 10 finalists in Falling Walls Venture in 2019, and awarded as Google Cloud Startup in 2024.
