The HuBMAP JumpStart program provides junior investigators the opportunity to undertake independent, scientific research projects within their existing labs. JumpStart award candidates and recipients are already working within HuBMAP-supported labs, and apply for these grants to help advance their career and develop their independence in the workplace. Their projects align with the overall goals of HuBMAP, but take a new direction from their existing work with their lab's Principal Investigator.
Three JumpStart grants were awarded in 2021 to support young researchers at Purdue University, Vanderbilt University, and Yale University. You can learn more about the awardees and their research projects below.
Hang Hu, Purdue University
Hang's project is entitled: Self-supervised Mass Spectrometry Imaging Clustering with Convolutional Neural Network and Contrastive Learning. He aims to develop a novel self-supervised learning approach for efficient classification of mass spectrometry imaging data. Using this tool, the goal is to be able to cluster more than 1000 ion images in half an hour without any manual user annotation. About the researcher:
I am a 4th year Ph.D. candidate in Dr. Julia Laskin's research group at Purdue University. I investigate nano-DESI mass spectrometry imaging (MSI) and participates in the Computational Interdisciplinary Graduate Program. I am interested in the application of machine learning, computer vision and lab automation for MSI. Outside the lab, I usually run 15 miles a week, and I enjoy cooking!
Angela Kruse, Vanderbilt University
Angela's project is entitled: 3-D Multimodal Analysis of Eye and Pancreas Blocks Using Light Sheet Microscopy and Imaging Mass Spectrometry. Here is Angela's description of her project:
As technology develops, scientists are able to study thousands of molecules such as proteins or lipids from increasingly small tissue samples. One technology used by HuBMAP scientists is imaging mass spectrometry (IMS) which can be used to create a map showing the location of molecules in thin tissue sections. These maps can help improve our understanding of human biology, but it can be challenging or impossible to relate the information from a small tissue sample to an intact organ. To address this challenge, I will combine IMS with another technology called light sheet microscopy (LSM). LSM can be used to visualize specific proteins in very thick pieces of tissue. Using LSM, I will make a 3-dimensional (3-D) map of several major structures such as veins and islets in thick blocks of pancreas and eye tissue. Next, I will divide these blocks into thin sections and use IMS to map the peptides and lipids in these 2-D samples. Finally, I will combine each data type to reconstruct the pancreas and eye tissue blocks with all the molecular information we can gain through IMS inside the 3-D map made by LSM. This study is expected to help us better understand how molecular data from small samples relates to an intact human organ. Adding this organ-level context can help future scientists use our data most effectively.
About the researcher:
Angela Kruse is a Postdoctoral Research Fellow in the Mass Spectrometry Research Center at Vanderbilt University. She received her B.S. in Genetics and Plant Biology from the University of California, Berkeley and her Ph.D. in Plant Pathology with a focus in Biochemistry from Cornell University. Her current research goal is to better understand the molecular environment of human retinal, lens, and pancreatic tissues using a combination of imaging mass spectrometry, proteomics, biochemistry, and bioinformatics. She hopes to spend her career applying and integrating cutting edge technologies to address important challenges facing our society and planet. When not in the lab, Angela enjoys hiking with her dog Ginger and tending to her overlarge collection of houseplants. She comes from a large family with six older siblings, and is a classical flute and piccolo player.
Yang Liu, Yale University
Yang's project is entitled: Spatial multi-omics profiling of human kidney tissue using DBiT-seq. The human kidney is a structurally complex organ composed of different cell types. To understand how the kidney functions, we need to know not only what cell types are there, but where they are located and how they interact with their neighbors and environments. This project will study the human kidney using a newly built spatial omics sequencing tool, and explore the molecular basis of kidney functions. Especially, it will further contrast the spatial biomolecular atlas of kidney in young and old adults to investigate the effect of aging. About the researcher:
Dr. Yang Liu is a third year Postdoc working at Dr. Rong Fan’s lab, interested in building novel tools for spatial omics sequencing. He developed a high spatial resolution multi-omics sequencing technique, named DBiT-seq, which can achieve near single cell spatial resolution (10 µm) sequencing of RNA and protein on the same tissue section. His ongoing work includes developing DBiT-seq V2.0, building 3D human healthy heart Atlas and studying development of human tumor tissues. During PhD training, he worked primarily as an analytical chemist and toxicologist, focusing on the developments of a variety of highly sensitive analytical methods for the quantification of post-translational modifications. He is also highly interested in applying cutting-edge bioinformatic tools to understand spatial omics data.