Communication at the Cellular Level: Discovery and Application

Cell-cell communication is essential to the functioning of all multicellular organisms, and understanding these critical processes can help solve current biomedical problems. As a demonstration of the utility of this approach, existing knowledge of the interactions between B cells and T cells in the B cell maturation process is used to create a novel model to tackle the longstanding problem of B cell epitope prediction. Despite decades of effort and advancements in experimental and computational techniques, this problem remains challenging, with available tools performing only marginally better than random guess. Strikingly, the incorporation of cell-cell communication information significantly enhances the prediction of linear B cell epitopes while also provides interesting mechanistic insights to the underlying biological processes. However, current knowledge of cell-cell communication remains relatively incomplete. Despite the usefulness of understanding such interactions, most research focuses on intracellular rather than intercellular processes, in part due to the relative difficulty in observing and manipulating cell-cell communication among diverse cells. To help address this issue, I present an innovative approach that leverages recent advancements in spatially resolved transcriptomics technologies and multiple-instance learning to enable high-throughput detection of intercellular communications. This new approach addresses a number of shortcomings of existing methods such as poor specificity, limited to certain types of interactions, reliance on existing, limited databases, and lack of consideration of complex, multiple-to-one interactions. Furthermore, I demonstrate that this new method enables biologically and clinically relevant discoveries using various cancer datasets. Overall, this work represents a notable step in advancing the quantification of cell to cell communication as well as its application to solve contemporary biomedical problems.

Author dc:creator

• Zhu, James Zhiren

Contributors dc:contributor

• Zhan, Xiaowei
• Koh, Andrew Y.
• Satterthwaite, Anne B.

• Cell Communication
• Gene Expression Profiling
• Single-Cell Analysis
• Transcriptome

Language dc:language

en

Identifier

1522122379

OAI identifier oai:identifier

oai:utswmed-ir.tdl.org:2152.5/10621