Parallel single-b cell transcriptomics to elucidate swine b-cell repertoire

Authors: BRAM, STANLEY - University Of Illinois; LINDSEY, GRAEME - University Of Illinois; DRNEVICH, JENNY - University Of Illinois; XU, FANGXIU - University Of Illinois; WOZNIACK, MARCIN - University Of Illinois; Medina, Gisselle; MEHTA, ANGAD - University Of Illinois

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/19/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Pork is the most popular meat around the world, placing the health of pigs as a critical factor for both the world economy and food security. Infectious diseases in pigs not only threaten these sectors but also raise zoonotic concerns because pigs can harbor viruses that affect both animals and people, serving as mixing vessels and creating new viral strains. Designing vaccines for diseases that affect pigs has been challenging, mainly because we do not understand the pig immune system. Understanding how pigs fight off diseases could help improve the design of vaccines. In this study, we utilize computational tools to evaluate pig B cells repertoire at the single cell level and elucidate via transcriptomics the type of antibodies that different B cells can generate.

Technical Abstract: Pork is the most widely consumed meat on the planet, placing swine health as a critical factor for both the world economy and the food industry. Infectious diseases in pigs not only threaten these sectors but also raise zoonotic concerns, as pigs can act as “mixing vessels” for several animals and human viruses and can lead to the emergence of new viruses capable of infecting humans. Several efforts are ongoing to develop swine vaccines, albeit with limited success. This has been largely attributed to the complex nature of swine infections and incomplete understanding of the swine immune responses. Additionally, pig has been suggested to be a good experimental model to study human influenza. Despite the significant importance of studying swine immunology for model studies and the crucial need to develop better swine vaccines, there is still very limited information on the response of the swine adaptive immune system to several emerging pathogens. Particularly, very little is known about the swine B cell repertoire upon infection. Understanding the B cell repertoire is especially crucial towards designing better vaccines and can also provide insights into developing new diagnostic agents. Here, we developed methods for parallel sequencing of the global and immunoglobulin-specific transcriptomes from single swine B cells (up to 10,000 cells), followed by developing data analyses and machine learning pipeline that allows us to elucidate the swine B cell repertoire and get paired antibody sequences. We believe that these approaches will have significant implications in swine diseases, particularly in the context of swine mediated zoonosis and swine and human vaccine development.