Blyth, E. | Search bioRxiv

bioRxiv2021

Immune Cell Profiling Reveals MAIT and Effector Memory CD4+ T Cell Recovery Link to Control of Cytomegalovirus Reactivation after Stem Cell Transplant

Human cytomegalovirus (HCMV) reactivation is a major opportunistic infection after allogeneic haematopoietic stem cell transplantation and has a complex relationship with post-transplant immune reconstitution. Here, we used mass cytometry to comprehensively define global patterns of innate and adaptive immune cell reconstitution at key phases of HCMV reactivation (before detection, initial detection, peak and near resolution) in the first 100 days post-transplant. In addition to identifying patterns of immune reconstitution in those with or without HCMV reactivation, we found mucosal-associated invariant T (MAIT) cell levels at the initial detection of HCMV DNAemia distinguished patients who subsequently developed low-level versus high-level HCMV reactivation. In addition, early recovery of effector-memory CD4+ T cells distinguished low-level and high-level reactivation. Our data describe distinct immune signatures that emerged with HCMV reactivation post-HSCT, and highlight MAIT cell levels at the initial detection of reactivation as a potential prognostic marker to guide clinical decisions regarding pre-emptive therapy.

immunology↗

bioRxiv2021

Identifying cellular-to-phenotype associations by elucidating hierarchical relationships in high-dimensional cytometry data

High-throughput single cell technologies hold the promise of discovering novel cellular relationships with disease. However, analytical workflows constructed for these technologies to associate cell proportions with disease often employ unsupervised clustering techniques that overlook the valuable hierarchical structures that have been used to define cell types. We present treekoR, a framework that empirically recapitulates these structures, facilitating multiple quantifications and comparisons of cell type proportions. Our results from twelve case studies reinforce the importance of quantifying proportions relative to parent populations in the analyses of cytometry data -- as failing to do so can lead to missing important biological insights.

bioinformatics↗