Relative effect size-based profiles as an alternative to differentiation analysis in multi-species single-cell transcriptional studies.

Combining data from experiments on multispecies studies provides invaluable contributions to the understanding of basic disease mechanisms and pathophysiology of pathogens crossing species boundaries. The task of multispecies gene expression analysis, however, is often challenging given annotation inconsistencies and in cases of small sample sizes due to bias caused by batch effects. In this work we aim to demonstrate that an alternative approach to standard differential expression analysis in single cell RNA-sequencing (scRNA-seq) based on effect size profiles is suitable for the fusion of data from small samples and multiple organisms. The analysis pipeline is based on effect size metric profiles of samples in specific cell clusters. The effect size substitutes standard differentiation analyses based on p-values and profiles identified based on these effect size metrics serve as a tool to link cell type clusters between the studied organisms. The algorithms were tested on published scRNA-seq data sets derived from several species and subsequently validated on own data from human and bovine peripheral blood mononuclear cells stimulated with Mycobacterium tuberculosis. Correlation of the effect size profiles between clusters allowed for the linkage of human and bovine cell types. Moreover, effect size ratios were used to identify differentially regulated genes in control and stimulated samples. The genes identified through effect size profiling were confirmed experimentally using qPCR. We demonstrate that in situations where batch effects dominate cell type variation in single cell small sample size multispecies studies, effect size profiling is a valid alternative to traditional statistical inference techniques.

Optimized flow cytometry protocol for dihydrorhodamine 123-based detection of reactive oxygen species in leukocyte subpopulations in whole blood.

Reactive oxygen species (ROS) and the ability of immune cells to mount an oxidative burst represent an important defense during microbial invasion, but is also recognized for playing a significant role in the progression of inflammatory disorders and disease. Although neutrophils produce the strongest ROS-response, other leukocytes and their cell subsets could play a significant role. Isolation of specific cells for determining their ROS-response can affect their functionality and is laborious or hard to replicate in different settings. We have therefore established a whole blood assay, that only requires 100 µL heparinized blood and utilizes the dihydrorhodamine (DHR) 123 ROS-probe combined with cell surface antibody staining for the specific detection of ROS in several subsets of cells simultaneously using flow cytometry. Although the flow markers chosen are interchangeable with other direct conjugated and cell specific antibodies depending on the research question, we focused on neutrophils (SSChighCD16brightHLA-DRneg/low), eosinophils (SSChighCD16lowHLA-DRlow/negCD193positiveCD125positive) and monocyte subsets (SSCintermediateHLA-DRhighCD14low-positiveCD16negative-positive). As a RBC-lysis reagent we compared BD FACS Lysis Solution to the in-house prepared ammonium-chloride­potassium based ACK Lysis Buffer, that does not fix or permeabilize the immune cells. We find that ACK-lysis of stimulated and stained samples results in superior surface staining, decreased loss of cell subsets, and enhanced resolution of the DHR-signal. Compared to the other cells analyzed in healthy blood donors, neutrophils responded with the highest ROS-response to all tested stimuli (fMLP (low stimuli), E. coli, and PMA (high stimuli)), where eosinophils and the three monocyte subsets also showed an extensive ROS-response when stimulated with E. coli or PMA. Our assay provides the possibility for researchers to examine the ROS-response of specific cell subsets in specific patient groups ex vivo and could also allow the analysis of pharmacological intervention studies targeting ROS, which ultimately can advance the field of immunological research.