Direct comparison of mass cytometry and single-cell RNA sequencing of human peripheral blood mononuclear cells.

Single-cell methods offer a high-resolution approach for characterizing cell populations. Many studies rely on single-cell transcriptomics to draw conclusions regarding cell state and behavior, with the underlying assumption that transcriptomic readouts largely parallel their protein counterparts and subsequent activity. However, the relationship between transcriptomic and proteomic measurements is imprecise, and thus datasets that probe the extent of their concordance will be useful to refine such conclusions. Additionally, novel single-cell analysis tools often lack appropriate gold standard datasets for the purposes of assessment. Integrative (combining the two data modalities) and predictive (using one modality to improve results from the other) approaches in particular, would benefit from transcriptomic and proteomic data from the same sample of cells. For these reasons, we performed single-cell RNA sequencing, mass cytometry, and flow cytometry on a split-sample of human peripheral blood mononuclear cells. We directly compare the proportions of specific cell types resolved by each technique, and further describe the extent to which protein and mRNA measurements correlate within distinct cell types.

BMP-6 promotes type 2 immune response during enhancement of rat mandibular bone defect healing.

Introduction: Bone morphogenetic proteins (BMPs) are used as key therapeutic agents for the treatment of difficult fractures. While their effects on osteoprogenitors are known, little is known about their effects on the immune system. Methods: We used permutations of BMP-6 (B), vascular endothelial growth factor (V), and Hedgehog signaling pathway activator smoothened agonist (S), to treat a rat mandibular defect and investigated healing outcomes at week 8, in correlation with the cellular landscape of the immune cells in the fracture callus at week 2. Results: Maximum recruitment of immune cells to the fracture callus is known to occur at week 2. While the control, S, V, and VS groups remained as nonunions at week 8; all BMP-6 containing groups - B, BV, BS and BVS, showed near-complete to complete healing. This healing pattern was strongly associated with significantly higher ratios of CD4 T (CD45+CD3+CD4+) to putative CD8 T cells (CD45+CD3+CD4-), in groups treated with any permutation of BMP-6. Although, the numbers of putative M1 macrophages (CD45+CD3-CD11b/c+CD38high) were significantly lower in BMP-6 containing groups in comparison with S and VS groups, percentages of putative - Th1 cells or M1 macrophages (CD45+CD4+IFN-γ+) and putative - NK, NKT or cytotoxic CD8T cells (CD45+CD4-IFN-γ+) were similar in control and all treatment groups. Further interrogation revealed that the BMP-6 treatment promoted type 2 immune response by significantly increasing the numbers of CD45+CD3-CD11b/c+CD38low putative M2 macrophages, putative - Th2 cells or M2 macrophages (CD45+CD4+IL-4+) cells and putative - mast cells, eosinophils or basophils (CD45+CD4-IL-4+ cells). CD45- non-haematopoietic fractions of cells which encompass all known osteoprogenitor stem cells populations, were similar in control and treatment groups. Discussion: This study uncovers previously unidentified regulatory functions of BMP-6 and shows that BMP-6 enhances fracture healing by not only acting on osteoprogenitor stem cells but also by promoting type 2 immune response.

A developmental atlas of somatosensory diversification and maturation in the dorsal root ganglia by single-cell mass cytometry.

Precisely controlled development of the somatosensory system is essential for detecting pain, itch, temperature, mechanical touch and body position. To investigate the protein-level changes that occur during somatosensory development, we performed single-cell mass cytometry on dorsal root ganglia from C57/BL6 mice of both sexes, with litter replicates collected daily from embryonic day 11.5 to postnatal day 4. Measuring nearly 3 million cells, we quantified 30 molecularly distinct somatosensory glial and 41 distinct neuronal states across all timepoints. Analysis of differentiation trajectories revealed rare cells that co-express two or more Trk receptors and over-express stem cell markers, suggesting that these neurotrophic factor receptors play a role in cell fate specification. Comparison to previous RNA-based studies identified substantial differences between many protein-mRNA pairs, demonstrating the importance of protein-level measurements to identify functional cell states. Overall, this study demonstrates that mass cytometry is a high-throughput, scalable platform to rapidly phenotype somatosensory tissues.

FLOW-MAP: a graph-based, force-directed layout algorithm for trajectory mapping in single-cell time course datasets.

High-dimensional single-cell technologies present new opportunities for biological discovery, but the complex nature of the resulting datasets makes it challenging to perform comprehensive analysis. One particular challenge is the analysis of single-cell time course datasets: how to identify unique cell populations and track how they change across time points. To facilitate this analysis, we developed FLOW-MAP, a graphical user interface (GUI)-based software tool that uses graph layout analysis with sequential time ordering to visualize cellular trajectories in high-dimensional single-cell datasets obtained from flow cytometry, mass cytometry or single-cell RNA sequencing (scRNAseq) experiments. Here we provide a detailed description of the FLOW-MAP algorithm and how to use the open-source R package FLOWMAPR via its GUI or with text-based commands. This approach can be applied to many dynamic processes, including in vitro stem cell differentiation, in vivo development, oncogenesis, the emergence of drug resistance and cell signaling dynamics. To demonstrate our approach, we perform a step-by-step analysis of a single-cell mass cytometry time course dataset from mouse embryonic stem cells differentiating into the three germ layers: endoderm, mesoderm and ectoderm. In addition, we demonstrate FLOW-MAP analysis of a previously published scRNAseq dataset. Using both synthetic and experimental datasets for comparison, we perform FLOW-MAP analysis side by side with other single-cell analysis methods, to illustrate when it is advantageous to use the FLOW-MAP approach. The protocol takes between 30 min and 1.5 h to complete.

AN UPDATED DEBARCODING TOOL FOR MASS CYTOMETRY WITH CELL TYPE-SPECIFIC AND CELL SAMPLE-SPECIFIC STRINGENCY ADJUSTMENT.

Pooled sample analysis by mass cytometry barcoding carries many advantages: reduced antibody consumption, increased sample throughput, removal of cell doublets, reduction of cross-contamination by sample carryover, and the elimination of tube-to-tube-variability in antibody staining. A single-cell debarcoding algorithm was previously developed to improve the accuracy and yield of sample deconvolution, but this method was limited to using fixed parameters for debarcoding stringency filtering, which could introduce cell-specific or sample-specific bias to cell yield in scenarios where barcode staining intensity and variance are not uniform across the pooled samples. To address this issue, we have updated the algorithm to output debarcoding parameters for every cell in the sample-assigned FCS files, which allows for visualization and analysis of these parameters via flow cytometry analysis software. This strategy can be used to detect cell type-specific and sample-specific effects on the underlying cell data that arise during the debarcoding process. An additional benefit to this strategy is the decoupling of barcode stringency filtering from the debarcoding and sample assignment process. This is accomplished by removing the stringency filters during sample assignment, and then filtering after the fact with 1- and 2-dimensional gating on the debarcoding parameters which are output with the FCS files. These data exploration strategies serve as an important quality check for barcoded mass cytometry datasets, and allow cell type and sample-specific stringency adjustment that can remove bias in cell yield introduced during the debarcoding process.

Tom1 Modulates Binding of Tollip to Phosphatidylinositol 3-Phosphate via a Coupled Folding and Binding Mechanism.

Early endosomes represent the first sorting station for vesicular ubiquitylated cargo. Tollip, through its C2 domain, associates with endosomal phosphatidylinositol 3-phosphate (PtdIns(3)P) and binds ubiquitylated cargo in these compartments via its C2 and CUE domains. Tom1, through its GAT domain, is recruited to endosomes by binding to the Tollip Tom1-binding domain (TBD) through an unknown mechanism. Nuclear magnetic resonance data revealed that Tollip TBD is a natively unfolded domain that partially folds at its N terminus when bound to Tom1 GAT through high-affinity hydrophobic contacts. Furthermore, this association abrogates binding of Tollip to PtdIns(3)P by additionally targeting its C2 domain. Tom1 GAT is also able to bind ubiquitin and PtdIns(3)P at overlapping sites, albeit with modest affinity. We propose that association with Tom1 favors the release of Tollip from endosomal membranes, allowing Tollip to commit to cargo trafficking.