Kyra van der Pan (Leiden / NL), Indu Khatri (Leiden / NL), Enrique De La Rosa (Salamanca / ES), Sara Kassem (Leiden / NL), Anniek L de Jager (Leiden / NL), Brigitta AE Naber (Leiden / NL), Inge F de Laat (Leiden / NL), Alesha Louis (Leiden / NL), Marjolijn Hameetman (Leiden / NL), YK Onno Teng (Leiden / NL), Meta Roestenberg (Leiden / NL), Stijn Crobach (Leiden / NL), Wouter BL van den Bossche (Erasmus / NL), Daniela Damasceno (Salamanca / ES), José Manuel Sánchez-Santos (Salamanca / ES), Alberto Orfao (Salamanca / ES), Javier de las Rivas (Salamanca / ES), Jacques JM van Dongen (Leiden / NL; Salamanca / ES), Cristina Teodosio (Leiden / NL; Salamanca / ES), Paula Díez (Oviedo / ES; Leiden / NL; Salamanca / ES)
Monocytes (Mo) and macrophages (MAC) are key players in tissue-cleaning processes during body homeostasis and response to stressors (e.g. infection, cancer). Mo derive from precursor cells in the bone marrow (BM) and differentiate into MAC after leaving the bloodstream and entering tissues. Despite the existing knowledge about these cells, their plasticity, functional heterogeneity, and the discovery of new subsets, currently hamper the definition of their exact maturational relationship.
To address this, we combined single cell-based mass cytometry (CyTOF) and bulk mass spectrometry (MS)-based proteomics approaches to define the proteome and maturational relationship of monocytic cells across tissues (BM, peripheral blood (PB), skin, peritoneal dialysate (PD) and colon). Firstly, >100 proteins were screened to design a 35-marker CyTOF panel to evaluate >15 Mo/MAC populations. Based on this data, we purified 5 (pro)monocyte subsets from BM (n=4-5, from 9 donors), 8 monocytic subsets from PB (n=2-5, from 7 donors), and MAC from skin (n=4, from 7 donors), PD (n=3, from 6 donors) and colon (n=5, from 7 donors) samples, for TMT-based MS.
Based on population relationships, as defined using single-cell trajectory analysis, 11 distinct protein expression patterns were observed during maturation in BM, reflecting diverse functions (e.g. metabolism, signalling, lysosome assembly, antigen presentation) at different stages of differentiation. Analysis of PB subsets suggested a close relationship between CD62L- FcεRI- classical Mo (cMo), intermediate Mo (iMo) and CD36+ Slan- non-classical Mo (ncMo) subsets, with iMo acting as a bridge between cMo and ncMo. Within ncMo subpopulations, a distinct functional profile distinguished Slan- cells, primarily involved in metabolic and protein production processes, from CD36- subsets, showing a stronger commitment to protein production and vesicle transport. Regarding MAC, a common core functional identity signature encompassing 425 functions (79.6% of all MAC functions) was identified across all tissues. A microenvironment effect was also observed, as colon MAC exhibited distinctive TOR and TLR signalling pathways, skin MAC expressed proteins involved in cellular responses to gamma radiation, and PD MAC reflected processes like immunological synapse formation. Notably, when compared to Mo, CD62L+ FcεRI- cMo from PB displayed the closest resemblance to the general MAC signature, despite differences in their immune profiles. While MAC were prominently involved in antiviral responses, the cMo subset played a main role in T-cell activation, receptor signalling, cytokine production and antigen processing and presentation processes.
In conclusion, by integrating CyTOF and MS-based proteomics approaches, we provide a detailed proteome atlas of monocytes and MAC across tissues, shedding light on the complex maturational relationships and functional heterogeneity of these cells.