the antibod ies identified to work spatially were then validated at single - cell resolution, using macsima™ imaging cyclic staining ( mics ) technology and a 60 - plex antibod y panel ( figure 1 i ). unfortunately, we could not identify useful surface markers for all populations. for example, we did not identify enough discriminat ory surface markers that worked by confocal microscopy to disting uish the cdc subsets. notably, while cd103 has previously been proposed to disting uish hepatic cdc1s from cdc2s ( eckert et al., 2015 ), our data demonstrate that this is only expressed by a fraction of these cells ( figure s2 o ). to confirm the locations of the cdc subsets, we thus turned to molecular cartography™ ( resolve biosciences ) that allows for 100 - plex spatial mrna analysis. genes were selected based on the degs from the sc / snrna - seq data that were also spatially resolved according to visium. we also identified the portal - central trajectory in this dataset using cholangio cytes genes ( epcam and spp1 ) and known zonated hepatocyte genes ( glul, cyp2e1, hal, and sds; figure s2 p ). using expression of xcr1, clec9a ( cdc1s ) and cd209a, mgl2, and clec10a ( cdc2s ), we confirmed that both cdc1s and cdc2s were localized primarily at the pv ( figure 1 j ). as cdc2s shared a number of genes with monocyte-derived cells ( figure s2 a ), we also examined the expression of general monocyte / mac ( cd14, adgre1, axl, mafb, cx3cr1, and c5ar1 ) and kc - specific genes ( cd5l and vsig4 ) to further validate their identification as bona fide cdc2s ( figure 1 j ). the punctate nature of mrna expression in these analyses combined with the dendritic shape of myeloid cells renders it difficult to convincingly determine cell boundaries and to conclude these cdc2s and macs were distinc t cells. to validate this, we therefore developed a protocol that combines mrna detection ( rnascope ) with surface protein detection. examining expression of cdc - or mac - specific mrnas combined with protein surface markers confirmed the presence of pv cdc1, cdc2s, and non - kc macs ( figure 1 k ). taken together, by combining multiple spatial transcriptomic and proteomic approaches, we located all the cells within the murine liver and identified additional heterogeneity within the myeloid cells, not revealed when examining the sc / sn - rna - seq dataset in isolation. this highlights the power of combining single - cell and spatial proteogenomic techniques to investigate cellular heterogeneity. to better understand the non - kc macs, we zoomed in on myeloid cells ( cdcs, kcs, monocytes, and monocyte-derived cells ) in our sc / snrna - seq analysis defining 11 populations ( figures 2 a – 2c; table s2 ). this included kcs, 3 populations of non - kc macs and cells that had a profile intermediate between monocytes and patrolling monocytes or macs, termed transitioning monocytes. closer inspection of the non - kc macs identified cluster6 as peritoneal macs ( figure 2 b ). the degs between the remaining populations suggested that cluster7 likely resembles capsule macs ( sierro et al., 2017 ), expressing cd207 and cx3cr1 while cluster8 resembles gpnmb spp1 lipid-associated macrophages ( lams ) we recently described in the fatty liver ( remmerie et al., 2020; figures 2 a – 2d ). conversion of the cite - seq data into an fcs file allowed an in silico gating strategy to be defined ( figure s3 a ). validating this, we utilized the strategy to facs - purify the populations and assess gene expression ( figures s3 b – s3d ). fitting with a recent report ( jin et al., 2021 ), washing the liver prior to digestion enriched the peritoneal macs in the wash fraction, demonstrating these were contaminants on the liver surface rather than being present in the liver tissue itself ( figure s3 e ). while the cite - seq markers did not discriminat e between cluster7 and cluster8, adding cd207 to the panel enabled the non - kcs to be divided into cd207 and cd207 macs ( figure s3 f ). fitting with their designation as capsule macs, the relative abundance of cd207 macs was increased if we dissected and digested the capsule ( figure s3 f ). however, although molecular cartography confirmed the presence of cd207 macs in the capsule, it also revealed cd207 macs at the cv, which were rarely found at the pv ( figures 2 e – 2h and s3 g – s3j ). thus, cluster7 consists of both capsule and cv cd207 macs. this finding further demonstrates the need for spatial approaches to confirm cell identities. molecular cartography also identified macs at the pvs and cvs expressing ccr2 and chil3 ( figures 2 g, 2h, s3 h, and s3j ), resembling transitioning monocytes ( cluster11 ). finally, a population of gpnmb - expressing macs were found to be enriched around the bile ducts ( figures 2 g, 2h, s3 h, s3k, and s3l ). as gpnmb expression is cluster8 specific ( figure 2 b ), and these cells resemble lams ( remmerie et al., 2020 ), we termed these cells bile - duct lams. we next sought to investigate the differences between kcs and lams. analysis of go terms associated with biological processes for these cells suggested that kcs may play a role in regulating humoral responses, while lams were more broadly associated with immune responses ( figures 2 i and 2j ). consistent with this, in the 100 - plex protein microscopy data we noted that a significant proportion of the b cells present were interacting with kcs, which was not observed with t cells ( figure 2 k ). this suggests cross - talk between these two populations, potentially linked to the high expression of the b cell chemok ine cxcl13 by murine kcs ( table s2 ). to assess the inflammatory nature of lams compared with kcs, we facs - purified the cells and performed qpcr analysis to examine expression of various cytokines. to enable lam purification, we eliminated the capsule prior to digesting the tissue. fitting with the go analysis, lams expressed more il1b at steady state compared with kcs ( figure 2 l ). however, despite this, upon in vivo tlr4 stimulation, they were less responsive than kcs, both in terms of pro - and anti-inflammatory cytokines ( figure 2 l ), possibly indicative of lps tolerance. this may result from their location at the pv and hence exposure to blood from the intestine, although this remains to be tested. taken together this highlights the distinc t nature and functions of these cells; however, further research is required to determine the precise roles of these cells. as all the mac populations are in close contact with cd45 cells in their local environment ( bonnardel et al., 2019; figure s3 m ), we further analyzed the cd45 cells, identifying multiple subsets of ecs and scs and a gating strategy to disting uish them ( figures 3 a – 3c and s4 a – s4c; table s3 ). ecs could be further subdivided into 4 distinc t clusters and analysis of their locations allowed them to be identified as cv ecs ( cluster10 ), lsecs ( cluster9 ), pv ecs ( cluster11 ), and lymphatic ecs ( lecs; cluster12 ) ( figures 3 d, 3e, s4 d, and s4e ). as visium found fibroblasts at both the pvs and cvs ( figure 3 d ), and as a previous report has suggested the presence of distinc t subsets within these cells ( dobie et al., 2019 ), we further zoomed in on the scs to better assess their heterogeneity ( figures 3 f, 3g, s4 a – s4c, and s4f; table s4 ). this revealed subsets of mesothelial cells and fibroblasts restricted to the capsule ( figures 3 h and 3i ). myh11 vascular smooth muscle cells ( vsmcs ) were localized around hepatic arteries, pvs and cvs ( figures 3 f – 3h, 3j, and s4 g ) and mfap4 svep1 clic5 reln fibroblasts were found to be cv fibroblasts ( figures 3 g, 3h, 3j, and s4 g ). finally, we identified a subset of clic5 reln fibroblasts ( cluster3 ), which were localized around the cholangio cytes, that we termed bile - duct fibroblasts ( figures 3 j and s4 g ).