Animal needs were met in accordance with the European Community Council Directive 2010/63/EU (Decree: 2013-118 01/02/2013). The experimental facilities had received authorization to house experimental animals from the local bureau of veterinary services (Indre-et-Loire, France, authorization no. D 37-175-3), and all the experimental procedures were approved by the Val de Loire Ethics Committee (CEEA19) (authorization no. APAFlS#21604-201907250902391 v2 and #21515-2019071714558143 v2). All animal experimentations have been performed in the Infectiology of Farm, Model and Wildlife Animals Facility (PFIE, Centre INRAE Val de Loire: doi.org/10.15454/1.5572352821559333E12; a member of the National Infrastructure EMERG’IN: doi.org/10.15454/90CK-Y371). All the personnel involved had dedicated training in animal care, handling, and experimentation, as required by the French Ministry of Agriculture.

Pré-Alpes (C. parvum infection experiments) and Ile de France lambs (cell phenotyping) were respectively provided by the sheep farming of the PFIE and of the Animal Physiology Experimental Unit (UE PAO, Centre INRAE Val de Loire). Prim’Holstein calves with excellent health status were from approved local cattle breeders. For the intestinal MP cell subset characterization, 8-day-old, 10-day-old, and 4-month-old lambs and 3-year-old sheep were used. For the C. parvum lamb infection experiments, six or seven lambs per group (a non-infected group and an infected group) were enrolled at 1 day of age, after colostrum intake from their dams. For the calf study, we benefited from concomitant experiments enrolling young calves to collect intestinal samples from four 10-day-old non-infected animals and from three 12- to 13-day-old infected animals, inoculated at day 1 of age by oral route with 8 × 10⁶ oocysts of C. parvum INRAE strain resuspended in water. The number of animals used in each condition is summarized in Table 1 .

Tissues from IPP, JPP, and distal jejunum of lambs and calves were sampled and washed with PBS. Intestinal mucosa was isolated from the muscularis by scraping with a scalpel and enzymatically dissociated in culture medium (RPMI; 10% FBS; 100 U/mL penicillin; and 100 µg/mL streptomycin) with 0.02 MU/mL DNase I, 0.9 U/mL dispase II, and 0.8 mg/mL collagenase I (Sigma-Aldrich) for 30 min at +37°C under agitation at 700 rpm. Resulting intestinal cellular suspensions were filtered on 100-µm cell strainers and washed with culture medium. Red blood cells were removed by a 5-min incubation at room temperature (RT) with a lysis buffer (Sigma-Aldrich). A Ficoll gradient (Sigma-Aldrich) was performed and centrifuged at 2,000×g for 30 min at RT. Cells from the interphase were washed with culture medium to obtain the total isolated intestinal cells.

Isolated cells from IPP, JPP, and distal jejunum were resuspended as 2 × 10⁶ cells in FACS buffer (PBS; 2% FBS; 2 mM EDTA). Cells were next incubated for 15 min in Fc block (FACS buffer; 2% ovine or bovine serum according to the experiment). Staining was then performed by incubation with a viability marker (Zombie Aqua™ Fixable Viability Kit, BioLegend) and species cross-reacting antibodies are listed in Table 2 . The immunostaining of the cells with the antibodies was carried out in three steps of 30 min in the dark at 4°C+, each of them being separated with a series of three washes with FACS buffer. During the first step, the cells were stained with the mouse IgG1 anti-bovine CD14. In the second step, cells were incubated with the secondary antibody anti-mouse IgG1 (rat IgG1, BV711, clone A85-1, BD Biosciences) and a mix of primary antibodies composed of the mouse IgM anti-CD11c and the chicken anti-human Cadm1. In the last step, the cells were incubated with the secondary antibodies [anti-mouse IgM (rat IgG2a, APC-Cy7, clone RMM-1, BioLegend) and anti-chicken IgY (goat IgG, Alexa Fluor 647, polyclonal, Abcam)], the directly conjugated primary antibodies (anti-ovine MHCII-RPE, anti-bovine CD11b-FITC, and the anti-bovine CD172α⁻ RPE-Cy5), and the Aqua Zombie viability probe. The anti-bovine CD172α was stained with the LYNX Rapid RPE-Cy5 Antibody Conjugation Kit, according to the manufacturer’s instructions (Bio-Rad). After staining, cells were either fixed with Stabilizing Fixative buffer (BD Biosciences) or conserved in PBS respectively for flow cytometry analyses with the LSRFortessa X-20 flow cytometer (Becton Dickinson) or for cell sorting with the MoFlo Astrios EQ cell sorter (Beckman Coulter). Unstained cells and matched isotype controls were used to define gating thresholds. Gating on forward scatter (FSC) and side scatter (SSC) parameters was first used to exclude cell debris (i.e., FSC^low and SSC^low events), and viable cells were next selected by exclusion of dead cells (i.e., viability marker-positive cells). Finally, among CD11c⁺MHCII⁺ cells gated as MP cells, the following four subsets were discriminated and sorted: CD14⁺CD172α⁺Cadm1^intCD11b⁺ cells (subset 1), CD14⁻CD172α⁻Cadm1⁺CD11b⁻ cells (subset 2), CD14⁻CD172α⁺ Cadm1^intCD11b⁺ cells (subset 3), and CD14⁻CD172α^+/−Cadm1⁻CD11b⁻ cells (subset 4). The complete gating strategy is available in Supplementary File 1 .

For mRNA expression analyses in intestinal MP subsets, RNA were recovered from sorted cells with a lysis buffer [RNase/DNase-free water; 0.01 M DTT; 1% Tween 20; 0.83 U/µL RNAseOUT™ recombinant ribonuclease inhibitor (Invitrogen)] and immediately reverse-transcribed as previously described (25). For total intestinal tissue samples, RNA extractions were performed after homogenization in TRIzol (Invitrogen) with an Ultra-turrax and processed according to the manufacturer’s recommendations. Total RNA was reverse-transcribed with the iScript RT SuperMix kit (Bio-Rad). cDNA from sorted MP cell subsets and intestinal tissues were then amplified by quantitative real-time PCR (qPCR) with the FLUIDIGM^® method using an IFC Controller HX and BioMark™ HD thermal cycler (Fluidigm), according to the manufacturer’s instructions. We used a dynamic array IFC 96 × 96 (Fluidigm) to analyze the expression of a large panel of genes, whose primer sequences are listed in Supplementary Table 1 and previously published (26, 27). Data of mRNA gene expression were analyzed with the Real-Time PCR Analysis software (Fluidigm). Following normalization with three reference genes (HPRT, GAPDH, and ACTB), results were expressed as either 2^-ΔCt ratio (comparison of intestinal immune responses between non-infected and C. parvum-infected lambs) or relative gene expression (RT-qPCR analysis of sorted MP cells).

Mononuclear phagocytes were isolated as previously described from the IPP of a 10-day-old lamb and were analyzed with the 10X Genomics Chromium single-cell technology. Library was prepared according to the instructions of the 10X Genomics Single-Cell 3′ Reagent Kit v3.1 User Guide. Briefly, in order to sort viable CD11c⁺MHCII⁺ cells, total isolated intestinal cells were stained with a viability marker (Zombie Aqua™ Fixable Viability Kit, BioLegend) and with anti-bovine CD11c anti-bovine MHCII antibodies. Sorted MP cells were collected in RPMI containing 10% FBS, and 10,000 cells were used for library construction. First, MP suspension was mixed with a Master Mix containing reverse transcription (RT) reagents and loaded onto Chromium Next GEM Chip G, together with gel beads [containing an Illumina sequencing primer site, a 10X Genomics barcode, randomers called unique molecular identifiers (UMIs), and a poly-dT primer] and partitioning oil for the emulsion reaction. Nanoliter-scale Gel Beads-in-Emulsion (GEMs) were next generated with Chromium, such that each single cell was associated with a specific barcode and each of its transcripts was labeled with a UMI. After RT of mRNAs, the whole generated cDNAs were pooled following GEMs disruption/breakage, purified with Dynabeads^® MyOne™ SILANE (Thermo Fisher Scientific), amplified by PCR, and size-selected with SPRIselect (Beckman Coulter). The quality and quantity of cDNA were then assessed with an Agilent 2100 Bioanalyzer System with a High-Sensitivity DNA kit, according to the manufacturer’s instructions. Finally, the sequencing library construction was performed from cDNA and involved steps of enzymatic fragmentation, end repair, A-tailing, adaptor ligation, double-sided size selections with SPRIselect (Beckman Coulter), and sample index PCR, notably to add P5 and P7 primers used in Illumina amplification. Illumina paired-end sequencing of the library was realized at Integragen, using NovaSeqTM 6000 S2 systems. The read setup was as follows: read 1: 28 cycles, i7 index: 10 cycles, i5: 10 cycles, and read 2: 91 cycles.

The raw scRNA-seq FASTQ files were processed using Cell Ranger software (version 6.0.2, 10X Genomics) and aligned to the ARS-UI_Ramb_v2.0 reference genomes. Bam files and filtered expression matrices were generated using the “cellranger_count” pipeline. Matrices from Cellranger were further analyzed into R (version 4.10) using the Seurat R package (version 4.21) (28, 29). To exclude low-quality doublet and dead cells, cells that expressed less than 600 and more than 6,000 genes and had greater than 5% of mitochondrial genes were filtered out the analysis. Data were normalized using the default method (LogNormalize) in the Seurat package and highly variable genes were identified. Next, a linear dimensional reduction was performed on scaled data [principal component analysis (PCA)]. For further downstream analysis, the optimal number of principal components was identified by the elbowplot method. The first 20 principal components were selected for clustering the cells by the Louvain algorithm with 0.5 resolution. UMAP was employed for non-linear dimensional reduction and cluster visualization. To annotate clusters, the top 10 differentially expressed genes (DEGs) for each cluster (based on log2 fold change) were evaluated with the “FindAllMarkers” function and displayed on heatmaps or dot plots. Differential expression was also performed between two individual clusters to determine cell populations more accurately. Single-cell RNA-seq data were visualized in feature plots, violin plots, dot plots, and heatmaps using Seurat or ScCustomize R packages (version 0.7.0) (28, 30).

Graphical representations were created using the GraphPad Prism software (version 6.0) for histograms, the Kaluza Analysis software (version 2.1) for flow cytometry gating panels, the RStudio software (version 2023.03.0) for PCA, and heatmap representations and the Microsoft Excel program for pie charts. All statistical analyses were performed with the GraphPad Prism software (version 6.0). The appropriate statistical tests and post-hoc testing selected for each experiment are specified in figure legends.

The phenotypic characterization of intestinal MPs in 10-day-old neonatal ruminants was performed with flow cytometry analyses. Cells isolated from the IPP of young lambs and calves were analyzed for their cell surface expression of several markers used to distinguish MAC and DC subsets in various species (CD11c, MHCII, CD14, CD172α, CD11b, and Cadm1).

After the exclusion of dead cells, CD11c⁺MHCII⁺ cells were initially gated to select conventional DC (cDC), MAC, and newly recruited monocytes in the intestinal tissue, while excluding pDC with little or no expression of CD11c (12) ( Figure 1 ). Then, with expression of CD14 being widely used to differentiate MAC/monocytes from DCs, CD14⁺ cells were associated with putative MAC/newly recruited monocytes, and CD14⁻ cells were associated with putative cDCs. Finally, based on surface expression of CD14, CD172α, CD11b, and Cadm1, we distinguished one subset of putative MAC with a CD14⁺CD172α⁺Cadm1^intCD11b⁺ phenotype (subset 1, green) and three subsets of putative cDC with CD14⁻CD172α⁻Cadm1⁺CD11b⁻ (subset 2, purple), CD14⁻CD172α⁺Cadm1^intCD11b⁺ (subset 3, blue), and CD14⁻CD172α^+/−Cadm1⁻CD11b⁻ phenotypes (subset 4, yellow), in both species ( Figure 1 ). Furthermore, the combined expression of CD14, CD172α, and CD11b observed for subset 1 was described as specific for MAC/monocyte populations (31). Microscopic observation of the lamb cell morphology of subsets 1, 2, and 3 supports these assumptions, with subset 1 showing MAC-specific granules and intracellular vacuoles, while subsets 2 and 3 are somewhat smaller, with a larger nucleus and displaying DC-specific dendrite/pseudopod-like structures, as previously described (32–34) ( Figure 1A , pictures). Among DCs, high expression of Cadm1 without CD172α and CD11b is described as cDC1-specific, while the opposite is cDC2-specific (10–12), leading us to designate subsets 2 and 3 as putative cDC1 and cDC2, respectively. Subset 4 was present at a lower frequency and might represent another cDC subset.

Moreover, additional intestinal segments were investigated for MP populations in the same animals. Similar results were obtained for the distal jejunum (non-lymphoid tissue) and the JPP in both lamb and calf ( Supplementary Files 2, 3 ), indicating that the four MP subsets are present in the small intestine of young ruminants, regardless of the location (ileum or jejunum) and the presence of lymphoid structure or not.

In lamb and in the distal jejunum of calf, we also observed the distinction of two subpopulations among putative MAC (subset 1), according to a high or intermediate expression of CD11b, which was not explored further in this study ( Figure 1 ; Supplementary Files 2, 3 ).

Overall, subsets 1 and 2 are the most abundant cells within MPs in the intestine of lamb (according to the tissue, 24%–33% and 28%–34%, respectively) and calf (30%–44% and 22%–34%, respectively), followed by subset 3 (8%–12% for lamb and 14%–16% for calf) and the minor subset 4 (<6% for lamb and <10% for calf) ( Figure 1 ; Supplementary Files 2, 3 , pie charts). The main difference between lymphoid and non-lymphoid tissues is the lower proportion of CD11c⁺MHCII⁺ MPs in the IPP (3.4% ± 1.1% for lamb and 2.8% ± 0.8% for calf) and JPP (5.3% ± 1.0% for lamb and 5.8% ± 1.2% for calf) in comparison to the distal jejunum (12.3% ± 2.6% for lamb and 7.7% ± 1.6% for calf), which probably results from the large representation of lymphocytes in lymphoid tissues.

The intestinal immune system develops and matures with age with a rapid acceleration after birth upon contact with microbiota and alimentary antigens. A peculiarity of young ruminants is their large IPP, which starts to regress from approximately 3 months old until it disappears as an adult (19). C. parvum infection affects particularly the ileum of neonatal lambs while adults are strongly resistant to the infection (35, 36). Thus, the ovine intestinal MP subsets from birth to adult age were analyzed by flow cytometry. In IPP, a striking feature is the tripling of the proportion of putative cDC1 subset 2 within the 10 days after birth while those of putative cDC2 subset 3 decreases by almost 10-fold in the first month ( Figure 2 ). Similar observations, albeit at a lower magnitude, were found in the other intestinal segments analyzed, i.e., the distal jejunum (twofold increase and decrease for putative cDC1 subset 2 and putative cDC2 subset 3, respectively) and JPP (almost threefold increase and fourfold decrease for subsets 2 and 3, respectively) ( Supplementary File 4 ). This suggests that these changes in the proportion of putative cDC1 and cDC2 occur in both lymphoid and non-lymphoid structures in the small intestine of young lambs. At 3 years of age, the proportion of CD11c⁺MHCII⁺ was higher than in young animals due to the decrease in the presence of lymphocytes related to the involution of the IPP (data not shown).

Intestinal MP subsets primarily identified based on cell surface markers were further characterized by transcriptomic analyses following cell sorting. We studied the expression of hallmark genes belonging to the conserved transcriptomic signatures of mammalian MAC and cDC subsets across species (human, mouse, pig, chicken, cattle, and sheep) (10–12) and of genes involved in immune responses (69 genes in total listed in Supplementary Table 1 ).

First, we observed that CD14, CD172α, CADM1, and CD11B, the four genes coding for the corresponding surface proteins used for cell sorting, showed a specific pattern of expression for each cell subset from the intestine of lambs and calves ( Figure 3A ; Supplementary Files 5, 6 ) corresponding to those at the protein level ( Figure 1 ; Supplementary Files 2, 3 ).

In the IPP of lambs, the four MP subsets previously identified by flow cytometry are clearly distinguished from each other according to their gene expression profiles following PCA (PC1 = 50.54%, PC2 = 17.37%) ( Figure 3B ). The major gene expression of CD14, CD64, C5αR1, and MERTK, together with the absence of that of FLT3 and ZBTB46 in subset 1, confirmed their identification as MAC ( Figure 3C ). In parallel, subsets 2, 3, and 4 display co-expression of FLT3 and ZBTB46, two cDC hallmark genes, with subset 2 expressing the highest level of FLT3 ( Figure 3C ). The mutually exclusive gene expressions of BATF3, XCR1, IRF8, CADM1, CD26, and TLR3 in subset 2, and of IRF4, FCεR1α, CLEC6A, CLEC7A, CX3CR1, CD172α, CD11B, IL1β, TLR7, and TLR8 in subset 3 indicate that they correspond to cDC1 and cDC2, respectively ( Figure 3C ). In addition, the gene expression profiles of subsets 1 (MAC) and 3 (cDC2) are relatively close, showing the common expression of the majority of the genes studied but with different expression levels. cDC subset 4 has a more heterogeneous gene expression profile, sharing both feature gene expression of subset 2 (cDC1) (TLR9, CD26, IL12P40, and MIF) and subset 3 (cDC2) (TLR7, IRF4, CX3CR1, CLEC6A, and CCL5) ( Figure 3C ). Nevertheless, its high expression of IRF4 and closer proximity to cDC2 in PCA suggests that it might be a cDC2 subpopulation or a cDC2 subset in a different state of maturation (subset 4 will now be called “cDC no. 3“). Additional key genes known to describe the heterogeneity within cDC subpopulations were therefore further analyzed. As shown in Figure 3D , cDC no. 3 stands out by high expression of CCR7, CCL22, FSCN1, and STAT4, which are involved in the processes of activation, maturation, and migration of DC to mesenteric lymph nodes (37–39), indicating that they may correspond to migratory DCs. This subset also highly expresses BTLA and IDO1, two genes associated with immune regulatory activities (39–41) ( Figure 3D ). These results were also obtained in the distal jejunum and JPP of lambs, confirming that this subset characterization is present in the different parts of the small intestine ( Supplementary File 5 ).

In the IPP of calves, similar analyses confirm the characterization of MAC, cDC1, and cDC2 and therefore indicate that these populations might be present across ruminant species ( Supplementary File 6 ). However, in calves, PCA cannot really distinguish cDC2 from cDC no. 3 ( Supplementary File 6B ).

In order to better define DC and MAC subsets, a gene clustering was performed at the single-cell level. Alive CD11c⁺MHCII⁺ cells from the IPP of a 10-day-old lamb were sorted, and single-cell transcriptomes were obtained and processed as described in Materials and Methods. A resolution of 0.5 was chosen, resulting in 15 different clusters ( Supplementary File 7A ). We first analyzed FLT3 and CSF1R gene expression in UMAP plots to identify DC and monocytic cell clusters, respectively ( Supplementary File 7B ). Few cells (no. 13), lacking both FLT3 and CSF1R expression, were identified as B lymphocytes as indicated by their specific expression of LTB, JCHAIN, and MS4A1 genes and were excluded from further cluster analyses ( Supplementary File 7C ; Supplementary Table 2 ).

After reclustering ( Figures 4A-C ), FLT3-expressing DC cells could be associated with five clusters (clusters 1, 5, 9, 10, and 13) and CSF1R-expressing monocytic cells could be associated with seven clusters (clusters 0, 2, 3, 4, 6, 8, and 12), with two other clusters (clusters 7 and 11) expressing both FLT3 and CSF1R. In particular, c7 contained cells expressing either FLT3 or CSF1R ( Figure 4B ). CSF1R-expressing clusters were also characterized by the expression of additional signature genes for monocytic cells (CD68, MERTK, C1QA, C1QB, and C5AR1), absent from FLT3-expressing clusters with the exception of a part of cells in c7 ( Supplementary File 7D ). Moreover, the expression of the top 10 DEGs by each cluster (lowest p_val_adj, followed by highest avg_log2FC) visualized in a dot plot for all clusters highlighted the close proximity of DC cluster 7 and cluster 11 to monocytic cells ( Figure 4D ; Supplementary Table 3 ). In addition, DC clusters displayed common enriched gene ontology (GO) terms related to cytoskeleton organization while those for monocytic cell clusters were related to leukocyte activation and chemotaxis ( Figure 4E ).

Through flow cytometry, three subsets of DCs were phenotypically identified and suggested to be cDC1, cDC2, and migratory DCs with targeted gene expression analysis. Based on scRNA-seq data, a heatmap of the top 10 (adjusted p-value) DEGs between the seven FLT3-expressing clusters is shown in Figure 5A and the complete gene list is provided in Supplementary Table 4 . As shown in Figure 5B , the co-expression of key subset-specific genes clearly confirmed clusters 1, 5, 9, and 10 to be cDC1 (ANPEP, XCR1, CLEC9A, BATF3, and IRF8). Clusters 9 and 10 encompassed many genes of the cell cycle, with PCNA, MCM3, MCM4, MCM5, and SIVA1 expression that characterizes the S-phase of cells higher in c9 cells compared to cells of c10 expressing predominantly MKI67, CENPF, and TOP2A that characterize the G1-phase ( Supplementary File 8A, B ). In addition, enriched GO terms were typical for dividing cells such as nuclear division and nuclear DNA replication ( Figure 4E ). As visualized in the UMAP projection ( Figure 4 ) and according to specific gene expression, c10 conveys the impression of giving rise to c9 that later diverges to meet non-proliferative cDC1 clusters (c1 and c5). Clusters 1 and 5 shared cDC1 gene signature, but when compared, significant genes including PLAC8, ATP1B1, and LGALS1 were highly expressed in c1 compared to c5, which was enriched in transcripts for MRPL14, SLAMF8, VIM, and RBP4 genes, suggesting some diversity among cDC1 cells ( Supplementary File 8C ; Supplementary Table 6 ). Moreover, GO terms enriched for c1 were related to the negative regulation of immune response (e.g., negative regulation of immune system process/defense response/response to external stimulus) while those for c5 referred to immune cell activation (e.g., leukocyte/lymphocyte/T-cell activation involved in immune response) ( Supplementary File 8D ).

On the UMAP dot plot, c7, which expressed FLT3 gene, is closely localized to the CSF1R-expressing clusters corresponding to monocytic cells ( Figure 4A ). Compared to other FLT3-expressing clusters, c7 expressed a very low level of cDC1 key genes (IRF8, CLEC9A, XCR1, BATF3, and ANPEP) but a high level of SIRPA, CX3CR1, and CLEC7A, and was therefore designed as cDC2 ( Figure 5B ). Notably, c7 stood out because of its high expression of IL1RN, IFI6, FCER1G, BST2A, and CCL8 ( Figure 5A ).

Cells in c13 showing an isolated projection in the UMAP encompassed specific gene expression of migratory DCs such as CCR7, IL12B, CCL22, FSCN1, SAMSN1, IDO1, IL4L1, and MARCKSL1 ( Figure 5 ). This cluster could correspond to the cDC no. 3 cell population previously identified by flow cytometry as CD11c⁺MHCII⁺CD14⁻CD11b⁻Cadm1⁻.

Based on CSF1R expression, monocyte and MAC characterization resulted in the identification of eight clusters with distinct gene expression profiles ( Figure 4A ). Clusters 0, 2, 3, and 6 highly expressed genes commonly associated with MAC such as FCGR3A (CD16), CCL8, CD14, FCGR1A (CD64), OVA-DRA, and OVA-DMA ( Figure 6 ; Supplementary File 9A ; Supplementary Table 7 ). Among these clusters, c0 can be assigned to the main MAC cluster identified in the bovine MLN by Barut et al. (42) ( Figure 6A ; Supplementary Table 9 ) and c2 and c3 presented pro-inflammatory and anti-inflammatory MAC signatures. Cluster 6 was enriched in cell cycle-related genes including TOP2A, MKI67, PCNA, CENPF, and MCM5 and thus may represent a population of (tissue-resident) proliferating MAC that could participate in the replenishment of bona fide intestinal MAC by self-renewal, as reported in other species (17, 34, 43, 44) ( Figure 6 ; Supplementary Files 9D, E ).

A continuous increase in MAC-associated genes such as FCGR1A, OVA-DRA, OVA-DMA, and C1R from c8 via c4 toward c0, c2, and c3 ( Figure 6 ; Supplementary Table 8 ) was observed. Notably, among the most significant genes with higher expression in c4 compared to c8 were antigen presentation-related genes (OVA-DRA, OVA-DMA, OVA-DQA, and CD74) ( Supplementary File 9C ). Cells in c8 and c4 also expressed high levels of CD44, CLEC4E, and S100A9, reported to characterize monocytes and early MAC in the human intestine (17, 34), as well as VIM, S100A11, and ALO5XP, associated with monocytes in the bovine MLN (42) ( Figure 6 ; Supplementary Files 9A, C ). Moreover, c8 exclusively expressed CXXC5, a regulator of the differentiation of hematopoietic progenitors toward monocyte development (45) ( Figure 6B ; Supplementary File 9C ). Finally, expression of αVβ5 integrin, requiring the gene expression of both subunits IGTAV and ITGB5, was associated with mature MAC in the murine intestine (46). In our dataset, while expression of ITGAV was common for CSF1R-expressing clusters, ITGB5 expression was almost absent from c8 and increased from c4 to c0, c2, and c3 ( Figure 6 ). Taken together, these data suggest that a monocyte-to-MAC differentiation path from c8 considered as monocytes recently arrived in the intestinal mucosa, via c4 as an intermediary differentiation stage of MAC, toward mature MAC in c0, c2, and c3.

The kinetics of C. parvum infection in lambs was evaluated by daily monitoring of parasite excretion in the feces of animals, revealing that the peak of infection occurred at 5–6 dpi ( Figure 7A ), as previously observed in lambs with other C. parvum strains (47). The fecal parasite load then gradually decreased over time, leading to an approximate 100-fold decrease at 10 dpi, and thereafter, parasites started to become undetectable in the feces of lambs. In addition, the parasite load in different intestinal segments of lambs was measured with the N-Luc signal at the peak of infection and revealed the highest level of infection in the distal jejunum and IPP compared to the duodenum and colon (approximately 100 times less) ( Figure 7A ), confirming the preferential tropism of C. parvum for the distal part of the small intestine in this species. Clinical signs of lambs including body weight gain and fecal index were also daily monitored. Compared to the linear growth of uninfected animals, the weight of infected lambs stagnated from the onset of diarrhea (3 dpi) and decreased significantly at the peak of infection (5 dpi) ( Figure 7B ). Their daily body weight gain became similar to that of uninfected animals only after the end of the diarrheal episode (8 dpi).

To better understand the local immune responses to C. parvum infection in the intestine of ruminants, we analyzed the gene expression of known effectors of the anti-Cryptosporidium immune response in the intestine of infected lambs at two key time points: the infection peak, during which the innate immune response starts to control the parasite multiplication, and at 11–12 dpi, when the last parasites are very efficiently eliminated. The infection induced an increase of the gene expression of the chemokine CCL5 and the cytokine IFNγ (approximately 250 times) in the IPP of lambs during the resolution of infection ( Figure 8A ), which we also observed in the distal jejunum and JPP ( Supplementary File 10 ). We also observed an upregulation of the IL12p40 cytokine gene expression in the intestinal segments, but it was not significant ( Figure 8A ; Supplementary File 10 ).

Moreover, the infection induced the increase of the IDO1 gene expression in the distal small intestine of lambs from the peak of infection ( Figure 8A ; Supplementary File 10 ). IDO1 is an enzyme capable of catabolizing the tryptophan necessary for the parasite development, and is notably produced following the increase of the transcriptional factor STAT-1 in intestinal epithelial cells, induced by IFNγ (48). Thus, the weak increase of IDO1 in IPP at the peak of infection that subsequently intensified at 11–12 dpi could be linked to the increase of IFNγ observed only during the resolution of infection ( Figure 8A ).

Finally, results showed a decrease of the CCL20 gene expression at the peak of infection but no longer during the resolution ( Figure 8A ; Supplementary File 10 ). Similar results were observed in the neonatal murine model of C. parvum infection, with the highest diminution of CCL20 in the intestine at the peak of infection, but maintained at a lower amplitude in the later stages of the infection (49).

DCs, and especially cDC1, play a key role in controlling the acute phase of C. parvum infection in the murine neonatal model (7, 8, 50). Thus, to better characterize the intestinal cellular immune response to C. parvum infection in ruminants, we analyzed the abundance of MP subsets in the intestine of lambs and calves during the infection by flow cytometry. During the phase of parasite control (11–12 dpi), data highlighted an increase in MAC and cDC subset proportions except for the minor cDC no. 3 subset, with notably an earlier upregulation of cDC1 proportion already visible from the peak of infection (5 dpi) ( Figure 8B ; Supplementary File 11 ). In general, these results were observed regardless of the location in the intestine (ileum or jejunum) and the type of tissue (lymphoid or not). The increase of these cell subsets could be attributed to cell recruitment from blood precursors or to in situ proliferation.

The increase of cDC1 and MAC proportions in all three intestinal tissues in response to C. parvum infection was also found in calves at 11–12 dpi during the resolution of infection, as well as the lack of variation for cDC no. 3, but in contrast to the cDC2 proportion, which was only slightly increased in the IPP ( Supplementary File 12 ).