P015 CITE-seq analysis revealed immune cell diversity in colonic mesenteric lymph nodes from IBD patients
Bibliographic record
Abstract
Abstract Background Mononuclear phagocytes (MNPs), including dendritic cells (DCs), monocytes (Mo), and macrophages (Mac), are key inducers of the adaptive immune response. MNPs could circulate between blood, mucosa, and mesenteric lymph nodes (MLNs), where they interact with T cells, natural killer (NK) cells, and innate lymphoid cells (ILC), contributing to chronic inflammation. MNPs have been previously investigated at the transcriptomic level in the inflamed gut mucosa, but their molecular characterization at the single-cell level remains uncovered in inflamed MLNs of patients with inflammatory bowel diseases (IBD). Methods MLNs were collected from surgical colonic resections of patients with Crohn’s disease (CD; n=3) or ulcerative colitis (UC; n=3). Cell suspensions were multiplexed and then pooled for sorting CD45+CD3+CD19- T cells and CD45+CD3-CD19- non-T/non-B cells by flow cytometry. Next, sorted cells were combined and labeled with BD Abseq antibodies (antibodies conjugated to oligonucleotide tag). CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing), combining simultaneous RNA and protein expression, was performed on the BD RhapsodyTM platform. Results High-quality data from 3308 captured single cells (1471 from CD and 1837 from UC) identified four main immune cell populations (myeloid DCs/Mo/Mac, plasmacytoid DCs, T cells, and NK/innate lymphoid cells). We further segregated cell subsets into 16 MNP, 4 NK/ILC, and 9 T cell clusters. MNP subsets were characterized according to specific gene expression (HLA-DRA, CD1c, ITGAX, SIRPA, JCHAIN, IL3RA). They revealed transcriptionally distinct DC clusters, including one cluster of mature regulatory DC (mregDC) (LAMP3, CCR7), one cluster expressing AXL and THBD, and one cluster of CD103+ DCs expressing LTB, FLT3, and IL22RA2. Further analysis of MNP subsets also revealed 6 clusters of monocytes and macrophages, including inflammatory Mo, Inflammatory Mac, and regulatory Mac. Overall, the proportion of myeloid cells and pDC was higher in UC MLNs when compared to CD (29.6% and 21.6% versus 17.1% and 11.7%, p<0.0001) while the proportion of NK/ILC was higher in CD MLNs (11.7% versus 24.9%, p<0.0001). Comparison of differentially expressed genes (fold-change>1.5) between CD and UC samples showed that CD MLNs were enriched in NK-specific marker genes (KLRD1, IL2RB, NKG7, GZMA). In UC, the majority of upregulated genes related to myeloid gene markers (THBS1, HLA-DQA1, HLA-DRA, VCAN, IL1B, JCHAIN, and CXCL8). Conclusion CITE-Seq analysis of the colonic MLNs of patients with active IBD suggests differences in immune cell landscape gene expression between CD and UC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".