A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease.

Precision medicine in immune-mediated inflammatory diseases (IMIDs) requires a cellular understanding of treatment response. We describe a therapeutic atlas for Crohn's disease (CD) and ulcerative colitis (UC) following adalimumab, an anti-tumour necrosis factor (anti-TNF) treatment. We generated ~1 million single-cell transcriptomes, organised into 109 cell states, from 216 gut biopsies (41 subjects), revealing disease-specific differences. A systems biology-spatial analysis identified granuloma signatures in CD and interferon (IFN)-response signatures localising to T cell aggregates and epithelial damage in CD and UC. Pretreatment differences in epithelial and myeloid compartments were associated with remission outcomes in both diseases. Longitudinal comparisons demonstrated disease progression in nonremission: myeloid and T cell perturbations in CD and increased multi-cellular IFN signalling in UC. IFN signalling was also observed in rheumatoid arthritis (RA) synovium with a lymphoid pathotype. Our therapeutic atlas represents the largest cellular census of perturbation with the most common biologic treatment, anti-TNF, across multiple inflammatory diseases.

PEITH(Θ): perfecting experiments with information theory in Python with GPU support.

Motivation: Different experiments provide differing levels of information about a biological system. This makes it difficult, a priori, to select one of them beyond mere speculation and/or belief, especially when resources are limited. With the increasing diversity of experimental approaches and general advances in quantitative systems biology, methods that inform us about the information content that a given experiment carries about the question we want to answer, become crucial. Results: PEITH(Θ) is a general purpose, Python framework for experimental design in systems biology. PEITH(Θ) uses Bayesian inference and information theory in order to derive which experiments are most informative in order to estimate all model parameters and/or perform model predictions. Availability and implementation: https://github.com/MichaelPHStumpf/Peitho. Contact: m.stumpf@imperial.ac.uk or juliane.liepe@mpibpc.mpg.de.

The lifespan and kinetics of human dendritic cell subsets and their precursors in health and inflammation.

Dendritic cells (DC) are specialized mononuclear phagocytes that link innate and adaptive immunity. They comprise two principal subsets: plasmacytoid DC (pDC) and conventional DC (cDC). Understanding the generation, differentiation, and migration of cDC is critical for immune homeostasis. Through human in vivo deuterium-glucose labeling, we observed the rapid appearance of AXL+ Siglec6+ DC (ASDC) in the bloodstream. ASDC circulate for ∼2.16 days, while cDC1 and DC2 circulate for ∼1.32 and ∼2.20 days, respectively, upon release from the bone marrow. Interestingly, DC3, a cDC subset that shares several similarities with monocytes, exhibits a labeling profile closely resembling that of DC2. In a human in vivo model of cutaneous inflammation, ASDC were recruited to the inflammatory site, displaying a distinctive effector signature. Taken together, these results quantify the ephemeral circulating lifespan of human cDC and propose functions of cDC and their precursors that are rapidly recruited to sites of inflammation.

A human multi-cellular model shows how platelets drive production of diseased extracellular matrix and tissue invasion.

Guided by a multi-level "deconstruction" of omental metastases, we developed a tetra (four cell)-culture model of primary human mesothelial cells, fibroblasts, adipocytes, and high-grade serous ovarian cancer (HGSOC) cell lines. This multi-cellular model replicated key elements of human metastases and allowed malignant cell invasion into the artificial omental structure. Prompted by findings in patient biopsies, we used the model to investigate the role of platelets in malignant cell invasion and extracellular matrix, ECM, production. RNA (sequencing and quantitative polymerase-chain reaction), protein (proteomics and immunohistochemistry) and image analysis revealed that platelets stimulated malignant cell invasion and production of ECM molecules associated with poor prognosis. Moreover, we found that platelet activation of mesothelial cells was critical in stimulating malignant cell invasion. Whilst platelets likely activate both malignant cells and mesothelial cells, the tetra-culture model allowed us to dissect the role of both cell types and model the early stages of HGSOC metastases.