A physical wiring diagram for the human immune system.

The human immune system is composed of a distributed network of cells circulating throughout the body, which must dynamically form physical associations and communicate using interactions between their cell-surface proteomes1. Despite their therapeutic potential2, our map of these surface interactions remains incomplete3,4. Here, using a high-throughput surface receptor screening method, we systematically mapped the direct protein interactions across a recombinant library that encompasses most of the surface proteins that are detectable on human leukocytes. We independently validated and determined the biophysical parameters of each novel interaction, resulting in a high-confidence and quantitative view of the receptor wiring that connects human immune cells. By integrating our interactome with expression data, we identified trends in the dynamics of immune interactions and constructed a reductionist mathematical model that predicts cellular connectivity from basic principles. We also developed an interactive multi-tissue single-cell atlas that infers immune interactions throughout the body, revealing potential functional contexts for new interactions and hubs in multicellular networks. Finally, we combined targeted protein stimulation of human leukocytes with multiplex high-content microscopy to link our receptor interactions to functional roles, in terms of both modulating immune responses and maintaining normal patterns of intercellular associations. Together, our work provides a systematic perspective on the intercellular wiring of the human immune system that extends from systems-level principles of immune cell connectivity down to mechanistic characterization of individual receptors, which could offer opportunities for therapeutic intervention.

A nasal epithelial receptor for Staphylococcus aureus WTA governs adhesion to epithelial cells and modulates nasal colonization.

Nasal colonization is a major risk factor for S. aureus infections. The mechanisms responsible for colonization are still not well understood and involve several factors on the host and the bacterial side. One key factor is the cell wall teichoic acid (WTA) of S. aureus, which governs direct interactions with nasal epithelial surfaces. We report here the first receptor for the cell wall glycopolymer WTA on nasal epithelial cells. In several assay systems this type F-scavenger receptor, termed SREC-I, bound WTA in a charge dependent manner and mediated adhesion to nasal epithelial cells in vitro. The impact of WTA and SREC-I interaction on epithelial adhesion was especially pronounced under shear stress, which resembles the conditions found in the nasal cavity. Most importantly, we demonstrate here a key role of the WTA-receptor interaction in a cotton rat model of nasal colonization. When we inhibited WTA mediated adhesion with a SREC-I antibody, nasal colonization in the animal model was strongly reduced at the early onset of colonization. More importantly, colonization stayed low over an extended period of 6 days. Therefore we propose targeting of this glycopolymer-receptor interaction as a novel strategy to prevent or control S. aureus nasal colonization.

Cellular architecture shapes the naïve T cell response.

After antigen stimulation, naïve T cells display reproducible population-level responses, which arise from individual T cells pursuing specific differentiation trajectories. However, cell-intrinsic predeterminants controlling these single-cell decisions remain enigmatic. We found that the subcellular architectures of naïve CD8 T cells, defined by the presence (TØ) or absence (TO) of nuclear envelope invaginations, changed with maturation, activation, and differentiation. Upon T cell receptor (TCR) stimulation, naïve TØ cells displayed increased expression of the early-response gene Nr4a1, dependent upon heightened calcium entry. Subsequently, in vitro differentiation revealed that TØ cells generated effector-like cells more so compared with TO cells, which proliferated less and preferentially adopted a memory-precursor phenotype. These data suggest that cellular architecture may be a predeterminant of naïve CD8 T cell fate.

Targeting IL-1 controls refractory pityriasis rubra pilaris.

Pityriasis rubra pilaris (PRP) is a rare inflammatory skin disease with a poorly understood pathogenesis. Through a molecularly driven precision medicine approach and an extensive mechanistic pathway analysis in PRP skin samples, compared to psoriasis, atopic dermatitis, healed PRP, and healthy controls, we identified IL-1ß as a key mediator, orchestrating an NF-κB-mediated IL-1ß-CCL20 axis, including activation of CARD14 and NOD2. Treatment of three patients with the IL-1 antagonists anakinra and canakinumab resulted in rapid clinical improvement and reversal of the PRP-associated molecular signature with a 50% improvement in skin lesions after 2 to 3 weeks. This transcriptional signature was consistent with in vitro stimulation of keratinocytes with IL-1ß. With the central role of IL-1ß underscoring its potential as a therapeutic target, our findings propose a redefinition of PRP as an autoinflammatory keratinization disorder. Further clinical trials are needed to validate the efficacy of IL-1ß antagonists in PRP.

Ex vivo drug response heterogeneity reveals personalized therapeutic strategies for patients with multiple myeloma.

Multiple myeloma (MM) is a plasma cell malignancy defined by complex genetics and extensive patient heterogeneity. Despite a growing arsenal of approved therapies, MM remains incurable and in need of guidelines to identify effective personalized treatments. Here, we survey the ex vivo drug and immunotherapy sensitivities across 101 bone marrow samples from 70 patients with MM using multiplexed immunofluorescence, automated microscopy and deep-learning-based single-cell phenotyping. Combined with sample-matched genetics, proteotyping and cytokine profiling, we map the molecular regulatory network of drug sensitivity, implicating the DNA repair pathway and EYA3 expression in proteasome inhibitor sensitivity and major histocompatibility complex class II expression in the response to elotuzumab. Globally, ex vivo drug sensitivity associated with bone marrow microenvironmental signatures reflecting treatment stage, clonality and inflammation. Furthermore, ex vivo drug sensitivity significantly stratified clinical treatment responses, including to immunotherapy. Taken together, our study provides molecular and actionable insights into diverse treatment strategies for patients with MM.

Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis.

Myelofibrosis is a hematopoietic stem cell disorder belonging to the myeloproliferative neoplasms. Myelofibrosis patients frequently carry driver mutations in either JAK2 or Calreticulin (CALR) and have limited therapeutic options. Here, we integrate ex vivo drug response and proteotype analyses across myelofibrosis patient cohorts to discover targetable vulnerabilities and associated therapeutic strategies. Drug sensitivities of mutated and progenitor cells were measured in patient blood using high-content imaging and single-cell deep learning-based analyses. Integration with matched molecular profiling revealed three targetable vulnerabilities. First, CALR mutations drive BET and HDAC inhibitor sensitivity, particularly in the absence of high Ras pathway protein levels. Second, an MCM complex-high proliferative signature corresponds to advanced disease and sensitivity to drugs targeting pro-survival signaling and DNA replication. Third, homozygous CALR mutations result in high endoplasmic reticulum (ER) stress, responding to ER stressors and unfolded protein response inhibition. Overall, our integrated analyses provide a molecularly motivated roadmap for individualized myelofibrosis patient treatment.

Multiplexed high-throughput immune cell imaging reveals molecular health-associated phenotypes.

Phenotypic plasticity is essential to the immune system, yet the factors that shape it are not fully understood. Here, we comprehensively analyze immune cell phenotypes including morphology across human cohorts by single-round multiplexed immunofluorescence, automated microscopy, and deep learning. Using the uncertainty of convolutional neural networks to cluster the phenotypes of eight distinct immune cell subsets, we find that the resulting maps are influenced by donor age, gender, and blood pressure, revealing distinct polarization and activation-associated phenotypes across immune cell classes. We further associate T cell morphology to transcriptional state based on their joint donor variability and validate an inflammation-associated polarized T cell morphology and an age-associated loss of mitochondria in CD4+ T cells. Together, we show that immune cell phenotypes reflect both molecular and personal health information, opening new perspectives into the deep immune phenotyping of individual people in health and disease.

Deep Morphology Learning Enhances Ex Vivo Drug Profiling-Based Precision Medicine.

Drug testing in patient biopsy-derived cells can identify potent treatments for patients suffering from relapsed or refractory hematologic cancers. Here we investigate the use of weakly supervised deep learning on cell morphologies (DML) to complement diagnostic marker-based identification of malignant and nonmalignant cells in drug testing. Across 390 biopsies from 289 patients with diverse blood cancers, DML-based drug responses show improved reproducibility and clustering of drugs with the same mode of action. DML does so by adapting to batch effects and by autonomously recognizing disease-associated cell morphologies. In a post hoc analysis of 66 patients, DML-recommended treatments led to improved progression-free survival compared with marker-based recommendations and physician's choice-based treatments. Treatments recommended by both immunofluorescence and DML doubled the fraction of patients achieving exceptional clinical responses. Thus, DML-enhanced ex vivo drug screening is a promising tool in the identification of effective personalized treatments. SIGNIFICANCE: We have recently demonstrated that image-based drug screening in patient samples identifies effective treatment options for patients with advanced blood cancers. Here we show that using deep learning to identify malignant and nonmalignant cells by morphology improves such screens. The presented workflow is robust, automatable, and compatible with clinical routine. This article is highlighted in the In This Issue feature, p. 476.

Light-mediated discovery of surfaceome nanoscale organization and intercellular receptor interaction networks.

The molecular nanoscale organization of the surfaceome is a fundamental regulator of cellular signaling in health and disease. Technologies for mapping the spatial relationships of cell surface receptors and their extracellular signaling synapses would unlock theranostic opportunities to target protein communities and the possibility to engineer extracellular signaling. Here, we develop an optoproteomic technology termed LUX-MS that enables the targeted elucidation of acute protein interactions on and in between living cells using light-controlled singlet oxygen generators (SOG). By using SOG-coupled antibodies, small molecule drugs, biologics and intact viral particles, we demonstrate the ability of LUX-MS to decode ligand receptor interactions across organisms and to discover surfaceome receptor nanoscale organization with direct implications for drug action. Furthermore, by coupling SOG to antigens we achieved light-controlled molecular mapping of intercellular signaling within functional immune synapses between antigen-presenting cells and CD8+ T cells providing insights into T cell activation with spatiotemporal specificity. LUX-MS based decoding of surfaceome signaling architectures thereby provides a molecular framework for the rational development of theranostic strategies.

In-Depth Characterization of Monocyte-Derived Macrophages using a Mass Cytometry-Based Phagocytosis Assay.

Phagocytosis is a process in which target cells or particles are engulfed and taken up by other cells, typically professional phagocytes; this process is crucial in many physiological processes and disease states. The detection of targets for phagocytosis is directed by a complex repertoire of cell surface receptors. Pattern recognition receptors directly detect targets for binding and uptake, while opsonic and complement receptors detect objects coated by soluble factors. However, the importance of single and combinatorial surface marker expression across different phenotypes of professional phagocytes is not known. Here we developed a novel mass cytometry-based phagocytosis assay that enables the simultaneous detection of phagocytic events in combination with up to 40 other protein markers. We applied this assay to distinct monocyte derived macrophage (MDM) populations and found that prototypic M2-like MDMs phagocytose more E. coli than M1-like MDMs. Surface markers such as CD14, CD206, and CD163 rendered macrophages phagocytosis competent, but only CD209 directly correlated with the amount of particle uptake. Similarly, M2-like MDMs also phagocytosed more cancer cells than M1-like MDMs but, unlike M1-like MDMs, were insensitive to anti-CD47 opsonization. Our approach facilitates the simultaneous study of single-cell phenotypes, phagocytic activity, signaling and transcriptional events in complex cell mixtures.