A pharmacological toolkit for human microglia identifies Topoisomerase I inhibitors as immunomodulators for Alzheimer's disease.

While efforts to identify microglial subtypes have recently accelerated, the relation of transcriptomically defined states to function has been largely limited to in silico annotations. Here, we characterize a set of pharmacological compounds that have been proposed to polarize human microglia towards two distinct states - one enriched for AD and MS genes and another characterized by increased expression of antigen presentation genes. Using different model systems including HMC3 cells, iPSC-derived microglia and cerebral organoids, we characterize the effect of these compounds in mimicking human microglial subtypes in vitro. We show that the Topoisomerase I inhibitor Camptothecin induces a CD74high/MHChigh microglial subtype which is specialized in amyloid beta phagocytosis. Camptothecin suppressed amyloid toxicity and restored microglia back to their homeostatic state in a zebrafish amyloid model. Our work provides avenues to recapitulate human microglial subtypes in vitro, enabling functional characterization and providing a foundation for modulating human microglia in vivo.

AP-1 transcription factor network explains diverse patterns of cellular plasticity in melanoma cells.

Cellular plasticity associated with fluctuations in transcriptional programs allows individual cells in a tumor to adopt heterogeneous differentiation states and switch phenotype during their adaptive responses to therapies. Despite increasing knowledge of such transcriptional programs, the molecular basis of cellular plasticity remains poorly understood. Here, we combine multiplexed transcriptional and protein measurements at population and single-cell levels with multivariate statistical modeling to show that the state of AP-1 transcription factor network plays a unifying role in explaining diverse patterns of plasticity in melanoma. We find that a regulated balance among AP-1 factors cJUN, JUND, FRA2, FRA1, and cFOS determines the intrinsic diversity of differentiation states and adaptive responses to MAPK inhibitors in melanoma cells. Perturbing this balance through genetic depletion of specific AP-1 proteins, or by MAPK inhibitors, shifts cellular heterogeneity in a predictable fashion. Thus, AP-1 may serve as a critical node for manipulating cellular plasticity with potential therapeutic implications.

Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy.

Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish the efficacy of cancer drugs. Efficacious combination therapies are thus needed to block drug-tolerant cells via minimizing the impact of heterogeneity. Probabilistic models such as Bliss independence have been developed to evaluate drug interactions and their combination efficacy based on probabilities of specific actions mediated by drugs individually and in combination. In practice, however, these models are often applied to conventional dose-response curves in which a normalized parameter with a value between zero and one, generally referred to as fraction of cells affected (fa), is used to evaluate the efficacy of drugs and their combined interactions. We use basic probability theory, computer simulations, time-lapse live cell microscopy, and single-cell analysis to show that fa metrics may bias our assessment of drug efficacy and combination effectiveness. This bias may be corrected when dynamic probabilities of drug-induced phenotypic events, i.e. induction of cell death and inhibition of division, at a single-cell level are used as metrics to assess drug efficacy. Probabilistic phenotype metrics offer the following three benefits. First, in contrast to the commonly used fa metrics, they directly represent probabilities of drug action in a cell population. Therefore, they deconvolve differential degrees of drug effect on tumor cell killing versus inhibition of cell division, which may not be correlated for many drugs. Second, they increase the sensitivity of short-term drug response assays to cell-to-cell heterogeneities and the presence of drug-tolerant subpopulations. Third, their probabilistic nature allows them to be used directly in unbiased evaluation of synergistic efficacy in drug combinations using probabilistic models such as Bliss independence. Altogether, we envision that probabilistic analysis of single-cell phenotypes complements currently available assays via improving our understanding of heterogeneity in drug response, thereby facilitating the discovery of more efficacious combination therapies to block drug-tolerant cells.

Role of heterogeneous cell population on modulation of dendritic cell phenotype and activation of CD8 T cells for use in cell-based immunotherapies.

Dendritic cell (DC)-based immunotherapies have much utility in their ability to prime antigen-specific adaptive immune responses. However, there does not yet exist a consensus standard to how DCs should be primed. In this study, we aimed to determine the role of heterogeneous co-cultures, composed of both CD11c+ (DCs) and CD11c- cells, in combination with monophosphoryl lipid A (MPLA) stimulation on DC phenotype and function. Upon DC priming in different co-culture ratios, we observed reduced expression of MHCII and CD86 and increased antigen uptake among CD11c+ cells in a CD11c- dependent manner. DCs from all culture conditions were induced to mature by MPLA treatment, as determined by secretion of pro-inflammatory cytokines IL-12 and TNF-α. Antigen-specific stimulation of CD4+ T cells was not modulated by co-culture composition, in terms of proliferation nor levels of IFN-γ. However, the presence of CD11c- cells enhanced cross-presentation to CD8+ T cells compared to purified CD11c+ cells, resulting in increased cell proliferation along with higher IFN-γ production. These findings demonstrate the impact of cell populations present during DC priming, and point to the use of heterogeneous cultures of DCs and innate immune cells to enhance cell-mediated immunity.