Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging.

Multiplex tissue imaging are a collection of increasingly popular single-cell spatial proteomics and transcriptomics assays for characterizing biological tissues both compositionally and spatially. However, several technical issues limit the utility of multiplex tissue imaging, including the limited number of molecules (proteins and RNAs) that can be assayed, tissue loss, and protein probe failure. In this work, we demonstrate how machine learning methods can address these limitations by imputing protein abundance at the single-cell level using multiplex tissue imaging datasets from a breast cancer cohort. We first compared machine learning methods' strengths and weaknesses for imputing single-cell protein abundance. Machine learning methods used in this work include regularized linear regression, gradient-boosted regression trees, and deep learning autoencoders. We also incorporated cellular spatial information to improve imputation performance. Using machine learning, single-cell protein expression can be imputed with mean absolute error ranging between 0.05-0.3 on a [0,1] scale. Finally, we used imputed data to predict whether single cells were more likely to come from pre-treatment or post-treatment biopsies. Our results demonstrate (1) the feasibility of imputing single-cell abundance levels for many proteins using machine learning; (2) how including cellular spatial information can substantially enhance imputation results; and (3) the use of single-cell protein abundance levels in a use case to demonstrate biological relevance.

Regulation of Calcium Oscillations in ß-Cells by Co-activated Cannabinoid Receptors.

Pharmacological treatment of pancreatic ß cells targeting cannabinoid receptors 1 and 2 (CB1 and CB2) has been shown to result in significant effects on insulin release, possibly by modulating intracellular calcium levels ([Ca2+]i). It is unclear how the interplay of CB1 and CB2 affects insulin secretion. Here, we demonstrate by the use of highly specific receptor antagonists and the recently developed photo-releasable endocannabinoid 2-arachidonoylglycerol that both receptors have counteracting effects on cytosolic calcium oscillations. We further show that both receptors are juxtaposed in a way that increases [Ca2+]i oscillations in silent ß cells but dampens them in active ones. This study highlights a functional role of CB1 and CB2 acting in concert as a compensator/attenuator switch for regulating ß cell excitability.

Chemical Biology Toolbox for Studying Pancreatic Islet Function - A Perspective.

The islets of Langerhans represent one of the many complex endocrine organs in mammals. Traditionally, islet function is studied by a mixture of physiological, cell biological, and molecular biological methods. Recently, novel techniques stemming from the ever-increasing toolbox provided by chemical laboratories have been added to the repertoire. Many emerging techniques will soon be available to manipulate and monitor islet function at the single-cell level and potentially in intact model animals, as well as in isolated human islets. Here, we review the most current small-molecule-based and genetically encoded molecular tool sets available to study islet function. We provide an outlook regarding future tool developments that will impact islet research, with a special focus on the interplay between different islet cell types.

Endogenous Fatty Acids Are Essential Signaling Factors of Pancreatic ß-Cells and Insulin Secretion.

The secretion of insulin from ß-cells depends on extracellular factors, in particular glucose and other small molecules, some of which act on G-protein-coupled receptors. Fatty acids (FAs) have been discussed as exogenous secretagogues of insulin for decades, especially after the FA receptor GPR40 (G-protein-coupled receptor 40) was discovered. However, the role of FAs as endogenous signaling factors has not been investigated until now. In the present work, we demonstrate that lowering endogenous FA levels in ß-cell medium by stringent washing or by the application of FA-free (FAF) BSA immediately reduced glucose-induced oscillations of cytosolic Ca2+ ([Ca2+]i oscillations) in MIN6 cells and mouse primary ß-cells, as well as insulin secretion. Mass spectrometry confirmed BSA-mediated removal of FAs, with palmitic, stearic, oleic, and elaidic acid being the most abundant species. [Ca2+]i oscillations in MIN6 cells recovered when BSA was replaced by buffer or as FA levels in the supernatant were restored. This was achieved by recombinant lipase-mediated FA liberation from membrane lipids, by the addition of FA-preloaded FAF-BSA, or by the photolysis of cell-impermeant caged FAs. Our combined data support the hypothesis of FAs as essential endogenous signaling factors for ß-cell activity and insulin secretion.