Immunoprofiling Reveals Novel Mast Cell Receptors and the Continuous Nature of Human Lung Mast Cell Heterogeneity

Background

Immunohistochemical analysis of granule-associated proteases has revealed that human lung mast cells constitute a heterogeneous population of cells, with distinct subpopulations identified. However, a systematic and comprehensive analysis of cell-surface markers to study human lung mast cell heterogeneity has yet to be performed.

Methods

Human lung mast cells were obtained from lung lobectomies, and the expression of 332 cell-surface markers was analyzed using flow cytometry and the LEGENDScreen™ kit. Markers that exhibited high variance were selected for additional analyses to reveal whether they were correlated and whether discrete mast cell subpopulations were discernable.

Results

We identified the expression of 102 surface markers on human lung mast cells, 23 previously not described on mast cells, of which several showed high continuous variation in their expression. Six of these markers were correlated: SUSD2, CD49a, CD326, CD34, CD66 and HLA-DR. The expression of these markers was also correlated with the size and granularity of mast cells. However, no marker produced an expression profile consistent with a bi- or multimodal distribution.

Conclusions

LEGENDScreen analysis identified more than 100 cell-surface markers on mast cells, including 23 that, to the best of our knowledge, have not been previously described on human mast cells. The comprehensive expression profiling of the 332 surface markers did not identify distinct mast cell subpopulations. Instead, we demonstrate the continuous nature of human lung mast cell heterogeneity.

Synergy of Distinct Dopamine Projection Populations in Behavioral Reinforcement

Dopamine neurons of the ventral tegmental area (VTA) regulate reward association and motivation. It remains unclear whether there are distinct dopamine populations to mediate these functions. Using mouse genetics, we isolated two populations of dopamine-producing VTA neurons with divergent projections to the nucleus accumbens (NAc) core and shell. Inhibition of VTA-core-projecting neurons disrupted Pavlovian reward learning, and activation of these cells promoted the acquisition of an instrumental response. VTA-shell-projecting neurons did not regulate Pavlovian reward learning and could not facilitate acquisition of an instrumental response, but their activation could drive robust responding in a previously learned instrumental task. Both populations are activated simultaneously by cues, actions, and rewards, and this co-activation is required for robust reinforcement of behavior. Thus, there are functionally distinct dopamine populations in the VTA for promoting motivation and reward association, which operate on the same timescale to optimize behavioral reinforcement.

Pleiotropic Role and Bidirectional Immunomodulation of Innate Lymphoid Cells in Cancer

Innate lymphoid cells (ILCs) are largely tissue resident and respond rapidly toward the environmental signals from surrounding tissues and other immune cells. The pleiotropic function of ILCs in diverse contexts underpins its importance in the innate arm of immune system in human health and disease. ILCs derive from common lymphoid progenitors but lack adaptive antigen receptors and functionally act as the innate counterpart to T-cell subsets. The classification of different subtypes is based on their distinct transcription factor requirement for development as well as signature cytokines that they produce. The discovery and subsequent characterization of ILCs over the past decade have mainly focused on the regulation of inflammation, tissue remodeling, and homeostasis, whereas the understanding of the multiple roles and mechanisms of ILCs in cancer is still limited. Emerging evidence of the potent immunomodulatory properties of ILCs in early host defense signifies a major advance in the use of ILCs as promising targets in cancer immunotherapy. In this review, we will decipher the non-exclusive roles of ILCs associated with both protumor and antitumor activities. We will also dissect the heterogeneity, plasticity, genetic evidence, and dysregulation in different cancer contexts, providing a comprehensive understanding of the complexity and diversity. These will have implications for the therapeutic targeting in cancer.

Identification of NeuN immunopositive cells in the adult mouse subventricular zone

In the adult rodent subventricular zone (SVZ), there are neural stem cells (NSCs) and the specialized neurogenic niche is critical to maintain their stemness. To date, many cellular and noncellular factors that compose the neurogenic niche and markers to identify subpopulations of Type A cells have been confirmed. In particular, neurotransmitters regulate adult neurogenesis and mature neurons in the SVZ have been only partially analyzed. Moreover, Type A cells, descendants of NSCs, are highly heterogeneous and more molecular markers are still needed to identify them. In the present study, we systematically classified NeuN, commonly used as a marker of mature and immature post-mitotic neurons, immunopositive (+) cells within the adult mouse SVZ. These SVZ-NeuN+ cells (SVZ-Ns) were mainly classified into two types. One was mature SVZ-Ns (M-SVZ-Ns). Neurochemical properties of M-SVZ-Ns were similar to those of striatal neurons, but their birth date and morphology were different. M-SVZ-Ns were generated during embryonic and early postnatal stages with bipolar peaks and extended their processes along the wall of the lateral ventricle. The second type was small SVZ-Ns (S-SVZ-Ns) with features of Type A cells. They expressed not only markers of Type A cells, but also proliferated and migrated from the SVZ to the olfactory bulb. Furthermore, S-SVZ-Ns could be classified into two types by their spatial locations and glutamic acid decarboxylase 67 expression. Our data indicate that M-SVZ-Ns are a new component of the neurogenic niche and S-SVZ-Ns are newly identified subpopulations of Type A cells.

The distribution and heterogeneity of mast cells in tongue from five different avian species

This study was conducted with the aim of determining the morphology, distribution and heterogeneity of mast cells in the tongues of seagull (Larus fuscus), common buzzard (Buteo buteo), goose (Anser anser), white stork (Ciconia ciconia) and Gerze rooster. The study used five samples of tongue material from each of the healthy adult avian species. The samples were fixed in 10% neutral-buffered formalin (NBF) solution, then, after routine tissue follow-up, the samples blocked with paraplast. Cross-sections with 5-6 μm of thickness were stained with the 0.5% toluidine blue and alcian blue/safranin O (AB/SO). In all five avian species, it was found that the mast cells were in different sizes and round, oval or spindle-shaped based on their place of distribution. Mast cell numbers were determined in stained with toluidine blue, examined ×40 objectives in a 1 mm² area. It was observed that mast cell density in subepithelial lamina propria and microscopic papilla was higher in the tongues of all species. Mast cell distribution and heterogeneity varied through the tongue, and there were more mast cells in the dorsal side of the tongue than the ventral side. The highest amount of mast cells was found in the tongue of the Gerze rooster among all five species. In the tongue cross-sections stained with the combined method of alcian blue/safranin O (AB/SO), the mast cells were stained as AB (+), SO (+) and AB/SO (+) (mixed).

Optimized Energy Harvesting, Cluster-Head Selection and Channel Allocation for IoTs in Smart Cities

This paper highlights three critical aspects of the internet of things (IoTs), namely (1) energy efficiency, (2) energy balancing and (3) quality of service (QoS) and presents three novel schemes for addressing these aspects. For energy efficiency, a novel radio frequency (RF) energy-harvesting scheme is presented in which each IoT device is associated with the best possible RF source in order to maximize the overall energy that the IoT devices harvest. For energy balancing, the IoT devices in close proximity are clustered together and then an IoT device with the highest residual energy is selected as a cluster head (CH) on a rotational basis. Once the CH is selected, it assigns channels to the IoT devices to report their data using a novel integer linear program (ILP)-based channel allocation scheme by satisfying their desired QoS. To evaluate the presented schemes, exhaustive simulations are carried out by varying different parameters, including the number of IoT devices, the number of harvesting sources, the distance between RF sources and IoT devices and the primary user (PU) activity of different channels. The simulation results demonstrate that our proposed schemes perform better than the existing ones.

A computational approach to map nucleosome positions and alternative chromatin states with base pair resolution

Understanding chromatin function requires knowing the precise location of nucleosomes. MNase-seq methods have been widely applied to characterize nucleosome organization in vivo, but generally lack the accuracy to determine the precise nucleosome positions. Here we develop a computational approach leveraging digestion variability to determine nucleosome positions at a base-pair resolution from MNase-seq data. We generate a variability template as a simple error model for how MNase digestion affects the mapping of individual nucleosomes. Applied to both yeast and human cells, this analysis reveals that alternatively positioned nucleosomes are prevalent and create significant heterogeneity in a cell population. We show that the periodic occurrences of dinucleotide sequences relative to nucleosome dyads can be directly determined from genome-wide nucleosome positions from MNase-seq. Alternatively positioned nucleosomes near transcription start sites likely represent different states of promoter nucleosomes during transcription initiation. Our method can be applied to map nucleosome positions in diverse organisms at base-pair resolution.