Organized Chaos: Deciphering Immune Cell Heterogeneity’s Role in Inflammation in the Heart

During homeostasis, immune cells perform daily housekeeping functions to maintain heart health by acting as sentinels for tissue damage and foreign particles. Resident immune cells compose 5% of the cellular population in healthy human ventricular tissue. In response to injury, there is an increase in inflammation within the heart due to the influx of immune cells. Some of the most common immune cells recruited to the heart are macrophages, dendritic cells, neutrophils, and T-cells. In this review, we will discuss what is known about cardiac immune cell heterogeneity during homeostasis, how these cell populations change in response to a pathology such as myocardial infarction or pressure overload, and what stimuli are regulating these processes. In addition, we will summarize technologies used to evaluate cell heterogeneity in models of cardiovascular disease.

Ribonucleotide Reductase Regulatory Subunit M2 as a Driver of Glioblastoma TMZ-Resistance through Modulation of dNTP Production

Glioblastoma (GBM) remains one of the most resistant and fatal forms of cancer. Previous studies have examined primary and recurrent GBM tumors, but it is difficult to study tumor evolution during therapy where resistance develops. To investigate this, we performed an in vivo single-cell RNA sequencing screen in a patient-derived xenograft (PDX) model. Primary GBM was modeled by mice treated with DMSO control, recurrent GBM was modeled by mice treated with temozolomide (TMZ), and during therapy GBM was modeled by mice euthanized after two of five TMZ treatments. Our analysis revealed the cellular population present during therapy to be distinct from primary and recurrent GBM. We found the Ribonucleotide Reductase gene family to exhibit a unique signature in our data due to an observed subunit switch to favor RRM2 during therapy. GBM cells were shown to rely on RRM2 during therapy causing RRM2-knockdown (KD) cells to be TMZ-sensitive. Using targeted metabolomics, we found RRM2-KDs to produce less dGTP and dCTP than control cells in response to TMZ (p<0.0001). Supplementing RRM2-KDs with deoxycytidine and deoxyguanosine rescued TMZ-sensitivity, suggesting an RRM2-driven mechanism of chemoresistance, established by regulating the production of these nucleotides. In vivo, tumor-bearing mice treated with the RRM2-inhibitor, Triapine, in combination with TMZ, survived longer than mice treated with TMZ alone (p<0.01), indicating promising clinical opportunities in targeting RRM2. Our data present a novel understanding of RRM2 activity, and its alteration during therapeutic stress as response to TMZ-induced DNA damage.

Mathematical model and computational scheme for multi-phase modeling of cellular population and microenvironmental dynamics in soft tissue

In this paper we introduce a system of partial differential equations that is capable of modeling a variety of dynamic processes in soft tissue cellular populations and their microenvironments. The model is designed to be general enough to simulate such processes as tissue regeneration, tumor growth, immune response, and many more. It also has built-in flexibility to include multiple chemical fields and/or sub-populations of cells, interstitial fluid and/or extracellular matrix. The model is derived from the conservation laws for mass and linear momentum and therefore can be classified as a continuum multi-phase model. A careful choice of state variables provides stability in solving the system of discretized equations defining advective flux terms. A concept of deviation from normal allows us to use simplified constitutive relations for stresses. We also present an algorithm for computing numerical approximations to the solutions of the system and discuss properties of these approximations. We demonstrate several examples of applications of the model. Numerical simulations show a significant potential of the model for simulating a variety of processes in soft tissues.

Diagnosing a rare case of lymphocytic infiltration of the pituitary gland without the invasive procedure of pituitary biopsy

Background. Lymphocytic infiltration of the pituitary is an unusual inflammatory disorder of the pituitary and indicated to be autoimmune in origin. Presentations depend on the site of involvement and degree of destruction of the cellular population of the pituitary and may range from an asymptomatic state to pan-hypopituitarism with or without mass effects. In the present study, we represent a rare case of lymphocytic infiltration of the pituitary gland who was diagnosed with such condition and the subsequent management. Case presentation. A 22-year-old male who was admitted with symptoms of increased thirst and excessive fatigue. Following a thorough physical, clinical, laboratory, biochemistry, and imaging examinations a timely diagnosis of lymphocytic infiltration of the pituitary was made without using the invasive procedure of pituitary biopsy. In light of the diagnosis prompt management with the mainstay of glucocorticoid was started along with replenishing the other deficient hormones. In this study we describe a rare case of lymphocytic infiltration of the pituitary discussing in terms of epidemiology, sign and symptoms, laboratory evaluation, imaging studies, histopathology, management, and the usual outcome. Conclusion. Lymphocytic infiltration of the pituitary gland can be diagnosed with the clinical presentation along with lab evaluation and imaging but without pituitary biopsy, which could help in an early and accurate diagnosis which is the basis for better management of the rare condition.

Single-Cell Profiling Identifies Cell Subsets with Inflammatory Makers Expression in Colon of Heterogeneous Nuclear Ribonucleoprotein (hnRNPI) Knockout Mice

Objectives Previously we found that intestinal-epithelial-cell-specific-hnRNPI knockout (KO) upregulates pro-inflammatory cytokines expression in colon, suggesting a potential link between hnRNPI KO and colonic immunity. Moreover, high protein diets were found to inhibit the inflammatory responses in KO mice, mechanism remains unclear. Hence, this current study is aimed to profile cell types in colon of hnRNPI wildtype (WT) and KO mice, characterize differences on cellular population, and identify cell types mostly responsible for the cytokine expression. Methods In this study, whole colon tissues from WT and KO mice (n = 3) were collected for scRNA-seq. Single cells were filtered by mitochondria percentage and UMI counts. 31,798 cells were used for profiling. Uniform manifold approximation and projection (UMAP) was adopted for dimension reduction and graph clustering, proportion of each cell subtype was normalized to cell density. Gene expression of specific pro-inflammatory markers were calculated by Loupe Browser (10X Genomics). Results A total of 25 clusters were sorted to the following cell types: B-cell, endothelial, epithelial, erythrocytes, fibroblast, innate lymphoid cell (ILC), mast, monocytes, myeloid and T-cell. Comparing to WT, proportion of tuft cells is increased (P = 0.08) in KO. As for immune cells, total T-cell (P = 0.1), especially non-cytotoxic T-cell (P &lt; 0.05), as well as ILC (P &lt; 0.01) and naïve B-cell (P = 0.09) all increased in KO. Previously identified cytokines that were downregulated by the addition of dietary protein in KO showed associations to specific cell type clusters. Specifically, IL1β mostly expressed in myeloid cells, IL6 mostly in mast cells, Ccl2 mostly in myeloid and mast cells while Cxcl1 expressed evenly in different clusters. Conclusions In summary, this current study reports that hnRNPI knockout significantly affects the cellular population in colon, regulating pro-inflammatory responses by recruiting non-cytotoxic T-cell, naïve B-cell and ILC. Dietary protein may inhibit inflammation trigged by knockout of hnRNPI via modulations of cytokine expression in mast and myeloid cells. Funding Sources USDA Cooperative State Research, Education and Extension Service (Hatch project numbers # ILLU-971,351 and ILLU-698,923), and the Office of the Vice Chancellor for Research in University of Illinois at Urbana-Champaign.

Evaluation of the Influence of Faradarmani Consciousness Field on Viral Growth

The Consciousness Fields according to Taheri, are non-matter and non-energetic fields with the ability to have reproducible effects in the laboratory and experimental environments. Previous studies related to studying the effects of Faradarmani Consciousness Fields (FCF) on plant characteristics and animal disease models reveal that FCF functions in optimizing the system under study. Significant effects of Faradarmani Consciousness Fields on bacterial and cellular population growth led us to investigate the effectiveness of Faradarmani Consciousness Field on viral titer and type. For this, we stratified various viruses into envelope or non-envelope as well as DNA and RNA types. This study aims at assessing the influence of FCF on four types of virus combinations using TCID50 assay. We tested the effect of FCF on pre-determined titers of selected viruses and found that FCF changed the viral titers by 0.4 to 1.85 logs compared to the control group. As the results suggest, the physical structure of the viruses and their genome type have notable effects on their response to the FCF.

Single-Cell Transcriptome Profiling Reveals Intratumoral Heterogeneity in Human Chordomas

Background: Chordoma is a rare and aggressive bone tumor with high recurrence. The intra-tumoral heterogeneity of chordomas is poorly understood, limiting the development of effective therapeutic strategies. Methods: Single-cell RNA sequencing was performed to delineate the transcriptomic landscape of chordomas. Six tumor samples of pathologically classical chordomas were obtained, and 33,737 cells that passed quality control were included in the analysis. Results: The main cellular populations identified with specific markers were: chordomas cells (6392, 47.6%), fibroblasts (6945, 20.6%), mononuclear phagocytes (4734, 14.0%), and T/NK cells (3944, 11.7%). Downstream analysis was performed according to each cellular population. There were six subclusters of chordomas, which exhibited properties of an epithelial-like extracellular matrix, and stem cells with immunosuppression. Although few immune checkpoint was detected on cytotoxic immune cells such as T and NK cells, there was strong immunosuppression exerted by Tregs and M2 macrophages. In addition, the cellular interactions indicated an enhanced TGF-β signaling pathway as the main mechanism for tumor progression, invasion, and immunosuppression in chordomas. Conclusion: Our study contribute to the clarification of intra-tumoral heterogeneity, and may pave the way to identify potential therapeutic targets in chordomas.

Cellular Reprogramming in Bursts and Phases

As a biochemical process, direct cellular reprogramming is slow and complex. The early stages of this process is the most critical determinant of successful phenotypic conversion. This study provides insight into the statistical signatures that describe temporal structure in the reprogramming process. We examine two sources of variation in reprogramming cells: clonal instances from various tissues of origin and rate of expansion between these lines. Our analytical strategy involved modeling the potential of populations to reprogram, and then applying statistical models to capture this potential in action. This two-fold approach utilizes both conventional and novel techniques that allow us to infer and confirm a host of properties that define the phenomenon. These results can be summarized in a number of ways, and essentially suggest that reprogramming is organized around changes in gene expression phenotype (phases) which happens sporadically across a cellular population (bursts).

Intra-Ramanome Correlation Analysis Unveils Metabolite Conversion Network from an Isogenic Cellular Population

Revealing dynamic features of cellular systems, such as links among metabolic phenotypes, typically requires a time- or condition-series set of samples. Here Intra-Ramanome Correlation analysis (IRCA) was proposed to achieve this goal from just one snapshot of an isogenic population, by pairwise correlating among cells all the thousands of Raman bands from Single-cell Raman Spectra (SCRS), i.e., based on the intrinsic inter-cellular metabolic heterogeneity. IRCA of Chlamydomonas reinhardtii under nitrogen depletion revealed a metabolite conversion network at each time point and its temporal dynamics that feature protein-to-starch conversion followed by starch-to-TAG conversion (plus conversion of membrane lipids to TAG). Such correlation patterns in IRCA were abrased by knocking out the starch-biosynthesis pathway yet fully restored by genetic complementation. Extension to 64 ramanomes from microalgae, fungi and bacteria under various conditions suggests IRCA-derived metabolite conversion network as an intrinsic, reliable, species-resolved and state-sensitive metabolic signature of isogenic cellular population. The high throughput, low cost, excellent scalability and broad extendibility of IRCA suggest its broad application in cellular systems.