Immune Cell Dynamics Research Articles

Exploring anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-coronary artery bypass graft surgery.

This study leverages the GSE4386 dataset, obtained from atrial tissue samples post-coronary artery bypass graft (CABG) surgery, to investigate the impact of anesthetic agents (sevoflurane and propofol) on gene expression and immune cell infiltration. Hierarchical clustering and box plots were employed for dataset preprocessing, highlighting a significant outlier (sample GSM99282), subsequently removed to ensure data integrity. Differentially expressed genes (DEGs) were identified using volcano plots based on specific log-fold-change and P-value thresholds. Additional analyses included the Friends approach, Spearman's correlation, and gene set enrichment analysis (GSEA), exploring functional annotations and pathways. Heatmaps and bubble plots depicted DEGs, revealing distinct expression patterns between the sevoflurane and propofol groups. Friends analysis identified top genes based on log fold changes, further correlated using Spearman's method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses illustrated functional annotations of DEGs, while GSEA highlighted enriched biological categories. Immune cell infiltration analysis showcased varied cellular presence post-CABG. ESTIMATE algorithm scores demonstrated differences in immune, stroma, and estimate scores. Microenvironment Cell Populations-counter (MCPcounter) revealed an increased abundance of cytotoxic lymphocytes in the sevoflurane group, confirmed by a single sample GSEA. CIBERSORT algorithm identified distinct immune cell compositions, highlighting differences in macrophage M0 prevalence between sevoflurane and propofol groups. This comprehensive analysis provides insights into anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-CABG surgery. The identified DEGs and immune cell compositions offer potential biomarkers and therapeutic targets for refining anesthetic strategies in cardiac surgeries.

Lactate's impact on immune cells in sepsis: unraveling the complex interplay.

Lactate significantly impacts immune cell function in sepsis and septic shock, transcending its traditional view as just a metabolic byproduct. This review summarizes the role of lactate as a biomarker and its influence on immune cell dynamics, emphasizing its critical role in modulating immune responses during sepsis. Mechanistically, key lactate transporters like MCT1, MCT4, and the receptor GPR81 are crucial in mediating these effects. HIF-1α also plays a significant role in lactate-driven immune modulation. Additionally, lactate affects immune cell function through post-translational modifications such as lactylation, acetylation, and phosphorylation, which alter enzyme activities and protein functions. These interactions between lactate and immune cells are central to understanding sepsis-associated immune dysregulation, offering insights that can guide future research and improve therapeutic strategies to enhance patient outcomes.

Genetically predicted HLA-DR+ natural killer cells as potential mediators in the lipid-coronary artery disease/ calcification (CAD/CAC) causal pathway.

Coronary artery disease (CAD) imposes a significant global health burden, necessitating a deeper comprehension of its genetic foundations to uncover innovative therapeutic targets. Employing a comprehensive Mendelian randomization (MR) approach, we aimed to explore the genetic associations between lipid profiles, immune cell phenotypes, and CAD risk. Utilizing data from recent large-scale genome-wide association studies (GWAS), we scrutinized 179 lipid and 731 immune cell phenotypes to delineate their genetic contributions to CAD pathogenesis, including coronary artery calcification (CAC). Moreover, specific immune cell phenotypes were examined as potential mediators of the lipid-CAD/CAC causal pathway. Among the 162 lipid species with qualified instrumental variables (IVs) included in the analysis, we identified 36 lipids that exhibit a genetic causal relationship with CAD, with 29 being risk factors and 7 serving as protective factors. Phosphatidylethanolamine (18:0_20:4) with 8 IVs (OR, 95% CI, P-value: 1.04, 1.02-1.06, 1.50E-04) met the Bonferroni-corrected significance threshold (0.05/162=3.09E-04). Notably, all 18 shared lipids were determined to be risk factors for both CAD and CAC, including 16 triacylglycerol traits (15 of which had ≥ 3 IVs), with (50:1) exhibiting the highest risk [OR (95% CI) in CAC: 1.428 (1.129-1.807); OR (95% CI) in CAD: 1.119 (1.046-1.198)], and 2 diacylglycerol traits. Furthermore, we identified HLA DR+ natural killer cells (IVs = 3) as nominally significant with lipids and as potential mediators in the causal pathway between diacylglycerol (16:1_18:1) or various triacylglycerols and CAD (mediated effect: 0.007 to 0.013). This study provides preliminary insights into the genetic correlations between lipid metabolism, immune cell dynamics, and CAD susceptibility, highlighting the potential involvement of natural killer cells in the lipid-CAD/CAC causal pathway and suggesting new targets for therapy. Further evidence is necessary to substantiate our findings.

Exendin-4-enriched exosomes from hUCMSCs alleviate diabetic nephropathy via gut microbiota and immune modulation.

Diabetic nephropathy (DN) presents a significant therapeutic challenge, compounded by complex pathophysiological mechanisms. Recent studies suggest Exendin-4 (Ex-4) as a potential ameliorative agent for DN, albeit with unclear mechanisms. This research investigates the effects and underlying mechanisms of Ex-4-enriched exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSCs) on DN, focusing on their renoprotective properties and interactions with gut microbiota. Exosomes from hUCMSCs (hUCMSCs-Exo) were loaded with Ex-4 via electroporation. A streptozotocin (STZ) -induced DN mouse model was employed to assess the therapeutic impact of these engineered exosomes. The study further explored immune cell dynamics, mainly CD4+ regulatory T (Treg) cells, using bioinformatics, flow cytometry, and the influence of gut microbiota through antibiotic treatment and specific bacterial reintroduction. Treatment with hUCMSCs-Exo@Ex-4 significantly improved key DN markers, including blood glucose and proteinuria, alleviating kidney damage. A notable decrease in natural Treg cell infiltration in DN was observed, while Ex-4-loaded exosomes promoted CD4+ Treg cell induction. The therapeutic benefits of hUCMSCs-Exo@Ex-4 were diminished upon CD4+ Treg cell depletion, underscoring their role in this context. Notably, CD4+ Treg cell induction correlated with the presence of Prevotella species, and disruption of gut microbiota adversely affected these cells and the therapeutic efficacy of the treatment. However, the reintroduction of Prevotella strains counteracted these adverse effects. This study elucidates a novel therapeutic mechanism of Ex-4-loaded hUCMSCs exosomes in DN, highlighting the induction of CD4+ Treg cells mediated by specific gut microbiota components. These findings underscore the potential of leveraging gut microbiota and immune cell interplay in developing effective DN treatments.

Lab-on-chip technologies for exploring the gut-immune axis in metabolic disease.

The continued rise in metabolic diseases such as obesity and type 2 diabetes mellitus poses a global health burden, necessitating further research into factors implicated in the onset and progression of these diseases. Recently, the gut-immune axis, with diet as a main regulator, has been identified as a possible role player in their development. Translation of conventional 2D in vitro and animal models is however limited, while human studies are expensive and preclude individual mechanisms from being investigated. Lab-on-chip technology therefore offers an attractive new avenue to study gut-immune interactions. This review provides an overview of the influence of diet on gut-immune interactions in metabolic diseases and a critical analysis of the current state of lab-on-chip technology to study this axis. While there has been progress in the development of "immuno-competent" intestinal lab-on-chip models, with studies showing the ability of the technology to provide mechanical cues, support longer-term co-culture of microbiota and maintain in vivo-like oxygen gradients, platforms which combine all three and include intestinal and immune cells are still lacking. Further, immune cell types and inclusion of microenvironment conditions which enable in vivo-like immune cell dynamics as well as host-microbiome interactions are limited. Future model development should focus on combining these conditions to create an environment capable of hosting more complex microbiota and immune cells to allow further study into the effects of diet and related metabolites on the gut-immune ecosystem and their role in the prevention and development of metabolic diseases in humans.

Analysis of the differences in immune-related genes and immune cell subtypes in acute myocardial infarction.

Acute myocardial infarction (AMI) continues to be a leading cause of death globally, with distinct immune cell dynamics in ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) playing a critical role in disease progression and patient outcomes. Sample data for STEMI and NSTEMI were downloaded from the Sequence Read Archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra). Differences and correlations of immune infiltrating cells were assessed by CIBERSORT. Differentially expressed genes (DEGs) were identified between STEMI and NSTEMI, followed by functional analysis. Immune-related DEGs were further identified. Some immune-related DEGs were selected to perform expression verification using real-time PCR. There was a significant difference in immune cells between STEMI and NSTEMI, including activated dendritic cells, memory CD4 T cells, mast cells, and CD8 T cells. A total of 229 DEGs were identified, with functions related to inflammatory regulation and drug metabolism. A total of 21 immune-related DEGs, which may play important roles in STEMI and NSTEMI, were identified. Among the 21 immune-related DEGs, genes like CCL18, NRP2, CXCR2, CXCL9, KIR2DL4, BPIFB1, and IL33 were significantly correlated with immune cells and had a tendency for differential expression between STEMI and NSTEMI patients. Our study reveals differences in the distribution of immune cell subsets between STEMI and NSTEMI, highlighting key immune-related genes and their association with immune cells, which may provide new insights into the treatment of AMI.

Insights from the Analysis of the Sepsis Dataset: Understanding the Immune Dynamics and Molecular Pathways in Sepsis

Sepsis, a critical medical condition instigated by infections, profoundly alters molecular and cellular immune responses. This study focused on the GSE54514 dataset obtained from the GEO database to uncover the complex gene expression patterns and related pathways in sepsis. A total of 42 genes were found to be expressed differently in septic patients compared to those of healthy individuals. The enrichment analyses of pathways revealed the disruption of natural immune pathways such as toll-like receptor signaling, regulation of actin cytoskeleton, and NOD-like receptor signaling. Through ssGSEA analysis, we revealed a strong association between sepsis and immune cell dynamics, finding significant correlations with HLA-related genes and distinct immune cell populations. Furthermore, genes such as CCL5, CD274, CD3E, and CD8A were linked with pathways, notably the “ribosome” pathway, suggesting potential roles in sepsis-related immune responses. The extensive examination provides fresh perspectives on the gene expression and pathway changes in sepsis, laying the groundwork for upcoming therapeutic interventions and a more profound comprehension of this intricate condition.

Viperin mutation is linked to immunity, immune cell dynamics, and metabolic alteration during VHSV infection in zebrafish.

Viperin is a prominent antiviral protein found in animals. The primary function of Viperin is the production of 3'-deoxy-3',4'-didehydro-cytidine triphosphate (ddhCTP), an inhibitory nucleotide involved in viral RNA synthesis. Studies in mammalian models have suggested that ddhCTP interferes with metabolic proteins. However, this hypothesis has yet to be tested in teleost. In this study, the role of Viperin in regulating metabolic alterations during viral hemorrhagic septicemia virus (VHSV) infection was tested. When infected with VHSV, viperin -/- fish showed considerably higher mortality rates. VHSV copy number and the expression of the NP gene were significantly increased in viperin -/- fish. Metabolic gene analysis revealed significant differences in soda, hif1a, fasn, and acc expression, indicating their impact on metabolism. Cholesterol analysis in zebrafish larvae during VHSV infection showed significant upregulation of cholesterol production without Viperin. In vitro analysis of ZF4 cells suggested a considerable reduction in lipid production and a significant upregulation of reactive oxygen species (ROS) generation with the overexpression of viperin. Neutrophil and macrophage recruitment were significantly modulated in viperin -/- fish compared to the wild-type (WT) fish. Thus, we have demonstrated that Viperin plays a role in interfering with metabolic alterations during VHSV infection.

Novel insights into HBV‐hepatocellular carcinoma at single‐cell sequencing

AbstractA significant proportion of hepatocellular carcinoma (HCC) is pathologically associated with hepatitis B virus (HBV) infection, followed by unsatisfied clinical outcomes. The increasing unmet need for HBV‐associated hepatocellular carcinoma (HBV‐HCC) treatment drives to deeper understand the role of the intricate immune microenvironment, tumor cell plasticity and dynamics of tumor evolution in HBV‐associated hepatic carcinogenesis. Thus, a comprehensive understanding of cross‐talk between HBV, host cells, and tumor microenvironment is of fundamental importance for identifying immune imbalance and heterogeneity in HBV‐HCC. Over the past 5 years, the application of single‐cell RNA sequencing (scRNA‐seq) in the understanding of heterogeneity and dynamics of immune cells, clonal evolution, and cancer stem cell (CSC) subsets of tumor cells has established a landscape for HBV‐HCC tumor ecosystem. Novel insights into anatomizing immune escape mechanisms and tumor drug resistance have remarkably facilitated the revolution of HBV‐HCC clinical treatment. Here, we provided a summary of HCC at single‐cell resolution and details on the basic workflow, limitations, and improvements of scRNA‐seq. The review highlights novel insights derived from scRNA‐seq on advances in the immune microenvironment and tumor heterogeneity of HBV‐HCC.

Single Cell Multi-Omic Analysis of Tumor Microenvironment Evolution across the Disease Spectrum of Multiple Myeloma Identifies Differential Mechanisms of Immune Suppression

Background: Multiple myeloma (MM) is preceded by the precursor states of monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). The transformation of these precursors into myeloma is influenced not only by the evolution of tumor itself but also by the tumor microenvironment (TME). However, the specific molecular mechanisms and factors within the TME that drive this malignant progression remain largely unknown. Therefore, exploring the TME from non-malignant precursor stages to active myeloma could facilitate the development of novel therapeutic strategies aimed at slowing down this progression and possibly eradicating MM. Methods: We performed paired scRNA-seq, scTCR-seq and scBCR-seq on 148 freshly collected BM aspirate samplesincluding 73 relapsed refractory (RR) RRMM, 16 newly diagnosed (ND) MM, 34 SMM, 21 MGUS and 4 normal BM (nBM) samples. BM aspirates were subjected to CD138+ selection (n=19) or processed as whole BM (WBM) (n=129, among which 73 samples were also enriched for CD138+ cells). cDNA libraries were prepared from enriched CD138+ (n=92) and WBM samples (n=129) followed by simultaneous 5' gene expression (scRNA-seq) and T/B cell receptor sequencing (scTCR/BCR-seq). Single-cell data was processed as previously described (Dang et. al, Cancer Cell, 2023). Results: We profiled 656,371 high-quality cells including 344,665 CD138+ and 311,706 TME cells. We also obtained scTCR-seq and scBCR-seq data on 86,244 and 566,155 cells, respectively. Among them, 394,187 out of 652,399 cells had paired scRNA-seq data. Unsupervised clustering analysis revealed 15 different major TME cell types. Sub-clustering of each major cell type further resolved them into different subsets, resulting in a total of 94 TME cell subsets ( Figure). Overall, we observed a decreased proportion of CD4 T cells, B cells and progenitors and the enrichment of CD8 T cells, monocytes, and neutrophils along the nBM-MGUS-SMM-NDMM-RRMM axis. Notably, the most profound changes were identified within the context of RRMM. In lymphoid cells, we observed a stepwise decrease in mature B cells during disease progression. For T and NK cells, the naïve-like subsets were more abundant in normal bone marrow and the precursors. In contrast, the effector/cytotoxic subsets were enriched in symptomatic MM (NDMM and RRMM). Immunoregulatory T cells, including CD4T_C2 (Treg), CD4T_C4 (Th17) and CD4T_C7 (Tfh), showed an increased proportion within CD4 T cells in MM, particularly in RRMM compared with precursors. Furthermore, we identified a small exhaustion-like CD8 T cell subset which were enriched in RRMM. In myeloid cells, the classical monocytes showed a high degree of transcriptional homogeneity while the non-classical and intermediate monocytes were more heterogeneous. We observed a unique CD16_Mono_C0 subset which downregulated a considerable number of cytokine/chemokine receptors, almost exclusively unique to MM. The macrophage subsets displaying high phagocytosis signature (Macro_C0/3) were enriched in precursors. The monocyte-like macrophages (Macro_C1/2/4), which showed an angiogenesis phenotype, showed greater abundance in RRMM. Neutrophils were found exclusively in symptomatic MM, demonstrating elevated expression levels of TGFB1. Among the neutrophil subsets, those expressing myeloid checkpoints such as PILRA, SIRPA, and VSIR (Neutro_C0/3/4) exhibited increased prevalence in RRMM. In contrast, subsets expressing ARG1 and MMP9 (Neutro_C1/2) were more enriched in NDMM. Within the dendritic cell population, a specific subset characterized by high TGFB1 and VEGFA expression (cDC2_C1) was exclusively present in MM. Additionally, we observed an enriched proliferative dendritic cell subset in MM. Conclusions: We observed a notable pattern of cellular changes along the nBM-MGUS-SMM-NDMM-RRMM axis, indicating a progressive increase in immune suppression primarily driven by myeloid cells. These observations provide valuable insights into immune cell dynamics, their functional characteristics, and potential roles during disease progression and highlight potential targets for further investigation, especially in the context of RRMM.

Bone marrow stromal cell antigen-1 deficiency protects from acute kidney injury.

This study aimed to investigate the role of bone marrow stromal cell antigen-1 (Bst1; also known as CD157) in acute kidney injury (AKI). Bst1 is a cell surface molecule with various enzymatic activities and downstream intracellular signaling pathways that modulate the immune response. Previous research has linked Bst1 to diseases such as ovarian cancer, Parkinson's disease, and rheumatoid arthritis. We used bilateral ischemia-reperfusion injury (IRI) as an AKI model and created bone marrow chimeric mice to evaluate the role of Bst1 in bone marrow-derived cells. We also used flow cytometry to identify Bst1/CD157 expression in hematopoietic cells and evaluate immune cell dynamics in the kidney. The findings showed that Bst1-deficient (Bst1-/-) mice were protected against renal bilateral IRI. Bone marrow chimera experiments revealed that Bst1 expression on hematopoietic cells, but not parenchymal cells, induced renal IRI. Bst1 was mainly found in B cells and neutrophils by flow cytometry of the spleen and bone marrow. In vitro, migration of neutrophils from Bst1-/- mice was suppressed, and adoptive transfer of neutrophils from wild-type Bst1+/+ mice abolished the renal protective effect in Bst1 knockout mice. In conclusion, the study demonstrated that Bst1-/- mice are protected against renal IRI and that Bst1 expression in neutrophils plays a crucial role in inducing renal IRI. These findings suggest that targeting Bst1 in neutrophils could be a potential therapeutic strategy for AKI.NEW & NOTEWORTHY Acute kidney injury (AKI), a serious disease for which there is no effective Federal Drug Administration-approved treatment, is associated with high mortality rates. Bone marrow stromal cell antigen-1 (Bst1) is a cell surface molecule that can cause kidney fibrosis, but its role in AKI is largely unknown. Our study showed that Bst1-/- mice revealed a protective effect against renal bilateral ischemia-reperfusion injury (IRI). Adoptive transfer studies confirmed that Bst1 expression in hematopoietic cells, especially neutrophils, contributed to renal bilateral IRI.

A mathematical model of Familial Mediterranean Fever predicts mechanisms controlling inflammation

BackgroundFamilial Mediterranean Fever (FMF) is a monogenic disease caused by gain-of-function mutations in the MEditerranean FeVer (MEFV) gene. The molecular dysregulations induced by these mutations and the associated causal mechanisms are complex and intricate. ObjectiveWe sought to provide a computational model capturing the mechanistic details of biological pathways involved in FMF physiopathology and enabling the study of the patient's immune cell dynamics. MethodsWe carried out a literature survey to identify experimental studies published from January 2000 to December 2020, and integrated its results into a molecular map and a mathematical model. Then, we studied the network of molecular interactions and the dynamic of monocytes to identify key players for inflammation phenotype in FMF patients. ResultsWe built a molecular map of FMF integrating in a structured manner the current knowledge regarding pathophysiological processes participating in the triggering and perpetuation of the disease flares. The mathematical model derived from the map reproduced patient's monocyte behavior, in particular its proinflammatory role via the Pyrin inflammasome activation. Network analysis and in silico experiments identified NF-κB and JAK1/TYK2 as critical to modulate IL-1β- and IL-18-mediated inflammation. ConclusionThe in silico model of FMF monocyte proved its ability to reproduce in vitro observations. Considering the difficulties related to experimental settings and financial investments to test combinations of stimuli/perturbation in vitro, this model could be used to test complex hypotheses in silico, thus narrowing down the number of in vitro and ex vivo experiments to perform.

MHC II-EGFP Knock-in Mouse Model.

The MHC II-EGFP knock-in mouse model enables us to visualize and track MHC-II-expressing cells in vivo by expressing enhanced green fluorescent protein (EGFP) fused to the MHC class II molecule under the MHC II beta chain promoter. Using this model, we can easily identify MHC-II-expressing cells, including dendritic cells, B cells, macrophages, and ILC3s, which play a key role as antigen-presenting cells (APCs) for CD4+ T cells. In addition, we can also precisely identify and analyze APC-containing tissues and organs. Even after fixation, EGFP retains its fluorescence, so this model is suitable for immunofluorescence studies, facilitating an unbiased characterization of the histological context, especially with techniques such as light-sheet fluorescence microscopy. Furthermore, the MHC II-EGFP knock-in mouse model is valuable for studying the molecular mechanisms of MHC II gene regulation and expression by making it possible to correlate MHC II expression (MHC II-EGFP) with surface fraction through antibody detection, thereby shedding light on the intricate regulation of MHC II expression. Overall, this model is an essential asset for quantitative and systems immunological research, providing insights into immune cell dynamics and localization, with a tool for precise cell identification and with the ability to study MHC II gene regulation, thus furthering the understanding of immune responses and underlying mechanisms © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Characterization of antigen-specific MHC II loading compartment tubulation toward the immunological synapse Basic Protocol 2: Characterization of overall versus surface MHC II expression Basic Protocol 3: Identification and preparation of the lymphoid organs Basic Protocol 4: Quantification of APC content in lymphoid organs by fluorescence stereomicroscopy Basic Protocol 5: Quantification and measurement of intestinal lymphoid tissue by light-sheet fluorescence stereomicroscopy Basic Protocol 6: Visualization of corneal APCs Basic Protocol 7: Quantification of MHC II+ cells in maternal milk by flow cytometry Support Protocol 1: Cell surface staining and flow cytometry analysis of spleen mononuclear cells.

SAT102 Natural History Of Type 1 Diabetes In Humanized Mouse Model

Abstract Disclosure: A. Aldasouqi: None. S. Rafiqi: None. J.C. Jaume: None. S. Imam: None. Type 1 diabetes (T1D) is an autoimmune disease caused by an imbalance in T-regulatory and T-effector cells characterized by the destruction of insulin-producing beta cells by T-effector cells, leading to insulin deficiency and complexities like diabetic nephropathy, retinopathy, and neuropathy. Researchers at The University of Toledo have developed a humanized mice model which spontaneously develops T1D at 3-5 weeks of age and mimics human T1D. This study aims to monitor blood glucose levels before the onset of T1D (preweaning stage mice) and track the dynamics of immune cells using flow cytometry throughout the progression of the disease. Our results show that T-regulatory cells constitute 4.773% ± 0.81% cells at preweaning which drops to 2.60± 0.35 (%) in males and 1.78 ± 0.58 (%) in females at the 10th week while CD8+ T cells producing interferon-gamma (cytotoxic lymphocytes, CTLs) constitute 3.32 ± 0.60 (%) at preweaning, which increased to 27.625± 1.43 (%) in males and 21.13± 2.87 (%) in females as the disease progresses. This reduction in T-regulatory cells and enrichment of CD8s and CTLs leads to the destruction of beta cells as seen in humans as well. Dysregulation of immune responses can be correlated with the progression of diabetes in terms of blood glucose levels which increased from 147mg/dl (preweaning), peaked to 373mg/dl in 5th week, and was observed in partial remission stage around the 8th week as observed in human T1D ‘honeymoon period’. This study will help us to understand the immune dynamics in the progression of T1D as it helps us to present a better picture of the status of immune cells in a human-like immune system and provides benchmark data of the interplay of the immune system. Presentation: Saturday, June 17, 2023

Utilizing a Proximity Dependent Labeling Strategy to Study Cancer-Immune Intercellular Interactions In Vitro and In Vivo.

Immune cells play a critical role in surveilling and defending against cancer, emphasizing the importance of understanding how they interact and communicate with cancer cells to determine cancer status, treatment response, and the formation of the tumor microenvironment (TME). To this end, we conducted a study demonstrating the effectiveness of an enzyme-mediated intercellular proximity labeling (EXCELL) method, which utilizes a modified version of the sortase A enzyme known as mgSrtA, in detecting and characterizing immune-tumor cell interactions. The mgSrtA enzyme is expressed on the membrane of tumor cells, which is able to label immune cells that interact with tumor cells in a proximity-dependent manner. Our research indicates that the EXCELL technique can detect and characterize immune-tumor cell interactions in a time- and concentration-dependent manner, both in vitro and in vivo, without requiring pre-engineering of the immune cells. We also highlight its ability to detect various types of immune cell subpopulations in vivo that have migrated out of the tumor into the spleen, providing insights into the role of peripheral T-cell recruitment in tumor progression. Overall, our findings suggest that the EXCELL method has great potential for improving our understanding of immune cell dynamics within the TME, ultimately leading to more potent pharmacological effects and cancer immunotherapy strategies. SIGNIFICANCE STATEMENT: The enzyme-mediated intercellular proximity labeling method holds promise for detecting immune cell interactions with cancer cells, both in vitro and in vivo. It has important implications for studying immune tumor cell dynamics and potentially uncovering novel subtypes of immune cells within the tumor microenvironment, both prior to and during immunotherapeutic interventions.

Sensitivity Analysis of a 2D Stochastic Agent-Based and PDE Diffusion Model for Cancer-on-Chip Experiments

The present work extends a previous paper where an agent-based and two-dimensional partial differential diffusion model was introduced for describing immune cell dynamics (leukocytes) in cancer-on-chip experiments. In the present work, new features are introduced for the dynamics of leukocytes and for their interactions with tumor cells, improving the adherence of the model to what is observed in laboratory experiments. Each system’s solution realization is a family of biased random walk trajectories, affected by the chemotactic gradients and in turn affecting them. A sensitivity analysis with respect to the model parameters is performed in order to assess the effect of their variation on both tumor cells and on leukocyte dynamics.

Host microbiome in tuberculosis: disease, treatment, and immunity perspectives.

Tuberculosis (TB), an airborne pulmonary disease caused by Mycobacterium tuberculosis (M. tb), poses an unprecedented health and economic burden to most of the developing countries. Treatment of TB requires prolonged use of a cocktail of antibiotics, which often manifest several side effects, including stomach upset, nausea, and loss of appetite spurring on treatment non-compliance and the emergence of antibiotic resistant M. tb. The anti-TB treatment regimen causes imbalances in the composition of autochthonous microbiota associated with the human body, which also contributes to major side effects. The microbiota residing in the gastrointestinal tract play an important role in various physiological processes, including resistance against colonization by pathogens, boosting host immunity, and providing key metabolic functions. In TB patients, due to prolonged exposure to anti-tuberculosis drugs, the gut microbiota significantly loses its diversity and several keystone bacterial taxa. This loss may result in a significant reduction in the functional potency of the microbiota, which is a probable reason for poor treatment outcomes. In this review, we discuss the structural and functional changes of the gut microbiota during TB and its treatment. A major focus of the review is oriented to the gut microbial association with micronutrient profiles and immune cell dynamics during TB infection. Furthermore, we summarize the acquisition of anti-microbial resistance in M. tb along with the microbiome-based therapeutics to cure the infections. Understanding the relationship between these components and host susceptibility to TB disease is important to finding potential targets that may be used in TB prevention, progression, and cure.

Dynamic Multiplex Tissue Imaging in Inflammation Research.

Inflammation is a highly dynamic process with immune cells that continuously interact with each other and parenchymal components as they migrate through tissue. The dynamic cellular responses and interaction patterns are a function of the complex tissue environment that cannot be fully reconstructed ex vivo, making it necessary to assess cell dynamics and changing spatial patterning in vivo. These dynamics often play out deep within tissues, requiring the optical focus to be placed far below the surface of an opaque organ. With the emergence of commercially available two-photon excitation lasers that can be combined with existing imaging systems, new avenues for imaging deep tissues over long periods of time have become available. We discuss a selected subset of studies illustrating how two-photon microscopy (2PM) has helped to relate the dynamics of immune cells to their in situ function and to understand the molecular patterns that govern their behavior in vivo. We also review some key practical aspects of 2PM methods and point out issues that can confound the results, so that readers can better evaluate the reliability of conclusions drawn using this technology.

Distribution modeling quantifies collective TH cell decision circuits in chronic inflammation.

Immune responses are tightly regulated by a diverse set of interacting immune cell populations. Alongside decision-making processes such as differentiation into specific effector cell types, immune cells initiate proliferation at the beginning of an inflammation, forming two layers of complexity. Here, we developed a general mathematical framework for the data-driven analysis of collective immune cell dynamics. We identified qualitative and quantitative properties of generic network motifs, and we specified differentiation dynamics by analysis of kinetic transcriptome data. Furthermore, we derived a specific, data-driven mathematical model for T helper 1 versus T follicular helper cell-fate decision dynamics in acute and chronic lymphocytic choriomeningitis virus infections in mice. The model recapitulates important dynamical properties without model fitting and solely by using measured response-time distributions. Model simulations predict different windows of opportunity for perturbation in acute and chronic infection scenarios, with potential implications for optimization of targeted immunotherapy.

Innate adaptive immune cell dynamics in tonsillar tissues during chronic SIV infection.

HIV-infected patients are at higher risk of developing oral mucosal infection and Epstein-Barr virus (EBV)-associated B cell malignancies. However, the potential role of oral immunity in the pathogenesis of oral lesions is unknown. Tonsils are oral-pharyngeal mucosal-associated lymphoid tissues that play an important role in oral mucosal immunity. In this study, we investigated the changes of innate and adaptive immune cells in macaque tonsils during chronic SIV infection. We found significantly higher frequencies of classical monocytes, CD3+CD56+ (NKT-like) cells, CD3+CD4+CD8+ (DP), and CD161+ CD4 T cells in tonsils from chronic infected compared to naïve animals. On the contrary, intermediate monocytes and CD3+CD4-CD8- (DN) cells were lower in chronic SIV-infected macaques. We further confirmed a recently described small B-cell subset, NKB cells, were higher during chronic infection. Furthermore, both adaptive and innate cells showed significantly higher TNF-α and cytotoxic marker CD107a, while IL-22 production was significantly reduced in innate and adaptive immune cells in chronic SIV-infected animals. A dramatic reduction of IFN-γ production by innate immune cells might indicate enhanced susceptibility to EBV infection and potential transformation of B cells in the tonsils. In summary, our observation shows that the SIV-associated immune responses are distinct in the tonsils compared to other mucosal tissues. Our data extends our understanding of the oral innate immune system during SIV infection and could aid future studies in evaluating the role of tonsillar immune cells during HIV-associated oral mucosal infections.