Heterogeneity in immune responses: from populations to single cells

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

Unlocking ovarian cancer heterogeneity: advancing immunotherapy through single-cell transcriptomics

Ovarian cancer, a highly fatal gynecological cancer, warrants the need for understanding its heterogeneity. The disease's prevalence and impact are underscored with statistics on mortality rates. Ovarian cancer is categorized into distinct morphological groups, each with its characteristics and prognosis. Despite standard treatments, survival rates remain low due to relapses and chemoresistance. Immune system involvement is evident in ovarian cancer's progression, although the tumor employs immune evasion mechanisms. Immunotherapy, particularly immune checkpoint blockade therapy, is promising, but ovarian cancer's heterogeneity limits its efficacy. Single-cell sequencing technology could be explored as a solution to dissect the heterogeneity within tumor-associated immune cell populations and tumor microenvironments. This cutting-edge technology has the potential to enhance diagnosis, prognosis, and personalized immunotherapy in ovarian cancer, reflecting its broader application in cancer research. The present review focuses on recent advancements and the challenges in applying single-cell transcriptomics to ovarian cancer.

A comprehensive analysis of the immune system in healthy Vietnamese people

Lifestyle, diet, socioeconomic status and genetics all contribute to heterogeneity in immune responses. Vietnam is plagued with a variety of health problems, but there are no available data on immune system values in the Vietnamese population. This study aimed to establish reference intervals for immune cell parameters specific to the healthy Vietnamese population by utilizing multi-color flow cytometry (MCFC). We provide a comprehensive analysis of total leukocyte count, quantitative and qualitative shifts within lymphocyte subsets, serum and cytokine and chemokine levels and functional attributes of key immune cells including B cells, T cells, natural killer (NK) cells and their respective subpopulations. By establishing these reference values for the Vietnamese population, these data contribute significantly to our understanding of the human immune system variations across diverse populations. These data will be of substantial comparative value and be instrumental in developing personalized medical approaches and optimizing diagnostic strategies for individuals based on their unique immune profiles.

Single-Cell Analysis Reveals a Subset of High IL-12p40-Secreting Dendritic Cells within Mouse Bone Marrow-Derived Macrophages Differentiated with M-CSF

Macrophages and dendritic cells (DCs), although ontogenetically distinct, have overlapping functions and exhibit substantial cell-to-cell heterogeneity that can complicate their identification and obscure innate immune function. In this study, we report that M-CSF-differentiated murine bone marrow-derived macrophages (BMDMs) exhibit extreme heterogeneity in the production of IL-12, a key proinflammatory cytokine linking innate and adaptive immunity. A microwell secretion assay revealed that a small fraction of BMDMs stimulated with LPS secrete most IL-12p40, and we confirmed that this is due to extremely high expression of Il12b, the gene encoding IL-12p40, in a subset of cells. Using an Il12b-YFP reporter mouse, we isolated cells with high LPS-induced Il12b expression and found that this subset was enriched for genes associated with the DC lineage. Single-cell RNA sequencing data confirmed a DC-like subset that differentiates within BMDM cultures that is transcriptionally distinct but could not be isolated by surface marker expression. Although not readily apparent in the resting state, upon LPS stimulation, this subset exhibited a typical DC-associated activation program that is distinct from LPS-induced stochastic BMDM cell-to-cell heterogeneity. Overall, our findings underscore the difficulty in distinguishing macrophages and DCs even in widely used in vitro murine BMDM cultures and could affect the interpretation of some studies that use BMDMs to explore acute inflammatory responses.

Single-cell RNA-seq revealed heterogeneous responses and functional differentiation of hemocytes against white spot syndrome virus infection in Litopenaeus vannamei

Shrimp hemocytes are the vital immune cells participating in innate immune response to defend against viruses. However, the lack of specific molecular markers for shrimp hemocyte hindered the insightful understanding of their functional clusters and differential roles in combating microbial infections. In this study, we used single-cell RNA sequencing to map the transcriptomic landscape of hemocytes from the white spot syndrome virus (WSSV)-infected Litopenaeus vannamei and conjointly analyzed with our previous published single-cell RNA sequencing technology data from the healthy hemocytes. A total of 16 transcriptionally distinct cell clusters were identified, which occupied different proportions in healthy and WSSV-infected hemocytes and exerted differential roles in antiviral immune response. Following mapping of the sequencing data to the WSSV genome, we found that all types of hemocytes could be invaded by WSSV virions, especially the cluster 8, which showed the highest transcriptional levels of WSSV genes and exhibited a cell type-specific antiviral response to the viral infection. Further evaluation of the cell clusters revealed the delicate dynamic balance between hemocyte immune response and viral infestation. Unsupervised pseudo-time analysis of hemocytes showed that the hemocytes in immune-resting state could be significantly activated upon WSSV infection and then functionally differentiated to different hemocyte subsets. Collectively, our results revealed the differential responses of shrimp hemocytes and the process of immune-functional differentiation post-WSSV infection, providing essential resource for the systematic insight into the synergistic immune response mechanism against viral infection among hemocyte subtypes.

IMPORTANCE

Current knowledge of shrimp hemocyte classification mainly comes from morphology, which hinder in-depth characterization of cell lineage development, functional differentiation, and different immune response of hemocyte types during pathogenic infections. Here, single-cell RNA sequencing was used for mapping hemocytes during white spot syndrome virus (WSSV) infection in Litopenaeus vannamei, identifying 16 cell clusters and evaluating their potential antiviral functional characteristics. We have described the dynamic balance between viral infestation and hemocyte immunity. And the functional differentiation of hemocytes under WSSV stimulation was further characterized. Our results provided a comprehensive transcriptional landscape and revealed the heterogeneous immune response in shrimp hemocytes during WSSV infection.

scRNA-seq analysis discovered suppression of immunomodulatory dependent inflammatory response in PMBCs exposed to silver nanoparticles

The assessment of AgNPs toxicity in vitro and in vivo models are frequently conflicting and inaccurate. Nevertheless, single cell immunological responses in a heterogenous environment have received little attention. Therefore, in this study, we have performed in-depth analysis which clearly revealed cellular-metal ion association as well as specific immunological response. Our study didn't show significant population differences in PMBC between control and AgNPs group implying no toxicological response. To confirm it further, deep profiling identified differences in subsets and differentially expressed genes (DEGs) of monocytes, B cells and T cells. Notably, monocyte subsets showed significant upregulation of metallothionein (MT) gene expression such as MT1G, MT1X, MT1E, MT1A, and MT1F. On the other hand, downregulation of pro-inflammatory genes such as IL1β and CCL3 in both CD16 + and CD16- monocyte subsets were observed. This result indicated that AgNPs association with monocyte subsets de-promoted inflammatory responsive genes suggesting no significant toxicity observed in AgNPs treated group. Other cell types such as B cells and T cells also showed negligible differences in their subsets suggesting no toxicity response. Further, AgNPs treated group showed upregulation of cell proliferation, ribosomal synthesis, downregulation of cytokine release, and T cell differentiation inhibition. Overall, our results conclude that treatment of AgNPs to PMBC cells didn't display immunological related cytotoxicity response and thus motivate researchers to use them actively for biomedical applications.

Identification of druggable regulators of cell secretion via a kinome-wide screen and high-throughput immunomagnetic cell sorting

The identification of genetic regulators of cell secretions is challenging because it requires the sorting of a large number of cells according to their secretion patterns. Here we report the development and applicability of a high-throughput microfluidic method for the analysis of the secretion levels of large populations of immune cells. The method is linked with a kinome-wide loss-of-function CRISPR screen, immunomagnetically sorting the cells according to their secretion levels, and the sequencing of their genomes to identify key genetic modifiers of cell secretion. We used the method, which we validated against flow cytometry for cytokines secreted from primary mouse CD4+ (cluster of differentiation 4-positive) T cells, to discover a subgroup of highly co-expressed kinase-coding genes that regulate interferon-gamma secretion by these cells. We validated the function of the kinases identified using RNA interference, CRISPR knockouts and kinase inhibitors and confirmed the druggability of selected kinases via the administration of a kinase inhibitor in an animal model of colitis. The technique may facilitate the discovery of regulatory mechanisms for immune-cell activation and of therapeutic targets for autoimmune diseases.

Probing T-cell activation in nanoliter tumor co-cultures using membrane displacement trap arrays

Immune responses against cancer are inherently stochastic, with small numbers of individual T cells within a larger ensemble of lymphocytes initiating the molecular cascades that lead to tumor cytotoxicity. A potential source of this intra-tumor variability is the differential ability of immune cells to respond to tumor cells. Classical microwell co-cultures of T cells and tumor cells are inadequate for reliably culturing and analyzing low cell numbers needed to probe this variability, and have failed in recapitulating the heterogeneous small domains observed in tumors. Here we leverage a membrane displacement trap array technology that overcomes limitations of conventional microwell plates for immunodynamic studies. The microfluidic platform supports on-demand formation of dense nanowell cultures under continuous perfusion reflecting the tumor microenvironment, with real-time monitoring of T cell proliferation and activation within each nanowell. The system enables selective ejection of cells for profiling by fluorescence activated cell sorting, allowing observed on-chip variability in immune response to be correlated with off-chip quantification of T cell activation. The technology offers new potential for probing the molecular origins of T cell heterogeneity and identifying specific cell phenotypes responsible for initiating and propagating immune cascades within tumors. Insight Box Variability in T cell activation plays a critical role in the immune response against cancer. New tools are needed to unravel the mechanisms that drive successful anti-tumor immune response, and to support the development of novel immunotherapies utilizing rare T cell phenotypes that promote effective immune surveillance. To this end, we present a microfluidic cell culture platform capable of probing differential T cell activation in an array of nanoliter-scale wells coupled with off-chip cell analysis, enabling a high resolution view of variable immune response within tumor / T cell co-cultures containing cell ensembles orders of magnitude smaller than conventional well plate studies.

Nanosensor Chemical Cytometry: Advances and Opportunities in Cellular Therapy and Precision Medicine

With the definition of therapeutics now encompassing transplanted or engineered cells and their molecular products, there is a growing scientific necessity for analytics to understand this new category of drugs. This Perspective highlights the recent development of new measurement science on label-free single cell analysis, nanosensor chemical cytometry (NCC), and their potential for cellular therapeutics and precision medicine. NCC is based on microfluidics integrated with fluorescent nanosensor arrays utilizing the optical lensing effect of a single cell to real-time extract molecular properties and correlate them with physical attributes of single cells. This new class of cytometry can quantify the heterogeneity of the multivariate physicochemical attributes of the cell populations in a completely label-free and nondestructive way and, thus, suggest the vein-to-vein conditions for the safe therapeutic applications. After the introduction of the NCC technology, we suggest the technological development roadmap for the maturation of the new field: from the sensor/chip design perspective to the system/software development level based on hardware automation and deep learning data analytics. The advancement of this new single cell sensing technology is anticipated to aid rich and multivariate single cell data setting and support safe and reliable cellular therapeutics. This new measurement science can lead to data-driven personalized precision medicine.

Microfluidic single-cell migration chip reveals insights into the impact of extracellular matrices on cell movement

Cell migration is a complex process that plays a crucial role in normal physiology and pathologies such as cancer, autoimmune diseases, and mental disorders. Conventional cell migration assays face limitations in tracking a large number of individual migrating cells. To address this challenge, we have developed a high-throughput microfluidic cell migration chip, which seamlessly integrates robotic liquid handling and computer vision to swiftly monitor the movement of 3200 individual cells, providing unparalleled single-cell resolution for discerning distinct behaviors of the fast-moving cell population. This study focuses on the ECM's role in regulating cellular migration, utilizing this cutting-edge microfluidic technology to investigate the impact of ten different ECMs on triple-negative breast cancer cell lines. We found that collagen IV, collagen III, and collagen I coatings were the top enhancers of cell movement. Combining these ECMs increased cell motility, but the effect was sub-additive. Furthermore, we examined 87 compounds and found that while some compounds inhibited migration on all substrates, significantly distinct effects on differently coated substrates were observed, underscoring the importance of considering ECM coating. We also utilized cells expressing a fluorescent actin reporter and observed distinct actin structures in ECM-interacting cells. ScRNA-Seq analysis revealed that ECM coatings induced EMT and enhanced cell migration. Finally, we identified genes that were particularly up-regulated by collagen IV and the selective inhibitors successfully blocked cell migration on collagen IV. Overall, the study provides insights into the impact of various ECMs on cell migration and dynamics of cell movement with implications for developing therapeutic strategies to combat diseases related to cell motility.

Using combined single-cell gene expression, TCR sequencing and cell surface protein barcoding to characterize and track CD4+ T cell clones from murine tissues

Single-cell gene expression analysis using sequencing (scRNA-seq) has gained increased attention in the past decades for studying cellular transcriptional programs and their heterogeneity in an unbiased manner, and novel protocols allow the simultaneous measurement of gene expression, T-cell receptor clonality and cell surface protein expression. In this article, we describe the methods to isolate scRNA/TCR-seq-compatible CD4+ T cells from murine tissues, such as skin, spleen, and lymph nodes. We describe the processing of cells and quality control parameters during library preparation, protocols for multiplexing of samples, and strategies for sequencing. Moreover, we describe a step-by-step bioinformatic analysis pipeline from sequencing data generated using these protocols. This includes quality control, preprocessing of sequencing data and demultiplexing of individual samples. We perform quantification of gene expression and extraction of T-cell receptor alpha and beta chain sequences, followed by quality control and doublet detection, and methods for harmonization and integration of datasets. Next, we describe the identification of highly variable genes and dimensionality reduction, clustering and pseudotemporal ordering of data, and we demonstrate how to visualize the results with interactive and reproducible dashboards. We will combine different analytic R-based frameworks such as Bioconductor and Seurat, illustrating how these can be interoperable to optimally analyze scRNA/TCR-seq data of CD4+ T cells from murine tissues.

Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry

Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.

The Dual Role of the Innate Immune System in the Effectiveness of mRNA Therapeutics

Advances in molecular biology have revolutionized the use of messenger RNA (mRNA) as a therapeutic. The concept of nucleic acid therapy with mRNA originated in 1990 when Wolff et al. reported successful expression of proteins in target organs by direct injection of either plasmid DNA or mRNA. It took decades to bring the transfection efficiency of mRNA closer to that of DNA. The next few decades were dedicated to turning in vitro-transcribed (IVT) mRNA from a promising delivery tool for gene therapy into a full-blown therapeutic modality, which changed the biotech market rapidly. Hundreds of clinical trials are currently underway using mRNA for prophylaxis and therapy of infectious diseases and cancers, in regenerative medicine, and genome editing. The potential of IVT mRNA to induce an innate immune response favors its use for vaccination and immunotherapy. Nonetheless, in non-immunotherapy applications, the intrinsic immunostimulatory activity of mRNA directly hinders the desired therapeutic effect since it can seriously impair the target protein expression. Targeting the same innate immune factors can increase the effectiveness of mRNA therapeutics for some indications and decrease it for others, and vice versa. The review aims to present the innate immunity-related 'barriers' or 'springboards' that may affect the development of immunotherapies and non-immunotherapy applications of mRNA medicines.

Cellular heterogeneity of the developing worker honey bee (Apis mellifera) pupa: a single cell transcriptomics analysis

It is estimated that animals pollinate 87.5% of flowering plants worldwide and that managed honey bees (Apis mellifera) account for 30-50% of this ecosystem service to agriculture. In addition to their important role as pollinators, honey bees are well-established insect models for studying learning and memory, behavior, caste differentiation, epigenetic mechanisms, olfactory biology, sex determination, and eusociality. Despite their importance to agriculture, knowledge of honey bee biology lags behind many other livestock species. In this study, we have used scRNA-Seq to map cell types to different developmental stages of the worker honey bee (prepupa at day 11 and pupa at day 15) and sought to determine their gene expression signatures. To identify cell-type populations, we examined the cell-to-cell network based on the similarity of the single-cells transcriptomic profiles. Grouping similar cells together we identified 63 different cell clusters of which 17 clusters were identifiable at both stages. To determine genes associated with specific cell populations or with a particular biological process involved in honey bee development, we used gene coexpression analysis. We combined this analysis with literature mining, the honey bee protein atlas, and gene ontology analysis to determine cell cluster identity. Of the cell clusters identified, 17 were related to the nervous system and sensory organs, 7 to the fat body, 19 to the cuticle, 5 to muscle, 4 to compound eye, 2 to midgut, 2 to hemocytes, and 1 to malpighian tubule/pericardial nephrocyte. To our knowledge, this is the first whole single-cell atlas of honey bees at any stage of development and demonstrates the potential for further work to investigate their biology at the cellular level.

Perturbations in spike-specific peripheral T follicular helper cells in SARS-CoV2 breakthrough convalescent individuals immunized by BBV152 vaccine

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov2) infection has caused an increase in mortality and morbidity, but with vaccination, the disease severity has significantly reduced. With the emergence of various variants of concern (VOCs), the vaccine breakthrough infection has also increased. Here we studied circulating spike-specific T follicular response (cTfh) in infection-naïve vaccinees and convalescent vaccinees (individuals who got the Delta breakthrough infection after two doses of BBV152 vaccine) to understand their response as they are the most crucial cells that are involved in vaccine-mediated protection by helping in B-cell maturation. Our results indicated that cTfh cells in both the groups recognized the wild-type and Delta spike protein but memory response to the wild-type spike was superior in infection-naïve than in the convalescent group. The cytokine response, particularly interleukin-21 (IL-21) from cTfh, was also higher in infection-naïve than in convalescent vaccinees, indicating a dampened cTfh response in convalescent vaccinees after breakthrough infection. Also, there was a positive correlation between IL-21 from cTfh cells and neutralizing antibodies of infection-naïve vaccinees. Multiple cytokine analysis also revealed higher inflammation in convalescent vaccinees. Our data indicated that the necessity of a third booster dose may be individual-specific depending on the steady-state functional phenotype of immune cells.

Comparison of antiviral responses in two bat species reveals conserved and divergent innate immune pathways

Bats host a range of disease-causing viruses without displaying clinical symptoms. The mechanisms behind this are a continuous source of interest. Here, we studied the antiviral response in the Egyptian fruit bat and Kuhl's pipistrelle, representing two subordinal clades. We profiled the antiviral response in fibroblasts using RNA sequencing and compared bat with primate and rodent responses. Both bats upregulate similar genes; however, a subset of these genes is transcriptionally divergent between them. These divergent genes also evolve rapidly in sequence, have specific promoter architectures, and are associated with programs underlying tolerance and resistance. Finally, we characterized antiviral genes that expanded in bats, with duplicates diverging in sequence and expression. Our study reveals a largely conserved antiviral program across bats and points to a set of genes that rapidly evolve through multiple mechanisms. These can contribute to bat adaptation to viral infection and provide directions to understanding the mechanisms behind it.

Modeling the potential health impacts of delayed strain selection on influenza hospitalization and mortality with mRNA vaccines

Background

Influenza viruses are constantly evolving through antigenic drift, which makes vaccines potentially ill-matched to circulating strains due to the time between strain selection and distribution. mRNA technology could improve vaccine effectiveness (VE) by reducing this time. Significant private and public investments would be required to accommodate accelerated vaccine development and approval. Hence, it is important to understand the potential impact of mRNA technology on influenza hospitalizations and mortality.

Methods

We developed an age-stratified dynamic model of influenza transmission to evaluate the potential impact of increased VE (increased protection against either infection or only hospitalization) on hospitalizations and mortality in the United States. We assume that mRNA technology allows for delaying the time to strain choice, which might increase efficacy, but it does not reduce the time needed for distribution and administration, which might reduce availability. To assess this tradeoff, we evaluated two scenarios where strain choice was delayed until late summer resulting in a more effective vaccine available to (1) all age groups by October, or (2) adults 65 years and older starting in August.

Results

If not available until October, the vaccine would need a minimum of 95% effectiveness against infection to see a decrease in hospitalizations and deaths in all age groups. When delayed until November, even a 100% effective vaccine had no significant impact. For the elderly, the minimum required VE (against infection) was 50% to reduce hospitalizations and deaths. Moreover, a vaccine with 80% VE against infection available in August for the 65 + age group was better than a 95% effective vaccine available in October for all ages.

Conclusions

As the majority of influenza-associated hospitalizations and deaths are in adults 65 years and older, a combination policy targeting higher VE and coverage for this age group in the short term would be the most efficacious.

Immune heterogeneity in cardiovascular diseases from a single-cell perspective

A variety of immune cell subsets occupy different niches in the cardiovascular system, causing changes in the structure and function of the heart and vascular system, and driving the progress of cardiovascular diseases (CVDs). The immune cells infiltrating the injury site are highly diverse and integrate into a broad dynamic immune network that controls the dynamic changes of CVDs. Due to technical limitations, the effects and molecular mechanisms of these dynamic immune networks on CVDs have not been fully revealed. With recent advances in single-cell technologies such as single-cell RNA sequencing, systematic interrogation of the immune cell subsets is feasible and will provide insights into the way we understand the integrative behavior of immune populations. We no longer lightly ignore the role of individual cells, especially certain highly heterogeneous or rare subpopulations. We summarize the phenotypic diversity of immune cell subsets and their significance in three CVDs of atherosclerosis, myocardial ischemia and heart failure. We believe that such a review could enhance our understanding of how immune heterogeneity drives the progression of CVDs, help to elucidate the regulatory roles of immune cell subsets in disease, and thus guide the development of new immunotherapies.

Multichannel impedance cytometry downstream of cell separation by deterministic lateral displacement to quantify macrophage enrichment in heterogeneous samples

The integration of on-chip biophysical cytometry downstream of microfluidic enrichment for inline monitoring of phenotypic and separation metrics at single-cell sensitivity can allow for active control of separation and its application to versatile sample sets. We present integration of impedance cytometry downstream of cell separation by deterministic lateral displacement (DLD) for enrichment of activated macrophages from a heterogeneous sample, without the problems of biased sample loss and sample dilution caused by off-chip analysis. This required designs to match cell/particle flow rates from DLD separation into the confined single-cell impedance cytometry stage, the balancing of flow resistances across the separation array width to maintain unidirectionality, and the utilization of co-flowing beads as calibrated internal standards for inline assessment of DLD separation and for impedance data normalization. Using a heterogeneous sample with un-activated and activated macrophages, wherein macrophage polarization during activation causes cell size enlargement, on-chip impedance cytometry is used to validate DLD enrichment of the activated subpopulation at the displaced outlet, based on the multiparametric characteristics of cell size distribution and impedance phase metrics. This hybrid platform can monitor separation of specific subpopulations from cellular samples with wide size distributions, for active operational control and enhanced sample versatility.

Model reduction for the Chemical Master Equation: An information-theoretic approach

The complexity of mathematical models in biology has rendered model reduction an essential tool in the quantitative biologist's toolkit. For stochastic reaction networks described using the Chemical Master Equation, commonly used methods include time-scale separation, Linear Mapping Approximation, and state-space lumping. Despite the success of these techniques, they appear to be rather disparate, and at present, no general-purpose approach to model reduction for stochastic reaction networks is known. In this paper, we show that most common model reduction approaches for the Chemical Master Equation can be seen as minimizing a well-known information-theoretic quantity between the full model and its reduction, the Kullback-Leibler divergence defined on the space of trajectories. This allows us to recast the task of model reduction as a variational problem that can be tackled using standard numerical optimization approaches. In addition, we derive general expressions for propensities of a reduced system that generalize those found using classical methods. We show that the Kullback-Leibler divergence is a useful metric to assess model discrepancy and to compare different model reduction techniques using three examples from the literature: an autoregulatory feedback loop, the Michaelis-Menten enzyme system, and a genetic oscillator.

Investigating the effects of maltreatment and acute stress on the concordance of blood and DNA methylation methods of estimating immune cell proportions

BACKGROUND

Immune cell proportions can be used to detect pathophysiological states and are also critical covariates in genomic analyses. The complete blood count (CBC) is the most common method of immune cell proportion estimation, but immune cell proportions can also be estimated using whole-genome DNA methylation (DNAm). Although the concordance of CBC and DNAm estimations has been validated in various adult and clinical populations, less is known about the concordance of existing estimators among stress-exposed individuals. As early life adversity and acute psychosocial stress have both been associated with unique DNAm alterations, the concordance of CBC and DNAm immune cell proportion needs to be validated in various states of stress.

RESULTS

We report the correlation and concordance between CBC and DNAm estimates of immune cell proportions using the Illumina EPIC DNAm array within two unique studies: Study 1, a high-risk pediatric cohort of children oversampled for exposure to maltreatment (N = 365, age 8 to 14 years), and Study 2, a sample of young adults who have participated in an acute laboratory stressor with four pre- and post-stress measurements (N = 28, number of observations = 100). Comparing CBC and DNAm proportions across both studies, estimates of neutrophils (r = 0.948, p < 0.001), lymphocytes (r = 0.916, p < 0.001), and eosinophils (r = 0.933, p < 0.001) were highly correlated, while monocyte estimates were moderately correlated (r = 0.766, p < 0.001) and basophil estimates were weakly correlated (r = 0.189, p < 0.001). In Study 1, we observed significant deviations in raw values between the two approaches for some immune cell subtypes; however, the observed differences were not significantly predicted by exposure to child maltreatment. In Study 2, while significant changes in immune cell proportions were observed in response to acute psychosocial stress for both CBC and DNAm estimates, the observed changes were similar for both approaches.

CONCLUSIONS

Although significant differences in immune cell proportion estimates between CBC and DNAm exist, as well as stress-induced changes in immune cell proportions, neither child maltreatment nor acute psychosocial stress alters the concordance of CBC and DNAm estimation methods. These results suggest that the agreement between CBC and DNAm estimators of immune cell proportions is robust to exposure to child maltreatment and acute psychosocial stress.

The neuroimmune axis of Alzheimer's disease

Alzheimer's disease (AD) is a genetically complex and heterogeneous disorder with multifaceted neuropathological features, including β-amyloid plaques, neurofibrillary tangles, and neuroinflammation. Over the past decade, emerging evidence has implicated both beneficial and pathological roles for innate immune genes and immune cells, including peripheral immune cells such as T cells, which can infiltrate the brain and either ameliorate or exacerbate AD neuropathogenesis. These findings support a neuroimmune axis of AD, in which the interplay of adaptive and innate immune systems inside and outside the brain critically impacts the etiology and pathogenesis of AD. In this review, we discuss the complexities of AD neuropathology at the levels of genetics and cellular physiology, highlighting immune signaling pathways and genes associated with AD risk and interactions among both innate and adaptive immune cells in the AD brain. We emphasize the role of peripheral immune cells in AD and the mechanisms by which immune cells, such as T cells and monocytes, influence AD neuropathology, including microglial clearance of amyloid-β peptide, the key component of β-amyloid plaque cores, pro-inflammatory and cytotoxic activity of microglia, astrogliosis, and their interactions with the brain vasculature. Finally, we review the challenges and outlook for establishing immune-based therapies for treating and preventing AD.

Condyloma acuminata: An evaluation of the immune response at cellular and molecular levels

Condyloma acuminata (CA) is a benign proliferative disease mainly affecting in non-keratinized epithelia. Most cases of CA are caused by low-risk human papillomavirus (HPV), mainly HPV 6 and 11. The aim of the current study was to highlight the candidate genes and pathways associated with immune alterations in individuals who did not spontaneously eliminate the virus and, thus, develop genital warts. Paraffin-embedded condyloma samples (n = 56) were analyzed by immunohistochemistry using antibodies against CD1a, FOXP3, CD3, CD4, CD8, and IFN-γ. The immunomarkers were chosen based on the evaluation of the innate and adaptive immune pathways using qPCR analysis of 92 immune-related genes, applying a TaqMan Array Immune Response assay in HPV 6 or HPV 11 positive samples (n = 27). Gene expression analysis revealed 31 differentially expressed genes in CA lesions. Gene expression validation revealed upregulation of GZMB, IFNG, IL12B, and IL8 and downregulation of NFATC4 and IL7 in CA samples. Immunohistochemical analysis showed increased FOXP3, IFN-γ, CD1a, and CD4 expression in CA than in the control tissue samples. In contrast, CD3 and CD8 expression was decreased in CA lesion samples. Increased levels of pro-inflammatory cytokines in HPV-positive patients compared with HPV-negative patients seem to reflect the elevated immunogenicity of HPV-positive CA lesions. Host defense against HPV begins during the early stages of the innate immune response and is followed by activation of T lymphocytes, which are mainly represented by CD4+ and regulatory T cells. The low CD8+ T cell count in CA may contribute to this recurrent behavior. Additional studies are needed to elucidate the mechanism of host defense against HPV infection in CA.

Generation of tumor spheroids in microwells to study NK cell cytotoxicity, infiltration and phenotype

The development of new immunotherapeutic drugs and combinatorial strategies requires the implementation of novel methods to test their efficacy in vitro. Here, we present a series of miniaturized in vitro assays to assess immune cell cytotoxic activity, infiltration, and phenotype in renal carcinoma spheroids with the use of a recently developed multichambered microwell chip. We provide protocols for tumor spheroid formation, NK cell culture, fluorescence labelling and imaging of live or fixed cells directly in the chip together with data analysis.

Dielectrophoresis-Assisted Self-Digitization Chip for High-Efficiency Single-Cell Analysis

Single-cell analysis of cell phenotypic information such as surface protein expression and nucleic acid content is essential for understanding heterogeneity within cell populations. Here the design and use of a dielectrophoresis-assisted self-digitization (SD) microfluidics chip is described; it captures single cells in isolated microchambers with high efficiency for single-cell analysis. The self-digitization chip spontaneously partitions aqueous solution into microchambers through a combination of fluidic forces, interfacial tension, and channel geometry. Single cells are guided to and trapped at the entrances of microchambers by dielectrophoresis (DEP) due to local electric field maxima created by an externally applied AC voltage. Excess cells are flushed away, and trapped cells are released into the chambers and prepared for in situ analysis by turning off the external voltage, by running reaction buffer through the chip, and by sealing the chambers with a flow of an immiscible oil phase through the surrounding channels. The use of this device in single-cell analysis is demonstrated by performing single-cell nucleic acid quantitation based on loop-mediated isothermal amplification (LAMP). This platform provides a powerful new tool for single-cell research pertaining to drug discovery. For example, the single-cell genotyping of cancer-related mutant gene observed from the digital chip could be useful biomarker for targeted therapy.

Bibliometric analysis of single-cell sequencing researches on immune cells and their application of DNA damage repair in cancer immunotherapy

INTRODUCTION

In recent decades, single-cell sequencing technology has developed rapidly and used widely in various fields of life sciences, especially for the detection of immune cells. A bibliometric analysis of single-cell sequencing research work on immune cells published during the 2011-2021 period should provide new insight on the use of single-cell sequencing.

METHODS

We screened 1,460 publications on single-cell sequencing on immune cells according to the publication date, article type, language, and country.

REULTS

The United States published the first and largest number of articles, while China's research started relatively late, but ranked second in the number of publications. T cells were the most commonly studied immune cells by single-cell sequencing, followed by mononuclear macrophages. Cancer biology was the most common field of immune cell research by single-cell sequencing. Single-cell sequencing studies using γδ T cells were mainly in the fields of cancer biology and cell development, and focused over time from cell surface receptor to cell function. Through in-depth analysis of the articles on single-cell sequencing of T cells in the oncology field, our analysis found that immunotherapy and tumor microenvironment were the most popular research directions in recent years.

DISCUSSION

The combination of DNA damage repair and immunotherapy seems to provide a new strategy for cancer therapy.

Revising immune cell coordination: Origins and importance of single-cell variation

Moving from the optimalization of single-cell technologies to the interpretation of the multi-complex single-cell data, the field of immunoengineering is granted with numerous important insights into the coordination of immune cell activation and how to modulate it for therapeutic purposes. However, insights come with additional follow-up questions that challenge our perception on how immune responses are generated and fine-tuned to fight a wide array of pathogens in ever-changing and often unpredictable microenvironments. Are immune responses really either being tightly regulated by molecular determinants, or highly flexible attributed to stochasticity? What exactly makes up the basic rules by which single cells cooperate to establish tissue-level immunity? Taking the type I IFN system and its newest insights as a main example throughout this review, we revise the basic concepts of (single) immune cell coordination, redefine the concepts of noise, stochasticity and determinism, and highlight the importance of single-cell variation in immunology and beyond.

A Microfluidic Approach for Probing Heterogeneity in Cytotoxic T-Cells by Cell Pairing in Hydrogel Droplets

Cytotoxic T-cells (CTLs) exhibit strong effector functions to leverage antigen-specific anti-tumoral and anti-viral immunity. When naïve CTLs are activated by antigen-presenting cells (APCs) they display various levels of functional heterogeneity. To investigate this, we developed a single-cell droplet microfluidics platform that allows for deciphering single CTL activation profiles by multi-parameter analysis. We identified and correlated functional heterogeneity based on secretion profiles of IFNγ, TNFα, IL-2, and CD69 and CD25 surface marker expression levels. Furthermore, we strengthened our approach by incorporating low-melting agarose to encapsulate pairs of single CTLs and artificial APCs in hydrogel droplets, thereby preserving spatial information over cell pairs. This approach provides a robust tool for high-throughput and single-cell analysis of CTLs compatible with flow cytometry for subsequent analysis and sorting. The ability to score CTL quality, combined with various potential downstream analyses, could pave the way for the selection of potent CTLs for cell-based therapeutic strategies.

Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta

BACKGROUND

Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional features of thoracic aortic tissue.

METHODS

Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data.

RESULTS

We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes JUN, LTBP4 (latent transforming growth factor beta-binding protein 1), and IL34 (interleukin 34) in fibroblasts, ENTPD1, PDLIM5 (PDZ and LIM domain 5), ACTN4 (alpha-actinin-4), and GLRX in vascular smooth muscle cells, as well as LRP1 in macrophage populations.

CONCLUSIONS

Using nuclear RNA sequencing, we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single-nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.

Single-cell RNA-seq uncovered hemocyte functional subtypes and their differentiational characteristics and connectivity with morphological subpopulations in Litopenaeus vannamei

Hemocytes play central roles in shrimp immune system, whereas whose subclasses have not yet been completely defined. At present, the morphological classification of hemocytes is inadequate to classify the complete hemocyte repertoire and elucidate the functions and differentiation and maturation processes. Based on single-cell RNA sequencing (scRNA-seq) of hemocytes in healthy Litopenaeus vannamei, combined with RNA-FISH and flow cytometric sorting, we identified three hemocyte clusters including TGase+ cells, CTL+ cells and Crustin+ cells, and further determined their functional properties, potential differentiation trajectory and correspondence with morphological subpopulations. The TGase+ cells were mainly responsible for the coagulation, exhibiting distinguishable characteristics of hyalinocyte, and appeared to be developmentally arrested at an early stage of hemocyte differentiation. The CTL+ cells and Crustin+ cells arrested at terminal stages of differentiation mainly participated in recognizing foreign pathogens and initiating immune defense responses, owning distinctive features of granule-containing hemocytes. Furthermore, we have revealed the functional sub-clusters of three hemocyte clusters and their potential differentiation pathways according to the expression of genes involved in cell cycle, cell differentiation and immune response, and the successive differentiation and maturation of hyalinocytes to granule-containing hemocytes have also mapped. The results revealed the diversity of shrimp hemocytes and provide new theoretical rationale for hemocyte classification, which also facilitate systematic research on crustacean immunity.

Single-cell assessment of the modulation of macrophage activation by ex vivo intervertebral discs using impedance cytometry

Measurement of macrophage activation and its modulation for immune regulation is of great interest to arrest inflammatory responses associated with degeneration of intervertebral discs that cause chronic back pain, and with transplants that face immune rejection. Due to the phenotypic plasticity of macrophages that serve multiple immune functions, the net disease outcome is determined by a balance of subpopulations with competing functions, highlighting the need for single-cell methods to quantify heterogeneity in their activation phenotypes. However, since macrophage activation can follow several signaling pathways, cytometry after fluorescent staining of markers with antibodies does not often provide dose-dependent information on activation dynamics. We present high throughput single-cell impedance cytometry for multiparametric measurement of biophysical changes to individual macrophages for quantifying activation in a dose and duration dependent manner, without relying on a particular signaling pathway. Impedance phase metrics measured at two frequencies and the electrical diameter from impedance magnitude at lower frequencies are used in tandem to benchmark macrophage activation by degenerated discs against that from lipopolysaccharide stimulation at varying dose and duration levels, so that reversal of the activation state by curcumin can be ascertained. This label-free single-cell measurement method can form the basis for platforms to screen therapies for inflammation, thereby addressing the chronic problem of back pain.

Mathematical modelling of activation-induced heterogeneity in TNF, IL6, NOS2, and IL1β expression reveals cell state transitions underpinning macrophage responses to LPS

Background: Despite extensive work on macrophage heterogeneity, the mechanisms driving activation induced heterogeneity (AIH) in macrophages remain poorly understood. Here, we aimed to develop mathematical models to explore theoretical cellular states underpinning the empirically observed responses of macrophages following lipopolysaccharide (LPS) challenge.

Methods: We obtained empirical data following primary and secondary responses to LPS in two in vitro cellular models (bone marrow-derived macrophages or BMDMs, and RAW 264.7 cells) and single-cell protein measurements for four key inflammatory mediators: TNF, IL-6, pro-IL-1β, and NOS2, and used mathematical modelling to understand heterogeneity.

Results: For these four factors, we showed that macrophage community AIH is dependent on LPS dose and that altered AIH kinetics in macrophages responding to a second LPS challenge underpin hypo-responsiveness to LPS. These empirical data can be explained by a mathematical three-state model including negative, positive, and non-responsive states (NRS), but they are also compatible with a four-state model that includes distinct reversibly NRS and non-responsive permanently states (NRPS). Our mathematical model, termed NoRM (Non-Responsive Macrophage) model identifies similarities and differences between BMDM and RAW 264.7 cell responses. In both cell types, transition rates between states in the NoRM model are distinct for each of the tested proteins and, crucially, macrophage hypo-responsiveness is underpinned by changes in transition rates to and from NRS.

Conclusions: Overall, we provide a mathematical model for studying macrophage ecology and community dynamics that can be used to elucidate the role of phenotypically negative macrophage populations in AIH and, primary and secondary responses to LPS.

Developments of Conventional and Microfluidic Flow Cytometry Enabling High-Throughput Characterization of Single Cells

This article first reviews scientific meanings of single-cell analysis by highlighting two key scientific problems: landscape reconstruction of cellular identities during dynamic immune processes and mechanisms of tumor origin and evolution. Secondly, the article reviews clinical demands of single-cell analysis, which are complete blood counting enabled by optoelectronic flow cytometry and diagnosis of hematologic malignancies enabled by multicolor fluorescent flow cytometry. Then, this article focuses on the developments of optoelectronic flow cytometry for the complete blood counting by comparing conventional counterparts of hematology analyzers (e.g., DxH 900 of Beckman Coulter, XN-1000 of Sysmex, ADVIA 2120i of Siemens, and CELL-DYN Ruby of Abbott) and microfluidic counterparts (e.g., microfluidic impedance and imaging flow cytometry). Future directions of optoelectronic flow cytometry are indicated where intrinsic rather than dependent biophysical parameters of blood cells must be measured, and they can replace blood smears as the gold standard of blood analysis in the near future.

Hydrogels for Single-Cell Microgel Production: Recent Advances and Applications

Single-cell techniques have become more and more incorporated in cell biological research over the past decades. Various approaches have been proposed to isolate, culture, sort, and analyze individual cells to understand cellular heterogeneity, which is at the foundation of every systematic cellular response in the human body. Microfluidics is undoubtedly the most suitable method of manipulating cells, due to its small scale, high degree of control, and gentle nature toward vulnerable cells. More specifically, the technique of microfluidic droplet production has proven to provide reproducible single-cell encapsulation with high throughput. Various in-droplet applications have been explored, ranging from immunoassays, cytotoxicity assays, and single-cell sequencing. All rely on the theoretically unlimited throughput that can be achieved and the monodispersity of each individual droplet. To make these platforms more suitable for adherent cells or to maintain spatial control after de-emulsification, hydrogels can be included during droplet production to obtain “microgels.” Over the past years, a multitude of research has focused on the possibilities these can provide. Also, as the technique matures, it is becoming clear that it will result in advantages over conventional droplet approaches. In this review, we provide a comprehensive overview on how various types of hydrogels can be incorporated into different droplet-based approaches and provide novel and more robust analytic and screening applications. We will further focus on a wide range of recently published applications for microgels and how these can be applied in cell biological research at the single- to multicell scale.

Pump-free microfluidic magnetic levitation approach for density-based cell characterization

Magnetic levitation (MagLev) provides a simple but promising method for density-based analysis and detection down to the individual cell level. However, each existing MagLev configuration for the single-cell density measurement, mainly consisting of a capillary (∼50 mm) placed between two magnets, yields a fairly low sample utilization because of no knowledge about the sample cells in the regions other than the limited microscope vision. Moreover, the quantitative analysis may be affected due to the unclearly defined measurement area, which is specifically associated with the uneven magnetization of magnets, cell size, degree of aggregation. In this work, we explore a pump-free microfluidic magnetic levitation approach for density-based cell characterization, enabling sensitive and effective cellular density measurement on small sample volumes. The microfluidic MagLev comprises a pump-free microfluidic chip placed between two ring magnets with like poles facing. With no external pumps, connectors or control facility, much smaller amounts of fluids (∼4 μL) could be driven automatically in the entire microchannel in 16 s. Based on the pump-free mechanism, unique density signatures of cells from different lineages (ARPE-19, HCT116, HeLa, HT1080, Huh7) are characterized by monitoring the levitation profiles. Furthermore, variation in density of A549 lung cancer cells subjected to a drug treatment are observed in our platform, allowing evaluation of the efficacy of the drug treatment at the individual cell level. Thereby, the proposed pump-free microfluidic MagLev platform, a low-cost, fully automatic and portable design for label-free density-based cell characterization, provides a universal detection tool that operates efficiently within small-volume environments.

Mathematical modelling of activation-induced heterogeneity in TNF, IL6, NOS2, and IL1β expression reveals cell state transitions underpinning macrophage responses to LPS

Background: Despite extensive work on macrophage heterogeneity, the mechanisms driving activation induced heterogeneity (AIH) in macrophages remain poorly understood. Here, we aimed to develop mathematical models to explore theoretical cellular states underpinning the empirically observed responses of macrophages following lipopolysaccharide (LPS) challenge. Methods: We obtained empirical data following primary and secondary responses to LPS in two in vitro cellular models (bone marrow-derived macrophages or BMDMs, and RAW 264.7 cells) and single-cell protein measurements for four key inflammatory mediators: TNF, IL-6, pro-IL-1β, and NOS2, and used mathematical modelling to understand heterogeneity. Results: For these four factors, we showed that macrophage community AIH is dependent on LPS dose and that altered AIH kinetics in macrophages responding to a second LPS challenge underpin hypo-responsiveness to LPS. These empirical data can be explained by a mathematical three-state model including negative, positive, and non-responsive states (NRS), but they are also compatible with a four-state model that includes distinct reversibly NRS and non-responsive permanently states (NRPS). Our mathematical model, termed NoRM (Non-Responsive Macrophage) model identifies similarities and differences between BMDM and RAW 264.7 cell responses. In both cell types, transition rates between states in the NoRM model are distinct for each of the tested proteins and, crucially, macrophage hypo-responsiveness is underpinned by changes in transition rates to and from NRS. Conclusions: Overall, we provide a mathematical model for studying macrophage ecology and community dynamics that can be used to elucidate the role of phenotypically negative macrophage populations in AIH and, primary and secondary responses to LPS.

Bet-hedging in innate and adaptive immune systems

Immune system evolution is shaped by the fitness costs and trade-offs associated with mounting an immune response. Costs that arise mainly as a function of the magnitude of investment, including energetic and immunopathological costs, are well-represented in studies of immune system evolution. Less well considered, however, are the costs of immune cell plasticity and specialization. Hosts in nature encounter a large diversity of microbes and parasites that require different and sometimes conflicting immune mechanisms for defense, but it takes precious time to recognize and correctly integrate signals for an effective polarized response. In this perspective, we propose that bet-hedging can be a viable alternative to plasticity in immune cell effector function, discuss conditions under which bet-hedging is likely to be an advantageous strategy for different arms of the immune system, and present cases from both innate and adaptive immune systems that suggest bet-hedging at play.

Emerging roles for endogenous retroviruses in immune epigenetic regulation

In recent years, there has been significant progress toward understanding the transcriptional networks underlying mammalian immune responses, fueled by advances in regulatory genomic technologies. Epigenomic studies profiling immune cells have generated detailed genome-wide maps of regulatory elements that will be key to deciphering the regulatory networks underlying cellular immune responses and autoimmune disorders. Unbiased analyses of these genomic maps have uncovered endogenous retroviruses as an unexpected ally in the regulation of human immune systems. Despite their parasitic origins, studies are finding an increasing number of examples of retroviral sequences having been co-opted for beneficial immune function and regulation by the host cell. Here, we review how endogenous retroviruses have given rise to numerous regulatory elements that shape the epigenetic landscape of host immune responses. We will discuss the implications of these elements on the function, dysfunction, and evolution of innate immunity.

Glutamate metabolism directs energetic trade-offs to shape host-pathogen susceptibility in Drosophila

Individual hosts within populations often show inter-individual variation in their susceptibility to bacterial pathogen-related diseases. Utilizing Drosophila, we highlight that phenotypic variation in host-pathogen susceptibility within populations is driven by energetic trade-offs, facilitated by infection-mediated changes in glutamate metabolism. Furthermore, host-pathogen susceptibility is conditioned by life history, which adjusts immunometabolic sensing in muscles to direct vitamin-dependent reallocation of host energy substrates from the adipose tissue (i.e., a muscle-adipose tissue axis). Life history conditions inter-individual variation in the activation strength of intra-muscular NF-κB signaling. Limited intra-muscular NF-κB signaling activity allows for enhanced infection-mediated mitochondrial biogenesis and function, which stimulates glutamate dehydrogenase-dependent synthesis of glutamate. Muscle-derived glutamate acts as a systemic metabolite to promote lipid mobilization through modulating vitamin B enzymatic cofactor transport and function in the adipose tissue. This energy substrate reallocation improves pathogen clearance and boosts host survival. Finally, life history events that adjust energetic trade-offs can shape inter-individual variation in host-pathogen susceptibility after infection.

Computer vision reveals hidden variables underlying NF-κB activation in single cells

Individual cells are heterogeneous when responding to environmental cues. Under an external signal, certain cells activate gene regulatory pathways, while others completely ignore that signal. Mechanisms underlying cellular heterogeneity are often inaccessible because experiments needed to study molecular states destroy the very states that we need to examine. Here, we developed an image-based support vector machine learning model to uncover variables controlling activation of the immune pathway nuclear factor κB (NF-κB). Computer vision analysis predicts the identity of cells that will respond to cytokine stimulation and shows that activation is predetermined by minute amounts of “leaky” NF-κB (p65:p50) localization to the nucleus. Mechanistic modeling revealed that the ratio of NF-κB to inhibitor of NF-κB predetermines leakiness and activation probability of cells. While cells transition between molecular states, they maintain their overall probabilities for NF-κB activation. Our results demonstrate how computer vision can find mechanisms behind heterogeneous single-cell activation under proinflammatory stimuli.

Turning tumors from cold to inflamed to improve immunotherapy response

Immune checkpoint inhibitors have revolutionized the treatment landscape for a number of cancers over the last few decades. Nevertheless, a majority of patients still do not benefit from these treatments. Such patient-specific lack of response can be predicted, in part, from the immune phenotypes present in the tumor microenvironment. We provide a perspective on options to reprogram the tumors and their microenvironment to increase the therapeutic efficacy of immunotherapies and expand their efficacy against cold tumors. Additionally, we review data from current preclinical and clinical trials aimed at testing the different therapeutic options in monotherapy or preferably in combination with checkpoint inhibitors.

Probing Single-Cell Macrophage Polarization and Heterogeneity Using Thermo-Reversible Hydrogels in Droplet-Based Microfluidics

Human immune cells intrinsically exist as heterogenous populations. To understand cellular heterogeneity, both cell culture and analysis should be executed with single-cell resolution to eliminate juxtacrine and paracrine interactions, as these can lead to a homogenized cell response, obscuring unique cellular behavior. Droplet microfluidics has emerged as a potent tool to culture and stimulate single cells at high throughput. However, when studying adherent cells at single-cell level, it is imperative to provide a substrate for the cells to adhere to, as suspension culture conditions can negatively affect biological function and behavior. Therefore, we combined a droplet-based microfluidic platform with a thermo-reversible polyisocyanide (PIC) hydrogel, which allowed for robust droplet formation at low temperatures, whilst ensuring catalyzer-free droplet gelation and easy cell recovery after culture for downstream analysis. With this approach, we probed the heterogeneity of highly adherent human macrophages under both pro-inflammatory M1 and anti-inflammatory M2 polarization conditions. We showed that co-encapsulation of multiple cells enhanced cell polarization compared to single cells, indicating that cellular communication is a potent driver of macrophage polarization. Additionally, we highlight that culturing single macrophages in PIC hydrogel droplets displayed higher cell viability and enhanced M2 polarization compared to single macrophages cultured in suspension. Remarkably, combining phenotypical and functional analysis on single cultured macrophages revealed a subset of cells in a persistent M1 state, which were undetectable in conventional bulk cultures. Taken together, combining droplet-based microfluidics with hydrogels is a versatile and powerful tool to study the biological function of adherent cell types at single-cell resolution with high throughput.

Stimulus-specific responses in innate immunity: Multilayered regulatory circuits

Immune sentinel cells initiate immune responses to pathogens and tissue injury and are capable of producing highly stimulus-specific responses. Insight into the mechanisms underlying such specificity has come from the identification of regulatory factors and biochemical pathways, as well as the definition of signaling circuits that enable combinatorial and temporal coding of information. Here, we review the multi-layered molecular mechanisms that underlie stimulus-specific gene expression in macrophages. We categorize components of inflammatory and anti-pathogenic signaling pathways into five layers of regulatory control and discuss unifying mechanisms determining signaling characteristics at each layer. In this context, we review mechanisms that enable combinatorial and temporal encoding of information, identify recurring regulatory motifs and principles, and present strategies for integrating experimental and computational approaches toward the understanding of signaling specificity in innate immunity.

Nanosensor Chemical Cytometry for Characterizing the Efflux Heterogeneity of Nitric Oxide from Macrophages

Macrophages are a critical part of the human immune response, and their collective heterogeneity is implicated in disease progression and prevention. A nondestructive, label-free tool does not currently exist for profiling the dynamic, antigenic responses of single macrophages in a collection to correlate with specific molecular expression and correlated biophysical properties at the cellular level, despite the potential for diagnosis and therapeutics. Herein, we develop a nanosensor chemical cytometry (NCC) that can profile the heterogeneity of inducible nitric oxide synthase (iNOS) responses from macrophage populations. By integrating a near-infrared (nIR) fluorescent nanosensor array and collagen layer with microfluidics, the cellular lensing effect of the macrophage was utilized to characterize both nitric oxide (NO) efflux and refractive index (RI) changes at a single-cell level. Using a parallel, multichannel approach, distinct iNOS heterogeneities of macrophages can be monitored at an attomolar (10^-18 mol) sensitivity in a nondestructive and real-time manner with a throughput of exceeding the 200 cells/frame. We demonstrate that estimated mean NO efflux rates of macrophage populations are elevated from 342 (σ = 199) to 464 (σ = 206) attomol/cell·hr with a 3% larger increase in the heterogeneity, and estimated RI of macrophage decrease from 1.366 (σ = 0.015) to 1.359 (σ = 0.009) with trimodal subpopulations under lipopolysaccharide (LPS) activation. These measured values are also in good agreement with Griess assay results and previously reported measurements. This work provides an efficient strategy for single-cell analysis of macrophage populations for cellular manufacturing and biopharmaceutical engineering.

An automated real-time microfluidic platform to probe single NK cell heterogeneity and cytotoxicity on-chip

Cytotoxicity is a vital effector mechanism used by immune cells to combat pathogens and cancer cells. While conventional cytotoxicity assays rely on averaged end-point measures, crucial insights on the dynamics and heterogeneity of effector and target cell interactions cannot be extracted, emphasizing the need for dynamic single-cell analysis. Here, we present a fully automated droplet-based microfluidic platform that allowed the real-time monitoring of effector-target cell interactions and killing, allowing the screening of over 60,000 droplets identifying 2000 individual cellular interactions monitored over 10 h. During the course of incubation, we observed that the dynamics of cytotoxicity within the Natural Killer (NK) cell population varies significantly over the time. Around 20% of the total NK cells in droplets showed positive cytotoxicity against paired K562 cells, most of which was exhibited within first 4 h of cellular interaction. Using our single cell analysis platform, we demonstrated that the population of NK cells is composed of individual cells with different strength in their effector functions, a behavior masked in conventional studies. Moreover, the versatility of our platform will allow the dynamic and resolved study of interactions between immune cell types and the finding and characterization of functional sub-populations, opening novel ways towards both fundamental and translational research.

Spatially Resolved Immunometabolism to Understand Infectious Disease Progression

Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironment may instruct complex and diverse innate and adaptive cellular responses resulting in locally distinct molecular signatures. In turn, these molecular signatures may both drive and be responsive to local metabolic changes in immune as well as non-immune cells, ultimately shaping the outcome of infection. Given the spatial complexity of immune and inflammatory responses during infection, it is evident that understanding the spatial organization of transcripts, proteins, lipids, and metabolites is pivotal to delineating the underlying regulation of local immunity. Molecular imaging techniques like mass spectrometry imaging and spatially resolved, highly multiplexed immunohistochemistry and transcriptomics can define detailed metabolic signatures at the microenvironmental level. Moreover, a successful complementation of these two imaging techniques would allow multi-omics analyses of inflammatory microenvironments to facilitate understanding of disease pathogenesis and identify novel targets for therapeutic intervention. Here, we describe strategies for downstream data analysis of spatially resolved multi-omics data and, using leishmaniasis as an exemplar, describe how such analysis can be applied in a disease-specific context.

Immunoassay-based approaches for development of screening of chlorpyrifos

Chlorpyrifos (CPF) is an extensively used organophosphate pesticide for crop protection. However, there are concerns of it contaminating the environment and human health with estimated three lakh deaths annually. Detection of CPF in blood samples holds significance to avoid severe health outcomes due to continuous exposure. The most common techniques for CPF detection are Gas chromatography (GC) and high-performance liquid chromatography (HPLC). However, these techniques might not be feasible at the community healthcare level due to high-cost instrumentation, time-consuming sample preparation protocol and skilled analysts. Therefore, rapid, effective and economical methods such as immunoassay would be imperative for CPF detection in biological samples. The vital step in immunoassay development is the design of a potent immunogen from non-immunogenic molecules. The molecular modelling protocol could assist in redesigning known CPF linkers and inserting them at different substitutable positions of CPF to get distinctive CPF derivatives. Molecular docking and binding free energy analysis can be used to identify the CPF derivatives having a better binding affinity with carrier protein compared to CPF. The top-ranked CPF derivatives based on docking score and binding energy could be ideal for synthesis and immunogen development. The present review will comprehend technological trends in immunoassay kits for detecting chlorpyrifos from biological samples.