Distinct Subpopulations Research Articles

Genome-wide dissection of genes shaping inflorescence morphology in 242 Chinese south–north sorghum accessions

The inflorescences morphology (IM) of sorghum (Sorghum bicolor L. Moench) affects its resistance to pests, diseases, and grain yields. However, the specific genetic factors underlying in IM are not yet fully elucidated. Here we conducted a comprehensive genome-wide association analysis (GWAS) to identify the stable and adaptive Quantitative Trait Loci (QTL) for five IM traits (panicle length, the number of cob nodes, the number of primary branches, the largest length of the primary branch, and panicle type) in a sorghum panel, which adapted to different environments from the south to north in China. Totally, 2,015,850 high quality single nucleotide polymorphisms (SNPs) were obtained. Population structure analysis showed that two distinct genetic sub-populations were divided according to their geographic origin. Seventy-one QTLs distributed in 41 genetic regions on 9 chromosomes were identified. These regions harbored 21 high-confident candidate genes that were homologous to rice domestication genes, including 7 related to IM. Two domestication-related genes (Sobic.003G052700 and Sobic.006G247700) were located into two major QTL regions (QTL3.4721839 and QTL6.58709500) which were identified in multi-environments. Allelic variations in the two genes displayed a geographical pattern, indicating that different IM traits were selected by south and north sorghum breeders, such as south sorghums had long and loose panicles in order to adapt the hot and humid climate, while north sorghums had short and compact panicle to increase planting density and grain yield per unit area due to dry climate. This work provides new breeding strategies and resources for developing locally adapted sorghum varieties.

Evaluation of coronary microvascular dysfunction and vasospasm in patients with angina and non-obstructive coronary artery disease

Abstract Background Angina in the absence of obstructive coronary artery disease (CAD) is a growing cause of morbidity and mortality, exceeding the economic burden of CAD. Roughly 50-70% of patients undergoing invasive angiography for anginal symptoms have non-obstructive CAD. Within this category, there are distinct sub-populations including patients with angina without evidence of ischemia on prior stress testing (ANOCA), evidence of ischemia on stress testing (INOCA), or history of obstructive CAD with prior revascularization (ANOCA-HxCAD). Coronary microvascular dysfunction (CMD) and/or epicardial vasospasm are common causes of angina in the absence of epicardial CAD despite optimal medical therapy. Differences between these groups, in terms of risk factors and diagnoses remain relatively unknown. Purpose To compare clinical characteristics, symptoms, and diagnoses between patients with ANOCA, INOCA, and ANOCA-HxCAD. Methods In a prospective registry-based cohort study of 306 patients without obstructive CAD (<50% stenosis in epicardial artery) undergoing coronary functional angiography (CFA), we assessed differences in clinical characteristics, symptoms, and CFA diagnoses: (1) endothelial-independent CMD (coronary flow reserve [CFR] <2.5) to adenosine testing, (2) endothelial-dependent CMD (coronary blood flow [CBF]<50% or no change in vessel diameter to 54 mcg intracoronary acetylcholine [ACH]), (3) epicardial vasospasm to 108 mcg intracoronary ACH in 3 groups of patients (ANOCA, INOCA, and ANOCA-HxCAD). Results Among the 306 patients undergoing CFA, 89% were female with a median age of 58 years (49, 67). Patients with ANOCA-HxCAD had a significantly higher prevalence of hypertension, diabetes, heart failure with preserved ejection fraction, and experienced worse dyspnea on exertion as measured by University of San Diego Shortness of Breath (UCSD SOB) in comparison to ANOCA or INOCA patients. However, there were no differences between the groups in terms of anginal severity, functional capacity, or quality of life. In terms of CFA diagnoses, vasospasm was more prevalent in ANOCA-HxCAD (p<0.001) and CMD was more prevalent in ANOCA and INOCA patients (p=0.034) (Table 1). Conclusions Despite differences in clinical characteristics, patients without obstructive CAD have similar anginal severity, functional capacity, and quality of life regardless of evidence of ischemia on prior stress imaging or history of revascularization. There are differences in CFA diagnoses with higher prevalence of CMD in ANOCA and INOCA patients and higher prevalence of vasospasm in ANOCA-HxCAD patients. Determining the underlying diagnoses changes clinical management; therefore, CFA should be considered in all patients without obstructive CAD.

Integrative analysis of bulk and single-cell transcriptomic data reveals novel insights into lipid metabolism and prognostic factors in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is associated with high mortality rate. This study investigated the status of lipid metabolism-related genes in HCC. Bulk transcriptomic and single-cell sequencing data for HCC were retrieved from public databases. The single-cell sequencing data was subjected to dimensionality reduction, which facilitated the annotation of distinct cell subpopulations and marker gene expression analysis within each subpopulation. Genes associated with lipid metabolism in liver cells were identified, and a machine-learning model was developed using the bulk transcriptomic data randomly partitioned into training and validation sets. The efficacy of the model was validated using these two sets. A multifactorial Cox analysis on the model genes combined with clinical features, led to the identification of age, HMGCS2, HNRNPU, and RAN as independent prognostic factors, which were included in the nomogram model construction and validation. A weighted gene co-expression analysis of all genes of the bulk transcriptome samples revealed the correlation between gene modules and risk score. Genes with cor > 0.4 in the highest-expressing module were selected for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis. Immune-related analysis was conducted based on seven algorithms for immune cell infiltration prediction. For the genes in the nomogram model, the expression in clinical pathological factors was also analyzed. The drug sensitivity analysis offered a reference for the selection of targeting drugs. This investigation provides novel insights and a theoretical basis for the prognosis, treatment, and pharmaceutical advancements for patients diagnosed with HCC.

Epstein-Barr virus reactivation induces divergent abortive, reprogrammed, and host shutoff states by lytic progression.

Viral infection leads to heterogeneous cellular outcomes ranging from refractory to abortive and fully productive states. Single cell transcriptomics enables a high resolution view of these distinct post-infection states. Here, we have interrogated the host-pathogen dynamics following reactivation of Epstein-Barr virus (EBV). While benign in most people, EBV is responsible for infectious mononucleosis, up to 2% of human cancers, and is a trigger for the development of multiple sclerosis. Following latency establishment in B cells, EBV reactivates and is shed in saliva to enable infection of new hosts. Beyond its importance for transmission, the lytic cycle is also implicated in EBV-associated oncogenesis. Conversely, induction of lytic reactivation in latent EBV-positive tumors presents a novel therapeutic opportunity. Therefore, defining the dynamics and heterogeneity of EBV lytic reactivation is a high priority to better understand pathogenesis and therapeutic potential. In this study, we applied single-cell techniques to analyze diverse fate trajectories during lytic reactivation in three B cell models. Consistent with prior work, we find that cell cycle and MYC expression correlate with cells refractory to lytic reactivation. We further found that lytic induction yields a continuum from abortive to complete reactivation. Abortive lytic cells upregulate NFκB and IRF3 pathway target genes, while cells that proceed through the full lytic cycle exhibit unexpected expression of genes associated with cellular reprogramming. Distinct subpopulations of lytic cells further displayed variable profiles for transcripts known to escape virus-mediated host shutoff. These data reveal previously unknown and promiscuous outcomes of lytic reactivation with broad implications for viral replication and EBV-associated oncogenesis.

Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients

BackgroundBreast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis.MethodsWe used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. Single-cell RNA sequencing validated the model by examining gene expression heterogeneity at the cellular level.ResultsOur single-cell analyses revealed distinct subpopulations with different expressions of genes related to polyamine metabolism, highlighting the heterogeneity of the tumor microenvironment. The SuperPC model (a constructed risk score) demonstrated high accuracy when predicting patient outcomes. The immune profiling and functional enrichment analyses revealed that the genes identified play a crucial role in cell cycle control and immune modulation. Single-cell validation confirmed that polyamine metabolism genes were present in specific cell clusters. This highlights their potential as therapeutic targets.ConclusionsThis study integrates single cell omics with machine-learning to develop a robust scoring model for breast cancer based on polyamine metabolic pathways. Our findings offer new insights into tumor heterogeneity, and a novel framework to personalize prognosis. Single-cell technologies are being used in this context to enhance our understanding of the complex molecular terrain of breast cancer and support more effective clinical management.

Ultrastructural analysis of lamellar bodies in type II alveolar epithelial cells in the human lung.

Pulmonary surfactant is produced by type II alveolar epithelial cells (AEC2) and stored in lamellar bodies (LBs) prior to secretion. Here, we characterize AEC2 and their LBs in the human lung ultrastructurally and quantitatively. Five human lungs were analyzed by transmission electron microscopy, serial section electron tomography and stereology. A human lung contained about 24 billion AEC2 with a mean size of about 650 µm³. The number of AEC2 as well as the total volume of LBs per lung, about 1.9 mL, strongly correlated with total lung volume. A single AEC2 contained an LB volume of about 74 µm³. This amount was packed in about 324 LBs with a mean size of 0.24 µm³. Three morphologically distinct subpopulations of LBs were identified: 1.) isolated LBs which make up the majority (average 300 per AEC2), 2.) LBs connected to each other via pores (average 23 per AEC2), and 3.) LBs connected to the plasma membrane via a fusion pore (average 1 per AEC2). Along this sequence of subpopulations, the mean size of LBs increased. LBs that are connected either with each other or to the plasma membrane contained about 14% of an AEC2´s LB volume. This is in line with the concept of an intermediate surfactant pool, stored in LBs either directly or indirectly connected to the plasma membrane. In summary, this study provides quantitative reference data on surfactant-storing LBs in AEC2 as well as morphological evidence for an intermediate surfactant pool in the human lung.

No two clones are alike: characterization of heterologous subpopulations in a transgenic cell line of the model diatom Phaeodactylum tricornutum

BackgroundConjugation-based episome delivery is a highly efficient method used to transfer DNA into the diatom Phaeodactylum tricornutum, facilitating the production of recombinant proteins and high-value metabolites. However, previous reports have indicated phenotypic heterogeneity among individual cells from clonally propagated exconjugant cell lines, potentially affecting the stability of recombinant protein production in the diatom.ResultsHere, we characterized the differences between subpopulations with distinct fluorescence intensity phenotypes derived from a single exconjugant colony of P. tricornutum expressing the enhanced green fluorescent protein (eGFP). We analyzed the expression cassette sequence integrity, plasmid copy number, and global gene expression. Our findings reveal that lower copy numbers and the deletion of the expression cassette in part of the population contributed to low transgene expression. Gene co-expression analysis identified a set of genes with similar expression pattern to eGFP including a gene encoding a putative Flp recombinase, which may be related to variations in fluorescence intensity. These genes thus present themselves as potential candidates for increasing recombinant proteins production in P. tricornutum episomal expression system.ConclusionsOverall, our study elucidates genetic and transcriptomic differences between distinct subpopulations in a clonally propagated culture, contributes to a better understanding of heterogeneity in diatom expression systems for synthetic biology applications.

Detection and characterization of colorectal cancer by autofluorescence lifetime imaging on surgical specimens.

Colorectal cancer (CRC) ranks among the most prevalent malignancies worldwide, driving a quest for comprehensive characterization methods. We report a characterization of the ex vivo autofluorescence lifetime fingerprint of colorectal tissues obtained from 73 patients that underwent surgical resection. We specifically target the autofluorescence characteristics of collagens, reduced nicotine adenine (phosphate) dinucleotide (NAD(P)H), and flavins employing a fiber-based dual excitation (375nm and 445nm) optical imaging system. Autofluorescence-derived parameters obtained from normal tissues, adenomatous lesions, and adenocarcinomas were analyzed considering the underlying clinicopathological features. Our results indicate that differences between tissues are primarily driven by collagen and flavins autofluorescence parameters. We also report changes in the autofluorescence parameters associated with NAD(P)H that we tentatively attribute to intratumoral heterogeneity, potentially associated to the presence of distinct metabolic subpopulations. Changes in autofluorescence signatures of malignant tumors were also observed with lymphatic and venous invasion, differentiation grade, and microsatellite instability. Finally, we characterized the impact of radiative treatment in the autofluorescence fingerprints of rectal tissues and observed a generalized increase in the mean lifetime of radiated adenocarcinomas, which is suggestive of altered metabolism and structural remodeling. Overall, our preliminary findings indicate that multiparametric autofluorescence lifetime measurements have the potential to significantly enhance clinical decision-making in CRC, spanning from initial diagnosis to ongoing management. We believe that our results will provide a foundational framework for future investigations to further understand and combat CRC exploiting autofluorescence measurements.

Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations

Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression and there is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet systems to study these processes in vitro are limited. Single-cell RNA sequencing (scRNA-seq) has revealed that some cancer cell lines include distinct subpopulations. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. With clusterCleaver, ESAM and BST2/tetherin were experimentally validated as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification of surface markers for tracking and isolating transcriptomically distinct subpopulations within cell lines. This tool paves the way for studies on coexisting cancer cell subpopulations in well-defined in vitro systems.

Multiplexed single-cell imaging reveals diverging subpopulations with distinct senescence phenotypes during long-term senescence induction.

Cellular senescence is a phenotypic state that contributes to the progression of age-related disease through secretion of pro-inflammatory factors known as the senescence associated secretory phenotype (SASP). Understanding the process by which healthy cells become senescent and develop SASP factors is critical for improving the identification of senescent cells and, ultimately, understanding tissue dysfunction. Here, we reveal how the duration of cellular stress modulates the SASP in distinct subpopulations of senescent cells. We used multiplex, single-cell imaging to build a proteomic map of senescence induction in human epithelial cells induced to senescence over the course of 31 days. We map how the expression of SASP proteins increases alongside other known senescence markers such as p53, p21, and p16 INK4a . The aggregated population of cells responded to etoposide with an accumulation of stress response factors over the first 11 days, followed by a plateau in most proteins. At the single-cell level, however, we identified two distinct senescence cell populations, one defined primarily by larger nuclear area and the second by higher protein concentrations. Trajectory inference suggested that cells took one of two discrete molecular paths from unperturbed healthy cells, through a common transitional subpopulation, and ending at the discrete terminal senescence phenotypes. Our results underscore the importance of using single-cell proteomics to identify the mechanistic pathways governing the transition from senescence induction to a mature state of senescence characterized by the SASP.

Multi-Omics Profiling Unveils the Complexity and Dynamics of Immune Infiltrates in Intrahepatic Cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is a highly heterogeneous malignancy. The reasons behind the global rise in the incidence of ICC remain unclear, and there exists limited knowledge regarding the immune cells within the tumor microenvironment (TME). In this study, a more comprehensive analysis of multi-omics data was performed using machine learning methods. The study found that the immunoactivity of B cells, macrophages, and T cells in the infiltrating immune cells of ICC exhibits a significantly higher level of immunoactivity in comparison to other immune cells. During the immune sensing and response, the effect of antigen-presenting cells (APCs) such as B cells and macrophages on activating NK cells was weakened, while the effect of activating T cells became stronger. Simultaneously, four distinct subpopulations, namely BLp, MacrophagesLp, BHn, and THn, have been identified from the infiltrating immune cells, and their corresponding immune-related marker genes have been identified. The immune sensing and response model of ICC has been revised and constructed based on our current comprehension. This study not only helps to deepen the understanding the heterogeneity of infiltrating immune cells in ICC, but also may provide valuable insights into the diagnosis, evaluation, treatment, and prognosis of ICC.

Tetrahedral DNA-Based Ternary Recognition Ratiometric Fluorescent Probes for Real-Time In Situ Resolving Lysosome Subpopulations in Living Cells via Cl-, Ca2+, and pH.

Lysosomes are multifunctional organelles vital for cellular homeostasis with distinct subpopulations characterized by varying levels of Cl-, Ca2+, and H+. In situ visualization of these parameters is crucial for lysosomal research, yet developing probes that can simultaneously detect multiple ions remains challenging. Herein, we developed a lysosome-targeting ternary recognition ratiometric fluorescent probe based on tetrahedral DNA nanostructures (TDNs) to analyze lysosome subpopulations by Cl-, Ca2+, and pH. The TDN probe is assembled from four single-stranded DNAs, each end-modified with responsive fluorophores (Pr-Cl for Cl-, Pr-Ca for Ca2+, and Pr-pH for pH) or a reference fluorophore (Cy5). The fluorophores are integrated at the vertices of the rigid TDN to minimize mutual interference, and their fixed stoichiometry establishes a robust ternary recognition ratiometric fluorescence sensor for in situ resolution of lysosome subpopulations in living cells. Accordingly, a rise in lysosome subpopulations 2/6 characterized by low [Cl-], medium/high [Ca2+], and high pH was observed in the Niemann-Pick disease model cells but seldom observed in the control group. Conversely, there was a marked decline in the fraction of subpopulations 1/4/5 characterized by high [Cl-], medium to low [Ca2+], and pH. These changes were substantially reversed upon treatment. The probe holds great promise for studying lysosome subpopulations and the diagnosis and treatment of related diseases.

A modular circuit coordinates the diversification of courtship strategies.

Mate recognition systems evolve rapidly to reinforce the reproductive boundaries between species, but the underlying neural mechanisms remain enigmatic. Here we leveraged the rapid coevolution of female pheromone production and male pheromone perception in Drosophila1,2 to gain insight into how the architecture of mate recognition circuits facilitates their diversification. While in some Drosophila species females produce unique pheromones that act to arouse their conspecific males, the pheromones of most species are sexually monomorphic such that females possess no distinguishing chemosensory signatures that males can use for mate recognition3. We show that Drosophila yakuba males evolved the ability to use a sexually monomorphic pheromone, 7-tricosene, as an excitatory cue to promote courtship. By comparing key nodes in the pheromone circuits across multiple Drosophila species, we reveal that this sensory innovation arises from coordinated peripheral and central circuit adaptations: a distinct subpopulation of sensory neurons has acquired sensitivity to 7-tricosene and, in turn, selectively signals to a distinct subset of P1 neurons in the central brain to trigger courtship. Such a modular circuit organization, in which different sensory inputs can independently couple to parallel courtship control nodes, may facilitate the evolution of mate recognition systems by allowing novel sensory modalities to become linked to male arousal. Together, our findings suggest how peripheral and central circuit adaptations can be flexibly coordinated to underlie the rapid evolution of mate recognition strategies across species.

Modulating Immune Responses: The Double-Edged Sword of Platelet CD40L.

The CD40-CD40L receptor ligand pair plays a fundamental role in the modulation of the innate as well as the adaptive immune response, regulating monocyte, T and B cell activation, and antibody isotype switching. Although the expression and function of the CD40-CD40L dyad is mainly attributed to the classical immune cells, the majority of CD40L is expressed by activated platelets, either in a membrane-bound form or shed as soluble molecules in the circulation. Platelet-derived CD40L is involved in the communication with different immune cell subpopulations and regulates their functions effectively. Thus, platelet CD40L contributes to the containment and clearance of bacterial and viral infections, and additionally guides leukocytes to sites of infection. However, platelet CD40L promotes inflammatory cellular responses also in a pathophysiological context. For example, in HIV infections, platelet CD40L is supportive of neuronal inflammation, damage, and finally HIV-related dementia. In sepsis, platelet CD40L can induce extensive endothelial and epithelial damage resulting in barrier dysfunction of the gut, whereby the translocation of microbiota into the circulation further aggravates the uncontrolled systemic inflammation. Nevertheless, a distinct platelet subpopulation expressing CD40L under septic conditions can attenuate systemic inflammation and reduce mortality in mice. This review focuses on recent findings in the field of platelet CD40L biology and its physiological and pathophysiological implications, and thereby highlights platelets as vital immune cells that are essential for a proper immune surveillance. In this context, platelet CD40L proves to be an interesting target for various inflammatory diseases. However, either an agonism or a blockade of CD40L needs to be well balanced since both the approaches can cause severe adverse events, ranging from hyperinflammation to immune deficiency. Thus, an interference in CD40L activities should be likely done in a context-dependent and timely restricted manner.

Stability and computational analysis of Influenza-A epidemic model through double time delay

Delay factors demonstration has a significant role in controlling a strain of infectious disease instead of a pharmaceutical strategy. According to the World Health Organization (WHO), 3–5 million cases are reported annually and approximately 290,000 to 650,000 respiratory deaths annually. So, in the present study, we develop a delayed mathematical model based on delay differential equations (DDEs) for the influenza epidemic using a deterministic approach by introducing double delay parameters. The four distinct sub-populations are considered susceptible, exposed, infected, and recovered. For the rigorous analysis, the fundamental properties of the model like positivity, boundedness, existence, and uniqueness, were studied. The influenza-free equilibrium (IFE) and influenza-existing equilibrium (IEE), are the two nonnegative equilibrium points that the model demonstrates. Both locally and globally, the asymptotic stability of the equilibrium points of the model is established and shown under specific situations of reproduction number. Additionally, investigated the model's parameter sensitivity and determined the relative sensitivity of each parameter. Both standard and nonstandard methods—such as Euler, Runge-Kutta, and nonstandard finite difference with a delayed sense—are presented to make computational analysis support a dynamical analysis and the best visualization of results. The stability of the non-standard finite difference scheme is thoroughly analyzed around the steady states of the model. Additionally, the results show that the nonstandard finite difference approximation is an efficient, cost-effective method, independent of time step size, to solve such highly nonlinear and complex real-world problems.

12419 Single-nuclei Sequencing Of Normal Donor Cadaveric Parathyroid Glands Reveals Distinct Cellular Subpopulations With Key Differences In Gland Anatomical Location And Suppressed Vs Non-suppressed Physiological Status

Abstract Disclosure: T. Glinin: None. E. Khanafshar: None. J.A. Sosa: Advisory Board Member; Self; Novo Nordisk, AstraZeneca, Eli Lilly & Company. Grant Recipient; Self; Exelixis, Inc., Eli Lilly & Company. J. Koh: None. Despite the significant clinical burden of parathyroid disorders, little is known at the molecular level about the cellular composition of normal parathyroid glands (PTGs). We performed a single-nuclei RNAseq study of six cadaveric PTGs (three from the superior anatomical location, three inferior) from four donors (two female). A board-certified pathologist confirmed that the sequenced PTGs were histologically normal. Using the split-pool method, we sequenced 83,693 nuclei, generating 1.7B reads. Data integration was performed with the Harmony algorithm in Seurat 5.0.1. Cluster analysis revealed 14 discrete populations of PTG origin. Gene set enrichment identified clusters corresponding to endothelial cells, neurons, microglia, mast cells, dendritic cells, stromal fibroblasts, macrophages, and smooth muscle. The remaining six clusters were closely related but distinct populations sharing markers including PTH, CaSR, SPOCK3, PRKCE, and PLCB1 (p<2e-300 for group specificity) but with differentially expressed gene (DEG) patterns between clusters suggestive of specialized functions in VEGF signaling (KIAA1549L), GPCR downstream signaling (GRM7, ADGRL3), and subcellular spatial organization (SYNE1) (p<2e-24 for cluster specificity). Superior and inferior PTGs were distinguished by 8 superior-specific DEGs (p<2e-245) including HOXB3, expressed in 71% of superior PTG cells vs 6% of inferior PTG cells. Enhanced expression of HOXB3, a homeobox transcription factor found to inhibit tumorigenesis in multiple tissues, could explain in part why adenomas are three times less likely to arise in superior PTGs. During procurement, one of the presumptive normal donors was found to have a single grossly enlarged, hypercellular PTG, elevated PTH (140 pg/ml), and hypercalcemia (11.2 mg/dL), consistent with primary hyperparathyroidism (PHPT). In PHPT patients with a single tumor, contralateral PTGs are functionally suppressed by the dominant adenoma. We compared the histologically normal suppressed and unsuppressed PTGs. Fifteen genes were more highly expressed in suppressed PTGs, including LRP2, a multi-ligand receptor known to bind PTH (p = 2e-300). Fourteen genes were more highly expressed in unsuppressed PTGs (p<2.14e-296), including PDE11A, NRG2, NRXN3, and PRLR, which are all associated with GABA receptor signaling (q = 2.8e-5). These data independently support our group’s prior work proposing a role for the GABA receptor in PHPT. Differential expression in endothelial cells, neurons, and fibroblasts from suppressed PTGs suggests that non-endocrine cells may also be responsive to changes in PTG activity. Finally, the different proportions of cells with suppressed or unsuppressed gene expression signatures observed between clusters suggests that PTGs incorporate distinct populations of cells reflective of physiological activity or functional suppression. Presentation: 6/2/2024

Identification of KLHL17 as a prognostic marker for prostate cancer based on single-cell sequencing and in vitro/in vivo experiments

BackgroundProstate cancer (PCa) is a leading cause of cancer-related mortality among men, characterized by significant heterogeneity that complicates diagnosis and treatment.Methods and resultsTo enhance our understanding of PCa, we utilized single-cell RNA sequencing (scRNA-seq) data to identify distinct malignant epithelial cell subpopulations and their molecular characteristics. By integrating scRNA-seq data with bulk RNA-seq data, we constructed a prognostic risk score model. The influence of key genes identified in the risk score on PCa was validated through both in vitro and in vivo experiments. Our study revealed eight unique malignant epithelial cell clusters, each exhibiting distinct molecular characteristics and biological functions. KEGG and GO enrichment analyses highlighted their involvement in various pathways. The prognostic risk score model demonstrated strong predictive power for patient outcomes, particularly in predicting progression-free survival (PFS). Notably, KLHL17, identified as a high-risk gene, was found to significantly impact PCa cell proliferation, migration, invasion, and apoptosis upon knockdown. This finding was further validated in vivo using a subcutaneous xenograft tumor model, where reduced KLHL17 expression led to decreased tumor growth.ConclusionOur research provides a comprehensive analysis of PCa heterogeneity and highlights KLHL17 as a potential therapeutic target.

Mechanisms and Implications of Phenotypic Switching in Bacterial Pathogens.

Bacteria encounter various stressful conditions within a variety of dynamic environments, which they must overcome for survival. One way they achieve this is by developing phenotypic heterogeneity to introduce diversity within their population. Such distinct subpopulations can arise through endogenous fluctuations in regulatory components, wherein bacteria can express diverse phenotypes and switch between them, sometimes in a heritable and reversible manner. This switching may also lead to antigenic variation, enabling pathogenic bacteria to evade the host immune response. Therefore, phenotypic heterogeneity plays a significant role in microbial pathogenesis, immune evasion, antibiotic resistance, host niche tissue establishment and environmental persistence. This heterogeneity can result from stochastic and responsive switches, as well as various genetic and epigenetic mechanisms. The development of phenotypic heterogeneity may create clonal populations that differ in their level of virulence, contribute to the formation of biofilms, and allow for antibiotic persistence within select morphological variants. This review delves into the current understanding of the molecular switching mechanisms underlying phenotypic heterogeneity, highlighting their roles in establishing infections caused by select bacterial pathogens.

CXCL12+ Tumor-associated Endothelial Cells Promote Immune Resistance in Hepatocellular Carcinoma.

BackgroundThe tumor microenvironment (TME) plays a crucial role in the limited efficacy of existing treatments for hepatocellular carcinoma (HCC), with tumor-associated endothelial cells (TECs) serving as fundamental TME components that substantially influence tumor progression and treatment efficacy. However, the precise roles and mechanisms of TECs in HCC remain inadequately understood. MethodsWe employed a multi-omics profiling strategy to investigate the single-cell and spatiotemporal evolution of TECs within the microenvironment of HCC tumors showcasing varied responses to immunotherapy. Through an analysis of a clinical cohort of HCC patients, we explored the correlation between TEC subpopulations and immunotherapy outcomes. The influence of TEC subsets on the immune microenvironment was confirmed through comprehensive in vitro and in vivo studies. To further explore the mechanisms of distinct TEC subpopulations in microenvironmental modulation and their impact on immunotherapy, we utilized TEC subset-specific knockout mouse models as well as humanized mouse models. ResultsIn this research, we identified a new subset of CXCL12+ TECs that exert a crucial role in immune suppression within the HCC TME. Functionally, CXCL12+ TECs impede the differentiation of CD8+ naïve T cells into CD8+ cytotoxic T cells by secreting CXCL12. Furthermore, they attract myeloid-derived suppressor cells (MDSCs). A bispecific antibody was developed to target both CXCL12 and PD1 specifically, showing significant promise in bolstering anti-tumor immune responses and advancing HCC therapy. ConclusionsCXCL12+ TECs are pivotal in mediating immunosuppression within HCC microenvironment and targeting CXCL12+ TECs presents a promising approach to augment the efficacy of immunotherapies in HCC patients. Impact and implicationThis investigation reveals a pivotal mechanism in the HCC TME, where CXCL12+ TECs emerge as crucial modulators of immune suppression. The discovery of CXCL12+ TECs as inhibitors of CD8+ naïve T cell activation and recruiters of MDSCs significantly advances our grasp of the dynamic between HCC and immune regulation. Moreover, the development and application of a bispecific antibody precisely targeting CXCL12 and PD1 has proven to enhance immune responses in a humanized mouse HCC model. This finding underscores a promising therapeutic direction for HCC, offering the potential to amplify the impact of current immunotherapies.

Size photometry and fluorescence imaging of immobilized immersed extracellular vesicles.

Immunofluorescence analysis of individual extracellular vesicles (EVs) in common fluorescence microscopes is gaining popularity due to its accessibility and high fluorescence sensitivity; however, EV number and size are only measurable using fluorescent stains requiring extensive sample manipulations. Here we introduce highly sensitive label-free EV size photometry (SP) based on interferometric scattering (iSCAT) imaging of immersed EVs immobilized on a glass coverslip. We implement SP on a common inverted epifluorescence microscope with LED illumination and a simple 50:50 beamsplitter, permitting seamless integration of SP with fluorescence imaging (SPFI). We present a high-throughput SPFI workflow recording >10,000 EVs in 7min over ten 88×88µm2 fields of view, pre- and post-incubation imaging to suppress background, along with automated image alignment, aberration correction, spot detection and EV sizing. We achieve an EV sizing range from 37 to ∼220nm in diameter with a dual 440 and 740nm SP illumination scheme, and suggest that this range can be extended by more advanced image analysis or additional hardware customization. We benchmark SP to flow cytometry using calibrated silica nanoparticles and demonstrate superior, label-free sensitivity. We showcase SPFI's potential for EV analysis by experimentally distinguishing surface and volumetric EV dyes, observing the deformation of EVs adsorbed to a surface, and by uncovering distinct subpopulations in <100nm-in-diameter EVs with fluorescently tagged membrane proteins.