Variety Of Cell Types Research Articles

Extracellular vesicles from type-2 macrophages increase the survival of chronic lymphocytic leukemia cells ex vivo

The resistance of Chronic Lymphocytic Leukemia (CLL) B-cells to cell death is mainly attributed to interactions within their microenvironment, where they interact with various types of cells. Within this microenvironment, CLL-B-cells produce and bind cytokines, growth factors, and extracellular vesicles (EVs). In the present study, EVs purified from nurse-like cells and M2-polarized THP1 cell (M2-THP1) cultures were added to CLL-B-cells cultures. EVs were rapidly internalized by B-cells, leading to a decrease in apoptosis (P = 0.0162 and 0.0469, respectively) and an increased proliferation (P = 0.0335 and 0.0109). Additionally, they induced an increase in the resistance of CLL-B-cells to Ibrutinib, the Bruton kinase inhibitor in vitro (P = 0.0344). A transcriptomic analysis showed an increase in the expression of anti-apoptotic gene BCL-2 (P = 0.0286) but not MCL-1 and an increase in the expression of proliferation-inducing gene APRIL (P = 0.0286) following treatment with EVs. Meanwhile, an analysis of apoptotic protein markers revealed increased amounts of IGFBP-2 (P = 0.0338), CD40 (P = 0.0338), p53 (P = 0.0219) and BCL-2 (P = 0.0338). Finally, exploration of EVs protein content by mass spectrometry revealed they carry various proteins involved in known oncogenic pathways and the RNAseq analysis of CLL-B-cells treated or not with NLCs EVs show various differentially expressed genes.

Knock out aryl hydrocarbon receptor gene in adipose-derived mesenchymal stem cell line (PT-5006) by CRISPR/Cas9

Mesenchymal stem cells (MSCs) have garnered significant attention in biomedical studies due to their remarkable properties, such as self-renewal, differentiation into diverse cell types and immune responses. The proliferation and differentiation of MSCs are significantly influenced by the ligand-dependent transcription factor known as the aryl hydrocarbon receptor (AhR). In order to understand the roles of Ahr in adipose-derived MSCs (AD-MSCs), we disrupted the Ahr gene in this work using CRISPR/Cas9 gene editing technology. The gRNA/Cas9 dual vector and donor vector were introduced into the AD-MSC cell line (PT-5006). Green fluorescent protein (GFP) expression and puromycin resistance were used to identify the transfected cells. AhR-KO cells were cloned and confirmed by PCR and sequencing. By using RT-qPCR, the expression levels of AhR and the Ahr-related gene Cyp1B1 were investigated. The results showed that the knocked out of AhR using CRISPR/Cas9, resulting significantly decreased expression of 7.69-fold for AhR and 3.70-fold for Cyp1B1 in the cells. These cell clones and CRISPR/Cas9 vectors could be used as tools to investigate the functions of AhR in both AD-MSCs and other cell types.

Harmonic imaging for nonlinear detection of acoustic biomolecules.

Gas vesicles (GVs) based on acoustic reporter genes have emerged as potent contrast agents for cellular and molecular ultrasound imaging. These air-filled, genetically encoded protein nanostructures can be expressed in a variety of cell types in vivo to visualize cell location and activity or injected systemically to label and monitor tissue function. Distinguishing GVs from tissue signal deep inside intact organisms requires imaging approaches such as amplitude modulation (AM) or collapse-based pulse sequences, however they have limitations in sensitivity or require irreversible collapse of the GVs that restricts its scope for imaging dynamic cellular processes. To address these limitations, this study explores the utility of harmonic imaging to enhance the sensitivity of non-destructive imaging of GVs and cellular processes. Traditional fundamental-frequency imaging utilizing cross-wave AM (xAM) sequences has been deemed optimal for GV imaging. Contrary to this, we hypothesize that harmonic imaging, integrated with xAM could significantly elevate GV detection sensitivity. To verify our hypothesis, we conducted imaging on tissue-mimicking phantoms embedded with purified GVs, mammalian cells genetically modified to express GVs, and live mice after systemic GV infusion. Our findings reveal that harmonic xAM (HxAM) imaging markedly surpasses traditional xAM in isolating GVs' nonlinear acoustic signature, showcasing significant enhancements in signal-to-background and contrast-to-background ratios across all tested samples. Further investigation into the backscattered spectra elucidates the efficacy of harmonic imaging in conjunction with xAM. HxAM imaging enables the detection of lower concentrations of GVs and cells with ultrasound and extends the imaging depth in vivo by up to 20% and imaging performance metrics by up to 10dB. These advancements bolster the capabilities of ultrasound for molecular and cellular imaging, underscoring the potential of using harmonic signals to amplify GV detection.

Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia.

Sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli to the central nervous system. Single-cell RNA sequencing has provided insights into the diversity of sensory ganglia cell types in rodents, nonhuman primates, and humans, but it remains difficult to compare cell types across studies and species. We thus constructed harmonized atlases of the DRG and TG that describe and facilitate comparison of 18 neuronal and 11 non-neuronal cell types across six species and 31 datasets. We then performed single-cell/nucleus RNA sequencing of DRG from both human and the highly regenerative axolotl and found that the harmonized atlas also improves cell type annotation, particularly of sparse neuronal subtypes. We observed that the transcriptomes of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The resources presented here can guide future studies in comparative transcriptomics, simplify cell-type nomenclature differences across studies, and help prioritize targets for future analgesic development.

Spatial proteomic landscape of primary and relapsed hepatocellular carcinoma reveals immune escape characteristics in early relapse.

Surgical resection serves as the principal curative strategy for hepatocellular carcinoma (HCC), yet the incidence of postoperative recurrence remains alarmingly high. However, the spatial molecular structural alterations contributing to postoperative recurrence in HCC are still poorly understood. We employed imaging mass cytometry to profile the in-situ expression of 33 proteins within 358,729 single cells of 92 clinically annotated surgical specimens from 46 patients who were treated with surgical resections for primary and relapsed tumors. We revealed the recurrence progression of HCC was governed by the dynamic spatial distribution and functional interplay of diverse cell types across adjacent normal, tumor margin, and intratumor regions. Our exhaustive analyses revealed an aggressive, immunosuppression-related spatial ecosystem in relapsed HCC. Additionally, we illustrated the prominent implications of the TME of tumor margins in association with relapse HCC. Moreover, we identified a novel subpopulation of dendritic cells (PDL1+CD103+ DCs) enriched in the peritumoral area that correlated with early postoperative recurrence, which was further validated in an external cohort. Through the analysis of scRNA-seq data, we found the interaction of PDL1+CD103+ DCs with regulatory T cells and exhausted T cells enhanced immunosuppression and immune escape via multiple ligand-receptor pathways. We comprehensively depicted the spatial landscape of single-cell dynamics and multicellular architecture within primary and relapsed HCC. Our findings highlight spatial organization is a prominent determinant of HCC recurrence and provide a valuable insight into the immune evasion mechanisms driving recurrence.

Noble Metal Nanoparticle‐Based Aptasensors: A Powerful Tool for Exosomal Detection

AbstractExosomes, secreted by various types of cells, play a crucial role in cell‐to‐cell communication by transporting essential molecular cargos that largely mirror the pathophysiological attributes of their parent cells. Increasing evidence has shown that exosomes emerge as the reliable early biomarkers for different diseases. Clearly, exosomal detection with a high sensitivity and specificity becomes highly essential to advance the understanding of disease progression and to develop early diagnostic modalities. Among different types of biosensors, aptasensors have received significant attention as the diagnostic tools considering their programmability and targeting ability. Noble metal nanomaterials possess distinctive physicochemical properties, allowing for ready functionalization with aptamers via both physical adsorption and chemical immobilization. By utilizing the aptamers as the recognition elements, noble metal nanoparticle‐based aptasensors offer a promising platform for rapid, cost‐effective, and sensitive in situ detection of exosomes. In this review, the progress will summarized in exosomes as a biomarker for diseases and the recent advances in the use of noble metal nanoparticle/aptamer‐based sensors for analysis of exosomes and other extracellular vesicles.

MiR-18a affects hypoxia induced glucose metabolism transition in HT22 hippocampal neuronal cell line through the Hif1a gene

Hypoxia can cause a variety of diseases, including ischemic stroke and neurodegenerative diseases. Within a certain range of partial pressure of oxygen, cells can respond to changes in oxygen. Changes in oxygen concentration beyond a threshold will cause damage or even necrosis of tissues and organs, especially for the central nervous system. Therefore, it is very important to find appropriate measures to alleviate damage. MiRNAs can participate in the regulation of hypoxic responses in various types of cells. MiRNAs are involved in regulating hypoxic responses in many types of tissues by activating the hypoxia-inducible factor (HIF) to affect angiogenesis, glycolysis and other biological processes. By analyzing differentially expressed miRNAs in hypoxia and hypoxia-related studies, as well as the HT22 neuronal cell line under hypoxic stress, we found that the expression of miR-18a was changed in these models. MiR-18a could regulate glucose metabolism in HT22 cells under hypoxic stress by directly regulating the 3’UTR of the Hif1a gene. As a small molecule, miRNAs are easy to be designed into small nucleic acid drugs, so this study can provide a theoretical basis for the research and treatment of nervous system diseases caused by hypoxia.Graphical

Hyperactivation of SREBP induces pannexin-1-dependent lytic cell death

Sterol-regulatory element binding proteins (SREBPs) are a conserved transcription factor family governing lipid metabolism. When cellular cholesterol level is low, SREBP2 is transported from the endoplasmic reticulum to the Golgi apparatus where it undergoes proteolytic activation to generate a soluble N-terminal fragment, which drives the expression of lipid biosynthetic genes. Malfunctional SREBP activation is associated with various metabolic abnormalities. In this study, we find that overexpression of the active nuclear form SREBP2 (nSREBP2) causes caspase-dependent lytic cell death in various types of cells. These cells display typical pyroptotic and necrotic signatures, including plasma membrane ballooning and release of cellular contents. However, this phenotype is independent of the gasdermin family proteins or mixed lineage kinase domain-like (MLKL). Transcriptomic analysis identifies that nSREBP2 induces expression of p73, which further activates caspases. Through whole-genome CRISPR-Cas9 screening, we find that Pannexin-1 (PANX1) acts downstream of caspases to promote membrane rupture. Caspase-3 or 7 cleaves PANX1 at the C-terminal tail and increases permeability. Inhibition of the pore-forming activity of PANX1 alleviates lytic cell death. PANX1 can mediate gasdermins and MLKL-independent cell lysis during TNF-induced or chemotherapeutic reagents (doxorubicin or cisplatin)-induced cell death. Together, this study uncovers a noncanonical function of SREBPs as a potentiator of programmed cell death and suggests that PANX1 can directly promote lytic cell death independent of gasdermins and MLKL.

CD59 Protects Primary Human Cerebrovascular Smooth Muscle Cells from Cytolytic Membrane Attack Complex.

Cerebral amyloid angiopathy is characterized by a weakening of the small- and medium-sized cerebral arteries, as their smooth muscle cells are progressively replaced with acellular amyloid β, increasing vessel fragility and vulnerability to microhemorrhage. In this context, an aberrant overactivation of the complement system would further aggravate this process. The surface protein CD59 protects most cells from complement-induced cytotoxicity, but expression levels can fluctuate due to disease and varying cell types. The degree to which CD59 protects human cerebral vascular smooth muscle (HCSM) cells from complement-induced cytotoxicity has not yet been determined. To address this shortcoming, we selectively blocked the activity of HCSM-expressed CD59 with an antibody, and challenged the cells with complement, then measured cellular viability. Unblocked HCSM cells proved resistant to all tested concentrations of complement, and this resistance decreased progressively with increasing concentrations of anti-CD59 antibody. Complete CD59 blockage, however, did not result in a total loss of cellular viability, suggesting that additional factors may have some protective functions. Taken together, this implies that CD59 plays a predominant role in HCSM cellular protection against complement-induced cytotoxicity. The overexpression of CD59 could be an effective means of protecting these cells from excessive complement system activity, with consequent reductions in the incidence of microhemorrhage. The precise extent to which cellular repair mechanisms and other complement repair proteins contribute to this resistance has yet to be fully elucidated.

The expression patterns of different cell types and their interactions in the tumor microenvironment are predictive of breast cancer patient response to neoadjuvant chemotherapy.

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While the TME's impact on immunotherapy has been extensively studied, its role in chemotherapy response remains less explored. To address this, we developed DECODEM (DEcoupling Cell-type-specific Outcomes using DEconvolution and Machine learning), a generic computational framework leveraging cellular deconvolution of bulk transcriptomics to associate the gene expression of individual cell types in the TME with clinical response. Employing DECODEM to analyze the gene expression of breast cancer (BC) patients treated with neoadjuvant chemotherapy, we find that the gene expression of specific immune cells (myeloid, plasmablasts, B-cells) and stromal cells (endothelial, normal epithelial, CAFs) are highly predictive of chemotherapy response, going beyond that of the malignant cells. These findings are further tested and validated in a single-cell cohort of triple negative breast cancer. To investigate the possible role of immune cell-cell interactions (CCIs) in mediating chemotherapy response, we extended DECODEM to DECODEMi to identify such CCIs, validated in single-cell data. Our findings highlight the importance of active pre-treatment immune infiltration for chemotherapy success. The tools developed here are made publicly available and are applicable for studying the role of the TME in mediating response from readily available bulk tumor expression in a wide range of cancer treatments and indications.

Bioengineered human colon organoids with in vivo-like cellular complexity and function

Organoids and organs-on-a-chip have emerged as powerful tools for modeling human gut physiology and disease invitro. Although physiologically relevant, these systems often lack the environmental milieu, spatial organization, cell type diversity, and maturity necessary for mimicking human intestinal mucosa. To instead generate models closely resembling invivo tissue, we herein integrated organoid and organ-on-a-chip technology to develop an advanced human organoid model, called "mini-colons." By employing an asymmetric stimulation with growth factors, we greatly enhanced tissue longevity and replicated invivo-like diversity and patterning of proliferative and differentiated cell types. Mini-colons contain abundant mucus-producing goblet cells and, signifying mini-colon maturation, single-cell RNA sequencing reveals emerging mature and functional colonocytes. This methodology is expanded to generate microtissues from the small intestine and incorporate additional microenvironmental components. Finally, our bioengineered organoids provide a precise platform to systematically study human gut physiology and pathology, and a reliable preclinical model for drug safety assessment.

CAraCAl: CAMML with the integration of chromatin accessibility

BackgroundA vital step in analyzing single-cell data is ascertaining which cell types are present in a dataset, and at what abundance. In many diseases, the proportions of varying cell types can have important implications for health and prognosis. Most approaches for cell type annotation have centered around cell typing for single-cell RNA-sequencing (scRNA-seq) and have had promising success. However, reliable methods are lacking for many other single-cell modalities such as single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), which quantifies the extent to which genes of interest in each cell are epigenetically “open” for expression.ResultsTo leverage the informative potential of scATAC-seq data, we developed CAMML with the integration of chromatin accessibility (CAraCAl), a bioinformatic method that performs cell typing on scATAC-seq data. CAraCAl performs cell typing by scoring each cell for its enrichment of cell type-specific gene sets. These gene sets are composed of the most upregulated or downregulated genes present in each cell type according to projected gene activity.ConclusionsWe found that CAraCAl does not improve performance beyond CAMML when scRNA-seq is present, but if only scATAC-seq is available, CAraCAl performs cell typing relatively successfully. As such, we also discuss best practices for cell typing and the strengths and weaknesses of various cell annotation options.

Systemic and local regulation of hematopoietic homeostasis in health and disease.

Hematopoietic stem cells (HSCs) generate all blood cell lineages responsible for tissue oxygenation, life-long hematopoietic homeostasis and immune protection. In adulthood, HSCs primarily reside in the bone marrow (BM) microenvironment, consisting of diverse cell types that constitute the stem cell 'niche'. The adaptability of the hematopoietic system is required to respond to the needs of the host, whether to maintain normal physiology or during periods of physical, psychosocial or environmental stress. Hematopoietic homeostasis is achieved by intricate coordination of systemic and local factors that orchestrate the function of HSCs throughout life. However, homeostasis is not a static process; it modulates HSC and progenitor activity in response to circadian rhythms coordinated by the central and peripheral nervous systems, inflammatory cues, metabolites and pathologic conditions. Here, we review local and systemic factors that impact hematopoiesis, focusing on the implications of aging, stress and cardiovascular disease.

Parvalbumin-expressing basal forebrain neurons mediate learning from negative experience

Parvalbumin (PV)-expressing GABAergic neurons of the basal forebrain (BFPVNs) were proposed to serve as a rapid and transient arousal system, yet their exact role in awake behaviors remains unclear. We performed bulk calcium measurements and electrophysiology with optogenetic tagging from the horizontal limb of the diagonal band of Broca (HDB) while male mice were performing an associative learning task. BFPVNs responded with a distinctive, phasic activation to punishment, but showed slower and delayed responses to reward and outcome-predicting stimuli. Optogenetic inhibition during punishment impaired the formation of cue-outcome associations, suggesting a causal role of BFPVNs in associative learning. BFPVNs received strong inputs from the hypothalamus, the septal complex and the median raphe region, while they synapsed on diverse cell types in key limbic structures, where they broadcasted information about aversive stimuli. We propose that the arousing effect of BFPVNs is recruited by aversive stimuli to serve crucial associative learning functions.

PHusion - a robust and versatile toolset for automated detection and analysis of exocytosis.

Exocytosis is a fundamental process used by eukaryotes to regulate the composition of the plasma membrane and facilitate cell-cell communication. To investigate exocytosis in neuronal morphogenesis, previously we developed computational tools with a graphical user interface to enable the automatic detection and analysis of exocytic events from fluorescence timelapse images. Although these tools were useful, we found the code was brittle and not easily adapted to different experimental conditions. Here, we developed and validated a robust and versatile toolkit, named pHusion, for the analysis of exocytosis, written in ImageTank, a graphical programming language that combines image visualization and numerical methods. We tested pHusion using a variety of imaging modalities and pH-sensitive fluorophores, diverse cell types and various exocytic markers, to generate a flexible and intuitive package. Using this system, we show that VAMP3-mediated exocytosis occurs 30-times more frequently in melanoma cells compared with primary oligodendrocytes, that VAMP2-mediated fusion events in mature rat hippocampal neurons are longer lasting than those in immature murine cortical neurons, and that exocytic events are clustered in space yet random in time in developing cortical neurons.

Recent advances in understanding the molecular basis of infantile haemangioma development.

Infantile haemangioma (IH) - the most common vascular tumour of infancy - is comprised of diverse cell types, including endothelial cells, pericytes, fibroblasts and immune cells. IH is characterized by rapid proliferation followed by slow involution over 1-10 years. Most lesions regress spontaneously, but up to 10% can be disfiguring, with complications that require further medical treatment. Recent research has revealed the biological characteristics of IH, highlighting the involvement of angiogenesis and vasculogenesis during tumour formation. Gene expression profiling has provided vital insights into the underlying biological processes, with some of the key IH-related pathways identified, including vascular endothelial growth factor, the renin-angiotensin-aldosterone system, hypoxia-inducible factor 1α, Notch, platelet-derived growth factor, phosphoinositide 3-kinase/Akt/mammalian target of rapamycin, Janus kinase/signal transducers and activators of transcription, fibroblast growth factor, peroxisome proliferator-activated receptor-γ and insulin-like growth factor. Further evidence suggests extracellular matrix factors and hormone receptors regulate IH progression. In this review, we explore the molecular mechanisms involved in the proliferating, plateau and involuting phases of IH, identifying differentially expressed genes, targeted proteins and key signalling pathways. This knowledge will increase the broader understanding of vascular development, tissue remodelling and angiogenesis.

Large-scale foundation model on single-cell transcriptomics.

Large pretrained models have become foundation models leading to breakthroughs in natural language processing and related fields. Developing foundation models for deciphering the 'languages' of cells and facilitating biomedical research is promising yet challenging. Here we developed a large pretrained model scFoundation, also named 'xTrimoscFoundationα', with 100 million parameters covering about 20,000 genes, pretrained on over 50 million human single-cell transcriptomic profiles. scFoundation is a large-scale model in terms of the size of trainable parameters, dimensionality of genes and volume of training data. Its asymmetric transformer-like architecture and pretraining task design empower effectively capturing complex context relations among genes in a variety of cell types and states. Experiments showed its merit as a foundation model that achieved state-of-the-art performances in a diverse array of single-cell analysis tasks such as gene expression enhancement, tissue drug response prediction, single-cell drug response classification, single-cell perturbation prediction, cell type annotation and gene module inference.

Scanorama: integrating large and diverse single-cell transcriptomic datasets.

Merging diverse single-cell RNA sequencing (scRNA-seq) data from numerous experiments, laboratories and technologies can uncover important biological insights. Nonetheless, integrating scRNA-seq data encounters special challenges when the datasets are composed of diverse cell type compositions. Scanorama offers a robust solution for improving the quality and interpretation of heterogeneous scRNA-seq data by effectively merging information from diverse sources. Scanorama is designed to address the technical variation introduced by differences in sample preparation, sequencing depth and experimental batches that can confound the analysis of multiple scRNA-seq datasets. Here we provide a detailed protocol for using Scanorama within a Scanpy-based single-cell analysis workflow coupled with Google Colaboratory, a cloud-based free Jupyter notebook environment service. The protocol involves Scanorama integration, a process that typically spans 0.5-3 h. Scanorama integration requires a basic understanding of cellular biology, transcriptomic technologies and bioinformatics. Our protocol and new Scanorama-Colaboratory resource should make scRNA-seq integration more widely accessible to researchers.

Injury distance limits the transcriptional response to spinal injury.

The ability of neurons to sense and respond to damage is fundamental to homeostasis and nervous system repair. For some cell types, notably dorsal root ganglia (DRG) and retinal ganglion cells (RGCs), extensive profiling has revealed a large transcriptional response to axon injury that determines survival and regenerative outcomes. In contrast, the injury response of most supraspinal cell types, whose limited regeneration constrains recovery from spinal injury, is mostly unknown. Here we employed single-nuclei sequencing in mice to profile the transcriptional responses of diverse supraspinal cell types to spinal injury. Surprisingly, thoracic spinal injury triggered only modest changes in gene expression across all populations, including corticospinal tract (CST) neurons. Moreover, CST neurons also responded minimally to cervical injury but much more strongly to intracortical axotomy, including upregulation of numerous regeneration and apoptosis-related transcripts shared with injured DRG and RGC neurons. Thus, the muted response of CST neuron to spinal injury is linked to the injury's distal location, rather than intrinsic cellular characteristics. More broadly, these findings indicate that a central challenge for enhancing regeneration after a spinal injury is the limited sensing of distant injuries and the subsequent modest baseline neuronal response.

De novo prediction of functional effects of genetic variants from DNA sequences based on context-specific molecular information

Deciphering the functional effects of noncoding genetic variants stands as a fundamental challenge in human genetics. Traditional approaches, such as Genome-Wide Association Studies (GWAS), Transcriptome-Wide Association Studies (TWAS), and Quantitative Trait Loci (QTL) studies, are constrained by obscured the underlying molecular-level mechanisms, making it challenging to unravel the genetic basis of complex traits. The advent of Next-Generation Sequencing (NGS) technologies has enabled context-specific genome-wide measurements, encompassing gene expression, chromatin accessibility, epigenetic marks, and transcription factor binding sites, to be obtained across diverse cell types and tissues, paving the way for decoding genetic variation effects directly from DNA sequences only. The de novo predictions of functional effects are pivotal for enhancing our comprehension of transcriptional regulation and its disruptions caused by the plethora of noncoding genetic variants linked to human diseases and traits. This review provides a systematic overview of the state-of-the-art models and algorithms for genetic variant effect predictions, including traditional sequence-based models, Deep Learning models, and the cutting-edge Foundation Models. It delves into the ongoing challenges and prospective directions, presenting an in-depth perspective on contemporary developments in this domain.