The heterogeneity of erythroid cells: insight at the single-cell transcriptome level.

Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.

Endothelial Heterogeneity in the Response to Autophagy Drives Small Vessel Muscularization in Pulmonary Hypertension.

BACKGROUND: Endothelial cell (EC) apoptosis and proliferation of apoptosis-resistant cells is a hallmark of pulmonary hypertension (PH). Yet, why some ECs die and others proliferate and how this contributes to vascular remodeling is unclear. We hypothesized that this differential response may: (1) relate to different EC subsets, namely pulmonary artery (PAECs) versus microvascular ECs (MVECs); (2) be attributable to autophagic activation in both EC subtypes; and (3) cause replacement of MVECs by PAECs with subsequent distal vessel muscularization. METHODS: EC subset responses to chronic hypoxia were assessed by single-cell RNA sequencing of murine lungs. Proliferative versus apoptotic responses, activation, and role of autophagy were assessed in human and rat PAECs and MVECs, and in precision-cut lung slices of wild-type mice or mice with endothelial deficiency in the autophagy gene Atg7 (Atg7EN-KO). Abundance of PAECs versus MVECs in precapillary microvessels was assessed in lung tissue from patients with PH and animal models on the basis of structural or surface markers. RESULTS: In vitro and in vivo, PAECs proliferated in response to hypoxia, whereas MVECs underwent apoptosis. Single-cell RNA sequencing analyses support these findings in that hypoxia induced an antiapoptotic, proliferative phenotype in arterial ECs, whereas capillary ECs showed a propensity for cell death. These distinct responses were prevented in hypoxic Atg7EN-KO mice or after ATG7 silencing, yet replicated by autophagy stimulation. In lung tissue from mice, rats, or patients with PH, the abundance of PAECs in precapillary arterioles was increased, and that of MVECs reduced relative to controls, indicating replacement of microvascular by macrovascular ECs. EC replacement was prevented by genetic or pharmacological inhibition of autophagy in vivo. Conditioned medium from hypoxic PAECs yet not MVECs promoted pulmonary artery smooth muscle cell proliferation and migration in a platelet-derived growth factor-dependent manner. Autophagy inhibition attenuated PH development and distal vessel muscularization in preclinical models. CONCLUSIONS: Autophagic activation by hypoxia induces in parallel PAEC proliferation and MVEC apoptosis. These differential responses cause a progressive replacement of MVECs by PAECs in precapillary pulmonary arterioles, thus providing a macrovascular context that in turn promotes pulmonary artery smooth muscle cell proliferation and migration, ultimately driving distal vessel muscularization and the development of PH.

Macrophages preserve endothelial cell specialization in the adrenal gland to modulate aldosterone secretion and blood pressure.

Macrophages play crucial roles in organ-specific functions and homeostasis. In the adrenal gland, macrophages closely associate with sinusoidal capillaries in the aldosterone-producing zona glomerulosa. We demonstrate that macrophages preserve capillary specialization and modulate aldosterone secretion. Using macrophage-specific deletion of VEGF-A, single-cell transcriptomics, and functional phenotyping, we found that the loss of VEGF-A depletes PLVAP+ fenestrated endothelial cells in the zona glomerulosa, leading to increased basement membrane collagen IV deposition and subendothelial fibrosis. This results in increased aldosterone secretion, called "haptosecretagogue" signaling. Human aldosterone-producing adenomas also show capillary rarefaction and basement membrane thickening. Mice with myeloid cell-specific VEGF-A deletion exhibit elevated serum aldosterone, hypokalemia, and hypertension, mimicking primary aldosteronism. These findings underscore macrophage-to-endothelial cell signaling as essential for endothelial cell specialization, adrenal gland function, and blood pressure regulation, with broader implications for other endocrine organs.

A review concerning the breast cancer-related tumour microenvironment.

Breast cancer (BC) is currently the most common malignant tumour in women and one of the leading causes of their death around the world. New and increasingly personalised diagnostic and therapeutic tools have been introduced over the last few decades, along with significant advances regarding the study and knowledge related to BC. The tumour microenvironment (TME) refers to the tumour cell-associated cellular and molecular environment which can influence conditions affecting tumour development and progression. The TME is composed of immune cells, stromal cells, extracellular matrix (ECM) and signalling molecules secreted by these different cell types. Ever deeper understanding of TME composition changes during tumour development and progression will enable new and more innovative therapeutic strategies to become developed for targeting tumours during specific stages of its evolution. This review summarises the role of BC-related TME components and their influence on tumour progression and the development of resistance to therapy. In addition, an account on the modifications in BC-related TME components associated with therapy is given, and the completed or ongoing clinical trials related to this topic are presented.

10× single-cell sequencing revealed cellular composition heterogeneity in cardiac myxoma with malignant glandular properties.

Cardiac myxoma is the most common primary cardiac tumor in adults. The histogenesis and cellular composition of myxoma are still unclear. This study aims to reveal the role of myxoma cell components and their gene expression in tumor development. We obtained single living cells by enzymatic digestion of tissues from 4 cases of surgically resected cardiac myxoma. Of course, there was 1 case of glandular myxoma and 3 cases of nonglandular myxoma. Then, 10× single-cell sequencing was performed. We identified 12 types and 11 types of cell populations in glandular myxoma and nonglandular myxoma, respectively. Heterogeneous epithelial cells are the main components of glandular myxoma. The similarities and differences in T cells in both glandular and nonglandular myxoma were analyzed by KEGG and GO. The most important finding was that there was active communication between T cells and epithelial cells. These results clarify the possible tissue occurrence and heterogeneity of cardiac myxoma and provide a theoretical basis and guidance for clinical diagnosis and treatment.

A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations.

Rapid advancements in high-throughput single-cell RNA-seq (scRNA-seq) technologies and experimental protocols have led to the generation of vast amounts of genomic data that populates several online databases and repositories. Here, we systematically examined large-scale scRNA-seq databases, categorizing them based on their scope and purpose such as general, tissue-specific databases, disease-specific databases, cancer-focused databases, and cell type-focused databases. Next, we discuss the technical and methodological challenges associated with curating large-scale scRNA-seq databases, along with current computational solutions. We argue that understanding scRNA-seq databases, including their limitations and assumptions, is crucial for effectively utilizing this data to make robust discoveries and identify novel biological insights. Furthermore, we propose that bridging the gap between computational and wet lab scientists through user-friendly web-based platforms is needed for democratizing access to single-cell data. These platforms would facilitate interdisciplinary research, enabling researchers from various disciplines to collaborate effectively. This review underscores the importance of leveraging computational approaches to unravel the complexities of single-cell data and offers a promising direction for future research in the field.

Pancreatic ß-Cell Identity Change through the Lens of Single-Cell Omics Research.

The main hallmark in the development of both type 1 and type 2 diabetes is a decline in functional ß-cell mass. This decline is predominantly attributed to ß-cell death, although recent findings suggest that the loss of ß-cell identity may also contribute to ß-cell dysfunction. This phenomenon is characterized by a reduced expression of key markers associated with ß-cell identity. This review delves into the insights gained from single-cell omics research specifically focused on ß-cell identity. It highlights how single-cell omics based studies have uncovered an unexpected level of heterogeneity among ß-cells and have facilitated the identification of distinct ß-cell subpopulations through the discovery of cell surface markers, transcriptional regulators, the upregulation of stress-related genes, and alterations in chromatin activity. Furthermore, specific subsets of ß-cells have been identified in diabetes, such as displaying an immature, dedifferentiated gene signature, expressing significantly lower insulin mRNA levels, and expressing increased ß-cell precursor markers. Additionally, single-cell omics has increased insight into the detrimental effects of diabetes-associated conditions, including endoplasmic reticulum stress, oxidative stress, and inflammation, on ß-cell identity. Lastly, this review outlines the factors that may influence the identification of ß-cell subpopulations when designing and performing a single-cell omics experiment.

Cell Heterogeneity Analysis Revealed the Key Role of Fibroblasts in the Magnum Regression of Ducks.

Duck egg production, like that of laying hens, follows a typical low-peak-low cycle, reflecting the dynamics of the reproductive system. Post-peak, some ducks undergo a cessation of egg laying, indicative of a regression process in the oviduct. Notably, the magnum, being the longest segment of the oviduct, plays a crucial role in protein secretion. Despite its significance, few studies have investigated the molecular mechanisms underlying oviduct regression in ducks that have ceased laying eggs. In this study, we conducted single-cell transcriptome sequencing on the magnum tissue of Shaoxing ducks at 467 days of age, utilizing the 10× Genomics platform. This approach allowed us to generate a detailed magnum transcriptome map of both egg-laying and ceased-laying ducks. We collected transcriptome data from 13,708 individual cells, which were then subjected to computational analysis, resulting in the identification of 27 distinct cell clusters. Marker genes were subsequently employed to categorize these clusters into specific cell types. Our analysis revealed notable heterogeneity in magnum cells between the egg-laying and ceased-laying ducks, primarily characterized by variations in cells involved in protein secretion and extracellular matrix (ECM)-producing fibroblasts. Specifically, cells engaged in protein secretion were predominantly observed in the egg-laying ducks, indicative of their role in functional albumen deposition within the magnum, a phenomenon not observed in the ceased-laying ducks. Moreover, the proportion of THY1+ cells within the ECM-producing fibroblasts was found to be significantly higher in the egg-laying ducks (59%) compared to the ceased-laying ducks (24%). Similarly, TIMP4+ fibroblasts constituted a greater proportion of the ECM-producing fibroblasts in the egg-laying ducks (83%) compared to the ceased-laying ducks (58%). These findings suggest a potential correlation between the expression of THY1 and TIMP4 in ECM-producing fibroblasts and oviduct activity during functional reproduction. Our study provides valuable single-cell insights that warrant further investigation into the biological implications of fibroblast subsets in the degeneration of the reproductive tract. Moreover, these insights hold promise for enhancing the production efficiency of laying ducks.

From stem cells to pancreatic ß-cells: strategies, applications, and potential treatments for diabetes.

Loss and functional failure of pancreatic ß-cells results in disruption of glucose homeostasis and progression of diabetes. Although whole pancreas or pancreatic islet transplantation serves as a promising approach for ß-cell replenishment and diabetes therapy, the severe scarcity of donor islets makes it unattainable for most diabetic patients. Stem cells, particularly induced pluripotent stem cells (iPSCs), are promising for the treatment of diabetes owing to their self-renewal capacity and ability to differentiate into functional ß-cells. In this review, we first introduce the development of functional ß-cells and their heterogeneity and then turn to highlight recent advances in the generation of ß-cells from stem cells and their potential applications in disease modeling, drug discovery and clinical therapy. Finally, we have discussed the current challenges in developing stem cell-based therapeutic strategies for improving the treatment of diabetes. Although some significant technical hurdles remain, stem cells offer great hope for patients with diabetes and will certainly transform future clinical practice.

Unveiling the functional heterogeneity of cytokine-primed human umbilical cord mesenchymal stem cells through single-cell RNA sequencing.

BACKGROUND: Mesenchymal stem cells (MSCs) hold immense promise for use in immunomodulation and regenerative medicine. However, their inherent heterogeneity makes it difficult to achieve optimal therapeutic outcomes for a specific clinical disease. Primed MSCs containing a certain cytokine can enhance their particular functions, thereby increasing their therapeutic potential for related diseases. Therefore, understanding the characteristic changes and underlying mechanisms of MSCs primed by various cytokines is highly important. RESULTS: In this study, we aimed to reveal the cellular heterogeneity, functional subpopulations, and molecular mechanisms of MSCs primed with IFN-γ, TNF-α, IL-4, IL-6, IL-15, and IL-17 using single-cell RNA sequencing (scRNA-seq). Our results demonstrated that cytokine priming minimized the heterogeneity of the MSC transcriptome, while the expression of MSC surface markers exhibited only slight changes. Notably, compared to IL-6, IL-15, and IL-17; IFN-γ, TNF-α, and IL-4 priming, which stimulated a significantly greater number of differentially expressed genes (DEGs). Functional analysis, which included Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, indicated that IFN-γ, TNF-α, and IL-4-primed hUC-MSCs are involved in interferon-mediated immune-related processes, leukocyte migration, chemotaxis potential, and extracellular matrix and cell adhesion, respectively. Moreover, an investigation of various biological function scores demonstrated that IFN-γ-primed hUC-MSCs exhibit strong immunomodulatory ability, TNF-α-primed hUC-MSCs exhibit high chemotaxis potential, and IL-4-primed hUC-MSCs express elevated amounts of collagen. Finally, we observed that cytokine priming alters the distribution of functional subpopulations of MSCs, and these subpopulations exhibit various potential biological functions. Taken together, our study revealed the distinct regulatory effects of cytokine priming on MSC heterogeneity, biological function, and functional subpopulations at the single-cell level. CONCLUSIONS: These findings contribute to a comprehensive understanding of the inflammatory priming of MSCs, paving the way for their precise treatment in clinical applications.

Revealing Early Spatial Patterns of Cellular Responsivity in Fiber-Reinforced Microenvironments.

Fiber-reinforcement approaches have been used to replace aligned tissues with engineered constructs after injury or surgical resection, strengthening soft biomaterial scaffolds and replicating anisotropic, load-bearing properties. However, most studies focus on the macroscale aspects of these scaffolds, rarely considering the cell-biomaterial interactions that govern remodeling and extracellular matrix organization toward aligned neo-tissues. As initial cell-biomaterial responses within fiber-reinforced microenvironments likely influence the long-term efficacy of repair and regeneration strategies, here we elucidate the roles of spatial orientation, substrate stiffness, and matrix remodeling on early cell-fiber interactions. Bovine mesenchymal stromal cells (MSCs) were cultured in soft fibrin gels reinforced with a stiff 100 µm polyglycolide-co-caprolactone fiber. Gel stiffness and remodeling capacity were modulated by fibrinogen concentration and aprotinin treatment, respectively. MSCs were imaged at 3 days and evaluated for morphology, mechanoresponsiveness (nuclear Yes-associated protein [YAP] localization), and spatial features including distance and angle deviation from fiber. Within these constructs, morphological conformity decreased as a function of distance from fiber. However, these correlations were weak (R2 = 0.01043 for conformity and R2 = 0.05542 for nuclear YAP localization), illustrating cellular heterogeneity within fiber-enforced microenvironments. To better assess cell-fiber interactions, we applied machine-learning strategies to our heterogeneous dataset of cell-shape and mechanoresponsive parameters. Principal component analysis (PCA) was used to project 23 input parameters (not including distance) onto 5 principal components (PCs), followed by agglomerative hierarchical clustering to classify cells into 3 groups. These clusters exhibited distinct levels of morpho-mechanoresponse (combination of morphological conformity and YAP signaling) and were classified as high response (HR), medium response (MR), and low response (LR) clusters. Cluster distribution varied spatially, with most cells (61%) closest to the fiber (0-75 µm) belonging to the HR cluster, and most cells (55%) furthest from the fiber (225-300 µm) belonging to the LR cluster. Modulation of gel stiffness and fibrin remodeling showed differential effects for HR cells, with stiffness influencing the level of mechanoresponse and remodeling capacity influencing the location of responding cells. Together, these novel findings demonstrate early trends in cellular patterning of the fiber-reinforced microenvironment, showing how spatial orientation, substrate biophysical properties, and matrix remodeling may guide the amplitude and localization of cellular mechanoresponses. These trends may guide approaches to optimize the design of microscale scaffold architecture and substrate properties for enhancing organized tissue assembly at the macroscale.

Unveiling cell subpopulations in T1D mouse islets using single-cell RNA sequencing.

Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells by immune cells. The interactions among cells within the islets may be closely linked to the pathogenesis of T1D. In this study, we used single-cell RNA sequencing (scRNA-Seq) to analyze the cellular heterogeneity within the islets of a T1D mouse model. We established a T1D mouse model induced by streptozotocin and identified cell subpopulations using scRNA-Seq technology. Our results revealed 11 major cell types in the pancreatic islets of T1D mice, with heterogeneity observed in the alpha and beta cell subgroups, which may play a crucial role in the progression of T1D. Flow cytometry further confirmed a mature alpha and beta cell reduction in T1D mice. Overall, our scRNA-Seq analysis provided insights into the cellular heterogeneity of T1D islet tissue and highlighted the potential importance of alpha and beta cells in developing T1D.NEW & NOTEWORTHY In this study, we created a comprehensive single-cell atlas of pancreatic islets in a T1D mouse model using scRNA-Seq and identified 11 major cell types in the islets, highlighting the role of alpha and beta cells in T1D. This study revealed a significant reduction in the maturity alpha and beta cells in T1D mice through flow cytometry. It also demonstrated the heterogeneity of alpha and beta cells, potentially crucial for T1D progression. Overall, our scRNA-Seq analysis provided new insights for understanding and treating T1D by studying cell subtype changes and functions.

Single-cell transcriptomics reveal heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions.

Environmental cues, from biotic or abiotic origin, are major factors influencing plant growth and productivity. Interactions with biotic (e.g. symbionts and pathogens) and abiotic (e.g. changes in temperature, water or nutrient availability) factors trigger signaling and downstream transcriptome changes in plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, the heterogeneity of the responses, caused by the cellular complexity of organs, might be masked by homogenizing tissues. Thus, whether different cell types respond equally to environmental fluctuations, or whether subsets of the responses are cell-type specific, are long-lasting questions in plant biology. The recent break-through of single-cell transcriptomics in plant research offers an unprecedented view on cellular responses under changing environmental conditions. In this review, we discuss the contributions of single-cell transcriptomics towards the understanding of cell-type specific plant responses to biotic and abiotic environmental interactions. Besides major biological findings, we present some technical challenges coupled to single-cell studies of plant-environment interactions, proposing possible solutions and exciting paths for future research.

A high-resolution view of the heterogeneous aging endothelium.

Vascular endothelial cell (EC) aging has a strong impact on tissue perfusion and overall cardiovascular health. While studies confined to the investigation of aging-associated vascular readouts in one or a few tissues have already drastically expanded our understanding of EC aging, single-cell omics and other high-resolution profiling technologies have started to illuminate the intricate molecular changes underlying endothelial aging across diverse tissues and vascular beds at scale. In this review, we provide an overview of recent insights into the heterogeneous adaptations of the aging vascular endothelium. We address critical questions regarding tissue-specific and universal responses of the endothelium to the aging process, EC turnover dynamics throughout lifespan, and the differential susceptibility of ECs to acquiring aging-associated traits. In doing so, we underscore the transformative potential of single-cell approaches in advancing our comprehension of endothelial aging, essential to foster the development of future innovative therapeutic strategies for aging-associated vascular conditions.

A single-cell transcriptome atlas of Lueyang black-bone chicken skin.

As the largest organ of the body, the skin participates in various physiological activities, such as barrier function, sensory function, and temperature regulation, thereby maintaining the balance between the body and the natural environment. To date, compositional and transcriptional profiles in chicken skin cells have not been reported. Here, we report detailed transcriptome analyses of cell populations present in the skin of a black-feather chicken and a white-feather chicken using single-cell RNA sequencing (scRNA-seq). By analyzing cluster-specific gene expression profiles, we identified 12 cell clusters, and their corresponding cell types were also characterized. Subsequently, we characterized the subpopulations of keratinocytes, myocytes, mesenchymal cells, fibroblasts, and melanocytes. It is worth noting that we have identified a subpopulation of keratinocytes involved in pigment granule capture and a subpopulation of melanocytes involved in pigment granule deposition, both of which have a higher cell abundance in black-feather chicken compared to white-feather chicken. Meanwhile, we also compared the cellular heterogeneity features of Lueyang black-bone chicken skin with different feather colors. In addition, we also screened out 12 genes those could be potential markers of melanocytes. Finally, we validated the specific expression of SGK1, WNT5A, CTSC, TYR, and LAPTM5 in black-feather chicken, which may be the key candidate genes determining the feather color differentiation of Lueyang black-bone chicken. In summary, this study first revealed the transcriptome characteristics of chicken skin cells via scRNA-seq technology. These datasets provide valuable information for the study of avian skin characteristics and have important implications for future poultry breeding.

Investigating Heterogeneous Cell-Cycle Progression Using Single-Cell Imaging Approaches.

Investigating cell-cycle progression has been challenging due to the complex interconnectivity of regulatory processes and inherent cell-to-cell heterogeneity, which often require synchronization procedures. However, recent advancements in cell-cycle sensors and single-cell imaging techniques have turned this heterogeneity into an advantage for investigating the molecular mechanisms underlying diverse responses. This has led to significant progress in our understanding of cell-cycle regulation. In this paper, we present a comprehensive live single-cell imaging workflow that leverages cutting-edge live-cell sensors. These advanced single-cell imaging procedures provide promising opportunities for elucidating the molecular mechanisms underpinnings of heterogeneous responses in cell-cycle progression.

Density physics-informed neural networks reveal sources of cell heterogeneity in signal transduction.

The transduction time between signal initiation and final response provides valuable information on the underlying signaling pathway, including its speed and precision. Furthermore, multi-modality in a transduction-time distribution indicates that the response is regulated by multiple pathways with different transduction speeds. Here, we developed a method called density physics-informed neural networks (Density-PINNs) to infer the transduction-time distribution from measurable final stress response time traces. We applied Density-PINNs to single-cell gene expression data from sixteen promoters regulated by unknown pathways in response to antibiotic stresses. We found that promoters with slower signaling initiation and transduction exhibit larger cell-to-cell heterogeneity in response intensity. However, this heterogeneity was greatly reduced when the response was regulated by slow and fast pathways together. This suggests a strategy for identifying effective signaling pathways for consistent cellular responses to disease treatments. Density-PINNs can also be applied to understand other time delay systems, including infectious diseases.

Multiplex Profiling of Biomarker and Drug Uptake in Single Cells Using Microfluidic Flow Cytometry and Mass Spectrometry.

To perform multiplex profiling of single cells and eliminate the risk of potential sample loss caused by centrifugation, we developed a microfluidic flow cytometry and mass spectrometry system (µCytoMS) to evaluate the drug uptake and induced protein expression at the single cell level. It involves a microfluidic chip for the alignment and purification of single cells followed by detection with laser-induced fluorescence (LIF) and inductively coupled plasma mass spectrometry (ICP-MS). Biofunctionalized nanoprobes (BioNPs), conjugating ∼3000 6-FAM-Sgc8 aptamers on a single gold nanoparticle (AuNP) (Kd = 0.23 nM), were engineered to selectively bind with protein tyrosine kinase 7 (PTK7) on target cells. PTK7 expression induced by oxaliplatin (OXA) uptake was assayed with LIF, while ICP-MS measurement of 195Pt revealed OXA uptake of the drug in individual cells, which provided further in-depth information about the drug in relation to PTK7 expression. At an ultralow flow of ∼0.043 dyn/cm2 (20 µL/min), the chip facilitates the extremely fast focusing of BioNPs labeled single cells without the need for centrifugal purification. It ensures multiplex profiling of single cells at a throughput speed of 500 cells/min as compared to 40 cells/min in previous studies. Using a machine learning algorithm to initially profile drug uptake and marker expression in tumor cell lines, µCytoMS was able to perform in situ profiling of the PTK7 response to the OXA at single-cell resolution for tests done on clinical samples from 10 breast cancer patients. It offers great potential for multiplex single-cell phenotypic analysis and clinical diagnosis.

Hierarchical Dendritic Photonic Crystal Beads for Efficient Isolation and Proteomic Analysis of Multiple Cell Types.

Cell types with different morphology, and function collaborate to maintain organ function. As such, analyzing proteomic differences and connections between different types of cells forms the foundation for establishing functional connectomes and developing in vitro organoid simulation experiments. However, the efficiency of cell type isolation from organs is limited by time, equipment, and cost. Here, hierarchical dendritic photonic crystal beads (HDPCBs) featuring high-density functional groups via the self-assembly of dendritic mesoporous structure SiO2 nanoparticles (DM-SiO2) and grafting dendrimers onto the surface of dendritic mesoporous photonic crystal beads (DMPCBs) is developed. This platform integrates multitype cell separation with in situ protein cleavage processes. Efficient simultaneous isolation of Kupffer cells and Liver Sinusoidal Endothelial cells (LSECs) from liver, with high specificity and convenient operation in a short separation time are demonstrated. The results reveal 2832 and 3442 unique proteins identified in Kupffer cells and LSECs using only 50 HDPCBs, respectively. 764 and 629 over-expressed proteins associated with the function of Kupffer cells and LSECs are found, respectively. The work offers a new method for efficiently isolating multiple cell types from tissues and downstream proteomic analysis, ultimately facilitating the identification of primary cell compositions and functions.

Immunoblot Analysis from Single Cells Using Milo™ Single-Cell Western Platform.

In this new era of precision medicine, characterization of single-cell subpopulations to better understand disease etiology is paramount. It is thus an opportune time to explore techniques that allow molecular analysis of single cells and to better understand the basis of pathogenesis of diseases like cancer. Single-cell western blotting is one such method that allows analysis of single cells at the protein level. In contrast to traditional western blotting, which relies heavily on bulk analysis of lysates generated from tissues and is often indicative of the population average, this technique allows analysis of lysates from single-cell subpopulations thereby providing a glimpse into cell heterogeneity. The method entails the use of a chip containing 30 µm thick photoactivated polyacrylamide gel spotted with nearly 6400 microwells. Single cells loaded on the chip are captured in the microwells by passive gravity and are then lysed and electrophoresed using the MILO™ single-cell western platform. This method forgoes the use of transfer of proteins on a PVDF and a nitrocellulose membrane, as performed in traditional western blotting, and all other steps including probing of primary and fluorescent secondary antibodies against the protein of interest are performed directly on the chip. The proteins of interest can then be visualized by scanning a chip with the use of a microarray scanner. The entire procedure can be performed in as less as 4-6 h, and thus this method provides several advantages over traditional western blotting.