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PubMed2026

Single-Cell Proteomics Reveals Proteome Remodeling and Cellular Heterogeneity During NGF-Induced PC12 Neuronal Differentiation.

Single-cell proteomics enables direct measurement of cellular heterogeneity during dynamic biological processes, but its application to fragile and highly adherent neuronal models remains challenging. Here, we developed and applied an optimized single-cell proteomics workflow to characterize proteome remodeling during nerve growth factor (NGF)-induced differentiation of PC12 cells. To enable reliable single-cell analysis, we implemented gentle dissociation, antiaggregation strategies, and thermal inkjet-based cell dispensing, achieving high accuracy in single-cell isolation. Inclusion of n-dodecyl-β-d-maltoside (DDM) improved recovery of membrane-associated and low-solubility proteins. Coupled with LC-ion mobility-mass spectrometry, this workflow enabled quantification of 2,000-3,000 proteins per cell across the differentiation time course. Single-cell proteomic analysis revealed progressive and heterogeneous proteome remodeling during differentiation. While undifferentiated cells formed a relatively homogeneous population, later stages (Days 4-6) exhibited increased variability, including multimodal protein abundance distributions and separation into distinct subpopulations. Dimensionality reduction, clustering, and non-negative matrix factorization identified multiple coexisting proteomic states within the same time points, reflecting asynchronous differentiation trajectories. These subpopulations were characterized by coordinated differences in pathways related to intracellular trafficking, protein translation, cytoskeletal organization, and neuronal maturation. Comparison with bulk proteomics demonstrated that proteins associated with differentiated neuronal states, including those involved in neurite formation and structural remodeling, are underrepresented in population-averaged measurements but are enriched within specific single-cell subpopulations. Temporal and cluster-resolved analyses further revealed distinct protein expression trajectories, including early decreases in cell cycle and metabolic pathways and later increases in neuronal structural and regulatory proteins. Together, this study establishes an optimized workflow for single-cell proteomics of neuronal systems and demonstrates that NGF-induced PC12 differentiation proceeds through heterogeneous and divergent proteomic states that are not resolved by bulk analysis.

Animals↗
PubMed2025

Tribus: semi-automated discovery of cell identities and phenotypes from multiplexed imaging and proteomic data.

MOTIVATION: Multiplexed imaging and single-cell analysis are increasingly applied to investigate the tissue spatial ecosystems in cancer and other complex diseases. Accurate single-cell phenotyping based on marker combinations is a critical but challenging task due to (i) low reproducibility across experiments with manual thresholding, and, (ii) labor-intensive ground-truth expert annotation required for learning-based methods. RESULTS: We developed Tribus, an interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. We demonstrated that Tribus recovers fine-grained cell types, matching the gold standard annotations by human experts. Additionally, Tribus can target ambiguous populations and discover phenotypically distinct cell subtypes. Through benchmarking against three similar methods in four public datasets with ground truth labels, we show that Tribus outperforms other methods in accuracy and computational efficiency, reducing runtime by an order of magnitude. Finally, we demonstrate the performance of Tribus in rapid and precise cell phenotyping with two large in-house whole-slide imaging datasets. AVAILABILITY AND IMPLEMENTATION: Tribus is available at https://github.com/farkkilab/tribus as an open-source Python package.

Proteomics↗
PubMed2001

Cell sampling and analysis (SiCSA): metabolites measured at single cell resolution.

By using a fine oil-filled glass microcapillary mounted on a micromanipulator, the solutes of individual plant cells can be sampled. These samples can then be analysed using a range of physical and chemical methods. Hydrostatic pressure (cell pressure probe), osmotic pressure (picolitre osmometer), organic solutes (enzyme-linked fluorescence microscope spectrometry or capillary electrophoresis), inorganic solutes (X-ray microdroplet analysis or capillary electrophoresis), (14)C (mass spectrometry), proteins (microdroplet immunoblotting), and mRNA (rt PCR) have been measured. Collectively, the battery of techniques is called single cell sampling and analysis (SiCSA) and all of the techniques have relevance to the study of plant metabolism at the resolution of the individual cell. This review summarizes the techniques for SiCSA and presents examples of applications used in this laboratory, in particular those relating to cell metabolism.

Cells↗
PubMed2006

Recent advances in capillary electrophoretic analysis of individual cells.

Because variability exists within populations of cells, single-cell analysis has become increasingly important for probing complex cellular environments. Capillary electrophoresis (CE) is an excellent technique for identifying and quantifying the contents of single cells owing to its small volume requirements and fast, efficient separations with highly sensitive detection. Recent progress in both whole-cell and subcellular sampling has allowed researchers to study cellular function in the areas of neuroscience, oncology, enzymology, immunology, and gene expression.

Animals↗
PubMed2000

Expression profiling of single mammalian cells--small is beautiful.

Increasingly mRNA expression patterns established using a variety of molecular technologies such as cDNA microarrays, SAGE and cDNA display are being used to identify potential regulatory genes and as a means of providing valuable insights into the biological status of the starting sample. Until recently, the application of these techniques has been limited to mRNA isolated from millions or, at very best, several thousand cells thereby restricting the study of small samples and complex tissues. To overcome this limitation a variety of amplification approaches have been developed which are capable of broadly evaluating mRNA expression patterns in single cells. This review will describe approaches that have been employed to examine global gene expression patterns either in small numbers of cells or, wherever possible, in actual isolated single cells. The first half of the review will summarize the technical aspects of methods developed for single-cell analysis and the latter half of the review will describe the areas of biological research that have benefited from single-cell expression analysis.

Animals↗
PubMed2025

scACCorDiON: a clustering approach for explainable patient level cell-cell communication graph analysis.

MOTIVATION: Combining single-cell sequencing with ligand-receptor (LR) analysis paves the way for the characterization of cell communication events in complex tissues. In particular, directed weighted graphs naturally represent cell-cell communication events. However, current computational methods cannot yet analyze sample-specific cell-cell communication events, as measured in single-cell data produced in large patient cohorts. Cohort-based cell-cell communication analysis presents many challenges, such as the nonlinear nature of cell-cell communication and the high variability given by the patient-specific single-cell RNAseq datasets. RESULTS: Here, we present scACCorDiON (single-cell Analysis of Cell-Cell Communication in Disease clusters using Optimal transport in Directed Networks), an optimal transport algorithm exploring node distances on the Markov Chain as the ground metric between directed weighted graphs. Benchmarking indicates that scACCorDiON performs a better clustering of samples according to their disease status than competing methods that use undirected graphs. We provide a case study of pancreas adenocarcinoma, where scACCorDion detects a sub-cluster of disease samples associated with changes in the tumor microenvironment. Our study case corroborates that clusters provide a robust and explainable representation of cell-cell communication events and that the expression of detected LR pairs is predictive of pancreatic cancer survival. AVAILABILITY AND IMPLEMENTATION: The code of scACCorDiON is available at https://scaccordion.readthedocs.io/en/latest/. and https://doi.org/10.5281/zenodo.15267648. The survival analysis package can be found at https://github.com/CostaLab/scACCorDiON.su.

Humans↗
PubMed1995

Axogenesis in the embryonic brain of the grasshopper Schistocerca gregaria: an identified cell analysis of early brain development.

Axogenesis in the embryonic brain was studied at the single cell level in the grasshopper Schistocerca gregaria. A small set of individually identifiable pioneer neurons establishes a primary axon scaffold during early embryogenesis. At the beginning of scaffold formation, pioneering axons navigate along and between glial borders that surround clusters of proliferating neuroblasts. In each brain hemisphere, an axonal outgrowth cascade involving a series of pioneer neurons establishes a pathway from the optic ganglia to the brain midline. At the midline the primary preoral commissural interconnection in the embryonic brain is pioneered by a pair of midline-derived pioneer neurons. A second preoral commissural connection is pioneered by two pairs of pars intercerebralis pioneer neurons. Descending tracts are pioneered by the progeny of identified neuroblasts in the pars intercerebralis, deutocerebrum and tritocerebrum; the postoral tritocerebral commissure is pioneered by a pair of tritocerebral neurons. All of the pioneering brain neurons express the cell adhesion molecule fasciclin I during initial axon outgrowth and fasciculation. Once established, the primary axon scaffold of the brain is used for fasciculation by subsequently differentiating neurons and, by the 40% stage of embryogenesis, axonal projections that characterize the mature brain become evident. The single cell analysis of grasshopper brain development presented here sets the stage for manipulative cell biological experiments and provides the basis for comparative molecular genetic studies of embryonic brain development in Drosophila.

Animals↗
PubMed2025

Next-generation sequencing in breast cancer: current clinical applications and future directions.

INTRODUCTION: Breast cancer is a heterogeneous disease that claims 670,000 lives by 2022. Omic technologies, particularly next generation sequencing (NGS) offers promising avenues for precision medicine. American Society of Clinical Oncology (ASCO) outlines genomic testing's utility, emphasizing prognostic and diagnostic potential. OBJECTIVES: This review succinctly explores NGS's evolution and clinical applications of NGS in breast cancer, thereby guiding future research to enhance patient care. METHODS: Comprehensive literature searches were conducted using databases such as PubMed, Google Scholar, and ResearchGate, focusing on keywords including breast cancer, HER-2 low breast cancer, circulating tumour DNA, single-cell RNA sequencing, and next-generation sequencing. Peer-reviewed, high-quality articles published in English were selected for inclusion. RESULTS: Previous studies have explored the evolution of NGS technology and its clinical applications in breast cancer, including genomic and transcriptomic characterization, treatment guidance, and resistance prediction. Molecular profiling of challenging entities such as early-onset breast cancer and HER-2 low tumours was summarized, with key findings highlighted. This review also discusses emerging technologies, including circulating DNA and single-cell sequencing, as promising avenues for discovery. CONCLUSION: NGS has revealed the genomic and transcriptomic diversity of breast cancer, identifying actionable alterations associated with chemotherapy response and resistance to therapies such as trastuzumab, TKIs, and CDK4/6 inhibitors. Circulating tumour DNA (ctDNA) shows potential for diagnosis, prediction, prognosis, and monitoring, despite tumour heterogeneity. Single-cell analysis enables exploration of individual cell transcriptomes, though high costs and low throughput remain barriers to widespread adoption. HER2-low tumours continue to pose significant research challenges.

Humans↗
PubMed1983

Mass spectrometric analysis of drug-induced changes in Na+ and K+ contents of single bacterial cells.

Time-dependent changes in the intracellular Na+/K+ ratio of Escherichia coli, induced by the nitrofuran derivative HN32 [2,4-diamino-6-(5-nitrofuryl-2)-5-ethylpyrimidine], were measured by laser-induced mass spectrometry of single bacterial cells. The results show good agreement with data on viable cell and total cell counts, release of ATP and 14CO2 production demonstrating that the single cell analysis of intracellular sodium and potassium concentrations may supply reliable information on cell viability and, furthermore, offer additional information not available from established gross methods.

Escherichia coli↗
PubMed2004

Elemental and redox analysis of single bacterial cells by x-ray microbeam analysis.

High-energy x-ray fluorescence measurements were used to make elemental maps and qualitative chemical analyses of individual Pseudomonas fluorescens strain NCIMB 11764 cells. Marked differences between planktonic and adhered cells were seen in the morphology, elemental composition, and sensitivity to Cr(VI) of hydrated cells at spatial scales of 150 nm. This technology can be applied to natural geomicrobiological systems.

Bacterial Adhesion↗
PubMed2026

Whole-transcriptome-scale isoform-resolved spatial imaging of single cells in tissues.

Cell and tissue functions arise from complex interactions among numerous genes, and a systematic understanding of these functions requires isoform-resolved transcriptomic analysis of single cells with high spatial resolution. Here, we introduce an in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues. Using this approach, we imaged ∼33,000 distinct RNAs-including ∼23,000 genes and ∼10,000 isoforms-in the mouse brain. Our data enabled systematic analyses of region- and cell-type-specific gene programs and ligand-receptor-based cell-cell communications. These data further revealed rich spatial diversity and cell-type specificity in isoform usage across numerous genes, as well as brain structures particularly rich in isoform specificity. We anticipate broad application of this method for characterizing the molecular and cellular basis of tissue functions, unlocking previously inaccessible discoveries in cell and organismal biology.

Animals↗
PubMed1988

Transferrin secretion and hepatocyte ploidy: analysis at the single cell level using a semi-automatic image analysis method.

In a previous work it was shown that transferrin (Tf) secretion is directly related to the membrane surface area of hepatocytes (Péchinot D. et al. [31]). The aim of the present work was to search for a possible relationship between Tf secretion and hepatocytic ploidy using a semi-automatic image analysis method. A determination of Tf secretion by isolated normal adult hepatocytes was achieved at the single cell level, using a modified reverse hemolytic plaque test. A Feulgen reaction was also performed on these hepatocytes. It allowed the evaluation, for each secreting hepatocyte, of the quantity of Tf secreted and its nuclear characteristics. Discrimination between diploid (2c) and tetraploid (4c and 2c2c) hepatocytes was performed and the amount of Tf secreted by each subpopulation determined. It appeared that a 2-fold secretion ratio was not found between tetraploid and diploid hepatocytes. These results suggest, as Tf production is not directly proportional to the degree of ploidy of hepatocytes, that some not yet elucidated regulatory mechanisms may act on Tf gene expression.

Animals↗
PubMed1999

Analysis of progenitor cell involvement in B-CLL by simultaneous immunophenotypic and genotypic analysis at the single cell level.

B-cell chronic lymphocytic leukaemia (B-CLL) results from the clonal expansion of mature B lymphocytes. The detection of leukaemia-associated genetic markers in CD34-positive progenitor cells in a subset of B-CLL patients suggests that malignant transformation in B-CLL occurs in an immature progenitor cell compartment. To further quantify the percentage of B-CLL patients with genetically aberrant progenitor cells we have investigated CD34+ bone marrow cells in 11 B-CLL patients at the single cell level by simultaneous genetic and immunophenotypic analysis (FICTION). In five patients with trisomy 12, CD34+ haemopoietic progenitor cells were detectable on bone marrow smears. In one patient with trisomy 12, CD34+ progenitor cells were isolated by FACS sorting. In all six patients trisomy 12 was not found in the CD34+ cells. Progenitor cells were also analysed in three patients with Rb-deletion and in two patients with deletion of p53. In all patients the genetic marker was not detected in the CD34+ cells. In conclusion, we did not find genetically aberrant progenitor cells in this group of B-CLL patients. These results suggest that the subset of B-CLL patients with genetically aberrant CD34+ cells may be very small. This is of significance for our understanding of B-CLL biology and for future strategies using autologous stem cell transplantation.

Aged↗
PubMed2025

Single-Cell Force Spectroscopy Uncovers Root Zone- and Bacteria-Specific Interactions.

Understanding root-bacteria interactions with plant growth-promoting rhizobacteria (PGPR) is key to developing effective biofertilizers for sustainable agriculture. We performed single-cell force spectroscopy using the atomic force microscope (AFM) to study the primary attachment of two PGPR, Bacillus velezensis and Pseudomonas defensor, to different regions of Arabidopsis thaliana roots. Force measurements with individual cells uncovered distinct attachment strategies by each strain, involving binding via micrometer-long polymers from both bacteria and root surfaces. Flagella differentially affected the binding interactions of each PGPR; their removal altered binding characteristics differently for each strain, highlighting the importance of flagella in early root colonization. Using silica beads to mimic the negatively charged bacteria, we demonstrated the influence of electrostatic forces on root-bacteria interactions. We also examined interactions with abiotic surfaces of varying surface energies, revealing the roles of hydrophilic and hydrophobic forces in initial binding. Our measurements show that differences in the physicochemical properties of bacteria and roots are responsible for variations in primary attachment strategies between PGPR strains and root regions. Parallel fluorescence measurements corroborated our AFM single-cell analysis. Overall, our results provide a nanoscale view of bacterial attachment to roots, offering key insights into how beneficial bacteria colonize roots, crucial for enhancing biofertilizer effectiveness.

Plant Roots↗
PubMed2003

Identification of proteins in single-cell capillary electrophoresis fingerprints based on comigration with standard proteins.

In the previous paper in this Journal, we reported the use of capillary sieving electrophoresis to characterize proteins expressed by single cancer cells at specific phases in the cell cycle. Analysis of the data revealed one component with cell cycle-dependent changes in expression at the 99% confidence limit. However, the amount of protein present in a single cell is far too small to allow its direct identification by mass spectrometry. In this paper, we report a method by which such proteins can be tentatively identified. We perform standard SDS-PAGE electrophoresis of the proteins contained within a homogenate prepared from an HT29 cell culture. Proteins extracted from bands in the gel are identified by mass spectrometry. The proteins also provide a set of standards that can be used to spike the sample before capillary sieving electrophoresis (CSE) separation; comigration is taken as evidence for the identity of the target protein. In a proof-of-principle experiment, a single band migrating at approximately 47 kDa was isolated from the SDS-PAGE gel generated from the HT29 cell line. Proteins extracted from this band were used to spike a CSE separation of the same extract. This band comigrated with a cell cycle-dependent component identified from single-cell analysis. In-gel digestion and LC/MS/MS were used to identify five proteins, including cytokeratin 18, which is the product of the most highly expressed gene in this cell line.

Amino Acid Sequence↗
PubMed2004

Cytomics--new technologies: towards a human cytome project.

BACKGROUND: Molecular cell systems research (cytomics) aims at the understanding of the molecular architecture and functionality of cell systems (cytomes) by single-cell analysis in combination with exhaustive bioinformatic knowledge extraction. In this way, loss of information as a consequence of molecular averaging by cell or tissue homogenisation is avoided. PROGRESS: The cytomics concept has been significantly advanced by a multitude of current developments. Amongst them are confocal and laser scanning microscopy, multiphoton fluorescence excitation, spectral imaging, fluorescence resonance energy transfer (FRET), fast imaging in flow, optical stretching in flow, and miniaturised flow and image cytometry within laboratories on a chip or laser microdissection, as well as the use of bead arrays. In addition, biomolecular analysis techniques like tyramide signal amplification, single-cell polymerase chain reaction (PCR), and the labelling of biomolecules by quantum dots, magnetic nanobeads, or aptamers open new horizons of sensitivity and molecular specificity at the single-cell level. Data sieving or data mining of the vast amounts of collected multiparameter data for exhaustive multilevel bioinformatic knowledge extraction avoids the inadvertent loss of information from unknown molecular relations being inaccessible to an a priori hypothesis. CHALLENGE: It seems important to address the challenge of a human cytome project using hypothesis-driven molecular information collection from disease associated cell systems, supplemented by systematic and exhaustive knowledge extraction. This will allow the description of the molecular setup of normal and abnormal cell systems within a relational knowledge system, permitting the standardised discrimination of abnormal cell states in disease. As one of the consequences, individualised predictions of further disease course in patients (predictive medicine by cytomics) by characteristic discriminatory data patterns will permit individualised therapies, identification of new pharmaceutical targets, and establishment of a standardised framework of relevant molecular alterations in disease. This special issue of Cytometry, on new technologies in cytomics, focuses on prominent examples of this presently fast-moving scientific field, and represents one of the preconditions for the formulation of a human cytome project.

Cell Biology↗
PubMed2026

Integrative analysis of single-cell sequencing identifies CD8+ TIM3+ CD101+ T cell-associated genes as prognostic biomarkers in breast cancer.

BACKGROUND: Breast cancer is a prevalent and deadly malignancy that significantly impacts women's quality of life and imposes financial burdens. Despite therapeutic advancements, tumour heterogeneity and frequent relapses remain major challenges. Accordingly, this study aimed to characterize immune features associated with CD8+ TIM3+ CD101+ T cells and develop a prognostic signature for breast cancer. METHODS: This study integrated single-cell and bulk transcriptomic datasets to characterize CD8+ TIM3+ CD101+ T cell (CCT)-related immune features and construct a prognostic signature in breast cancer. Single-cell RNA-seq data were sourced from the Gene Expression Omnibus (GEO) repository, and bulk transcriptomic data were from The Cancer Genome Atlas (TCGA) and GEO databases. Analytical methods included pseudo-time trajectory reconstruction (Monocle2), intercellular signalling analysis (CellChat), functional enrichment (ClusterProfiler), and immune profiling (ssGSEA). Prognostic modeling was conducted using least absolute shrinkage and selection operator (LASSO) Cox regression, with validation via Kaplan-Meier and time-dependent receiver operating characteristic (ROC) analyses. RESULTS: Single-cell analysis identified 17 clusters spanning seven cell types, including T cells, myeloid cells, and epithelial cells. T-cell sub-clustering revealed four subtypes. Pseudotime analysis suggested a potential state-transition relationship between CD8+ CD101- TIM3+ and CD8+ CD101+ TIM3+ T-cell states. A total of 121 differentially expressed genes were enriched in vital biological processes. An 11-gene prognostic model showed strong predictive power across cohorts. Single-cell T-cell reclustering identified a CD8+ CD101+ TIM3+ T-cell subpopulation, which was primarily characterized by the expression of markers such as CD101 and HAVCR2/TIM3. CONCLUSIONS: This study maps cellular heterogeneity and molecular networks in breast cancer, offering insights for targeted therapy and improved prognosis.

Breast invasive carcinoma↗
PubMed1995

Epithelial cell polarity in early Xenopus development.

The Xenopus blastula consists of two morphologically distinct cell types. Polarized epithelial cells build up the embryonic surface and fence off an inner non-polarized cell population. We examined the establishment of this early functional cell diversification in the embryo by single cell analysis, in vitro cell culture, and transplantation experiments. Single blastomeres from a 64-cell embryo (1/64 cells) exhibit several features of polarized cells. The plasma membrane of 1/64 cells consists of an apical domain, which is inherited from the original egg membrane, and a basolateral domain derived from newly formed membrane during cleavage. These are inherent, cell-autonomous properties of the blastomeres, as they form and are maintained in blastomeres raised in the absence of any cell interactions in calcium free medium. Upon in vitro culture a single 1/64 cell gives rise to an aggregate of two different cell types. Cells carrying a part of the former egg membrane domain differentiate into polarized epithelial cells, whereas cells lacking this membrane domain are not polarized. These results demonstrate that the inclusion of the egg membrane, rather than external signals related to the position of a cell in the intact embryo, is required for the apical/basolateral differentiation of the surface epithelium. This view is supported by cell transplantation studies. A single 1/64 cell was implanted into the blastocoel of a stage 8 blastula embryo. The progeny of the implanted cell proliferate within the host embryo and split into two morphologically distinct populations with different cell behaviours. Cells incorporating a part of the egg membrane form coherent patches of polarized epithelial cell sheets in the interior of the host embryo. In contrast, cells lacking egg membrane do not exhibit any characteristics of polarized cells and eventually spread into different regions of the host embryo. Our results show that the egg membrane and/or components of the submembrane cortex play a determinative role in the formation of the blastula epithelium.

Animals↗