Quantification of single-cell nanoparticle concentrations and the distribution of these concentrations in cell population

Quantification of nanoparticle uptake into cells is necessary for numerous applications in cellular imaging and therapy. Herein, synchrotron X-ray fluorescence (SXRF) microscopy, a promising tool to quantify elements in plant and animal cells, was employed to quantify and characterize the distribution of titanium dioxide (TiO 2 ) nanosphere uptake in a population of single cells. These results were compared with average nanoparticle concentrations per cell obtained by widely used inductively coupled plasma mass spectrometry (ICP-MS). The results show that nanoparticle concentrations per cell quantified by SXRF were of one to two orders of magnitude greater compared with ICP-MS. The SXRF results also indicate a Gaussian distribution of the nanoparticle concentration per cell. The results suggest that issues relevant to the field of single-cell analysis, the limitation of methods to determine physical parameters from large population averages leading to potentially misleading information and the lack of any information about the cellular heterogeneity are equally relevant for quantification of nanoparticles in cell populations.

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Beyond Single-Cell Analysis of Metallodrugs by ICP-MS: Targeting Cellular Substructures

International Journal of Molecular Sciences ◽

10.3390/ijms22179468 ◽

2021 ◽

Vol 22 (17) ◽

pp. 9468

Author(s):

Audrey Galé ◽

Lukas Hofmann ◽

Nicola Lüdi ◽

Martin Nils Hungerbühler ◽

Christoph Kempf ◽

...

Keyword(s):

Single Cell ◽

Inductively Coupled Plasma ◽

Single Cell Analysis ◽

Single Cells ◽

Cancer Cell Line ◽

Advanced Lung Cancer ◽

Lower Amount ◽

Platinum Resistance ◽

Cell Organelles ◽

Icp Ms

Platinum compounds such as cisplatin (cisPt) embody the backbone of combination chemotherapy protocols against advanced lung cancer. However, their efficacy is primarily limited by inherent or acquired platinum resistance, the origin of which has not been fully elucidated yet, although of paramount interest. Using single cell inductively coupled plasma mass spectrometry (SC-ICP-MS), this study quantifies cisPt in single cancer cells and for the first time in isolated nuclei. A comparison of cisPt uptake was performed between a wild type (wt) cancer cell line and related resistant sublines. In both, resistant cells, wt cells, and their nuclei, cisPt uptake was measured at different incubation times. A lower amount of cisPt was found in resistant cell lines and their nuclei compared to wt cells. Moreover, the abundance of internalized cisPt decreased with increasing resistance. Interestingly, concentrations of cisPt found within the nuclei were higher than compared to cellular concentrations. Here, we show, that SC-ICP-MS allows precise and accurate quantification of metallodrugs in both single cells and cell organelles such as nuclei. These findings pave the way for future applications investigating the potency and efficacy of novel metallodrugs developed for cancer treatment.

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Highly efficient single-cell analysis of microbial cells by time-resolved inductively coupled plasma mass spectrometry

Journal of Analytical Atomic Spectrometry ◽

10.1039/c4ja00040d ◽

2014 ◽

Vol 29 (9) ◽

pp. 1598-1606 ◽

Cited By ~ 35

Author(s):

Shin-ichi Miyashita ◽

Alexander S. Groombridge ◽

Shin-ichiro Fujii ◽

Ayumi Minoda ◽

Akiko Takatsu ◽

...

Keyword(s):

Single Cell ◽

Inductively Coupled Plasma ◽

Single Cell Analysis ◽

High Time Resolution ◽

Time Resolved ◽

Microbial Cells ◽

Inductively Coupled ◽

Highly Efficient ◽

Icp Ms ◽

Plasma Mass Spectrometry

Highly efficient single-cell elemental analysis of microbial cells was achieved using a developed ICP-MS system with approximately 100% cell introduction efficiency and high time resolution.

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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2

Genome Biology ◽

10.1186/s13059-021-02267-5 ◽

2021 ◽

Vol 22 (1) ◽

Cited By ~ 4

Author(s):

Harrison Specht ◽

Edward Emmott ◽

Aleksandra A. Petelski ◽

R. Gray Huffman ◽

David H. Perlman ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Single Cell Protein ◽

Cellular Heterogeneity ◽

Cell Protein ◽

Alternatively Activated Macrophages ◽

Monocytes And Macrophages ◽

Molecular Phenotypes ◽

Post Transcriptional Regulation

Abstract Background Macrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of the limitations of quantitative single-cell protein analysis. Results To overcome this limitation, we develop SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantifies over 3042 proteins in 1490 single monocytes and macrophages in 10 days of instrument time, and the quantified proteins allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. Parallel measurements of transcripts by 10× Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus, SCoPE2 supports quantification with improved count statistics. This allowed exploring regulatory interactions, such as interactions between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Conclusions Even in a homogeneous environment, macrophage proteomes are heterogeneous. This heterogeneity correlates to the inflammatory axis of classically and alternatively activated macrophages. Our methodology lays the foundation for automated and quantitative single-cell analysis of proteins by mass spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.

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Unified single-cell analysis of testis gene regulation and pathology in 5 mouse strains

10.1101/393769 ◽

2018 ◽

Cited By ~ 7

Author(s):

Min Jung ◽

Daniel Wells ◽

Jannette Rusch ◽

Suhaira Ahmed ◽

Jonathan Marchini ◽

...

Keyword(s):

Gene Regulation ◽

Single Cell ◽

Web Application ◽

Single Cell Analysis ◽

De Novo ◽

Single Cells ◽

Cellular Heterogeneity ◽

Mouse Strains ◽

Seminiferous Tubules ◽

Sequence Motifs

AbstractBy removing the confounding factor of cellular heterogeneity, single cell genomics can revolutionize the study of development and disease, but methods are needed to simplify comparison among individuals. To develop such a framework, we assayed the transcriptome in 62,600 single cells from the testes of wildtype mice, and mice with gonadal defects due to disruption of the genes Mlh3, Hormad1, Cul4a or Cnp. The resulting expression atlas of distinct cell clusters revealed novel markers and new insights into testis gene regulation. By jointly analysing mutant and wildtype cells using a model-based factor analysis method, SDA, we decomposed our data into 46 components that identify novel meiotic gene regulatory programmes, mutant-specific pathological processes, and technical effects. Moreover, we identify, de novo, DNA sequence motifs associated with each component, and show that SDA can be used to impute expression values from single cell data. Analysis of SDA components also led us to identify a rare population of macrophages within the seminiferous tubules of Mlh3-/- and Hormad1-/- testes, an area typically associated with immune privilege. We provide a web application to enable interactive exploration of testis gene expression and components at http://www.stats.ox.ac.uk/~wells/testisAtlas.html

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SIMBA: SIngle-cell eMBedding Along with features

10.1101/2021.10.17.464750 ◽

2021 ◽

Author(s):

Huidong Chen ◽

Jayoung Ryu ◽

Michael Edward Vinyard ◽

Adam Lerer ◽

Luca Pinello

Keyword(s):

Gene Regulation ◽

Single Cell ◽

Dna Sequences ◽

Single Cell Analysis ◽

Single Cells ◽

Cellular Heterogeneity ◽

Omics Data ◽

Cell Analysis ◽

Genomic Features ◽

The Individual

Recent advances in single cell omics technologies enable the individual or joint profiling of cellular measurements including gene expression, epigenetic features, chromatin structure and DNA sequences. Currently, most single-cell analysis pipelines are cluster-centric, i.e., they first cluster cells into non-overlapping cellular states and then extract their defining genomic features. These approaches assume that discrete clusters correspond to biologically relevant subpopulations and do not explicitly model the interactions between different feature types. However, cellular processes are defined in individual cells and inherently involve multiple genomic features that interact with each other and together provide complementary views on principles of gene regulation. In addition, single-cell methods are generally designed for a particular task as distinct single-cell problems are formulated differently. To address these current shortcomings, we present SIMBA, a single-cell embedding method that embeds single cells along with their defining features, such as genes, chromatin accessible regions, and transcription factor binding sequences, into a common latent space. By leveraging the co-embedding of cells and features, SIMBA allows for cellular heterogeneity study, clustering-free marker discovery, gene regulation inference, batch effect removal, and omics data integration. SIMBA has been extensively applied to scRNA-seq, scATAC-seq, and dual-omics data. We show that SIMBA provides a single framework that allows diverse single-cell analysis problems to be formulated in a common way and thus simplifies the development of new analyses and integration of other single-cell modalities.

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A strategy to address dissociation-induced compositional and transcriptional bias for single-cell analysis of the human mammary gland

10.1101/2021.02.11.430721 ◽

2021 ◽

Author(s):

Lisa K. Engelbrecht ◽

Alecia-Jane Twigger ◽

Hilary M. Ganz ◽

Christian J. Gabka ◽

Andreas R. Bausch ◽

...

Keyword(s):

Mammary Gland ◽

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Cellular Heterogeneity ◽

Normal Mammary Gland ◽

Isolated Cells ◽

Tissue Dissociation ◽

New Strategy ◽

Gland Function

SummarySingle-cell transcriptomics provide insights into cellular heterogeneity and lineage dynamics that are key to better understanding normal mammary gland function as well as breast cancer initiation and progression. In contrast to murine tissue, human mammary glands require laborious dissociation protocols to isolate single cells. This leads to unavoidable procedure-induced compositional and transcriptional bias. Here, we present a new strategy on how to identify and minimize systematic error by combining different tissue dissociation strategies and then directly comparing composition and transcriptome of isolated cells using single-cell RNA sequencing and flow cytometry. Depending on the tissue isolation strategy, we found dramatic differences in abundance and heterogeneity of certain stromal cells types. Moreover, we identified lineage-specific dissociation-induced gene expression changes that, if left unchecked, could lead to misinterpretation of cellular heterogeneity and, since the basal epithelial population is particularly affected by this, wrongful assignment of putative stem cell populations.

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Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis

Communications Biology ◽

10.1038/s42003-020-0896-2 ◽

2020 ◽

Vol 3 (1) ◽

Cited By ~ 2

Author(s):

Maeve O’Huallachain ◽

Felice-Alessio Bava ◽

Mary Shen ◽

Carolina Dallett ◽

Sri Paladugu ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Single Cell Analysis ◽

Single Cells ◽

Model Systems ◽

Cellular Heterogeneity ◽

Human Model ◽

Targeted Analysis ◽

Technological Advances ◽

And Function

AbstractSingle-cell omics provide insight into cellular heterogeneity and function. Recent technological advances have accelerated single-cell analyses, but workflows remain expensive and complex. We present a method enabling simultaneous, ultra-high throughput single-cell barcoding of millions of cells for targeted analysis of proteins and RNAs. Quantum barcoding (QBC) avoids isolation of single cells by building cell-specific oligo barcodes dynamically within each cell. With minimal instrumentation (four 96-well plates and a multichannel pipette), cell-specific codes are added to each tagged molecule within cells through sequential rounds of classical split-pool synthesis. Here we show the utility of this technology in mouse and human model systems for as many as 50 antibodies to targeted proteins and, separately, >70 targeted RNA regions. We demonstrate that this method can be applied to multi-modal protein and RNA analyses. It can be scaled by expansion of the split-pool process and effectively renders sequencing instruments as versatile multi-parameter flow cytometers.

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Single-cell analysis by use of ICP-MS

Journal of Analytical Atomic Spectrometry ◽

10.1039/d0ja00194e ◽

2020 ◽

Vol 35 (9) ◽

pp. 1784-1813 ◽

Cited By ~ 2

Author(s):

Sarah Theiner ◽

Konrad Loehr ◽

Gunda Koellensperger ◽

Larissa Mueller ◽

Norbert Jakubowski

Keyword(s):

Mass Spectrometry ◽

Single Cell ◽

Inductively Coupled Plasma ◽

Single Cell Analysis ◽

Review Article ◽

Cell Analysis ◽

Inductively Coupled ◽

Icp Ms ◽

Plasma Mass Spectrometry ◽

Recent Trends

This tutorial review article is highlighting the fundamentals, instrumentation, and most recent trends of single-cell analysis by use of inductively coupled plasma-mass spectrometry (ICP-MS).

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Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity

10.1101/665307 ◽

2019 ◽

Cited By ~ 20

Author(s):

Harrison Specht ◽

Edward Emmott ◽

Aleksandra A. Petelski ◽

R. Gray Huffman ◽

David H. Perlman ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Single Cell Protein ◽

Cellular Heterogeneity ◽

Cell Protein ◽

Alternatively Activated Macrophages ◽

Monocytes And Macrophages ◽

Molecular Phenotypes ◽

Post Transcriptional Regulation

AbstractMacrophages are innate immune cells with diverse functional and molecular phenotypes. This diversity is largely unexplored at the level of single-cell proteomes because of limitations of quantitative single-cell protein analysis. To overcome this limitation, we developed SCoPE2, which substantially increases quantitative accuracy and throughput while lowering cost and hands-on time by introducing automated and miniaturized sample preparation. These advances enable us to analyze the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells in the absence of polarizing cytokines. SCoPE2 quantified over 3,042 proteins in 1,490 single monocytes and macrophages in ten days of instrument time, and the quantified proteins allow us to discern single cells by cell type. Furthermore, the data uncover a continuous gradient of proteome states for the macrophages, suggesting that macrophage heterogeneity may emerge in the absence of polarizing cytokines. This gradient correlates to the inflammatory axis of classically and alternatively activated macrophages. Parallel measurements of transcripts by 10x Genomics suggest that our measurements sample 20-fold more protein copies than RNA copies per gene, and thus SCoPE2 supports quantification with improved count statistics. The joint distributions of proteins and transcripts allowed exploring regulatory interactions, such as between the tumor suppressor p53, its transcript, and the transcripts of genes regulated by p53. Our methodology lays the foundation for quantitative single-cell analysis of proteins by mass-spectrometry and demonstrates the potential for inferring transcriptional and post-transcriptional regulation from variability across single cells.Abstract Figure

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Exploring endocytic compartment morphology with systematic genetics and single cell image analysis

10.1101/724989 ◽

2019 ◽

Author(s):

Mojca Mattiazzi Usaj ◽

Nil Sahin ◽

Helena Friesen ◽

Carles Pons ◽

Matej Usaj ◽

...

Keyword(s):

Image Analysis ◽

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Endocytic Pathway ◽

Cellular Heterogeneity ◽

Incomplete Penetrance ◽

Coat Proteins ◽

Mutant Phenotypes ◽

Membrane Components

ABSTRACTEndocytosis is a conserved process that mediates the internalization of nutrients and plasma membrane components, including receptors, for sorting to endosomes and the vacuole (lysosome). We combined systematic yeast genetics, high-content screening, and neural network-based image analysis of single cells to screen for genes that influence the morphology of four main endocytic compartments: coat proteins, actin patches, late endosome, and vacuole. This unbiased approach identified 17 mutant phenotypes and ∼1600 genes whose perturbation affected at least one of the four compartments. Numerous mutants were associated with multiple phenotypes, indicating that morphological pleiotropy is often seen within the endocytic pathway. Morphological profiles based on the 17 aberrant phenotypes were highly correlated for functionally related genes, enabling prediction of gene function. Incomplete penetrance was prevalent, and single-cell analysis enabled exploration of the mechanisms underlying cellular heterogeneity, which include replicative age, organelle inheritance, and stress response.

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