Deep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies

Yang, Liwei; George, Justin; Wang, Jun

doi:10.1002/pmic.201900226

Cited by 49 publications

(49 citation statements)

References 109 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This may be a further direction for increasing the information for AOP development to advance from the cellular to tissue and organ response. Remarkable developments have recently been made for single-cell proteomics and metabolomics (Yang et al 2019;Duncan et al 2019). However, compared to sequencing-based approaches, the applicability of these methods is still limited by the number of cells that can be profiled, or the number of biomolecules detected in parallel.…”

Section: Which Omics Layers To Use For Toxicological Research Questionsmentioning

confidence: 99%

Prospects and challenges of multi-omics data integration in toxicology

et al. 2020

View full text Add to dashboard Cite

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.Archives of Toxicology (2020) 94:371-388Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

show abstract

Section: Which Omics Layers To Use For Toxicological Research Questionsmentioning

confidence: 99%

Prospects and challenges of multi-omics data integration in toxicology

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Moreover, methods such as single-cell combinatorial indexed Hi-C (Sci-Hi-C) ( Ramani et al, 2020 ) and DamID ( Kind et al, 2015 ) can provide information about chromosome configuration and genome organization. In the near future, other methods in the emerging fields of single-cell proteomics and metabolomics are expected to shed additional light on cell phenotype at the single-cell level ( Ali et al, 2019 ; Yang et al, 2019 ), thus allowing for a more dynamic picture of cellular heterogeneity. Finally, any information gained from such single-cell analysis will need to be validated through functional genomic analysis.…”

Section: Future Opportunitiesmentioning

confidence: 99%

Midbrain Dopaminergic Neuron Development at the Single Cell Level: In vivo and in Stem Cells

Ásgrímsdóttir

Arenas

2020

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

Parkinson's disease (PD) is a progressive neurodegenerative disorder that predominantly affects dopaminergic (DA) neurons of the substantia nigra. Current treatment options for PD are symptomatic and typically involve the replacement of DA neurotransmission by DA drugs, which relieve the patients of some of their motor symptoms. However, by the time of diagnosis, patients have already lost about 70% of their substantia nigra DA neurons and these drugs offer only temporary relief. Therefore, cell replacement therapy has garnered much interest as a potential treatment option for PD. Early studies using human fetal tissue for transplantation in PD patients provided proof of principle for cell replacement therapy, but they also highlighted the ethical and practical difficulties associated with using human fetal tissue as a cell source. In recent years, advancements in stem cell research have made human pluripotent stem cells (hPSCs) an attractive source of material for cell replacement therapy. Studies on how DA neurons are specified and differentiated in the developing mouse midbrain have allowed us to recapitulate many of the positional and temporal cues needed to generate DA neurons in vitro. However, little is known about the developmental programs that govern human DA neuron development. With the advent of single-cell RNA sequencing (scRNA-seq) and bioinformatics, it has become possible to analyze precious human samples with unprecedented detail and extract valuable high-quality information from large data sets. This technology has allowed the systematic classification of cell types present in the human developing midbrain along with their gene expression patterns. By studying human development in such an unbiased manner, we can begin to elucidate human DA neuron development and determine how much it differs from our knowledge of the rodent brain. Importantly, this molecular description of the function of human cells has become and will increasingly be a reference to define, evaluate, and engineer cell types for PD cell replacement therapy and disease modeling.

show abstract

“…Single cell analysis continues to have a major impact on our understanding of cell subtypes, biology, and medicine. [ 1,2 ] The same is likely true for analyses of single exosomes or extracellular vesicles (EV) in general. It has become apparent that EV populations can be even more heterogeneous than the parental cells from which they are derived.…”

Section: Introductionmentioning

confidence: 99%

Single Extracellular Vesicle Protein Analysis Using Immuno‐Droplet Digital Polymerase Chain Reaction Amplification

Wang

Carlson

et al. 2020

Adv. Biosys.

View full text Add to dashboard Cite

due to selective shedding of proteins and nucleic acid cargo, the much smaller size and payload capacity of EV, and stochastic cellular effects. In order to use EV more efficiently as biomarkers of disease, we need a better understanding of their composition and heterogeneity. A number of single EV analytical methods have been proposed. These include analysis by microscopic imaging of immobilized vesicles (SEA), [5,6] modified flow cytometry, [5,7-10] and digital detection using ELISA [11] or nucleic acid-based amplification. [28] In spite of this progress, it remains challenging to detect rare proteins in single EV, given the inherent signal/background limitations of direct fluorescence imaging and relatively modest enzyme mediated signal amplification in ELISA. Here we describe a new method for ultrasensitive detection of proteins in single EV that exploits antibody-based immuno-droplet digital polymerase chain reaction (iddPCR). The described method is not only sensitive but also allows multiplexing (currently up to three proteins). We used uniquely designed DNA barcoded antibodies for protein recognition. The labeled EV are encapsulated into 70 µm droplets in which PCR amplifies the message of the DNA barcode. Using different There is a need for novel analytical techniques to study the composition of single extracellular vesicles (EV). Such techniques are required to improve the understanding of heterogeneous EV populations, to allow identification of unique subpopulations, and to enable earlier and more sensitive disease detection. Because of the small size of EV and their low protein content, ultrahigh sensitivity technologies are required. Here, an immuno-droplet digital polymerase chain reaction (iddPCR) amplification method is described that allows multiplexed single EV protein profiling. Antibody-DNA conjugates are used to label EV, followed by stochastic microfluidic incorporation of single EV into droplets. In situ PCR with fluorescent reporter probes converts and amplifies the barcode signal for subsequent read-out by droplet imaging. In these proof-of-principle studies, it is shown that multiplex protein analysis is possible in single EV, opening the door for future analyses.

show abstract

Deep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies

Cited by 49 publications

References 109 publications

Prospects and challenges of multi-omics data integration in toxicology

Prospects and challenges of multi-omics data integration in toxicology

Midbrain Dopaminergic Neuron Development at the Single Cell Level: In vivo and in Stem Cells

Single Extracellular Vesicle Protein Analysis Using Immuno‐Droplet Digital Polymerase Chain Reaction Amplification

Contact Info

Product

Resources

About