Phospho-seq: Integrated, multi-modal profiling of intracellular protein dynamics in single cells

Background:

Profiling of proteins using “multiomic” technology

Multimodal omics techniques involve the simultaneous readout of multiple types of omics data (such as transcriptomics and proteomics) to generate a more comprehensive understanding of biological systems. The first generation of methods to quantify proteins alongside other omics modalities [see CITE-seq (Stoeckius et al., 2017), REAP-seq (Wong et al., 2022), DOGMA-seq (Mimitou et al., 2021) and TEA-seq (Swanson et al., 2021)] were limited to the detection of surface proteins. Although hematopoietic samples can be characterised very effectively with these methods, there is a need for experimental protocols to measure intracellular and intranuclear protein levels in order to inter alia identify signalling cascades and characterise disease states. Some pioneering approaches [see ASAP-seq (Mimitou et al., 2021), inCITE-seq (Chung et al., 2021), NEAT-seq (Chen et al., 2022) and QuRIE-seq (Rivello et al., 2021)] to measure proteins inside cells have been published recently.  However, they are limited in scalability due to reliance on commercially available conjugated antibodies and do not allow for trimodal readout in the same biological system.

Bridge Integration

The Satija lab recently published a preprint (Hao et al., 2022) to  computationally harmonise unimodal single-cell measurements from two omics modalities (RNA and protein, chromatin, histone, or methylation) using separate multi-omics datasets as molecular bridges. The bridge dataset measures both modalities simultaneously, enabling the mapping of single-omics datasets onto each other. This enables the study of relationships between multiple omics readouts and facilitates experimental designs, as multi-omic technologies may only be applied to a subset of the experimental samples while cheaper/high-quality single-omics can be performed for all samples. In this preprint, Blair and colleagues use bridge integration to integrate single cell transcriptomics readouts into Phospho-seq.

Fig. 1 Bridge Integration. Figure taken from Blair et al. (2023), BioRxiv published under the CC-BY-NC-ND 4.0 International license.

Key Findings

Benchtop Preparation of Barcoded Antibodies for Protein Staining

Phospho-seq adapts a benchtop conjugation strategy described in van Buggenum et al. (2016) to generate large custom uniquely-indexed DNA-bound antibody panels for protein staining. As this method is easy to use, cost-efficient and compatible with commercially available antibodies (unconjugated and conjugated), the approach is scalable and suitable for many experimental settings.

Phospho-Seq Workflow

Following dissociation, single cells are subjected to fixation to maintain structural integrity and detergent-based permeabilization enabling oligonucleotide-tagged (barcoded) antibodies to enter the nucleus and the cytoplasm to bind their target proteins. Single-stranded DNA binding protein is added to the antibody pool to prevent nonspecific binding of cellular components to the barcoded antibodies thereby reducing background noise.

Finally, scATAC seq is performed using the Tn5 transposase enzyme and the 10x scATAC-seq kit to identify regions of chromatin that are accessible to transcription factors and other regulatory proteins. The method involves the use of a transposase enzyme that can insert sequencing adapters into open chromatin regions, followed by sequencing to identify the location and accessibility of these regions across the genome.

Fig. 2 Phospho-Seq Workflow. Figure taken and from Blair et al. (2023), BioRxiv published under the CC-BY-NC-ND 4.0 International license and converted into landscape orientation.

 

In order to improve cell annotation and construct gene regulatory networks, single cell transcriptomics data is required alongside chromatin accessibility and proteomics readouts. Initially, the authors tried to directly generate trimodal readout in Phospho-seq, however they observed a considerable decrease in data quality due to incompatible fixation and permeabilization conditions for RNA and ATAC readout. Hence, they used a recently developed computational approach, bridge integration, to map single cell transcriptomics data to the Phospho-seq data yielding high quality trimodal data.

Phospho-seq Measurements Improve Biological Understanding

The authors demonstrated that the proteomics readout alongside a chromatin accessibility measurement is suitable to distinguish cell types. For instance, they found that the segregation and differentiation capacity of different induced pluripotent stem cell (iPSC) lines can be better explained by their readout instead of epigenetic differences.

Moreover, different distributions of unphosphorylated and phosphorylated proteins were measured upon activation of a signalling cascade indicating that the readout can be used as a proxy for stimulation even when the total abundance of the proteins remained the same.

This is highly relevant as it was also shown in the preprint that for some transcription factors (TFs), phosphorylation levels of nuclear TFs correlated with its activity while no correlation was found between the total abundance and the activity. The authors therefore suggested that phosphorylated TF levels may be more informative with regards to TF activity and reflect cellular states. Finally, the authors demonstrated that Phospho-seq is applicable to a broad range of samples as could be seen by its suitability to cell cultures, iPSCs and organoids.

Conclusion and Perspective

This preprint builds upon recently published multiomics approaches, allowing for the simultaneous characterization of intranuclear, intracellular, and cell surface proteins alongside RNA levels and chromatin accessibility. This method can improve our understanding of intracellular protein dynamics and posttranslational modifications, which cannot be detected by transcriptomics approaches. Furthermore, the method can potentially be combined with other state-of-the-art sequence-based omics approaches to measure more modalities simultaneously. A fixation and permeabilization routine compatible with scATAC and scRNA sequencing techniques could enable direct simultaneous measurement replacing the bridge integration.

Recent advances in sequence-based single-cell transcriptomics have led to the emergence of numerous single-molecule protein sequencing and fingerprinting technologies. This might create the opportunity to study the diversity of proteoforms and to distinguish between different posttranslational modifications, alternative splicing and germline variants in the future.

What I liked about this preprint

It is inspiring to read a preprint in a pioneering field and to see how novel methods build and expand upon previous ones. I found it particularly interesting how the authors integrated their recently published bridge integration into Phospho-seq and how it can help to obtain multimodal data. Additionally, it is beneficial if a method follows the FAIR guidelines, making all machines, reagents, and datasets publicly available and accessible to the community.

References

Chen, A. F., Parks, B., Kathiria, A. S., Ober-Reynolds, B., Goronzy, J. J., & Greenleaf, W. J. (2022). NEAT-seq: simultaneous profiling of intra-nuclear proteins, chromatin accessibility and gene expression in single cells. Nature Methods, 19(5), 547–553. https://doi.org/10.1038/s41592-022-01461-y

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Tags: omics, proteomics, sequencing, single cell

doi: https://doi.org/10.1242/prelights.34400

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