High-throughput precision measurement of subcellular localization in single cells

Shedding Light on Intracellular Proteins using Flow Cytometry

Intracellular protein abundance is routinely measured in mammalian cells using population-based techniques such as western blotting which fail to capture single cell protein levels or using fluorescence microscopy which is although suitable for single cell protein detection but not for rapid analysis of large no. of cells. Flow cytometry offers rapid, high-throughput, multiparameter-based analysis of intracellular protein expression in statistically significant no. of cells at single cell resolution. In past few decades, customized assays have been developed for flow cytometric detection of specific intracellular proteins. This review discusses the scope of flow cytometry for intracellular protein detection in mammalian cells along with specific applications. Technological advancements to overcome the limitations of traditional flow cytometry for the same are also discussed.

A method to study human synaptic protein-protein interactions by using flow cytometry coupled to proximity ligation assay (Syn-FlowPLA)

BACKGROUND

Synapses are highly specialized sites characterized by intricate networks of protein-protein interactions (PPIs) important to maintain healthy synapses. Therefore, mapping these networks could address unsolved questions about human cognition, synaptic plasticity, learning, and memory in physiological and pathological conditions. The limitation of analyzing synaptic interactions in living humans has led to the development of methods to isolate synaptic terminals (synaptosomes) from cryopreserved human brains.

NEW METHOD

Here, we established a method to detect synaptic PPIs by applying flow cytometric proximity ligation assay (FlowPLA) to synaptosomes isolated from frozen human frontal cortex (FC) and hippocampus (HP) (Syn-FlowPLA).

RESULTS

Applying this method in synaptosomes, we were able to detect the known post-synaptic interactions between distinct subtypes of N-methyl-D-aspartate glutamate receptors (NMDARs) and their anchoring postsynaptic density 95 protein (PSD95). Moreover, we detected the known pre-synaptic interactions between the SNARE complex proteins synaptosomal-associated protein of 25 kDa (SNAP25), synaptobrevin (VAMP2), and syntaxin 1a (STX1A). As a negative control, we analyzed the interaction between mitochondrial superoxide dismutase 2 (SOD2) and PSD95, which are not expected to be physically associated.

COMPARISON WITH EXISTING METHODS

PPIs have been studied in vitro primarily by co-immunoprecipitation, affinity chromatography, protein-fragment complementation assays (PCAs), and flow cytometry. All these are valid approaches; however, they require more steps or combination with other techniques. PLA technology identifies PPIs with high specificity and sensitivity.

CONCLUSIONS

The Syn-FlowPLA described here allows rapid analyses of PPIs, specifically within the synaptic compartment isolated from frozen autopsy specimens, achieving greater target sensitivity. Syn-FlowPLA, as presented here, is therefore a useful method to study human synaptic PPI in physiological and pathological conditions.

Measurement methods of single cell drug response

In the last decades, a wide multitude of research activity has been focused on the development of new drugs, and devoted to overcome the challenges of high cost and low efficiency in drug evaluation. The measurement of drug response at the single cell level is a quicker, more direct and more accurate way to reflect drug efficacy, which can shorten the drug development period and reduce research costs. Therefore, the single cell drug response (SCDR) measurement technology has aroused extensive attention from researchers, and has become a hot topic in the fields of drug research and cell biology. Recent years have seen the emergence of various SCDR measurement technologies that feature different working principles and different levels of measurement performance. To better examine, compare and summarize the characteristics and functions of these technologies, we select signal-to-noise ratio, throughput, content, invasion, and device complexity as the criteria to evaluate them from the drug efficacy perspective. This review aims to highlight sixteen kinds of SCDR measurement technologies, including patch-clamp technique, live-cell interferometry, capillary electrophoresis, secondary ion mass spectrometry, and more, and report widespread representative examples of SCDR measurement the recent approaches for over the past forty years. Based on their reaction principles, these technologies are classified into four categories: electrical, optical, electrochemical, and mass spectrometry, and a detailed comparison is made between them. After in-depth understanding of these technologies, it is expected to improve or integrate these technologies to propose better SCDR measurement strategies, and explore methods in new drug development and screening, as well as disease diagnosis and treatment.

Computational methods for protein localization prediction

The accurate annotation of protein localization is crucial in understanding protein function in tandem with a broad range of applications such as pathological analysis and drug design. Since most proteins do not have experimentally-determined localization information, the computational prediction of protein localization has been an active research area for more than two decades. In particular, recent machine-learning advancements have fueled the development of new methods in protein localization prediction. In this review paper, we first categorize the main features and algorithms used for protein localization prediction. Then, we summarize a list of protein localization prediction tools in terms of their coverage, characteristics, and accessibility to help users find suitable tools based on their needs. Next, we evaluate some of these tools on a benchmark dataset. Finally, we provide an outlook on the future exploration of protein localization methods.

Flow cytometry: principles, applications and recent advances

Flow cytometry (FCM) is a sophisticated technique that works on the principle of light scattering and fluorescence emission by the specific fluorescent probe-labeled cells as they pass through a laser beam. It offers several unique advantages as it allows fast, relatively quantitative, multiparametric analysis of cell populations at the single cell level. In addition, it also enables physical sorting of the cells to separate the subpopulations based on different parameters. In this constantly evolving field, innovative technologies such as imaging FCM, mass cytometry and Raman FCM are being developed in order to address limitations of traditional FCM. This review explains the general principles, main applications and recent advances in the field of FCM.

In Situ Analysis of DNA-Protein Complex Formation upon Radiation-Induced DNA Damage

The importance of determining at the cellular level the formation of DNA–protein complexes after radiation-induced lesions to DNA is outlined by the evidence that such interactions represent one of the first steps of the cellular response to DNA damage. These complexes are formed through recruitment at the sites of the lesion, of proteins deputed to signal the presence of DNA damage, and of DNA repair factors necessary to remove it. Investigating the formation of such complexes has provided, and will probably continue to, relevant information about molecular mechanisms and spatiotemporal dynamics of the processes that constitute the first barrier of cell defense against genome instability and related diseases. In this review, we will summarize and discuss the use of in situ procedures to detect the formation of DNA-protein complexes after radiation-induced DNA damage. This type of analysis provides important information on the spatial localization and temporal resolution of the formation of such complexes, at the single-cell level, allowing the study of heterogeneous cell populations.

Barcoded DNA nanostructures for the multiplexed profiling of subcellular protein distribution

Massively parallel DNA sequencing is established, yet high-throughput protein profiling remains challenging. Here, we report a barcoding approach that leverages the combinatorial sequence content and the configurational programmability of DNA nanostructures for high-throughput multiplexed profiling of the subcellular expression and distribution of proteins in whole cells. The barcodes are formed by in situ hybridization of tetrahedral DNA nanostructures and short DNA sequences conjugated with protein-targeting antibodies, and by nanostructure-assisted ligation (either enzymatic or chemical) of the nanostructures and exogenous DNA sequences bound to nanoparticles of different sizes (which cause these localization sequences to differentially distribute across subcellular compartments). Compared with linear DNA barcoding, the nanostructured barcodes enhance the signal by more than 100-fold. By implementing the barcoding approach on a microfluidic device for the analysis of rare patient samples, we show that molecular subtypes of breast cancer can be accurately classified and that subcellular spatial markers of disease aggressiveness can be identified.

Prediction of Apoptosis Protein Subcellular Localization with Multilayer Sparse Coding and Oversampling Approach

The prediction of apoptosis protein subcellular localization plays an important role in understanding the progress in cell proliferation and death. Recently computational approaches to this issue have become very popular, since the traditional biological experiments are so costly and time-consuming that they cannot catch up with the growth rate of sequence data anymore. In order to improve the prediction accuracy of apoptosis protein subcellular localization, we proposed a sparse coding method combined with traditional feature extraction algorithm to complete the sparse representation of apoptosis protein sequences, using multilayer pooling based on different sizes of dictionaries to integrate the processed features, as well as oversampling approach to decrease the influences caused by unbalanced data sets. Then the extracted features were input to a support vector machine to predict the subcellular localization of the apoptosis protein. The experiment results obtained by Jackknife test on two benchmark data sets indicate that our method can significantly improve the accuracy of the apoptosis protein subcellular localization prediction.

HiPLA: High-throughput imaging proximity ligation assay

Protein-protein interactions are essential for cellular structure and function. To delineate how the intricate assembly of protein interactions contribute to cellular processes in health and disease, new methodologies that are both highly sensitive and can be applied at large scale are needed. Here, we develop HiPLA (high-throughput imaging proximity ligation assay), a method that employs the well-established antibody-based proximity ligation assay in a high-throughput imaging screening format as a novel means to systematically visualize protein interactomes. Using HiPLA with a library of antibodies targeting nuclear proteins, we probe the interaction of 60 proteins and associated post-translational modifications (PTMs) with the nuclear lamina in a model of the premature aging disorder Hutchinson-Gilford progeria syndrome (HGPS). We identify a subset of proteins that differentially interact with the nuclear lamina in HGPS. Using HiPLA in combination with quantitative indirect immunofluorescence, we find that the majority of differential interactions are accompanied by corresponding changes in expression of the interacting protein. Taken together, HiPLA offers a novel approach to probe cellular protein-protein interaction at a large scale and reveals mechanistic insights into the assembly of protein complexes.

Protein fishing from single live cells

Intracellular protein and proteomic studies using mass spectrometry, imaging microscopy, flow cytometry, or western blotting techniques require genetic manipulation, cell permeabilization, and/or cell lysis. We present a biophysical method that employs a nanoaspirator to 'fish' native cytoplasmic or nuclear proteins from single mammalian cells, without compromising cell viability, followed by ex cellulo quantitative detection. Our work paves the way for spatiotemporally-controlled, quantitative, live, single-cell proteomics.

Subcellular Peptide Localization in Single Identified Neurons by Capillary Microsampling Mass Spectrometry

Single cell mass spectrometry (MS) is uniquely positioned for the sequencing and identification of peptides in rare cells. Small peptides can take on different roles in subcellular compartments. Whereas some peptides serve as neurotransmitters in the cytoplasm, they can also function as transcription factors in the nucleus. Thus, there is a need to analyze the subcellular peptide compositions in identified single cells. Here, we apply capillary microsampling MS with ion mobility separation for the sequencing of peptides in single neurons of the mollusk Lymnaea stagnalis, and the analysis of peptide distributions between the cytoplasm and nucleus of identified single neurons that are known to express cardioactive Phe-Met-Arg-Phe amide-like (FMRFamide-like) neuropeptides. Nuclei and cytoplasm of Type 1 and Type 2 F group (Fgp) neurons were analyzed for neuropeptides cleaved from the protein precursors encoded by alternative splicing products of the FMRFamide gene. Relative abundances of nine neuropeptides were determined in the cytoplasm. The nuclei contained six of these peptides at different abundances. Enabled by its relative enrichment in Fgp neurons, a new 28-residue neuropeptide was sequenced by tandem MS.

Improved efficiency of in situ protein analysis by proximity ligation using UnFold probes

We have redesigned probes for in situ proximity ligation assay (PLA), resulting in more efficient localized detection of target proteins. In situ PLA depends on recognition of target proteins by pairs of antibody-oligonucleotide conjugates (PLA probes), which jointly give rise to DNA circles that template localized rolling circle amplification reactions. The requirement for dual recognition of the target proteins improves selectivity by ignoring any cross-reactivity not shared by the antibodies, and it allows detection of protein-protein interactions and post-translational modifications. We herein describe an improved design of the PLA probes –UnFold probes – where all elements required for formation of circular DNA strands are incorporated in the probes. Premature interactions between the UnFold probes are prevented by including an enzymatic “unfolding” step in the detection reactions. This allows DNA circles to form by pairs of reagents only after excess reagents have been removed. We demonstrate the performance of UnFold probes for detection of protein-protein interactions and post-translational modifications in fixed cells and tissues, revealing considerably more efficient signal generation. We also apply the UnFold probes to detect IL-6 in solution phase after capture on solid supports, demonstrating increased sensitivity over both normal sandwich enzyme-linked immunosorbent assays and conventional PLA assays.