Proximity Ligation Assay: High-Sensitivity Protein Analysis

Proximity ligation assay, usually called PLA, detects proteins at concentrations so low that most conventional methods miss them entirely. The technique was first demonstrated in 2002, when researchers showed it could pick up as few as about 40 zeptomoles of a target protein, an amount roughly equivalent to 24,000 molecules in a test tube. It works by converting a protein-binding event into a DNA signal that can be amplified and counted, effectively translating the language of proteins into the language of nucleic acids, where amplification tools are far more powerful. That basic trick has since been adapted to visualize where proteins interact inside cells, track viral infections, profile cancer biomarkers, and measure chemical modifications on proteins that other assays struggle to see.

How the Assay Works

The core idea behind PLA is elegant: two antibody probes, each carrying a short strand of DNA, bind to the same target protein or to two proteins sitting close together. When those probes land near enough to each other, their attached DNA strands can be joined by an enzymatic ligation reaction. If the probes are too far apart, ligation fails and no signal is produced. That distance-dependent step is what gives PLA its specificity. Only proteins that are physically close together, generally within about 40 nanometers, produce a signal.

Once ligation succeeds, the joined DNA forms a circular template. A specialized enzyme called phi29 DNA polymerase then copies that circle over and over in a process called rolling circle amplification, producing a long single strand of DNA that contains hundreds of repeated copies of the original circle. This DNA strand collapses into a compact bundle roughly one to two microns across, which can be tagged with fluorescent probes and seen under a microscope as a bright dot.

² Each dot represents a single molecular event, meaning you can literally count individual protein complexes in a cell. The phi29 polymerase is remarkably efficient at this job: with random primers, it can amplify circular DNA templates roughly 10,000-fold in a few hours.³

An improved version of the in situ probes, called UnFold probes, streamlined the process by building the circle-forming and template oligonucleotides directly onto the antibodies themselves. These probes use hairpin structures that keep the DNA strands locked and unable to interact until an enzymatic “unfolding” step removes uracil bases and frees the reactive ends. This design eliminates the need to add separate DNA oligonucleotides after the antibody-binding step, reducing handling and background noise.⁴

Why PLA Detects What Other Methods Cannot

The original 2002 proof of concept used DNA aptamers rather than antibodies to detect the cytokine platelet-derived growth factor, reaching a sensitivity of about 40 zeptomoles without any wash or separation steps.⁵ A zeptomole is 10⁻²¹ moles, a quantity far below the detection floor of standard immunoassays like ELISA, which typically bottom out in the picomole-to-femtomole range. The reason PLA achieves this is straightforward: it converts each protein-binding event into a DNA molecule, and DNA can be amplified exponentially. Protein-based detection methods have no equivalent amplification step.

There is also a built-in specificity advantage. Because two independent recognition events must happen in close proximity for a signal to form, a single antibody binding nonspecifically to the wrong target does not generate a false positive on its own. Both probes have to land, and they have to land within about 40 nanometers of each other. That dual-recognition requirement dramatically reduces the background noise that plagues single-antibody assays.

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Mapping Protein-Protein Interactions Inside Cells

The most widely adopted use of PLA is detecting protein-protein interactions at their natural levels inside cells, without the need to overexpress tagged fusion proteins or pull complexes out of cell lysates. Each fluorescent dot marks the exact subcellular location where two proteins sit close enough to be considered interacting. This is a major advantage over co-immunoprecipitation, which tells you that two proteins associate somewhere in a cell homogenate but cannot say where.

In one large-scale study, researchers assembled roughly 700 primary antibodies and used in situ PLA to test 1,204 endogenous protein-protein interactions in HeLa cells, finding that 557 of them tested positive.⁷ That kind of systematic screening at endogenous expression levels would be extremely difficult with most other techniques. It also showed that PLA can scale beyond one-off experiments into pathway-level analysis.

Post-Translational Modifications and Single-Protein Detection

PLA is not limited to pairs of different proteins. By targeting a protein with one antibody and a specific modification on that same protein with a second antibody, you can detect post-translational modifications like phosphorylation with spatial resolution in intact tissue. Researchers have used this approach to study protein phosphorylation and protein interactions in smooth muscle tissues during contraction, demonstrating that the assay can provide unbiased quantitation of phosphorylation events in intact tissue rather than crushed cell extracts.⁸

You can also quantify a single protein species by using two secondary antibodies directed against the same primary antibody, one carrying the PLUS oligonucleotide and the other the MINUS. When both secondary probes bind the same primary antibody molecule, the proximity constraint is automatically satisfied, and a signal appears.² This mode lets PLA function as a highly sensitive single-protein detection assay, not just an interaction assay, which broadens its utility for biomarker quantification.

A related advance combined padlock probes for mRNA detection with in situ PLA, allowing simultaneous readout of gene expression and protein interactions or modifications in the same cell. That protocol takes about a day and a half and gives you co-registered information at both the transcript and protein level.⁹

Multiplexed Detection From Small Samples

A key practical limitation of many protein assays is the inability to measure more than one or two targets at a time without splitting a precious sample into multiple reactions. PLA sidesteps this by encoding each protein target with a unique DNA sequence. Because the readout is nucleic acid-based, you can use real-time PCR or even next-generation sequencing to distinguish dozens of targets simultaneously.

One multiplexed PLA approach demonstrated detection of several proteins in parallel using real-time PCR to quantify the unique DNA identifiers produced by each protein’s probe pair.¹⁰ A further development, called ProteinSeq, pushed this to 35 proteins measured simultaneously from just 5 microliters of blood plasma, achieving better sensitivity than conventional sandwich immunoassays. The researchers noted minimal increases in background as they multiplexed more targets, suggesting higher levels of multiplexing should be feasible.¹¹ For clinical settings where sample volume is limited, such as neonatal blood draws or liquid biopsies, measuring dozens of proteins from a single droplet is a meaningful advantage.

Cancer Research and Clinical Tissue

Cancer biology has been a natural home for PLA, especially for studying receptor dimerization. Many cancer-driving signals depend not just on whether a receptor is present on a cell, but on whether it forms active complexes with other receptors. The HER2 and HER3 receptor pair is a prime example: their dimerization drives resistance to certain hormone therapies and chemotherapy in breast cancer. PLA has been used to detect HER2:HER2 and HER2:HER3 protein complexes at the single-molecule level in clinical breast cancer tissue, successfully demonstrating that these complexes carry prognostic significance.¹²

More recently, researchers developed a microfluidic approach that quantifies HER2-HER3 dimerization at the level of individual circulating tumor cells, the rare cancer cells shed into the bloodstream.¹³ This is a setting where material is extremely limited and conventional protein assays often fall short. PLA’s ability to work on paraffin-embedded clinical specimens, the standard format in pathology archives, also makes it practical for retrospective studies on stored tissue.⁶

Tracking Viral Proteins in Infected Cells

Infectious disease research has increasingly adopted PLA to study how viral proteins interact with host machinery inside cells. In HIV-1 research, for instance, PLA has been used to detect the proximity between the viral Tat protein and its cellular partner p65 inside infected host cells.¹⁴ This is difficult to study by conventional means because the interaction happens at endogenous expression levels in the complex environment of an actual infection.

PLA has also been adapted to visualize where the Ebola virus glycoprotein engages its intracellular receptor. Researchers used proximity ligation to monitor binding between the cleaved viral glycoprotein and the receptor NPC1 inside intact infected cells, providing spatial information about exactly where in the cell the virus latches onto its receptor.¹⁵ The researchers noted the approach could be generalized to other viruses whose receptor interactions have been difficult to study with existing tools.

During the COVID-19 pandemic, an aptamer-based PLA was developed for detecting the SARS-CoV-2 nucleocapsid protein in serum, achieving a limit of detection around 37.5 picograms per milliliter.¹⁶ Using aptamers instead of antibodies as recognition elements can reduce production costs and offers the flexibility to rapidly develop probes against new targets, a useful trait when a novel pathogen emerges.

Single-Cell and Microfluidic Formats

Averaging protein levels across thousands of cells obscures the cell-to-cell variability that drives drug resistance, immune evasion, and other clinically important behaviors. Several groups have pushed PLA into single-cell territory. One automated microfluidic system improved the sensitivity of digital PLA by up to 55-fold compared to standard formats, reaching a detection limit of about 2,277 protein copies per cell and achieving detection efficiency down to as few as 29 protein molecules.¹⁷

Another approach combined PLA with digital PCR on a self-priming microfluidic chip, achieving femtomolar detection limits with a linear dynamic range spanning three to four orders of magnitude. The researchers used it to measure CD147, a biomarker associated with liver cancer, in individual cancer cells and compared the results to a non-cancerous cell line.¹⁸ These formats are still largely in the research-tool phase, but they demonstrate where the technology is heading: precise protein measurements in individual cells, bridging the gap between bulk proteomics and single-cell transcriptomics.

The Quantification Problem

For all its sensitivity, PLA has a significant quantitative limitation that users need to understand. A head-to-head comparison with fluorescence resonance energy transfer (FRET) found that PLA signals saturate at high expression levels of the target proteins. While FRET signals scaled linearly with the amount of bound fluorescent antibody, PLA signals flattened out and could not be brought back into a linear range even by shortening the rolling circle amplification step.¹⁹

The practical consequence is that PLA works best as a detection and localization tool: it tells you that an interaction exists and roughly where it happens. It is less reliable as a ruler for measuring how much of an interaction there is, especially when protein levels are high. The researchers concluded that PLA should be treated as a semiquantitative measure and that caution is warranted when interpreting PLA data in a strictly quantitative way. For experiments where the goal is to compare, say, treated vs. untreated cells at moderate expression levels, PLA’s quantitative performance can still be useful. But if you need precise dose-response curves or absolute quantification at high concentrations, complementary methods may be needed.

False Positives, Background Noise, and Essential Controls

Because PLA amplifies signal so aggressively, even rare nonspecific events can produce visible dots. One recent study examined this problem in detail and found that when both antibody probes are enriched within a confined space, such as inside or around a cell that expresses both target proteins, the likelihood of detecting nonspecific signals increases. Under transient overexpression conditions, this effect becomes especially pronounced. The researchers found that using extracellular tagging strategies and avoiding detergent permeabilization of the cell membrane for membrane protein targets significantly reduced background noise, because it prevented both probes from accumulating inside the cell.²⁰

Proper controls are critical and often underappreciated by new users. Recommended controls include running each primary antibody alone with both PLA probes to confirm the antibody works in this format, running same-species PLA probes (where ligation cannot occur) as a negative control to establish the nonspecific background level, and running no-primary-antibody and no-probe conditions to confirm that signals depend on the intended recognition events.²¹ Skipping these controls is one of the most common mistakes in published PLA experiments and makes it difficult to distinguish genuine interactions from artifacts.

Tissue Fixation and Sample Preparation Artifacts

PLA’s compatibility with formalin-fixed, paraffin-embedded tissue makes it attractive for clinical and pathology applications, but fixation introduces its own complications. The degree of protein crosslinking varies between tissue samples depending on fixation time, fixative concentration, and tissue type, and this variability directly affects antigen retrieval efficiency. Signal intensity can also differ depending on the inflammatory status of the tissue and the abundance of the target antigens, complicating direct comparisons between samples.²²

None of these issues are unique to PLA; any antibody-based assay on fixed tissue faces the same challenges. But because PLA produces discrete countable dots rather than a diffuse stain, inconsistent fixation can turn a clean quantitative readout into a noisy one. Researchers working with clinical archival tissue typically need to optimize antigen retrieval conditions for each tissue type and include same-slide controls to account for batch-to-batch variability in fixation.

Combining PLA With Other Spatial Techniques

One of the more creative recent developments is combining PLA with fluorescence in situ hybridization to detect RNA-protein proximity at specific genomic sites. Researchers used this combination to determine whether repair factors like 53BP1 and TIRR sit near RNA transcribed at DNA double-strand breaks, providing a way to study how RNA molecules influence the DNA damage response in their native spatial context.²³ Another adaptation targeted RNA-protein complexes more broadly, using PLA to detect the proximity between specific RNA-binding proteins and their RNA targets in cell lines.²¹

A further application combined PLA with exosome analysis. Exosomes are tiny vesicles that cells release into body fluids, and their surface proteins carry diagnostic information. One approach used PLA-triggered rolling circle amplification on microchip-captured exosomes to identify specific glycosylation patterns on exosomal proteins, converting glycan levels into absorbance signals that could be quantified.²⁴ These hybrid assays illustrate that PLA’s core proximity-to-DNA-signal logic is modular enough to be plugged into a variety of analytical workflows, extending its reach well beyond traditional immunohistochemistry.