In situ PLA principle
Two primary antibodies raised in different species recognize the target
antigen or antigens of interest. Species-specific secondary antibodies,
called PLA probes, each with a unique short DNA strand attached to it,
bind to the primary antibodies. When the PLA probes are in close
proximity (<40 nm), the DNA strands can interact through a subsequent addition of
two other circle-forming DNA oligonucleotides. After joining of the two added oligonucleotides by enzymatic ligation,
they are amplified via rolling circle amplification using a polymerase. After the amplification reaction, several-hundredfold replication of the DNA
circle has occurred, and labeled complementary oligonucleotide probes highlight the product. The resulting high concentration of fluorescence
in each single-molecule amplification product is easily visible as a distinct bright dot when viewed with a fluorescence microscope.

View in situ PLA technology animation
Unmodified cells
In situ PLA can be used on unmodified cells and tissues. The
PLA technology works on fresh, frozen and FFPE tissue. Other methods
such as BRET, FRET and BiFC act on genetically modified cells with
usually overexpressed fusion protein complexes.
Dual recognition
In situ PLA technology requires positive identification of two
different epitopes on the same protein or complex, resulting
in profoundly enhanced specificity over assays that depend on single
binding recognition.
DNA amplification
In situ PLA technology couples recognition to the possibility to amplify the signal by generating a DNA surrogate of the protein.
Localization of the signal
In situ PLA technology generates a localized, discrete signal
which is anchored to one of the proximity probes, thereby revealing the
exact position of the event.
Digital counting
In situ PLA technology provides an objective means of
quantifying and comparing events among different cells, tissues and
treatments, which can be automated for screening purposes.

In situ PLA shows the exact location of events in intact cells and facilitates quantification and automation of image analysis.