Pixelgen Technologies is a life science tools company founded in 2020 by serial entrepreneurs behind multiple innovative products and companies in the life sciences and located in Stockholm, Sweden.

The Pixelgen Single Cell Spatial Proteomics Kit price can be found in our webshop (link).

You can place an order directly on our website (https://shop.pixelgen.com/) or email hello@pixelgen.com and we will contact you.

The name of our technology is Molecular Pixelation (MPX™) and it is currently applied to deeply phenotype immune cells by building spatial 3D maps of the cell surface proteins in a highly multiplexed and low resolution manner.

The name of our product is Pixelgen Single Cell Spatial Proteomics Kit, Immunology Panel 1, Human (Pixelgen SCSP Kit).

Other technologies that detect protein expression on a single cell will not offer multiplex spatial relationships between the proteins on the cell surface, for up to 1000 cells in parallel per sample. MPX is unique by offering relative abundance data, co-localization data of protein pairs and polarity data of each protein, for every single cell. Up to 1000 cells per reaction can be assessed, generating up to 3 million data points per sample.

There are three boxes that come with the kit, one box for +4C storage and two boxes for -20C storage.

The kits have a 6 months shelf-life from production date.
Please store the different components at their recommended temperatures, as specified in the kit documentation.

The kit is enough for running 8 reactions in parallel, with 300 – 1000 cells output per reaction.

The Countess™ II Automated Cell Counter (ThermoFisher) has been used during validation and optimization of MPX™.

Hemocytometers and single-use counting hemocytometers have been used during validation and optimization of MPX™.

Yes, the protocol contains many stopping points to offer flexibility, as noted in the protocol.

If you intend to run the protocol consecutively from live cells to sequence-ready library, we recommend planning for 3 days.

If you intend to fix live cells and then freeze for -80C storage for up to 3 months, we recommend 2 hours for fixing and freezing, and then 2 days for running the remainder of the protocol, including thawing of fixed cells.

A suggested workflow would be to perform fixation and AOC binding day 1, perform pixelation steps on day 2 and finally quality control and NGS on day 3.

If there is a need to use other PCR primers than the ones supplied with the kit, please contact support for guidance.

Yes – The workflow has been validated on frozen fixed cells as well as on frozen live cells.

MPX requires 500 000 – 1 000 000 live cells as input.

There are two types of controls in the AOC panel. The first part consists of mouse isotype control antibodies (mIgG1, mIgG2a, mIgG2b) that can be  used to set non-specific binding levels. The other part contains an intracellular marker to validate that the cell membrane is intact and not permeabilized.

It is always recommended to include a control sample in the experimental design. The kind of control sample depends on the experiment but each sample condition should have a control for comparison and differential analysis.

We recommend PBMCs or isolated immune cells. The panel contains targets for T-cells, B-cells, NK cells and monocytes.

No, this is not recommended. The antibodies have been validated with the fixation protocol that is in the MPX User Manual and other fixation protocols might impact the antibody binding negatively and should therefore not be used.

Antibody Oligonucleotide Conjugate

The AOC panel in MPX consists of monoclonal antibodies.

The panel included in the kit is fixed with targets that have been extensively validated.

We do have a target wish list where we are more than happy to receive your feedback, please fill in the form here

The product we offer at this time contains a fixed panel, The Immunology Panel I, Human.

We are open to discussing your interest in different targets for potential future panels, Please fill in the form in the link and we will add your suggestions to our wish list.

We have a target wish list where we are more than happy to receive your feedback, please fill in the form link.

Please find the complete list of targets here.

The Pixelgen® Single Cell Spatial Proteomics panel is focused on immunology, targeting 80 validated and exploratory surface protein assays that have been carefully selected in collaboration with leading experts in the field. The panel was designed to cover a variety of immune cell types including targets for cell activation, cell adhesion, cell-cell communication, etc.

The specificity of each antibody was first validated prior to conjugation using flow cytometry on PFA-fixed cells, and the specificity of each AOC was validated using MPX.

We recommend PBMCs or isolated immune cells. The panel contains targets for T-cells, B-cells, NK cells and monocytes.

No, our antibodies have been validated for use with PFA fixed cells in suspension only.

The DNA barcode is unique to the antibody type, whereas the UMI is unique for each conjugate oligonucleotide molecule. For example, 5 different anti-CD3 antibodies will all have the CD3 barcode, but unique UMIs.

The UMI stands for Unique Molecular Identifier and is used to identify the oligonucleotide conjugated to the antibody. The UPI stands for Unique Pixel Identifier and is used to identify the pixel.  

There is a pool of different A pixels, where each A pixel has a Unique Pixel Identifier A (UPI-A). Each A pixel is a rolling circle amplification product and will have several repeats of its UPI-A, but UPI-As between A pixels differ. The same stands for B pixels and UPI-Bs.

As this is performed in a standard PCR tube format in bulk, partitioning is performed by the unique properties of the Molecular Pixelation assay itself.

Each pixel will typically bind 5 – 10 antibody molecules, which will all incorporate the same UPI.

Each cell will typically be divided into 500 – 1500 pixels or spatial zones for unstimulated PBMCs. This may vary depending on sample type, condition and cell size.

The Pixelator software is compatible with 300 – 1000 cells output per reaction.

The DNA-pixels are <100 nm in size, as measured by scanning electron microscopy.

Yes relative abundance, within the same run and same target. The abundance capabilities are on par with flow cytometry.

It is dependent on the antibody clone and equivalent to flow cytometry for PFA fixed cells.

Specificity is equivalent to flow cytometry for PFA fixed cells.

There is no need for additional instruments other than available in a standard cell/molecular lab. For complete lists of required equipment and consumables for Pixelgen SCSP Kit, please contact Pixelgen Scientific Application Support.

We recommend 120 000 reads per cell (which includes reads for PhiX).

Since there are regions of low diversity in the reads, 15% PhiX is required.

Any pair format can be used as long as read1 is >= 28 cycles and read2 >= 66 cycles. Single end sequencing needs to be >132 bp (e.g. 150 SE).

NextSeq2000 and NovaSeq6000 sequencing

The Pixelator software is compatible with 300 – 1000 cells output per reaction

Please find recommendations here: https://software.pixelgen.com/pixelator/usage/requirements and here:

https://software.pixelgen.com/nf-core-pixelator/getting-started/requirements

The NGS FASTQ files are imported to Pixelgen’s open source software Pixelator, undergoing several steps of quality control and analysis. The read sequences from the Unique Molecular Identifier (UMI), the antibody barcode on the AOC, and the Unique Pixel Identifier A (UPI-A) and Unique Pixel Identifier B (UPI-B) of the amplicon, are used to produce a graph, ultimately generating a network of protein connections. Each graph is a reconstruction of the surface of a cell. https://software.pixelgen.com/common/what-is-mpx.

To run Pixelator you need to be familiar with working on the command line.

You need to be familiar with a programming language for data analysis such as Python or R. A basic understanding of analyzing single-cell data can be helpful but not mandatory.

Pixelator will generate absolute and centered log-ratio (CLR) abundance data for each marker in the panel for every single cell, a polarity score for each marker in the panel for every single cell as well as colocalization score for each marker pair in the panel for every single cell. You will therefore get both abundance data as well as spatial metrics.

Pixelator returns two main outputs: a Web Report with quality control summaries and plots, and a .pxl file for downstream data analysis. https://software.pixelgen.com/pixelator/outputs/.

The .pxl file contains a number of elements that can be used for downstream analysis

• Adata: AnnData file containing the cell by cell count data, similarly to other single cell omics techniques
• Polarization – a table containing the spatial protein polarity scores per each detected cell.
• Colocalization – a table containing the spatial protein-protein colocalization scores per each detected cell.
• Edgelist – A table containing the edgelist; a list of edges in the graph components which each correspond to a cell. This file is used to visualize individual cells, and has been used to calculate spatial statistics like polarization scores and colocalization scores.
• Metadata is a file with information about the Pixelator run
  

For more information, check our software page about the .pxl file (https://software.pixelgen.com/pixelator/outputs/pxl-file/)

The polarity score of a marker will tell you if the spatial distribution of that marker is non-random, as well as how non-random it is. The more polarized a marker is in a cell, the higher the polarity score. For more details, please see link.

The co-localization score of two markers will tell you if the two markers appear at the same locations more often than expected by random chance, as well as how co-localized they are. The more co-localized two markers are in a cell, the higher the co-localization score. For more details, please see link.

One of the tutorials is aimed for 2D cell visualization, see link.

Example code for 3D visualization can be found in Advanced Topics, see link.

Yes. Please see link.

Yes. Please see link.

Yes. Please see link.

We recommend that you run Pixelator through our nf-core/pixelator. For more information, please visit link.

We have tutorials based on both R and Python.

It is compatible with Python versions from 3.8 to 3.10.

R version v4.3.1+.

A component is a reconstruction of a cell, in a graph format consisting of nodes and edges.