Spatial Technologies Unit

The Spatial Technologies Unit (STU) at BIDMC is a production-grade facility supporting DF/HCC investigators in cutting-edge spatial tissue profiling and single-cell studies—often from the same tissue block. The STU operates across a wide range of projects, including basic science, translational research, clinical trials (correlative and endpoint studies), and industry-sponsored investigations. It also serves as a core facility for programmatic grants (e.g., U54, P01).

Established with a four-part mandate, the STU:

• Provides full-service support (from tissue to complete data analysis) using the latest spatial transcriptomic and proteomic technologies
• Offers hands-on training and education in experimental design, grant writing, and data analysis
• Develops and pilots new spatial assays and technologies
• Enables spatial tissue profiling assays to reach patient care

Key Services

By colocalizing spatial technologies with comprehensive supportive infrastructure (NGS, tissue processing, imaging, bioinformatics) the STU can provide A-Z spatial and single cell services, enabling DF/HCC researchers to focus on science and discovery. For all services the STU can provide tissue processing (sectioning, slide loading), data generation (assay, imaging/sequencing), data processing, and complete data analysis.

Imaging – Based Spatial Transcriptomics

These technologies enable the quantification of large numbers of genes at single cell and single molecule resolution

• 10x Genomics Xenium – from a few hundred genes to 5,100 genes. Support modules, partially custom or full custom panels. RNA + Protein support.

• Vizgen MERSCOPE – up to 1,000 genes quantified as single cell and single molecule resolution. Supports full custom panels. RNA + Protein support.

Spatial Sequencing

Spatial sequencing technologies perform similarly to imaging-based spatial transcriptomics, while enabling very high throughput, short turnaround time, and low cost per sample. 

• Singular Genomics G4X – up to 500 genes at single cell and single molecule resolution. Supports modules, partially custom or full custom target panels. RNA + Protein support + TCR/BCR in situ.

Sequencing-based Spatial Transcriptomics

Sequencing-based spatial transcriptomics goes beyond gene panels, enabling whole transcriptome applications in situ.

• 10x Genomics Visium HD, direct placement (v1), and v2 – whole transcriptome investigations at 2um (single cell) or 55um resolution. RNA + Protein support.
• Bruker / NanoString GeoMx DSP – whole transcriptome or 570+ antibodies quantified at regions of interest across a whole pathology slide. RNA + Protein support.

Spatial Proteomics

Assays based on multiplexed immunofluorescence enable the quantification of small or large numbers of proteins at single cell resolution. All assays provided by the STU use technologies where the sample is stained once (not cyclic staining/bleaching), preserving the sample integrity and providing high quality data from the first to the last marker. 

• Akoya PhenoImager HT – quantification of up to 9 markers at single cell resolution. Protein + RNA support.
• Akoya PhenoCycler and PhenoCycler Fusion – quantification of up to 100 antibodies at single cell resolution. Protein + RNA support.
• Slide Auto-Staining – The STU can automate the staining for both provided assays using its Leica Bond Rx or the OT-2 robotic platform, providing high data quality and reproducibility, especially useful for clinical trials or large scale/multi-part projects.

Super Resolution Microscopy

• Bruker Vutara VXL - enabling super resolution (STORM) using multiple channels capturing protein, RNA or chromatin targets.

Single Cell 

The STU supports all 10x Genomics single cell assays on FFPE, fresh, or frozen samples. With the 10x Genomics Chromium Connect robotics platform and the 10x Genomics Chromium X controller, the latest technologies can be performed manually, partially, or fully automated at scale.

• Tissue dissociation and generation of single cell or single nucleus suspensions
• snPathoSeq Single nucleus RNAseq of FFPE samples with data quality comparable to frozen tissue (Wang, et al, Nature / Communications Biology 2024). 
• Single cell/nucleus RNAseq using 10x Genomics 3’, 5’ or Flex Assays
• Single cell immunoprofiling (gene expression + TCR/BCR sequencing per cell) 
• CITE-Seq (concurrent gene expression + surface protein abundance using barcoded antibodies + (optional) TCR/BCR)
• High throughput antigen validation (gene expression + TCR/BCR + barcoded dextramer studies)

Additional Services

• Tissue Microarray generation using the Epredia Grand Master in order to reduce cost per sample. Punch biopsies can also be exported in parallel for bulk RNAseq or single cell apart from the TMA spatial interrogation.
• Whole slide scanning (20x, 40x) using brightfield or fluorescence (9 different channels)

Training and Education

The STU can support seminars and lectures on single cell/spatial technologies as well as their applications in specific domains.

• Seminars & Lectures: Topical talks for researchers and clinicians
• Workshops: Technology-specific sessions, remote or in-person
• Hands-on Training: Instrument use and protocol walkthroughs
• Grant Writing / Strategic Advisory: High-level support in grant strategy, IP, and leadership for investigators and stakeholders.

Bioinformatics and Single Cell/Spatial Data Analysis

The STU specializes in the analysis and integration of single cell and spatial tissue profiling data. All assays and modalities provided by the STU are also supported for data analysis. Services include:

• Data pre-processing (already included for most assays)
• Downstream data analyses, including UMAP generation, clustering, annotation (in silico and manual), group comparisons (abundance, expression), spatial neighborhoods, cell-cell communication (single cell or in situ), functional analyses
• Figure generation for manuscripts/grants
• Grant writing / manuscript writing support

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PUBLICATION ACKNOWLEDGEMENT:

If research supported by this core facility results in publication, please acknowledge this support by including the following in your publication(s):
"We thank Dana-Farber/Harvard Cancer Center in Boston, MA, for the use of the Spatial Technologies Unit (RRID:SCR_024905), which provided __________ service. Dana-Farber/Harvard Cancer Center is supported in part by an NCI Cancer Center Support Grant # NIH 5 P30 CA06516."