CD90 Thy-1.1 Antibody

Basic Research Questions

• What is CD90 (Thy-1) and how is it distributed across different tissues?

  CD90, also known as Thy-1, is a 25-35 kDa GPI-anchored glycoprotein belonging to the immunoglobulin superfamily. It plays crucial roles in cell-cell interactions, adhesion, and signal transduction. In mice, CD90 shows differential expression between strains, with CD90.1 (Thy-1.1) specifically expressed in PL and AKR mouse strains. The protein is found on hematopoietic stem cells, thymocytes, mature T cells, neural cells, and numerous other cell types . Studies have demonstrated its presence in mesangial cells of the kidney, medullary cells of the adrenal gland, lymphocytes of the thymus and spleen, as well as neural tissues including somas, dendrites, and axons . This wide distribution makes CD90 a valuable marker for multiple research fields including immunology, neurobiology, and stem cell biology.

• What are the key differences between CD90.1 (Thy-1.1) and CD90.2 (Thy-1.2) allelic variants?

  Mice possess two allelic variants of the CD90 protein: Thy-1.1 (CD90.1) and Thy-1.2 (CD90.2). These variants differ by only one amino acid , yet this difference is sufficient to allow for specific antibody recognition. The Thy-1.1 variant is predominantly found in PL and AKR mouse strains, while Thy-1.2 is expressed in most common laboratory mouse strains . This allelic difference is particularly valuable for transplantation studies, adoptive transfer experiments, and lineage tracing, as it allows researchers to distinguish donor cells from recipient cells when using congenic mouse strains. When designing experiments, researchers must carefully select antibodies specific to the correct allelic variant to ensure accurate detection and prevent false negative results.

• What applications are anti-CD90.1 antibodies most commonly used for in immunological research?

  Anti-CD90.1 antibodies serve multiple research purposes with distinct methodological requirements:

  Application	Common Clones	Optimal Formats	Key Considerations
  Flow Cytometry	HIS51, OX-7, 19E12	Fluorochrome-conjugated	Use ≤0.06 μg per test in 100 μL volume
  Immunohistochemistry	OX-7	Purified or biotinylated	PLP-AMeX tissue processing method recommended
  In Vivo Depletion	OX-7	Low endotoxin preparations	Requires careful dosing optimization
  T Cell Activation	Various	Cross-linking formats	Can provide both TCR-independent activation and costimulation
  Cell Sorting	HIS51, OX-7	Bright fluorochromes (PE, APC)	Cell numbers can range from 10^5 to 10^8 cells/test

  Each application requires specific antibody preparations and concentration optimization to achieve reliable results.

• How should researchers optimize anti-CD90.1 antibody concentration for flow cytometry?

  Optimizing anti-CD90.1 antibody concentration for flow cytometry requires systematic titration to achieve optimal signal-to-noise ratio while minimizing reagent usage. Begin by preparing single-cell suspensions from Thy-1.1-positive tissues such as thymocytes or splenocytes from appropriate mouse strains. Create a serial dilution series of the antibody and stain equal cell numbers (typically 10^5-10^6) with each concentration. Based on published protocols, the HIS51 clone can be used at concentrations of ≤0.06 μg per test, where a test is defined as the amount needed to stain cells in a 100 μL volume .

  Cell numbers should be determined empirically but can range from 10^5 to 10^8 cells per test. Always include appropriate controls (unstained, isotype, and negative biological controls) and analyze results by evaluating both the percentage of positive cells and the separation between positive and negative populations. The optimal concentration provides clear separation without excessive antibody consumption, allowing for reproducible and cost-effective experiments.

• What controls are essential when using anti-CD90.1 antibodies in experimental systems?

  Rigorous controls are critical for ensuring the reliability and specificity of anti-CD90.1 antibody experiments:

  • Isotype controls: Use antibodies matching the isotype (e.g., Mouse IgG2a,κ for 19E12 or IgG1 for OX-7), host species, and conjugated fluorochrome to assess non-specific binding .

  • Negative biological controls: Include samples from CD90.2-expressing mice (e.g., C57BL/6) or CD90-negative cell lines to confirm specificity.

  • Positive biological controls: Use known CD90.1-expressing samples such as thymocytes from PL or AKR mice .

  • For flow cytometry: Include fluorescence minus one (FMO) controls to properly set gates and compensate for spectral overlap.

  • For in vivo studies: Include both untreated animals and isotype control antibody-treated groups to distinguish specific from non-specific effects.

  These controls help identify false positives, confirm binding specificity, and ensure experimental rigor and reproducibility.

Advanced Research Questions

• How can CD90.1 be effectively employed as a congenic marker in adoptive transfer experiments?

  CD90.1 (Thy-1.1) provides an excellent congenic marker system for tracking cells in adoptive transfer experiments due to the allelic differences between mouse strains. This approach requires careful experimental design and specialized methods:

  Experimental workflow:

  1. Isolate CD90.1-positive cells from donor mice (e.g., B6.PL-Thy1a/CyJ which express CD90.1 on a C57BL/6 background)

  2. Transfer into CD90.2-positive recipient mice (standard C57BL/6)

  3. Analyze recipient tissues using anti-CD90.1 antibodies to specifically identify donor-derived cells

  To maximize sensitivity, perform preliminary spike-in experiments to determine detection limits by mixing known numbers of CD90.1+ cells with CD90.2+ cells. Consider combining CD90.1 staining with other phenotypic markers to track differentiation or activation status of transferred populations. This system allows for elegant lineage tracing experiments without requiring genetic manipulation or cell labeling, enabling studies of cell migration, differentiation, and function in complex in vivo environments .

• What mechanisms underlie the dual signaling capacity of CD90 in T cell activation?

  CD90 exhibits a remarkable dual signaling capacity in T cells that distinguishes it from conventional surface markers. Research has demonstrated that CD90 cross-linking can both substitute for TCR signaling under certain conditions and provide potent costimulation during antigen-specific T cell activation .

  This dual capacity involves several molecular mechanisms:

  • GPI-anchor localization: CD90's GPI anchor facilitates its concentration in lipid rafts, organizing signaling molecules spatially

  • Src-family kinase recruitment: CD90 clustering activates protein tyrosine kinases involved in T cell signaling

  • Calcium flux modulation: CD90 engagement influences intracellular calcium mobilization patterns

  Experimental approaches to investigate these mechanisms include:

  1. Phosphorylation analysis of signaling intermediates following CD90 cross-linking

  2. Lipid raft disruption studies using cholesterol-depleting agents

  3. Combinatorial stimulation assays with variable CD28 co-engagement

  Understanding this dual signaling capacity has important implications for T cell homeostasis in the absence of antigen stimulation and could inform the development of novel immunotherapeutic approaches .

• How does anti-Thy-1 antibody-mediated complement-dependent cytotoxicity differ across tissues?

  Anti-Thy-1 antibody-mediated complement-dependent cytotoxicity (CDC) shows striking tissue selectivity that cannot be explained by Thy-1 expression patterns alone. Research has revealed that despite expressing Thy-1.1, different tissues show variable susceptibility to CDC:

  Tissue	Thy-1.1 Expression	CDC Sensitivity	Mechanism
  Kidney mesangial cells	Positive	High	Low expression of complement regulatory proteins (Crry, CD55)
  Adrenal medullary cells	Positive	Low	High expression of protective Crry and CD55
  Thymic lymphocytes	Positive	Low	High expression of protective Crry and CD55

  This differential sensitivity forms the basis of the anti-Thy-1 nephritis model, where selective damage to kidney mesangial cells occurs despite the broader expression of Thy-1. The protection mechanism involves membrane complement regulatory proteins (mCRPs), particularly Crry and CD55, which inhibit various stages of the complement cascade. Researchers can exploit or mitigate this tissue selectivity by manipulating complement activation or mCRP expression, allowing for targeted therapeutic approaches .

• What experimental approaches can resolve contradictions in CD90.1's reported functions across different tissues?

  CD90.1's diverse expression patterns and apparently contradictory functions across tissues require sophisticated experimental approaches to resolve:

  1. Tissue-specific conditional knockout systems:

     • Generate floxed CD90.1 mice crossed with tissue-specific Cre lines

     • Compare phenotypes across different conditional knockouts to isolate tissue-specific functions

  2. Domain-specific antibody blocking:

     • Develop antibodies targeting different epitopes of CD90.1

     • Compare functional outcomes when blocking different structural domains

  3. In situ interaction studies:

     • Employ proximity ligation assays to identify tissue-specific binding partners

     • Use FRET/FLIM techniques to visualize molecular interactions in living tissues

  4. Single-cell multi-omics approaches:

     • Combine transcriptomics, proteomics, and epigenetics at single-cell resolution

     • Identify tissue-specific molecular signatures associated with CD90.1 function

  These approaches can help reconcile seemingly contradictory roles of CD90.1 in T cell activation, neural development, and fibroblast function by revealing context-dependent molecular interactions and signaling pathways .

• How can anti-CD90.1 antibodies be optimized for in vivo depletion studies?

  In vivo depletion using anti-CD90.1 antibodies requires careful optimization to achieve effective and specific elimination of target cells:

  Critical parameters for optimization:

  1. Antibody selection: Use low-endotoxin, azide-free preparations specifically designated for in vivo use, such as the OX-7 clone . The antibody should be purified to high homogeneity and tested for sterility.

  2. Dosing strategy: Conduct dose-response experiments, typically starting with 100-500 μg per mouse. Monitor depletion kinetics to establish appropriate experimental timeframes and determine whether multiple injections are needed.

  3. Administration route options:

     • Intraperitoneal: Most common, suitable for systemic depletion

     • Intravenous: Faster distribution but higher risk of adverse reactions

     • Local administration: For site-specific depletion studies

  4. Verification methods:

     • Flow cytometric analysis of blood and tissues to assess depletion efficiency

     • Functional assays to confirm biological effect

     • Tissue histology to evaluate organ-specific depletion

  5. Potential complications and solutions:

     • Complement consumption: Space injections to allow complement regeneration

     • Anti-antibody responses: Use same-species derived antibodies

     • Non-specific inflammation: Monitor cytokine profiles

  This approach is particularly valuable for selectively depleting CD90.1+ donor cells in congenic transfer systems without affecting host CD90.2+ cells, allowing for elegant lineage ablation studies .

• What are the best practices for using anti-CD90.1 antibodies in multiparameter flow cytometry?

  Multiparameter flow cytometry with anti-CD90.1 antibodies requires careful panel design and optimization:

  1. Panel design considerations:

     • Fluorochrome selection: The HIS51 clone conjugated to APC has an excitation range of 633-647 nm and emission at 660 nm, making it compatible with red lasers

     • Brightness matching: Pair CD90.1 antibody brightness with antigen density

     • Spectral overlap minimization: Position CD90.1 to avoid spillover with critical markers

  2. Staining protocol optimization:

     • Buffer selection: Use buffers containing protein (BSA or FBS) and sodium azide

     • Incubation conditions: Stain at 4°C for 30 minutes, protected from light

     • Washing steps: Include sufficient washing to reduce background

  3. Control strategies:

     • FMO controls: Include CD90.1-FMO to set accurate gates

     • Compensation controls: Single-stained controls for each fluorochrome

     • Doublet discrimination: Critical when analyzing tissues with potential cell clumping

  4. Data analysis approaches:

     • Sequential gating: Begin with FSC/SSC to identify cells, then exclude debris and doublets

     • Visualization techniques: Consider visualization tools like t-SNE or UMAP for high-parameter data

     • Statistical validation: Employ appropriate statistical tests based on experimental design

  Following these practices ensures optimal resolution of CD90.1-positive populations in complex samples and maximizes data quality .

• How does CD90.1's role in T cell signaling compare to its function in neuronal tissues?

  CD90.1 exhibits context-dependent functions that vary significantly between immune and neuronal tissues:

  Feature	T Cell Function	Neuronal Function
  Signaling Partners	Associates with TCR/CD3 complex, Lck, Fyn	Interacts with integrins, L1, F3/contactin
  Functional Role	T cell activation, costimulation	Neurite outgrowth, synaptogenesis
  Cellular Location	Concentrated in immunological synapses	Present in growth cones and synapses
  Signaling Pathways	Activates MAP kinases, calcium mobilization	Regulates Src-family kinases, RhoA
  Response to Cross-linking	Cell activation, proliferation	Growth cone collapse, neurite retraction

  The molecular basis for these tissue-specific functions likely involves:

  1. Differential glycosylation patterns between cell types affecting binding properties

  2. Tissue-specific binding partners that modify downstream signaling

  3. Different lipid raft compositions altering signaling complex formation

  4. Developmentally regulated expression patterns

  Experimental approaches to compare these functions include cross-tissue adoptive transfers, domain swapping experiments, and comparative proteomics of CD90.1-associated complexes in different tissues .