GPSM1 Antibody

What is GPSM1 and what are its primary biological functions?

GPSM1, also known as Activator of G protein signaling 3 (AGS3), functions as a guanine nucleotide dissociation inhibitor (GDI) that modulates heterotrimeric G-protein signaling. It keeps G(i/o) alpha subunits in their GDP-bound form, thus uncoupling heterotrimeric G-proteins signaling from G protein-coupled receptors. GPSM1 plays crucial roles in:

• Controlling spindle orientation and asymmetric cell fate of cerebral cortical progenitors

• Regulating macroautophagy in intestinal cells

• Modulating drug addiction pathways

• Influencing inflammatory responses via macrophage polarization

• Promoting cancer cell proliferation and affecting apoptosis

GPSM1 exhibits strong genetic association with Type 2 diabetes and Body Mass Index in population studies, implicating its role in metabolic regulation .

Which experimental techniques commonly employ GPSM1 antibodies?

GPSM1 antibodies can be utilized in multiple experimental applications:

• Western Blotting (WB): Typically at dilutions of 1:500-1:2000

• Immunohistochemistry (IHC): Optimally at dilutions of 1:50-1:300

• ELISA: Generally used at dilutions of 1:5000-1:10000

• Immunofluorescence (IF): For cellular localization studies

The selection of technique should be guided by your specific research question and experimental model.

What are the key considerations when selecting a GPSM1 antibody?

When selecting a GPSM1 antibody, researchers should consider:

• Target epitope: Antibodies targeting different regions (e.g., AA 1-166, AA 60-300, AA 158-457) may yield different results based on protein conformation and interactions

• Clonality: Both monoclonal and polyclonal antibodies are available; monoclonals offer higher specificity while polyclonals may provide stronger signals

• Host species: Available in rabbit, mouse, and other hosts, which is important for co-localization studies

• Validated applications: Ensure the antibody has been validated for your specific application

• Reactivity: Confirm cross-reactivity with your species of interest (human, mouse, rat)

How should I design experiments to study GPSM1's role in cancer progression?

Based on recent research, effective experimental designs should include:

Cell-based approaches:

• Loss-of-function studies: Use shRNA or siRNA to knockdown GPSM1 in cancer cell lines (e.g., BALL-1 and Reh cells for B-ALL studies)

• Gain-of-function studies: Adenovirus-mediated GPSM1 overexpression to examine effects on proliferation and apoptosis

• Cell viability assays: CCK-8 assays at multiple time points (48h, 72h, 96h) following GPSM1 manipulation

• Apoptosis assessment: Annexin V-PE/7-AAD dual staining followed by flow cytometry

• Cell cycle analysis: PI staining and flow cytometry

In vivo approaches:

• Orthotopic xenograft models using GPSM1-manipulated cancer cells

• Analysis of tumor growth, invasion, and metastasis

• Immunohistochemical analysis of tumor sections for GPSM1 expression

For colorectal cancer research specifically, consider the relationship between GPSM1 expression and immune checkpoint blockade resistance .

What controls should be included when conducting GPSM1 knockdown experiments?

Proper experimental controls are critical for GPSM1 functional studies:

• Negative control siRNA/shRNA (non-targeting sequence)

• Empty vector control for overexpression studies

• Untransfected/untreated cells (blank control)

• Quantification of knockdown efficiency at both mRNA level (by RT-qPCR) and protein level (by Western blot)

• Inclusion of housekeeping genes/proteins (e.g., GAPDH) for normalization

• Time-course analysis to account for temporal changes in expression

In one study, siRNA-mediated knockdown of GPSM1 achieved 48% and 42% reduction at the mRNA level in BALL-1 and Reh cells respectively, with protein interference efficiency of 45% and 60% .

What are the recommended protocols for analyzing GPSM1's impact on downstream signaling pathways?

To analyze GPSM1's effects on downstream signaling:

• For G-protein signaling studies:

  • Analyze cAMP levels as GPSM1 may affect adenylyl cyclase activity

  • Examine Gαi subunit binding through co-immunoprecipitation

  • Assess GDP/GTP binding states of G proteins

• For cancer signaling pathways:

  • Focus on ADCY6-RAPGEF3-JNK signaling axis in B-ALL

  • Measure expression levels of ADCY6 and RAPGEF3 following GPSM1 manipulation

  • Assess JNK phosphorylation status by Western blotting

• For inflammatory pathways:

  • Analyze NF-κB signaling components (phospho-IKKα-IKKβ, IκBα, phospho-P65)

  • Measure nuclear translocation of P65 using nuclear/cytoplasmic fractionation

  • Quantify inflammatory cytokine production (TNF-α, IL-6, CCL2, IL-1β)

How should I interpret discrepancies between GPSM1 expression data from different experimental platforms?

When facing discrepancies in GPSM1 expression data:

• Consider methodological differences:

  • Antibody epitope targets may affect detection efficiency

  • Fixation protocols can influence antibody accessibility

  • Detection methods (colorimetric vs. fluorescent) vary in sensitivity

• Account for biological variables:

  • Cell type-specific expression patterns (e.g., higher in leukemia cell lines compared to control cell lines)

  • Context-dependent regulation (e.g., induction following biological insults)

  • Post-translational modifications affecting epitope recognition

• Validation strategies:

  • Use multiple antibodies targeting different epitopes

  • Complement antibody-based detection with mRNA analysis

  • Perform genetic manipulation (knockdown/overexpression) to verify specificity

What factors might cause variability in GPSM1 detection in tissue samples?

Variability in GPSM1 detection can result from:

How can I resolve weak or inconsistent signals when using GPSM1 antibodies in Western blotting?

To improve GPSM1 detection in Western blotting:

• Sample preparation optimization:

  • Ensure complete lysis using appropriate buffers (containing protease inhibitors)

  • Optimize protein loading (30-50 μg total protein typically works well)

  • Use fresh samples when possible

• Technical adjustments:

  • Try different antibody dilutions (start with manufacturer's recommendation, then 1:500-1:2000)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Test alternative blocking agents (5% BSA often performs better than milk for phospho-epitopes)

  • Increase sensitivity using enhanced chemiluminescence reagents

• Control experiments:

  • Run positive controls (e.g., BALL-1 cell lysate which expresses high GPSM1 levels)

  • Include GPSM1 knockdown samples as negative controls

  • Verify loading consistency with housekeeping proteins like GAPDH

How can GPSM1 antibodies be used to investigate the role of GPSM1 in tumor microenvironment modulation?

Recent research has revealed GPSM1's important role in tumor microenvironment regulation, particularly in:

• Macrophage polarization studies:

  • Use multiplex immunofluorescence with GPSM1 antibodies alongside macrophage markers (CD68, CD163)

  • Analyze co-localization of GPSM1 with M1 vs. M2 macrophage markers

  • Quantify GPSM1 expression in tumor-associated macrophages vs. cancer cells

  • Assess correlation between GPSM1 levels and macrophage infiltration

• Immunosuppressive mechanisms:

  • Investigate how GPSM1 expression correlates with immune checkpoint molecule expression

  • Study GPSM1's relationship to anti-PD-1 therapy resistance

  • Examine GPSM1's role in macrophage colony-stimulating factor expression

• In vitro co-culture systems:

  • Establish tumor cell-macrophage co-cultures with GPSM1-manipulated cells

  • Use flow cytometry and mass cytometry to analyze cellular phenotypes

  • Monitor cytokine/chemokine profiles using Luminex or ELISA

What approaches can be used to study GPSM1's interaction with G-protein signaling components?

To investigate GPSM1's interactions with G-protein signaling:

• Protein-protein interaction studies:

  • Co-immunoprecipitation of GPSM1 with Gα subunits (particularly Gαi/o)

  • Proximity ligation assays to visualize interactions in situ

  • FRET/BRET approaches for real-time interaction monitoring

• Functional analyses:

  • Measure G-protein activation using GTP-binding assays

  • Assess downstream cAMP levels and PKA activity

  • Examine CREB phosphorylation and nuclear translocation

  • Analyze calcium signaling pathways, as GSEA studies suggest GPSM1 positively correlates with calcium signaling

• Structural considerations:

  • Focus on GPSM1's guanine nucleotide dissociation inhibitor (GDI) activity

  • Study how GPSM1 influences GDP/GTP exchange on Gα subunits

  • Investigate the competition between GPSM1 GPR motifs and other Gα-interacting proteins

What experimental designs can elucidate GPSM1's role in metabolic disorders?

To investigate GPSM1's role in metabolic regulation:

• Animal models:

  • Use myeloid-specific GPSM1 knockout mice (e.g., GPSM1 f/f; Lyz2-Cre)

  • Challenge with high-fat diet to induce metabolic dysfunction

  • Assess glucose tolerance, insulin sensitivity, and lipid profiles

  • Analyze liver steatosis and adipose tissue inflammation

• Mechanistic investigations:

  • Study GPSM1's effect on the Gαi3/cAMP/PKA/CREB signaling axis

  • Examine how GPSM1 influences TNFAIP3 transcription

  • Analyze NF-κB signaling in response to metabolic stimuli (e.g., palmitic acid)

  • Investigate links between GPSM1 and TLR4-induced inflammatory responses

• Translational approaches:

  • Measure GPSM1 expression in visceral fat from individuals with obesity

  • Correlate expression levels with clinical metabolic parameters

  • Explore small molecule inhibitors (e.g., AN-465/42243987) that modify GPSM1 function

What techniques can reveal the regulatory mechanisms controlling GPSM1 protein stability and function?

To investigate GPSM1 regulation:

• Post-translational modification studies:

  • Analyze GPSM1 ubiquitination status (particularly K63-polyubiquitination)

  • Investigate the role of deubiquitinases (e.g., USP9X) in preventing GPSM1 degradation

  • Examine phosphorylation sites that might affect protein stability or function

• Transcriptional regulation:

  • Use ChIP-PCR to identify transcription factors regulating GPSM1 expression

  • Study how GPSM1 influences MEIS3 nuclear translocation

  • Analyze promoter activity under different cellular conditions

• Protein-protein interaction network:

  • Employ mass spectrometry to identify novel GPSM1 interactors

  • Use co-immunoprecipitation to verify specific interactions

  • Create domain mutants to map critical interaction interfaces

These methodologies have revealed that GPSM1 stability is regulated by deubiquitination via USP9X, and that stabilized GPSM1 can promote MEIS3 nuclear translocation, activating macrophage colony-stimulating factor expression .

How can GPSM1 be targeted therapeutically in cancer and metabolic diseases?

Emerging research suggests several approaches for therapeutic targeting of GPSM1:

• In cancer therapy:

  • Ruxolitinib has emerged as a promising GPSM1-targeting candidate for colorectal cancer

  • Combination therapy with immune checkpoint inhibitors (anti-PD-1) shows improved efficacy

  • This approach works in both microsatellite instability-high and microsatellite stable CRC models

• For metabolic disorders:

  • Small-molecule compound AN-465/42243987 suppresses pro-inflammatory phenotypes by inhibiting GPSM1 function

  • Targeting the GPSM1-mediated Gαi3/cAMP/PKA/CREB axis may provide therapeutic benefits

  • Modulation of GPSM1 in myeloid cells could reduce metabolic inflammation

• Target validation approaches:

  • Genetic validation using conditional knockout models

  • Pharmacological inhibition with structure-based designed compounds

  • PROTAC-based approaches for targeted GPSM1 degradation

What are the most reliable methods for quantifying changes in GPSM1 expression and activity?

For accurate quantification of GPSM1:

• Expression analysis:

  • RT-qPCR for mRNA quantification (normalize to stable reference genes like GAPDH)

  • Western blotting with densitometry (45-60% protein reduction observed with effective knockdown)

  • Flow cytometry for cellular level quantification

  • Digital PCR for absolute quantification

• Activity assessment:

  • Functional readouts of downstream pathways (ADCY6-RAPGEF3-JNK signaling)

  • Measurement of G-protein dissociation via BRET-based biosensors

  • Assessment of second messenger production (cAMP, calcium flux)

  • Quantification of target gene expression

• Clinical correlation:

  • Use ROC analysis to determine diagnostic value (AUC values above 0.5 indicate discrimination ability)

  • Survival analysis comparing high vs. low GPSM1 expression groups

  • Multivariate analysis to control for confounding factors