SGMS1 Antibody, Biotin conjugated

What is SGMS1 and why is it significant in research?

SGMS1 (Sphingomyelin Synthase 1) is a bidirectional lipid cholinephosphotransferase that plays a crucial role in sphingolipid metabolism. It catalyzes the conversion of phosphatidylcholine (PC) and ceramide to sphingomyelin (SM) and diacylglycerol (DAG), as well as the inverse reaction. The directionality depends on the relative concentrations of DAG and ceramide as phosphocholine acceptors. SGMS1 has gained research significance due to its role in cellular membrane composition, signal transduction pathways, and its potential implications in various pathological conditions. Recent research has identified SGMS1 as a novel direct target of GATA1 and TAL1 transcription factors, with high SGMS1 levels associated with cell cycle regulation through the G2/M checkpoint in certain cell types .

What is the advantage of using biotin-conjugated SGMS1 antibodies compared to unconjugated versions?

Biotin-conjugated SGMS1 antibodies offer several methodological advantages over unconjugated antibodies. The biotin-streptavidin system provides one of the strongest non-covalent biological interactions known, enabling enhanced sensitivity in detection systems. This conjugation allows for amplification of signal through secondary detection with streptavidin conjugated to various reporter molecules (e.g., HRP, fluorophores). Additionally, biotin-conjugated antibodies eliminate the need for species-specific secondary antibodies, reducing background issues in multi-labeling experiments. They are particularly valuable in techniques requiring increased sensitivity such as immunohistochemistry of tissues with low SGMS1 expression or when performing multiplexed immunoassays where signal enhancement is crucial .

Which cell types and tissues predominantly express SGMS1?

SGMS1 expression has been documented across various tissues, with notable presence in brain, heart, kidney, liver, muscle, and stomach. When designing experiments, researchers should consider tissue-specific expression levels for proper controls and interpretation. At the subcellular level, SGMS1 localizes primarily to the Golgi apparatus membrane as a multi-pass membrane protein, which has implications for experimental design in subcellular fractionation studies. Expression patterns can vary under different physiological and pathological conditions, particularly in malignancies where SGMS1 has been associated with GATA1-positive erythroleukemic Acute Myeloid Leukemia cells .

What are the optimal applications for biotin-conjugated SGMS1 antibodies?

Biotin-conjugated SGMS1 antibodies excel in several experimental applications where signal amplification is beneficial. The primary applications include:

The biotin conjugation is particularly advantageous for techniques requiring signal amplification and in multiplex detection systems where secondary antibody cross-reactivity must be minimized .

How can I validate the specificity of SGMS1 antibodies in my experimental system?

Validating antibody specificity is critical for generating reliable research data. For SGMS1 antibodies, employ these methodological approaches:

• Positive and negative control samples: Use tissues/cells known to express SGMS1 (brain, heart, kidney, liver) versus those with minimal expression.

• siRNA/shRNA knockdown: Compare SGMS1 detection in control versus knockdown samples (as demonstrated in the ENCODE project with TAL1 siRNA).

• Recombinant protein competition: Pre-incubate antibody with recombinant SGMS1 protein (particularly the immunogen sequence, e.g., AA 48-137 for relevant antibodies).

• Western blot analysis: Verify presence of a single band at the expected molecular weight (~42 kDa for SGMS1).

• Multiple antibody comparison: Test different SGMS1 antibodies targeting distinct epitopes to confirm consistent staining patterns.

For biotin-conjugated antibodies specifically, include additional controls for endogenous biotin by using streptavidin-only detection in parallel to exclude false positives from endogenous biotin-containing proteins .

What experimental considerations are important when studying SGMS1 in relation to cell cycle regulation?

When investigating SGMS1's role in cell cycle regulation, particularly at the G2/M checkpoint, implement these methodological approaches:

• Synchronization protocols: Use nocodazole (100 ng/mL for 12 hours) to induce G2/M arrest, followed by release and time-point analysis (e.g., at 0h and 2h post-release).

• Stable knockdown models: Generate stable SGMS1 knockdown cell lines using validated shRNA constructs to assess long-term effects on cell cycle progression.

• Flow cytometry analysis: Combine SGMS1 detection with DNA content analysis using propidium iodide or DAPI staining.

• Correlation with cell cycle markers: Co-stain for established cell cycle markers (cyclin B1, phospho-histone H3) alongside SGMS1.

• Functional rescue experiments: Reintroduce wild-type or mutant SGMS1 in knockdown models to verify specificity of observed cell cycle effects.

This approach enables rigorous assessment of SGMS1's functional significance in cell cycle regulation, particularly in GATA1-positive cells where SGMS1 expression has been shown to influence cell cycle progression through G2/M checkpoints .

How can I optimize biotin-conjugated SGMS1 antibody detection in tissues with high endogenous biotin?

Endogenous biotin can significantly compromise the specificity of biotin-conjugated antibody detection, particularly in tissues like liver, kidney, and brain that naturally contain high biotin levels. To overcome this challenge:

• Biotin blocking step: Before primary antibody incubation, block endogenous biotin using a commercial avidin/biotin blocking kit (sequential incubation with avidin followed by biotin).

• Alternative detection systems: Consider using tyramide signal amplification (TSA) with the biotin-conjugated SGMS1 antibody, which provides signal enhancement while reducing background.

• Tissue pre-treatment: Include a 0.3% hydrogen peroxide step in methanol (10 minutes) before blocking to quench endogenous peroxidase and partially reduce biotin reactivity.

• Control slides: Process parallel tissue sections with streptavidin-detection reagent only (no primary antibody) to assess endogenous biotin signal.

• Quantitative analysis correction: Subtract the mean fluorescence intensity of biotin-only controls from experimental samples during quantification.

What are the optimal preparation methods for membrane proteins like SGMS1 in immunoblotting applications?

As a multi-pass membrane protein localized to the Golgi apparatus, SGMS1 requires specialized extraction protocols for effective immunodetection:

• Membrane fraction enrichment: For optimal SGMS1 detection, prepare total membrane fractions rather than using whole cell lysates. This typically requires:

  • Homogenization in isotonic buffer (250 mM sucrose, 10 mM Tris-HCl, pH 7.4, 1 mM EDTA)

  • Sequential centrifugation steps (1,000×g to remove nuclei, followed by ultracentrifugation at ≥100,000×g to collect membrane fractions)

  • Resuspension in buffer containing 0.5% SDS with sonication

• Sample loading: Use 60 μg of total membrane preparation rather than standard 20 μg whole cell lysate for optimal detection.

• Heat denaturation considerations: Limit heating to 37°C for 10 minutes rather than boiling to prevent aggregation of transmembrane domains.

• Gel composition: Use gradient gels (4-12% or 4-15%) to better resolve membrane proteins.

• Transfer conditions: Implement extended transfer times (overnight at low voltage) with the addition of 0.05% SDS in transfer buffer to enhance elution of hydrophobic proteins.

These specialized approaches significantly improve detection of membrane-bound SGMS1 and provide more reliable quantification in experimental comparisons .

How can I effectively use SGMS1 antibodies in ChIP experiments to investigate GATA1/TAL1 regulation?

Chromatin immunoprecipitation (ChIP) experiments to investigate transcriptional regulation of SGMS1 by GATA1/TAL1 require specific optimization:

• Cross-linking optimization: Use 1% formaldehyde for 10 minutes at room temperature for efficient cross-linking of transcription factors to the SGMS1 promoter.

• Sonication parameters: Process nuclear lysates with 10% output, 20s × 6 cycles with 50s rest periods to achieve optimal chromatin shearing (target fragment size: 200-500 bp).

• Antibody selection: For GATA1 ChIP, use purified rabbit monoclonal antibodies (e.g., ab181544) at 6 μg per immunoprecipitation for maximum enrichment.

• Control design: Include IgG control (purified rabbit monoclonal, ab172730) and positive control regions known to bind GATA1/TAL1.

• Primer design for qPCR validation: Target the SGMS1 promoter region based on ChIP-Seq data from the ENCODE project (ENCFF000YNI; ENCSR000EFT for GATA1 and ENCFF509LKA; ENCSR000EHB for TAL1).

This methodological approach enables robust investigation of the transcriptional regulation of SGMS1, validating its status as a direct target of GATA1/TAL1 transcription factors in relevant cell types .

What are the common pitfalls when using biotin-conjugated SGMS1 antibodies in multiplexed immunoassays?

When incorporating biotin-conjugated SGMS1 antibodies in multiplexed detection systems, researchers should address these potential challenges:

• Cross-reactivity with other biotinylated antibodies: In multi-antibody panels, ensure temporal or spatial separation of biotinylated antibodies by:

  • Sequential detection with complete streptavidin blocking between steps

  • Using different reporter systems (e.g., biotin-SGMS1 with streptavidin-Cy3 and directly conjugated antibodies for other targets)

• Signal bleed-through: When using fluorescent streptavidin conjugates:

  • Establish proper compensation controls

  • Select fluorophores with minimal spectral overlap

  • Analyze single-stained controls for each fluorophore

• Quantitative limitations: In co-localization studies:

  • Be aware that signal amplification from biotin-streptavidin interaction may distort relative quantification

  • Use standardized positive controls with known SGMS1 expression levels

  • Consider ratiometric analysis rather than absolute intensity measurements

• Inconsistent conjugation efficiency: Between antibody lots:

  • Validate each new lot against a reference standard

  • Determine optimal working dilution for each new lot

  • Request biotin:protein ratio from manufacturers when possible

These methodological considerations help ensure reliable results when integrating biotin-conjugated SGMS1 antibodies into complex immunodetection protocols .

What quality control measures ensure reliable results with SGMS1 antibodies in transcriptional regulation studies?

When investigating SGMS1 in the context of transcriptional regulation by GATA1/TAL1, implement these quality control measures:

• Antibody validation with knockdown controls:

  • Generate GATA1 or TAL1 knockdown models and confirm corresponding SGMS1 expression changes

  • Compare against published RNAseq data from TAL1 siRNA experiments (ENCSR336ZWX vs ENCSR641CMW)

• Correlation analysis validation:

  • Verify SGMS1 expression correlation with GATA1/TAL1 using multiple datasets

  • Use Pearson correlation analysis in both cell lines (DepMap portal) and patient samples (TCGA database)

  • Calculate statistical significance based on T-statistics for correlation values

• ChIP-seq data integration:

  • Compare experimental ChIP results with published datasets

  • Visualize data using Integrative Genomics Viewer for consistency

  • Validate binding site predictions with targeted mutagenesis experiments

• Patient stratification controls:

  • When examining SGMS1 in AML, stratify patients by GATA1 expression

  • Use established GATA1+ erythroleukemia/megakaryoblastic leukemia (M6/M7 AML) samples as reference

How does SGMS1 expression correlate with clinical outcomes in hematological malignancies?

Recent research has revealed significant correlations between SGMS1 expression and clinical outcomes in hematological malignancies:

The relationship between SGMS1 expression and patient outcomes appears particularly pronounced in GATA1-positive leukemias, suggesting a mechanistic connection between transcriptional regulation of SGMS1 and disease progression. These findings indicate potential therapeutic opportunities through SGMS1 modulation, particularly in combination with established microtubule-targeting chemotherapeutics .

What are the current methodological approaches to investigate SGMS1 enzymatic activity in research contexts?

Investigating SGMS1 enzymatic activity requires specialized methodological approaches beyond simple protein detection:

• In vitro sphingomyelin synthase activity assay:

  • Membrane fraction preparation (as detailed previously)

  • Incubation with C6-NBD-ceramide and phosphatidylcholine substrates

  • Lipid extraction using chloroform:methanol (2:1, v/v)

  • TLC separation of reaction products

  • Fluorescence detection and quantification of C6-NBD-sphingomyelin formation

• Cellular sphingomyelin synthase activity measurement:

  • Metabolic labeling with [³H]choline or [³H]sphingosine

  • Pulse-chase experimental design for kinetic analysis

  • Lipid extraction and HPLC separation

  • Scintillation counting for quantification

• Mass spectrometry-based sphingolipid profiling:

  • Liquid chromatography-tandem mass spectrometry (LC-MS/MS)

  • Targeted multiple reaction monitoring (MRM) for specific sphingolipid species

  • Internal standard addition for absolute quantification

  • Software analysis (e.g., Skyline) for data processing

• Inhibitor-based studies:

  • Application of bacterial PC-phospholipase C inhibitor D609

  • Dose-response relationship establishment (IC₅₀ determination)

  • Comparison of inhibition in wild-type versus SGMS1-overexpressing systems

These biochemical approaches provide functional assessment of SGMS1 activity beyond expression levels, critical for understanding its role in sphingolipid metabolism and cellular signaling pathways .

How can researchers effectively combine SGMS1 antibody staining with cell cycle analysis in flow cytometry?

To elucidate SGMS1's role in cell cycle regulation, particularly at the G2/M checkpoint, sophisticated flow cytometry protocols can integrate protein expression with cell cycle status:

• Sample preparation protocol:

  • Harvest cells during exponential growth phase

  • Fix with 70% ethanol (dropwise addition while vortexing)

  • Permeabilize with 0.25% Triton X-100 in PBS (10 minutes on ice)

  • Block with 3% BSA in PBS (30 minutes at room temperature)

  • Incubate with biotin-conjugated SGMS1 antibody (1:100 dilution, 1 hour)

  • Detect with streptavidin-conjugated fluorophore (e.g., Streptavidin-PE)

  • Counterstain DNA with DAPI or propidium iodide (PI)

• Gating strategy for analysis:

  • Initial gating on FSC/SSC to exclude debris

  • Single cell selection using pulse width parameter

  • Cell cycle phase determination based on DNA content

  • SGMS1 expression analysis within each cell cycle phase

• Experimental design for mechanistic studies:

  • Nocodazole synchronization (100 ng/mL, 12 hours)

  • Time-course analysis after release (0h, 2h, 4h, 6h)

  • Co-staining with phospho-histone H3 (Ser10) for mitotic cells

  • SGMS1 inhibitor treatment (e.g., D609) to assess functional consequences

• Data analysis approach:

  • Median fluorescence intensity calculation for SGMS1 in each cell cycle phase

  • Bivariate analysis of SGMS1 versus DNA content

  • Statistical comparison between control and experimental conditions

This integrated approach provides mechanistic insights into how SGMS1 levels fluctuate throughout the cell cycle and how its modulation affects cell cycle progression, particularly at the G2/M checkpoint in GATA1-positive cells .

What are the emerging applications of SGMS1 antibodies in translational research?

Biotin-conjugated SGMS1 antibodies are finding expanded applications in translational research contexts, particularly in cancer biology and personalized medicine approaches. Recent methodological advances include:

• Tissue microarray analysis: High-throughput screening of SGMS1 expression across multiple patient samples enables correlation with clinical parameters and survival outcomes in various malignancies.

• Circulating tumor cell detection: Using SGMS1 as part of antibody panels for detecting and characterizing circulating tumor cells, particularly in GATA1-positive malignancies.

• Drug sensitivity prediction: Correlating SGMS1 expression levels with response to microtubule-targeting agents and other chemotherapeutics to develop predictive biomarkers.

• Multi-omics integration: Combining SGMS1 protein detection with genomic, transcriptomic, and metabolomic data to create comprehensive disease profiles.

These emerging applications highlight the increasing importance of SGMS1 in translational research contexts, with biotin-conjugated antibodies offering particular advantages in multiplexed detection systems and high-sensitivity applications .

What methodological advances are needed to better understand SGMS1's role in cellular processes?

Despite significant progress, several methodological gaps remain in fully understanding SGMS1 biology:

• Spatiotemporal dynamics visualization: Development of live-cell imaging approaches with fluorescent-tagged SGMS1 to track its localization and activity in real-time during cell cycle progression and in response to stimuli.

• Substrate-specific activity measurement: Creation of more selective assays that can distinguish between different sphingomyelin synthase family members (SGMS1 vs. SGMS2) and their substrate preferences.

• Structure-function relationship elucidation: Generation of domain-specific antibodies that can distinguish active vs. inactive conformations of SGMS1 or detect post-translational modifications.

• Single-cell analysis protocols: Adaptation of current methodologies to enable single-cell resolution of SGMS1 expression and activity, particularly in heterogeneous tissue environments.

• Improved animal models: Development of conditional and tissue-specific SGMS1 knockout/knockin models to better understand its role in development and disease.