ST13 Antibody

What is the ST13 protein and why is it significant in research?

ST13 (Suppression of Tumorigenicity 13) is a co-chaperone protein that interacts with heat shock protein 70 (Hsc70). It contains three distinct interaction domains: an N-terminal dimerization domain, a TRP repeat domain, and a C-terminal STI1 domain. ST13 has significant research importance due to its roles in:

• Lipid metabolism regulation in pancreatic tissue

• Protection against acinar steatosis and injury in chronic pancreatitis

• Tumor suppression in colorectal cancer by inhibiting cell proliferation and migration

• Regulation of arachidonic acid pathway homeostasis via binding with Sdf2l1

Its altered expression in pathological conditions makes it a valuable research target for understanding disease mechanisms and potential therapeutic development.

What applications are ST13 antibodies typically used for?

ST13 antibodies are validated for multiple research applications with specific recommended dilutions:

These applications enable researchers to detect and quantify ST13 expression, localization, and interactions in various experimental models and human pathological specimens.

What is the difference between monoclonal and polyclonal ST13 antibodies?

The choice between monoclonal and polyclonal ST13 antibodies depends on your experimental requirements:

Monoclonal antibodies offer greater specificity and reproducibility, making them ideal for quantitative applications, while polyclonal antibodies may provide better sensitivity for detecting low-abundance proteins or denatured epitopes.

How can I validate ST13 antibody specificity in my experimental system?

Thorough validation of ST13 antibody specificity is critical for reliable research outcomes. Implement these methodological approaches:

• Positive and negative controls:

  • Positive: Use tissues/cells known to express ST13 (e.g., HEK-293 cells, mouse testis tissue)

  • Negative: Include ST13 knockout cells or ST13-depleted samples via RNAi

• Multiple antibody comparison:

  • Test at least two antibodies targeting different ST13 epitopes

  • Compare staining/banding patterns between antibodies

• Genetic manipulation validation:

  • Overexpress ST13 and confirm increased signal intensity

  • Perform siRNA/shRNA-mediated knockdown and verify signal reduction

  • The shRNA-ST13 knockdown system has demonstrated approximately 90% reduction in ST13 expression in SW620 cells

• Immunoprecipitation-mass spectrometry:

  • Perform IP with ST13 antibody followed by mass spectrometry

  • Confirm presence of ST13 peptides in immunoprecipitated material

Maintain detailed records of validation experiments to ensure reproducibility and reliability of subsequent research findings.

How does ST13 protein structure influence antibody selection for studying its interactions with binding partners?

ST13 has a complex domain structure that directly influences antibody selection when studying protein-protein interactions:

• Domain-specific considerations:

  • N-terminal Hip dimerization domain (aa 1-112)

  • TRP repeat domain (aa 113-214) - critical for Sdf2l1 binding

  • C-terminal STI1 domain (aa 215-371)

• Antibody epitope mapping:

  • Select antibodies targeting non-interaction regions when studying binding partners

  • Avoid antibodies against the TRP repeat domain when studying Sdf2l1 interactions, as they may interfere with binding

• Conformational vs. linear epitopes:

  • For native interaction studies, use antibodies recognizing conformational epitopes

  • For denatured protein detection, select antibodies against linear epitopes

Research has demonstrated that the TRP repeat domain (aa 113-214) is essential for ST13's interaction with Sdf2l1 in co-immunoprecipitation experiments . Therefore, antibodies targeting other regions would be preferable when studying this specific interaction.

What are the critical considerations when designing experiments to investigate ST13's role in chronic pancreatitis using antibody-based techniques?

When investigating ST13's role in chronic pancreatitis (CP), consider these specialized experimental design elements:

• Model selection:

  • Use both alcoholic (ACP) and non-alcoholic CP (nACP) models to comprehensively understand ST13 function

  • Include controls that account for different lipid metabolism patterns in ACP versus nACP

• Temporal considerations:

  • Design time-course experiments to capture dynamic changes in ST13 expression

  • Include early and late CP stages to track progression

• Co-immunoprecipitation strategy:

  • Target the ST13-Sdf2l1 interaction specifically

  • Use antibodies that don't interfere with the TRP repeat domain (aa 113-214)

  • Include controls for non-specific binding

• Downstream signaling analysis:

  • Monitor IRE1α-XBP1s pathway components alongside ST13

  • Assess arachidonic acid (AA) pathway metabolites

  • Consider parecoxib treatment groups to connect findings to potential therapeutic applications

• Translational relevance:

  • Include human CP tissue samples for validation

  • Consider 68Ga-FAPI-04 PET/CT imaging correlation studies

Research has demonstrated that St13 overexpression protects against acinar steatosis and injury in CP through interaction with Sdf2l1, which promotes arachidonic acid pathway homeostasis via the IRE1α-XBP1s pathway .

What are the optimal conditions for Western blotting using ST13 antibodies?

For optimal Western blot results with ST13 antibodies, follow these protocol considerations:

• Sample preparation:

  • Use RIPA buffer with protease inhibitors for cell/tissue lysis

  • Include phosphatase inhibitors if studying ST13 phosphorylation states

• Gel electrophoresis parameters:

  • Use 10-12% SDS-PAGE gels for optimal resolution of ST13 (45-50 kDa)

  • Load 20-50 μg total protein per lane (cell lysates)

• Transfer conditions:

  • Transfer to PVDF membrane (preferred over nitrocellulose)

  • Semi-dry transfer: 15V for 30 minutes or wet transfer: 100V for 1 hour

• Blocking and antibody incubation:

  Step	Recommendation	Duration
  Blocking	5% non-fat milk in TBST	1 hour at RT
  Primary antibody	1:1000-1:6000 dilution in 5% BSA-TBST	Overnight at 4°C
  Washing	TBST buffer	3 × 10 minutes
  Secondary antibody	HRP-conjugated, 1:5000 in 5% milk-TBST	1 hour at RT

• Detection optimization:

  • Enhanced chemiluminescence (ECL) detection

  • Exposure time: Start with 30 seconds, adjust as needed

  • Expected molecular weight: 45-50 kDa

For reproducible results, maintain consistent sample loading, transfer efficiency, and antibody concentrations across experiments.

How can I optimize immunohistochemistry protocols for ST13 detection in different tissue types?

Optimizing IHC protocols for ST13 detection requires tissue-specific considerations:

• Fixation and antigen retrieval:

  • Formalin-fixed paraffin-embedded (FFPE) sections: 4-5 μm thickness

  • Primary antigen retrieval recommendation: TE buffer pH 9.0

  • Alternative: Citrate buffer pH 6.0 for challenging tissues

  • Heat-induced epitope retrieval: 95-98°C for 15-20 minutes

• Blocking and antibody parameters:

  Tissue Type	Blocking Solution	Antibody Dilution	Incubation
  Pancreatic tissue	5% goat serum, 1% BSA	1:200-1:500	Overnight, 4°C
  Colon tissue	5% goat serum, 0.3% Triton X-100	1:200-1:1000	Overnight, 4°C
  Other epithelial tissues	3% BSA, 0.1% Tween-20	1:500	Overnight, 4°C

• Signal amplification and detection:

  • DAB chromogen development: 5-10 minutes at RT

  • Counterstain: Hematoxylin (1-3 minutes)

  • For fluorescent detection: Alexa Fluor secondaries (1:500 dilution)

• Tissue-specific considerations:

  • Pancreatic tissue: Reduce endogenous enzyme activity with additional H₂O₂ treatment

  • High-fat tissues: Extend deparaffinization and washing steps

  • Colon tissues: Has been successfully used to study ST13 expression in colorectal cancer

• Controls:

  • Positive control: Human colon cancer tissue

  • Negative control: Primary antibody omission

  • Absorption control: Pre-incubation with immunizing peptide

Thorough optimization is particularly important when studying ST13 in chronic pancreatitis, as lipid metabolism disruptions can affect staining quality .

What approaches can resolve discrepancies in ST13 expression data between different antibody-based detection methods?

When faced with discrepancies in ST13 expression data across different antibody-based methods, implement this systematic troubleshooting approach:

• Methodological cross-validation:

  • Compare protein levels (Western blot) with mRNA expression (qRT-PCR)

  • Research shows good correlation between ST13 protein and mRNA levels in genetic manipulation experiments

  • Use multiple antibody-based techniques (WB, IHC, IP) in parallel

• Epitope accessibility analysis:

  • Different antibodies may detect distinct ST13 conformations

  • Native conditions (IP/IF) versus denatured (WB) may give different results

  • Test both monoclonal (single epitope) and polyclonal (multiple epitopes) antibodies

• Post-translational modification considerations:

  • Phosphorylation status may affect antibody recognition

  • Investigate ubiquitination patterns affecting protein stability

  • Consider protein-protein interactions masking epitopes

• Quantitative analysis refinement:

  Method	Normalization Approach	Quantification Method
  Western blot	Multiple housekeeping proteins	Densitometry with linear range validation
  IHC	Area normalization, internal controls	H-score or automated image analysis
  qRT-PCR	Multiple reference genes	ΔΔCt method with efficiency correction

• Biological variability assessment:

  • Discrepancies may reflect actual biological differences

  • Consider subcellular localization effects on detection

  • Evaluate effects of cell/tissue heterogeneity on aggregate signal

When studying ST13 in different models of chronic pancreatitis or cancer, discrepancies may reflect genuine biological differences rather than technical artifacts, as ST13 expression varies significantly between alcoholic and non-alcoholic CP .

How should I design experiments to investigate the interaction between ST13 and Sdf2l1 using antibody-based approaches?

To effectively study the ST13-Sdf2l1 interaction, implement this comprehensive experimental design:

• Co-immunoprecipitation strategy:

  • Forward IP: Use anti-ST13 antibody to pull down complexes, detect Sdf2l1

  • Reverse IP: Use anti-Sdf2l1 antibody, detect ST13

  • Controls: IgG control, lysates from cells with ST13 or Sdf2l1 knockdown

  • Detection: Western blot with specific antibodies for each protein

• Domain mapping experiments:

  • Create constructs similar to those used in research:

    • Full-length ST13 (#1)

    • ∆aa 1-112 (#2, lacking N-terminal domain)

    • ∆aa 113-214 (#3, lacking TRP repeat domain)

    • ∆aa 215-371 (#4, lacking C-terminal STI1 domain)

  • Express tagged versions (Flag-tagged ST13, myc-tagged Sdf2l1)

  • Perform pull-down experiments to identify interaction domains

• Proximity ligation assay (PLA):

  • Visualize endogenous protein interactions in situ

  • Use specific primary antibodies against ST13 and Sdf2l1

  • Quantify interaction signals across different cellular conditions

• Functional validation approaches:

  • siRNA-mediated knockdown of ST13 or Sdf2l1

  • Rescue experiments with wild-type or domain-mutated constructs

  • Analyze downstream effects on IRE1α-XBP1s pathway and AA pathway homeostasis

Previous research has conclusively demonstrated that the TRP repeat domain (aa 113-214) of ST13 is essential for its interaction with Sdf2l1, as deletion of this region abolished binding in co-immunoprecipitation experiments .

What control experiments are essential when studying ST13's tumor suppressive role using antibody-based techniques?

When investigating ST13's tumor suppressive functions, include these critical control experiments:

• Expression manipulation controls:

  • Vector-only controls (Lenti-Mock) alongside ST13 overexpression

  • Scrambled shRNA controls (shRNA-Mock) alongside ST13 knockdown

  • Rescue experiments with wild-type ST13 in knockdown cells

• Functional controls for proliferation assays:

  • Multiple time points (3-5 days) to capture growth curve dynamics

  • Multiple methods: MTT assay and colony formation assay

  • Positive and negative growth regulator controls

• In vivo model controls:

  • Contralateral injections of control and experimental cells

  • Time-course tumor measurements (volume, weight)

  • Histological confirmation of ST13 expression levels in tumors

  • Research shows shRNA-ST13 xenografts developed ~75% larger tumors than controls

• Antibody validation controls:

  • Confirm specificity via western blot in manipulated cell lines

  • Use multiple antibodies targeting different ST13 epitopes

  • Include isotype controls for immunohistochemistry

• Mechanistic pathway controls:

  • Evaluate associated signaling pathways (e.g., cell cycle regulators)

  • Assess direct ST13 targets and binding partners

  • Include positive controls for each signaling pathway examined

Published research has validated the tumor suppressive role of ST13 in colorectal cancer using multiple complementary approaches, demonstrating that ST13 overexpression significantly reduces proliferation while knockdown enhances tumorigenicity both in vitro and in vivo .

How can I design experiments to investigate ST13's role in lipid metabolism disorders using antibody-based detection methods?

To comprehensively investigate ST13's role in lipid metabolism disorders:

• Model selection and validation:

  • Utilize both alcoholic CP (ACP) and non-alcoholic CP (nACP) models

  • Include appropriate controls for each model

  • Validate ST13 expression levels in each model using:

    • Western blot (protein levels)

    • qRT-PCR (mRNA levels)

    • IHC (tissue localization and expression pattern)

• Intervention experimental design:

  Group	Intervention	Control	Analysis Time Points
  ACP model	ST13 overexpression	Vector control	Baseline, 1, 2, 4 weeks
  nACP model	ST13 knockdown	Scrambled shRNA	Baseline, 1, 2, 4 weeks
  AA pathway	Parecoxib treatment	Vehicle control	During CP development

• Comprehensive analytical approach:

  • Lipidomic profiling to quantify arachidonic acid and metabolites

  • Immunoblotting for IRE1α-XBP1s pathway components

  • Co-immunoprecipitation to assess ST13-Sdf2l1 interaction

  • Histological assessment of acinar steatosis

• Translational validation:

  • Compare findings with human CP patient samples

  • Correlate with non-invasive imaging (68Ga-FAPI-04 PET/CT)

  • Analyze ST13 expression patterns in relation to disease severity

Research has demonstrated that ST13 protects against acinar steatosis and injury in CP by binding Sdf2l1, which promotes arachidonic acid pathway homeostasis via regulation of the IRE1α-XBP1s pathway . These mechanistic insights provide potential therapeutic targets for CP treatment.

What are common issues encountered with ST13 western blotting and how can they be resolved?

When troubleshooting ST13 western blotting problems, consider these common issues and solutions:

• No signal or weak signal:

  • Increase antibody concentration (try 1:500 instead of 1:6000)

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

  • Use enhanced detection systems (high-sensitivity ECL)

  • Check protein transfer efficiency with reversible stain

  • Verify ST13 expression in your sample type

• Multiple or non-specific bands:

  • Increase blocking stringency (5% BSA instead of milk)

  • Add 0.1% Tween-20 to antibody dilution

  • Optimize primary antibody dilution (1:2000-1:6000)

  • Use freshly prepared samples to minimize degradation

  • Consider using monoclonal antibody for higher specificity

• Inconsistent molecular weight:

  • Expected ST13 molecular weight: 45-50 kDa

  • Post-translational modifications may alter migration

  • Use positive control lysate (HEK-293 cells or mouse testis)

  • Include molecular weight markers on both sides of gel

• High background:

  Issue	Solution
  Membrane issues	Use fresh PVDF, pre-wet in methanol
  Washing inadequate	Increase wash times (4 × 10 minutes)
  Detection problem	Decrease exposure time, use fresh ECL
  Antibody concentration	Dilute primary (1:4000-1:6000) and secondary (1:10000)

• Quantification problems:

  • Use appropriate normalization controls

  • Ensure detection is within linear range

  • Average multiple independent experiments (n≥3)

  • Use image analysis software with background subtraction

The ST13 protein frequently shows minor variation in molecular weight (45-50 kDa range) across different sample types and gel conditions .

How can I address tissue-specific challenges when using ST13 antibodies in immunohistochemistry?

Different tissues present unique challenges for ST13 immunohistochemistry that require specific optimization:

• Pancreatic tissue challenges:

  • High endogenous enzyme activity: Use additional peroxidase quenching (3% H₂O₂, 15 minutes)

  • Fatty infiltration in CP: Extend deparaffinization steps

  • Dense fibrosis: Increase antigen retrieval time to 25-30 minutes

  • Solution: TE buffer pH 9.0 typically yields better results than citrate buffer

• Colon tissue optimization:

  • Mucin content: Add Triton X-100 (0.1%) to antibody diluent

  • Background staining: Extended blocking (2 hours)

  • Optimal antibody dilution: 1:200-1:500 for human colon cancer tissues

  • Control: Normal adjacent tissue as internal control

• Liver tissue considerations:

  • High background: Use avidin-biotin blocking kit prior to antibody incubation

  • Endogenous biotin: Switch to polymer-based detection systems

  • Lipofuscin autofluorescence: Add Sudan Black B treatment if using fluorescent detection

  • Fixation sensitivity: Limit fixation time to 24 hours maximum

• Brain tissue adaptations:

  Challenge	Solution
  Blood-brain barrier proteins	Increase Triton X-100 to 0.3%
  Lipid-rich regions	Add delipidation step (chloroform:methanol)
  Antigen masking	Extended antigen retrieval (30 minutes)
  Autofluorescence	Treat with sodium borohydride

• General optimization strategy:

  • Start with manufacturer-recommended protocol

  • Perform antibody titration for each tissue type

  • Test multiple antigen retrieval methods

  • Include appropriate positive and negative controls

For studying ST13 in chronic pancreatitis, researchers should be particularly attentive to tissue processing, as lipid droplet preservation is crucial for accurately assessing the relationship between ST13 and acinar steatosis .

What strategies can overcome limitations in detecting low abundance of ST13 protein in certain cell types or conditions?

To enhance detection of low-abundance ST13 protein:

• Sample enrichment techniques:

  • Immunoprecipitation before Western blotting

  • Subcellular fractionation to concentrate compartment-specific ST13

  • Use larger protein amounts (50-100 μg) for Western blotting

  • More concentrated lysates (reduce buffer volume)

• Signal amplification methods:

  • Tyramide signal amplification (TSA) for IHC/IF

  • High-sensitivity chemiluminescent substrates for Western blot

  • Use biotinylated secondary antibodies with streptavidin-HRP

  • Consider polymer-based detection systems for IHC

• Antibody optimization:

  • Higher concentration of primary antibody (1:200-1:500)

  • Extended incubation times (48 hours at 4°C for IHC)

  • Combination of multiple antibodies targeting different epitopes

  • Use polyclonal antibodies for potentially higher sensitivity

• Technical modifications:

  Technique	Standard Approach	Enhanced Sensitivity Approach
  Western blot	10% gel, PVDF	Gradient gel, low-fluorescence PVDF
  IHC	DAB detection	Amplification with TSA
  IF	Direct detection	Multi-layer detection, signal stacking
  Exposure	Standard	Extended exposure with low background

• Control experiments:

  • Positive control with ST13 overexpression to validate detection

  • Systematic validation of all reagents

  • Parallel detection of high-abundance proteins to confirm technique

  • Internal standard curve with recombinant ST13 protein

Research has demonstrated that detection sensitivity is particularly important when studying the dynamic regulation of ST13 in response to disease progression, as its expression may vary significantly between different models and stages of chronic pancreatitis .