MACC1 Antibody, Biotin conjugated

What is MACC1 and why is it significant in cancer research?

MACC1 (Metastasis Associated In Colon Cancer 1) functions as a key transcriptional regulator of MET and has been identified as an oncogene in gastric cancer and other malignancies. Its significance lies in its role in promoting cancer progression through enhancement of glycolysis and metabolic plasticity. MACC1 has been linked to metastasis, chemoresistance, and poor prognosis in gastric cancer patients, making it an important target for cancer research and therapeutic development . Research utilizing MACC1 antibodies helps investigate these pathways and potential intervention strategies.

What are the technical specifications of the biotin-conjugated MACC1 antibody?

The biotin-conjugated MACC1 antibody is a polyclonal antibody produced in rabbits that specifically targets human Metastasis Associated In Colon Cancer 1 protein. The antibody is generated using recombinant human MACC1 protein (amino acids 371-514) as the immunogen. It belongs to the IgG isotype, has a purity greater than 95%, and is purified through Protein G affinity chromatography. The antibody is supplied in liquid form in a buffer containing 0.01 M PBS (pH 7.4), 0.03% Proclin-300, and 50% glycerol . This biotin conjugation enhances detection sensitivity in various immunoassay applications.

What is the relationship between MACC1 and MACC1-AS1 in cancer biology?

MACC1-AS1 is the antisense long non-coding RNA (lncRNA) of MACC1 that plays a crucial regulatory role in MACC1 expression. Research has shown that MACC1-AS1 stabilizes MACC1 mRNA through direct physical binding, thereby post-transcriptionally enhancing MACC1 expression. This regulatory mechanism contributes to metabolic plasticity in cancer cells by promoting glycolysis and enhancing antioxidant capabilities. The MACC1-AS1/MACC1 axis is coordinated by the AMPK/Lin28 pathway, with MACC1-AS1 promoting Lin28 translocation from the nucleus to the cytoplasm . Understanding this relationship is essential for comprehensive investigation of MACC1-mediated oncogenic mechanisms.

How should I design experiments to validate MACC1 antibody specificity in my cancer models?

To validate MACC1 antibody specificity in cancer models, implement a multi-tiered verification approach. First, perform western blotting using cell lines with known MACC1 expression levels (both high and low expresser cell lines) to confirm the antibody detects a band of the expected molecular weight (~97 kDa). Include MACC1 knockdown (siRNA or CRISPR) and overexpression controls alongside wild-type samples. Second, employ immunofluorescence co-staining with another validated MACC1 antibody raised against a different epitope to confirm localization patterns. Third, validate with immunoprecipitation followed by mass spectrometry to confirm the antibody pulls down the MACC1 protein. Finally, include negative controls like isotype controls and secondary-only staining to rule out non-specific binding. For the biotin-conjugated version specifically, perform blocking experiments with free biotin to confirm specificity of the conjugated antibody detection system .

What are the optimal conditions for using biotin-conjugated MACC1 antibody in ELISA applications?

For optimal ELISA performance with biotin-conjugated MACC1 antibody, begin with antibody titration experiments to determine the ideal concentration range, typically starting between 0.1-1.0 μg/ml. The antibody performs optimally in standard ELISA buffer (PBS pH 7.4 with 0.05% Tween-20 and 1-3% BSA or casein as a blocking agent). Given its biotin conjugation, utilize streptavidin-HRP as the detection system, which provides enhanced sensitivity through the strong biotin-streptavidin interaction. Incubate samples at room temperature for 1-2 hours or at 4°C overnight, followed by streptavidin-HRP incubation for 30-60 minutes. After thorough washing, develop with TMB substrate and monitor color development for 5-30 minutes before stopping the reaction with acid. To preserve antibody functionality, avoid repeated freeze-thaw cycles and store aliquots at -20°C, protecting from light exposure as recommended by the manufacturer . Each new experimental system requires optimization of antibody dilutions by the end user.

How can I effectively incorporate this antibody into multiplexed immunoassays with other biomarkers?

To successfully incorporate biotin-conjugated MACC1 antibody into multiplexed immunoassays, careful optimization of several parameters is essential. First, minimize antibody cross-reactivity by conducting preliminary single-plex experiments to establish baseline performance and ensure specificity. When developing the multiplex panel, select additional antibodies with complementary conjugates (e.g., fluorophores, enzymes) that operate in non-overlapping detection channels to avoid signal interference with the biotin-streptavidin system. Perform sequential incubations rather than simultaneous antibody additions if cross-reactivity is suspected. Enhance blocking protocols using both protein blockers (BSA, casein) and additional biotin blocking reagents to prevent non-specific binding and reduce background. For quantitative assays, develop standard curves for each target protein individually and in combination to identify any matrix effects. Finally, validate the multiplex assay by comparing results with established single-plex assays and checking for correlation to confirm the integrity of each biomarker detection when used in combination .

What are the critical factors affecting biotin-conjugated MACC1 antibody stability and performance?

Several critical factors influence the stability and performance of biotin-conjugated MACC1 antibody. Temperature fluctuations represent a primary concern, as repeated freeze-thaw cycles can significantly compromise antibody integrity; therefore, storing the antibody in small working aliquots at -20°C is essential. Light exposure must be minimized, as biotin conjugates are particularly susceptible to photodegradation that can diminish signal strength. The buffer composition (0.01 M PBS, pH 7.4, 0.03% Proclin-300, and 50% glycerol) maintains optimal antibody conformation, and deviations in pH or salt concentration during experimental procedures can affect binding efficiency . Additionally, competing endogenous biotin in biological samples may interfere with detection systems, necessitating appropriate blocking steps. Microbial contamination can degrade antibody proteins, so aseptic technique during handling is crucial. Finally, the concentration of reducing agents in experimental buffers should be carefully controlled, as they can disrupt the disulfide bonds essential for antibody structure and function.

How can I troubleshoot weak or non-specific signals when using this antibody in immunoassays?

When encountering weak or non-specific signals with biotin-conjugated MACC1 antibody, implement a systematic troubleshooting approach. For weak signals, first verify antibody integrity by performing a dot blot with recombinant MACC1 protein as a positive control. Increase antibody concentration incrementally (while maintaining manufacturer's recommended range) or extend incubation time to enhance signal intensity. Evaluate detection reagent functionality by testing with other biotin-conjugated antibodies. For non-specific signals, optimize blocking conditions using different blockers (5% BSA, casein, commercial blockers) and increase blocking time to reduce background. Incorporate additional washing steps with increased stringency (higher salt concentration or 0.1% Tween-20). If endogenous biotin interference is suspected, pre-block samples with streptavidin followed by free biotin. Verify sample integrity by checking for protein degradation through SDS-PAGE. Consider using tissue or cell samples with confirmed MACC1 expression as positive controls, while incorporating MACC1 knockdown samples as negative controls. Finally, test alternative detection methods, such as switching from colorimetric to chemiluminescent detection for improved signal-to-noise ratio .

What strategies can mitigate the impact of endogenous biotin interference in experimental samples?

To mitigate endogenous biotin interference when using biotin-conjugated MACC1 antibody, implement a comprehensive strategy starting with sample pretreatment. Employ an avidin/streptavidin blocking step followed by excess free biotin before introducing the biotin-conjugated antibody—this sequential approach effectively masks endogenous biotin while saturating remaining avidin/streptavidin binding sites. Consider using commercially available endogenous biotin blocking kits specifically designed for this purpose. For tissue samples, extend fixation time and incorporate additional washing steps with specialized buffers containing non-ionic detergents to remove unbound endogenous biotin. When working with serum samples known to contain high biotin levels, implement dialysis or ultrafiltration preprocessing to reduce biotin concentration. Alternative detection systems can also be considered if biotin interference persists—for instance, directly conjugated fluorophores or enzyme-labeled secondary antibodies that bypass the biotin-avidin interaction entirely. Finally, timing considerations are important; collect samples after sufficient washout periods if subjects were taking biotin supplements, and schedule experiments when endogenous biotin levels are expected to be lowest .

How can the biotin-conjugated MACC1 antibody be utilized to investigate MACC1-AS1/MACC1 interactions?

To investigate MACC1-AS1/MACC1 interactions using biotin-conjugated MACC1 antibody, implement RNA-protein complex immunoprecipitation methodologies. Begin with crosslinking experiments using formaldehyde or UV to stabilize RNA-protein interactions in situ. Utilize the biotin-conjugated MACC1 antibody with streptavidin magnetic beads to immunoprecipitate MACC1 protein complexes, followed by RNA extraction and RT-qPCR to detect co-precipitated MACC1-AS1. For comprehensive interaction analysis, couple this approach with RNA immunoprecipitation sequencing (RIP-seq) to identify all RNAs associated with MACC1 protein. To validate direct binding, perform RNA pull-down assays using biotinylated MACC1-AS1 as bait, followed by western blotting with the MACC1 antibody to detect protein interaction . Additionally, implement fluorescence microscopy techniques like proximity ligation assay (PLA) or fluorescence resonance energy transfer (FRET) using the biotin-conjugated MACC1 antibody paired with fluorophore-labeled MACC1-AS1 probes to visualize co-localization and interaction dynamics in intact cells. These multifaceted approaches provide mechanistic insights into how MACC1-AS1 stabilizes MACC1 mRNA and influences its expression in the context of cancer metabolic plasticity.

What analytical techniques can be employed to study MACC1's role in metabolic plasticity using this antibody?

To investigate MACC1's role in metabolic plasticity using biotin-conjugated MACC1 antibody, implement an integrated analytical workflow combining immunological detection with metabolic profiling. First, utilize the antibody for immunoprecipitation followed by mass spectrometry to identify MACC1-interacting proteins involved in metabolic pathways. Couple this with chromatin immunoprecipitation sequencing (ChIP-seq) to map MACC1 binding sites on metabolic gene promoters. For functional metabolic analysis, perform Seahorse XF assays measuring oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in cells with varying MACC1 expression levels, validating MACC1 presence using the biotin-conjugated antibody in parallel samples. Implement isotope tracing metabolomics with 13C-glucose or 13C-glutamine to track metabolic flux through glycolysis and TCA cycle, correlating with MACC1 expression quantified via immunoblotting. For in situ analysis, combine immunofluorescence using the biotin-conjugated MACC1 antibody with fluorescent metabolic probes like 2-NBDG (glucose uptake) to visualize co-localization of MACC1 with areas of high metabolic activity . Additionally, develop a proximity-based assay using the biotin-conjugated antibody to detect MACC1 interaction with metabolic enzymes like hexokinase 2 (HK2) and glucose transporter 1 (GLUT1) under different metabolic stress conditions, providing insight into how MACC1 coordinates metabolic adaptation.

How can researchers investigate the AMPK/Lin28 pathway's role in MACC1 regulation using this antibody?

To investigate the AMPK/Lin28 pathway's role in MACC1 regulation using biotin-conjugated MACC1 antibody, implement a comprehensive experimental strategy combining protein-protein interaction studies with functional analyses. First, perform co-immunoprecipitation experiments using the biotin-conjugated MACC1 antibody and streptavidin beads to pull down MACC1 complexes, followed by immunoblotting for AMPK and Lin28 to establish physical associations. Implement proximity ligation assays (PLA) combining the biotin-conjugated MACC1 antibody with antibodies against phosphorylated AMPK and Lin28 to visualize protein interactions in situ. For functional analysis, conduct AMPK modulation experiments using activators (AICAR, metformin) and inhibitors (Compound C, dorsomorphin), followed by assessment of MACC1 expression levels via western blotting and RT-qPCR . Employ subcellular fractionation to track Lin28 nuclear-cytoplasmic shuttling following AMPK activation/inhibition, correlating with MACC1 mRNA stability measured by actinomycin D chase experiments. Utilize RNA immunoprecipitation (RIP) assays with the biotin-conjugated MACC1 antibody to identify mRNA binding partners affected by AMPK/Lin28 modulation. Finally, implement CRISPR-based genetic screens targeting components of the AMPK/Lin28 pathway while monitoring MACC1 expression and stability, providing a comprehensive understanding of this regulatory axis in metabolic adaptation and cancer progression.

How should researchers interpret contradictory MACC1 expression data across different cancer types?

When interpreting contradictory MACC1 expression data across cancer types, researchers should implement a multi-faceted analytical framework. First, consider tissue specificity and cellular context—MACC1 may exhibit diverse functions depending on the tissue microenvironment and underlying molecular subtypes. MACC1 has been primarily characterized in gastric cancer where it promotes glycolysis and metabolic plasticity, but its expression patterns and functional significance may vary in other malignancies . Evaluate methodological differences that might contribute to discrepancies, including antibody specificity, detection techniques (IHC vs. RNA-seq), and subcellular localization assessment. The biotin-conjugated MACC1 antibody might detect different epitopes than antibodies used in other studies, potentially recognizing distinct MACC1 isoforms or post-translationally modified variants. Consider genetic and epigenetic heterogeneity across tumors, as MACC1 regulation by MACC1-AS1 might differ based on lncRNA expression patterns specific to certain cancer types . Analyze MACC1 in relation to its regulatory network, particularly the AMPK/Lin28 pathway, which may exhibit tissue-specific activation patterns. Finally, conduct survival analyses stratified by cancer type and stage to determine whether MACC1's prognostic significance is universally applicable or context-dependent, allowing for more nuanced interpretation of seemingly contradictory expression data.

What considerations are important when correlating MACC1 protein levels with mRNA stability and MACC1-AS1 expression?

When correlating MACC1 protein levels with mRNA stability and MACC1-AS1 expression, researchers must address several critical considerations. First, establish temporal dynamics by implementing time-course experiments that capture the sequence of MACC1-AS1 upregulation, changes in MACC1 mRNA half-life, and subsequent protein accumulation. The relationship is not necessarily linear, as research has demonstrated that MACC1-AS1 stabilizes MACC1 mRNA through direct binding, but additional post-transcriptional and translational regulatory mechanisms may influence the ultimate protein output . Implement actinomycin D chase experiments paired with RT-qPCR to accurately quantify MACC1 mRNA stability alongside MACC1-AS1 expression levels. Account for potential feedback loops, as MACC1 protein may reciprocally regulate MACC1-AS1 transcription. Evaluate subcellular localization patterns, as MACC1-AS1 functions primarily in the cytoplasm where it stabilizes MACC1 mRNA, but protein translation efficiency and localization may be independently regulated . Consider metabolic stress conditions, which have been shown to induce MACC1-AS1 expression, potentially creating context-dependent correlation patterns. Finally, incorporate analysis of the AMPK/Lin28 pathway activity, as Lin28 translocation from nucleus to cytoplasm following MACC1-AS1-mediated AMPK activation represents a key mechanistic link in this regulatory axis . These multifaceted considerations enable more accurate interpretation of the complex relationship between MACC1-AS1, mRNA stability, and resulting protein expression.

How can researchers integrate MACC1 antibody-based findings with broader cancer metabolism research?

To integrate MACC1 antibody-based findings with broader cancer metabolism research, researchers should implement a systems biology approach that connects molecular mechanisms to metabolic phenotypes. First, combine immunodetection of MACC1 using the biotin-conjugated antibody with comprehensive metabolomic profiling to establish correlations between MACC1 expression patterns and metabolite signatures across cancer types and under various stress conditions. Develop in vitro models with controlled MACC1 expression levels (through overexpression or knockdown) and assess metabolic reprogramming using techniques like Seahorse analysis (for glycolysis and oxidative phosphorylation), 13C-isotope tracing (for metabolic flux), and assessment of redox status (NADPH/NADP+ and GSH/GSSG ratios) . Implement computational modeling to predict how MACC1-mediated metabolic alterations might influence drug sensitivity and resistance mechanisms. Explore the relationship between MACC1 and other established metabolic regulators such as HIF-1α, c-Myc, and p53 through co-immunoprecipitation and co-expression analyses. Assess how MACC1-driven metabolic adaptations influence the tumor microenvironment by examining immune cell function and stromal interactions. Finally, evaluate potential therapeutic opportunities by testing metabolic inhibitors (glycolysis inhibitors, glutaminase inhibitors) in combination with MACC1-targeting approaches, monitoring treatment efficacy using the biotin-conjugated MACC1 antibody to track protein expression changes . This integrated approach bridges molecular findings with functional metabolic outcomes, advancing our understanding of cancer metabolism.

What emerging technologies might enhance MACC1 detection and functional analysis beyond current antibody-based methods?

Emerging technologies poised to enhance MACC1 detection and functional analysis beyond current antibody-based methods include several innovative approaches. CRISPR-based tagging systems such as CRISPR-Cas13 RNA targeting could enable live-cell visualization of MACC1 mRNA dynamics without requiring antibodies, providing insights into real-time regulation by MACC1-AS1 . Nanobody technology—using single-domain antibody fragments—offers superior tissue penetration and reduced background compared to conventional antibodies, potentially improving MACC1 detection sensitivity in complex tissues. Mass cytometry (CyTOF) combined with metal-labeled antibodies could revolutionize multiplexed detection of MACC1 alongside dozens of other cancer-related proteins and metabolic markers in single cells. Advanced spatial transcriptomics and proteomics platforms like Visium, MERFISH, or Digital Spatial Profiling (DSP) would enable simultaneous visualization of MACC1 protein, MACC1-AS1, and metabolic enzymes within the spatial context of tumor tissues . Aptamer-based detection systems represent another frontier, where synthetic nucleic acid aptamers selected for high-affinity MACC1 binding could provide detection specificity comparable to antibodies but with improved stability and reduced batch-to-batch variation. Finally, FRET-based biosensors designed to detect MACC1 protein-protein interactions could reveal dynamic relationships with metabolic enzymes and AMPK/Lin28 pathway components in living cells, significantly advancing our understanding of MACC1's role in cancer metabolic plasticity.

What are the most promising directions for investigating MACC1's role in tumor metabolic adaptation to therapy?

The most promising directions for investigating MACC1's role in tumor metabolic adaptation to therapy include several integrated research approaches. First, researchers should implement longitudinal studies examining MACC1 and MACC1-AS1 expression dynamics during treatment response and resistance development, using biotin-conjugated MACC1 antibody to monitor protein levels in patient samples before, during, and after therapy. Metabolic flux analysis using stable isotope-labeled metabolites (13C-glucose, 13C-glutamine) could reveal how MACC1 overexpression redirects metabolic pathways under therapeutic pressure, particularly focusing on enhanced glycolysis and redox homeostasis mechanisms previously linked to MACC1 function . Development of therapy-resistant cell lines with modulated MACC1 expression would provide valuable models to dissect metabolic vulnerabilities that emerge during treatment adaptation. Single-cell approaches combining MACC1 protein detection with metabolic profiling could identify rare subpopulations with unique metabolic phenotypes that drive therapy resistance. Investigation of microenvironmental factors, particularly nutrient and oxygen gradients, would enhance understanding of how MACC1 enables adaptation to stressed conditions created by anti-angiogenic therapies . Finally, combination strategies targeting both MACC1-mediated metabolic adaptations and primary oncogenic drivers could be evaluated, utilizing dual inhibition of glycolysis alongside conventional chemotherapy or targeted agents. These multifaceted approaches promise to uncover MACC1's contribution to metabolic plasticity during therapy and identify novel intervention points to overcome treatment resistance.

Technical Considerations Table