MLXIP Antibody

What is MLXIP and why is it an important research target?

MLXIP (MLX Interacting Protein, also known as MondoA) is a member of the Myc superfamily of transcription factors that functions as part of a heterodimer with Max-like protein X (MLX) to activate transcription. It binds to the canonical E box sequence 5'-CACGTG-3' and plays a crucial role in transcriptional activation of glycolytic target genes and glucose-responsive gene regulation . MLXIP contributes to the regulation of glucose homeostasis as the MLXIP/MLX heterodimer activates expression of thioredoxin-interacting protein (TXNIP), a potent inhibitor of cellular glucose uptake and aerobic glycolysis . Additionally, the mammalian target of rapamycin (mTOR) interacts with this pathway by binding to MLXIP, thereby preventing MLXIP/MLX heterodimer formation . MLXIP interaction with Myc may also be involved in metabolic reprogramming and tumorigenesis, making it an important target for cancer research .

Which applications are MLXIP antibodies validated for?

MLXIP antibodies have been validated for multiple applications across different research methodologies:

It is recommended to optimize dilutions for each specific experimental system to obtain optimal results, as antibody performance can be sample-dependent .

What are the key considerations for choosing between different MLXIP antibody clones?

When selecting an MLXIP antibody, researchers should consider:

• Target epitope region: Different antibodies target distinct regions of MLXIP (N-terminal, middle region, C-terminal). For example, some antibodies target amino acids 1-217 , others target regions near the N-terminus , and some target the C-terminal region . The epitope location can affect detection of specific isoforms or post-translationally modified forms.

• Isoform detection: MLXIP has multiple isoforms, including isoform 1 (~110 kDa) and isoform 3 (~69 kDa) . Some antibodies can recognize multiple isoforms while others may be more specific.

• Observed molecular weight: The calculated molecular weight of MLXIP is approximately 100-101 kDa, but the observed molecular weight in Western blots is often around 130 kDa , suggesting post-translational modifications.

• Host species and clonality: Most MLXIP antibodies are rabbit polyclonals , though some mouse monoclonal options exist . Consider the host species in relation to your secondary detection systems and other antibodies in multiplexed experiments.

• Validated applications: Ensure the antibody has been validated for your specific application through published literature or manufacturer validation data .

What are the recommended protocols for using MLXIP antibodies in Western blot experiments?

For optimal Western blot results with MLXIP antibodies:

• Sample preparation:

  • Use established cell lines known to express MLXIP, such as K-562, HeLa, Jurkat, or 293T cells

  • Prepare whole cell lysates using standard lysis buffers containing protease inhibitors

  • Load 15-50 μg of total protein per lane as demonstrated in validated experiments

• Electrophoresis and transfer:

  • Use standard SDS-PAGE conditions, ensuring adequate resolution in the 100-130 kDa range

  • For complete detection of MLXIP isoforms, use gels with appropriate resolution range (e.g., 6-12% acrylamide)

• Antibody incubation:

  • Block membrane using standard blocking buffer (e.g., 5% non-fat dry milk or BSA in TBST)

  • Dilute primary MLXIP antibody according to manufacturer recommendations (typically 1:200-1:1000 or 1-2 μg/mL )

  • Incubate at 4°C overnight for optimal results

  • Use appropriate HRP-conjugated secondary antibodies at recommended dilutions

• Detection:

  • Develop using ECL technique with appropriate exposure times (30 seconds has been reported as effective )

  • Expected band size: calculated 101 kDa; observed typically around 130 kDa

  • Some antibodies may detect multiple isoforms (isoform 1 at ~110 kDa and isoform 3 at ~69 kDa)

• Controls:

  • Include positive control lysates from cells known to express MLXIP

  • Consider using MLXIP knockdown or knockout samples as negative controls when available

How should MLXIP antibodies be optimized for immunohistochemistry applications?

For immunohistochemistry with MLXIP antibodies:

• Sample preparation:

  • MLXIP is widely expressed in adult tissues, with highest abundance in skeletal muscle

  • Both human and mouse skeletal muscle tissues have been validated for IHC applications

  • Use standard fixation protocols (typically formalin fixation and paraffin embedding)

• Antigen retrieval:

  • Recommended antigen retrieval with TE buffer pH 9.0

  • Alternatively, citrate buffer pH 6.0 may be used

  • Optimize retrieval conditions for your specific tissue and fixation method

• Antibody incubation:

  • Block sections using appropriate blocking solution

  • Dilute MLXIP antibody at 1:20-1:200 as recommended

  • Incubate at optimal temperature and duration (typically 4°C overnight or room temperature for 1-2 hours)

• Detection system:

  • Use polymer-based or biotin-streptavidin detection systems with appropriate secondary antibodies

  • Include proper controls (primary antibody omission, isotype controls)

• Counterstaining and mounting:

  • Use standard hematoxylin counterstaining

  • Mount with compatible mounting medium

• Evaluation:

  • MLXIP shows both cytoplasmic and nuclear localization, with subcellular distribution dependent on cellular conditions

  • Evaluate staining in the context of known MLXIP biology (e.g., mitochondrial outer membrane, cytoplasmic, and nuclear localization patterns)

What are the critical factors for successful immunoprecipitation using MLXIP antibodies?

For effective immunoprecipitation of MLXIP:

• Antibody selection:

  • Choose antibodies specifically validated for IP applications

  • Use 0.5-4.0 μg antibody for 1.0-3.0 mg of total protein lysate as recommended

• Lysate preparation:

  • Use cell lines with documented MLXIP expression (e.g., K-562 cells)

  • Prepare lysates using gentle lysis buffers that preserve protein-protein interactions

  • Include protease and phosphatase inhibitors to prevent degradation and modification

• Pre-clearing step:

  • Pre-clear lysates with appropriate control beads/resin to reduce non-specific binding

  • Use protein A/G beads for rabbit polyclonal antibodies

• Immunoprecipitation procedure:

  • Incubate lysates with MLXIP antibody overnight at 4°C with gentle rotation

  • Add appropriate beads and continue incubation

  • Wash stringently to reduce background while preserving specific interactions

  • Elute under appropriate conditions for downstream applications

• Controls and validation:

  • Include isotype control antibodies to identify non-specific interactions

  • Validate IP success by Western blot, using a portion of the IP product

  • Consider using a second MLXIP antibody recognizing a different epitope for validation in Western blot

• Co-IP considerations:

  • MLXIP forms heterodimers with MLX, which can be co-immunoprecipitated

  • Consider potential interactions with mTOR or components of glucose sensing pathways

How can ChIP assays using MLXIP antibodies be optimized to study transcriptional regulation?

Chromatin immunoprecipitation (ChIP) with MLXIP antibodies requires careful optimization:

• Experimental design:

  • Select ChIP-certified antibodies specifically validated for this application

  • MLXIP binds DNA as a heterodimer with MLX at canonical E box sequences (5'-CACGTG-3')

  • Consider known MLXIP target genes, including those involved in glycolytic pathways

• Chromatin preparation:

  • Optimize crosslinking conditions (typically 1% formaldehyde for 10-15 minutes)

  • Ensure effective sonication/fragmentation to generate appropriate DNA fragment sizes (200-500 bp)

  • Verify fragmentation efficiency by agarose gel electrophoresis

• Immunoprecipitation:

  • Use optimized antibody amounts based on preliminary titration experiments

  • Include appropriate controls (IgG control, input DNA, positive control antibody)

  • Extend incubation times (overnight at 4°C) to enhance binding efficiency

• Washing and elution:

  • Use stringent washing conditions to reduce background

  • Optimize reverse crosslinking conditions

• PCR primers design:

  • Design primers around known or predicted MLXIP binding sites

  • Include primers for established MLXIP target genes as positive controls

  • Consider primers for known E-box containing promoters

• Data analysis:

  • Normalize ChIP-qPCR data to input DNA and IgG controls

  • For ChIP-seq applications, use appropriate peak calling algorithms

  • Consider integrated analysis with transcriptomic data to correlate binding with expression changes

• Validation:

  • Confirm findings with reporter assays or directed mutagenesis of binding sites

  • Consider comparing wildtype and MLXIP knockdown/knockout conditions

What strategies are effective for studying MLXIP subcellular localization and shuttling using immunofluorescence?

MLXIP exhibits complex subcellular localization patterns, including cytoplasmic, nuclear, and mitochondrial outer membrane localization . To effectively study its shuttling:

• Antibody selection and optimization:

  • Use antibodies validated for immunofluorescence/ICC applications

  • Optimize antibody dilution (recommended 1:10-1:100)

  • HepG2 cells have been validated for IF/ICC detection of MLXIP

• Experimental conditions to consider:

  • Glucose levels: MLXIP localization responds to cellular glucose levels

  • Cell cycle stage: May affect transcription factor distribution

  • Cell density and growth conditions: Can influence metabolic state

• Co-localization studies:

  • Mitochondrial markers (e.g., MitoTracker or TOMM20) to confirm outer mitochondrial membrane localization

  • Nuclear markers (e.g., DAPI) to assess nuclear translocation

  • MLX co-staining to examine heterodimer formation and co-localization

• Live-cell imaging considerations:

  • For dynamic studies, consider GFP-tagged MLXIP constructs

  • Time-lapse imaging following glucose level changes

• Fixation and permeabilization optimization:

  • Test multiple fixation methods (paraformaldehyde, methanol) as they may differentially preserve subcellular structures

  • Optimize permeabilization to ensure antibody access while preserving cellular architecture

• Quantitative analysis:

  • Measure nuclear/cytoplasmic ratios across conditions

  • Quantify co-localization coefficients with mitochondrial markers

  • Track dynamic changes in response to perturbations

• Advanced microscopy techniques:

  • Consider super-resolution microscopy for detailed subcellular localization

  • FRET analysis for protein-protein interactions if using fluorescently tagged constructs

How can researchers effectively use MLXIP antibodies to investigate glucose-responsive gene regulation pathways?

To study MLXIP's role in glucose-responsive gene regulation:

• Experimental design considerations:

  • MLXIP/MLX heterodimer activates expression of thioredoxin-interacting protein (TXNIP), which inhibits glucose uptake and glycolysis

  • mTOR suppresses TXNIP pathway activation by binding to MLXIP

  • Design experiments with varying glucose concentrations to observe dynamic responses

• Combined methodological approaches:

  • ChIP or ChIP-seq to identify MLXIP binding sites under different glucose conditions

  • RNA-seq to correlate binding with transcriptional changes

  • Western blotting to assess MLXIP and target protein levels

  • Co-IP to examine dynamic interaction partners under different metabolic states

• Key pathway components to monitor:

  • MLXIP and MLX levels and heterodimer formation

  • TXNIP expression as a primary downstream target

  • mTOR interaction with MLXIP under varying conditions

  • Glucose uptake and glycolytic flux measurements as functional readouts

• Perturbation strategies:

  • MLXIP knockdown or knockout using siRNA or CRISPR-Cas9

  • mTOR inhibitors to assess pathway regulation

  • Glucose level manipulation protocols

  • Hypoxia conditions that may affect metabolic programming

• Temporal considerations:

  • Time-course experiments to capture dynamic responses

  • Acute vs. chronic glucose level changes

• Cell type selection:

  • Focus on metabolically relevant cell types (e.g., hepatocytes, myocytes, adipocytes)

  • Consider tissue-specific expression patterns, with skeletal muscle showing highest abundance

What are common issues with MLXIP antibody-based experiments and how can they be resolved?

How do different isoforms and post-translational modifications of MLXIP affect antibody recognition and experimental interpretation?

MLXIP exists in multiple isoforms and undergoes various post-translational modifications, which can significantly impact antibody recognition:

• Isoform considerations:

  • MLXIP has multiple isoforms, including isoform 1 (~110 kDa) and isoform 3 (~69 kDa)

  • The calculated molecular weight is approximately 100-101 kDa, but the observed molecular weight is often around 130 kDa, suggesting extensive post-translational modifications

  • Antibody epitope location determines which isoforms will be detected

  • N-terminal targeting antibodies may detect different isoform subsets than C-terminal antibodies

• Post-translational modifications:

  • Phosphorylation may affect subcellular localization and DNA binding

  • MLXIP's apparent higher molecular weight (130 kDa vs. calculated 100 kDa) suggests significant post-translational modifications

  • Modified forms may show different subcellular distributions or functional properties

• Experimental strategies:

  • Use antibodies targeting different epitopes to compare detection patterns

  • Consider phosphatase treatment of samples to assess phosphorylation impact

  • When interpreting localization studies, consider that modifications may affect shuttling between compartments

• Data interpretation considerations:

  • Always report both calculated and observed molecular weights

  • Specify which antibody (targeting which epitope) was used for detection

  • Consider running parallel experiments with antibodies recognizing different regions

  • For functional studies, determine which isoforms are being measured and their relative contributions

What controls and validation methods are essential for ensuring specificity and reproducibility in MLXIP antibody experiments?

To ensure robust and reproducible MLXIP antibody experiments:

• Essential controls:

  • Positive controls: Cell lines with known MLXIP expression (K-562, HeLa, Jurkat, 293T)

  • Negative controls: MLXIP knockdown or knockout samples where available

  • Isotype controls: Particularly important for IP, ChIP, and flow cytometry applications

  • Secondary antibody-only controls: To assess non-specific binding of secondary detection systems

• Antibody validation strategies:

  • Multiple antibody approach: Use antibodies targeting different epitopes to confirm results

  • Peptide competition: Pre-incubation with immunizing peptide should abolish specific signal

  • Genetic validation: Use samples with MLXIP genetic modification (siRNA, CRISPR)

  • Cross-application validation: Confirm findings using multiple techniques (e.g., WB and IF)

• Reproducibility considerations:

  • Antibody lot testing: Test new lots against previous ones before adoption

  • Detailed protocol documentation: Record all experimental variables

  • Consistency in sample preparation: Standardize lysis buffers, fixation protocols, etc.

  • Quantitative assessment: Use quantitative measures rather than subjective assessments

• Advanced validation approaches:

  • Mass spectrometry validation of immunoprecipitated proteins

  • CRISPR-Cas9 knockout followed by antibody testing

  • Recombinant protein controls at known concentrations

  • Cross-reactivity testing across species if working with non-human models

How are MLXIP antibodies being used to investigate metabolic reprogramming in cancer research?

MLXIP's role in glucose metabolism makes it particularly relevant to cancer research, where metabolic reprogramming is a hallmark:

• Current research applications:

  • MLXIP interaction with Myc may be involved in metabolic reprogramming and tumorigenesis

  • MLXIP/MLX regulation of TXNIP affects glucose uptake and glycolysis, processes often dysregulated in cancer

  • Antibody-based detection of MLXIP expression and localization in tumor samples

  • Investigation of mTOR-MLXIP interactions in cancer contexts

• Methodological approaches:

  • IHC analysis of MLXIP expression in tumor microarrays

  • Co-localization studies with metabolic enzymes in cancer cell lines

  • ChIP-seq to identify altered MLXIP binding patterns in cancer models

  • IP-mass spectrometry to identify cancer-specific interaction partners

• Key research questions being addressed:

  • How does MLXIP expression correlate with cancer progression and prognosis?

  • Does MLXIP subcellular localization differ in cancer cells compared to normal cells?

  • Can targeting MLXIP-dependent pathways provide therapeutic opportunities?

  • How do oncogenic signals modify MLXIP function and target gene selection?

• Technical considerations:

  • Use of patient-derived xenografts and primary cancer samples

  • Integration with metabolomics approaches

  • Comparison across cancer types with different metabolic signatures

What are the methodological considerations for multiplex approaches combining MLXIP antibodies with other metabolic regulators?

For comprehensive analysis of metabolic regulation networks involving MLXIP:

• Multiplex immunofluorescence considerations:

  • Antibody selection: Ensure primary antibodies are from different host species

  • Cross-reactivity testing: Validate antibody specificity in multiplex context

  • Sequential staining protocols: Consider tyramide signal amplification for sequential detection

  • Spectral unmixing: Employ appropriate controls for multi-fluorophore separation

• Co-immunoprecipitation strategies:

  • Sequential IP: First IP with MLXIP antibody followed by secondary IP for interacting partners

  • Combined IP: Simultaneous use of antibodies against MLXIP and potential partners

  • Mass spectrometry analysis of MLXIP complexes under different metabolic conditions

  • Proximity ligation assays to confirm protein-protein interactions in situ

• Integrated ChIP approaches:

  • Sequential ChIP (Re-ChIP): To identify genomic regions co-bound by MLXIP and other factors

  • ChIP-seq with motif analysis: To identify co-occurring binding motifs for MLXIP and other factors

  • Integration with accessibility data (ATAC-seq) and histone modification profiles

  • CUT&RUN or CUT&Tag alternatives for higher resolution binding profiles

• Key interaction partners to consider:

  • MLX: Primary heterodimer partner

  • mTOR: Regulates MLXIP-MLX interaction

  • ChREBP: Another glucose-responsive transcription factor with overlapping functions

  • TXNIP: Key downstream target and metabolic regulator

How can researchers design effective experiments to distinguish MLXIP functions from closely related transcription factors?

MLXIP belongs to a family of transcription factors with overlapping functions, particularly ChREBP (MondoB):

• Antibody selection strategies:

  • Choose antibodies validated for specificity against related family members

  • Verify cross-reactivity profiles against recombinant proteins

  • Select antibodies targeting divergent regions between family members

• Genetic approaches:

  • CRISPR-Cas9 knockout of MLXIP with rescue experiments using related factors

  • Selective knockdown using siRNA targeting unique sequence regions

  • Domain swap experiments to identify functional specificities

• Binding site discrimination:

  • Compare ChIP-seq profiles of MLXIP and related factors

  • Motif analysis to identify subtle binding preference differences

  • In vitro DNA binding assays with purified proteins and variant binding sites

• Functional readouts:

  • Transcriptome profiling after selective knockdown

  • Metabolic flux analysis to identify factor-specific metabolic impacts

  • Promoter-reporter assays with mutations in binding sites

• Context-dependent approaches:

  • Tissue-specific expression analysis (MLXIP is highest in skeletal muscle)

  • Response to different metabolic stimuli that may differentially affect family members

  • Cell-type specific regulatory network analysis

• Temporal dynamics:

  • Time-course experiments to identify differences in activation/deactivation kinetics

  • Pulse-chase approaches to measure protein stability differences

  • Real-time imaging of factor recruitment to target loci

What is a recommended experimental workflow for investigating MLXIP-mediated transcriptional regulation in metabolic disease models?

For studying MLXIP in metabolic disease contexts, consider this integrated approach:

• Expression profiling:

  • Western blot analysis of MLXIP levels across disease models using validated antibodies (1:200-1:1000 dilution)

  • IHC assessment of tissue-specific expression patterns (1:20-1:200 dilution)

  • qPCR analysis of MLXIP and MLX mRNA levels

• Localization studies:

  • IF/ICC to determine subcellular distribution (1:10-1:100 dilution)

  • Subcellular fractionation followed by Western blot

  • Compare distribution patterns between healthy and disease states

• DNA binding and target gene regulation:

  • ChIP-seq using ChIP-certified antibodies to map genome-wide binding

  • qRT-PCR of known target genes, particularly TXNIP

  • Reporter assays with E-box containing promoters

• Protein interactions:

  • Co-IP of MLXIP and MLX to assess heterodimer formation (0.5-4.0 μg antibody for 1.0-3.0 mg lysate)

  • IP-mass spectrometry to identify novel interaction partners

  • Investigation of mTOR-MLXIP interaction under different metabolic conditions

• Functional manipulation:

  • CRISPR-Cas9 or siRNA-mediated knockdown/knockout

  • Overexpression studies with wildtype and mutant MLXIP

  • Metabolic flux analysis following MLXIP manipulation

• Integration with clinical parameters:

  • Correlation of MLXIP expression/localization with disease markers

  • Response to therapeutic interventions

What antibody-based approaches are most effective for studying MLXIP in the context of mitochondrial metabolism?

Given MLXIP's association with the mitochondrial outer membrane , specialized approaches are needed:

• Localization studies:

  • High-resolution microscopy with co-staining for mitochondrial markers

  • Super-resolution techniques to precisely map MLXIP location on mitochondria

  • IF with recommended dilutions (1:10-1:100)

• Biochemical fractionation:

  • Mitochondrial isolation followed by Western blot (1:200-1:1000 dilution)

  • Protease protection assays to determine membrane topology

  • Density gradient separation of mitochondrial compartments

• Proximity-based approaches:

  • Proximity ligation assays to detect MLXIP interactions with mitochondrial proteins

  • BioID or APEX2 proximity labeling with MLXIP as bait

  • FRET-based detection of protein interactions at mitochondrial membranes

• Functional assays:

  • Mitochondrial respiration measurements after MLXIP manipulation

  • Assessment of glucose oxidation vs. glycolysis

  • Mitochondrial membrane potential in response to MLXIP perturbation

• Perturbation approaches:

  • Mitochondrial stress induction (e.g., FCCP, antimycin A) and assessment of MLXIP response

  • Glucose deprivation/reintroduction experiments

  • Hypoxia response studies

• Advanced microscopy techniques:

  • Live-cell imaging of fluorescently tagged MLXIP in relation to mitochondria

  • Time-lapse studies during metabolic transitions

  • Correlative light and electron microscopy for ultrastructural localization

How should researchers approach quantification and statistical analysis of MLXIP antibody-based experimental data?

Robust quantification and statistical analysis are essential for reproducible MLXIP research:

• Western blot quantification:

  • Normalize MLXIP signal to appropriate loading controls

  • Consider the non-linear nature of chemiluminescent detection

  • Use biological replicates (n≥3) for statistical power

  • Report both observed molecular weight (typically 130 kDa) and band intensity measures

• Immunofluorescence quantification:

  • Measure nuclear/cytoplasmic ratios for localization studies

  • Use z-stack acquisitions to capture full signal

  • Implement automated, unbiased analysis workflows

  • Report co-localization coefficients with appropriate controls

• ChIP data analysis:

  • For ChIP-qPCR: Normalize to input and IgG controls

  • For ChIP-seq: Use appropriate peak calling algorithms

  • Perform motif enrichment analysis for E-box sequences

  • Integrate with gene expression data to identify functional binding

• Statistical approaches:

  • Use appropriate statistical tests based on data distribution

  • Correct for multiple testing when analyzing genome-wide data

  • Implement mixed-effects models for data with nested variables

  • Report effect sizes alongside p-values

• Visualization strategies:

  • Present full blot images with molecular weight markers

  • Use consistent scales for comparative analyses

  • Include representative images alongside quantification

  • Consider dimensionality reduction for complex datasets

• Replication and validation:

  • Distinguish technical from biological replicates

  • Validate key findings using complementary methodologies

  • Consider sample size calculations for appropriate power

What criteria should be used to evaluate antibody specificity in MLXIP research and how do they impact data interpretation?

Critical evaluation of MLXIP antibody specificity is crucial for reliable research: