CALS11 Antibody

What is CALS11 Antibody and what is its target protein?

CALS11 Antibody targets Calsarcin-1 (also known as Myozenin-2), a Z-disc protein found in striated muscle tissues. Calsarcin-1 is a member of a novel family of calcineurin-interacting proteins that localize to the sarcomere. This protein is approximately 32 kDa (human/mouse 264-aa, with ~88% identity between species) and interacts with α-actinin and calcineurin . Calsarcin-1 expression is primarily found in slow-twitch muscle fibers (soleus and plantaris) and is dependent on chronic motor neuron stimulation . The protein does not have catalytic activity itself but plays an important role in regulating signaling pathways in muscle cells .

What is the biological significance of Calsarcin-1 in cardiac function?

Calsarcin-1 plays a critical role in protecting against pathological cardiac hypertrophy through its interaction with calcineurin signaling pathways. Research has demonstrated that:

• Calsarcin-1 inhibits hypertrophy resulting from Gq-agonist stimulation, including angiotensin-II (Ang-II), endothelin-1, and phenylephrine

• Overexpression of Calsarcin-1 reduces expression of calcineurin-sensitive genes, including MCIP1.4

• In transgenic mice overexpressing Calsarcin-1 (CS1Tg), Ang-II treatment does not induce cardiac hypertrophy, unlike in wild-type mice

• CS1Tg mice show blunted induction of hypertrophic gene programs (atrial natriuretic factor, brain natriuretic peptide)

These findings indicate that Calsarcin-1 prevents Ang-II-induced cardiomyocyte hypertrophy at least partly through inhibition of calcineurin signaling, making it a potential target for treating pathological cardiac hypertrophy .

What applications is CALS11 Antibody suitable for?

Based on the available data, CALS11 Antibody has been validated for the following applications:

The antibody has been specifically designed to react with human samples using recombinant full-length protein corresponding to human CA11 as the immunogen .

How should I design an effective validation strategy for CALS11 Antibody?

An effective validation strategy for CALS11 Antibody should follow these evidence-based approaches:

• Cell line selection: Identify cells expressing Calsarcin-1 using RNA expression data (e.g., TPM >2) from databases like The Human Protein Atlas

• CRISPR knockout validation: Generate an isogenic CRISPR knockout (KO) cell line for the most rigorous validation

  • Use 8 common cell line backgrounds that are amenable to CRISPR-Cas9 technology

  • Test antibody performance against paired wild-type and KO cells

• Multiple application testing: Validate the antibody across different applications

  • Western blot: Test on cell lysates from wild-type and KO cells

  • IP: Test on non-denaturing cell lysates, evaluating immunocapture via WB

  • IF: Image mosaic of parental and KO cells in the same field to reduce bias

• Controls implementation :

  • Unstained cells to address autofluorescence

  • Negative cell populations not expressing Calsarcin-1

  • Isotype control (antibody of same class with no known specificity)

  • Secondary antibody-only control

• Peer review: Have results technically reviewed by scientific advisors before final determination of antibody quality

This comprehensive approach ensures reliable and reproducible results across research applications.

What factors should be considered when designing flow cytometry experiments with antibodies against intracellular proteins like Calsarcin-1?

When designing flow cytometry experiments for intracellular proteins like Calsarcin-1, researchers should consider several critical factors :

• Target localization and cell preparation:

  • Determine if the target is intracellular (requiring fixation and permeabilization)

  • For intracellular proteins like Calsarcin-1, cells must be fixed to prevent loss of cellular contents

• Antibody characteristics:

  • Know the primary antibody's clonality, host species, and epitope recognition site

  • For membrane-spanning antigens, determine if the antibody targets the intracellular C-terminal or extracellular N-terminal

• Proper controls:

  • Unstained cells: Address false positives from autofluorescence

  • Negative cells: Populations not expressing the protein of interest

  • Isotype control: Antibody of the same class with no known specificity

  • Secondary antibody control: Cells treated with only labeled secondary antibody

• Technical considerations:

  • Block with 10% normal serum from same host species as secondary antibody

  • Ensure cell viability >90% to avoid false positives from dead cells

  • Use appropriate cell concentration (10^5-10^6) to avoid clogging

  • Perform all steps on ice with PBS containing 0.1% sodium azide to prevent internalization

Understanding these factors is essential for generating reliable flow cytometry data, especially for intracellular muscle proteins like Calsarcin-1 .

What are the key considerations for antibody specificity assessment in experimental design?

Assessing antibody specificity is crucial for experimental integrity. Key considerations include :

• Knockout validation: The optimal methodology involves testing the antibody against:

  • Wild-type cells expressing the target protein

  • Isogenic CRISPR knockout cells lacking the target protein

• Multi-application testing: Test specificity across different applications:

  • Western blot: Look for correct band sizes and absence in KO cells

  • Immunoprecipitation: Verify target capture via subsequent WB

  • Immunofluorescence: Compare staining patterns between WT and KO cells

• Cross-reactivity assessment:

  • Test against closely related proteins (e.g., for CALS11, test against other calsarcins)

  • Verify no significant sequence homology with other proteins in the family

• Control implementation:

  • Include isotype controls to assess non-specific binding through Fc receptors

  • Use blocking agents to reduce background and improve signal-to-noise ratio

  • Implement secondary antibody-only controls to identify non-specific binding

• Data reporting and verification:

  • Document all validation results thoroughly

  • Have results reviewed by independent experts

  • Make validation data publicly available

This comprehensive approach helps ensure that experimental outcomes truly reflect the biology of the target protein rather than artifacts from non-specific antibody binding.

How do I establish the analytical measurement interval and proper controls for antibody-based detection methods?

Establishing a reliable analytical measurement interval (AMI) for antibody-based assays requires systematic validation and appropriate controls :

• Calibration curve establishment:

  • Generate a standard curve using serial dilutions of a verified standard

  • Plot using a 4 Parametric Logarithmic (4PL) model

  • Identify the analytical measuring interval where the assay provides reliable quantification

• Control implementation:

  • Include negative controls (samples known to lack the target)

  • Use positive controls with known concentrations of the target protein

  • Include calibration standards traceable to international reference materials

• Precision testing:

  • Test intra-assay precision (replicates within the same run)

  • Evaluate inter-assay precision (across different days)

  • Assess repeatability through multiple tests of the same samples

• Linearity determination:

  • Create linearity sample panels through serial 2-fold dilutions

  • Test recovery at multiple concentrations

  • Verify linear response across the reported range

• Detection limits:

  • Determine Limit of Detection (LOD) using appropriately diluted standards

  • Establish Limit of Quantification (LOQ) where reliable quantification begins

  • Document the upper limit of quantification

The established AMI should be clearly documented and reported with all experimental results to ensure proper interpretation of quantitative data .

What methods can be used to study protein-protein interactions involving Calsarcin-1?

Several methodologies can be employed to study Calsarcin-1 interactions with binding partners like calcineurin and α-actinin :

• Yeast two-hybrid screening:

  • Can identify novel interaction partners

  • Used to discover calsarcins as calcineurin-binding proteins

  • Helpful for mapping specific interaction domains

• Co-immunoprecipitation:

  • Using epitope-tagged proteins in transfected cells

  • With native proteins from cardiomyocytes

  • Triple-immunoprecipitation approach can demonstrate trimeric complexes

• Domain mapping:

  • Create N- and C-terminal truncations to characterize interaction domains

  • Combine with yeast two-hybrid assays

  • Complement with immunoprecipitation experiments

• Subcellular co-localization:

  • Immunostaining of cardiomyocytes

  • Analysis of cryosections from adult mouse heart and skeletal muscle

  • Use of Z-line markers like α-actinin for co-localization studies

Through these methods, researchers identified that:

• Amino acids 153-200 of calsarcin-1 are necessary for α-actinin-2 interaction

• Residues 217-240 are necessary for calcineurin binding

• Calsarcin-1 localizes to the sarcomere and overlaps with α-actinin at the Z-line

• Calcineurin also localizes to the Z-line in muscle cells

These findings demonstrate the power of combining multiple interaction analysis methods to build a comprehensive understanding of protein binding networks.

How can antibodies be used for quantitative assessment of neutralizing activity?

Antibodies can be used for quantitative assessment of neutralizing activity through specialized assays that measure functional inhibition. Key methodological considerations include :

• Assay principle:

  • Blocking Enzyme-Linked Immunosorbent Assay (ELISA) to detect neutralizing antibodies

  • Measure inhibition of binding between target protein and its receptor

  • Calculate percent signal inhibition compared to controls

• Semi-quantitative analysis workflow:

  • Calculate percent signal inhibition for samples

  • Generate a calibration curve with standardized materials

  • Interpolate sample concentrations from the curve

  • Report results in standardized units (e.g., BAU/mL)

• Reference materials:

  • Use international standards (e.g., WHO International Standards)

  • Include national reference materials for calibration

  • Ensure traceability to recognized standards

• Analytical considerations:

  • Establish a clear cutoff for positivity (e.g., 30% inhibition)

  • Define the analytical measuring interval (AMI)

  • Report numerical results only for samples within the AMI

• Interpretation:

  • Correlate neutralizing antibody levels with protective immunity

  • Consider the timing of sample collection relative to infection or vaccination

  • Acknowledge limitations in predicting in vivo protection

This approach has been successfully used to quantify neutralizing antibodies against pathogens like SARS-CoV-2, demonstrating the correlation between antibody levels and protection from infection .

How does the antibody-secreting cell (ASC) response develop during infection and how can it be measured?

The antibody-secreting cell (ASC) response follows a highly conserved timeline during infection that can be measured and utilized for diagnostic purposes :

• Timeline of ASC response:

  • ASCs appear in peripheral blood shortly after infection

  • Peak response occurs between day 7-8 of illness

  • Response largely disappears after day 14 from symptom onset

  • This timing is conserved across different bacterial and viral pathogens

• Measurement methods:

  • ELISpot to detect antigen-specific IgG, IgA, or IgM ASCs

  • Flow cytometry to enumerate plasmablasts

  • Antibody from lymphocyte supernatant (ALS) assays

• Diagnostic value:

  • ~90% sensitivity and >80% specificity for pathogen detection

  • Can distinguish between different pathogens (e.g., RSV vs. influenza)

  • Useful for identifying infection etiology when other methods fail

• Response kinetics by pathogen:

  Pathogen	ASC Detection Window	Peak Response	Key Findings
  Tuberculosis	Early in infection	Variable	86-90% sensitivity, 80% specificity for symptomatic TB vs. latent TB
  Pneumococcus	Day 7-10	~10-1,000 ASCs/million PBMCs	100% sensitivity and specificity in bacteremic pneumonia
  RSV	Day 7-14	~300 ASCs/million PBMCs at day 10	Detectable by day 2, 100% of cases by day 11
  Influenza	Day 4-11	~1,000 ASCs/million PBMCs	100% detection by days 4-11

• Research applications:

  • Studying B cell receptor evolution during immune response

  • Investigating variations in magnitude of ASC response

  • Developing novel diagnostic tests for infection

This approach provides valuable insights into infection biology and offers potential for new diagnostic methodologies with advantages over current methods.

What factors contribute to antibody specificity in experimental design?

Multiple factors contribute to antibody specificity in experimental design, with implications for research validity :

• Binding mode identification:

  • Different antibodies associate with distinct binding modes

  • Biophysics-informed models can identify and disentangle multiple binding modes

  • Computational analysis of selection experiments can reveal binding characteristics

• Selection methodology:

  • Phage display experiments against combinations of ligands

  • High-throughput sequencing and computational analysis

  • Identification of antibodies that discriminate between similar epitopes

• Validation approach:

  • Use of isogenic knockout cells as gold standard controls

  • Testing across multiple applications (WB, IP, IF)

  • Verification against closely related proteins

• Target characteristics:

  • Expression level in experimental system

  • Subcellular localization (membrane, cytoplasmic, nuclear)

  • Post-translational modifications

  • Accessibility of epitopes

• Protocol optimization:

  • Appropriate blocking to reduce non-specific binding

  • Optimal antibody concentration determination

  • Proper washing procedures

  • Addition of detergents or carriers to reduce background

By considering these factors in experimental design, researchers can significantly enhance antibody specificity and generate more reliable, reproducible results across different experimental systems and applications.

How can antibodies be used as therapeutic agents in disease treatment?

Antibodies have demonstrated considerable potential as therapeutic agents across various diseases, with several key applications and considerations :

• Neutralization mechanisms:

  • Direct binding to pathogens or target proteins

  • Blocking of protein-receptor interactions

  • Prevention of cellular entry for viruses

  • Inhibition of pathological signaling pathways

• Administration approaches:

  • Intravenous infusion for systemic distribution

  • Regular dosing schedules (e.g., once every eight weeks)

  • Long-acting formulations for extended protection

• Clinical applications:

  • Viral infections: Broadly neutralizing antibodies (bNAbs) against HIV or SARS-CoV-2

  • Autoimmune conditions: Targeting specific inflammatory pathways

  • Cancer: Binding to tumor-specific antigens

  • Cardiovascular disease: Modulating pathological signaling cascades

• Case study: SARS-CoV-2 antibody (SC27):

  • Discovered from a single patient with hybrid immunity

  • Able to neutralize all known variants of SARS-CoV-2

  • Targets the spike protein to prevent cell attachment

  • Identified using advanced antibody sequencing technology (Ig-Seq)

• Case study: Humanized CXCL12 antibody for alopecia areata:

  • Delays disease onset in mouse models

  • Modulates immune responses through specific pathways

  • Decreases T cell and dendritic cell/macrophage populations

  • Downregulates key genes including Ifng, Cd8a, Ccr5, Ccl4, Ccl5, and Il21r

This therapeutic potential demonstrates how antibodies can be engineered for specific disease targets, offering promising new treatment modalities across multiple conditions.

What are the essential controls and validation steps for antibody characterization?

Comprehensive antibody characterization requires rigorous controls and validation steps to ensure reliability and reproducibility :

• Experimental controls:

  • Isogenic knockout cell lines as gold standard negative controls

  • Positive control cells/tissues with verified target expression

  • Isotype controls matched to antibody class and species

  • Secondary antibody-only controls

  • Unstained samples to assess autofluorescence

• Application-specific validation:

  • Western blot: Verify band sizes, absence in KO cells, reproducibility

  • Immunoprecipitation: Confirm target capture via subsequent detection

  • Immunofluorescence: Compare staining patterns between positive and negative samples

  • Flow cytometry: Include viability dyes, isotype controls, blocking reagents

• Analytical validation parameters:

  • Linearity: Test through serial dilutions of positive samples

  • Precision: Evaluate intra- and inter-assay variability

  • Repeatability: Test same samples across multiple days

  • Detection limits: Determine LOD and LOQ

• Documentation and reporting:

  • Record all validation procedures and results

  • Publish validation data alongside research findings

  • Deposit data in public repositories

  • Include detailed methods sections in publications

• Calibration to standards:

  • Use international reference materials when available

  • Include calibration to national standards

  • Report results in standardized units for comparability

Following these validation steps ensures that antibody-based research produces reliable, reproducible, and translatable results that advance scientific understanding.

How does class switch recombination affect antibody specificity and function?

Class switch recombination (CSR) is a critical process that influences antibody specificity and function through changes in the constant regions of heavy chains :

• Mechanism of CSR:

  • Changes the constant heavy chain (CH) from Cμ (IgM) to downstream CH (Cγs, Cε, or Cα)

  • Occurs through DNA recombination and looping-out of intervening sequences

  • Requires activation-induced (cytidine) deaminase (AID)

  • Involves switch (S) regions that lie upstream of each CH region (except Cδ)

• Functional implications:

  • Different antibody classes (IgM, IgG, IgE, IgA) have distinct effector functions

  • Sequential class switching is required for generating high-affinity antibodies

  • Low-affinity IgE can compete with high-affinity IgE for receptor binding

  • This competition can prevent anaphylaxis and provide protective effects

• Research relevance:

  • Understanding class switching helps interpret antibody responses

  • Different isotypes (IgG, IgM, IgA) indicate different stages of immune response

  • Detection of specific isotypes provides insight into infection timeline

  • Measuring class-switched antibodies can indicate mature immune responses

This process represents a fundamental aspect of antibody biology that directly impacts experimental design decisions, particularly in selecting appropriate isotypes for detection and in interpreting results of serological assays.

What recent advances have occurred in antibody technology for research and therapeutic applications?

Recent advances in antibody technology have significantly enhanced both research capabilities and therapeutic applications :

• Computational antibody design:

  • Biophysics-informed models to predict antibody-antigen interactions

  • Identification of different binding modes for similar ligands

  • Custom antibody design with specific binding profiles

  • Computational prediction of cross-reactivity and specificity

• Novel therapeutic antibodies:

  • Broadly neutralizing antibodies against viral pathogens

  • Discovery of SC27, an antibody effective against all SARS-CoV-2 variants

  • Humanized antibodies with reduced immunogenicity

  • Antibodies targeting specific signaling pathways (e.g., CXCL12 for alopecia areata)

• Advanced screening methodologies:

  • High-throughput phage display with multiple ligand combinations

  • Single-cell RNA sequencing to analyze immune responses

  • Ig-Seq technology combining single-cell DNA sequencing and proteomics

  • Systematic approaches to antibody validation

• Therapeutic applications:

  • Long-acting antibody infusions for prevention (e.g., HIV prevention)

  • Antibody treatments for immunocompromised patients

  • Enhanced understanding of hybrid immunity (combined vaccination and infection)

  • Development of universal antibodies effective against multiple variants

These advances demonstrate the rapidly evolving landscape of antibody technology, offering new opportunities for both research tools and therapeutic interventions across multiple disease areas.

How can antibodies be used to study the expression patterns and functions of Calsarcin-1 in different muscle types?

Antibodies provide valuable tools for investigating Calsarcin-1 expression patterns and functions across different muscle types :

• Expression pattern analysis:

  • Western blot analysis of different muscle types shows Calsarcin-1 is expressed in cardiac and slow-twitch skeletal muscle fibers

  • Only faint expression is detected in gastrocnemius muscle, confirming slow fiber-restricted expression

  • Northern blot analysis demonstrates upregulation during differentiation of C2 skeletal muscle cell line

• Subcellular localization:

  • Immunostaining of neonatal rat cardiomyocytes shows Calsarcin-1 localizes to the sarcomere

  • Co-staining with α-actinin confirms Z-line localization

  • Similar patterns observed in adult mouse heart and skeletal muscle sections

• Functional studies:

  • Overexpression studies in cardiomyocytes using adenoviral gene transfer

  • Generation of transgenic mice (CS1Tg) overexpressing Calsarcin-1

  • Comparison of wild-type and CS1Tg mice under Ang-II stimulation

  • Assessment of hypertrophic gene program induction (ANF, BNP)

• Interaction analysis:

  • Coimmunoprecipitation of Calsarcin-1 with calcineurin and α-actinin

  • Domain mapping to identify interaction regions

  • Triple-immunoprecipitation to demonstrate trimeric complexes

  • Yeast two-hybrid screening to identify additional binding partners

These methodologies have revealed that Calsarcin-1:

• Is predominantly expressed in slow-twitch muscle fibers and throughout cardiac development

• Localizes to the Z-line of the sarcomere

• Interacts with calcineurin and α-actinin through specific domains

• Plays a protective role against pathological cardiac hypertrophy

What are the best practices for data reporting and standardization in antibody-based research?

Standardized data reporting is essential for ensuring reproducibility and comparability in antibody-based research :

• Antibody validation reporting:

  • Document complete validation procedures

  • Report testing across multiple applications

  • Include positive and negative controls used

  • Specify exact protocols for validation experiments

• Data table standardization:

  • Use consistent formats for data presentation

  • Include all relevant experimental parameters

  • Provide raw data alongside processed results

  • Ensure tables contain adequate metadata

• Clinical and research data standards:

  • Report patient demographics and sample characteristics

  • Document collection methods and timing

  • Include biochemistry, treatment, and follow-up data

  • Use standardized diagnostic criteria

• Technical reporting requirements:

  • Specify antibody source, catalog number, and lot

  • Report dilutions, incubation times, and detection methods

  • Include analytical parameters (LOD, LOQ, AMI)

  • Document calibration to reference standards

• Public data sharing:

  • Deposit validation data in public repositories

  • Share sequence data in appropriate databases (e.g., GISAID, European Nucleotide Archive)

  • Make raw data available alongside publications

  • Follow FAIR principles (Findable, Accessible, Interoperable, Reusable)