FAM185A antibodies are polyclonal or recombinant reagents designed to detect the FAM185A protein in various experimental settings. These antibodies are primarily used for:
Immunohistochemistry (IHC): Detecting cytoplasmic FAM185A expression in human tissues (e.g., strong positivity in duodenal glandular cells) .
Western Blot (WB) and ELISA: Quantifying protein levels in lysates or serum samples .
Specificity: Antibodies like 20911-1-AP are validated via knockout/knockdown controls in WB and IHC .
Cross-reactivity: No significant cross-reactivity with homologous proteins reported, though isoform-specific detection requires further study (isoform 2 lacks a 118 aa segment compared to isoform 1) .
Functional Studies: No peer-reviewed studies directly link FAM185A antibodies to mechanistic insights or therapeutic targeting. Current use is restricted to basic research .
Disease Associations: FAM185A is tentatively linked to megaesophagus (GeneCards ), but causal relationships remain unconfirmed.
Antibody Selection: Prioritize antibodies with application-specific validation (e.g., HPA020470 for IHC, 20911-1-AP for WB).
Controls: Include recombinant FAM185A protein (e.g., Novus Biologicals ) for competitive assays.
FAM185A (family with sequence similarity 185, member A) is a human protein encoded by the FAM185A gene (Gene ID: 222234). The protein consists of 393 amino acids with a calculated molecular weight of 42 kDa, although it is often observed at both 42 kDa and 30 kDa in experimental settings . The protein is also known as Protein FAM185A, and its UniProt ID is Q8N0U4 . The gene's GenBank accession number is BC029175 .
While the precise function of FAM185A remains under investigation, its expression pattern can provide insights into potential biological roles. According to human protein atlas data, FAM185A exhibits differential expression across various cell types .
Several validated antibodies against FAM185A are available for research applications:
| Antibody ID | Type | Host | Format | Primary Applications | Reactivity |
|---|---|---|---|---|---|
| 20911-1-AP | Polyclonal | Rabbit IgG | Unconjugated | WB, IHC, ELISA | Human |
| HPA020470 | Polyclonal | Rabbit | Unconjugated | WB, IF, IHC | Human |
These antibodies have been generated using specific immunogens derived from FAM185A protein sequences. For instance, the 20911-1-AP antibody was generated using a FAM185A fusion protein (Ag15041) , while HPA020470 was generated using a specific sequence fragment: RTLKEWTLQVSPFGRLRARLPCHLAVRPLDPLTYPDGDRVLVAVCGVEGGVRGLDGLQVKYDEDLEEMAIVSDTIHPQASVEV .
For Western blot applications using FAM185A antibodies, the following methodology is recommended:
Antibody dilution: The optimal dilution range for 20911-1-AP is 1:500-1:2000 . For HPA020470, a concentration of 0.04-0.4 μg/mL is recommended .
Sample preparation: FAM185A has been successfully detected in various human cell lines including HeLa, HEK-293, and MCF-7 cells .
Expected bands: Researchers should anticipate bands at approximately 42 kDa (calculated molecular weight) and 30 kDa (potentially a splice variant or processed form) .
Optimization note: As with all antibodies, titration in each specific experimental system is highly recommended to obtain optimal results, as signal strength can vary between cell and tissue types .
Protocol specificity: Follow the manufacturer-specific protocols provided with each antibody for best results. For instance, Proteintech provides specific WB protocols for their FAM185A antibody (20911-1-AP) .
For optimal immunohistochemistry applications with FAM185A antibodies:
Antibody dilution: Use 20911-1-AP at 1:20-1:200 for IHC applications . For HPA020470, the recommended dilution is 1:50-1:200 .
Antigen retrieval: For 20911-1-AP, antigen retrieval with TE buffer pH 9.0 is suggested. Alternatively, citrate buffer pH 6.0 can be used .
Positive controls: Human hepatocirrhosis tissue and human spleen tissue have been validated as positive controls for FAM185A detection .
Signal specificity: Careful optimization of antibody concentration is essential to minimize background staining while maximizing specific signal detection.
Visualization system: Standard detection systems compatible with rabbit antibodies are suitable for visualization of FAM185A staining.
To ensure optimal stability and performance of FAM185A antibodies:
Cross-reactivity is a significant concern in antibody-based research. For FAM185A antibodies:
Validation through multiple approaches: Combine different detection methods (e.g., WB, IHC, and IF) to confirm specificity. Consistency across methods increases confidence in antibody specificity .
Genetic approaches: Consider using CRISPR/Cas9 knockout or siRNA knockdown of FAM185A as negative controls to validate antibody specificity. This is particularly important given the potential for genetic variation in human samples .
Recombinant expression validation: Some FAM185A antibodies, like HPA020470, have undergone enhanced validation through recombinant expression systems . This validation approach provides stronger evidence for antibody specificity.
Multiple antibody comparison: Use antibodies from different sources or those targeting different epitopes of FAM185A to confirm results. Consistent results with different antibodies provide stronger evidence for specific detection .
Pre-absorption controls: Consider performing pre-absorption controls with recombinant FAM185A protein to demonstrate binding specificity of the antibody.
Genetic variations can significantly impact antibody recognition and experimental interpretations:
Single nucleotide polymorphisms (SNPs): Genetic variations in the FAM185A gene might alter epitopes recognized by antibodies. This is particularly relevant for polyclonal antibodies that recognize multiple epitopes .
Splice variants: The observation of both 42 kDa and 30 kDa bands suggests potential splice variants or post-translational modifications of FAM185A . Researchers should consider which isoform is relevant to their specific research question.
Population differences: Consider the genetic background of your biological samples, as different populations may exhibit different frequencies of genetic variants that could affect antibody binding .
Epitope knowledge: Understanding the specific epitope(s) recognized by your antibody can help predict potential impacts of genetic variations. For example, the immunogen sequence for HPA020470 is known, allowing researchers to assess whether known polymorphisms occur within this region .
Controls with variant sequences: In cases where specific variants are suspected, consider using recombinant proteins with the variant sequence as controls to assess potential impacts on antibody binding .
While standard immunoprecipitation (IP) protocols provide a starting point, optimization for FAM185A requires specific considerations:
Antibody selection: For IP applications, choose antibodies that have been validated for this purpose or those with high affinity. Polyclonal antibodies often perform well in IP due to their recognition of multiple epitopes .
Lysate preparation:
Use buffer systems that maintain native protein conformation while efficiently extracting FAM185A
Consider the subcellular localization of FAM185A when selecting extraction methods
Include appropriate protease and phosphatase inhibitors to prevent degradation
Antibody-bead coupling:
Pre-clear lysates to reduce non-specific binding
Consider crosslinking the antibody to beads to prevent antibody co-elution
Optimize antibody:bead ratios for maximum capture efficiency
Washing conditions:
Balance stringency to minimize background while maintaining specific interactions
Consider a gradient of salt concentrations in wash buffers to determine optimal conditions
Include controls for non-specific binding using isotype-matched control antibodies
Elution and detection:
Optimize elution conditions based on downstream applications
Confirm successful precipitation through Western blotting using a different FAM185A antibody that recognizes a different epitope
Discrepancies between RNA and protein levels are common in biological research and require careful interpretation:
Post-transcriptional regulation: FAM185A may be subject to microRNA regulation or other post-transcriptional mechanisms that affect the correlation between mRNA and protein levels .
Protein stability and turnover: Differences in protein half-life compared to mRNA stability can lead to temporal disconnections between transcript and protein abundance .
Detection sensitivity differences: RNA detection methods (e.g., RNA-seq) often have different sensitivity thresholds compared to protein detection methods (e.g., Western blot, IHC) .
Tissue and cell-type specificity: RNA expression data from single-cell sequencing indicates differential expression across cell types. Consider whether your protein detection method is analyzing the same cell population as your RNA data .
Methodological validation:
Confirm antibody specificity through multiple approaches
Consider quantitative protein methods (e.g., mass spectrometry) to validate antibody-based detection
When possible, perform RNA and protein analyses on the same samples to minimize biological variability
Multiplexed immunofluorescence allows simultaneous detection of multiple proteins, requiring specific optimization for FAM185A:
Antibody compatibility:
Ensure primary antibodies originate from different host species to avoid cross-reactivity
If using multiple rabbit antibodies (common for FAM185A), consider sequential staining with thorough blocking between rounds
Test for potential cross-reactivity between all antibodies in the panel
Signal optimization:
Spectral considerations:
Choose fluorophores with minimal spectral overlap
Include single-stain controls for spectral unmixing if using confocal microscopy with spectral detection
Consider the autofluorescence profile of your tissue/cells
Validation controls:
Include both positive and negative controls for each target
Consider co-localization patterns with known interaction partners as biological validation
Image acquisition and analysis:
Standardize exposure settings across samples
Use appropriate image analysis software for quantification
Consider machine learning approaches for complex pattern recognition
Integrating antibody-based detection with omics methodologies provides a more comprehensive understanding of FAM185A biology:
Proteomics integration:
Use immunoprecipitation with FAM185A antibodies followed by mass spectrometry to identify interaction partners
Compare protein abundance measurements from antibody-based methods with label-free quantification from proteomics
Consider targeted proteomics approaches (MRM/PRM) to quantify FAM185A in complex samples
Transcriptomics correlation:
Epigenomics insights:
Correlate FAM185A expression with epigenetic modifications at the gene locus
Consider the impact of chromatin state on expression variability across cell types
Functional genomics:
Combine antibody detection with CRISPR screens to place FAM185A in functional networks
Use phospho-specific antibodies (if available) to connect FAM185A to signaling networks
Systems biology approaches:
Integrate multiple data types to build predictive models of FAM185A function
Use network analysis to identify potential functional modules involving FAM185A
Epitope masking can significantly impact antibody detection and requires methodological solutions:
Optimization of fixation protocols:
Compare different fixatives (formalin, methanol, acetone) for their impact on epitope accessibility
Test different fixation durations to balance structural preservation with epitope accessibility
For particularly challenging epitopes, consider non-crosslinking fixatives
Antigen retrieval methodologies:
Denaturation conditions in Western blotting:
Test different detergents and reducing agents in sample preparation
Compare heat denaturation temperatures and durations
Consider native vs. denaturing conditions based on the epitope characteristics
Antibody combination strategies:
Use multiple antibodies recognizing different epitopes of FAM185A
Develop sequential or simultaneous staining protocols to maximize detection
Alternative approaches:
Consider protein tagging strategies (e.g., FLAG, HA) for recombinant expression systems
For particularly challenging applications, consider proximity ligation assays to amplify weak signals
Inconsistent banding patterns are a common challenge that requires systematic troubleshooting:
Multiple band analysis:
Sample preparation optimization:
Test different lysis buffers to ensure complete protein extraction
Include appropriate protease inhibitors to prevent degradation
Standardize protein quantification and loading amounts
Transfer efficiency assessment:
Verify transfer efficiency using reversible protein stains
Optimize transfer conditions for proteins in the molecular weight range of FAM185A
Consider transfer method modifications for proteins that may be difficult to transfer
Blocking optimization:
Compare different blocking agents (BSA, milk, commercial blockers) for optimal signal-to-noise ratio
Test blocking duration and temperature effects on specific and non-specific binding
Positive and negative controls:
Immunohistochemistry can be prone to artifacts that require careful consideration during interpretation:
Edge artifacts and tissue damage:
Exclude tissue edges and damaged areas from analysis
Ensure proper fixation throughout the tissue sample
Consider whole-slide imaging for comprehensive assessment
Endogenous peroxidase activity:
Ensure adequate blocking of endogenous peroxidase activity in tissues
Use appropriate controls without primary antibody to assess background
Consider alternative detection systems for tissues with high peroxidase activity
Non-specific binding issues:
Optimize blocking conditions (time, temperature, blocking agent)
Include isotype control antibodies at the same concentration
Consider pre-absorption controls with recombinant FAM185A
Fixation and processing artifacts:
Standardize fixation protocols across samples
Be aware of potential antigen loss or modification during processing
Consider the impact of decalcification on epitope recognition in bone tissues
Interpretation guidelines: