DRT111 Antibody

What is DRT111 and what cellular functions does it perform?

DRT111 (DNA-DAMAGE REPAIR/TOLERATION PROTEIN111), also known as SPLICING FACTOR FOR PHYTOCHROME SIGNALING (SFPS), is a splicing factor that plays a crucial role in pre-mRNA processing in plants. It interacts with Arabidopsis Splicing Factor1 (SF1), which is involved in 3′ splicing site recognition, indicating that DRT111 functions in early steps of the spliceosome machinery . DRT111 has been shown to control splicing of ABI3 and acts upstream of the splicing factor SUPPRESSOR OF ABI3–ABI5 . Additionally, DRT111 regulates expression and splicing of genes involved in osmotic-stress responses, abscisic acid (ABA) signaling, light perception, and mRNA processing .

Where is DRT111 primarily expressed in plant tissues?

DRT111 is ubiquitously expressed throughout plant development, but with distinct tissue-specific patterns. Analysis of public databases, including the eFP platform, indicates highest transcript abundance in dry seeds . Histochemical analysis using β-glucuronidase (GUS) under the control of the DRT111 promoter revealed significant expression in guard cells and cells surrounding the base of trichomes . This expression pattern correlates with DRT111's functional role in ABA-mediated responses in both seed development and stomatal movements.

What are the key considerations when designing antibodies for plant splicing factors like DRT111?

When designing antibodies for plant splicing factors like DRT111, researchers should consider several critical factors. First, identify unique epitopes by analyzing the protein sequence to find regions with low homology to other splicing factors, avoiding highly conserved domains that might cross-react. Second, consider protein accessibility—since splicing factors operate in nuclear speckles as part of complex protein assemblies , target epitopes that remain accessible when the protein is in its native conformation and cellular context. Third, account for post-translational modifications that might affect antibody recognition. Finally, validate the antibody against both recombinant protein and native plant extracts, particularly from tissues with high DRT111 expression such as dry seeds and guard cells .

What computational approaches could improve antibody design for detecting DRT111?

Recent advances in computational antibody design could significantly improve antibodies targeting DRT111. Fine-tuned RFdiffusion networks represent a promising approach, as they can design antibody variable domains (VHHs or scFvs) with atomic-level precision to specific epitopes . The process involves: (1) identifying accessible, unique epitopes on DRT111; (2) using RFdiffusion to design CDR loops that specifically target these epitopes; (3) employing ProteinMPNN to optimize CDR loop sequences; and (4) filtering designs using fine-tuned RoseTTAFold2 to predict binding accuracy . This computational pipeline, combined with experimental validation through yeast display or E. coli expression systems, could yield highly specific antibodies against DRT111 that maintain their intended epitope selectivity .

What protein extraction protocols are optimal for maintaining DRT111 integrity in different plant tissues?

For optimal DRT111 extraction while maintaining protein integrity, tissue-specific approaches are recommended. For seed tissues, which show highest DRT111 expression , use a modified TCA-acetone precipitation method: grind seeds in liquid nitrogen, extract in buffer containing 10% TCA in acetone with 0.07% β-mercaptoethanol at -20°C, followed by washing with acetone containing 0.07% β-mercaptoethanol and drying. For vegetative tissues, particularly guard cells where DRT111 is also highly expressed , employ a phenol extraction method: homogenize tissue in extraction buffer (0.7M sucrose, 0.1M KCl, 0.5M Tris-HCl pH 7.5, 50mM EDTA, 2% β-mercaptoethanol, 1mM PMSF), extract with Tris-buffered phenol, and precipitate proteins using 0.1M ammonium acetate in methanol. Include protease inhibitors and phosphatase inhibitors throughout both protocols to preserve post-translational modifications that might affect antibody recognition.

What are the best immunolocalization techniques for visualizing DRT111 in plant cells?

For visualizing DRT111 in plant cells, confocal immunofluorescence microscopy with specific optimizations is recommended. Fix tissues in 4% paraformaldehyde, then perform cell wall digestion with a pectolyase/cellulase mixture to enhance antibody penetration. Use antigen retrieval methods (sodium citrate buffer, pH 6.0, 95°C for 10 minutes) to expose epitopes. Based on DRT111's known localization in nuclear speckles where it interacts with SF1 , counterstain with DAPI for nuclear visualization and consider co-immunostaining with antibodies against known splicing factors to confirm nuclear speckle localization. For super-resolution visualization of splicing complexes, techniques such as structured illumination microscopy (SIM) or stochastic optical reconstruction microscopy (STORM) provide detailed information about DRT111's precise subnuclear organization within the spliceosome machinery.

How can DRT111 antibodies be used to investigate stress-induced splicing dynamics?

DRT111 antibodies can illuminate stress-induced splicing dynamics through several advanced approaches. RNA immunoprecipitation (RIP) using DRT111 antibodies allows identification of transcripts directly bound by DRT111 under different stress conditions, particularly after long-term ABA or PEG treatments that induce DRT111 expression . Combine this with RNA-seq to profile splicing changes genome-wide. For temporal dynamics, employ time-course chromatin immunoprecipitation (ChIP) studies to track DRT111 recruitment to chromatin during transcription-coupled splicing. Use proximity ligation assays (PLA) to visualize interactions between DRT111 and other splicing factors like SF1 during stress responses. For functional studies, implement DRT111 immunodepletion from nuclear extracts followed by in vitro splicing assays to directly assess its role in processing specific pre-mRNAs identified in transcriptome studies of drt111 mutants .

What techniques can resolve contradictory data between DRT111 antibody signals and transcriptomic findings?

When facing contradictions between antibody-based detection and transcriptomic data for DRT111, a systematic troubleshooting approach is essential. First, validate antibody specificity using multiple controls: Western blots comparing wild-type plants with drt111 knockout mutants; competitive binding assays with recombinant DRT111; and epitope mapping to confirm target recognition. Second, consider post-transcriptional regulation by comparing protein levels (Western blot) with transcript levels (RT-qPCR) across different tissues and conditions. Third, assess protein turnover rates using cycloheximide chase assays, as protein stability may vary under different conditions despite similar transcript levels. Fourth, examine potential post-translational modifications using phospho-specific antibodies or mass spectrometry, as these could affect antibody recognition without changing transcript abundance. Finally, use alternative detection methods such as targeted mass spectrometry or proximity labeling approaches to provide independent verification of DRT111 presence and abundance.

How can CRISPR-based approaches complement antibody studies of DRT111?

CRISPR-based approaches provide powerful complementary tools to antibody studies of DRT111. First, generate epitope-tagged DRT111 lines by CRISPR-mediated homology-directed repair to insert GFP, HA, or FLAG tags, enabling detection with validated commercial antibodies. This circumvents potential limitations of direct DRT111 antibodies. Second, create conditional DRT111 knockout or knockdown lines using CRISPR interference (CRISPRi) or inducible degradation systems, allowing temporal control over DRT111 depletion to study acute versus chronic loss. Third, implement CRISPR activation (CRISPRa) to upregulate DRT111 expression, mimicking stress-induced upregulation observed during long-term ABA or PEG treatments . For spatial studies, use tissue-specific promoters to drive Cas9 expression, enabling tissue-restricted DRT111 manipulation to dissect its role in seed development versus stomatal function . Finally, combine these approaches with RNA-seq to correlate DRT111 activity with global splicing patterns under various conditions.

What are the best approaches for studying DRT111 interactions with the spliceosome complex?

To study DRT111 interactions within the spliceosome complex, researchers should employ a multi-faceted approach integrating various advanced techniques. Begin with proximity-dependent biotin identification (BioID) or APEX2 proximity labeling using DRT111 as the bait protein to comprehensively map its protein interaction network in living cells. Follow with co-immunoprecipitation coupled with mass spectrometry to identify stable interaction partners, building on known interactions such as with SF1 . For dynamic studies of interaction kinetics, implement fluorescence recovery after photobleaching (FRAP) using fluorescently tagged DRT111 to measure residence time within nuclear speckles. Analyze specific spliceosomal interactions using structural approaches such as cryo-electron microscopy of purified complexes. For functional analysis, utilize RNA antisense purification (RAP) coupled with mass spectrometry to identify DRT111-associated proteins on specific target transcripts identified in transcriptome studies . Together, these approaches can reveal how DRT111 dynamically associates with the spliceosome to regulate alternative splicing in response to developmental and environmental cues.

What are the most common causes of false positives in DRT111 immunodetection, and how can they be prevented?

False positives in DRT111 immunodetection can arise from several sources, each requiring specific preventative measures. Cross-reactivity with related splicing factors represents the most common issue—prevent this by extensive antibody validation using drt111 knockout mutants as negative controls and peptide competition assays. Non-specific binding to RNA-binding proteins can occur due to DRT111's nucleic acid association—reduce this by including RNase treatment in immunoprecipitation protocols and implementing stringent washing conditions (high salt, mild detergents). Autofluorescence from plant tissues, particularly seed coats where DRT111 is highly expressed , can interfere with immunofluorescence—mitigate by including spectral unmixing during confocal microscopy and appropriate autofluorescence controls. Post-fixation artifacts might arise during sample preparation—prevent by comparing different fixation methods (paraformaldehyde vs. methanol) and including native condition controls when possible. Finally, to confirm specificity in all applications, validate findings using orthogonal detection methods such as RNA-seq to correlate protein detection with known mRNA processing outcomes in DRT111 functional studies .

How can researchers distinguish between splice variants of DRT111 using antibody-based methods?

To distinguish between splice variants of DRT111 using antibody-based methods, researchers should implement an isoform-specific detection strategy. First, analyze DRT111 transcript variants identified in RNA-seq data to map unique peptide sequences specific to each isoform. Then, develop isoform-specific antibodies targeting these unique regions, particularly in alternatively spliced exons. For precise quantification, use multiple reaction monitoring (MRM) mass spectrometry with synthetic peptide standards representing each isoform. For tissue localization studies, implement RNAscope in situ hybridization with isoform-specific probes alongside immunofluorescence to correlate transcript and protein isoform distribution. When analyzing isoform-specific functions, combine isoform-specific antibodies with chromatin immunoprecipitation followed by sequencing (ChIP-seq) to identify potentially different genomic targeting patterns. For developmental studies, track isoform abundance changes during seed development and germination, where DRT111 plays critical regulatory roles . This comprehensive approach enables precise characterization of DRT111 splice variant expression, localization, and function across different tissues and developmental stages.