DYNC1LI1 Antibody

What is DYNC1LI1 and what are its primary cellular functions?

DYNC1LI1 (Dynein, Cytoplasmic 1, Light Intermediate Chain 1) is a crucial subunit of the cytoplasmic dynein 1 complex that plays essential roles in intracellular retrograde transport along cytoskeletal microtubules toward the minus end. This protein is fundamentally important for basic cellular functions including cell division and cell migration. Unlike lower eukaryotes that possess only one DLIC gene, mammals have two DLIC genes: Dync1li1 and Dync1li2. The structure of DYNC1LI1 includes a conserved C-terminus with helical propensity and a conserved N-terminal GTPase-like domain that tightly binds to the dynein heavy chain (DHC). Proper functioning of DYNC1LI1 is critical for maintaining cellular homeostasis, as disruptions in its expression or function have been associated with multiple pathological conditions, particularly various cancer types including pancreatic ductal adenocarcinoma, hepatocellular carcinoma, prostate cancer, and colorectal cancer .

How do DYNC1LI1 antibodies differ in their binding specificity and what epitope regions are most commonly targeted?

DYNC1LI1 antibodies vary significantly in their binding specificity, with many commercial antibodies targeting the C-terminal region of the protein. For instance, the ABIN2790248 antibody specifically targets the C-terminal region of human DYNC1LI1 and recognizes the amino acid sequence "AEDDQVFLMK LQSLLAKQPP TAAGRPVDAS PRVPGGSPRT PNRSVSSNVA" . Other antibodies may target different regions such as amino acids 167-233 or 451-523, depending on the specific research application requirements. The choice of epitope region can significantly impact antibody performance in different experimental contexts. C-terminal antibodies are often preferred for their specificity since this region shows less homology with related proteins, reducing cross-reactivity issues. When selecting an antibody, researchers should carefully consider whether their experimental questions require detection of specific structural domains or post-translational modifications, as this will influence which epitope region should be targeted .

What are the optimal conditions for using DYNC1LI1 antibodies in Western blotting applications?

For optimal Western blotting using DYNC1LI1 antibodies, sample preparation is critical. Total protein should be extracted using appropriate lysis buffers containing protease inhibitors, such as the protocol described in research utilizing 15 μg of protein per lane denatured in 1X NuPAGE™ LDS sample buffer for 10 minutes at 95°C. Protein separation is typically performed via 12% SDS-PAGE followed by transfer onto a PVDF membrane (0.2 μm). For membrane blocking, 3% bovine serum albumin for 1 hour at room temperature has proven effective before proceeding with antibody incubation. Anti-DYNC1LI1 antibodies like ab154251 have been successfully used at 1:1,000 dilution with 1-hour incubation at room temperature . Alternative antibodies like 25326-1-AP have been validated in multiple cell lines including K-562, HeLa, and Jurkat cells . For optimal detection, an appropriate HRP-conjugated secondary antibody and enhanced chemiluminescence system should be employed. Researchers should include appropriate loading controls such as β-actin (1:1,000, MAB1501R) and may need to optimize antibody concentration, incubation time, and washing steps based on their specific experimental conditions and sample types .

How should immunohistochemistry protocols be optimized when using DYNC1LI1 antibodies on tissue sections?

Optimization of immunohistochemistry (IHC) protocols for DYNC1LI1 antibodies requires careful attention to tissue fixation, antigen retrieval, and antibody dilution. For validated antibodies like 25326-1-AP, successful IHC has been demonstrated in mouse pancreas tissue. Antigen retrieval is a critical step, with recommended protocols including TE buffer at pH 9.0, although citrate buffer at pH 6.0 can serve as an alternative approach depending on tissue type and fixation methods . Tissue sections should be deparaffinized thoroughly and blocked with appropriate blocking solution to minimize non-specific binding. When establishing optimal antibody dilution, researchers should perform dilution series tests starting with manufacturer recommendations and adjust based on signal-to-noise ratio. For visualization systems, both chromogenic (DAB or AEC) and fluorescent detection methods have been successfully employed with DYNC1LI1 antibodies. Importantly, researchers should include appropriate positive and negative controls; pancreatic tissue sections have proven to be reliable positive controls for DYNC1LI1 expression. Overnight antibody incubation at 4°C often yields better results for IHC applications than shorter incubations at higher temperatures, particularly for tissues with lower target protein expression .

What are the key considerations for immunofluorescence staining with DYNC1LI1 antibodies?

Successful immunofluorescence (IF) staining with DYNC1LI1 antibodies requires careful attention to several key factors. Cell fixation method significantly impacts staining quality, with 4% paraformaldehyde (10-15 minutes at room temperature) generally providing good results while preserving cellular architecture. Permeabilization optimization is crucial since DYNC1LI1 is an intracellular protein; 0.1-0.3% Triton X-100 for 5-10 minutes typically provides adequate access while maintaining structural integrity. For blocking, 5-10% normal serum from the species of secondary antibody origin for 30-60 minutes helps minimize background. The antibody 25326-1-AP has been successfully validated for IF in K-562 cells, serving as a good positive control . For colocalization studies, researchers should select compatible antibody pairs (considering species origin and isotype) to enable simultaneous visualization of DYNC1LI1 with interacting partners or cellular structures. When imaging, confocal microscopy is recommended to precisely resolve DYNC1LI1's subcellular localization along microtubules and near various organelles. For quantitative IF analysis, standardized image acquisition parameters and careful background subtraction are essential to accurately compare DYNC1LI1 expression or localization across experimental conditions .

How is DYNC1LI1 expression altered in cancer tissues, and what methods provide reliable quantification?

DYNC1LI1 expression exhibits significant alterations in various cancer tissues, with particularly notable upregulation in metastatic cancers. Research utilizing cDNA arrays from colorectal cancer tissues has demonstrated significantly increased DYNC1LI1 expression in samples from patients with metastasis (n=10) compared to patients without metastasis (n=30, P<0.01) . For reliable quantification of these expression changes, reverse transcription-quantitative PCR (RT-qPCR) has proven to be the gold standard method. The protocol typically involves RNA extraction using specialized kits (such as Easy Pure Total RNA Mini kit), followed by reverse transcription with oligo(dT)12 primers and High Capacity cDNA Reverse Transcriptase kits. Quantitative expression analysis should always include appropriate housekeeping genes for normalization. Western blotting provides complementary protein-level validation, with densitometric analysis enabling semi-quantitative assessment of expression differences. For tissue-level analysis, tissue microarrays combined with immunohistochemistry allow higher throughput screening across multiple patient samples. When conducting such studies, researchers should carefully match case and control tissues for variables like patient age, sex, and tissue handling protocols to avoid introducing technical artifacts that might confound expression differences .

What is the relationship between DYNC1LI1 expression and mucin production in colorectal cancer research?

Research has revealed a significant relationship between DYNC1LI1 expression and mucin production patterns in colorectal cancer, with important implications for chemotherapy response. When DYNC1LI1 is knocked down in LS 174T cells (an AJCC Stage II CRC cell line), distinct alterations in mucin expression are observed: MUC1 expression decreases significantly (0.06-fold), while MUC2, MUC4, and MUC5AC expression levels increase substantially (2.70-fold, 4.17-fold, and 2.75-fold, respectively) . This mucin expression profile alteration (low MUC1, high MUC2/MUC4/MUC5AC) correlates with increased sensitivity to 5-fluorouracil (5-FU) treatment. To investigate this relationship, researchers typically employ lentiviral constructs containing shRNA targeting DYNC1LI1 (e.g., pLKO_TRC005-DYNC1LI1, clone ID: TRCN0000299843) with appropriate controls (e.g., pLKO_TRC005-luciferase). Following stable knockdown establishment through puromycin selection (2 mg/ml), mucin expression patterns are analyzed via RT-qPCR and western blotting. Chemosensitivity is then assessed using MTT assays in the presence of chemotherapeutic agents like 5-FU or oxaliplatin. This methodological approach allows researchers to establish causal relationships between DYNC1LI1 expression, mucin production patterns, and therapeutic response in colorectal cancer models .

How does DYNC1LI1 knockdown affect cellular functions in cancer cell lines, and what methods are most effective for functional studies?

DYNC1LI1 knockdown induces multiple cellular phenotypes in cancer cell lines, profoundly affecting intracellular transport, organelle structure, and chemotherapeutic sensitivity. For effective functional studies, lentiviral-mediated shRNA delivery has proven particularly successful, as exemplified by the use of pLKO_TRC005-DYNC1LI1 (clone ID: TRCN0000299843) with multiplicity of infection of 3 for stable knockdown . Alternative approaches include siRNA-mediated transient knockdown, which is suitable for short-term studies without the need for selection. For phenotypic assessment, researchers should implement multi-parameter analysis including:

When conducting these studies, researchers should include appropriate controls for both the knockdown (e.g., shLUC-expressing cells) and the functional assays. Knockdown efficiency should be consistently verified at both mRNA level (RT-qPCR) and protein level (western blot) throughout the experimental period to account for potential compensation mechanisms that may emerge during extended culture periods .

How can DYNC1LI1 antibodies be utilized in colocalization studies to investigate protein interactions and cellular trafficking?

Colocalization studies using DYNC1LI1 antibodies can provide valuable insights into protein interactions and trafficking pathways when performed with appropriate methodological rigor. For optimal results, researchers should employ high-resolution confocal microscopy with careful attention to the selection of fluorophore pairs to minimize spectral overlap. Double or triple immunolabeling protocols should incorporate DYNC1LI1 antibodies alongside markers for specific cellular compartments or potential interaction partners. Important markers to consider include Rab7 for late endosomes, dynactin p150 for the dynein/dynactin complex, RILP for dynein-endosome interactions, and LC3 for autophagosomes . The spatial relationship between DYNC1LI1 and these markers can reveal functional associations and trafficking patterns. For quantitative colocalization analysis, researchers should employ established algorithms such as Pearson's correlation coefficient or Manders' overlap coefficient, calculated using specialized image analysis software (ImageJ with Coloc2 plugin, Imaris, or similar). Live-cell imaging approaches using fluorescently tagged DYNC1LI1 constructs can complement fixed-cell studies by capturing dynamic aspects of protein trafficking. When investigating DYNC1LI1's role in specific transport processes, photoactivatable or photoconvertible fusion proteins can provide temporal resolution of protein movement along defined cellular tracks .

What strategies can overcome cross-reactivity issues when working with DYNC1LI1 antibodies in experimental systems?

Overcoming cross-reactivity challenges with DYNC1LI1 antibodies requires a multi-faceted approach combining careful antibody selection, rigorous validation, and optimized experimental conditions. Researchers should prioritize antibodies targeting unique epitopes in the C-terminal region of DYNC1LI1, which shows less homology with DYNC1LI2 and other related proteins. For instance, antibodies like ABIN2790248 that target specific C-terminal sequences can provide improved specificity . Comprehensive validation is essential and should include:

• Western blot analysis with positive control lysates (K-562, HeLa, or Jurkat cells) alongside negative control samples where DYNC1LI1 has been knocked down by siRNA or shRNA .

• Peptide competition assays using the immunizing peptide to confirm binding specificity.

• Parallel testing of multiple antibodies raised against different epitopes of DYNC1LI1 to confirm consistent staining patterns.

• Cross-validation using orthogonal detection methods (e.g., mass spectrometry) when feasible.

Experimentally, optimizing blocking conditions (3-5% BSA or serum matched to secondary antibody species) and including additional washing steps with higher detergent concentrations (0.1-0.3% Tween-20) can reduce non-specific binding. For applications in tissues with known high background, pre-absorption of antibodies against tissues from knockout models or against recombinant related proteins can further enhance specificity. Finally, researchers should always include specific knockdown/knockout controls in their experimental design to definitively distinguish specific from non-specific signals .

How can DYNC1LI1 antibodies be effectively used to study neurodegenerative conditions related to dynein dysfunction?

DYNC1LI1 antibodies provide valuable tools for investigating neurodegenerative conditions related to dynein dysfunction, particularly given the evidence that mice with Dync1li1 point mutations exhibit altered dendrite morphology in cortical and dorsal root ganglia neurons . For effective application in neurodegenerative research, investigators should implement a comprehensive experimental approach incorporating tissue-specific and subcellular analyses. In neuronal cultures or brain tissue sections, co-immunostaining with neuronal markers (MAP2, NeuN) and dendritic/axonal markers enables assessment of DYNC1LI1 distribution within neuronal compartments. High-resolution imaging techniques, particularly super-resolution microscopy (STED, STORM, or PALM), can resolve DYNC1LI1 localization along microtubule tracks within fine neuronal processes. For functional studies, knockdown/knockout models paired with morphological analyses (dendrite length, branching complexity, spine density) can reveal DYNC1LI1's role in maintaining neuronal architecture. Live imaging using fluorescently tagged cargo proteins in neurons with modified DYNC1LI1 expression can demonstrate transport defects in real-time. Additionally, researchers should consider biochemical fractionation approaches to assess DYNC1LI1's association with specific neuronal compartments or protein aggregates characteristic of various neurodegenerative conditions. When examining potential disease mechanisms, correlative analyses between DYNC1LI1 distribution/function and pathological markers (e.g., amyloid plaques, neurofibrillary tangles, α-synuclein aggregates) may reveal specific roles in disease pathogenesis .

What are the most common technical issues when using DYNC1LI1 antibodies and how can they be resolved?

Researchers frequently encounter several technical challenges when working with DYNC1LI1 antibodies, each requiring specific troubleshooting strategies. One common issue is weak or absent signal in Western blotting, which can be addressed by: 1) increasing protein loading (20-30 μg per lane), 2) optimizing antibody concentration through titration experiments, 3) extending primary antibody incubation to overnight at 4°C, and 4) implementing more sensitive detection systems such as enhanced chemiluminescence plus (ECL+) reagents. For high background in immunostaining applications, researchers should: 1) implement more stringent blocking with 5% BSA or 10% serum, 2) use longer/additional washing steps with increased detergent concentration (0.1-0.3% Triton X-100 or Tween-20), 3) reduce primary antibody concentration, and 4) ensure specificity through proper controls. Multiple bands on Western blots may indicate protein degradation, post-translational modifications, or non-specific binding; these can be addressed by: 1) adding fresh protease inhibitors to lysis buffers, 2) using gradient gels for better separation, 3) implementing peptide competition assays to identify specific bands, and 4) validating with DYNC1LI1 knockdown samples. For successful IHC applications in formalin-fixed tissues, antigen retrieval optimization is critical, with TE buffer at pH 9.0 recommended for DYNC1LI1 antibodies, though citrate buffer at pH 6.0 can serve as an alternative when necessary .

How should researchers optimize DYNC1LI1 knockdown experiments to ensure specificity and efficiency?

Optimizing DYNC1LI1 knockdown experiments requires careful consideration of multiple factors to ensure both specificity and efficiency. For lentiviral shRNA approaches, which provide stable knockdown, researchers should:

• Test multiple shRNA constructs targeting different regions of DYNC1LI1 mRNA. The construct pLKO_TRC005-DYNC1LI1 (clone ID: TRCN0000299843) has been validated for effective knockdown .

• Optimize viral transduction by testing different multiplicities of infection (MOI); an MOI of 3 has proven effective in previous studies .

• Determine the optimal puromycin concentration through kill curve analysis; 2 mg/ml has been successfully used for selection .

For siRNA-mediated transient knockdown:

• Design or select siRNAs with minimal off-target effects, preferably those validated in previous studies.

• Optimize transfection reagent type and concentration for your specific cell line.

• Establish a time course analysis post-transfection to determine the window of maximum knockdown.

For both approaches, validation is critical:

• Quantify knockdown efficiency at both mRNA level (RT-qPCR) and protein level (Western blotting).

• Include appropriate controls (shLUC or siNC) in all experiments.

• Test for potential compensatory upregulation of related proteins, particularly DYNC1LI2, which may mask phenotypes.

• Design rescue experiments with RNAi-resistant DYNC1LI1 constructs to confirm phenotype specificity.

Finally, researchers should be aware that complete DYNC1LI1 ablation may have detrimental effects on cell viability, potentially necessitating inducible knockdown systems for studying severe phenotypes .

What quality control measures should be implemented when working with newly purchased or newly purified DYNC1LI1 antibodies?

Implementation of comprehensive quality control measures for DYNC1LI1 antibodies is essential to ensure experimental reliability and reproducibility. Upon receiving a new antibody, researchers should perform initial characterization tests including:

• Western blot validation using positive control lysates from cells known to express DYNC1LI1 (K-562, HeLa, or Jurkat cells) alongside negative controls (DYNC1LI1 knockdown samples) . The antibody should detect a single band at the expected molecular weight (~56 kDa).

• Immunoprecipitation followed by mass spectrometry analysis to confirm that the antibody specifically pulls down DYNC1LI1 and its known interaction partners.

• Cross-comparison with alternative DYNC1LI1 antibodies targeting different epitopes to verify consistent staining patterns.

• Epitope blocking experiments using the immunizing peptide to confirm binding specificity.

• Testing across multiple applications (WB, IHC, IF) using standardized protocols to establish suitability for specific experimental purposes.

For long-term quality management:

• Prepare small single-use aliquots to avoid freeze-thaw cycles and maintain antibody performance.

• Include positive and negative controls in every experiment.

• Maintain detailed records of lot numbers, application-specific working dilutions, and optimization parameters.

• Periodically revalidate antibody performance, especially when transitioning to new experimental models.

• Implement lot-to-lot comparison testing when receiving new batches of the same antibody to ensure consistent performance.

These quality control measures not only ensure experimental reliability but also facilitate troubleshooting if unexpected results occur during research applications .