DARS2 Antibody

What are the optimal applications for DARS2 antibodies in research?

DARS2 antibodies have been successfully validated for several key applications in research, with varying optimal dilution ratios:

These applications allow researchers to evaluate DARS2 expression, localization, and protein interactions in various experimental contexts. For Western blot applications, DARS2 typically appears at 66-74 kDa, with some published studies reporting bands at 55 kDa, 50 kDa, or 66 kDa . When working with new cell lines or tissues, it is advisable to first optimize antibody concentrations through dilution series experiments.

How should DARS2 antibodies be stored and handled to maintain optimal activity?

Most commercial DARS2 antibodies are supplied in PBS with 0.02% sodium azide and 50% glycerol at pH 7.3. For long-term storage, maintain at -20°C where they typically remain stable for at least one year after shipment. For smaller volume antibodies (20μl), manufacturers often include 0.1% BSA as a stabilizer .

Important handling considerations:

• Avoid repeated freeze-thaw cycles by aliquoting upon receipt

• Bring to room temperature before opening to prevent condensation

• Centrifuge briefly before use to collect solution at the bottom of the tube

• Return promptly to -20°C after use

• For diluted working solutions, prepare fresh for each experiment or store at 4°C for no longer than one week

What are the common challenges in validating DARS2 antibody specificity?

Validating DARS2 antibody specificity requires careful experimental design to avoid cross-reactivity and false positives. The most rigorous approach involves:

• Positive controls: Use tissues/cells with known DARS2 expression (e.g., K-562 cells, human placenta tissue)

• Negative controls: Include DARS2 knockdown or knockout samples alongside test samples

• Multiple detection methods: Validate findings using at least two techniques (e.g., WB and IHC)

• Peptide competition assays: Pre-incubate antibody with immunizing peptide to confirm specificity

Multiple studies have used siRNA-mediated DARS2 knockdown to validate antibody specificity, demonstrating reduced antibody signal in Western blot and immunohistochemistry applications . This approach provides convincing evidence for antibody specificity while simultaneously allowing functional studies of DARS2 depletion.

How does DARS2 expression correlate with cancer progression and prognosis?

Research demonstrates that DARS2 expression is significantly altered in multiple cancer types, with distinct patterns across different malignancies:

For bladder cancer specifically, DARS2 upregulation correlates with tumor progression and poor prognosis . Functional studies demonstrate that DARS2 knockdown inhibits cancer cell proliferation, metastasis, and tumorigenesis . When designing experiments to assess DARS2's role in cancer, researchers should include corresponding normal tissue controls and stratify samples by tumor stage and grade to properly evaluate expression patterns.

What is the relationship between DARS2 and immune cell infiltration in tumors?

DARS2 expression correlates distinctly with immune cell infiltration patterns across different cancer types:

In bladder cancer:

• Negative correlation with immune-active cells: CD4+ T cells (R= -0.251, P < 0.001) and NK cells (R= -0.067, P < 0.001)

• Positive correlation with immunosuppressive cells: MDSCs (R= 0.372, P < 0.001) and macrophages (R= 0.196, P < 0.01)

• Positive correlation with CD8+ T cells (R= 0.203, P < 0.001)

• Positive correlation with PD-L1 expression (R= 0.202, P < 0.001)

In lung adenocarcinoma:

• Negative correlation with B cells (r = -0.244, P = 5.32e-8)

• Negative correlation with CD4+ T cells (r = -0.206, P = 4.91e-6)

• Negative correlation with dendritic cells (r = -0.143, P = 1.55e-3)

When designing immunology-focused experiments, consider including co-staining for DARS2 and immune cell markers to validate these correlations in your specific experimental model. Flow cytometry and multiplex immunohistochemistry approaches are particularly valuable for characterizing these relationships.

How is DARS2 implicated in neurological disease pathogenesis?

DARS2 mutations cause leukoencephalopathy with brainstem and spinal cord involvement and lactate elevation (LBSL), a rare neurological disorder. Key aspects of DARS2 in LBSL include:

• Most LBSL patients (88%) carry a mutation in the intron 2 splice acceptor region, with one specific mutation (c.228-20_21delTTinsC) having a carrier frequency of 1:95 in the Finnish population

• This mutation affects exon 3 splicing, causing a frameshift (p.R76SfsX5) and premature stop codon

• The mutation is "leaky," allowing some production of functional mt-AspRS protein

• Neural cells, particularly neurons, show profound splicing defects in this region, significantly reducing functional mt-AspRS levels

When studying DARS2 in neurological contexts, researchers should consider tissue-specific expression patterns and employ neuron-specific cell models to recapitulate disease-relevant conditions. Additionally, evaluating both protein levels and enzymatic activity provides more comprehensive insights into DARS2's role in disease pathogenesis.

What are the recommended controls for DARS2 knockdown and overexpression studies?

For rigorous DARS2 functional studies, implement these experimental controls:

For knockdown experiments:

• Negative control siRNA/shRNA: Use non-targeting sequences with similar GC content

• Multiple siRNA sequences: Employ at least two distinct DARS2-targeting sequences to rule out off-target effects

• Rescue experiments: Re-express siRNA-resistant DARS2 to confirm phenotype specificity

• Quantification controls: Measure knockdown efficiency by both qRT-PCR and Western blot

For overexpression experiments:

• Empty vector control: Must match backbone of DARS2 expression vector

• Tagged vs. untagged constructs: Compare to ensure tag doesn't interfere with function

• Expression level monitoring: Use inducible systems to achieve physiologically relevant levels

• Functional validation: Confirm increased aminoacylation activity using biochemical assays

Research has demonstrated that DARS2 knockdown significantly inhibits cell proliferation in lung adenocarcinoma cell lines (A549 and H1299) and bladder cancer cell lines, validating the effectiveness of this approach for functional studies .

How can researchers effectively analyze DARS2 splicing patterns in different cell types?

DARS2 splicing analysis is particularly important given the splice site mutations in LBSL. For comprehensive splicing analysis:

• Primer design strategy:
  Design primers that anneal to exon-exon junctions (exons 2, 3, and 4) to differentiate between inclusion and exclusion of exon 3

• Quantitative assessment methods:

  • RT-PCR with visualization on agarose gels for qualitative assessment

  • RT-qPCR with exon junction-specific primers for quantitative analysis

  • RNA-seq with junction reads analysis for genome-wide splicing context

  • Minigene assays to test specific splicing regulatory elements

• Cell type considerations:
  Compare splicing patterns across relevant cell types (neurons, glia, cancer cells) as splicing efficiency varies significantly between cell types

A study by Wang et al. using DTUrtle (v0.8.1) for differential transcript usage analysis and BRIE2 (v2.0.5) for differential spliced exon analysis demonstrated cell type-specific splicing patterns of DARS2 . This methodological approach provides a comprehensive framework for researchers investigating splicing variations.

What methodologies are recommended for investigating DARS2's role beyond its canonical aminoacylation function?

Recent research suggests DARS2 may have non-canonical functions beyond aminoacylation. To investigate these:

• Protein interaction studies:

  • Co-immunoprecipitation followed by mass spectrometry to identify novel binding partners

  • Proximity labeling methods (BioID, APEX) to catalog the protein neighborhood

  • Yeast two-hybrid screening for direct interaction partners

• Subcellular localization analysis:

  • Super-resolution microscopy with mitochondrial and other organelle markers

  • Subcellular fractionation with Western blot analysis

  • Live-cell imaging with fluorescently tagged DARS2

• Pathway analysis approaches:

  • Phosphoproteomics to identify signaling pathways affected by DARS2 perturbation

  • Transcriptomics to identify gene expression networks regulated by DARS2

  • Metabolomics to identify metabolic pathways affected by DARS2 activity

Recent studies suggest DARS2 may be involved in mitophagy regulation through interactions with PINK1, offering a novel research direction beyond its classical role . Additionally, research by Sauter et al. identified DARS2 missense mutations in regions conserved only in mammals, suggesting evolutionarily acquired supplementary functions that may be involved in disease pathology .

How can researchers effectively investigate DARS2's relationship with PD-L1 and immune regulation?

To investigate DARS2's role in immune regulation through PD-L1:

• Expression correlation analysis:

  • Perform co-expression analysis in patient samples and cell lines

  • Use multivariate analysis to control for confounding factors

  • Employ multiplexed IHC to visualize co-localization in tissue sections

• Mechanistic investigations:

  • Assess PD-L1 levels after DARS2 knockdown/overexpression by flow cytometry and Western blot

  • Examine transcriptional regulation using reporter assays and ChIP

  • Investigate protein stability using pulse-chase experiments and proteasome inhibitors

• Functional immune assays:

  • Co-culture cancer cells with immune cells to measure functional consequences

  • Use immune cell killing assays with DARS2-modulated cancer cells

  • Analyze immune checkpoint blockade efficacy in DARS2-high versus DARS2-low models

Research has demonstrated that in bladder cancer, DARS2 expression positively correlates with PD-L1 expression (R= 0.202, P < 0.001), and knockdown experiments showed that DARS2 modulation affects PD-L1 levels . This suggests DARS2 may facilitate immune evasion, making it a potential predictive indicator for immune therapy responses.

What methodology is recommended for studying the relationship between DARS2 and cancer cell cycle regulation?

For investigating DARS2's role in cell cycle regulation:

• Cell cycle analysis approaches:

  • Flow cytometry with propidium iodide or DAPI staining

  • EdU incorporation assays for S-phase analysis

  • Time-lapse microscopy with cell cycle reporters (FUCCI system)

• Cell cycle protein expression:

  • Western blot analysis of key regulators (CDK4, CDK6, p53, p21)

  • Immunofluorescence for spatial distribution of cell cycle markers

  • Proteomic analysis of cell cycle protein complexes

• Functional assays:

  • Cell synchronization followed by release with DARS2 modulation

  • CDK activity assays to assess direct functional impact

  • Rescue experiments with cell cycle regulators

Research by Liu et al. found that DARS2 knockdown in bladder cancer cells reduced CDK4 expression while CDK6, p53, and p21 levels remained unchanged, suggesting DARS2 specifically promotes G1-to-S phase transition by upregulating CDK4 . This methodological approach provides a template for researchers investigating DARS2's role in cell cycle regulation across different cancer types.

What are the best approaches for developing DARS2 as a prognostic biomarker in clinical research?

For developing DARS2 as a clinical biomarker:

• Biomarker validation approach:

  • Multi-cohort analysis with discovery and validation sets

  • Multivariate analysis controlling for clinical variables

  • Comparison with established biomarkers

  • Standardized cutoff determination using ROC analysis

• Technical considerations:

  • Antibody validation across multiple platforms (IHC, ELISA, multiplex assays)

  • Standard operating procedures for specimen handling

  • Internal controls for normalization

  • Reproducibility testing across laboratories

• Combined biomarker strategies:

  • Creation of multi-gene prognostic scores

  • Integration with established clinical parameters

  • Machine learning approaches for biomarker panel optimization

Research has demonstrated the potential of DARS2 as a prognostic biomarker, particularly when combined with other markers. In bladder cancer, researchers developed a DARS2-PINK1-CDK4 axis expression score that showed significant prognostic value across multiple datasets . This multi-gene approach improved prognostic accuracy compared to DARS2 expression alone.

How can researchers address variable DARS2 molecular weight observations in Western blot applications?

DARS2 has been reported with varying molecular weights across studies, creating potential confusion in data interpretation:

To resolve discrepancies:

• Include positive control samples with known DARS2 expression

• Use multiple antibodies targeting different epitopes

• Verify specificity through knockdown/knockout experiments

• Consider pre-process mature mitochondrial DARS2 versus precursor forms

• Note differences in rat DARS2, which has a ~40 amino acid N-terminal extension that can be removed without affecting catalytic activity

These variations may reflect biological differences in DARS2 processing or technical differences in experimental conditions rather than antibody specificity issues.

How should researchers reconcile contradictory findings on DARS2 expression across different cancer types?

DARS2 shows divergent expression patterns across cancer types, with overexpression in some (bladder cancer, lung adenocarcinoma) and underexpression in others (kidney cancers, thyroid carcinoma) . To reconcile these differences:

• Technical reconciliation:

  • Standardize analysis methods across studies

  • Verify antibody specificity in each tissue type

  • Use multiple detection methods (protein and mRNA)

  • Include appropriate tissue-specific controls

• Biological interpretation:

  • Consider tissue-specific mitochondrial dependency

  • Analyze mitochondrial content differences between tissues

  • Examine tissue-specific splicing patterns

  • Investigate tissue-specific roles beyond aminoacylation

• Experimental approach:

  • Perform systematic pan-cancer analysis with consistent methodology

  • Use paired normal-tumor samples for each cancer type

  • Stratify by molecular subtypes within each cancer type

  • Correlate with mitochondrial function metrics

Understanding these context-dependent patterns is crucial for developing DARS2-targeted therapeutic strategies and avoiding off-target effects in tissues where DARS2 levels are reduced in cancer.

What experimental approaches can clarify whether DARS2's role in disease is primarily through its canonical function or through non-canonical activities?

To distinguish between canonical and non-canonical DARS2 functions:

• Separation-of-function mutations:

  • Engineer mutations that specifically disrupt aminoacylation without affecting protein interactions

  • Compare phenotypes between complete knockout and function-specific mutants

  • Use domain deletion constructs to map functional regions

• Biochemical activity assays:

  • Measure aminoacylation activity using in vitro assays

  • Correlate activity levels with disease phenotypes

  • Use aminoacylation inhibitors to phenocopy genetic approaches

• Evolutionary analysis:

  • Focus on mutations in mammalian-specific conserved regions vs. universally conserved regions

  • Compare functions across species with different DARS2 domain architectures

  • Analyze disease mutations for their evolutionary conservation patterns

Sauter et al. identified missense mutations in DARS2 regions conserved only in mammals, suggesting evolutionarily acquired supplementary functions may contribute to LBSL pathology . Additionally, research on DARS2's role in mitophagy regulation through PINK1 pathway modulation points to non-canonical functions beyond aminoacylation .