tuf Antibody

What is the TUFM protein and what biological functions does it serve?

TUFM (also known as EF-Tu or P43) is a mitochondrial protein that promotes the GTP-dependent binding of aminoacyl-tRNA to the A-site of ribosomes during protein biosynthesis. Beyond this primary function, TUFM also plays crucial roles in the regulation of autophagy and innate immunity. The protein recruits ATG5-ATG12 complexes and NLRX1 at mitochondria, serving as a checkpoint of the RIGI-MAVS pathway. Through these interactions, TUFM inhibits RLR-mediated type I interferon production while simultaneously promoting autophagy . This multifunctional nature makes TUFM an important target for researchers studying mitochondrial translation, cellular stress responses, and immunological pathways.

What types of anti-TUFM antibodies are available for research applications?

Researchers can access multiple formats of anti-TUFM antibodies, each with specific characteristics suitable for different experimental needs:

• Polyclonal antibodies (e.g., ab264370): These are produced in rabbits using synthetic peptides corresponding to the C-terminal region (amino acids 400 to C-terminus) of human TUFM. These antibodies recognize multiple epitopes on the TUFM protein, potentially providing stronger signals for applications like Western blotting .

• Recombinant monoclonal antibodies (e.g., ab173300): These offer higher specificity and batch-to-batch consistency. The recombinant monoclonal format (EPR12797(B)) has been cited in multiple peer-reviewed publications, demonstrating reliability across various research contexts .

The selection between these formats should be guided by the specific research application, required sensitivity, and the need for reproducibility in experimental designs.

What are the validated applications for anti-TUFM antibodies?

Anti-TUFM antibodies have been validated for multiple research applications with varying degrees of confidence:

The recombinant monoclonal format offers broader application versatility, while the polyclonal antibody has been specifically optimized for Western blotting applications . When selecting an anti-TUFM antibody, researchers should consider which applications are critical for their experimental design and choose accordingly.

What is the expected molecular weight for TUFM detection?

The predicted molecular weight for TUFM protein is 50 kDa, which should be the expected band size in Western blot applications. This has been consistently observed across multiple cell lines, including HeLa (human epithelial cell line from cervix adenocarcinoma), HEK-293T (human epithelial cell line from embryonic kidney transformed with large T antigen), and Jurkat (human T cell leukemia cell line from peripheral blood) . Any significant deviation from this expected molecular weight may indicate post-translational modifications, protein degradation, or potential non-specific binding.

How can anti-TUFM antibodies be optimized for studying mitochondrial translation dynamics?

For studying mitochondrial translation dynamics using anti-TUFM antibodies, researchers should implement several optimization strategies. First, subcellular fractionation to isolate mitochondria is critical before immunoprecipitation or Western blotting to reduce cytoplasmic contamination. When performing co-immunoprecipitation studies to investigate TUFM interactions with other mitochondrial translation components, use mild detergents (0.5-1% CHAPS or digitonin) rather than stronger ones like Triton X-100 to preserve protein-protein interactions .

For pulse-chase experiments tracking newly synthesized mitochondrial proteins, combine anti-TUFM immunoprecipitation with metabolic labeling using 35S-methionine/cysteine in the presence of cycloheximide (to inhibit cytoplasmic translation). This approach allows specific examination of TUFM's role in mitochondrial protein synthesis kinetics. Additionally, when performing immunofluorescence microscopy, co-staining with established mitochondrial markers (such as TOMM20 or MitoTracker dyes) enables precise localization studies of TUFM within the mitochondrial network .

What methodological approaches enable investigation of TUFM's role in autophagy and innate immunity?

Investigating TUFM's role in autophagy and innate immunity requires specialized experimental designs. For autophagy studies, researchers should perform dual immunostaining with anti-TUFM and anti-LC3B antibodies to visualize co-localization during autophagosome formation. Quantitative assessment can be achieved through Pearson's correlation coefficient analysis of confocal microscopy images .

For studying TUFM's interaction with the ATG5-ATG12 complex and NLRX1 at mitochondria, proximity ligation assays (PLA) offer superior sensitivity compared to conventional co-immunoprecipitation. When investigating TUFM's checkpoint function in the RIGI-MAVS pathway, researchers should design experiments comparing wild-type cells with TUFM-depleted cells following stimulation with RLR agonists (like poly(I:C) or 5'ppp-RNA). Measuring type I interferon production through ELISA or reporter assays while simultaneously assessing autophagy markers enables comprehensive analysis of TUFM's dual regulatory functions .

A crucial methodological consideration is the use of appropriate mitochondrial stress inducers (like CCCP, antimycin A, or paraquat) to trigger mitophagy and observe TUFM's recruitment dynamics to damaged mitochondria using time-lapse microscopy combined with immunofluorescence.

How can researchers effectively use tuf gene sequences for bacterial species identification?

The tuf gene (encoding elongation factor Tu) provides superior discrimination for bacterial species identification compared to traditional 16S rRNA gene analysis, particularly for closely related species. For effective implementation, researchers should:

• Use universal primers that target conserved regions of the tuf gene to amplify a 761-bp portion, as demonstrated in streptococcal species studies .

• Employ direct sequencing of PCR amplicons rather than cloning to avoid potential PCR artifacts, followed by quality-filtered sequence analysis.

• Develop species-specific internal probes based on the 15-31% nucleotide sequence divergence observed between different bacterial species, enabling highly specific detection systems .

The tuf-based detection system offers exceptional sensitivity (1-10 genome copies per PCR) for streptococcal species, making it valuable for samples with low bacterial loads . When designing phylogenetic analyses, researchers should use both neighbor-joining and maximum-likelihood methods to construct robust evolutionary trees based on tuf sequences. This approach reveals evolutionary relationships that may not be evident with 16S rRNA gene analysis alone, particularly for very closely related species that differ by only a few nucleotides in their 16S sequences .

What validation strategies ensure anti-TUFM antibody specificity?

Comprehensive validation of anti-TUFM antibody specificity requires multiple complementary approaches:

• Genetic validation: Compare antibody reactivity in wild-type cells versus TUFM-knockout cells generated using CRISPR-Cas9. The absence of signal in knockout cells provides definitive evidence of specificity.

• Peptide competition assays: Pre-incubate the antibody with excess immunogen peptide prior to the primary application. Signal disappearance confirms epitope-specific binding.

• Independent antibody validation: Compare staining patterns using antibodies targeting different TUFM epitopes. Consistent patterns across multiple antibodies increase confidence in specificity .

• Cross-species reactivity assessment: Test the antibody against TUFM orthologs from different species to determine evolutionary conservation of the epitope. Antibodies recognizing highly conserved epitopes may offer broader research applications.

• Mass spectrometry validation: Perform immunoprecipitation followed by mass spectrometry to identify all proteins captured by the antibody, confirming TUFM enrichment and identifying potential cross-reactive proteins.

These validation steps should be documented with appropriate positive and negative controls to ensure reliable experimental outcomes.

What are common causes of background signal when using anti-TUFM antibodies?

Background signals when using anti-TUFM antibodies can arise from several sources that require systematic troubleshooting:

• Non-specific binding: Polyclonal antibodies may recognize epitopes shared with other proteins, particularly other GTP-binding proteins with structural similarity to TUFM. Increasing blocking buffer concentration (5% BSA or 5% milk) and extending blocking time (2-3 hours) can reduce this issue .

• Suboptimal antibody concentration: Titrate antibody concentrations carefully, as excessive antibody concentrations increase background. For Western blotting, concentrations as low as 0.1 μg/mL have been demonstrated effective for anti-TUFM antibody (ab264370) .

• Sample preparation artifacts: Incomplete cell lysis or protein denaturation can expose hydrophobic regions, increasing non-specific binding. Optimize lysis conditions and ensure complete protein denaturation for Western blotting applications.

• Inadequate washing: Particularly for immunohistochemistry and immunofluorescence applications, insufficient washing between antibody incubation steps can leave residual primary or secondary antibody. Implement additional washing steps with gentle agitation to improve signal-to-noise ratio .

• Cross-reactivity with secondary antibody: Validate that secondary antibodies do not bind endogenous immunoglobulins in your sample by performing secondary-only controls.

How should researchers optimize detection conditions for low-abundance TUFM in different cellular compartments?

Detecting low-abundance TUFM in different cellular compartments requires specialized approaches:

• Signal amplification systems: For immunohistochemistry, employ tyramide signal amplification (TSA) or polymer-based detection systems rather than conventional ABC methods to enhance sensitivity while maintaining specificity .

• Subcellular fractionation: For biochemical studies, perform careful subcellular fractionation to concentrate TUFM from specific compartments (mitochondria, cytosol, or associated with autophagosomes) before analysis.

• Epitope retrieval optimization: For formalin-fixed tissues, test both citrate buffer (pH 6.0) and EDTA buffer (pH 9.0) for antigen retrieval, as demonstrated in optimal staining of human breast and colon tissues with anti-TUFM antibody (ab173300) .

• Super-resolution microscopy: For precise localization studies, conventional confocal microscopy may be insufficient. Techniques like Structured Illumination Microscopy (SIM) or Stimulated Emission Depletion (STED) microscopy provide superior resolution for studying TUFM distribution within mitochondria or at mitochondria-autophagosome interfaces.

• Antibody incubation conditions: Extended primary antibody incubation (overnight at 4°C) with gentle agitation improves detection of low-abundance targets without increasing background.

What protocol modifications are necessary when studying TUFM in different model organisms?

When adapting anti-TUFM protocols across model organisms, researchers must account for sequence conservation and tissue-specific factors:

• Epitope conservation analysis: Before experimental application, perform sequence alignment of the antibody's target epitope across species to predict cross-reactivity. For the ab264370 antibody targeting human TUFM aa 400 to C-terminus, sequence conservation analysis with potential model organisms is essential .

• Species-specific blocking agents: When working with tissues from rodents or other mammals, include species-appropriate serum in blocking buffers to prevent non-specific binding to endogenous immunoglobulins.

• Tissue-specific protocol modifications:

  • For brain tissue: Extended fixation may be necessary, but excessive fixation can mask epitopes. Balance fixation time carefully and optimize antigen retrieval.

  • For muscle tissue: Enhanced permeabilization (0.5% Triton X-100 instead of standard 0.1-0.2%) improves antibody penetration.

  • For adipose tissue: Lipid-rich environments may cause non-specific antibody retention. Additional washing steps with detergent-containing buffers are recommended.

• Positive control selection: Include tissues or cells known to express high levels of TUFM (such as heart, liver, or HeLa cells) as positive controls when testing new species applications .

• Signal detection optimization: Different species may require adjusted exposure times for Western blot or modified amplification systems for immunohistochemistry due to variation in protein abundance or tissue autofluorescence.

How can researchers design experiments to distinguish between TUFM's translational and non-translational functions?

Designing experiments to differentiate between TUFM's canonical role in translation and its non-canonical functions in autophagy and immunity requires sophisticated approaches:

• Domain-specific mutants: Generate TUFM constructs with point mutations in the GTP-binding domain (affecting translation) versus mutations in regions involved in ATG5-ATG12 binding (affecting autophagy). Express these in TUFM-knockout backgrounds to dissect function-specific effects .

• Temporal separation of functions: Use reversible translation inhibitors (like cycloheximide) to temporarily block TUFM's translational role, then monitor autophagy induction or immune signaling to identify translation-independent functions.

• Compartment-specific analysis: Create chimeric TUFM constructs with additional localization signals to redirect a portion of cellular TUFM to specific compartments (enhanced mitochondrial targeting versus cytosolic retention), then assess how altered localization affects each functional pathway.

• Interaction-specific inhibitors: Develop peptide inhibitors that specifically disrupt TUFM's interaction with autophagy machinery without affecting its GTP-binding activity, enabling selective inhibition of non-translational functions.

• Stress-specific response analysis: Compare TUFM's interactions and modifications under conditions that specifically stress translation (such as mitochondrial ribosomes inhibitors) versus those that primarily activate autophagy or immune responses (like nutrient deprivation or viral RNA mimetics).

What considerations should guide experimental design when using tuf for bacterial diagnostics?

When designing bacterial diagnostic systems based on the tuf gene, researchers should consider several critical factors:

• Primer design strategy: Target regions with high interspecies variability flanked by conserved sequences. The 761-bp portion of the tuf gene provides sufficient discriminatory power for most streptococcal species while maintaining amplification efficiency .

• Detection limit optimization: For clinical applications, protocols should be optimized to achieve detection sensitivity of 1-10 genome copies per PCR reaction, as demonstrated for streptococcal species .

• Cross-reactivity assessment: Comprehensive testing against closely related species is essential. While streptococcal-specific primers showed excellent specificity, cross-amplification with certain Enterococcus and Lactococcus species has been observed, necessitating additional internal probes for absolute specificity .

• Validation against diverse strains: Test primers against multiple clinical isolates of each target species to account for intraspecies variation and avoid false negatives due to strain-specific polymorphisms.

• Multiplexing potential: When designing diagnostic panels, consider compatibility of tuf-based primers with other targets for multiplex PCR applications. Careful primer design can enable simultaneous detection of multiple pathogens while maintaining sensitivity and specificity.

How can anti-TUFM antibodies be incorporated into high-throughput screening methodologies?

Integrating anti-TUFM antibodies into high-throughput screening requires adaptation of standard protocols:

• Automated immunofluorescence: Optimize anti-TUFM antibody (ab173300) dilution (typically 1:100) for automated liquid handling systems and high-content imaging platforms . Standardize image acquisition parameters across plates to enable quantitative comparison.

• Flow cytometry-based screens: Adapt intracellular staining protocols using permeabilized cells with anti-TUFM antibody at appropriate dilution (1:10 for flow cytometry as demonstrated with ab173300) . Implement automated gating strategies based on negative controls.

• ELISA-based quantification: Develop sandwich ELISA using capture and detection antibodies targeting different TUFM epitopes, enabling quantitative assessment of TUFM levels across multiple samples simultaneously.

• Multiplex bead arrays: Conjugate anti-TUFM antibodies to spectrally distinct beads for incorporation into multiplex assays that simultaneously measure TUFM alongside other proteins involved in mitochondrial function or autophagy.

• Microfluidic applications: Optimize antibody concentrations and binding conditions for microfluidic chip-based assays that can assess TUFM levels or activity in minimal sample volumes, particularly valuable for precious clinical samples.

When implementing these high-throughput approaches, include appropriate positive and negative controls on each plate or in each batch to account for inter-assay variability.

How should researchers interpret conflicting results between different anti-TUFM antibody applications?

When facing conflicting results between different anti-TUFM antibody applications, researchers should implement a systematic analysis framework:

• Epitope accessibility assessment: Different applications (Western blot vs. immunoprecipitation vs. immunofluorescence) expose different epitopes. Polyclonal antibodies (ab264370) may recognize multiple epitopes, providing signal in denaturing conditions (Western blot) but potentially missing conformational epitopes important in native applications . Conversely, monoclonal antibodies (ab173300) recognize specific epitopes that may be masked in certain applications .

• Cross-validation approach: When results conflict, employ orthogonal detection methods. For example, if immunofluorescence and Western blot results disagree, validate with mass spectrometry or RNA interference to confirm specificity.

• Application-specific considerations:

  • For Western blotting: Evaluate reducing vs. non-reducing conditions, as disulfide bonds may affect epitope accessibility

  • For immunoprecipitation: Compare native vs. crosslinked conditions to assess whether protein-protein interactions mask the epitope

  • For immunohistochemistry: Compare different fixation and antigen retrieval methods, as demonstrated with citrate buffer for the ab173300 antibody

• Statistical analysis: Implement quantitative analysis with appropriate statistical tests when comparing signal intensity across applications to determine if differences are significant or within expected technical variation.

What statistical approaches best analyze tuf gene sequence data for phylogenetic studies?

For robust phylogenetic analysis of tuf gene sequence data, researchers should employ multiple complementary statistical approaches:

• Distance-based methods: Calculate nucleotide sequence divergence percentages between species (ranging from 15-31% for streptococcal species) . Use neighbor-joining algorithms with bootstrap analysis (minimum 1000 replicates) to assess confidence in branching patterns.

• Character-based methods: Implement maximum likelihood and Bayesian inference approaches that account for nucleotide substitution models specific to the tuf gene. The GTR+I+G model (General Time Reversible with Invariant sites and Gamma distribution) often provides appropriate complexity for bacterial gene analysis.

• Congruence testing: Compare phylogenetic trees generated from tuf sequences with those from established markers like 16S rRNA. Incongruent branching patterns may indicate horizontal gene transfer events or different evolutionary pressures on the respective genes .

• Clade support validation: Beyond bootstrap values, implement alternative support metrics like approximate likelihood ratio tests (aLRT) and SH-like tests to assess confidence in specific branches of the phylogenetic tree.

• Recombination detection: Prior to phylogenetic analysis, test for potential recombination events within the tuf gene using methods such as RDP4 or GARD, as recombination can confound phylogenetic inference.

This multi-faceted statistical approach provides more robust evolutionary insights than relying on a single method, particularly for closely related bacterial species where 16S rRNA sequences may be nearly identical but tuf sequences offer greater discrimination .