Recombinant Uncharacterized protein Rv2076c/MT2136 (Rv2076c, MT2136)

What is Recombinant Uncharacterized protein Rv2076c/MT2136?

Recombinant Uncharacterized protein Rv2076c/MT2136 is a full-length protein consisting of 83 amino acids. It is typically expressed with an N-terminal His-tag in E. coli expression systems to facilitate purification and functional studies. The amino acid sequence of this protein is MVVCLIGGVAGSLWPRPAGRLRGGCYFAFMGVAWVLLAISAIANAVKGSLWWDIWSLGLLVLIPAVVYGKMRRSRRISSDQDR . Despite appearing in genomic analyses of mycobacterial species, its specific functions remain largely uncharacterized, making it an interesting target for fundamental research in mycobacterial biology .

What is the source and taxonomic origin of Rv2076c/MT2136?

The Rv designation typically refers to genes from Mycobacterium tuberculosis H37Rv reference genome. While commercially available recombinant versions may be labeled as human proteins when expressed in human expression systems, genomic evidence indicates that Rv2076c/MT2136 is a mycobacterial protein that appears in genome sequence analyses of various mycobacterial species, including M. suricattae . This protein is of particular interest as it has been identified as conserved across certain mycobacterial lineages during comparative genomic studies .

What are the optimal storage conditions for recombinant Rv2076c/MT2136?

For optimal stability and activity, recombinant Rv2076c/MT2136 should be stored at -20°C to -80°C upon receipt, with aliquoting necessary for multiple uses to avoid repeated freeze-thaw cycles. The lyophilized protein is typically reconstituted in deionized sterile water to a concentration of 0.1-1.0 mg/mL, with the addition of 5-50% glycerol (final concentration) recommended for long-term storage. Working aliquots can be stored at 4°C for up to one week, but repeated freezing and thawing should be avoided to maintain protein integrity .

How should I design experiments to characterize the function of Rv2076c/MT2136?

When designing experiments to characterize Rv2076c/MT2136, begin by clearly defining your variables. Treat the protein's presence, concentration, or activity as your independent variable, while selecting appropriate dependent variables such as cellular responses, binding interactions, or enzymatic activities based on bioinformatic predictions of its function .

A systematic experimental approach would include:

• Bioinformatic analysis to predict potential functions based on sequence homology

• Protein-protein interaction studies to identify binding partners

• Cellular localization experiments to determine subcellular distribution

• Loss-of-function studies using gene knockdown/knockout in mycobacterial models

• Gain-of-function studies by overexpression in appropriate cellular systems

Control for extraneous variables by maintaining consistent experimental conditions and including appropriate positive and negative controls in all assays .

What are the key considerations for expression and purification of Rv2076c/MT2136?

When expressing and purifying Rv2076c/MT2136, several methodological considerations are critical for obtaining high-quality protein:

• Expression system selection: While E. coli is commonly used for recombinant expression, consider that the native protein comes from mycobacteria, which may have different post-translational modifications. For specific applications, mycobacterial expression systems might provide more native-like protein .

• Purification strategy: The commercially available protein includes an N-terminal His-tag, allowing for purification using nickel affinity chromatography. Consider whether the tag might interfere with function in your specific experimental context, and whether tag removal might be necessary .

• Quality control: Verify protein purity using SDS-PAGE (should be >90% pure) and consider additional characterization by mass spectrometry to confirm identity and integrity .

• Buffer optimization: The protein is typically maintained in Tris/PBS-based buffer with 6% trehalose at pH 8.0, but buffer conditions may need optimization depending on downstream applications .

How can I design experiments to investigate Rv2076c/MT2136 in the context of mycobacterial pathogenesis?

Investigating Rv2076c/MT2136 in the context of mycobacterial pathogenesis requires a multi-faceted experimental approach:

• Comparative genomics: Analyze the conservation and variation of Rv2076c across pathogenic and non-pathogenic mycobacterial species to infer its potential role in virulence .

• Infection models: Design experiments using appropriate in vitro (macrophage infection) or in vivo (animal model) systems with wild-type and Rv2076c-mutant mycobacterial strains.

• Host response analysis: Measure key parameters such as bacterial survival, cytokine production, and host cell death to determine if Rv2076c affects host-pathogen interactions.

• Between-subjects design: Compare groups infected with wild-type versus Rv2076c-deficient strains, ensuring random assignment of subjects to minimize bias .

• Within-subjects design: For time-course experiments, follow the same infection over time to track progression and host response dynamics .

What structural analyses can reveal the function of Rv2076c/MT2136?

Advanced structural analyses can provide significant insights into the potential function of this uncharacterized protein:

• Predictive structural modeling: Use approaches such as AlphaFold to predict the 3D structure based on the amino acid sequence MVVCLIGGVAGSLWPRPAGRLRGGCYFAFMGVAWVLLAISAIANAVKGSLWWDIWSLGLLVLIPAVVYGKMRRSRRISSDQDR .

• Experimental structure determination: Consider X-ray crystallography or NMR spectroscopy for high-resolution structural analysis of the purified recombinant protein.

• Structural homology analysis: Compare predicted or determined structures with known protein structures to identify potential functional domains.

• Molecular dynamics simulations: Investigate protein flexibility and potential binding sites through computational modeling.

• Structure-guided mutagenesis: Based on structural insights, design targeted mutations of key residues to test functional hypotheses.

The presence of hydrophobic stretches in the sequence suggests potential membrane association, which should be considered when designing structural studies and may require specialized approaches for membrane proteins .

How can genomic and transcriptomic data be leveraged to understand Rv2076c/MT2136 function?

Integrating genomic and transcriptomic approaches provides powerful insights into Rv2076c function:

• Comparative genomics analysis: Analyze the conservation of Rv2076c across mycobacterial species, particularly noting presence/absence patterns between pathogenic and non-pathogenic strains .

• Synteny analysis: Examine the genomic context of Rv2076c to identify functionally related genes that may be co-regulated or participate in the same pathway.

• Expression correlation studies: Analyze RNA-seq data to identify genes with expression patterns that correlate with Rv2076c under various conditions, suggesting functional relationships.

• Condition-specific expression analysis: Examine how Rv2076c expression changes under different stress conditions, in different growth phases, or during infection.

• Regulatory network mapping: Identify potential transcription factors that regulate Rv2076c expression through motif analysis and chromatin immunoprecipitation studies.

When analyzing genomic data, ensure appropriate quality control measures are applied to sequencing data, including adapter removal, quality trimming, and validation using multiple alignment tools as described in methodological approaches for mycobacterial genomics .

What approaches can be used to study potential protein-protein interactions of Rv2076c/MT2136?

To elucidate the functional role of Rv2076c through its protein interactions, consider these methodological approaches:

• Pull-down assays: Use the His-tagged recombinant Rv2076c protein as bait to identify interacting partners from mycobacterial lysates, followed by mass spectrometry identification .

• Yeast two-hybrid screening: Screen mycobacterial genomic libraries to identify potential interacting partners in a high-throughput manner.

• Co-immunoprecipitation: Develop specific antibodies against Rv2076c for immunoprecipitation of native protein complexes from mycobacterial cells.

• Proximity-dependent biotin labeling (BioID or APEX): Express Rv2076c fused to a biotin ligase in mycobacterial cells to identify proximal proteins in its native environment.

• Surface plasmon resonance or isothermal titration calorimetry: Quantitatively measure binding affinities and kinetics between purified Rv2076c and candidate interacting partners.

• Cross-linking mass spectrometry: Use chemical cross-linkers to capture transient protein interactions followed by mass spectrometry analysis.

When designing these experiments, careful consideration of experimental controls is essential. Include non-specific proteins (e.g., GFP) as negative controls for pull-down experiments, and validate key interactions through multiple independent methods .

How should I analyze data from functional studies of Rv2076c/MT2136?

Data analysis for functional studies of Rv2076c should follow these methodological principles:

• Statistical approach selection: For comparing experimental groups (e.g., wild-type vs. Rv2076c mutant), select appropriate statistical tests based on data distribution, sample size, and experimental design.

• Replication and technical considerations: Include both biological and technical replicates to account for variability, with a minimum of three independent experiments.

• Normalization strategies: When measuring protein activity or expression, normalize to appropriate housekeeping proteins or total protein content to account for loading variations.

• Dose-response relationships: If studying concentration-dependent effects, perform full dose-response curves rather than single concentrations to establish mechanism of action.

• Time-course analysis: For dynamic processes, capture multiple time points to understand the kinetics of Rv2076c-mediated effects.

• Integration of multiple assays: Combine results from different experimental approaches (e.g., binding, localization, functional assays) for a comprehensive understanding of protein function.

Avoid common pitfalls such as p-hacking by pre-defining analysis parameters and considering multiple hypothesis testing corrections when appropriate .

What bioinformatic approaches can predict the function of Rv2076c/MT2136?

When the experimental characterization of Rv2076c is limited, bioinformatic approaches can provide valuable predictive insights:

• Sequence homology analysis: Compare the Rv2076c sequence (MVVCLIGGVAGSLWPRPAGRLRGGCYFAFMGVAWVLLAISAIANAVKGSLWWDIWSLGLLVLIPAVVYGKMRRSRRISSDQDR) with characterized proteins across species to identify potential homologs .

• Domain and motif prediction: Scan the sequence for recognized functional domains, transmembrane regions, signal peptides, and other functional motifs.

• Structural prediction and comparative modeling: Use tools like AlphaFold to predict three-dimensional structure and compare with known structures to infer function.

• Genomic context analysis: Examine neighboring genes in the mycobacterial genome to identify potential operons or functional relationships.

• Evolutionary analysis: Perform phylogenetic analysis to understand conservation patterns across mycobacterial species and strains, particularly between pathogenic and non-pathogenic lineages .

• Network-based function prediction: Integrate available protein-protein interaction data, co-expression patterns, and mutual exclusivity patterns in different mycobacterial lineages to predict functional associations.

When applying these approaches, it's important to critically evaluate prediction confidence by considering multiple lines of evidence rather than relying on a single prediction method .

How can Rv2076c/MT2136 be studied in the context of drug resistance mechanisms?

Investigating Rv2076c in relation to drug resistance mechanisms requires specialized experimental approaches:

• Expression analysis in resistant strains: Compare Rv2076c expression levels between drug-sensitive and resistant clinical isolates of M. tuberculosis using qPCR or RNA-seq.

• Genetic association studies: Analyze whole genome sequencing data from clinical isolates to identify potential associations between Rv2076c mutations and resistance phenotypes .

• Overexpression and knockout studies: Determine whether modulation of Rv2076c levels affects minimum inhibitory concentrations (MICs) of various antimicrobial agents.

• Protein-drug interaction studies: Investigate whether Rv2076c directly interacts with antimicrobial compounds using techniques such as drug affinity responsive target stability (DARTS) or cellular thermal shift assays (CETSA).

• Pathway analysis: Determine if Rv2076c influences known resistance mechanisms by affecting cell wall permeability, efflux pump activity, or drug-modifying enzymes.

When designing these experiments, include appropriate controls such as well-characterized resistance genes and multiple drug classes to differentiate specific versus general resistance mechanisms .

What are the considerations for developing antibodies against Rv2076c/MT2136?

Developing effective antibodies against Rv2076c requires careful consideration of multiple factors:

• Immunogen design: Based on the amino acid sequence (MVVCLIGGVAGSLWPRPAGRLRGGCYFAFMGVAWVLLAISAIANAVKGSLWWDIWSLGLLVLIPAVVYGKMRRSRRISSDQDR), select antigenic regions with high predicted surface exposure and low sequence similarity to host proteins .

• Production strategy options:

  • Polyclonal antibodies: Immunize animals with recombinant His-tagged Rv2076c protein

  • Monoclonal antibodies: Screen hybridoma clones for specificity and sensitivity

  • Recombinant antibodies: Consider phage display technology for difficult targets

• Validation approach:

  • Western blot analysis using recombinant protein as positive control

  • Immunoprecipitation to confirm native protein recognition

  • Immunofluorescence to verify specificity in fixed mycobacterial cells

  • Preabsorption controls to confirm specificity

  • Testing against Rv2076c knockout strains as negative controls

• Cross-reactivity assessment: Test antibodies against homologous proteins from related mycobacterial species to determine specificity versus broad reactivity.

• Application optimization: Different applications (Western blot, ELISA, IHC, IP) may require different antibody characteristics, necessitating application-specific validation .

What are the major research gaps in understanding Rv2076c/MT2136 function?

Despite genomic identification and availability of recombinant Rv2076c protein, significant knowledge gaps remain:

• Functional characterization: The specific biochemical and cellular functions of Rv2076c remain largely unknown, limiting our understanding of its role in mycobacterial biology.

• Structural information: Detailed three-dimensional structural data is lacking, which would provide insights into potential functional mechanisms.

• Regulation mechanisms: The conditions under which Rv2076c is expressed and the regulatory networks controlling its expression are poorly understood.

• Interacting partners: Comprehensive protein-protein interaction networks involving Rv2076c have not been established, limiting our understanding of its functional context.

• Role in pathogenesis: The potential contribution of Rv2076c to mycobacterial virulence, persistence, or immune evasion remains to be elucidated.

• Clinical relevance: The significance of Rv2076c in clinical outcomes, drug resistance, or as a potential biomarker or therapeutic target requires further investigation .

Addressing these knowledge gaps requires integrated approaches combining genomics, proteomics, structural biology, and functional studies in relevant model systems .

How can Rv2076c/MT2136 research contribute to tuberculosis treatment strategies?

Research on Rv2076c has potential implications for tuberculosis treatment strategies through multiple avenues:

• Novel drug target identification: If Rv2076c is found to be essential for mycobacterial survival or virulence, it could represent a novel target for antimicrobial development.

• Resistance mechanism understanding: Elucidating whether Rv2076c plays a role in drug resistance mechanisms could inform strategies to overcome or prevent resistance.

• Diagnostic development: If Rv2076c shows strain-specific variations or is differentially expressed in certain disease states, it could have potential as a diagnostic biomarker.

• Vaccine antigen evaluation: Assessment of Rv2076c immunogenicity and conservation across clinical strains could inform its potential inclusion in subunit vaccine formulations.

• Host-pathogen interaction insights: Understanding how Rv2076c might interact with host factors could reveal new approaches to modulate host response for therapeutic benefit.