Recombinant Uncharacterized protein Rv2083/MT2145 (Rv2083, MT2145)

What is Recombinant Uncharacterized Protein Rv2083/MT2145?

Recombinant Uncharacterized Protein Rv2083/MT2145 is a protein derived from Mycobacterium tuberculosis, the bacterium responsible for tuberculosis. Despite its potential significance in pathogenesis, its specific functions remain largely uncharacterized. The recombinant form is typically produced through genetic engineering techniques, primarily in Escherichia coli (E. coli) expression systems, for research purposes including vaccine development studies.

What bioinformatic approaches can be used for initial characterization of Rv2083/MT2145?

Initial characterization of Rv2083/MT2145 should employ a systematic bioinformatic workflow:

• Sequence analysis using BLAST for homology detection

• Motif and domain identification using NCBI Conserved Domain Database (CDD)

• Physicochemical property prediction (instability index, theoretical pI, GRAVY values)

• Subcellular localization prediction using tools like PSORTb

• Secretory nature analysis using SignalP 5.0

• Structure prediction through homology modeling or ab initio approaches

This multi-faceted approach provides a foundation for understanding potential functions before experimental validation. In similar analyses of uncharacterized proteins, researchers have found that approximately 70% of hypothetical proteins demonstrate stability with instability index values below 40, while about 70% typically show negative GRAVY values indicating non-polar nature .

What are the key physicochemical properties to analyze for Rv2083/MT2145?

The following physicochemical properties should be systematically analyzed:

When characterizing uncharacterized proteins, researchers typically find theoretical pI values ranging from 4.05 to 11.99, with specific distributions varying by organism and protein family .

What expression systems are most suitable for Rv2083/MT2145?

While multiple expression systems can be employed for recombinant protein production, each offers distinct advantages for expressing Rv2083/MT2145:

E. coli remains the preferable host for recombinant proteins due to its low cost, well-known biochemistry and genetics, rapid growth, and good productivity . The selection should be guided by specific experimental objectives and protein characteristics.

How can Rv2083/MT2145 expression in E. coli be optimized?

Optimizing expression of Rv2083/MT2145 in E. coli requires systematic adjustment of multiple parameters:

• Codon optimization: Adjusting the coding sequence to match E. coli codon usage preferences can increase expression by many folds, particularly for mycobacterial genes which may contain rare codons .

• Fusion tags selection:

  • Addition of solubility-enhancing tags (SUMO, MBP, TRX, Fh8) at the N-terminus

  • Inclusion of purification tags (His, GST) for downstream processing

  • Combination tags that enhance both solubility and purification efficiency

• Expression conditions optimization:

  • Lower post-induction temperature (16-25°C) to enhance proper folding

  • Reduced IPTG concentration (0.1-0.5 mM) to slow expression rate

  • Addition of chemical chaperones (sorbitol, glycerol, arginine) to culture medium

  • Co-expression with molecular chaperones (GroEL/GroES, DnaK/DnaJ)

• Inclusion body management strategies:

  • Refolding protocols using stepwise dialysis

  • Solubilization in mild detergents rather than chaotropic agents

  • On-column refolding during purification

Implementation of these strategies has been shown to increase soluble protein yields by 2-10 fold in challenging recombinant protein expression systems.

What advanced purification strategies are effective for obtaining high-purity Rv2083/MT2145?

A multi-step purification strategy is typically required to obtain research-grade Rv2083/MT2145:

• Initial capture: Affinity chromatography (IMAC for His-tagged protein)

• Intermediate purification: Ion exchange chromatography based on predicted pI

• Polishing: Size exclusion chromatography for final purity enhancement

• Quality control: SDS-PAGE, Western blot, and mass spectrometry validation

For structural studies requiring ultra-pure protein, additional considerations include:

• Buffer optimization through thermal shift assays to enhance stability

• Removal of fusion tags with high-specificity proteases (TEV, PreScission)

• Monitoring protein homogeneity through dynamic light scattering

When designing purification protocols, researchers should consider that approximately 23-27% of mycobacterial hypothetical proteins may localize to the cytoplasmic membrane, which can impact solubilization and purification strategies .

What experimental approaches are most effective for determining the structure of Rv2083/MT2145?

Structural determination of Rv2083/MT2145 requires a strategic combination of techniques:

The strategic approach should begin with crystallization trials while simultaneously pursuing lower-resolution techniques to gain preliminary structural insights. Prior to expensive structural studies, computational prediction through AlphaFold2 or RoseTTAFold can provide valuable initial models.

How can binding partners and interaction networks of Rv2083/MT2145 be identified?

Identifying the interaction network of Rv2083/MT2145 requires a multi-technique approach:

• In vitro methods:

  • Pull-down assays using tagged Rv2083/MT2145 as bait

  • Surface plasmon resonance to measure binding kinetics

  • Isothermal titration calorimetry for thermodynamic parameters

  • Fluorescence-labeled binding assays similar to those used for bio-nanocapsules

• Cellular methods:

  • Bacterial two-hybrid screening

  • Co-immunoprecipitation followed by mass spectrometry

  • Chemical cross-linking coupled with mass spectrometry

  • Proximity-dependent biotin labeling (BioID, APEX)

• Computational predictions:

  • Protein-protein interaction databases mining

  • Structural docking simulations

  • Co-expression network analysis across tuberculosis transcriptome datasets

Combining these approaches provides a comprehensive view of potential interaction partners, which can significantly accelerate functional characterization of this uncharacterized protein.

How can contradictions in experimental data about Rv2083/MT2145 be analyzed and resolved?

Resolving contradictions in experimental data requires systematic investigation:

• Identify the specific contradiction:

  • Document exact experimental conditions from conflicting studies

  • Compare protein constructs (tags, mutations, truncations)

  • Evaluate expression systems and purification methods

• Design controlled experiments:

  • Perform side-by-side comparisons under identical conditions

  • Use multiple orthogonal techniques to measure the same parameter

  • Include positive and negative controls for validation

• Statistical analysis:

  • Apply appropriate statistical tests to determine significance

  • Consider sample size and statistical power

  • Evaluate potential biases in experimental design

• Replication and validation:

  • Reproduce key experiments with blinded analysis

  • Collaborate with independent laboratories

  • Consider biological variability vs. technical artifacts

When reporting contradictory results, clear articulation in the results section of scientific papers is essential, avoiding terms like "increased" or "decreased" for insignificant changes and reserving these words for statistically significant differences .

How can Rv2083/MT2145 be evaluated as a potential vaccine candidate?

Evaluating Rv2083/MT2145 as a vaccine candidate requires systematic assessment of multiple parameters:

• Antigenicity and immunogenicity assessment:

  • In silico prediction of B-cell and T-cell epitopes

  • Experimental validation through ELISPOT or IFN-γ release assays

  • Analysis of antigen presentation by different MHC alleles

• Safety profile determination:

  • Allergenicity prediction using computational tools

  • Homology analysis with human proteins to avoid cross-reactivity

  • In vitro cytotoxicity testing in relevant cell lines

• Formulation optimization:

  • Adjuvant selection and combination testing

  • Stability studies under various storage conditions

  • Delivery system development (liposomes, nanoparticles)

• Preclinical efficacy studies:

  • Challenge studies in appropriate animal models

  • Correlates of protection identification

  • Dose-response relationship determination

For effective vaccine development, proteins should be non-homologous to human proteins (to avoid cross-reactivity), antigenic, non-allergenic, and potentially contain virulence factors. Studies of hypothetical proteins have shown that approximately 99.7% are typically non-homologous to human proteins, while 36-41% demonstrate antigenicity properties favorable for vaccine development .

What experimental design principles should guide research on Rv2083/MT2145?

Research on Rv2083/MT2145 should follow these experimental design principles:

• Clearly define variables:

  • Independent variables (protein concentration, buffer conditions, etc.)

  • Dependent variables (binding affinity, enzymatic activity, etc.)

  • Control variables to maintain consistency

• Formulate specific, testable hypotheses based on:

  • Bioinformatic predictions

  • Preliminary data

  • Literature on related proteins

• Design controlled experiments:

  • Include appropriate positive and negative controls

  • Minimize confounding variables

  • Use randomization and blinding where possible

• Plan appropriate measurements:

  • Select techniques with suitable sensitivity and specificity

  • Determine sample size through power analysis

  • Establish clear endpoints and success criteria

• Consider replication strategies:

  • Technical replicates to assess method reliability

  • Biological replicates to account for natural variation

  • Independent experimental repetitions

Following these principles ensures that research on Rv2083/MT2145 yields reliable, reproducible results that can advance our understanding of this uncharacterized protein.

How can cellular localization and trafficking of Rv2083/MT2145 be determined in mycobacterial cells?

Understanding the cellular localization of Rv2083/MT2145 requires complementary approaches:

• Computational prediction:

  • PSORTb analysis for subcellular localization

  • SignalP for secretion signal identification

  • TMHMM for transmembrane domain prediction

  • These predictions can classify proteins into cytoplasmic, cytoplasmic membrane, extracellular, or unknown locations

• Fluorescence microscopy techniques:

  • GFP fusion constructs for live cell imaging

  • Immunofluorescence with specific antibodies

  • Time-lapse imaging for dynamic trafficking studies

• Biochemical fractionation:

  • Differential centrifugation to separate cellular compartments

  • Detergent solubility analysis for membrane association

  • Protease protection assays for topology determination

• Proximity labeling approaches:

  • BioID or APEX2 fusion to identify neighboring proteins

  • Spatially-restricted enzymatic tagging of interaction partners

When characterizing hypothetical proteins, subcellular localization studies typically find that approximately 32-38% localize to the cytoplasm, 23-27% to the cytoplasmic membrane, 1-3% to extracellular spaces, and 37-40% have unknown localization .

How can multi-omics data be integrated to understand the biological context of Rv2083/MT2145?

Integrating multi-omics data provides comprehensive insights into Rv2083/MT2145 function:

• Data acquisition and integration strategy:

  • Transcriptomics: RNA-seq under various conditions

  • Proteomics: Quantitative MS analysis

  • Metabolomics: Changes associated with protein expression

  • Interactomics: Protein-protein interaction networks

• Correlation analysis:

  • Co-expression patterns with known proteins

  • Temporal relationships during infection process

  • Stress response signatures

• Network reconstruction:

  • Contextual positioning within metabolic networks

  • Regulatory network mapping

  • Functional module identification

• Condition-specific analysis:

  • Differential expression during host infection

  • Response to antibiotic treatment

  • Nutrient limitation effects

This systems biology approach can reveal functional associations even when direct biochemical functions remain uncharacterized, providing valuable context for targeted experimental studies.

What are the current challenges in functional annotation of uncharacterized proteins like Rv2083/MT2145?

Several significant challenges persist in characterizing proteins like Rv2083/MT2145:

• Technical limitations:

  • Difficulty in expressing mycobacterial proteins in heterologous systems

  • Limited sensitivity of assays for detecting subtle biochemical activities

  • Challenges in crystallizing proteins for structural determination

• Biological complexity:

  • Potential moonlighting functions (multiple distinct roles)

  • Context-dependent activity requiring specific co-factors or conditions

  • Functional redundancy masking phenotypes in knockout studies

• Computational challenges:

  • Remote homology detection limitations

  • Difficulty predicting novel folds or enzymatic activities

  • Integration of conflicting predictions from different algorithms

• Experimental design issues:

  • Selection of appropriate cellular or biochemical assays

  • Development of specific antibodies or detection methods

  • Design of relevant phenotypic screens

Addressing these challenges requires innovative approaches combining computational prediction, high-throughput screening, and targeted biochemical characterization within physiologically relevant contexts.