The Recombinant UPF0749 protein Rv1825/MT1873, also known as Rv1825 and MT1873, is a protein of interest in life sciences research, particularly in the context of Mycobacterium tuberculosis. This protein is part of a broader category of proteins known as UPF0749, which are involved in various biochemical functions and pathways. The recombinant form of this protein is produced in E. coli and is often used for research purposes.
Source: The recombinant UPF0749 protein Rv1825/MT1873 is expressed in Escherichia coli (E. coli) .
Tag: This protein is typically His-tagged, which facilitates purification and detection .
Amino Acid Sequence: The protein sequence includes the amino acids from position 29 to 292, with a specific sequence provided in the product details .
Protein Length: The full-length mature protein consists of 264 amino acids (from 29 to 292) .
Recombinant UPF0749 protein Rv1825/MT1873 is primarily used in research settings for studying protein functions, interactions, and pathways. It can be utilized in assays such as ELISA for detecting antibodies or in biochemical studies to understand its role in Mycobacterium tuberculosis.
UPF0749 protein Rv1825/MT1873 is an uncharacterized protein originating from Mycobacterium tuberculosis, the causative agent of tuberculosis. It belongs to the DUF881 (Domain of Unknown Function 881) family, indicating that its specific biological function remains incompletely characterized. The full-length protein consists of 292 amino acids, with the mature protein typically considered to comprise amino acids 29-292 . While classified as "uncharacterized," structural studies have yielded significant insights into its physical properties, with its crystal structure available in protein databases (PDB ID: 3GMG) .
The crystal structure of Rv1825/MT1873 has been determined and analyzed using multiple structural classification approaches. According to the ECOD database, it possesses an "a+b two layers" architecture within the "Alpha-beta plaits" homology group . The CATH database similarly classifies it as an "Alpha Beta" class protein with "2-Layer Sandwich" architecture and "Alpha-Beta Plaits" topology . These structural classifications provide researchers with a framework for comparing this protein to other structurally similar proteins, potentially offering insights into function despite its "uncharacterized" status.
While the exact role of Rv1825/MT1873 in M. tuberculosis pathogenesis has not been definitively established, its study is relevant to understanding tuberculosis. M. tuberculosis can invade various organs but primarily affects the lungs due to the absence of competing flora in the alveoli, allowing inhaled bacteria to establish infection . Researchers investigating Rv1825/MT1873's potential role in pathogenesis should consider several methodological approaches:
Gene knockout/knockdown studies to observe changes in virulence
Protein localization experiments to determine if Rv1825/MT1873 is surface-exposed or secreted
Host-pathogen interaction assays to identify potential binding partners
Expression analysis under various infection-relevant conditions
The increasing prevalence of multi-resistant strains of M. tuberculosis globally highlights the importance of understanding the function of all M. tuberculosis proteins, including uncharacterized ones like Rv1825/MT1873 .
As an uncharacterized protein, determining the function of Rv1825/MT1873 requires a multi-faceted approach:
Structural homology modeling: Comparing the crystal structure with functionally characterized proteins to identify potential shared mechanisms
Sequence conservation analysis: Examining evolutionary conservation patterns across mycobacterial species to identify functionally important residues
Protein-protein interaction studies: Using techniques such as co-immunoprecipitation or yeast two-hybrid screens to identify binding partners
Transcriptomic analysis: Determining under what conditions Rv1825/MT1873 is upregulated or downregulated
Machine learning approaches: Applying computational algorithms that integrate multiple data types to predict function
Each method provides complementary information, and convergent evidence from multiple approaches strengthens functional predictions.
M. tuberculosis is prone to developing drug resistance through both spontaneous mutations (primary resistance) and mutation selection (secondary resistance) . While the specific involvement of Rv1825/MT1873 in resistance mechanisms is not detailed in current literature, researchers interested in this question could employ several strategies:
Comparing expression levels between drug-sensitive and resistant strains
Analyzing structural features for potential binding sites that might interact with antimicrobial compounds
Creating overexpression or knockout strains to test for altered drug susceptibility profiles
Examining potential structural similarities to known drug resistance determinants
Screening for physical interactions with known drug targets or drug molecules
Given the global health challenge posed by multi-resistant M. tuberculosis strains, this represents an important area for investigation .
| Expression System | Advantages | Considerations |
|---|---|---|
| E. coli | High yield, cost-effective, rapid expression | Potential issues with protein folding, lack of post-translational modifications |
| Yeast | Better protein folding, some post-translational modifications | Longer expression time, more complex media requirements |
| Baculovirus | Superior folding for complex proteins, extensive post-translational modifications | Higher cost, technical complexity, longer timeline |
| Mammalian Cell | Native-like folding and modifications | Highest cost, lowest yield, most complex methodology |
For most basic research applications, E. coli expression using a construct comprising amino acids 29-292 with an N-terminal His-tag has proven effective . This suggests that the first 28 amino acids might constitute a signal peptide or otherwise hinder recombinant expression.
While specific optimization parameters must be determined empirically for each expression construct, the following general purification workflow has proven effective:
Immobilized metal affinity chromatography (IMAC): For His-tagged constructs, using Ni-NTA or similar resins
Buffer optimization: Purified protein shows stability in Tris/PBS-based buffer with 6% Trehalose at pH 8.0
Quality control: SDS-PAGE analysis should demonstrate >90% purity
Storage preparation: Lyophilization or flash-freezing of purified protein in appropriate storage buffer
For specialized applications requiring higher purity, additional purification steps such as size exclusion chromatography or ion exchange chromatography may be warranted.
To maintain protein stability and activity, the following storage protocols are recommended:
Store lyophilized powder at -20°C to -80°C until reconstitution
Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL
Add glycerol to a final concentration between 5-50% (with 50% being optimal for longest storage)
Prepare multiple small-volume aliquots to avoid repeated freeze-thaw cycles
For working solutions, store at 4°C for no more than one week
Repeated freeze-thaw cycles significantly reduce protein stability and should be strictly avoided through proper aliquoting procedures .
The structural analysis of Rv1825/MT1873 can be approached through multiple complementary techniques:
X-ray crystallography: Already performed (PDB ID: 3GMG), revealing the alpha-beta two-layer sandwich architecture
NMR spectroscopy: For analyzing dynamic properties and potential ligand interactions
Circular dichroism (CD): To analyze secondary structure content and thermal stability
Small-angle X-ray scattering (SAXS): For studying the protein in solution and detecting conformational changes
Hydrogen-deuterium exchange mass spectrometry: To identify regions of structural flexibility
Computational approaches: Molecular dynamics simulations to predict protein motion and stability
Structural classification databases provide valuable context for interpreting results:
Several computational approaches can identify potential functional regions within Rv1825/MT1873:
Cavity detection algorithms: Programs like CASTp, POCKET, and fpocket can identify potential binding pockets
Electrostatic surface mapping: To identify charged regions that might participate in interactions
Sequence conservation mapping: Using ConSurf or similar tools to map evolutionary conservation onto structure
Molecular docking: Virtual screening for potential ligands or substrates
Machine learning approaches: Newer methods integrating multiple data types for function prediction
These computational predictions should guide experimental design rather than being considered definitive, with wet-lab validation essential for confirming predicted functional sites.
Rv1825/MT1873 has potential applications in tuberculosis vaccine research strategies:
Subunit vaccine component: As a recombinant protein antigen either alone or as part of a multi-antigen formulation
Epitope identification: Mapping immunogenic regions that could be incorporated into epitope-based vaccines
Carrier protein: Potentially serving as a carrier for mycobacterial antigens or adjuvants
Diagnostic marker: Development of serological tests to detect TB-specific immune responses
Researchers should note that while recombinant Rv1825/MT1873 is valuable for vaccine research, all experimental materials can only be used for research purposes and cannot be used directly on humans or animals . Progression to clinical applications requires extensive additional testing following regulatory guidelines.
To assess the potential of Rv1825/MT1873 in vaccine development, researchers should consider:
T-cell response assays: ELISPOT or intracellular cytokine staining to measure Th1/Th17 responses
Antibody profiling: ELISA or multiplex assays to quantify humoral responses
Epitope mapping: Using peptide arrays or phage display to identify immunodominant regions
Antigen presentation studies: Determining how the protein is processed and presented by APCs
Challenge studies: Using appropriate animal models to assess protective efficacy
Cross-reactivity testing: Evaluating specificity against non-tuberculous mycobacteria
These assays should be performed in a systematic manner, beginning with in vitro studies before progressing to appropriate animal models.
Mass spectrometry offers powerful tools for characterizing Rv1825/MT1873:
Intact protein MS: Confirming molecular weight and verifying expression construct accuracy
Peptide mapping: Identifying post-translational modifications and confirming sequence coverage
Hydrogen-deuterium exchange: Probing structural dynamics and solvent accessibility
Cross-linking MS: Identifying intra-molecular or protein-protein interactions
Native MS: Analyzing oligomeric state and non-covalent interactions
MRM/PRM: Developing targeted quantification methods for complex samples
For recombinant His-tagged constructs, researchers should account for the additional mass of the tag and any linker sequences when interpreting mass spectrometry data.
Quality control for purified Rv1825/MT1873 should include:
Western blotting: Confirming identity using anti-His or protein-specific antibodies
Size exclusion chromatography: Assessing aggregation state and homogeneity
Dynamic light scattering: Measuring particle size distribution and polydispersity
Circular dichroism: Verifying secondary structure content matches predictions
Thermal shift assays: Determining protein stability and identifying stabilizing buffer conditions
Activity assays: If function is known or hypothesized, relevant functional assays
These quality control measures are essential for ensuring experimental reproducibility and interpreting biological results correctly.
Several cutting-edge approaches could advance understanding of Rv1825/MT1873:
Cryo-electron microscopy: For higher-resolution structural studies or examining protein complexes
AlphaFold and similar AI approaches: For improved structural prediction and functional inference
CRISPR interference in mycobacteria: For precise gene regulation studies
Proximity labeling approaches: For identifying interaction partners in their native context
Single-cell transcriptomics: For understanding expression patterns during infection
Structural mass spectrometry: For analyzing conformational dynamics
Integration of multiple advanced technologies will likely be necessary to fully elucidate the function of this currently uncharacterized protein.
A systematic approach to functional characterization might include:
Start with bioinformatic analysis of sequence and structure
Generate testable hypotheses based on structural similarities and genomic context
Design targeted mutagenesis of predicted functional residues
Develop biochemical assays based on structural features (e.g., testing for enzymatic activity)
Create knockout or conditional expression strains to observe phenotypic effects
Investigate expression patterns under different growth and stress conditions
Test for interactions with host cells or components
This process should be iterative, with each round of experiments refining hypotheses and guiding subsequent investigations.