KEGG: mva:Mvan_3406
STRING: 350058.Mvan_3406
Recombinant Mycobacterium vanbaalenii UPF0060 membrane protein Mvan_3406 is a full-length membrane protein derived from Mycobacterium vanbaalenii. According to available research data, it consists of 108 amino acids and belongs to the UPF0060 family (Uncharacterized Protein Family 0060). When produced recombinantly, it is typically expressed with a His-tag in E. coli expression systems to facilitate purification and experimental applications .
Based on available data, E. coli has been successfully employed as an expression host for Mvan_3406. When working with membrane proteins like Mvan_3406, researchers should consider specialized E. coli strains (such as C41/C43 or Lemo21) that are optimized for membrane protein expression. Additionally, expression parameters including induction temperature, inducer concentration, and expression duration should be optimized to maximize protein yield while minimizing toxicity and inclusion body formation .
When designing experiments to characterize Mvan_3406 function, researchers should implement a multi-faceted approach:
Begin with clear hypotheses about potential functions based on bioinformatic analyses and sequence homology with characterized proteins.
Implement factorial experimental designs when testing multiple variables (e.g., pH, temperature, ligands) that might affect protein activity or stability.
Include appropriate positive and negative controls in all experiments.
Ensure sufficient biological and technical replicates to achieve statistical power.
Consider within-subject designs where appropriate to control for variability between expression batches.
This systematic approach aligns with established principles of experimental design in biological research and will help generate robust, reproducible data .
When addressing within-subject variability in Mvan_3406 research:
Implement blocking approaches by treating experimental batches or expression runs as blocks to account for batch-to-batch variability.
Consider using repeated measures ANOVA or mixed-effects models that explicitly account for the correlation structure of within-subject measurements.
When comparing treatments or conditions, randomize the order of treatments within each subject to minimize sequence effects.
Calculate appropriate sample sizes before beginning experiments, recognizing that within-subject designs typically require fewer subjects than between-subject designs for equivalent statistical power.
Document all relevant experimental conditions meticulously to identify potential sources of variability.
These approaches will help ensure that observed effects can be confidently attributed to experimental manipulations rather than uncontrolled variability .
Given the challenges inherent to membrane protein purification, researchers should consider the following strategies for Mvan_3406:
Begin with careful membrane isolation using differential centrifugation or density gradient techniques.
Select appropriate detergents for solubilization—starting with milder detergents like DDM or LMNG that maintain native protein conformation.
Utilize the His-tag for affinity purification with optimized imidazole concentration gradients to separate full-length protein from truncated products.
Consider implementing a two-step purification strategy with affinity chromatography followed by size exclusion chromatography.
Validate protein purity and integrity using SDS-PAGE, Western blotting, and mass spectrometry.
For membrane proteins like Mvan_3406, maintaining the native conformation throughout purification is critical for subsequent functional studies .
When presenting data from Mvan_3406 studies, researchers should follow these guidelines for maximum clarity and impact:
Organize information in a logical sequence, beginning with basic characterization data before presenting more complex functional analyses.
Use tables for summarizing large datasets such as protein properties, purification yields, or activity measurements across multiple conditions.
Present comparative data (e.g., activity profiles under different conditions) in clearly labeled graphs rather than as text.
Employ consistent formatting and units throughout all data presentations.
Ensure that each data presentation directly addresses a specific research question or hypothesis.
Avoid redundancy by selecting the most appropriate format (text, table, or figure) for each dataset.
This structured approach to data presentation enhances clarity and facilitates interpretation by other researchers in the field .
The statistical approach should be dictated by the experimental design and research questions. For Mvan_3406 studies:
For simple comparisons between two conditions, t-tests (paired or unpaired as appropriate) may be sufficient.
For more complex designs involving multiple factors, factorial ANOVA with appropriate post-hoc tests should be implemented.
When dealing with repeated measurements (such as activity over time), repeated measures ANOVA or mixed-effects models are most appropriate.
For dose-response relationships, non-linear regression models should be considered.
For all analyses, researchers should verify that their data meet the assumptions of the statistical test being applied, and apply transformations or non-parametric alternatives as needed.
The chosen statistical approach should be determined a priori as part of the experimental design, not after data collection .
When confronted with contradictory results in Mvan_3406 studies, researchers should systematically:
Compare methodological details across studies, including expression constructs, purification methods, and assay conditions.
Examine whether differences in protein tags or expression systems might contribute to functional discrepancies.
Consider whether post-translational modifications, which may vary across expression systems, could explain functional differences.
Evaluate the statistical power of each study and whether sample sizes were sufficient to detect effects reliably.
Design reconciliation experiments that specifically address the contradictions by systematically varying the conditions that differ between studies.
This methodical approach can help identify the sources of discrepancies and advance understanding rather than creating confusion in the literature.
For identifying Mvan_3406's interaction partners, consider these methodologies:
Co-immunoprecipitation (Co-IP) using antibodies against the His-tag or against Mvan_3406 itself, followed by mass spectrometry identification of co-precipitated proteins.
Pull-down assays using immobilized Mvan_3406 as bait to capture interacting proteins from cellular lysates.
Proximity-based labeling approaches such as BioID or APEX, which are particularly valuable for membrane proteins as they can identify neighboring proteins in their native environment.
Crosslinking mass spectrometry (XL-MS) to capture and identify transient interactions.
Bioluminescence resonance energy transfer (BRET) or fluorescence resonance energy transfer (FRET) for monitoring interactions in living cells.
These complementary approaches can provide a comprehensive interaction network, though each has specific strengths and limitations for membrane protein studies .
To investigate the physiological role of Mvan_3406 in Mycobacterium vanbaalenii:
Generate knockout or conditional mutants using CRISPR-Cas9 or homologous recombination, then assess phenotypic changes under various growth conditions.
Perform RNA-seq and proteomic analyses comparing wild-type and Mvan_3406-deficient strains to identify affected pathways.
Conduct metabolomic profiling to detect metabolic alterations associated with Mvan_3406 manipulation.
Monitor expression levels of Mvan_3406 under various environmental conditions (temperature, pH, nutrient availability) to identify regulatory patterns.
Perform complementation studies with wild-type and mutant versions of Mvan_3406 to confirm phenotype-genotype relationships.
This multi-faceted approach can provide insights into the protein's function within the broader context of mycobacterial biology.
For structural characterization of membrane proteins like Mvan_3406:
Optimize detergent screening to identify conditions that maintain native conformation while facilitating structural studies.
Consider lipid nanodiscs or amphipols as alternatives to detergents for maintaining a more native-like environment.
For X-ray crystallography, implement crystallization techniques specifically developed for membrane proteins, such as lipidic cubic phase crystallization.
Employ cryo-electron microscopy, which has revolutionized membrane protein structural biology by eliminating the need for crystallization.
Use integrative structural biology approaches that combine multiple experimental techniques (X-ray, NMR, cryo-EM, SAXS) with computational modeling to overcome the limitations of any single method.
These approaches address the unique challenges of membrane protein structural biology while maximizing the likelihood of obtaining informative structural data .
| Property | Specification | Additional Notes |
|---|---|---|
| Source Organism | Mycobacterium vanbaalenii | Environmental mycobacterium |
| Expression Host | E. coli | Prokaryotic expression system |
| Protein Tag | His-tag | Facilitates purification via IMAC |
| Protein Length | 108 amino acids (Full length) | Relatively small membrane protein |
| Protein Family | UPF0060 | Uncharacterized Protein Family |
| Theoretical MW | Not specified in available data | Can be calculated from amino acid sequence |
| Purification Method | Immobilized metal affinity chromatography | Utilizing His-tag |
This table summarizes the key properties of recombinant Mvan_3406 based on available research data .
| Control Type | Purpose | Implementation |
|---|---|---|
| Negative Control | Account for background/non-specific effects | Empty vector or irrelevant membrane protein expressed under identical conditions |
| Positive Control | Validate assay functionality | Well-characterized membrane protein with known activity in the assay system |
| Vehicle Control | Account for effects of buffers/solvents | Samples containing all components except Mvan_3406 |
| Concentration Controls | Establish dose-response relationships | Series of defined Mvan_3406 concentrations |
| Time Course Controls | Determine temporal dynamics | Measurements at multiple time points |
| Denatured Protein Control | Distinguish specific from non-specific effects | Heat-denatured or chemically inactivated Mvan_3406 |
Implementing these controls ensures experimental rigor and facilitates interpretation of results in functional studies .
| Design Aspect | Within-Subject Design | Between-Subject Design |
|---|---|---|
| Statistical Power | Higher for same sample size | Lower for same sample size |
| Control of Individual Variability | High - each subject serves as own control | Low - relies on randomization |
| Required Sample Size | Smaller | Larger |
| Risk of Carryover Effects | High - potential sequence effects | None |
| Analysis Complexity | Higher - must account for correlation structure | Lower - observations are independent |
| Appropriate Statistical Tests | Repeated measures ANOVA, mixed models | Standard ANOVA, t-tests |
| Application in Mvan_3406 Research | Comparing protein activity across conditions | Comparing wild-type vs. mutant proteins |
Understanding these design tradeoffs helps researchers select the most appropriate experimental approach for their specific research questions .
When encountering low expression yields of Mvan_3406, researchers should systematically:
Optimize codon usage for the expression host by synthesizing a codon-optimized gene.
Test multiple expression vectors with different promoters, fusion tags, and signal sequences.
Screen various E. coli strains specifically developed for membrane protein expression (C41, C43, Lemo21).
Evaluate expression conditions including temperature (typically lowering to 18-25°C), inducer concentration, and duration.
Consider autoinduction media which can provide more consistent results than IPTG induction for membrane proteins.
Explore eukaryotic expression systems (yeast, insect cells) if E. coli expression remains problematic.
This systematic optimization approach addresses the common challenges associated with membrane protein expression .
To address protein aggregation during Mvan_3406 purification:
Screen multiple detergents and detergent concentrations to identify optimal solubilization conditions.
Include glycerol (5-10%) in purification buffers to stabilize the protein.
Add specific lipids that might be required for protein stability.
Optimize buffer composition including pH, salt concentration, and reducing agents.
Consider on-column refolding approaches if the protein consistently aggregates during purification.
Implement size exclusion chromatography as a final purification step to separate aggregated from properly folded protein.
These approaches can significantly improve the proportion of functional, non-aggregated protein obtained during purification .
To confirm that purified Mvan_3406 retains its native conformation and functional properties:
Perform circular dichroism (CD) spectroscopy to assess secondary structure content.
Use fluorescence spectroscopy to evaluate tertiary structure integrity.
Conduct thermal stability assays (differential scanning fluorimetry) to compare stability across purification conditions.
Perform size exclusion chromatography coupled with multi-angle light scattering (SEC-MALS) to confirm the oligomeric state.
Develop functional assays based on predicted activities or interaction partners.
Assess membrane integration using liposome reconstitution followed by protease protection assays.
These complementary approaches provide a comprehensive assessment of protein integrity beyond simple purity measures.