The Recombinant Methanocaldococcus jannaschii Putative ABC Transporter Permease Protein MJ0877 is a recombinant protein derived from the archaeon Methanocaldococcus jannaschii. This protein is part of the ABC transporter family, which plays a crucial role in transporting various substrates across cellular membranes using ATP hydrolysis for energy . The MJ0877 protein is specifically identified as a putative ABC transporter permease, suggesting its involvement in the transport of molecules across cell membranes.
The amino acid sequence of the MJ0877 protein is as follows: MDANLLGEKYAISVGVDIKSLRMWLIILSCVLTATVVAFTGPIAFVGITCPILARMICGT SKHIYVIPVTMLLGAVFLVVADILTRPGVLISSTNVLPLLCPLSIIGAPIAIIIYLKIRK MGI .
ABC transporters, including the MJ0877 protein, utilize the energy from ATP binding and hydrolysis to transport substrates across cell membranes. They consist of two main domains: the transmembrane domain (TMD) and the nucleotide-binding domain (NBD). The TMD is responsible for substrate recognition and transport, while the NBD binds ATP and drives the transport process through conformational changes .
The recombinant MJ0877 protein is expressed in E. coli and purified to a high purity level, making it suitable for various biochemical studies .
While specific applications of the MJ0877 protein are not widely documented, ABC transporters in general are crucial for understanding cellular transport mechanisms and have implications in fields such as biotechnology and medicine. For instance, ABC transporters are involved in drug resistance mechanisms in bacteria, making them targets for therapeutic interventions .
This protein is likely a component of a binding-protein-dependent transport system. Its function is probably the translocation of substrate across the membrane.
ABC transporters constitute one of the largest families of membrane proteins across various organisms, including archaea . In M. jannaschii, MJ0877 is part of a broader system of ABC transporters that are essential for survival in extreme environments.
Unlike many bacterial ABC transporters that have been extensively characterized, archaeal ABC transporters - particularly those from hyperthermophiles like M. jannaschii - remain less well understood. Research comparing MJ0877 with other archaeal ABC transporters reveals conserved structural features typical of the ABC transporter superfamily, including:
Membrane-spanning domains that form the translocation pathway
Nucleotide-binding domains that bind and hydrolyze ATP
Substrate-binding proteins that confer specificity
The evolutionary position of M. jannaschii as one of the most deeply rooted organisms in the archaeal domain makes its ABC transporters particularly valuable for understanding the evolution of membrane transport systems . Genome sequencing of M. jannaschii was a milestone event, being the first archaeal genome to be completely sequenced, which helped establish the three-domain classification of life (Bacteria, Archaea, and Eukarya) .
Successful expression of recombinant MJ0877 requires careful optimization of expression systems and conditions. Based on research protocols, the following methodological approach is recommended:
Expression System Selection:
E. coli expression systems are most commonly used due to their simplicity and high yield potential for MJ0877
Alternative expression hosts include yeast, baculovirus, or mammalian cell systems for specific experimental requirements
Expression Protocol:
Clone the MJ0877 gene (coding for amino acids 1-123) into an appropriate expression vector with a His-tag for purification purposes
Transform the construct into an E. coli strain optimized for protein expression (BL21, Rosetta, or similar)
Culture conditions:
Growth medium: LB or 2YT media supplemented with appropriate antibiotics
Induction: 0.5-1.0 mM IPTG at OD600 of 0.6-0.8
Post-induction: Continue culture for 4 hours at 37°C or overnight at lower temperatures (16-25°C)
Purification Strategy:
Cell lysis using mechanical disruption (sonication or cell disrupter)
Membrane fraction isolation through ultracentrifugation (100,000 g for 1 hour)
Solubilization of membrane proteins using appropriate detergents
Affinity chromatography using Ni-NTA or Streptactin XT columns (depending on tag)
Buffer optimization: Tris-based buffer with 50% glycerol at pH 8.0
The final product should have a purity greater than 90% as determined by SDS-PAGE, and lyophilization is recommended for long-term storage .
Establishing a genetic system for M. jannaschii has been challenging due to its extremophilic nature, but recent advances have made it possible. The following methodology has proven successful:
Growth and Culture Conditions:
Culture M. jannaschii in specialized medium with H₂ and CO₂ mixture (80:20, v/v) at 80°C
For liquid culture: Use sealed serum bottles with anaerobic conditions
For solid medium: Prepare plates with Gelrite® as a gelling agent (0.7% final concentration) with additional reducing agents (cysteine or titanium (III) citrate)
Transformation Protocol:
Prepare suicide vector construct containing:
Homologous regions flanking the target gene (MJ0877)
Desired genetic modifications (knockout, tag addition, etc.)
Selectable marker (e.g., mevinolin resistance)
Linearize the vector to promote double crossover recombination
Apply heat shock for transformation rather than chemical treatments like PEG or liposomes
Select transformants on solid medium containing appropriate antibiotics (mevinolin at 10-20 μM)
Verification Methods:
PCR-based analysis of chromosomal DNA to confirm successful genetic modification
Western blot analysis using appropriate antibodies if protein tagging was performed
Functional assays to verify phenotypic changes resulting from genetic manipulation
This approach has been successfully demonstrated for other proteins in M. jannaschii, providing a framework for genetic manipulation of MJ0877 .
Studies on ABC transporter permeases in various prokaryotes provide insights into potential roles of MJ0877 in membrane stability and antibiotic resistance. While direct evidence for MJ0877 is limited, comparative analysis with homologous proteins reveals:
Membrane Integrity Maintenance:
ABC transporter permeases like MJ0877 are crucial for maintaining membrane homeostasis. Research on related proteins demonstrates that:
These proteins often mediate the transport of lipids and other molecules essential for membrane structure
Mutation or deletion of ABC transporter permease genes frequently results in altered membrane composition and integrity
Changes in membrane properties can affect cellular responses to environmental stressors
Antibiotic Resistance Implications:
Studies on ABC transporter permease homologs reveal potential roles in antibiotic resistance mechanisms:
| Antibiotic Class | Sensitivity Change in Permease Mutants | Proposed Mechanism |
|---|---|---|
| Tetracyclines (doxycycline, tigecycline) | Increased sensitivity | Altered membrane permeability affecting drug influx/efflux |
| Polymyxins (colistin) | Increased sensitivity | Disrupted membrane stability affecting resistance to membrane-disrupting agents |
| Chloramphenicol | Increased sensitivity | Modified facilitated diffusion across membrane |
| Combined agents (EDTA + membrane-active compounds) | Dramatic synergistic sensitivity | Compromised membrane barrier function |
These findings suggest that MJ0877 may play a similar role in M. jannaschii, potentially affecting its resistance to membrane-active compounds in its extreme environment .
Descriptive Statistics:
For continuous variables (e.g., transport rates, binding affinities): Use mean and standard deviation for normally distributed data or median and interquartile range for non-normally distributed data
For categorical variables (e.g., substrate specificity, localization): Use proportions or percentages
Inferential Statistics Based on Research Question:
| Research Question Type | Recommended Statistical Test | Data Requirements |
|---|---|---|
| Comparing MJ0877 activity under different conditions | Paired t-test (paired samples) or independent t-test (unpaired samples) | Normally distributed continuous data |
| Comparing MJ0877 activity under different conditions (non-parametric) | Wilcoxon signed-rank test (paired) or Mann-Whitney U test (unpaired) | Non-normally distributed continuous data |
| Comparing multiple experimental conditions | One-way ANOVA with post-hoc tests | Normally distributed data with homogeneous variance |
| Comparing multiple experimental conditions (non-parametric) | Kruskal-Wallis H test | Non-normally distributed data |
| Correlation between variables (e.g., substrate concentration vs. transport rate) | Pearson correlation coefficient (linear) or Spearman rank correlation (non-linear) | Continuous variables |
| Predicting outcomes based on multiple variables | Multiple linear regression or logistic regression | Dependent on outcome variable type |
Special Considerations for MJ0877 Research:
Test for normality using Shapiro-Wilk or Kolmogorov-Smirnov tests before selecting parametric tests
Consider repeated measures designs when testing the same protein preparation under different conditions
Use appropriate post-hoc corrections (e.g., Bonferroni, Tukey HSD) for multiple comparisons
Consider mixed-effects models when combining data from multiple experimental batches
The ability of MJ0877 to function at the extreme temperatures (up to 80°C) encountered by M. jannaschii in deep-sea hydrothermal vents results from specific structural adaptations. Analysis of MJ0877 and other proteins from this hyperthermophilic archaeon reveals:
Primary Sequence Adaptations:
Increased proportion of charged amino acids (particularly glutamic acid and lysine) that form salt bridges
Higher frequency of hydrophobic residues in the protein core
Reduced frequency of thermolabile amino acids (asparagine, glutamine, cysteine, and methionine)
Structural Stabilization Mechanisms:
Extensive ionic interactions forming networks of salt bridges
Enhanced hydrophobic packing in the protein core
Shorter surface loops that are less susceptible to thermal fluctuations
Additional disulfide bonds for increased stability
The membrane-spanning regions of MJ0877 (amino acids 18-38, 46-66, and 76-96) contain predominantly hydrophobic residues that anchor the protein within the lipid bilayer, while the charged residues at position 6-10 (KYAIS) and 115-119 (KIRKM) likely participate in ionic interactions with other components of the ABC transporter complex .
Determining the substrate specificity of MJ0877 requires a systematic experimental approach combining biochemical, biophysical, and genetic techniques:
In Vitro Transport Assays:
Reconstitution of purified MJ0877 into liposomes with its associated ATP-binding protein
Preparation of radioactively labeled or fluorescently tagged potential substrates
Measurement of substrate uptake into liposomes under varying conditions
Competition assays with unlabeled substrates to determine binding specificity
Binding Studies:
Isothermal Titration Calorimetry (ITC) to measure binding affinities of potential substrates
Surface Plasmon Resonance (SPR) to analyze binding kinetics
Fluorescence-based binding assays using intrinsic tryptophan fluorescence or extrinsic fluorescent probes
Genetic Approaches:
Generation of MJ0877 knockout strains using the genetic system described in section 2.2
Complementation studies with wild-type and mutant versions of MJ0877
Growth analyses of knockout and complemented strains on various substrates
Suppressor mutation analysis to identify interacting genes/proteins
Structural Biology Techniques:
X-ray crystallography or cryo-electron microscopy of MJ0877 with bound substrates
Homology modeling combined with molecular dynamics simulations
Site-directed mutagenesis of predicted substrate-binding residues
EPR spectroscopy combined with site-directed spin labeling to probe conformational changes upon substrate binding
These approaches should be performed under conditions mimicking the native environment of M. jannaschii (high temperature, appropriate pH, and ionic strength) to obtain physiologically relevant results.
Investigating protein-protein interactions involving MJ0877 requires specialized techniques that can capture these interactions under conditions that maintain protein structure and function:
Co-immunoprecipitation with Tagged Variants:
Express MJ0877 with affinity tags (as described in sections 2.1 and 2.2)
Perform gentle solubilization of membrane complexes using mild detergents
Capture MJ0877 complexes using tag-specific antibodies or affinity resins
Identify interacting partners through mass spectrometry analysis
In Vivo Crosslinking:
Treat living M. jannaschii cells with membrane-permeable crosslinkers
Lyse cells and isolate crosslinked complexes
Analyze complexes by SDS-PAGE followed by Western blotting or mass spectrometry
Reverse crosslinking and confirm interactions through secondary methods
Förster Resonance Energy Transfer (FRET):
Generate fusion proteins of MJ0877 and potential partners with appropriate fluorophores
Express the fusion proteins in M. jannaschii or a suitable model system
Measure energy transfer between fluorophores as an indication of protein proximity
Analyze FRET efficiency under different conditions (substrate availability, ATP concentration)
Split-protein Complementation Assays:
Split a reporter protein (e.g., luciferase) into two non-functional fragments
Fuse these fragments to MJ0877 and potential interaction partners
Co-express the fusion proteins in an appropriate host
Measure reporter activity as an indication of protein-protein interaction
These approaches can help map the complete interaction network of MJ0877 within the ABC transporter complex and identify regulatory proteins that modulate its activity .
An integrated computational and experimental approach provides the most comprehensive understanding of MJ0877 function. The following workflow demonstrates how these approaches can complement each other:
Computational Analysis Pipeline:
Sequence Analysis:
Multiple sequence alignment with homologous proteins
Identification of conserved motifs and functional residues
Phylogenetic analysis to trace evolutionary relationships
Structural Prediction:
Homology modeling based on crystal structures of related ABC transporter permeases
Molecular dynamics simulations at high temperatures to mimic native conditions
Docking studies with potential substrates and interacting proteins
Systems Biology Approaches:
Network analysis to identify functional associations
Gene co-expression analysis using transcriptomic data
Metabolic modeling to predict the impact of MJ0877 on cellular metabolism
Integration with Experimental Data:
Use computational predictions to guide experimental design:
Target specific residues for mutagenesis based on structural models
Select potential substrates for transport assays based on docking results
Identify potential interacting partners for experimental validation
Refine computational models with experimental data:
Update structural models based on crosslinking constraints
Refine substrate specificity predictions based on transport assay results
Adjust network models based on protein-protein interaction data
Iterative improvement cycle:
Generate new hypotheses based on integrated data
Design targeted experiments to test specific aspects of these hypotheses
Incorporate new experimental results into refined computational models
This integrated approach has successfully elucidated the function of several ABC transporters and can be effectively applied to understand MJ0877's role in M. jannaschii .
Working with membrane proteins like MJ0877 presents several challenges that researchers should anticipate and address:
Problem: Membrane proteins often express poorly in heterologous systems
Solutions:
Optimize codon usage for the expression host
Use lower growth temperatures (16-25°C) during expression
Test different expression hosts (C41/C43 E. coli strains designed for membrane proteins)
Consider cell-free expression systems specifically optimized for membrane proteins
Use autoinduction media instead of IPTG induction
Problem: Hyperthermophilic proteins may misfold at mesophilic temperatures
Solutions:
Express at elevated temperatures if the host can tolerate it
Include molecular chaperones as co-expression partners
Use fusion tags that enhance solubility (SUMO, MBP, etc.)
Optimize buffer conditions to stabilize the native conformation
Add stabilizing agents like glycerol, specific ions, or substrate analogs
Problem: Incomplete solubilization from membranes
Solutions:
Screen multiple detergents (DDM, LMNG, CHAPS) for optimal extraction
Optimize detergent:protein ratio
Test different solubilization temperatures and times
Consider detergent mixtures or newer amphipathic polymers (SMALPs)
Use sequential extraction with increasing detergent concentrations
Problem: Functional activity diminishes during purification
Solutions:
When faced with inconsistent results in MJ0877 research, systematic troubleshooting and robust experimental design are essential:
Source Analysis and Validation:
Verify protein identity and integrity:
Confirm protein sequence by mass spectrometry
Check for degradation using SDS-PAGE and Western blotting
Verify proper folding using circular dichroism or other spectroscopic methods
Assess protein activity:
Develop reliable activity assays with appropriate controls
Determine batch-to-batch variation in specific activity
Standardize protein:lipid:detergent ratios for consistent measurements
Experimental Design Considerations:
Control environmental variables:
Temperature fluctuations (especially critical for thermophilic proteins)
pH stability throughout the experiment
Buffer composition and ionic strength
Presence of contaminating ATPases or phosphatases
Standardize data collection:
Use standardized protocols with detailed methodology documentation
Implement appropriate data collection methods as outlined in section 2.3
Ensure consistent time points and measurement parameters
Include internal standards and reference controls in each experiment
Statistical Approaches for Handling Inconsistent Data:
Identify and handle outliers appropriately:
Use statistical tests to identify outliers (Grubbs' test, Dixon's Q test)
Consider whether outliers represent true biological variation or technical errors
Report all data transparently, including outliers
Apply appropriate statistical methods:
Implement meta-analytical approaches:
Combine data from multiple experiments using formal meta-analysis
Weight results based on sample size and variance
Test for heterogeneity across experiments to identify sources of inconsistency