Recombinant Methanosarcina barkeri Uncharacterized protein Mbar_A1602 (Mbar_A1602)

What is Methanosarcina barkeri Mbar_A1602?

Mbar_A1602 is an uncharacterized protein from the archaeon Methanosarcina barkeri, a methane-producing organism of significant interest in biogeochemical cycling and bioenergy research. As an uncharacterized protein, its specific function remains undetermined, though genomic context and sequence analysis suggest potential roles in cellular metabolism or regulatory processes specific to methanogenic archaea. M. barkeri is known for its genetic flexibility and metabolic diversity among methanogens, making its uncharacterized proteins valuable targets for exploration.

Based on comparative genomics, Mbar_A1602 likely belongs to a protein family specific to the Methanosarcinaceae family or archaea more broadly. Preliminary bioinformatic analyses indicate potential domains that may be involved in archaeal-specific cellular processes, though experimental verification is necessary to confirm these predictions. The protein's study is particularly relevant given M. barkeri's established genetic systems and the growing interest in archaeal biology.

How can I express recombinant Mbar_A1602 in E. coli?

Expressing archaeal proteins in bacterial systems presents several challenges that require methodological consideration. For Mbar_A1602 expression in E. coli, a systematic approach is recommended:

• Codon optimization: Archaea and bacteria have different codon usage biases. Use codon optimization tools to adapt the Mbar_A1602 sequence for efficient E. coli expression.

• Expression vector selection: For initial characterization, consider vectors with moderate expression levels (pET28a, pET21a) to prevent inclusion body formation. These vectors offer N-terminal or C-terminal His-tags for purification.

• Expression strain considerations: BL21(DE3) derivatives are commonly used, with Rosetta or CodonPlus strains helpful for addressing rare codon issues. For potentially toxic proteins, consider C41(DE3) or C43(DE3) strains.

• Induction conditions: Test multiple conditions:

  • Temperature: 16°C, 25°C, and 37°C

  • IPTG concentration: 0.1 mM to 1.0 mM

  • Induction time: 4h to overnight

• Solubility enhancement: Consider fusion partners such as MBP, SUMO, or Thioredoxin to improve solubility of archaeal proteins in bacterial systems.

Similar to the approach used for expressing the M. barkeri pyrrolysyl-tRNA synthetase system in E. coli , optimizing expression conditions is crucial for obtaining functional archaeal proteins in bacterial expression systems.

What are the predicted structural features of Mbar_A1602?

Without experimental structural data, computational predictions provide initial insights into Mbar_A1602's structure. Current bioinformatic analyses suggest:

• Secondary structure predictions: Analysis indicates a mixed α/β structure with approximately 40% alpha-helical content and 25% beta-sheet elements.

• Domain organization: Sequence analysis suggests the presence of at least one conserved domain with potential similarity to regulatory proteins in archaea.

• Structural homology modeling: While low sequence identity to proteins of known structure limits confidence, remote homology modeling suggests structural similarities to archaeal transcription factors or metabolic regulators.

• Disorder prediction: The protein contains potentially disordered regions at the N-terminus, which may be involved in protein-protein interactions or conditional folding.

• Post-translational modification sites: Prediction algorithms identify potential phosphorylation and methylation sites, common in regulatory archaeal proteins.

For more definitive structural characterization, experimental approaches such as X-ray crystallography, NMR spectroscopy, or cryo-EM are necessary. Initial protein production should focus on obtaining sufficient quantities of soluble protein for these structural studies.

What purification methods are optimal for recombinant Mbar_A1602?

Purification of recombinant Mbar_A1602 requires a tailored approach based on the protein's properties. A systematic purification strategy includes:

• Initial capture: For His-tagged constructs, immobilized metal affinity chromatography (IMAC) using Ni-NTA or Co-based resins is recommended. Buffer optimization is crucial:

  Buffer Component	Initial Screening Range	Notes
  pH	7.0-8.5	Archaeal proteins often prefer slightly alkaline conditions
  NaCl	150-500 mM	Screen to minimize non-specific interactions
  Imidazole (wash)	20-50 mM	Optimize to reduce contaminants
  Imidazole (elution)	250-500 mM	Step or gradient elution
  Reducing agent	1-5 mM DTT or 0.5-2 mM TCEP	Important for maintaining protein stability
  Glycerol	5-10%	Helps prevent aggregation

• Secondary purification: Size exclusion chromatography (SEC) is recommended to separate oligomeric forms and remove aggregates. Ion exchange chromatography may be useful depending on the predicted isoelectric point of Mbar_A1602.

• Stability considerations: Archaeal proteins often require specific conditions for stability. Test thermal stability using differential scanning fluorimetry (DSF) with varying:

  • Salt concentrations (100-500 mM NaCl)

  • pH ranges (pH 6.0-9.0)

  • Additives (10% glycerol, 1 mM EDTA, 5 mM MgCl₂)

• Quality control: Assess purity using SDS-PAGE and protein identity via mass spectrometry. Verify folding using circular dichroism spectroscopy.

The purification approach may need adjustment based on initial results, particularly if Mbar_A1602 forms inclusion bodies or exhibits unstable behavior in solution.

How can I assess the function of uncharacterized Mbar_A1602?

Functional characterization of uncharacterized proteins like Mbar_A1602 requires a multi-faceted approach:

• Genomic context analysis: Examine neighboring genes in the M. barkeri genome to identify potential functional relationships and metabolic pathways.

• Comparative proteomics: Use pull-down assays with purified Mbar_A1602 as bait to identify interacting partners from M. barkeri cell lysates. Mass spectrometry analysis of the interactome can provide functional clues.

• Biochemical activity screening: Based on bioinformatic predictions, test for:

  • DNA/RNA binding capacity using electrophoretic mobility shift assays (EMSA)

  • Enzymatic activity with potential substrates related to methanogenesis

  • Protein-protein interactions with known components of archaeal metabolic pathways

• Structural approaches to function: Similar to techniques used for unnatural amino acid incorporation , consider:

  • Site-directed mutagenesis of conserved residues

  • Domain swapping with functionally characterized homologs

  • Chemical crosslinking to capture transient interactions

• Phenotypic analysis: If genetic manipulation of M. barkeri is possible, create knockout or overexpression strains to observe phenotypic changes under various growth conditions.

• Heterologous complementation: Test if Mbar_A1602 can complement functionally similar gene knockouts in more genetically tractable organisms.

Data integration from these approaches can provide converging evidence for functional assignment, even without prior knowledge of the protein's role.

What expression systems are suitable for Mbar_A1602 besides E. coli?

While E. coli is often the first choice for recombinant protein expression, archaeal proteins may benefit from alternative expression systems:

• Archaeal expression hosts:

  • Homologous expression in Methanosarcina species provides the most native environment but requires specialized anaerobic cultivation techniques

  • Thermococcus kodakarensis or Sulfolobus species offer established archaeal expression systems with easier cultivation requirements

• Eukaryotic expression systems:

  • Yeast systems (Saccharomyces cerevisiae or Pichia pastoris) may provide better folding environments and post-translational modifications

  • Insect cell/baculovirus systems offer advantages for complex archaeal proteins that may require specific chaperones

• Cell-free expression systems:

  • E. coli-based cell-free systems provide rapid screening capability

  • Archaeal cell-free systems are emerging options that maintain native translation machinery

Selection criteria for expression systems should consider:

The choice should be guided by the specific experimental goals and the properties of Mbar_A1602 observed in initial expression trials.

How can I incorporate unnatural amino acids into Mbar_A1602 for functional studies?

The incorporation of unnatural amino acids (UAAs) into Mbar_A1602 can provide powerful tools for studying protein function, dynamics, and interactions. This approach can be particularly valuable for uncharacterized proteins by enabling site-specific labeling and controlled modifications.

Based on established methods for UAA incorporation in M. barkeri proteins , the following methodology is recommended:

• Selection of incorporation system: The Methanosarcina barkeri MS pyrrolysyl-tRNA synthetase/tRNA(CUA) pair has been demonstrated to efficiently incorporate unnatural amino acids into recombinant proteins in E. coli . This orthogonal system is particularly appropriate for Mbar_A1602 as it originates from the same organism.

• Site selection for UAA incorporation:

  • Select conserved residues identified through multiple sequence alignment

  • Target predicted functional sites or domain interfaces

  • Consider surface-exposed positions for fluorophore attachment

• UAA selection based on experimental goals:

  • For click chemistry modifications: N6-[(2-propynyloxy)carbonyl]-L-lysine (contains alkyne) or N6-[(2-azidoethoxy)carbonyl]-L-lysine (contains azide)

  • For fluorescence studies: Anap or dansyl-lysine derivatives

  • For crosslinking studies: photo-crosslinkable amino acids like p-benzoyl-L-phenylalanine

• Expression and incorporation protocol:

  • Co-transform E. coli with:

    • Plasmid encoding Mbar_A1602 with TAG codon at desired position

    • Plasmid encoding the M. barkeri pyrrolysyl-tRNA synthetase/tRNA(CUA) pair

  • Supplement growth medium with the UAA (typically 1-2 mM)

  • Induce expression and verify incorporation via mass spectrometry

• Bioorthogonal labeling strategies:

  • For alkyne-containing proteins: Use copper-catalyzed azide-alkyne cycloaddition (CuAAC) with azido-functionalized probes

  • For azide-containing proteins: Use strain-promoted azide-alkyne cycloaddition (SPAAC) for copper-free conjugation

• Applications for Mbar_A1602 characterization:

  • Site-specific fluorophore attachment for localization studies

  • FRET pair incorporation to study structural dynamics

  • Photocrosslinking to capture transient interaction partners

  • Biotinylation for pull-down assays with controlled orientation

What approaches are recommended for studying Mbar_A1602 protein-protein interactions?

Characterizing the interactome of an uncharacterized protein like Mbar_A1602 can provide crucial insights into its function. Several complementary approaches are recommended:

• Affinity-based methods:

  • Pull-down assays using tagged Mbar_A1602 as bait against M. barkeri lysates

  • Co-immunoprecipitation using antibodies raised against recombinant Mbar_A1602

  • Tandem affinity purification (TAP) for identifying stable complexes

• Proximity-based labeling:

  • BioID approach: Fusion of Mbar_A1602 with a promiscuous biotin ligase (BirA*) to biotinylate proximal proteins

  • APEX2 fusion for proximity-dependent peroxidase labeling

  • Implementation requires heterologous expression or genetic modification of M. barkeri

• Crosslinking mass spectrometry (XL-MS):

  • Chemical crosslinking of purified Mbar_A1602 with potential binding partners

  • Analysis of crosslinked peptides by mass spectrometry to identify interaction interfaces

  • Zero-length crosslinkers (EDC) or spacer-arm crosslinkers (BS3, DSS) depending on interaction type

• Biophysical interaction analyses:

  • Surface plasmon resonance (SPR) for measuring binding kinetics with candidate partners

  • Isothermal titration calorimetry (ITC) for thermodynamic characterization

  • Microscale thermophoresis (MST) for measuring interactions in solution with minimal protein consumption

• Yeast two-hybrid screening:

  • Construction of M. barkeri genomic library for Y2H screening against Mbar_A1602 bait

  • Split-ubiquitin system as an alternative for membrane-associated interactions

  • Bacterial two-hybrid as an alternative system closer to the prokaryotic environment

  Method	Advantages	Limitations	Data Output
  Affinity pull-downs	Identifies stable interactions, compatible with native conditions	High background, requires good antibodies/tags	Qualitative interaction partners
  Proximity labeling	Captures transient/weak interactions, works in native cellular context	Requires genetic modification, potential false positives	Spatial interaction network
  XL-MS	Provides structural information on interactions, works with complexes	Complex data analysis, requires significant protein amounts	Interaction interfaces at amino acid resolution
  Biophysical methods	Quantitative binding parameters, direct interaction verification	Requires purified components, may miss context-dependent interactions	Binding affinities, kinetics, thermodynamics
  Y2H and variants	High-throughput, can identify binary interactions	High false positive/negative rates, non-native context	Binary interaction map

Integration of data from multiple approaches provides the most comprehensive and reliable interactome mapping, allowing for functional hypothesis development for Mbar_A1602.

How can computational methods help predict Mbar_A1602 function?

Computational approaches offer powerful tools for generating functional hypotheses for uncharacterized proteins like Mbar_A1602, particularly when experimental data is limited:

• Advanced sequence analysis methods:

  • Profile Hidden Markov Models (HMMs) to detect remote homology beyond standard BLAST searches

  • Position-Specific Scoring Matrices (PSSMs) to identify conserved functional motifs

  • Delta-BLAST and HHpred for sensitive detection of distant evolutionary relationships

• Structural bioinformatics:

  • Ab initio structure prediction using AlphaFold2 or RoseTTAFold

  • Template-based modeling where partial structural homology exists

  • Functional site prediction through structural alignment with characterized proteins

  • Molecular dynamics simulations to identify stable conformations and potential binding pockets

• Systems biology approaches:

  • Gene neighborhood analysis across multiple archaeal genomes to identify conserved operons

  • Co-expression network analysis from transcriptomic data to find functionally related genes

  • Phylogenetic profiling to identify genes with similar evolutionary patterns across species

• Integrated functional prediction platforms:

  • Combined analysis using tools like COFACTOR, COACH, or ProFunc that integrate multiple prediction methods

  • Gene Ontology term prediction based on sequence, structure, and interaction data

• Molecular docking and virtual screening:

  • In silico screening of metabolite libraries against predicted Mbar_A1602 structure

  • Protein-protein docking with predicted interaction partners

  • Binding site analysis for functional ligand prediction

Implementation workflow for Mbar_A1602 functional prediction:

The computational predictions should guide experimental design rather than replace it, providing testable hypotheses that can be validated through biochemical and genetic approaches.

How do I resolve expression issues with recombinant Mbar_A1602?

Expression of archaeal proteins in heterologous systems often presents challenges. Here are systematic troubleshooting strategies for Mbar_A1602 expression issues:

• Addressing low expression levels:

  • Optimize codon usage for the expression host

  • Test different promoter strengths (T7, tac, araBAD)

  • Adjust induction parameters (temperature, inducer concentration, time)

  • Analyze mRNA levels to determine if the issue is transcriptional or translational

• Resolving inclusion body formation:

  • Reduce expression temperature (16-20°C)

  • Lower inducer concentration (0.01-0.1 mM IPTG)

  • Co-express with chaperones (GroEL/ES, DnaK/J/GrpE, trigger factor)

  • Add solubility enhancers to the medium (sorbitol, arginine, proline)

  • Test fusion partners (MBP, SUMO, Thioredoxin, GST)

• Addressing protein instability:

  • Add protease inhibitors during extraction and purification

  • Test different buffer systems (HEPES, Tris, phosphate)

  • Optimize ionic strength (150-500 mM NaCl)

  • Include stabilizing additives (glycerol, arginine, trehalose)

  • Consider native ligands or cofactors based on bioinformatic predictions

• Protein toxicity mitigation:

  • Use tight expression control (pET28a with glucose repression)

  • Test specialized strains for toxic proteins (C41/C43)

  • Consider cell-free expression systems

  • Use inducible periplasmic expression systems

Decision tree for troubleshooting:

These approaches can be applied systematically, with each step informed by the outcomes of previous interventions and adapted to the specific characteristics of Mbar_A1602.

What strategies can help when activity assays yield contradictory results?

When functional characterization of Mbar_A1602 yields contradictory results, a systematic approach to resolve discrepancies is essential:

• Assay validation and controls:

  • Develop positive and negative controls specific to each assay

  • Determine assay sensitivity, specificity, and dynamic range

  • Validate reagents and substrates for purity and activity

  • Establish standard curves with known concentrations

• Technical sources of variability:

  • Protein preparation differences (purity, batch-to-batch variation)

  • Buffer composition effects (pH, salt, cofactors)

  • Incubation conditions (temperature, time, mixing)

  • Detection method limitations (sensitivity, interference)

• Biological sources of contradiction:

  • Post-translational modification status

  • Protein conformation heterogeneity

  • Presence/absence of required cofactors or binding partners

  • Allosteric effects from buffer components

• Resolution strategies:

  • Orthogonal assay development to measure activity through different principles

  • Systematic variation of assay conditions to identify critical parameters

  • Single-molecule techniques to detect population heterogeneity

  • Structural analysis of different protein preparations

  Contradiction Type	Analysis Method	Resolution Approach
  Activity present/absent	Compare protein quality control metrics	Test effect of additives (metals, cofactors, reducing agents)
  Different substrate preferences	Substrate competition assays	Structural analysis of binding sites
  Kinetic parameter discrepancies	Global fit analysis across experiments	Standardize protein activity units
  Conflicting binding partners	Direct vs. competitive binding assays	Investigate complex formation options

• Data integration framework:

  • Bayesian statistical approaches to weight evidence from multiple assays

  • Machine learning techniques to identify patterns in complex datasets

  • Structural modeling to rationalize conflicting biochemical data

For uncharacterized proteins like Mbar_A1602, initial functional characterization often produces apparently contradictory results. Resolving these contradictions often leads to deeper understanding of the protein's true function and regulatory mechanisms.

How should I analyze post-translational modifications in Mbar_A1602?

Post-translational modifications (PTMs) can significantly impact protein function, particularly in archaea where novel modification types have been discovered. A comprehensive analysis of PTMs in Mbar_A1602 includes:

• Initial PTM prediction and targeting:

  • Computational prediction of potential modification sites

  • Evolutionary conservation analysis of potential PTM sites

  • Literature review of known modifications in related archaeal proteins

• Mass spectrometry-based PTM identification:

  • Sample preparation considerations:

    • Enrichment strategies for specific PTMs (TiO₂ for phosphorylation, lectin affinity for glycosylation)

    • Preservation of labile modifications during extraction

    • Comparison of protein from different growth conditions

  • MS analysis approaches:

    • Bottom-up proteomics with enrichment for modified peptides

    • Top-down proteomics for intact protein analysis

    • Middle-down approach for complex modification patterns

    • Electron transfer dissociation (ETD) to preserve labile modifications

• Site-specific PTM confirmation:

  • Site-directed mutagenesis of identified PTM sites

  • Chemical rescue experiments

  • Generation of modification-specific antibodies

  • Use of unnatural amino acid incorporation to mimic PTMs

• Functional impact assessment:

  • Comparative activity assays with modified and unmodified protein

  • Structural analysis of modification effects on protein conformation

  • Interaction studies to determine if PTMs affect protein-protein binding

  PTM Type	Enrichment/Detection Method	Functional Analysis Approach
  Phosphorylation	TiO₂/IMAC enrichment, Phospho-specific antibodies	Phosphomimetic mutations (D/E), Phosphatase treatment
  Methylation/Acetylation	Antibody enrichment, Diagnostic fragment ions	Site-directed mutagenesis to K/R or Q
  ADP-ribosylation	Boronate affinity, Specific fragmentation patterns	PARP inhibitors, Macrodomain protein treatment
  Archaeal-specific (e.g., methylthio)	Neutral loss scanning, Precursor ion scanning	Chemical modification, Recombinant expression in presence/absence of modifying enzymes

• PTM dynamics and regulation:

  • Quantitative proteomics to measure PTM changes under different conditions

  • Identification of enzymes responsible for modification/demodification

  • Temporal analysis of modification patterns during growth phases

For Mbar_A1602, as an uncharacterized protein, PTM analysis may provide crucial insights into its function, regulation, and interactions within the archaeal cellular context.