Recombinant Photobacterium profundum Anaerobic glycerol-3-phosphate dehydrogenase subunit B (glpB)

What is Photobacterium profundum and why is it significant for high-pressure research?

Photobacterium profundum is a Gram-negative bacterium originally isolated from the Sulu Sea. It has significant importance in high-pressure research because it's a piezophilic (pressure-loving) organism that grows optimally at 28 MPa and 15°C, while also being capable of growth at atmospheric pressure . This versatility makes it an ideal model organism for studying adaptations to high hydrostatic pressure environments.

The ability of P. profundum to grow across a wide pressure range allows for both easy genetic manipulation and culture under standard laboratory conditions, while still providing insights into deep-sea adaptations . The strain SS9 is particularly well-studied as a model piezophile, with its genome consisting of two chromosomes and an 80 kb plasmid, which has been fully sequenced to facilitate genetic and molecular studies .

P. profundum has revealed numerous pressure-adaptive mechanisms, including modifications to membrane composition, protein structure, and metabolic pathways that enable life in the deep sea, making it invaluable for understanding the fundamental biological principles of life under extreme pressure conditions .

What is the anaerobic glycerol-3-phosphate dehydrogenase complex and what role does the glpB subunit play?

The anaerobic glycerol-3-phosphate dehydrogenase is a respiratory enzyme complex composed of three subunits (GlpA, GlpB, and GlpC) that catalyzes the oxidation of glycerol-3-phosphate to dihydroxyacetone phosphate under anaerobic conditions . This reaction is crucial for anaerobic respiration using alternative electron acceptors such as fumarate.

The specific composition of the complex is:

The GlpB subunit (encoded by the glpB gene) is 419 amino acids in length and contains iron-sulfur clusters that participate in electron transfer during the catalytic process . While GlpA contains the FAD cofactor necessary for the initial electron transfer from glycerol-3-phosphate, GlpB serves as an intermediate electron carrier, transferring electrons through its iron-sulfur clusters to the membrane-bound GlpC subunit, which then passes electrons to the electron transport chain .

This complex is particularly important for P. profundum as it allows for energy generation under the anaerobic conditions often found in deep-sea environments, contributing to the organism's ability to thrive under high pressure .

How does glpB expression differ between high-pressure and atmospheric-pressure conditions?

The expression of glpB, as part of the anaerobic glycerol-3-phosphate dehydrogenase complex, shows differential regulation depending on pressure conditions in Photobacterium profundum. Based on proteomic analyses comparing growth at atmospheric pressure (0.1 MPa) versus high pressure (28 MPa), proteins involved in key metabolic pathways display significant expression differences .

The expression of glpB is likely regulated by the transcription factor Fnr (Fumarate and Nitrate Reduction), which responds to anaerobic conditions . At high pressure, where oxygen solubility decreases and anaerobic conditions may predominate, Fnr-regulated genes including the glpABC operon would be expected to show increased expression, although direct experimental confirmation in P. profundum would require targeted studies .

Furthermore, the ratio of aerobic to anaerobic glycerol-3-phosphate dehydrogenases is known to shift depending on the available terminal electron acceptors, with the anaerobic form (including glpB) likely being more highly expressed under high pressure conditions where fumarate may serve as a primary electron acceptor .

How do the kinetic properties of recombinant P. profundum glpB differ when expressed in heterologous systems under varying pressure conditions?

The kinetic properties of recombinant P. profundum glpB when expressed in heterologous systems would likely show pressure-dependent variations that reflect its adaptation to its native environment. Though specific kinetic studies on recombinant glpB are not detailed in the provided search results, a methodological approach to this question would involve:

• Expression System Selection:

  • E. coli-based expression systems would be convenient but may not properly fold a pressure-adapted protein

  • Expression in a moderate piezophile might better preserve native properties

  • Cell-free protein synthesis under pressure could provide an alternative approach

• Pressure-Dependent Kinetic Parameters:

  Parameter	Expected Trend with Increasing Pressure	Methodological Approach
  Km for glycerol-3-phosphate	Likely optimized at 28 MPa	High-pressure stopped-flow spectroscopy
  kcat	May show maximum at pressures matching native environment	Activity assays in pressure vessels
  Protein stability	Enhanced stability at high pressure compared to mesophilic homologs	Fluorescence or CD spectroscopy under pressure
  Electron transfer rates	Potentially pressure-optimized	Time-resolved spectroscopy

• Functional Assembly Assessment:
  The proper assembly of the GlpABC complex when expressing recombinant glpB would need to be verified, particularly when co-expressed with either native P. profundum glpA and glpC or with homologs from the expression host. Blue native PAGE or size exclusion chromatography under varying pressure conditions could evaluate complex formation.

• Pressure-Induced Conformational Changes:
  High-pressure NMR or SAXS studies on the purified recombinant protein could reveal pressure-induced conformational changes that might explain kinetic differences observed.

It should be noted that recombinant expression might not perfectly replicate the native environment of P. profundum. The cytoplasmic composition, including ion concentrations and molecular crowding agents, differs between piezophilic and non-piezophilic organisms and may affect protein function independently of pressure effects .

What are the evolutionary implications of horizontal gene transfer in the acquisition of pressure-adapted glpB in different Photobacterium strains?

The evolutionary acquisition of pressure-adapted glpB in Photobacterium strains likely involves horizontal gene transfer (HGT), which has significant implications for our understanding of deep-sea adaptation mechanisms. The search results indicate that genome plasticity between different bathytypes (depth-adapted ecotypes) of P. profundum contains signatures of HGT, suggesting this as a mechanism for rapid adaptation to different depth environments .

Key evolutionary considerations include:

• Selective Pressures Across Depth Gradients:
  The ocean represents a continuous gradient of increasing pressure with depth, creating distinct selective environments that favor different variants of metabolic enzymes like glpB. Comparative genomic analyses between strains isolated from different depths reveal genetic features specific to each strain that confer abilities to cope with depth-specific environmental stresses .

• Mosaic Nature of Adaptation:
  Rather than a single gene determining the environmental niche of each strain, multiple genetic features collectively contribute to depth adaptation. The glpABC operon may represent one component of a larger adaptive package that has been horizontally transferred between strains or acquired from other deep-sea bacteria .

• Potential Sources of Pressure-Adapted Genes:

  Potential HGT Source	Evidence	Evolutionary Significance
  Other Photobacterium species	Genomic islands with divergent GC content	Adaptation within genus across depth gradients
  Unrelated piezophilic bacteria	Genes with phylogenetic incongruence	Convergent evolution of pressure adaptation
  Mobile genetic elements	Association with insertion sequences or transposons	Mechanism for rapid adaptation

• Rapid Bathytype Conversion:
  The search results indicate the feasibility of "bathytype conversion," suggesting that the acquisition of specific genetic elements can rapidly convert a shallow-water strain to one capable of surviving at depth . If the glpABC operon is among these transferable elements, it would suggest that metabolic adaptation through acquisition of pressure-adapted enzymes is a key step in colonizing new depth niches.

• Maintenance of Genetic Diversity:
  The existence of distinct bathytypes within Photobacterium suggests that despite the potential for HGT, selective pressures maintain genetic diversity across the depth gradient, with each variant optimized for its particular depth niche .

Future research examining the molecular signatures of selection in glpB across multiple strains isolated from different depths could provide more specific evidence for the role of HGT in the evolution of pressure-adapted glycerol-3-phosphate metabolism.

What are the optimal conditions for expressing recombinant P. profundum glpB in E. coli expression systems?

Expressing recombinant P. profundum glpB in E. coli requires careful optimization to ensure proper folding and functionality of this pressure-adapted protein. While the search results don't provide specific protocols for glpB expression, a methodological approach based on general principles and the available information about P. profundum can be outlined:

Optimized Expression Protocol:

• Vector Selection and Construct Design:

  • Use pET-based vectors with T7 promoter for high-level expression

  • Include a C-terminal His-tag to avoid interfering with N-terminal folding

  • Consider including the complete glpABC operon for proper complex assembly

  • Codon optimization may not be necessary as both organisms are gamma-proteobacteria

• Expression Strain Selection:

  E. coli Strain	Advantages	Considerations
  BL21(DE3)	High expression levels	May form inclusion bodies
  Rosetta(DE3)	Supplies rare codons	Useful if codon usage differs
  ArcticExpress	Low-temperature expression	Helpful for proper folding
  SHuffle	Enhanced disulfide bond formation	Beneficial if disulfide bonds present

• Culture Conditions:

  • Growth temperature: 15-17°C (matching P. profundum's optimal temperature)

  • Medium: Marine broth supplemented with glucose and HEPES buffer (pH 7.5)

  • Induction: Low IPTG concentration (0.1-0.2 mM) to prevent inclusion body formation

  • Post-induction: Extended expression time (24-48 hours) at low temperature

• Pressure Considerations:

  • Standard E. coli expression occurs at atmospheric pressure

  • For functional studies, consider using pressure vessels for post-expression assays

  • For specialized studies, pressure-resistant E. coli strains might be considered

• Solubility Enhancement Strategies:

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

  • Fusion with solubility tags (MBP, SUMO)

  • Addition of osmolytes that may mimic high-pressure environments

• Purification Approach:

  • Cell lysis under anaerobic conditions to preserve iron-sulfur clusters

  • Immobilized metal affinity chromatography (IMAC) under reducing conditions

  • Size exclusion chromatography to verify complex formation if co-expressing with glpA and glpC

  • All buffers should contain glycerol and reducing agents to stabilize the protein

• Functional Verification:

  • Enzymatic activity assays under anaerobic conditions

  • Spectroscopic analysis to confirm iron-sulfur cluster incorporation

When expressing proteins from piezophilic organisms, it's important to recognize that the recombinant protein may not fully replicate the native properties without the high-pressure environment. For detailed functional studies, the purified protein should be analyzed under varying pressure conditions using specialized equipment .

What techniques are most effective for assessing the activity of recombinant glpB in vitro under high-pressure conditions?

Assessing the activity of recombinant glpB under high-pressure conditions requires specialized techniques that maintain anaerobic conditions while allowing precise control of hydrostatic pressure. While specific methods for glpB are not detailed in the search results, a comprehensive methodological approach can be outlined:

High-Pressure Enzymatic Activity Assessment:

• Specialized Equipment Requirements:

  • High-pressure optical cells with sapphire windows

  • Pressure intensifiers with precise control systems

  • Spectrophotometric or fluorometric detection systems compatible with pressure vessels

  • Anaerobic chambers for sample preparation

• Activity Assay Methodologies:

  Technique	Principle	Pressure Range	Advantages
  Stopped-flow spectroscopy	Rapid mixing followed by absorbance monitoring	Up to 200 MPa	Real-time kinetics
  High-pressure cuvettes	Static measurements in pressure-resistant cells	Up to 600 MPa	Simple implementation
  Quench-flow systems	Reaction termination after pressure exposure	Up to 400 MPa	Time-resolved measurements
  Microfluidic devices	Miniaturized reaction chambers	Up to 100 MPa	Minimal sample requirements

• Reaction Monitoring Approaches:

  • Direct monitoring: Track NAD+/NADH absorbance changes at 340 nm

  • Coupled assays: Link glycerol-3-phosphate oxidation to secondary reactions

  • Artificial electron acceptors: Use dyes like dichlorophenolindophenol (DCPIP)

  • Product quantification: Measure dihydroxyacetone phosphate formation

• Pressure Adaptation Assessment:

  • Pressure-dependent kinetic parameters (Km, Vmax, kcat)

  • Pressure stability profiles (activity retention after pressure exposure)

  • Comparative analysis with non-piezophilic homologs (e.g., from E. coli)

  • Pressure-dependent substrate specificity changes

• Practical Considerations:

  • Buffer systems should be insensitive to pressure-induced pH changes

  • Temperature control is critical as pressure increases generate heat

  • Protein concentration may need adjustment as pressure can affect protein-protein interactions

  • Control experiments with pressure-sensitive enzymes should be included

• Complex Assembly Analysis:
  For full functional characterization, the GlpABC complex should be reconstituted:

  • Co-purification of all three subunits

  • Verification of complex integrity under pressure (native PAGE after pressure treatment)

  • Membrane reconstitution for more native-like conditions

• Advanced Spectroscopic Techniques:

  • High-pressure EPR for iron-sulfur cluster analysis

  • FTIR spectroscopy to monitor pressure-induced conformational changes

  • Resonance Raman spectroscopy for active site coordination assessment

When working with anaerobic enzymes like glpB, all solutions must be thoroughly degassed and procedures performed under strict anaerobic conditions, typically in an anaerobic chamber with oxygen scavengers present in all buffers . Additionally, the iron-sulfur clusters in glpB are oxygen-sensitive and require reducing agents like dithiothreitol or dithionite in all buffers to maintain their integrity.

How can site-directed mutagenesis be used to identify pressure-adaptive residues in P. profundum glpB?

Site-directed mutagenesis represents a powerful approach to identify specific residues in P. profundum glpB that contribute to pressure adaptation. Based on comparative genomics between piezophilic and non-piezophilic strains, a systematic mutagenesis strategy can be developed to understand the molecular basis of pressure adaptation .

Methodological Approach for Identifying Pressure-Adaptive Residues:

• Target Residue Identification:

  • Comparative sequence analysis between SS9 (piezophilic) and 3TCK (non-piezophilic) glpB

  • Focus on residues under positive selection between depth-adapted strains

  • Prioritize substitutions in the following regions:

    • Iron-sulfur cluster coordination sites

    • Subunit interaction interfaces

    • Regions with altered flexibility/rigidity

    • Surface-exposed charged residues

• Mutation Design Strategy:

  Mutation Type	Purpose	Examples
  Conservative substitutions	Test specific physicochemical properties	V→I, D→E, K→R
  Non-conservative substitutions	Dramatic alteration of properties	G→P, D→K, F→A
  Reciprocal substitutions	Swap residues between piezophilic and non-piezophilic	SS9→3TCK and vice versa
  Chimeric constructs	Swap entire domains between strains	Replace Fe-S binding domain

• Mutagenesis Protocol:

  • QuikChange or Q5 site-directed mutagenesis for single substitutions

  • Gibson Assembly or Golden Gate cloning for multiple mutations or chimeras

  • Verification by sequencing before expression

  • Expression in E. coli under conditions optimized as described in question 4.1

• Functional Characterization:

  • Pressure-dependent enzyme kinetics (Km, kcat, substrate specificity)

  • Pressure stability profiles (activity retention after pressure exposure)

  • Thermal stability analysis (DSC or thermal shift assays)

  • Structural analysis (if possible, using high-pressure X-ray crystallography)

• Complementation Studies:

  • Generate glpB knockout in P. profundum SS9

  • Complement with mutant variants

  • Test growth under various pressure conditions

  • Measure glycerol-3-phosphate dehydrogenase activity in cell extracts

• Comprehensive Mutational Analysis:

  • Alanine scanning of critical regions

  • Saturation mutagenesis of key residues

  • Creation of pressure-adapted variants in non-piezophilic homologs

• Advanced Structural Analysis:

  • Molecular dynamics simulations of wild-type and mutant proteins under pressure

  • Hydrogen-deuterium exchange mass spectrometry to assess conformational changes

  • NMR studies of dynamics under varying pressure conditions

A systematic approach would begin with identifying residues unique to piezophilic strains, followed by creating reciprocal mutations (swapping residues between piezophilic and non-piezophilic variants). The most informative approach would likely involve creating chimeric proteins where domains from the piezophilic glpB are swapped with corresponding regions from non-piezophilic homologs, allowing identification of pressure-adaptive modules within the protein .

How can researchers distinguish between pressure-specific and general stress responses when analyzing differential expression of glpB?

Distinguishing pressure-specific from general stress responses when analyzing glpB expression requires careful experimental design and data analysis. Based on the proteomic studies of P. profundum grown under different pressure conditions , a comprehensive approach can be outlined:

Methodological Framework for Response Differentiation:

• Experimental Design Considerations:

  • Multi-factorial design including:

    • Pressure variation (0.1 MPa, 10 MPa, 28 MPa, 50 MPa)

    • Temperature variation (4°C, 15°C, 25°C)

    • Nutrient limitation stresses

    • Oxidative stress conditions

  • Time-course experiments to distinguish immediate vs. adaptive responses

  • Appropriate controls with mesophilic bacteria (e.g., E. coli) for comparison

• Expression Analysis Approaches:

  Technique	Application	Resolution	Advantages
  qRT-PCR	Targeted gene expression	Single gene	High sensitivity
  RNA-Seq	Transcriptome-wide analysis	Genome-wide	Contextual information
  Proteomics	Protein abundance	Proteome-wide	Post-transcriptional insights
  Ribosome profiling	Translation rates	Translatome	Translation efficiency

• Statistical Analysis Framework:

  • Principal Component Analysis to separate pressure effects from other stresses

  • Two-way ANOVA to identify interaction effects between pressure and other variables

  • Regression models to identify pressure-response thresholds

  • Bayesian network analysis to identify causal relationships in stress response networks

• Response Classification Matrix:

  Response Pattern	Interpretation	Example Signature
  Pressure-specific	Responds only to pressure changes	Expression changes at high pressure regardless of other conditions
  General stress	Responds to multiple stressors	Similar response to pressure, temperature, oxidative stress
  Pressure-enhanced	General response amplified by pressure	Low expression under other stresses, high under pressure
  Pressure-repressed	General response inhibited by pressure	High expression under other stresses, low under pressure

• Regulatory Network Analysis:

  • ChIP-seq to identify transcription factor binding (e.g., Fnr) under different conditions

  • Promoter analysis to identify pressure-responsive elements

  • Correlation networks to identify co-regulated genes

  • Comparison with known stress regulons (heat shock, cold shock, oxidative stress)

• Comparative Genomics Integration:

  • Compare expression patterns between piezophilic and non-piezophilic strains

  • Identify pressure-specific regulatory elements conserved in piezophiles

  • Analyze patterns across multiple species with different pressure optima

Research by Campanaro et al. demonstrated that while some genes respond specifically to pressure changes, others respond to the secondary effects of pressure, such as changes in membrane fluidity or protein stability . True pressure-specific responses would show consistent patterns across various experimental conditions where pressure is the only variable changed, while general stress responses would show similar expression changes under different types of stress.

For glpB specifically, comparison with other anaerobic metabolism genes and correlation with the expression of known pressure-responsive genes would help classify its response pattern .

What bioinformatic approaches can identify potential pressure-adaptive features in the glpB sequence across different Photobacterium strains?

Identifying pressure-adaptive features in glpB sequences across Photobacterium strains requires sophisticated bioinformatic approaches that integrate evolutionary analysis with structural predictions. Based on comparative genomics between different bathytypes of P. profundum , the following comprehensive bioinformatic framework can be developed:

Bioinformatic Analysis Pipeline:

• Sequence Collection and Alignment:

  • Gather glpB sequences from Photobacterium strains isolated from different depths

  • Include outgroups from related genera from various environments

  • Generate high-quality multiple sequence alignments using MAFFT or MUSCLE

  • Refine alignments focusing on functional domains and catalytic sites

• Evolutionary Analysis Approaches:

  Method	Application	Output	Significance
  dN/dS analysis	Detect positive selection	Sites under selection	Adaptive evolution signatures
  Ancestral sequence reconstruction	Trace evolutionary history	Historical mutations	Adaptation trajectory
  Phylogenetic profiling	Correlate with depth distribution	Clade-specific features	Convergent adaptations
  Branch-site models	Detect lineage-specific selection	Branch-specific adaptations	Bathytype-specific features

• Structural Bioinformatics:

  • Homology modeling of glpB from different depth isolates

  • Molecular dynamics simulations under various pressure conditions

  • Identification of pressure-sensitive regions (cavities, flexible loops)

  • Analysis of electrostatic surface potential differences

  • Prediction of pressure effects on protein-protein interfaces

  • Assessment of iron-sulfur cluster coordination environments

• Amino Acid Composition Analysis:

  • Comparative analysis of physicochemical properties:

    • Volume, flexibility, hydrophobicity

    • Charged vs. neutral residues

    • Hydrogen bonding potential

  • Statistical analysis of depth-correlated substitution patterns

  • Identification of co-evolving residue networks

• Machine Learning Approaches:

  • Feature extraction from sequences correlated with isolation depth

  • Supervised learning to identify pressure-adaptive signatures

  • Classification of sequences by predicted pressure optima

  • Importance ranking of position-specific features

• Functional Domain Analysis:

  Domain	Analysis Focus	Expected Adaptations
  Fe-S binding	Coordination geometry	Pressure-stable metal binding
  Subunit interfaces	Interface packing	Optimized interactions under pressure
  Catalytic residues	Active site geometry	Pressure-resistant catalysis
  Surface loops	Flexibility/rigidity	Compensatory mechanisms for compression

• Horizontal Gene Transfer Detection:

  • Genomic context analysis around glpB

  • Codon usage analysis to detect recent transfers

  • Phylogenetic incongruence testing

  • Identification of mobile genetic elements associated with glpB

The comparative genomic analysis between P. profundum strains SS9 (piezophilic) and 3TCK (non-piezophilic) has already revealed genomic features that correlate with environmental differences . Applying these approaches specifically to glpB would identify signatures of adaptation to different pressure regimes, particularly focusing on residues under positive selection that might confer pressure tolerance.

Machine learning approaches could be particularly powerful when applied to a larger dataset of sequences from various depths, potentially identifying subtle patterns of adaptation that might not be apparent from standard evolutionary analyses alone.

How can researchers integrate proteomic and genetic data to understand the role of glpB in high-pressure adaptation of P. profundum?

Integrating proteomic and genetic data provides a comprehensive understanding of glpB's role in high-pressure adaptation in P. profundum. Based on the proteomic studies comparing growth at atmospheric versus high pressure and comparative genomics between strains , a multi-omics integration strategy can be developed:

Multi-omics Integration Framework:

• Data Collection and Standardization:

  • Genomic data: Sequence variations in glpB between strains

  • Transcriptomic data: Expression levels under varying conditions

  • Proteomic data: Protein abundance and post-translational modifications

  • Metabolomic data: Glycerol-3-phosphate metabolism intermediates

  • Phenotypic data: Growth rates under different pressure/substrate conditions

• Multi-layered Data Analysis:

  Data Integration Approach	Application	Output	Insight Gained
  Correlation networks	Connect expression with phenotypes	Network modules	Functional associations
  Pathway enrichment	Contextualize within metabolism	Pathway regulation	Metabolic adaptation
  Protein-protein interaction mapping	Identify complex formation	Interaction networks	Pressure effects on complexes
  Genome-scale metabolic modeling	Predict metabolic flux	Flux distributions	System-level adaptations

• Differential Expression Analysis Framework:

  • Compare transcriptomics and proteomics to identify:

    • Transcriptionally vs. post-transcriptionally regulated changes

    • Protein stability differences under pressure

    • Translational efficiency variations

  • Correlation with metabolic flux changes:

    • Glycerol-3-phosphate utilization rates

    • Alternate carbon source preferences

    • Energy production efficiency

• Structure-Function Correlation:

  • Map sequence variations to:

    • Protein abundance changes

    • Post-translational modifications

    • Complex formation efficiency

    • Catalytic activity

  • Identify structure-based explanations for pressure adaptation

• Systems Biology Modeling:

  Model Type	Application	Advantage
  Metabolic control analysis	Determine flux control coefficients	Identify rate-limiting steps
  Kinetic modeling	Simulate pathway dynamics	Predict pressure responses
  Constraint-based modeling	Predict optimal flux distributions	System-level adaptation
  Agent-based modeling	Simulate cellular adaptation	Evolutionary trajectories

• Experimental Validation Strategy:

  • Generate targeted mutations based on integrated analysis

  • Measure effects on:

    • Protein expression and stability

    • Complex formation

    • Enzymatic activity under pressure

    • Growth phenotypes

  • Validate model predictions with metabolic flux analysis

The proteomic analysis of P. profundum SS9 has already revealed differential expression of proteins involved in key metabolic pathways under different pressure conditions . By integrating this with genetic data comparing piezophilic and non-piezophilic strains , researchers can identify specific adaptations in glpB that contribute to these metabolic shifts.

A particularly powerful approach would be to correlate structural variations in glpB between strains with pressure-dependent changes in glycerol-3-phosphate dehydrogenase activity, complex formation efficiency, and post-translational modifications. This would provide mechanistic insights into how specific sequence adaptations enable function under high pressure conditions.