Recombinant Photobacterium profundum Ribosomal RNA small subunit methyltransferase C (rsmC)

What is the function of rsmC in bacterial systems based on current research?

Based on studies in related bacteria like Erwinia carotovora, rsmC functions as a novel regulatory gene that activates RsmA production and represses extracellular enzyme production, rsmB transcription, and virulence . RsmA is an RNA-binding protein, while rsmB is a regulatory RNA (where Rsm stands for "regulator of secondary metabolites") . In E. carotovora knockout studies, an rsmC mutant showed higher basal levels of various enzymes (Pel, Peh, Cel, Prt) and harpin, as well as increased amounts of rsmB, pel-1, peh-1, celV, and hrpN transcripts, while levels of rsmA transcripts and RsmA protein were low .

In the context of P. profundum, we can hypothesize that rsmC may play a similar regulatory role, potentially with adaptations related to pressure response, as P. profundum strains show remarkable differences in their physiological responses to pressure based on their original isolation depths .

How do P. profundum strains from different ocean depths compare genetically?

P. profundum strains isolated from different depths exhibit significant genetic and physiological differences that reflect their adaptation to specific environmental conditions:

Both strains have unusually large intergenic regions that have been shown to be transcribed and differentially expressed as a function of pressure, suggesting an important physiological role in pressure adaptation .

What methylation mechanisms have been identified in bacterial systems that might inform rsmC research?

Recent research on bacterial methylation systems provides insights that could be relevant to rsmC studies:

• Protein lysine methylation has been identified as an important posttranslational modification in bacteria, with roles in immune evasion and adherence to host cells .

• In Acinetobacter sp. Tol 5, researchers identified widespread lysine methylation across multiple residues of an outer membrane protein (AtaA) and its dedicated methyltransferase (KmtA) .

• Bioinformatic analysis revealed that outer membrane protein lysine methyltransferase genes are widely distributed among gram-negative bacteria, suggesting that methylation is a ubiquitous regulatory mechanism in prokaryotes .

• While rsmC is an RNA methyltransferase rather than a protein methyltransferase, similar analytical approaches (particularly LC-MS methods) could be adapted for studying rsmC targets and activities .

• In Erwinia species, Southern blot data and PCR analysis demonstrated the presence of rsmC sequences across multiple subspecies, suggesting evolutionary conservation of this regulatory mechanism .

What culture conditions are optimal for studying P. profundum strains for rsmC expression analysis?

Based on published methodologies for P. profundum research, the following conditions are recommended:

For strain SS9 (deep-sea piezopsychrophilic):

• Media: 75% strength 2216 Marine Agar

• Temperature: Low temperature (4-15°C)

• Pressure: High hydrostatic pressure (optimal pressure should be determined experimentally)

• Antibiotics (if needed): kanamycin (200 μg/ml) or streptomycin (150 μg/ml)

• X-Gal: 40 μg/ml in N,N-dimethylformamide (for reporter constructs)

For strain 3TCK (shallow-water non-piezophilic):

• Media: 75% strength 2216 Marine Agar

• Temperature: Standard marine temperature (15-25°C)

• Pressure: Atmospheric pressure

• Antibiotics: Same as for SS9

For experimental comparisons, cultures should be grown to late exponential phase before harvesting for analysis . When studying pressure effects, appropriate pressure chambers with temperature control should be employed.

What cloning and expression strategies should be considered for recombinant P. profundum rsmC?

Based on successful approaches for P. profundum genes, the following strategy is recommended:

• Gene amplification: PCR amplify the rsmC gene with high-fidelity polymerase using primers with appropriate restriction sites (XhoI and KpnI have been successfully used for other P. profundum genes) .

• Vector selection: For P. profundum genes, vectors like pFL122 have been successfully used . Consider including affinity tags for purification.

• Transformation method: Introduction of plasmids into P. profundum is best achieved by tri-parental conjugations using helper E. coli strain pRK2073 .

• Verification: Confirm correct insertion by restriction digestion and sequencing.

• Deletion constructs: For functional studies, deletion constructs can be created by cutting with appropriate restriction enzymes and re-ligating, as demonstrated with the Δ22 deletion obtained by cutting pFL303 with EcoRI .

• Expression optimization: Consider using Response Surface Methodology (RSM) to optimize expression conditions by systematically varying parameters like temperature and induction time3.

How can researchers effectively measure rsmC methyltransferase activity?

A comprehensive approach to measuring rsmC methyltransferase activity should include:

• In vitro methylation assays:

  • Incubate purified recombinant rsmC with potential RNA substrates

  • Use radiolabeled S-adenosyl methionine (SAM) as methyl donor

  • Quantify incorporation of methyl groups by scintillation counting or autoradiography

• Mass spectrometry-based detection:

  • Apply label-free liquid chromatography-mass spectrometry (LC-MS) methods similar to those used for detecting protein methylation in Acinetobacter

  • Compare methylation patterns between wild-type and rsmC-deficient strains

  • Identify specific methylation sites on target RNAs

• Functional assays:

  • Create reporter systems based on known methyltransferase targets

  • Measure changes in reporter activity in response to rsmC expression

  • Use complementation assays with rsmC mutants to validate function

• Comparative analysis:

  • Compare activity of rsmC from piezophilic (SS9) and non-piezophilic (3TCK) strains

  • Test activity under different pressure and temperature conditions

  • Correlate activity with physiological outcomes

How can Response Surface Methodology (RSM) be applied to optimize recombinant rsmC expression and activity studies?

RSM provides a powerful statistical approach for optimizing multiple variables affecting rsmC expression and activity:

• Experimental design:

  • Start with a first-order design (e.g., factorial design) to screen important factors

  • Identify factors that significantly affect rsmC expression or activity

  • Follow the path of steepest ascent to approach the optimal region3

• Model development:

  • For initial screening, use linear models to identify direction of improvement

  • Once near the optimum, apply central composite design to fit quadratic models3

  • The mathematical form for the path of steepest ascent can be calculated (e.g., ΔTemperature = (1.9/4.6) × ΔTime)3

• Optimization process:

  • For example, if starting with time (30-40 min) and temperature (150-160°C), follow the steepest ascent direction

  • For each increment in time (e.g., 10 min), calculate the corresponding increment in temperature (e.g., 4°C)3

  • Continue experiments along this path until reaching maximum response

  • Design second-order experiments around the maximum to precisely locate the optimum3

• Visualization:

  • Use contour plots to visualize the response surface

  • The direction of steepest ascent is perpendicular to the contour lines3

  • In regions with significant curvature, quadratic models are necessary to identify the true optimum3

What approaches can identify potential targets of rsmC-mediated methylation in P. profundum?

A systematic approach to identifying rsmC methylation targets should include:

• Comparative transcriptomics:

  • Compare wild-type and rsmC knockout strains using RNA-seq

  • Identify differentially expressed genes that may be regulated by rsmC

  • Focus on genes involved in pressure adaptation or stress response

• Immunoprecipitation approaches:

  • Express tagged rsmC protein

  • Perform RNA immunoprecipitation to capture interacting RNAs

  • Sequence captured RNAs to identify binding sites and potential methylation targets

• Direct detection of methylation:

  • Apply LC-MS methods similar to those used for protein methylation detection

  • Analyze RNA samples from wild-type and rsmC-deficient strains

  • Look for methyl modifications on specific RNA nucleotides

• Predictive bioinformatics:

  • Analyze sequence and structural motifs in known methyltransferase targets

  • Scan the P. profundum transcriptome for similar motifs

  • Prioritize candidates for experimental validation

Based on knowledge of rsmC in E. carotovora, potential targets might include regulatory RNAs similar to rsmB or mRNAs encoding regulatory proteins similar to RsmA .

How might pressure affect rsmC expression and function in piezophilic versus non-piezophilic strains?

To investigate pressure effects on rsmC, researchers should consider:

• Comparative expression analysis:

  • Culture SS9 (piezophilic) and 3TCK (non-piezophilic) under varying pressure conditions

  • Measure rsmC mRNA and protein levels using qRT-PCR and Western blotting

  • Determine if pressure induces differential expression patterns between strains

• Functional genomics approaches:

  • Create rsmC promoter-reporter fusions

  • Monitor activity under different pressure conditions

  • Identify pressure-responsive regulatory elements

• Structural adaptation investigation:

  • Analyze differences in rsmC protein structure between SS9 and 3TCK

  • Determine if pressure-induced conformational changes affect activity

  • Identify amino acid substitutions that might contribute to pressure adaptation

• Physiological impact assessment:

  • Examine phenotypic changes in wild-type versus rsmC mutants under pressure

  • Measure growth rates, gene expression patterns, and metabolic activities

  • Correlate with the large intergenic regions that are differentially expressed under pressure

What molecular mechanisms could explain rsmC's role in bacterial adaptation to environmental conditions?

Based on known functions of methyltransferases and regulators of secondary metabolism:

• Regulatory network modulation:

  • In E. carotovora, rsmC activates RsmA production and represses rsmB transcription

  • This affects the expression of virulence factors and extracellular enzymes

  • In P. profundum, similar regulatory networks might control pressure-responsive genes

• RNA structure and function modification:

  • Methylation can alter RNA folding and stability

  • This might affect translation efficiency under different pressure conditions

  • Could be particularly important for adaptation to extreme environments

• Ribosome function modulation:

  • As a ribosomal RNA methyltransferase, rsmC likely modifies rRNA

  • Modifications could affect ribosome assembly or function

  • This might enhance translation under high pressure or low temperature

• Integration with stress response pathways:

  • Methylation might link environmental sensing with gene expression

  • Could coordinate responses to multiple stressors (pressure, temperature, nutrients)

  • May interact with the large intergenic regions that are differentially expressed under pressure

How can researchers distinguish between pressure-specific and general stress responses in methylation studies?

A systematic approach to differentiate pressure-specific from general stress responses includes:

• Multi-factor experimental design:

  • Test combinations of pressure, temperature, nutrient limitation, and other stressors

  • Use factorial designs to identify interaction effects

  • Apply RSM to model complex response surfaces3

• Comparative analysis across strains:

  • Compare responses in piezophilic (SS9) versus non-piezophilic (3TCK) strains

  • Include additional control strains adapted to other stressors but not pressure

  • Identify methylation patterns unique to pressure adaptation

• Time-course experiments:

  • Monitor changes in methylation patterns over time after pressure changes

  • Distinguish immediate responses from long-term adaptations

  • Correlate with expression of stress response genes

• Genetic manipulation:

  • Create targeted mutations in rsmC and related genes

  • Test pressure sensitivity of mutants versus sensitivity to other stressors

  • Use complementation studies to confirm specificity

What are the implications of rsmC research for understanding bacterial adaptation to extreme environments?

Studying rsmC in P. profundum has broader implications for understanding bacterial adaptation:

• Evolutionary insights:

  • Comparison of rsmC sequences across bacterial species can reveal evolutionary adaptations

  • Similar to how outer membrane protein lysine methyltransferases form distinct evolutionary clusters

  • May provide insights into the evolution of pressure adaptation mechanisms

• Novel regulatory mechanisms:

  • Understanding how methylation contributes to gene regulation under extreme conditions

  • May reveal new paradigms for bacterial adaptation to environmental stressors

  • Particularly relevant for the unusual large intergenic regions found in P. profundum

• Biotechnological applications:

  • Knowledge of pressure adaptation mechanisms could inform development of pressure-resistant enzymes

  • Potential applications in deep-sea biotechnology and bioremediation

  • Might enable new approaches for heterologous expression of deep-sea bacterial proteins

• Methodological advances:

  • Techniques developed for studying methylation in extremophiles can be applied to other systems

  • Integration of RSM approaches for optimizing complex biological processes3

  • Novel approaches for detecting and quantifying RNA modifications

• Ecological significance:

  • Better understanding of how bacteria adapt to specific marine niches

  • Insights into microbial community structure across ocean depth gradients

  • Potential implications for understanding deep-sea ecosystem function

What are the recommended controls for experiments involving recombinant P. profundum rsmC?

To ensure robust and interpretable results, the following controls should be included:

• For gene expression studies:

  • Empty vector controls

  • Inactive mutant rsmC (e.g., with mutations in catalytic residues)

  • Wild-type and knockout strains for in vivo studies

  • Housekeeping genes as reference for normalization

• For methyltransferase activity assays:

  • No-enzyme controls

  • Heat-inactivated enzyme controls

  • No-substrate controls

  • Known methyltransferase with defined activity as positive control

• For pressure experiments:

  • Atmospheric pressure controls

  • Gradual versus sudden pressure changes

  • Temperature-matched controls (as pressure changes can affect temperature)

  • Piezophilic (SS9) and non-piezophilic (3TCK) strains for comparison

• For in vivo photoreactivation studies (if examining UV responses):

  • Untreated controls

  • UV irradiated without blue light recovery

  • UV irradiated with blue light recovery

  • Specific power and timing parameters should be controlled (e.g., germicidal lamp at 253.7 nm for 10 seconds at 220 μW/cm²)

How can inconsistencies in methylation pattern data be resolved and interpreted?

When faced with inconsistent methylation data, researchers should:

• Technical validation:

  • Repeat experiments with increased replication

  • Use multiple detection methods (e.g., both radioactive assays and mass spectrometry)

  • Standardize sample preparation and analysis protocols

  • Include internal standards for normalization

• Biological context consideration:

  • Test if inconsistencies correlate with specific growth conditions

  • Examine if there are growth phase-dependent effects

  • Consider potential post-translational regulation of rsmC activity

  • Evaluate if heterogeneity represents functional diversity rather than error

• Statistical approaches:

  • Apply appropriate statistical tests for the data distribution

  • Use models that account for both fixed and random effects

  • Consider Bayesian approaches for integrating prior knowledge

  • Use RSM to model complex relationships between variables3

• Data integration strategies:

  • Correlate methylation data with transcriptomics and proteomics

  • Look for patterns across different types of measurements

  • Consider evolutionary conservation of methylation sites

  • Develop predictive models that incorporate multiple data types

What are the most promising avenues for future research on P. profundum rsmC?

Based on current knowledge, the following research directions show particular promise:

• Comparative analysis of rsmC across pressure-adapted strains:

  • Sequence and functional comparison between SS9, 3TCK, and other P. profundum strains

  • Correlation of rsmC sequence variations with pressure adaptation

  • Identification of critical domains and residues for pressure-responsive function

• Investigation of the role of rsmC in regulating the transcribed intergenic regions:

  • P. profundum has unusually large intergenic regions that are transcribed and pressure-responsive

  • Determine if rsmC methylates or regulates these non-coding transcripts

  • Explore potential role in pressure adaptation mechanisms

• Integration of methylation mechanisms with other regulatory systems:

  • Explore interactions with quorum sensing systems (similar to how RsmC effects in E. carotovora are partially dependent on N-(3-oxohexanoyl)-L-homoserine lactone)

  • Investigate potential coordination with other post-transcriptional regulatory mechanisms

  • Determine how methylation contributes to global gene expression patterns

• Application of advanced methodologies:

  • Use of LC-MS methods similar to those used for protein methylation studies

  • Application of RSM for systematic optimization of experimental conditions3

  • Development of high-throughput screening approaches for methyltransferase activity