Recombinant Enterococcus faecalis Uncharacterized RNA methyltransferase EF_0728 (EF_0728)

What is EF_0728 and what is its predicted function?

EF_0728 is an uncharacterized RNA methyltransferase from Enterococcus faecalis that likely belongs to the family of enzymes that catalyze post-transcriptional RNA modifications. Based on sequence homology and structural predictions, it may be functionally similar to characterized RNA methyltransferases like RlmN, which catalyzes the formation of N2-methyladenosine (m2A) in both ribosomal RNA and transfer RNA. RlmN in E. faecalis has been shown to methylate A2503 in 23S rRNA at the peptidyl transferase center in the 50S ribosomal subunit and A37 in the subset of tRNAs bearing adenine at this position in the anticodon stem loop . The methylation activity of these enzymes often requires Fe-S cluster cofactors and S-adenosylmethionine (SAM) as a methyl donor.

How does EF_0728 compare to other characterized bacterial RNA methyltransferases?

EF_0728 shares several conserved domains with other bacterial RNA methyltransferases, particularly those involved in rRNA and tRNA modifications. Comparative sequence analysis suggests it may contain an Fe-S cluster binding motif typical of radical SAM enzymes, similar to RlmN. While RlmN has been characterized in E. coli and to some extent in E. faecalis, EF_0728 remains largely uncharacterized. Analysis of deletion mutants for related methyltransferases in E. faecalis has shown complete loss of specific methylation marks (such as m2A) in both 23S rRNA and tRNA , suggesting these enzymes play non-redundant roles in RNA modification.

Why is studying EF_0728 important for understanding bacterial physiology?

RNA methyltransferases play crucial roles in bacterial physiology by:

• Regulating translation efficiency through rRNA and tRNA modifications

• Contributing to antibiotic resistance mechanisms, particularly against drugs targeting the ribosome

• Participating in stress response pathways

• Potentially serving as sensors for environmental conditions such as oxidative stress

Recent research has shown that related RNA methyltransferases in E. faecalis respond to reactive oxygen species (ROS) exposure, suggesting they may function as redox-sensitive molecular switches linking environmental stresses to epitranscriptomic regulation . This connection between RNA modification enzymes and stress response makes EF_0728 a potentially important target for understanding how this opportunistic pathogen adapts to host environments and antibiotic treatments.

What are the most effective approaches for recombinant expression and purification of EF_0728?

For recombinant expression and purification of EF_0728, a methodical approach following these steps is recommended:

• Vector selection: Use pET-based expression vectors with appropriate affinity tags (His6 or GST) for E. coli expression systems.

• Host strain optimization: BL21(DE3) derivatives such as Rosetta or Arctic Express strains are recommended for overcoming codon bias and improving protein folding.

• Expression conditions: Optimize induction parameters (temperature, IPTG concentration, duration) with particular attention to:

  • Low-temperature induction (16-18°C) to improve protein folding

  • Supplementation with iron and sulfur sources for proper Fe-S cluster formation

  • Co-expression with chaperones if initial expression yields are low

• Anaerobic purification: Perform protein purification under strictly anaerobic conditions to preserve Fe-S cluster integrity using:

  • IMAC (immobilized metal affinity chromatography) for initial capture

  • Size exclusion chromatography for final polishing

  • All buffers should contain reducing agents (DTT or β-mercaptoethanol)

This approach follows established protocols for related Fe-S cluster-containing methyltransferases while addressing the specific challenges of EF_0728 expression .

How can I design a robust experimental setup to characterize EF_0728 enzymatic activity?

A systematic experimental design to characterize EF_0728 enzymatic activity should include:

For robust analysis, implement the following steps:

• Substrate preparation: Generate potential RNA substrates through in vitro transcription, focusing on both rRNA fragments and tRNA molecules with potential methylation sites.

• Activity assays: Incubate purified EF_0728 with RNA substrates in the presence of SAM and analyze using LC-MS to detect methylated products .

• Kinetic analysis: Determine enzyme kinetics by varying substrate concentrations and measuring initial reaction rates.

• Inhibition studies: Test sensitivity to known methyltransferase inhibitors to further characterize catalytic mechanisms.

This experimental design incorporates multiple controls and validation steps to ensure reliability and reproducibility of results .

What are the best methods for generating and validating EF_0728 knockout mutants in E. faecalis?

For generating and validating EF_0728 knockout mutants in E. faecalis, a comprehensive approach includes:

• Mutant construction:

  • Utilize allelic exchange methods with temperature-sensitive plasmids (pGhost system)

  • Apply CRISPR-Cas9 based genome editing for precise deletions

  • Consider creating both complete gene deletions and point mutations in catalytic residues

• Selection strategies:

  • Use antibiotic markers (erythromycin, chloramphenicol) for initial selection

  • Apply counterselection with p-chlorophenylalanine (p-Cl-Phe) for markerless deletions

• Validation methods:

  • PCR verification with primers flanking the deletion region

  • Whole-genome sequencing to confirm single-site modification

  • RT-qPCR to verify absence of transcript

  • Western blotting if antibodies are available

  • LC-MS/MS analysis of RNA to confirm loss of specific methylation marks

• Phenotypic characterization:

  • Growth curves under various conditions

  • Antibiotic susceptibility testing

  • Stress response assays (oxidative, temperature, pH)

  • Ribosome profile analysis

This systematic approach ensures the generation of clean genetic backgrounds for studying EF_0728 function in its native context .

How can I determine the specific RNA substrates and modification sites of EF_0728?

To determine the specific RNA substrates and modification sites of EF_0728, implement a multi-faceted approach:

• In vitro substrate screening:

  • Test purified EF_0728 against various RNA substrates including rRNA fragments, full-length tRNAs, and synthetic oligonucleotides

  • Use radioactive [3H]-SAM to track methyl transfer activity

  • Perform competition assays with unlabeled potential substrates

• RNA-seq based approaches:

  • Compare epitranscriptome maps between wild-type and EF_0728 deletion strains

  • Apply specific antibody-based enrichment methods for methylated nucleosides

  • Use chemical methods that specifically react with methylated positions

• Mass spectrometry analysis:

  • Digest potential RNA substrates with nuclease P1 after methyltransferase reaction

  • Analyze by LC-MS to identify methylated nucleosides

  • Perform MS/MS analysis to confirm the exact position of methylation

• Structural probing:

  • Use selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) to identify structural changes in RNA upon methylation

  • Apply dimethyl sulfate (DMS) probing to identify changes in base accessibility after modification

This comprehensive approach will reveal both the identity of RNA substrates and the precise positions modified by EF_0728, providing crucial information about its biological function .

What factors influence the substrate specificity of EF_0728 compared to other RNA methyltransferases?

Several key factors influence the substrate specificity of RNA methyltransferases like EF_0728:

• Structural determinants:

  • RNA secondary structure requirements

  • Specific sequence motifs around the modification site

  • Tertiary interactions that position the target nucleotide

• Protein domains:

  • Presence of RNA-binding domains that recognize specific RNA structures

  • Flexibility of the active site to accommodate different substrates

  • Allosteric regulation of enzyme activity

• Cofactor requirements:

  • The integrity of the Fe-S cluster has been shown to be essential for activity

  • Redox state of the enzyme, particularly in response to ROS exposure

  • Availability of SAM and other potential cofactors

Related RNA methyltransferases show specific patterns for substrate recognition. For example, RlmN requires a specific structural context around A2503 in 23S rRNA and A37 in tRNAs . By comparing substrate preferences of EF_0728 with those of characterized enzymes, researchers can gain insights into the evolutionary relationships and potential functional redundancy among these enzymes.

How does oxidative stress affect the enzymatic activity of EF_0728 and what are the implications for bacterial physiology?

Oxidative stress significantly impacts the activity of Fe-S cluster-containing RNA methyltransferases like EF_0728, with important physiological implications:

• Direct effects on enzyme activity:

  • ROS-mediated inactivation of the Fe-S cluster leads to decreased methyltransferase activity

  • Large decreases in specific methylation marks (such as m2A) have been observed following exposure to ROS-generating compounds like menadione

  • Sublethal doses of antibiotics that induce ROS (erythromycin, chloramphenicol) also reduce methyltransferase activity

• Changes in protein expression patterns:

  • Loss of methyltransferase activity alters the translation of specific proteins

  • Increased expression of stress response proteins (e.g., superoxide dismutase)

  • Decreased expression of virulence factors

• Adaptive responses:

  • The ROS-sensing capability of these enzymes may represent an evolved mechanism to rapidly adjust translation in response to environmental stresses

  • This creates a direct link between oxidative stress and epitranscriptomic regulation

• Implications for antibiotic resistance:

  • Antibiotics that generate ROS may paradoxically trigger adaptive responses through this pathway

  • The connection between RNA methylation and stress response suggests potential targets for combination therapies

These findings suggest that EF_0728 and related enzymes may function as redox-sensitive molecular switches that link environmental and antibiotic-induced ROS exposure to changes in the epitranscriptome, ultimately affecting protein synthesis and bacterial adaptation .

What is the connection between EF_0728 activity and antibiotic resistance mechanisms in E. faecalis?

The connection between EF_0728 activity and antibiotic resistance in E. faecalis likely involves several interrelated mechanisms:

• Direct modification of ribosomal RNA:

  • Methylation of specific rRNA nucleotides can directly alter antibiotic binding sites

  • Modification at or near the peptidyl transferase center could affect the binding of macrolides, lincosamides, and streptogramins

  • Changes in RNA structure due to methylation may indirectly affect binding of other ribosome-targeting antibiotics

• Translation regulation under stress:

  • RNA methyltransferase activity influences the translation of specific proteins

  • Loss of RlmN activity has been shown to increase expression of superoxide dismutase and decrease virulence proteins, mimicking the effects of oxidative stress exposure

  • This regulated expression may help bacteria survive antibiotic exposure

• Sensing antibiotic-induced stress:

  • Sublethal doses of antibiotics like erythromycin and chloramphenicol induce ROS production

  • ROS can inactivate Fe-S cluster-containing methyltransferases like EF_0728

  • This inactivation triggers adaptive responses that may enhance survival

• Bacterial persistence:

  • Changes in translation efficiency can lead to slower growth and metabolic shifts

  • These changes may contribute to persistence phenotypes, allowing bacteria to survive antibiotic treatment

Understanding these connections provides insights into potential combination therapies targeting both the antibiotic resistance mechanism and the adaptive response pathway .

How can I design experiments to evaluate the role of EF_0728 in oxidative stress response?

To evaluate the role of EF_0728 in oxidative stress response, design experiments that systematically assess the relationship between oxidative stress, methyltransferase activity, and bacterial physiology:

• Exposure studies:

  • Subject wild-type and EF_0728 deletion mutants to various ROS-generating agents:

    • Menadione (superoxide generator)

    • Hydrogen peroxide

    • Paraquat

    • Sublethal doses of antibiotics known to induce ROS

• Activity assays under stress conditions:

  • Purify EF_0728 and expose it to oxidizing conditions in vitro

  • Measure activity before and after exposure

  • Assess Fe-S cluster integrity using UV-visible spectroscopy

  • Determine if activity can be rescued by reconstitution of the Fe-S cluster

• Epitranscriptome analysis:

  • Compare methylation patterns in wild-type and mutant strains under normal and stress conditions

  • Use LC-MS/MS to quantify changes in specific modified nucleosides

  • Identify which RNA modifications are most sensitive to oxidative stress

• Proteome analysis:

  • Perform quantitative proteomics on wild-type vs. EF_0728 deletion strains

  • Compare protein expression profiles under normal and stress conditions

  • Identify proteins whose translation is specifically affected by loss of EF_0728

• Survival assays:

  • Test survival rates of wild-type and mutant strains under various stress conditions

  • Assess recovery after exposure to determine if EF_0728 affects adaptation

This experimental design allows for a comprehensive assessment of EF_0728's role in sensing and responding to oxidative stress .

What regulatory pathways control EF_0728 expression in response to environmental stressors?

The regulatory pathways controlling EF_0728 expression in response to environmental stressors likely involve multiple mechanisms:

• Transcriptional regulation:

  • Analyze the promoter region of EF_0728 for binding sites of known stress-responsive transcription factors:

    • SoxRS and OxyR homologs (oxidative stress regulators)

    • Heat shock and general stress response regulators

    • Metal-responsive transcription factors

  • Perform chromatin immunoprecipitation (ChIP) assays to identify proteins binding to the EF_0728 promoter under different conditions

• Post-transcriptional regulation:

  • Assess mRNA stability under different stress conditions

  • Investigate the role of small RNAs in regulating EF_0728 expression

  • Examine the potential for auto-regulation through RNA structure

• Post-translational regulation:

  • Determine if EF_0728 undergoes modifications affecting its activity:

    • Phosphorylation

    • Acetylation

    • Redox-sensitive modifications

  • Investigate protein-protein interactions that might regulate EF_0728 activity

• Experimental approaches:

  • Use reporter gene fusions to monitor EF_0728 expression in real-time

  • Perform RNA-seq and ribosome profiling to assess transcriptional and translational responses

  • Apply proteomics approaches to identify stress-induced modifications

Understanding these regulatory mechanisms will provide insights into how E. faecalis integrates environmental signals to modulate epitranscriptomic modifications and adapt to changing conditions .

How should I analyze and interpret LC-MS data for RNA methylation studies involving EF_0728?

For effective analysis and interpretation of LC-MS data in RNA methylation studies involving EF_0728, follow these methodological steps:

• Sample preparation optimization:

  • Ensure complete nuclease digestion of RNA to individual nucleosides

  • Include internal standards for quantification

  • Consider enrichment steps for low-abundance modifications

• Data acquisition parameters:

  • Optimize chromatographic separation for nucleosides of interest

  • Use multiple reaction monitoring (MRM) for targeted analysis

  • Employ high-resolution MS for discovery of novel modifications

• Analytical workflow:

  • Track the disappearance of unreacted substrates and formation of methylated products

  • Calculate conversion rates from the difference between unreacted substrate before and after the reaction

  • Confirm by measuring the formation of the methylated product

  • Apply proper statistical analysis for biological replicates

• Data interpretation considerations:

  • Compare methylation patterns between wild-type and EF_0728 mutant strains

  • Consider the presence of interfering compounds or isobaric modifications

  • Evaluate the influence of RNA purity on reaction efficiency

  • Account for the dynamic nature of modifications under different conditions

• Quantitative analysis:

  • Establish standard curves for accurate quantification

  • Use isotopically labeled internal standards when possible

  • Apply appropriate normalization methods

This systematic approach enables reliable analysis of EF_0728-mediated RNA methylation and allows for meaningful comparisons across different experimental conditions .

What are common challenges in interpreting data from EF_0728 functional studies and how can they be addressed?

Researchers face several common challenges when interpreting data from EF_0728 functional studies, along with strategic approaches to address them:

• Distinguishing direct vs. indirect effects:

  • Challenge: Determining whether observed phenotypes are directly caused by loss of EF_0728 activity or are secondary effects.

  • Solution: Use catalytically inactive point mutants alongside complete deletion mutants to distinguish between structural and enzymatic roles of the protein.

• Identifying specific substrates:

  • Challenge: Determining which RNAs are directly modified by EF_0728 versus those modified by other methyltransferases.

  • Solution: Combine in vitro enzymatic assays with in vivo epitranscriptome mapping to confirm genuine substrates.

• Redundancy with other methyltransferases:

  • Challenge: Overlapping functions with other RNA modification enzymes may mask phenotypes.

  • Solution: Create and analyze double or triple mutants lacking multiple methyltransferases to reveal functional redundancies.

• Environmental influences on activity:

  • Challenge: Activity may vary significantly based on growth conditions, making results difficult to interpret.

  • Solution: Standardize growth conditions and test a matrix of relevant environmental variables to establish condition-dependent effects.

• Technical variability in RNA modification detection:

  • Challenge: Low abundance modifications may be near the detection limit of analytical methods.

  • Solution: Implement enrichment techniques and use multiple detection methods (LC-MS/MS, antibody-based detection, chemical reactivity) to verify results .

By anticipating these challenges and implementing appropriate experimental controls and analytical approaches, researchers can generate more reliable and interpretable data from EF_0728 functional studies.

How can I resolve contradictory results between in vitro enzymatic assays and in vivo phenotypes in EF_0728 studies?

Resolving contradictions between in vitro enzymatic assays and in vivo phenotypes requires a systematic troubleshooting approach:

• Analyze experimental conditions:

  • In vitro conditions may not accurately reflect the cellular environment

  • Adjust buffer composition, pH, and temperature to better mimic physiological conditions

  • Include cellular factors that might be missing in purified systems

• Consider enzyme state and modifications:

  • The recombinant enzyme may lack post-translational modifications present in vivo

  • The Fe-S cluster integrity is critical and may be compromised during purification

  • Consider co-factors or protein partners that may be required in vivo but absent in vitro

• Evaluate substrate accessibility:

  • In cells, RNA structure and protein binding may restrict access to methylation sites

  • RNA substrates in vitro may not adopt native conformations

  • Use structure probing techniques to compare RNA conformations in different contexts

• Implement bridging experiments:

  • Develop cell extract-based assays that provide an intermediate between purified components and whole cells

  • Perform in vitro assays with native substrates isolated from cells

  • Use in vivo chemical probing to assess modification status directly in cells

• Address methodological limitations:

  • Different detection methods have varying sensitivities and specificities

  • Use multiple independent techniques to verify results

  • Implement proper controls to account for technical variability

This comprehensive approach allows researchers to identify the factors responsible for apparent contradictions and develop a unified model of EF_0728 function that reconciles in vitro and in vivo observations.

What cutting-edge approaches can be applied to study the structural dynamics of EF_0728-RNA interactions?

Several cutting-edge approaches can provide unprecedented insights into the structural dynamics of EF_0728-RNA interactions:

• Cryo-electron microscopy (Cryo-EM):

  • Capture EF_0728 bound to its RNA substrates at near-atomic resolution

  • Visualize conformational changes during the catalytic cycle

  • Identify the binding mode and specific contacts with RNA substrates

• Hydrogen-deuterium exchange mass spectrometry (HDX-MS):

  • Map protein-RNA interaction surfaces

  • Detect conformational changes upon substrate binding or under different redox conditions

  • Identify regions with dynamic flexibility important for catalysis

• Single-molecule techniques:

  • Apply single-molecule FRET to observe real-time conformational changes

  • Use optical tweezers to measure binding forces and kinetics

  • Implement nanopore technology to detect modifications at single-nucleotide resolution

• Time-resolved structural studies:

  • Utilize time-resolved X-ray crystallography to capture catalytic intermediates

  • Apply temperature-jump NMR to observe conformational transitions

  • Implement rapid freeze-quench EPR to track changes in the Fe-S cluster during catalysis

• Computational approaches:

  • Molecular dynamics simulations of EF_0728-RNA complexes

  • Quantum mechanical/molecular mechanical (QM/MM) calculations to model the reaction mechanism

  • Machine learning approaches to predict RNA binding sites and modification targets

These advanced methods, when combined with traditional biochemical and genetic approaches, can provide a comprehensive understanding of how EF_0728 recognizes, binds, and modifies its RNA substrates, and how these interactions are affected by environmental conditions such as oxidative stress .

How can systems biology approaches be used to understand the global impact of EF_0728 activity on cellular physiology?

Systems biology approaches offer powerful tools to elucidate the global impact of EF_0728 activity on cellular physiology:

• Multi-omics integration:

  • Combine epitranscriptomics, transcriptomics, proteomics, and metabolomics data

  • Correlate changes in RNA modifications with alterations in gene expression, protein levels, and metabolic fluxes

  • Develop computational models to predict the consequences of perturbations in EF_0728 activity

• Network analysis:

  • Construct gene regulatory networks affected by EF_0728 activity

  • Identify key nodes and hubs where methylation-dependent regulation has broad impacts

  • Map the connections between stress response pathways and RNA modification systems

• Temporal dynamics:

  • Perform time-course experiments following EF_0728 inactivation or stress exposure

  • Track the propagation of effects through different cellular systems

  • Develop mathematical models of the kinetics of adaptation responses

• Comparative systems biology:

  • Compare the role of EF_0728 across different bacterial species

  • Identify conserved and species-specific aspects of RNA modification functions

  • Examine how different ecological niches shape the evolution of RNA modification systems

• Synthetic biology approaches:

  • Engineer synthetic circuits incorporating EF_0728 as a regulatory element

  • Create reporter systems to monitor RNA modification levels in real-time

  • Develop tunable systems to control EF_0728 activity and observe global responses

By integrating these systems-level approaches, researchers can develop comprehensive models of how EF_0728-mediated RNA modifications influence cellular physiology across different conditions, providing insights into both basic biology and potential applications in biotechnology and medicine .

What are the emerging hypotheses about the evolutionary significance of RNA methyltransferases like EF_0728 in bacterial adaptation?

Several emerging hypotheses address the evolutionary significance of RNA methyltransferases like EF_0728 in bacterial adaptation:

• Stress response integration hypothesis:

  • RNA methyltransferases evolved as direct sensors of environmental stressors (particularly ROS)

  • The Fe-S cluster sensitivity provides an elegant mechanism to directly couple oxidative stress to translational reprogramming

  • This connection allows rapid adaptation without requiring transcriptional responses

• Antibiotic resistance modulation hypothesis:

  • RNA modifications serve as a "first line of defense" against ribosome-targeting antibiotics

  • The ability to sense antibiotic-induced stress through ROS detection provides an early warning system

  • This mechanism may have evolved in soil bacteria constantly exposed to naturally produced antibiotics

• Translational fine-tuning hypothesis:

  • RNA methyltransferases provide an additional layer of gene regulation at the translational level

  • Specific modifications can alter ribosome dynamics at particular codons or mRNA contexts

  • This mechanism allows rapid adaptation to changing environments without requiring new protein synthesis

• Host-pathogen co-evolution hypothesis:

  • In pathogens like E. faecalis, RNA modifications help adapt to host defense mechanisms

  • The ability to sense host-generated ROS through methyltransferase inactivation triggers appropriate responses

  • This system may have been selected during evolution of commensalism and pathogenicity

• Epitranscriptome plasticity hypothesis:

  • RNA modifications represent a form of non-genetic inheritance that can be rapidly adjusted

  • Changes in modification patterns can be transmitted through generations during infection or colonization

  • This provides a form of adaptive memory that is more flexible than genetic mutations

These hypotheses are not mutually exclusive and likely represent different facets of the complex evolutionary history of RNA modification systems in bacteria. Testing these hypotheses requires comparative genomics, experimental evolution, and detailed mechanistic studies across diverse bacterial species .