Recombinant Porphyromonas gingivalis tRNA1 (Val) (adenine (37)-N6)-methyltransferase (PG_1104)

What is the molecular structure and function of PG_1104 in Porphyromonas gingivalis?

PG_1104 is a tRNA1 (Val) (adenine(37)-N6)-methyltransferase from Porphyromonas gingivalis that catalyzes the formation of N6-methyladenosine at position 37 in valine tRNA. The enzyme belongs to the methyltransferase family that utilizes S-adenosyl methionine (SAM) as a methyl donor . The protein has a full length of 255 amino acids and contains characteristic methyltransferase domains . Like other tRNA methyltransferases, PG_1104 modifies specific nucleosides in tRNA molecules to ensure proper tRNA folding, stability, and accurate codon recognition during translation .

How does the recombinant PG_1104 differ from its native form in P. gingivalis?

The recombinant PG_1104 protein is expressed in E. coli systems with a His-tag for purification purposes, which may affect its solubility and tertiary structure compared to the native form . While the catalytic core remains functionally similar, the recombinant form may exhibit different kinetic parameters due to the absence of bacterial post-translational modifications that occur in P. gingivalis. Studies comparing native and recombinant forms have shown that while both retain methyltransferase activity, the recombinant enzyme typically demonstrates >90% purity by SDS-PAGE analysis but may have 10-15% lower specific activity than the native enzyme .

What are the optimal buffer conditions for measuring PG_1104 methyltransferase activity?

Based on established protocols for tRNA methyltransferases, optimal activity assay conditions for PG_1104 include:

For activity measurement, using position-specific labeled tRNA substrates (<10 nM) and analyzing methylation under single turnover conditions provides the most accurate results .

What methodologies can be used to confirm successful methylation of tRNA substrates by PG_1104?

Several complementary approaches can verify PG_1104 methylation activity:

• Methyltransferase assay using radiolabeled SAM: Incubate enzyme with ³H-labeled SAM and tRNA substrate, then measure incorporation of radioactive methyl groups via filter binding assay or scintillation counting .

• RNA-SCRATCh (Site-specific Capture and Release Analysis of Transcripts) method: This technique allows verification of the identity and stoichiometry of the modification at specific sites by:

  • Isolating the 3' fragment containing the modification site

  • Radioactively labeling the fragment

  • Digesting to nucleosides

  • Separating by thin-layer chromatography

  • Visualizing by autoradiography

• High-resolution liquid chromatography-mass spectrometry (LC-MS): For precise identification of modified nucleosides within tRNA molecules .

• Reverse transcriptase-based methods: Utilizing the characteristic "RT-error signature" at methylation sites to detect modifications through next-generation sequencing approaches .

Which amino acid residues are critical for the catalytic activity of PG_1104, and how can they be experimentally verified?

Critical residues in PG_1104's catalytic domain include:

• The GxGxG SAM-binding motif: Essential for SAM binding and positioning

• Conserved acidic residues in β-strands 1-4: Particularly the acidic residue at the end of the first β-strand

• Histidine residues in the catalytic pocket: Critical for methyltransferase function

These residues can be verified through:

• Site-directed mutagenesis: Creating point mutations (e.g., E→A or H→A substitutions) and assessing activity loss

• Structural analyses: Using AlphaFold predictions (pLDDT scores >70) to identify confidently predicted domains and residues

• Comparative analysis: Alignment with homologous enzymes whose critical residues have been established

For example, in related methyltransferases, mutation of key acidic residues (corresponding to D72 in yeast Trm9) or histidine residues (corresponding to H116) completely abolished enzyme activity .

How does PG_1104 achieve target specificity for the adenine at position 37 in tRNA(Val)?

PG_1104 achieves its remarkable target specificity through:

Experimental evidence from related tRNA methyltransferases suggests that recognition often involves multiple contact points with the tRNA substrate beyond just the target nucleoside .

How does PG_1104 differ from other tRNA methyltransferases in P. gingivalis and other bacterial species?

PG_1104 belongs to a specific subclass of tRNA methyltransferases that targets position 37 adenosine in tRNA. Key differences include:

Unlike METTL1/WDR4 complexes that are upregulated in certain cancers and regulate oncogenic transcript translation , bacterial tRNA methyltransferases like PG_1104 are more specialized and often essential for proper translation in their respective organisms .

How can PG_1104 be utilized to study the broader impact of tRNA modifications on bacterial translation dynamics?

PG_1104 offers several sophisticated research applications:

• Ribosome profiling with PG_1104 knockout strains: This approach can reveal translational pausing at valine codons, demonstrating the role of m⁶A37 in translation efficiency .

• Proteome-wide analysis: Quantitative proteomics comparing wild-type and PG_1104-deficient P. gingivalis can identify proteins whose expression is most affected by the loss of this modification, potentially revealing valine codon usage bias effects .

• tRNA modification profiling: Mass spectrometry-based approaches like RNA-SCRATCh can be combined with knockout studies to establish modification networks and interdependencies between different tRNA modifications .

• In vitro translation systems: Reconstituted translation systems using purified components can directly test how the presence or absence of PG_1104-mediated modifications affects the speed and accuracy of translation at different valine codons .

What approaches can be used to develop specific inhibitors of PG_1104 for potential therapeutic applications?

Development of selective PG_1104 inhibitors would involve:

• Structure-based drug design:

  • Generate high-resolution structures of PG_1104 using X-ray crystallography or cryo-EM, especially in complex with substrates

  • Use computational docking studies to identify pocket-binding small molecules

  • Focus on compounds that compete with SAM binding or interfere with tRNA recognition

• High-throughput screening approaches:

  • Develop a fluorescence-based methyltransferase assay suitable for screening compound libraries

  • Screen for compounds that inhibit methyltransferase activity using radiometric assays with ³H-labeled SAM

  • Conduct secondary screens to confirm specificity against human methyltransferases

• Biological validation:

  • Test candidate inhibitors for effects on P. gingivalis growth and virulence

  • Evaluate ability to reduce periodontal tissue destruction in infection models

  • Assess potential for combination therapy with existing periodontal treatments

Targeting bacterial tRNA methyltransferases offers potential antimicrobial strategies with reduced risk of affecting human homologs due to structural differences between bacterial and mammalian enzymes .

What are the optimal conditions for expressing and purifying active recombinant PG_1104?

Based on established protocols for similar tRNA methyltransferases, optimal expression and purification conditions include:

For optimal activity, the recombinant enzyme should demonstrate >90% purity by SDS-PAGE, without evidence of degradation or aggregation, and maintain activity for at least 6 months when stored appropriately at -80°C .

How can RNA substrates be prepared for in vitro studies of PG_1104 activity?

Preparation of suitable tRNA substrates for PG_1104 studies requires several sophisticated approaches:

• In vitro transcription of tRNA:

  • Create template plasmids encoding T7 promoter, hammerhead ribozyme, and tRNA sequence

  • Generate tRNA by run-off transcription with T7 RNA polymerase

  • Include CCA at the 3' end for proper tRNA structure

• Generating position-specific labeled tRNA:

  • Synthesize tRNA in fragments (nucleotides 9-72 by transcription)

  • 5'-end label specific positions (e.g., position 37)

  • Use splint-guided ligation to join fragments

• Purification and quality control:

  • Purify by gel electrophoresis to ensure homogeneity

  • Verify correct folding by native gel analysis and thermal denaturation

  • Confirm structure by chemical probing methods

For accurate kinetic studies, it's crucial to ensure that the in vitro transcribed tRNAs adopt the correct three-dimensional structure, which can be verified using comparative analysis with native tRNAs by circular dichroism spectroscopy .

What experimental approaches can differentiate the role of PG_1104 from other P. gingivalis methyltransferases in pathogenicity?

Several sophisticated experimental approaches can isolate PG_1104's specific contributions:

• CRISPR-Cas9 genome editing in P. gingivalis:

  • Generate precise knockouts of PG_1104 without polar effects

  • Create catalytically inactive mutants (point mutations in active site)

  • Develop complementation strains expressing wild-type or mutant versions

• Comparative virulence assays:

  • Mouse periodontitis models comparing wild-type, knockout, and complemented strains

  • Quantitative assessment of alveolar bone loss

  • Analysis of neutrophil infiltration and inflammatory response

• Transcriptome and proteome profiling:

  • RNA-seq to identify genes with altered expression in PG_1104 mutants

  • Ribosome profiling to detect translational pauses at valine codons

  • Proteomics to identify proteins most affected by loss of m⁶A37 modification

• Genetic interaction mapping:

  • Construction of double mutants with other tRNA modification enzymes

  • Synthetic lethality screening to identify functional relationships

  • Epistasis analysis to place PG_1104 in genetic pathways

These approaches would distinguish direct effects of PG_1104 from indirect consequences of altered translation, revealing its specific contribution to P. gingivalis pathogenicity .

How does the function of PG_1104 in P. gingivalis compare to its homologs in other microorganisms in the oral microbiome?

A systems biology perspective reveals interesting functional divergence:

While these enzymes share the fundamental function of tRNA modification, evolutionary divergence has led to differences in:

• Substrate specificity: PG_1104's restriction to tRNA(Val) contrasts with the broader specificity of homologs in other organisms

• Structural organization: Unlike mammalian enzymes that often require protein partners (e.g., METTL1/WDR4), bacterial methyltransferases like PG_1104 typically function independently

• Regulation patterns: Expression of PG_1104 likely responds to environmental cues specific to the periodontal pocket, while homologs in other organisms may be constitutively expressed

This divergence creates potential opportunities for selective targeting of P. gingivalis through PG_1104 inhibition while minimizing effects on commensal oral microbiota .

What computational approaches can predict the impact of PG_1104 inhibition on the broader oral microbiome?

Advanced computational methods to predict ecological consequences include:

• Genome-scale metabolic modeling:

  • Construct metabolic models of P. gingivalis with and without PG_1104 function

  • Integrate models with other oral microbiome members

  • Simulate community-level effects of PG_1104 inhibition

• Codon usage analysis:

  • Compare valine codon usage patterns across oral microbiome species

  • Identify organisms with similar reliance on valine codons that might be collaterally affected

  • Predict differential sensitivity to PG_1104 inhibition based on codon bias

• Protein interaction network analysis:

  • Construct interactome maps incorporating PG_1104's role

  • Identify hub proteins dependent on proper valine incorporation

  • Predict cascading effects through bacterial protein networks

• Molecular dynamics simulations:

  • Model structural effects of m⁶A37 absence on tRNA(Val) folding and function

  • Simulate interactions between modified/unmodified tRNAs and the ribosome

  • Predict translation efficiency changes at specific valine codons

These approaches could predict both direct effects on P. gingivalis and potential broader ecological shifts in the oral microbiome following targeted inhibition of PG_1104 .