Recombinant Pseudomonas putida Ribosomal RNA large subunit methyltransferase E (rlmE)

What is rlmE and what is its primary function in bacteria?

RlmE is a ribosomal RNA modification enzyme that methylates a specific uridine residue (U2552) in the 23S rRNA of bacterial ribosomes, creating Um2552. This modification is situated adjacent to G2553, which is an essential base that anchors the 3' CCA terminus of the A-site tRNA in the peptidyl-transferase center (PTC) of the ribosome . Unlike many other rRNA modification enzymes, rlmE plays a significant role in bacterial growth and ribosome biogenesis. The primary function of rlmE extends beyond its methyltransferase activity, as it facilitates large ribosomal subunit (LSU) assembly through mechanisms that are partially independent of its modification activity . This dual functionality makes rlmE unique among rRNA modification enzymes and particularly important for bacterial cellular physiology.

How does deletion of rlmE affect bacterial growth and ribosome assembly?

The deletion of rlmE (ΔrlmE) results in a notable 2-4 fold decrease in growth rate compared to wild-type bacterial cells, making it one of the few rRNA modification enzymes whose deletion causes a significant growth phenotype . The growth defect is particularly pronounced at lower temperatures, indicating temperature-dependent functions. The primary cause of this growth impairment is defective ribosome assembly, specifically affecting the large ribosomal subunit (LSU) . Unlike most other rRNA modification enzyme deletions, which have minimal effects on ribosome biogenesis, rlmE deletion leads to significant accumulation of incomplete LSU precursors. Interestingly, the severe assembly phenotype of ΔrlmE strains can be partially rescued by overexpression of small GTPases such as Obg and EngA, suggesting that rlmE has functions in ribosome LSU assembly that are independent of its methylase activity and pointing to functional redundancy between RNA modification enzymes and certain small GTPases .

What are the optimal storage and handling conditions for recombinant P. putida rlmE?

For optimal preservation of recombinant Pseudomonas putida rlmE protein activity, proper storage conditions are essential. The shelf life of the protein is influenced by multiple factors including buffer composition, storage temperature, and the intrinsic stability of the protein itself . For liquid formulations of recombinant P. putida rlmE, the recommended storage temperature is -20°C to -80°C, which typically provides a shelf life of approximately 6 months . Lyophilized (freeze-dried) formulations offer extended stability, with a shelf life of up to 12 months when stored at -20°C to -80°C .

When working with the protein, minimize freeze-thaw cycles as these can significantly reduce activity through structural damage. For research applications requiring long-term storage, aliquoting the protein into single-use volumes before freezing is recommended to avoid repeated freeze-thaw cycles. The recombinant P. putida rlmE protein should maintain >85% purity as verified by SDS-PAGE, which is crucial for ensuring experimental reproducibility and reliable results .

What is the amino acid sequence of P. putida rlmE and how is it characterized?

The recombinant Pseudomonas putida rlmE protein has a defined amino acid sequence that has been characterized and documented. According to the product information, the sequence is: "MVQRSKSSAN WLREHFNDPF VKQAQKDGYR SRASYKLLEI QEKDRLI" . This sequence corresponds to the Uniprot accession number B0KHY6, identifying it as the rlmE protein from Pseudomonas putida strain GB-1 .

For characterization purposes, recombinant rlmE protein is typically analyzed using SDS-PAGE to confirm purity (>85%) . Further characterization might include activity assays to verify the methyltransferase function, typically by measuring the enzyme's ability to transfer methyl groups to substrate rRNA. Western blotting, mass spectrometry, and circular dichroism can provide additional structural and functional information. For researchers studying rlmE function, it's important to note that the protein's activity should be verified before use in experiments, particularly after extended storage periods.

How can researchers design experiments to distinguish between rlmE's methyltransferase activity and its assembly-promoting function?

Complementation studies in ΔrlmE strains provide another powerful approach. By comparing the ability of wild-type rlmE, catalytically inactive rlmE mutants, and rlmE from diverse bacterial species to rescue growth and assembly phenotypes, researchers can identify domains critical for assembly-promoting functions versus methyltransferase activity . The finding that overexpression of small GTPases (Obg and EngA) can partially rescue ΔrlmE phenotypes suggests examining protein-protein interactions between rlmE and these GTPases through co-immunoprecipitation or bacterial two-hybrid assays .

For direct assessment of methyltransferase activity, researchers should develop in vitro methylation assays using purified recombinant rlmE protein and substrate rRNA fragments. Mass spectrometry and primer extension analyses can then quantify Um2552 formation. To monitor ribosome assembly, researchers can employ sucrose gradient centrifugation combined with quantitative rRNA analysis to track accumulation of specific assembly intermediates in various genetic backgrounds. Cryo-electron microscopy of ribosomes from wild-type versus ΔrlmE strains provides structural insights into assembly defects.

What approaches can be used to study the cumulative effects of multiple rRNA modification enzyme deletions including rlmE?

Creating and analyzing multiple knockout strains represents a powerful strategy for understanding the collective contribution of rRNA modifications to bacterial fitness and ribosome function. As demonstrated in recent research, constructing an E. coli strain lacking 10 genes encoding enzymes that modify 23S rRNA around the peptidyl-transferase center revealed severe growth and ribosome assembly defects that weren't apparent in single deletion strains . This approach allows researchers to overcome the functional redundancy that often masks phenotypes in single deletion mutants.

When designing such experiments, researchers should employ a systematic combination of gene deletions, starting with functionally related modification enzymes. For instance, combining deletions of enzymes that modify nucleotides in proximity within the ribosome structure (e.g., those modifying the PTC region) may reveal synergistic effects . The creation of these multiple knockout strains can be accomplished using sequential application of CRISPR-Cas9 genome editing or traditional recombineering techniques with selectable markers.

Phenotypic characterization should be comprehensive, examining growth rates across different temperatures (as lower temperatures often exacerbate assembly defects), antibiotic susceptibilities (as many antibiotics target the ribosome), and translation fidelity using reporter systems . Ribosome profiling and polysome analysis will reveal effects on translation efficiency and accuracy. For deeper mechanistic insights, researchers should employ complementation studies with individual modification enzymes to determine their hierarchical importance, as demonstrated in recent work showing that RlmB, RlmKL, RlmN, and RluC, in addition to the previously known RlmE, facilitate large ribosomal subunit assembly .

How can adaptive laboratory evolution (ALE) be applied to study rlmE function in Pseudomonas putida?

Adaptive laboratory evolution (ALE) offers a powerful approach to investigate rlmE function in P. putida by allowing bacteria to evolve solutions to fitness challenges imposed by rlmE modification or deletion. To implement this approach, researchers should establish a dual-chamber semi-continuous log-phase bioreactor system with anti-biofilm design features, which is particularly important for P. putida due to its propensity for biofilm formation during long-term cultivation .

The experimental design should begin with creating a ΔrlmE P. putida strain and confirming its growth defect phenotype. This strain would then be subjected to long-term cultivation in the automated bioreactor system, maintaining cells in continuous log phase through iterative regrowth cycles . The evolution experiment should run for at least 40 days (comparable to the 42-day protocol validated for P. putida in previous studies), with samples collected periodically for phenotypic and genomic analysis .

What analytical techniques are most appropriate for detecting and quantifying Um2552 modification in bacterial ribosomes?

Detection and quantification of the Um2552 modification in bacterial ribosomes require sophisticated analytical approaches that can provide both positional and quantitative information. Mass spectrometry (MS) techniques represent the gold standard for modification analysis, with liquid chromatography-tandem mass spectrometry (LC-MS/MS) being particularly powerful. For this approach, researchers should isolate total rRNA, enzymatically digest it to nucleosides, and analyze the resulting mixture by LC-MS/MS to detect and quantify the Um modified nucleoside.

For site-specific detection, a combination of techniques is optimal. Primer extension analysis using reverse transcriptase can identify 2'-O-methylated positions through characteristic reverse transcriptase stops or pauses at low dNTP concentrations. RiboMeth-seq represents a more comprehensive approach, utilizing alkaline hydrolysis (which is blocked at 2'-O-methylated positions) followed by next-generation sequencing to map all 2'-O-methylation sites across the entire ribosome. For researchers specifically studying rlmE activity, comparing profiles from wild-type and ΔrlmE strains will precisely identify the Um2552 position.

HPLC analysis of ribose methylation can provide quantitative information about modification levels, which is particularly valuable when studying partial loss-of-function mutations in rlmE. For structural studies examining how Um2552 influences ribosome conformation, cryo-electron microscopy of purified ribosomes from wild-type and ΔrlmE strains offers direct visualization of structural differences resulting from the absence of this modification.

How can contradictions in research findings about rlmE function be systematically analyzed and resolved?

When faced with contradictory findings regarding rlmE function across different studies, researchers should implement a systematic approach to analysis and resolution. First, establish a comprehensive comparison framework documenting experimental conditions across studies, including bacterial strains, growth media, temperature, and specific assays used . This framework should explicitly identify apparent contradictions, such as differences in reported growth phenotypes or ribosome assembly effects.

To resolve contradictions, researchers should design validation experiments that directly test competing hypotheses under standardized conditions. For instance, if different growth phenotypes are reported for ΔrlmE strains, researchers should obtain or recreate these strains using identical deletion boundaries and test them side-by-side across multiple growth conditions . For contradictions in biochemical functions, in vitro reconstitution of rlmE activity using purified components can eliminate variables introduced by cellular contexts.

Machine learning approaches can assist in identifying patterns across datasets that might explain contradictions. For example, analyzing the complete set of genes affected in different genetic backgrounds might reveal compensatory mechanisms unique to specific laboratory strains . Additionally, researchers should consider strain-specific genetic modifiers by whole-genome sequencing of strains showing divergent phenotypes.

The CONTRADOC approach developed for analyzing self-contradictions in documents can be adapted to scientific literature analysis, helping researchers systematically identify and classify types of contradictions in the literature about rlmE function . Finally, resolution may come through more nuanced models of rlmE function that incorporate strain-specific, condition-dependent, or species-specific aspects of its dual roles in methylation and ribosome assembly.

Comparison of Growth and Assembly Phenotypes in rRNA Modification Enzyme Deletion Strains

This table synthesizes data from the literature regarding the phenotypic effects of deleting various rRNA modification enzymes. RlmE stands out as having the most severe individual effect, while others show more pronounced phenotypes when deleted in combination . The temperature sensitivity of these defects suggests that rRNA modifications may be particularly important for maintaining ribosome structural integrity under stress conditions.

Recombinant P. putida RlmE Protein Properties

This table provides detailed information about the recombinant P. putida rlmE protein available for research, including its sequence, physical properties, and recommended storage conditions . This information is essential for researchers designing experiments involving purified rlmE protein, ensuring experimental reproducibility and reliability.

Experimental Design for Studying RlmE Assembly Function

A comprehensive experimental workflow for investigating rlmE's role in ribosome assembly should incorporate multiple complementary approaches. Begin with genetic manipulation by creating precise deletion mutants of rlmE in your bacterial model system using CRISPR-Cas9 or homologous recombination techniques . In parallel, generate point mutants that specifically abolish methyltransferase activity while preserving protein structure.

For phenotypic characterization, growth curve analysis should be performed across multiple temperatures (20°C, 30°C, 37°C, 42°C) in both rich and minimal media to fully reveal condition-dependent effects of rlmE deletion. Ribosome assembly analysis using sucrose gradient fractionation will allow visualization and quantification of ribosomal subunits, completed ribosomes, and assembly intermediates in wild-type versus mutant strains .

Complementation experiments are crucial for distinguishing between methyltransferase-dependent and assembly-specific functions. Transform ΔrlmE strains with plasmids expressing wild-type rlmE, catalytically inactive rlmE, or heterologous rlmE from different species to identify functionally important domains. Additionally, overexpress known ribosome assembly factors (particularly small GTPases like Obg and EngA) to assess their ability to suppress rlmE deletion phenotypes .

For molecular interaction studies, employ pull-down assays or bacterial two-hybrid screens to identify proteins that interact with rlmE during ribosome assembly. RNA-protein interaction analysis using techniques like CLIP-seq can identify RNA binding sites beyond the modification target. Finally, structural studies using cryo-electron microscopy of ribosomes isolated from different genetic backgrounds will provide direct visualization of assembly defects and structural alterations resulting from rlmE absence.

Adaptive Laboratory Evolution Protocol for RlmE Function Analysis

To implement ALE for studying rlmE function in P. putida, researchers should follow this methodological framework based on validated approaches:

• Bioreactor Setup and Strain Preparation:

  • Construct a dual-chamber semi-continuous log-phase bioreactor with anti-biofilm features specifically designed for P. putida

  • Create ΔrlmE P. putida strain using precise genome editing

  • Prepare control wild-type strain with identical genetic background

  • Validate growth defect phenotype before beginning evolution

• Evolution Protocol:

  • Inoculate separate bioreactor chambers with ΔrlmE and wild-type strains

  • Implement automated dilution cycles maintaining continuous log-phase growth

  • Program temperature control for constant or fluctuating temperature regimes

  • Run evolution for minimum 42 days with sample collection at regular intervals

• Sample Analysis Pipeline:

  • Phenotypic characterization: Growth rate measurement, ribosome profiling

  • Genomic analysis: Whole genome sequencing of evolved populations at days 0, 14, 28, and 42

  • Mutation identification: Bioinformatic pipeline to identify fixed mutations

  • Functional validation: Reintroduce identified mutations into original ΔrlmE strain

This protocol leverages the DIY automated evolution framework validated for P. putida while focusing specifically on adaptations related to rlmE function . The approach allows identification of compensatory pathways that can overcome rlmE deficiency, providing insights into the wider regulatory networks connected to ribosome assembly and rRNA modification.