Recombinant Acinetobacter sp. Alanine--tRNA ligase (alaS), partial

What is the primary function of Alanine--tRNA ligase in bacterial translation?

Alanine--tRNA ligase (AlaRS) performs the essential function of attaching alanine to its cognate tRNA^Ala molecules, creating alanyl-tRNA^Ala that can be used by ribosomes during mRNA decoding. This aminoacylation reaction occurs in two steps: first, AlaRS activates free alanine by forming an aminoacyl-adenylate intermediate, and second, it transfers the activated amino acid onto the tRNA molecule . This process represents a critical step in translating genetic information from nucleic acids to functional proteins. In bacteria such as Acinetobacter sp., this enzyme ensures accurate incorporation of alanine during protein synthesis, which is fundamental to cellular viability.

How is AlaRS structurally classified among aminoacyl-tRNA synthetases?

AlaRS belongs to Class II aminoacyl-tRNA synthetases, distinguished by specific structural characteristics. While Class I aaRSs possess a Rossmann fold similar to dinucleotide-binding folds found in glyceraldehyde-3-phosphate dehydrogenases for ATP binding, Class II enzymes like AlaRS feature a seven-stranded antiparallel β-sheet structure in their ATP-binding domain . This structural distinction influences ATP-binding modes and tRNA interaction mechanisms. Additionally, Class II aaRSs, including AlaRS, typically acylate the 3'-OH group of the terminal adenosine in tRNA (with the exception of PheRS) . The structural classification of AlaRS provides important context for understanding its evolutionary relationships with other synthetases and informs experimental approaches for structural studies.

What quality control mechanisms does AlaRS employ to ensure translational fidelity?

AlaRS employs sophisticated quality control mechanisms to maintain translational fidelity, primarily through its post-transfer proofreading activity. This editing function specifically prevents the accumulation of misacylated tRNAs, particularly Ser-tRNA^Ala and Gly-tRNA^Ala, which could otherwise lead to mistranslation events . The proofreading occurs in a specialized editing domain that recognizes and hydrolyzes incorrectly charged tRNAs. When defects occur in this proofreading function, the result is global dysregulation of the proteome, leading to significant phenotypic consequences including impaired growth, reduced motility, and altered antibiotic sensitivity profiles . This quality control system is particularly important because serine and glycine share chemicophysical properties with alanine, making them challenging for the enzyme to discriminate during the initial aminoacylation step.

How can recombinant AlaRS be effectively expressed and purified for in vitro studies?

For effective expression and purification of recombinant Acinetobacter sp. AlaRS, researchers should employ a systematic approach beginning with gene optimization. The alaS gene should be codon-optimized for the expression host (typically E. coli) and cloned into an expression vector with an appropriate affinity tag (His-tag or GST-tag). Expression conditions require careful optimization, including IPTG concentration (typically 0.1-1.0 mM), temperature (16-37°C), and duration (4-18 hours). Lower temperatures (16-25°C) often enhance solubility of full-length AlaRS.

For purification, a multi-step approach yields best results: initial capture via affinity chromatography (Ni-NTA for His-tagged constructs), followed by ion-exchange chromatography to remove nucleic acid contaminants (crucial for synthetase studies), and size-exclusion chromatography for final polishing. Buffer composition is critical, typically containing 20-50 mM Tris-HCl (pH 7.5-8.0), 100-300 mM NaCl, 5-10 mM MgCl₂ (essential for structural integrity), 1-5 mM DTT or β-mercaptoethanol, and 5-10% glycerol to enhance stability. Activity validation through aminoacylation assays using radiolabeled amino acids or indirect pyrophosphate detection methods should follow purification to confirm functional integrity of the recombinant enzyme.

How do mutations in the editing domain of Acinetobacter sp. AlaRS affect tRNA mischarging and bacterial physiology?

Mutations in the editing domain of Acinetobacter sp. AlaRS can have profound effects on both tRNA charging accuracy and bacterial physiology. Research has demonstrated that defects in AlaRS proofreading activity, particularly those affecting the hydrolysis of Ser-tRNA^Ala, lead to global proteome dysregulation . These editing-deficient variants allow misacylated tRNAs to accumulate, resulting in mistranslation events where serine is incorporated at alanine codons.

Methodologically, researchers can evaluate these effects through several approaches. Mistranslation can be quantified using mass spectrometry to detect serine incorporation at alanine positions in reporter proteins. In vitro tRNA charging assays with purified wild-type and mutant enzymes can measure misacylation rates by monitoring the formation of Ser-tRNA^Ala versus Ala-tRNA^Ala. The physiological consequences can be assessed by comparing growth curves, biofilm formation, motility assays, and antibiotic minimum inhibitory concentration (MIC) determinations between wild-type and editing-deficient strains.

Of particular interest are second-site suppressor mutations within the AlaRS proofreading domain that can alleviate the phenotypic defects caused by primary editing mutations . These suppressors reveal previously uncharacterized residues that function in the quality control mechanism and provide insight into the structural features necessary for efficient proofreading.

What approaches can be used to characterize the kinetic parameters of wild-type versus engineered variants of Acinetobacter AlaRS?

Characterizing kinetic parameters of wild-type and engineered Acinetobacter AlaRS variants requires rigorous biochemical approaches. The standard method employs a two-step analysis of the aminoacylation reaction:

For the first step (amino acid activation), researchers can use ATP-PPi exchange assays measuring the rate of isotope-labeled PPi incorporation into ATP, which reflects the formation of aminoacyl-adenylate intermediates. This provides KM values for amino acid and ATP substrates along with kcat determinations.

For the complete reaction (tRNA charging), researchers typically use filter-binding assays with radioactively labeled amino acids (³H-alanine, ³H-serine) to monitor charged tRNA formation over time. Alternative approaches include pyrophosphate detection assays using coupled enzyme systems that produce colorimetric or fluorescent signals.

When comparing wild-type and variant enzymes, the focus should be on:

• Substrate specificity ratios (kcat/KM for alanine versus serine)

• Editing efficiency (measured through deacylation assays with pre-charged Ser-tRNA^Ala)

• Rate-limiting step determination (through pre-steady-state kinetics)

Data from these experiments are typically represented in Michaelis-Menten plots and can be compiled into tables comparing the following parameters:

This systematic approach allows researchers to quantitatively determine how specific mutations affect both the synthetic and editing activities of AlaRS variants.

How does the specificity of Acinetobacter AlaRS compare with orthologs from other bacterial species?

The specificity of Acinetobacter AlaRS can be compared with orthologs from other bacterial species through comparative biochemical and structural analyses. While the core function of attaching alanine to tRNA^Ala is conserved, species-specific variations in substrate recognition, editing efficiency, and structural features exist.

Methodologically, this comparison requires expression and purification of AlaRS from multiple species, followed by parallel biochemical characterization. Experimental approaches should include:

• Sequence alignment and phylogenetic analysis to identify conserved and divergent residues

• Cross-species aminoacylation assays to test if AlaRS from one species can charge tRNA^Ala from another

• Comparative misacylation analysis with non-cognate amino acids (particularly serine and glycine)

• Structural studies using X-ray crystallography or cryo-EM to identify species-specific structural elements

Research has shown that while the basic mechanisms of quality control are conserved across bacterial AlaRS enzymes, the efficiency of editing mechanisms can vary significantly. For example, some bacterial species may have evolved more stringent editing mechanisms in response to their specific ecological niches or metabolic requirements. The comparative approach reveals evolutionary adaptations in AlaRS function and can identify species-specific features that might be exploited for antimicrobial development targeting pathogenic Acinetobacter strains.

What experimental approaches can determine if truncated forms of Acinetobacter AlaRS retain specific catalytic activities?

Determining whether truncated forms of Acinetobacter AlaRS retain specific catalytic activities requires systematic domain mapping and functional characterization. Based on structural and functional studies of related AlaRS enzymes, researchers should design a series of N-terminal and C-terminal truncations targeting specific domains: the aminoacylation domain, the editing domain, and the C-terminal domain involved in tRNA recognition .

The experimental workflow should include:

• Design and expression of truncated variants based on structural predictions

• Purification of soluble protein fragments using optimized conditions for each construct

• Activity testing using domain-specific assays:

  • Aminoacylation domain: ATP-PPi exchange assays to test alanine activation

  • Editing domain: deacylation assays using pre-charged Ser-tRNA^Ala

  • tRNA binding: gel-shift assays or surface plasmon resonance with tRNA^Ala

Past research with AlaRS from other species has demonstrated that "based on structural and functional results, alanine activation, tRNA charging and editing activities were found to depend on the size of the truncature" . This suggests that careful design of truncation boundaries is critical to retain function.

Results should be presented as a comparison table of activities across different truncated variants:

This approach not only reveals which domains are necessary and sufficient for specific activities but also identifies potential interactions between domains that may enhance catalytic efficiency.

What potential role does Acinetobacter AlaRS play in antibiotic resistance mechanisms?

Acinetobacter AlaRS may play significant roles in antibiotic resistance mechanisms through several potential pathways. Research has demonstrated that defects in AlaRS proofreading activity can lead to altered antibiotic sensitivity profiles , suggesting a connection between translational fidelity and antimicrobial resistance.

Several mechanisms should be investigated:

• Mistranslation-induced stress responses: Compromised AlaRS editing activity leads to proteome dysregulation, potentially activating stress response pathways that confer generalized resistance to antibiotics. This can be studied by comparing transcriptome profiles between wild-type and editing-deficient strains using RNA-seq.

• Altered cell envelope properties: Mistranslation may affect the composition and integrity of cell envelope proteins, potentially modifying permeability to antibiotics. This hypothesis can be tested using membrane permeability assays with fluorescent dyes and comparing antibiotic accumulation within cells.

• Plasmid-mediated resistance: In the context of horizontal gene transfer, mobile genetic elements carrying modified alaS genes might contribute to resistance phenotypes. This connection is supported by research showing that "plasmids are playing the major role in the diffusions of antimicrobial resistance in Gram-negative bacteria" .

• AlaRS as a direct antibiotic target: Several aminoacyl-tRNA synthetases are targets for existing antibiotics, and changes in AlaRS structure might confer resistance to such compounds. Structure-based drug design approaches can identify potential binding sites for inhibitors.

Methodologically, researchers should combine genetic approaches (gene knockouts, site-directed mutagenesis) with physiological assays (MIC determinations, time-kill curves) and molecular techniques (proteomics, transcriptomics) to elucidate the specific contributions of AlaRS to antibiotic resistance in Acinetobacter species.

What are the critical controls needed when assessing AlaRS fidelity in vivo versus in vitro?

For in vitro fidelity assessment:

• Enzyme purity controls: Recombinant AlaRS preparations should be verified by SDS-PAGE and mass spectrometry to ensure absence of contaminating synthetases or editing factors.

• tRNA substrate quality controls: tRNA^Ala should be tested for integrity using gel electrophoresis under denaturing conditions to confirm appropriate folding.

• Amino acid purity controls: HPLC analysis of amino acid stocks should confirm absence of contaminating amino acids, particularly serine and glycine in alanine preparations.

• Time-course controls: Reactions should include early time points to measure initial rates before product inhibition becomes significant.

• Temperature and buffer composition controls: Identical conditions must be maintained across variant enzymes being compared.

For in vivo fidelity assessment:

• Strain background controls: Isogenic strains differing only in the alaS gene should be used to eliminate confounding genetic factors.

• Growth phase standardization: Cells should be harvested at identical growth phases when comparing mistranslation rates.

• Reporter system controls: When using reporter proteins to detect mistranslation, control constructs lacking alanine sites should be included.

• Metabolic state controls: Growth conditions should be standardized to control for amino acid pool variations that might influence charging fidelity.

Bridging the gap between systems requires:

• Correlation analyses between in vitro kinetic parameters and in vivo phenotypic outcomes

• Complementation experiments where purified AlaRS variants are introduced into editing-deficient cells to rescue phenotypes

These controls ensure that observed differences in fidelity represent genuine enzymatic properties rather than experimental artifacts.

How can researchers effectively design assays to detect and quantify misacylated tRNAs in Acinetobacter species?

Detecting and quantifying misacylated tRNAs in Acinetobacter species requires specialized assays that capture the transient nature of these molecules. Researchers should consider a multi-method approach combining both direct and indirect techniques.

Direct detection methods:

• Acid gel electrophoresis: This technique separates aminoacyl-tRNAs based on the charge characteristics of the attached amino acid. Researchers should extract total tRNA under acidic conditions to preserve the aminoacyl bond, followed by separation on acid urea polyacrylamide gels and northern blotting with probes specific for tRNA^Ala.

• Mass spectrometry-based approaches: Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) can identify and quantify misacylated tRNAs after RNase digestion. This method requires careful optimization of digestion conditions and chromatographic separation to distinguish between Ala-tRNA^Ala and Ser-tRNA^Ala.

• Microarray-based detection: Custom microarrays with oligonucleotide probes complementary to different tRNA species can be used after selective labeling of aminoacyl-tRNAs.

Indirect detection methods:

• Reporter systems: Engineered proteins with critical alanine residues whose function is compromised when replaced by serine can serve as in vivo reporters of mistranslation.

• Antibody-based detection: Custom antibodies that recognize peptides containing serine at positions encoded by alanine codons can be used in immunoblotting assays.

For quantitative analysis, researchers should implement internal standards and calibration curves using synthetic aminoacyl-tRNAs. Comparative data should be presented as ratios of misacylated to correctly acylated tRNA^Ala across different experimental conditions.

When working specifically with Acinetobacter species, researchers must optimize nucleic acid extraction protocols to account for the robust cell envelope of these gram-negative bacteria, often requiring additional lysis steps compared to protocols developed for E. coli.

How should researchers interpret contradictory results between in vivo phenotypes and in vitro biochemical data for AlaRS variants?

When faced with contradictory results between in vivo phenotypes and in vitro biochemical data for AlaRS variants, researchers should systematically evaluate several factors that could explain these discrepancies rather than dismissing either dataset.

First, examine fundamental differences between the experimental systems:

• Cellular factors: The in vivo environment contains additional proteins that may interact with AlaRS, modifying its activity. For example, second-site suppressor mutations within the AlaRS proofreading domain can alleviate phenotypic defects , suggesting complex intramolecular interactions not replicated in simplified biochemical assays.

• Substrate availability: In vivo amino acid pools fluctuate with metabolic state, potentially affecting the competition between alanine and near-cognate amino acids for AlaRS active site.

• tRNA modifications: Post-transcriptional modifications of tRNA^Ala may differ between in vivo and in vitro conditions, affecting recognition by AlaRS.

• Protein stability and turnover: AlaRS variants might have different half-lives in vivo that aren't reflected in purified protein studies.

Methodological approaches to resolve contradictions:

• Intermediate systems: Develop cell extract-based assays that preserve cellular components while allowing biochemical manipulation.

• Correlation analysis: Plot in vitro parameters (e.g., mischarging rates) against in vivo phenotypes (e.g., growth rates) across multiple AlaRS variants to identify non-linear relationships.

• Mathematical modeling: Develop kinetic models incorporating multiple parameters to predict how biochemical properties translate to cellular phenotypes.

• Proteome-wide effects: Use quantitative proteomics to assess how mistranslation affects the broader proteome, as "defects in AlaRS proofreading of Ser-tRNA^Ala lead to global dysregulation of the E. coli proteome" which may explain phenotypic complexities.

When reporting contradictory results, researchers should present both datasets transparently, propose testable hypotheses to explain discrepancies, and design experiments that bridge the gap between in vitro and in vivo systems.

What statistical approaches are most appropriate for analyzing kinetic data from multiple AlaRS variants?

When analyzing kinetic data from multiple AlaRS variants, researchers should employ statistical approaches that account for the hierarchical nature of enzyme kinetic parameters and enable meaningful comparisons across variants. The statistical framework should address both technical variability and biological significance.

For parameter estimation from primary data:

• Non-linear regression analysis should be used to fit Michaelis-Menten or more complex kinetic models to initial velocity data. Software packages like GraphPad Prism, R (with packages like 'drc'), or Python (with 'scipy.optimize') provide robust fitting algorithms.

• Bootstrapping methods are recommended for generating confidence intervals around KM and kcat estimates, providing more reliable uncertainty measurements than standard errors from regression.

• Global fitting approaches should be considered when analyzing multiple datasets simultaneously, particularly when certain parameters are expected to be conserved across experimental conditions.

For comparing parameters across variants:

• Analysis of Variance (ANOVA) followed by appropriate post-hoc tests (Tukey HSD for all pairwise comparisons or Dunnett's test for comparisons against wild-type) should be used when comparing multiple variants.

• Linear mixed-effects models can account for batch effects and repeated measurements when experiments are conducted across multiple days or with different enzyme preparations.

• Multivariate analysis techniques such as Principal Component Analysis (PCA) or hierarchical clustering can identify patterns across multiple kinetic parameters (KM, kcat, specificity constants) that may not be apparent when analyzing each parameter individually.

Data presentation should include:

• Scatter plots of individual replicates alongside means and confidence intervals

• Residual plots from model fitting to identify systematic deviations

• Correlation matrices between different kinetic parameters to identify relationships

When interpreting statistical significance, researchers should consider not only p-values but also effect sizes and biological relevance. A statistically significant difference in KM may not translate to physiologically relevant effects if the change is small relative to cellular substrate concentrations.

How might understanding AlaRS mechanisms in Acinetobacter contribute to novel antimicrobial development?

Understanding AlaRS mechanisms in Acinetobacter species presents several promising avenues for novel antimicrobial development. The essential nature of aminoacyl-tRNA synthetases for protein synthesis combined with structural and functional differences between bacterial and human orthologs makes AlaRS an attractive target for selective inhibition.

Strategic approaches for antimicrobial development include:

• Exploiting species-specific active site features: Detailed structural analysis of Acinetobacter AlaRS may reveal unique binding pocket characteristics that differ from human AlaRS, enabling the design of selective inhibitors. Structure-based drug design combining X-ray crystallography with computational docking studies can identify lead compounds that bind specifically to bacterial enzymes.

• Targeting the editing domain: The post-transfer editing mechanism of AlaRS is critical for bacterial viability and fitness . Compounds that disrupt this quality control function could induce mistranslation stress, leading to growth defects and increased antibiotic susceptibility. This approach is particularly promising as "defects in AlaRS proofreading of Ser-tRNA^Ala lead to global dysregulation of the proteome, subsequently causing defects in growth, motility, and antibiotic sensitivity" .

• Exploiting non-canonical functions: Research into aminoacyl-tRNA synthetases has revealed various functions beyond tRNA charging, including regulatory roles in gene expression and stress responses. Identifying and targeting Acinetobacter-specific non-canonical functions could provide selective antimicrobial strategies.

• Combination therapy approaches: Sublethal inhibition of AlaRS could sensitize Acinetobacter to existing antibiotics by inducing proteome stress. This hypothesis is supported by observations that editing defects alter antibiotic sensitivity profiles.

Methodological considerations for this research direction include:

• High-throughput screening platforms using purified AlaRS

• Whole-cell assays to evaluate compound penetration and activity

• Resistance development studies to assess the barrier to resistance

• Animal infection models to validate in vivo efficacy

This research direction holds particular promise for addressing multidrug-resistant Acinetobacter baumannii infections, which represent a critical challenge in healthcare settings.

What role might computational approaches play in predicting effects of AlaRS mutations in Acinetobacter species?

Computational approaches offer powerful tools for predicting the effects of AlaRS mutations in Acinetobacter species, enabling researchers to prioritize experimental efforts and gain mechanistic insights. These in silico methods span multiple scales from atomic-level simulations to systems biology models.

At the structural level, researchers can apply:

• Molecular dynamics (MD) simulations to assess how mutations affect protein flexibility, substrate binding, and domain interactions. These simulations can reveal subtle conformational changes that might impact enzyme function, particularly for the editing domain where "previously uncharacterized residues within the AlaRS proofreading domain function in quality control" .

• Quantum mechanics/molecular mechanics (QM/MM) approaches to model the chemical reaction mechanisms of amino acid activation and transfer, predicting how mutations might alter transition states and reaction energetics.

• Homology modeling when crystallographic structures are unavailable, using existing structures of AlaRS from related bacteria as templates.

At the systems level, computational approaches include:

• Flux balance analysis incorporating mistranslation rates to predict growth phenotypes

• Codon usage analysis to identify potential systematic effects on the proteome

• Evolutionary sequence analysis to distinguish conserved residues from species-specific adaptations

For practical implementation, researchers should:

• Use tools like GROMACS or NAMD for MD simulations with appropriate force fields for protein-nucleic acid interactions

• Apply machine learning approaches trained on existing mutation datasets to predict phenotypic outcomes

• Develop integrated models that connect molecular-level changes to cellular physiology

Computational predictions should be presented with appropriate validation metrics and confidence assessments. Results can be organized in mutation effect prediction tables:

These computational approaches accelerate hypothesis generation and experimental design while providing mechanistic understanding of mutation effects.