Recombinant Acinetobacter sp. Imidazole glycerol phosphate synthase subunit HisH (hisH)

What is the function of Imidazole glycerol phosphate synthase subunit HisH in Acinetobacter species?

The HisH subunit of Imidazole glycerol phosphate synthase in Acinetobacter species functions as a glutamine amidotransferase that catalyzes the fifth step in the histidine biosynthesis pathway. This enzyme is essential for catalyzing the conversion of N'-[(5'-phosphoribulosyl)formimino]-5-aminoimidazole-4-carboxamide ribonucleotide (PRFAR) to imidazole glycerol phosphate and 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR). As part of a heterodimeric complex with HisF, the HisH subunit specifically hydrolyzes glutamine to provide the ammonia needed for this reaction, making it crucial for nitrogen metabolism and amino acid biosynthesis in these bacteria.

How conserved is the hisH gene across different Acinetobacter species?

The hisH gene shows significant conservation across Acinetobacter species, though specific sequence variations exist that reflect the evolutionary relationships between species. Similar to what has been observed with other genes in Acinetobacter, such as aminoglycoside nucleotidyltransferases, sequence analysis reveals evidence of horizontal gene transfer events affecting the evolution of this gene . Phylogenetic analysis typically shows clustering of hisH sequences consistent with species boundaries, but with occasional inconsistencies that suggest horizontal gene transfer events. These transfer events parallel what has been observed with resistance genes in Acinetobacter species, where homologous recombination facilitates gene movement between different species.

What expression systems are most effective for producing recombinant Acinetobacter HisH protein?

For recombinant production of Acinetobacter HisH protein, several expression systems have proven effective, with E. coli-based systems being the most commonly employed. The pET expression system using E. coli BL21(DE3) strains typically yields high expression levels with proper folding of the HisH protein. When considering expression systems, researchers should note:

• E. coli-based systems require optimization of induction conditions (IPTG concentration, temperature, and duration) to maximize soluble protein yield

• Mammalian cell expression systems, while more complex, can provide properly folded protein with post-translational modifications when needed, similar to the high-yield expression system used for recombinant hemagglutinin protein production

• Codon optimization based on the expression host is often necessary to improve expression levels

• Co-expression with the HisF subunit may improve solubility and stability of the HisH protein

How can I design experiments to investigate horizontal gene transfer of hisH genes in Acinetobacter species?

Investigating horizontal gene transfer (HGT) of hisH genes in Acinetobacter species requires a multi-faceted experimental approach:

• Comparative genomic analysis: First, collect genomic data from multiple Acinetobacter species and perform sequence alignment of the hisH gene and surrounding regions. Look for incongruence between gene trees and species trees, which may indicate HGT events.

• Recombination detection: Employ recombination detection algorithms such as the Ordered Painting algorithm used in studies of aminoglycoside nucleotidyltransferase genes . This approach helps identify potential recombination hotspots.

• Experimental validation: Design PCR assays targeting the hisH region and flanking sequences to verify computational predictions. Include primers that span potential recombination junctions.

• Population studies: Sample Acinetobacter from different environments to assess the natural distribution of hisH variants and potential correlation with ecological niches.

• Phylogenetic analysis: Construct phylogenetic trees based on hisH sequences and compare with trees based on housekeeping genes or whole-genome phylogenies.

When analyzing results, pay particular attention to sequence regions with unusually high identity between distantly related species, as this can indicate recent HGT events, similar to the pattern observed with ant(3")-II genes in Acinetobacter, where 100% sequence identity was found in the transferred region while flanking regions showed only 74-84% identity .

What are the structural determinants of the interaction between HisH and HisF subunits in Acinetobacter?

The interaction between HisH and HisF subunits in Acinetobacter involves specific structural elements that ensure proper assembly and function of the heterodimeric enzyme complex:

• Interface composition: The interaction interface typically involves hydrophobic core residues surrounded by polar and charged amino acids that form hydrogen bonds and salt bridges between the subunits.

• Conserved motifs: Key conserved motifs in HisH include the glutamine amidotransferase catalytic triad (Cys-His-Glu) that is essential for glutamine hydrolysis.

• Allosteric communication: Structural studies are needed to identify the pathways of allosteric communication between the HisF active site (where PRFAR binding occurs) and the HisH active site (where glutamine is hydrolyzed).

• Conformational changes: Upon substrate binding, conformational changes occur that synchronize the activities of both subunits.

To investigate these structural determinants experimentally:

• Perform site-directed mutagenesis of interface residues to assess their contribution to complex stability and activity

• Use X-ray crystallography or cryo-EM to determine the 3D structure of the complex

• Apply hydrogen-deuterium exchange mass spectrometry to map dynamic interactions between the subunits

• Employ molecular dynamics simulations to predict conformational changes upon substrate binding

How does recombination frequency of hisH compare to antibiotic resistance genes in Acinetobacter species?

The recombination frequency of hisH genes can be compared to antibiotic resistance genes in Acinetobacter species by analyzing their relative positions in genome-wide recombination rate distributions. Current research on antibiotic resistance genes in Acinetobacter provides a valuable comparative framework:

• Relative recombination rates: Studies on aminoglycoside nucleotidyltransferase genes (ant(3")-II) have shown they are located in recombination hotspots. In A. baumannii, ant(3")-IIa ranked as the 126th most recombined gene out of 2282 genes, while across all Acinetobacter species carrying ant(3")-II genes, it ranked 17th out of 1694 genes . Similar analysis for hisH would determine its relative recombination frequency.

• Hotspot identification: Using algorithms like OrderedPainting to identify recombination hotspots across the genome allows quantitative comparison between hisH and known mobile resistance genes.

• Flanking region analysis: Examination of genomic regions surrounding hisH can reveal whether it resides in a recombination hotspot similar to ant(3")-II genes, which are part of a ~2 kbp recombination hotspot .

• Interspecies transfer evidence: Analysis of sequence identity across species can provide evidence of horizontal gene transfer events, similar to the observation of ant(3")-IIc being 100% identical between A. gyllenbergii NIPH 230 and A. parvus CIP 102637 .

This comparison is important as it provides insight into whether metabolic genes like hisH follow similar evolutionary patterns as resistance genes, potentially suggesting common mechanisms of bacterial genome plasticity.

What is the optimal protocol for purifying recombinant Acinetobacter HisH protein for structural studies?

For optimal purification of recombinant Acinetobacter HisH protein suitable for structural studies, the following protocol is recommended:

• Construct design:

  • Include a cleavable His-tag (preferably N-terminal)

  • Consider co-expression with HisF to improve solubility

  • Optimize codon usage for the expression host

• Expression conditions:

  • Transform into E. coli BL21(DE3) or Rosetta(DE3) for rare codon supplementation

  • Grow at 37°C until OD₆₀₀ reaches 0.6-0.8

  • Induce with 0.1-0.5 mM IPTG

  • Shift to 18-20°C for overnight expression to maximize soluble protein

• Lysis and initial purification:

  • Resuspend cells in buffer containing 50 mM Tris-HCl pH 8.0, 300 mM NaCl, 5% glycerol, 5 mM β-mercaptoethanol, and protease inhibitors

  • Lyse cells by sonication or high-pressure homogenization

  • Clarify lysate by centrifugation at 20,000 × g for 30 minutes

• Chromatography steps:

  • Immobilized metal affinity chromatography (IMAC) using Ni-NTA resin

  • Tag cleavage with TEV protease during overnight dialysis

  • Second IMAC to remove uncleaved protein and TEV protease

  • Size exclusion chromatography using a Superdex 75 or 200 column

• Quality control:

  • Assess purity by SDS-PAGE (>95% for structural studies)

  • Verify identity by mass spectrometry

  • Check for proper folding using circular dichroism

  • Perform dynamic light scattering to confirm monodispersity

• Storage:

  • Concentrate to 10-20 mg/ml for crystallization

  • Flash-freeze aliquots in liquid nitrogen

  • Store at -80°C with minimal freeze-thaw cycles

This protocol should yield high-purity protein suitable for crystallization trials or other structural studies.

How can I design an experimental assay to measure the enzymatic activity of recombinant HisH from Acinetobacter?

To design a robust experimental assay for measuring the enzymatic activity of recombinant HisH from Acinetobacter, implement the following methodology:

• Assay principle:
  The glutamine amidotransferase activity of HisH can be measured by either:

  • Coupled assay tracking glutamate production

  • Direct measurement of ammonia release

  • Monitoring the complete IGP synthase reaction when co-expressed with HisF

• Spectrophotometric coupled assay:

  • Mix purified HisH (and HisF if testing the complete reaction) with reaction buffer (50 mM HEPES pH 7.5, 100 mM NaCl, 5 mM MgCl₂)

  • Add glutamine (typically 1-10 mM)

  • For complete reaction, add PRFAR substrate (0.1-1 mM)

  • Include glutamate dehydrogenase, NAD+, and α-ketoglutarate to couple glutamate production to NADH formation

  • Monitor absorbance increase at 340 nm as NADH is produced

• Experimental design considerations:

  • Include appropriate controls:

    • No enzyme control

    • Heat-inactivated enzyme control

    • Known active enzyme as positive control

  • Determine enzyme kinetics parameters (Km and kcat)

  • Test pH and temperature optima

  • Assess effects of potential inhibitors or activators

• Data analysis:

  • Calculate reaction rates from the linear portion of progress curves

  • Generate Michaelis-Menten plots to determine kinetic parameters

  • Use regression analysis to determine the coefficient of determination (R²) for data quality assessment

  • Apply appropriate statistical methods to compare different conditions

• Validation:

  • Test the effect of site-directed mutations in the catalytic triad

  • Compare activity with and without the HisF subunit

  • Verify reproducibility across multiple protein preparations

When designing this experimental assay, follow the principles of good experimental design as outlined in research methodology guidelines , including proper replication, randomization, and blinding when possible.

What statistical approaches should I use to analyze sequence variation in hisH genes across clinical and environmental Acinetobacter isolates?

When analyzing sequence variation in hisH genes across clinical and environmental Acinetobacter isolates, employ the following statistical approaches:

• Sequence diversity metrics:

  • Calculate nucleotide diversity (π) within and between populations

  • Determine haplotype diversity (Hd) and the number of haplotypes

  • Compute Tajima's D to test for selection or demographic effects

  • Measure Ka/Ks ratios to detect potential selection pressures

• Population structure analysis:

  • Perform Analysis of Molecular Variance (AMOVA) to partition genetic variation

  • Apply population differentiation measures (FST) between clinical and environmental isolates

  • Use Structure or BAPS software to identify potential population substructures

  • Create Minimum Spanning Networks to visualize relationships between haplotypes

• Recombination detection:

  • Implement statistical methods like PHI test, NSS, or MaxChi to detect recombination events

  • Apply the Ordered Painting algorithm used in studies of other Acinetobacter genes

  • Calculate linkage disequilibrium decay with physical distance

• Phylogenetic analyses:

  • Construct Maximum Likelihood or Bayesian phylogenetic trees

  • Perform bootstrap analysis or calculate posterior probabilities to assess node support

  • Compare hisH gene trees with species trees to identify inconsistencies suggesting HGT

  • Test alternative tree topologies using likelihood ratio tests

• Statistical testing and data visualization:

  • Apply appropriate parametric or non-parametric tests (t-test, Mann-Whitney U test) to compare metrics between groups

  • Use regression analysis to determine correlations between genetic and phenotypic variables

  • Calculate coefficients of determination (R²) to assess the strength of correlations

  • Create Principal Component Analysis (PCA) or Multidimensional Scaling (MDS) plots to visualize relationships

• Sample size considerations:

  • Ensure adequate sampling of both clinical and environmental isolates

  • Perform power analysis to determine if the sample size is sufficient

  • Consider rarefaction analysis to account for uneven sampling

These statistical approaches will provide a comprehensive analysis of hisH sequence variation and help identify patterns related to ecology, pathogenicity, and evolutionary history of Acinetobacter species.

How does the genetic context of hisH differ between pathogenic and non-pathogenic Acinetobacter species?

The genetic context of hisH genes in Acinetobacter species shows notable differences between pathogenic and non-pathogenic strains, providing insights into their evolution and functional relationships:

• Operon structure variation:

  • In pathogenic species like A. baumannii, the hisH gene often exists in a complete histidine biosynthesis operon with conserved gene order

  • Non-pathogenic environmental Acinetobacter species may show alternative operon arrangements or partial operons

  • The proximity of regulatory elements differs, potentially affecting expression patterns

• Flanking mobile genetic elements:

  • Pathogenic strains often show evidence of mobile genetic elements surrounding metabolic genes, similar to what has been observed with resistance genes

  • The presence of insertion sequences or transposable elements near hisH may correlate with pathogenicity

  • These mobile elements can facilitate horizontal gene transfer between species

• Recombination hotspots:

  • Analysis should determine whether hisH genes are located in recombination hotspots in different species

  • Similar to ant(3")-II genes, which are located in recombination hotspots enabling frequent transfer between Acinetobacter species

  • The intensity of DNA transfer at the hisH locus compared to the global genome recombination rate can be quantified

• Synteny analysis:

  • Comparative analysis of gene order conservation around hisH across species

  • Identification of species-specific genes adjacent to hisH

  • Assessment of whether genomic islands are associated with hisH in pathogenic strains

What experimental approaches can determine if hisH variants contribute to virulence or antibiotic resistance in Acinetobacter?

To determine if hisH variants contribute to virulence or antibiotic resistance in Acinetobacter, implement the following experimental approaches:

• Genotype-phenotype correlation studies:

  • Sequence hisH from diverse clinical and environmental isolates

  • Measure antibiotic susceptibility profiles using standardized methods

  • Assess virulence in infection models

  • Perform statistical analysis to identify correlations between specific hisH variants and phenotypes

• Gene knockout and complementation studies:

  • Generate hisH knockout mutants in different Acinetobacter strains

  • Complement with different hisH variants

  • Compare phenotypes between wild-type, knockout, and complemented strains

  • Measure growth rates in histidine-limited media to confirm functional differences

• Transcriptomic and proteomic analyses:

  • Compare gene expression profiles between strains with different hisH variants

  • Identify differentially expressed genes related to virulence or resistance

  • Use RNA-seq to detect potential regulatory effects of hisH variants

  • Perform proteomic analysis to detect changes in protein abundance

• In vivo infection models:

  • Test virulence of strains with different hisH variants in appropriate animal models

  • Measure bacterial burden, host response, and survival rates

  • Evaluate competitive fitness using mixed infections with labeled strains

  • Assess in vivo antibiotic efficacy against different variants

• Structural and biochemical characterization:

  • Purify recombinant HisH proteins with different variants

  • Compare enzymatic activities using standardized assays

  • Determine structural differences using X-ray crystallography or cryo-EM

  • Assess protein stability and interaction with HisF subunit

• Experimental evolution:

  • Subject Acinetobacter strains to selective pressures (antibiotics, nutrient limitation)

  • Monitor changes in hisH sequence over time

  • Correlate evolved hisH variants with phenotypic adaptations

  • Test fitness costs of acquired mutations

How can protein engineering approaches be used to enhance the stability or activity of recombinant Acinetobacter HisH?

Protein engineering approaches can significantly enhance the stability and activity of recombinant Acinetobacter HisH through the following methodologies:

• Rational design strategies:

  • Identify and modify surface-exposed hydrophobic residues to improve solubility

  • Introduce disulfide bridges at strategic positions to enhance thermostability

  • Optimize the charge distribution on the protein surface

  • Strengthen the interface between HisH and HisF subunits by introducing additional hydrogen bonds or salt bridges

• Directed evolution approaches:

  • Error-prone PCR to generate random mutations throughout the hisH gene

  • DNA shuffling between hisH genes from different Acinetobacter species

  • Create focused mutation libraries targeting the active site or subunit interface

  • Implement high-throughput screening assays to identify improved variants

• Computational design methods:

  • Use molecular dynamics simulations to identify flexible regions that could be stabilized

  • Apply energy minimization algorithms to predict stabilizing mutations

  • Employ consensus design approaches based on multiple sequence alignments

  • Use machine learning algorithms trained on enzyme variants to predict beneficial mutations

• Experimental validation:

  • Measure thermal stability using differential scanning fluorimetry

  • Determine pH stability profiles for engineered variants

  • Assess long-term storage stability at different temperatures

  • Compare enzymatic activity using standardized assays described in section 3.2

• Structural analysis:

  • Obtain crystal structures of improved variants to understand molecular basis of enhancement

  • Use hydrogen-deuterium exchange mass spectrometry to map dynamic regions

  • Compare conformational ensembles between wild-type and engineered variants

When designing experimental procedures for protein engineering, follow established experimental design principles , including proper controls and statistical analysis methods to ensure valid comparisons between protein variants.

What are the implications of horizontal gene transfer for designing experiments with recombinant HisH across different Acinetobacter species?

The prevalence of horizontal gene transfer (HGT) in Acinetobacter species has important implications for experimental design when working with recombinant HisH across different species:

• Selection of representative variants:

  • Perform phylogenetic analysis to identify distinct HisH clades

  • Include representatives from each major clade rather than assuming species-specific patterns

  • Consider potential recombination events when interpreting functional differences

  • Recognize that HisH variants may not follow species boundaries due to HGT, similar to what has been observed with resistance genes

• Experimental controls and references:

  • Use multiple reference strains rather than a single type strain

  • Include strains with well-characterized recombination histories

  • Consider using synthetic gene constructs based on consensus sequences

  • Create chimeric proteins to study the effects of specific recombination events

• Functional interpretation caveats:

  • Avoid attributing functional differences to species-specific adaptations without considering HGT

  • Analyze flanking genes that may have co-transferred with hisH during recombination

  • Consider potential co-adaptation between HisH and HisF subunits from different sources

  • Test combinations of HisH and HisF from different species to assess compatibility

• Evolutionary context for interpretation:

  • Map experimental results onto reconciled gene and species trees

  • Identify potential donor-recipient relationships

  • Consider selective pressures that might drive HGT of metabolic genes

  • Compare patterns observed in hisH with those seen in resistance genes like ant(3")-II

• Documentation and reporting standards:

  • Clearly report the exact strain and sequence used for each experiment

  • Provide complete phylogenetic context when publishing results

  • Deposit all sequences in public databases with appropriate metadata

  • Describe any evidence of recombination that might affect interpretation

Understanding the implications of HGT ensures that experiments with recombinant HisH are designed and interpreted appropriately, avoiding misconceptions about species-specific properties that may actually result from gene transfer events.

How should I analyze and interpret discrepancies in experimental results between different Acinetobacter HisH variants?

When faced with discrepancies in experimental results between different Acinetobacter HisH variants, apply the following analytical framework:

• Systematic verification of experimental conditions:

  • Ensure protein purity is equivalent across all variants (>95% for accurate comparisons)

  • Verify protein folding using circular dichroism or fluorescence spectroscopy

  • Confirm that storage conditions haven't differentially affected protein samples

  • Re-sequence expression constructs to rule out unintended mutations

• Statistical analysis of reproducibility:

  • Calculate coefficients of determination (R²) between replicate experiments

  • Apply appropriate statistical tests to determine if differences are significant

  • Use regression analysis to identify potential correlations between protein variants and functional parameters

  • Consider power analysis to ensure sample size is sufficient for detecting true differences

• Structural context interpretation:

  • Map variant residues onto protein structure to assess potential functional impacts

  • Consider effects on protein dynamics and conformational changes

  • Evaluate potential allosteric effects that might explain functional differences

  • Examine subunit interface residues that might affect HisH-HisF interactions

• Evolutionary context analysis:

  • Consider the evolutionary history of the variants, including potential horizontal gene transfer events

  • Determine if variants cluster with functional differences according to phylogeny

  • Assess if discrepancies correlate with ecological niches or pathogenicity

  • Evaluate potential co-evolution with interacting partners

• Resolving conflicting results:

  • Design additional experiments targeting specific hypotheses to explain discrepancies

  • Consider employing alternative assay methods to cross-validate findings

  • Isolate variables by creating chimeric proteins to pinpoint determinants of functional differences

  • Collaborate with structural biologists or computational biologists to gain mechanistic insights

• Reporting guidelines for discrepancies:

  • Transparently describe all observed discrepancies

  • Present alternative interpretations of conflicting results

  • Propose testable hypotheses to resolve contradictions

  • Avoid overinterpreting limited data when discrepancies exist

This analytical framework helps researchers systematically address experimental discrepancies, transforming them from challenges into opportunities for deeper mechanistic understanding of HisH function and evolution.

What statistical methods should I use to compare recombination frequencies of hisH with other conserved genes in Acinetobacter genomes?

To rigorously compare recombination frequencies of hisH with other conserved genes in Acinetobacter genomes, implement the following statistical methods:

• Recombination detection and quantification:

  • Apply the Ordered Painting algorithm as used in studies of ant(3")-II genes

  • Calculate the rank of hisH in terms of recombination frequency among all common genes

  • Determine if hisH falls within the range of predicted recombination hotspots

  • Use multiple recombination detection methods (PHI test, MaxChi, NSS) for robust analysis

• Comparative metrics development:

  • Create a normalized recombination index that accounts for gene length and conservation level

  • Calculate the ratio of recombination events to nucleotide diversity

  • Measure recombination frequency relative to flanking genes

  • Quantify the intensity of DNA transfer at the hisH locus compared to the global genome recombination rate

• Statistical comparison approaches:

  • Group genes into functional categories and compare recombination rates between categories using ANOVA

  • Apply non-parametric tests (Kruskal-Wallis, Mann-Whitney U) for non-normally distributed data

  • Use permutation tests to establish significance thresholds for recombination hotspots

  • Create null distributions by random sampling of genomic regions of similar size and conservation

• Correlation analyses:

  • Test for correlation between recombination frequency and functional importance using regression analysis

  • Calculate coefficients of determination (R²) to quantify the strength of correlations

  • Perform multivariate analysis to identify factors associated with high recombination rates

  • Employ machine learning approaches to identify genetic or structural features predictive of recombination hotspots

• Visual representation of comparative data:

  • Create genome-wide recombination frequency maps highlighting hisH and other genes of interest

  • Plot the distribution of recombination rates across the genome with confidence intervals

  • Use heatmaps to visualize recombination patterns across multiple Acinetobacter species

  • Present comparative data in tables rather than lists for improved clarity

• Statistical power considerations:

  • Calculate minimum detectable effect sizes based on the number of genomes analyzed

  • Perform bootstrap analysis to assess the robustness of recombination frequency estimates

  • Consider the impact of sampling bias on recombination detection

  • Use simulation studies to validate statistical methods

These statistical approaches provide a comprehensive framework for comparing recombination frequencies between hisH and other conserved genes, enabling researchers to place hisH in the broader context of Acinetobacter genome evolution.