Recombinant Salmonella paratyphi C Elongation factor G (fusA), partial

What is Salmonella paratyphi C and how does it relate to other Salmonella typhoid agents?

Salmonella paratyphi C is a human-restricted pathogen that causes paratyphoid fever, a systemic infection similar to typhoid fever. It belongs to the group of typhoidal Salmonella serovars along with S. typhi and S. paratyphi A and B. While these pathogens cause similar clinical manifestations, they have distinct evolutionary histories. Genomic analyses reveal that S. paratyphi C is more closely related to S. choleraesuis (primarily a swine pathogen) than to other human-adapted typhoid agents like S. typhi or S. paratyphi A . This suggests that the typhoid-causing ability evolved through convergent evolution rather than from a common typhoid ancestor . S. paratyphi C likely diverged from a common ancestor with S. choleraesuis relatively recently by adapting to the human host and accumulating genomic changes that facilitated this host shift .

What is Elongation Factor G (fusA) and what is its significance in bacterial research?

Elongation Factor G (fusA) is an essential protein in bacterial protein synthesis that catalyzes the translocation step during translation. While not explicitly detailed in the search results, this protein is crucial for bacterial survival and is highly conserved across bacterial species. In the context of S. paratyphi C research, studying fusA is significant because:

• As an essential gene, it provides insights into core bacterial functions

• Its conservation makes it useful for phylogenetic analyses to understand evolutionary relationships between Salmonella strains

• Structural differences in fusA between bacterial and eukaryotic elongation factors make it a potential target for antimicrobial development

• Recombinant expression allows for detailed biochemical characterization and structure-function studies

How can I clone the fusA gene from Salmonella paratyphi C for recombinant expression?

Methodological approach:

• Extract genomic DNA from S. paratyphi C using standard bacterial genomic DNA isolation protocols

• Design primers based on the published S. paratyphi C genome sequence (RKS4594 strain has a fully sequenced genome of 4,833,080 bp)

• Consider the genetic relationship between S. paratyphi C and S. choleraesuis when designing primers, as they share high sequence identity (they share 4346 genes, accounting for over 97% of their genomes)

• Amplify the fusA gene or its partial sequence using PCR

• Clone the amplified product into an appropriate expression vector with a tag for purification

• Transform into a suitable E. coli expression strain

• Induce expression and purify using affinity chromatography

What are the genomic characteristics of Salmonella paratyphi C compared to other Salmonella strains?

S. paratyphi C has several distinctive genomic features:

• Genome size: The chromosome is 4,833,080 bp with a G+C content of 52.2%

• It contains a virulence plasmid (pSPCV) of 55,414 bp

• The genome includes 4,578 chromosomal and 62 plasmid-encoded intact coding sequences

• It contains 149 chromosomal and 3 plasmid pseudogenes

• Compared to S. typhimurium LT2, S. paratyphi C RKS4594 has four insertions totaling 176 kb (including the 90 kb SPI7) and seven deletions totaling 165 kb

• The genome exhibits structural rearrangements, including an inversion of 1602 kb covering the ter region and the translocation of the 43 kb I-CeuI F fragment

Table 1. Comparison of S. paratyphi C RKS4594 genome features:

The data is adapted from the analysis of S. paratyphi C strain RKS4594 .

How can I analyze potential functional differences between recombinant fusA from S. paratyphi C and other Salmonella serovars?

Methodological approach:

• Express and purify recombinant fusA proteins from different Salmonella serovars (S. paratyphi C, S. typhi, S. choleraesuis)

• Perform comparative biochemical characterization:

  • Translation efficiency assays measuring GTP hydrolysis rates

  • Ribosome binding affinity using surface plasmon resonance

  • Structural analysis using X-ray crystallography or cryo-EM

• Conduct computational analyses:

  • Multiple sequence alignment to identify key differences in amino acid sequence

  • Homology modeling to predict structural differences

  • Molecular dynamics simulations to assess potential functional implications

• Analyze the evolutionary relationship of fusA genes in the context of the divergent and convergent evolution patterns observed between S. paratyphi C and other typhoid agents

• Consider that S. paratyphi C has experienced "enormous selection pressures during its adaptation to man" as suggested by differential nucleotide substitutions compared to S. choleraesuis , which may have affected essential genes like fusA

How might genomic rearrangements in S. paratyphi C influence the expression and function of essential genes like fusA?

S. paratyphi C exhibits significant genomic plasticity, with different strains showing diverse genome structures . These rearrangements might affect essential gene expression in several ways:

• Altered gene proximity to replication origin: Genome inversions and translocations can change a gene's position relative to oriC, potentially affecting its expression timing and level during the cell cycle

• Modified operon structure: Rearrangements may disrupt or create new operons, affecting co-transcription of genes

• Changed regulatory context: Essential genes like fusA may come under the influence of different regulatory elements after genomic rearrangements

• Impact on supercoiling: Large inversions, like the 1602 kb inversion observed in some S. paratyphi C strains , can alter local DNA supercoiling, affecting transcription

• Potential impact on translation: If tRNA genes are affected by rearrangements, this could influence translation efficiency of specific codons in fusA

Research approaches to investigate these effects include:

• Comparative transcriptomics of strains with different genomic arrangements

• Reporter gene assays at different genomic locations

• Analysis of codon usage in fusA relative to the tRNA pool in different strains

What strategies can optimize the expression and purification of functional recombinant S. paratyphi C fusA protein?

Methodological approach:

• Expression optimization:

  • Test multiple expression vectors with different promoters (T7, tac, araBAD)

  • Evaluate various E. coli expression strains (BL21(DE3), Rosetta, Arctic Express)

  • Optimize induction conditions (temperature, IPTG concentration, induction time)

  • Consider codon optimization based on S. paratyphi C preference for rare codons

• Solubility enhancement:

  • Test fusion partners (MBP, SUMO, thioredoxin)

  • Evaluate the effect of chaperone co-expression

  • Consider expressing functional domains separately if the full-length protein is problematic

• Purification strategy:

  • Design a two-step purification protocol: affinity chromatography followed by size exclusion

  • Optimize buffer conditions (pH, salt concentration, stabilizing additives)

  • Implement quality control using dynamic light scattering to assess aggregation

• Functional validation:

  • Develop in vitro translation assays using S. paratyphi C ribosomes

  • Measure GTPase activity compared to commercially available EF-G

  • Assess ribosome binding and translocation efficiency

How can recombinant fusA be used to study the evolutionary relationships between S. paratyphi C and other Salmonella serovars?

The evolutionary relationship between S. paratyphi C and other Salmonella serovars shows interesting patterns. S. paratyphi C is more closely related to S. choleraesuis (a swine pathogen) than to other human-adapted typhoid agents . This suggests S. paratyphi C emerged through adaptive evolution from an animal pathogen to become human-restricted. Essential genes like fusA can serve as molecular markers in evolutionary studies:

• Sequence-based approaches:

  • Conduct phylogenetic analysis of fusA sequences across multiple Salmonella serovars

  • Calculate dN/dS ratios to identify selection pressures (S. paratyphi C shows greater dN than dS substitutions compared to S. choleraesuis, indicating positive selection during host adaptation)

  • Compare rates of synonymous substitutions to estimate divergence times

• Structure-function analysis:

  • Identify amino acid changes specific to human-adapted strains

  • Assess functional implications through site-directed mutagenesis

  • Perform complementation studies in fusA mutants

• Contextual genomic analysis:

  • Analyze the genomic context of fusA in different serovars considering the genomic rearrangements observed in S. paratyphi C

  • Investigate if fusA is part of the core genome shared between S. paratyphi C and S. choleraesuis (they share 4346 genes)

What are the implications of host adaptation on essential genes like fusA in S. paratyphi C?

S. paratyphi C has undergone substantial genomic changes during adaptation to humans from a common ancestor with S. choleraesuis . Essential genes like fusA may reflect these adaptation processes:

• Selective pressures:

  • The higher ratio of non-synonymous to synonymous substitutions between S. paratyphi C and S. choleraesuis suggests positive selection during host adaptation

  • Essential genes might show subtle changes that maintain function while optimizing for the human host environment

• Codon usage adaptation:

  • Human adaptation may drive codon optimization in highly expressed genes like fusA

  • Analysis of codon adaptation index (CAI) in fusA compared to other housekeeping genes can reveal adaptation signatures

• Pseudogenization and gene retention:

  • While S. paratyphi C has 149 chromosomal pseudogenes , essential genes like fusA are maintained

  • The maintenance pattern of translation machinery genes contrasted with pseudogenization patterns can reveal adaptation priorities

• Methodological approaches:

  • Comparative analysis of fusA sequences from multiple clinical isolates of S. paratyphi C

  • Functional complementation studies using fusA from different serovars

  • In vitro translation assays comparing kinetic parameters of fusA from human-adapted versus animal-adapted strains

What are common challenges in expressing recombinant S. paratyphi C fusA and how can they be addressed?

The expression of large bacterial proteins like Elongation Factor G (typically around 77 kDa) can present several challenges:

• Protein solubility issues:

  • Problem: Recombinant fusA forms inclusion bodies

  • Solution: Lower induction temperature (16-20°C), reduce inducer concentration, use solubility-enhancing tags like MBP or SUMO, or co-express with chaperones

• Incomplete translation:

  • Problem: Truncated protein products due to rare codons or mRNA secondary structure

  • Solution: Use Rosetta or CodonPlus strains that provide rare tRNAs, or optimize codons for E. coli expression

• Protein activity loss:

  • Problem: Purified protein lacks GTPase or translation activity

  • Solution: Optimize buffer conditions (test different pH ranges, add stabilizing agents like glycerol or arginine), purify with GTP or GDP bound, minimize freeze-thaw cycles

• Ribosome contamination:

  • Problem: Native affinity of fusA for ribosomes leads to co-purification

  • Solution: Include high salt wash steps (500 mM NaCl), add GDP or GTP to dissociate ribosome complexes, consider ion exchange chromatography after affinity purification

How can I assess whether my recombinant S. paratyphi C fusA protein is properly folded and functional?

Methodological approach:

• Structural integrity assessment:

  • Circular dichroism (CD) spectroscopy to confirm secondary structure content

  • Thermal shift assays to determine protein stability

  • Size exclusion chromatography to verify monodispersity

  • Limited proteolysis to assess compact folding

• Functional assays:

  • GTPase activity assay (colorimetric phosphate release)

  • Ribosome binding assay using surface plasmon resonance or fluorescence anisotropy

  • In vitro translation assay using purified translation components

  • Poly(Phe) synthesis assay as a minimal translation system

• Comparative benchmarking:

  • Compare activity parameters with commercially available EF-G

  • Assess activity relative to native S. paratyphi C EF-G (if available)

  • Compare with recombinant EF-G from related Salmonella serovars

• Biophysical characterization:

  • Differential scanning fluorimetry to assess nucleotide binding

  • Intrinsic fluorescence to monitor conformational changes upon GTP binding

How can I investigate potential differences in fusA expression levels across diverse S. paratyphi C genomic structures?

Given the diverse genome structures observed in wild-type S. paratyphi C strains , expression of essential genes like fusA might vary:

• Strain collection and characterization:

  • Obtain diverse clinical isolates of S. paratyphi C

  • Perform I-CeuI digestion and PFGE to determine genome arrangements

  • Sequence the fusA gene and promoter regions to identify potential variations

• Expression analysis:

  • qRT-PCR to quantify fusA mRNA levels across strains with different genome structures

  • Western blotting with anti-EF-G antibodies to compare protein levels

  • Ribosome profiling to assess translation efficiency of fusA

• Promoter activity analysis:

  • Clone promoter regions from different strains into reporter constructs

  • Measure reporter activity under various growth conditions

  • Perform 5' RACE to identify potential alternative transcription start sites

• Context analysis:

  • Map the position of fusA relative to origin and terminus in strains with different genome arrangements

  • Analyze if rearrangements have placed fusA near genomic islands or other regulatory elements

  • Consider effects of the translocation of I-CeuI fragments (as seen in some strains) on fusA expression

How can recombinant S. paratyphi C fusA contribute to understanding typhoid pathogenesis evolution?

The evolutionary history of typhoid-causing Salmonella suggests convergent evolution rather than divergence from a common typhoid ancestor . Recombinant fusA can contribute to understanding this evolution:

• Comparative functional studies:

  • Express and characterize fusA from multiple typhoid-causing Salmonella (S. typhi, S. paratyphi A, B, C)

  • Compare biochemical properties and efficiency in translation

  • Determine if convergent functional adaptations exist despite different genetic backgrounds

• Host adaptation signatures:

  • Analyze if fusA shows similar or different adaptation patterns across independently evolved typhoid agents

  • Identify if specific domains or residues are under similar selection pressures in different typhoid agents

• Evolution rate analysis:

  • Calculate evolutionary rates of fusA compared to other housekeeping genes

  • Determine if essential genes like fusA evolve at different rates in typhoid versus non-typhoid Salmonella

  • Correlate with the "enormous selection pressures" identified during S. paratyphi C adaptation to humans

• Structure-function relationships:

  • Use structural biology approaches to identify if similar functional adaptations occurred through different structural modifications in different typhoid agents

What are the implications of S. paratyphi C genome plasticity for essential gene function and evolution?

S. paratyphi C strains exhibit remarkable genome plasticity with diverse structures among wild-type strains . This plasticity has several implications for essential genes like fusA:

• Genome structure and gene expression correlation:

  • Different genome arrangements might affect essential gene expression patterns

  • The inversions and translocations observed in S. paratyphi C may affect gene dosage effects during replication

• Evolutionary constraints:

  • Despite genomic rearrangements, essential genes must maintain function

  • Investigate if rearrangements occur preferentially in regions that don't disrupt essential gene expression

• Adaptation mechanisms:

  • Genomic plasticity may provide a mechanism for S. paratyphi C to adapt to host environments

  • Essential genes like fusA may maintain core function while allowing flexibility in other genome regions

• Methodological approaches:

  • Compare transcriptomes of strains with different genome structures

  • Analyze if recombination breakpoints avoid essential gene clusters

  • Investigate if strains with different genome arrangements show differences in growth rates or virulence that might correlate with essential gene expression

How can structural studies of recombinant S. paratyphi C fusA inform potential antimicrobial development?

Structural studies of recombinant fusA from S. paratyphi C could reveal:

• Unique structural features:

  • Crystallize and determine the structure of S. paratyphi C fusA

  • Compare with structures from other bacterial and eukaryotic elongation factors

  • Identify unique pockets or interfaces that could be targeted by antibiotics

• Functional domain analysis:

  • Characterize the GTP-binding domain structure and dynamics

  • Analyze the ribosome interaction interface

  • Identify regions that differ between bacterial and human elongation factors

• Drug development approaches:

  • Perform in silico screening against identified unique pockets

  • Design peptidomimetics targeting fusA-ribosome interfaces

  • Develop assays to screen for inhibitors of S. paratyphi C fusA function

• Resistance mechanisms analysis:

  • Map known fusidic acid resistance mutations on the S. paratyphi C fusA structure

  • Predict potential resistance hotspots specific to typhoid agents

  • Design inhibitors that target conserved regions less prone to resistance-conferring mutations

How should functional data from recombinant S. paratyphi C fusA be interpreted in the context of its evolutionary history?

When analyzing functional data from recombinant S. paratyphi C fusA, consider:

• Evolutionary context:

  • S. paratyphi C evolved from a common ancestor with S. choleraesuis relatively recently

  • There was positive selection during adaptation to humans (higher dN than dS)

  • Essential gene function is maintained despite genome rearrangements and plasticity

• Comparative benchmarks:

  • Compare functional parameters with those from closely related S. choleraesuis fusA

  • Contrast with more distantly related S. typhi fusA

  • Consider if functional differences reflect adaption to human hosts

• Methodological approach:

  • Normalize activity measurements across different experimental conditions

  • Use multiple assays to build a comprehensive functional profile

  • Consider the effect of experimental conditions on activity measurements

• Evolutionary rate analysis:

  • Analyze if fusA evolves at different rates in different Salmonella lineages

  • Determine if specific domains are under different selective pressures

  • Compare with evolutionary rates of other translation factors

What statistical approaches are most appropriate for analyzing comparative fusA sequence and functional data across Salmonella serovars?

• Sequence analysis statistics:

  • Maximum likelihood methods for phylogenetic tree construction

  • Bayesian approaches to estimate divergence times

  • PAML analysis to calculate dN/dS ratios and identify sites under positive selection

  • Codon-based Z-test of selection to compare evolutionary pressures

• Structural comparison methods:

  • Root mean square deviation (RMSD) calculation for structural alignments

  • Principal component analysis to identify major structural variations

  • Normal mode analysis to compare dynamic properties

• Functional data analysis:

  • ANOVA with post-hoc tests for comparing activity parameters across multiple serovars

  • Linear mixed-effects models when analyzing data with potential batch effects

  • Bootstrapping approaches for robust confidence interval estimation

  • Correlation analysis between sequence divergence and functional parameters

• Integrated analysis approaches:

  • Machine learning methods to identify sequence features that correlate with functional differences

  • Network analysis to place fusA in the context of other translation factors

  • Clustering methods to identify patterns in multi-parameter datasets

When interpreting results, consider the close relationship between S. paratyphi C and S. choleraesuis (sharing 97% of genes) compared to other Salmonella serovars.