Recombinant Shigella boydii serotype 18 Phosphoserine aminotransferase (serC)

How should researchers optimize expression and purification of recombinant serC from Shigella boydii serotype 18?

For optimal expression and purification of recombinant Shigella boydii serotype 18 serC, researchers should consider:

• Expression System: The protein has been successfully expressed in yeast expression systems that can manage proper folding of bacterial proteins .

• Purification Protocol:

  • Use affinity chromatography with appropriate tags (determined during the manufacturing process)

  • Aim for >85% purity as verified by SDS-PAGE

  • Consider size exclusion chromatography as a second purification step to improve homogeneity

• Storage Conditions:

  • Store at -20°C for short-term use

  • For extended storage, maintain at -20°C or -80°C

  • Avoid repeated freeze-thaw cycles

  • Working aliquots can be stored at 4°C for up to one week

• Reconstitution:

  • Briefly centrifuge the vial before opening

  • Reconstitute in deionized sterile water to 0.1-1.0 mg/mL

  • Add glycerol to a final concentration of 5-50% (optimally 50%) for long-term storage

  • Aliquot to minimize freeze-thaw cycles

What are the distinguishing biochemical characteristics of Shigella boydii serotypes?

While the search results focus specifically on serotype 18 phosphoserine aminotransferase, general biochemical characteristics of Shigella boydii include:

Understanding these biochemical properties is essential for confirming the identity of S. boydii isolates before proceeding with specific serC characterization studies .

What structural analysis techniques are most effective for characterizing the active site of Shigella boydii serotype 18 Phosphoserine aminotransferase?

For comprehensive structural characterization of the active site, researchers should employ a multi-method approach:

• X-ray Crystallography:

  • Grow protein crystals using hanging drop vapor diffusion

  • Collect diffraction data at resolutions better than 2.0 Å

  • Process with programs like XDS, CCP4, or PHENIX

  • Molecular replacement using related aminotransferase structures (PLP-dependent enzymes)

• NMR Spectroscopy:

  • Similar to techniques used in characterizing S. boydii O antigens

  • Employ two-dimensional COSY, TOCSY, ROESY experiments

  • Use H-detected 1H, 13C and 1H, 31P HMQC for phosphate group interactions

• Molecular Dynamics Simulations:

  • Simulate substrate binding and catalytic mechanisms

  • Identify key residues involved in substrate specificity

  • Predict effects of site-directed mutagenesis

• Site-Directed Mutagenesis:

  • Target conserved catalytic residues (based on sequence alignments with other phosphoserine aminotransferases)

  • Measure kinetic parameters of mutants to determine functional significance

  • Use the RED recombination system of phage lambda for precise genetic modifications

How can serC gene sequence analysis contribute to understanding Shigella boydii evolution and pathogenicity?

Genetic analysis of the serC gene provides valuable insights into evolutionary relationships and pathogenicity:

• Comparative Genomics Approach:

  • Analyze serC sequences across all Shigella boydii serotypes (1-20) and related Enterobacteriaceae

  • Construct phylogenetic trees to establish evolutionary relationships

  • Examine conservation of catalytic domains versus variable regions

• Methodological Steps:

  • Extract genomic DNA using standard protocols

  • Amplify serC using targeted PCR or whole-genome sequencing

  • Perform multiple sequence alignment with MUSCLE or CLUSTALW

  • Calculate genetic distances and construct phylogenetic trees using neighbor-joining, maximum likelihood, or Bayesian methods

  • Map gene locations relative to pathogenicity islands or mobile genetic elements

• Research Findings from Related Studies:

  • S. boydii O antigen gene clusters show evidence of horizontal gene transfer

  • Higher sequence similarity has been observed between some S. boydii strains and V. cholerae than between different Shigella species

  • Molecular serotyping through RFLP analysis of O-antigen biosynthesis loci can distinguish between serotypes

• Applications:

  • Develop molecular markers for epidemiological tracking

  • Identify potential targets for vaccine development

  • Understand mechanisms of antimicrobial resistance acquisition

What are the recommended protocols for studying enzyme kinetics of Shigella boydii serC compared to other phosphoserine aminotransferases?

For rigorous enzyme kinetic characterization:

• Standard Activity Assay:

  • Measure the conversion of 3-phosphohydroxypyruvate to L-phosphoserine

  • Monitor NADH oxidation in a coupled assay system

  • Perform at physiological pH (7.2-7.6) and temperature (37°C)

  • Include PLP (pyridoxal phosphate) as an essential cofactor

• Comparative Kinetic Analysis:

• Comparative Analysis Framework:

  • Compare with serC from other Shigella species and E. coli

  • Analyze differences in substrate preference, reaction rate, and regulatory patterns

  • Correlate kinetic differences with amino acid substitutions in sequence alignments

• Special Considerations:

  • Ensure PLP saturation in all assays

  • Account for potential product inhibition

  • Consider using isothermal titration calorimetry for thermodynamic parameters

How does serC contribute to Shigella boydii metabolism and virulence?

The phosphoserine aminotransferase (serC) plays critical roles in both metabolism and potentially virulence:

• Metabolic Functions:

  • Essential enzyme in serine biosynthesis pathway

  • Connects amino acid metabolism with central carbon metabolism

  • May contribute to metabolic adaptation during infection

• Potential Virulence Connections:

  • Amino acid biosynthesis pathways are often upregulated during host colonization

  • Metabolic fitness contributes to survival within host environments

  • Similar to findings in S. boydii type 13 and 20, genetic analysis should examine if serC is located near virulence-associated genes

• Experimental Approaches to Study These Connections:

  • Create serC knockout mutants using RED recombination system

  • Replace serC with chloramphenicol acetyltransferase (CAT) gene

  • Assess colonization and virulence in cell culture and animal models

  • Compare expression levels during different infection stages

  • Perform transcriptomic analysis to identify co-regulated genes

• Methodological Considerations:

  • For genetic knockouts, use primers that carry ~36 bp flanking the target gene

  • Select transformants with appropriate antibiotic markers

  • Confirm mutations by PCR and functional assays

  • Consider complementation studies to confirm phenotype specificity

What bioinformatic approaches are recommended for analyzing serC sequence variations across Shigella boydii serotypes?

For comprehensive bioinformatic analysis:

• Sequence Acquisition and Processing:

  • Obtain serC sequences from public databases (GenBank, UniProt)

  • Include serC from S. boydii serotype 18 (strain CDC 3083-94 / BS512) as reference

  • Process sequences using standard bioinformatic pipelines

  • Ensure proper annotation of functional domains

• Comparative Analysis Framework:

• Integration with Other Data:

  • Correlate sequence variations with serotype-specific characteristics

  • Map variations to functional domains using Pfam and other domain databases

  • Analyze co-evolution patterns with other virulence-associated genes

• Advanced Analysis:

  • Apply machine learning approaches to predict functional impact of variations

  • Use molecular dynamics simulations to assess structural impacts

  • Perform network analysis to identify functional associations with other proteins

What are the challenges in developing selective inhibitors of Shigella boydii serC and how might they be overcome?

Developing selective inhibitors presents several challenges and opportunities:

• Key Challenges:

  • High conservation of active site architecture among aminotransferases

  • Potential cross-reactivity with human phosphoserine aminotransferase

  • Need for sufficient selectivity to avoid disrupting human gut microbiome

  • Ensuring adequate cellular penetration of inhibitors

• Strategic Approaches:

  • Structure-based drug design targeting non-conserved regions

  • Fragment-based screening focused on allosteric sites

  • Exploitation of differences in substrate binding pockets

  • Development of prodrugs activated by Shigella-specific enzymes

• Methodological Workflow:

  • Perform detailed structural comparison between bacterial and human serC

  • Identify unique features in Shigella boydii serotype 18 serC

  • Use virtual screening to identify candidate compounds

  • Validate hits with in vitro enzyme assays

  • Test selectivity against human serC and other bacterial serC enzymes

  • Evaluate cellular activity in infection models

• Potential Starting Points:

  • PLP-dependent enzyme inhibitors with modifications for selectivity

  • Transition state analogs of phosphoserine aminotransferase reaction

  • Allosteric modulators identified through fragment screening

  • Peptide-based inhibitors targeting unique surface epitopes

What are the optimal storage and handling conditions for maintaining serC activity in experimental studies?

Based on recombinant protein datasheet information, researchers should adhere to these guidelines:

• Storage Recommendations:

  • Store protein at -20°C for routine use

  • For long-term storage, maintain at -20°C or -80°C

  • Add glycerol to a final concentration of 5-50% (optimally 50%) to prevent freeze damage

  • Aliquot samples to avoid repeated freeze-thaw cycles

• Working Solution Preparation:

  • Centrifuge vial briefly before opening to collect contents at bottom

  • Reconstitute lyophilized protein in deionized sterile water to 0.1-1.0 mg/mL

  • For working solutions, store at 4°C for no more than one week

• Activity Preservation:

  • Include PLP (pyridoxal phosphate) in buffers to stabilize the enzyme

  • Maintain reducing conditions with DTT or β-mercaptoethanol

  • Use buffers in the pH range 7.0-8.0 for optimal stability

  • Consider adding protease inhibitors for extended incubations

• Quality Control:

  • Verify enzymatic activity periodically using standard assays

  • Monitor protein integrity via SDS-PAGE

  • Assess oligomeric state by size exclusion chromatography

How can researchers validate the identity and purity of recombinant Shigella boydii serotype 18 serC preparations?

A multi-method approach ensures proper validation:

• Purity Assessment:

  • SDS-PAGE analysis (target: >85% purity)

  • Western blot with anti-His tag or specific anti-serC antibodies

  • Mass spectrometry to confirm molecular weight

  • Reverse-phase HPLC profile

• Identity Confirmation:

• Functional Validation:

  • Enzyme activity assay using standard substrates

  • Proper cofactor (PLP) binding assessed by absorbance at 420 nm

  • pH and temperature optima consistent with expected values

  • Kinetic parameters within expected ranges

• Oligomeric State Analysis:

  • Size exclusion chromatography to determine native molecular weight

  • Dynamic light scattering to assess homogeneity

  • Native PAGE to examine quaternary structure

What are the recommended controls for experiments involving genetic manipulation of serC in Shigella boydii?

For rigorous genetic studies, implement these controls:

• For Gene Knockout/Mutagenesis Experiments:

  • Wild-type parental strain maintained under identical conditions

  • Empty vector control for plasmid-based studies

  • Complementation with wild-type serC to confirm phenotype specificity

  • Confirmation of mutation by PCR, sequencing, and protein expression analysis

  • Off-target effects assessment using whole-genome sequencing

• RED Recombination System Controls:

  • When using the RED recombination system for genetic manipulation:

    • Include a control transformation without RED induction

    • Use positive control with known recombination target

    • Confirm recombination using PCR with primers flanking the targeted region

    • Verify expression changes at both RNA and protein levels

• Phenotypic Characterization Controls:

  • Media controls (minimal vs. complete medium)

  • Growth conditions standardization (temperature, aeration)

  • Serine supplementation controls to bypass metabolic defects

  • Stress response controls to differentiate specific from general effects

• Advanced Controls for Specificity:

  • Perform genetic complementation with serC from other species

  • Create point mutations affecting catalytic activity versus protein stability

  • Analyze polar effects on downstream genes

  • Include metabolic profiling to detect compensatory pathways

How does Shigella boydii serotype 18 serC compare structurally and functionally with serC from other enterobacteria?

A systematic comparison reveals important similarities and differences:

• Sequence and Structural Comparison:

  • Perform multiple sequence alignment with serC from E. coli, Salmonella, and other Shigella serotypes

  • Compare known or predicted structures using superimposition techniques

  • Calculate root-mean-square deviation (RMSD) for backbone atoms

  • Identify conserved catalytic residues versus variable peripheral regions

• Functional Comparison:

• Evolutionary Insights:

  • Similar to studies of O antigen gene clusters, serC analysis may reveal:

    • Evidence of horizontal gene transfer

    • Correlations with pathogenicity

    • Adaptation to specific environmental conditions

    • Sequence similarities that cross species boundaries, as seen between S. boydii and V. cholerae

• Methodological Considerations:

  • Express and purify multiple serC proteins under identical conditions

  • Use standardized assay conditions for direct comparison

  • Consider both in vitro enzyme assays and in vivo complementation studies

What computational approaches can predict interactions between serC and other proteins in Shigella boydii metabolic pathways?

Multiple computational strategies can elucidate protein-protein interactions:

• Sequence-Based Prediction Methods:

  • Use tools like STRING, MINT, and IntAct to predict interactions

  • Apply homology-based transfer of known interactions from model organisms

  • Analyze gene neighborhood and gene fusion events

  • Examine co-expression patterns across different conditions

• Structure-Based Approaches:

  • Perform protein-protein docking using tools like HADDOCK, ClusPro, or Rosetta

  • Analyze surface complementarity and electrostatic compatibility

  • Identify potential binding interfaces using hydrophobicity analysis

  • Validate with molecular dynamics simulations

• Network Analysis:

  • Construct metabolic network models including serC

  • Identify hub proteins and bottleneck enzymes

  • Analyze flux distribution under different conditions

  • Predict metabolic consequences of serC perturbation

• Experimental Validation Strategies:

  • Co-immunoprecipitation followed by mass spectrometry

  • Bacterial two-hybrid or split-GFP assays

  • Crosslinking studies coupled with proteomic analysis

  • Metabolic flux analysis to confirm predicted pathway interactions

How can advanced genomics techniques contribute to understanding the role of serC in Shigella pathogenesis?

Integration of multiple genomic approaches provides comprehensive insights:

• Comparative Genomic Analysis:

  • Whole genome sequencing of multiple S. boydii serotype 18 isolates

  • Comparison with other S. boydii serotypes (1-20)

  • Analysis of genomic context around serC gene

  • Assessment of horizontal gene transfer evidence, similar to O antigen gene clusters

• Transcriptomic Approaches:

  • RNA-Seq under various conditions (e.g., standard growth, stress, infection models)

  • Differential expression analysis to identify co-regulated genes

  • Identification of serC regulation mechanisms

  • Construction of gene regulatory networks

• Functional Genomics:

  • Transposon mutagenesis to identify genetic interactions

  • CRISPR interference to modulate serC expression

  • Synthetic lethality screening to identify backup pathways

  • Metabolomic profiling to characterize pathway flux

• Integration with Pathogenesis Research:

  • Correlation of serC variations with virulence phenotypes

  • In vivo expression technology (IVET) to assess in-host expression

  • Signature-tagged mutagenesis to evaluate contribution to colonization

  • Similar to approaches used for S. boydii serotype 20 characterization, applying molecular subtyping methods like PFGE to examine strain relationships

What are the emerging technologies that could advance Shigella boydii serC research?

Several cutting-edge technologies show promise for advancing this research field:

• CRISPR-Cas9 Applications:

  • Precise genome editing for targeted mutations

  • CRISPRi for tunable gene expression control

  • CRISPR screening for genetic interaction mapping

  • Base editing for introducing specific amino acid changes

• Single-Cell Technologies:

  • Single-cell RNA-Seq to examine expression heterogeneity

  • Microfluidics for high-throughput phenotyping

  • Live-cell imaging of serC-fluorescent protein fusions

  • Spatial transcriptomics to map expression in infection contexts

• Structural Biology Advancements:

  • Cryo-electron microscopy for high-resolution structures

  • AlphaFold and related AI tools for structure prediction

  • Hydrogen-deuterium exchange mass spectrometry for dynamics

  • Time-resolved X-ray crystallography for catalytic mechanisms

• Systems Biology Integration:

  • Multi-omics data integration

  • Machine learning for prediction of emergent properties

  • Genome-scale metabolic modeling

  • Protein-protein interaction network analysis