Recombinant Herpetosiphon aurantiacus Serine hydroxymethyltransferase (glyA)

What is the primary function of Serine hydroxymethyltransferase (glyA) in Herpetosiphon aurantiacus?

Herpetosiphon aurantiacus Serine hydroxymethyltransferase (SHMT), encoded by the glyA gene, primarily catalyzes the reversible interconversion of serine and glycine with tetrahydrofolate (THF) serving as the one-carbon carrier. This reaction represents a major source of one-carbon groups essential for the biosynthesis of purines, thymidylate, methionine, and other critical biomolecules. Additionally, H. aurantiacus glyA exhibits THF-independent aldolase activity toward beta-hydroxyamino acids, producing glycine and aldehydes via a retro-aldol mechanism . This dual functionality makes glyA a central player in bacterial metabolism, connecting amino acid metabolism with nucleotide synthesis pathways.

To study this function experimentally, researchers typically employ spectrophotometric assays measuring the formation of 5,10-methylene-THF, which can be coupled to dihydrofolate reductase activity for continuous monitoring of reaction progress. Isotope labeling with 13C-serine can also help track the flow of one-carbon units through metabolic networks.

What are the key structural features of H. aurantiacus glyA protein?

H. aurantiacus SHMT is a 419-amino acid protein with a molecular weight of approximately 45.1 kDa . The protein belongs to the SHMT family and shares conserved structural domains with other bacterial SHMTs, including:

The protein's sequence (MSLMDVLRQQDPDLAQAIDSEAERQRHGIELIASENYVSSAVLAAQGSVLTNKYAEGYPRKRYYGGCEFVDVAEDLAIKRAKQLFGAEHVNVQPHSGAQANMAVQLATLEHGDRVLGMSLAHGGHLTHGHPLNFSGKSYEIHGYGVDRETEQIDYEEVAEIAHKTQPKMIICGASAYPRNINFDLLRTIADNVGAILMADIAHIAGLVAAGLHPSPIGVAQYVTTTTHKTLRGPRGGMIMCSAEHGKNIDKTVFPGVQGGPLMHVIAAKAVAFGEALQPEYRDYMRRVVENAKVLAEALTNEGLRIVSGGTDNHLLLVDLTPVNATGKDAEKALDHAGITVNKNAIPFDPKPPMTASGLRFGTPAATTRGFGPNEMRQIAVWVGQIVRELGNKSLQAKIAGEVRELCAAFPVPGQPEYV) contains numerous conserved motifs characteristic of the SHMT family .

To characterize these structural features experimentally, researchers commonly employ X-ray crystallography, circular dichroism, and site-directed mutagenesis approaches.

How is the glyA gene conserved across bacterial species?

The glyA gene is highly conserved across bacterial species, with SHMT being an almost ubiquitous enzyme in bacterial metabolism. Comparative genomic analyses have revealed that out of 618 bacterial genomes with glyA genes, 555 also possess ygfA genes encoding 5-formyltetrahydrofolate cyclo-ligase (5-FCL) . This high conservation reflects the essential role of SHMT in providing one-carbon units for various biosynthetic pathways.

The sequence homology between H. aurantiacus glyA and homologs from other species ranges from moderate to high, with conserved catalytic residues showing the highest degree of conservation. Phylogenetic analysis techniques can be used to track the evolutionary relationships between SHMT proteins across different bacterial phyla.

Methodologically, researchers can employ:

• Multiple sequence alignment tools (MUSCLE, CLUSTAL)

• Phylogenetic tree construction (Maximum Likelihood, Bayesian approaches)

• Synteny analysis to examine gene neighborhood conservation

• Structural superimposition of crystal structures when available

What are the optimal conditions for expressing recombinant H. aurantiacus glyA?

The optimal expression of recombinant H. aurantiacus glyA requires careful consideration of expression system, temperature, induction conditions, and buffer composition. While specific optimization would be required for any given research objective, the following general approach is recommended:

For expression validation, researchers should employ SDS-PAGE analysis, western blotting, and activity assays. The expected molecular weight of recombinant H. aurantiacus glyA is approximately 45.1 kDa (may vary with tag addition) . If expression yields are low, researchers can consider codon optimization, as rare codons may impact translation efficiency in E. coli.

Additionally, implementing systems for rare tRNA supplementation can be beneficial, as demonstrated in functional complementation studies where E. coli cells harboring pACYC-RP and pSC101-RIL (encoding rare tRNAs) were utilized successfully for heterologous protein expression .

What assays can be used to measure the enzymatic activity of H. aurantiacus glyA?

Multiple complementary assays can be employed to characterize the enzymatic activities of H. aurantiacus glyA:

• Spectrophotometric assay for SHMT activity:

  • Measure the formation of 5,10-methylene-THF (absorption at 340 nm)

  • Couple with NADPH-dependent reduction to track reaction progress

  • Requires purified enzyme, L-serine, THF, and PLP

• Radiometric assay:

  • Use 14C-labeled serine to track conversion to glycine

  • Separate products by TLC or HPLC

  • Quantify using scintillation counting

• THF-independent aldolase activity assay:

  • Monitor formation of glycine and aldehydes from β-hydroxyamino acids

  • Can be coupled to glycine oxidase reactions for continuous monitoring

  • Spectrophotometric detection of aldehyde formation using 2,4-dinitrophenylhydrazine

• Functional complementation assay:

  • Transform an E. coli ΔygfA strain with a plasmid expressing H. aurantiacus glyA

  • Test growth on media with glycine as sole nitrogen source

  • This approach tests the enzyme's ability to prevent 5-CHO-THF accumulation

Kinetic parameters (Km, Vmax, kcat) should be determined for both the forward and reverse reactions to fully characterize the enzyme's behavior. Inhibition studies using established SHMT inhibitors can provide additional insights into the active site architecture.

How can I achieve high-purity preparations of recombinant H. aurantiacus glyA?

Producing high-purity recombinant H. aurantiacus glyA for structural and functional studies requires a systematic purification strategy:

• Affinity chromatography (primary step):

  • Express glyA with an affinity tag (His6, GST, or MBP)

  • Use appropriate affinity resin (Ni-NTA for His-tagged proteins)

  • Include PLP (50 μM) in all buffers to maintain stability

  • Elute with imidazole gradient (for His-tagged proteins)

• Ion exchange chromatography (secondary step):

  • Based on the theoretical pI of H. aurantiacus glyA

  • Use anion exchange (e.g., Q-Sepharose) at pH > pI

  • Apply salt gradient for elution

• Size exclusion chromatography (polishing step):

  • Separate oligomeric states and remove aggregates

  • Concentrate protein to 5-10 mg/mL before loading

  • Monitor oligomeric state (expected to be tetrameric)

• Quality control methods:

  • SDS-PAGE for purity assessment (aim for >95%)

  • Dynamic light scattering for homogeneity analysis

  • Mass spectrometry for identity confirmation

  • Activity assays to confirm functional integrity

Buffer optimization is critical for maintaining enzyme stability. The addition of glycerol (10%), reducing agents (1-5 mM DTT or β-mercaptoethanol), and PLP (50 μM) often enhances protein stability during purification and storage. For long-term storage, flash-freezing in liquid nitrogen and storage at -80°C with 20% glycerol is recommended.

How does H. aurantiacus glyA relate to folate metabolism and how can this be studied?

H. aurantiacus glyA plays a central role in folate metabolism as SHMT catalyzes reactions involving tetrahydrofolate (THF). The enzyme's reaction serves as the major source of one-carbon groups required for the biosynthesis of purines, thymidylate, methionine, and other important biomolecules . This positions glyA at a critical intersection of amino acid metabolism and nucleic acid synthesis.

Key aspects of this relationship include:

• Production of 5,10-methylene-THF:

  • SHMT converts serine and THF to glycine and 5,10-methylene-THF

  • This provides one-carbon units for downstream folate-dependent reactions

• Relationship with 5-formyltetrahydrofolate (5-CHO-THF):

  • SHMT can inadvertently produce 5-CHO-THF as a side reaction

  • Accumulation of 5-CHO-THF can inhibit SHMT and other folate-dependent enzymes

• Interplay with formyltetrahydrofolate cyclo-ligase (5-FCL):

  • In many organisms, 5-FCL (encoded by ygfA) converts inhibitory 5-CHO-THF back to THF

  • In organisms lacking ygfA, alternative enzymes like formiminotransferase may fulfill this function

To study these relationships, researchers can employ:

• Metabolomic profiling of folate derivatives using LC-MS/MS

• Isotope labeling to track one-carbon flow through metabolic networks

• Functional complementation assays in E. coli ΔygfA strains grown on media with glycine as nitrogen source

• Enzyme inhibition studies examining the effects of various folate derivatives

Research has shown that E. coli cells lacking the ygfA gene accumulate 5-CHO-THF when supplemented with glycine, and completely replacing the NH4Cl nitrogen source with glycine leads to a severe growth defect. This defect is likely due to inhibition of SHMT and glycine cleavage system by 5-CHO-THF accumulation .

What site-directed mutagenesis approaches can reveal about H. aurantiacus glyA catalytic mechanisms?

Site-directed mutagenesis is a powerful approach to elucidate the catalytic mechanism of H. aurantiacus glyA. By systematically altering key amino acid residues and characterizing the resulting mutant enzymes, researchers can identify essential catalytic residues and understand their specific roles.

Recommended mutagenesis targets include:

The experimental workflow should include:

• Identification of key residues based on sequence alignment with well-characterized SHMTs

• Primer design and PCR-based mutagenesis

• Expression and purification of mutant proteins using protocols identical to wild-type

• Comparative biochemical characterization (kinetic parameters, substrate specificity)

• Spectroscopic characterization to assess PLP binding and enzyme conformational changes

• Thermal stability analysis to distinguish catalytic vs. structural effects

For advanced mechanistic insights, researchers should consider:

• Double-mutant cycle analysis to identify cooperative interactions

• Hydrogen-deuterium exchange mass spectrometry to probe conformational dynamics

• Pre-steady-state kinetics to identify rate-limiting steps in catalysis

How can I investigate the dual functionality of H. aurantiacus glyA in one-carbon metabolism?

H. aurantiacus glyA exhibits dual functionality: the canonical SHMT activity (serine-glycine interconversion) and THF-independent aldolase activity toward β-hydroxyamino acids . Investigating this dual functionality requires specialized experimental approaches:

• Separation of activities:

  • Design reaction conditions that selectively promote one activity over the other

  • Vary cofactor availability (presence/absence of THF)

  • Analyze product formation using HPLC or LC-MS

• Selective inhibition studies:

  • Use inhibitors specific to SHMT activity vs. aldolase activity

  • Antifolates may inhibit the THF-dependent reaction while leaving aldolase activity intact

  • Measure inhibition constants for both activities separately

• Substrate competition experiments:

  • Measure activity with mixed substrates to determine preference

  • Analyze product distribution using isotope-labeled substrates

  • Calculate relative efficiency for different reaction pathways

• In vivo metabolic impact:

  • Create an expression system in a suitable host (e.g., E. coli)

  • Monitor metabolite levels using targeted metabolomics

  • Assess growth phenotypes under conditions favoring each reaction type

• Structural studies:

  • Crystal structures with different ligands/substrates bound

  • Molecular dynamics simulations to understand conformational changes

  • Docking studies to predict substrate binding modes

To distinguish between the two activities experimentally, separate assays should be developed:

• For SHMT activity: Monitor serine-glycine interconversion in the presence of THF

• For aldolase activity: Measure glycine formation from β-hydroxyamino acids in the absence of THF

The results should be analyzed to determine whether these activities share the same active site or utilize different catalytic residues, which would inform enzyme engineering efforts to enhance one activity over the other.

How can researchers address contradictory kinetic data for H. aurantiacus glyA?

When confronted with contradictory kinetic data for H. aurantiacus glyA across different studies or experimental conditions, researchers should employ a systematic troubleshooting approach:

• Methodological standardization:

  • Ensure consistent enzyme preparation methods

  • Standardize assay conditions (temperature, pH, buffer composition)

  • Use the same substrate sources and preparation methods

  • Employ consistent analytical techniques for product quantification

• Enzyme state considerations:

  • Assess oligomeric state influence (monomer/dimer/tetramer equilibrium)

  • Determine PLP occupancy and its impact on activity

  • Evaluate potential allosteric regulation mechanisms

  • Check for post-translational modifications or oxidation states

• Advanced kinetic analysis:

  • Perform global fitting of data across multiple experiments

  • Apply more complex kinetic models (Ordered Bi-Bi, Random Bi-Bi)

  • Consider product inhibition and substrate inhibition effects

  • Use numerical integration for time-course analysis rather than initial rates

• Reconciliation approaches:

  • Design critical experiments that directly test competing hypotheses

  • Perform replication with biological and technical replicates

  • Employ orthogonal methods to verify key findings

  • Use statistical methods to identify outliers or systematic errors

A decision table for resolving contradictory data might include:

For definitive resolution, researchers should consider combining biochemical approaches with structural studies and computational modeling to develop a comprehensive understanding of the enzyme's behavior.

What approaches are effective for analyzing H. aurantiacus glyA expression in native vs. heterologous systems?

Comparing H. aurantiacus glyA expression and activity between native and heterologous systems presents unique challenges that require specialized analytical approaches:

• Expression level analysis:

  • qRT-PCR for mRNA quantification in both systems

  • Western blotting with anti-SHMT antibodies

  • Mass spectrometry-based proteomics for absolute quantification

  • Activity assays normalized to total protein content

• Post-translational modification assessment:

  • Mass spectrometry to identify and compare modifications

  • Phosphoproteomics or glycoproteomics if relevant

  • Activity comparisons before and after phosphatase treatment

  • 2D gel electrophoresis to separate protein isoforms

• Protein folding and cofactor binding:

  • Circular dichroism to compare secondary structure content

  • Fluorescence spectroscopy to assess PLP binding

  • Thermal shift assays to evaluate protein stability

  • Size exclusion chromatography to determine oligomeric state

• Functional comparison:

  • Side-by-side kinetic parameter determination

  • Substrate specificity profiles

  • Inhibitor sensitivity patterns

  • pH and temperature optima

• Computational analysis:

  • Codon usage comparison between native and heterologous hosts

  • Prediction of mRNA secondary structures affecting translation

  • Signal sequence and subcellular localization prediction

  • Protein-protein interaction network differences

When examining functional properties, researchers should be particularly mindful of the potential for differing post-translational modifications, cofactor availability, and protein-protein interactions between the native H. aurantiacus environment and heterologous expression systems. The complementation assay developed for 5-CHO-THF metabolism in E. coli, based on deleting the gene encoding 5-FCL (ygfA), provides a useful functional readout that can be employed to assess activity in heterologous systems .

How can evolutionary analysis inform functional studies of H. aurantiacus glyA?

Evolutionary analysis provides valuable context for functional studies of H. aurantiacus glyA by revealing conservation patterns, adaptation signatures, and functional relationships with homologs in other organisms.

Methodological approaches include:

• Phylogenetic analysis:

  • Construct maximum likelihood or Bayesian trees of SHMT homologs

  • Identify phylogenetic clustering patterns

  • Determine if H. aurantiacus glyA exhibits expected evolutionary relationships

  • Identify potential horizontal gene transfer events

• Selection pressure analysis:

  • Calculate dN/dS ratios across the gene sequence

  • Identify sites under positive, negative, or relaxed selection

  • Compare selection patterns in different bacterial lineages

  • Correlate selection patterns with functional domains

• Ancestral sequence reconstruction:

  • Infer ancestral SHMT sequences at key evolutionary nodes

  • Experimentally characterize reconstructed ancestral enzymes

  • Compare kinetic properties to understand functional evolution

  • Identify key mutations that altered substrate specificity

• Correlation with genomic context:

  • Analyze gene neighborhood conservation

  • Identify co-evolving gene clusters

  • Compare with patterns observed in bacterial genomes that have FT rather than 5-FCL

  • Infer functional associations from gene co-occurrence patterns

Systematic analysis of 621 bacterial and 19 archaeal genomes has revealed that while 618 have glyA genes encoding SHMT, only 555 have ygfA genes specifying 5-FCL, with 63 organisms lacking ygfA . This pattern suggests evolutionary adaptation in folate metabolism across different bacterial lineages. The finding that formiminotransferase (FT) genes are frequently present when ygfA is absent provides an example of how evolutionary analysis can reveal functional replacements .

When designing experiments based on evolutionary insights, researchers should:

• Test functions predicted by comparative genomics

• Target highly conserved residues for mutagenesis studies

• Examine variant residues that might confer species-specific properties

• Consider reconstructing and testing ancestral sequences

What crystallization strategies are most effective for H. aurantiacus glyA structural studies?

Crystallization of H. aurantiacus SHMT presents several challenges due to its size (45.1 kDa), potential conformational flexibility, and cofactor requirements. Successful structural determination requires strategic approaches:

• Pre-crystallization optimization:

  • Ensure >95% purity by SDS-PAGE

  • Verify homogeneity by dynamic light scattering

  • Optimize buffer conditions for maximal stability

  • Consider limited proteolysis to identify stable domains

• Crystallization condition screening:

  • Commercial sparse matrix screens (initial screening)

  • Grid screens around promising conditions

  • Include PLP cofactor in all trials

  • Test with and without substrates/substrate analogs

• Protein modifications to enhance crystallization:

  • Surface entropy reduction (SER) - mutate surface clusters of Lys/Glu to Ala

  • Truncate flexible regions identified by limited proteolysis

  • Create fusion proteins with crystallization chaperones (T4 lysozyme, MBP)

  • Test both His-tagged and tag-cleaved versions

• Advanced crystallization techniques:

  • Microseeding to improve crystal quality

  • Counter-diffusion methods for slow equilibration

  • Lipidic cubic phase for membrane-associating forms

  • In situ proteolysis during crystallization

• Crystal handling and data collection strategies:

  • Optimize cryoprotection conditions

  • Test multiple crystals to identify best diffraction

  • Consider room temperature data collection

  • Use micro-focus beamlines for small crystals

For structural determination of H. aurantiacus glyA complexes, researchers should:

• Co-crystallize with substrate analogs or inhibitors

• Soak crystals with ligands when co-crystallization fails

• Capture different catalytic states using substrate/product combinations

• Consider time-resolved crystallography for reaction intermediates

How can isotope labeling approaches illuminate H. aurantiacus glyA metabolic roles?

Isotope labeling represents a powerful approach to elucidate the metabolic roles of H. aurantiacus glyA in one-carbon metabolism and amino acid interconversion:

• Steady-state metabolic flux analysis:

  • Culture cells with 13C-labeled serine, glycine, or glucose

  • Harvest cells at steady state

  • Extract and analyze metabolites using LC-MS/MS

  • Calculate flux distributions using computational modeling

• Pulse-chase experiments:

  • Briefly expose cells to labeled substrate ("pulse")

  • Switch to unlabeled media ("chase")

  • Sample at multiple time points

  • Track label movement through metabolic pathways

• In vitro enzyme mechanistic studies:

  • Use deuterium-labeled substrates (2H-serine)

  • Measure kinetic isotope effects

  • Identify rate-limiting steps in catalysis

  • Elucidate reaction mechanisms

• Protein-substrate interaction analysis:

  • Nuclear magnetic resonance (NMR) with 15N/13C-labeled enzyme

  • Hydrogen-deuterium exchange mass spectrometry

  • Chemical crosslinking with isotope-coded linkers

  • Identify substrate binding residues and conformational changes

• In vivo cross-feeding experiments:

  • Create auxotrophic strains dependent on H. aurantiacus glyA

  • Grow with labeled precursors

  • Analyze metabolite exchange between cells

  • Determine the role in community metabolism

The data analysis workflow should include:

• Mass isotopomer distribution analysis (MIDA)

• Correction for natural isotope abundance

• Computational modeling of metabolic networks

• Statistical analysis for significance testing

Researchers can apply these methods to investigate how H. aurantiacus glyA contributes to folate metabolism and one-carbon transfer reactions. The approach can particularly help determine whether the THF-independent aldolase activity has physiological significance or is merely a side reaction .

What computational approaches can predict substrate specificity determinants in H. aurantiacus glyA?

Computational methods offer valuable insights into substrate specificity determinants of H. aurantiacus glyA without extensive experimental testing:

• Homology modeling and structural analysis:

  • Construct a 3D model based on homologous SHMT structures

  • Identify the active site pocket and substrate-binding residues

  • Calculate electrostatic and hydrophobic properties of the binding site

  • Compare with well-characterized SHMT structures

• Molecular docking studies:

  • Dock various potential substrates in the active site

  • Calculate binding energies and interaction patterns

  • Rank substrates by predicted affinity

  • Identify key residues for substrate recognition

• Molecular dynamics simulations:

  • Simulate enzyme-substrate complexes over nanosecond timescales

  • Analyze conformational changes upon substrate binding

  • Calculate residence times of substrates in active site

  • Identify water-mediated interactions

• Quantum mechanics/molecular mechanics (QM/MM) calculations:

  • Model reaction mechanisms with electronic structure methods

  • Calculate energy profiles for different substrates

  • Predict transition state structures

  • Estimate activation energies for catalysis

• Machine learning approaches:

  • Train models on known SHMT substrate preferences

  • Identify sequence and structural features that correlate with specificity

  • Predict specificity for novel substrates

  • Design mutations to alter specificity

Implementation strategy:

• Begin with sequence-based predictions and homology modeling

• Progress to molecular docking of known and potential substrates

• Validate key predictions with site-directed mutagenesis

• Refine models based on experimental feedback

Specific tools that may be employed include:

• SWISS-MODEL or I-TASSER for homology modeling

• AutoDock or Glide for molecular docking

• GROMACS or AMBER for molecular dynamics simulations

• Gaussian or ORCA for QM calculations

• TensorFlow or scikit-learn for machine learning implementations

These computational approaches can help predict how H. aurantiacus glyA might interact with both its canonical substrates (serine, glycine, THF) and alternative substrates in its THF-independent aldolase activity , guiding experimental design for enzyme characterization and engineering.