Recombinant Desulfotomaculum reducens Argininosuccinate synthase (argG)

What is the role of Argininosuccinate synthase in Desulfotomaculum reducens?

Argininosuccinate synthase (encoded by the argG gene) catalyzes the penultimate step in the arginine biosynthetic pathway, combining citrulline and aspartate to form argininosuccinate. In sulfate-reducing bacteria like Desulfotomaculum reducens, this enzyme plays a critical role in nitrogen metabolism and may be particularly important under stress conditions. The enzyme's activity directly affects arginine production, which is essential for protein synthesis and potentially for stress responses. Similar to findings in other bacteria, the enzyme likely functions as part of the urea cycle, affecting levels of metabolites including citrulline, argininosuccinate, arginine, and ornithine .

What experimental systems are most suitable for expressing recombinant Desulfotomaculum reducens Argininosuccinate synthase?

For efficient expression of recombinant Desulfotomaculum reducens Argininosuccinate synthase, consider implementing a systematic approach to expression system selection:

The expression method should be selected based on downstream applications. For structural studies requiring large protein quantities, BL21(DE3) may be optimal despite potential folding challenges. For functional studies where proper folding is critical, anaerobic expression systems might be more appropriate despite their technical complexity .

What are the fundamental challenges in purifying active Argininosuccinate synthase from recombinant systems?

Purifying active Argininosuccinate synthase presents several methodological challenges that require careful optimization:

• Oxygen sensitivity: As the protein originates from an anaerobic organism, exposure to oxygen during purification may lead to structural changes or loss of activity. Implement oxygen-free buffers and consider using anaerobic chambers for critical purification steps.

• Stability concerns: The enzyme may exhibit limited stability in standard buffer conditions. Test multiple buffer compositions varying in pH (7.0-8.5), salt concentration (100-500 mM NaCl), and stabilizing agents (5-10% glycerol, 1-5 mM DTT).

• Protein solubility: Recombinant expression often leads to inclusion body formation. Address this by:

  • Testing multiple induction conditions (temperature, IPTG concentration)

  • Using solubility-enhancing fusion tags (MBP, SUMO)

  • Developing effective refolding protocols if extraction from inclusion bodies is necessary

• Preservation of enzymatic activity: Activity loss during purification is common. Monitor enzyme activity throughout the purification process using the citrulline-aspartate conversion assay to identify steps that compromise function .

How can researchers design experiments to investigate the regulatory mechanisms controlling argG expression in Desulfotomaculum reducens under varying environmental conditions?

To systematically investigate the regulatory mechanisms controlling argG expression in Desulfotomaculum reducens, implement a multi-faceted experimental design that addresses both transcriptional and post-translational regulation:

• Promoter analysis and transcription factor identification:

  • Perform 5' RACE to precisely map the transcription start site

  • Construct reporter gene fusions (e.g., lacZ, gfp) with varying lengths of the argG promoter region

  • Use electrophoretic mobility shift assays (EMSA) with cell extracts from different growth conditions to identify DNA-binding proteins

  • Verify binding sites through DNase I footprinting or ChIP-seq

• Environmental condition matrix:
  Design a factorial experimental approach testing argG expression across multiple variables:

  Environmental Factor	Test Conditions	Measurement Methods
  Sulfate availability	0, 5, 20, 50 mM	RT-qPCR, Western blot
  Nitrogen source	NH4+, NO3-, organic N	RT-qPCR, enzyme activity
  Growth phase	Early, mid, late exponential, stationary	Time-course sampling
  Oxidative/nitrosative stress	Various H2O2 or NO concentrations	Stress-response profiling
  Carbon source	Lactate, pyruvate, H2/CO2	Metabolic profiling

• Post-transcriptional regulation analysis:

  • Evaluate mRNA stability through rifampicin chase experiments

  • Assess ribosome binding through polysome profiling

  • Investigate possible small RNA regulators through co-immunoprecipitation with RNA-binding proteins

• Post-translational regulation:

  • Develop assays to detect potential ubiquitination sites similar to the K234 residue identified in homologous enzymes

  • Use phosphoproteomic approaches to identify regulatory phosphorylation sites

  • Implement site-directed mutagenesis to verify the functional significance of identified post-translational modifications

This experimental design adheres to the core principles of randomization and controlled variable manipulation to ensure valid results .

What methodological approaches can be used to characterize the kinetic parameters of recombinant Desulfotomaculum reducens Argininosuccinate synthase and how do these compare to the enzyme from other organisms?

A comprehensive kinetic characterization of recombinant Desulfotomaculum reducens Argininosuccinate synthase requires a multi-step methodology that enables meaningful cross-species comparison:

• Enzyme preparation and quality control:

  • Purify to >95% homogeneity using affinity chromatography followed by size exclusion

  • Verify purity by SDS-PAGE and identity by mass spectrometry

  • Confirm native conformation through circular dichroism

  • Determine oligomeric state by analytical ultracentrifugation

• Steady-state kinetic analysis:

  • Implement a high-throughput spectrophotometric assay measuring argininosuccinate formation

  • Determine Km and kcat values for both substrates (citrulline and aspartate) through initial velocity measurements

  • Calculate catalytic efficiency (kcat/Km) under varying pH and temperature conditions

• Pre-steady-state kinetics:

  • Use stopped-flow spectroscopy to identify rate-limiting steps

  • Characterize product release by analyzing burst kinetics

  • Determine binding order through product inhibition studies

• Cross-species comparison:

  Parameter	D. reducens	E. coli	Mammalian	Archaea
  Km (Citrulline)	X mM	Y mM	Z mM	W mM
  Km (Aspartate)	X mM	Y mM	Z mM	W mM
  kcat	X s-1	Y s-1	Z s-1	W s-1
  pH optimum	X	Y	Z	W
  Temperature optimum	X°C	Y°C	Z°C	W°C
  Allosteric regulators	To be determined	Known factors	Known factors	Known factors

• Structural basis for kinetic differences:

  • Generate homology models based on crystal structures from other organisms

  • Identify active site residues that might account for kinetic differences

  • Verify through site-directed mutagenesis and kinetic analysis of mutant enzymes

This methodological framework enables researchers to systematically characterize the enzyme and place findings in an evolutionary context .

How does post-translational modification affect the stability and activity of Argininosuccinate synthase in Desulfotomaculum reducens, and what experimental approaches can detect these modifications?

Investigating post-translational modifications (PTMs) of Argininosuccinate synthase in Desulfotomaculum reducens requires a systematic multi-technique approach:

• Identification of potential PTM sites:

  • Perform in silico analysis using prediction algorithms for ubiquitination, phosphorylation, acetylation, and methylation sites

  • Compare conserved residues with known modification sites in homologous proteins, particularly focusing on the K234 residue identified as a ubiquitination site in other systems

• Detection methodologies:

  Modification Type	Detection Method	Technical Considerations	Controls
  Ubiquitination	Immunoprecipitation with anti-ubiquitin antibodies followed by Western blot	Include proteasome inhibitors during extraction	Use K-to-R mutants as negative controls
  Phosphorylation	LC-MS/MS with phosphopeptide enrichment	Consider multiple enrichment strategies (TiO2, IMAC)	Include phosphatase treatment controls
  Acetylation	Anti-acetyllysine antibodies and MS	Extract proteins in deacetylase inhibitors	Use established acetylation sites as positive controls
  Redox modifications	Differential alkylation followed by MS	Perform extraction under anaerobic conditions	Include oxidation and reduction controls

• Functional impact assessment:

  • Generate site-directed mutants mimicking modified states (e.g., K→Q for acetylation, S→E for phosphorylation)

  • Measure enzyme kinetics of wild-type vs. modified-mimic proteins

  • Assess protein stability through thermal shift assays and limited proteolysis

  • Determine half-life differences in vivo using pulse-chase experiments

• Regulatory context exploration:

  • Identify the E3 ligases potentially responsible for ubiquitination through BioID or proximity labeling approaches

  • Characterize the kinases/phosphatases involved in dynamic phosphorylation using inhibitor studies and protein interaction analysis

  • Investigate environmental conditions that alter the PTM profile

This methodological framework allows researchers to not only identify PTMs but also understand their functional significance in regulating Argininosuccinate synthase activity in response to changing cellular conditions .

What strategies can be employed to develop a high-throughput screening system for identifying inhibitors or activators of Desulfotomaculum reducens Argininosuccinate synthase?

Developing a robust high-throughput screening (HTS) system for Argininosuccinate synthase modulators requires careful assay design and validation:

• Primary assay development:

  • Adapt the enzymatic reaction to a colorimetric or fluorometric readout suitable for microplate format

  • Options include:

    • Coupling to pyrophosphate release using commercial enzyme systems

    • Detecting argininosuccinate formation through selective chemistry

    • Using fluorescently-labeled substrates to track reaction progress

  • Optimize buffer conditions, enzyme concentration, and reaction time for maximum signal-to-noise ratio

  • Implement Z'-factor analysis to validate assay quality (aim for Z' > 0.7)

• Assay miniaturization and automation:

  • Scale to 384 or 1536-well format with automated liquid handling

  • Develop stable reagent preparations that maintain activity during screening campaigns

  • Establish robust positive (known inhibitors) and negative controls

  • Implement quality control metrics for day-to-day and plate-to-plate variability

• Compound library selection and screening strategy:

  Library Type	Advantages	Considerations	Follow-up Testing
  Diversity-based	Broad chemical space	Lower hit rate expected	Structural clustering of hits
  Fragment-based	Efficient exploration of chemical space	Requires sensitive detection	Fragment growing/linking strategies
  Natural product	Novel scaffolds, evolved inhibitors	Extract complexity	Fractionation and structure determination
  Focused libraries	Higher hit rate	Limited chemical diversity	SAR development

• Counter-screening cascade:

  • Implement a hierarchical screening funnel:

    • Primary HTS → Dose-response confirmation → Orthogonal assay validation

    • Counter-screen against related enzymes to assess selectivity

    • Evaluate compound aggregation potential through detergent sensitivity

    • Assess compound interference with detection system

• Hit validation and characterization:

  • Determine mechanism of inhibition through kinetic studies

  • Evaluate binding using biophysical methods (SPR, ITC, thermal shift)

  • Assess cellular activity in bacterial systems

  • Use structure-based approaches to guide optimization if structural data is available

This comprehensive screening strategy leverages principles of experimental design, including randomization, proper controls, and systematic variable manipulation, to ensure robust identification of genuine modulators .

What are the optimal conditions for measuring Argininosuccinate synthase activity in vitro, and how can researchers troubleshoot common issues with the assay?

Establishing reliable in vitro assay conditions for Argininosuccinate synthase requires methodical optimization and systematic troubleshooting:

• Standard assay conditions:

  • Buffer composition: 50 mM HEPES (pH 7.5), 100 mM KCl, 5 mM MgCl2, 1 mM DTT

  • Substrate concentrations: 1-5 mM citrulline, 1-5 mM aspartate, 1-2 mM ATP

  • Temperature: 30°C for mesophilic bacteria (adjust for thermophiles)

  • Reaction time: Establish linear range (typically 10-30 minutes)

• Activity detection methods:

  Method	Principle	Sensitivity	Limitations
  Coupled spectrophotometric	Links ATP hydrolysis to NADH oxidation	Moderate (μM range)	Interference from coupling enzymes
  Radioactive	[14C]-citrulline or [14C]-aspartate incorporation	High (nM range)	Requires radioisotope handling
  HPLC-based	Direct detection of argininosuccinate	Moderate-high	Lower throughput
  Colorimetric	Specific detection of reaction products	Moderate	Potential interference
  Mass spectrometry	Direct product quantification	High	Specialized equipment needed

• Common troubleshooting strategies:

  Issue	Potential Causes	Solutions
  Low/no activity	Enzyme denaturation	Add stabilizers (glycerol, BSA), check pH
  	Oxygen exposure	Prepare reagents anaerobically, add reducing agents
  	Inhibitory contaminants	Purify enzyme further, test alternative buffer components
  High background	Contaminating enzymatic activities	Include control without substrate, increase purification stringency
  	Non-enzymatic reactions	Run controls without enzyme
  Poor reproducibility	Enzyme instability	Aliquot and store at -80°C, avoid freeze-thaw cycles
  	Variable substrate quality	Use freshly prepared substrates
  Substrate inhibition	High substrate concentrations	Determine optimal concentration ranges through kinetic analysis

• Validation approaches:

  • Verify enzyme identity using mass spectrometry or immunodetection

  • Confirm assay specificity using known inhibitors or substrate analogs

  • Demonstrate linear relationship between enzyme concentration and activity

  • Compare wild-type enzyme with catalytically inactive mutants (e.g., K165Q and K176Q in homologous systems)

This methodological framework provides researchers with robust protocols and troubleshooting strategies to ensure reliable measurement of Argininosuccinate synthase activity .

How can researchers effectively express and purify sufficient quantities of Desulfotomaculum reducens Argininosuccinate synthase for structural studies?

Obtaining sufficient quantities of properly folded recombinant Desulfotomaculum reducens Argininosuccinate synthase for structural studies requires a systematic optimization approach:

• Expression system selection and optimization:

  • Construct multiple expression vectors with different fusion tags (His6, MBP, SUMO, GST)

  • Compare expression levels in various E. coli strains (BL21(DE3), C41(DE3), SHuffle, Rosetta)

  • Screen expression conditions using a factorial design approach:

  Parameter	Variables to Test	Monitoring Method
  Induction temperature	16°C, 25°C, 30°C, 37°C	SDS-PAGE analysis
  IPTG concentration	0.1 mM, 0.5 mM, 1.0 mM	Western blot
  Media composition	LB, TB, auto-induction	Total protein yield
  Induction duration	4h, 8h, 16h, 24h	Soluble vs. insoluble fraction
  Additives	Glycylglycine, ethanol, sorbitol	Enhancement of soluble fraction

• Large-scale expression protocol:

  • Implement best conditions from optimization screens

  • Consider using bioreactor cultivation for increased biomass

  • For anaerobic proteins, evaluate expression under microaerobic conditions

  • Include protease inhibitors during harvest to prevent degradation

• Multi-step purification strategy:

  • Initial capture: Affinity chromatography based on fusion tag

  • Tag removal: Site-specific protease cleavage (PreScission, TEV, or SUMO protease)

  • Intermediate purification: Ion exchange chromatography

  • Polishing: Size exclusion chromatography

  • Concentrate to 5-15 mg/mL for crystallization trials

• Quality control assessments:

  • Purity: SDS-PAGE and mass spectrometry

  • Homogeneity: Dynamic light scattering and analytical SEC

  • Structural integrity: Circular dichroism and thermal shift assays

  • Functionality: Enzymatic activity compared to native enzyme

• Specific considerations for structural studies:

  • For X-ray crystallography: Screen for crystallization using commercial sparse matrix screens

  • For cryo-EM: Evaluate sample on negative stain EM before proceeding to cryo conditions

  • For NMR studies: Establish expression in minimal media with isotope labeling

This methodological approach incorporates principles of experimental design including variable manipulation and systematic optimization to maximize the likelihood of obtaining properly folded, active protein suitable for structural studies .

What experimental approaches can elucidate the structural determinants of substrate specificity in Desulfotomaculum reducens Argininosuccinate synthase?

Investigating the structural determinants of substrate specificity in Argininosuccinate synthase requires an integrated approach combining computational, biochemical, and structural methods:

• Sequence and structural analysis:

  • Perform multiple sequence alignment of Argininosuccinate synthase across diverse organisms

  • Identify conserved and variable residues in substrate-binding regions

  • Generate homology models based on existing crystal structures

  • Use computational docking to predict substrate interactions

• Site-directed mutagenesis strategy:

  • Design a panel of mutants targeting:

    • Absolutely conserved residues (likely catalytic)

    • Residues that differ between Desulfotomaculum and other species (specificity-determining)

    • Second-shell residues that may influence active site geometry

  Residue Type	Experimental Approach	Expected Outcome	Controls
  Catalytic residues	Conservative and non-conservative mutations	Complete activity loss	Wild-type enzyme
  Specificity-determining	Swap with residues from other species	Altered substrate preference	Wild-type kinetics
  Second-shell	Systematic alanine scanning	Subtle kinetic effects	Structural analysis

• Substrate analog studies:

  • Synthesize or obtain structural analogs of citrulline and aspartate

  • Perform competitive inhibition studies to map binding determinants

  • Use isothermal titration calorimetry to measure binding thermodynamics

• Protein engineering approaches:

  • Create chimeric enzymes combining domains from different species

  • Implement directed evolution with selection for altered specificity

  • Test rational design based on computational predictions

• Structural validation:

  • Pursue co-crystallization with substrates, products, or substrate analogs

  • Use hydrogen-deuterium exchange mass spectrometry to map conformational changes upon binding

  • Implement FRET-based assays to monitor substrate-induced conformational changes

• Correlation with enzyme function:

  • Measure kinetic parameters (Km, kcat) for each mutant with natural substrates

  • Test activity with non-native substrates to assess specificity changes

  • Evaluate product distribution when multiple reaction pathways are possible

This multi-faceted experimental approach provides comprehensive insights into the structural basis of substrate recognition and catalysis, guiding potential protein engineering efforts for biotechnological applications .

How should researchers analyze and interpret contradictory data when studying the metabolic context of Argininosuccinate synthase in Desulfotomaculum reducens?

When confronted with contradictory data regarding Argininosuccinate synthase in Desulfotomaculum reducens, implement a systematic approach to data analysis and interpretation:

• Methodological validation and troubleshooting:

  • Re-evaluate experimental techniques for potential systematic errors

  • Verify reagent quality and experimental conditions

  • Implement positive and negative controls for each assay system

  • Assess reproducibility through multiple independent replicates

• Systematic approach to contradictory findings:

  Data Contradiction Type	Analysis Approach	Resolution Strategy
  Enzyme activity discrepancies	Compare assay conditions	Standardize methods or explain context-dependency
  Expression level inconsistencies	Evaluate growth conditions	Map regulatory networks in different conditions
  Metabolic flux contradictions	Perform isotope tracing studies	Quantify actual metabolic contributions
  Phenotypic variations	Genetic background verification	Sequence verification and strain validation

• Integration of multi-omics data:

  • Combine transcriptomic, proteomic, and metabolomic data to build a holistic view

  • Implement correlation network analysis to identify consistent patterns amid contradictions

  • Use principal component analysis to identify major sources of variation

  • Apply Bayesian statistical approaches for conflicting datasets

• Alternative hypothesis generation:

  • Formulate multiple working models that could explain apparently contradictory results

  • Design critical experiments to differentiate between alternative hypotheses

  • Consider context-dependent regulation and moonlighting functions

  • Evaluate post-translational modifications that might explain functional differences

• Literature-based resolution approaches:

  • Perform systematic review of related enzymes in other organisms

  • Identify experimental conditions that might explain divergent results

  • Consider evolutionary context and metabolic adaptations in anaerobic bacteria

This methodological framework enables researchers to systematically address contradictory data, potentially revealing important regulatory mechanisms or novel enzyme functions that explain the apparent contradictions .

What statistical approaches are most appropriate for analyzing the kinetic parameters of Argininosuccinate synthase and comparing them across different experimental conditions?

Statistical analysis of enzyme kinetic parameters requires rigorous methodological approaches to ensure valid comparisons across experimental conditions:

• Statistical treatment of initial velocity data:

  • Fit raw kinetic data to appropriate models (Michaelis-Menten, Hill, etc.) using non-linear regression

  • Apply weighting schemes based on experimental error structure

  • Calculate confidence intervals for all derived parameters

  • Use information criteria (AIC, BIC) to select the most appropriate kinetic model

• Comparing kinetic parameters across conditions:

  Parameter Comparison	Statistical Approach	Required Sample Size	Assumptions
  Single parameter, two conditions	Student's t-test or Mann-Whitney	n ≥ 3 per condition	Normality (for t-test)
  Single parameter, multiple conditions	ANOVA with post-hoc tests	n ≥ 3 per condition	Normality, equal variance
  Multiple parameters, multiple conditions	MANOVA	n ≥ 5 per condition	Multivariate normality
  Complex experimental designs	Mixed-effects models	Depends on design	Model-specific

• Accounting for experimental variability:

  • Implement bootstrap or jackknife resampling for robust error estimation

  • Use global fitting approaches for datasets with shared parameters

  • Account for both random and systematic errors in uncertainty propagation

  • Consider Bayesian approaches with informative priors for small datasets

• Graphical representation of statistical results:

  • Create forest plots for comparing parameter values across conditions

  • Use volcano plots to visualize both magnitude and statistical significance

  • Implement spider/radar plots for multiparameter comparisons

  • Create interactive visualizations for exploring multidimensional parameter spaces

• Addressing common statistical pitfalls:

  • Correct for multiple comparisons using Bonferroni, Holm, or false discovery rate methods

  • Assess the influence of outliers through sensitivity analysis

  • Validate statistical assumptions through residual analysis

  • Implement power analysis to ensure adequate sample sizes

This statistical framework ensures robust analysis of enzyme kinetic data while maintaining experimental design integrity through proper randomization and variable control .

What are the most promising future research directions for studying Recombinant Desulfotomaculum reducens Argininosuccinate synthase in the context of microbial metabolism and stress response?

The study of Recombinant Desulfotomaculum reducens Argininosuccinate synthase opens several promising research avenues that integrate metabolic engineering, systems biology, and environmental microbiology:

• Systems-level metabolic integration:

  • Map the connectivity between arginine biosynthesis and central metabolic pathways in sulfate-reducing bacteria

  • Investigate metabolic flux redistribution under varying environmental stressors

  • Develop genome-scale metabolic models incorporating enzyme kinetics and regulation

  • Explore metabolic interactions in mixed microbial communities containing Desulfotomaculum reducens

• Stress response mechanisms:

  • Characterize the role of arginine biosynthesis in nitrite stress tolerance, similar to that observed in Desulfovibrio species

  • Investigate potential connections between arginine metabolism and sulfate reduction under limiting conditions

  • Explore the role of post-translational modifications in rapid adaptation to changing environments

  • Develop experimental designs to test the relationship between arginine biosynthesis and biofilm formation

• Biotechnological applications:

  • Engineer Argininosuccinate synthase variants with enhanced catalytic efficiency

  • Develop biosensors based on Argininosuccinate synthase regulation for environmental monitoring

  • Explore applications in bioremediation of metal-contaminated sites

  • Investigate potential antimicrobial targets based on differences between bacterial and human enzymes

• Evolutionary perspectives:

  • Conduct comparative genomic and structural analyses across diverse bacterial phyla

  • Investigate horizontal gene transfer events affecting argG distribution

  • Reconstruct the evolutionary history of the urea cycle and arginine metabolism in anaerobic bacteria

  • Explore functional divergence of Argininosuccinate synthase orthologs

• Methodological innovations:

  • Develop improved expression systems for oxygen-sensitive enzymes from anaerobic bacteria

  • Create advanced biophysical techniques for studying enzyme dynamics under anaerobic conditions

  • Implement synthetic biology approaches to create minimal systems for studying arginine metabolism

  • Develop computational models predicting enzyme behavior under varying environmental conditions

This research agenda incorporates experimental design principles including factorial approaches, controlled variable manipulation, and randomization to ensure robust and reproducible findings in this emerging field .

How can interdisciplinary approaches enhance our understanding of the structure-function relationships in Desulfotomaculum reducens Argininosuccinate synthase?

Advancing our understanding of structure-function relationships in Desulfotomaculum reducens Argininosuccinate synthase requires integration of diverse methodological approaches across multiple disciplines:

• Structural biology integration:

  • Combine X-ray crystallography, cryo-EM, and NMR spectroscopy for multi-scale structural insights

  • Implement hydrogen-deuterium exchange mass spectrometry to map conformational dynamics

  • Use small-angle X-ray scattering (SAXS) to study solution behavior and conformational ensembles

  • Apply computational approaches including molecular dynamics simulations to explore conformational landscapes

• Chemical biology approaches:

  Approach	Application	Expected Insights	Technical Considerations
  Activity-based protein profiling	Identify active site residues	Catalytic mechanism	Requires specific probe design
  Click chemistry	Track post-translational modifications	Regulatory mechanisms	May require genetic code expansion
  Crosslinking mass spectrometry	Map protein-protein interactions	Metabolic complexes	Optimization of crosslinker chemistry
  Photoaffinity labeling	Identify allosteric sites	Regulatory hotspots	Probe design affects specificity

• Systems biology integration:

  • Combine transcriptomics, proteomics, and metabolomics to map regulatory networks

  • Implement flux balance analysis to quantify metabolic contributions

  • Develop kinetic models incorporating structural constraints

  • Use network analysis to identify key regulatory nodes

• Computational approaches:

  • Implement machine learning for prediction of functional sites from sequence/structure

  • Use quantum mechanics/molecular mechanics (QM/MM) to study reaction mechanisms

  • Apply evolutionary coupling analysis to identify co-evolving residue networks

  • Develop integrative modeling approaches combining diverse experimental data

• Emerging technologies:

  • Apply single-molecule techniques to study conformational dynamics

  • Implement microfluidic platforms for high-throughput functional screening

  • Use synthetic biology to create minimal systems for hypothesis testing

  • Develop biosensors based on Argininosuccinate synthase for real-time activity monitoring

This interdisciplinary framework enables researchers to connect molecular-level structural insights with cellular function, providing a comprehensive understanding of how Argininosuccinate synthase contributes to Desulfotomaculum reducens metabolism and adaptation to environmental challenges .

What are the essential resources and databases that researchers should consult when studying Recombinant Desulfotomaculum reducens Argininosuccinate synthase?

Researchers investigating Recombinant Desulfotomaculum reducens Argininosuccinate synthase should utilize these essential resources organized by research phase:

• Sequence and structural information:

  • UniProt for protein sequence and annotation

  • Protein Data Bank (PDB) for related enzyme structures

  • BRENDA enzyme database for biochemical and molecular information

  • KEGG for metabolic pathway mapping

  • PFAM and InterPro for domain analysis and functional annotation

• Genomic and transcriptomic resources:

  Resource Type	Recommended Databases	Information Provided	Usage Notes
  Bacterial genomes	NCBI RefSeq, MicrobesOnline	Complete genome sequence	Compare genomic context across species
  Transcriptomics	GEO, ArrayExpress	Expression profiles	Identify co-regulated genes
  Regulon databases	RegPrecise, RegulonDB	Predicted regulatory sites	Map potential regulatory networks
  Metagenomic resources	IMG/M, MG-RAST	Environmental distribution	Ecological context of enzyme variants

• Specialized sulfate-reducing bacteria resources:

  • DvH Database (Desulfovibrio vulgaris Hildenborough resources)

  • SRB Web Server for comparative genomics of sulfate-reducing bacteria

  • Anaerobic microorganism collection databases (DSMZ, ATCC)

  • Desulfotomaculum comparative genomics databases

• Experimental design and methodological resources:

  • Enzyme Assay Guide for standardized activity measurement

  • Protein Expression and Purification Series for anaerobic protein handling

  • PDB for experimental conditions successful with homologous proteins

  • Protocols for anaerobic cultivation and manipulation

• Bioinformatics and analysis tools:

  • PyMOL, UCSF Chimera for structural visualization and analysis

  • MEGA for phylogenetic analysis

  • I-TASSER for protein structure prediction

  • HMMER for sensitive sequence searches

  • DynaFit or KinTek Explorer for enzyme kinetics analysis

• Literature resources:

  • Regular monitoring of specialized journals:

    • Journal of Bacteriology

    • Environmental Microbiology

    • FEMS Microbiology Reviews

    • Biochemistry

    • Structure

  • Citation alerts for key papers on argininosuccinate synthase and sulfate-reducing bacteria

  • Conference proceedings from American Society for Microbiology and enzymology conferences