Recombinant Talaromyces stipitatus Putative dipeptidase TSTA_079200 (TSTA_079200)

What is the taxonomic classification and origin of TSTA_079200?

TSTA_079200 is a putative dipeptidase from Talaromyces stipitatus, a fungal organism previously classified as Penicillium stipitatum. The specific strain references include ATCC 10500 / CBS 375.48 / QM 6759 / NRRL 1006 . Talaromyces stipitatus is closely related to Talaromyces marneffei (formerly Penicillium marneffei), which is known as an AIDS-associated pathogen endemic to tropical regions of Southeast Asia . A genus-wide reclassification has moved many Penicillium species to the Talaromyces genus, including T. stipitatus .

The genome of T. stipitatus ATCC10500 has been fully sequenced, with a determined genome size of 35.6 Mb and genome coverage of 8.1× . The annotated genome sequence has been deposited at GenBank under accession numbers EQ962652 and EQ963471, with the whole-genome shotgun master record accession number ABAS00000000 .

What are the optimal storage and handling conditions for recombinant TSTA_079200?

For optimal maintenance of TSTA_079200 activity and stability, the following protocol is recommended:

• Storage conditions: Store at -20°C/-80°C for extended periods. Working aliquots can be maintained at 4°C for up to one week .

• Reconstitution procedure:

  • Briefly centrifuge the vial containing lyophilized protein before opening

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

  • For long-term storage, add glycerol to a final concentration of 5-50% (typically 50%)

• Buffer composition: The protein is typically provided in a Tris/PBS-based buffer with 6% Trehalose at pH 8.0 , or alternatively in a Tris-based buffer with 50% glycerol optimized for protein stability .

• Critical precautions: Repeated freeze-thaw cycles should be avoided as they can compromise protein integrity and enzymatic activity .

How can researchers design effective dipeptidase activity assays for TSTA_079200?

While the search results don't provide specific assay protocols for TSTA_079200, researchers can adapt approaches from related dipeptidase studies like the S. hominis PepV investigation . A comprehensive approach would include:

• Coupled enzyme assay: Design an assay where dipeptidase activity is linked to a secondary reaction producing a measurable signal. For example, the hydrolysis of dipeptides could release amino acids that serve as substrates for amino acid oxidases, producing hydrogen peroxide that can be measured colorimetrically .

• Substrate screening panel: Test activity against diverse dipeptides to establish substrate preference profiles. This should include variations in:

  • Amino acid side chain properties (polar, nonpolar, charged)

  • Peptide bond stereochemistry

  • N- and C-terminal modifications

• Analytical approaches:

  • HPLC or LC-MS quantification of substrate disappearance and product formation

  • Colorimetric or fluorometric detection using modified substrates

  • Enzyme kinetics determination (Km, kcat, kcat/Km) for preferred substrates

• Optimization parameters:

  • pH optimization (typically 6.0-9.0 range)

  • Temperature profile (25-50°C)

  • Metal cofactor requirements (common for dipeptidases)

The experimental design should include appropriate controls to account for potential non-enzymatic hydrolysis of substrates and interference from buffer components.

How might structural biology approaches enhance understanding of TSTA_079200 function?

Advanced structural biology techniques would provide critical insights into TSTA_079200's catalytic mechanism and substrate specificity. A comprehensive approach would include:

• Structure determination:

  • X-ray crystallography of purified recombinant TSTA_079200 in both apo form and with bound substrates/inhibitors

  • Cryo-EM studies as an alternative approach for structural characterization

  • NMR studies for dynamic aspects of protein-substrate interactions

• Computational modeling:

  • Homology modeling based on related dipeptidases if crystal structure is unavailable

  • Molecular docking of potential substrates to predict binding modes

  • Molecular dynamics simulations to study conformational changes during catalysis

• Structure-guided mutagenesis:

  • Identify catalytic residues through structural analysis

  • Design mutations to probe substrate binding determinants

  • Apply similar approaches to those used for S. hominis PepV, where a D437A mutation resulted in a sixfold increase in catalytic efficiency (kcat/Km)

Through integration of structural data with biochemical characterization, researchers can develop detailed models of TSTA_079200's active site architecture and substrate recognition mechanisms.

How does TSTA_079200 compare to other fungal dipeptidases in terms of sequence conservation and substrate specificity?

A comparative analysis of TSTA_079200 with other fungal dipeptidases would involve:

• Phylogenetic analysis:

  • Multiple sequence alignment with dipeptidases from diverse fungal species

  • Construction of phylogenetic trees to visualize evolutionary relationships

  • Identification of conserved motifs and catalytically important residues

• Comparative biochemistry:

  • Side-by-side testing of substrate preferences across different fungal dipeptidases

  • Comparison of kinetic parameters for common dipeptide substrates

  • Investigation of inhibitor sensitivity profiles

• Structural comparison:

  • Superimposition of TSTA_079200 structure (experimental or predicted) with known dipeptidase structures

  • Comparison of active site architecture and substrate binding pockets

  • Analysis of metal coordination geometry if TSTA_079200 is confirmed as a metalloenzyme

This comparative approach would reveal whether TSTA_079200 possesses unique features that might reflect specialized functions in T. stipitatus compared to dipeptidases from other fungi.

What is the potential role of TSTA_079200 in the secondary metabolism of Talaromyces stipitatus?

The genome of T. stipitatus contains 61 secondary metabolite biosynthetic gene clusters, comparable to the numbers found in Aspergillus niger and Aspergillus terreus . Investigating the potential involvement of TSTA_079200 in secondary metabolism would require:

• Genomic context analysis:

  • Determine whether TSTA_079200 is located within or adjacent to any secondary metabolite gene clusters

  • Compare with the known tropolone biosynthetic gene cluster (tropA, tropB, tropC) in T. stipitatus

  • Analyze co-expression patterns with genes involved in secondary metabolism

• Metabolomic profiling:

  • Compare metabolite profiles between wild-type and TSTA_079200 knockout or overexpression strains

  • Use stable isotope labeling to track potential dipeptidase-dependent metabolic pathways

  • Focus on peptide-derived secondary metabolites that might require dipeptidase activity

• Biochemical characterization with specialized substrates:

  • Test activity against dipeptides found in nonribosomal peptide secondary metabolites

  • Investigate potential roles in peptide-based siderophore biosynthesis

  • Examine activity toward dipeptide intermediates in specialized metabolic pathways

This investigation would help determine whether TSTA_079200 plays a specialized role in secondary metabolism beyond general protein turnover and nutrient acquisition.

How can CRISPR-Cas9 gene editing be utilized to investigate the physiological importance of TSTA_079200?

CRISPR-Cas9 technology offers powerful tools for functional genomics studies of TSTA_079200 in its native context. A comprehensive approach would include:

• Gene knockout strategy:

  • Design guide RNAs targeting the TSTA_079200 gene locus

  • Develop transformation protocols optimized for T. stipitatus

  • Include appropriate selection markers and screening methods

  • Verify gene deletion using PCR, sequencing, and protein detection methods

• Phenotypic characterization:

  • Growth analysis under various nutrient conditions

  • Morphological examination during different developmental stages

  • Secondary metabolite production analysis using LC-MS or GC-MS

  • Stress tolerance assays (oxidative, temperature, pH, osmotic)

• Complementation studies:

  • Reintroduce wild-type TSTA_079200 to confirm phenotype restoration

  • Introduce site-directed mutants to identify critical functional residues

  • Use controlled expression systems to investigate dosage effects

• Advanced genetic approaches:

  • Create conditional knockdowns if TSTA_079200 proves essential

  • Generate fluorescently tagged versions for localization studies

  • Perform promoter swapping to investigate regulation

This comprehensive genetic approach would provide definitive evidence regarding the physiological importance of TSTA_079200 in T. stipitatus.

How should researchers address potential inconsistencies in TSTA_079200 activity measurements across different experimental conditions?

When encountering variability in dipeptidase activity measurements, researchers should systematically investigate:

• Protein quality factors:

  • Batch-to-batch variation in recombinant protein expression

  • Potential differences in post-translational modifications

  • Protein stability under different storage and handling conditions

  • Effects of freeze-thaw cycles on activity retention

• Assay condition variables:

  • pH and buffer composition effects on activity

  • Temperature sensitivity and potential thermal inactivation

  • Dependence on metal cofactors and potential chelator contamination

  • Substrate concentration effects and potential substrate inhibition

• Experimental design considerations:

  • Establish statistically robust replicate numbers (minimum n=3)

  • Include internal controls for normalization across experiments

  • Develop standardized protocols with detailed parameters

  • Implement rigorous data analysis methods including outlier identification

• Troubleshooting approaches:

  • Time-course experiments to identify stability issues

  • Side-by-side testing of different protein preparations

  • Systematic variation of single parameters while controlling others

  • Correlation analysis between activity and protein structural integrity

By methodically addressing these potential sources of variability, researchers can develop robust and reproducible assay systems for TSTA_079200 characterization.

What methodological approaches can address the challenge of distinguishing TSTA_079200 activity from other endogenous peptidases in complex biological samples?

When studying TSTA_079200 in complex biological contexts, researchers must employ strategies to specifically identify its activity:

• Selective inhibition approach:

  • Develop a panel of class-specific protease inhibitors

  • Identify inhibitors that selectively target or spare TSTA_079200

  • Use combinatorial inhibitor treatments to isolate specific activities

• Substrate specificity profiling:

  • Identify unique substrate preferences of TSTA_079200

  • Design substrates with modifications that favor TSTA_079200 over other peptidases

  • Employ competition assays with selective substrates

• Immunological methods:

  • Develop specific antibodies against TSTA_079200

  • Use immunodepletion to remove TSTA_079200 from complex samples

  • Perform activity assays before and after immunodepletion

• Genetic approaches in model systems:

  • Compare activities in wild-type vs. TSTA_079200 knockout strains

  • Use overexpression systems to amplify TSTA_079200-specific signals

  • Employ RNA interference for targeted knockdown of TSTA_079200

• Mass spectrometry-based approaches:

  • Use MALDI-TOF or LC-MS/MS to identify specific cleavage products

  • Employ isotope-labeled substrates to track TSTA_079200-specific hydrolysis

  • Perform activity-based protein profiling with selective probes

These complementary approaches would allow researchers to confidently attribute observed activities to TSTA_079200 rather than other peptidases present in complex biological samples.

How might TSTA_079200 be investigated in the context of fungal-host interactions and potential pathogenicity?

While T. stipitatus itself is not known as a major pathogen, its close relative T. marneffei is an AIDS-associated pathogen . Investigating potential roles of TSTA_079200 homologs in pathogenicity would involve:

• Comparative genomics approach:

  • Identify TSTA_079200 homologs in pathogenic Talaromyces species

  • Compare sequence conservation and predicted structures

  • Analyze genomic context in pathogenic vs. non-pathogenic species

• Functional studies in infection models:

  • Generate knockout strains of the TSTA_079200 homolog in T. marneffei

  • Assess virulence in appropriate infection models

  • Investigate specific host-pathogen interactions that might involve dipeptidase activity

• Host factor interactions:

  • Test activity against host-derived peptide substrates

  • Investigate potential immunomodulatory effects of dipeptidase activity

  • Examine interactions with host defense peptides

• Translational potential:

  • Assess TSTA_079200 homologs as potential diagnostic biomarkers

  • Evaluate as targets for antifungal drug development

  • Investigate immunological responses to fungal dipeptidases during infection

This research direction would provide valuable insights into the potential contribution of dipeptidases to fungal pathogenicity and host-pathogen interactions.

How can heterologous expression systems be optimized for large-scale production of functionally active TSTA_079200?

Optimizing heterologous expression for scale-up production of TSTA_079200 requires addressing several key challenges:

• Expression system selection and optimization:

  Expression System	Advantages	Challenges	Optimization Strategies
  E. coli	Proven successful for TSTA_079200	Potential folding issues	Optimize codon usage; low-temperature expression; co-expression with chaperones
  Yeast (P. pastoris)	Better folding of fungal proteins	Lower yields than E. coli	Optimize media composition; fed-batch fermentation; strain engineering
  Insect cells	Superior folding of complex proteins	Higher cost; technical complexity	Optimize MOI; harvest timing; cell density management

• Expression construct design:

  • Test multiple fusion tags (His, GST, MBP, SUMO) for optimal solubility and activity

  • Optimize linker sequences between tag and target protein

  • Design constructs with precision protease cleavage sites for tag removal

  • Consider synthetic gene optimization for expression host

• Process development for scale-up:

  • Establish reproducible fed-batch fermentation protocols

  • Develop robust downstream processing workflow

  • Implement quality control checkpoints throughout the process

  • Design stability studies to determine optimal formulation conditions

• Activity preservation strategies:

  • Identify stabilizing buffer additives (glycerol, trehalose, specific ions)

  • Establish optimal pH and temperature ranges for long-term stability

  • Develop lyophilization protocols that preserve activity upon reconstitution

  • Test various storage formats (solution, frozen, lyophilized)

By systematically addressing these aspects, researchers can develop efficient production systems for generating research-grade TSTA_079200 with consistent activity and purity.