Recombinant Mesoplasma florum Protein nrdI (nrdI)

What is Mesoplasma florum nrdI protein and what is its significance in molecular biology?

Protein nrdI from Mesoplasma florum is a 151-amino acid protein involved in ribonucleotide reduction pathways. The significance of studying nrdI lies in understanding minimal bacterial systems, as M. florum represents a near-minimal bacterium that serves as an attractive model for systems biology and synthetic biology applications . The protein has the UniProt identification number Q6F0T6 and contains specific functional domains that facilitate electron transfer in nucleotide metabolism . Its study contributes to our understanding of essential cellular functions in genetically reduced organisms, providing insights into the minimal genetic requirements for life.

What are the structural features of recombinant M. florum nrdI protein?

Recombinant M. florum nrdI protein consists of 151 amino acids with the following sequence: MHDDIKLVSGEEIVKPTGEVHVVYFSSISNNNTHRFIQKLSVKNSRIPYELEEEINVDSDYVLITPTYSGGGEFTSGAVPKQVIKFLNKENNRNYCRGVIASGNTNFGNTFAMAGPILSKKLNVPLLYQFELLGTQNDVEKINEILKEFWGK . The protein contains specific functional domains that contribute to its role in ribonucleotide reduction. When produced as a recombinant protein, it typically achieves purity levels >85% as determined by SDS-PAGE . The structural analysis of nrdI reveals conserved motifs that are crucial for its function in the ribonucleotide reductase system, which is essential for DNA synthesis and repair in M. florum.

How does M. florum nrdI compare to similar proteins in other minimal bacterial systems?

M. florum nrdI can be compared to analogous proteins in other minimal bacterial systems such as Mycoplasma genitalium, Mycoplasma pneumoniae, and the synthetic minimal cell JCVI-syn3A. When considering the broader metabolic context, M. florum shares approximately 25-47% of its gene-associated reactions with these other minimal bacterial systems . This comparison provides insights into the conservation of essential functions across reduced genomes. The table below shows the comparison of metabolic models between M. florum and other minimal bacteria:

This comparative analysis demonstrates that while these organisms have reduced genomes, they maintain essential metabolic functions, including those involving redox proteins like nrdI .

What are the optimal conditions for expression and purification of recombinant M. florum nrdI?

For optimal expression of recombinant M. florum nrdI, yeast expression systems have been successfully employed as indicated in the product information . When working with this recombinant protein, researchers should follow these methodological steps:

• Express the full-length protein (amino acids 1-151) in an appropriate yeast expression system.

• Purify using affinity chromatography, with the tag type determined during the manufacturing process.

• Verify purity using SDS-PAGE, aiming for >85% purity.

• For reconstitution, briefly centrifuge the protein vial before opening and reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL.

• Add glycerol to a final concentration of 5-50% (typically 50%) before aliquoting for long-term storage.

• Store at -20°C/-80°C, with an expected shelf life of 6 months for liquid form and 12 months for lyophilized form .

To maintain protein activity, avoid repeated freeze-thaw cycles and consider storing working aliquots at 4°C for up to one week .

How can researchers effectively transform M. florum for nrdI expression studies?

Researchers have three effective transformation methods available for M. florum, which can be applied to nrdI expression studies:

• Polyethylene glycol (PEG)-mediated transformation: This method has demonstrated transformation frequencies of approximately 4.1 × 10^-6 transformants per viable cell when using appropriate oriC-based plasmids .

• Electroporation: This alternative method requires less material and hands-on time than PEG-mediated transformation, reaching frequencies up to 7.87 × 10^-6 transformants per viable cell .

• Conjugation from Escherichia coli: This approach has yielded transformation frequencies of approximately 8.44 × 10^-7 transformants per viable cell, representing the first reported example of plasmid conjugation from E. coli to a Mollicutes species .

For each method, plasmids harboring both rpmH-dnaA and dnaA-dnaN intergenic regions from M. florum have proven most effective for stable maintenance throughout multiple generations . When designing plasmids for nrdI expression studies, researchers should consider that plasmids containing both oriC intergenic regions (with or without the dnaA gene) transform at similar frequencies, suggesting that cis-expression of DnaA protein is not essential for proper plasmid replication and maintenance in M. florum .

What antibiotic selection markers are compatible with M. florum genetic systems for nrdI studies?

Functional antibiotic resistance genes that have been demonstrated to work effectively in M. florum include:

• Tetracycline resistance: The tetM gene, encoding a tetracycline ribosomal protection protein, has been successfully used as a selectable marker in oriC plasmids. For optimal function, this gene should be recoded to be functional in both E. coli and M. florum .

• Puromycin resistance: Antibiotic resistance genes conferring resistance to puromycin have been demonstrated to function in M. florum .

• Spectinomycin/streptomycin resistance: Genes conferring resistance to these antibiotics have also been proven functional in M. florum genetic systems .

When designing selection strategies, researchers should consider the integration tendency of oriC-based plasmids with the M. florum chromosome. Southern blotting analysis has shown that these plasmids frequently recombine at the oriC region due to sequence homology, resulting in heterogeneous populations of cells containing both extrachromosomal and integrated forms of the plasmids .

How can nrdI studies contribute to our understanding of M. florum as a minimal cell model?

Studies of nrdI in M. florum provide significant insights into minimal cellular systems through several approaches:

• Metabolic network analysis: M. florum's metabolic model (iJL208) includes 208 genes (30.6% of the total genome), 370 total reactions, and 351 metabolites . Understanding nrdI's role within this network helps elucidate essential redox pathways in minimal cells.

• Comparative genomics: By comparing nrdI function in M. florum with analogous proteins in other minimal bacteria like Mycoplasma genitalium, Mycoplasma pneumoniae, and synthetic minimal cells like JCVI-syn3A, researchers can identify core functions preserved across minimal genomes .

• Systems biology integration: nrdI studies can be integrated with other omics data to create comprehensive models of minimal cellular function. For instance, the lactate dehydrogenase pathway (LDH: Mfl596) shows approximately 4-8 fold higher protein expression levels compared to genes of the pyruvate dehydrogenase complex (PDH: Mfl039, Mfl040, Mfl041, and Mfl042) . Similar approaches can be applied to understand nrdI's regulatory context.

• Synthetic biology applications: As a component of a near-minimal cellular chassis, understanding nrdI's function contributes to efforts to build an M. florum-based minimal cellular system for synthetic biology applications .

These approaches collectively enhance our understanding of the essential components required for life and provide a foundation for synthetic biology applications.

What methodological approaches can resolve the issue of plasmid integration when studying nrdI expression?

When studying nrdI expression in M. florum, researchers must address the tendency of oriC-based plasmids to recombine with the host chromosome. The following methodological approaches can help resolve this issue:

What strategies can be employed to analyze the functional interaction of nrdI with ribonucleotide reductase systems in M. florum?

To analyze the functional interaction of nrdI with ribonucleotide reductase systems in M. florum, researchers can employ several advanced strategies:

• Metabolic flux analysis: Using genome-scale metabolic modeling, researchers can predict the impact of nrdI perturbations on nucleotide metabolism pathways. Similar approaches have been applied to study metabolic fluxes in M. florum, such as the positive linear relationship between predicted growth rate and lactate secretion rate .

• Protein-protein interaction studies: Recombinant nrdI protein can be used in co-immunoprecipitation or cross-linking experiments to identify direct interaction partners within the ribonucleotide reductase system.

• In vitro activity assays: Purified recombinant nrdI (>85% purity by SDS-PAGE) can be used in enzymatic assays to measure electron transfer activities and define optimal conditions for protein function .

• Genetic complementation: Researchers can test whether M. florum nrdI can functionally complement nrdI mutations in other bacterial systems, providing insights into the conservation of function across species.

• Structural biology approaches: Using the defined protein sequence (MHDDIKLVSGEEIVKPTGEVHVVYFSSISNNNTHRFIQKLSVKNSRIPYELEEEINVDSDYVLITPTYSGGGEFTSGAVPKQVIKFLNKENNRNYCRGVIASGNTNFGNTFAMAGPILSKKLNVPLLYQFELLGTQNDVEKINEILKEFWGK), researchers can perform structural analyses to identify functional domains and predict interaction interfaces .

• Systems-level integration: Integration of nrdI functional data with broader metabolic models, such as the iJL208 model of M. florum, can contextualize the role of this protein within the minimal cellular system .

How can researchers address stability issues with recombinant M. florum nrdI during experimental procedures?

To address stability issues with recombinant M. florum nrdI during experimental procedures, researchers should implement these methodological approaches:

• Optimal storage conditions: The shelf life of liquid nrdI preparations is typically 6 months at -20°C/-80°C, while lyophilized forms can be stable for up to 12 months at the same temperatures . Researchers should aliquot the protein to avoid repeated freeze-thaw cycles.

• Working aliquot management: For ongoing experiments, store working aliquots at 4°C for no more than one week to maintain protein activity .

• Glycerol addition: Add glycerol to a final concentration of 5-50% (with 50% being typical) before long-term storage to prevent freezing damage .

• Reconstitution protocol: When reconstituting lyophilized protein, briefly centrifuge the vial before opening to bring contents to the bottom. Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL .

• Buffer optimization: Consider testing different buffer compositions to identify conditions that maximize protein stability during experimental procedures.

• Activity monitoring: Implement regular activity assays to monitor protein function throughout storage and experimental procedures, allowing early detection of activity loss.

• Reducing agents: Consider adding reducing agents to buffers when appropriate to maintain the redox state of functional domains within the nrdI protein.

What factors affect transformation efficiency when introducing nrdI expression constructs into M. florum?

Several factors influence transformation efficiency when introducing nrdI expression constructs into M. florum:

• Plasmid design: Plasmids harboring both rpmH-dnaA and dnaA-dnaN intergenic regions have demonstrated optimal transformation frequencies (approximately 4.1 × 10^-6 transformants per viable cell), while plasmids containing only one intergenic region failed to produce detectable transformants .

• Transformation method: Three methods have been validated for M. florum transformation, each with different efficiencies:

  • Polyethylene glycol (PEG)-mediated transformation: ~4.1 × 10^-6 transformants per viable cell

  • Electroporation: Up to 7.87 × 10^-6 transformants per viable cell

  • Conjugation from E. coli: Up to 8.44 × 10^-7 transformants per viable cell

• DnaA boxes arrangement: The presence and arrangement of DnaA boxes within the plasmid construct significantly impact replication efficiency. Seven putative DnaA boxes have been identified within the oriC region of M. florum, with four located in the rpmH-dnaA intergenic region and three in the dnaA-dnaN intergenic region .

• Antibiotic selection: The choice of antibiotic resistance marker affects selection efficiency. Validated markers for M. florum include tetracycline resistance (tetM), puromycin resistance, and spectinomycin/streptomycin resistance genes .

• Homologous recombination: OsiC-based plasmids frequently recombine with the host chromosome due to sequence homology, which may affect stable expression of introduced constructs. Southern blot analysis has shown that plasmids can exist in both extrachromosomal and integrated forms within the same clonal population .

• Conjugative machinery: When using conjugation for transformation, the choice of conjugative system can impact transfer efficiency. The RP4 conjugation machinery has been demonstrated to work with M. florum, but alternative systems might provide improved transfer rates .

How can researchers distinguish between genomic and plasmid-derived nrdI expression in M. florum studies?

Distinguishing between genomic and plasmid-derived nrdI expression in M. florum studies requires sophisticated methodological approaches:

• Epitope tagging: Add unique epitope tags (such as His, FLAG, or HA) to the plasmid-derived nrdI, allowing differentiation from the native protein using tag-specific antibodies in Western blot analysis.

• Southern blot analysis: This technique can identify the genomic location and distinguish between integrated and extrachromosomal forms of the plasmid. Similar approaches have been used to analyze oriC plasmids in M. florum, revealing that most tested clones exhibit both forms simultaneously .

• Quantitative PCR (qPCR): Design primers specific to unique regions of the plasmid construct versus the genomic copy to quantify relative expression levels.

• RNA-seq analysis: Deep sequencing of transcripts with subsequent mapping to reference sequences can distinguish expression levels between genomic and plasmid variants, especially if the plasmid-derived nrdI contains silent mutations or codon optimizations.

• Promoter swapping: Replace the native promoter in the plasmid construct with an inducible or constitutive promoter that differs from the genomic version, allowing temporal control and differentiation of expression.

• Knockout complementation: In advanced systems, researchers could attempt to knock out the genomic nrdI and complement with the plasmid-derived version, ensuring all expression comes from the plasmid.

• Mass spectrometry: If amino acid differences exist between the genomic and plasmid versions, mass spectrometry can be used to distinguish between the protein variants.

What potential exists for using nrdI as a target for developing minimal synthetic cells based on M. florum?

The potential for using nrdI as a target in developing minimal synthetic cells based on M. florum encompasses several promising research directions:

• Essential gene validation: As M. florum represents a near-minimal cellular chassis for synthetic biology, characterizing the essentiality of nrdI provides critical information for determining the minimal gene set required for viable synthetic cells .

• Redox pathway engineering: nrdI's role in electron transfer for ribonucleotide reduction makes it a potential target for engineering optimized redox pathways in synthetic minimal cells.

• Metabolic modeling integration: The existing genome-scale metabolic model for M. florum (iJL208) includes 208 genes (30.6% of the total genome), 370 reactions, and 351 metabolites . Integrating nrdI function into this model can help predict system-wide effects of genetic modifications in synthetic cell design.

• Orthogonal systems development: Engineering variant nrdI proteins that function with synthetic ribonucleotide reductase systems could provide orthogonal pathways for nucleotide metabolism in minimal cells.

• Genetic tool expansion: The genetic tools developed for M. florum, including oriC-based plasmids and transformation methods, provide a foundation for manipulating nrdI and other genes in the development of synthetic cells .

• Cross-species functionality: Comparative analysis of nrdI function across minimal bacterial systems could inform the design of synthetic cells with optimized or hybrid nucleotide metabolism pathways .

• Synthetic biology standardization: Characterizing nrdI function contributes to the standardization of biological parts for synthetic biology applications using minimal cells as chassis.

How might advanced computational modeling enhance our understanding of nrdI function in M. florum?

Advanced computational modeling can significantly enhance our understanding of nrdI function in M. florum through several approaches:

What are the methodological frontiers for studying nrdI protein interactions in minimal bacterial systems?

The methodological frontiers for studying nrdI protein interactions in minimal bacterial systems include several innovative approaches:

• In vivo proximity labeling: Techniques such as BioID or APEX2 can be adapted for M. florum to identify proteins that interact with nrdI in their native cellular environment.

• Cryo-electron microscopy: Advanced structural biology techniques can visualize nrdI-containing protein complexes at near-atomic resolution, revealing the structural basis of functional interactions.

• Single-molecule tracking: Fluorescently labeled nrdI can be tracked in living cells to observe its dynamic behavior and interactions with other cellular components.

• Microfluidics-based approaches: High-throughput microfluidic systems can analyze nrdI function under precisely controlled conditions and in combination with various potential interaction partners.

• Synthetic genetic arrays: Systematic genetic interaction mapping in M. florum could reveal functional relationships between nrdI and other genes in the minimal genome.

• Cell-free expression systems: Reconstituted cell-free systems using M. florum components could allow controlled studies of nrdI function outside the complexity of the living cell.

• CRISPR-based technologies: Adapted for M. florum, these technologies could enable precise manipulation of nrdI and potential interaction partners to study their functional relationships.

• Cross-linking mass spectrometry: This technique can capture transient interactions between nrdI and other proteins, providing a comprehensive map of its interaction network.

• Integrative modeling: Combining experimental data from multiple sources can create comprehensive models of nrdI function within the minimal bacterial system context.