Recombinant Candida maltosa 40S ribosomal protein S13 (RPS13)

What are the RNA-binding properties of C. maltosa RPS13 and how can they be experimentally determined?

The RNA-binding properties of C. maltosa RPS13 can be investigated using techniques analogous to those employed for human RPS13. Nitrocellulose binding assays conducted at high salt concentrations (250 mM KCl) are particularly effective for reducing non-specific binding due to electrostatic interactions between positively charged ribosomal proteins and negatively charged RNA . When characterizing the RNA-binding specificity, it is essential to include appropriate controls such as non-specific RNA competitors like adenovirus major late RNA or synthetic polynucleotides such as poly(AU) . For C. maltosa RPS13, researchers should calculate apparent association constants through quantitative binding experiments with labeled RNA transcripts containing putative binding regions. The specificity of binding can be further validated through competition experiments with both specific and non-specific RNA competitors to establish binding preferences .

Ribonuclease protection assays provide complementary data on the specific RNA regions protected by RPS13 binding. These assays can identify protection patterns near functionally important regions such as splice sites, which might indicate regulatory roles similar to those observed in human RPS13 . For more detailed characterization, structural techniques such as X-ray crystallography or NMR spectroscopy of the RPS13-RNA complex would provide atomic-level insights into the binding interface. High-throughput approaches like SELEX (Systematic Evolution of Ligands by Exponential Enrichment) or RNA-seq following crosslinking and immunoprecipitation (CLIP-seq) can help identify the complete repertoire of RNA sequences recognized by C. maltosa RPS13 in a more comprehensive manner.

How can RPS13 be used as a reference gene in C. maltosa gene expression studies?

RPS13 serves as an effective reference gene for normalization in quantitative PCR experiments involving Candida species due to its relatively stable expression across different conditions. When designing qPCR experiments using RPS13 as a reference gene, researchers should first validate its expression stability under their specific experimental conditions . The approach demonstrated in macaque studies provides a useful template, where RPS13 was successfully employed as an endogenous control for normalizing gene expression data . Researchers should design and validate primers specific to C. maltosa RPS13, ensuring they produce a single amplicon of the expected size, as confirmed through melt curve analysis during qPCR .

For C. maltosa studies, primer design should target conserved regions of the RPS13 gene to ensure specificity and efficiency. The forward primer sequence 5'-CCCACTTGGTTGAAGTTGA-3' and reverse primer sequence 5'-CAGGATCACACCGATTTGT-3' used for RPS13 in other studies can serve as templates, though they should be adapted based on the C. maltosa RPS13 sequence . When employing RPS13 as a reference gene, researchers should include appropriate controls in their qPCR reactions, including no-reverse transcriptase and non-template controls, to ensure the validity of their results . It is also advisable to use multiple reference genes in addition to RPS13 to improve the robustness of normalization, particularly when studying conditions that might affect ribosome biogenesis or protein synthesis pathways.

What are the optimal conditions for heterologous expression of recombinant C. maltosa RPS13?

For optimal heterologous expression of recombinant C. maltosa RPS13, researchers should consider several expression systems and conditions to maximize yield and maintain proper folding of this ribosomal protein. E. coli remains the most common expression system for recombinant proteins due to its rapid growth, high expression levels, and established protocols. When expressing C. maltosa RPS13 in E. coli, BL21(DE3) or Rosetta strains are preferred as they are designed to enhance expression of eukaryotic proteins by providing rare codons that might be present in the C. maltosa sequence. Expression vectors containing strong inducible promoters like T7 or tac, coupled with appropriate fusion tags (His6, GST, or MBP) facilitate both expression and subsequent purification steps.

Temperature optimization is crucial for expressing ribosomal proteins like RPS13, as lower temperatures (16-20°C) during induction often improve protein solubility by slowing down expression and allowing proper folding. For C. maltosa RPS13, which likely contains RNA-binding domains similar to human RPS13, the concentration of inducer (IPTG for lac-based promoters) should be carefully titrated, with lower concentrations (0.1-0.5 mM) potentially yielding more soluble protein . Alternative expression hosts such as yeast systems (Pichia pastoris or Saccharomyces cerevisiae) may provide advantages for expressing C. maltosa proteins due to their closer evolutionary relationship and similar post-translational modification machinery. Considering that human RPS13 exhibits specific RNA-binding properties with an apparent association constant of 5.0 × 10^7 M^-1, the expression conditions should aim to preserve these functional characteristics in the recombinant C. maltosa homolog .

What purification strategies yield the highest activity for recombinant C. maltosa RPS13?

Purification of recombinant C. maltosa RPS13 requires strategies that maintain its native conformation and RNA-binding capacity while achieving high purity. A multi-step purification approach typically yields the best results for ribosomal proteins. For His-tagged RPS13, immobilized metal affinity chromatography (IMAC) using Ni-NTA resin serves as an effective initial capture step, ideally performed under native conditions with buffers containing 20-50 mM imidazole to reduce non-specific binding. Since ribosomal proteins are often positively charged due to their RNA-binding properties, ion exchange chromatography (particularly cation exchange) provides a powerful second purification step, with elution using a salt gradient (typically 0-1M NaCl or KCl).

Size exclusion chromatography (SEC) as a final polishing step helps separate monomeric RPS13 from aggregates and contaminating proteins of different sizes. Throughout the purification process, buffers should be optimized to maintain protein stability and activity—typically containing 20-50 mM Tris or phosphate buffer (pH 7.0-8.0), 100-300 mM NaCl or KCl, and potentially 1-5 mM DTT or β-mercaptoethanol to maintain reduced cysteine residues. Based on protocols used for human RPS13, activity assays should be conducted at each purification step to monitor the RNA-binding function, particularly using nitrocellulose binding assays with labeled RNA transcripts . For functional studies, it's critical to verify that the purified recombinant C. maltosa RPS13 maintains specific RNA binding with minimal non-specific interactions, which can be assessed using competition assays with specific and non-specific RNA competitors as demonstrated for human RPS13 .

Does C. maltosa RPS13 autoregulate its expression through mechanisms similar to human RPS13?

Investigation of potential autoregulatory mechanisms for C. maltosa RPS13 should begin with comparative sequence analysis of the RPS13 gene and its introns across Candida species. The high conservation of intron 1 observed in mammalian and avian RPS13 genes suggests functional importance in autoregulation, making this region a primary target for investigation in C. maltosa . Researchers should examine whether the C. maltosa RPS13 gene contains conserved introns, particularly focusing on potential regulatory elements within these intronic regions. In human RPS13, the protein has been shown to inhibit excision of intron 1 from its pre-mRNA in vitro, providing a negative feedback mechanism that regulates its own expression . Similar in vitro splicing assays can be developed for C. maltosa using transcripts containing the RPS13 gene's introns and purified recombinant RPS13 protein.

RNA electrophoretic mobility shift assays (EMSA) and ribonuclease protection assays should be employed to determine if C. maltosa RPS13 can bind specifically to its own pre-mRNA, particularly near splice sites as observed with human RPS13 . For cellular validation of autoregulation, minigene constructs containing the C. maltosa RPS13 gene with and without intron 1 can be transfected into appropriate cell lines, followed by quantification of expression levels using real-time PCR . If autoregulation exists, overexpression of RPS13 should lead to reduced splicing efficiency of intron 1 and consequently decreased mature mRNA levels. Structural analysis of the RNA-protein interaction would provide further insights into the molecular mechanism of autoregulation, potentially identifying conserved features between human and C. maltosa RPS13 autoregulatory systems.

What role might C. maltosa RPS13 play in antifungal resistance mechanisms?

The potential role of RPS13 in antifungal resistance mechanisms in Candida maltosa warrants investigation given the increasing concerns about antifungal resistance in Candida species. Recent research has identified multiple mutations in genes related to ribosome function that contribute to antifungal resistance in various Candida species . To investigate this for C. maltosa RPS13, researchers should begin by comparing RPS13 sequences from antifungal-resistant and susceptible C. maltosa strains to identify potential mutations associated with resistance. Next, gene editing techniques can be employed to introduce these mutations into susceptible strains to determine if they confer increased resistance to various antifungal classes (azoles, echinocandins, and amphotericin B) .

Functional studies should examine whether alterations in RPS13 affect ribosome assembly, translation efficiency, or specific stress response pathways that might contribute to antifungal resistance. Transcriptomic and proteomic analyses of strains with modified RPS13 can reveal broader changes in gene expression patterns that might explain resistance mechanisms. Additionally, researchers should investigate potential interactions between RPS13 and known resistance-related proteins, such as drug efflux pumps or enzymes involved in cell wall synthesis. Centers for Disease Control and Prevention have emphasized the importance of early identification and prevention measures for drug-resistant Candida species, highlighting the clinical significance of understanding the molecular basis of resistance . Comparative studies across multiple Candida species, including C. albicans, C. parapsilosis complex, and C. glabrata, would provide valuable insights into whether RPS13-mediated resistance mechanisms are conserved or species-specific .

How can CRISPR-Cas9 be utilized to modify the RPS13 gene in C. maltosa?

CRISPR-Cas9 technology offers powerful approaches for precise genetic modification of the RPS13 gene in Candida maltosa, enabling detailed functional studies of this ribosomal protein. When designing a CRISPR-Cas9 system for C. maltosa, researchers should first optimize codon usage of the Cas9 gene for expression in this organism, as has been done for other Candida species. Guide RNA (gRNA) design is critical and should target unique sequences within the RPS13 gene to minimize off-target effects, with specific attention to the PAM (protospacer adjacent motif) requirements of the Cas9 variant being used. Multiple gRNAs targeting different regions of the RPS13 gene should be designed and tested to identify those with the highest editing efficiency.

For delivery of the CRISPR-Cas9 components into C. maltosa, electroporation or lithium acetate-based transformation methods adapted from protocols for other Candida species can be employed. When studying essential genes like RPS13, conditional knockout strategies are preferable, such as placing the gene under the control of inducible promoters or using auxin-inducible degron tags for protein-level regulation. Homology-directed repair templates should be designed to introduce specific mutations of interest or reporter tags while maintaining the reading frame and expression levels of RPS13. Following transformation, comprehensive screening methods including PCR, Sanger sequencing, and potentially whole-genome sequencing should be employed to confirm successful gene editing and identify any off-target effects. Phenotypic characterization of the modified strains should include growth rate analysis, ribosome profiling, and specific functional assays related to translation efficiency and accuracy.

What approaches can be used to study the impact of RPS13 on C. maltosa pathogenicity?

Investigating the relationship between RPS13 and C. maltosa pathogenicity requires integrating molecular genetics with infection models. Using CRISPR-Cas9 or other genetic manipulation techniques, researchers can create strains with modified RPS13 expression levels (overexpression, knockdown, or conditional knockout) or introduce specific mutations to assess their impact on virulence factors. Critical virulence determinants to evaluate include adherence to epithelial cells, biofilm formation, hyphal morphogenesis, and secretion of hydrolytic enzymes. The mechanisms of epithelial cell invasion described for C. albicans—including attachment to epithelial cells, recognition by epithelial cells, induction of endocytosis, and initiation of apoptotic events—provide a framework for investigating similar processes in C. maltosa .

How does C. maltosa RPS13 compare structurally and functionally to RPS13 proteins from other Candida species?

Comparative analysis of RPS13 across Candida species provides valuable insights into evolutionary conservation and species-specific adaptations of this essential ribosomal protein. Sequence alignment of RPS13 proteins from C. maltosa, C. albicans, C. glabrata, C. parapsilosis, and C. tropicalis reveals the degree of conservation within the genus Candida . Researchers should focus on identifying conserved functional domains related to RNA binding, ribosome assembly, and potential regulatory regions. Particular attention should be paid to regions with known functions in human RPS13, such as those involved in binding to intron 1 of its pre-mRNA for autoregulation . Structural prediction using homology modeling based on available crystal structures of RPS13 from other eukaryotes can highlight species-specific structural features that might relate to functional differences.

Functional comparisons require expression and purification of RPS13 from multiple Candida species, followed by in vitro assays testing RNA binding specificity, autoregulatory potential, and contribution to ribosome assembly. These analyses will determine whether the apparent association constant of 5.0 × 10^7 M^-1 observed for human RPS13 binding to its pre-mRNA is conserved in Candida species . Complementation studies in which the native RPS13 gene is replaced with orthologs from other species can reveal functional equivalence or species-specific requirements. Evolutionary rate analysis comparing synonymous and non-synonymous substitution rates can identify regions under selective pressure, potentially indicating functional importance or adaptation to specific environmental niches. Integration of these comparative analyses with ecological and pathogenicity data for different Candida species may reveal correlations between RPS13 features and pathogenic potential or habitat specificity.

What computational tools are most useful for analyzing C. maltosa RPS13 structure and function?

Computational analysis of C. maltosa RPS13 requires a suite of bioinformatic tools addressing different aspects of protein structure and function. For primary sequence analysis, BLAST and CLUSTAL Omega enable identification of homologs and multiple sequence alignments to reveal conserved regions across species. Phylogenetic analysis tools such as MEGA, PhyML, or MrBayes can construct evolutionary trees to place C. maltosa RPS13 in proper evolutionary context within the Candida genus and broader fungal kingdom. Structure prediction through homology modeling using SWISS-MODEL, Phyre2, or I-TASSER produces three-dimensional models based on known structures of RPS13 from other organisms, which can be visualized and analyzed using PyMOL or UCSF Chimera.

For RNA-binding site prediction, tools such as BindN, RBPmap, and catRAPID identify potential nucleic acid interaction surfaces based on amino acid composition, charge distribution, and structural features. Molecular dynamics simulations using GROMACS or AMBER can provide insights into the dynamic behavior of C. maltosa RPS13, particularly its interactions with RNA and other ribosomal components. Functional domain analysis using InterPro, Pfam, or SMART identifies conserved domains and their potential roles. Codon usage analysis tools are valuable for optimizing heterologous expression of C. maltosa RPS13 in various expression systems. Sequence-based prediction of post-translational modifications using NetPhos, UbPred, or GPS helps identify potential regulatory sites affecting protein function. Integrating these computational approaches provides a comprehensive understanding of C. maltosa RPS13 that guides experimental design and interpretation of results in the broader context of ribosomal protein biology and fungal evolution.