Recombinant Saccharomyces cerevisiae Putative increased recombination centers protein 11 (IRC11)

What is IRC11 and what is its function in Saccharomyces cerevisiae?

IRC11 (Putative Increased Recombination Centers Protein 11) is a 156-amino acid protein encoded by the IRC11 gene (YOR013W) in Saccharomyces cerevisiae. While its precise molecular function remains under investigation, it's classified among proteins involved in recombination center regulation based on genetic studies.

IRC11 likely contributes to homologous recombination pathways that are critical for maintaining genomic stability in yeast. Its classification suggests a potential role in regulating recombination frequency, possibly by interacting with known recombination machinery components. The protein's modest size (156 amino acids) suggests it may function as part of a larger complex rather than as an independent enzymatic unit.

How does IRC11 deletion affect yeast phenotypes?

IRC11 knockout studies suggest it may function in recombination regulation, though the phenotypes are subtle compared to major recombination factors. Based on current understanding of increased recombination center proteins:

• IRC11 deletion likely doesn't compromise cell viability under standard growth conditions, unlike deletion of essential recombination factors (MRE11, RAD50, XRS2)

• Deletion may increase recombination frequencies at certain genomic loci

• Effects may be more pronounced under genotoxic stress conditions

• IRC11 knockout phenotypes likely interact with mutations in other recombination pathway genes

For comprehensive phenotypic assessment, researchers should measure:

• Spontaneous recombination rates using reporter systems

• Sensitivity to DNA-damaging agents (UV, MMS, hydroxyurea)

• Genetic interactions with known recombination mutants

• Cell cycle progression under normal and stress conditions

What are the recommended methods for expressing and purifying recombinant IRC11?

Based on established protocols for recombinant yeast proteins:

Expression system optimization:

• E. coli is the preferred expression system (BL21(DE3) strain recommended)

• Add N-terminal His-tag for simplified purification

• Express as a full-length protein (1-156aa) rather than truncated versions

• Optimize induction conditions: 0.5mM IPTG, 16-20°C overnight for improved solubility

Purification protocol:

• Harvest cells and lyse in Tris/PBS-based buffer (pH 8.0) containing:

  • 300mM NaCl

  • 20mM imidazole

  • 1mM DTT

  • Protease inhibitor cocktail

  • Optional: 6% trehalose for stability

• Purify using immobilized metal affinity chromatography (IMAC):

  • Bind to Ni-NTA resin

  • Wash with buffer containing 50mM imidazole

  • Elute with buffer containing 250mM imidazole

• Further purification by size exclusion chromatography

• Storage recommendations:

  • Store in Tris/PBS buffer with 6% trehalose (pH 8.0)

  • Add 5-50% glycerol before freezing at -20°C/-80°C

  • Avoid repeated freeze-thaw cycles

  • Working aliquots can be stored at 4°C for up to one week

What antibody options exist for IRC11 detection and what are their applications?

Commercial antibodies against IRC11 are available for research applications:

Available antibody specifications:

• Polyclonal rabbit antibody against recombinant S. cerevisiae IRC11

• Raised against full-length recombinant IRC11 protein

• Supplied in liquid form in 50% glycerol, 0.01M PBS (pH 7.4) with 0.03% Proclin 300 preservative

• Purified by antigen affinity methods

Recommended applications:

• Western blotting:

  • Use 1:1000-1:2000 dilution

  • Confirm using anti-tubulin as loading control

  • Block with 5% non-fat milk in TBST

• ELISA assays:

  • For quantitative detection of IRC11 in cell lysates

  • Use standard curves with purified recombinant IRC11

• Immunoprecipitation:

  • For studying protein-protein interactions

  • Cross-validate findings with reciprocal IP

• Immunofluorescence:

  • Requires additional validation

  • Fixation optimization may be necessary

How does IRC11 interact with known recombination pathways in yeast?

While specific IRC11 interaction data is limited, its function can be contextualized within established yeast recombination pathways:

• Homologous recombination (HR) connections:

  • IRC11 likely functions in similar contexts as other recombination center proteins

  • May interact with the MRX complex (Mre11-Rad50-Xrs2), which is crucial for processing double-strand breaks (DSBs)

  • Could potentially function alongside Rad51, a key recombination protein

• Non-homologous end joining (NHEJ) relation:

  • Some recombination proteins like Rev7 promote NHEJ while inhibiting HR in yeast

  • IRC11 could potentially influence the choice between repair pathways similar to Rev7

  • Interaction with NHEJ factors like Ku70/Ku80 should be investigated

• Cell cycle checkpoint interactions:

  • Recombination and checkpoint pathways function independently but synergistically to suppress recombination

  • IRC11 might function within this regulatory network

  • Study potential genetic interactions with RAD9-mediated checkpoint genes

To systematically map IRC11's role:

• Perform synthetic genetic array (SGA) analysis with IRC11 deletion

• Analyze epistasis relationships with known recombination mutants

• Measure recombination rates in double mutants (IRC11 with checkpoint or recombination genes)

• Assess IRC11's influence on radiation-induced recombination frequencies

What experimental approaches best characterize IRC11's role in DNA repair?

Several complementary approaches can elucidate IRC11's function in DNA repair:

• Recombination assays:

  • Suicide-deletion assay using I-SceI endonuclease to measure NHEJ efficiency

  • Homology-directed translocation assays to measure recombination frequencies

  • Heteroallelic recombination systems to measure gene conversion rates

• DNA damage sensitivity testing:

  • Analyze sensitivity to various DNA-damaging agents (UV, X-rays, MMS, HU)

  • Compare survival curves between wild-type and IRC11 mutant strains

  • Construct exposure response curves at multiple doses

• Microscopy techniques:

  • Immunofluorescence to track IRC11 localization after DNA damage

  • Live-cell imaging with fluorescently tagged IRC11

  • Co-localization studies with known repair factors

• Biochemical approaches:

  • In vitro assays to test potential enzymatic activities

  • Pull-down experiments to identify interaction partners

  • ChIP assays to detect genomic binding sites

Example experimental design for damage sensitivity assay:

How can researchers measure the effect of IRC11 on recombination frequencies?

To quantify IRC11's impact on recombination, several established systems can be employed:

• Plasmid-based recombination assays:

  • Use systems like the 2-μm plasmid assay to measure plasmid segregation efficiency

  • Compare plasmid loss rates between wild-type and IRC11 mutant strains

  • Calculate segregation efficiency as the ratio of colonies on selective media to total colonies

• Chromosomal recombination reporters:

  • Direct-repeat recombination systems with selectable markers

  • Heteroallelic recombination systems to detect gene conversion events

  • Homology-directed translocation assay systems

• Radiation-induced recombination measurement:

  • Expose cells to defined X-ray or UV doses (e.g., 2, 4, 8 krad X-ray or 60, 90, 120, 150 J/m²)

  • Measure recombination frequencies using appropriate reporter systems

  • Calculate net recombination frequencies by subtracting spontaneous frequencies

• Quantitative PCR approaches:

  • Design primers specific to recombination products

  • Use real-time PCR to quantify recombination events

  • Similar to the approach used for HAC1 splicing detection

Example data presentation format:

How does IRC11 expression vary under different environmental conditions?

To comprehensively characterize IRC11 expression patterns:

• Growth condition variations:

  • Test standard laboratory conditions vs. stress conditions

  • Compare rich media (YPD) vs. minimal media (SC)

  • Examine growth at different temperatures (23°C, 30°C, 37°C, 39°C)

  • Assess expression during fermentation at different pH levels (3.5, 4.5, 5.5, 6.5)

• Cell cycle analysis:

  • Synchronize cells using α-factor arrest-release

  • Collect samples at defined time points throughout the cell cycle

  • Quantify IRC11 mRNA and protein levels

• DNA damage response:

  • Treat cells with various DNA-damaging agents (MMS, UV, X-rays)

  • Monitor expression changes using RT-qPCR and Western blot

  • Track expression kinetics during DNA damage response

• Promoter analysis:

  • Use promoter replacement strategies (e.g., with strong TDH3 promoter)

  • Apply CRISPR-Cas9 to modify endogenous promoter elements

  • Correlate expression changes with phenotypic outcomes

Methodological approach for RT-qPCR analysis:

• Design primers specific to IRC11 mRNA

• Use reference genes like ACT1 for normalization

• Present data as fold-change relative to standard conditions

• Analyze statistical significance using appropriate tests (ANOVA, t-test)

What genetic interactions does IRC11 display with other recombination and checkpoint pathway genes?

To map IRC11's functional relationships:

• Systematic double knockout analysis:

  • Generate double mutants with key recombination genes (RAD51, RAD52, MRE11, RAD50, XRS2)

  • Create double mutants with checkpoint genes (RAD9, MEC1)

  • Assess synthetic lethality or fitness defects

• Quantitative phenotypic analysis:

  • Measure recombination rates in single vs. double mutants

  • Compare radiation sensitivity between single and double mutants

  • Assess growth rates using doubling time measurements

• Epistasis analysis:

  • Determine whether IRC11 functions upstream, downstream, or in parallel to known pathways

  • Analyze double and triple mutant phenotypes to establish pathway relationships

  • Use overexpression studies to complement deletion phenotypes

Research has shown that double mutants defective in both recombination repair genes and checkpoint function exhibit synergistic increases in spontaneous recombination rates . Similar analysis with IRC11 could reveal its pathway position.

Example genetic interaction data presentation:

How do IRC11 functions compare with its homologs in other species?

To understand IRC11's evolutionary context:

• Homology identification:

  • Perform BLAST searches against fungal genomes

  • Conduct phylogenetic analysis of IRC family proteins across yeast species

  • Use more sensitive profile-based searches (HMM) for distant homologs

• Functional complementation:

  • Express putative homologs in S. cerevisiae IRC11Δ strains

  • Test if homologs rescue IRC11 deletion phenotypes

  • Analyze domain conservation and functional motifs

• Comparative genomics:

  • Assess IRC11 conservation across Saccharomycetales species

  • Compare with related proteins in pathogenic yeasts like Candida albicans

  • Determine if IRC11-like proteins exist in higher eukaryotes

• Evolutionary rate analysis:

  • Calculate selection pressure (dN/dS ratios) on IRC11 across species

  • Identify rapidly evolving vs. conserved regions

  • Correlate with functional importance (essential genes typically show higher conservation)

Methodological considerations:

• For distant homologs, focus on structural similarity rather than sequence identity

• Consider synteny (conservation of chromosomal context) as evidence for orthology

• Test multiple alignment algorithms to improve homology detection

• Use protein structure prediction to identify functional conservation despite sequence divergence

What are the challenges in reconciling contradictory data about IRC11 function?

Researchers may encounter contradictory results when studying IRC11. Strategies to address such conflicts include:

• Experimental variability assessment:

  • Biological replicates show high variability even for established phenotypes

  • Multiple replicates are essential (>7) to achieve acceptable confidence intervals

  • Day-specific stress or culture conditions can cause significant variability

• Strain background considerations:

  • Compare results between different strain backgrounds (BY4741 vs. CEN.PK vs. W303)

  • Check for suppressor mutations that might affect phenotypic outcomes

  • Consider different auxotrophic markers that might influence results

• Growth condition standardization:

  • Standard laboratory environments may mask phenotypes

  • Test multiple media formulations (YPD, SC, YNB)

  • Examine different carbon sources (glucose, galactose)

• Statistical rigor:

  • Apply appropriate statistical tests (Wilcoxon, t-test, ANOVA)

  • Be cautious about statistical significance with large sample sizes

  • Consider biological significance beyond statistical significance

As noted in studies of other yeast genes, "although often significant from a statistical viewpoint due to the huge number of microcolonies that were analyzed, the differences that fluctuate sometimes in one direction and sometimes in the other [...] suggest that the initial expression level in a cell does not influence the subsequent growth rate" . Similar challenges may apply to IRC11 research.

What novel approaches could reveal IRC11's precise molecular function?

Emerging technologies offer new opportunities to characterize IRC11:

• Proteomics approaches:

  • BioID or APEX proximity labeling to identify interaction partners in vivo

  • Crosslinking mass spectrometry (XL-MS) to map protein interaction interfaces

  • Hydrogen-deuterium exchange mass spectrometry for structural dynamics

• High-resolution microscopy:

  • Super-resolution microscopy to visualize IRC11 localization at recombination centers

  • Single-molecule tracking to monitor IRC11 dynamics during recombination

  • FRET-based approaches to detect protein-protein interactions in living cells

• Genomics methods:

  • ChIP-seq to identify IRC11 binding sites genome-wide

  • CUT&RUN for higher resolution binding profiles

  • HiChIP to detect long-range chromatin interactions mediated by IRC11

• CRISPR-based approaches:

  • CRISPRi for tunable repression of IRC11 expression

  • CRISPR activation to study overexpression effects

  • Base editing to introduce specific mutations without DSB formation

How might IRC11 research contribute to broader understanding of genetic stability mechanisms?

IRC11 research has implications beyond basic yeast biology:

• Model system advantages:

  • S. cerevisiae is an ideal model for studying fundamental recombination mechanisms

  • Many recombination pathways are conserved from yeast to humans

  • Yeast genetic robustness studies reveal functional backup systems

• Translational relevance:

  • Understanding recombination regulation has implications for genomic instability in cancer

  • Recombination proteins are potential therapeutic targets

  • Insights from yeast homologs inform human disease mechanisms

• Biotechnology applications:

  • Improved yeast strains with optimized recombination properties for genetic engineering

  • Enhanced homologous recombination for gene targeting applications

  • Exploitation of yeast recombination for synthetic biology applications

• Evolutionary insights:

  • How recombination center proteins evolved to maintain genomic stability

  • Relationship between environmental adaptation and recombination regulation

  • Role of recombination in yeast population genetics and speciation