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Updated: Jun 19, 2026
Yeast As a Chassis for Developing Functional Assays to Study Human P53
Published on: August 4, 2019
Assessing pathogenicity of MLH1 variants by co-expression of human MLH1 and PMS2 genes in yeast
Matjaz Vogelsang1, Aleksandra Comino, Neja Zupanec
1Department for Biosynthesis and Biotransformation, National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana, Slovenia. matjaz.vogelsang@ki.si
Background:
Loss of DNA mismatch repair (MMR) in humans, mainly due to mutations in the hMLH1 gene, is linked to hereditary nonpolyposis colorectal cancer (HNPCC). Because not all MLH1 alterations result in loss of MMR function, accurate characterization of variants and their classification in terms of their effect on MMR function is essential for reliable genetic testing and effective treatment. To date, in vivo assays for functional characterization of MLH1 mutations performed in various model systems have used episomal expression of the modified MMR genes. We describe here a novel approach to determine accurately the functional significance of hMLH1 mutations in vivo, based on co-expression of human MLH1 and PMS2 in yeast cells.
Methods:
Yeast MLH1 and PMS1 genes, whose protein products form the MutLalpha complex, were replaced by human orthologs directly on yeast chromosomes by homologous recombination, and the resulting MMR activity was tested.
Results:
The yeast strain co-expressing hMLH1 and hPMS2 exhibited the same mutation rate as the wild-type. Eight cancer-related MLH1 variants were introduced, using the same approach, into the prepared yeast model, and their effect on MMR function was determined. Five variants (A92P, S93G, I219V, K618R and K618T) were classified as non-pathogenic, whereas variants T117M, Y646C and R659Q were characterized as pathogenic.
Conclusion:
Results of our in vivo yeast-based approach correlate well with clinical data in five out of seven hMLH1 variants and the described model was thus shown to be useful for functional characterization of MLH1 variants in cancer patients found throughout the entire coding region of the gene.
Insights
This study developed a novel yeast model to accurately assess the function of MLH1 gene variants, crucial for diagnosing hereditary nonpolyposis colorectal cancer (HNPCC). The findings aid in classifying MLH1 variants for improved genetic testing and patient treatment.
Area of Science:
- Genetics
- Molecular Biology
- Cancer Research
Background:
- Loss of DNA mismatch repair (MMR) due to hMLH1 gene mutations is linked to hereditary nonpolyposis colorectal cancer (HNPCC).
- Accurate functional characterization of MLH1 variants is essential for genetic testing and treatment of HNPCC.
- Existing in vivo assays often use episomal expression, which may not fully reflect in vivo conditions.
Purpose of the Study:
- To develop and validate a novel in vivo yeast-based model for accurate functional characterization of hMLH1 variants.
- To assess the pathogenicity of cancer-related hMLH1 variants using this new model.
- To improve the reliability of genetic testing for HNPCC patients.
Main Methods:
- Replaced yeast MLH1 and PMS1 genes with human orthologs (hMLH1 and hPMS2) on yeast chromosomes via homologous recombination.
- Co-expressed hMLH1 and hPMS2 in yeast to create a functional human MMR system.
- Introduced eight cancer-related hMLH1 variants into the yeast model and assessed their effect on MMR activity.
Main Results:
- The yeast strain co-expressing hMLH1 and hPMS2 demonstrated MMR activity comparable to wild-type yeast.
- Five of the eight tested hMLH1 variants (A92P, S93G, I219V, K618R, K618T) were classified as non-pathogenic.
- Three variants (T117M, Y646C, R659Q) were classified as pathogenic, indicating a loss of MMR function.
Conclusions:
- The novel yeast-based model accurately characterizes the functional significance of hMLH1 variants in vivo.
- Results from this model correlate well with existing clinical data for most tested variants.
- This approach provides a valuable tool for functional characterization of MLH1 variants across the entire coding region in cancer patients.
