Signification and Application of Mutator and Antimutator Phenotype-Induced Genetic Variations in Evolutionary Adaptation and Cancer Therapeutics.

Mutations present a dichotomy in their implications for cellular processes. They primarily arise from DNA replication errors or damage repair processes induced by environmental challenges. Cumulative mutations underlie genetic variations and drive evolution, yet also contribute to degenerative diseases such as cancer and aging. The mutator phenotype elucidates the heightened mutation rates observed in malignant tumors. Evolutionary adaptation, analogous to bacterial and eukaryotic systems, manifests through mutator phenotypes during changing environmental conditions, highlighting the delicate balance between advantageous mutations and their potentially detrimental consequences. Leveraging the genetic tractability of Saccharomyces cerevisiae offers unique insights into mutator phenotypes and genome instability akin to human cancers. Innovative reporter assays in yeast model organisms enable the detection of diverse genome alterations, aiding a comprehensive analysis of mutator phenotypes. Despite significant advancements, our understanding of the intricate mechanisms governing spontaneous mutation rates and preserving genetic integrity remains incomplete. This review outlines various cellular pathways affecting mutation rates and explores the role of mutator genes and mutation-derived phenotypes, particularly prevalent in malignant tumor cells. An in-depth comprehension of mutator and antimutator activities in yeast and higher eukaryotes holds promise for effective cancer control strategies.

Characterization of POLE c.1373A > T p.(Tyr458Phe), causing high cancer risk.

The cancer syndrome polymerase proofreading-associated polyposis results from germline mutations in the POLE and POLD1 genes. Mutations in the exonuclease domain of these genes are associated with hyper- and ultra-mutated tumors with a predominance of base substitutions resulting from faulty proofreading during DNA replication. When a new variant is identified by gene testing of POLE and POLD1, it is important to verify whether the variant is associated with PPAP or not, to guide genetic counseling of mutation carriers. In 2015, we reported the likely pathogenic (class 4) germline POLE c.1373A > T p.(Tyr458Phe) variant and we have now characterized this variant to verify that it is a class 5 pathogenic variant. For this purpose, we investigated (1) mutator phenotype in tumors from two carriers, (2) mutation frequency in cell-based mutagenesis assays, and (3) structural consequences based on protein modeling. Whole-exome sequencing of two tumors identified an ultra-mutator phenotype with a predominance of base substitutions, the majority of which are C > T. A SupF mutagenesis assay revealed increased mutation frequency in cells overexpressing the variant of interest as well as in isogenic cells encoding the variant. Moreover, exonuclease repair yeast-based assay supported defect in proofreading activity. Lastly, we present a homology model of human POLE to demonstrate structural consequences leading to pathogenic impact of the p.(Tyr458Phe) mutation. The three lines of evidence, taken together with updated co-segregation and previously published data, allow the germline variant POLE c.1373A > T p.(Tyr458Phe) to be reclassified as a class 5 variant. That means the variant is associated with PPAP.

Detection and characterization of constitutive replication origins defined by DNA polymerase epsilon.

BACKGROUND: Despite the process of DNA replication being mechanistically highly conserved, the location of origins of replication (ORI) may vary from one tissue to the next, or between rounds of replication in eukaryotes, suggesting flexibility in the choice of locations to initiate replication. Lists of human ORI therefore vary widely in number and location, and there are currently no methods available to compare them. Here, we propose a method of detection of ORI based on somatic mutation patterns generated by the mutator phenotype of damaged DNA polymerase epsilon (POLE). RESULTS: We report the genome-wide localization of constitutive ORI in POLE-mutated human tumors using whole genome sequencing data. Mutations accumulated after many rounds of replication of unsynchronized dividing cell populations in tumors allow to identify constitutive origins, which we show are shared with high fidelity between individuals and tumor types. Using a Smith-Waterman-like dynamic programming approach, we compared replication origin positions obtained from multiple different methods. The comparison allowed us to define a consensus set of replication origins, identified consistently by multiple ORI detection methods. Many DNA features co-localized with the consensus set of ORI, including chromatin loop anchors, G-quadruplexes, S/MARs, and CpGs. Among all features, the H2A.Z histone exhibited the most significant association. CONCLUSIONS: Our results show that mutation-based detection of replication origins is a viable approach to determining their location and associated sequence features.

Common themes in antimicrobial and anticancer drug resistance.

Antimicrobial and anticancer drug resistance represent two of the main global challenges for the public health, requiring immediate practical solutions. In line with this, we need a better understanding of the origins of drug resistance in prokaryotic and eukaryotic cells and the evolutionary processes leading to the occurrence of adaptive phenotypes in response to the selective pressure of therapeutic agents. The purpose of this paper is to present some of the analogies between the antimicrobial and anticancer drug resistance. Antimicrobial and anticancer drugs share common targets and mechanisms of action as well as similar mechanisms of resistance (e.g., increased drug efflux, drug inactivation, target alteration, persister cells' selection, protection of bacterial communities/malignant tissue by an extracellular matrix, etc.). Both individual and collective stress responses triggered by the chemotherapeutic agent involving complex intercellular communication processes, as well as with the surrounding microenvironment, will be considered. The common themes in antimicrobial and anticancer drug resistance recommend the utility of bacterial experimental models for unraveling the mechanisms that facilitate the evolution and adaptation of malignant cells to antineoplastic drugs.

Comprehensive Analyses of Mutation-Derived Long-Chain Noncoding RNA Signatures of Genome Instability in Kidney Renal Papillary Cell Carcinoma.

Background: The role of long-chain noncoding RNA (lncRNA) in genomic instability has been demonstrated to be increasingly importance. Therefore, in this study, lncRNAs associated with genomic instability were identified and kidney renal papillary cell carcinoma (KIRP)-associated predictive features were analysed to classify high-risk patients and improve individualised treatment. Methods: The training (n = 142) and test (n = 144) sets were created using raw RNA-seq and patient's clinical data of KIRP obtained from The Cancer Genome Atlas (TCGA).There are 27 long-chain noncoding RNAs (lncRNAs) that are connected with genomic instability, these lncRNAs were identified using the 'limma' R package based on the numbers of somatic mutations and lncRNA expression profiles acquired from KIRP TCGA cohort. Furthermore, Cox regression analysis was carried out to develop a genome instability-derived lncRNA-based gene signature (GILncSig), whose prognostic value was confirmed in the test cohort as well as across the entire KIRP TCGA dataset. Results: A GILncSig derived from three lncRNAs (BOLA3-AS1, AC004870, and LINC00839), which were related with poor KIRP survival, was identified, which was split up into high- and low-risk groups. Additionally, the GILncSig was found to be an independent prognostic predictive index in KIRP using univariate and multivariate Cox analysis. Furthermore, the prognostic significance and characteristics of GilncSig were confirmed in the training test and TCGA sets. GilncSig also showed better predictive performance than other prognostic lncRNA features. Conclusion: The function of lncRNAs in genomic instability and the genetic diversity of KIRP were elucidated in this work. Moreover, three lncRNAs were screened for prediction of the outcome of KIRP survival and novel insights into identifying cancer biomarkers related to genomic instability were discussed.

Germline MBD4 deficiency causes a multi-tumor predisposition syndrome.

We report an autosomal recessive, multi-organ tumor predisposition syndrome, caused by bi-allelic loss-of-function germline variants in the base excision repair (BER) gene MBD4. We identified five individuals with bi-allelic MBD4 variants within four families and these individuals had a personal and/or family history of adenomatous colorectal polyposis, acute myeloid leukemia, and uveal melanoma. MBD4 encodes a glycosylase involved in repair of G:T mismatches resulting from deamination of 5'-methylcytosine. The colorectal adenomas from MBD4-deficient individuals showed a mutator phenotype attributable to mutational signature SBS1, consistent with the function of MBD4. MBD4-deficient polyps harbored somatic mutations in similar driver genes to sporadic colorectal tumors, although AMER1 mutations were more common and KRAS mutations less frequent. Our findings expand the role of BER deficiencies in tumor predisposition. Inclusion of MBD4 in genetic testing for polyposis and multi-tumor phenotypes is warranted to improve disease management.

Computational detection of a genome instability-derived lncRNA signature for predicting the clinical outcome of lung adenocarcinoma.

Evidence has been emerging of the importance of long non-coding RNAs (lncRNAs) in genome instability. However, no study has established how to classify such lncRNAs linked to genomic instability, and whether that connection poses a therapeutic significance. Here, we established a computational frame derived from mutator hypothesis by combining profiles of lncRNA expression and those of somatic mutations in a tumor genome, and identified 185 candidate lncRNAs associated with genomic instability in lung adenocarcinoma (LUAD). Through further studies, we established a six lncRNA-based signature, which assigned patients to the high- and low-risk groups with different prognosis. Further validation of this signature was performed in a number of separate cohorts of LUAD patients. In addition, the signature was found closely linked to genomic mutation rates in patients, indicating it could be a useful way to quantify genomic instability. In summary, this research offered a novel method by through which more studies may explore the function of lncRNAs and presented a possible new way for detecting biomarkers associated with genomic instability in cancers.

Six mutator-derived lncRNA signature of genome instability for predicting the clinical outcome of colon cancer.

BACKGROUND: Colon adenocarcinoma (COAD) is one of the most common malignancies worldwide. Genomic instability is one of the hallmarks of colon cancer and is associated with prognosis. Nevertheless, the impact of genome instability-associated long non-coding RNAs (lncRNAs) along with their clinical significance in cancers has remained mostly unexplored. METHODS: In this study, a mutator hypothesis-derived computational frame integrating the somatic mutation profiles and lncRNA expression profiles in a tumor genome was developed, which enabled the identification of 137 novel genomic instability-associated lncRNAs in colon cancer. Subsequently, a genome instability-derived lncRNA signature (GILncSig) segregated the patients into low- and high-risk groups with prominent differences in outcomes. RESULTS: Combined with the overall survival data, we established 6 six lncRNA-based signature to predict prognosis, which were LINC00896, AC007996.1, NKILA, AP003555.2, MIRLET7BHG, and AC009237.14. We found that the expression level of PD-L1 (CD274) and somatic mutations in the high-risk group were higher than those in the low-risk group. This suggests that high-risk patients may be sensitive to immunotherapy. We further found that the prognosis of patients in the high-risk group was significantly lower than that of patients in the low-risk group, and that patients' prognosis was likely to be worse as the patient's risk score increased. CONCLUSIONS: In conclusion, this study explores the role of lncRNAs in genomic instability and cancer prognosis and provides a new idea for the prognostic prediction of colon cancer.

Genomic Instability-Related LncRNA Signature Predicts the Prognosis and Highlights LINC01614 Is a Tumor Microenvironment-Related Oncogenic lncRNA of Papillary Thyroid Carcinoma.

BACKGROUND: Genomic instability (GI) is among the top ten characteristics of malignancy. Long non-coding RNAs (lncRNAs) are promising cancer biomarkers that are reportedly involved in GI. So far, the clinical value of GI-related lncRNAs (GIlncs) in papillary thyroid cancer (PTC) has not been clarified. METHODS: Integrative analysis of lncRNA expression and somatic mutation profiles was performed to identify GIlncs. Analysis of differentially expressed lncRNAs in the group with high- and low- cumulative number of somatic mutations revealed significant GIlncs in PTC. Univariate and multivariate Cox proportional hazard regression analyses were performed to identify hub-GIlncs. RESULTS: A computational model based on four lncRNAs (FOXD2-AS1, LINC01614, AC073257.2, and AC005082.1) was identified as a quantitative index using an in-silicon discovery cohort. GILS score was significantly associated with poor prognosis, as validated in the TCGA dataset and further tested in our local RNA-Seq cohort. Moreover, a combination of clinical characteristics and the composite GILS-clinical prognostic nomogram demonstrates satisfactory discrimination and calibration. Furthermore, the GILS score and FOXD2-AS1, LINC01614, AC073257.2, and AC005082.1 were also associated with driver mutations and multiple clinical-pathological variables, respectively. Moreover, RNA-Seq confirmed the expression patterns of FOXD2-AS1, LINC01614, AC073257.2, and AC005082.1 in PTC and normal thyroid tissues. Biological experiments demonstrated that downregulated or overexpressed LINC01614 affect PTC cell proliferation, migration, and invasion in vitro. Activation of the stromal and immune cell infiltration was also observed in the high LINC01614 group in the PTC microenvironment. CONCLUSION: In summary, we identified a signature for clinical outcome prediction in PTC comprising four lncRNAs associated with GI. A better understanding of the GI providing an alternative evaluation of the progression risk of PTC. Our study also demonstrated LINC01614 as a novel oncogenic lncRNA and verified its phenotype in PTC.

Calculated identification of mutator-derived lncRNA signatures of genomic instability to predict the clinical outcome of muscle-invasive bladder cancer.

BACKGROUND: Muscle-invasive bladder cancer (MIBC) is one of the most important type of bladder cancer, with a high morbidity and mortality rate. Studies have found that long non-coding RNA (lncRNA) plays a key role in maintaining genomic instability. However, Identification of lncRNAs related to genomic instability (GIlncRNAs) and their clinical significance in cancers have not been extensively studied yet. METHODS: Here, we downloaded the lncRNA expression profiles, somatic mutation profiles and clinical related data in MIBC patients from The Cancer Genome Atlas (TCGA) database. A lncRNA computational framework was used to find differentially expressed GIlncRNAs. Multivariate Cox regression analysis was used to construct a genomic instability-related lncRNA signature (GIlncSig). Univariate and multivariate Cox analyses were used to assess the independent prognostic for the GIlncSig and other key clinical factors. RESULTS: We found 43 differentially expressed GIlncRNAs and constructed the GIlncSig with 6 GIlncRNAs in the training cohort. The patients were divided into two risk groups. The overall survival of patients in the high-risk group was lower than that in the low-risk group (P < 0.001), which were further verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression showed that the GIlncSig was an independent prognostic factor. In addition, the GIlncSig correlated with the genomic mutation rate of MIBC, indicating its potential as a measure of the degree of genomic instability. The GIlncSig was able to divide FGFR3 wild- and mutant-type patients into two risk groups, and effectively enhanced the prediction effect. CONCLUSION: Our study introduced an important reference for further research on the role of GIlncRNAs, and provided prognostic indicators and potential biological therapy targets for MIBC.

A modified fluctuation assay reveals a natural mutator phenotype that drives mutation spectrum variation within Saccharomyces cerevisiae.

Although studies of Saccharomyces cerevisiae have provided many insights into mutagenesis and DNA repair, most of this work has focused on a few laboratory strains. Much less is known about the phenotypic effects of natural variation within S. cerevisiae's DNA repair pathways. Here, we use natural polymorphisms to detect historical mutation spectrum differences among several wild and domesticated S. cerevisiae strains. To determine whether these differences are likely caused by genetic mutation rate modifiers, we use a modified fluctuation assay with a CAN1 reporter to measure de novo mutation rates and spectra in 16 of the analyzed strains. We measure a 10-fold range of mutation rates and identify two strains with distinctive mutation spectra. These strains, known as AEQ and AAR, come from the panel's 'Mosaic beer' clade and share an enrichment for C > A mutations that is also observed in rare variation segregating throughout the genomes of several Mosaic beer and Mixed origin strains. Both AEQ and AAR are haploid derivatives of the diploid natural isolate CBS 1782, whose rare polymorphisms are enriched for C > A as well, suggesting that the underlying mutator allele is likely active in nature. We use a plasmid complementation test to show that AAR and AEQ share a mutator allele in the DNA repair gene OGG1, which excises 8-oxoguanine lesions that can cause C > A mutations if left unrepaired.

An MHV-68 Mutator Phenotype Mutant Virus, Confirmed by CRISPR/Cas9-Mediated Gene Editing of the Viral DNA Polymerase Gene, Shows Reduced Viral Fitness.

Drug resistance studies on human γ-herpesviruses are hampered by the absence of an in vitro system that allows efficient lytic viral replication. Therefore, we employed murine γ-herpesvirus-68 (MHV-68) that efficiently replicates in vitro as a model to study the antiviral resistance of γ-herpesviruses. In this study, we investigated the mechanism of resistance to nucleoside (ganciclovir (GCV)), nucleotide (cidofovir (CDV), HPMP-5azaC, HPMPO-DAPy) and pyrophosphate (foscarnet (PFA)) analogues and the impact of these drug resistance mutations on viral fitness. Viral fitness was determined by dual infection competition assays, where MHV-68 drug-resistant viral clones competed with the wild-type virus in the absence and presence of antivirals. Using next-generation sequencing, the composition of the viral populations was determined at the time of infection and after 5 days of growth. Antiviral drug resistance selection resulted in clones harboring mutations in the viral DNA polymerase (DP), denoted Y383SGCV, Q827RHPMP-5azaC, G302WPFA, K442TPFA, G302W+K442TPFA, C297WHPMPO-DAPy and C981YCDV. Without antiviral pressure, viral clones Q827RHPMP-5azaC, G302WPFA, K442TPFA and G302W+K442TPFA grew equal to the wild-type virus. However, in the presence of antivirals, these mutants had a growth advantage over the wild-type virus that was moderately to very strongly correlated with antiviral resistance. The Y383SGCV mutant was more fit than the wild-type virus with and without antivirals, except in the presence of brivudin. The C297W and C981Y changes were associated with a mutator phenotype and had a severely impaired viral fitness in the absence and presence of antivirals. The mutator phenotype caused by C297W in MHV-68 DP was validated by using a CRISPR/Cas9 genome editing approach.

Evolutionary epidemiology of Streptococcus iniae: Linking mutation rate dynamics with adaptation to novel immunological landscapes.

Pathogens continuously adapt to changing host environments where variation in their virulence and antigenicity is critical to their long-term evolutionary success. The emergence of novel variants is accelerated in microbial mutator strains (mutators) deficient in DNA repair genes, most often from mismatch repair and oxidized-guanine repair systems (MMR and OG respectively). Bacterial MMR/OG mutants are abundant in clinical samples and show increased adaptive potential in experimental infection models, yet the role of mutators in the epidemiology and evolution of infectious disease is not well understood. Here we investigated the role of mutation rate dynamics in the evolution of a broad host range pathogen, Streptococcus iniae, using a set of 80 strains isolated globally over 40 years. We have resolved phylogenetic relationships using non-recombinant core genome variants, measured in vivo mutation rates by fluctuation analysis, identified variation in major MMR/OG genes and their regulatory regions, and phenotyped the major traits determining virulence in streptococci. We found that both mutation rate and MMR/OG genotype are remarkably conserved within phylogenetic clades but significantly differ between major phylogenetic lineages. Further, variation in MMR/OG loci correlates with occurrence of atypical virulence-associated phenotypes, infection in atypical hosts (mammals), and atypical (osseous) tissue of a vaccinated primary host. These findings suggest that mutators are likely to facilitate adaptations preceding major diversification events and may promote emergence of variation permitting colonization of a novel host tissue, novel host taxa (host jumps), and immune-escape in the vaccinated host.

Aspirin and the chemoprevention of cancers: A mathematical and evolutionary dynamics perspective.

Epidemiological data indicate that long-term low dose aspirin administration has a protective effect against the occurrence of colorectal cancer, both in sporadic and in hereditary forms of the disease. The mechanisms underlying this protective effect, however, are incompletely understood. The molecular events that lead to protection have been partly defined, but remain to be fully characterized. So far, however, approaches based on evolutionary dynamics have not been discussed much, but can potentially offer important insights. The aim of this review is to highlight this line of investigation and the results that have been obtained. A core observation in this respect is that aspirin has a direct negative impact on the growth dynamics of the cells, by influencing the kinetics of tumor cell division and death. We discuss the application of mathematical models to experimental data to quantify these parameter changes. We then describe further mathematical models that have been used to explore how these aspirin-mediated changes in kinetic parameters influence the probability of successful colony growth versus extinction, and how they affect the evolution of the tumor during aspirin administration. Finally, we discuss mathematical models that have been used to investigate the selective forces that can lead to the rise of mismatch-repair deficient cells in an inflammatory environment, and how this selection can be potentially altered through aspirin-mediated interventions. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.

Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer.

Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.

The Mutator Phenotype: Adapting Microbial Evolution to Cancer Biology.

The mutator phenotype hypothesis was postulated almost 40 years ago to reconcile the observation that while cancer cells display widespread mutational burden, acquisition of mutations in non-transformed cells is a rare event. Moreover, it also suggested that cancer evolution could be fostered by increased genome instability. Given the evolutionary conservation throughout the tree of life and the genetic tractability of model organisms, yeast and bacterial species pioneered studies to dissect the functions of genes required for genome maintenance (caretaker genes) or for cell growth control (gatekeeper genes). In this review, we first provide an overview of what we learned from model organisms about the roles of these genes and the genome instability that arises as a consequence of their dysregulation. We then discuss our current understanding of how mutator phenotypes shape the evolution of bacteria and yeast species. We end by bringing clinical evidence that lessons learned from single-cell organisms can be applied to tumor evolution.

New Phenotypes of Potato Co-induced by Mismatch Repair Deficiency and Somatic Hybridization.

As plants are sessile they need a very efficient system for repairing damage done by external or internal mutagens to their DNA. Mismatch repair (MMR) is one of the systems that maintain genome integrity and prevent homeologous recombination. In all eukaryotes mismatches are recognized by evolutionary conserved MSH proteins often acting as heterodimers, the constant component of which is MSH2. Changes affecting the function of MSH2 gene may induce a 'mutator' phenotype and microsatellite instability (MSI), as is demonstrated in MSH2 knock-out and silenced lines of Arabidopsis thaliana. The goal of this study was to screen for 'mutator' phenotypes in somatic hybrids between potato cvs. 'Delikat' and 'Désirée' and MMR deficient Solanum chacoense transformed using antisense (AS) or dominant negative mutant (DN) AtMSH2 genes. The results demonstrate that first generation fusion hybrids have a range of morphological abnormalities caused by uniparental MMR deficiency; these mutant phenotypes include: dwarf or gigantic plants; bushiness; curled, small, large or abnormal leaves; a deterioration in chloroplast structure; small deep-purple tubers and early dehiscent flowers. Forty percent of the viable somatic hybrids planted in a greenhouse, (10 out of 25 genotypes) had mutant phenotypes accompanied by MSI. The majority of the hybrids with 'mutator' phenotypes cultured on media containing kanamycin developed roots so sustaining the presence of selectable marker gene nptII, from the initial constructs. Here for the first time, MMR deficiency combined with somatic hybridization, are used to induce new phenotypes in plants, which supports the role of MMR deficiency in increasing introgressions between two related species.

Whole-genome sequencing enabling the detection of a colistin-resistant hypermutating Citrobacter werkmanii strain harbouring a novel metallo-ß-lactamase VIM-48.

Citrobacter spp. harbouring metallo-ß-lactamases (MBLs) have been reported from various countries and different sources, but their isolation from clinical specimens remains a rare event in Europe. MBL-harbouring Enterobacteriaceae are considered a major threat in infection control as therapeutic options are often limited to colistin. In this study, whole-genome sequencing was applied to characterise five clinical isolates of multidrug-resistant Citrobacter werkmanii obtained from rectal swabs. Four strains possessed a class 1 integron with a novel blaVIM-48 MBL resistance gene and the aminoglycoside acetyltransferase gene aacA4, whilst one isolate harboured a blaIMP-8 MBL. Resistance to colistin evolved in one strain isolated from a patient who had received colistin orally for 8 days. Genomic comparison of this strain with a colistin-susceptible pre-treatment isolate from the same patient revealed 66 single nucleotide polymorphisms (SNPs) and 26 indels, indicating the presence of a mutator phenotype. This was confirmed by the finding of a SNP in the mutL gene that led to a significantly truncated protein. Additionally, an amino acid change from glycine to serine at position 53 was observed in PmrA. Mutations in the pmrA gene have been previously described as mediating colistin resistance in different bacterial species and are the most likely reason for the susceptibility change observed. To the best of our knowledge, this is the first description of a colistin-resistant Citrobacter spp. isolated from a human sample. This study demonstrates the power of applying next-generation sequencing in a hospital setting to trace and understand evolving resistance at the level of individual patients.

Reconstitution of Saccharomyces cerevisiae DNA polymerase ε-dependent mismatch repair with purified proteins.

Mammalian and Saccharomyces cerevisiae mismatch repair (MMR) proteins catalyze two MMR reactions in vitro. In one, mispair binding by either the MutS homolog 2 (Msh2)-MutS homolog 6 (Msh6) or the Msh2-MutS homolog 3 (Msh3) stimulates 5' to 3' excision by exonuclease 1 (Exo1) from a single-strand break 5' to the mispair, excising the mispair. In the other, Msh2-Msh6 or Msh2-Msh3 activate the MutL homolog 1 (Mlh1)-postmeiotic segregation 1 (Pms1) endonuclease in the presence of a mispair and a nick 3' to the mispair, to make nicks 5' to the mispair, allowing Exo1 to excise the mispair. DNA polymerase δ (Pol δ) is thought to catalyze DNA synthesis to fill in the gaps resulting from mispair excision. However, colocalization of the S. cerevisiae mispair recognition proteins with the replicative DNA polymerases during DNA replication has suggested that DNA polymerase ε (Pol ε) may also play a role in MMR. Here we describe the reconstitution of Pol ε-dependent MMR using S. cerevisiae proteins. A mixture of Msh2-Msh6 (or Msh2-Msh3), Exo1, RPA, RFC-Δ1N, PCNA, and Pol ε was found to catalyze both short-patch and long-patch 5' nick-directed MMR of a substrate containing a +1 (+T) mispair. When the substrate contained a nick 3' to the mispair, a mixture of Msh2-Msh6 (or Msh2-Msh3), Exo1, RPA, RFC-Δ1N, PCNA, and Pol ε was found to catalyze an MMR reaction that required Mlh1-Pms1. These results demonstrate that Pol ε can act in eukaryotic MMR in vitro.

Mismatch Repair Incompatibilities in Diverse Yeast Populations.

An elevated mutation rate can provide cells with a source of mutations to adapt to changing environments. We identified a negative epistatic interaction involving naturally occurring variants in the MLH1 and PMS1 mismatch repair (MMR) genes of Saccharomyces cerevisiae We hypothesized that this MMR incompatibility, created through mating between divergent S. cerevisiae, yields mutator progeny that can rapidly but transiently adapt to an environmental stress. Here we analyzed the MLH1 and PMS1 genes across 1010 S. cerevisiae natural isolates spanning a wide range of ecological sources (tree exudates, Drosophila, fruits, and various fermentation and clinical isolates) and geographical sources (Europe, America, Africa, and Asia). We identified one homozygous clinical isolate and 18 heterozygous isolates containing the incompatible MMR genotype. The MLH1-PMS1 gene combination isolated from the homozygous clinical isolate conferred a mutator phenotype when expressed in the S288c laboratory background. Using a novel reporter to measure mutation rates, we showed that the overall mutation rate in the homozygous incompatible background was similar to that seen in compatible strains, indicating the presence of suppressor mutations in the clinical isolate that lowered its mutation rate. This observation and the identification of 18 heterozygous isolates, which can lead to MMR incompatible genotypes in the offspring, are consistent with an elevated mutation rate rapidly but transiently facilitating adaptation. To avoid long-term fitness costs, the incompatibility is apparently buffered by mating or by acquiring suppressors. These observations highlight effective strategies in eukaryotes to avoid long-term fitness costs associated with elevated mutation rates.