Mutational profiling of mitochondrial DNA reveals an epithelial ovarian cancer-specific evolutionary pattern contributing to high oxidative metabolism.

BACKGROUND: Epithelial ovarian cancer (EOC) heavily relies on oxidative phosphorylation (OXPHOS) and exhibits distinct mitochondrial metabolic reprogramming. Up to now, the evolutionary pattern of somatic mitochondrial DNA (mtDNA) mutations in EOC tissues and their potential roles in metabolic remodelling have not been systematically elucidated. METHODS: Based on a large somatic mtDNA mutation dataset from private and public EOC cohorts (239 and 118 patients, respectively), we most comprehensively characterised the EOC-specific evolutionary pattern of mtDNA mutations and investigated its biological implication. RESULTS: Mutational profiling revealed that the mitochondrial genome of EOC tissues was highly unstable compared with non-cancerous ovary tissues. Furthermore, our data indicated the delayed heteroplasmy accumulation of mtDNA control region (mtCTR) mutations and near-complete absence of mtCTR non-hypervariable segment (non-HVS) mutations in EOC tissues, which is consistent with stringent negative selection against mtCTR mutation. Additionally, we observed a bidirectional and region-specific evolutionary pattern of mtDNA coding region mutations, manifested as significant negative selection against mutations in complex V (ATP6/ATP8) and tRNA loop regions, and potential positive selection on mutations in complex III (MT-CYB). Meanwhile, EOC tissues showed higher mitochondrial biogenesis compared with non-cancerous ovary tissues. Further analysis revealed the significant association between mtDNA mutations and both mitochondrial biogenesis and overall survival of EOC patients. CONCLUSIONS: Our study presents a comprehensive delineation of EOC-specific evolutionary patterns of mtDNA mutations that aligned well with the specific mitochondrial metabolic remodelling, conferring novel insights into the functional roles of mtDNA mutations in EOC tumourigenesis and progression.

Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations.

Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients.

A Sound and Vibration Fusion Method for Fault Diagnosis of Rolling Bearings under Speed-Varying Conditions.

The fault diagnosis of rolling bearings is critical for the reliability assurance of mechanical systems. The operating speeds of the rolling bearings in industrial applications are usually time-varying, and the monitoring data available are difficult to cover all the speeds. Though deep learning techniques have been well developed, the generalization capacity under different working speeds is still challenging. In this paper, a sound and vibration fusion method, named the fusion multiscale convolutional neural network (F-MSCNN), was developed with strong adaptation performance under speed-varying conditions. The F-MSCNN works directly on raw sound and vibration signals. A fusion layer and a multiscale convolutional layer were added at the beginning of the model. With comprehensive information, such as the input, multiscale features are learned for subsequent classification. An experiment on the rolling bearing test bed was carried out, and six datasets under various working speeds were constructed. The results show that the proposed F-MSCNN can achieve high accuracy with stable performance when the speeds of the testing set are the same as or different from the training set. A comparison with other methods on the same datasets also proves the superiority of F-MSCNN in speed generalization. The diagnosis accuracy improves by sound and vibration fusion and multiscale feature learning.

Mutational signature of mtDNA confers mechanistic insight into oxidative metabolism remodeling in colorectal cancer.

Rationale: Mitochondrial dysfunction caused by mitochondrial DNA (mtDNA) mutations and subsequent metabolic defects are closely involved in tumorigenesis and progression in a cancer-type specific manner. To date, the mutational pattern of mtDNA somatic mutations in colorectal cancer (CRC) tissues and its clinical implication are still not completely clear. Methods: In the present study, we generated a large mtDNA somatic mutation dataset from three CRC cohorts (432, 1,015, and 845 patients, respectively) and then most comprehensively characterized the CRC-specific evolutionary pattern and its clinical implication. Results: Our results showed that the mtDNA control region (mtCTR) with a high mutation density exhibited a distinct mutation spectrum characterizing a high enrichment of L-strand C > T mutations, which was contrary to the H-strand C > T mutational bias observed in the mtDNA coding region (mtCDR) (P < 0.001). Further analysis clearly confirmed the relaxed evolutionary selection of mtCTR mutations, which was mainly characterized by the similar distribution of hypervariable region (HVS) and non-HVS mutation density. Moreover, significant negative selection was identified in mutations of mtDNA complex V (ATP6/ATP8) and tRNA loop regions. Although our data showed that oxidative metabolism was commonly increased in CRC cells, mtDNA somatic mutations in CRC tissues were not closely associated with mitochondrial biogenesis, oxidative metabolism, and clinical progression, suggesting a cancer-type specific relationship between mtDNA mutations and mitochondrial metabolic functions in CRC cells. Conclusion: Our study identified the CRC-specific evolutionary mode of mtDNA mutations, which is possibly matched to specific mitochondrial metabolic remodeling and confers new mechanic insight into CRC tumorigenesis.

mitoSomatic: a tool for accurate identification of mitochondrial DNA somatic mutations without paired controls.

Mitochondrial DNA (mtDNA) somatic mutations play important roles in the initiation and progression of cancer. Although next-generation sequencing (NGS) of paired tumor and control samples has become a common practice to identify tumor-specific mtDNA mutations, the unique nature of mtDNA and NGS-associated sequencing bias could cause false-positive/-negative somatic mutation calling. Additionally, there are clinical scenarios where matched control tissues are unavailable for comparison. Therefore, a novel approach for accurately identifying somatic mtDNA variants is greatly needed, particularly in the absence of matched controls. In this study, the ground truth mtDNA variants orthogonally validated by triple-paired tumor, adjacent nontumor, and blood samples were used to develop mitoSomatic, a random forest-based machine learning tool. We demonstrated that mitoSomatic achieved area under the curve (AUC) values over 0.99 for identifying somatic mtDNA variants without paired control in three tumor types. In addition, mitoSomatic was also applicable in nontumor tissues such as adjacent nontumor and blood samples, suggesting the flexibility of mitoSomatic's classification capability. Furthermore, analysis of triple-paired samples identified a small group of variants with uncertain somatic/germline origin, whereas application of mitoSomatic significantly facilitated the prediction of their possible source. Finally, a control-free evaluation of the public pan-cancer NGS dataset with mitoSomatic revealed a substantial number of variants that were probably misclassified by conventional tumor-control comparison, further emphasizing the usefulness of mitoSomatic in application. Taken together, our study demonstrates that mitoSomatic is valuable for accurately identifying somatic mtDNA variants in mtDNA NGS data without paired controls, applicable for both tumor and nontumor tissues.

Mutational profiling of mtDNA control region reveals tumor-specific evolutionary selection involved in mitochondrial dysfunction.

BACKGROUND: Mitochondrial DNA (mtDNA) mutations alter mitochondrial function in oxidative metabolism and play an important role in tumorigenesis. A series of studies have demonstrated that the mtDNA control region (mtCTR), which is essential for mtDNA replication and transcription, represents a mutational hotspot in human tumors. However, a comprehensive pan-cancer evolutionary pattern analysis of mtCTR mutations is urgently needed. METHODS: We generated a comprehensive combined dataset containing 10026 mtDNA somatic mutations from 4664 patients, covering 20 tumor types based on public and private next-generation sequencing data. FINDINGS: Our results demonstrated a significantly higher and much more variable mutation rate in mtCTR than in the coding region across different tumor types. Moreover, our data showed a remarkable distributional bias of tumor somatic mutations between the hypervariable segment (HVS) and non-HVS, with a significantly higher mutation density and average mutation sites in HVS. Importantly, the tumor-specific mutational pattern between mtCTR HVS and non-HVS was identified, which was classified into three evolutionary selection types (relaxed, moderate, and strict constraint types). Analysis of substitution patterns revealed that the prevalence of CH > TH in non-HVS greatly contributed to the mutational selection pattern of mtCTR across different tumor types. Furthermore, we found that the mutational pattern of mtCTR in the four tumor types was clearly associated with mitochondrial biogenesis, mitochondrial oxidative metabolism, and the overall survival of patients. INTERPRETATION: Our results suggest that somatic mutations in mtCTR may be shaped by tumor-specific selective pressure and are involved in tumorigenesis. FUNDINGS: National Natural Science Foundation of China [grants 82020108023, 81830070, 81872302], and Autonomous Project of State Key Laboratory of Cancer Biology, China [grants CBSKL2019ZZ06, CBSKL2019ZZ27].

Next-Generation Sequencing-Based Analysis of Urine Cell-Free mtDNA Reveals Aberrant Fragmentation and Mutation Profile in Cancer Patients.

BACKGROUND: Many studies have demonstrated the high efficacy of cell-free nuclear DNA in cancer diagnostics. Compared to nuclear DNA, mitochondrial DNA (mtDNA) exhibits distinct characteristics, including multiple copies per cell and higher mutation frequency. However, the potential applicability of cell-free mtDNA (cf-mtDNA) in plasma and urine remains poorly investigated. METHODS: Here, we comprehensively analyzed the fragmentomic and mutational characteristics of cf-mtDNA in urine and plasma samples from controls and cancer patients using next-generation sequencing. RESULTS: Compared to plasma cf-mtDNA, urine cf-mtDNA exhibited increased copy numbers and wider spread in fragment size distributions. Based on 2 independent animal models, urine cf-mtDNA originated predominantly from local shedding and transrenal excretion. Further analysis indicated an enhanced fragmentation of urine cf-mtDNA in renal cell carcinoma (RCC) and colorectal cancer (CRC) patients. Using the mtDNA sequence of peripheral blood mononuclear cells for reference, the mutant fragments were shorter than wild-type fragments in urine cf-mtDNA. Size selection of short urine cf-mtDNA fragments (<150 bp) significantly enhanced the somatic mutation detection. Our data revealed remarkably different base proportions of fragment ends between urine and plasma cf-mtDNA that also were associated with fragment size. Moreover, both RCC and CRC patients exhibited significantly higher T-end and lower A-end proportions in urine cf-mtDNA than controls. By integrating the fragmentomic and mutational features of urine cf-mtDNA, our nomogram model exhibited a robust efficacy for cancer diagnosis. CONCLUSIONS: Our proof-of-concept findings revealed aberrant fragmentation and mutation profiles of urine cf-mtDNA in cancer patients that have diagnostic potential.

mitoDataclean: A machine learning approach for the accurate identification of cross-contamination-derived tumor mitochondrial DNA mutations.

Next-generation sequencing (NGS) of mitochondrial DNA (mtDNA) has widespread applications in aging and cancer studies. However, cross-contamination of mtDNA constitutes a major concern. Previous methods for the detection of mtDNA contamination mainly focus on haplogroup-level phylogeny, but neglect haplotype-level differences, leading to limited sensitivity and accuracy. In our study, we present mitoDataclean, a random-forest-based machine learning package for accurate identification of cross-contamination, evaluation of contamination levels and detection of contamination-derived variants in mtDNA NGS data. Comprehensive optimization of mitoDataclean revealed that training simulation with mixtures of small haplogroup distance and low polymorphic difference was critical for optimal modeling. Compared to existing methods, mitoDataclean exhibited significantly improved sensitivity and accuracy for the detection of sample contamination in simulated data. In addition, mitoDataclean achieved area under the curve values of 0.91 and 0.97 for discerning genuine and contamination-derived mtDNA variants in a simulated Western dataset and private sequencing contamination data, respectively, suggesting that this tool may be applicable for different populations and samples with different sources of contamination. Finally, mitoDataclean was further evaluated in several private and public datasets and showed a robust ability for contamination detection. Altogether, our study demonstrates that mitoDataclean may be used for accurate detection of contaminated samples and contamination-derived variants in mtDNA NGS data.

Multiple-level copy number variations in cell-free DNA for prognostic prediction of HCC with radical treatments.

Copy number variations (CNVs) in cell-free DNA (cfDNA) are emerging as noninvasive biomarkers for various cancers. However, multiple-level analysis of cfDNA CNVs for hepatocellular carcinoma (HCC) patients with radical treatments remains uninvestigated. Here, CNVs at genome-wide, chromosomal-arm, and bin levels were analyzed in cfDNA from 117 HCC patients receiving radical treatments. Then, the relationship between cfDNA CNVs and clinical outcomes was explored. Our results showed that a concordant profile of CNVs was observed between cfDNA and tumor tissue DNA. Three genome-wide CNV indicators including tumor fraction (TFx), prediction score (P-score), and stability score (S-score) were calculated and demonstrated to exhibit significant correlation with poorer overall survival (OS) and recurrence-free survival (RFS). Furthermore, the high-frequency cfDNA CNVs at chromosomal-arm level including the loss of 4q, 17p, and 19p and the gain of 8q and 1q clearly predicted HCC prognosis. Finally, a bin-level risk score was constructed to improve the ability of CNVs in predicting prognosis. Altogether, our study indicates that the multiple-level cfDNA CNVs are significantly associated with OS and RFS in HCC patients with radical treatments, suggesting that cfDNA CNVs detected by low-coverage whole-genome sequencing (WGS) may be used as potential prognostic biomarkers of HCC patients.

Mitochondrial DNA haplogroup M7 confers a reduced risk of colorectal cancer in a Han population from northern China.

Mitochondria are central eukaryotic organelles in cellular metabolism and ATP production. Mitochondrial DNA (mtDNA) alterations have been implicated in the development of colorectal cancer (CRC). However, there are few reports on the association between mtDNA haplogroups or single nucleotide polymorphisms (SNPs) and the risk of CRC. The mtDNA of 286 Northern Han Chinese CRC patients were sequenced by next-generation sequencing technology. MtDNA data from 811 Han Chinese population controls were collected from two public data sets. Then, logistic regression analysis was used to determine the effect of mtDNA haplogroup or SNP on the risk of CRC. We found that patients with haplogroup M7 exhibited a reduced risk of CRC when compared to patients with other haplogroups (odds ratio [OR] = 0.532, 95% confidence interval [CI] = 0.285-0.937, p = 0.036) or haplogroup B (OR = 0.477, 95% CI = 0.238-0.916, p = 0.030). Furthermore, haplogroup M7 was still associated with the risk of CRC when the validation and combined control cohort were used. In addition, several haplogroup M7 specific SNPs, including 199T>C, 4071C>T and 6455C>T, were significantly associated with the risk of CRC. Our results indicate the risk potential of mtDNA haplogroup M7 and SNPs in CRC in Northern China.

NGS-based accurate and efficient detection of circulating cell-free mitochondrial DNA in cancer patients.

Mitochondrial DNA (mtDNA) mutations are closely implicated in the pathogenesis of multiple cancers, making circulating cell-free mtDNA (ccf-mtDNA) as a potential non-invasive tumor biomarker. However, an effective approach to comprehensively profile ccf-mtDNA mutations is still lacking. In this study, we first characterized ccf-mtDNA by low-depth whole-genome sequencing (WGS) and found that plasma DNA samples exhibited a dramatic decrease in mtDNA copy number when compared with fresh tumor tissues. Further analysis revealed that plasma ccf-mtDNA had a biased distribution of fragment size with a peak around 90 bp. Based on these insights, we developed a robust captured-based mtDNA deep-sequencing approach that enables accurate and efficient detection of plasma ccf-mtDNA mutations by systematic optimization of probe quantity and length, hybridization temperature, and PCR amplification cycles. Moreover, we found that placement of isolated plasma for 6 h at both 4°C and room temperature (RT) led to a dramatic decrease of ccf-mtDNA stability, highlighting the importance of proper plasma sample processing. We further showed that the optimized approach can successfully detect a substantial fraction of tumor-specific mtDNA mutations in plasma ccf-mtDNA specifically from hepatocellular carcinoma (HCC) patients but not from colorectal cancer (CRC) patients, suggesting the presence of a potential cancer-specific difference in the abundance of tumor-derived mtDNA in plasma.

An innovative data analysis strategy for accurate next-generation sequencing detection of tumor mitochondrial DNA mutations.

Next-generation sequencing technology has been commonly applied to detect mitochondrial DNA (mtDNA) mutations, which are reported to be strongly associated with cancers. However, several key challenges still exist regarding bioinformatics analysis of mtDNA sequencing data that greatly affect the detection accuracy of mtDNA mutations. Here we comprehensively evaluated several key analysis procedures in three different sample types. We found that a trimming procedure was essential for improving mtDNA mapping performance in plasma but not tissue samples. Mapping with a revised Cambridge reference sequence and human genome 19 reference was strongly suggested for mtDNA mutation detection in plasma samples because of the extreme abundance of nuclear DNA of mitochondrial origin. Moreover, our results showed that a setting of 3 mismatches was most appropriate for mtDNA mutation calling. Importantly, we revealed the presence of a negative logarithmic relationship between mtDNA site sequencing depth and minimum detectable mutation frequency and built an innovative and efficient filtering strategy to increase the accuracy and sensitivity of mutation detection. Finally, we verified that higher sequencing depth was required for a PCR-based compared with a capture-based enrichment strategy. We established an innovative data analysis strategy that is of great significance for improving the accuracy of mtDNA mutation detection for different types of tumor samples.

Optimized high-fidelity 3DPCR to assess potential mitochondrial targeting by activation-induced cytidine deaminase.

Activation-induced cytidine deaminase (AID) initiates somatic hypermutation and class switch recombination of immunoglobulin genes in B cells, whereas off-targeted AID activity contributes to oncogenic mutations and chromosomal translocations associated with B cell malignancies. Paradoxically, only a minority of AID is allowed to access the nuclear genome, but the majority of AID is retained in the cytoplasm. It is unknown whether cytoplasmic AID can access and target the mitochondrial genome [mitochondrial DNA (mtDNA)]. To address this issue, we developed high-fidelity differential DNA denaturation PCR, which allowed the enrichment of genuine mtDNA mutations and therefore the identification of endogenous mtDNA mutation signatures in vitro. With this approach, we showed that AID targeting to mtDNA is a rare event in AID-expressing lymphoma lines. Further biochemical and microscopic analysis revealed that a fraction of cytosol AID is associated with the outer membrane of mitochondria but unable to access the mitochondrial matrix. Together, our data suggested that the mitochondrial genome is protected from AID-mediated mutagenesis by physical segregation of AID from accessing mtDNA within the mitochondrial matrix.

Mutation signatures in germline mitochondrial genome provide insights into human mitochondrial evolution and disease.

Variations in mitochondrial DNA (mtDNA) have been fundamental for understanding human evolution and are causative for a plethora of inherited mitochondrial diseases, but the mutation signatures of germline mtDNA and their value in understanding mitochondrial pathogenicity remain unknown. Here, we carried out a systematic analysis of mutation patterns in germline mtDNA based on 97,566 mtDNA variants from 45,494 full-length sequences and revealed a highly non-stochastic and replication-coupled mutation signature characterized by nucleotide-specific mutation pressure (G > T>A > C) and position-specific selection pressure, suggesting the existence of an intensive mutation-selection interplay in germline mtDNA. We provide evidence that this mutation-selection interplay has strongly shaped the mtDNA sequence during evolution, which not only manifests as an oriented alteration of amino acid compositions of mitochondrial encoded proteins, but also explains the long-lasting mystery of CpG depletion in mitochondrial genome. Finally, we demonstrated that these insights may be integrated to better understand the pathogenicity of disease-implicated mitochondrial variants.

Propranolol induces hemangioma endothelial cell apoptosis via a p53­BAX mediated pathway.

The use of propranolol for the treatment of infantile hemangioma (IH) has been widely investigated in recent years. However, the underlying therapeutic mechanism of propranolol for the treatment of IH remains poorly understood. The aim of the present study was to investigate the expression of proteins regulated by cellular tumor antigen p53 (p53) in associated apoptosis pathways in IH endothelial cells (HemECs) treated with propranolol. Furthermore, the present study aimed to investigate the exact apoptotic pathway underlying the therapeutic effect of propranolol against IH. In the present study, HemECs were subcultured and investigated using an inverted phase contrast microscope, immunocytochemical staining and a scanning electron microscope (SEM). Experimental groups and blank control groups were prepared. All groups were subjected to drug treatment. A high p53 expression model of HemECs was successfully established via transfection, and a low p53 expression model of HemECs was established using pifithrin­α. The apoptosis rate of each group was determined using Annexin V­fluorescein isothiocyanate/propidium iodide double staining and flow cytometry. The expression levels of downstream proteins regulated by p53 [tumour necrosis factor receptor superfamily member 6 (FAS), p53­induced death domain­containing protein (PIDD), death receptor 5 (DR5), BH3­interacting domain death agonist (BID), apoptosis regulator BAX (BAX), p53 unregulated modulator of apoptosis (PUMA), phosphatidylinositol­glycan biosynthesis class S protein (PIGS), and insulin­like growth factor­binding protein 3 (IGF­BP3)] were revealed in the experimental and control groups via western blotting. Microscopic observation revealed the growth of an adherent monolayer of cells, which were closely packed and exhibited contact inhibition. Immunocytochemical staining demonstrated increased expression of clotting factor VIII. SEM analysis revealed presence of Weibel­Palade bodies. The results of the analyses verified that the cultured cells were HemECs. The staining of the samples resulted in a significantly increased rate of apoptosis in experimental groups compared with the blank control group. This result suggested that there is an association between p53 expression and the rate of apoptosis of propranolol­treated HemECs. The results of the western blot analysis demonstrated an upregulation of BAX expression and a downregulation of IGF­BP3 expression in the HemECs treated with propranolol. There were no significant differences in the expression levels of FAS, DR5, PIDD, BID, PUMA and PIGS between experimental and control groups. This result suggests that p53 has an important role in HemEC apoptosis. The results of the present study additionally suggest that the propranolol­induced HemEC apoptosis pathway is a mitochondrial apoptosis pathway and is regulated by p53­BAX signaling.

AID-associated DNA repair pathways regulate malignant transformation in a murine model of BCL6-driven diffuse large B-cell lymphoma.

Somatic hypermutation and class-switch recombination of the immunoglobulin (Ig) genes occur in germinal center (GC) B cells and are initiated through deamination of cytidine to uracil by activation-induced cytidine deaminase (AID). Resulting uracil-guanine mismatches are processed by uracil DNA glycosylase (UNG)-mediated base-excision repair and MSH2-mediated mismatch repair (MMR) to yield mutations and DNA strand lesions. Although off-target AID activity also contributes to oncogenic point mutations and chromosome translocations associated with GC and post-GC B-cell lymphomas, the role of downstream AID-associated DNA repair pathways in the pathogenesis of lymphoma is unknown. Here, we show that simultaneous deficiency of UNG and MSH2 or MSH2 alone causes genomic instability and a shorter latency to the development of BCL6-driven diffuse large B-cell lymphoma (DLBCL) in a murine model. The additional development of several BCL6-independent malignancies in these mice underscores the critical role of MMR in maintaining general genomic stability. In contrast, absence of UNG alone is highly protective and prevents the development of BCL6-driven DLBCL. We further demonstrate that clonal and nonclonal mutations arise within non-Ig AID target genes in the combined absence of UNG and MSH2 and that DNA strand lesions arise in an UNG-dependent manner but are offset by MSH2. These findings lend insight into a complex interplay whereby potentially deleterious UNG activity and general genomic instability are opposed by the protective influence of MSH2, producing a net protective effect that promotes immune diversification while simultaneously attenuating malignant transformation of GC B cells.

A DNA break- and phosphorylation-dependent positive feedback loop promotes immunoglobulin class-switch recombination.

The ability of activation-induced cytidine deaminase (AID) to efficiently mediate class-switch recombination (CSR) is dependent on its phosphorylation at Ser38; however, the trigger that induces AID phosphorylation and the mechanism by which phosphorylated AID drives CSR have not been elucidated. Here we found that phosphorylation of AID at Ser38 was induced by DNA breaks. Conversely, in the absence of AID phosphorylation, DNA breaks were not efficiently generated at switch (S) regions in the immunoglobulin heavy-chain locus (Igh), consistent with a failure of AID to interact with the endonuclease APE1. Additionally, deficiency in the DNA-damage sensor ATM impaired the phosphorylation of AID at Ser38 and the interaction of AID with APE1. Our results identify a positive feedback loop for the amplification of DNA breaks at S regions through the phosphorylation- and ATM-dependent interaction of AID with APE1.

The role of activation-induced cytidine deaminase in lymphomagenesis.

PURPOSE OF REVIEW: Activation-induced cytidine deaminase (AID) is expressed in germinal center B cells and initiates the events that lead to somatic hypermutation and class switch recombination of immunoglobulin genes. In addition to this fundamental role in immune diversification, aberrant targeting of AID activity contributes to point mutations and translocations of oncogenes associated with B-cell lymphoma. This review discusses recent findings on the role of AID in lymphomagenesis. RECENT FINDINGS: AID is expressed in many malignancies of mature B-cell origin and contributes to the development of lymphoma in several mouse models. The mechanism that guides AID to its genetic target is unknown and may be relatively nonspecific, as numerous nonimmunoglobulin genes appear to be targeted by AID in both normal and neoplastic B cells. Indeed, AID binds to genes on every chromosome throughout the genome and can induce double-stranded DNA breaks that lead to chromosome translocations at these sites. SUMMARY: Emerging evidence supports a key role of AID in lymphomagenesis through genome-wide off-target induction of point mutations and chromosome translocations. Additional work is needed to further define the full scope and consequences of off-target AID activity in human lymphoma as well as to understand the protective mechanisms that break down during the development and progression of disease.

The circadian clock influences heart performance.

Circadian clocks are believed to provide the selective advantage of anticipation, thus allowing organisms to respond efficiently to stimuli at the appropriate moment. Disrupted circadian rhythms have been found to affect a variety of basic physiological processes. However, the importance of the circadian clock in regulating heart performance remains undetermined. We hypothesized that the circadian clock plays a crucial role in heart performance through the anticipation of daily workload. Echocardiography was employed to monitor heart function and structure in mice in a noninvasive, real-time manner. In wild-type mice, both the ejection fraction (EF) and the shortening fraction (FS), two important markers of cardiac function, show diurnal variation. In addition, the amplitude of the EF and the FS enlarges in response to forced exercise in a time-dependent manner. The diurnal variations in EF and FS are altered in mice with disruptions in circadian clock genes and are significantly attenuated under an imposed light regimen. Furthermore, it shows that the overexpression of peroxisome proliferator-activated receptor gamma coactivator 1 alpha (Pgc1α) under control of the muscle creatine kinase (MCK) promoter inhibited clock gene expression in the heart and muscle and decreased the expression of peroxisome proliferator-activated receptor alpha (Pparα), metabolic genes glucose transporter (Glut4), and acetyl-coA synthetase (Acs1). Pgc1α overexpression abolished the diurnal variation of EF. We thus propose that PGC1α might play an important role in circadian-mediated, impaired cardiac function by regulating the circadian rhythm of metabolic genes.

Interaction of MAGED1 with nuclear receptors affects circadian clock function.

The circadian clock has a central role in physiological adaption and anticipation of day/night changes. In a genetic screen for novel regulators of circadian rhythms, we found that mice lacking MAGED1 (Melanoma Antigen Family D1) exhibit a shortened period and altered rest-activity bouts. These circadian phenotypes are proposed to be caused by a direct effect on the core molecular clock network that reduces the robustness of the circadian clock. We provide in vitro and in vivo evidence indicating that MAGED1 binds to RORalpha to bring about positive and negative effects on core clock genes of Bmal1, Rev-erbalpha and E4bp4 expression through the Rev-Erbalpha/ROR responsive elements (RORE). Maged1 is a non-rhythmic gene that, by binding RORalpha in non-circadian way, enhances rhythmic input and buffers the circadian system from irrelevant, perturbing stimuli or noise. We have thus identified and defined a novel circadian regulator, Maged1, which is indispensable for the robustness of the circadian clock to better serve the organism.