Spontaneous histone exchange between nucleosomes.

The nucleosome is the fundamental gene-packing unit in eukaryotes. Nucleosomes comprise ∼147 bp DNA wrapped around an octameric histone protein core composed of two H2A-H2B dimers and one (H3-H4)2 tetramer. The strong yet flexible DNA-histone interactions are the physical basis of the dynamic regulation of genes packaged in chromatin. The dynamic nature of DNA-histone interactions also implies that nucleosomes dissociate DNA-histone contacts both transiently and repeatedly. This kinetic instability may lead to spontaneous nucleosome disassembly or histone exchange between nucleosomes. At high nucleosome concentrations, nucleosome-nucleosome collisions and subsequent histone exchange would be a more likely event, where nucleosomes could act as their own histone chaperone. This spontaneous histone exchange could serve as a mechanism for maintaining overall chromatin stability, although it has never been reported. Here we employed three-color single-molecule FRET (smFRET) to demonstrate that histone H2A-H2B dimers are exchanged spontaneously between nucleosomes on a time scale of a few tens of seconds at a physiological nucleosome concentration. We show that the rate of histone exchange increases at a higher monovalent salt concentration, with histone-acetylated nucleosomes, and in the presence of histone chaperone Nap1, while it remains unchanged at a higher temperature, and decreases upon DNA methylation. These results support the notion of histone exchange via transient and repetitive partial disassembly of the nucleosome and corroborate spontaneous histone diffusion in a compact chromatin context, modulating the local concentrations of histone modifications and variants.

Deep learning-based prognostication in idiopathic pulmonary fibrosis using chest radiographs.

OBJECTIVES: To develop and validate a deep learning-based prognostic model in patients with idiopathic pulmonary fibrosis (IPF) using chest radiographs. METHODS: To develop a deep learning-based prognostic model using chest radiographs (DLPM), the patients diagnosed with IPF during 2011-2021 were retrospectively collected and were divided into training (n = 1007), validation (n = 117), and internal test (n = 187) datasets. Up to 10 consecutive radiographs were included for each patient. For external testing, three cohorts from independent institutions were collected (n = 152, 141, and 207). The discrimination performance of DLPM was evaluated using areas under the time-dependent receiver operating characteristic curves (TD-AUCs) for 3-year survival and compared with that of forced vital capacity (FVC). Multivariable Cox regression was performed to investigate whether the DLPM was an independent prognostic factor from FVC. We devised a modified gender-age-physiology (GAP) index (GAP-CR), by replacing DLCO with DLPM. RESULTS: DLPM showed similar-to-higher performance at predicting 3-year survival than FVC in three external test cohorts (TD-AUC: 0.83 [95% CI: 0.76-0.90] vs. 0.68 [0.59-0.77], p < 0.001; 0.76 [0.68-0.85] vs. 0.70 [0.60-0.80], p = 0.21; 0.79 [0.72-0.86] vs. 0.76 [0.69-0.83], p = 0.41). DLPM worked as an independent prognostic factor from FVC in all three cohorts (ps < 0.001). The GAP-CR index showed a higher 3-year TD-AUC than the original GAP index in two of the three external test cohorts (TD-AUC: 0.85 [0.80-0.91] vs. 0.79 [0.72-0.86], p = 0.02; 0.72 [0.64-0.80] vs. 0.69 [0.61-0.78], p = 0.56; 0.76 [0.69-0.83] vs. 0.68 [0.60-0.76], p = 0.01). CONCLUSIONS: A deep learning model successfully predicted survival in patients with IPF from chest radiographs, comparable to and independent of FVC. CLINICAL RELEVANCE STATEMENT: Deep learning-based prognostication from chest radiographs offers comparable-to-higher prognostic performance than forced vital capacity. KEY POINTS: • A deep learning-based prognostic model for idiopathic pulmonary fibrosis was developed using 6063 radiographs. • The prognostic performance of the model was comparable-to-higher than forced vital capacity, and was independent from FVC in all three external test cohorts. • A modified gender-age-physiology index replacing diffusing capacity for carbon monoxide with the deep learning model showed higher performance than the original index in two external test cohorts.

Methods to investigate nucleosome structure and dynamics with single-molecule FRET.

The nucleosome is the fundamental building block of chromatin. Changes taking place at the nucleosome level are the molecular basis of chromatin transactions with various enzymes and factors. These changes are directly and indirectly regulated by chromatin modifications such as DNA methylation and histone post-translational modifications including acetylation, methylation, and ubiquitylation. Nucleosomal changes are often stochastic, unsynchronized, and heterogeneous, making it very difficult to monitor with traditional ensemble averaging methods. Diverse single-molecule fluorescence approaches have been employed to investigate the structure and structural changes of the nucleosome in the context of its interactions with various enzymes such as RNA Polymerase II, histone chaperones, transcription factors, and chromatin remodelers. We utilize diverse single-molecule fluorescence methods to study the nucleosomal changes accompanying these processes, elucidate the kinetics of these processes, and eventually learn the implications of various chromatin modifications in directly regulating these processes. The methods include two- and three-color single-molecule fluorescence resonance energy transfer (FRET), single-molecule fluorescence correlation spectroscopy, and fluorescence (co-)localization. Here we report the details of the two- and three-color single-molecule FRET methods we currently use. This report will help researchers design their single-molecule FRET approaches to investigating chromatin regulation at the nucleosome level.

Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.

OBJECTIVES: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model. METHODS: DL models were trained to simultaneously predict five morphological and histopathological features using preoperative chest CT scans from patients with resected lung adenocarcinomas. The DL score was validated in temporal and external test sets, with freedom from recurrence (FFR) and overall survival (OS) as outcomes. Discrimination was evaluated using the time-dependent area under the receiver operating characteristic curve (TD-AUC) and compared with the DL discrete-time survival model. Additionally, we performed multivariable Cox regression analysis. RESULTS: In the temporal test set (640 patients; median age, 64 years), the TD-AUC was 0.79 for 5-year FFR and 0.73 for 5-year OS. In the external test set (846 patients; median age, 65 years), the TD-AUC was 0.71 for 5-year OS, equivalent to the pathologic stage (0.71 vs. 0.71 [p = 0.74]). The prognostic value of the DL score was independent of clinical factors (adjusted per-percentage hazard ratio for FFR (temporal test), 1.02 [95% CI: 1.01-1.03; p < 0.001]; OS (temporal test), 1.01 [95% CI: 1.002-1.02; p = 0.01]; OS (external test), 1.01 [95% CI: 1.005-1.02; p < 0.001]). Our model showed a higher TD-AUC than the DL discrete-time survival model, but without statistical significance (2.5-year OS: 0.73 vs. 0.68; p = 0.13). CONCLUSION: The CT-based prognostic score from collective deep learning of morphological and histopathological features showed potential in predicting survival in lung adenocarcinomas. CLINICAL RELEVANCE STATEMENT: Collective CT-based deep learning of morphological and histopathological features presents potential for enhancing lung adenocarcinoma prognostication and optimizing pre-/postoperative management. KEY POINTS: • A CT-based prognostic model was developed using collective deep learning of morphological and histopathological features from preoperative CT scans of 3181 patients with resected lung adenocarcinoma. • The prognostic performance of the model was comparable-to-higher performance than the pathologic T category or stage. • Our approach yielded a higher discrimination performance than the direct survival prediction model, but without statistical significance (0.73 vs. 0.68; p=0.13).

The Effects of Histone H2B Ubiquitylations on the Nucleosome Structure and Internucleosomal Interactions.

Eukaryotic gene compaction takes place at multiple levels to package DNA to chromatin and chromosomes. Two of the most fundamental levels of DNA packaging are at the nucleosome and dinucleosome stacks. The nucleosome is the basic gene-packing unit and is composed of DNA wrapped around a histone core. Nucleosomes stack with one another for further compaction of DNA. The first stacking step leads to dinucleosome formation, which is driven by internucleosomal interactions between various parts of two nucleosomes. Histone proteins are rich targets for post-translational modifications, some of which affect the structure of the nucleosome and the interactions between nucleosomes. These effects are often implicated in the regulation of various genomic transactions. In particular, histone H2B ubiquitylation has been associated with facilitated transcription and hexasome formation. Here, we employed semi-synthetically ubiquitylated histone H2B and single-molecule FRET to investigate the effects of H2B ubiquitylations at lysine 34 (H2BK34) and lysine 120 (H2BK120) on the structure of the nucleosome and the interactions between two nucleosomes. Our results suggest that H2BK34 ubiquitylation widens the DNA gyre gap in the nucleosome and stabilizes long- and short-range internucleosomal interactions while H2BK120 ubiquitylation does not affect the nucleosome structure or internucleosomal interactions. These results suggest potential roles for H2B ubiquitylations in facilitated transcription and hexasome formation while maintaining the structural integrity of chromatin.

Selective production of retinol by engineered Saccharomyces cerevisiae through the expression of retinol dehydrogenase.

Retinol is a fat-soluble vitamin A that is widely used in the food and pharmaceutical industries. Currently, retinol is commercially produced by chemical synthesis. Microbial production of retinol has been alternatively explored but restricted to a mixture of retinoids including retinol, retinal, and retinoic acid. Thus, we introduced heterologous retinol dehydrogenase into retinoids mixture-producing Saccharomyces cerevisiae for the selective production of retinol using xylose. Expression of human RDH10 and Escherichia coli ybbO led to increase in retinol production, but retinal remained as a major product. In contrast, S. cerevisiae harboring human RDH12 produced retinol selectively with negligible production of retinal. The resulting strain (SR8A-RDH12) produced retinol only. However, more glycerol was accumulated due to intracellular redox imbalance. Therefore, Lactococcus lactis noxE coding for H2 O-forming NADH oxidase was additionally introduced to resolve the redox imbalance. The resulting strain produced 52% less glycerol and more retinol with a 30% higher yield than a parental strain. As the produced retinol was not stable, we examined culture and storage conditions including temperature, light, and antioxidants for the optimal production of retinol. In conclusion, we achieved selective production of retinol efficiently from xylose by introducing human RDH12 and NADH oxidase into S. cerevisiae.

Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis.

OBJECTIVES: To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases. METHODS: This retrospective study included 131 patients who underwent contrast-enhanced DECT (80-kVp and 150-kVp with a tin filter) in the portal venous phase for hepatic metastasis surveillance. Linearly blended images simulating 100-kVp images (100-kVp), standard 40-keV VMI images (40-keV VMI), and post-processed 40-keV VMI using a vendor-agnostic DLM (i.e., DLM 40-keV VMI) were reconstructed. Lesion conspicuity and diagnostic acceptability were assessed by three independent reviewers and compared using the Wilcoxon signed-rank test. The contrast-to-noise ratios (CNRs) were also measured placing ROIs in metastatic lesions and liver parenchyma. The detection performance of hepatic metastases was assessed by using a jackknife alternative free-response ROC method. The consensus by two independent radiologists was used as the reference standard. RESULTS: DLM 40-keV VMI, compared to 40-keV VMI and 100-kVp, showed a higher lesion-to-liver CNR (8.25 ± 3.23 vs. 6.05 ± 2.38 vs. 5.99 ± 2.00), better lesion conspicuity (4.3 (4.0-4.7) vs. 3.7 (3.7-4.0) vs. 3.7 (3.3-4.0)), and better diagnostic acceptability (4.3 (4.0-4.3) vs. 3.0 (2.7-3.3) vs. 4.0 (4.0-4.3)) (p < 0.001 for all). For lesion detection (246 hepatic metastases in 68 patients), the figure of merit was significantly higher with DLM 40-keV VMI than with 40-keV VMI (0.852 vs. 0.822, p = 0.012), whereas no significant difference existed between DLM 40-keV VMI and 100-kVp (0.852 vs. 0.842, p = 0.31). CONCLUSIONS: DLM 40-keV VMI provided better image quality and comparable diagnostic performance for detecting hypoenhancing hepatic metastases compared to linearly blended images. KEY POINTS: • DLM 40-keV VMI provides a superior image quality compared with 40-keV or 100-kVp for assessing hypoenhancing hepatic metastasis. • DLM 40-keV VMI has the highest CNR and lesion conspicuity score for hypoenhancing hepatic metastasis due to noise reduction and structural preservation. • DLM 40-keV VMI provides higher lesion detectability than standard 40-keV VMI (p = 0.012).

Association between long-term exposure to particulate matter and childhood cancer: A retrospective cohort study.

BACKGROUND: Although particulate matter is a known carcinogen, its association with childhood cancer is inconclusive. The present study aimed to examine the association between long-term exposure to particulate matter and childhood cancer. METHODS: A retrospective cohort was constructed from the claims database of the Korea National Health Insurance Service, including children born in seven metropolitan cities in Korea between 2002 and 2012. Monthly mean concentrations of particulate matter with aerodynamic diameter <10 µm (PM10) and other air pollutants (NO2, SO2, CO, and O3) were calculated using data from the AirKorea. Monthly mean concentrations of particulate matter with aerodynamic diameter <2.5 µm (PM2.5) were estimated based on a data fusion approach. Cumulative exposure was assessed by averaging the monthly concentrations accounting for the residential mobility of the children. The occurrence of cancer was identified by the appearance of diagnosis codes in the claims database. Hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated using Cox proportional regression, adjusting for potential confounders and O3 concentrations. RESULTS: During the study period, 1,725 patients were newly diagnosed with cancer among 1,261,855 children. HR of all cancers per 10 µg/m3 increment in annual mean concentrations of PM2.5 and PM10 were 3.02 (95% CI: 1.63, 5.59) and 1.04 (0.74, 1.45), respectively. CONCLUSION: PM2.5 exposure was positively associated with childhood cancer in a large retrospective cohort with exposure assessment accounting for residential mobility.

Enzyme aggregation and fragmentation induced by catalysis relevant species.

It is usually assumed that enzymes retain their native structure during catalysis. However, the aggregation and fragmentation of proteins can be difficult to detect and sometimes conclusions are drawn based on the assumption that the protein is in its native form. We have examined three model enzymes, alkaline phosphatase (AkP), hexokinase (HK) and glucose oxidase (GOx). We find that these enzymes aggregate or fragment after addition of chemical species directly related to their catalysis. We used several independent techniques to study this behavior. Specifically, we found that glucose oxidase and hexokinase fragment in the presence of D-glucose but not L-glucose, while hexokinase aggregates in the presence of Mg2+ ion and either ATP or ADP at low pH. Alkaline phosphatase aggregates in the presence of Zn2+ ion and inorganic phosphate. The aggregation of hexokinase and alkaline phosphatase does not appear to attenuate their catalytic activity. Our study indicates that specific multimeric structures of native enzymes may not be retained during catalysis and suggests pathways for different enzymes to associate or separate over the course of substrate turnover.

Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer.

Road surfaces should be maintained in excellent condition to ensure the safety of motorists. To this end, there exist various road-surface monitoring systems, each of which is known to have specific advantages and disadvantages. In this study, a smartphone-based dual-acquisition method system capable of acquiring images of road-surface anomalies and measuring the acceleration of the vehicle upon their detection was developed to explore the complementarity benefits of the two different methods. A road test was conducted in which 1896 road-surface images and corresponding three-axis acceleration data were acquired. All images were classified based on the presence and type of anomalies, and histograms of the maximum variations in the acceleration in the gravitational direction were comparatively analyzed. When the types of anomalies were not considered, it was difficult to identify their effects using the histograms. The differences among histograms became evident upon consideration of whether the vehicle wheels passed over the anomalies, and when excluding longitudinal anomalies that caused minor changes in acceleration. Although the image-based monitoring system used in this research provided poor performance on its own, the severity of road-surface anomalies was accurately inferred using the specific range of the maximum variation of acceleration in the gravitational direction.

Sleep, fatigue and alertness during working hours among rotating-shift nurses in Korea: An observational study.

AIMS: To determine the effects of sleep parameters and fatigue on the decline in alertness of nurses across shifts. BACKGROUND: Shift work can lead to nurse fatigue owing to insufficient sleep and inadequate recovery time between shifts. Nurse fatigue has adverse effects on alertness and can affect provision of quality care. METHODS: An observational study using wrist actigraphs was conducted from 2019 to 2020. Participants were 82 rotating-shift nurses who provided direct nursing care in acute hospitals in South Korea. They wore actigraphs for 14 days to measure sleep parameters and predict hourly alertness and reported subjective fatigue before and after every shift. RESULTS: Nurses demonstrated shorter sleep hours, lower sleep efficiency and longer sleep latency before night shifts compared with other shifts. Fatigue was the highest before day shifts. Sleep parameters and fatigue significantly affected the steep decline in alertness in participants with alertness scores below 70. CONCLUSIONS: Sleep parameters and fatigue level contributed to the differences in decline in alertness across shifts. IMPLICATION FOR NURSING MANAGEMENT: Findings inform nurse managers, administrators to develop interventions to reduce fatigue, improve sleep quantity and quality and increase alertness among rotating-shift nurses. Management, institutional and individual factors should be considered when developing interventions.

Single-molecule FRET method to investigate the dynamics of transcription elongation through the nucleosome by RNA polymerase II.

Transcription elongation through the nucleosome is a precisely coordinated activity to ensure timely production of RNA and accurate regulation of co-transcriptional histone modifications. Nucleosomes actively participate in transcription regulation at various levels and impose physical barriers to RNA polymerase II (RNAPII) during transcription elongation. Despite its high significance, the detailed dynamics of how RNAPII translocates along nucleosomal DNA during transcription elongation and how the nucleosome structure dynamically conforms to the changes necessary for RNAPII progression remain poorly understood. Transcription elongation through the nucleosome is a complex process and investigating the changes of the nucleosome structure during this process by ensemble measurements is daunting. This is because it is nearly impossible to synchronize elongation complexes within a nucleosome or a sub-nucleosome to a designated location at a high enough efficiency for desired sample homogeneity. Here we review our recently developed single-molecule FRET experimental system and method that has fulfilled this deficiency. With our method, one can follow the changes in the structure of individual nucleosomes during transcription elongation. We demonstrated that this method enables the detailed measurements of the kinetics of transcription elongation through the nucleosome and its regulation by a transcription factor, which can be easily extended to investigations of the roles of environmental variables and histone post-translational modifications in regulating transcription elongation.

Classification and Segmentation of Longitudinal Road Marking using Convolutional Neural Networks for Dynamic Retroreflection Estimation.

Road markings constitute one of the most important elements of the road. Moreover, they are managed according to specific standards, including a criterion for a luminous contrast, which can be referred to as retroreflection. Retroreflection can be used to measure the reflection properties of road markings or other road facilities. It is essential to manage retroreflection in order to improve road safety and sustainability. In this study, we propose a dynamic retroreflection estimation method for longitudinal road markings, which employs a luminance camera and convolutional neural networks (CNNs). The images that were captured by a luminance camera were input into a classification and regression CNN model in order to determine whether the longitudinal road marking was accurately acquired. A segmentation model was also developed and implemented in order to accurately present the longitudinal road marking and reference plate if a longitudinal road marking was determined to exist in the captured image. The retroreflection was dynamically measured as a driver drove along an actual road; consequently, the effectiveness of the proposed method was demonstrated.

Super-Resolution Optical Lithography with DNA.

We developed an efficient, versatile, and accessible super-resolution microscopy method to construct a nanoparticle assembly at a spatial resolution below the optical diffraction limit. The method utilizes DNA and a photoactivated DNA cross-linker. Super-resolution optical techniques have been used only as a means to make measurements below the light diffraction limit. Furthermore, no optical technique is currently available to construct nanoparticle assemblies with a precisely designed shape and internal structure at a resolution of a few tens of nanometers (nm). Here we demonstrate that we can fulfill this deficiency by utilizing spontaneous structural dynamics of DNA hairpins combined with single-molecule fluorescence resonance energy transfer (smFRET) microscopy and a photoactivated DNA cross-linker. The stochastic fluorescence blinking due to the spontaneous folding and unfolding motions of DNA hairpins enables us to precisely localize a folded hairpin and solidify it only when it is within a predesigned target area whose size is below the diffraction limit. As the method is based on an optical microscope and an easily clickable DNA cross-linking reagent, it will provide an efficient means to create large nanoparticle assemblies with a shape and internal structure at an optical super-resolution, opening a wide window of opportunities toward investigating their photophysical and optoelectronic properties and developing novel devices.

Ferroptosis as a Novel Therapeutic Target for Friedreich's Ataxia.

Friedreich ataxia (FRDA) is a progressive neuro- and cardio-degenerative disorder characterized by ataxia, sensory loss, and hypertrophic cardiomyopathy. In most cases, the disorder is caused by GAA repeat expansions in the first introns of both alleles of the FXN gene, resulting in decreased expression of the encoded protein, frataxin. Frataxin localizes to the mitochondrial matrix and is required for iron-sulfur-cluster biosynthesis. Decreased expression of frataxin is associated with mitochondrial dysfunction, mitochondrial iron accumulation, and increased oxidative stress. Ferropotosis is a recently identified pathway of regulated, iron-dependent cell death, which is biochemically distinct from apoptosis. We evaluated whether there is evidence for ferroptotic pathway activation in cellular models of FRDA. We found that primary patient-derived fibroblasts, murine fibroblasts with FRDA-associated mutations, and murine fibroblasts in which a repeat expansion had been introduced (knockin/knockout) were more sensitive than normal control cells to erastin, a known ferroptosis inducer. We also found that the ferroptosis inhibitors ethyl 3-(benzylamino)-4-(cyclohexylamino)benzoate (SRS11-92) and ethyl 3-amino-4-(cyclohexylamino)benzoate, used at 500 nM, were efficacious in protecting human and mouse cellular models of FRDA treated with ferric ammonium citrate (FAC) and an inhibitor of glutathione synthesis [L-buthionine (S,R)-sulfoximine (BSO)], whereas caspase-3 inhibitors failed to show significant biologic activity. Cells treated with FAC and BSO consistently showed decreased glutathione-dependent peroxidase activity and increased lipid peroxidation, both hallmarks of ferroptosis. Finally, the ferroptosis inhibitor SRS11-92 decreased the cell death associated with frataxin knockdown in healthy human fibroblasts. Taken together, these data suggest that ferroptosis inhibitors may have therapeutic potential in FRDA.

The elongation factor Spt4/5 regulates RNA polymerase II transcription through the nucleosome.

RNA polymerase II (RNAPII) passes through the nucleosome in a coordinated manner, generating several intermediate nucleosomal states as it breaks and then reforms histone-DNA contacts ahead of and behind it, respectively. Several studies have defined transcription-induced nucleosome intermediates using only RNA Polymerase. However, RNAPII is decorated with elongation factors as it transcribes the genome. One such factor, Spt4/5, becomes an integral component of the elongation complex, making direct contact with the 'jaws' of RNAPII and nucleic acids in the transcription scaffold. We have characterized the effect of incorporating Spt4/5 into the elongation complex on transcription through the 601R nucleosome. Spt4/5 suppressed RNAPII pausing at the major H3/H4-induced arrest point, resulting in downstream re-positioning of RNAPII further into the nucleosome. Using a novel single molecule FRET system, we found that Spt4/5 affected the kinetics of DNA re-wrapping and stabilized a nucleosomal intermediate with partially unwrapped DNA behind RNAPII. Comparison of nucleosomes of different sequence polarities suggest that the strength of the DNA-histone interactions behind RNAPII specifies the Spt4/5 requirement. We propose that Spt4/5 may be important to coordinate the mechanical movement of RNAPII through the nucleosome with co-transcriptional chromatin modifications during transcription, which is affected by the strength of histone-DNA interactions.

DNA Oxidation and Excision Repair Pathways.

The physiological impact of the aberrant oxidation products on genomic DNA were demonstrated by embryonic lethality or the cancer susceptibility and/or neurological symptoms of animal impaired in the base excision repair (BER); the major pathway to maintain genomic integrity against non-bulky DNA oxidation. However, growing evidence suggests that other DNA repair pathways or factors that are not primarily associated with the classical BER pathway are also actively involved in the mitigation of oxidative assaults on the genomic DNA, according to the corresponding types of DNA oxidation. Among others, factors dedicated to lesion recognition in the nucleotide excision repair (NER) pathway have been shown to play eminent roles in the process of lesion recognition and stimulation of the enzyme activity of some sets of BER factors. Besides, substantial bulky DNA oxidation can be preferentially removed by a canonical NER mechanism; therefore, loss of function in the NER pathway shares common features arising from BER defects, including cancer predisposition and neurological disorders, although NER defects generally are nonlethal. Here we discuss recent achievements for delineating newly arising roles of NER lesion recognition factors to facilitate the BER process, and cooperative works of BER and NER pathways in response to the genotoxic oxidative stress.

Emerin suppresses Notch signaling by restricting the Notch intracellular domain to the nuclear membrane.

Emerin is an inner nuclear membrane protein that is involved in maintaining the mechanical integrity of the nuclear membrane. Increasing evidence supports the involvement of emerin in the regulation of gene expression; however, its precise function remains to be elucidated. Here, we show that emerin downregulated genes downstream of Notch signaling, which are activated exclusively by the Notch intracellular domain (NICD). Deletion mutant experiments revealed that the transmembrane domain of emerin is important for the inhibition of Notch signaling. Emerin interacted directly and colocalized with the NICD at the nuclear membrane. Emerin knockdown induced the phosphorylation of ERK and AKT, increased endogenous Notch signaling, and inhibited hydrogen peroxide-induced apoptosis in HeLa cells. Notably, the downregulation of barrier-to-autointegration factor (BAF) or lamin A/C increased Notch signaling by inducing the release of emerin into the cytosol, implying that nuclear membrane-bound emerin acts as an endogenous inhibitor of Notch signaling. Taken together, our results indicate that emerin negatively regulates Notch signaling by promoting the retention of the NICD at the nuclear membrane. This mechanism could constitute a new therapeutic target for the treatment of emerin-related diseases.

Chromatin structure-dependent conformations of the H1 CTD.

Linker histones are an integral component of chromatin but how these proteins promote assembly of chromatin fibers and higher order structures and regulate gene expression remains an open question. Using Förster resonance energy transfer (FRET) approaches we find that association of a linker histone with oligonucleosomal arrays induces condensation of the intrinsically disordered H1 CTD in a manner consistent with adoption of a defined fold or ensemble of folds in the bound state. However, H1 CTD structure when bound to nucleosomes in arrays is distinct from that induced upon H1 association with mononucleosomes or bare double stranded DNA. Moreover, the H1 CTD becomes more condensed upon condensation of extended nucleosome arrays to the contacting zig-zag form found in moderate salts, but does not detectably change during folding to fully compacted chromatin fibers. We provide evidence that linker DNA conformation is a key determinant of H1 CTD structure and that constraints imposed by neighboring nucleosomes cause linker DNAs to adopt distinct trajectories in oligonucleosomes compared to H1-bound mononucleosomes. Finally, inter-molecular FRET between H1s within fully condensed nucleosome arrays suggests a regular spatial arrangement for the H1 CTD within the 30 nm chromatin fiber.