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At least 451 records · Page 25

Machine learning based job status prediction in scientific clusters

Large high-performance computing systems are built with increasing number of components with more CPU cores, more memory, and more storage space. At the same time, scientific applications have been growing in complexity. Together, they are leading to more frequent unsuccessful job statuses on HPC systems. From measured job statuses, 23.4% of CPU time was spent to the unsuccessful jobs. Here, we set out to study whether these unsuccessful job statuses could be anticipated from known job characteristics. To explore this possibility, we have developed a job status prediction method for the execution of jobs on scientific clusters. The Random Forests algorithm was applied to extract and characterize the patterns of unsuccessful job statuses. Experimental results show that our method can predict the unsuccessful job statuses from the monitored ongoing job executions in 99.8% the cases with 83.6% recall and 94.8% precision. Lastly, this prediction accuracy can be sufficiently high that it can be used to mitigation procedures of predicted failures.

97 MATHEMATICS AND COMPUTING↗

Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb

Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb-Enhancer Genie (LEG), a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface. We predict limb enhancers using a combination of > 50 published limb-specific datasets and clusters of evolutionarily conserved transcription factor binding sites, taking advantage of the patterns observed at previously in vivo validated elements. By combining different statistical models, our approach outperforms current state-of-the-art methods and provides interpretable measures of feature importance. Our results indicate that including a previously unappreciated score that quantifies tissue-specific nuclease accessibility significantly improves prediction performance. We demonstrate the utility of our approach through in vivo validation of newly predicted elements. Moreover, we describe general features that can guide the type of datasets to include when predicting tissue-specific enhancers genome-wide, while providing an accessible resource to the general biological community and facilitating the functional interpretation of genetic studies of limb malformations.

59 BASIC BIOLOGICAL SCIENCES↗

FLS2-BAK1 Extracellular Domain Interaction Sites Required for Defense Signaling Activation

Signaling initiation by receptor-like kinases (RLKs) at the plasma membrane of plant cells often requires regulatory leucine-rich repeat (LRR) RLK proteins such as SERK or BIR proteins. The present work examined how the microbe-associated molecular pattern (MAMP) receptor FLS2 builds signaling complexes with BAK1 (SERK3). We first, using in vivo methods that validate separate findings by others, demonstrated that flg22 (flagellin epitope) ligand-initiated FLS2-BAK1 extracellular domain interactions can proceed independent of intracellular domain interactions. We then explored a candidate SERK protein interaction site in the extracellular domains (ectodomains; ECDs) of the significantly different receptors FLS2, EFR (MAMP receptors), PEPR1 (damage-associated molecular pattern (DAMP) receptor), and BRI1 (hormone receptor). Repeat conservation mapping revealed a cluster of conserved solvent-exposed residues near the C-terminus of models of the folded LRR domains. However, site-directed mutagenesis of this conserved site in FLS2 did not impair FLS2-BAK1 ECD interactions, and mutations in the analogous site of EFR caused receptor maturation defects. Hence this conserved LRR C-terminal region apparently has functions other than mediating interactions with BAK1. In vivo tests of the subsequently published FLS2-flg22-BAK1 ECD co-crystal structure were then performed to functionally evaluate some of the unexpected configurations predicted by that crystal structure. In support of the crystal structure data, FLS2-BAK1 ECD interactions were no longer detected in in vivo co-immunoprecipitation experiments after site-directed mutagenesis of the FLS2 BAK1-interaction residues S554, Q530, Q627 or N674. In contrast, in vivo FLS2-mediated signaling persisted and was only minimally reduced, suggesting residual FLS2-BAK1 interaction and the limited sensitivity of co-immunoprecipitation data relative to in vivo assays for signaling outputs. However, Arabidopsis plants expressing FLS2 with the Q530A+Q627A double mutation were impaired both in detectable interaction with BAK1 and in FLS2-mediated responses, lending overall support to current models of FLS2 structure and function.

59 BASIC BIOLOGICAL SCIENCES↗

Star Formation, Supernovae, Iron, and α: Consistent Cosmic and Galactic Histories

Recent versions of the observed cosmic star formation history (SFH) have resolved an inconsistency with the stellar mass density history. We show that the revised SFH also scales up the delay-time distribution (DTD) of Type Ia supernovae (SNe Ia), as determined from the observed volumetric SN Ia rate history, aligning it with other field-galaxy SN Ia DTD measurements. The revised-SFH-based DTD has a t{sup −1.1±0.1} form and a Hubble-time-integrated production efficiency of N/M{sub ⋆}=1.3±0.1 SNe Ia per 1000 M{sub ⊙} of formed stellar mass. Using these revised histories and updated empirical iron yields of the various SN types, we re-derive the cosmic iron accumulation history. Core-collapse SNe and SNe Ia have contributed about equally to the total mass of iron in the universe today. We find the track of the average cosmic gas element in the [α/Fe] versus [Fe/H] abundance-ratio plane. The track is broadly similar to the observed main locus of Galactic stars in this plane, indicating a Milky Way (MW) SFH similar in form to the cosmic one. We easily find a simple MW SFH that makes the track closely match this stellar locus. Galaxy clusters appear to have a higher-normalization DTD. This cluster DTD, combined with a short-burst MW SFH peaked at z = 3, produces a track that matches remarkably well the observed “high-α” locus of MW stars, suggesting the halo/thick-disk population has had a galaxy-cluster-like formation mode. Thus, a simple two-component SFH, combined with empirical DTDs and SN iron yields, suffices to closely reproduce the MW’s stellar abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗

The Hubble space telescope UV legacy survey of galactic globular clusters. I. Overview of the project and detection of multiple stellar populations

In this paper we describe a new UV-initiative Hubble Space Telescope project (GO-13297) that will complement the existing F606W and F814W database of the Advanced Camera for Surveys Globular Cluster (GC) Treasury by imaging most of its clusters through UV/blue WFC3/UVIS filters F275W, F336W, and F438W. This “magic trio” of filters has shown an uncanny ability to disentangle and characterize multiple population (MP) patterns in GCs in a way that is exquisitely sensitive to C, N, and O abundance variations. Combination of these passbands with those in the optical also gives the best leverage for measuring helium enrichment. The dozen clusters that had previously been observed in these bands exhibit a bewildering variety of MP patterns, and the new survey will map the full variance of the phenomenon. The ubiquity of multiple stellar generations in GCs has made the formation of these cornerstone objects more intriguing than ever; GC formation and the origin of their MPs have now become one and the same problem. In this paper we will describe the database and our data reduction strategy, as well as the uses we intend to make of the final photometry, astrometry, and PMs. We will also present preliminary color–magnitude diagrams from the data so far collected. These diagrams also draw on data from GO-12605 and GO-12311, which served as a pilot project for the present GO-13297.

79 ASTRONOMY AND ASTROPHYSICS↗

A weather pattern responsible for increasing wildfires in the western United States

Abstract The western United States (U.S.) has been experiencing more severe wildfires, in part due to climate change, but the underlying synoptic patterns and their modulation in driving fire weather is unclear. Here we investigated the relationship between weather regimes (WRs) and fire weather indices, specifically vapor pressure deficit (VPD) and the Canadian Forest Fire Weather Index. By identifying five singular WRs using k-means clustering, we found that a particular regime (WR-2), one characterized by a distinct tripolar wave train pattern over the continental U.S., has exhibited an increased frequency since 1980. The ascribed WR-2 regime was found to be mainly responsible for rising trends in the fire weather indices, especially VPD. Further, the average fire indices of the WR-2 regime played a more important role than the frequency in shaping the rising trends in the fire weather indices. The increased frequency of the WR-2 WR was mainly attributed to anthropogenic forcing and, the year-to-year variation of the frequency was associated with sea surface temperature anomalies over the subtropical eastern Pacific. Human-induced climate change might have furthered the exacerbation of wildfire danger in the western U.S. by modulating the behaviors of WRs and fire weather indices.

Zhang, Wei (ORCID:0000000221698749)↗

Extension of Large Fire Emissions From Summer to Autumn and Its Drivers in the Western US

Abstract Burned areas in the western US have increased ten‐fold since 1980s, which are attributable to multiple factors, including increasing heat, changing precipitation patterns, and extended drought. To better understand how these factors contribute to large fire emissions (gridded monthly fire emissions >95th percentile of all the fire emissions in the western US; 0.009 Gg/month), we build a machine learning model to predict fire emissions (PM 2.5 ) over the western US at 0.25° resolution, interpreted using explainable artificial intelligence (XAI). From the predictor contributions derived from XAI, we conduct k‐means clustering analysis to identify four clusters of predictor variables representing different drivers of large fire emissions. The four clusters feature the contributions of fuel load (Cluster 1) and different levels of dryness (Cluster 2–4), controlled by fuel moisture, drought condition, and fire‐favorable large‐scale meteorological patterns featuring high temperature, high pressure, and low relative humidity. In the past two decades, large fire emissions peak in summer. However, large fire emissions increased significantly in September and October in 2010–2020 relative to 2000–2009, extending the peak large fire emissions from summer to autumn. The larger enhancements of large fire emissions during autumn compared to summer are contributed by decreased fuel moisture, along with more frequent concurrent fire‐favorable large‐scale meteorological patterns and drought. These results highlight fuel drying as a common driver supported by multiple drivers, such as warmer temperature and more frequent synoptic patterns favorable for fires, in increasing the autumn risk of large fire emissions across the western US.

54 ENVIRONMENTAL SCIENCES↗

Two-component vector solitons in defocusing Kerr-type media with spatially modulated nonlinearity

We present a class of exact solutions to the coupled (2+1)-dimensional nonlinear Schrödinger equation with spatially modulated nonlinearity and a special external potential, which describe the evolution of two-component vector solitons in defocusing Kerr-type media. We find a robust soliton solution, constructed with the help of Whittaker functions. For specific choices of the topological charge, the radial mode number and the modulation depth, the solitons may exist in various forms, such as the half-moon, necklace-ring, and sawtooth vortex-ring patterns. Our results show that the profile of such solitons can be effectively controlled by the topological charge, the radial mode number, and the modulation depth. - Highlights: • Two-component vector soliton clusters in defocusing Kerr-type media are reported. • These soliton clusters are constructed with the help of Whittaker functions. • The half-moon, necklace-ring and vortex-ring patterns are found. • The profile of these solitons can be effectively controlled by three soliton parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Signatures of large-scale cold fronts in the optically-selected merging cluster HSC J085024+001536

Abstract We represent a joint X-ray, weak-lensing, and optical analysis of the optically-selected merging cluster, HSC J085024+001536, from the Subaru HSC-SSP survey. Both the member galaxy density and the weak-lensing mass map show that the cluster is composed of south-east and north-west components. The two-dimensional weak-lensing analysis shows that the south-east component is the main cluster, and the sub-cluster and main cluster mass ratio is $0.32^{+0.75}_{-0.23}$. The north-west sub-cluster is offset by ∼700 kpc from the main cluster center, and their relative line-of-sight velocity is ∼1300 km s−1 from spectroscopic redshifts of member galaxies. The X-ray emission is concentrated around the main cluster, while the gas mass fraction within a sphere of 1′ radius of the sub-cluster is only $f_{\mathrm{gas}}=4.0^{+2.3}_{-3.3}\%$, indicating that the sub-cluster gas was stripped by ram pressure. An X-ray residual image shows three arc-like excess patterns, of which two are symmetrically located at ∼550 kpc from the X-ray morphological center, and the other is close to the X-ray core. The excess close to the sub-cluster has a cold-front feature where dense-cold gas and thin-hot gas contact. The two outer excesses are tangentially elongated about ∼450–650 kpc, suggesting that the cluster is merged with a non-zero impact parameter. Overall features revealed by the multi-wavelength datasets indicate that the cluster is at the second impact or later. Since the optically-defined merger catalog is unbiased for merger boost of the intracluster medium, X-ray follow-up observations will pave the way to understand merger physics at various phases.

Tanaka, Keigo↗

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

Rainfall↗

Isotopomer-selective spectra of a single intact H 2 O molecule in the Cs + (D 2 O) 5 H 2 O isotopologue: Going beyond pattern recognition to harvest the structural information encoded in vibrational spectra

We report the vibrational signatures of a single H 2 O water molecule occupying distinct sites of the hydration network in the Cs + (H 2 O) 6 cluster. This is accomplished using isotopomer selective IR-IR hole-burning on the Cs + (D 2 O) 5 (H 2 O) clusters formed by gas-phase exchange of a single, intact H 2 O molecule for D 2 O in the Cs + (D 2 O) 6 ion. The OH stretching pattern of the Cs + (H 2 O) 6 isotopologue is accurately recovered by superposition of the isotopomer spectra, thus establishing that the H 2 O incorporation is random and that the OH stretching manifold is largely due to contributions from decoupled water molecules. This behavior enables a powerful new way to extract structural information from vibrational spectra of size-selected clusters by explicitly identifying the local environments responsible for specific infrared features. The Cs + (H 2 O) 6 structure was unambiguously assigned to the 4.1.1 isomer (a homodromic water tetramer with two additional flanking water molecules) from the fact that its computed IR spectrum matches the observed overall pattern and recovers the embedded correlations in the two OH stretching bands of the water molecule in the Cs + (D 2 O) 5 (H 2 O) isotopomers. The 4.1.1 isomer is the lowest in energy among other candidate networks at advanced (e.g., CCSD(T)) levels of theoretical treatment after corrections for (anharmonic) zero-point energy (ZPE). With the structure in hand, we then explore the mechanical origin of the various band locations using a local electric field formalism. Furthermore, this approach promises to provide a transferrable scheme for the prediction of the OH stretching fundamentals displayed by water networks in close proximity to solute ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sensitivity to Thermonuclear Reaction Rates in Modeling the Abundance Anomalies of NGC 2419

Abundance anomalies in globular clusters provide strong evidence for multiple stellar populations within each cluster. These populations are usually interpreted as distinct generations, with the currently observed second-generation stars having formed in part from the ejecta of massive, first-generation “polluter” stars, giving rise to the anomalous abundance patterns. The precise nature of the polluters and their enrichment mechanism are still unclear. Even so, the chemical abundances measured in second-generation stars within the globular cluster NGC 2419 provide insight into this puzzling process. Previous work used Monte Carlo nuclear reaction network calculations to constrain the temperature–density conditions that could reproduce the observed abundances, thereby placing robust limits on the origins of the polluter material. The effect of individual reaction rates on these conditions has not been studied, however. Thus, we perform an exhaustive sensitivity study on the nuclear physics input to determine which reactions have the greatest impact on these predictions. We find that the {sup 30}Si(p,γ){sup 31}P, {sup 37}Ar(p,γ){sup 38}K, {sup 38}Ar(p,γ){sup 39}K, and {sup 39}K(p,γ){sup 40}Ca reactions are all critical in determining the temperature–density conditions, and ultimately, the origins of the polluter material. We conclude with recommendations for future experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

traffic flow management↗

Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

weather↗

Field-assisted patterned dissolution of silver nanoparticles in phosphate glass

Phosphate glass samples doped with silver ions through a Na⁺-Ag⁺ ion-exchange process were treated in a hydrogen atmosphere at temperatures near 430°C for durations ranging from 4 to 5 h. Such treatment causes metallic silver precipitation at the surface as well as nanoclustering of silver atoms under the surface under conditions very similar to those used for silicate glasses. The presence of silver clusters resulted in a characteristic coloring of the glass and was verified by the observation of a plasmon resonance peak near 410–420 nm in the absorption spectra. Applying a DC voltage between 1.4 and 2 kV at temperatures between 120 and 130°C led to dissolution of the clusters in the area under the positive electrode, thereby bleaching the glass color. The use of a patterned doped-silicon electrode further led to the formation of a 300 nm thick surface relief on the glass surface and of a volume complex permittivity grating extending at least 4 μm under the surface. Such volume complex refractive index gratings may find applications in passive or active (laser) photonic devices in rare-earth doped phosphate glasses, where conventional bulk grating formation techniques have limited applicability.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Coordination of the Ser2056 and Thr2609 Clusters of DNA-PKcs in Regulating Gamma Rays and Extremely Low Fluencies of Alpha-Particle Irradiation to G 0 /G 1 Phase Cells

The catalytic subunit of DNA dependent protein kinase (DNA-PKcs) and its kinase activity are critical for mediation of non-homologous end-joining (NHEJ) of DNA double-strand breaks (DSB) in mammalian cells after gamma-ray irradiation. Additionally, DNA-PKcs phosphorylations at the T2609 cluster and the S2056 cluster also affect DSB repair and cellular sensitivity to gamma radiation. Previously we reported that phosphorylations within these two regions affect not only NHEJ but also homologous recombination repair (HRR) dependent DSB repair. In this study, we further examine phenotypic effects on cells bearing various combinations of mutations within either or both regions. Effects studied included cell killing as well as chromosomal aberration induction after 0.5–8 Gy gamma-ray irradiation delivered to synchronized cells during the G0/G1 phase of the cell cycle. Blocking phosphorylation within the T2609 cluster was most critical regarding sensitization and depended on the number of available phosphorylation sites. It was also especially interesting that only one substitution of alanine in each of the two clusters separately abolished the restoration of wild-type sensitivity by DNA-PKcs. Similar patterns were seen for induction of chromosomal aberrations, reflecting their connection to cell killing. To study possible change in coordination between HRR and NHEJ directed repair in these DNA-PKcs mutant cell lines, we compared the induction of sister chromatid exchanges (SCEs) by very low fluencies of alpha particles with mutant cells defective in the HRR pathway that is required for induction of SCEs. Finally, levels of true SCEs induced by very low fluence of alpha-particle irradiation normally seen in wild-type cells were only slightly decreased in the S2056 cluster mutants, but were completely abolished in the T2609 cluster mutants and were indistinguishable from levels seen in HRR deficient cells. Again, a single substitution in the S2056 together with a single substitution in the T2609 cluster abolished SCE formation and thus also effectively interferes with HRR.

59 BASIC BIOLOGICAL SCIENCES↗