Significance of the dissociation of Dna2 by flap endonuclease 1 to Okazaki fragment processing in Saccharomyces cerevisiae

Okazaki fragments are initiated by short RNA/DNA primers, which are displaced into flap intermediates for processing. Flap endonuclease 1 (FEN1) and Dna2 are responsible for flap cleavage. Replication protein A (RPA)-bound flaps inhibit cleavage by FEN1 but stimulate Dna2, requiring that Dna2 cleaves prior to FEN1. Upon cleavage, Dna2 leaves a short flap, which is then cut by FEN1 forming a nick for ligation. Both enzymes require a flap with a free 5'-end for tracking to the cleavage sites. Previously, we demonstrated that FEN1 disengages the tracking mechanism of Dna2 to remove it from the flap. To determine why the disengagement mechanism evolved, we measured FEN1 dissociation of Dna2 on short RNA and DNA flaps, which occur during flap processing. Dna2 tracked onto these flaps but could not cleave, presenting a block to FEN1 entry. However, FEN1 disengaged these nonproductively bound Dna2 molecules, proceeding on to conduct proper cleavage. These results clarify the importance of disengagement. Additional results showed that flap substrate recognition and tracking by FEN1, as occur during fragment processing, are required for effective displacement of the flap-bound Dna2. Dna2 was recently shown to dissociate flap-bound RPA, independent of cleavage. Using a nuclease-defective Dna2 mutant, we reconstituted the sequential dissociation reactions in the proposed RPA/Dna2/FEN1 pathway showing that, even without cutting, Dna2 enables FEN1 to cleave RPA-coated flaps. In summary, RPA, Dna2, and FEN1 have evolved highly coordinated binding properties enabling one protein to succeed the next for proper and efficient Okazaki flap processing

Dna2 is a structure-specific nuclease, with affinity for 5'-flap intermediates

Dna2 is a nuclease/helicase with proposed roles in DNA replication, double-strand break repair and telomere maintenance. For each role Dna2 is proposed to process DNA substrates with a 5'-flap. To date, however, Dna2 has not revealed a preference for binding or cleavage of flaps over single-stranded DNA. Using DNA binding competition assays we found that Dna2 has substrate structure specificity. The nuclease displayed a strong preference for binding substrates with a 5'-flap or some variations of flap structure. Further analysis revealed that Dna2 recognized and bound both the single-stranded flap and portions of the duplex region immediately downstream of the flap. A model is proposed in which Dna2 first binds to a flap base, and then the flap threads through the protein with periodic cleavage, to a terminal flap length of ~5 nt. This resembles the mechanism of flap endonuclease 1, consistent with cooperation of these two proteins in flap processing

Towards a Satellite Formaldehyde in situ Hybrid Estimate for Organic Aerosol Abundance

Organic aerosol (OA) is one of the main components of the global particulate burden and intimately links natural and anthropogenic emissions with air quality and climate. It is challenging to accurately represent OA in global models. Direct quantification of global OA abundance is not possible with current remote sensing technology; however, it may be possible to exploit correlations of OA with remotely observable quantities to infer OA spatiotemporal distributions. In particular, formaldehyde (HCHO) and OA share common sources via both primary emissions and secondary production from oxidation of volatile organic compounds (VOCs). Here, we examine OAHCHO correlations using data from summertime airborne campaigns investigating biogenic (NASA SEAC4RS and DC3), biomass burning (NASA SEAC4RS), and anthropogenic conditions (NOAA CalNex and NASA KORUS-AQ). In situ OA correlates well with HCHO (r=0.590.97), and the slope and intercept of this relationship depend on the chemical regime. For biogenic and anthropogenic regions, the OAHCHO slopes are higher in low NOx conditions, because HCHO yields are lower and aerosol yields are likely higher. The OAHCHO slope of wildfires is over 9 times higher than that for biogenic and anthropogenic sources. The OAHCHO slope is higher for highly polluted anthropogenic sources (e.g., KORUS-AQ) than less polluted (e.g., CalNex) anthropogenic sources. Near-surface OAs over the continental US are estimated by combining the observed in situ relationships with HCHO column retrievals from NASA's Ozone Monitoring Instrument (OMI). HCHO vertical profiles used in OA estimates are from climatology a priori profiles in the OMI HCHO retrieval or output of specific period from a newer version of GEOS-Chem. Our OA estimates compare well with US EPA IMPROVE data obtained over summer months (e.g., slope =0.600.62, r=0.56 for August 2013), with correlation performance comparable to intensively validated GEOS-Chem (e.g., slope =0.57, r=0.56) with IMPROVE OA and superior to the satellite-derived total aerosol extinction (r=0.41) with IMPROVE OA. This indicates that OA estimates are not very sensitive to these HCHO vertical profiles and that a priori profiles from OMI HCHO retrieval have a similar performance to that of the newer model version in estimating OA. Improving the detection limit of satellite HCHO and expanding in situ airborne HCHO and OA coverage in future missions will improve the quality and spatiotemporal coverage of our OA estimates, potentially enabling constraints on global OA distribution

Profiles of Reactive Trace Gases over Remote Oceans During ATom

The Atmospheric Tomography (ATom) mission deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft on four campaigns spanning each season. ATom systematically sampled the atmosphere from 0.2 to 12 kilometer altitude, from 85 degrees North Latitude to 65 degrees South Latitude, in both the Pacific and the Atlantic to provide detailed profiles of chemical composition over the remote oceans. We will present profiles of reactive trace species, such as O3, NOx, NOy, HOx, HCHO, and several other short-lived source gases. We will combine these measurements with results from a 0-D box model to show their utility in (1) evaluating gradients in latitude/season, (2) identifying contributions of pollution from long-range and convective transport, and (3) evaluating column measurements from remote sensing satellite instruments

Genetic inhibition of hepatic acetyl-CoA carboxylase activity increases liver fat and alters global protein acetylationa

Lipid deposition in the liver is associated with metabolic disorders including fatty liver disease, type II diabetes, and hepatocellular cancer. The enzymes acetyl-CoA carboxylase 1 (ACC1) and ACC2 are powerful regulators of hepatic fat storage; therefore, their inhibition is expected to prevent the development of fatty liver. In this study we generated liver-specific ACC1 and ACC2 double knockout (LDKO) mice to determine how the loss of ACC activity affects liver fat metabolism and whole-body physiology. Characterization of LDKO mice revealed unexpected phenotypes of increased hepatic triglyceride and decreased fat oxidation. We also observed that chronic ACC inhibition led to hyper-acetylation of proteins in the extra-mitochondrial space. In sum, these data reveal the existence of a compensatory pathway that protects hepatic fat stores when ACC enzymes are inhibited. Furthermore, we identified an important role for ACC enzymes in the regulation of protein acetylation in the extra-mitochondrial space

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

Plasminogen Alleles Influence Susceptibility to Invasive Aspergillosis

Invasive aspergillosis (IA) is a common and life-threatening infection in immunocompromised individuals. A number of environmental and epidemiologic risk factors for developing IA have been identified. However, genetic factors that affect risk for developing IA have not been clearly identified. We report that host genetic differences influence outcome following establishment of pulmonary aspergillosis in an exogenously immune suppressed mouse model. Computational haplotype-based genetic analysis indicated that genetic variation within the biologically plausible positional candidate gene plasminogen (Plg; Gene ID 18855) correlated with murine outcome. There was a single nonsynonymous coding change (Gly110Ser) where the minor allele was found in all of the susceptible strains, but not in the resistant strains. A nonsynonymous single nucleotide polymorphism (Asp472Asn) was also identified in the human homolog (PLG; Gene ID 5340). An association study within a cohort of 236 allogeneic hematopoietic stem cell transplant (HSCT) recipients revealed that alleles at this SNP significantly affected the risk of developing IA after HSCT. Furthermore, we demonstrated that plasminogen directly binds to Aspergillus fumigatus. We propose that genetic variation within the plasminogen pathway influences the pathogenesis of this invasive fungal infection