Explore the vast range of titles available.

Replication Protein A (RPA), the major eukaryotic single stranded DNA-binding protein, binds to exposed ssDNA to protect it from nucleases, participates in a myriad of nucleic acid transactions and coordinates the recruitment of other important players. RPA is a heterotrimer and coats long stretches of single-stranded DNA (ssDNA). The precise molecular architecture of the RPA subunits and its DNA binding domains (DBDs) during assembly is poorly understood. Using cryo electron microscopy we obtained a 3D reconstruction of the RPA trimerisation core bound with ssDNA (∼55 kDa) at ∼4.7 Å resolution and a dimeric RPA assembly on ssDNA. FRET-based solution studies reveal dynamic rearrangements of DBDs during coordinated RPA binding and this activity is regulated by phosphorylation at S178 in RPA70. We present a structural model on how dynamic DBDs promote the cooperative assembly of multiple RPAs on long ssDNA. Replication Protein A (RPA) coats single stranded DNA (ssDNA) generated during DNA recombination, replication and repair. Here the authors present a structural model suggesting how RPA’s DNA-binding domains promote cooperative assembly of multiple RPAs on long ssDNA.

Replication protein A (RPA) coordinates important DNA metabolic events by stabilizing single-stranded DNA (ssDNA) intermediates, activating the DNA-damage response and handing off ssDNA to the appropriate downstream players. Six DNA-binding domains (DBDs) in RPA promote high-affinity binding to ssDNA yet also allow RPA displacement by lower affinity proteins. We generated fluorescent versions of Saccharomyces cerevisiae RPA and visualized the conformational dynamics of individual DBDs in the context of the full-length protein. We show that both DBD-A and DBD-D rapidly bind to and dissociate from ssDNA while RPA remains bound to ssDNA. The recombination mediator protein Rad52 selectively modulates the dynamics of DBD-D. These findings reveal how RPA-interacting proteins with lower ssDNA binding affinities can access the occluded ssDNA and remodel individual DBDs to replace RPA.A combination of bulk and single-molecule fluorescence analysis reveals the choreography of binding and rearrangement of individual DNA-binding domains of RPA during homologous recombination.

ABSTRACT Molecular machines within cells dynamically assemble, disassemble, and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy (CoSMoS), in which individual labeled molecules are seen transiently associating with a surface-tethered partner, or other total internal reflection fluorescence microscopy (TIRFM) approaches in which the interactions elicit changes in fluorescence in the labeled surface-tethered partner. When multiple interacting partners can form ternary, quaternary and higher order complexes, the types of spatial and temporal organization of these complexes can be deduced from the order of appearance and reorganization of the components. Time evolution of complex architectures can be followed by changes in the fluorescence behavior in multiple channels. Here, we describe the kinetic event resolving algorithm (KERA), a software tool for organizing and sorting the discretized fluorescent trajectories from a range of single-molecule experiments. KERA organizes the data in groups by transition patterns, and displays exhaustive dwell-time data for each interaction sequence. Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics and architecture of the macromolecular complexes. We demonstrate KERA’s utility by analyzing conformational dynamics of two DNA binding proteins: RPA and XPD helicase. Competing Interest Statement The authors have declared no competing interest. Footnotes * Updated supplementary information * https://github.com/MSpiesLab/KERA

Nucleotide excision repair (NER) promotes genomic integrity by correcting bulky DNA adducts damage caused by external factors such as ultraviolet light. Defects in NER enzymes are associated with pathological conditions such as Xeroderma Pigmentosum, trichothiodystrophy, and Cockayne syndrome. A critical step in NER is the binding of the Xeroderma Pigmentosum group A protein (XPA) to the DNA adduct. To better capture the dynamics of XPA interactions with DNA during NER we have utilized the fluorescence enhancement through non-canonical amino acids (FEncAA) approach. 4-azido-L-phenylalanine (4AZP) was incorporated at Arg-153 in human XPA and conjugated to Cy3 using strain-promoted azide-alkyne cycloaddition. The resulting fluorescent human XPA protein (hXPACy3) shows no loss in DNA binding activity and generates a robust change in fluorescence upon binding to DNA. Here we describe methods to generate hXPACy3 and detail experimental conditions required to stably maintain the protein during biochemical and biophysical studies.Competing Interest StatementThe authors have declared no competing interest.

Replication protein A (RPA) coordinates important DNA metabolic events by stabilizing single-strand DNA (ssDNA) intermediates, activating the DNA damage response, and handing off ssDNA to appropriate downstream players. Six DNA binding domains (DBDs) in RPA promote high affinity binding to ssDNA, but also allow RPA displacement by lower affinity proteins. We have made fluorescent versions of RPA and visualized the conformational dynamics of individual DBDs in the context of the full-length protein. We show that both DBD-A and DBD-D rapidly bind to and dissociate from ssDNA, while RPA as a whole remains bound to ssDNA. The recombination mediator protein Rad52 selectively modulates the dynamics of DBD-D. This demonstrates how RPA interacting proteins, with lower ssDNA binding affinity, can access the occluded ssDNA and remodel individual DBDs to replace RPA. The choreography of binding and rearrangement of the individual domains of RPA during homologous recombination is revealed.

Climate change is expected to profoundly affect key food production sectors, including fisheries and agriculture. However, the potential impacts of climate change on these sectors are rarely considered jointly, especially below national scales, which can mask substantial variability in how communities will be affected. Here, we combine socioeconomic surveys of 3,008 households and intersectoral multi-model simulation outputs to conduct a sub-national analysis of the potential impacts of climate change on fisheries and agriculture in 72 coastal communities across five Indo-Pacific countries (Indonesia, Madagascar, Papua New Guinea, Philippines, and Tanzania). Our study reveals three key findings: First, overall potential losses to fisheries are higher than potential losses to agriculture. Second, while most locations (> 2/3) will experience potential losses to both fisheries and agriculture simultaneously, climate change mitigation could reduce the proportion of places facing that double burden. Third, potential impacts are more likely in communities with lower socioeconomic status.

Loss of imprinting at IGF2, generally through an H19-independent mechanism, is associated with a large percentage of patients with the overgrowth and cancer predisposition condition Beckwith-Wiedemann syndrome (BWS). Imprinting control elements are proposed to exist within the KvLQT1 locus, because multiple BWS-associated chromosome rearrangements disrupt this gene. We have identified an evolutionarily conserved, maternally methylated CpG island (KvDMR1) in an intron of the KvLQT1 gene. Among 12 cases of BWS with normal H19 methylation, 5 showed demethylation of KvDMR1 in fibroblast or lymphocyte DNA; whereas, in 4 cases of BWS with H19 hypermethylation, methylation at KvDMR1 was normal. Thus, inactivation of H19 and hypomethylation at KvDMR1 (or an associated phenomenon) represent distinct epigenetic anomalies associated with biallelic expression of IGF2. Reverse transcription-PCR analysis of the human and syntenic mouse loci identified the presence of a KvDMR1-associated RNA transcribed exclusively from the paternal allele and in the opposite orientation with respect to the maternally expressed KvLQT1 gene. We propose that KvDMR1 and/or its associated antisense RNA (KvLQT1-AS) represents an additional imprinting control element or center in the human 11p15.5 and mouse distal 7 imprinted domains.

Exercise, especially in the heat, can contribute to acute kidney injury, which can expedite chronic kidney disease onset. The additional stress of ibuprofen use is hypothesized to increase renal stress. To observe the effects of endurance cycling in the heat on renal function. Secondarily, we investigated the effect of ibuprofen ingestion on kidney stress. Randomized, placebo controlled and observational methods were utilized. Forty cyclists (52±9y, 21.7±6.5% body fat) volunteered and completed an endurance cycling event (5.7±1.2h) in the heat (33.2±5.0°C, 38.4±10.7% RH). Thirty-five participants were randomized to ingest a placebo (n=17) or 600mg ibuprofen (n=18) pre-event. A blood sample was drawn before and following the event. Serum creatinine was assessed by colorimetric assay. An ELISA was used to measure serum neutrophil gelatinase-associated lipocalin. Fractional excretion of sodium was calculated after urinary and serum electrolyte analyses. Placebo versus ibuprofen groups contributed no significant difference in any variable (p>0.05). Serum creatinine significantly increased from pre- (0.52±0.14mg/dL) to post-event (0.88±0.21mg/dL; p<0.001). Serum neutrophil gelatinase-associated lipocalin significantly increased (pre: 68.51±17.54ng/mL; post: 139.12±36.52ng/mL; p<0.001) and fractional excretion of sodium was significantly reduced from pre- (0.52±0.24%) to post-event (0.27±0.18%; p<0.001). Changes in renal biomarkers suggest mild acute kidney injury and reduced kidney function during a single bout of endurance cycling in the heat, without influence from moderate ibuprofen ingestion.

We investigated the impact of nutrient intake on hydration biomarkers in cyclists before and after a 161 km ride, including one hour after a 650 mL water bolus consumed post-ride. To control for multicollinearity, we chose a clustering-based, machine learning statistical approach. Five hydration biomarkers (urine color, urine specific gravity, plasma osmolality, plasma copeptin, and body mass change) were configured as raw- and percent change. Linear regressions were used to test for associations between hydration markers and eight predictor terms derived from 19 nutrients merged into a reduced-dimensionality dataset through serial k-means clustering. Most predictor groups showed significant association with at least one hydration biomarker: (1) Glycemic Load + Carbohydrates + Sodium, (2) Protein + Fat + Zinc, (3) Magnesium + Calcium, (4) Pinitol, (5) Caffeine, (6) Fiber + Betaine, and (7) Water; potassium + three polyols, and mannitol + sorbitol showed no significant associations with any hydration biomarker. All five hydration biomarkers were associated with at least one nutrient predictor in at least one configuration. We conclude that in a real-life scenario, some nutrients may serve as mediators of body water, and urine-specific hydration biomarkers may be more responsive to nutrient intake than measures derived from plasma or body mass.