A Predictive Thermal Habitat Model for Harbor Seals in the Northwest Atlantic

We analyzed projections of current and future ambient temperatures along the eastern United States in relationship to the thermal tolerance of harbor seals in air. Using the earth systems model (HadGEM2-ES) and representative concentration pathways (RCPs) 4.5 and 8.5, which are indicative of two different atmospheric CO2 concentrations, we were able to examine possible shifts in distribution based on three metrics: current preferences, the thermal limit of juveniles, and the thermal limits of adults. Our analysis focused on average ambient temperatures because harbor seals are least effective at regulating their body temperature in air, making them most susceptible to rising air temperatures in the coming years. Our study focused on the months of May, June, and August from 2041-2060 (2050) and 2061-2080 (2070) as these are the historic months in which harbor seals are known to annually come ashore to pup, breed, and molt. May, June, and August are also some of the warmest months of the year. We found that breeding colonies along the eastern United States will be limited by the thermal tolerance of juvenile harbor seals in air, while their foraging range will extend as far south as the thermal tolerance of adult harbor seals in air. Our analysis revealed that in 2070, harbor seal pups should be absent from the United States coastline nearing the end of the summer due to exceptionally high air temperatures.

Mass spectrometry-based thermal shift assay for protein-ligand binding analysis.

Described here is a mass spectrometry-based screening assay for the detection of protein-ligand binding interactions in multicomponent protein mixtures. The assay utilizes an oxidation labeling protocol that involves using hydrogen peroxide to selectively oxidize methionine residues in proteins in order to probe the solvent accessibility of these residues as a function of temperature. The extent to which methionine residues in a protein are oxidized after specified reaction times at a range of temperatures is determined in a MALDI analysis of the intact proteins and/or an LC-MS analysis of tryptic peptide fragments generated after the oxidation reaction is quenched. Ultimately, the mass spectral data is used to construct thermal denaturation curves for the detected proteins. In this proof-of-principle work, the protocol is applied to a four-protein model mixture comprised of ubiquitin, ribonuclease A (RNaseA), cyclophilin A (CypA), and bovine carbonic anhydrase II (BCAII). The new protocol's ability to detect protein-ligand binding interactions by comparing thermal denaturation data obtained in the absence and in the presence of ligand is demonstrated using cyclosporin A (CsA) as a test ligand. The known binding interaction between CsA and CypA was detected using both the MALDI- and LC-MS-based readouts described here.

Thermodynamic analysis of ligand-induced changes in protein thermal unfolding applied to high-throughput determination of ligand affinities with extrinsic fluorescent dyes.

The quantification of protein-ligand interactions is essential for systems biology, drug discovery, and bioengineering. Ligand-induced changes in protein thermal stability provide a general, quantifiable signature of binding and may be monitored with dyes such as Sypro Orange (SO), which increase their fluorescence emission intensities upon interaction with the unfolded protein. This method is an experimentally straightforward, economical, and high-throughput approach for observing thermal melts using commonly available real-time polymerase chain reaction instrumentation. However, quantitative analysis requires careful consideration of the dye-mediated reporting mechanism and the underlying thermodynamic model. We determine affinity constants by analysis of ligand-mediated shifts in melting-temperature midpoint values. Ligand affinity is determined in a ligand titration series from shifts in free energies of stability at a common reference temperature. Thermodynamic parameters are obtained by fitting the inverse first derivative of the experimental signal reporting on thermal denaturation with equations that incorporate linear or nonlinear baseline models. We apply these methods to fit protein melts monitored with SO that exhibit prominent nonlinear post-transition baselines. SO can perturb the equilibria on which it is reporting. We analyze cases in which the ligand binds to both the native and denatured state or to the native state only and cases in which protein:ligand stoichiometry needs to treated explicitly.