Modeling Genomes to Phenomes to Populations in a Changing Climate: The Need for Collaborative Networks

Condensed Abstract Climate is changing globally and its impacts can arise at different levels of biological organization; yet, cross-level consequences of climate change are still poorly understood. Designing effective environmental management and adaptation plans requires implementation of mechanistic models that span the biological hierarchy. Because biological systems are inherently complex and dynamic in nature, dealing with complexities efficiently necessitates simplification of systems or approximation of relevant processes, but there is little consensus on mathematical approaches to scale from genes to populations. Here we present an effort that aims to bring together groups that often do not interact, but that are essential to illuminating the complexities of life: empirical scientists and mathematical modelers, spanning levels of biological organization from genomes to organisms to populations. Through interplay between theory, models, and data, we aim to facilitate the generation of a new synthesis and a conceptual framework for biology across levels

Muscular Apoptosis but Not Oxidative Stress Increases with Old Age in a Long-Lived Diver, the Weddell Seal

Seals experience repeated bouts of ischemia–reperfusion while diving, potentially exposing their tissues to increased oxidant generation and thus oxidative damage and accelerated aging. We contrasted markers of oxidative damage with antioxidant profiles across age and sex for propulsive (longissismus dorsi) and maneuvering (pectoralis) muscles of Weddell seals to determine whether previously observed morphological senescence is associated with oxidative stress. In longissismus dorsi, old (age 17–26 years) seals exhibited a nearly 2-fold increase in apoptosis over young (age 9–16 years) seals. There was no evidence of age-associated changes in lipid peroxidation or enzymatic antioxidant profiles. In pectoralis, 4-hydroxynonenal-Lys (4-HNE-Lys) levels increased 1.5-fold in old versus young seals, but lipid hydroperoxide levels and apoptotic index did not vary with age. Glutathione peroxidase activity was 1.5-fold higher in pectoralis of old versus young animals, but no other antioxidants changed with age in this muscle. With respect to sex, no differences in lipid hydroperoxides or apoptosis were observed in either muscle. Males had higher HSP70 expression (1.4-fold) and glutathione peroxidase activity (1.3-fold) than females in longissismus dorsi, although glutathione reductase activity was 1.4-fold higher in females. No antioxidants varied with sex in pectoralis. These results show that apoptosis is not associated with oxidative stress in aged Weddell seal muscles. Additionally, the data suggest that adult seals utilize sex-specific antioxidant strategies in longissismus dorsi but not pectoralis to protect skeletal muscles from oxidative damage

Sulfide Catabolism Ameliorates Hypoxic Brain Injury

The mammalian brain is highly vulnerable to oxygen deprivation, yet the mechanism underlying the brain’s sensitivity to hypoxia is incompletely understood. Hypoxia induces accumulation of hydrogen sulfide, a gas that inhibits mitochondrial respiration. Here, we show that, in mice, rats, and naturally hypoxia-tolerant ground squirrels, the sensitivity of the brain to hypoxia is inversely related to the levels of sulfide:quinone oxidoreductase (SQOR) and the capacity to catabolize sulfide. Silencing SQOR increased the sensitivity of the brain to hypoxia, whereas neuron-specific SQOR expression prevented hypoxia-induced sulfide accumulation, bioenergetic failure, and ischemic brain injury. Excluding SQOR from mitochondria increased sensitivity to hypoxia not only in the brain but also in heart and liver. Pharmacological scavenging of sulfide maintained mitochondrial respiration in hypoxic neurons and made mice resistant to hypoxia. These results illuminate the critical role of sulfide catabolism in energy homeostasis during hypoxia and identify a therapeutic target for ischemic brain injury

Diving Deep: Understanding the Genetic Components of Hypoxia Tolerance in Marine Mammals

Marine mammals have highly specialized physiology, exhibited in many species by extreme breath-holding capabilities that allow deep dives and extended submergence. Cardiovascular control and cell-level hypoxia tolerance are key features of this phenotype. Identifying genomic signatures tied to physiology will be valuable in understanding these natural model species, which may generate translational opportunities to human diseases arising from hypoxic stress or tissue injury. Genomic analyses have now been conducted in dolphins, river dolphins, minke whales, bowhead whales, and polar bears, with multispecies studies exploring evolutionary signals across marine mammal lineages, encompassing extinct and extant divers. Single-species genome studies for sirenians do not yet exist. Extant marine mammals arose in three lineages from separate aquatic recolonizations. Their physiological specializations, along with these independent origins create an interesting case to examine convergent evolution. Although molecular mechanisms of hypoxia tolerance are not universally apparent across marine mammal genomic studies, altered evolutionary rates have been identified for genes linked to oxygen binding and transport (e.g., MB, HBA, and HBB), blood pressure control (e.g., endothelin pathway genes), and cell protection in multiple species. Despite convergent phenotypes across clades, instances of identical molecular convergence have been uncommon. Given the inherent logistical and regulatory difficulties associated with functional genetic experiments in marine mammals, several avenues of further investigation are suggested to enable validation of candidate genes for hypoxia tolerance: leveraging phylogeny to better understand convergent phenotypes; ontogenic studies to identify regulation of key genes underlying the elite, adult, hypoxia-tolerant physiology; and cell culture manipulations to understand gene function

Cytoskeletal Regulation Dominates Temperature-Sensitive Proteomic Changes of Hibernation in Forebrain of 13-Lined Ground Squirrels

<div><p>13-lined ground squirrels, <i>Ictidomys tridecemlineatus</i>, are obligate hibernators that transition annually between summer homeothermy and winter heterothermy – wherein they exploit episodic torpor bouts. Despite cerebral ischemia during torpor and rapid reperfusion during arousal, hibernator brains resist damage and the animals emerge neurologically intact each spring. We hypothesized that protein changes in the brain underlie winter neuroprotection. To identify candidate proteins, we applied a sensitive 2D gel electrophoresis method to quantify protein differences among forebrain extracts prepared from ground squirrels in two summer, four winter and fall transition states. Proteins that differed among groups were identified using LC-MS/MS. Only 84 protein spots varied significantly among the defined states of hibernation. Protein changes in the forebrain proteome fell largely into two reciprocal patterns with a strong body temperature dependence. The importance of body temperature was tested in animals from the fall; these fall animals use torpor sporadically with body temperatures mirroring ambient temperatures between 4 and 21°C as they navigate the transition between summer homeothermy and winter heterothermy. Unlike cold-torpid fall ground squirrels, warm-torpid individuals strongly resembled the homeotherms, indicating that the changes observed in torpid hibernators are defined by body temperature, not torpor per se. Metabolic enzymes were largely unchanged despite varied metabolic activity across annual and torpor-arousal cycles. Instead, the majority of the observed changes were cytoskeletal proteins and their regulators. While cytoskeletal structural proteins tended to differ seasonally, i.e., between summer homeothermy and winter heterothermy, their regulatory proteins were more strongly affected by body temperature. Changes in the abundance of various isoforms of the microtubule assembly and disassembly regulatory proteins dihydropyrimidinase-related protein and stathmin suggested mechanisms for rapid cytoskeletal reorganization on return to euthermy during torpor-arousal cycles.</p></div

Significant pathway enrichments in squirrel forebrain for two primary hierarchical clusters.

<p>Note. Hierarchical Cluster 1, with seven significantly enriched functional annotation clusters, contains proteins decreased in cold T_b, whereas hierarchical Cluster 2, with two significant functional annotation clusters, contains proteins increased at cold T_b, and decreased during euthermy (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071627#pone-0071627-g002" target="_blank">Fig. 2</a>). Enrichment score gives the mean <i>p</i>-value among members of each annotation cluster (negative log). Enrichment data were calculated by DAVID Bioinformatics Resources v6.7 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071627#pone.0071627-Huang1" target="_blank">[25]</a>.</p

Sampled state separation by Random Forests. Data were clustered by Random Forests (50,000 trees) after variable selection to determine the minimum input protein spots required for the lowest classification error among groups. This was accomplished with (A) 22 protein spots for the base states and (B) 11 for winter states only (see Fig. 5).

<p>Sampled state separation by Random Forests. Data were clustered by Random Forests (50,000 trees) after variable selection to determine the minimum input protein spots required for the lowest classification error among groups. This was accomplished with (A) 22 protein spots for the base states and (B) 11 for winter states only (see Fig. 5).</p

Posttranslational modification of a microtubule regulating protein. (A) Boxplots of the relative abundance of six DPYSL2 isoforms reveal two reciprocal abundance patterns; animal groups are as in Figure 1. (B) Representative images from an EAr 2D gel stained for total protein (top panel) or phosphoprotein (bottom panel); note the transition between the two patterns in panel A occurs at an isoelectric point consistent with a shift between the phosphorylated and unphosphorylated form of the protein. (C) Relative degree of isoform phosphorylation quantified from EAr and IBA phosphoprotein-stained gels increases as spots migrate further left on 2D gels (i.e., become more acidic), and supports categorizing the two abundance patterns by phosphorylation state. (D) Representative 2D western blots from LT and IBA show that the unphosphorylated forms are most abundant in euthermic states such as IBA, while phosphorylated forms are largely absent. (E) A 1D western blot (α-DPYSL2) shows no signifi

<p>Posttranslational modification of a microtubule regulating protein. (A) Boxplots of the relative abundance of six DPYSL2 isoforms reveal two reciprocal abundance patterns; animal groups are as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0071627#pone-0071627-g001" target="_blank">Figure 1</a>. (B) Representative images from an EAr 2D gel stained for total protein (top panel) or phosphoprotein (bottom panel); note the transition between the two patterns in panel A occurs at an isoelectric point consistent with a shift between the phosphorylated and unphosphorylated form of the protein. (C) Relative degree of isoform phosphorylation quantified from EAr and IBA phosphoprotein-stained gels increases as spots migrate further left on 2D gels (i.e., become more acidic), and supports categorizing the two abundance patterns by phosphorylation state. (D) Representative 2D western blots from LT and IBA show that the unphosphorylated forms are most abundant in euthermic states such as IBA, while phosphorylated forms are largely absent. (E) A 1D western blot (α-DPYSL2) shows no significant change in total DPYSL2 content among forebrain of LT, IBA or SA 13-lined ground squirrels (SA data not shown). In panels A–D the dotted blue line separates the phosphorylated and unphosphorylated forms of DPYSL2; in panels D–E, DPYSL2 antibody labeling is denoted as α-DPYSL2.</p

The fall proteome tracks body temperature.

<p>Fall transition individuals were held in warm (T_a = 18–20°C, #41–46) or cold rooms (T_a = 4°C, #47–52). (A) Unsupervised classification of all states using the most important predictors determined in Fig. 3A maintains the segregation of states by T_b. The mixed physiology of Fall animals can test the effect of T_b. (B) Unsupervised classification quantified proximity of FT individuals based on the defined groups as training data. In all but three individuals, more than 50% of the FT proteome was similar to summer or spring euthermic ground squirrels (x-axis: animal ID). The three exceptions were cold torpid (* denotes torpid), and instead had proteomes more proximate to LT/EAr. The absence of a similar pattern in the two warm-housed but torpid individuals (T_b = 18–21°C), supports the hypothesis that the LT/EAr proteome is defined by T_b, and not torpor per se. (C) Proximity to the euthermic groups (SA+SpC+IBA) correlates significantly with T_b.</p

Forebrain proteome heat map.

<p>The forebrain proteome of cold-T_b ground squirrels demonstrated a reciprocal abundance pattern to euthermic animals. (A) Heat map y-axis: Individual ground squirrels grouped by state. Heat map x-axis (bottom): Protein spots (Spot Number.GeneID) that differed significantly by hibernation state (ANOVA q) and identified by LC-MS/MS were hierarchically clustered (X-axis (top): dendrogram). Blank squares in the heat map represent samples in which a given protein spot was not recovered. (B & C) Means with 95% confidence intervals are plotted for the two reciprocal clusters.</p