Noninvasive Immunometabolic Cardiac Inflammation Imaging Using Hyperpolarized Magnetic Resonance.

RATIONALE: Current cardiovascular clinical imaging techniques offer only limited assessment of innate immune cell-driven inflammation, which is a potential therapeutic target in myocardial infarction (MI) and other diseases. Hyperpolarized magnetic resonance (MR) is an emerging imaging technology that generates contrast agents with 10- to 20 000-fold improvements in MR signal, enabling cardiac metabolite mapping. OBJECTIVE: To determine whether hyperpolarized MR using [1-13C]pyruvate can assess the local cardiac inflammatory response after MI. METHODS AND RESULTS: We performed hyperpolarized [1-13C]pyruvate MR studies in small and large animal models of MI and in macrophage-like cell lines and measured the resulting [1-13C]lactate signals. MI caused intense [1-13C]lactate signal in healing myocardial segments at both day 3 and 7 after rodent MI, which was normalized at both time points after monocyte/macrophage depletion. A near-identical [1-13C]lactate signature was also seen at day 7 after experimental MI in pigs. Hyperpolarized [1-13C]pyruvate MR spectroscopy in macrophage-like cell suspensions demonstrated that macrophage activation and polarization with lipopolysaccharide almost doubled hyperpolarized lactate label flux rates in vitro; blockade of glycolysis with 2-deoxyglucose in activated cells normalized lactate label flux rates and markedly inhibited the production of key proinflammatory cytokines. Systemic administration of 2-deoxyglucose after rodent MI normalized the hyperpolarized [1-13C]lactate signal in healing myocardial segments at day 3 and also caused dose-dependent improvement in IL (interleukin)-1ß expression in infarct tissue without impairing the production of key reparative cytokines. Cine MRI demonstrated improvements in systolic function in 2-DG (2-deoxyglucose)-treated rats at 3 months. CONCLUSIONS: Hyperpolarized MR using [1-13C]pyruvate provides a novel method for the assessment of innate immune cell-driven inflammation in the heart after MI, with broad potential applicability across other cardiovascular disease states and suitability for early clinical translation.

The von Hippel-Lindau Chuvash mutation in mice alters cardiac substrate and high-energy phosphate metabolism.

Hypoxia-inducible factor (HIF) appears to function as a global master regulator of cellular and systemic responses to hypoxia. HIF pathway manipulation is of therapeutic interest; however, global systemic upregulation of HIF may have as yet unknown effects on multiple processes. We used a mouse model of Chuvash polycythemia (CP), a rare genetic disorder that modestly increases expression of HIF target genes in normoxia, to understand what these effects might be within the heart. An integrated in and ex vivo approach was employed. Compared with wild-type controls, CP mice had evidence (using in vivo magnetic resonance imaging) of pulmonary hypertension, right ventricular hypertrophy, and increased left ventricular ejection fraction. Glycolytic flux (measured using [(3)H]glucose) in the isolated contracting perfused CP heart was 1.8-fold higher. Net lactate efflux was 1.5-fold higher. Furthermore, in vivo (13)C-magnetic resonance spectroscopy (MRS) of hyperpolarized [(13)C1]pyruvate revealed a twofold increase in real-time flux through lactate dehydrogenase in the CP hearts and a 1.6-fold increase through pyruvate dehydrogenase. (31)P-MRS of perfused CP hearts under increased workload (isoproterenol infusion) demonstrated increased depletion of phosphocreatine relative to ATP. Intriguingly, no changes in cardiac gene expression were detected. In summary, a modest systemic dysregulation of the HIF pathway resulted in clear alterations in cardiac metabolism and energetics. However, in contrast to studies generating high HIF levels within the heart, the CP mice showed neither the predicted changes in gene expression nor any degree of LV impairment. We conclude that the effects of manipulating HIF on the heart are dose dependent.

A new multiplex qPCR assay to detect and differentiate big cat species in the illegal wildlife trade.

All species of big cats, including tigers, cheetahs, leopards, lions, snow leopards, and jaguars, are protected under the Convention on the International Trade in Endangered Species (CITES). This is due in large part to population declines resulting from anthropogenic factors, especially poaching and the unregulated and illegal trade in pelts, bones, teeth and other products that are derived from these iconic species. To enhance and scale up monitoring for big cat products in this trade, we created a rapid multiplex qPCR test that can identify and differentiate DNA from tiger (Panthera tigris), cheetah (Acinonyx jubatus), leopard (Panthera pardus), lion (Panthera leo), snow leopard (Panthera uncia), and jaguar (Panthera onca) in wildlife products using melt curve analysis to identify each species by its unique melt peak temperature. Our results showed high PCR efficiency (> 90%), sensitivity (detection limit of 5 copies of DNA per PCR reaction) and specificity (no cross amplification between each of the 6 big cat species). When paired with a rapid (< 1 h) DNA extraction protocol that amplifies DNA from bone, teeth, and preserved skin, total test time is less than three hours. This test can be used as a screening method to improve our understanding of the scale and scope of the illegal trade in big cats and aid in the enforcement of international regulations that govern the trade in wildlife and wildlife products, both ultimately benefiting the conservation of these species worldwide.

Effects of coancestry on accuracy of individual assignments to population of origin: examples using Great Lakes lake trout (Salvelinus namaycush).

Methods for assigning individuals to population of origin are widely used in ecological genetics, resources management, and forensics. Characteristics of genetic data obtained from putative source populations that enhance accuracy of assignment are well established. How non-independence within and among unknown individuals to be classified [i.e., gene correlations within individual (inbreeding) and gene correlations among individuals within group (coancestry)] affect assignment accuracy is poorly understood. We used empirical data for six microsatellite loci and offspring from full-sib crosses of hatchery strains of lake trout (Salvelinus namaycush; Salmonidae) representing known levels of coancestry (mean theta = 0.006 and 0.06) within families to investigate how gene correlations can affect assignment. Additional simulations were conducted to further investigating the influence of allelic diversity (2, 6 or 10 alleles per locus) and inbreeding (F = 0.00, 0.05, and 0.15) on assignment accuracy for cases of low and high inter-population variance in allele frequency (mean F (st) = 0.01 and 0.1, respectively). Inbreeding had no effect on accuracy of assignments. In contrast, variance in assignment accuracy across replicated simulations, and for each empirical case study increased with increasing coancestry, reflecting non-independence of probabilities of correct assignment among members of kin groups. Empirical estimates of assignment error rates should be interpreted with caution if appreciable levels of coancestry are suspected. Additional emphasis should be placed on sampling designs (spatially and temporally) that define or minimize the potential for sampling related individuals.