Living on the edge: substrate competition explains loss of robustness in mitochondrial fatty-acid oxidation disorders

Background

Defects in genes involved in mitochondrial fatty-acid oxidation (mFAO) reduce the ability of patients to cope with metabolic challenges. mFAO enzymes accept multiple substrates of different chain length, leading to molecular competition among the substrates. Here, we combined computational modeling with quantitative mouse and patient data to investigate whether substrate competition affects pathway robustness in mFAO disorders.

Results

First, we used comprehensive biochemical analyses of wild-type mice and mice deficient for medium-chain acyl-CoA dehydrogenase (MCAD) to parameterize a detailed computational model of mFAO. Model simulations predicted that MCAD deficiency would have no effect on the pathway flux at low concentrations of the mFAO substrate palmitoyl-CoA. However, high concentrations of palmitoyl-CoA would induce a decline in flux and an accumulation of intermediate metabolites. We proved computationally that the predicted overload behavior was due to substrate competition in the pathway. Second, to study the clinical relevance of this mechanism, we used patients’ metabolite profiles and generated a humanized version of the computational model. While molecular competition did not affect the plasma metabolite profiles during MCAD deficiency, it was a key factor in explaining the characteristic acylcarnitine profiles of multiple acyl-CoA dehydrogenase deficient patients. The patient-specific computational models allowed us to predict the severity of the disease phenotype, providing a proof of principle for the systems medicine approach.

Conclusion

We conclude that substrate competition is at the basis of the physiology seen in patients with mFAO disorders, a finding that may explain why these patients run a risk of a life-threatening metabolic catastrophe.

     

Rigorous Training of Dogs Leads to High Accuracy in Human Scent Matching-To-Sample Performance

Human scent identification is based on a matching-to-sample task in which trained dogs are required to compare a scent sample collected from an object found at a crime scene to that of a suspect. Based on dogs’ greater olfactory ability to detect and process odours, this method has been used in forensic investigations to identify the odour of a suspect at a crime scene. The excellent reliability and reproducibility of the method largely depend on rigor in dog training. The present study describes the various steps of training that lead to high sensitivity scores, with dogs matching samples with 90% efficiency when the complexity of the scents presented during the task in the sample is similar to that presented in the in lineups, and specificity reaching a ceiling, with no false alarms in human scent matching-to-sample tasks. This high level of accuracy ensures reliable results in judicial human scent identification tests. Also, our data should convince law enforcement authorities to use these results as official forensic evidence when dogs are trained appropriately.     

Binuclear rhenium carbonyl nitrosyls related to dicobalt octacarbonyl and their decarbonylation products

The geometries and thermochemistry of Re₂(NO)₄(CO) _n (n?=?4, 3, 2, 1, 0) structures isovalent with the binuclear cobalt carbonyls Co₂(CO) _n+4 have been examined using density functional theory. Eight low-energy Re₂(NO)₄(CO)₄ structures, all with formal Re–Re single bonds, lie within 6 kcal mol^?1 of the global minimum. These eight structures include unbridged structures as well as structures with two bridging NO groups but no structures with bridging CO groups. Similarly, five low-energy Re₂(NO)₄(CO)₃ structures, all with formal Re=Re double bonds, lie within 6 kcal mol^?1 of the global minimum. Again these five structures include unbridged structures as well as structures with one or two bridging NO groups but no structures with bridging CO groups. The Re₂(NO)₄(CO) _n (n?=?4, 3) appear to be fluxional systems similar to the well-known Co₂(CO)₈ for which doubly bridged and unbridged structures have approximately the same energies. The lowest energy Re₂(NO)₄(CO)₂ structures have formal Re=Re double bonds including a structure with a five-electron donor bridging η²-μ-NO group. Isomeric Re₂(NO)₄(CO)₂ structures with formal Re≡Re triple bonds lie approximately ～10 kcal mol^?1 above the global minimum. For the more highly unsaturated Re₂(NO)₄(CO) and Re₂(NO)₄ systems, the lowest energy structures have formal Re≡Re triple bonds of length ～2.6 Å. Higher energy Re₂(NO)₄(CO) structures have shorter Re–Re distances of length ～2.5 Å suggesting formal quadruple bonds.

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Graphical Abstract The geometries and thermochemistry of Re₂(NO)₄(CO) _n (n?=?4, 3, 2, 1, 0) structures isovalent with the binuclear cobalt carbonyls Co₂(CO) _n+4 have been examined using density functional theory. A number of energetically closely spaced Re₂(NO)₄(CO)₄ and Re₂(NO)₄(CO)₃ structures are found, including unbridged and NO-bridged structures but no CO-bridged structures. The Re₂(NO)₄(CO) _n (n?=?2, 1, 0) systems provide examples of Re–Re multiple bonds of orders ranging from 2 to 4.

     

Estimating Neospora caninum prevalence in wildlife populations using Bayesian inference

Prevalence of disease in wildlife populations, which is necessary for developing disease models and conducting epidemiologic analyses, is often understudied. Laboratory tests used to screen for diseases in wildlife populations often are validated only for domestic animals. Consequently, the use of these tests for wildlife populations may lead to inaccurate estimates of disease prevalence. We demonstrate the use of Bayesian latent class analysis (LCA) in determining the specificity and sensitivity of a competitive enzyme‐linked immunosorbent assay (cELISA; VMRD^®, Inc.) serologic test used to identify exposure to Neospora caninum (hereafter N. caninum) in three wildlife populations in southeastern Ohio, USA. True prevalence of N. caninum exposure in these populations was estimated to range from 0.1% to 3.1% in American bison (Bison bison), 51.0% to 53.8% in Père David's deer (Elaphurus davidianus), and 40.0% to 45.9% in white‐tailed deer (Odocoileus virginianus). The accuracy of the cELISA in American bison and Père David's deer was estimated to be close to the 96% sensitivity and 99% specificity reported by the manufacturer. Sensitivity in white‐tailed deer, however, ranged from 78.9% to 99.9%. Apparent prevalence of N. caninum from the test results is not equal to the true prevalence in white‐tailed deer and Père David's deer populations. Even when these species inhabit the same community, the true prevalence in the two deer populations differed from the true prevalence in the American bison population. Variances in prevalence for some species suggest differences in the epidemiology of N. caninum for these colocated populations. Bayesian LCA methods could be used as in this example to overcome some of the constraints on validating tests in wildlife species. The ability to accurately evaluate disease status and prevalence in a population improves our understanding of the epidemiology of multihost pathogen systems at the community level.