MitoPhen database: a human phenotype ontology-based approach to identify mitochondrial DNA diseases

Diagnosing mitochondrial disorders remains challenging. This is partly because the clinical phenotypes of patients overlap with those of other sporadic and inherited disorders. Although the widespread availability of genetic testing has increased the rate of diagnosis, the combination of phenotypic and genetic heterogeneity still makes it difficult to reach a timely molecular diagnosis with confidence. An objective, systematic method for describing the phenotypic spectra for each variant provides a potential solution to this problem. We curated the clinical phenotypes of 6688 published individuals with 89 pathogenic mitochondrial DNA (mtDNA) mutations, collating 26 348 human phenotype ontology (HPO) terms to establish the MitoPhen database. This enabled a hypothesis-free definition of mtDNA clinical syndromes, an overview of heteroplasmy-phenotype relationships, the identification of under-recognized phenotypes, and provides a publicly available reference dataset for objective clinical comparison with new patients using the HPO. Studying 77 patients with independently confirmed positive mtDNA diagnoses and 1083 confirmed rare disease cases with a non-mitochondrial nuclear genetic diagnosis, we show that HPO-based phenotype similarity scores can distinguish these two classes of rare disease patients with a false discovery rate <10% at a sensitivity of 80%. Enriching the MitoPhen database with more patients will improve predictions for increasingly rare variants.     

Thermodynamic characterization of binding Oxytricha nova single strand telomere DNA with the alpha protein N-terminal domain

The Oxytricha nova telemere binding protein alpha subunit binds single strand DNA and participates in a nucleoprotein complex that protects the very ends of chromosomes. To understand how the N-terminal, DNA binding domain of alpha interacts with DNA we measured the stoichiometry, enthalpy (DeltaH), entropy (DeltaS), and dissociation constant (K(D-DNA)) for binding telomere DNA fragments at different temperatures and salt concentrations using native gel electrophoresis and isothermal titration calorimetry (ITC). About 85% of the total free energy of binding corresponded with non-electrostatic interactions for all DNAs. Telomere DNA fragments d(T(2)G(4)), d(T(4)G(4)), d(G(3)T(4)G(4)), and d(G(4)T(4)G(4)) each formed monovalent protein complexes. In the case of d(T(4)G(4)T(4)G(4)), which has two tandemly repeated d(TTTTTGGGG) telomere motifs, two binding sites were observed. The high-affinity "A site" has a dissociation constant, K(D-DNA(A)) = 13(+/-4) nM, while the low-affinity "B site" is characterized by K(D-DNA(B)) = 5600(+/-600) nM at 25 degrees C. Nucleotide substitution variants verified that the A site corresponds principally with the 3'-terminal portion of d(T(4)G(4)T(4)G(4)). The relative contributions of entropy (DeltaS) and enthalpy (DeltaH) for binding reactions were DNA length-dependent as was heat capacity (DeltaCp). These trends with respect to DNA length likely reflect structural transitions in the DNA molecule that are coupled with DNA-protein association. Results presented here are important for understanding early intermediates and subsequent stages in the assembly of the full telomere nucleoprotein complex and how binding events can prepare the telomere DNA for extension by telomerase, a critical event in telomere biology.     

External air pollution costs of telework

Background, Aims and Scope  Telework is associated with a number of costs and benefits, including reduced company overhead costs, need for office and parking space, office energy consumption, increased productivity, reduced absenteeism, retention of specialized employees, reduction in transportation-related fuel consumption and air pollution, and many others. This paper applies a systems model to telework and nontelework scenarios to quantify direct energy and fuel costs and external costs related to air emissions from transportation, heating, cooling, lighting, and electronic and electrical equipment use both at the company and the home office, including rebound effects. Methods  E-COMMUTair, a scalable web-based tool created by the authors and designed to assess the air pollution effects of individual or company telework programs versus nontelework is employed along with Monte Carlo simulation and sensitivity analysis. E-COMMUTair is using the latest available U.S. energy use and air emission factors. The external costs of air emissions are estimated. The role of telecommuting frequency is emphasized, and differences between various states are explored. The paper identifies the drivers of external costs, and presents an example breakeven analysis focused on CO₂ and key model parameters. Results and Discussion  Nontelework’s external costs are equal to or higher than telework’s costs for every model component, demonstrating that telework programs could provide benefits, including monetary benefits, to society. Transportation is the major contributor to the total costs, with home heating and cooling, and office cooling following. Most of the monetary costs associated with transportation are borne by individuals rather than society. Teleworking employees increase their home-related expenses but reduce their travel-related expenses, ending up with smaller total costs. Energy and fuel costs get reduced in the office space when telework programs are applied, resulting in benefits to companies. Energy and external costs decrease as telework frequency increases. When compared to not teleworking, 5-day telework scenarios on cooling days in California can have about 50–70% lower total costs. The probabilistic analysis confirms the results of the deterministic analysis. The sensitivity analysis reveals that for the nontelework scenario, transportation-related variables such as commuting distance and average number of passengers affect CO₂, CO, and NO_x emissions, while for the telework part, frequency and the number of roundtrips are the most relevant. Conclusions  Both analyses show that telework programs have the potential to lower both energy and external costs creating a favorable bottom line for society, employees, and companies by decreasing tailpipe emissions, lowering transportation costs, and decreasing energy costs at the company office. However, important parameters such as telecommuting frequency, characteristics of the office and home space, climate patterns, and rebound effects that determine external costs along with the price of gasoline, electricity and natural gas in the state where the program is implemented can greatly influence the final results, and should be carefully examined. Recommendations and Perspectives  The effects of telework programs on people’s daily lives are complex and difficult to predict and quantify. The current analysis showed that significant financial benefits can be expected from telework programs, but as seen often in environmental policy-making, the details of implementation will make or break the success of a program. formerly Postdoctoral Researcher, University of California, Berkeley ESS-Submission Editor: Dr. Gerald Rebitzer (Gerald.Rebitzer@alcan.com)     

WGCNA: an R package for weighted correlation network analysis

Background

Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints.

Results

A supervised multivariate modelling approach with the objective to model the time-related variation in the data for short and sparsely sampled time-series is described. A set of piecewise Orthogonal Projections to Latent Structures (OPLS) models are estimated, describing changes between successive time points. The individual OPLS models are linear, but the piecewise combination of several models accommodates modelling and prediction of changes which are non-linear with respect to the time course. We demonstrate the method on both simulated and metabolic profiling data, illustrating how time related changes are successfully modelled and predicted.

Conclusion

The proposed method is effective for modelling and prediction of short and multivariate time series data. A key advantage of the method is model transparency, allowing easy interpretation of time-related variation in the data. The method provides a competitive complement to commonly applied multivariate methods such as OPLS and Principal Component Analysis (PCA) for modelling and analysis of short time-series data.     

Hemolysis and hyperhomocysteinemia caused by cobalamin deficiency: three case reports and review of the literature

Background

Molecular characterisation of normal karyotype acute myeloid leukemia (NK-AML) allows prognostic stratification and potentially can alter treatment choices and pathways. Approximately 45–60% of patients with NK-AML carry NPM1 gene mutations and are associated with a favourable clinical outcome when FLT3-internal tandem duplications (ITD) are absent. High resolution melting (HRM) is a novel screening method that enables rapid identification of mutation positive DNA samples.

Results

We developed HRM assays to detect NPM1 mutations and FLT3-ITD and tested diagnostic samples from 44 NK-AML patients. Eight were NPM1 mutation positive only, 4 were both NPM1 mutation and FLT3-ITD positive and 4 were FLT3-ITD positive only. A novel point mutation Y572C (c.1715A>G) in exon 14 of FLT3 was also detected. In the group with de novo NK-AML, 40% (12/29) were NPM1 mutation positive whereas NPM1 mutations were observed in 20% (3/15) of secondary NK-AML cases. Sequencing was performed and demonstrated 100% concordance with the HRM results.

Conclusion

HRM is a rapid and efficient method of screening NK-AML samples for both novel and known NPM1 and FLT3 mutations. NPM1 mutations can be observed in both primary and secondary NK-AML cases.     

Macromolecular crowding modulates α-synuclein amyloid fiber growth

The crowdedness of living cells, hundreds of milligrams per milliliter of macromolecules, may affect protein folding, function, and misfolding. Still, such processes are most often studied in dilute solutions in vitro. To assess consequences of the in vivo milieu, we here investigated the effects of macromolecular crowding on the amyloid fiber formation reaction of α-synuclein, the amyloidogenic protein in Parkinson’s disease. For this, we performed spectroscopic experiments probing individual steps of the reaction as a function of the macromolecular crowding agent Ficoll70, which is an inert sucrose-based polymer that provides excluded-volume effects. The experiments were performed at neutral pH at quiescent conditions to avoid artifacts due to shaking and glass beads (typical conditions for α-synuclein), using amyloid fiber seeds to initiate reactions. We find that both primary nucleation and fiber elongation steps during α-synuclein amyloid formation are accelerated by the presence of 140 and 280 mg/mL Ficoll70. Moreover, in the presence of Ficoll70 at neutral pH, secondary nucleation appears favored, resulting in faster overall α-synuclein amyloid formation. In contrast, sucrose, a small-molecule osmolyte and building block of Ficoll70, slowed down α-synuclein amyloid formation. The ability of cell environments to modulate reaction kinetics to a large extent, such as severalfold faster individual steps in α-synuclein amyloid formation, is an important consideration for biochemical reactions in living systems.