Legionella pneumophila Secretes a Mitochondrial Carrier Protein during Infection

The Mitochondrial Carrier Family (MCF) is a signature group of integral membrane proteins that transport metabolites across the mitochondrial inner membrane in eukaryotes. MCF proteins are characterized by six transmembrane segments that assemble to form a highly-selective channel for metabolite transport. We discovered a novel MCF member, termed Legionella nucleotide carrier Protein (LncP), encoded in the genome of Legionella pneumophila, the causative agent of Legionnaire's disease. LncP was secreted via the bacterial Dot/Icm type IV secretion system into macrophages and assembled in the mitochondrial inner membrane. In a yeast cellular system, LncP induced a dominant-negative phenotype that was rescued by deleting an endogenous ATP carrier. Substrate transport studies on purified LncP reconstituted in liposomes revealed that it catalyzes unidirectional transport and exchange of ATP transport across membranes, thereby supporting a role for LncP as an ATP transporter. A hidden Markov model revealed further MCF proteins in the intracellular pathogens, Legionella longbeachae and Neorickettsia sennetsu, thereby challenging the notion that MCF proteins exist exclusively in eukaryotic organisms

An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers

Introduction: Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. Methods: We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. Results: We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. Conclusions: This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.Peer reviewe

Application of quadratically-constrained model predictive control in power systems

This is the author accepted manuscript. The final version is available from IEEE via http://dx.doi.org/10.1109/ICARCV.2014.7064303Simulations for the quadratically-constrained model\ud predictive control (qc-MPC) with power system linear models are\ud studied in this work. In qc-MPC, the optimization is imposed\ud with two additional constraints to achieve the closed-loop system\ud stability and the recursive-feasibility simultaneously. Instead of\ud engaging the traditional terminal constraint for MPC, both\ud constraints in qc-MPC are imposed on the first control vector\ud of the MPC control sequence. As a result, qc-MPC has the\ud potential for further extension to the control of network centric\ud power systems. The algorithm of qc-MPC has been developed\ud in a previous paper. Here, simulation studies with small-signal\ud linear models of three typical power systems are presented\ud to demonstrate its efficacy. We also develop a computational\ud strategy for the decentralized static state-feedback control using\ud the same quadratic dissipativity constraint as of the qc-MPC.\ud Only state constraints are considered in the state feedback design.\ud A comparison is then provided in the simulation study of qc-MPC\ud relatively to the constrained-state feedback control.This publication is made possible by the Singapore National Research\ud Foundation under its Campus for Research Excellence And Technological\ud Enterprise (CREATE) programm

Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

This paper proposes an efficient energy management system (EMS) for industrial microgrids (MGs). Many industries deploy large pumps for their processes. Oftentimes, such pumps are operated during hours of peak electricity prices. A lot of industries use a mix of captive generation and imported utility electricity to meet their energy requirements. The MG considered in this paper includes diesel generators, battery energy storage systems, renewable energy sources, flexible loads, and interruptible loads. Pump loads found in shipyard dry docks are modelled as exemplar flexible industrial loads. The proposed EMS has a two-stage architecture. An optimal MG scheduling problem including pump scheduling and curtailment of interruptible loads (ILs) is formulated and solved in the first stage. An optimal power flow problem is solved in the second stage to verify the feasibility of the MG schedule with the network constraints. An iterative procedure is used to coordinate the two EMS stages. Multiple case studies are used to demonstrate the utility of the proposed EMS. The case studies highlight the efficacy of load management strategies such as pump scheduling and curtailment of ILs in reducing the total electricity cost of the MG