Mitofusin 2 regulates STIM1 migration from the Ca2+ store to the plasma membrane in cells with depolarized mitochondria

Store-operated Ca2+ channels in the plasma membrane (PM) are activated by the depletion of Ca2+ from the endoplasmic reticulum (ER) and constitute a widespread and highly conserved Ca2+ influx pathway. After store emptying, the ER Ca2+ sensor STIM1 forms multimers, which then migrate to ER-PM junctions where they activate the Ca2+ release-activated Ca2+ channel Orai1. Movement of an intracellular protein to such specialized sites where it gates an ion channel is without precedence, but the fundamental question of how STIM1 migrates remains unresolved. Here, we show that trafficking of STIM1 to ER-PM junctions and subsequent Ca2+ release-activated Ca2+ channel activity is impaired following mitochondrial depolarization. We identify the dynamin-related mitochondrial protein mitofusin 2, mutations of which causes the inherited neurodegenerative disease Charcot-Marie-Tooth IIa in humans, as an important component of this mechanism. Our results reveal a molecular mechanism whereby a mitochondrial fusion protein regulates protein trafficking across the endoplasmic reticulum and reveals a homeostatic mechanism whereby mitochondrial depolarization can inhibit store-operated Ca2+ entry, thereby reducing cellular Ca2+ overload.     

Genome-wide association and genomic prediction for host response to porcine reproductive and respiratory syndrome virus infection

Background

Host genetics has been shown to play a role in porcine reproductive and respiratory syndrome (PRRS), which is the most economically important disease in the swine industry. A region on Sus scrofa chromosome (SSC) 4 has been previously reported to have a strong association with serum viremia and weight gain in pigs experimentally infected with the PRRS virus (PRRSV). The objective here was to identify haplotypes associated with the favorable phenotype, investigate additional genomic regions associated with host response to PRRSV, and to determine the predictive ability of genomic estimated breeding values (GEBV) based on the SSC4 region and based on the rest of the genome. Phenotypic data and 60 K SNP genotypes from eight trials of ~200 pigs from different commercial crosses were used to address these objectives.

Results

Across the eight trials, heritability estimates were 0.44 and 0.29 for viral load (VL, area under the curve of log-transformed serum viremia from 0 to 21 days post infection) and weight gain to 42 days post infection (WG), respectively. Genomic regions associated with VL were identified on chromosomes 4, X, and 1. Genomic regions associated with WG were identified on chromosomes 4, 5, and 7. Apart from the SSC4 region, the regions associated with these two traits each explained less than 3% of the genetic variance. Due to the strong linkage disequilibrium in the SSC4 region, only 19 unique haplotypes were identified across all populations, of which four were associated with the favorable phenotype. Through cross-validation, accuracies of EBV based on the SSC4 region were high (0.55), while the rest of the genome had little predictive ability across populations (0.09).

Conclusions

Traits associated with response to PRRSV infection in growing pigs are largely controlled by genomic regions with relatively small effects, with the exception of SSC4. Accuracies of EBV based on the SSC4 region were high compared to the rest of the genome. These results show that selection for the SSC4 region could potentially reduce the effects of PRRS in growing pigs, ultimately reducing the economic impact of this disease.     

Trainable High Resolution Melt Curve Machine Learning Classifier for Large-Scale Reliable Genotyping of Sequence Variants

High resolution melt (HRM) is gaining considerable popularity as a simple and robust method for genotyping sequence variants. However, accurate genotyping of an unknown sample for which a large number of possible variants may exist will require an automated HRM curve identification method capable of comparing unknowns against a large cohort of known sequence variants. Herein, we describe a new method for automated HRM curve classification based on machine learning methods and learned tolerance for reaction condition deviations. We tested this method in silico through multiple cross-validations using curves generated from 9 different simulated experimental conditions to classify 92 known serotypes of Streptococcus pneumoniae and demonstrated over 99% accuracy with 8 training curves per serotype. In vitro verification of the algorithm was tested using sequence variants of a cancer-related gene and demonstrated 100% accuracy with 3 training curves per sequence variant. The machine learning algorithm enabled reliable, scalable, and automated HRM genotyping analysis with broad potential clinical and epidemiological applications.     

Inhibitory Effects of Salinomycin on Cell Survival,Colony Growth,Migration, and Invasion of Human Non-Small Cell Lung Cancer A549 and LNM35: Involvement of NAG-1

A major challenge for oncologists and pharmacologists is to develop more potent and less toxic drugs that will decrease the tumor growth and improve the survival of lung cancer patients. Salinomycin is a polyether antibiotic used to kill gram-positive bacteria including mycobacteria, protozoans such as plasmodium falciparum, and the parasites responsible for the poultry disease coccidiosis. This old agent is now a serious anti-cancer drug candidate that selectively inhibits the growth of cancer stem cells. We investigated the impact of salinomycin on survival, colony growth, migration and invasion of the differentiated human non-small cell lung cancer lines LNM35 and A549. Salinomycin caused concentration- and time-dependent reduction in viability of LNM35 and A549 cells through a caspase 3/7-associated cell death pathway. Similarly, salinomycin (2.5–5 µM for 7 days) significantly decreased the growth of LNM35 and A549 colonies in soft agar. Metastasis is the main cause of death related to lung cancer. In this context, salinomycin induced a time- and concentration-dependent inhibition of cell migration and invasion. We also demonstrated for the first time that salinomycin induced a marked increase in the expression of the pro-apoptotic protein NAG-1 leading to the inhibition of lung cancer cell invasion but not cell survival. These findings identify salinomycin as a promising novel therapeutic agent for lung cancer.     

Utilization of acrylonitrile by bacteria isolated from petrochemical waste waters

A bacterium, utilising acrylonitrile as a sole source of carbon and nitrogen, was isolated from Indian Petrochemical Corporation Limited (IPCL) waste waters and identified as Arthrobacter sp. This strain could also utilize acetonitrile, acetamide and acrylamide individually as a source of carbon and nitrogen. The metabolic studies with the whole cells indicated the sequential conversion of the nitrile to the respective amide and then to the respective acid and ammonia. The rate of nitrile hydrolysis was slower than the corresponding amide hydrolysis. Acrylic acid, the end product of acrylonitrile breakdown, did not support the growth when provided as a carbon source.     

Ethanol and sugar tolerance of Candida shehatae

Summary Candida shehatae ATCC 22984 fermented solutions of up to 260 g/L sugars derived by hydrolysis of whole barley. These solutions contained hexose: pentose 7030, the hexose being mainly glucose from the barley starch and the pentose being mainly xylose. At sugar concentrations of 180 g/L, fermentation was complete in 72 h, yielding 84 g/L ethanol, 0.47 g ethanol/g sugar. At 260 g/L, fermentation ceased when ethanol concentration reached 100 g/L, but resumed when the ethanol was removed by vacuum distillation, to yield finally 0.50 g ethanol/g sugar.