FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis

Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci) to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ

Targeted apoptosis in ovarian cancer cells through mitochondrial dysfunction in response to Sambucus nigra agglutinin

Ovarian carcinoma (OC) patients encounter the severe challenge of clinical management owing to lack of screening measures, chemoresistance and finally dearth of non-toxic therapeutics. Cancer cells deploy various defense strategies to sustain the tumor microenvironment, among which deregulated apoptosis remains a versatile promoter of cancer progression. Although recent research has focused on identifying agents capable of inducing apoptosis in cancer cells, yet molecules efficiently breaching their survival advantage are yet to be classified. Here we identify lectin, Sambucus nigra agglutinin (SNA) to exhibit selectivity towards identifying OC by virtue of its specific recognition of α-2, 6-linked sialic acids. Superficial binding of SNA to the OC cells confirm the hyper-sialylated status of the disease. Further, SNA activates the signaling pathways of AKT and ERK1/2, which eventually promotes de-phosphorylation of dynamin-related protein-1 (Drp-1). Upon its translocation to the mitochondrial fission loci Drp-1 mediates the central role of switch in the mitochondrial phenotype to attain fragmented morphology. We confirmed mitochondrial outer membrane permeabilization resulting in ROS generation and cytochrome-c release into the cytosol. SNA response resulted in an allied shift of the bioenergetics profile from Warburg phenotype to elevated mitochondrial oxidative phosphorylation, altogether highlighting the involvement of mitochondrial dysfunction in restraining cancer progression. Inability to replenish the SNA-induced energy crunch of the proliferating cancer cells on the event of perturbed respiratory outcome resulted in cell cycle arrest before G2/M phase. Our findings position SNA at a crucial juncture where it proves to be a promising candidate for impeding progression of OC. Altogether we unveil the novel aspect of identifying natural molecules harboring the inherent capability of targeting mitochondrial structural dynamics, to hold the future for developing non-toxic therapeutics for treating OC

Molecular mechanisms of atlastin-mediated ER membrane fusion revealed by a FRET-based single-vesicle fusion assay

Homotypic fusion of endoplasmic reticulum membranes is driven by atlastin GTPases; however, the underlying mechanism remains largely unknown. Here, using a FRET-based single-vesicle fusion assay with liposomes bearing the yeast atlastin Sey1p, we investigated the molecular mechanisms of atlastin-mediated membrane tethering and fusion. Although Sey1p-bearing proteoliposomes frequently underwent membrane tethering in a GTP hydrolysis-dependent manner as reported in studies using bulk assays, only a small fraction of the tethered liposomes proceeded to fusion. Strikingly, the rest of the tethered liposomes failed to fuse or dissociate. This stable tethering, however, did not require continued GTP hydrolysis because GTP omission and magnesium chelation did not disrupt tethering. Interestingly, an increased Sey1p density on the membrane markedly accelerated tethering but barely affected the fusion rate of the tethered liposomes, indicating that Sey1p requires additional factors to support efficient fusion in vivo. Finally, the assay also revealed that Sey1p-mediated liposome fusion occurs through hemifusion, suggesting the mechanistic conservation between biological membrane fusion events despite the existence of diverse fusogens

Glucocorticoid receptor isoforms direct distinct mitochondrial programs to regulate ATP production

The glucocorticoid receptor (GR), a nuclear receptor and major drug target, has a highly conserved minor splice variant, GRγ, which differs by a single arginine within the DNA binding domain. GRγ, which comprises 10% of all GR transcripts, is constitutively expressed and tightly conserved through mammalian evolution, suggesting an important non-redundant role. However, to date no specific role for GRγ has been reported. We discovered significant differences in subcellular localisation, and nuclear-cytoplasmic shuttling in response to ligand. In addition the GRγ transcriptome and protein interactome was distinct, and with a gene ontology signal for mitochondrial regulation which was confirmed using Seahorse technology. We propose that evolutionary conservation of the single additional arginine in GRγ is driven by a distinct, non-redundant functional profile, including regulation of mitochondrial function