AUTOCOUNTER, an ImageJ JavaScript to analyze LC3B-GFP expression dynamics in autophagy-induced astrocytoma cells

An ImageJ JavaScript, AUTOCOUNTER, was specifically developed to monitor and measure LC3B-GFP expression in living human astrocytoma cells, namely T98G and U373-MG. Discrete intracellular GFP fluorescent spots derived from transduction of a Baculovirus replication-defective vector (BacMam LC3B-GFP), followed by microscope examinations at different times. After viral transgene expression, autophagy was induced by Rapamycin administration and assayed in ph-p70S6K/p70S6K and LC3B immunoblotting expression as well as by electron microscopy examinations. A mutated transgene, defective in LC3B lipidation, was employed as a negative control to further exclude fluorescent dots derived from protein intracellular aggregation. The ImageJ JavaScript was then employed to evaluate and score the dynamics changes of the number and area of LC3B-GFP puncta per cell in time course assays and in complex microscope examinations. In conclusion, AUTOCOUNTER enabled to quantify LC3B-GFP expression and to monitor dynamics changes in number and shapes of autophagosomal-like vesicles: it might therefore represent a suitable algorithmic tool for in vitro autophagy modulation studies

Genetic characterization of Barbari goats using microsatellite markers

Genetic variation in Barbari goats, a highly prolific breed distributed widely in the northern part of India, known for better milk and meat quality, was studied as a part of genetic characterization and conservation. The genomic DNA from 50 unrelated Barbari goats were amplified via PCR with a panel of 21 microsatellite markers, and resolved through 6 per cent denaturing polyacrylamide gel electrophoresis followed by silver staining. The number of alleles ranged from 4 to 11, with allele sizes ranging from 88 to 220 bp. The distribution of allele frequencies was between 0.0104 and 0.5208. Polymorphism information content varied from 0.5563 to 0.8348. The population was not in Hardy-Weinberg equilibrium for all except two microsatellite loci (ILSTS044 and ILSTS060). The observed heterozygosity ranged from 0.8478 to 1.0000 while the expected heterozygosity ranged from 0.6208 to 0.8509. Based on the results of the present study, there is a good scope for exploiting the genetic variability in the Barbari goats for further improvement of performance

ATG7 Promotes Bladder Cancer Invasion via Autophagy-Mediated Increased ARHGDIB mRNA Stability

Since invasive bladder cancer (BC) can progress to life threatening metastases, understanding the molecular mechanisms underlying BC invasion is crucial for potentially decreasing the mortality of this disease. Herein, it is discovered that autophagy-related gene 7 (ATG7) is remarkably overexpressed in human invasive BC tissues. The knockdown of ATG7 in human BC cells dramatically inhibits cancer cell invasion, revealing that ATG7 is a key player in regulating BC invasion. Mechanistic studies indicate that MIR190A is responsible for ATG7 mRNA stability and protein overexpression by directly binding to ATG7 mRNA 3'-UTR. Furthermore, ATG7-mediated autophagy promotes HNRNPD (ARE/poly(U)-binding/degradation factor 1) protein degradation, and in turn reduces HNRNPD interaction with ARHGDIB mRNA, resulting in the elevation of ARHGDIB mRNA stability, and subsequently leading to BC cell invasion. The identification of the MIR190A/ATG7 autophagic mechanism regulation of HNRNPD/ARHGDIB expression provides an important insight into understanding the nature of BC invasion and suggests that autophagy may represent a potential therapeutic strategy for the treatment of human BC patients

Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival

<p>Abstract</p> <p>Background</p> <p>Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival.</p> <p>Methods</p> <p>A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers.</p> <p>Results</p> <p>A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. <it>Pik3r1</it>, <it>E2f3, Akr1c3</it>, <it>Csf1</it>, <it>Jag2</it>, <it>Plcg1</it>, <it>Rpl37a</it>, <it>Sod2</it>, <it>Topors</it>, <it>Hras</it>, <it>Mdm2, Camk2g</it>, <it>Fstl1</it>, <it>Il13ra1</it>, <it>Mtap </it>and <it>Tp53 </it>were associated with multiple survival events.</p> <p>Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for <it>Syne1</it>, <it>Pdcd4</it>, <it>Ighg1</it>, <it>Tgfa</it>, <it>Pla2g7</it>, and <it>Paics</it>. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. <it>C2</it>, <it>Egfr</it>, <it>Prkcb</it>, <it>Igf2bp3</it>, and <it>Gdf10 </it>had gender-dependent associations; <it>Sox10</it>, <it>Rps20</it>, <it>Rab31</it>, and <it>Vav3 </it>had race-dependent associations; <it>Chi3l1</it>, <it>Prkcb</it>, <it>Polr2d</it>, and <it>Apool </it>had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death.</p> <p>Conclusions</p> <p>Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.</p

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field