University of Georgia

About: University of Georgia is a education organization based out in Athens, Georgia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 41934 authors who have published 93622 publications receiving 3713212 citations. The organization is also known as: UGA & Franklin College.

The NextGen Model Atmosphere grid for $3000\le \Teff \le 10000\K$

Abstract: We present our NextGen Model Atmosphere grid for low mass stars for effective temperatures larger than $3000\K$. These LTE models are calculated with the same basic model assumptions and input physics as the VLMS part of the NextGen grid so that the complete grid can be used, e.g., for consistent stellar evolution calculations and for internally consistent analysis of cool star spectra. This grid is also the starting point for a large grid of detailed NLTE model atmospheres for dwarfs and giants (Hauschildt et al, in preparation). The models were calculated from $3000\K$ to $10000\K$ (in steps of $200\K$) for $3.5 \le \logg \le 5.5$ (in steps of 0.5) and metallicities of $-4.0 \le \mh \le 0.0$. We discuss the results of the model calculations and compare our results to the Kurucz 1994 grid. Some comparisons to standard stars like Vega and the Sun are presented and compared with detailed NLTE calculations.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Field guide to next-generation DNA sequencers

Abstract: The diversity of available 2 nd and 3 rd generation DNA sequencing platforms is increasing rapidly. Costs for these systems range from $10 ⁄Mb for 454 and some Ion Torrent chips). In terms of cost per nonmultiplexed sample and instrument run time, the Pacific Biosciences and Ion Torrent platforms excel, with the 454 GS Junior and Illumina MiSeq also notable in this regard. All platforms allow multiplexing of samples, but details of library preparation, experimental design and data analysis can constrain the options. The wide range of characteristics among available platforms provides opportunities both to conduct groundbreaking studies and to waste money on scales that were previously infeasible. Thus, careful thought about the desired characteristics of these systems is warranted before purchasing or using any of them. Updated information from this guide will be maintained at: http://dna.uga.edu/ and http://tomato.biol.trinity.edu/blog/.

Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis

Abstract: Ustilago maydis is a ubiquitous pathogen of maize and a well-established model organism for the study of plant-microbe interactions. This basidiomycete fungus does not use aggressive virulence strategies to kill its host. U. maydis belongs to the group of biotrophic parasites (the smuts) that depend on living tissue for proliferation and development. Here we report the genome sequence for a member of this economically important group of biotrophic fungi. The 20.5-million-base U. maydis genome assembly contains 6,902 predicted protein-encoding genes and lacks pathogenicity signatures found in the genomes of aggressive pathogenic fungi, for example a battery of cell-wall-degrading enzymes. However, we detected unexpected genomic features responsible for the pathogenicity of this organism. Specifically, we found 12 clusters of genes encoding small secreted proteins with unknown function. A significant fraction of these genes exists in small gene families. Expression analysis showed that most of the genes contained in these clusters are regulated together and induced in infected tissue. Deletion of individual clusters altered the virulence of U. maydis in five cases, ranging from a complete lack of symptoms to hypervirulence. Despite years of research into the mechanism of pathogenicity in U. maydis, no 'true' virulence factors had been previously identified. Thus, the discovery of the secreted protein gene clusters and the functional demonstration of their decisive role in the infection process illuminate previously unknown mechanisms of pathogenicity operating in biotrophic fungi. Genomic analysis is, similarly, likely to open up new avenues for the discovery of virulence determinants in other pathogens.