ABSTRACT
Cellular lipid metabolism is tightly regulated and requires a sophisticated interplay of multiple subcellular organelles to adapt to changing nutrient supply. PEX19 was originally described as an essential peroxisome biogenesis factor that selectively targets membrane proteins to peroxisomes. Metabolic aberrations that were associated with compromised PEX19 functions, were solely attributed to the absence of peroxisomes, which is also considered the underlying cause for Zellweger Spectrum Disorders. More recently, however, it was shown that PEX19 also mediates the targeting of the VCP/P97-recuitment factor UBXD8 to the ER from where it partitions to lipid droplets (LDs) but the physiological consequences remained elusive. Here, we addressed the intriguing possibility that PEX19 coordinates the functions of the major cellular sites of lipid metabolism. We exploited the farnesylation of PEX19 and deciphered the organelle-specific functions of PEX19 using systems level approaches. Non-farnesylated PEX19 is sufficient to fully restore the metabolic activity of peroxisomes, while farnesylated PEX19 controls lipid metabolism by a peroxisome-independent mechanism that can be attributed to sorting a specific protein subset to LDs. In the absence of this PEX19-dependent LD proteome, cells accumulate excess triacylglycerols and fail to fully deplete their neutral lipid stores under catabolic conditions, highlighting a hitherto unrecognized function of PEX19 in controlling neutral lipid storage and LD dynamics.
ABSTRACT
Surface pockets, cavities, and tunnels in the 3D structures of proteins play integral functional roles such as enabling enzymatic catalysis, ligand binding, or transport of ions or small molecules across biomembranes. ProPores2 facilitates understanding and analysis of these processes by identifying pores and lining residues, determining their axes, and opening closed connections via side-chain rotation. The fast stand-alone tool introduces a novel mode for pore identification, improved axis determination, and additional features such as parallel batch processing and a graphical user interface. The new web service features an integrated and customizable protein viewer with an option to analyze and view more than one structure at once. This feature facilitates side-by-side comparisons of pores in different conformations of the same protein or of identified pores before and after opening gates within the same protein. ProPores2 is freely and publicly available at https://service.bioinformatik.uni-saarland.de/propores.
Subject(s)
Proteins , Software , InternetABSTRACT
Proteins rarely carry out their cellular functions in isolation. Instead, eukaryotic proteins engage in about six interactions with other proteins on average. The aggregated protein interactome of an organism forms a "hairy ball"-type protein-protein interaction (PPI) network. Yet, in a typical human cell, only about half of all proteins are expressed at a particular time. Hence, it has become common practice to prune the full PPI network to the subset of expressed proteins. If RNAseq data is available, one can further resolve the specific protein isoforms present in a cell or tissue. Here, we review various approaches, software tools and webservices that enable users to construct context-specific or tissue-specific PPI networks and how these are rewired between two cellular conditions. We illustrate their different functionalities on the example of the interactions involving the human TNR6 protein. In an outlook, we describe how PPI networks may be integrated with epigenetic data or with data on the activity of splicing factors.
ABSTRACT
Summary: Mutations in genomic key elements can influence gene expression and function in various ways, and hence greatly contribute to the phenotype. We developed MutaNET to score the impact of individual mutations on gene regulation and function of a given genome. MutaNET performs statistical analyses of mutations in different genomic regions. The tool also incorporates the mutations in a provided gene regulatory network to estimate their global impact. The integration of a next-generation sequencing pipeline enables calling mutations prior to the analyses. As application example, we used MutaNET to analyze the impact of mutations in antibiotic resistance (AR) genes and their potential effect on AR of bacterial strains. Availability and implementation: MutaNET is freely available at https://sourceforge.net/projects/mutanet/. It is implemented in Python and supported on Mac OS X, Linux and MS Windows. Step-by-step instructions are available at http://service.bioinformatik.uni-saarland.de/mutanet/. Contact: volkhard.helms@bioinformatik.uni-saarland.de. Supplementary information: Supplementary data are available at Bioinformatics online.
