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Identification of the major functional proteins of prokaryotic lipid droplets.

ABSTRACT: Storage of cellular triacylglycerols (TAGs) in lipid droplets (LDs) has been linked to the progression of many metabolic diseases in humans, and to the development of biofuels from plants and microorganisms. However, the biogenesis and dynamics of LDs are poorly understood. Compared with other organisms, bacteria seem to be a better model system for studying LD biology, because they are relatively simple and are highly efficient in converting biomass to TAG. We obtained highly purified LDs from Rhodococcus sp. RHA1, a bacterium that can produce TAG from many carbon sources, and then comprehensively characterized the LD proteome. Of the 228 LD-associated proteins identified, two major proteins, ro02104 and PspA, constituted about 15% of the total LD protein. The structure predicted for ro02104 resembles that of apolipoproteins, the structural proteins of plasma lipoproteins in mammals. Deletion of ro02104 resulted in the formation of supersized LDs, indicating that ro02104 plays a critical role in cellular LD dynamics. The putative ? helix of the ro02104 LD-targeting domain (amino acids 83-146) is also similar to that of apolipoproteins. We report the identification of 228 proteins in the proteome of prokaryotic LDs, identify a putative structural protein of this organelle, and suggest that apolipoproteins may have an evolutionarily conserved role in the storage and trafficking of neutral lipids.

SUBMITTER: Ding Y

PROVIDER: S-EPMC3276463 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Identification of the major functional proteins of prokaryotic lipid droplets.

Ding Yunfeng Y Yang Li L Zhang Shuyan S Wang Yang Y Du Yalan Y Pu Jing J Peng Gong G Chen Yong Y Zhang Huina H Yu Jinhai J Hang Haiying H Wu Peng P Yang Fuquan F Yang Hongyuan H Steinbüchel Alexander A Liu Pingsheng P

Journal of lipid research 20111215 3

Storage of cellular triacylglycerols (TAGs) in lipid droplets (LDs) has been linked to the progression of many metabolic diseases in humans, and to the development of biofuels from plants and microorganisms. However, the biogenesis and dynamics of LDs are poorly understood. Compared with other organisms, bacteria seem to be a better model system for studying LD biology, because they are relatively simple and are highly efficient in converting biomass to TAG. We obtained highly purified LDs from ...[more]

PMID: 22180631

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Project description:Mycobacterium tuberculosis is a global pathogen of significant medical importance. A key aspect of its life cycle is the ability to enter into an altered physiological state of nonreplicating persistence during latency and resist elimination by the host immune system. One mechanism by which M. tuberculosis facilitates its survival during latency is by producing and metabolizing intracytoplasmic lipid droplets (LDs). LDs are quasi-organelles consisting of a neutral lipid core such as triacylglycerol surrounded by a phospholipid monolayer and proteins. We previously reported that PspA (phage shock protein A) associates with LDs produced in Mycobacterium In particular, the loss or overproduction of PspA alters LD homeostasis in Mycobacterium smegmatis and attenuates the survival of M. tuberculosis during nonreplicating persistence. Here, M. tuberculosis PspA (PspAMtb) and a ΔpspA M. smegmatis mutant were used as model systems to investigate the mechanism by which PspA associates with LDs and determine if other Mycobacterium proteins associate with LDs using a mechanism similar to that for PspA. Through this work, we established that the amphipathic helix present in the first α-helical domain (H1) of PspA is both necessary and sufficient for the targeting of this protein to LDs. Furthermore, we identified other Mycobacterium proteins that also possess amphipathic helices similar to PspA H1, including a subset that localize to LDs. Altogether, our results indicate that amphipathic helices may be an important mechanism by which proteins target LDs in prokaryotes.IMPORTANCEMycobacterium spp. are one of the few prokaryotes known to produce lipid droplets (LDs), and their production has been linked to aspects of persistent infection by M. tuberculosis Unfortunately, little is known about LD production in these organisms, including how LDs are formed, their function, or the identity of proteins that associate with them. In this study, an established M. tuberculosis LD protein and a surrogate Mycobacterium host were used as model systems to study the interactions between proteins and LDs in bacteria. Through these studies, we identified a commonly occurring protein motif that is able to facilitate the association of proteins to LDs in prokaryotes.

Project description:MotivationAccurate prediction of genes encoding small proteins (on the order of 50 amino acids or less) remains an elusive open problem in bioinformatics. Some of the best methods for gene prediction use either sequence composition analysis or sequence similarity to a known protein coding sequence. These methods often fail for small proteins, however, either due to a lack of experimentally verified small protein coding genes or due to the limited statistical significance of statistics on small sequences. Our approach is based upon the hypothesis that true small proteins will be under selective pressure for encoding the particular amino acid sequence, for ease of translation by the ribosome and for structural stability. This stability can be achieved either independently or as part of a larger protein complex. Given this assumption, it follows that small proteins should display conserved local protein structure properties much like larger proteins. Our method incorporates neural-net predictions for three local structure alphabets within a comparative genomic approach using a genomic alignment of 22 closely related bacteria genomes to generate predictions for whether or not a given open reading frame (ORF) encodes for a small protein.ResultsWe have applied this method to the complete genome for Escherichia coli strain K12 and looked at how well our method performed on a set of 60 experimentally verified small proteins from this organism. Out of a total of 11 407 possible ORFs, we found that 6 of the top 10 and 27 of the top 100 predictions belonged to the set of 60 experimentally verified small proteins. We found 35 of all the true small proteins within the top 200 predictions. We compared our method to Glimmer, using a default Glimmer protocol and a modified small ORF Glimmer protocol with a lower minimum size cutoff. The default Glimmer protocol identified 16 of the true small proteins (all in the top 200 predictions), but failed to predict on 34 due to size cutoffs. The small ORF Glimmer protocol made predictions for all the experimentally verified small proteins but only contained 9 of the 60 true small proteins within the top 200 predictions.Contactjsamayoa@jhu.edu

Dataset Information

Identification of the major functional proteins of prokaryotic lipid droplets.

Publications

Identification of the major functional proteins of prokaryotic lipid droplets.

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