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[
FASEB J,
2020]
Fas-apoptotic inhibitory molecule 2 (FAIM2) is a member of the transmembrane BAX inhibitor motif-containing (TMBIM) family. TMBIM family is comprised of six anti-apoptotic proteins that suppress cell death by regulating endoplasmic reticulum Ca<sup>2+</sup> homeostasis. Recent studies have implicated two TMBIM proteins, GRINA and BAX Inhibitor-1, in mediating cytoprotection via autophagy. However, whether FAIM2 plays a role in autophagy has been unknown. Here we show that FAIM2 localizes to the lysosomes at basal state and facilitates autophagy through interaction with microtubule-associated protein 1 light chain 3 proteins in human neuroblastoma SH-SY5Y cells. FAIM2 overexpression increased autophagy flux, while autophagy flux was impaired in shRNA-mediated knockdown (shFAIM2) cells, and the impairment was more evident in the presence of rapamycin. In shFAIM2 cells, autophagosome maturation through fusion with lysosomes was impaired, leading to accumulation of autophagosomes. A functional LC3-interacting region motif within FAIM2 was essential for the interaction with LC3 and rescue of autophagy flux in shFAIM2 cells while LC3-binding property of FAIM2 was dispensable for the anti-apoptotic function in response to Fas receptor-mediated apoptosis. Suppression of autophagosome maturation was also observed in a null mutant of Caenorhabditis elegans lacking
xbx-6, the ortholog of FAIM2. Our study suggests that FAIM2 is a novel regulator of autophagy mediating autophagosome maturation through the interaction with LC3.
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[
Biochem Soc Trans,
2003]
Despite the central role of the 26 S proteasome in eukaryotic cells, many facets of its structural organization and functioning are still poorly understood. To learn more about the interactions between its different subunits, as well as its possible functional partners in cells, we performed, with Marc Vidal's laboratory (Dana-Farber Cancer Institute, Boston, MA, U.S.A.), a systematic two-hybrid analysis using Caenorhaditis elegans 26 S proteasome subunits as baits (Davy, Bello, Thierry-Mieg, Vaglio, Hitti, Doucette-Stamm, Thierry-Mieg, Reboul, Boulton, Walhout et al. (2001) EMBO Rep. 2, 821-828). A pair-wise matrix of all subunit combinations allowed us to detect numerous possible intra-complex interactions, among which some had already been reported by others and eight were novel. Interestingly, four new interactions were detected between two ATPases of the 19 S regulatory complex and three alpha-subunits of the 20 S proteolytic core. Possibly, these interactions participate in the association of these two complexes to form the 26 S proteasome. Proteasome subunit sequences were also used to screen a cDNA library to identify new interactors of the complex. Among the interactors found, most (58) have no clear connection to the proteasome, and could be either substrates or potential cofactors of this complex. Few interactors (7) could be directly or indirectly linked to proteolysis. The others (12) interacted with more than one proteasome subunit, forming 'interaction clusters' of
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[
Methods Mol Biol,
2021]
Genetic interaction screens have played a critical role in better understanding epistasis and functional relationships among genes. These screens have been conducted at multiple scales, ranging from testing pairwise interactions genome-wide in yeast and bacteria, to more focused screens in multicellular organisms and cultured cells. Here, I describe a strategy that facilitates genetic interaction screens with loss of function alleles in the model organism Caenorhabditis elegans. I also present a simple downstream assay to measure the effects of combinations of mutations on fitness.
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[
BMC Bioinformatics,
2009]
BACKGROUND: The assembly of reliable and complete protein-protein interaction (PPI) maps remains one of the significant challenges in systems biology. Computational methods which integrate and prioritize interaction data can greatly aid in approaching this goal. RESULTS: We developed a Bayesian inference framework which uses phylogenetic relationships to guide the integration of PPI evidence across multiple datasets and species, providing more accurate predictions. We apply our framework to reconcile seven eukaryotic interactomes: H. sapiens, M. musculus, R. norvegicus, D. melanogaster, C. elegans, S. cerevisiae and A. thaliana. Comprehensive GO-based quality assessment indicates a 5% to 44% score increase in predicted interactomes compared to the input data. Further support is provided by gold-standard MIPS, CYC2008 and HPRD datasets. We demonstrate the ability to recover known PPIs in well-characterized yeast and human complexes (26S proteasome, endosome and exosome) and suggest possible new partners interacting with the putative SWI/SNF chromatin remodeling complex in A. thaliana. CONCLUSION: Our phylogeny-guided approach compares favorably to two standard methods for mapping PPIs across species. Detailed analysis of predictions in selected functional modules uncovers specific PPI profiles among homologous proteins, establishing interaction-based partitioning of protein families. Provided evidence also suggests that interactions within core complex subunits are in general more conserved and easier to transfer accurately to other organisms, than interactions between these subunits.
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[
BMC Genomics,
2013]
BACKGROUND: Known protein interaction networks have very particular properties. Old proteins tend to have more interactions than new ones. One of the best statistical representatives of this property is the node degree distribution (distribution of proteins having a given number of interactions). It has previously been shown that this distribution is very close to the sum of two distinct exponential components. In this paper, we asked: What are the possible mechanisms of evolution for such types of networks? To answer this question, we tested a kinetic model for simplified evolution of a protein interactome. Our proposed model considers the emergence of new genes and interactions and the loss of old ones. We assumed that there are generally two coexisting classes of proteins. Proteins constituting the first class are essential only for ecological adaptations and are easily lost when ecological conditions change. Proteins of the second class are essential for basic life processes and, hence, are always effectively protected against deletion. All proteins can transit between the above classes in both directions. We also assumed that the phenomenon of gene duplication is always related to ecological adaptation and that a new copy of a duplicated gene is not essential. According to this model, all proteins gain new interactions with a rate that preferentially increases with the number of interactions (the rich get richer). Proteins can also gain interactions because of duplication. Proteins lose their interactions both with and without the loss of partner genes. RESULTS: The proposed model reproduces the main properties of protein-protein interaction networks very well. The connectivity of the oldest part of the interaction network is densest, and the node degree distribution follows the sum of two shifted power-law functions, which is a theoretical generalization of the previous finding. The above distribution covers the wide range of values of node degrees very well, much better than a power law or generalized power law supplemented with an exponential cut-off. The presented model also relates the total number of interactome links to the total number of interacting proteins. The theoretical results were for the interactomes of A. thaliana, B. taurus, C. elegans, D. melanogaster, E. coli, H. pylori, H. sapiens, M. musculus, R. norvegicus and S. cerevisiae. CONCLUSIONS: Using these approaches, the kinetic parameters could be estimated. Finally, the model revealed the evolutionary kinetics of proteome formation, the phenomenon of protein differentiation and the process of gaining new interactions.
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[
FEBS J,
2018]
The Notch pathway is a widely conserved cell signaling system found in most metazoans. In Caenorhabditis elegans, GLP-1/Notch signaling is required for developmental cell fate decisions in multiple contexts. A recent report provides a potential link between DNA replication and Notch-dependent proliferation in the C. elegans germline.
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[
Sci Rep,
2015]
The increasing ease and accuracy of protein-protein interaction detection has resulted in the ability to map the interactomes of multiple species. We now have an opportunity to compare species to better understand how interactomes evolve. As DNA and protein sequence alignment algorithms were required for comparative genomics, network alignment algorithms are required for comparative interactomics. A number of network alignment methods have been developed for protein-protein interaction networks, where proteins are represented as vertices linked by edges if they interact. Recently, protein interactions have been mapped at the level of amino acid positions, which can be represented as an interface-interaction network (IIN), where vertices represent binding sites, such as protein domains and short sequence motifs. However, current algorithms are not designed to align these networks and generally fail to do so in practice. We present a greedy algorithm, GreedyPlus, for IIN alignment, combining data from diverse sources, including network, protein and binding site properties, to identify putative orthologous relationships between interfaces in available worm and yeast data. GreedyPlus is fast and simple, allowing for easy customization of behaviour, yet still capable of generating biologically meaningful network alignments.
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[
Science,
1997]
The Caenorhabditis elegans survival gene
ced-9 regulates
ced-4 activity and inhibits cell death, but the mechanism by which this occurs is unknown. Through a genetic screen for CED-4-binding proteins, CED-9 was identified as an interacting partner of CED-4. CED-9, but not loss-of-function mutants, associated specifically with CED-4 in yeast or mammalian cells. The CED-9 protein localized primarily to intracellular membranes and the perinuclear region, whereas CED-4 was distributed in the cytosol. Expression of CED-9, but not a mutant lacking the carboxy-terminal hydrophobic domain, targeted CED-4 from the cytosol to intracellular membranes in mammalian cells. Thus, the actions of CED-4 and CED-9 are directly linked, which could provide the basis for the regulation of programmed cell death in C. elegans.AD - Department of Pathology and Comprehensive Cancer Center, The University of Michigan Medical School, Ann Arbor, MI 48109, USA.FAU - Wu, DAU - Wu DFAU - Wallen, H DAU - Wallen HDFAU - Nunez, GAU - Nunez GLA - engID - CA-64556/CA/NCIID - T32A107413-03/PHSPT - Journal ArticleCY - UNITED STATESTA - ScienceJID - 0404511RN - 0 (Calcium-Binding Proteins)RN - 0 (Ced-4 protein)RN - 0 (Ced-9 protein)RN - 0 (Helminth Proteins)RN - 0 (Proto-Oncogene Proteins)RN - 0 (bcl-x protein)SB - IM
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[
Aging Cell,
2017]
As in other poikilotherms, longevity in C.elegans varies inversely with temperature; worms are longer-lived at lower temperatures. While this observation may seem intuitive based on thermodynamics, the molecular and genetic basis for this phenomenon is not well understood. Several recent reports have argued that lifespan changes across temperatures are genetically controlled by temperature-specific gene regulation. Here, we provide data that both corroborate those studies and suggest that temperature-specific longevity is more the rule than the exception. By measuring the lifespans of worms with single modifications reported to be important for longevity at 15, 20, or 25C, we find that the effect of each modification on lifespan is highly dependent on temperature. Our results suggest that genetics play a major role in temperature-associated longevity and are consistent with the hypothesis that while aging in C. elegans is slowed by decreasing temperature, the major cause(s) of death may also be modified, leading to different genes and pathways becoming more or less important at different temperatures. These differential mechanisms of age-related death are not unlike what is observed in humans, where environmental conditions lead to development of different diseases of aging.
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[
Genetics,
2013]
Intraneuronal deposition of aggregated proteins in tauopathies, Parkinson disease, or familial encephalopathy with neuroserpin inclusion bodies (FENIB) leads to impaired protein homeostasis (proteostasis). FENIB represents a conformational dementia, caused by intraneuronal polymerization of mutant variants of the serine protease inhibitor neuroserpin. In contrast to the aggregation process, the kinetic relationship between neuronal proteostasis and aggregation are poorly understood. To address aggregate formation dynamics, we studied FENIB in Caenorhabditis elegans and mice. Point mutations causing FENIB also result in aggregation of the neuroserpin homolog SRP-2 most likely within the ER lumen in worms, recapitulating morphological and biochemical features of the human disease. Intriguingly, we identified conserved protein quality control pathways to modulate protein aggregation both in worms and mice. Specifically, downregulation of the unfolded protein response (UPR) pathways in the worm favors mutant SRP-2 accumulation, while mice overexpressing a polymerizing mutant of neuroserpin undergo transient induction of the UPR in young but not in aged mice. Thus, we find that perturbations of proteostasis through impairment of the heat shock response or altered UPR signaling enhance neuroserpin accumulation in vivo. Moreover, accumulation of neuroserpin polymers in mice is associated with an age-related induction of the UPR suggesting a novel interaction between aging and ER overload. These data suggest that targets aimed at increasing UPR capacity in neurons are valuable tools for therapeutic intervention.