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Abstract The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis–mass spectrometry (LiP–MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP–MS detects well-characterized PPIs, including antibody–target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson’s disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

The human genome encodes approximately 20,000 proteins, many still uncharacterised. It has become clear that scientific research tends to focus on well-studied proteins, leading to a concern that poorly understood genes are unjustifiably neglected. To address this, we have developed a publicly available and customisable "Unknome database" that ranks proteins based on how little is known about them. We applied RNA interference (RNAi) in Drosophila to 260 unknown genes that are conserved between flies and humans. Knockdown of some genes resulted in loss of viability, and functional screening of the rest revealed hits for fertility, development, locomotion, protein quality control, and resilience to stress. CRISPR/Cas9 gene disruption validated a component of Notch signalling and 2 genes contributing to male fertility. Our work illustrates the importance of poorly understood genes, provides a resource to accelerate future research, and highlights a need to support database curation to ensure that misannotation does not erode our awareness of our own ignorance.

The function of de novo lipogenesis (DNL) in adipocytes has been a mystery as it contributes little to fat storage in these cells. Here, the authors show that DNL is a critical source of fatty acids for membrane-expanding processes like autophagy.

Summary: Disruption of adipocyte de novo lipogenesis (DNL) by deletion of fatty acid synthase (FASN) in mice induces browning in inguinal white adipose tissue (iWAT). However, adipocyte FASN knockout (KO) increases acetyl-coenzyme A (CoA) and malonyl-CoA in addition to depletion of palmitate. We explore which of these metabolite changes triggers adipose browning by generating eight adipose-selective KO mouse models with loss of ATP-citrate lyase (ACLY), acetyl-CoA carboxylase 1 (ACC1), ACC2, malonyl-CoA decarboxylase (MCD) or FASN, or dual KOs ACLY/FASN, ACC1/FASN, and ACC2/FASN. Preventing elevation of acetyl-CoA and malonyl-CoA by depletion of adipocyte ACLY or ACC1 in combination with FASN KO does not block the browning of iWAT. Conversely, elevating malonyl-CoA levels in MCD KO mice does not induce browning. Strikingly, adipose ACC1 KO induces a strong iWAT thermogenic response similar to FASN KO while also blocking malonyl-CoA and palmitate synthesis. Thus, ACC1 and FASN are strong suppressors of adipocyte thermogenesis through promoting lipid synthesis rather than modulating the DNL intermediates acetyl-CoA or malonyl-CoA.