Nature: Blocking FSH induces thermogenic adipose tissue and reduces body fat (Liu et al.) ➡ apparently, this could be used to treat osteoporosis and obesity associated with menopause… Looks like a nice study, but haven’t scrutinised it properly.
Nature: Genetic wiring maps of single-cell protein states reveal an off-switch for GPCR signalling (Brockmann et al.). Skimmed this through, and basically the group applies high-throughput technology and protein abundance as a readout for phenotypes arising from random mutagenesis in haploid cells to identify novel regulators of signal trasnduction. They identify a new mechanisms whereby Gβγ is targeted for degradation by KCTD5 to limit the ability of GPCRs to trigger PI3K/AKT activation.
Nature resource-type paper that is important for mining -omics datasets / hypothesis generation: Architecture of the human interactome defines protein communities and disease networks (Huttlin et al.) ➡ the resource is called BioPlex 2.0; this is the abstract of the paper describing what it’s all about:
“The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein– protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease1–3. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification–mass spectrometry methodology4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering5 of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.”
Nature News & Views on the ATP-independent mitochondrial regulation of cell fate decisions in haematopoietic stem cells which was demonstrated by two independent studies recently (linked to within the news and views). It is very interesting because it is linked back to mTOR signalling and also demonstrates the importance of mitochondria in cells that are otherwise very glycolytic and don’t rely on mitochondria to generate energy. Title to search for if interested: Mitochondria link metabolism and epigenetics in haematopoiesis (Schell, J. & Rutter, J.).
Nature News & Views (Cell forces meet cell metabolism) on another interesting mechanism relating to how cell obtain their energy during the costly process of cell-cell adhesion, with link to the original paper that reported this (. Very interesting because it is relevant for understanding how cell-cell interactions link to intracellular metabolism regulation. In the described case, force exerted through E-cadherins links to AMPK activation and increased glycolysis in epithelial cells. Also remindes me of the recent paper linking PI3K activation and remodelling of the actin cytoskeleton to release Aldolase and trigger glycolysis in preparation for cell migration (by Lewis Cantley’s group). Must admit that I haven’t read the original paper discussed in this News and Views and after skimming through the quality of the figures and methods, I already noted wrong statistics (t tests instead of 1-Way ANOVA or 2-Way ANOVA!!).
eLife: Synergistic interactions with PI3K inhibition that induce apoptosis (Zwang et al.). This group looked for genes that promote breast cancer cell survival in the face of PI3K inhibition (the initial cells they use have PIK3CA H1047R and ERBB2 amplification, they then confirm in additional cell lines). They performed a shRNA-based apoptosis screen and identified PIM2, ZAK, TACC1, ZFR and ZNF565 as genes whose inhibition in the presence of the p110α/δ inhibitor GDC0941 (625 nM). It is interesting to note that from the initial shRNA screen where 54 candidates were identified, only 5 were confirmed upon orthogonal validation. Goes to show the importance of validation experiments, which they also do for the 5 final candidates by overexpressing them to check that the phenotype is rescued – a method which validated 3/5 candidates. All 5 eventually validated in vivo. I like the fact that they drug concentrations are not ridiculously high (which is the case for many papers, confounding their findings), and they also test additional inhibitors in the context of the proposed interactions and find that the effect is p110α-dependent and occurs throught he canonical signalling pathway (AKT etc.).They also use z-score filtering following the initial screen to account both for the magnitude of the effect and the consistency of replicates. Another interesting thing in this paper: they use a so-called BH3 profiling assay to determine mitochondrial priming (i.e. the proportion of anti-apoptotic and apoptotic proteins). In brief, you permeabilise the cells and incubate them with increasing concentrations of synthetic BIM peptide; you then fix the cells and stain for endogenous cytochrome c, then perform flow cytometry to quantify loss of cytochrome c (measure of mitochondrial depolarisation).
FEBS Journal: The energy sensing LKB1-AMPKα1 pathway regulates IGF1 secretion and consequent activation of the IGF1R-PKB pathway in primary hepatocytes (Chen et al.) – it is a small study limited to primary hepatocytes, and the effects are not striking, but might be interesting to read anyway. Looks like metformin reduces IGF1 secretion.
EMBO News & Views covering the 2 most recent Mitofusin papers: Let’s burn whatever you have: mitofusin 2 metabolically re-wires brown adipose tissue (Scheideler, M. & Herzig, S.)
On the biophysical/hardcore biochemistry side of things, some studies looking at molecular Cas9 mechanisms:
PNAS: Mechanisms of dupex DNA destabilisation by RNA-guided Cas9 nuclease during target interrogation (Mekler et al.)
PNAS: High-throughput biochemical profiling reveals sequence determinants of dCas9 off-target binding and unbinding (Boyle et al.)
Also on the techy side from Jennifer Lippincott-Schwartz’ lab in Nature: Applying systems-level spectral imaging and analysis to reveal the organelle interactome (Valm et al.)
Out of general interest and haven’t read beyond abstract, but in Science this week: Rapid binge-like eating and body weight gain driven by zona incerta GABA neuron activation (Zhang, X. & van den Pol, A)