Centriolar satellites are small electron‐dense granules that cluster in the vicinity of centrosomes. Satellites have been implicated in multiple critical cellular functions including centriole duplication, centrosome maturation, and ciliogenesis, but their precise composition and assembly properties have remained poorly explored. Here, we perform in vivo proximity‐dependent biotin identification (Bio ID ) on 22 human satellite proteins, to identify 2,113 high‐confidence interactions among 660 unique polypeptides. Mining this network, we validate six additional satellite components. Analysis of the satellite interactome, combined with subdiffraction imaging, reveals the existence of multiple unique microscopically resolvable satellite populations that display distinct protein interaction profiles. We further show that loss of satellites in PCM 1‐depleted cells results in a dramatic change in the satellite interaction landscape. Finally, we demonstrate that satellite composition is largely unaffected by centriole depletion or disruption of microtubules, indicating that satellite assembly is centrosome‐independent. Together, our work offers the first systematic spatial and proteomic profiling of human centriolar satellites and paves the way for future studies aimed at better understanding the biogenesis and function(s) of these enigmatic structures.

Zika virus (ZIKV) is a membrane enveloped Flavivirus with a positive strand RNA genome, transmitted by mosquitoes. The geographical range of ZIKV has dramatically expanded in recent decades resulting in increasing numbers of infected individuals, and the spike in ZIKV infections has been linked to significant increases in both Guillain-Barré syndrome and microcephaly. Although a large number of host proteins have been physically and/or functionally linked to other Flaviviruses, very little is known about the virus-host protein interactions established by ZIKV. Here we map host cell protein interaction profiles for each of the ten polypeptides encoded in the ZIKV genome, generating a protein topology network comprising 3033 interactions among 1224 unique human polypeptides. The interactome is enriched in proteins with roles in polypeptide processing and quality control, vesicle trafficking, RNA processing and lipid metabolism.>60% of the network components have been previously implicated in other types of viral infections; the remaining interactors comprise hundreds of new putative ZIKV functional partners. Mining this rich data set, we highlight several examples of how ZIKV may usurp or disrupt the function of host cell organelles, and uncover an important role for peroxisomes in ZIKV infection.

The worldwide SARS-CoV-2 outbreak poses a serious challenge to human societies and economies. SARS-CoV-2 proteins orchestrate complex pathogenic mechanisms that underlie COVID-19 disease. Thus, understanding how viral polypeptides rewire host protein networks enables better-founded therapeutic research. In complement to existing proteomic studies, in this study we define the first proximal interaction network of SARS-CoV-2 proteins, at the whole proteome level in human cells. Applying a proximity-dependent biotinylation (BioID)-based approach greatly expanded the current knowledge by detecting interactions within poorly soluble compartments, transient, and/or of weak affinity in living cells. Our BioID study was complemented by a stringent filtering and uncovered 2,128 unique cellular targets (1,717 not previously associated with SARS-CoV-1 or 2 proteins) connected to the N- and C-ter BioID-tagged 28 SARS-CoV-2 proteins by a total of 5,415 (5,236 new) proximal interactions. In order to facilitate data exploitation, an innovative interactive 3D web interface was developed to allow customized analysis and exploration of the landscape of interactions (accessible at http://www.sars-cov-2-interactome.org/). Interestingly, 342 membrane proteins including interferon and interleukin pathways factors, were associated with specific viral proteins. We uncovered ORF7a and ORF7b protein proximal partners that could be related to anosmia and ageusia symptoms. Moreover, comparing proximal interactomes in basal and infection-mimicking conditions (poly(I:C) treatment) allowed us to detect novel links with major antiviral response pathway components, such as ORF9b with MAVS and ISG20; N with PKR and TARB2; NSP2 with RIG-I and STAT1; NSP16 with PARP9-DTX3L. Altogether, our study provides an unprecedented comprehensive resource for understanding how SARS-CoV-2 proteins orchestrate host proteome remodeling and innate immune response evasion, which can inform development of targeted therapeutic strategies.

The identification of ubiquitin E3 ligase substrates has been challenging, due in part to low-affinity, transient interactions, the rapid degradation of targets and the inability to identify proteins from poorly soluble cellular compartments. SCF ␤-TrCP1 and SCF ␤-TrCP2 are well-studied ubiquitin E3 ligases that target substrates for proteasomal degradation, and play important roles in Wnt, Hippo, and NFB signaling. Combining 26S proteasome inhibitor (MG132) treatment with proximity-dependent biotin labeling (BioID) and semiquantitative mass spectrometry, here we identify SCF ␤-TrCP1/2 interacting partners. Based on their enrichment in the presence of MG132, our data identify over 50 new putative SCF ␤-TrCP1/2 substrates. We validate 12 of these new substrates and reveal previously unsuspected roles for ␤-TrCP in the maintenance of nuclear membrane integrity, processing (P)-body turnover and translational control. Together, our data suggest that ␤-TrCP is an important hub in the cellular stress response. The technique presented here represents a complementary approach to more standard IP-MS methods and should be broadly applicable for the identification of substrates for many ubiquitin E3 ligases. Molecular & Cellular

Carbonic anhydrase IX (CAIX) is a hypoxia inducible factor 1-induced, cell surface pH regulating enzyme with an established role in tumor progression and clinical outcome. However, the molecular basis of CAIX-mediated tumor progression remains unclear. Here, we have utilized proximity dependent biotinylation (BioID) to map the CAIX ‘interactome’ in breast cancer cells in order to identify physiologically relevant CAIX-associating proteins with potential roles in tumor progression. High confidence proteins identified include metabolic transporters, β1 integrins, integrin-associated protein CD98hc and matrix metalloprotease 14 (MMP14). Biochemical studies validate the association of CAIX with α2β1 integrin, CD98hc and MMP14, and immunofluorescence microscopy demonstrates colocalization of CAIX with α2β1 integrin and MMP14 in F-actin/cofilin-positive lamellipodia/pseudopodia, and with MMP14 to cortactin/Tks5-positive invadopodia. Modulation of CAIX expression and activity results in significant changes in cell migration, collagen degradation and invasion. Mechanistically, we demonstrate that CAIX associates with MMP14 through potential phosphorylation residues within its intracellular domain, and that CAIX enhances MMP14-mediated collagen degradation by directly contributing hydrogen ions required for MMP14 catalytic activity. These findings establish hypoxia-induced CAIX as a novel metabolic component of cellular migration and invasion structures, and provide new mechanistic insights into its role in tumor cell biology.

Ecology and evolution unfold in spatially structured communities, where dispersal links dynamics across scales. Because dispersal is multicausal, identifying general drivers remains challenging. In a coordinated distributed experiment spanning organisms from protozoa to vertebrates, we tested whether two fundamental determinants of local dynamics, top-down and bottom-up control, generally explain active dispersal. We show that both factors consistently increased emigration rates and use metacommunity modelling to highlight consequences on local and regional dynamics.

Limited dispersal is classically considered as a prerequisite for ecological specialization to evolve, such that generalists are expected to show greater dispersal propensity compared with specialists. However, when individuals choose habitats that maximize their performance instead of dispersing randomly, theory predicts dispersal with habitat choice to evolve in specialists, while generalists should disperse more randomly. We tested whether habitat choice is associated with thermal niche specialization using microcosms of the ciliate Tetrahymena thermophila, a species that performs active dispersal. We found that thermal specialists preferred optimal habitats as predicted by theory, a link that should make specialists more likely to track suitable conditions under environmental changes than expected under the random dispersal assumption. Surprisingly, generalists also performed habitat choice but with a preference for suboptimal habitats. Since this result challenges current theory, we developed a metapopulation model to understand under which circumstances such a preference for suboptimal habitats should evolve. We showed that competition between generalists and specialists may favor a preference for niche margins in generalists under environmental variability. Our results demonstrate that the behavioral dimension of dispersal—here, habitat choice—fundamentally alters our predictions of how dispersal evolve with niche specialization, making dispersal behaviors crucial for ecological forecasting facing environmental changes.

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