Protein interactions regulate the systems-level behavior of cells; thus, deciphering the structure and dynamics of protein interaction networks in their cellular context is a central goal in biology. We have performed a genome-wide in vivo screen for protein-protein interactions in Saccharomyces cerevisiae by means of a protein-fragment complementation assay (PCA). We identified 2770 interactions among 1124 endogenously expressed proteins. Comparison with previous studies confirmed known interactions, but most were not known, revealing a previously unexplored subspace of the yeast protein interactome. The PCA detected structural and topological relationships between proteins, providing an 8-nanometer-resolution map of dynamically interacting complexes in vivo and extended networks that provide insights into fundamental cellular processes, including cell polarization and autophagy, pathways that are evolutionarily conserved and central to both development and human health.T he elucidation of protein-protein interaction networks (PINs, or interactomes) holds the promise of answering fundamental questions about how the biochemical machinery of cells organizes matter, information, and energy transformations to perform specific functions (1). An essential and rarely addressed question is whether protein complexes and PINs that are reconstructed or reconstituted in vitro or removed from the normal context in which they are expressed reflect their organization in living cells. For eukaryotes, the test bed for large-scale analysis of PINs is the yeast Saccharomyces cerevisiae, where several PIN analyses have been performed using yeast two-hybrid screens (Y2H) (2-4) or tandem affinity purification followed by massspectrometric analyses (TAP-MSs) (5-8). Each approach captures specific features of protein interactions; two-hybrid methods are best at measuring direct binary interactions between pairs of proteins, whereas affinity purification techniques best capture stable protein complexes. However, neither approach measures interactions between proteins in their natural cellular context, and are not easily amenable to studying protein complexes that are transiently associated or dynamic under different conditions, that do not survive in vitro purification, or that cannot be transported to the nucleus and form interactions in the absence of other

Spindle alignment is the process in which the two spindle poles are directed toward preselected and opposite cell ends. In budding yeast, the APC-related molecule Kar9 is required for proper alignment of the spindle with the mother-bud axis. We find that Kar9 localizes to the prospective daughter cell spindle pole. Kar9 is transferred from the pole to cytoplasmic microtubules, which are then guided in a myosin-dependent manner to the bud. Clb4/Cdc28 kinase phosphorylates Kar9 and accumulates on the pole destined to the mother cell. Mutations that block phosphorylation at Cdc28 consensus sites result in localization of Kar9 to both poles and target them both to the bud. Thus, Clb4/Cdc28 prevents Kar9 loading on the mother bound pole. In turn, asymmetric distribution of Kar9 ensures that only one pole orients toward the bud. Our results indicate that Cdk1-dependent spindle asymmetry ensures proper alignment of the mitotic spindle with the cell division axis.

Centrosomes organize the bipolar mitotic spindle, and centrosomal defects cause chromosome instability. Protein phosphorylation modulates centrosome function, and we provide a comprehensive map of phosphorylation on intact yeast centrosomes (18 proteins). Mass spectrometry was used to identify 297 phosphorylation sites on centrosomes from different cell cycle stages. We observed different modes of phosphoregulation via specific protein kinases, phosphorylation site clustering, and conserved phosphorylated residues. Mutating all eight cyclin-dependent kinase (Cdk)–directed sites within the core component, Spc42, resulted in lethality and reduced centrosomal assembly. Alternatively, mutation of one conserved Cdk site within γ-tubulin (Tub4-S360D) caused mitotic delay and aberrant anaphase spindle elongation. Our work establishes the extent and complexity of this prominent posttranslational modification in centrosome biology and provides specific examples of phosphorylation control in centrosome function.

Often the time derivative of a measured variable is of as much interest as the variable itself. For a growing population of biological cells, for example, the population's growth rate is typically more important than its size. Here we introduce a non-parametric method to infer first and second time derivatives as a function of time from time-series data. Our approach is based on Gaussian processes and applies to a wide range of data. In tests, the method is at least as accurate as others, but has several advantages: it estimates errors both in the inference and in any summary statistics, such as lag times, and allows interpolation with the corresponding error estimation. As illustrations, we infer growth rates of microbial cells, the rate of assembly of an amyloid fibril and both the speed and acceleration of two separating spindle pole bodies. Our algorithm should thus be broadly applicable.