Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of cofactors ...(cochaperones) that regulate their specificity and function. However, how these cochaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone-cochaperone-client interaction network in human cells. We uncover hundreds of chaperone clients, delineate their participation in specific cochaperone complexes, and establish a surprisingly distinct network of protein-protein interactions for cochaperones. As a salient example of the power of such analysis, we establish that NUDC family cochaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network and its regulation in development and disease and expand the use of chaperones as sensors for drug-target engagement.
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•Client interactions for >60 chaperones and cochaperones mapped by AP-MS and LUMIER•Characterization of cellular roles of cochaperones and their client specificities•NUDC family cochaperones associate with β-propeller domains (Kelch, WD40, and RCC1)•Cochaperones may promote the evolutionary diversification of client folds
Mass spectrometry and quantitative LUMIER assays map the proteostasis network in human cells, revealing hundreds of new client proteins, their integration into the network, and the client specificity of most cochaperones.
Characterizing the extent and logic of signaling networks is essential to understanding specificity in such physiological and pathophysiological contexts as cell fate decisions and mechanisms of ...oncogenesis and resistance to chemotherapy. Cell-based RNA interference (RNAi) screens enable the inference of large numbers of genes that regulate signaling pathways, but these screens cannot provide network structure directly. We describe an integrated network around the canonical receptor tyrosine kinase (RTK)-Ras-extracellular signal-regulated kinase (ERK) signaling pathway, generated by combining parallel genome-wide RNAi screens with protein-protein interaction (PPI) mapping by tandem affinity purification-mass spectrometry. We found that only a small fraction of the total number of PPI or RNAi screen hits was isolated under all conditions tested and that most of these represented the known canonical pathway components, suggesting that much of the core canonical ERK pathway is known. Because most of the newly identified regulators are likely cell type- and RTK-specific, our analysis provides a resource for understanding how output through this clinically relevant pathway is regulated in different contexts. We report in vivo roles for several of the previously unknown regulators, including CG10289 and PpV, the Drosophila orthologs of two components of the serine/threonine-protein phosphatase 6 complex; the Drosophila ortholog of TepIV, a glycophosphatidylinositol-linked protein mutated in human cancers; CG6453, a noncatalytic subunit of glucosidase II; and Rtf1, a histone methyltransferase.
A major goal of large-scale genomics projects is to enable the use of data from high-throughput experimental methods to predict complex phenotypes such as disease susceptibility. The DREAM5 Systems ...Genetics B Challenge solicited algorithms to predict soybean plant resistance to the pathogen Phytophthora sojae from training sets including phenotype, genotype, and gene expression data. The challenge test set was divided into three subcategories, one requiring prediction based on only genotype data, another on only gene expression data, and the third on both genotype and gene expression data. Here we present our approach, primarily using regularized regression, which received the best-performer award for subchallenge B2 (gene expression only). We found that despite the availability of 941 genotype markers and 28,395 gene expression features, optimal models determined by cross-validation experiments typically used fewer than ten predictors, underscoring the importance of strong regularization in noisy datasets with far more features than samples. We also present substantial analysis of the training and test setup of the challenge, identifying high variance in performance on the gold standard test sets.
This book introduces beginning students and non-specialists to the diversity and richness of African languages. In addition to providing a solid background to the study of African languages, the book ...presents linguistic phenomena not found in European languages. A goal of this book is to stimulate interest in African languages and address the question: What makes African languages so fascinating? The orientation adopted throughout the book is a descriptive one, which seeks to characterize African languages in a relatively succinct and neutral manner, and to make the facts accessible to a wide variety of readers. The author's lengthy acquaintance with the continent and field experiences in western, eastern, and southern Africa allow for both a broad perspective and considerable depth in selected areas. The original examples are often the author's own but also come from other sources and languages not often referenced in the literature. This text also includes a set of sound files illustrating the phenomena under discussion, be they the clicks of Khoisan, talking drums, or the ideophones (words like English lickety-split) found almost everywhere, which will make this book a valuable resource for teacher and student alike.
Using a reduced subset of SNPs in a linear mixed model can improve power for genome-wide association studies, yet this can result in insufficient correction for population stratification. We propose ...a hybrid approach using principal components that does not inflate statistics in the presence of population stratification and improves power over standard linear mixed models.
Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts and may ...not optimize power. All existing methods require time cost O(MN(2)) (where N is the number of samples and M is the number of SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here we present a far more efficient mixed-model association method, BOLT-LMM, which requires only a small number of O(MN) time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to 9 quantitative traits in 23,294 samples from the Women's Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for genome-wide association studies in large cohorts.
Background: Traditionally, clinical learning for medical students consists of short-term and opportunistic encounters with primarily acute-care patients, supervised by an array of clinician ...preceptors. In response to educational concerns, some medical schools have developed longitudinal placements rather than short-term rotations. Many of these longitudinal placements are also integrated across the core clinical disciplines, are commonly termed longitudinal integrated clerkships (LICs) and often situated in rural locations. This review aimed to explore, analyse and synthesise evidence relating to the effectiveness of longitudinal placements, for medical students in particular to determine which aspects are most critical to successful outcomes.
Method: Extensive search of the literature resulted in 1679 papers and abstracts being considered, with 53 papers ultimately being included for review. The review group coded these 53 papers according to standard BEME review guidelines. Specific information extracted included: data relating to effectiveness, the location of the study, number of students involved, format, length and description of placement, the learning outcomes, research design, the impact level for evaluation and the main evaluation methods and findings. We applied a realist approach to consider what works well for whom and under what circumstances.
Findings: The early LICs were all community-based immersion programs, situated in general practice and predominantly in rural settings. More recent LIC innovations were situated in tertiary-level specialist ambulatory care in urban settings. Not all placements were integrated across medical disciplines but were longitudinal in relation to location, patient base and/or supervision. Twenty-four papers focussed on one of four programs from different viewpoints. Most evaluations were student opinion (survey, interview, focus group) and/or student assessment results. Placements varied from one half day per week for six months through to full time immersion for more than 12 months.
The predominant mechanism relating to factors influencing effectiveness was continuity of one or more of: patient care, supervision and mentorship, peer group and location. The success of LICs and participation satisfaction depended on the preparation of both students and clinical supervisors, and the level of support each received from their academic institutions.
Conclusion: Longitudinal placements, including longitudinal integrated placements, are gaining in popularity as an alternative to traditional block rotations. Although relatively few established LICs currently exist, medical schools may look for ways to incorporate some of the principles of LICs more generally in their clinical education programmes. Further research is required to ascertain the optimum length of time for placements depending on the defined learning outcomes and timing within the programme, which students are most likely to benefit and the effects of context such as location and type of integration.
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