A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection.

The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a protein's sub-cellular localisation to one or more of these compartments can therefore be a first step in determining its function. High-throughput and high-accuracy mass spectrometry-based sub-cellular proteomic methods can now shed light on the localisation of thousands of proteins at once. Machine learning algorithms are then typically employed to make protein-organelle assignments. However, these algorithms are limited by insufficient and incomplete annotation. We propose a semi-supervised Bayesian approach to novelty detection, allowing the discovery of additional, previously unannotated sub-cellular niches. Inference in our model is performed in a Bayesian framework, allowing us to quantify uncertainty in the allocation of proteins to new sub-cellular niches, as well as in the number of newly discovered compartments. We apply our approach across 10 mass spectrometry based spatial proteomic datasets, representing a diverse range of experimental protocols. Application of our approach to hyperLOPIT datasets validates its utility by recovering enrichment with chromatin-associated proteins without annotation and uncovers sub-nuclear compartmentalisation which was not identified in the original analysis. Moreover, using sub-cellular proteomics data from Saccharomyces cerevisiae, we uncover a novel group of proteins trafficking from the ER to the early Golgi apparatus. Overall, we demonstrate the potential for novelty detection to yield biologically relevant niches that are missed by current approaches.

Characterisation of protein isoforms encoded by the Drosophila Glycogen Synthase Kinase 3 gene shaggy.

The Drosophila shaggy gene (sgg, GSK-3) encodes multiple protein isoforms with serine/threonine kinase activity and is a key player in diverse developmental signalling pathways. Currently it is unclear whether different Sgg proteoforms are similarly involved in signalling or if different proteoforms have distinct functions. We used CRISPR/Cas9 genome engineering to tag eight different Sgg proteoform classes and determined their localization during embryonic development. We performed proteomic analysis of the two major proteoform classes and generated mutant lines for both of these for transcriptomic and phenotypic analysis. We uncovered distinct tissue-specific localization patterns for all of the tagged proteoforms we examined, most of which have not previously been characterised directly at the protein level, including one proteoform initiating with a non-standard codon. Collectively, this suggests complex developmentally regulated splicing of the sgg primary transcript. Further, affinity purification followed by mass spectrometric analyses indicate a different repertoire of interacting proteins for the two major proteoforms we examined, one with ubiquitous expression (Sgg-PB) and one with nervous system specific expression (Sgg-PA). Specific mutation of these proteoforms shows that Sgg-PB performs the well characterised maternal and zygotic segmentations functions of the sgg locus, while Sgg-PA mutants show adult lifespan and locomotor defects consistent with its nervous system localisation. Our findings provide new insights into the role of GSK-3 proteoforms and intriguing links with the GSK-3α and GSK-3ß proteins encoded by independent vertebrate genes. Our analysis suggests that different proteoforms generated by alternative splicing are likely to perform distinct functions.

Mapping the Saccharomyces cerevisiae Spatial Proteome with High Resolution Using hyperLOPIT.

The subcellular localization of proteins is a posttranslational modification of paramount importance. The ability to study subcellular and organelle proteomes improves our understanding of cellular homeostasis and cellular dynamics. In this chapter, we describe a protocol for the unbiased and high-throughput study of protein subcellular localization in the yeast Saccharomyces cerevisiae: hyperplexed localization of organelle proteins by isotope tagging (hyperLOPIT), which involves biochemical fractionation of Saccharomyces cerevisiae and high resolution mass spectrometry-based protein quantitation using TMT 10-plex isobaric tags. This protocol enables the determination of the subcellular localizations of thousands of proteins in parallel in a single experiment and thereby deep sampling and high-resolution mapping of the spatial proteome.

Transcriptional regulation of the genes involved in protein metabolism and processing in Saccharomyces cerevisiae.

Topological analysis of large networks, which focus on a specific biological process or on related biological processes, where functional coherence exists among the interacting members, may provide a wealth of insight into cellular functionality. This work presents an unbiased systems approach to analyze genetic, transcriptional regulatory and physical interaction networks of yeast genes possessing such functional coherence to gain novel biological insight. The present analysis identified only a few transcriptional regulators amongst a large gene cohort associated with the protein metabolism and processing in yeast. These transcription factors are not functionally required for the maintenance of these tasks in growing cells. Rather, they are involved in rewiring gene transcription in response to such major challenges as starvation, hypoxia, DNA damage, heat shock or the accumulation of unfolded proteins. Indeed, only a subset of these proteins were captured empirically in the nuclear-enriched fraction of non-stressed yeast cells, suggesting that the transcriptional regulation of protein metabolism and processing in yeast is primarily concerned with maintaining cellular robustness in the face of threat by either internal or external stressors.

A Protocol to Map the Spatial Proteome Using HyperLOPIT in Saccharomyces cerevisiae.

The correct subcellular localization of proteins is vital for cellular function and the study of this process at the systems level will therefore enrich our understanding of the roles of proteins within the cell. Multiple methods are available for the study of protein subcellular localization, including fluorescence microscopy, organelle cataloging, proximity labeling methods, and whole-cell protein correlation profiling methods. We provide here a protocol for the systems-level study of the subcellular localization of the yeast proteome, using a version of hyperplexed Localization of Organelle Proteins by Isotope Tagging (hyperLOPIT) that has been optimized for use with Saccharomyces cerevisiae. The entire protocol encompasses cell culture, cell lysis by nitrogen cavitation, subcellular fractionation, monitoring of the fractionation using Western blotting, labeling of samples with TMT isobaric tags and mass spectrometric analysis. Also included is a brief explanation of downstream processing of the mass spectrometry data to produce a map of the spatial proteome. If required, the nitrogen cavitation lysis and Western blotting portions of the protocol may be performed independently of the mass spectrometry analysis. The protocol in its entirety, however, enables the unbiased, systems-level and high-resolution analysis of the localizations of thousands of proteins in parallel within a single experiment.

The subcellular organisation of Saccharomyces cerevisiae.

Subcellular protein localisation is essential for the mechanisms that govern cellular homeostasis. The ability to understand processes leading to this phenomenon will therefore enhance our understanding of cellular function. Here we review recent developments in this field with regard to mass spectrometry, fluorescence microscopy and computational prediction methods. We highlight relative strengths and limitations of current methodologies focussing particularly on studies in the yeast Saccharomyces cerevisiae. We further present the first cell-wide spatial proteome map of S. cerevisiae, generated using hyperLOPIT, a mass spectrometry-based protein correlation profiling technique. We compare protein subcellular localisation assignments from this map, with two published fluorescence microscopy studies and show that confidence in localisation assignment is attained using multiple orthogonal methods that provide complementary data.

Using hyperLOPIT to perform high-resolution mapping of the spatial proteome.

The organization of eukaryotic cells into distinct subcompartments is vital for all functional processes, and aberrant protein localization is a hallmark of many diseases. Microscopy methods, although powerful, are usually low-throughput and dependent on the availability of fluorescent fusion proteins or highly specific and sensitive antibodies. One method that provides a global picture of the cell is localization of organelle proteins by isotope tagging (LOPIT), which combines biochemical cell fractionation using density gradient ultracentrifugation with multiplexed quantitative proteomics mass spectrometry, allowing simultaneous determination of the steady-state distribution of hundreds of proteins within organelles. Proteins are assigned to organelles based on the similarity of their gradient distribution to those of well-annotated organelle marker proteins. We have substantially re-developed our original LOPIT protocol (published by Nature Protocols in 2006) to enable the subcellular localization of thousands of proteins per experiment (hyperLOPIT), including spatial resolution at the suborganelle and large protein complex level. This Protocol Extension article integrates all elements of the hyperLOPIT pipeline, including an additional enrichment strategy for chromatin, extended multiplexing capacity of isobaric mass tags, state-of-the-art mass spectrometry methods and multivariate machine-learning approaches for analysis of spatial proteomics data. We have also created an open-source infrastructure to support analysis of quantitative mass-spectrometry-based spatial proteomics data (http://bioconductor.org/packages/pRoloc) and an accompanying interactive visualization framework (http://www. bioconductor.org/packages/pRolocGUI). The procedure we outline here is applicable to any cell culture system and requires ∼1 week to complete sample preparation steps, ∼2 d for mass spectrometry data acquisition and 1-2 d for data analysis and downstream informatics.

SWATH-MS dataset of heat-shock treated Drosophila melanogaster embryos.

Data independent acquisition (DIA) has emerged as a promising mass spectrometry based approach, combining the advantages of shotgun and targeted proteomics. Here we applied a DIA approach (termed SWATH) to monitor the dynamics of the Drosophila melanogaster embryonic proteome upon heat-shock treatment. Embryos were incubated for 0.5, 1 or 3 h at 37 °C to induce heat-shock or maintained at 25 °C. The present dataset contains SWATH files acquired on a Sciex Triple-TOF 6600. A spectral library built in-house was used to analyse these data and led to the quantification of more than 2500 proteins at every timepoint. The files presented here are permanent digital maps and can be reanalysed to search for new questions. The data have been deposited with the ProteomeXchange Consortium with the dataset identifier PRIDE: PXD004753.

SWATH-MS data of Drosophila melanogaster proteome dynamics during embryogenesis.

Embryogenesis is one of the most important processes in the life of an animal. During this dynamic process, progressive cell division and cellular differentiation are accompanied by significant changes in protein expression at the level of the proteome. However, very few studies to date have described the dynamics of the proteome during the early development of an embryo in any organism. In this dataset, we monitor changes in protein expression across a timecourse of more than 20 h of Drosophila melanogaster embryonic development. Mass-spectrometry data were produced using a SWATH acquisition mode on a Sciex Triple-TOF 6600. A spectral library built in-house was used to analyse these data and more than 1950 proteins were quantified at each embryonic timepoint. The files presented here are a permanent digital map and can be reanalysed to test against new hypotheses. The data have been deposited with the ProteomeXchange Consortium with the dataset identifier PRIDE: PXD0031078.

A foundation for reliable spatial proteomics data analysis.

Quantitative mass-spectrometry-based spatial proteomics involves elaborate, expensive, and time-consuming experimental procedures, and considerable effort is invested in the generation of such data. Multiple research groups have described a variety of approaches for establishing high-quality proteome-wide datasets. However, data analysis is as critical as data production for reliable and insightful biological interpretation, and no consistent and robust solutions have been offered to the community so far. Here, we introduce the requirements for rigorous spatial proteomics data analysis, as well as the statistical machine learning methodologies needed to address them, including supervised and semi-supervised machine learning, clustering, and novelty detection. We present freely available software solutions that implement innovative state-of-the-art analysis pipelines and illustrate the use of these tools through several case studies involving multiple organisms, experimental designs, mass spectrometry platforms, and quantitation techniques. We also propose sound analysis strategies for identifying dynamic changes in subcellular localization by comparing and contrasting data describing different biological conditions. We conclude by discussing future needs and developments in spatial proteomics data analysis.

Carotid magnetization-prepared rapid acquisition with gradient-echo signal is associated with acute territorial cerebral ischemic events detected by diffusion-weighted MRI.

BACKGROUND: Carotid intraplaque hemorrhage has been associated with symptomatic stroke and can be accurately detected with magnetization-prepared rapid acquisition with gradient-echo (MPRAGE). Currently, there are no studies analyzing carotid MPRAGE signal and territorial ischemic events defined by diffusion restriction in the acute setting. Our aim was to determine the association of carotid MPRAGE signal with acute territorial ischemic events using carotid MPRAGE and brain diffusion tensor imaging. METHODS AND RESULTS: After the addition of the MPRAGE sequence to the neck MR angiographic protocol, 159 patients with suspected acute stroke were evaluated with both brain diffusion tensor imaging and carotid MPRAGE sequences over 2 years, providing 318 carotid artery and paired brain images for analysis. Forty-eight arteries were excluded due to extracarotid sources of brain ischemia and 4 were excluded due to carotid occlusion. Two hundred sixty-six arteries were eligible for data analysis. Carotid MPRAGE-positive signal was associated with an acute cerebral territorial ischemic event with a relative risk of 6.4 (P<0.001). The relative risk of a diffusion tensor imaging-positive territorial ischemic event with carotid MPRAGE-positive signal was increased in mild, moderate, and severe stenosis categories (10.3, P<0.001; 2.9, P=0.01; and 2.2, P=0.01, respectively). CONCLUSIONS: In the workup of acute stroke, carotid MPRAGE-positive signal was associated with an increased risk of territorial cerebral ischemic events as detected objectively by brain diffusion tensor imaging. The relative risk of stroke was increased in all carotid stenosis categories but was most elevated in the mild stenosis category.

Composite mantle cell and diffuse large B-cell lymphoma: report of two cases.

Composite lymphomas are rare and involve the concurrent evolution of 2 distinct lymphoma types within a single organ or tissue. This study describes 2 cases of composite mantle cell lymphoma (MCL) and diffuse large B-cell lymphoma (DLBCL), which has not previously been reported. Each case demonstrated distinct populations of CD20 positive small and large atypical B cells. In both cases, only the small lymphocytes were positive for CD5 and cyclin D1, and fluorescence in situ hybridization (FISH) showed a t(11;14) translocation in the small lymphocytes but not in the large cells. Molecular studies for B-cell clonality showed a possible clonal relationship between the 2 components in one case but not the other. This study describes in detail the morphology, immunophenotype, FISH, and molecular analysis of both components in each case. To the authors' knowledge, this represents the first report of juxtaposition of MCL with DLBCL that does not represent transformation of the mantle cell component.

Histiocytic sarcoma in a 3-year-old male: a case report.

We describe a pediatric patient with histiocytic sarcoma involving the T6 and L4 vertebral bodies and the lungs. His tumor progressed during chemotherapy designed for Langerhans' cell histiocytosis and sarcoma. High-dose radiation, on the other hand, was effective.

Interstitial deletion 8q11.2-q13 with congenital anomalies of CHARGE association.

Specific genetic loci responsible for CHARGE association are currently unknown. Herein, we describe a neonate with clinical manifestations consistent with CHARGE association who has a de novo interstitial deletion involving bands 8q11.2 to 8q13. Genetic mapping and genomic microarray technology have been used to more accurately define the breakpoints of this deletion. Within the deleted region, there are approximately 150 expressed genes, one or more of which may contribute to the manifestations of CHARGE association.