The molecular cytoarchitecture of the adult mouse brain.

The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types and their positions within individual anatomical structures remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA sequencing with Slide-seq1,2-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signalling, elucidated region-specific specializations in activity-regulated gene expression and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource ( www.BrainCellData.org ), should find diverse applications across neuroscience, including the construction of new genetic tools and the prioritization of specific cell types and circuits in the study of brain diseases.

Ageing hallmarks exhibit organ-specific temporal signatures.

Ageing is the single greatest cause of disease and death worldwide, and understanding the associated processes could vastly improve quality of life. Although major categories of ageing damage have been identified-such as altered intercellular communication, loss of proteostasis and eroded mitochondrial function1-these deleterious processes interact with extraordinary complexity within and between organs, and a comprehensive, whole-organism analysis of ageing dynamics has been lacking. Here we performed bulk RNA sequencing of 17 organs and plasma proteomics at 10 ages across the lifespan of Mus musculus, and integrated these findings with data from the accompanying Tabula Muris Senis2-or 'Mouse Ageing Cell Atlas'-which follows on from the original Tabula Muris3. We reveal linear and nonlinear shifts in gene expression during ageing, with the associated genes clustered in consistent trajectory groups with coherent biological functions-including extracellular matrix regulation, unfolded protein binding, mitochondrial function, and inflammatory and immune response. Notably, these gene sets show similar expression across tissues, differing only in the amplitude and the age of onset of expression. Widespread activation of immune cells is especially pronounced, and is first detectable in white adipose depots during middle age. Single-cell RNA sequencing confirms the accumulation of T cells and B cells in adipose tissue-including plasma cells that express immunoglobulin J-which also accrue concurrently across diverse organs. Finally, we show how gene expression shifts in distinct tissues are highly correlated with corresponding protein levels in plasma, thus potentially contributing to the ageing of the systemic circulation. Together, these data demonstrate a similar yet asynchronous inter- and intra-organ progression of ageing, providing a foundation from which to track systemic sources of declining health at old age.

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer.

An Optimized Chromatographic Strategy for Multiplexing In Parallel Reaction Monitoring Mass Spectrometry: Insights from Quantitation of Activated Kinases.

Reliable quantitation of protein abundances in defined sets of cellular proteins is critical to numerous biological applications. Traditional immunodetection-based methods are limited by the quality and availability of specific antibodies, especially for site-specific post-translational modifications. Targeted proteomic methods, including the recently developed parallel reaction monitoring (PRM) mass spectrometry, have enabled accurate quantitative measurements of up to a few hundred specific target peptides. However, the degree of practical multiplexing in label-free PRM workflows remains a significant limitation for the technique. Here we present a strategy for significantly increasing multiplexing in label-free PRM that takes advantage of the superior separation characteristics and retention time stability of meter-scale monolithic silica-C18 column-based chromatography. We show the utility of the approach in quantifying kinase abundances downstream of previously developed active kinase enrichment methodology based on multidrug inhibitor beads. We examine kinase activation dynamics in response to three different MAP kinase inhibitors in colorectal carcinoma cells and demonstrate reliable quantitation of over 800 target peptides from over 150 kinases in a single label-free PRM run. The kinase activity profiles obtained from these analyses reveal compensatory activation of TGF-ß family receptors as a response to MAPK blockade. The gains achieved using this label-free PRM multiplexing strategy will benefit a wide array of biological applications.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

The role of plantigrady and heel-strike in the mechanics and energetics of human walking with implications for the evolution of the human foot.

Human bipedal locomotion is characterized by a habitual heel-strike (HS) plantigrade gait, yet the significance of walking foot-posture is not well understood. To date, researchers have not fully investigated the costs of non-heel-strike (NHS) walking. Therefore, we examined walking speed, walk-to-run transition speed, estimated locomotor costs (lower limb muscle volume activated during walking), impact transient (rapid increase in ground force at touchdown) and effective limb length (ELL) in subjects (n=14) who walked at self-selected speeds using HS and NHS gaits. HS walking increases ELL compared with NHS walking since the center of pressure translates anteriorly from heel touchdown to toe-off. NHS gaits led to decreased absolute walking speeds (P=0.012) and walk-to-run transition speeds (P=0.0025), and increased estimated locomotor energy costs (P<0.0001) compared with HS gaits. These differences lost significance after using the dynamic similarity hypothesis to account for the effects of foot landing posture on ELL. Thus, reduced locomotor costs and increased maximum walking speeds in HS gaits are linked to the increased ELL compared with NHS gaits. However, HS walking significantly increases impact transient values at all speeds (P<0.0001). These trade-offs may be key to understanding the functional benefits of HS walking. Given the current debate over the locomotor mechanics of early hominins and the range of foot landing postures used by nonhuman apes, we suggest the consistent use of HS gaits provides key locomotor advantages to striding bipeds and may have appeared early in hominin evolution.

An ontogenetic framework linking locomotion and trabecular bone architecture with applications for reconstructing hominin life history.

The ontogeny of bipedal walking is considered uniquely challenging, due in part to the balance requirements of single limb support. Thus, locomotor development in humans and our bipedal ancestors may track developmental milestones including the maturation of the neuromuscular control system. Here, we examined the ontogeny of locomotor mechanics in children aged 1-8, and bone growth and development in an age-matched skeletal sample to identify bony markers of locomotor development. We show that step-to-step variation in mediolateral tibia angle relative to the vertical decreases with age, an indication that older children increase stability. Analyses of trabecular bone architecture in the distal tibia of an age-matched skeletal sample (the Norris Farms #36 archaeological skeletal collection) show a bony signal of this shift in locomotor stability. Using a grid of eleven cubic volumes of interest (VOI) in the distal metaphysis of each tibia, we show that the degree of anisotropy (DA) of trabecular struts changes with age. Intra-individual variation in DA across these VOIs is generally high at young ages, likely reflecting variation in loading due to kinematic instability. With increasing age, mean DA converges on higher values and becomes less variable across the distal tibia. We believe the ontogeny of distal tibia trabecular architecture reflects the development of locomotor stability in bipeds. We suggest this novel bony marker of development may be used to assess the relationship between locomotor development and other life history milestones in fossil hominins.

C/EBPα and DEK coordinately regulate myeloid differentiation.

The transcription factor C/EBPα is a critical mediator of myeloid differentiation and is often functionally impaired in acute myeloid leukemia. Recent studies have suggested that oncogenic FLT3 activity disrupts wild-type C/EBPα function via phosphorylation on serine 21 (S21). Despite the apparent role of pS21 as a negative regulator of C/EBPα transcription activity, the mechanism by which phosphorylation tips the balance between transcriptionally competent and inhibited forms remains unresolved. In the present study, we used immuno-affinity purification combined with quantitative mass spectrometry to delineate the proteins associated with C/EBPα on chromatin. We identified DEK, a protein with genetic links to leukemia, as a member of the C/EBPα complexes, and demonstrate that this association is disrupted by S21 phosphorylation. We confirmed that DEK is recruited specifically to chromatin with C/EBPα to enhance GCSFR3 promoter activation. In addition, we demonstrated that genetic depletion of DEK reduces the ability of C/EBPα to drive the expression of granulocytic target genes in vitro and disrupts G-CSF-mediated granulocytic differentiation of fresh human BM-derived CD34(+) cells. Our data suggest that C/EBPα and DEK coordinately activate myeloid gene expression and that S21 phosphorylation on wild-type C/EBPα mediates protein interactions that regulate the differentiation capacity of hematopoietic progenitors.

Library dependent LC-MS/MS acquisition via mzAPI/Live.

The use of MS for characterization of small molecules, nucleotides, and proteins in model organisms as well as primary tissues and clinical samples continues to proliferate at a rapid pace. The complexity and dynamic range of target analytes in biological systems hinders comprehensive analysis and simultaneously drives improvements in instrument hardware and software. As a result, state-of-the-art commercial mass spectrometers are equipped with sophisticated embedded control systems that provide robust acquisition methods accessed through intuitive graphical interfaces. Although optimized for speed, these preconfigured scan functions are otherwise closed to end-user customization beyond simple, analytical-centric parameters supplied by the manufacturer. Here, we present an open-source framework (mzAPI/Live) that enables users to generate arbitrarily complex LC-MS(n) acquisition methods via simple Python scripting. As a powerful proof-of-concept, we demonstrate real-time assignment of tandem mass spectra through rapid query of NIST peptide libraries. This represents an unprecedented capability to make acquisition decisions based on knowledge of analyte structures determined during the run itself, thus providing a path toward biology-driven MS data acquisition for the broader community.

mzResults: an interactive viewer for interrogation and distribution of proteomics results.

The growing use of mass spectrometry in the context of biomedical research has been accompanied by an increased demand for distribution of results in a format that facilitates rapid and efficient validation of claims by reviewers and other interested parties. However, the continued evolution of mass spectrometry hardware, sample preparation methods, and peptide identification algorithms complicates standardization and creates hurdles related to compliance with journal submission requirements. Moreover, the recently announced Philadelphia Guidelines (1, 2) suggest that authors provide native mass spectrometry data files in support of their peer-reviewed research articles. These trends highlight the need for data viewers and other tools that work independently of manufacturers' proprietary data systems and seamlessly connect proteomics results with original data files to support user-driven data validation and review. Based upon our recently described API(1)-based framework for mass spectrometry data analysis (3, 4), we created an interactive viewer (mzResults) that is built on established database standards and enables efficient distribution and interrogation of results associated with proteomics experiments, while also providing a convenient mechanism for authors to comply with data submission standards as described in the Philadelphia Guidelines. In addition, the architecture of mzResults supports in-depth queries of the native mass spectrometry files through our multiplierz software environment. We use phosphoproteomics data to illustrate the features and capabilities of mzResults.

mzServer: web-based programmatic access for mass spectrometry data analysis.

Continued progress toward systematic generation of large-scale and comprehensive proteomics data in the context of biomedical research will create project-level data sets of unprecedented size and ultimately overwhelm current practices for results validation that are based on distribution of native or surrogate mass spectrometry files. Moreover, the majority of proteomics studies leverage discovery-mode MS/MS analyses, rendering associated data-reduction efforts incomplete at best, and essentially ensuring future demand for re-analysis of data as new biological and technical information become available. Based on these observations, we propose to move beyond the sharing of interpreted spectra, or even the distribution of data at the individual file or project level, to a system much like that used in high-energy physics and astronomy, whereby raw data are made programmatically accessible at the site of acquisition. Toward this end we have developed a web-based server (mzServer), which exposes our common API (mzAPI) through very intuitive (RESTful) uniform resource locators (URL) and provides remote data access and analysis capabilities to the research community. Our prototype mzServer provides a model for lab-based and community-wide data access and analysis.

Online nanoflow multidimensional fractionation for high efficiency phosphopeptide analysis.

Despite intense, continued interest in global analyses of signaling cascades through mass spectrometry-based studies, the large-scale, systematic production of phosphoproteomics data has been hampered in-part by inefficient fractionation strategies subsequent to phosphopeptide enrichment. Here we explore two novel multidimensional fractionation strategies for analysis of phosphopeptides. In the first technique we utilize aliphatic ion pairing agents to improve retention of phosphopeptides at high pH in the first dimension of a two-dimensional RP-RP. The second approach is based on the addition of strong anion exchange as the second dimension in a three-dimensional reversed phase (RP)-strong anion exchange (SAX)-RP configuration. Both techniques provide for automated, online data acquisition, with the 3-D platform providing the highest performance both in terms of separation peak capacity and the number of unique phosphopeptide sequences identified per µg of cell lysate consumed. Our integrated RP-SAX-RP platform provides several analytical figures of merit, including: (1) orthogonal separation mechanisms in each dimension; (2) high separation peak capacity (3) efficient retention of singly- and multiply-phosphorylated peptides; (4) compatibility with automated, online LC-MS analysis. We demonstrate the reproducibility of RP-SAX-RP and apply it to the analysis of phosphopeptides derived from multiple biological contexts, including an in vitro model of acute myeloid leukemia in addition to primary polyclonal CD8(+) T-cells activated in vivo through bacterial infection and then purified from a single mouse.

The cell type composition of the adult mouse brain revealed by single cell and spatial genomics.

The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types, and their positions within individual anatomical structures, remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA-seq with Slide-seq-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain, and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signaling, elucidated region-specific specializations in activity-regulated gene expression, and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource (BrainCellData.org) should find diverse applications across neuroscience, including the construction of new genetic tools, and the prioritization of specific cell types and circuits in the study of brain diseases.

Nanoflow low pressure high peak capacity single dimension LC-MS/MS platform for high-throughput, in-depth analysis of mammalian proteomes.

The use of narrow bore LC capillaries operated at ultralow flow rates coupled with mass spectrometry provides a desirable convergence of figures of merit to support high-performance LC-MS/MS analysis. This configuration provides a viable means to achieve in-depth protein sequence coverage while maintaining a high rate of data production. Here we explore potential performance improvements afforded by use of 25 µm × 100 cm columns fabricated with 5 µm diameter reversed phase particles and integrated electrospray emitter tips. These columns achieve a separation peak capacity of ≈750 in a 600-min gradient, with average chromatographic peak widths of less than 1 min. At room temperature, a pressure drop of only ≈1500 psi is sufficient to maintain an effluent flow rate of ≤10 nL/min. Using mouse embryonic stem cells as a model for complex mammalian proteomes, we reproducibly identify over 4000 proteins across duplicate 600 min LC-MS/MS analyses.

Online nanoflow reversed phase-strong anion exchange-reversed phase liquid chromatography-tandem mass spectrometry platform for efficient and in-depth proteome sequence analysis of complex organisms.

The dynamic range of protein expression in complex organisms coupled with the stochastic nature of discovery-driven tandem mass spectrometry (MS/MS) analysis continues to impede comprehensive sequence analysis and often provides only limited information for low-abundance proteins. High-performance fractionation of proteins or peptides prior to mass spectrometry analysis can mitigate these effects, though achieving an optimal combination of automation, reproducibility, separation peak capacity, and sample yield remains a significant challenge. Here we demonstrate an automated nanoflow 3-D liquid chromatography (LC)-MS/MS platform based on high-pH reversed phase (RP), strong anion exchange (SAX), and low-pH reversed phase (RP) separation stages for analysis of complex proteomes. We observed that RP-SAX-RP outperformed RP-RP for analysis of tryptic peptides derived from Escherichia coli and enabled identification of proteins present at a level of 50 copies per cell in Saccharomyces cerevisiae, corresponding to an estimated detection limit of 500 amol, from 40 µg of total lysate on a low-resolution 3-D ion trap mass spectrometer. A similar study performed on a LTQ-Orbitrap yielded over 4000 unique proteins from 5 µg of total yeast lysate analyzed in a single, 101 fraction RP-SAX-RP LC-MS/MS acquisition, providing an estimated detection limit of 65 amol for proteins expressed at 50 copies per cell.

Unbiased Proteomic Profiling Uncovers a Targetable GNAS/PKA/PP2A Axis in Small Cell Lung Cancer Stem Cells.

Using unbiased kinase profiling, we identified protein kinase A (PKA) as an active kinase in small cell lung cancer (SCLC). Inhibition of PKA activity genetically, or pharmacologically by activation of the PP2A phosphatase, suppresses SCLC expansion in culture and in vivo. Conversely, GNAS (G-protein α subunit), a PKA activator that is genetically activated in a small subset of human SCLC, promotes SCLC development. Phosphoproteomic analyses identified many PKA substrates and mechanisms of action. In particular, PKA activity is required for the propagation of SCLC stem cells in transplantation studies. Broad proteomic analysis of recalcitrant cancers has the potential to uncover targetable signaling networks, such as the GNAS/PKA/PP2A axis in SCLC.

multiplierz: an extensible API based desktop environment for proteomics data analysis.

BACKGROUND: Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge. RESULTS: We describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines. CONCLUSION: Collectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.

Integration of Tumor Genomic Data with Cell Lines Using Multi-dimensional Network Modules Improves Cancer Pharmacogenomics.

Leveraging insights from genomic studies of patient tumors is limited by the discordance between these tumors and the cell line models used for functional studies. We integrate omics datasets using functional networks to identify gene modules reflecting variation between tumors and show that the structure of these modules can be evaluated in cell lines to discover clinically relevant biomarkers of therapeutic responses. Applied to breast cancer, we identify 219 gene modules that capture recurrent alterations and subtype patients and quantitate various cell types within the tumor microenvironment. Comparison of modules between tumors and cell lines reveals that many modules composed primarily of gene expression and methylation are poorly preserved. In contrast, preserved modules are highly predictive of drug responses in a manner that is robust and clinically relevant. This work addresses a fundamental challenge in pharmacogenomics that can only be overcome by the joint analysis of patient and cell line data.

Synthetic Lethal Targeting of ARID1A-Mutant Ovarian Clear Cell Tumors with Dasatinib.

New targeted approaches to ovarian clear cell carcinomas (OCCC) are needed, given the limited treatment options in this disease and the poor response to standard chemotherapy. Using a series of high-throughput cell-based drug screens in OCCC tumor cell models, we have identified a synthetic lethal (SL) interaction between the kinase inhibitor dasatinib and a key driver in OCCC, ARID1A mutation. Imposing ARID1A deficiency upon a variety of human or mouse cells induced dasatinib sensitivity, both in vitro and in vivo, suggesting that this is a robust synthetic lethal interaction. The sensitivity of ARID1A-deficient cells to dasatinib was associated with G1-S cell-cycle arrest and was dependent upon both p21 and Rb. Using focused siRNA screens and kinase profiling, we showed that ARID1A-mutant OCCC tumor cells are addicted to the dasatinib target YES1. This suggests that dasatinib merits investigation for the treatment of patients with ARID1A-mutant OCCC. Mol Cancer Ther; 15(7); 1472-84. ©2016 AACR.