Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.
Numerous software tools exist for data-independent acquisition (DIA) analysis of clinical samples, necessitating their comprehensive benchmarking. We present a benchmark dataset comprising real-world inter-patient heterogeneity, which we use for in-depth benchmarking of DIA data analysis workflows for clinical settings. Combining spectral libraries, DIA software, sparsity reduction, normalization, and statistical tests results in 1428 distinct data analysis workflows, which we evaluate based on their ability to correctly identify differentially abundant proteins. From our dataset, we derive bootstrap datasets of varying sample sizes and use the whole range of bootstrap datasets to robustly evaluate each workflow. We find that all DIA software suites benefit from using a gas-phase fractionated spectral library, irrespective of the library refinement used. Gas-phase fractionation-based libraries perform best against two out of three reference protein lists. Among all investigated statistical tests non-parametric permutation-based statistical tests consistently perform best.
BackgroundProteomic analyses of clinical specimens often rely on human tissues preserved through formalin-fixation and paraffin embedding (FFPE). Minimal sample consumption is the key to preserve the integrity of pathological archives but also to deal with minimal invasive core biopsies. This has been achieved by using the acid-labile surfactant RapiGest in combination with a direct trypsinization (DTR) strategy. A critical comparison of the DTR protocol with the most commonly used filter aided sample preparation (FASP) protocol is lacking. Furthermore, it is unknown how common histological stainings influence the outcome of the DTR protocol.MethodsFour single consecutive murine kidney tissue specimens were prepared with the DTR approach or with the FASP protocol using both 10 and 30 k filter devices and analyzed by label-free, quantitative liquid chromatography–tandem mass spectrometry (LC–MS/MS). We compared the different protocols in terms of proteome coverage, relative label-free quantitation, missed cleavages, physicochemical properties and gene ontology term annotations of the proteins. Additionally, we probed compatibility of the DTR protocol for the analysis of common used histological stainings, namely hematoxylin & eosin (H&E), hematoxylin and hemalaun. These were proteomically compared to an unstained control by analyzing four human tonsil FFPE tissue specimens per condition.ResultsOn average, the DTR protocol identified 1841 ± 22 proteins in a single, non-fractionated LC–MS/MS analysis, whereas these numbers were 1857 ± 120 and 1970 ± 28 proteins for the FASP 10 and 30 k protocol. The DTR protocol showed 15% more missed cleavages, which did not adversely affect quantitation and intersample comparability. Hematoxylin or hemalaun staining did not adversely impact the performance of the DTR protocol. A minor perturbation was observed for H&E staining, decreasing overall protein identification by 13%.ConclusionsIn essence, the DTR protocol can keep up with the FASP protocol in terms of qualitative and quantitative reproducibility and performed almost as well in terms of proteome coverage and missed cleavages. We highlight the suitability of the DTR protocol as a viable and straightforward alternative to the FASP protocol for proteomics-based clinical research.Electronic supplementary materialThe online version of this article (10.1186/s12014-018-9188-y) contains supplementary material, which is available to authorized users.
Background: Lung cancer is the leading cause of cancer related death worldwide. Over the past 15 years no major improvement of survival rates could be accomplished. The recently discovered histone methyltransferase KMT9 that acts as epigenetic regulator of prostate tumor growth has now raised hopes of enabling new cancer therapies. In this study, we aimed to identify the function of KMT9 in lung cancer. Methods:We unraveled the KMT9 transcriptome and proteome in A549 lung adenocarcinoma cells using RNA-Seq and mass spectrometry and linked them with functional cell culture, real-time proliferation and flow cytometry assays. Results:We show that KMT9α and -β subunits of KMT9 are expressed in lung cancer tissue and cell lines. Importantly, high levels of KMT9α correlate with poor patient survival. We identified 460 genes that are deregulated at the RNA and protein level upon knock-down of KMT9α in A549 cells. These genes cluster with proliferation, cell cycle and cell death gene sets as well as with subcellular organelles in gene ontology analysis. Knock-down of KMT9α inhibits lung cancer cell proliferation and induces non-apoptotic cell death in A549 cells. Conclusions:The novel histone methyltransferase KMT9 is crucial for proliferation and survival of lung cancer cells harboring various mutations. Small molecule inhibitors targeting KMT9 therefore should be further examined as potential milestones in modern epigenetic lung cancer therapy. Additional file 5. Certificate NCI-H2087. Results and certificate of STRprofiling and cell authentication. Additional file 6. Certificate CRL-7000. Results and certificate of STRprofiling and cell authentication. "HS 1.Lu" is a synonym of CRL-7000. Additional file 7. Certificate IMR-90. Results and certificate of STR-profiling and cell authentication. Additional file 8. KMT9α expression is significantly increased in stage 1 and 3 lung adenocarcinoma from the TCGA cohort. a TCGA lung adenocarcinoma samples were divided according to stage and the KMT9α expression analyzed. Data represent interquartile range including minimum, 25th percentile, median, 75th percentile and maximum values. Significance was accessed by t test. b TCGA lung adenocarcinoma samples were divided according to histopathologic subtypes and the KMT9α expression analyzed. Data represent interquartile range including minimum, 25th percentile, median, 75th percentile and maximum values. Significance was accessed by t test. Subgroups with p-value < 0.05 when compared to normal are marked by "*". Abbreviations NSCLC: Non-small cell lung cancer; SCLC: Small cell lung cancer; SSC: Side scatter; FSC: Forward scatter; RNA-Seq: RNA sequencing; qRT-PCR: Quantitative real-time polymerase chain reaction. of Cologne,
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