MSnbase, Efficient and Elegant R-Based Processing and Visualization of Raw Mass Spectrometry Data

Gatto, Laurent; Gibb, Sebastian; Rainer, Johannes Michael

doi:10.1021/acs.jproteome.0c00313

Cited by 82 publications

(66 citation statements)

References 27 publications

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“…The raw data was first converted to mzXML format using MSConvert GUI [ 25 ]. Converted LC-MS data files were read into R (v4.0.2) to be visualised and processed by the MSnbase package [ 26 , 27 ]. Chromatograms of each oligonucleotide strand were manually evaluated to determine their elution range (retention time range of the chromatogram peak) and detected charge states ( Table 1 ).…”

Section: Methodsmentioning

confidence: 99%

A Compositional Model to Predict the Aggregated Isotope Distribution for Average DNA and RNA Oligonucleotides

et al. 2021

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Structural modifications of DNA and RNA molecules play a pivotal role in epigenetic and posttranscriptional regulation. To characterise these modifications, more and more MS and MS/MS- based tools for the analysis of nucleic acids are being developed. To identify an oligonucleotide in a mass spectrum, it is useful to compare the obtained isotope pattern of the molecule of interest to the one that is theoretically expected based on its elemental composition. However, this is not straightforward when the identity of the molecule under investigation is unknown. Here, we present a modelling approach for the prediction of the aggregated isotope distribution of an average DNA or RNA molecule when a particular (monoisotopic) mass is available. For this purpose, a theoretical database of all possible DNA/RNA oligonucleotides up to a mass of 25 kDa is created, and the aggregated isotope distribution for the entire database of oligonucleotides is generated using the BRAIN algorithm. Since this isotope information is compositional in nature, the modelling method is based on the additive log-ratio analysis of Aitchison. As a result, a univariate weighted polynomial regression model of order 10 is fitted to predict the first 20 isotope peaks for DNA and RNA molecules. The performance of the prediction model is assessed by using a mean squared error approach and a modified Pearson’s χ² goodness-of-fit measure on experimental data. Our analysis has indicated that the variability in spectral accuracy contributed more to the errors than the approximation of the theoretical isotope distribution by our proposed average DNA/RNA model. The prediction model is implemented as an online tool. An R function can be downloaded to incorporate the method in custom analysis workflows to process mass spectral data.

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Section: Methodsmentioning

confidence: 99%

A Compositional Model to Predict the Aggregated Isotope Distribution for Average DNA and RNA Oligonucleotides

et al. 2021

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“…Dimensionality reduction. Principal component analysis was performed using Perseus or R. t-distributed stochastic neighbour embedding (t-SNE) was performed using the R packages MSnbase (version 2.15.7) 93 and pRoloc (version 1.30.0) 94 , with the perplexity parameter tuned to 50. To generate a curated subcellular marker protein set for dataset annotation, the validated mouse marker protein set from pRoloc was filtered to exclude (i) non-nuclear marker proteins for which there was evidence for nuclear localisation in Gene Ontology, UniProt or Cell Atlas, (ii) nuclear marker proteins for which there was evidence for non-nuclear localisation in Gene Ontology, UniProt or Cell Atlas and (iii) marker proteins that did not have supporting Cell Atlas evidence with supported or enhanced reliability 37 .…”

Section: Ms Data Analysismentioning

confidence: 99%

Characterisation of a nucleo-adhesome

Byron

Griffith

Herrero

et al. 2021

Preprint

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In addition to central functions in cell adhesion signalling, integrin-associated proteins have wider roles at sites distal to adhesion receptors. In experimentally defined adhesomes, we noticed that there is clear enrichment of proteins that localise to the nucleus, and conversely, we now report that nuclear proteomes contain a class of adhesome components that localise to the nucleus. We here defined a nucleo-adhesome, providing experimental evidence for a remarkable scale of nuclear localisation of adhesion proteins, establishing a framework for interrogating nuclear adhesion protein functions. In adding to nuclear FAK's known roles in regulating transcription, we now show that nuclear FAK regulates expression of many adhesion-related proteins that localise to the nucleus and that nuclear FAK binds to the adhesome component and nuclear protein Hic-5. FAK and Hic-5 work together in the nucleus, co-regulating a subset of genes transcriptionally. We describe the first nucleo-adhesome using a squamous cancer cell model, and demonstrate the new principle that there are nuclear adhesion protein subcomplexes that cooperate to control transcription.

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“…Integration of the mass spectrometry and genomic sequences was achieved through R scripts and several packages including MSnbase (44) and Open Babel (45).…”

Section: Rippsmentioning

confidence: 99%

Genome-guided discovery of natural products through multiplexed low coverage whole-genome sequencing of soil Actinomycetes on Oxford Nanopore Flongle

Rajwani

Ohlemacher

Zhao

et al. 2021

Preprint

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Genome-mining is an important tool for discovery of new natural products; however, the number of publicly available genomes for natural product-rich microbes such as Actinomycetes, relative to human pathogens with smaller genomes, is small. To obtain contiguous DNA assemblies and identify large (ca. 10 to greater than 100 Kb) biosynthetic gene clusters (BGCs) with high-GC (>70%) and -repeat content, it is necessary to use long-read sequencing methods when sequencing Actinomycete genomes. One of the hurdles to long-read sequencing is the higher cost. In the current study, we assessed Flongle, a recently launched platform by Oxford Nanopore Technologies, as a low-cost DNA sequencing option to obtain contiguous DNA assemblies and analyze BGCs. To make the workflow more cost-effective, we multiplexed up to four samples in a single Flongle sequencing experiment while expecting low-sequencing coverage per sample. We hypothesized that contiguous DNA assemblies might enable analysis of BGCs even at low sequencing depth. To assess the value of these assemblies, we collected high-resolution mass-spectrometry data and conducted a multi-omics analysis to connect BGCs to secondary metabolites. In total, we assembled genomes for 20 distinct strains across seven sequencing experiments. In each experiment, 50% of the bases were in reads longer than 10 Kb, which facilitated the assembly of reads into contigs with an average N50 value of 3.5 Mb. The programs antiSMASH and PRISM predicted 629 and 295 BGCs, respectively. We connected BGCs to metabolites for N,N-dimethyl cyclic-ditryptophan, a novel lassopeptide and three known Actinomycete-associated siderophores, namely mirubactin, heterobactin and salinichelin.

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MSnbase, Efficient and Elegant R-Based Processing and Visualization of Raw Mass Spectrometry Data

Cited by 82 publications

References 27 publications

A Compositional Model to Predict the Aggregated Isotope Distribution for Average DNA and RNA Oligonucleotides

A Compositional Model to Predict the Aggregated Isotope Distribution for Average DNA and RNA Oligonucleotides

Characterisation of a nucleo-adhesome

Genome-guided discovery of natural products through multiplexed low coverage whole-genome sequencing of soil Actinomycetes on Oxford Nanopore Flongle

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