MegaGO: A Fast Yet Powerful Approach to Assess Functional Gene Ontology Similarity across Meta-Omics Data Sets

Verschaffelt, Pieter; Bossche, Tim Van Den; Gabriel, Wassim; Burdukiewicz, Michał; Soggiu, Alessio; Martens, Lennart; Renard, Bernhard Y.; Schiebenhoefer, Henning; Mesuere, Bart

doi:10.1021/acs.jproteome.0c00926

Cited by 11 publications

(9 citation statements)

References 28 publications

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“…We observed that the functional similarity between data sets acquired with different workflows on each sample is extremely high, and this regardless of the approach chosen. For the peptide-centric approach, we compared the Gene Ontology (GO) terms (GO domain “biological process”) provided by Unipept for each of the identified peptides with MegaGO 64 , resulting in MegaGO similarities of 0.96 or higher. Notably, 95% of the identified peptides were associated with at least one GO term.…”

Section: Resultsmentioning

confidence: 99%

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

et al. 2021

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Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

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Section: Resultsmentioning

confidence: 99%

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

et al. 2021

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“…Interestingly, there appears to be an important contribution to any observed differences from the sequence database used for identification. This is particularly evident in the protein inference step, where peptide-level degeneracy in the database becomes an important factor in the outcome of protein grouping, as already shown and discussed previously 63,64 . Overall, functional profiles of different proteomics workflows were quite similar, which is a reassuring characteristic due to the unique perspective provided by proteomics on the functional level.…”

Section: Discussionmentioning

confidence: 72%

Critical Assessment of Metaproteome Investigation (CAMPI): A Multi-Lab Comparison of Established Workflows

Bossche

Kunath

Schallert

et al. 2021

Preprint

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Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carried out the first community-driven, multi-lab comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluated the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, lab-assembled human intestinal model and a human fecal sample. We observed that variability at the peptide level was predominantly due to wet-lab workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappeared at protein group level. While differences were observed for predicted community composition, similar functional profiles were obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-lab studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

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“…Knowledge of relations between toxicity pathways may also inform the ranking and/or severity weighting. As a step in this direction, it was illustrated how derivation of the genomic RPP could be supported by approaches for assessing semantic similarities between GO terms using the web application by Verschaffelt et al (2021) as an example. Interestingly, the similarity score across the genomic RPP was dose dependent (Table 4).…”

Section: Discussionmentioning

confidence: 99%

“…Comparison of GO categories using tools for computation of similarity scores may potentially help to refine the determination of Sijk values as well as supporting parameterization of the systemic weight function, w(S), in equation (3). To illustrate this potential the web application (MegaGO) from Verschaffelt et al, (2021) was used that calculates similarity between GO terms with the relevance semantic similarity metric (Lin, 1998). The tool provides a score between 0 and 1 for each of the three GO domains, but for the present data a score for "biological process" results exclusively since this is the only domain covered.…”

Section: Refinement Of S-values and Severity Weightingmentioning

confidence: 99%

“…4. Similarity score according to the application by Verschaffelt et al, (2021) between sets of GO categories that differ in dose location with regard to log mean BMD described by the percentile range (Px-y) To address potentials for further development Table 4 presents results from comparison of GO categories using the web application from Verschaffelt et al (2021). As shown, sematic similarity across the GO terms appears to be dosedependent: i.e., as the dose separation between groups of GO terms increases the similarity score decreases.…”

Section: Altex Accepted Manuscriptmentioning

confidence: 99%

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A novel method for combining outcomes with different severities or gene-level classifications

Sand

2021

ALTEX

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Chemical risk assessment is currently based on consideration of health effects individually. The present work discusses a method for combining data by characterizing the dose-related sequence of the development of lowerto higher-order toxicological effects, or the range of bioactivity observed at genomic level, caused by a chemical/mixture. A "reference point profile" is defined as the relation between benchmark doses for considered effects (or bioactivity measures), and a standardized severity or rank score determined for these effects. For a given dose of a chemical/mixture the probability for exceeding the reference point profile can be assessed. An overall toxicological response can also be derived at the same dose by integrating contributions across all effects, with a rational for severity weighing. Conversely, dose equivalents corresponding to specified responses can be estimated. The variation in reference point profiles across chemicals suggests that joint consideration of effects under the proposed concept differentiates the consequence of chemical exposure, both at genomic and apical levels, to a higher extent compared to using a specific effect as a basis. This may help to refine development of points of departures or sets of such values describing a range of health concerns. Analysis and comparison of apical and genomic reference point profiles, as well as consideration of functional relations between gene-sets within such analyses, may aid in the transition towards a NAM-based risk assessment paradigm that to a higher degree may require methods for combination of effect data compared to relying on specific outcomes.

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MegaGO: A Fast Yet Powerful Approach to Assess Functional Gene Ontology Similarity across Meta-Omics Data Sets

Cited by 11 publications

References 28 publications

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Critical Assessment of Metaproteome Investigation (CAMPI): A Multi-Lab Comparison of Established Workflows

A novel method for combining outcomes with different severities or gene-level classifications

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