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A Taguchi Design of Experiments Approach for Untargeted Metabolomics Sample Preparation Optimization

ABSTRACT: Metabolomics commonly uses analytical techniques such as nuclear magnetic resonance (NMR) and liquid chromatography coupled to mass spectrometry (LC-MS) to quantify and identify metabolites associated with biological variation. Metabolome coverage from non-targeted LC-MS studies relies heavily on the pre-analytical protocols (e.g., homogenization and extraction) used. Chosen protocols impact which metabolites are successfully measured, which in turn impacts biological conclusions. Different homogenization and extraction methods produce significant variability in metabolome coverage, sample reproducibility, and extraction efficiency. Herein we describe an efficient Taguchi method design of experiments (DOE) approach to optimize the extraction solvent and volume, extraction time, and LC reconstitution solvent for a sequential non-polar and polar Caenorhabditis elegans extraction. DOE is rarely used in metabolomics yet provides a systematic approach for optimizing sample preparation while simultaneously decreasing the number of experiments required to obtain high-quality data.

ORGANISM(S): Caenorhabditis Elegans C. Elegans

TISSUE(S): Worms

SUBMITTER: Brianna Garcia

PROVIDER: ST002046 | MetabolomicsWorkbench | Thu Dec 16 00:00:00 GMT 2021

REPOSITORIES: MetabolomicsWorkbench

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Project description:Understanding the interplay of the proteome and the metabolome aids in understanding cellular phenotypes. To enable more robust inferences from such multi-omics analyses, combining proteomic and metabolomic datasets from the same sample provides major benefits by reducing technical variation between extracts during the pre-analytical phase, decreasing sample variation due to varying cellular content between aliquots, and limiting the required sample amount. We evaluated the advantages, practicality and feasibility of a single-sample workflow for combined proteome and metabolome analysis. In the workflow, termed MTBE-SP3, we combined a fully automated protein lysis and extraction protocol (autoSP3) with a semi-automated biphasic 75% EtOH/MTBE extraction for quantification of polar/non-polar metabolites. Additionally, we compared the resulting proteome of various biological matrices (FFPE tissue, fresh-frozen tissue, plasma, serum and cells) between autoSP3 and MTBE-SP3. Our analysis revealed that the single-sample workflow provided similar results to those obtained from autoSP3 alone, with an 85-98% overlap of proteins detected across the different biological matrices. Additionally, it provides distinct advantages by decreasing (tissue) heterogeneity by retrieving metabolomics and proteomic data from the identical biological material, and limiting the total amount of required material. Lastly, we applied MTBE-SP3 to a lung adenocarcinoma cohort of 10 patients. Integrating the metabolic and proteomic alterations between tumour and non-tumour adjacent tissue yielded consistent data independent of the method used. This revealed mitochondrial dysfunction in tumor tissue through deregulation of OGDH, SDH family enzymes and PKM. In summary, MTBE-SP3 enables the facile and confident parallel measurement of proteins and metabolites obtained from the same sample. This workflow is particularly applicable for studies with limited sample availability and offers the potential to enhance the integration of metabolomic and proteomic datasets.

Project description:The continuing ‘desire’ in obtaining more quantitative and detailed information from cellular proteomics experiments in regards to proteome coverage and protein modifications asks for a systematic investigation of the protein extraction and digestion protocols, in particular when working with unicellular organisms with a strong cell wall such as the model yeast S. cerevisiae. The selection of a suitable sample preparation workflow is crucial to obtain in-depth proteome coverage, as the use of certain sample preparation protocols may bias the protein identification or induce (unexpected) peptide modifications. Here, we made an extensive comparison of preparation workflows commonly applied to S. cerevisiae. Workflows were compared on the basis of identified MS/MS spectra, peptide sequences and number and type of modifications using both restricted (Peaks) and unrestricted (TagGraph) database search approaches. The proteome coverage was mainly affected by the sample collection approach, while it was maximized using a FASP. Extensive reagent specific peptide modifications were detected when using formic acid, but also when using acetone. Such artefacts split the analyte mass signals and generate additional chemical noise that may also elute differently compared to the native peptide. The use of both an unrestricted and restricted database search increased identification rates significantly and resulted in the identification of approximately 70% of the MS2 spectra for the best protocol. The unidentified spectra were assessed by their de novo sequencing score. This confirmed that those spectra consisted by a majority of very low quality spectra, insufficient to match to database sequences. However, a small fraction of the unidentified spectra showed high quality, which presumably derive from unknown sequence variants not present in the database. This study demonstrates the high importance of the sample preparation workflow and the obtained results will guide researchers in the field to optimize sample preparation procedures.

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A Taguchi Design of Experiments Approach for Untargeted Metabolomics Sample Preparation Optimization

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