Integrated proteomic and metabolomic analyses of the mitochondrial neurodegenerative disease MELAS

Uittenbogaard, Martine; Navarro, Ryan; Ahmed, Mustafa; Gropman, Andrea; Chiaramello, Anne; Hao, Ling

doi:10.1039/d1mo00416f

Cited by 11 publications

(10 citation statements)

References 55 publications

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“…The routine bottom-up proteomics workflow was conducted for contaminant-only samples, HEK cells, and mouse brain lysates as described previously. , Briefly, disulfide bonds were reduced using 5 mM Tris(2-carboxyethyl)phosphine (TCEP) for 30 min, 15 mM iodoacetamide for 30 min in dark, and 5 mM TCEP for 10 min on a ThermoMixer shaking at 1,200 rpm at 37 °C. Protein digestions were conducted using various enzymes (contaminant-only samples) and trypsin/Lys-C (HEK and mouse samples) for 18 h at 37 °C on the ThermoMixer and quenched with 10% trifluoroacetic acid until pH < 3.…”

Section: Methodsmentioning

confidence: 99%

Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

et al. 2022

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Mass spectrometry-based proteomics is constantly challenged by the presence of contaminant background signals. In particular, protein contaminants from reagents and sample handling are almost impossible to avoid. For data-dependent acquisition (DDA) proteomics, an exclusion list can be used to reduce the influence of protein contaminants. However, protein contamination has not been evaluated and is rarely addressed in data-independent acquisition (DIA). How protein contaminants influence proteomic data is also unclear. In this study, we established new protein contaminant FASTA and spectral libraries that are applicable to all proteomic workflows and evaluated the impact of protein contaminants on both DDA and DIA proteomics. We demonstrated that including our contaminant libraries can reduce false discoveries and increase protein identifications, without influencing the quantification accuracy in various proteomic software platforms. With the pressing need to standardize proteomic workflow in the research community, we highly recommend including our contaminant FASTA and spectral libraries in all bottom-up proteomic data analysis. Our contaminant libraries and a step-by-step tutorial to incorporate these libraries in various DDA and DIA data analysis platforms can be valuable resources for proteomic researchers, freely accessible at https://github.com/HaoGroup-ProtContLib.

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Section: Methodsmentioning

confidence: 99%

Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

et al. 2022

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“…The routine bottom-up proteomic workflow was conducted for contaminant-only samples, HEK cells and mouse brain lysates as described previously. 30,31 Briefly, disulfide bonds were reduced using 5 mM Tris(2-carboxylethyl)phosphine (TCEP) for 30 min, 15 mM of iodoacetamide for 30 min in dark, and 5 mM TCEP for 10 min on a ThermoMixer shaking at 1,200 rpm at 37 ºC.…”

Section: Proteomic Sample Preparationmentioning

confidence: 99%

“…Contaminant FASTA library has been widely used for DDA proteomics, but is rarely included in DIA data analysis. 26,30,37,38 Since DIA uses a much wider precursor isolation window (4-15 Da) compared to DDA (0.4-2 Da), contaminant peptides in DIA are more likely to be coeluted and co-fragmented with other peptides. If not addressed properly, contaminant peptides can cause false identifications of peptides/proteins.…”

Section: Contaminant Peptides Can Cause False Discoveries In Dia Prot...mentioning

confidence: 99%

“…The routine bottom-up proteomic workflow was conducted for contaminant-only samples, HEK cells and mouse brain lysates as described previously. 35,36 Briefly, disulfide bonds were reduced using 5 mM Tris(2-carboxylethyl)phosphine (TCEP) for 30 min, 15 mM of iodoacetamide for 30 min in dark, and 5 mM TCEP for 10 min on a ThermoMixer shaking at 1,200 rpm at 37 ºC. Protein digestions were conducted using various enzymes (contaminant-only samples) and Trypsin/Lys-C (HEK and mouse samples) for 18 hours at 37 ºC on a ThermoMixer, and quenched with 10% trifluoroacetic acid until pH < 3.…”

Section: Proteomic Sample Preparationmentioning

confidence: 99%

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Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

Frankenfield

Ahmed

et al. 2022

Preprint

Self Cite

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Mass spectrometry-based proteomics is constantly challenged by the presence of contaminant background signals. In particular, protein contaminants from reagents and sample handling are often abundant and impossible to avoid. For data-dependent acquisition (DDA) proteomics, exclusion list can be used to reduce the influence of protein contaminants. However, protein contamination has not been evaluated and is rarely addressed in data-independent acquisition (DIA). How protein contaminants influence proteomics data is also unclear. In this study, we established the protein contaminant FASTA and spectral libraries that are applicable to all proteomic workflows and evaluated the impact of protein contaminants on both DDA and DIA proteomics. We demonstrated that including our contaminant libraries can reduce false discoveries and increase protein identifications, without influencing the quantification accuracy in various proteomic software platforms. With the pressing need to standardize proteomic workflow in the research community, we highly recommend including our contaminant FASTA or spectral libraries in all bottom-up proteomics workflow. Our contaminant libraries and a step-by-step tutorial to incorporate these libraries in different DDA and DIA data analysis platforms can be a valuable resource for proteomics researchers, which are freely accessible at https://github.com/HaoGroup-ProtContLib.

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“…Therefore, integrated DIA and DDA acquisition modes, which could produce complementary mass spectrometry information from each other, were applied for the comprehensive characterization of compounds from herbal medicines. 10 Moreover, considering that natural herbal medicines oen contained the identical structures of isomers with similar chromatographic retention behaviors that could hardly be separated or detected by common modes of the instrument, the ion mobility model was introduced as an additional dimension of ions separation based on their charge state, size and shape. 11 The exploitation of mass spectrometry data in different scan modes offers the opportunity to analyze chemical components from multiple perspectives.…”

Section: Introductionmentioning

confidence: 99%

Combining multiple acquisition modes and computational data annotation for structural characterization in traditional Chinese medicine: Miao Nationality medicine Qijiao Shengbai Capsule as a case study

Zhang

Dou

et al. 2022

RSC Adv.

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Integrated proteomic and metabolomic analyses of the mitochondrial neurodegenerative disease MELAS

Abstract: MELAS (mitochondrial encephalomyopathy, lactic acidosis, stroke-like episodes) is a progressive neurodegenerative disease caused by pathogenic mitochondrial DNA variants. The pathogenic mechanism of MELAS remains enigmatic due to the exceptional clinical...

Cited by 11 publications

References 55 publications

Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics

Combining multiple acquisition modes and computational data annotation for structural characterization in traditional Chinese medicine: Miao Nationality medicine Qijiao Shengbai Capsule as a case study

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