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DirectMS1Quant: ultrafast quantitative proteomics with MS/MS-free mass spectrometry. Part 1/2

ABSTRACT: Recently, we presented the DirectMS1 method of ultrafast proteome-wide analysis based on minute-long LC gradients and MS1-only mass spectra acquisition. Currently, the method provides the depth of human cell proteome coverage of 2500 proteins at 1% false discovery rate (FDR) when using 5-min LC gradients and 7.3 min runtime in total. While the standard MS/MS approaches provide 4000 to 5000 protein identifications within a couple of hours of instrumentation time, we advocate here that the higher number of identified proteins does not always translate into better quantitation quality of the proteome analysis. To further elaborate on this issue we performed one-by-one comparison of quantitation results obtained using DirectMS1 with three most popular MS/MS-based proteomic methods: label-free quantification (LFQ) and tandem mass tag (TMT) -based data dependent acquisition (DDA), and data independent acquisition (DIA). For the comparison we performed a series of proteome-wide analysis of well-characterized (ground truth) and real world biological samples, including a mix of UPS1 proteins spiked at different concentrations into E. coli digest used as a background and a set of glioblastoma cell lines. MS1-only data was analyzed using a novel quantitation workflow called DirectMS1Quant developed in this work. The results obtained in this study demonstrated comparable quantitation efficiency of 5 min DirectMS1 with both TMT and DIA methods utilizing 10 to 20-fold longer instrumentation time.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

TISSUE(S): Cell Culture

SUBMITTER: Mark Ivanov

LAB HEAD: Mikhail V. Gorshkov

PROVIDER: PXD033350 | Pride | 2023-08-25

REPOSITORIES: Pride

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			Action	DRS
	20211102-1627_LUM2_1000455_FKJ_JB_Ecoli_UPS_1_01.raw	Raw
	20211102-1636_LUM2_1000456_FKJ_JB_Ecoli_UPS_1_02.raw	Raw
	20211102-1645_LUM2_1000457_FKJ_JB_Ecoli_UPS_1_03.raw	Raw
	20211102-1704_LUM2_1000459_FKJ_JB_Ecoli_UPS_8_01.raw	Raw
	20211102-1713_LUM2_1000460_FKJ_JB_Ecoli_UPS_8_02.raw	Raw

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Project description:The sensitivity of single-cell proteomics (SCP) has increased dramatically in recent years due to advances in experimental design, sample preparation, separations and mass spectrometry instrumentation. However, further increasing the sensitivity of SCP methods and instrumentation will enable the study of proteins within single cells that are expressed at copy numbers too small to be measured by current methods. Here we further increase SCP sensitivity by combining efficient nanoPOTS sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to extend the achievable proteome coverage for single cells to >3,000 for single-cell data analyses. WWA is based on data-dependent acquisition (DDA) but employs larger precursor isolation windows to intentionally co-isolate and co-fragment additional precursors along with the selected precursor. The resulting chimeric MS2 spectra are then resolved using the CHIMERYS search engine within Proteome Discoverer 3.0. Compared to standard DDA workflows, WWA employing isolation windows of 8-12 Th increases peptide and proteome coverage by ~28% and ~39%, respectively. For a 40 min LC gradient operated at ~15 nL/min, we identified an average of 2,150 proteins per single-cell-sized aliquots of protein digest directly from MS2 spectra, which increased to an average 3,524 proteins including proteins identified with MS1-level feature matching. Reducing the active gradient to 20 min resulted in only a 10% decrease in proteome coverage. We also compared performance of WWA with DIA underperformed relative to WWA in terms of proteome coverage, especially with faster separations. Average proteome coverage for single HeLa and K562 cells was respectively 1,758 and 1,642 based on MS2 identifications with 1% false discovery rate and 3042 and 2891 with MS1 feature matching. As such, WWA combined with efficient sample preparation and rapid separations extends the depths of the proteome that can be studied at the single-cell level.

Project description:We highlight the leap in performance made possible with new instrumentation in the Thermo Scientific Orbitrap Astral™ mass spectrometer. Integrated alongside a high-resolution accurate mass (HRAM) Orbitrap analyzer, the instrument introduces a fast-switching quadrupole mass filter congruent with downstream speeds of ion detection, a dual-pressure ion processor cell which fragments ions in the high-pressure cell before they are moved to the low-pressure cell for further accumulation and orthogonal extraction to the Astral analyzer, and a high dynamic range detector. Altogether, ions can be manipulated in five stages of the MS at once (Orbitrap, ion routing multipole, two ion processor stages, Astral analyzer), allowing for a high degree of parallelization which enables MS/MS scan speeds of 200 Hz while HRAM MS1 full scans are synchronously acquired in the Orbitrap analyzer. To provide such fast scan speeds, the Astral analyzer is capable of single-ion detection sensitivity like a linear ion trap, all while enabling resolving powers of 80,000 at m/z 524. Here, in triplicate 7-min microflow active LC gradients on the Orbitrap Astral MS, we report 7,852 protein groups from 94,267 peptides on average. When employing 15-, 30-, and 60-min active, nano-LC gradients, triplicate experiments yield an average of 9,831, 10,411, and 10,645 unique protein groups from 195,612, 234,406, and 245,754 unique peptides, respectively. These nanoflow methods delivered a median sequence coverage of 38%, 42.4% and 44.4% across identified proteins for each respective gradient length. Our 30-min method delivered approximately 347 proteins per minute. Finally, we applied our 30-min active gradient method to analyze a CRISPR-Cas9 knockout (KO) of the mitochondrial gene MGME1 in human HAP1 cells. There, we quantified an average of 10,353 proteins across three technical replicates and find 449 significantly up- or down-regulated proteins relative to wild-type (WT) HAP1 proteins. Proteins from the same sample quantified using a 61-min active gradient Orbitrap Ascend DIA method show strong fold-change correlations to and gene ontology (GO) term agreement with our results.Building upon the immense progress of the mass spectrometry and proteomics communities of the past ten years, here we report alongside other recent works, that the one-hour human proteome is now within reach.

Project description:Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis. </br></br> Serum metabolome of 40 age-related macular degeneration patients and 20 control samples was analyzed using untargeted mass spectrometry. We used data dependent acquisition data to build a MS/MS spectral assay library for more than 1,000 compounds and performed targeted extraction of MS2 ion chromatograms from data independent acquisition analysis.

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DirectMS1Quant: ultrafast quantitative proteomics with MS/MS-free mass spectrometry. Part 1/2

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