Sample Size-Comparable Spectral Library Enhances Data-Independent Acquisition-Based Proteome Coverage of Low-Input Cells

Siyal, Asad Ali; Chen, Eric Sheng-Wen; Chan, Hsin-Ju; Kitata, Reta Birhanu; Yang, Jhih‐Ci; Tu, Hsiung‐Lin; Chen, Yu‐Ju

doi:10.1021/acs.analchem.1c03477

Cited by 19 publications

(21 citation statements)

References 23 publications

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“…However, the higher input libraries almost doubled the number of peptide detections versus directDIA. Our findings confirm previous reports 59…”

Section: Improvement Of Scp-ms On Lit-dia By Searching Against Chroma...supporting

confidence: 94%

Optimizing linear ion trap data independent acquisition towards single cell proteomics

Phlairaharn

Krismer

et al. 2023

Preprint

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A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

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“…However, the higher input libraries almost doubled the number of peptide detections versus directDIA. Our findings confirm previous reports 59…”

Section: Improvement Of Scp-ms On Lit-dia By Searching Against Chroma...supporting

confidence: 94%

Optimizing linear ion trap data independent acquisition towards single cell proteomics

Phlairaharn

Krismer

et al. 2023

Preprint

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“…Brunner et al included a similar platform during their recent demonstration of advances in instrument development to analyze single-cell proteomes on a trapped ion mobility mass spectrometer with diaPASEF . Currently, most single-cell proteomics and low-input proteomics studies were performed on an orbitrap mass analyzer instrument ,− or a time-of-flight instrument. ,, Linear ion traps stand as an attractive alternative mass analyzer to orbitraps for low-input applications in mass spectrometry-based proteomics thanks to their increased sensitivity and efficient scanning speed. To enhance the results of data acquisition for low-input quantitative proteomics experiments, data-independent acquisition (DIA) is an attractive approach, as precursor ions are fragmented and acquired independently from their intensity, which makes this acquisition method less biased and reduces missing values compared to data-dependent acquisition (DDA)…”

Section: Introductionmentioning

confidence: 99%

High Sensitivity Limited Material Proteomics Empowered by Data-Independent Acquisition on Linear Ion Traps

et al. 2022

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In recent years, the concept of cell heterogeneity in biology has gained increasing attention, concomitant with a push toward technologies capable of resolving such biological complexity at the molecular level. For single-cell proteomics using Mass Spectrometry (scMS) and low-input proteomics experiments, the sensitivity of an orbitrap mass analyzer can sometimes be limiting. Therefore, low-input proteomics and scMS could benefit from linear ion traps, which provide faster scanning speeds and higher sensitivity than an orbitrap mass analyzer, however at the cost of resolution. We optimized an acquisition method that combines the orbitrap and linear ion trap, as implemented on a tribrid instrument, while taking advantage of the high-field asymmetric waveform ion mobility spectrometry (FAIMS) pro interface, with a prime focus on low-input applications. First, we compared the performance of orbitrap-versus linear ion trap mass analyzers. Subsequently, we optimized critical method parameters for low-input measurement by data-independent acquisition on the linear ion trap mass analyzer. We conclude that linear ion traps mass analyzers combined with FAIMS and Whisper flow chromatography are well-tailored for low-input proteomics experiments, and can simultaneously increase the throughput and sensitivity of large-scale proteomics experiments where limited material is available, such as clinical samples and cellular subpopulations.

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“…We found that 120-min LC gradient was more suitable for peptide injection amount > 2 ng (~ 10 PACCs), whereas 15-min LC gradient produced was more appropriate for the injection amount < 2 ng (~ 10 PACCs). By applying and investigating directDIA search method using different co-searching groups (i.e., internal libraries), we observed approximately a four-fold difference between the internal library size and total number of detected precursors of a DIA raw file produced the highest protein identification rate with good reproducibility [ 35 ]. Of note, 1500–3000 proteins were identified from 10 to 140 mammalian cells (equaled to 0.5–7 ng of peptides) by using narrow-bore columns (i.d.…”

Section: Discussionmentioning

confidence: 99%

Optimized data-independent acquisition approach for proteomic analysis at single-cell level

et al. 2022

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Background Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. Methods We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. Results We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. Conclusions Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

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Sample Size-Comparable Spectral Library Enhances Data-Independent Acquisition-Based Proteome Coverage of Low-Input Cells

Cited by 19 publications

References 23 publications

Optimizing linear ion trap data independent acquisition towards single cell proteomics

Optimizing linear ion trap data independent acquisition towards single cell proteomics

High Sensitivity Limited Material Proteomics Empowered by Data-Independent Acquisition on Linear Ion Traps

Optimized data-independent acquisition approach for proteomic analysis at single-cell level

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