Increasing the throughput of sensitive proteomics by plexDIA

Derks, Jason; Leduc, Andrew; Wallmann, Georg; Huffman, R. Gray; Willetts, Matthew; Khan, Saad; Specht, Harrison; Ralser, Markus; Demichev, Vadim; Slavov, Nikolai

doi:10.1038/s41587-022-01389-w

Cited by 169 publications

(313 citation statements)

References 69 publications

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“…2. Supplemental software 2 provides 4 predefined layouts optimized for different experimental designs, including label-free MS 23 , SCoPE2 14 , and plexDIA 24 .…”

Section: Results Npop Enables Flexible Droplet Sample Preparationmentioning

confidence: 99%

“…Before injecting samples for analysis, wells can be rehydrated with 0.1 % formic acid (which may contain isobaric carrier diluted to the desired concentration), resealed with foil, and placed into a compatible autosampler for automated sample injection and MS analysis, Taking advantage of the flexibility afforded by nPOP, we quantified proteins with two different methods, one performing quantification at MS1 level and the other at MS2 level. Specifically, using nPOP we prepared multiplexed single-cell samples for data independent acquisition by plex-DIA 24,26 and for prioritized data acquisition by pSCoPE 27 , Fig. 2.…”

Section: Results Npop Enables Flexible Droplet Sample Preparationmentioning

confidence: 99%

“…2e. To validate this observation, we prepared an additional biological replicate, analyzed by an orthogonal mass spectrometry quantitation method, plexDIA, which performs precursor quantitation at the MS1 level 24 . When projecting melanoma cells analyzed by plexDIA into a low dimensional space via PCA, we similarly noticed two distinct clusters separated on PC1, Extended Data Fig.…”

Section: Results Npop Enables Flexible Droplet Sample Preparationmentioning

confidence: 99%

“…Important biological observations, such as the gradient of protein abundance in non-primed melamona cells, were demonstrated by two very different MS methodologies. This demonstration was crucially enabled by the flexibility of nPOP sample preparation tow work with both 18-plex isobaric mass tags 27,35 and 3-plex non-isobaric mass and plexDIA 24,26 . This flexibility stems from the ease of computationally programming different droplet layouts and workflows, Fig.…”

Section: Discussionmentioning

confidence: 99%

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Exploring functional protein covariation across single cells using nPOP

Leduc

Huffman

Slavov

2021

Preprint

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Many biological functions, such as the cell division cycle, are intrinsically single-cell processes regulated in part by protein synthesis and degradation. Investigating such processes has motivated the development of single-cell mass spectrometry (MS) proteomics. To further advance single-cell MS proteomics, we developed a method for automated nano-ProteOmic sample Preparation (nPOP). nPOP uses piezo acoustic dispensing to isolate individual cells in 300 picoliter volumes and performs all subsequent preparation steps in small droplets on a hydrophobic slide. This allows massively parallel sample preparation, including lysing, digesting, and labeling individual cells in volumes below 20 nl. Single-cell protein analysis using nPOP classified cells by cell type and by cell cycle phase. Furthermore, the data allowed us to quantify the covariation between cell cycle protein markers and thousands of proteins. Based on this covariation, we identify cell cycle associated proteins and functions that are shared across cell types and those that differ between cell types.

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“…2. Supplemental software 2 provides 4 predefined layouts optimized for different experimental designs, including label-free MS 23 , SCoPE2 14 , and plexDIA 24 .…”

Section: Results Npop Enables Flexible Droplet Sample Preparationmentioning

confidence: 99%

Section: Results Npop Enables Flexible Droplet Sample Preparationmentioning

confidence: 99%

Section: Results Npop Enables Flexible Droplet Sample Preparationmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Exploring functional protein covariation across single cells using nPOP

Leduc

Huffman

Slavov

2021

Preprint

Self Cite

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“…3 However, recent advances in the field, employing many clever methods and advanced sample preparation techniques, greatly improved the capability of single-cell proteomics, thus narrowing the gap to other omics techniques. [4][5][6][7][8][9][10] The unparalleled advantages of single-cell proteomics lay within its ability to measure protein directly, making the identification of subtle differences in protein activation states and post-translational events possible. With better sensitivity and higher throughput, it is reasonable to expect singlecell proteomics will help us to better capture rare but important cellular events in the foreseeable future.…”

Section: Introductionmentioning

confidence: 99%

Automated container-less cell processing method for single-cell proteomics

Matsumoto

Shao

Bogosavljevic

et al. 2022

Preprint

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Single-cell genomics and transcriptomics studies enabled us to characterize cell heterogeneity in various tissues, which helped us to better understand the biological system and disease progression. Single-cell proteomics, which directly measures the protein expression level, has the potential to further enhance our knowledge by providing not only a more direct measurement but also crucial information cannot be captured by genomics or transcriptomics study, such as protein activation states and post-translation modification events. One of the main challenges of single-cell proteomics is the large sample loss during sample preparation, which is largely unavoidable using standard proteomics protocols. Protein and peptide loss to the container surface is a well-known phenomenon but often overlooked in larger-scale (>1 microgram) proteomics experiments. When it comes to single-cell proteomics with only picograms of protein samples, this loss becomes non-negligible and often dictates the outcomes of the experiment. More importantly, sample processing through multiple pipette tips and containers often introduces random errors, which undermine the ability to detect true heterogenous cellular events. To solve these problems and further improve the throughput and reproducibility of the single-cell proteomics experiments, we developed an automated container-less cell processing platform, utilizing acoustic levitation to process cell samples in the air. Our platform automatically performs cell lysis, protein reduction, alkylation, digestion, and peptide labeling in the air, without any sample transfer step or container. The digested and labeled peptides are then directly injected into the capillary LC-MS/MS system for analysis, eliminating manual steps and conserving most of the sample materials for proteomics analysis. Our initial test shows at least 30% improvement in peptide signals over conventional methods. This process can be performed in parallel to further improve sample processing throughput.

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Controlling Pericellular Oxygen Tension in Cell Culture Reveals Distinct Breast Cancer Responses to Low Oxygen Tensions

Rogers,

Colombani,

Khan

et al. 2024

Advanced Science

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In oxygen (O2)‐controlled cell culture, an indispensable tool in biological research, it is presumed that the incubator setpoint equals the O2 tension experienced by cells (i.e., pericellular O2). However, it is discovered that physioxic (5% O2) and hypoxic (1% O2) setpoints regularly induce anoxic (0% O2) pericellular tensions in both adherent and suspension cell cultures. Electron transport chain inhibition ablates this effect, indicating that cellular O2 consumption is the driving factor. RNA‐seq analysis revealed that primary human hepatocytes cultured in physioxia experience ischemia‐reperfusion injury due to cellular O2 consumption. A reaction‐diffusion model is developed to predict pericellular O2 tension a priori, demonstrating that the effect of cellular O2 consumption has the greatest impact in smaller volume culture vessels. By controlling pericellular O2 tension in cell culture, it is found that hypoxia vs. anoxia induce distinct breast cancer transcriptomic and translational responses, including modulation of the hypoxia‐inducible factor (HIF) pathway and metabolic reprogramming. Collectively, these findings indicate that breast cancer cells respond non‐monotonically to low O2, suggesting that anoxic cell culture is not suitable for modeling hypoxia. Furthermore, it is shown that controlling atmospheric O2 tension in cell culture incubators is insufficient to regulate O2 in cell culture, thus introducing the concept of pericellular O2‐controlled cell culture.

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Increasing the throughput of sensitive proteomics by plexDIA

Cited by 169 publications

References 69 publications

Exploring functional protein covariation across single cells using nPOP

Exploring functional protein covariation across single cells using nPOP

Automated container-less cell processing method for single-cell proteomics

Controlling Pericellular Oxygen Tension in Cell Culture Reveals Distinct Breast Cancer Responses to Low Oxygen Tensions

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