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Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry.

ABSTRACT: Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomic analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.

SUBMITTER: Gebreyesus ST

PROVIDER: S-EPMC8748772 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Streamlined Single-cell Proteomics by an Integrated Microfluidic Chip and Data-independent Acquisition Mass Spectrometry

Project description:Single-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomics analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.

2021-11-12 | PXD023325 | JPOST Repository

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics.

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Project description:Data independent acquisition (DIA) mass spectrometry is an emerging technique that offers more complete detection and quantification of peptides and proteins across multiple samples. DIA allows fragment-level quantification, which can be considered as repeated measurements of the abundance of the corresponding peptides and proteins in the downstream statistical analysis. However, few statistical approaches are available for aggregating these complex fragment-level data into peptide- or protein-level statistical summaries. In this work, we describe a software package, mapDIA, for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples. Using a comprehensive set of simulation datasets, we show that mapDIA detects differentially expressed proteins with accurate control of the false discovery rates. We also describe the analysis procedure in detail using two recently published DIA datasets generated for 14-3-3? dynamic interaction network and prostate cancer glycoproteome.The software was written in C++ language and the source code is available for free through SourceForge website http://sourceforge.net/projects/mapdia/.This article is part of a Special Issue entitled: Computational Proteomics.

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Project description:Adductomics studies are used for the detection and characterization of various chemical modifications (adducts) of nucleic acids and proteins. The advancements in liquid chromatography coupled with high-resolution tandem mass spectrometry (HRMS/MS) have resulted in efficient methods for qualitative and quantitative adductomics. We developed an HRMS-based method for the simultaneous analysis of RNA and DNA adducts in a single run and demonstrated its application using Baltic amphipods, useful sentinels of environmental disturbances, as test organisms. The novelty of this method is screening for RNA and DNA adducts by a single injection on an Orbitrap HRMS instrument using full scan and data-independent acquisition. The MS raw files were processed with an open-source program, nLossFinder, to identify and distinguish RNA and DNA adducts based on the characteristic neutral loss of ribonucleosides and 2'-deoxyribonucleosides, respectively. In the amphipods, in addition to the nearly 150 putative DNA adducts characterized earlier, we detected 60 putative RNA adducts. For the structural identification of the detected RNA adducts, the MODOMICS database was used. The identified RNA adducts included simple mono- and dimethylation and other larger functional groups on different ribonucleosides and deaminated product inosine. However, 54 of these RNA adducts are not yet structurally identified, and further work on their characterization may uncover new layers of information related to the transcriptome and help understand their biological significance. Considering the susceptibility of nucleic acids to environmental factors, including pollutants, the developed multi-adductomics methodology with further advancement has the potential to provide biomarkers for diagnostics of pollution effects in biota.

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Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry.

Project description:Physiological processes in multicellular organisms depend on the function and interactions of specialized cell types operating in context. Some of these cell types are rare and thus obtainable only in minute quantities. For example, tissue-specific stem and progenitor cells are numerically scarce, but functionally highly relevant, and fulfill critical roles in development, tissue maintenance, and disease. Whereas low numbers of cells are routinely analyzed by genomics and transcriptomics, corresponding proteomic analyses have so far not been possible due to methodological limitations. Here we describe a sensitive and robust quantitative technique based on data-independent acquisition mass spectrometry. We quantified the proteome of sets of 25,000 human hematopoietic stem/multipotent progenitor cells (HSC/MPP) and three committed progenitor cell subpopulations of the myeloid differentiation pathway (common myeloid progenitors, megakaryocyte-erythrocyte progenitors, and granulocyte-macrophage progenitors), isolated by fluorescence-activated cell sorting from five healthy donors. On average, 5,851 protein groups were identified per sample. A subset of 4,131 stringently filtered protein groups was quantitatively compared across the 20 samples, defining unique signatures for each subpopulation. A comparison of proteomic and transcriptomic profiles indicated HSC/MPP-specific divergent regulation of biochemical functions such as telomerase maintenance and quiescence-inducing enzymes, including isocitrate dehydrogenases. These are essential for maintaining stemness and were detected at proteome, but not transcriptome, level. The method is equally applicable to almost any rare cell type, including healthy and cancer stem cells or physiologically and pathologically infiltrating cell populations. It thus provides essential new information toward the detailed biochemical understanding of cell development and functionality in health and disease.

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Project description:Advances in tandem mass spectrometry (MS/MS) acquisition rate have steadily led to increased performance in shotgun proteomics experiments. To that end, contemporary mass spectrometers are outfitted with multiple analyzers allowing for the simultaneous collection of survey (MS1) and MS/MS spectra. In the latest generation Orbitrap hybrid, MS/MS scans can be acquired at a high rate using the dual cell linear ion trap analyzer, all while the next precursor is being dissociated in a collision cell and a MS1 scan is occurring in the Orbitrap. Often overlooked in these experiments is that the ion trap scan duration is highly variable and dependent upon precursor mass. Here, we examine the use of various static mass-to-charge ratio scan ranges for ion trap MS/MS acquisition and determine performance relative to conventional dynamic mass-to-charge ratio range scanning. We demonstrate that a fixed mass-to-charge ratio scan range can generate 12% more MS/MS scans and more unique peptide identifications as compared to the standard dynamic approach, respectively.

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Comparative proteomics analysis of Tibetan hull-less barley under osmotic stress via data-independent acquisition mass spectrometry.

Project description:BACKGROUND:Tibetan hull-less barley (Hordeum vulgare L. var. nudum) is one of the primary crops cultivated in the mountains of Tibet and encounters low temperature, high salinity, and drought. Specifically, drought is one of the major abiotic stresses that affect and limit Tibetan barley growth. Osmotic stress is often simultaneously accompanied by drought conditions. Thus, to improve crop yield, it is critical to explore the molecular mechanism governing the responses of hull-less barley to osmotic/drought stress conditions. FINDINGS:In this study, we used quantitative proteomics by data-independent acquisition mass spectrometry to investigate protein abundance changes in tolerant (XL) and sensitive (DQ) cultivars. A total of 6,921 proteins were identified and quantified in all samples. Two distinct strategies based on pairwise and time-course comparisons were utilized in the comprehensive analysis of differentially abundant proteins. Further functional analysis of differentially abundant proteins revealed that some hormone metabolism-associated and phytohormone abscisic acid-induced genes are primarily affected by osmotic stress. Enhanced regulation of reactive oxygen species (may promote the tolerance of hull-less barley under osmotic stress. Moreover, we found that some regulators, such as GRF, PR10, MAPK, and AMPK, were centrally positioned in the gene regulatory network, suggesting that they may have a dominant role in the osmotic stress response of Tibetan barley. CONCLUSIONS:Our findings highlight a subset of proteins and processes that are involved in the alleviation of osmotic stress. In addition, this study provides a large-scale and multidimensional proteomic data resource for the further investigation and improvement of osmotic/drought stress tolerance in hull-less barley or other plant species.

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Integrated microfluidic device for automated single cell analysis using electrophoretic separation and electrospray ionization mass spectrometry.

Project description:A microfabricated fluidic device was developed for the automated real-time analysis of individual cells using capillary electrophoresis (CE) and electrospray ionization-mass spectrometry (ESI-MS). The microfluidic structure incorporates a means for rapid lysis of single cells within a free solution electrophoresis channel, where cellular constituents were separated, and an integrated electrospray emitter for ionization of separated components. The eluent was characterized using mass spectrometry. Human erythrocytes were used as a model system for this study. In this monolithically integrated device, cell lysis occurs at a channel intersection using a combination of rapid buffer exchange and an increase in electric field strength. An electroosmotic pump is incorporated at the end of the electrophoretic separation channel to direct eluent to the integrated electrospray emitter. The dissociated heme group and the alpha and beta subunits of hemoglobin from individual erythrocytes were detected as cells continuously flowed through the device. The average analysis throughput was approximately 12 cells per minute, demonstrating the potential of this method for high-throughput single cell analysis.

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