Nanoproteomics comes of age

Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics

Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.

SPPUSM: An MS/MS spectra merging strategy for improved low-input and single-cell proteome identification

Single and rare cell analysis provides unique insights into the investigation of biological processes and disease progress by resolving the cellular heterogeneity that is masked by bulk measurements. Although many efforts have been made, the techniques used to measure the proteome in trace amounts of samples or in single cells still lag behind those for DNA and RNA due to the inherent non-amplifiable nature of proteins and the sensitivity limitation of current mass spectrometry. Here, we report an MS/MS spectra merging strategy termed SPPUSM (same precursor-produced unidentified spectra merging) for improved low-input and single-cell proteome data analysis. In this method, all the unidentified MS/MS spectra from multiple test files are first extracted. Then, the corresponding MS/MS spectra produced by the same precursor ion from different files are matched according to their precursor mass and retention time (RT) and are merged into one new spectrum. The newly merged spectra with more fragment ions are next searched against the database to increase the MS/MS spectra identification and proteome coverage. Further improvement can be achieved by increasing the number of test files and spectra to be merged. Up to 18.2% improvement in protein identification was achieved for 1 ng HeLa peptides by SPPUSM. Reliability evaluation by the "entrapment database" strategy using merged spectra from human and E. coli revealed a marginal error rate for the proposed method. For application in single cell proteome (SCP) study, identification enhancement of 28%-61% was achieved for proteins for different SCP data. Furthermore, a lower abundance was found for the SPPUSM-identified peptides, indicating its potential for more sensitive low sample input and SCP studies.

Data-Dependent Acquisition with Precursor Coisolation Improves Proteome Coverage and Measurement Throughput for Label-Free Single-Cell Proteomics

We combined efficient sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to quantify >3,000 proteins from single cells in rapid label-free analyses. WWA employs large isolation windows to intentionally co-isolate and co-fragment adjacent precursors along with the selected precursor. Optimized WWA increased the number of MS2-identified proteins by ≈40 % relative to standard data-dependent acquisition. For a 40-min LC gradient operated at ≈15 nL/min, we identified an average of 3,524 proteins per single-cell-sized aliquot of protein digest. Reducing the active gradient to 20 min resulted in a modest 10 % decrease in proteome coverage. Using this platform, we compared protein expression between single HeLa cells having an essential autophagy gene, atg9a, knocked out, with their isogenic WT parental line. Similar proteome coverage was observed, and 268 proteins were significantly up- or downregulated. Protein upregulation primarily related to innate immunity, vesicle trafficking and protein degradation.

Polymeric Nanoparticles and Nanogels: How Do They Interact with Proteins?

Polymeric nanomaterials, nanogels, and solid nanoparticles can be fabricated using single or double emulsion methods. These materials hold great promise for various biomedical applications due to their biocompatibility, biodegradability, and their ability to control interactions with body fluids and cells. Despite the increasing use of nanoparticles in biomedicine and the plethora of publications on the topic, the biological behavior and efficacy of polymeric nanoparticles (PNPs) have not been as extensively studied as those of other nanoparticles. The gap between the potential of PNPs and their applications can mainly be attributed to the incomplete understanding of their biological identity. Under physiological conditions, such as specific temperatures and adequate protein concentrations, PNPs become coated with a "protein corona" (PC), rendering them potent tools for proteomics studies. In this review, we initially investigate the synthesis routes and chemical composition of conventional PNPs to better comprehend how they interact with proteins. Subsequently, we comprehensively explore the effects of material and biological parameters on the interactions between nanoparticles and proteins, encompassing reactions such as hydrophobic bonding and electrostatic interactions. Moreover, we delve into recent advances in PNP-based models that can be applied to nanoproteomics, discussing the new opportunities they offer for the clinical translation of nanoparticles and early prediction of diseases. By addressing these essential aspects, we aim to shed light on the potential of polymeric nanoparticles for biomedical applications and foster further research in this critical area.

Omics and systems view of innate immune pathways

Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.

Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery

The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Chromatographic separation of peptides and proteins for characterization of proteomes

Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.

Unveiling and application of the chicken egg proteome: An overview on a two-decade achievement

Egg proteins are not only the most complete and ideal form of protein for human or embryo nutrition but also play the vital role in the food industry. Egg proteins are subjected to many potential changes under various conditions, which may further alter the nutritional value, physicochemical-properties, and bioactivities of proteins. Recent advances in our understanding of the proteome of raw egg matrix from different species and dynamic changes occurring during storage and incubation are developing rapidly. This review provides a comprehensive overview of the main characteristics of chicken egg proteome, covering all its components and applications under various conditions, such as markers detection, egg quality evaluation, genetic and biological unknown identification, and embryonic nutritional supplementation, which not only contributes to our in-depth understanding of each constituent functionality of proteome, but also provides information to increase the value to egg industry.

Gold Nanoparticles Contact with Cancer Cell: A Brief Update

The fine-tuning of the physicochemical properties of gold nanoparticles has facilitated the rapid development of multifunctional gold-based nanomaterials with diagnostic, therapeutic, and therapeutic applications. Work on gold nanoparticles is increasingly focusing on their cancer application. This review provides a summary of the main biological effects exerted by gold nanoparticles on cancer cells and highlights some critical factors involved in the interaction process (protein corona, tumor microenvironment, surface functionalization). The review also contains a brief discussion of the application of gold nanoparticles in target discovery.

New Views of Old Proteins: Clarifying the Enigmatic Proteome

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.

Digital Microfluidics Supported Microproteomics for Quantitative Proteome Analysis of Single Caenorhabditis elegans Nematodes

Miniaturization of sample preparation, including omissible manual sample handling steps, is key for reproducible nanoproteomics, as material is often restricted to only hundreds of cells or single model organisms. Here, we demonstrate a highly sensitive digital microfluidics (DMF)-based sample preparation workflow making use of single-pot solid-phase enhanced sample preparation (SP3) in combination with high-field asymmetric-waveform ion mobility spectrometry (FAIMS), and fast and sensitive ion trap detection on an Orbitrap tribrid MS system. Compared to a manual in-tube SP3-supported sample preparation, the numbers of identified peptides and proteins were markedly increased, while lower standard deviations between replicates were observed. We repeatedly identified up to 5000 proteins from single nematodes. Moreover, label-free quantification of protein changes in single Caenorhabditis elegans treated with a heat stimulus yielded 45 differentially abundant proteins when compared to the untreated control, highlighting the potential of this technology for low-input proteomics studies. LC-MS data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD033143.

Infrared Laser Ablation Microsampling for Small Volume Proteomics

Infrared (IR) laser ablation was used to remove localized tissue regions from which proteins were extracted and processed with a low volume sample preparation workflow for bottom-up proteomics by liquid chromatography tandem mass spectrometry (LC-MS/MS). A polytetrafluoroethylene (PTFE) coated glass slide with 2 mm diameter microwells was used to capture ablated rat brain tissue for in situ protein digestion with submicroliter solution volumes. The resulting peptides were analyzed with LC-MS/MS for protein identification and label-free quantification. The method was used to identify an average of 600, 1350, and 1900 proteins from ablation areas of 0.01, 0.04, and 0.1 mm², respectively, from a 50 μm thick rat brain tissue section. Differential proteomics of 0.01 mm² regions captured from cerebral cortex and corpus callosum was accomplished to demonstrate the capabilities of the approach.

Infrared Laser Ablation Microsampling with a Reflective Objective

A Schwarzschild reflective objective with a numerical aperture of 0.3 and working distance of 10 cm was used for laser ablation sampling of tissue for off-line mass spectrometry. The objective focused the laser to a diameter of 5 μm and produced 10 μm ablation spots on thin ink films and tissue sections. Rat brain tissue sections 50 μm thick were ablated in transmission geometry, and the ablated material was captured in a microcentrifuge tube containing solvent. Proteins from ablated tissue sections were quantified with a Bradford assay, which indicated that approximately 300 ng of protein was captured from a 1 mm² area of ablated tissue. Areas of tissue ranging from 0.01 to 1 mm² were ablated and captured for bottom-up proteomics. Proteins were extracted from the captured tissue and digested for liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis for peptide and protein identification.

A systematic review of the proteomic profile of in vivo acquired enamel pellicle on permanent teeth

OBJECTIVES

To provide a comprehensive review on the proteomic profile of in vivo acquired enamel pellicle (AEP) formed on permanent teeth.

DATA/SOURCES

PubMed, EMBASE (Ovid) and Web of Science databases were searched for eligible studies (up to December 2020). Studies reporting mass spectrometry-based proteomic analysis of in vivo AEP were included. Risk of bias assessment was performed. Qualitative and quantitative proteomic data were extracted, integrated, then followed by bioinformatic analysis.

STUDY SELECTION

Eleven studies were included, involving 122 systemically and dentally healthy adults from four different research groups. Pooled AEP samples from study participants were the normal practice for all included studies. A total of 257/93/108/870 non-redundant proteins were detectable from the in vivo ≤ 5 min/10-min/60-min/2-h AEP samples, respectively. Fifteen "core in vivo 2-h AEP proteins", generally associated with immune and/or inflammatory responses, were consistently identifiable from all four research groups. Eight included studies conducted relative quantitative proteomic analysis, while no statistical analysis could be undertaken due to the inherent limitation of the relative quantification in the proteomics analyses of these studies.

CONCLUSIONS

A systematic review on adult in vivo AEP proteomic profile was undertaken. The results provide a comprehensive appreciation of the AEP proteome in healthy individuals from in vivo sampling. Further studies are warranted to clarify the biological role of AEP on oral health, particularly at an individual level.

CLINICAL SIGNIFICANCE

A comprehensive appreciation of the proteomic profile of in vivo AEP in healthy individuals is essential to further understand its functions in oral health and disease. The information generated also provides insights for future studies.

Ultrasensitive NanoLC-MS of Subnanogram Protein Samples Using Second Generation Micropillar Array LC Technology with Orbitrap Exploris 480 and FAIMS PRO

In the light of the ongoing single-cell revolution, scientific disciplines are combining forces to retrieve as much relevant data as possible from trace amounts of biological material. For single-cell proteomics, this implies optimizing the entire workflow from initial cell isolation down to sample preparation, liquid chromatography (LC) separation, mass spectrometer (MS) data acquisition, and data analysis. To demonstrate the potential for single-cell and limited sample proteomics, we report on a series of benchmarking experiments where we combine LC separation on a new generation of micropillar array columns with state-of-the-art Orbitrap MS/MS detection and high-field asymmetric waveform ion mobility spectrometry (FAIMS). This dedicated limited sample column has a reduced cross section and micropillar dimensions that have been further downscaled (interpillar distance and pillar diameter by a factor of 2), resulting in improved chromatography at reduced void times. A dilution series of a HeLa tryptic digest (5-0.05 ng/μL) was used to explore the sensitivity that can be achieved. Comparative processing of the MS/MS data with Sequest HT, MS Amanda, Mascot, and SpectroMine pointed out the benefits of using Sequest HT together with INFERYS when analyzing sample amounts below 1 ng. Here, 2855 protein groups were identified from just 1 ng of HeLa tryptic digest hereby increasing detection sensitivity as compared to a previous contribution by a factor well above 10. By successfully identifying 1486 protein groups from as little as 250 pg of HeLa tryptic digest, we demonstrate outstanding sensitivity with great promise for use in limited sample proteomics workflows.

Recent technical progress in sample preparation and liquid-phase separation-mass spectrometry for proteomic analysis of mass-limited samples

Mass spectrometry (MS)-based proteomics has enabled the identification and quantification of thousands of proteins from complex proteomes in a single experiment. However, its performance for mass-limited proteome samples (e.g., single cells and tissue samples from laser capture microdissection) is still not satisfying. The development of novel proteomic methodologies with better overall sensitivity is vital. During the last several years, substantial technical progress has been achieved for the preparation and liquid-phase separation-MS characterization of mass-limited proteome samples. In this review, we summarize recent technological progress of sample preparation, liquid chromatography (LC)-MS, capillary zone electrophoresis (CZE)-MS and MS instrumentation for bottom-up proteomics of trace biological samples, highlight some exciting applications of the novel techniques for single-cell proteomics, and provide a very brief perspective about the field at the end.

Characterization of cellular oxidative stress response by stoichiometric redox proteomics

The thiol redox proteome refers to all proteins whose cysteine thiols are subjected to various redox-dependent posttranslational modifications (PTMs) including S-glutathionylation (SSG), S-nitrosylation (SNO), S-sulfenylation (SOH), and S-sulfhydration (SSH). These modifications can impact various aspects of protein function such as activity, binding, conformation, localization, and interactions with other molecules. To identify novel redox proteins in signaling and regulation, it is highly desirable to have robust redox proteomics methods that can provide global, site-specific, and stoichiometric quantification of redox PTMs. Mass spectrometry (MS)-based redox proteomics has emerged as the primary platform for broad characterization of thiol PTMs in cells and tissues. Herein, we review recent advances in MS-based redox proteomics approaches for quantitative profiling of redox PTMs at physiological or oxidative stress conditions and highlight some recent applications. Considering the relative maturity of available methods, emphasis will be on two types of modifications: 1) total oxidation (i.e., all reversible thiol modifications), the level of which represents the overall redox state, and 2) S-glutathionylation, a major form of reversible thiol oxidation. We also discuss the significance of stoichiometric measurements of thiol PTMs as well as future perspectives toward a better understanding of cellular redox regulatory networks in cells and tissues.

Deep Profiling of Microgram-Scale Proteome by Tandem Mass Tag Mass Spectrometry

Tandem mass tag (TMT)-based mass spectrometry (MS) enables deep proteomic profiling of more than 10,000 proteins in complex biological samples but requires up to 100 μg protein in starting materials during a standard analysis. Here, we present a streamlined protocol to quantify more than 9000 proteins with 0.5 μg protein per sample by 16-plex TMT coupled with two-dimensional liquid chromatography and tandem mass spectrometry (LC/LC-MS/MS). In this protocol, we optimized multiple conditions to reduce sample loss, including processing each sample in a single tube to minimize surface adsorption, increasing digestion enzymes to shorten proteolysis and function as carriers, eliminating a desalting step between digestion and TMT labeling, and developing miniaturized basic pH LC for prefractionation. By profiling 16 identical human brain tissue samples of Alzheimer's disease (AD), vascular dementia (VaD), and non-dementia controls, we directly compared this new microgram-scale protocol to the standard-scale protocol, quantifying 9116 and 10,869 proteins, respectively. Importantly, bioinformatics analysis indicated that the microgram-scale protocol had adequate sensitivity and reproducibility to detect differentially expressed proteins in disease-related pathways. Thus, this newly developed protocol is of general application for deep proteomics analysis of biological and clinical samples at sub-microgram levels.

In-Depth Mass Spectrometry-Based Single-Cell and Nanoscale Proteomics

Leukemic stem cells are highly dynamic and heterogeneous. Analysis of leukemic stem cells at the single-cell level should provide a wealth of insights that would not be possible using bulk measurements. Mass spectrometry (MS)-based proteomic workflows can quantify hundreds or thousands of proteins from a biological sample and has proven invaluable for biomedical research, but samples comprising large numbers of cells are typically required due to limited sensitivity. Recent developments in sample processing, chromatographic separations, and MS instrumentation are now extending in-depth proteome profiling to single mammalian cells. Here, we describe specific techniques that increase the sensitivity of single-cell proteomics by orders of magnitude, enabling the promise of single-cell proteomics to become a reality. We anticipate such techniques can significantly advance the understanding of leukemic stem cells.

Single-cell Proteomics: Progress and Prospects

MS-based proteome profiling has become increasingly comprehensive and quantitative, yet a persistent shortcoming has been the relatively large samples required to achieve an in-depth measurement. Such bulk samples, typically comprising thousands of cells or more, provide a population average and obscure important cellular heterogeneity. Single-cell proteomics capabilities have the potential to transform biomedical research and enable understanding of biological systems with a new level of granularity. Recent advances in sample processing, separations and MS instrumentation now make it possible to quantify >1000 proteins from individual mammalian cells, a level of coverage that required an input of thousands of cells just a few years ago. This review discusses important factors and parameters that should be optimized across the workflow for single-cell and other low-input measurements. It also highlights recent developments that have advanced the field and opportunities for further development.

MINIATURIZATION IN MASS SPECTROMETRY

Expectations for continuous miniaturization in mass spectrometry are not declining for years. Portable instruments are highly welcome by the industry, science, space agencies, forensic laboratories, and many other units. All are striving for the small, cheap, and as good as possible instruments. This review describes the recent developments of miniature mass spectrometers and also provides selected applications where these devices are used. Upcoming perspectives of further development are also discussed. @ 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

Simple Method to Quantify Protein Abundances from 1000 Cells

The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens

RNA sequencing is considered the gold standard for high-throughput profiling of gene expression at the transcriptional level. Its increasing importance in cancer research and molecular diagnostics is reflected in the growing number of its mentions in scientific literature and clinical trial reports. However, the use of different reagents and protocols for RNA sequencing often produces incompatible results. Recently, we published the Oncobox Atlas of RNA sequencing profiles for normal human tissues obtained from healthy donors killed in road accidents. This is a database of molecular profiles obtained using uniform protocol and reagents settings that can be broadly used in biomedicine for data normalization in pathology, including cancer. Here, we publish new original 39 breast cancer (BC) and 19 lung cancer (LC) RNA sequencing profiles obtained for formalin-fixed paraffin-embedded (FFPE) tissue samples, fully compatible with the Oncobox Atlas. We performed the first correlation study of RNA sequencing and immunohistochemistry-measured expression profiles for the clinically actionable biomarker genes in FFPE cancer tissue samples. We demonstrated high (Spearman's rho 0.65-0.798) and statistically significant (p < 0.00004) correlations between the RNA sequencing (Oncobox protocol) and immunohistochemical measurements for HER2/ERBB2, ER/ESR1 and PGR genes in BC, and for PDL1 gene in LC; AUC: 0.963 for HER2, 0.921 for ESR1, 0.912 for PGR, and 0.922 for PDL1. To our knowledge, this is the first validation that total RNA sequencing of archived FFPE materials provides a reliable estimation of marker protein levels. These results show that in the future, RNA sequencing can complement immunohistochemistry for reliable measurements of the expression biomarkers in FFPE cancer samples.

Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform

Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. However, one significant technical gap of top-down proteomics is the inability to analyze a low amount of biological samples, which limits its access to isolated rare cells, fine needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (nanodroplet processing in one pot for trace samples), into a top-down proteomic workflow. A unique combination of a nonionic detergent dodecyl-β-d-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing nonspecific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ∼170 to ∼620 proteoforms from ∼70 to ∼770 HeLa cells containing ∼10 to ∼115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical research, particularly where clinical specimens are not available in amounts amenable to standard workflows.

Developing front-end devices for improved sample preparation in MS-based proteome analysis

Chemical analysis has long relied on instrumentation, from the simplest (eg, burets) to the more sophisticated (eg, mass spectrometers) to facilitate precision measurements. Regardless of their complexity, the development of a new instrumental device can be a valued approach to address problems in science. In this perspective, we outline the process of novel device design, from early phase conception to the manufacturing and testing of the tool or gadget. Focus is placed on the development of improved front-end devices to facilitate protein sample manipulations ahead of mass spectrometry, which therefore augment the proteomics workflow. Highlighted are some of the many training secrets, choices, and challenges that are inherent to the often iterative process of device design. In hopes of inspiring others to pursue instrument design to address relevant research questions, we present a summary list of points to consider prior to innovating their own devices.

Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry

Single-cell proteomics can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. Here we report on improved single-cell proteome coverage through the combination of the previously developed nanoPOTS platform with further miniaturization of liquid chromatography (LC) separations and implementation of an ultrasensitive latest generation mass spectrometer. Following nanoPOTS sample preparation, protein digests from single cells were separated using a 20 μm i.d. in-house-packed nanoLC column. Separated peptides were ionized using an etched fused-silica emitter capable of stable operation at the ∼20 nL/min flow rate provided by the LC separation. Ultrasensitive LC-MS analysis was achieved using the Orbitrap Eclipse Tribrid mass spectrometer. An average of 362 protein groups were identified by tandem mass spectrometry (MS/MS) from single HeLa cells, and 874 protein groups were identified using the Match Between Runs feature of MaxQuant. This represents an >70% increase in label-free proteome coverage for single cells relative to previous efforts using larger bore (30 μm i.d.) LC columns coupled to a previous-generation Orbitrap Fusion Lumos mass spectrometer.

High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform

Effective extension of mass spectrometry-based proteomics to single cells remains challenging. Herein we combined microfluidic nanodroplet technology with tandem mass tag (TMT) isobaric labeling to significantly improve analysis throughput and proteome coverage for single mammalian cells. Isobaric labeling facilitated multiplex analysis of single cell-sized protein quantities to a depth of ∼1 600 proteins with a median CV of 10.9% and correlation coefficient of 0.98. To demonstrate in-depth high throughput single cell analysis, the platform was applied to measure protein expression in 72 single cells from three murine cell populations (epithelial, immune, and endothelial cells) in <2 days instrument time with over 2 300 proteins identified. Principal component analysis grouped the single cells into three distinct populations based on protein expression with each population characterized by well-known cell-type specific markers. Our platform enables high throughput and unbiased characterization of single cell heterogeneity at the proteome level.

Automated Nanoflow Two-Dimensional Reversed-Phase Liquid Chromatography System Enables In-Depth Proteome and Phosphoproteome Profiling of Nanoscale Samples

Two-dimensional reversed-phase capillary liquid chromatography (2D RPLC) separations have enabled comprehensive proteome profiling of biological systems. However, milligram sample quantities of proteins are typically required due to significant losses during offline fractionation. Such a large sample requirement generally precludes the application samples in the nanogram to low-microgram range. To achieve in-depth proteomic analysis of such small-sized samples, we have developed the nanoFAC (nanoflow Fractionation and Automated Concatenation) 2D RPLC platform, in which the first dimension high-pH fractionation was performed on a 75-μm i.d. capillary column at a 300 nL/min flow rate with automated fraction concatenation, instead of on a typically used 2.1 mm column at a 200 μL/min flow rate with manual concatenation. Each fraction was then fully transferred to the second-dimension low-pH nanoLC separation using an autosampler equipped with a custom-machined syringe. We have found that using a polypropylene 96-well plate as collection device as well as the addition of n-Dodecyl β-d-maltoside (0.01%) in the collection buffer can significantly improve sample recovery. We have demonstrated the nanoFAC 2D RPLC platform can achieve confident identifications of ∼49,000-94,000 unique peptides, corresponding to ∼6,700-8,300 protein groups using only 100-1000 ng of HeLa tryptic digest (equivalent to ∼500-5,000 cells). Furthermore, by integrating with phosphopeptide enrichment, the nanoFAC 2D RPLC platform can identify ∼20,000 phosphopeptides from 100 μg of MCF-7 cell lysate.