The advantages of top-down proteomics (TDP) in the characterization of proteoforms, resulting from genetic variations, alternative splicing, and post-translational modifications (PTMs), have been well documented. However, TDP applications on limited samples have been less explored, and no direct comparison with the bottom-up proteomics (BUP) approach for the same scarce amounts of samples has been conducted to date. In this work, we processed ∼100-1000 HeLa cells using bottom-up and top-down workflows and subjected sample volumes equivalent to ∼25 and up to ∼250 HeLa cells to liquid chromatography-mass spectrometry (LC-MS)-based TDP and BUP analyses. Porous layer open-tubular (PLOT) columns were used for the separation of intact proteins in TDP MS, while traditional bead-packed columns were used for the BUP workflow. Up to 500 proteoforms and nearly 1300 proteins from cell lysates equivalent to ∼25 HeLa cells were identified in TDP and BUP, respectively. Interestingly, among all the unambiguously identified proteins from both ∼25 HeLa and ∼250 HeLa cell lysates in TDP, ∼20-30% were not identified in BUP under the same sample loading, suggesting significant complementarity between TDP and BUP approaches. Additionally, biologically relevant PTMs (e.g., acetylation, phosphorylation, and methylation) were reliably characterized in TDP as different proteoforms. We anticipate that TDP, enhanced by ultralow-flow PLOT chromatography columns coupled to MS, could be a supplementary or an alternative approach for limited-sample analysis, as it eliminates the need for protein digestion and minimizes sample cleanup, enabling rapid sample preparation while preserving proteoform information.

Mass spectrometry (MS)-based top-down proteomics (TDP) has emerged as a powerful tool for characterizing proteoforms to advance both fundamental and translational research. TDP requires high-efficiency liquid-phase separation, high-resolution MS, and tandem MS. Capillary zone electrophoresis (CZE)-MS has been proposed as a promising analytical technique for protein analysis decades ago because of its unique and valuable features, including high separation efficiency and high detection sensitivity. However, CZE-MS has not been widely adopted by the proteomics community, mainly due to concerns with its robustness and reproducibility. Here, we hypothesized that CZE-MS is sufficiently robust and reproducible for broad adoption due to the continued efforts of the community over the last three decades. In this work, for the first time, research teams from around the world validated the robustness, repeatability, and reproducibility of CZE-MS for TDP in both simple and complex model proteoform mixtures employing a full spectrum of commercially available capillary electrophoresis (CE)-MS interfaces, instrumentation, and compared CZE-MS performance with state-of-the-art liquid chromatography (LC)-MS methods. This study offers the research community an informative resource of ready-to-use experimental CE-MS techniques and a better understanding of the CZE-MS approach and its potential in TDP, accelerating the broad adoption of CZE-MS in proteoform research.

This work focuses on profiling N-linked glycans by capillary electrophoresis coupled to mass spectrometry using a novel fluorescent and mass spectrometry (MS) active derivatization tag. The label is based on 2-phenylpyridine bearing tertiary amine and hydrazide functionalities. It provides efficient labeling via hydrazone formation chemistry, promising fluorescence properties, and ionization efficiency in the positive ion MS mode. Electrophoretic analysis in a neutral-coated capillary allowed baseline separation of maltooligosaccharides with limits of detection in nanomolar concentrations. The developed labeling method was successfully applied to the analyses of N-linked glycans released from several glycoproteins such as bovine ribonuclease B, human immunoglobulin G, or chicken albumin.

Despite significant recent progress in the field of mass spectrometry (MS)-based top-down proteomics (TDP), the analysis of limited samples is still a major challenge. Here, we explored the potential of ultralow flow (ULF) liquid chromatography (LC) porous layer open tubular (PLOT) columns interfaced with MS via high-field asymmetric waveform ion mobility spectrometry (FAIMS) to enable high-sensitivity TDP analysis of small populations of mammalian cells. The developed robust and easy-to-use platform delivered high reproducibility of retention times (RSD < 0.4%) and high separation performance for intact proteins (∼14-s peak full width at half-maximum and peak capacity of >125 for a 60 min effective gradient). The FAIMS-based experiments resulted in a ∼2-fold increase in identifications compared to the control experiments for ∼200 HeLa cell aliquots, i.e., 819 vs 454 proteins and 2645 vs 1305 proteoforms, respectively. The pilot ULF LC-MS analysis of six HeLa cells yielded 29 ± 3 proteins and 38 ± 2 proteoforms, on average, and a total of 44 proteins and 68 proteoforms. Data revealed a high degree of acetylation, methylation, phosphorylation, glycosylation, lactylation, and other relevant post-translational modifications. Notably, the presented protein identification results for limited samples are comparable to those of recent large-scale TDP studies of bulk samples, demonstrating the potential to enable informative single-cell TDP profiling.

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. PLOTrap combines the sample loop with the trap column for efficient nanoflow liquid chromatography sample cleanup and injection.

The study introduces a charge-based fractionation method for fractionating plasma-derived extracellular vesicles (EVs) into sub-populations aimed at the improved purification from free plasma proteins to enhance the diagnostic potential of EV sub-populations for specific pathophysiological states. Here, we present a novel approach for EV fractionation that leverages EVs' inherent surface charges, differentiating them from other plasma components and, thus, reducing the sample complexity and increasing the purity of EVs. The developed method was optimized and thoroughly evaluated using proteomic analysis, transmission electron microscopy, nanoparticle tracking, and western blotting of isolated EVs from healthy donors. Subsequently, we pilot-tested the developed technique for its applicability to real-world specimens using a small set of clinical prostate cancer samples and matched controls. The presented technique demonstrates the effective isolation and fractionation of EV sub-populations based on their surface charge, which may potentially help enhance EV-based diagnostics, biomarker discovery, and basic biology research. The method is designed to be straightforward, scalable, easy-to-use, and it does not require specialized skills or equipment.

Deep proteomic profiling of complex biological and medical samples available at low nanogram and subnanogram levels is still challenging. Thorough optimization of settings, parameters, and conditions in nanoflow liquid chromatography-tandem mass spectrometry (MS)-based proteomic profiling is crucial for generating informative data using amount-limited samples. This study demonstrates that by adjusting selected instrument parameters, e.g., ion injection time, automated gain control, and minimally altering the conditions for resuspending or storing the sample in solvents of different compositions, up to 15-fold more thorough proteomic profiling can be achieved compared to conventionally used settings. More specifically, the analysis of 1 ng of the HeLa protein digest standard by Q Exactive HF-X Hybrid Quadrupole-Orbitrap and Orbitrap Fusion Lumos Tribrid mass spectrometers yielded an increase from 1758 to 5477 (3-fold) and 281 to 4276 (15-fold) peptides, respectively, demonstrating that higher protein identification results can be obtained using the optimized methods. While the instruments applied in this study do not belong to the latest generation of mass spectrometers, they are broadly used worldwide, which makes the guidelines for improving performance desirable to a wide range of proteomics practitioners.

BACKGROUND:Glycosylation analysis is still challenging, not only because of the extreme structure complexity and conjugation diversity of glycans but also because of instrumental aspects such as the sensitivity limits of analyses. Therefore, glycan analysis by chromatographic methods is very often combined with fluorescence detection in addition to MS. The majority of fluorescent labeling employed before LC separation is based on 2-aminobenzamide, which has several disadvantages such as low labeling yield, poor fluorescence properties, and MS ionization efficiency. Therefore, even after several decades of development of new labels, there is still a need for new labeling tags with improved characteristics.RESULTS:We present the application of a newly synthesized fluorescent label designed for oligosaccharide and glycan analysis by high-performance liquid chromatography with fluorescence detection (HPLC/FLD). The novel hydrazide derivative of dipyrrometheneboron difluoride (BODIPY) was synthesized from 2,4-dimethylpyrrole, methyl succinyl chloride, and boron trifluoride etherate followed by a reaction with hydrazine. The synthesized label was characterized by several analytical methods including NMR, UV/Vis and fluorescence spectroscopy, and mass spectrometry. The labeling reaction via hydrazone formation chemistry was optimized by labeling of maltooligosaccharide standards. The analysis of maltohexaose labeled by BODIPY-hydrazide followed by HPLC/FLD analysis provided the limit of detection in the low tens of femtomole. The presented method based on fluorescence detection is at least 30 times more sensitive than the standard approach employing labeling by 2-aminobenzamide. In addition, the labeling method by BODIPY-hydrazide was used for N-linked glycan profiling of several glycoproteins (ribonuclease B, immunoglobulin G) by RP-HPLC/FLD as well as HILIC/FLD analysis.SIGNIFICANCE:This work represents the design, synthesis, and application of a new fluorescent label based on the BODIPY core and hydrazone formation chemistry for oligosaccharide and glycan analysis by HPLC/FLD. The proposed approach significantly improved the oligosaccharide and glycan analysis in comparison to the commonly used procedure employing 2-aminobenzamide.

Clinical and biological samples are often scarce and precious (e.g., rare cell isolates, microneedle tissue biopsies, small-volume liquid biopsies, and even single cells or organelles). Typical large-scale proteomic methods, where significantly higher protein amounts are analyzed, are not directly transferable to the analysis of limited samples due to their incompatibility with pg-, ng-, and low-μg-level protein sample amounts. Here, we report the on-microsolid-phase extraction tip (OmSET)-based sample preparation workflow for sensitive analysis of limited biological samples to address this challenge. The developed platform was successfully tested for the analysis of 100-10,000 typical mammalian cells and is scalable to allow for lower and larger protein amounts and more samples to be analyzed (i.e., higher throughput of analysis).

Ultralow flow LC employs ultra‐narrow bore columns and mid‐range pL/min to low nL/min flow rates (i.e., ≤20 nL/min). The separation columns that are used under these conditions are typically 2–30 μm in inner diameter. Ultralow flow LC systems allow for exceptionally high sensitivity and frequently high resolution. There has been an increasing interest in the analysis of scarce biological samples, for example, circulating tumor cells, extracellular vesicles, organelles, and single cells, and ultralow flow LC was efficiently applied to such samples. Hence, advances towards dedicated ultralow flow LC instrumentation, technical approaches, and higher throughput (e.g., tens‐to‐hundreds of single cells analyzed per day) were recently made. Here, we review the types of ultralow flow LC technology, followed by a discussion of selected representative ultralow flow LC applications, focusing on the progress made in bioanalysis of amount‐limited samples during the last 10 years. We also discuss several recently reported high‐sensitivity applications utilizing flow rates up to 100 nL/min, which are below commonly used nanoLC flow rates. Finally, we discuss the path forward for future developments of ultralow flow LC.

In this work, we developed an ultra-sensitive CE-MS/MS method for bottom-up proteomics analysis of limited samples, down to sub-nanogram levels of total protein. Analysis of 880 and 88 pg of the HeLa protein digest standard by CE-MS/MS yielded ∼1100 ± 46 and ∼160 ± 59 proteins, respectively, demonstrating higher protein and peptide identifications than the current state-of-the-art CE-MS/MS-based proteomic analyses with similar amounts of sample. To demonstrate potential applications of our ultra-sensitive CE-MS/MS method for the analysis of limited biological samples, we digested 500 and 1000 HeLa cells using a miniaturized in-solution digestion workflow. From 1-, 5-, and 10-cell equivalents injected from the resulted digests, we identified 744 ± 127, 1139 ± 24, and 1271 ± 6 proteins and 3353 ± 719, 5709 ± 513, and 8527 ± 114 peptide groups, respectively. Furthermore, we performed a comparative assessment of CE-MS/MS and two reversed-phased nano-liquid chromatography (RP-nLC-MS/MS) methods (monolithic and packed columns) for the analysis of a ∼10 ng HeLa protein digest standard. Our results demonstrate complementarity in the protein- and especially peptide-level identifications of the evaluated CE-MS- and RP-nLC-MS-based methods. The techniques were further assessed to detect post-translational modifications and highlight the strengths of the CE-MS/MS approach in identifying potentially important and biologically relevant modified peptides. With a migration window of ∼60 min, CE-MS/MS identified ∼2000 ± 53 proteins on average from a single injection of ∼8.8 ng of the HeLa protein digest standard. Additionally, an average of 232 ± 10 phosphopeptides and 377 ± 14 N-terminal acetylated peptides were identified in CE-MS/MS analyses at this sample amount, corresponding to 2- and 1.5-fold more identifications for each respective modification found by nLC-MS/MS methods.

Proteomic analysis of limited samples and single cells requires specialized methods that prioritize high sensitivity and minimize sample loss. Consequently, sample preparation is one of the most important steps in limited sample analysis workflows to prevent sample loss. In this work, we have eliminated sample handling and transfer steps by processing intact cells directly in the separation capillary, online with capillary electrophoresis coupled to tandem mass spectrometry (CE-MS/MS) for top-down proteomic (TDP) analysis of low numbers of mammalian cancer cells (<10) and single cells. We assessed spray voltage injection of intact cells from a droplet of cell suspension (∼1000 cells) and demonstrated 0-9 intact cells injected with a dependency on the duration of spray voltage application. Spray voltage applied for 2 min injected an average of 7 ± 2 cells and resulted in 33-57 protein and 40-88 proteoform identifications (N = 4). To analyze single cells, manual cell loading by hydrodynamic pressure was used. Replicates of single HeLa cells (N = 4) lysed on the capillary and analyzed by CE-MS/MS demonstrated a range of 17-40 proteins and 23-50 proteoforms identified. An additional cell line, THP-1, was analyzed at the single-cell level, and proteoform abundances were compared to show the capabilities of single-cell TDP (SC-TDP) for assessing cellular heterogeneity. This study demonstrates the initial application of TDP in single-cell proteome-level profiling. These results represent the highest reported identifications from TDP analysis of a single HeLa cell and prove the tremendous potential for CE-MS/MS on-capillary sample processing for high sensitivity analysis of single cells and limited samples.

nformative and deep proteomic and glycomic characterization of limited availability biological and medical samples has been a significant challenge. Here, we describe our current and recent efforts in advancing sample preparation as well as miniaturized electric field- and pressure-driven separation approaches interfaced with high-end mass spectrometry (MS) to enhance the sensitivity and depth of proteomic and glycomic profiling of several types of limited biological and clinically relevant samples.

In this work, we pioneered the assessment of coupling high-field asymmetric waveform ion mobility spectrometry (FAIMS) with ultrasensitive capillary electrophoresis hyphenated with tandem mass spectrometry (CE-MS/MS) to achieve deeper proteome coverage of low nanogram amounts of digested cell lysates. An internal stepping strategy using three or four compensation voltages per analytical run with varied cycle times was tested to determine optimal FAIMS settings and MS parameters for the CE-FAIMS-MS/MS method. The optimized method applied to bottom-up proteomic analysis of 1 ng of HeLa protein digest standard identified 1314 ± 30 proteins, 4829 ± 200 peptide groups, and 7577 ± 163 peptide spectrum matches (PSMs) corresponding to a 16, 25, and 22% increase, respectively, over CE-MS/MS alone, without FAIMS. Furthermore, the percentage of acquired MS/MS spectra that resulted in PSMs increased nearly 2-fold with CE-FAIMS-MS/MS. Label-free quantitation of proteins and peptides was also assessed to determine the precision of replicate analyses from FAIMS methods with increased cycle times. Our results also identified from 1 ng of HeLa protein digest without any prior enrichment 76 ± 9 phosphopeptides, 18% of which were multiphosphorylated. These results represent a 46% increase in phosphopeptide identifications over the control experiments without FAIMS yielding 2.5-fold more multiphosphorylated peptides.

In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 μL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.

Cancer is driven by both genetic aberrations in the tumor cells and fundamental changes in the tumor microenvironment (TME). These changes offer potential targets for novel therapeutics, yet lack of in vitro 3D models recapitulating this complex microenvironment impedes such progress. Here, we generated several tumor-stroma scaffolds reflecting the dynamic in vivo breast TME, using a high throughput microfluidic system. Alginate (Alg) or alginate-alginate sulfate (Alg/Alg-S) hydrogels were used as ECM-mimics, enabling the encapsulation and culture of tumor cells, fibroblasts and immune cells (macrophages and T cells, of the innate and adaptive immune systems, respectively). Specifically, Alg/Alg-S was shown capable of capturing and presenting growth factors and cytokines with binding affinity that is comparable to heparin. Viability and cytotoxicity were shown to strongly correlate with the dynamics of cellular milieu, as well as hydrogel type. Using on-chip immunofluorescence, production of reactive oxygen species and apoptosis were imaged and quantitatively analyzed. We then show how macrophages in our microfluidic system were shifted from a proinflammatory to an immunosuppressive phenotype when encapsulated in Alg/Alg-S, reflecting in vivo TME dynamics. LC-MS proteomic profiling of tumor cells sorted from the TME scaffolds revealed upregulation of proteins involved in cell-cell interactions and immunomodulation in Alg/Alg-S scaffolds, correlating with in vivo findings and demonstrating the appropriateness of Alg/Alg-S as an ECM biomimetic. Finally, we show the formation of large tumor-derived vesicles, formed exclusively in Alg/Alg-S scaffolds. Altogether, our system offers a robust platform for quantitative description of the breast TME that successfully recapitulates in vivo patterns. STATEMENT OF SIGNIFICANCE: Cancer progression is driven by profound changes in both tumor cells and surrounding stroma. Here, we present a high throughput microfluidic system for the generation and analysis of dynamic tumor-stroma scaffolds, that mimic the complex in vivo TME cell proportions and compositions, constructing robust in vitro models for the study of the TME. Utilizing Alg/Alg-S as a bioinspired ECM, mimicking heparin's in vivo capabilities of capturing and presenting signaling molecules, we show how Alg/Alg-S induces complex in vivo-like responses in our models. Alg/Alg-S is shown here to promote dynamic protein expression patterns, that can serve as potential therapeutic targets for breast cancer treatment. Formation of large tumor-derived vesicles, observed exclusively in the Alg/Alg-S scaffolds suggests a mechanism for tumor survival.

In this work, we pioneered a combination of ultralow flow (ULF) high-efficiency ultranarrow bore monolithic LC columns coupled to MS via a high-field asymmetric waveform ion mobility spectrometry (FAIMS) interface to evaluate the potential applicability for high sensitivity, robust, and reproducible proteomic profiling of low nanogram-level complex biological samples. As a result, ULF LC-FAIMS-MS brought unprecedented sensitivity levels and high reproducibility in bottom-up proteomic profiling. In addition, FAIMS improved the dynamic range, signal-to-noise ratios, and detection limits in ULF LC-MS-based measurements by significantly reducing chemical noise in comparison to the conventional nanoESI interface used with the same ULF LC-MS setup. Two, three, or four compensation voltages separated by at least 15 V were tested within a single LC-MS run using the FAIMS interface. The optimized ULF LC-ESI-FAIMS-MS/MS conditions resulted in identification of 2,348 ± 42 protein groups, 10,062 ± 285 peptide groups, and 15,734 ± 350 peptide-spectrum matches for 1 ng of a HeLa digest, using a 1 h gradient at the flow rate of 12 nL/min, which represents an increase by 38%, 91%, and 131% in respective identifications, as compared to the control experiment (without FAIMS). To evaluate the practical utility of the ULF LC-ESI-FAIMS-MS platform in proteomic profiling of limited samples, approximately 100, 1,000, and 10,000 U937 myeloid leukemia cells were processed, and a one-tenth of each sample was analyzed. Using the optimized conditions, we were able to reliably identify 251 ± 54, 1,135 ± 80, and 2,234 ± 25 protein groups from injected aliquots corresponding to ∼10, 100, and 1,000 processed cells.

With the advent of more sensitive and higher duty cycle mass spectrometers, analysis of limited samples, e.g., limited cell populations, microneedle biopsies, extracellular vesicles isolated from minute volumes of physiological fluids (i.e., liquid biopsies) or even single cells, is getting more feasible. However, each step of the analytical workflow, including sample preparation, liquid chromatography (LC) separation, interfacing with mass spectrometry (MS), MS data acquisition, data analysis and data interpretation requires additional advancements to enable deep proteomic profiling of such limited samples. In this study, we investigated MS data acquisition parameters on two different, commonly used mass spectrometers to enhance the sensitivity of proteomic profiling of limited samples. Our experiments indicate that nanoLC-MS/MS-based proteomic analysis of scarce samples requires adjustments of the commonly used default data acquisition settings on a mass spectrometer that work effectively for conventional sample amounts. Here we show that by using specific values of the ion injection time and AGC minimum settings in MS/MS data acquisition depending on the amount of sample results in an increase in the numbers of identified peptides and proteins. We applied commonly used settings, and then altered them to analyze HeLa tryptic digest at the levels of 1, 10 and 100 ng, which are equivalent to approximately 5, 50 and 500 cells on either an Orbitrap QE HFX or a Lumos Fusion (Thermo Fisher Scientific). By changing certain parameters for each sample amount, we were able to identify 2-4-fold more peptides and proteins, and therefore, significantly improve the protein and peptide profiling efficiency, in comparison to the commonly used settings. However, this is only a small step toward ultra-sensitive proteomic profiling. Improvements in LC separation and column material as well as sample preparation are also critical for further advances in highly sensitive analysis.

Motivation: Accurate estimation of false discovery rate (FDR) of spectral identification is a central problem in mass spectrometry-based proteomics. Over the past two decades, target decoy approaches (TDAs) and decoy-free approaches (DFAs), have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra. Results: We introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs, and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms.

In this study, the ionic profile and pH of exhaled breath condensate (EBC) in a group of patients with acid and weakly acid reflux and no-reflux controls were compared. A portable sampler was used for non-invasive EBC collection from five exhalations. The ionic profile (anions, cations, organic acids) and pH of the collected EBC samples were measured by capillary electrophoresis with contactless conductivity detection and a pH micro-electrode, respectively. Several ions were elevated in the patient groups. Sodium cation was elevated in weakly acid reflux (significance level p < 0.01) and acid reflux (p < 0.05) compared to no-reflux controls. Butyrate and propionate were elevated in both acid reflux and weakly acid reflux compared to no-reflux controls (butyrate: p < 0.01, propionate: p < 0.05). The median values of pH (after de-aeration with N-2) were also significantly higher (p < 0.01) in groups with acid reflux and weakly acid reflux than in the control group with no reflux. The ionic analysis and simultaneous pH measurement offer a simple, cheap, fast, and non-invasive approach in gastroesophageal reflux disease diagnostics.