Protein profile of exhaled breath condensate determined by high resolution mass spectrometry

Wearable sampling of proteins from human exhaled aerosols for nano-liquid chromatography-tandem mass spectrometry analysis: A pilot study

RATIONALE

Human exhaled breath usually contains unique proteins that may provide clues to characterize individual physiological activities and many diseases. However, the concentration of exhaled proteins in exhaled breath is extremely low and usually does not reach the detection limits of all online breath mass spectrometry instruments. Therefore, developing a new breath sampler for collecting and characterizing exhaled proteins is important.

METHODS

In this study, a new mask-based wearable sampler was developed by fixing metal materials into the inner surface of the KN95 mask. Human exhaled proteins could be directly adsorbed onto the metal material while wearing the mask. After sampling, the collected proteins were eluted, digested, and identified using nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS).

RESULTS

The adsorption of exhaled proteins was evaluated, showing that modified gold foil is an effective material for collecting exhaled proteins. Various endogenous proteins were successfully identified from exhaled breath, many of which can be potential biomarkers for disease diagnosis.

CONCLUSIONS

By coupling the newly developed mask sampler with nano-LC-MS/MS, human exhaled proteins were successfully collected and identified. Our results show that the mask sampler is wearable, simple, and convenient, and the method is noninvasive for investigating disease diagnosis and human health.

Elevated glutathione in researchers exposed to engineered nanoparticles due to potential adaptation to oxidative stress

Aim: To find a practical biomonitoring method for researchers exposed to nanoparticles causing oxidative stress. Methods: In a continuation of a study in 2016-2018, biological samples (plasma, urine and exhaled breath condensate [EBC]) were collected in 2019-2020 from 43 researchers (13.8 ± 3.0 years of exposure) and 45 controls. Antioxidant status was assessed using glutathione (GSH) and ferric-reducing antioxidant power, while oxidative stress was measured as thiobarbituric acid reactive substances, all using spectrophotometric methods. Researchers' personal nanoparticle exposure was monitored. Results: Plasma GSH was elevated in researchers both before and after exposure (p < 0.01); postexposure plasma GSH correlated with nanoparticle exposure, and GSH in EBC increased. Conclusion: The results suggest adaptation to chronic exposure to nanoparticles, as monitored by plasma and EBC GSH.

Real-time breath analysis towards a healthy human breath profile

The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human 'profile' against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant (p< 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

Characterization and optimization of 5´ untranslated region containing poly-adenine tracts in Kluyveromyces marxianus using machine-learning model

BACKGROUND

The 5´ untranslated region (5´ UTR) plays a key role in regulating translation efficiency and mRNA stability, making it a favored target in genetic engineering and synthetic biology. A common feature found in the 5´ UTR is the poly-adenine (poly(A)) tract. However, the effect of 5´ UTR poly(A) on protein production remains controversial. Machine-learning models are powerful tools for explaining the complex contributions of features, but models incorporating features of 5´ UTR poly(A) are currently lacking. Thus, our goal is to construct such a model, using natural 5´ UTRs from Kluyveromyces marxianus, a promising cell factory for producing heterologous proteins.

RESULTS

We constructed a mini-library consisting of 207 5´ UTRs harboring poly(A) and 34 5´ UTRs without poly(A) from K. marxianus. The effects of each 5´ UTR on the production of a GFP reporter were evaluated individually in vivo, and the resulting protein abundance spanned an approximately 450-fold range throughout. The data were used to train a multi-layer perceptron neural network (MLP-NN) model that incorporated the length and position of poly(A) as features. The model exhibited good performance in predicting protein abundance (average R2 = 0.7290). The model suggests that the length of poly(A) is negatively correlated with protein production, whereas poly(A) located between 10 and 30 nt upstream of the start codon (AUG) exhibits a weak positive effect on protein abundance. Using the model as guidance, the deletion or reduction of poly(A) upstream of 30 nt preceding AUG tended to improve the production of GFP and a feruloyl esterase. Deletions of poly(A) showed inconsistent effects on mRNA levels, suggesting that poly(A) represses protein production either with or without reducing mRNA levels.

CONCLUSION

The effects of poly(A) on protein production depend on its length and position. Integrating poly(A) features into machine-learning models improves simulation accuracy. Deleting or reducing poly(A) upstream of 30 nt preceding AUG tends to enhance protein production. This optimization strategy can be applied to enhance the yield of K. marxianus and other microbial cell factories.

Advances in proteomics methods for the analysis of exhaled breath condensate

The analysis of exhaled breath condensate (EBC) demonstrates a promising avenue of minimally invasive biopsies for diagnostics. EBC is obtained by cooling exhaled air and collecting the condensation to be utilized for downstream analysis using various analytical methods. The aqueous phase of breath contains a large variety of miscible small compounds including polar electrolytes, amino acids, cytokines, chemokines, peptides, small proteins, metabolites, nucleic acids, and lipids/eicosanoids-however, these analytes are typically present at minuscule levels in EBC, posing a considerable technical challenge. Along with recent improvements in devices for breath collection, the sensitivity and resolution of liquid chromatography coupled to online mass spectrometry-based proteomics has attained subfemtomole sensitivity, vastly enhancing the quality of EBC sample analysis. As a result, proteomics analysis of EBC has been expanding the field of breath biomarker research. We present an au courant overview of the achievements in proteomics of EBC, the advancement of EBC collection devices, and the current and future applications for EBC biomarker analysis.

A clinical proteomics study of exhaled breath condensate and biomarkers for pulmonary embolism

Pulmonary embolism (PE) can be a diagnostic challenge. Current diagnostic markers for PE are unspecific and new diagnostic tools are needed. The air we exhale is a possible new source for biomarkers which can be tapped into by analysing the exhaled breath condensate (EBC). We analysed the EBC from patients with PE and controls to investigate if the EBC is a useful source for new diagnostic biomarkers of PE. We collected and analysed EBC samples from patients with suspected PE and controls matched on age and sex. Patients in whom PE was ruled out after diagnostic work-up were included in the control group to increase the sensitivity and generalizability of the identified markers. EBC samples were collected using an RTube™. The protein composition of the EBCs were analysed using data dependent label-free quantitative nano liquid chromatography-tandem mass spectrometry. EBC samples from 28 patients with confirmed PE, and 49 controls were analysed. A total of 928 EBC proteins were identified in the 77 EBC samples. As expected, a low protein concentration was determined which resulted in many proteins with unmeasurable levels in several samples. The levels of HSPA5, PEBP1 and SFTPA2 were higher and levels of POF1B, EPPK1, PSMA4, ALDOA, and CFL1 were lower in PE compared with controls. In conclusion, the human EBC contained a variety of endogenous proteins and may be a source for new diagnostic markers of PE and other diseases.

Proteomic characteristics and diagnostic potential of exhaled breath particles in patients with COVID-19

BACKGROUND

SARS-CoV-2 has been shown to predominantly infect the airways and the respiratory tract and too often have an unpredictable and different pathologic pattern compared to other respiratory diseases. Current clinical diagnostical tools in pulmonary medicine expose patients to harmful radiation, are too unspecific or even invasive. Proteomic analysis of exhaled breath particles (EBPs) in contrast, are non-invasive, sample directly from the pathological source and presents as a novel explorative and diagnostical tool.

METHODS

Patients with PCR-verified COVID-19 infection (COV-POS, n = 20), and patients with respiratory symptoms but with > 2 negative polymerase chain reaction (PCR) tests (COV-NEG, n = 16) and healthy controls (HCO, n = 12) were prospectively recruited. EBPs were collected using a "particles in exhaled air" (PExA 2.0) device. Particle per exhaled volume (PEV) and size distribution profiles were compared. Proteins were analyzed using liquid chromatography-mass spectrometry. A random forest machine learning classification model was then trained and validated on EBP data achieving an accuracy of 0.92.

RESULTS

Significant increases in PEV and changes in size distribution profiles of EBPs was seen in COV-POS and COV-NEG compared to healthy controls. We achieved a deep proteome profiling of EBP across the three groups with proteins involved in immune activation, acute phase response, cell adhesion, blood coagulation, and known components of the respiratory tract lining fluid, among others. We demonstrated promising results for the use of an integrated EBP biomarker panel together with particle concentration for diagnosis of COVID-19 as well as a robust method for protein identification in EBPs.

CONCLUSION

Our results demonstrate the promising potential for the use of EBP fingerprints in biomarker discovery and for diagnosing pulmonary diseases, rapidly and non-invasively with minimal patient discomfort.

A Mycobacterium tuberculosis fingerprint in human breath allows tuberculosis detection

An estimated one-third of tuberculosis (TB) cases go undiagnosed or unreported. Sputum samples, widely used for TB diagnosis, are inefficient at detecting infection in children and paucibacillary patients. Indeed, developing point-of-care biomarker-based diagnostics that are not sputum-based is a major priority for the WHO. Here, in a proof-of-concept study, we tested whether pulmonary TB can be detected by analyzing patient exhaled breath condensate (EBC) samples. We find that the presence of Mycobacterium tuberculosis (Mtb)-specific lipids, lipoarabinomannan lipoglycan, and proteins in EBCs can efficiently differentiate baseline TB patients from controls. We used EBCs to track the longitudinal effects of antibiotic treatment in pediatric TB patients. In addition, Mtb lipoarabinomannan and lipids were structurally distinct in EBCs compared to ex vivo cultured bacteria, revealing specific metabolic and biochemical states of Mtb in the human lung. This provides essential information for the rational development or improvement of diagnostic antibodies, vaccines and therapeutic drugs. Our data collectively indicate that EBC analysis can potentially facilitate clinical diagnosis of TB across patient populations and monitor treatment efficacy. This affordable, rapid and non-invasive approach seems superior to sputum assays and has the potential to be implemented at point-of-care.

OUP accepted manuscript

Background

COVID-19 is a highly contagious respiratory disease that can be transmitted through human exhaled breath. It has caused immense loss and has challenged the healthcare sector. It has affected the economy of countries and thereby affected numerous sectors. Analysis of human breath samples is an attractive strategy for rapid diagnosis of COVID-19 by monitoring breath biomarkers.

Content

Breath collection is a noninvasive process. Various technologies are employed for detection of breath biomarkers like mass spectrometry, biosensors, artificial learning, and machine learning. These tools have low turnaround time, robustness, and provide onsite results. Also, MS-based approaches are promising tools with high speed, specificity, sensitivity, reproducibility, and broader coverage, as well as its coupling with various chromatographic separation techniques providing better clinical and biochemical understanding of COVID-19 using breath samples.

Summary

Herein, we have tried to review the MS-based approaches as well as other techniques used for the analysis of breath samples for COVID-19 diagnosis. We have also highlighted the different breath analyzers being developed for COVID-19 detection.

Putative Biomarkers for Acute Pulmonary Embolism in Exhaled Breath Condensate

Current diagnostic markers for pulmonary embolism (PE) are unspecific. We investigated the proteome of the exhaled breath condensate (EBC) in a porcine model of acute PE in order to identify putative diagnostic markers for PE. EBC was collected at baseline and after the induction of autologous intermediate-risk PE in 14 pigs, plus four negative control pigs. The protein profiles of the EBC were analyzed using label-free quantitative nano liquid chromatography-tandem mass spectrometry. A total of 897 proteins were identified in the EBCs from the pigs. Alterations were found in the levels of 145 different proteins after PE compared with the baseline and negative controls: albumin was among the most upregulated proteins, with 14-fold higher levels 2.5 h after PE (p-value: 0.02). The levels of 49 other proteins were between 1.3- and 17.1-fold higher after PE. The levels of 95 proteins were lower after PE. Neutrophil gelatinase-associated lipocalin (fold change 0.3, p-value < 0.01) was among the most reduced proteins 2.5 h after PE. A prediction model based on penalized regression identified five proteins including albumin and neutrophil gelatinase-associated lipocalin. The model was capable of discriminating baseline samples from EBC samples collected 2.5 h after PE correctly in 22 out of 27 samples. In conclusion, the EBC from pigs with acute PE contained several putative diagnostic markers of PE.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Mass spectrometry based proteome profiling of the exhaled breath condensate for lung cancer biomarkers search

INTRODUCTION

Lung cancer remains the most prevalent cause of cancer mortality worldwide mainly due to insufficient availability of early screening methods for wide-scale application. Exhaled breath condensate (EBC) is currently considered as one of the promising targets for early screening and is particularly attractive due to its absolutely noninvasive collection and possibility for long-term frozen storage. EBC proteome analysis can provide valuable information about the (patho)physiological changes in the respiratory system and may help to identify in time a high risk of lung cancer. Mass spectrometry (MS) profiling of EBC proteome seems to have no alternative in obtaining the most extensive data and characteristic marker panels for screening.

AREAS COVERED

This special report summarizes the data of several proteomic studies of EBC in normal and lung cancer (from 2012 to 2021, PubMed), focuses on the possible reasons for the significant discrepancy in the results, and discusses some aspects for special attention in further studies.

EXPERT OPINION

The significant discrepancy in the results of various studies primarily highlights the need to create standardized protocols for the collection and preparation of EBC for proteomic analysis. The application of quantitative and targeted LC-MS/MS based approaches seems to be the most promising in further EBC proteomic studies.

Mass Spectrometry-Based Human Breath Analysis: Towards COVID-19 Diagnosis and Research

COVID-19 is a highly contagious respiratory disease that can be infected through human exhaled breath. Human breath analysis is an attractive strategy for rapid diagnosis of COVID-19 in a non-invasive way by monitoring breath biomarkers. Mass spectrometry (MS)-based approaches offer a promising analytical platform for human breath analysis due to their high speed, specificity, sensitivity, reproducibility, and broad coverage, as well as its versatile coupling methods with different chromatographic separation, and thus can lead to a better understanding of the clinical and biochemical processes of COVID-19. Herein, we try to review the developments and applications of MS-based approaches for multidimensional analysis of COVID-19 breath samples, including metabolites, proteins, microorganisms, and elements. New features of breath sampling and analysis are highlighted. Prospects and challenges on MS-based breath analysis related to COVID-19 diagnosis and study are discussed.

Comparative proteomic analysis of exhaled breath condensate between lung adenocarcinoma and CT-detected benign pulmonary nodule patients

BACKGROUND

Lung cancer is the leading cause of cancer mortality worldwide. The collection of exhaled breath condensate (EBC) is a non-invasive method that may have enormous potential as a biomarker for the early detection of lung cancer.

OBJECTIVE

To investigate the proteomic differences of EBC between lung cancer and CT-detected benign nodule patients, and determine whether these proteins could be potential biomarkers.

METHODS

Proteomic analysis was performed on individual samples from 10 lung cancer patients and 10 CT-detected benign nodule patients using data-independent acquisition (DIA) mass spectrometry.

RESULTS

A total of 1,254 proteins were identified, and 21 proteins were differentially expressed in the lung adenocarcinoma group compared to the benign nodule group (p< 0.05). The GO analysis showed that most of these proteins were involved in neutrophil-related biological processes, and the KEGG analysis showed these proteins were mostly annotated to pyruvate and propanoate metabolism. Through protein-protein interactions (PPIs) analysis, ME1 and LDHB contributed most to the interaction-network of these proteins.

CONCLUSION

Significantly differentially expressed proteins were detected between lung cancer and the CT-detected benign nodule group from EBC samples, and these proteins might serve as potential novel biomarkers of EBC for early lung cancer detection.

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Metabolomics of Exhaled Breath Condensate by Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry: A Methodological Approach

:

Respiratory diseases present a very high prevalence in the general population, with an increase in morbidity, mortality and health-care expenses worldwide. They are complex and heterogeneous pathologies that may present different pathological facets in different subjects, often with personal evolution. Therefore, there is a need to identify patients with similar characteristics, prognosis or treatment, defining the so-called phenotype, but also to mark specific differences within each phenotype, defining the endotypes.

:

Biomarkers are very useful to study respiratory phenotypes and endotypes. Metabolomics, one of the recently introduced “omics”, is becoming a leading technique for biomarker discovery. For the airways, metabolomics appears to be well suited as the respiratory tract offers a natural matrix, the Exhaled Breath Condensate (EBC), in which several biomarkers can be measured. In this review, we will discuss the main methodological issues related to the application of Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) to EBC metabolomics for investigating respiratory diseases.

Nitric Oxide and Biological Mediators in Pediatric Chronic Rhinosinusitis and Asthma

BACKGROUND

In the context of the so-called unified airway theory, chronic rhinosinusitis (CRS) and asthma may coexist. The inflammation underlying these conditions can be studied through the aid of biomarkers. Main body: We described the main biological mediators that have been studied in pediatric CRS and asthma, and, according to the available literature, we reported their potential role in the diagnosis and management of these conditions. As for CRS, we discussed the studies that investigated nasal nitric oxide (nNO), pendrin, and periostin. As for asthma, we discussed the role of fractional exhaled nitric oxide (feNO), the role of periostin, and that of biological mediators measured in exhaled breath condensate (EBC) and exhaled air (volatile organic compounds, VOCs).

CONCLUSION

Among non-invasive biomarkers, nNO seems the most informative in CRS and feNO in asthma. Other biological mediators seem promising, but further studies are needed before they can be applied in clinical practice.

Exhaled breath condensate biomarkers for lung cancer

Lung cancer is the main cause of cancer incidence and mortality worldwide and the identification of clinically useful biomarkers for lung cancer detection at both early and metastatic stage is a pressing medical need. Although many improvements have been made in the treatment and in the early screening of this cancer, most diagnosis are made at a late stage, when a lot of genetic and epigenetic changes have occurred. A promising source of biomarkers reflective of the pathogenesis of lung cancer is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules such as DNAs, RNAs, proteins, metabolites and volatile compounds are present in EBC, and their presence/absence or their variation in concentrations can be used as biomarkers. The aims of this review are to briefly describe exhaled breath composition, firstly, and then to document some of the EBC candidate biomarkers for lung cancer by dividing them according to their origin (genome, transcriptome, epigenome, metabolome, proteome and microbiota) in order to demonstrate the potential use of EBC as a helpful tool in cancer diagnostics, molecular profiling, therapy monitoring and screening of high risk individuals.

Proteomics of exhaled breath condensate in stable COPD and non-COPD controls using tandem mass tags (TMTs) quantitative mass spectrometry: A pilot study

Chronic obstructive pulmonary disease (COPD) is a type of obstructive lung disease characterized by long-term breathing problems and poor airflow. Exhaled breath condensate (EBC) is now a safe and clinically significant measurement which has a huge potential to measure biomarkers in COPD. Previous studies profiled the pooled EBC samples from COPD or control participants due to technological limitations. In our study, 32 COPD patients and 28 control individuals were enrolled, and their EBC were collected. After matching with sex, age and smoking history, EBC samples of 19 COPD patients and 19 control individuals were analyzed using tandem mass tags (TMTs) quantitative mass spectrometry individually. A total of 257 proteins were identified. Compared with control group, 24 proteins (15 upregulated and 9 downregulated) were differentially expressed in COPD patients. The GO analysis of these differential proteins expressed mostly in the cytoplasm, and the KEGG analysis showed they had a predominant role in inflammatory response. And ACTB, UBC, TUBB and CCT2 involving in cell motility and cytoskeleton played important role in the interaction-net of these proteins. To sum up, we found some proteins might be novel biomarkers of EBC in COPD and TMTs was available to analyze proteomics in individual EBC samples. SIGNIFICANCE: It is still difficult to understand the mechanism of airway inflammation in COPD. Exhaled breath condensate(EBC) might be a great study object, but due to technological limitations, researchers preferred to use pooled EBC samples. This study analyzed individual EBC samples, which would deepen our understanding of the pathogenesis of COPD. And this method can be applied to individual EBC samples for further airway investigations of different purpose and different complexity.

Evolution of clinical and environmental health applications of exhaled breath research: Review of methods and instrumentation for gas-phase, condensate, and aerosols

Human breath, along with urine and blood, has long been one of the three major biological media for assessing human health and environmental exposure. In fact, the detection of odor on human breath, as described by Hippocrates in 400 BC, is considered the first analytical health assessment tool. Although less common in comparison to contemporary bio-fluids analyses, breath has become an attractive diagnostic medium as sampling is non-invasive, unlimited in timing and volume, and does not require clinical personnel. Exhaled breath, exhaled breath condensate (EBC), and exhaled breath aerosol (EBA) are different types of breath matrices used to assess human health and disease state. Over the past 20 years, breath research has made many advances in assessing health state, overcoming many of its initial challenges related to sampling and analysis. The wide variety of sampling techniques and collection devices that have been developed for these media are discussed herein. The different types of sensors and mass spectrometry instruments currently available for breath analysis are evaluated as well as emerging breath research topics, such as cytokines, security and airport surveillance, cellular respiration, and canine olfaction.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Proteomic characterization of human exhaled breath condensate

To improve biomedical knowledge and to support biomarker discovery studies, it is essential to establish comprehensive proteome maps for human tissues and biofluids, and to make them publicly accessible. In this study, we performed an in-depth proteomics characterization of exhaled breath condensate (EBC), a sample obtained non-invasively by condensation of exhaled air that contains submicron droplets of airway lining fluid. Two pooled samples of EBC, each obtained from 10 healthy donors, were processed using a straightforward protocol based on sample lyophilization, in-gel digestion and liquid chromatography tandem-mass spectrometry analysis. Two 'technical' control samples were processed in parallel to the pooled samples to correct for exogenous protein contamination. A total of 229 unique proteins were identified in EBC among which 153 proteins were detected in both EBC pooled samples. A detailed bioinformatics analysis of these 153 proteins showed that most of the proteins identified corresponded to proteins secreted in the respiratory tract (lung, bronchi). Eight proteins were salivary proteins. Our dataset is described and has been made accessible through the ProteomeXchange database (dataset identifier: PXD007591) and is expected to be useful for future MS-based biomarker studies using EBC as the diagnostic specimen.

Non-invasive lung disease diagnostics from exhaled microdroplets of lung fluid: perspectives and technical challenges

The combination of ultra-sensitive assay techniques and recent improvements in the instrumentation used to collect microdroplets of lung fluid (MLF) from exhaled breath has enabled the development of non-invasive lung disease diagnostics that are based on MLF analysis. In one example of this approach, electrospun nylon filters were used to collect MLFs from patients with pulmonary tuberculosis. The filters were washed to obtain liquid probes, which were then tested for human immunoglobulin A (h-IgA) and fractions of h-IgA specific to ESAT-6 and Psts-1, two antigens secreted by Mycobacterium tuberculosis. Probes collected for 10 min contained 100-1500 fg of h-IgA and, in patients with pulmonary tuberculosis, a portion of these h-IgA molecules showed specificity to the secreted antigens. Separate MLFs and their dry residues were successfully collected using an electrostatic collector and impactor developed especially for this purpose. Visualization of MLF dry residues by atomic force microscopy made it possible to estimate the lipid content in each MLF and revealed mucin molecules in some MLFs. This exciting new approach will likely make it possible to detect biomarkers in individual MLFs. MLFs emerging from an infection site ('hot' microdroplets) are expected to be enriched with infection biomarkers. This paper discusses possible experimental approaches to detecting biomarkers in single MLFs, as well as certain technological problems that need to be resolved in order to develop new non-invasive diagnostics based on analysing biomarkers in separate MLFs.

Exhaled breath condensate biomarkers for the early diagnosis of lung cancer using proteomics

We explored whether the proteomic analysis of exhaled breath condensate (EBC) may provide biomarkers for noninvasive screening for the early detection of lung cancer (LC). EBC was collected from 192 individuals [49 control (C), 49 risk factor-smoking (S), 46 chronic obstructive pulmonary disease (COPD) and 48 LC]. With the use of liquid chromatography and tandem mass spectrometry, 348 different proteins with a different pattern among the four groups were identified in EBC samples. Significantly more proteins were identified in the EBC from LC compared with other groups (C: 12.4 ± 1.3; S: 15.3 ± 1; COPD: 14 ± 1.6; LC: 24.2 ± 3.6; P = 0.0001). Furthermore, the average number of proteins identified per sample was significantly higher in LC patients, and receiver operating characteristic curve (ROC) analysis showed an area under the curve of 0.8, indicating diagnostic value. Proteins frequently detected in EBC, such as dermcidin and hornerin, along with others much less frequently detected, such as hemoglobin and histones, were identified. Cytokeratins (KRTs) were the most abundant proteins in EBC samples, and levels of KRT6A, KRT6B, and KRT6C isoforms were significantly higher in samples from LC patients ( P = 0.0031, 0.0011, and 0.0009, respectively). Moreover, the amount of most KRTs in EBC samples from LC patients showed a significant positive correlation with tumor size. Finally, we used a random forest algorithm to generate a robust model using EBC protein data for the diagnosis of patients with LC where the area under the ROC curve obtained indicated a good classification (82%). Thus this study demonstrates that the proteomic analysis of EBC samples is an appropriated approach to develop biomarkers for the diagnosis of lung cancer.

Exhaled breath condensate for lung cancer protein analysis: a review of methods and biomarkers

Lung cancer is a leading cause of cancer-related deaths worldwide, and is considered one of the most aggressive human cancers, with a 5 year overall survival of 10-15%. Early diagnosis of lung cancer is ideal; however, it is still uncertain as to what technique will prove successful in the systematic screening of high-risk populations, with the strongest evidence currently supporting low dose computed tomography (LDCT). Analysis of exhaled breath condensate (EBC) has recently been proposed as an alternative low risk and non-invasive screening method to investigate early-stage neoplastic processes in the airways. However, there still remains a relative paucity of lung cancer research involving EBC, particularly in the measurement of lung proteins that are centrally linked to pathogenesis. Considering the ease and safety associated with EBC collection, and advances in the area of mass spectrometry based profiling, this technology has potential for use in screening for the early diagnosis of lung cancer. This review will examine proteomics as a method of detecting markers of neoplasia in patient EBC with a particular emphasis on LC, as well as discussing methodological challenges involving in proteomic analysis of EBC specimens.

Potential of Mass Spectrometry in Developing Clinical Laboratory Biomarkers of Nonvolatiles in Exhaled Breath

BACKGROUND

Exhaled breath contains nonvolatile substances that are part of aerosol particles of submicrometer size. These particles are formed and exhaled as a result of normal breathing and contain material from distal airways of the respiratory system. Exhaled breath can be used to monitor biomarkers of both endogenous and exogenous origin and constitutes an attractive specimen for medical investigations.

CONTENT

This review summarizes the present status regarding potential biomarkers of nonvolatile compounds in exhaled breath. The field of exhaled breath condensate is briefly reviewed, together with more recent work on more selective collection procedures for exhaled particles. The relation of these particles to the surfactant in the terminal parts of the respiratory system is described. The literature on potential endogenous low molecular weight compounds as well as protein biomarkers is reviewed. The possibility to measure exposure to therapeutic and abused drugs is demonstrated. Finally, the potential future role and importance of mass spectrometry is discussed.

SUMMARY

Nonvolatile compounds exit the lung as aerosol particles that can be sampled easily and selectively. The clinical applications of potential biomarkers in exhaled breath comprise diagnosis of disease, monitoring of disease progress, monitoring of drug therapy, and toxicological investigations.

Recent applications of CE- and HPLC-MS in the analysis of human fluids

The present review intends to cover the literature on the use of CE-/LC-MS for the analysis of human fluids, from 2010 until present. It has been planned to provide an overview of the most recent practical applications of these techniques to less extensively used human body fluids, including, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate, tear fluid, breast fluid, amniotic fluid, and cerumen. Potential pitfalls related to fluid collection and sample preparation, with particular attention to sample clean-up procedures, and methods of analysis, from the research laboratory to a clinical setting will also be addressed. While being apparent that proteomics/metabolomics represent the most prominent approaches for global identification/quantification of putative biomarkers for a variety of human diseases, evidence is also provided of the suitability of these sophisticated techniques for the detection of heterogeneous components carried by these fluids.