Proteome Profiling of the Exhaled Breath Condensate after Long-Term Spaceflights

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.

Direct RNA sequencing of astronaut blood reveals spaceflight-associated m6A increases and hematopoietic transcriptional responses

The advent of civilian spaceflight challenges scientists to precisely describe the effects of spaceflight on human physiology, particularly at the molecular and cellular level. Newer, nanopore-based sequencing technologies can quantitatively map changes in chemical structure and expression at single molecule resolution across entire isoforms. We perform long-read, direct RNA nanopore sequencing, as well as Ultima high-coverage RNA-sequencing, of whole blood sampled longitudinally from four SpaceX Inspiration4 astronauts at seven timepoints, spanning pre-flight, day of return, and post-flight recovery. We report key genetic pathways, including changes in erythrocyte regulation, stress induction, and immune changes affected by spaceflight. We also present the first m6A methylation profiles for a human space mission, suggesting a significant spike in m6A levels immediately post-flight. These data and results represent the first longitudinal long-read RNA profiles and RNA modification maps for each gene for astronauts, improving our understanding of the human transcriptome's dynamic response to spaceflight.

Cytoskeletal Alteration Is an Early Cellular Response in Pulmonary Epithelium Infected with Aspergillus fumigatus Rather than Scedosporium apiospermum

Invasive aspergillosis and scedosporiosis are life-threatening fungal infections with similar clinical manifestations in immunocompromised patients. Contrarily, Scedosporium apiospermum is susceptible to some azole derivative but often resistant to amphotericin B. Histopathological examination alone cannot diagnose these two fungal species. Pathogenesis studies could contribute to explore candidate protein markers for new diagnosis and treatment methods leading to a decrease in mortality. In the present study, proteomics was conducted to identify significantly altered proteins in A549 cells infected with or without Aspergillus fumigatus and S. apiospermum as measured at initial invasion. Protein validation was performed with immunogold labelling alongside immunohistochemical techniques in infected A549 cells and lungs from murine models. Further, cytokine production was measured, using the Bio-Plex-Multiplex immunoassay. The cytoskeletal proteins HSPA9, PA2G4, VAT1, PSMA2, PEX1, PTGES3, KRT1, KRT9, CLIP1 and CLEC20A were mainly changed during A. fumigatus infection, while the immunologically activated proteins WNT7A, GAPDH and ANXA2 were principally altered during S. apiospermum infection. These proteins are involved in fungal internalisation and structural destruction leading to pulmonary disorders. Interleukin (IL)-21, IL-1α, IL-22, IL-2, IL-8, IL-12, IL-17A, interferon-γ and tumour necrosis factor-α were upregulated in both aspergillosis and scedosporiosis, although more predominately in the latter, in accordance with chitin synthase-1 and matrix metalloproteinase levels. Our results demonstrated that during invasion, A. fumigatus primarily altered host cellular integrity, whereas S. apiospermum chiefly induced and extensively modulated host immune responses.

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.

Short Time-Series Expression Transcriptome Data Reveal the Gene Expression Patterns of Dairy Cow Mammary Gland as Milk Yield Decreased Process

The existing research on dairy cow mammary gland genes is extensive, but there have been few reports about dynamic changes in dairy cow mammary gland genes as milk yield decrease. For the first time, transcriptome analysis based on short time-series expression miner (STEM) and histological observations were performed using the Holstein dairy cow mammary gland to explore gene expression patterns in this process of decrease (at peak, mid-, and late lactation). Histological observations suggested that the number of mammary acinous cells at peak/mid-lactation was significantly higher than that at mid-/late lactation, and the lipid droplets area secreted by dairy cows was almost unaltered across the three stages of lactation (p > 0.05). Totals of 882 and 1439 genes were differentially expressed at mid- and late lactation, respectively, compared to peak lactation. Function analysis showed that differentially expressed genes (DEGs) were mainly related to apoptosis and energy metabolism (fold change ≥ 2 or fold change ≤ 0.5, p-value ≤ 0.05). Transcriptome analysis based on STEM identified 16 profiles of differential gene expression patterns, including 5 significant profiles (false discovery rate, FDR ≤ 0.05). Function analysis revealed DEGs involved in milk fat synthesis were downregulated in Profile 0 and DEGs in Profile 12 associated with protein synthesis. These findings provide a foundation for future studies on the molecular mechanisms underlying mammary gland development in dairy cows.

Proteome of exhaled breath condensate on exposure to high-temperature thermoheliox

The proteome of exhaled breath condensate was analyzed by mass spectrometry before and immediately after the thermoheliox procedure and after a 3 h relaxation. The major part of the proteome remained unchanged and there was no extensive cell destruction.

[Thermal heliox proteome. High-temperature heliox does not cause destruction of human respiratory system cells]

AIM

Conducting a pilot study to assess the effect of thermal heliox on the state of the respiratory tract by studying of the exhaled breath condensate protein composition before the thermal heliox procedure, immediately after and after three hours of relaxation Materials and methods. A comparative study of the exhaled breath condensates (EBC) protein composition of five non-smoking healthy donors was carried out. The EBC was taken before the respiratory procedure, immediately after a 20-minute inhalation by mixture of He/O2 gases (70/30) heated to 70C and 3 hours later. The protein composition was determined by chromatography-mass spectrometric analysis after selective tryptic hydrolysis. The results were processed using the Mascot program and the UniProt database.

RESULTS

After the heliox procedure, the volume of the collected condensate (11.5 ml) decreases by an average of 32% and is practically restored after three hours of relaxation. Most proteins were consistent for all samples, regardless of the thermal heliox procedure. These are keratins, several proteins of the immune system (immunoglobulins, compliment proteins), tubulin. In samples after thermal heliox, the appearance of small amounts of additional proteins is observed. These are proteins of muscle metabolism (actin and calmodulin), fibrinogen, traces of hemoglobin, apolipoprotein, type B creatine kinase. After three hours of relaxation, tubulin disappears in the EBC.

CONCLUSION

Most exhaled proteins are the same before, after the procedure, and for three hours of relaxation. The results obtained demonstrate the relative safety of the use of high temperature heliox as a therapeutic agent.

Correlation and association analyses in microbiome study integrating multiomics in health and disease

Correlation and association analyses are one of the most widely used statistical methods in research fields, including microbiome and integrative multiomics studies. Correlation and association have two implications: dependence and co-occurrence. Microbiome data are structured as phylogenetic tree and have several unique characteristics, including high dimensionality, compositionality, sparsity with excess zeros, and heterogeneity. These unique characteristics cause several statistical issues when analyzing microbiome data and integrating multiomics data, such as large p and small n, dependency, overdispersion, and zero-inflation. In microbiome research, on the one hand, classic correlation and association methods are still applied in real studies and used for the development of new methods; on the other hand, new methods have been developed to target statistical issues arising from unique characteristics of microbiome data. Here, we first provide a comprehensive view of classic and newly developed univariate correlation and association-based methods. We discuss the appropriateness and limitations of using classic methods and demonstrate how the newly developed methods mitigate the issues of microbiome data. Second, we emphasize that concepts of correlation and association analyses have been shifted by introducing network analysis, microbe-metabolite interactions, functional analysis, etc. Third, we introduce multivariate correlation and association-based methods, which are organized by the categories of exploratory, interpretive, and discriminatory analyses and classification methods. Fourth, we focus on the hypothesis testing of univariate and multivariate regression-based association methods, including alpha and beta diversities-based, count-based, and relative abundance (or compositional)-based association analyses. We demonstrate the characteristics and limitations of each approaches. Fifth, we introduce two specific microbiome-based methods: phylogenetic tree-based association analysis and testing for survival outcomes. Sixth, we provide an overall view of longitudinal methods in analysis of microbiome and omics data, which cover standard, static, regression-based time series methods, principal trend analysis, and newly developed univariate overdispersed and zero-inflated as well as multivariate distance/kernel-based longitudinal models. Finally, we comment on current association analysis and future direction of association analysis in microbiome and multiomics studies.