Targeted mass spectrometry analysis of neutrophil-derived proteins released during sepsis progression

Sepsis: deriving biological meaning and clinical applications from high-dimensional data

The pathophysiology of sepsis is multi-facetted and highly complex. As sepsis is a leading cause of global mortality that still lacks targeted therapies, increased understanding of its pathogenesis is vital for improving clinical care and outcomes. An increasing number of investigations seeks to unravel the complexity of sepsis through high-dimensional data analysis, enabled by advances in -omics technologies. Here, we summarize progress in the following major -omics fields: genomics, epigenomics, transcriptomics, proteomics, lipidomics, and microbiomics. We describe what these fields can teach us about sepsis, and highlight current trends and future challenges. Finally, we focus on multi-omics integration, and discuss the challenges in deriving biological meaning and clinical applications from these types of data.

The plasma peptides of sepsis

Background

A practical strategy to discover sepsis specific proteins may be to compare the plasma peptides and proteins from patients in the intensive care unit with and without sepsis. The aim was to discover proteins and/or peptides that show greater observation frequency and/or precursor intensity in sepsis. The endogenous tryptic peptides of ICU-Sepsis were compared to ICU Control, ovarian cancer, breast cancer, female normal, sepsis, heart attack, Alzheimer’s and multiple sclerosis along with their institution-matched controls, female normals and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual sepsis and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The protein observation frequency of ICU-sepsis versus ICU Control was subsequently tested by Chi square analysis. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 showed increased observation frequency by Chi square (χ² > 9, p < 0.003) and/or precursor intensity in sepsis. Cellular gene symbols with large Chi square values from tryptic peptides included POTEB, CTNNA1, U2SURP, KIF24, NLGN2, KSR1, GTF2H1, KIT, RPS6KL1, VAV2, HSPA7, SMC2, TCEB3B, ZNF300, SUPV3L1, ADAMTS20, LAMB4, MCCC1, SUPT6H, SCN9A, SBNO1, EPHA1, ABLIM2, cB5E3.2, EPHA10, GRIN2B, HIVEP2, CCL16, TKT, LRP2 and TMF1 amongst others showed increased observation frequency. Similarly, increased frequency of tryptic phosphopeptides were observed from POM121C, SCN8A, TMED8, NSUN7, SLX4, MADD, DNLZ, PDE3B, UTY, DEPDC7, MTX1, MYO1E, RXRB, SYDE1, FN1, PUS7L, FYCO1, USP26, ACAP2, AHI1, KSR2, LMAN1, ZNF280D and SLC8A2 amongst others. Increases in mean precursor intensity in peptides from common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 as well as cellular proteins such as COL24A1, POTEB, KANK1, SDCBP2, DNAH11, ADAMTS7, MLLT1, TTC21A, TSHR, SLX4, MTCH1, and PUS7L among others were associated with sepsis. The processing of SAA1 included the cleavage of the terminal peptide D/PNHFRPAGLPEKY from the most hydrophilic point of SAA1 on the COOH side of the cystatin C binding that was most apparent in ICU-Sepsis patients compared to all other diseases and controls. Additional cleavage of SAA1 on the NH2 terminus side of the cystatin binding site were observed in ICU-Sepsis. Thus there was disease associated variation in the processing of SAA1 in ICU-Sepsis versus ICU controls or other diseases and controls.

Conclusion

Specific proteins and peptides that vary between diseases might be discovered by the random and independent sampling of multiple disease and control plasma from different hospital and clinics by LC–ESI–MS/MS for storage in a relational SQL Server database and analysis with the R statistical system that will be a powerful tool for clinical research. The processing of SAA1 may play an unappreciated role in the inflammatory response to Sepsis.

Heparinoid sevuparin inhibits Streptococcus-induced vascular leak through neutralizing neutrophil-derived proteins

Acute lung injury (ALI) and respiratory distress can develop as a consequence of sepsis with pathogens such as group A Streptococcus (GAS). In the pathogenesis of sepsis-associated ALI, endothelial barrier disruption brought on by phagocyte activation is considered a causative factor. Here, we find that sevuparin, a heparinoid with low anticoagulant activity, prevents neutrophil-induced lung plasma leakage in a murine model of systemic inflammation evoked by heat-killed GAS (hkGAS). Furthermore, using human neutrophils and endothelial cell monolayers, we demonstrate that sevuparin inhibits hkGAS-induced endothelial barrier disruption by neutralizing the activity of neutrophil-derived proteins. By mass spectrometry of neutrophil secretion, we identify proteins, including serprocidins, S100 proteins, and histone H4, that interact with sevuparin and that are responsible for the disruptive effect on endothelial integrity. Collectively, our results demonstrate the critical role of neutrophil-derived proteins in vascular hyperpermeability caused by GAS and suggest sevuparin as a potential therapeutic in acute neutrophilic inflammation.-Rasmuson, J., Kenne, E., Wahlgren, M., Soehnlein, O., Lindbom, L. Heparinoid sevuparin inhibits Streptococcus-induced vascular leak through neutralizing neutrophil-derived proteins.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Sepsis Through the Eyes of Proteomics: The Progress in the Last Decade

Sepsis is a systemic inflammatory response caused by infection whose molecular mechanisms are still not completely understood. The early detection of sepsis remains a great challenge for clinicians because no single biomarker capable of its reliable prediction, hence, delayed diagnosis frequently undermines treatment efforts, thereby contributing to high mortality. There are several experimental approaches used to reveal the molecular mechanism of sepsis progression. Proteomics coupled with mass spectrometry made possible to identify differentially expressed proteins in clinical samples. Recent advancement in liquid chromatography-based separation methods and mass spectrometers resolution and sensitivity with absolute quantitation methods, made possible to use proteomics as a powerful tool for study of clinical samples with higher coverage proteome profiles. In recent years, number of proteomic studies have been done under sepsis and/or in response to endotoxin and showed various signaling pathways, functions, and biomarkers. This review enlightened the proteomic progress in the last decade in sepsis.

Age-Related Changes in Immunological and Physiological Responses Following Pulmonary Challenge

This review examines the current status of knowledge of sepsis and pneumonia in the elderly population and how the dynamics of the pulmonary challenge affects outcome and consequences. Led by an unprecedented shift in demographics, where a larger proportion of the population will reach an older age, clinical and experimental research shows that aging is associated with certain pulmonary changes, but it is during infectious insult of the lungs, as in the case of pneumonia, that the age-related differences in responsiveness and endurance become obvious and lead to a worse outcome than in the younger population. This review points to the neutrophil, and the endothelium as important players in understanding age-associated changes in responsiveness to infectious challenge of the lung. It also addresses how the immunological set-point influences injury-repair phases, remote organ damage and how intake of drugs may alter the state of responsiveness in the users. Further, it points out the importance of considering age as a factor in inclusion criteria in clinical trials, in vitro/ex vivo experimental designs and overall interpretation of results.

Mass spectrometry for the discovery of biomarkers of sepsis

Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These "omics" strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.

Cancer associated proteins in blood plasma: Determining normal variation

Protein biomarkers have the potential to improve diagnosis, stratification of patients into treatment cohorts, follow disease progression and treatment response. One distinct group of potential biomarkers comprises proteins which have been linked to cancer, known as cancer associated proteins (CAPs). We determined the normal variation of 86 CAPs in 72 individual plasma samples collected from ten individuals using SRM mass spectrometry. Samples were collected weekly during 5 weeks from ten volunteers and over one day at nine fixed time points from three volunteers. We determined the degree of the normal variation depending on interpersonal variation, variation due to time of day, and variation over weeks and observed that the variation dependent on the time of day appeared to be the most important. Subdivision of the proteins resulted in two predominant protein groups containing 21 proteins with relatively high variation in all three factors (day, week and individual), and 22 proteins with relatively low variation in all factors. We present a strategy for prioritizing biomarker candidates for future studies based on stratification over their normal variation and have made all data publicly available. Our findings can be used to improve selection of biomarker candidates in future studies and to determine which proteins are most suitable depending on study design.