New Approaches to Identify Sepsis Biomarkers: The Importance of Model and Sample Source for Mass Spectrometry

Combination of HBA1, TTR, and SERPINF2 in plasma defines phenotype correlated with severe burn outcome

Recent advancements in proteomics allow for the concurrent identification and quantification of multiple proteins. This study aimed to identify proteins associated with severe burn pathology and establish a clinically useful molecular pathology classification. In a retrospective observational study, blood samples were collected from severe burn patients. Proteins were measured using mass spectrometry, and prognosis-related proteins were extracted by comparing survivors and non-survivors. Enrichment and ROC analyses evaluated the extracted proteins, followed by latent class analysis. Measurements were performed on 83 burn patients. In the non-survivor group, ten proteins significantly changing on the day of injury were associated with metabolic processes and toxin responses. ROC analysis identified HBA1, TTR, and SERPINF2 with AUCs > 0.8 as predictors of 28-day mortality. Latent class analysis classified three molecular pathotypes, and plasma mass spectrometry revealed ten proteins associated with severe burn prognosis. Molecular pathotypes based on HBA1, TTR, and SERPINF2 significantly correlated with outcomes.

Compliance with SEP-1 guidelines is associated with improved outcomes for septic shock but not for severe sepsis

BACKGROUND

In 2018, the Centers for Medicaid and Medicare Services (CMS) issued a protocol for the treatment of sepsis. This bundle protocol, titled SEP-1 is a multicomponent 3 h and 6 h resuscitation treatment for patients with the diagnosis of either severe sepsis or septic shock. The SEP-1 bundle includes antibiotic administration, fluid bolus, blood cultures, lactate measurement, vasopressors for fluid-refractory hypotension, and a reevaluation of volume status. We performed a retrospective analysis of patients diagnosed with either severe sepsis or septic shock comparing mortality outcomes based on compliance with the updated SEP-1 bundle at a rural community hospital.

METHODS

Mortality outcome and readmission data were extracted from an electronic medical records database from January 1, 2019, to June 30, 2020. International Classification of Diseases (ICD)-10 codes were used to identify patients with either severe sepsis or septic shock. Once identified, patients were separated into four populations: patients with severe sepsis who met SEP-1, patients with severe sepsis who failed SEP-1, patients with septic shock who met SEP-1, and patients with septic shock who failed SEP-1. A patient who met bundle criteria (SEP-1 criteria) received each component of the bundle in the time allotted. Using chi-squared test of homogeneity, mortality outcomes for population proportions were investigated. Two sample proportion summary hypothesis test and 95% confidence intervals (CI) determined significance in mortality outcomes.

RESULTS

Out of our 1122 patient population, 437 patients qualified to be measured by CMS criteria. Of the 437 patients, 195 met the treatment bundle and 242 failed the treatment bundle. Upon comparing the two groups, we found the probable difference in mortality rate between the met(14.87%) and failed bundle(27.69%) groups to be significant(95% CI: 5.28-20.34, P=0.0013). However, the driving force of this result lies in the subgroup of patients with severe sepsis with septic shock, which show a higher mortality rate compared to the subgroup with just severe sepsis. The difference was within the range of 3.31% to 29.71%.

CONCLUSION

This study shows that with septic shock obtained a benefit, decreased mortality, when the SEP-1 bundle was met. However, meeting the SEP-1 bundle had no benefit for patients who had the diagnosis of severe sepsis alone. The significant difference in mortality, found between the met and failed bundle groups, is primarily due to the number of patients with septic shock, and whether or not those patients with septic shock met or failed the bundle.

Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

The profound effects of and distress caused by the global COVID-19 pandemic highlighted what has been known in the health sciences a long time ago: that bacteria, fungi, viruses, and parasites continue to present a major threat to human health. Infectious diseases remain the leading cause of death worldwide, with antibiotic resistance increasing exponentially due to a lack of new treatments. In addition to this, many pathogens share the common trait of having the ability to modulate, and escape from, the host immune response. The challenge in medical microbiology is to develop and apply new experimental approaches that allow for the identification of both the microbe and its drug susceptibility profile in a time-sensitive manner, as well as to elucidate their molecular mechanisms of survival and immunomodulation. Over the last three decades, proteomics has contributed to a better understanding of the underlying molecular mechanisms responsible for microbial drug resistance and pathogenicity. Proteomics has gained new momentum as a result of recent advances in mass spectrometry. Indeed, mass spectrometry-based biomedical research has been made possible thanks to technological advances in instrumentation capability and the continuous improvement of sample processing and workflows. For example, high-throughput applications such as SWATH or Trapped ion mobility enable the identification of thousands of proteins in a matter of minutes. This type of rapid, in-depth analysis, combined with other advanced, supportive applications such as data processing and artificial intelligence, presents a unique opportunity to translate knowledge-based findings into measurable impacts like new antimicrobial biomarkers and drug targets. In relation to the Research Topic “Proteomic Approaches to Unravel Mechanisms of Resistance and Immune Evasion of Bacterial Pathogens,” this review specifically seeks to highlight the synergies between the powerful fields of modern proteomics and microbiology, as well as bridging translational opportunities from biomedical research to clinical practice.

Evaluation of the Molecular Mechanisms of Sepsis Using Proteomics

Sepsis is a complex syndrome promoted by pathogenic and host factors; it is characterized by dysregulated host responses and multiple organ dysfunction, which can lead to death. However, its underlying molecular mechanisms remain unknown. Proteomics, as a biotechnology research area in the post-genomic era, paves the way for large-scale protein characterization. With the rapid development of proteomics technology, various approaches can be used to monitor proteome changes and identify differentially expressed proteins in sepsis, which may help to understand the pathophysiological process of sepsis. Although previous reports have summarized proteomics-related data on the diagnosis of sepsis and sepsis-related biomarkers, the present review aims to comprehensively summarize the available literature concerning “sepsis”, “proteomics”, “cecal ligation and puncture”, “lipopolysaccharide”, and “post-translational modifications” in relation to proteomics research to provide novel insights into the molecular mechanisms of sepsis.

The Secretome Deregulations in a Rat Model of Endotoxemic Shock

Introduction

Septic shock is a systemic inflammatory response syndrome associated with organ failures. Earlier clinical diagnosis would be of benefit to a decrease in the mortality rate. However, there is currently a lack of predictive biomarkers. The secretome is the set of proteins secreted by a cell, tissue, or organism at a given time and under certain conditions. The plasma secretome is easily accessible from biological fluids and represents a good opportunity to discover new biomarkers that can be studied with nontargeted “omic” strategies.

Aims

To identify relevant deregulated proteins (DEP) in the secretome of a rat endotoxemic shock model.

Methods

Endotoxemic shock was induced in rats by intravenous injection of lipopolysaccharides (LPS, S. enterica typhi, 0.5 mg/kg) and compared to controls (Ringer Lactate, iv). Under isoflurane anesthesia, carotid cannulation allowed mean arterial blood pressure (MAP) and heart rate (HR) monitoring and blood sampling at different time points (T0 and T50 or T0 and T90, with EDTA and protease inhibitor). Samples were prepared for large-scale tandem mass spectrometry (MS-MS) based on a label-free quantification to allow identification of the proteins deregulated upon endotoxemic conditions. A Gene Ontology (GO) analysis defined several clusters of biological processes (BP) in which the DEP are involved.

Results

Ninety minutes after shock induction, the LPS group presents a reduction in MAP (-45%, p < 0.05) and increased lactate levels (+27.5%, p < 0.05) compared to the control group. Proteomic analyses revealed 10 and 33 DEP in the LPS group, respectively, at 50 and 90 minutes after LPS injection. At these time points, GO-BP showed alterations in pathways involved in oxidative stress response and coagulation.

Conclusion

This study proposes an approach to identify relevant DEP in septic shock and brings new insights into the understanding of the secretome adaptations upon sepsis.