The plasma peptides of sepsis

Comprehensive analysis of immunogenic cell death-related gene and construction of prediction model based on WGCNA and multiple machine learning in severe COVID-19

The death of coronavirus disease 2019 (COVID-19) is primarily due to from critically ill patients, especially from ARDS complications caused by SARS-CoV-2. Therefore, it is essential to contribute an in-depth understanding of the pathogenesis of the disease and to identify biomarkers for predicting critically ill patients at the molecular level. Immunogenic cell death (ICD), as a specific variant of regulatory cell death driven by stress, can induce adaptive immune responses against cell death antigens in the host. Studies have confirmed that both innate and adaptive immune pathways are involved in the pathogenesis of SARS-CoV-2 infection. However, the role of ICD in the pathogenesis of severe COVID-19 has rarely been explored. In this study, we systematically evaluated the role of ICD-related genes in COVID-19. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis based on ICD differentially expressed genes. The results showed that immune infiltration characteristics were altered in severe and non-severe COVID-19. In addition, we used multiple machine learning methods to screen for five risk genes (KLF5, NSUN7, APH1B, GRB10 and CD4), which are used to predict COVID-19 severity. Finally, we constructed a nomogram to predict the risk of severe COVID-19 based on the classification and recognition model, and validated the model with external data sets. This study provides a valuable direction for the exploration of the pathogenesis and progress of COVID-19, and helps in the early identification of severe cases of COVID-19 to reduce mortality.

A neuroligin-2-YAP axis regulates progression of pancreatic intraepithelial neoplasia

Pancreatic ductal adenocarcinoma (PDAC) is a tumor with a dismal prognosis that arises from precursor lesions called pancreatic intraepithelial neoplasias (PanINs). Progression from low- to high-grade PanINs is considered as tumor initiation, and a deeper understanding of this switch is needed. Here, we show that synaptic molecule neuroligin-2 (NLGN2) is expressed by pancreatic exocrine cells and plays a crucial role in the regulation of contact inhibition and epithelial polarity, which characterize the switch from low- to high-grade PanIN. NLGN2 localizes to tight junctions in acinar cells, is diffusely distributed in the cytosol in low-grade PanINs and is lost in high-grade PanINs and in a high percentage of advanced PDACs. Mechanistically, NLGN2 is necessary for the formation of the PALS1/PATJ complex, which in turn induces contact inhibition by reducing YAP function. Our results provide novel insights into NLGN2 functions outside the nervous system and can be used to model PanIN progression.

Advances in molecular agents targeting toll-like receptor 4 signaling pathways for potential treatment of sepsis

Sepsis is a systemic inflammatory response syndrome caused by an infection. Toll-like receptor 4 (TLR4) is activated by endogenous molecules released by injured or necrotic tissues. Additionally, TLR4 is remarkably sensitive to infection of various bacteria and can rapidly stimulate host defense responses. The TLR4 signaling pathway plays an important role in sepsis by activating the inflammatory response. Accordingly, as part of efforts to improve the inflammatory response and survival rate of patients with sepsis, several drugs have been developed to regulate the inflammatory signaling pathways mediated by TLR4. Inhibition of TLR4 signal transduction can be directed toward either TLR4 directly or other proteins in the TLR4 signaling pathway. Here, we review the advances in the development of small-molecule agents and peptides targeting regulation of the TLR4 signaling pathway, which are characterized according to their structural characteristics as polyphenols, terpenoids, steroids, antibiotics, anthraquinones, inorganic compounds, and others. Therefore, regulating the expression of the TLR4 signaling pathway and modulating its effects has broad prospects as a target for the treatment of lung, liver, kidneys, and other important organs injury in sepsis.

Dysfunction of Drosophila mitochondrial carrier homolog (Mtch) alters apoptosis and disturbs development

Mitochondrial carrier homologs 1 (MTCH1) and 2 (MTCH2) are orphan members of the mitochondrial transporter family SLC25. Human MTCH1 is also known as presenilin 1-associated protein, PSAP. MTCH2 is a receptor for tBid and is related to lipid metabolism. Both proteins have been recently described as protein insertases of the outer mitochondrial membrane. We have depleted Mtch in Drosophila and show here that mutant flies are unable to complete development, showing an excess of apoptosis during pupation; this observation was confirmed by RNAi in Schneider cells. These findings are contrary to what has been described in humans. We discuss the implications in view of recent reports concerning the function of these proteins.

Nuclear pore protein POM121 regulates subcellular localization and transcriptional activity of PPARγ

Manipulation of the subcellular localization of transcription factors by preventing their shuttling via the nuclear pore complex (NPC) emerges as a novel therapeutic strategy against cancer. One transmembrane component of the NPC is POM121, encoded by a tandem gene locus POM121A/C on chromosome 7. Overexpression of POM121 is associated with metabolic diseases (e.g., diabetes) and unfavorable clinical outcome in patients with colorectal cancer (CRC). Peroxisome proliferator-activated receptor-gamma (PPARγ) is a transcription factor with anti-diabetic and anti-tumoral efficacy. It is inhibited by export from the nucleus to the cytosol via the RAS-RAF-MEK1/2-ERK1/2 signaling pathway, a major oncogenic driver of CRC. We therefore hypothesized that POM121 participates in the transport of PPARγ across the NPC to regulate its transcriptional activity on genes involved in metabolic and tumor control. We found that POM121A/C mRNA was enriched and POM121 protein co-expressed with PPARγ in tissues from CRC patients conferring poor prognosis. Its interactome was predicted to include proteins responsible for tumor metabolism and immunity, and in-silico modeling provided insights into potential 3D structures of POM121. A peptide region downstream of the nuclear localization sequence (NLS) of POM121 was identified as a cytoplasmic interactor of PPARγ. POM121 positivity correlated with the cytoplasmic localization of PPARγ in patients with KRAS mutant CRC. In contrast, POM121A/C silencing by CRISPR/Cas9 sgRNA or siRNA enforced nuclear accumulation of PPARγ and activated PPARγ target genes promoting lipid metabolism and cell cycle arrest resulting in reduced proliferation of human CRC cells. Our data suggest the POM121-PPARγ axis as a potential drugable target in CRC.

Applications of Mass Spectrometry in the Characterization, Screening, Diagnosis, and Prognosis of COVID-19

Mass spectrometry (MS) is a powerful analytical technique that plays a central role in modern protein analysis and the study of proteostasis. In the field of advanced molecular technologies, MS-based proteomics has become a cornerstone that is making a significant impact in the post-genomic era and as precision medicine moves from the research laboratory to clinical practice. The global dissemination of COVID-19 has spurred collective efforts to develop effective diagnostics, vaccines, and therapeutic interventions. This chapter highlights how MS seamlessly integrates with established methods such as RT-PCR and ELISA to improve viral identification and disease progression assessment. In particular, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) takes the center stage, unraveling intricate details of SARS-CoV-2 proteins, revealing modifications such as glycosylation, and providing insights critical to formulating therapies and assessing prognosis. However, high-throughput analysis of MALDI data presents challenges in manual interpretation, which has driven the development of programmatic pipelines and specialized packages such as MALDIquant. As we move forward, it becomes clear that integrating proteomic data with various omic findings is an effective strategy to gain a comprehensive understanding of the intricate biology of COVID-19 and ultimately develop targeted therapeutic paradigms.

GWAS reveals genetic basis of a predisposition to severe COVID-19 through in silico modeling of the FYCO1 protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is heavily reliant on its natural ability to "hack" the host's genetic and biological pathways. The genetic susceptibility of the host is a key factor underlying the severity of the disease. Polygenic risk scores are essential for risk assessment, risk stratification, and the prevention of adverse outcomes. In this study, we aimed to assess and analyze the genetic predisposition to severe COVID-19 in a large representative sample of the Russian population as well as to build a reliable but simple polygenic risk score model with a lower margin of error. Another important goal was to learn more about the pathogenesis of severe COVID-19. We examined the tertiary structure of the FYCO1 protein, the only gene with mutations in its coding region and discovered changes in the coiled-coil domain. Our findings suggest that FYCO1 may accelerate viral intracellular replication and excessive exocytosis and may contribute to an increased risk of severe COVID-19. We found significant associations between COVID-19 and LZTFL1, FYCO1, XCR1, CCR9, TMLHE-AS1, and SCYL2 at 3p21.31. Our findings further demonstrate the polymorphic nature of the severe COVID-19 phenotype.

Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis

BACKGROUND

Neonatal sepsis (NS), a life-threatening condition, is characterized by organ dysfunction and is the most common cause of neonatal death. However, the pathogenesis of NS is unclear and the clinical inflammatory markers currently used are not ideal for diagnosis of NS. Thus, exploring the link between immune responses in NS pathogenesis, elucidating the molecular mechanisms involved, and identifying potential therapeutic targets is of great significance in clinical practice. Herein, our study aimed to explore immune-related genes in NS and identify potential diagnostic biomarkers. Datasets for patients with NS and healthy controls were downloaded from the GEO database; GSE69686 and GSE25504 were used as the analysis and validation datasets, respectively. Differentially expressed genes (DEGs) were identified and Gene Set Enrichment Analysis (GSEA) was performed to determine their biological functions. Composition of immune cells was determined and immune-related genes (IRGs) between the two clusters were identified and their metabolic pathways were determined. Key genes with correlation coefficient > 0.5 and p < 0.05 were selected as screening biomarkers. Logistic regression models were constructed based on the selected biomarkers, and the diagnostic models were validated.

RESULTS

Fifty-two DEGs were identified, and GSEA indicated involvement in acute inflammatory response, bacterial detection, and regulation of macrophage activation. Most infiltrating immune cells, including activated CD8 + T cells, were significantly different in patients with NS compared to the healthy controls. Fifty-four IRGs were identified, and GSEA indicated involvement in immune response and macrophage activation and regulation of T cell activation. Diagnostic models of DEGs containing five genes (PROS1, TDRD9, RETN, LOC728401, and METTL7B) and IRG with one gene (NSUN7) constructed using LASSO algorithm were validated using the GPL6947 and GPL13667 subset datasets, respectively. The IRG model outperformed the DEG model. Additionally, statistical analysis suggested that risk scores may be related to gestational age and birth weight, regardless of sex.

CONCLUSIONS

We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS. Our findings provide a new perspective for future research on NS pathogenesis.

Prospective study and validation of early warning marker discovery based on integrating multi-omics analysis in severe burn patients with sepsis

Background

Early detection, timely diagnosis and rapid response are essential for case management and precautions of burn-associated sepsis. However, studies on indicators for early warning and intervention have rarely been conducted. This study was performed to better understand the pathophysiological changes and targets for prevention of severe burn injuries.

Methods

We conducted a multi-center, prospective multi-omics study, including genomics, microRNAomics, proteomics and single-cell transcriptomics, in 60 patients with severe burn injuries. A mouse model of severe burn injuries was also constructed to verify the early warning ability and therapeutic effects of potential markers.

Results

Through genomic analysis, we identified seven important susceptibility genes (DNAH11, LAMA2, ABCA2, ZFAND4, CEP290, MUC20 and ENTPD1) in patients with severe burn injuries complicated with sepsis. Through plasma miRNAomics studies, we identified four miRNAs (hsa-miR-16-5p, hsa-miR-185-5p, hsa-miR-451a and hsa-miR-423-5p) that may serve as early warning markers of burn-associated sepsis. A proteomic study indicated the changes in abundance of major proteins at different time points after severe burn injury and revealed the candidate early warning markers S100A8 and SERPINA10. In addition, the proteomic analysis indicated that neutrophils play an important role in the pathogenesis of severe burn injuries, as also supported by findings from single-cell transcriptome sequencing of neutrophils. Through further studies on severely burned mice, we determined that S100A8 is also a potential early therapeutic target for severe burn injuries, beyond being an early warning indicator.

Conclusions

Our multi-omics study identified seven susceptibility genes, four miRNAs and two proteins as early warning markers for severe burn-associated sepsis. In severe burn-associated sepsis, the protein S100A8 has both warning and therapeutic effects.

Downregulation of ITIH3 contributes to cisplatin-based chemotherapy resistance in ovarian carcinoma via the Bcl-2 mediated anti-apoptosis signaling pathway

Platinum resistance of ovarian cancer is one of the primary factors of poor prognosis and inter-α-trypsin inhibitor heavy chain 3 (ITIH3) is a potential DDP resistance-associated gene. The present study assessed protein expression levels of ITIH3 in human ovarian cancer and evaluated the relationship between its expression and platinum-resistance in patients. Furthermore, the effect of ITIH3 on cisplatin (DDP)-resistant ovarian cancer cells and the underlying molecular mechanism were evaluated. Tissue microarrays of ovarian cancer samples were used to assess the association between ITIH3 protein expression levels and drug resistance and the prognosis of ovarian cancer. ITIH3 RNA interference (RNAi) ovarian cancer cell lines were constructed and expression levels of anti- and pro-apoptotic proteins of the Bcl-2 associated pathway, including Bcl-2, Bcl-xL, Mcl-1, Bak, Bim, Bax, caspase 3 and poly ADP-ribose polymerase (PARP), were assessed following DDP treatment. The Bcl-2 inhibitor ABT-737 was used to rescue DDP-resistance induced by loss of ITIH3 in vitro. Finally, a subcutaneous xenograft tumor model was used to evaluate the effect of multiple DDP injections on expression levels of apoptosis-related proteins like Bcl-2, Bcl-xL, Bak, caspase 3 and PARP. The results of tissue microarray immunohistochemistry revealed that decreased ITIH3 protein expression levels were associated with a shorter overall survival for patients with ovarian cancer. The results of Cell Counting Kit-8 assay showed that the half-maximal inhibitory concentration and resistance index of DDP in SKOV3-ITIH3 and OVCAR3-ITIH3 RNAi cells were significantly higher than in control groups. Following DDP treatment, the results of western blotting revealed that expression levels of anti-apoptotic proteins of the Bcl-2 family significantly increased in SKOV3-ITIH3 and OVCAR3-ITIH3 RNAi cells. Pro-apoptotic protein expression was not significantly changed following DDP treatment, whereas cleaved caspase 3, caspase 3 and cleaved (C-PARP) were markedly downregulated. The Bcl-2 inhibitor ABT-737 was demonstrated to reverse increased DDP resistance induced by ITIH3 expression in flow cytometric and western blotting analysis. In the subcutaneous murine xenograft model, an increased number of DDP injections yielded a decrease in phosphorylated Bcl-2, cleaved caspase 3, caspase 3 and C-PARP protein expression levels in the SKOV3-ITIH3 RNAi group tested by western blotting. To the best of our knowledge, this is the first study to demonstrate that ITIH3 could be a vital molecule involved in chemosensitivity via regulation of the Bcl-2 family-mediated apoptotic pathway. Lower protein expression levels of ITIH3 were significantly associated with platinum resistance and poor prognosis in ovarian cancer. ITIH3 may predict cisplatin-resistance in ovarian cancer.

Characterization of a proteomic profile associated with organ dysfunction and mortality of sepsis and septic shock

INTRODUCTION

The search for new biomarkers that allow an early diagnosis in sepsis and predict its evolution has become a necessity in medicine. The objective of this study is to identify, through omics techniques, potential protein biomarkers that are expressed in patients with sepsis and their relationship with organ dysfunction and mortality.

METHODS

Prospective, observational and single-center study that included adult patients (≥ 18 years) who were admitted to a tertiary hospital and who met the criteria for sepsis. A mass spectrometry-based approach was used to analyze the plasma proteins in the enrolled subjects. Subsequently, using recursive feature elimination classification and cross-validation with a vector classifier, an association of these proteins with mortality and organ dysfunction was established. The protein-protein interaction network was analyzed with String software.

RESULTS

141 patients were enrolled in this study. Mass spectrometry identified 177 proteins. Of all of them, and by recursive feature elimination, nine proteins (GPX3, APOB, ORM1, SERPINF1, LYZ, C8A, CD14, APOC3 and C1QC) were associated with organ dysfunction (SOFA > 6) with an accuracy of 0.82 ± 0.06, precision of 0.85 ± 0.093, sensitivity 0.81 ± 0.10, specificity 0.84 ± 0.10 and AUC 0.82 ± 0.06. Twenty-two proteins (CLU, LUM, APOL1, SAA1, CLEBC3B, C8A, ITIH4, KNG1, AGT, C7, SAA2, APOH, HRG, AFM, APOE, APOC1, C1S, SERPINC1, IGFALS, KLKB1, CFB and BTD) were associated with mortality with an accuracy of 0.86 ± 0.05, a precision of 0.91 ± 0.05, a sensitivity of 0.91 ± 0.05, a specificity of 0.72 ± 0.17, and an area under the curve (AUC) of 0.81 ± 0.08 with a confidence interval of 95%.

CONCLUSION

In sepsis there are proteomic patterns associated with organ dysfunction and mortality.

Diagnosis of Neonatal Sepsis: The Role of Inflammatory Markers

This is a narrative review on the role of biomarkers in the diagnosis of neonatal sepsis. We describe the difficulties to obtain standardized definitions in neonatal sepsis and discuss the limitations of published evidence of cut-off values and their sensitivities and specificities. Maternal risk factors influence the results of inflammatory markers as do gestational age, the time of sampling, the use of either cord blood or neonatal peripheral blood, and some non-infectious causes. Current evidence suggests that the use of promising diagnostic markers such as CD11b, CD64, IL-6, IL-8, PCT, and CRP, either alone or in combination, might enable clinicians discontinuing antibiotics confidently within 24-48 h. However, none of the current diagnostic markers is sensitive and specific enough to support the decision of withholding antibiotic treatment without considering clinical findings. It therefore seems to be justified that antibiotics are often initiated in ill term and especially preterm infants. Early markers like IL-6 and later markers like CRP are helpful in the diagnosis of neonatal sepsis considering the clinical aspect of the neonate, the gestational age, maternal risk factors and the time (age of the neonate regarding early-onset sepsis) of blood sampling.

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

From bedside to bench: regulation of host factors in SARS-CoV-2 infection

The zoonotic coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2), which causes COVID-19 (coronavirus disease-2019), has resulted in a pandemic. This has led to an urgent need to understand the molecular determinants of SARS-CoV-2 infection, factors associated with COVID-19 heterogeneity and severity, and therapeutic options for these patients. In this review, we discuss the role of host factors in SARS-CoV-2 infection and describe variations in host factor expression as mechanisms underlying the symptoms and severity of COVID-19. We focus on two host factors, angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), implicated in SARS-CoV-2 infection. We also discuss genetic variants associated with COVID-19 severity revealed in selected patients and based on genome-wide association studies (GWASs). Furthermore, we highlight important advances in cell and chromatin biology, such as single-cell RNA and chromatin sequencing and chromosomal conformation assays, as methods that may aid in the discovery of viral-host interactions in COVID-19. Understanding how regulation of host factor genes varies in physiological and pathological states might explain the heterogeneity observed in SARS-CoV-2 infection, help identify pathways for therapeutic development, and identify patients most likely to progress to severe COVID-19.

Glycoproteoform Profiles of Individual Patients' Plasma Alpha-1-Antichymotrypsin are Unique and Extensively Remodeled Following a Septic Episode

Sepsis and septic shock remain the leading causes of death in intensive care units (ICUs), yet the pathogenesis originating from the inflammatory response during sepsis remains ambiguous. Acute-phase proteins are typically highly glycosylated, and the nature of the glycans have been linked to the incidence and severity of such inflammatory responses. To further build upon these findings we here monitored, the longitudinal changes in the plasma proteome and, in molecular detail, glycoproteoform profiles of alpha-1-antichymotrypsin (AACT) extracted from plasma of ten individual septic patients. For each patient we included four different time-points, including post-operative (before sepsis) and following discharge from the ICU. We isolated AACT from plasma depleted for albumin, IgG and serotransferrin and used high-resolution native mass spectrometry to qualitatively and quantitatively monitor the multifaceted glycan microheterogeneity of desialylated AACT, which allowed us to monitor how changes in the glycoproteoform profiles reflected the patient's physiological state. Although we observed a general trend in the remodeling of the AACT glycoproteoform profiles, e.g. increased fucosylation and branching/LacNAc elongation, each patient exhibited unique features and responses, providing a resilient proof-of-concept for the importance of personalized longitudinal glycoproteoform profiling. Importantly, we observed that the AACT glycoproteoform changes induced by sepsis did not readily subside after discharge from ICU.