Identification of Key mRNAs and lncRNAs in Neonatal Sepsis by Gene Expression Profiling

Bioinformatics in Neonatal/Pediatric Medicine-A Literature Review

Bioinformatics is a scientific field that uses computer technology to gather, store, analyze, and share biological data and information. DNA sequences of genes or entire genomes, protein amino acid sequences, nucleic acid, and protein-nucleic acid complex structures are examples of traditional bioinformatics data. Moreover, proteomics, the distribution of proteins in cells, interactomics, the patterns of interactions between proteins and nucleic acids, and metabolomics, the types and patterns of small-molecule transformations by the biochemical pathways in cells, are further data streams. Currently, the objectives of bioinformatics are integrative, focusing on how various data combinations might be utilized to comprehend organisms and diseases. Bioinformatic techniques have become popular as novel instruments for examining the fundamental mechanisms behind neonatal diseases. In the first few weeks of newborn life, these methods can be utilized in conjunction with clinical data to identify the most vulnerable neonates and to gain a better understanding of certain mortalities, including respiratory distress, bronchopulmonary dysplasia, sepsis, or inborn errors of metabolism. In the current study, we performed a literature review to summarize the current application of bioinformatics in neonatal medicine. Our aim was to provide evidence that could supply novel insights into the underlying mechanism of neonatal pathophysiology and could be used as an early diagnostic tool in neonatal care.

Liver proteomic analysis reveals the key proteins involved in host immune response to sepsis

Background

Sepsis is a serious infection-induced response in the host, which can result in life-threatening organ dysfunction. It is of great importance to unravel the relationship between sepsis and host immune response and its mechanisms of action. Liver is one of the most vulnerable organs in sepsis, however, the specific pathogenesis of septic liver injury has not been well understood at the protein level.

Methods

A total of 12 healthy Sprague-Dawley (SD) male rats aged from 6 to 8 weeks were adaptively housed in individual cages in the specific pathogen free animal room. These lab rats were grouped into two groups: treatment (N = 9) and control (N = 3) groups; only three mice from the treatment group survived and were used for subsequent experiments. A TMT-based proteomic analysis for liver tissue was performed in the septic rat model.

Results

A total of 37,012 unique peptides were identified, and then 6,166 proteins were determined, among which 5,701 were quantifiable. Compared to the healthy control group, the septic rat group exhibited 162 upregulated and 103 downregulated differentially expressed proteins (DEPs). The upregulated and downregulated DEPs were the most significantly enriched into the complement and coagulation cascades and metabolic pathways. Protein-protein interaction (PPI) analysis further revealed that the upregulated and downregulated DEPs each clustered in a PPI network. Several highly connected upregulated and downregulated DEPs were also enriched into the complement and coagulation cascades pathways and metabolic pathways, respectively. The parallel reaction monitoring (PRM) results of the selected DEPs were consistent with the results of the TMT analysis, supporting the proteomic data.

Conclusion

Our findings highlight the roles of complement and coagulation cascades and metabolic pathways that may play vital roles in the host immune response. The DEPs may serve as clinically potential treatment targets for septic liver injury.

Protein-mediated interactions in the dynamic regulation of acute inflammation

Protein-mediated interactions are the fundamental mechanism through which cells regulate health and disease. These interactions require physical contact between proteins and their respective targets of interest. These targets include not only other proteins but also nucleic acids and other important molecules as well. These proteins are often involved in multibody complexes that work dynamically to regulate cellular health and function. Various techniques have been adapted to study these important interactions, such as affinity-based assays, mass spectrometry, and fluorescent detection. The application of these techniques has led to a greater understanding of how protein interactions are responsible for both the instigation and resolution of acute inflammatory diseases. These pursuits aim to provide opportunities to target specific protein interactions to alleviate acute inflammation.

Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis

BACKGROUND

Although significant advances have been made in intensive care medicine and antibacterial treatment, sepsis is still a common disease with high mortality. The condition of sepsis patients changes rapidly, and each hour of delay in the administration of appropriate antibiotic treatment can lead to a 4-7% increase in fatality. Therefore, early diagnosis and intervention may help improve the prognosis of patients with sepsis.

METHODS

We obtained single-cell sequencing data from 12 patients. This included 14,622 cells from four patients with bacterial infectious sepsis and eight patients with sepsis admitted to the ICU for other various reasons. Monocyte differentiation trajectories were analyzed using the "monocle" software, and differentiation-related genes were identified. Based on the expression of differentiation-related genes, 99 machine-learning combinations of prognostic signatures were obtained, and risk scores were calculated for all patients. The "scissor" software was used to associate high-risk and low-risk patients with individual cells. The "cellchat" software was used to demonstrate the regulatory relationships between high-risk and low-risk cells in a cellular communication network. The diagnostic value and prognostic predictive value of Enah/Vasp-like (EVL) were determined. Clinical validation of the results was performed with 40 samples. The "CBNplot" software based on Bayesian network inference was used to construct EVL regulatory networks.

RESULTS

We systematically analyzed three cell states during monocyte differentiation. The differential analysis identified 166 monocyte differentiation-related genes. Among the 99 machine-learning combinations of prognostic signatures constructed, the Lasso + CoxBoost signature with 17 genes showed the best prognostic prediction performance. The highest percentage of high-risk cells was found in state one. Cell communication analysis demonstrated regulatory networks between high-risk and low-risk cell subpopulations and other immune cells. We then determined the diagnostic and prognostic value of EVL stabilization in multiple external datasets. Experiments with clinical samples demonstrated the accuracy of this analysis. Finally, Bayesian network inference revealed potential network mechanisms of EVL regulation.

CONCLUSIONS

Monocyte differentiation-related prognostic signatures based on the Lasso + CoxBoost combination were able to accurately predict the prognostic status of patients with sepsis. In addition, low EVL expression was associated with poor prognosis in sepsis.

ADAM10-a "multitasker" in sepsis: focus on its posttranslational target

BACKGROUND

Sepsis has a complex pathogenesis in which the uncontrolled systemic inflammatory response triggered by infection leads to vascular barrier disruption, microcirculation dysfunction and multiple organ dysfunction syndrome. Numerous recent studies reveal that a disintegrin and metalloproteinase 10 (ADAM10) acts as a "molecular scissor" playing a pivotal role in the inflammatory response during sepsis by regulating proteolysis by cleaving various membrane protein substrates, including proinflammatory cytokines, cadherins and Notch, which are involved in intercellular communication. ADAM10 can also act as the cellular receptor for Staphylococcus aureus α-toxin, leading to lethal sepsis. However, its substrate-specific modulation and precise targets in sepsis have not yet to be elucidated.

METHODS

We performed a computer-based online search using PubMed and Google Scholar for published articles concerning ADAM10 and sepsis.

CONCLUSIONS

In this review, we focus on the functions of ADAM10 in sepsis-related complex endothelium-immune cell interactions and microcirculation dysfunction through the diversity of its substrates and its enzymatic activity. In addition, we highlight the posttranslational mechanisms of ADAM10 at specific subcellular sites, or in multimolecular complexes, which will provide the insight to intervene in the pathophysiological process of sepsis caused by ADAM10 dysregulation.

Human Cell-Camouflaged Nanomagnetic Scavengers Restore Immune Homeostasis in a Rodent Model with Bacteremia

Bloodstream infection caused by antimicrobial resistance pathogens is a global concern because it is difficult to treat with conventional therapy. Here, scavenger magnetic nanoparticles enveloped by nanovesicles derived from blood cells (MNVs) are reported, which magnetically eradicate an extreme range of pathogens in an extracorporeal circuit. It is quantitatively revealed that glycophorin A and complement receptor (CR) 1 on red blood cell (RBC)-MNVs predominantly capture human fecal bacteria, carbapenem-resistant (CR) Escherichia  coli, and extended-spectrum beta-lactamases-positive (ESBL-positive) E. coli, vancomycin-intermediate Staphylococcus aureus (VISA), endotoxins, and proinflammatory cytokines in human blood. Additionally, CR3 and CR1 on white blood cell-MNVs mainly contribute to depleting the virus envelope proteins of Zika, SARS-CoV-2, and their variants in human blood. Supplementing opsonins into the blood significantly augments the pathogen removal efficiency due to its combinatorial interactions between pathogens and CR1 and CR3 on MNVs. The extracorporeal blood cleansing enables full recovery of lethally infected rodent animals within 7 days by treating them twice in series. It is also validated that parameters reflecting immune homeostasis, such as blood cell counts, cytokine levels, and transcriptomics changes, are restored in blood of the fatally infected rats after treatment.

Aberrant long non-coding RNA cancer susceptibility 15 (CASC15) plays a diagnostic biomarker and regulates inflammatory reaction in neonatal sepsis

Neonatal sepsis (NS) is one of the important causes of neonatal death. There are many studies to confirm the role of long non-coding RNA (lncRNA) in neonatal infectious diseases. This study aimed to explore the level of cancer susceptibility 15 (CASC15) and its effect on inflammatory response in NS. Seventy-nine neonatal pneumonia (NP) patients and 80 NS patients were enrolled in this study. Reverse Transcription-quantitative PCR (RT-qPCR) was used to determine the expression levels of CASC15 and miR-144-3p. Receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic value of CASC15 in NS. RAW264.7 cells were stimulated with LPS to simulate the inflammatory response in NS patients, and the regulation and mechanism of CASC15 on the inflammatory response were explored in this in vitro cell model. Serum CASC15 was upregulated in NS patients, and it had the ability to distinguish NS patients from NP patients. LPS stimulation increased the expression of CASC15 and simultaneously stimulated the secretion of inflammatory cytokines, while the knockdown of CASC15 alleviated the inflammatory response induced by LPS stimulation. Besides, serum miR-144-3p was reduced in NS patients, and luciferase reporter genes showed that miR-144-3p was a direct target of CASC15. Overexpression of CASC15 may promote the inflammatory response of NS by targeted regulating the expression of miR-144-3p, which may provide us with new insights in the treatment of NS.

Clinical Significance of the Serum lncRNA NORAD Expression in Patients with Neonatal Sepsis and Its Association with miR-410-3p

Purpose

Neonatal sepsis (NS) is one of the most crucial causes of death in newborns. This investigation aimed to validate the expression level of NORAD and the probable mechanism underlying the function of NORAD in NS.

Patients and Methods

The expression of NORAD and miR-410-3p was identified by qRT-PCR. The diagnostic sensitivity and specificity of NORAD were examined by the ROC curve. The NS cell models were established by the treatment of lipopolysaccharide (LPS) in the macrophage RAW264.7 cells. The luciferase report assay was performed to detect the target relationship between NORAD and miR-410-3p and the association between them was revealed by Pearson correlation.

Results

The expression of NORAD was at a higher level in the NS group than in the pneumonia controls. The levels of NORAD could sever as a diagnostic marker on discriminating NS patients from pneumonia neonates. The expression of IL-6, IL-8, and TNF-α was enhanced in the macrophage cells under LPS circumstances, while NORAD knockdown reversed the overexpression of these pro-inflammatory cytokines. Besides, miR-410-3p was a possible ceRNA of NORAD by the finding that the luciferase activity fell in the co-transfection of miR-410-3p mimics and WT-NORAD group. In vitro, LPS management could inhibit the expression of miR-410-3p, while silenced NORAD ameliorated the suppressed miR-410-3p levels. Decreased expression of miR-410-3p was discovered in NS patients and the changes of miR-410-3p expression were correlated with the levels of NORAD in the NS patients.

Conclusion

We found a raised level of NORAD in the NS patients and it might be a diagnostic indicator for NS patients. NORAD elimination meliorated the inflammation actions steered by LPS. MiR-410-3p was a target of NORAD and lowly expressed in the NS patients.

MYD88, NFKB1, and IL6 transcripts overexpression are associated with poor outcomes and short survival in neonatal sepsis

Toll-like receptor (TLR) family signature has been implicated in sepsis etiopathology. We aimed to evaluate the genetic profile of TLR pathway-related key genes; the myeloid differentiation protein 88 (MYD88), IL1 receptor-associated kinase 1 (IRAK1), the nuclear factor kappa-B1 (NFKB1), and interleukin 6 (IL6) in the blood of neonates with sepsis at the time of admission and post-treatment for the available paired-samples. This case–control study included 124 infants with sepsis admitted to the neonatal intensive care unit and 17 controls. The relative gene expressions were quantified by TaqMan Real-Time qPCR and correlated to the clinic-laboratory data. MYD88, NFKB1, and IL6 relative expressions were significantly higher in sepsis cases than controls. Higher levels of MYD88 and IL6 were found in male neonates and contributed to the sex-based separation of the cases by the principal component analysis. ROC analysis revealed MYD88 and NFKB1 transcripts to be good biomarkers for sepsis. Furthermore, patients with high circulatory MYD88 levels were associated with poor survival, as revealed by Kaplan–Meier curves analysis. MYD88, NFKB1, and IL6 transcripts showed association with different poor-outcome manifestations. Clustering analysis split the patient cohort into three distinct groups according to their transcriptomic signature and CRP levels. In conclusion, the study TLR pathway-related transcripts have a gender-specific signature, diagnostic, and prognostic clinical utility in neonatal sepsis.

The Role of Long Non-coding RNAs in Sepsis-Induced Cardiac Dysfunction

Sepsis is a syndrome with life-threatening organ dysfunction induced by a dysregulated host response to infection. The heart is one of the most commonly involved organs during sepsis, and cardiac dysfunction, which is usually indicative of an extremely poor clinical outcome, is a leading cause of death in septic cases. Despite substantial improvements in the understanding of the mechanisms that contribute to the origin and responses to sepsis, the prognosis of sepsis-induced cardiac dysfunction (SICD) remains poor and its molecular pathophysiological changes are not well-characterized. The recently discovered group of mediators known as long non-coding RNAs (lncRNAs) have presented novel insights and opportunities to explore the mechanisms and development of SICD and may provide new targets for diagnosis and therapeutic strategies. LncRNAs are RNA transcripts of more than 200 nucleotides with limited or no protein-coding potential. Evidence has rapidly accumulated from numerous studies on how lncRNAs function in associated regulatory circuits during SICD. This review outlines the direct evidence of the effect of lncRNAs on SICD based on clinical trials and animal studies. Furthermore, potential functional lncRNAs in SICD that have been identified in sepsis studies are summarized with a proven biological function in research on other cardiovascular diseases.