Metabolic systems analysis of LPS induced endothelial dysfunction applied to sepsis patient stratification

Metabolic signatures of acute respiratory distress syndrome: COVID versus non-COVID

Acute respiratory distress syndrome (ARDS) is a fatal pulmonary disorder characterized by severe hypoxia and inflammation. ARDS is commonly triggered by systemic and pulmonary infections, with bacteria and viruses. Notable pathogens include Pseudomonas aeruginosa, Streptococcus aureus, Enterobacter species, coronaviruses, influenza viruses, and herpesviruses. COVID-19 ARDS represents the latest etiological phenotype of the disease. The pathogenesis of ARDS caused by bacteria and viruses exhibits variations in host immune responses and lung mesenchymal injury. We postulate that the systemic and pulmonary metabolomics profiles of ARDS induced by COVID-19 pathogens may exhibit distinctions compared with those induced by other infectious agents. This review aims to compare metabolic signatures in blood and lung specimens specifically within the context of ARDS. Both prevalent and phenotype-specific metabolomic signatures, including but not limited to glycolysis, ketone body production, lipid oxidation, and dysregulation of the kynurenine pathways, were thoroughly examined in this review. The distinctions in metabolic signatures between COVID-19 and non-COVID ARDS have the potential to reveal new biomarkers, elucidate pathogenic mechanisms, identify druggable targets, and facilitate differential diagnosis in the future.

Reconstruction of cell-specific models capturing the influence of metabolism on DNA methylation in cancer

The imbalance of epigenetic regulatory mechanisms such as DNA methylation, which can promote aberrant gene expression profiles without affecting the DNA sequence, may cause the deregulation of signaling, regulatory, and metabolic processes, contributing to a cancerous phenotype. Since some metabolites are substrates and cofactors of epigenetic regulators, their availability can be affected by characteristic cancer cell metabolic shifts, feeding cancer onset and progression through epigenetic deregulation. Hence, there is a need to study the influence of cancer metabolic reprogramming in DNA methylation to design new effective treatments. In this study, a generic Genome-Scale Metabolic Model (GSMM) of a human cell, integrating DNA methylation or demethylation reactions, was obtained and used for the reconstruction of Genome-Scale Metabolic Models enhanced with Enzymatic Constraints using Kinetic and Omics data (GECKOs) of 31 cancer cell lines. Furthermore, cell-line-specific DNA methylation levels were included in the models, as coefficients of a DNA composition pseudo-reaction, to depict the influence of metabolism over global DNA methylation in each of the cancer cell lines. Flux simulations demonstrated the ability of these models to provide simulated fluxes of exchange reactions similar to the equivalent experimentally measured uptake/secretion rates and to make good functional predictions. In addition, simulations found metabolic pathways, reactions and enzymes directly or inversely associated with the gene promoter methylation. Two potential candidates for targeted cancer epigenetic therapy were identified.

LASSO regression shows histidine and sphingosine 1 phosphate are linked to both sepsis mortality and endothelial damage

Sepsis is a major cause of death worldwide, with a mortality rate that has remained stubbornly high. The current gold standard of risk stratifying sepsis patients provides limited mechanistic insight for therapeutic targeting. An improved ability to predict sepsis mortality and to understand the risk factors would allow better treatment targeting. Sepsis causes metabolic dysregulation in patients; therefore, metabolomics offers a promising tool to study sepsis. It is also known that that in sepsis endothelial cells affecting their function regarding blood clotting and vascular permeability. We integrated metabolomics data from patients admitted to an intensive care unit for sepsis, with commonly collected clinical features of their cases and two measures of endothelial function relevant to blood vessel function, platelet endothelial cell adhesion molecule and soluble thrombomodulin concentrations in plasma. We used least absolute shrinkage and selection operator penalized regression, and pathway enrichment analysis to identify features most able to predict 30-day survival. The features important to sepsis survival include carnitines, and amino acids. Endothelial proteins in plasma also predict 30-day mortality and the levels of these proteins also correlate with a somewhat overlapping set of metabolites. Overall metabolic dysregulation, particularly in endothelial cells, may be a contributory factor to sepsis response. By exploring sepsis metabolomics data in conjunction with clinical features and endothelial proteins we have gained a better understanding of sepsis risk factors.

Transcriptome-based biomarker prediction for Parkinson's disease using genome-scale metabolic modeling

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Identification of PD biomarkers is crucial for early diagnosis and to develop target-based therapeutic agents. Integrative analysis of genome-scale metabolic models (GEMs) and omics data provides a computational approach for the prediction of metabolite biomarkers. Here, we applied the TIMBR (Transcriptionally Inferred Metabolic Biomarker Response) algorithm and two modified versions of TIMBR to investigate potential metabolite biomarkers for PD. To this end, we mapped thirteen post-mortem PD transcriptome datasets from the substantia nigra region onto Human-GEM. We considered a metabolite as a candidate biomarker if its production was predicted to be more efficient by a TIMBR-family algorithm in control or PD case for the majority of the datasets. Different metrics based on well-known PD-related metabolite alterations, PD-associated pathways, and a list of 25 high-confidence PD metabolite biomarkers compiled from the literature were used to compare the prediction performance of the three algorithms tested. The modified algorithm with the highest prediction power based on the metrics was called TAMBOOR, TrAnscriptome-based Metabolite Biomarkers by On-Off Reactions, which was introduced for the first time in this study. TAMBOOR performed better in terms of capturing well-known pathway alterations and metabolite secretion changes in PD. Therefore, our tool has a strong potential to be used for the prediction of novel diagnostic biomarkers for human diseases.

MDSCs in sepsis-induced immunosuppression and its potential therapeutic targets

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. In sepsis, a complicated immune response is initiated, which varies over time with sustained excessive inflammation and immunosuppression. Identifying a promising way to orchestrate sepsis-induced immunosuppression is a challenge. Myeloid-derived suppressor cells (MDSCs) comprise pathologically activated neutrophils and monocytes with potent immunosuppressive activity. They play an important part in inhibiting innate and adaptive immune responses, and have emerged as part of the immune response in sepsis. MDSCs numbers are persistently high in sepsis patients, and associated with nosocomial infections and other adverse clinical outcomes. However, their characteristics and functional mechanisms during sepsis have not been addressed fully. Our review sheds light on the features and suppressive mechanism of MDSCs. We also review the potential applications of MDSCs as biomarkers and targets for clinical treatment of sepsis.

Endothelial Cell Phenotypes Demonstrate Different Metabolic Patterns and Predict Mortality in Trauma Patients

In trauma patients, shock-induced endotheliopathy (SHINE) is associated with a poor prognosis. We have previously identified four metabolic phenotypes in a small cohort of trauma patients (N = 20) and displayed the intracellular metabolic profile of the endothelial cell by integrating quantified plasma metabolomic profiles into a genome-scale metabolic model (iEC-GEM). A retrospective observational study of 99 trauma patients admitted to a Level 1 Trauma Center. Mass spectrometry was conducted on admission samples of plasma metabolites. Quantified metabolites were analyzed by computational network analysis of the iEC-GEM. Four plasma metabolic phenotypes (A-D) were identified, of which phenotype D was associated with an increased injury severity score (p < 0.001); 90% (91.6%) of the patients who died within 72 h possessed this phenotype. The inferred EC metabolic patterns were found to be different between phenotype A and D. Phenotype D was unable to maintain adequate redox homeostasis. We confirm that trauma patients presented four metabolic phenotypes at admission. Phenotype D was associated with increased mortality. Different EC metabolic patterns were identified between phenotypes A and D, and the inability to maintain adequate redox balance may be linked to the high mortality.

Endothelial cell metabolism in sepsis

BACKGROUND

Endothelial dysfunction in sepsis is a pathophysiological feature of septic organ failure. Endothelial cells (ECs) exhibit specific metabolic traits and release metabolites to adapt to the septic state in the blood to maintain vascular homeostasis.

METHODS

Web of Science and PubMed were searched from inception to October 1, 2022. The search was limited to the English language only. Two reviewers independently identified studies related to EC metabolism in sepsis. The exclusion criteria were duplicate articles according to multiple search criteria.

RESULTS

Sixty articles were included, and most of them were cell and animal studies. These studies reported the role of glycolysis, oxidative phosphorylation, fatty acid metabolism, and amino acid metabolism in EC homeostasis. including glycolysis, oxidative phosphorylation, fatty acid metabolism and amino acid metabolism. However, dysregulation of EC metabolism can contribute to sepsis progression.

CONCLUSION

There are few clinical studies on EC metabolism in sepsis. Related research mainly focuses on basic research, but some scientific problems have also been clarified. Therefore, this review may provide an overall comprehension and novel aspects of EC metabolism in sepsis.

Endogenous Glycosaminoglycans in Various Pathologic Plasma Samples as Measured by a Fluorescent Quenching Method

Endogenous glycosaminoglycans (GAGs) with a similar structure to heparin are widely distributed in various tissues. A fluorescence probe, namely Heparin Red, can detect polyanionic GAGs in plasma samples. The purpose of this study is to measure endogenous GAGs in various plasma samples obtained from different pathologic states in comparison to healthy controls utilizing this method. Plasma samples were obtained from patient groups including atrial fibrillation (AF), end-stage-renal-disease (ESRD), diabetes mellitus (DM), sepsis, cancer, liver disease (LD), and pulmonary embolism (PE). Normal human plasma (NHP) was used as healthy controls. The Heparin Red kit from Red Probes (Münster, Germany) was used for the quantification of endogenous GAGs in each sample before and after heparinase I degradation. All results were compiled as group means  ±  SD for comparison. NHP was found to have relatively low levels of endogenous GAGs with a mean concentration of 0.06 μg/mL. The AF, ESRD, DM, and sepsis patient samples had a mean endogenous GAG concentration of 0.55, 0.72, 0.92, and 0.94 μg/mL, respectively. The levels of endogenous GAGs were highest in cancer, LD, and PE patient plasma samples with a mean concentration of 1.95, 2.78, and 2.83 μg/mL, respectively. Heparinase I degradation resulted in a decline in GAG levels in plasma samples. These results clearly show that detectable Heparin Red sensitive endogenous GAGs are present in circulating plasma at varying levels in various patient groups. Additional studies are necessary to understand this complex pathophysiology.

Inhibition of Phosphoinositide 3-Kinase Gamma Protects Endothelial Cells via the Akt Signaling Pathway in Sepsis-Induced Acute Kidney Injury

INTRODUCTION

Sepsis is a primary cause of death in critically ill patients and is characterized by multiple organ dysfunction, including sepsis-induced acute kidney injury (AKI), which contributes to high mortality in sepsis. However, its pathophysiological mechanisms remain unclear. The kidney has one of the richest and most diversified endothelial cell populations in the body. This study was designed to investigate the effects of endothelial dysfunction in sepsis-induced AKI and explore possible intervention measures to offer new insight into the pathogenesis and treatment of sepsis-induced AKI.

METHODS

The circulating levels of endothelial adhesion molecules were detected in patients with sepsis and healthy controls to observe the role of endothelial damage in sepsis and sepsis-induced AKI. A murine sepsis model induced by cecal ligation and perforation was pretreated with a phosphoinositide 3-kinase gamma (PI3Kγ) inhibitor (CZC24832), and survival, kidney damage, and renal endothelial injury were assessed by pathological examination, immunohistochemistry, quantitative polymerase chain reaction, and Western blotting. Lipopolysaccharides and CZC24832 were administered to human umbilical vein endothelial cells in vitro, and endothelial cell function and the expression of adhesion molecules were evaluated.

RESULTS

Endothelial damage was more serious in sepsis-induced AKI than that in non-AKI, and the inhibition of PI3Kγ alleviates renal endothelial injury in a murine sepsis model, protecting endothelial cell function and repairing endothelial cell injury through the Akt signaling pathway.

CONCLUSIONS

In this study, endothelial cell dysfunction plays an important role in sepsis-induced AKI, and the inhibition of PI3Kγ alleviates endothelial cell injury in sepsis-induced AKI through the PI3Kγ/Akt pathway, providing novel targets for treating sepsis and related kidney injury.

Single cell atlas identifies lipid-processing and immunomodulatory endothelial cells in healthy and malignant breast

Since a detailed inventory of endothelial cell (EC) heterogeneity in breast cancer (BC) is lacking, here we perform single cell RNA-sequencing of 26,515 cells (including 8433 ECs) from 9 BC patients and compare them to published EC taxonomies from lung tumors. Angiogenic ECs are phenotypically similar, while other EC subtypes are different. Predictive interactome analysis reveals known but also previously unreported receptor-ligand interactions between ECs and immune cells, suggesting an involvement of breast EC subtypes in immune responses. We also identify a capillary EC subtype (LIPEC (Lipid Processing EC)), which expresses genes involved in lipid processing that are regulated by PPAR-γ and is more abundant in peri-tumoral breast tissue. Retrospective analysis of 4648 BC patients reveals that treatment with metformin (an indirect PPAR-γ signaling activator) provides long-lasting clinical benefit and is positively associated with LIPEC abundance. Our findings warrant further exploration of this LIPEC/PPAR-γ link for BC treatment.

Tumor blood vessels contribute to cancer growth, invasion and metastasis. Here, by using single cell transcriptomics, the authors report an inventory of endothelial cell heterogeneity in patients with breast cancer, including a subtype that expresses genes involved in lipid processing and is regulated by PPAR-γ.

An explorative metabolomic analysis of the endothelium in pulmonary hypertension

Pulmonary hypertension (PH) is classified into five clinical diagnostic groups, including group 1 [idiopathic pulmonary arterial hypertension (IPAH) and connective tissue disease-associated PAH (CTD-aPAH)] and group 4 (chronic thromboembolic pulmonary hypertension (CTEPH)). PH is a progressive, life-threatening, incurable disease. The pathological mechanisms underlying PH remain elusive; recent evidence has revealed that abnormal metabolic activities in the endothelium may play a crucial role. This research introduces a novel approach for studying PH endothelial function, building on the genome-scale metabolic reconstruction of the endothelial cell (EC) to investigate intracellular metabolism. We demonstrate that the intracellular metabolic activities of ECs in PH patients cluster into four phenotypes independent of the PH diagnosis. Notably, the disease severity differs significantly between the metabolic phenotypes, suggesting their clinical relevance. The significant metabolic differences between the PH phenotypes indicate that they may require different therapeutic interventions. In addition, diagnostic capabilities enabling their identification is warranted to investigate whether this opens a novel avenue of precision medicine.

Reconstruction of tissue-specific genome-scale metabolic models for human cancer stem cells

Cancer Stem Cells (CSCs) contribute to cancer aggressiveness, metastasis, chemo/radio-therapy resistance, and tumor recurrence. Recent studies emphasized the importance of metabolic reprogramming of CSCs for the maintenance and progression of the cancer phenotype through both the fulfillment of the energetic requirements and the supply of substrates fundamental for fast-cell growth, as well as through metabolite-induced epigenetic regulation. Therefore, it is of paramount importance to develop therapeutic strategies tailored to target the metabolism of CSCs. In this work, we built computational Genome-Scale Metabolic Models (GSMMs) for CSCs of different tissues. Flux simulations were then used to predict metabolic phenotypes, identify potential therapeutic targets, and spot already-known Transcription Factors (TFs), miRNAs and antimetabolites that could be used as part of drug repurposing strategies against cancer. Results were in accordance with experimental evidence, provided insights of new metabolic mechanisms for already known agents, and allowed for the identification of potential new targets and compounds that could be interesting for further in vitro and in vivo validation.

Cholecalciferol and metformin protect against lipopolysaccharide-induced endothelial dysfunction and senescence by modulating sirtuin-1 and protein arginine methyltransferase-1

Endothelial cell activation through nuclear factor-kappa-B (NFkB) and mitogen-activated protein kinases leads to increased biosynthesis of pro-inflammatory mediators, cellular injury and vascular inflammation under lipopolysaccharide (LPS) exposure. Recent studies report that LPS up-regulated global methyltransferase activity. In this study, we observed that a combination treatment with metformin (MET) and cholecalciferol (VD) blocked the LPS-induced S-adenosylmethionine (SAM)-dependent methyltransferase (SDM) activity in Eahy926 cells. We found that LPS challenge (i) increased arginine methylation through up-regulated protein arginine methyltransferase-1 (PRMT1) mRNA, intracellular concentrations of asymmetric dimethylarginine (ADMA) and homocysteine (HCY); (ii) up-regulated cell senescence through mitigated sirtuin-1 (SIRT1) mRNA, nicotinamide adenine dinucleotide (NAD+) concentration, telomerase activity and total antioxidant capacity; and (iii) lead to endothelial dysfunction through compromised nitric oxide (NOx) production. However, these LPS-mediated cellular events in Eahy926 cells were restored by the synergistic effect of MET and VD. Taken together, this study identified that the dual compound effect inhibits LPS-induced protein arginine methylation, endothelial senescence and dysfunction through the components of epigenetic machinery, SIRT1 and PRMT1, which is a previously unidentified function of the test compounds. In silico results identified the presence of vitamin D response element (VDRE) sequence on PRMT1 suggesting that VDR could regulate PRMT1 gene expression. Further characterization of the cellular events associated with the dual compound challenge, using gene silencing approach or adenoviral constructs for SIRT1 and/or PRMT1 under inflammatory stress, could identify therapeutic strategies to address the endothelial consequences in vascular inflammation-mediated atherosclerosis.

Therapeutic Potential of Extracellular Vesicles for Sepsis Treatment

Sepsis is a deadly condition lacking a specific treatment despite decades of research. This has prompted the exploration of new approaches, with extracellular vesicles (EVs) emerging as a focal area. EVs are nanosized, cell-derived particles that transport bioactive components (i.e., proteins, DNA, and RNA) between cells, enabling both normal physiological functions and disease progression depending on context. In particular, EVs have been identified as critical mediators of sepsis pathophysiology. However, EVs are also thought to constitute the biologically active component of cell-based therapies and have demonstrated anti-inflammatory, anti-apoptotic, and immunomodulatory effects in sepsis models. The dual nature of EVs in sepsis is explored here, discussing their endogenous roles and highlighting their therapeutic properties and potential. Related to the latter component, prior studies involving EVs from mesenchymal stem/stromal cells (MSCs) and other sources are discussed and emerging producer cells that could play important roles in future EV-based sepsis therapies are identified. Further, how methodologies could impact therapeutic development toward sepsis treatment to enhance and control EV potency is described.

ARDS metabolic fingerprints: characterization, benchmarking, and potential mechanistic interpretation

In this study, we aimed to identify acute respiratory distress syndrome (ARDS) metabolic fingerprints in selected patient cohorts and compare the metabolic profiles of direct versus indirect ARDS and hypoinflammatory versus hyperinflammatory ARDS. We hypothesized that the biological and inflammatory processes in ARDS would manifest as unique metabolomic fingerprints that set ARDS apart from other intensive care unit (ICU) conditions and could help examine ARDS subphenotypes and clinical subgroups. Patients with ARDS (n = 108) and ICU ventilated controls (n = 27) were included. Samples were randomly divided into 2/3 training and 1/3 test sets. Samples were analyzed using ¹H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry. Twelve proteins/cytokines were also measured. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to select the most differentiating ARDS metabolites and protein/cytokines. Predictive performance of OPLS-DA models was measured in the test set. Temporal changes of metabolites were examined as patients progressed through ARDS until clinical recovery. Metabolic profiles of direct versus indirect ARDS subgroups and hypoinflammatory versus hyperinflammatory ARDS subgroups were compared. Serum metabolomics and proteins/cytokines had similar area under receiver operator curves when distinguishing ARDS from ICU controls. Pathway analysis of ARDS differentiating metabolites identified a dominant involvement of serine-glycine metabolism. In longitudinal tracking, the identified pathway metabolites generally exhibited correction by 7-14 days, coinciding with clinical improvement. ARDS subphenotypes and clinical subgroups were metabolically distinct. However, our identified metabolic fingerprints are not ARDS diagnostic biomarkers, and further research is required to ascertain generalizability. In conclusion, patients with ARDS are metabolically different from ICU controls. ARDS subphenotypes and clinical subgroups are metabolically distinct.

Endothelial response to glucose: dysfunction, metabolism, and transport

The endothelial cell response to glucose plays an important role in both health and disease. Endothelial glucose-induced dysfunction was first studied in diabetic animal models and in cells cultured in hyperglycemia. Four classical dysfunction pathways were identified, which were later shown to result from the common mechanism of mitochondrial superoxide overproduction. More recently, non-coding RNA, extracellular vesicles, and sodium-glucose cotransporter-2 inhibitors were shown to affect glucose-induced endothelial dysfunction. Endothelial cells also metabolize glucose for their own energetic needs. Research over the past decade highlighted how manipulation of endothelial glycolysis can be used to control angiogenesis and microvascular permeability in diseases such as cancer. Finally, endothelial cells transport glucose to the cells of the blood vessel wall and to the parenchymal tissue. Increasing evidence from the blood-brain barrier and peripheral vasculature suggests that endothelial cells regulate glucose transport through glucose transporters that move glucose from the apical to the basolateral side of the cell. Future studies of endothelial glucose response should begin to integrate dysfunction, metabolism and transport into experimental and computational approaches that also consider endothelial heterogeneity, metabolic diversity, and parenchymal tissue interactions.

The Glycocalyx and Its Role in Vascular Physiology and Vascular Related Diseases

Purpose

In 2007 the two senior authors wrote a review on the structure and function of the endothelial glycocalyx layer (Weinbaum in Annu Rev Biomed Eng 9:121–167, 2007). Since then there has been an explosion of interest in this hydrated gel-like structure that coats the luminal surface of endothelial cells that line our vasculature due to its important functions in (A) basic vascular physiology and (B) vascular related diseases. This review will highlight the major advances that have occurred since our 2007 paper.

Methods

A literature search mainly focusing on the role of the glycocalyx in the two major areas described above was performed using electronic databases.

Results

In part (A) of this review, the new formulation of the century old Starling principle, now referred to as the Michel–Weinbaum glycoclayx model or revised Starling hypothesis, is described including new subtleties and physiological ramifications. New insights into mechanotransduction and release of nitric oxide due to fluid shear stress sensed by the glycocalyx are elaborated. Major advances in understanding the organization and function of glycocalyx components, and new techniques for measuring both its thickness and spatio-chemical organization based on super resolution, stochastic optical reconstruction microscopy (STORM) are presented. As discussed in part (B) of this review, it is now recognized that artery wall stiffness associated with hypertension and aging induces glycocalyx degradation, endothelial dysfunction and vascular disease. In addition to atherosclerosis and cardiovascular diseases, the glycocalyx plays an important role in lifestyle related diseases (e.g., diabetes) and cancer. Infectious diseases including sepsis, Dengue, Zika and Corona viruses, and malaria also involve the glycocalyx. Because of increasing recognition of the role of the glycocalyx in a wide range of diseases, there has been a vigorous search for methods to protect the glycocalyx from degradation or to enhance its synthesis in disease environments.

Conclusion

As we have seen in this review, many important developments in our basic understanding of GCX structure, function and role in diseases have been described since the 2007 paper. The future is wide open for continued GCX research.

Single-Cell RNA Sequencing Maps Endothelial Metabolic Plasticity in Pathological Angiogenesis

Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor angiogenesis and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcriptomes. By single-cell RNA sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference predicted that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. ECs displayed metabolic transcriptome heterogeneity during cell-cycle progression and in quiescence. Hypothesizing that conserved genes are important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome-scale metabolic modeling, and gene expression meta-analysis in cross-species datasets, followed by in vitro and in vivo validation, to identify SQLE and ALDH18A1 as previously unknown metabolic angiogenic targets.

Glycocalyx in Endotoxemia and Sepsis

Along with the recognition of a crucial role played by endothelial dysfunction secondarily igniting cardiovascular, pulmonary, and renal complications, investigational focus has extended toward endothelial glycocalyx. This delicate coating of cells, including the vascular endothelium, regulates permeability, leukocyte traffic, nitric oxide production, and coagulation, and harbors diverse growth and survival factors. In this brief overview, we discuss the metabolic signatures of sepsis as they relate to the loss of glycocalyx integrity and highlight the contribution of several proteases, heparanase, and hyaluronidase to the shedding of glycocalyx. Clinical manifestations of glycocalyx degradation in unraveling acute respiratory distress syndrome and the cardiovascular, microcirculatory, and renal complications of sepsis are concisely presented. Finally, we list therapeutic strategies for preventing the degradation of, and for restoration of, the glycocalyx.

Comparative Metabolic Network Flux Analysis to Identify Differences in Cellular Metabolism

Metabolic network flux analysis uses genome-scale metabolic reconstructions to integrate transcriptomics, proteomics, and/or metabolomics data to allow for comprehensive interpretation of genotype to metabolic phenotype relationships. The compilation of many Constraint-based model analysis methods into one MATLAB package, the COBRAtoolbox, has opened the possibility of using these methods to the many biologists with some knowledge of the commonly used statistical program, MATLAB. Here we outline the steps required to take a published genome-scale metabolic reconstruction and interrogate its consistency and biological feasibility. Subsequently, we demonstrate how mRNA expression data and metabolomics data, relating to one or more cell types or biological contexts, can be applied to constrain and generate metabolic models descriptive of metabolic flux phenotypes. Finally, we describe the comparison of the resulting models and model outputs with the aim of identifying metabolic biomarkers and changes in cellular metabolism.

Current status and applications of genome-scale metabolic models

Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction associations for entire metabolic genes in an organism, and can be simulated to predict metabolic fluxes for various systems-level metabolic studies. Since the first GEM for Haemophilus influenzae was reported in 1999, advances have been made to develop and simulate GEMs for an increasing number of organisms across bacteria, archaea, and eukarya. Here, we review current reconstructed GEMs and discuss their applications, including strain development for chemicals and materials production, drug targeting in pathogens, prediction of enzyme functions, pan-reactome analysis, modeling interactions among multiple cells or organisms, and understanding human diseases.

Cooling therapy upregulates protein C activation in heat stressed rats: An experimental study

Protein C (PC) pathway homeostasis is implicated in heat stress (HS). This study determines whether cooling could improve the PC pathway in HS. Fifty-six anesthetized rats were warmed to achieve HS (rectal temperature [Tr] 42°C). These rats were divided into seven groups: (a) control group:sacrifice immediately 15 min after HS; (b) HS+I:sacrifice immediately after 15 min ice-water treatment or (c) 3 hr after HS; (d) HS+C:sacrifice immediately after 15-min cold-water treatment or (e) 3 hr after HS; (f) HS: sacrifice immediately 15 min after HS or (g) 3 hr after HS. Plasma PC, activated protein C (APC), and soluble thrombomodulin (sTM) levels were tested at both time points. After cooling, Tr in the HS+I and HS+C groups significantly decreased, when compared with the HS group, and Tr was significantly lower in the HS+I group than in the HS+C group ( p < 0.05). Furthermore, sTM levels were highest in the HS group among the groups at both time points. Plasma PC and APC levels increased after HS. In the HS+I and HS+C groups, plasma APC levels and the APC/PC ratio significantly increased at both time points. The proportions were significantly higher in the HS+I group than in the HS+C group, and there was no significant increase in APC/PC ratio in the HS group. Cooling exerts an anticoagulant effect following HS by increasing APC levels. Ice-water blanket therapy is more effective than cold-water blanket therapy in increasing APC levels.

Transcriptional Analysis of Sepsis-Induced Activation and Damage of the Adrenal Endothelial Microvascular Cells

Bacterial sepsis is a serious threat to the body homeostasis and is often associated with high mortality in non-coronary intensive stations. In order to survive sepsis, rapid activation of the hypothalamus-pituitary-adrenal gland axis and sympathomedullary system is necessary. In many patients with sepsis, the function of those two arms of the stress system is dysregulated with underlying mechanisms remaining unknown. In our previous experimental studies, we have demonstrated that LPS-induced systemic inflammation and CLP-induced peritonitis can result in adrenal gland damage. Histological and transcriptomic analysis revealed a potential involvement of the adrenal microvascular endothelium in this process. However, our knowledge about the function of adrenal microvascular cells during sepsis is scarce. In the present study, we have characterized transcriptomic alterations in isolated mouse adrenal microvascular endothelial cells induced by systemic administration of bacterial LPS. Our results revealed that LPS induced a distinct transcriptomic profile in the adrenal microvascular cells, including multiple genes regulating inflammation, activation of the coagulation cascade and vascular permeability. Activation of those genes may be potentially involved in the damage to the microvascular endothelium and altogether contribute to the sepsis-mediated adrenal dysregulation.