The role of propionic acid at diagnosis predicts mortality in patients with septic shock

Gut Microbiome-Based Therapeutics in Critically Ill Adult Patients-A Narrative Review

The gut microbiota plays a crucial role in the human microenvironment. Dysbiosis of the gut microbiota is a common pathophysiological phenomenon in critically ill patients. Therefore, utilizing intestinal microbiota to prevent complications and improve the prognosis of critically ill patients is a possible therapeutic direction. The gut microbiome-based therapeutics approach focuses on improving intestinal microbiota homeostasis by modulating its diversity, or treating critical illness by altering the metabolites of intestinal microbiota. There is growing evidence that fecal microbiota transplantation (FMT), selective digestive decontamination (SDD), and microbiota-derived therapies are all effective treatments for critical illness. However, different treatments are appropriate for different conditions, and more evidence is needed to support the selection of optimal gut microbiota-related treatments for different diseases. This narrative review summarizes the curative effects and limitations of microbiome-based therapeutics in different critically ill adult patients, aiming to provide possible directions for gut microbiome-based therapeutics for critically ill patients such as ventilator-associated pneumonia, sepsis, acute respiratory distress syndrome, and COVID-19, etc.

Protein modification by short-chain fatty acid metabolites in sepsis: a comprehensive review

Sepsis is a major life-threatening syndrome of organ dysfunction caused by a dysregulated host response due to infection. Dysregulated immunometabolism is fundamental to the onset of sepsis. Particularly, short-chain fatty acids (SCFAs) are gut microbes derived metabolites serving to drive the communication between gut microbes and the immune system, thereby exerting a profound influence on the pathophysiology of sepsis. Protein post-translational modifications (PTMs) have emerged as key players in shaping protein function, offering novel insights into the intricate connections between metabolism and phenotype regulation that characterize sepsis. Accumulating evidence from recent studies suggests that SCFAs can mediate various PTM-dependent mechanisms, modulating protein activity and influencing cellular signaling events in sepsis. This comprehensive review discusses the roles of SCFAs metabolism in sepsis associated inflammatory and immunosuppressive disorders while highlights recent advancements in SCFAs-mediated lysine acylation modifications, such as substrate supplement and enzyme regulation, which may provide new pharmacological targets for the treatment of sepsis.

Application background and mechanism of short-chain fatty acids in sepsis-associated encephalopathy

Sepsis-associated encephalopathy (SAE) is a frequent brain dysfunction found in sepsis patients, manifesting as delirium, cognitive impairment, and abnormal behaviors. The gut microbiome and short-chain fatty acids (SCFAs) are particularly associated with neuroinflammation in patients with SAE, thus noticeably attracting scholars’ attention. The association of brain function with the gut-microbiota-brain axis was frequently reported. Although the occurrence, development, and therapeutic strategies of SAE have been extensively studied, SAE remains a critical factor in determining the long-term prognosis of sepsis and is typically associated with high mortality. This review concentrated on the interaction of SCFAs with microglia in the central nervous system and discussed the anti-inflammatory and immunomodulatory effects of SCFAs by binding to free fatty acid receptors or acting as histone deacetylase inhibitors. Finally, the prospects of dietary intervention using SCFAs as dietary nutrients in improving the prognosis of SAE were reviewed.

Effect of Admission and Discharge Times on Hospital Mortality in Patients With Sepsis

OBJECTIVES

To assess whether the time of admission/discharge time from the ICU and weekend admission are independently associated with hospital mortality in critically ill patients with sepsis.

DESIGN

Retrospective study. Each 24-hour period (08:00 to 07:59 hr) was split into three time periods, defined as "day" (08:00 to 16:59 hr), "evening" (17:00 to 23:59 hr), and "night" (00:00 to 07:59 hr). Weekends were defined as 17:00 hours on Friday to 07:59 hours on Monday. Multivariate logistic regression models were conducted to assess the association between the ICU admission/discharge time, weekend admission, and hospital mortality.

SETTING

Single-center ICUs in China.

PATIENTS

Characteristics and clinical outcomes of 1,341 consecutive septic patients admitted to the emergency ICU, general ICU, or cardiovascular ICU in a tertiary teaching hospital were collected.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

ICU mortality rates were 5.8%, 11.9%, and 10.6%, and hospital mortality rates were 7.3%, 15.6%, and 17.1% during the day, evening, and night time, respectively. Hospital mortality was adjusted for patient to nurse (P/N) ratio, disease severity, Charlson index, age, gender, mechanical ventilation, and shock. Notably, ICU admission time and weekend admission were not predictors of mortality after adjustment. The P/N ratio at admission was significantly associated with mortality ( p < 0.05). The P/N ratio and compliance with the Surviving Sepsis Campaign (SSC) were significantly correlated. After risk adjustment for illness severity at time of ICU discharge and Charlson index, the time of discharge was no longer a significant predictor of mortality.

CONCLUSIONS

ICU admission/discharge time and weekend admission were not independent risk factors of hospital mortality in critically ill patients with sepsis. The P/N ratio at admission, which can affect the compliance rate with SSC, was a predictor of hospital survival. Unstable state on transfer from the ICU was the main risk factor for in-hospital death. These findings may have implications for the management of septic patients.

Characterization of diet-dependent temporal changes in circulating short-chain fatty acid concentrations: A randomized crossover dietary trial

BACKGROUND

Production of SCFAs from food is a complex and dynamic saccharolytic fermentation process mediated by both human and gut microbial factors. Knowledge of SCFA production and of the relation between SCFA profiles and dietary patterns is lacking.

OBJECTIVES

Temporal changes in SCFA concentrations in response to 2 contrasting diets were investigated using a novel GC-MS method.

METHODS

Samples were obtained from a randomized, controlled, crossover trial designed to characterize the metabolic response to 4 diets. Participants (n = 19) undertook these diets during an inpatient stay (of 72 h). Serum samples were collected 2 h after breakfast (AB), after lunch (AL), and after dinner (AD) on day 3, and a fasting sample (FA) was obtained on day 4. The 24-h urine samples were collected on day 3. In this substudy, samples from the 2 extreme diets representing a diet with high adherence to WHO healthy eating recommendations and a typical Western diet were analyzed using a bespoke GC-MS method developed to detect and quantify 10 SCFAs and precursors in serum and urine samples.

RESULTS

Considerable interindividual variation in serum SCFA concentrations was observed across all time points, and temporal fluctuations were observed for both diets. Although the sample collection timing exerted a greater magnitude of effect on circulating SCFA concentrations, the unhealthy diet was associated with a lower concentration of acetic acid (FA: coefficient: -17.0; SE: 5.8; P-trend = 0.00615), 2-methylbutyric acid (AL: coefficient: -0.1; SE: 0.028; P-trend = 4.13 × 10-4 and AD: coefficient: -0.1; SE: 0.028; P-trend = 2.28 × 10-3), and 2-hydroxybutyric acid (FA: coefficient: -15.8; SE: 5.11; P-trend: 4.09 × 10-3). In contrast, lactic acid was significantly higher in the unhealthy diet (AL: coefficient: 750.2; SE: 315.2; P-trend = 0.024 and AD: coefficient: 1219.3; SE: 322.6; P-trend: 8.28 × 10-4).

CONCLUSIONS

The GC-MS method allowed robust mapping of diurnal patterns in SCFA concentrations, which were affected by diet, and highlighted the importance of standardizing the timing of SCFA measurements in dietary studies. This trial was registered on the NIHR UK clinical trial gateway and with ISRCTN as ISRCTN43087333.

Systemic inflammation and metabolic disturbances underlie inpatient mortality among ill children with severe malnutrition

Children admitted to hospital with an acute illness and concurrent severe malnutrition [complicated severe malnutrition (CSM)] have a high risk of dying. The biological processes underlying their mortality are poorly understood. In this case-control study nested within a multicenter randomized controlled trial among children with CSM in Kenya and Malawi, we found that blood metabolomic and proteomic profiles robustly differentiated children who died (n = 92) from those who survived (n = 92). Fatalities were characterized by increased energetic substrates (tricarboxylic acid cycle metabolites), microbial metabolites (e.g., propionate and isobutyrate), acute phase proteins (e.g., calprotectin and C-reactive protein), and inflammatory markers (e.g., interleukin-8 and tumor necrosis factor-α). These perturbations indicated disruptions in mitochondria-related bioenergetic pathways and sepsis-like responses. This study identified specific biomolecular disturbances associated with CSM mortality, revealing that systemic inflammation and bioenergetic deficits are targetable pathophysiological processes for improving survival of this vulnerable population.

Aminophylline modulates the permeability of endothelial cells via the Slit2-Robo4 pathway in lipopolysaccharide-induced inflammation

Sepsis and septic shock are the main cause of mortality in intensive care units. The prevention and treatment of sepsis remains a significant challenge worldwide. The endothelial cell barrier plays a critical role in the development of sepsis. Aminophylline, a non-selective phosphodiesterase inhibitor, has been demonstrated to reduce endothelial cell permeability. However, little is known regarding the role of aminophylline in regulating vascular permeability during sepsis, as well as the potential underlying mechanisms. In the present study, the Slit2/Robo4 signaling pathway, the downstream protein, vascular endothelial (VE)-cadherin and endothelial cell permeability were investigated in a lipopolysaccharide (LPS)-induced inflammation model. It was indicated that, in human umbilical vein endothelial cells (HUVECs), LPS downregulated Slit2, Robo4 and VE-cadherin protein expression levels and, as expected, increased endothelial cell permeability in vitro during inflammation. After administration of aminophylline, the protein expression levels of Slit2, Robo4 and VE-cadherin were upregulated and endothelial cell permeability was significantly improved. These results suggested that the permeability of endothelial cells could be mediated by VE-cadherin via the Slit2/Robo4 signaling pathway. Aminophylline reduced endothelial permeability in a LPS-induced inflammation model. Therefore, aminophylline may represent a promising candidate for modulating vascular permeability induced by inflammation or sepsis.

Clinical utility of characterizing intestinal flora in septic kidney injury

The incidence of septic acute kidney injury (AKI) is increasing, it has become a major threat to human health because of its acute onset, poor prognosis, and high hospital costs. The most common cause of AKI in critical-care units is sepsis. Septic AKI is a complex and multi-factorial process; its pathogenesis is not fully understood. In sepsis, the destruction of mucosal barriers, intestinal flora disorders, intestinal ischemia/reperfusion injury, use of antibiotics, and lack of intestinal nutrients lead to an inflammatory reactions that in turn affects the metabolism and immunity of the host. Such changes further influence the occurrence and development of AKI. New technology is enabling various detection methods for intestinal flora. Clinical application of these methods in septic renal injury is expected to clarify the relationship among pathogenesis, disease progression mechanism, and intestinal flora.

Applying mass spectrometry-based assays to explore gut microbial metabolism and associations with disease

The workings of the gut microbiome have gained increasing interest in recent years through the mounting evidence that the microbiota plays an influential role in human health and disease. A principal focus of this research seeks to further understand the production of metabolic by-products produced by bacteria resident in the gut, and the subsequent interaction of these metabolites on host physiology and pathophysiology of disease. Gut bacterial metabolites of interest are predominately formed via metabolic breakdown of dietary compounds including choline and ʟ-carnitine (trimethylamine N-oxide), amino acids (phenol- and indole-containing uremic toxins) and non-digestible dietary fibers (short-chain fatty acids). Investigations have been accelerated through the application of mass spectrometry (MS)-based assays to quantitatively assess the concentration of these metabolites in laboratory- and animal-based experiments, as well as for direct circulating measurements in clinical research populations. This review seeks to explore the impact of these metabolites on disease, as well as to introduce the application of MS for those less accustomed to its use as a clinical tool, highlighting pertinent research related to its use for measurements of gut bacteria-mediated metabolites to further understand their associations with disease.

A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock

Septic shock is induced by an uncontrolled inflammatory immune response to pathogens and the survival rate of patients with pediatric septic shock (PSS) is particularly low, with a mortality rate of 25‑50%. The present study explored the mechanisms of PSS using four microarray datasets (GSE26378, GSE26440, GSE13904 and GSE4607) that were obtained from the Gene Expression Omnibus database. Based on the MetaDE package, the consistently differentially expressed genes (DEGs) in the four datasets were screened. Using the WGCNA package, the disease‑associated modules and genes were identified. Subsequently, the optimal feature genes were further selected using the caret package. Finally, a support vector machine (SVM) classifier based on the optimal feature genes was built using the e1071 package. Initially, there were 2,699 consistent DEGs across the four datasets. From the 10 significantly stable modules across the datasets, four stable modules (including the magenta, purple, turquoise and yellow modules), in which the consistent DEGs were significantly enriched (P<0.05), were further screened. Subsequently, six optimal feature genes (including cysteine rich transmembrane module containing 1, S100 calcium binding protein A9, solute carrier family 2 member 14, stomatin, uridine phosphorylase 1 and utrophin) were selected from the genes in the four stable modules. Additionally, an effective SVM classifier was constructed based on the six optimal genes. The SVM classifier based on the six optimal genes has the potential to be applied for PSS diagnosis. This may improve the accuracy of early PSS diagnosis and suggest possible molecular targets for interventions.