Computational Analysis of Insulin-Glucagon Signalling Network: Implications of Bistability to Metabolic Homeostasis and Disease states

Combating chronic kidney disease-associated cachexia: A literature review of recent therapeutic approaches

In 2008, the Society on Sarcopenia, Cachexia, and Wasting Disorders introduced a generic definition for all types of cachexia: "a complex metabolic syndrome associated with the underlying illness characterized by a loss of muscle, with or without fat loss". It is well-known that the presence of inflammatory burden in end-stage renal disease (ESRD) patients may lead to the evolution of cachexia. Since the etiology of cachexia in chronic kidney disease (CKD) is multifactorial, thus the successful treatment must involve several concomitant measures (nutritional interventions, appetite stimulants, and anti-inflammatory pharmacologic agents) to provide integrated effective therapeutic modalities to combat causative factors and alleviate the outcomes of patients. Given the high mortality rate associated with cachexia, developing new therapeutic modalities are prerequisite for ameliorating patients with CKD worldwide. The present review aims to discuss some therapeutic strategies and provide an update on advances in nutritional approaches to counteract cachexia.

Experimentally-driven mathematical model to understand the effects of matrix deprivation in breast cancer metastasis

Normal epithelial cells receive proper signals for growth and survival from attachment to the underlying extracellular matrix (ECM). They perceive detachment from the ECM as a stress and die - a phenomenon termed as 'anoikis'. However, metastatic cancer cells acquire anoikis-resistance and circulate through the blood and lymphatics to seed metastasis. Under normal (adherent) growth conditions, the serine-threonine protein kinase Akt stimulates protein synthesis and cell growth, maintaining an anabolic state in the cancer cell. In contrast, previously we showed that the stress due to matrix deprivation is sensed by yet another serine-threonine kinase, AMP-activated protein kinase (AMPK), that inhibits anabolic pathways while promoting catabolic processes. We illustrated a switch from Akthigh/AMPKlow in adherent condition to AMPKhigh/Aktlow in matrix-detached condition, with consequent metabolic switching from an anabolic to a catabolic state, which aids cancer cell stress-survival. In this study, we utilized these experimental data and developed a deterministic ordinary differential equation (ODE)-based mechanistic mathematical model to mimic attachment-detachment signaling network. To do so, we used the framework of insulin-glucagon signaling with consequent metabolic shifts to capture the pathophysiology of matrix-deprived state in breast cancer cells. Using the developed metastatic breast cancer signaling (MBCS) model, we identified perturbation of several signaling proteins such as IRS, PI3K, PKC, GLUT1, IP3, DAG, PKA, cAMP, and PDE3 upon matrix deprivation. Further, in silico molecular perturbations revealed that several feedback/crosstalks like DAG to PKC, PKC to IRS, S6K1 to IRS, cAMP to PKA, and AMPK to Akt are essential for the metabolic switching in matrix-deprived cancer cells. AMPK knockdown simulations identified a crucial role for AMPK in maintaining these adaptive changes. Thus, this mathematical framework provides insights on attachment-detachment signaling with metabolic adaptations that promote cancer metastasis.

Network medicine based approach for identifying the type 2 diabetes, osteoarthritis and triple negative breast cancer interactome: Finding the hub of hub genes

The increasing prevalence of multi-morbidities, particularly the incidence of breast cancer in diabetic/osteoarthritic patients emphasize on the need for exploring the underlying molecular mechanisms resulting in carcinogenesis. To address this, present study employed a systems biology approach to identify switch genes pivotal to the crosstalk between diseased states resulting in multi-morbid conditions. Hub genes previously reported for type 2 diabetes mellitus (T2DM), osteoarthritis (OA), and triple negative breast cancer (TNBC), were extracted from published literature and fed into an integrated bioinformatics analyses pipeline. Thirty-one hub genes common to all three diseases were identified. Functional enrichment analyses showed these were mainly enriched for immune and metabolism associated terms including advanced glycation end products (AGE) pathways, cancer pathways, particularly breast neoplasm, immune system signalling and adipose tissue. The T2DM-OA-TNBC interactome was subjected to protein-protein interaction network analyses to identify meta hub/clustered genes. These were prioritized and wired into a three disease signalling map presenting the enriched molecular crosstalk on T2DM-OA-TNBC axes to gain insight into the molecular mechanisms underlying disease-disease interactions. Deciphering the molecular bases for the intertwined metabolic and immune states may potentiate the discovery of biomarkers critical for identifying and targeting the immuno-metabolic origin of disease.

Daily Brain Metabolic Rhythms of Wild Nocturnal Bats

Circadian rhythms are found in a wide range of organisms and have garnered significant research interest in the field of chronobiology. Under normal circadian function, metabolic regulation is temporally coordinated across tissues and behaviors within a 24 h period. Metabolites, as the closest molecular regulation to physiological phenotype, have dynamic patterns and their relationship with circadian regulation remains to be fully elucidated. In this study, untargeted brain metabolomics was employed to investigate the daily rhythms of metabolites at four time points corresponding to four typical physiological states in Vespertilio sinensis. Key brain metabolites and associated physiological processes active at different time points were detected, with 154 metabolites identified as rhythmic. Analyses of both metabolomics and transcriptomics revealed that several important physiological processes, including the pentose phosphate pathway and oxidative phosphorylation, play key roles in regulating rhythmic physiology, particularly in hunting and flying behaviors. This study represents the first exploration of daily metabolic dynamics in the bat brain, providing insights into the complex regulatory network of circadian rhythms in mammals at a metabolic level. These findings serve as a valuable reference for future studies on circadian rhythms in nocturnal mammals.

Dynamic Muscle Function Parameters in Indian Children and Adolescents with Type 1 Diabetes Mellitus: A Case-Control Study

Introduction

Recent evidence reveals that type 1 diabetes mellitus (T1DM) impairs muscle function (MF) in adolescents. However, despite its importance in physical well-being, data on dynamic MF in Indian children and adolescents (C and Y) with T1DM are scarce. We assessed MF using Jumping Mechanography (JM, a measurement method for motion analysis and assessment of muscle power and force). (1) To assess dynamic MF by JM in C and Y with T1DM as compared to healthy controls (2) To determine predictors of MF in children with T1DM.

Methods

A cross-sectional observational study on 266 children (133 - T1DM duration >1 year with no known comorbidities + 133 age and gender-matched healthy controls) aged 6-19 years. Anthropometry, body composition, and MF (maximum relative power Pmax/mass, maximum relative force Fmax/BW by JM) were recorded. The lean mass index (LMI) was calculated as lean mass (kg)/height (m2). HbA1c was assessed in T1DM. Independent sample t-test and linear regression were performed.

Results

MF parameters (Pmax/mass 33.5 ± 7.2 vs 38.0 ± 8.6 W/kg and Fmax/BW 10.5 ± 2.9 vs 11.4 ± 4.1 N/kg, P < 0.05) were significantly lower in T1DM group vs controls. Positive association of body mass index and LMI with both MF parameters and negative association of insulin requirement and HbA1c with Fmax was observed in T1DM. Predictors of MF identified were MMI (Pmax/mass:b = 1.6,95%CI = 0.6-2.6; Fmax/BW:b =2.0,95%CI = 1.6-2.4) and HbA1c (Pmax/mass:b = -2.1,95%CI = -4.5--0.5; Fmax/BW:b = -1.1,95%CI = -2.0--0.2) (P < 0.05).

Conclusion

C and Y with T1DM exhibits compromised muscle function. Poor glycaemic control increases the risk of having decreased MF, irrespective of diabetes duration and may contribute to sarcopenia in adulthood.

Higher Glycemic Index and Glycemic Load Diet Is Associated with Slower Disease Progression in Amyotrophic Lateral Sclerosis

OBJECTIVE

High-caloric diets may slow the progression of amyotrophic lateral sclerosis; however, key macronutrients have not been identified. We examined whether dietary macronutrients are associated with the rate of progression and length of survival among the prospective cohort study participants.

METHODS

Participants with a confirmed diagnosis of sporadic amyotrophic lateral sclerosis enrolled in the Multicenter Cohort Study of Oxidative Stress were included (n = 304). We evaluated baseline macronutrient intake assessed by food frequency questionnaire in relation to change in revised amyotrophic lateral sclerosis functional rating scale total-score, and tracheostomy-free survival using linear regression and Cox proportional hazard models. Baseline age, sex, disease duration, diagnostic certainty, body mass index, bulbar onset, revised amyotrophic lateral sclerosis functional rating scale total-score, and forced vital capacity were included as covariates.

RESULTS

Baseline higher glycemic index and load were associated with less decline of revised amyotrophic lateral sclerosis functional rating scale total score at 3-month follow-up (β = -0.13, 95% CI -0.2, -0.01, p = 0.03) and (β = -0.01, 95% CI -0.03, -0.0007, p = 0.04), respectively. Glycemic index second-quartile, third-quartile, and fourth-quartile groups were associated with less decline at 3 months by 1.9 (95% CI -3.3, -0.5, p = 0.008), 2.0 (95% CI -3.3, -0.6, p = 0.006), and 1.6 (95% CI -3.0, -0.2, p = 0.03) points compared with the first-quartile group; the glycemic load fourth-quartile group had 1.4 points less decline compared with the first-quartile group (95% CI -2.8, 0.1, p = 0.07). Higher glycemic index was associated with a trend toward longer tracheostomy-free survival (HR 0.97, 95% CI 0.93, 1.00, p = 0.07).

INTERPRETATION

Higher dietary glycemic index and load are associated with slower disease progression in amyotrophic lateral sclerosis. ANN NEUROL 2024;95:217-229.

Gut microbiota and its roles in the pathogenesis and therapy of endocrine system diseases

A new field of microbial research is the relationship between microorganisms and multicellular hosts. It is known that gut microbes can cause various endocrine system diseases, such as diabetes and thyroid disease. Changes in the composition or structure and the metabolites of gut microbes may cause gastrointestinal disorders, including ulcers or intestinal perforation and other inflammatory and autoimmune diseases. In recent years, reports on the interactions between intestinal microorganisms and endocrine system diseases have been increasingly documented. In the meantime, the treatment based on gut microbiome has also been paid much attention. For example, fecal microbiota transplantation is found to have a therapeutic effect on many diseases. As such, understanding the gut microbiota-endocrine system interactions is of great significance for the theranostic of endocrine system diseases. Herein, we summarize the relations of gut microbiome with endocrine system diseases, and discuss the potentials of regulating gut microbiome in treating those diseases. In addition, the concerns and possible solutions regarding the gut microbiome-based therapy are discussed.

Chronic inflammatory arthritis drives systemic changes in circadian energy metabolism

Chronic inflammation underpins many human diseases. Morbidity and mortality associated with chronic inflammation are often mediated through metabolic dysfunction. Inflammatory and metabolic processes vary through circadian time, suggesting an important temporal crosstalk between these systems. Using an established mouse model of rheumatoid arthritis, we show that chronic inflammatory arthritis results in rhythmic joint inflammation and drives major changes in muscle and liver energy metabolism and rhythmic gene expression. Transcriptional and phosphoproteomic analyses revealed alterations in lipid metabolism and mitochondrial function associated with increased EGFR-JAK-STAT3 signaling. Metabolomic analyses confirmed rhythmic metabolic rewiring with impaired β-oxidation and lipid handling and revealed a pronounced shunt toward sphingolipid and ceramide accumulation. The arthritis-related production of ceramides was most pronounced during the day, which is the time of peak inflammation and increased reliance on fatty acid oxidation. Thus, our data demonstrate that localized joint inflammation drives a time-of-day–dependent build-up of bioactive lipid species driven by rhythmic inflammation and altered EGFR-STAT signaling.

Continuous variable responses and signal gating form kinetic bases for pulsatile insulin signaling and emergence of resistance

Evolutionarily conserved insulin signaling is central to nutrient sensing, storage, and utilization across tissues. Dysfunctional insulin signaling is associated with metabolic disorders, cancer, and aging. Hence, the pathway components have emerged as key targets for pharmacological interventions in addition to insulin administration itself. Despite this, activation–inactivation dynamics of individual components, which exert regulatory control in a physiological context, is poorly understood. Now, with our systems-based approach, we reveal kinetic parameters, which define the flow of information through both metabolic and growth-factor arms and thus determine signaling architecture. We also provide a kinetic basis for 1) the advantage of pulsatile-fasted insulin signaling that enables fed-insulin response and 2) the detrimental impact of repeat fed-insulin inputs that causes resistance.

Understanding kinetic control of biological processes is as important as identifying components that constitute pathways. Insulin signaling is central for almost all metazoans, and its perturbations are associated with various developmental disorders, metabolic diseases, and aging. While temporal phosphorylation changes and kinetic constants have provided some insights, constant or variable parameters that establish and maintain signal topology are poorly understood. Here, we report kinetic parameters that encode insulin concentration and nutrient-dependent flow of information using iterative experimental and mathematical simulation-based approaches. Our results illustrate how dynamics of distinct phosphorylation events collectively contribute to selective kinetic gating of signals and maximum connectivity of the signaling cascade under normo-insulinemic but not hyper-insulinemic states. In addition to identifying parameters that provide predictive value for maintaining the balance between metabolic and growth-factor arms, we posit a kinetic basis for the emergence of insulin resistance. Given that pulsatile insulin secretion during a fasted state precedes a fed response, our findings reveal rewiring of insulin signaling akin to memory and anticipation, which was hitherto unknown. Striking disparate temporal behavior of key phosphorylation events that destroy the topology under hyper-insulinemic states underscores the importance of unraveling regulatory components that act as bandwidth filters. In conclusion, besides providing fundamental insights, our study will help in identifying therapeutic strategies that conserve coupling between metabolic and growth-factor arms, which is lost in diseases and conditions of hyper-insulinemia.

Robust adaptation of PKCζ-IRS1 insulin signaling pathways through integral feedback control

Insulin signaling pathways in muscle tissue play a major role in maintaining glucose homeostasis. Dysregulation in these pathways results in the onset of serious metabolic disorders like type 2 diabetes. Robustness is an essential characteristic of insulin signaling pathways that ensures reliable signal transduction in the presence of perturbations as a result of several feedback mechanisms. Integral control, according to control engineering, provides reliable setpoint tracking and disturbance rejection. The presence of negative feedback and integrating process is crucial for biological processes to achieve integral control. The existence of an integral controller leads to the rejection of perturbations which resulted in the robust regulation of biochemical entities within acceptable levels. In the presentin silicoresearch work, the presence of integral control in the protein kinase Cζ- insulin receptor substrate-1 (PKCζ-IRS1) pathway is identified, verified mathematically and model is simulated in Cell Designer. The data is exported to Minitab software and robustness analysis is carried out statistically using the Mann-Whitney test. The p-value of the results obtained with given parameters perturbed by ±1% is greater than the significance level of 0.05 (0.2132 for 1% error in k7(rate constant of IRS1 phosphorylation), 0.2096 for -1% error in k7, 0.9037 for both ±1% error in insulin and 0.9037 for ±1% error in k1(association rate constant of the first molecule of insulin to bind the insulin receptor), indicated that our hypothesis is proved The results satisfactorily indicate that even when perturbations are present, glucose homeostasis in muscle tissue is robust due to the presence of integral regulation in the PKCζ-IRS1 insulin signaling pathways. In this paper, we have analysed the findings from the framework of robust control theory, which has allowed us to examine that how PKCζ-IRS1 insulin signaling pathways produces desired output in presence of perturbations.

ROS systems are a new integrated network for sensing homeostasis and alarming stresses in organelle metabolic processes

Reactive oxygen species (ROS) are critical for the progression of cardiovascular diseases, inflammations and tumors. However, the mechanisms of how ROS sense metabolic stress, regulate metabolic pathways and initiate proliferation, inflammation and cell death responses remain poorly characterized. In this analytic review, we concluded that: 1) Based on different features and functions, eleven types of ROS can be classified into seven functional groups: metabolic stress-sensing, chemical connecting, organelle communication, stress branch-out, inflammasome-activating, dual functions and triple functions ROS. 2) Among the ROS generation systems, mitochondria consume the most amount of oxygen; and nine types of ROS are generated; thus, mitochondrial ROS systems serve as the central hub for connecting ROS with inflammasome activation, trained immunity and immunometabolic pathways. 3) Increased nuclear ROS production significantly promotes cell death in comparison to that in other organelles. Nuclear ROS systems serve as a convergent hub and decision-makers to connect unbearable and alarming metabolic stresses to inflammation and cell death. 4) Balanced ROS levels indicate physiological homeostasis of various metabolic processes in subcellular organelles and cytosol, while imbalanced ROS levels present alarms for pathological organelle stresses in metabolic processes. Based on these analyses, we propose a working model that ROS systems are a new integrated network for sensing homeostasis and alarming stress in metabolic processes in various subcellular organelles. Our model provides novel insights on the roles of the ROS systems in bridging metabolic stress to inflammation, cell death and tumorigenesis; and provide novel therapeutic targets for treating those diseases. (Word count: 246).