Network medicine: facilitating a new view on complex diseases.

Complex diseases are prevalent medical conditions which are characterized by inter-patient heterogeneity with regards to symptom profiles, disease trajectory, comorbidities, and treatment response. Their pathophysiology involves a combination of genetic, environmental, and psychosocial factors. The intricacies of complex diseases, encompassing different levels of biological organization in the context of environmental and psychosocial factors, makes them difficult to study, understand, prevent, and treat.

The choice of the objective function in flux balance analysis is crucial for predicting replicative lifespans in yeast.

Flux balance analysis (FBA) is a powerful tool to study genome-scale models of the cellular metabolism, based on finding the optimal flux distributions over the network. While the objective function is crucial for the outcome, its choice, even though motivated by evolutionary arguments, has not been directly connected to related measures. Here, we used an available multi-scale mathematical model of yeast replicative ageing, integrating cellular metabolism, nutrient sensing and damage accumulation, to systematically test the effect of commonly used objective functions on features of replicative ageing in budding yeast, such as the number of cell divisions and the corresponding time between divisions.

Optimizing study design in LPS challenge studies for quantifying drug induced inhibition of TNFα response: Did we miss the prime time?

In this work we evaluate the study design of LPS challenge experiments used for quantification of drug induced inhibition of TNFα response and provide general guidelines of how to improve the study design. Analysis of model simulated data, using a recently published TNFα turnover model, as well as the optimal design tool PopED have been used to find the optimal values of three key study design variables - time delay between drug and LPS administration, LPS dose, and sampling time points - that in turn could make the resulting TNFα response data more informative. Our findings suggest that the current rule of thumb for choosing the time delay should be reconsidered, and that the placement of the measurements after maximal TNFα response are crucial for the quality of the experiment.

Multi-scale model suggests the trade-off between protein and ATP demand as a driver of metabolic changes during yeast replicative ageing.

The accumulation of protein damage is one of the major drivers of replicative ageing, describing a cell's reduced ability to reproduce over time even under optimal conditions. Reactive oxygen and nitrogen species are precursors of protein damage and therefore tightly linked to ageing. At the same time, they are an inevitable by-product of the cell's metabolism.

Scalable and flexible inference framework for stochastic dynamic single-cell models.

Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cellular processes and to rationalise cell-to-cell variability within the population.

The Effect of Lithium on the Budding Yeast upon Stress Adaptation.

Lithium salts are used in the treatment of mood disorders, cancer, and Alzheimer's disease. It has been shown to prolong life span in several phyla; however, not yet in budding yeast. In our study, we investigate the influence of lithium on yeast cells' viability by characterizing protein aggregate formation, cell volume, and molecular crowding in the context of stress adaptation.

The effect of stress on biophysical characteristics of misfolded protein aggregates in living Saccharomyces cerevisiae cells.

Aggregation of misfolded or damaged proteins is often attributed to numerous metabolic and neurodegenerative disorders. To reveal underlying mechanisms and cellular responses, it is crucial to investigate protein aggregate dynamics in cells. Here, we used super-resolution single-molecule microscopy to obtain biophysical characteristics of individual aggregates of a model misfolded protein ∆ssCPY* labelled with GFP.

Modelling of glucose repression signalling in yeast Saccharomyces cerevisiae.

Saccharomyces cerevisiae has a sophisticated signalling system that plays a crucial role in cellular adaptation to changing environments. The SNF1 pathway regulates energy homeostasis upon glucose derepression; hence, it plays an important role in various processes, such as metabolism, cell cycle and autophagy. To unravel its behaviour, SNF1 signalling has been extensively studied.

Second-generation TNFα turnover model for improved analysis of test compound interventions in LPS challenge studies.

This study presents a non-linear mixed effects model describing tumour necrosis factor alpha (TNFα) release after lipopolysaccharide (LPS) provocations in absence or presence of anti-inflammatory test compounds. Inter-occasion variability and the pharmacokinetics of two test compounds have been added to this second-generation model, and the goal is to produce a framework of how to model TNFα response in LPS challenge studies in vivo and demonstrate its general applicability regardless of occasion or type of test compound. Model improvements based on experimental data were successfully implemented and provided a robust model for TNFα response after LPS provocation, as well as reliable estimates of the median pharmacodynamic parameters.

A novel yeast hybrid modeling framework integrating Boolean and enzyme-constrained networks enables exploration of the interplay between signaling and metabolism.

The interplay between nutrient-induced signaling and metabolism plays an important role in maintaining homeostasis and its malfunction has been implicated in many different human diseases such as obesity, type 2 diabetes, cancer, and neurological disorders. Therefore, unraveling the role of nutrients as signaling molecules and metabolites together with their interconnectivity may provide a deeper understanding of how these conditions occur. Both signaling and metabolism have been extensively studied using various systems biology approaches.

A novel stepwise integrative analysis pipeline reveals distinct microbiota-host interactions and link to symptoms in irritable bowel syndrome.

Although incompletely understood, microbiota-host interactions are assumed to be altered in irritable bowel syndrome (IBS). We, therefore, aimed to develop a novel analysis pipeline tailored for the integrative analysis of microbiota-host interactions and association to symptoms and prove its utility in a pilot cohort. A multilayer stepwise integrative analysis pipeline was developed to visualize complex variable associations.

Cell polarisation in a bulk-surface model can be driven by both classic and non-classic Turing instability.

The GTPase Cdc42 is the master regulator of eukaryotic cell polarisation. During this process, the active form of Cdc42 is accumulated at a particular site on the cell membrane called the pole. It is believed that the accumulation of the active Cdc42 resulting in a pole is driven by a combination of activation-inactivation reactions and diffusion.

The synergy of damage repair and retention promotes rejuvenation and prolongs healthy lifespans in cell lineages.

Damaged proteins are inherited asymmetrically during cell division in the yeast Saccharomyces cerevisiae, such that most damage is retained within the mother cell. The consequence is an ageing mother and a rejuvenated daughter cell with full replicative potential. Daughters of old and damaged mothers are however born with increasing levels of damage resulting in lowered replicative lifespans.

Mig1 localization exhibits biphasic behavior which is controlled by both metabolic and regulatory roles of the sugar kinases.

Glucose, fructose and mannose are the preferred carbon/energy sources for the yeast Saccharomyces cerevisiae. Absence of preferred energy sources activates glucose derepression, which is regulated by the kinase Snf1. Snf1 phosphorylates the transcriptional repressor Mig1, which results in its exit from the nucleus and subsequent derepression of genes.

Fine-Tuning of Energy Levels Regulates via a SNF1-Dependent Feedback Loop.

Nutrient sensing pathways are playing an important role in cellular response to different energy levels. In budding yeast, , the sucrose non-fermenting protein kinase complex SNF1 is a master regulator of energy homeostasis. It is affected by multiple inputs, among which energy levels is the most prominent.

Symmetry structures in dynamic models of biochemical systems.

Understanding the complex interactions of biochemical processes underlying human disease represents the holy grail of systems biology. When processes are modelled in ordinary differential equation (ODE) fashion, the most common tool for their analysis is linear stability analysis where the long-term behaviour of the model is determined by linearizing the system around its steady states. However, this asymptotic behaviour is often insufficient for completely determining the structure of the underlying system.

Synergistic effects of repair, resilience and retention of damage determine the conditions for replicative ageing.

Accumulation of damaged proteins is a hallmark of ageing, occurring in organisms ranging from bacteria and yeast to mammalian cells. During cell division in Saccharomyces cerevisiae, damaged proteins are retained within the mother cell, resulting in an ageing mother while a new daughter cell exhibits full replicative potential. The cell-specific features determining the ageing remain elusive.

Analysis of Wild Raspberries (Rubus idaeus L.): Optimization of the Ultrasonic-Assisted Extraction of Phenolics and a New Insight in Phenolics Bioaccessibility.

A simple and efficient ultrasonic-assisted extraction (UAE) technique was developed in order to find optimal conditions for the extraction of total phenolic compounds, flavonoids and anthocyanins in wild raspberry (Rubus idaeus L.) fruits. Several extraction variables, including methanol composition (v/v, %), solid-solvent ratio (g/mL), time (min) and extraction temperature (°C) were optimized using response surface methodology (RSM).

Adaptive damage retention mechanism enables healthier yeast population.

During cytokinesis in budding yeast (Saccharomyces cerevisiae) damaged proteins are distributed asymmetrically between the daughter and the mother cell. Retention of damaged proteins is a crucial mechanism ensuring a healthy daughter cell with full replicative potential and an ageing mother cell. However, the protein quality control (PQC) system is tuned for optimal reproduction success which suggests optimal health and size of the population, rather than long-term survival of the mother cell.

Challenge model of TNF turnover at varying LPS and drug provocations.

A mechanism-based biomarker model of TNF-response, including different external provocations of LPS challenge and test compound intervention, was developed. The model contained system properties (such as k, k), challenge characteristics (such as k, k, K, S, SC) and test-compound-related parameters (I, IC). The exposure to test compound was modelled by means of first-order input and Michaelis-Menten type of nonlinear elimination.

Cardiac troponin T concentrations and patient-specific risk of myocardial infarction using the novel PALfx parameter.

Background: Myocardial infarction (MI) is more likely if the heart damage biomarker cardiac troponin T (cTnT) is elevated in a blood sample from a patient with chest pain. There is no conventional method to estimate the risk of MI at a specific cTnT concentration. The purpose of this study was to evaluate the performance of a novel method that converts cTnT concentrations to patient-specific risks of MI.

Robustness of Nutrient Signaling Is Maintained by Interconnectivity Between Signal Transduction Pathways.

Systems biology approaches provide means to study the interplay between biological processes leading to the mechanistic understanding of the properties of complex biological systems. Here, we developed a vector format rule-based Boolean logic model of the yeast cAMP-PKA, Snf1, and the Snf3-Rgt2 pathway to better understand the role of crosstalk on network robustness and function. We identified that phosphatases are the common unknown components of the network and that crosstalk from the cAMP-PKA pathway to other pathways plays a critical role in nutrient sensing events.

Atmospheric Solids Analysis Probe with Mass Spectrometry for Chlorpyrifos and Chlorpyrifos-Oxon Determination in Apples.

Chlorpyrifos (CPS) is a toxic pesticide present in several pesticide formulations, with low degradability by natural processes. The degradation leads to the toxic metabolite chlorpyrifos-oxon (CPO). The analytical techniques used for the CPS and CPO analysis, like UPLC-PDA and GC-MS, are accurate but also expensive and time consuming, and they need sample pretreatment.

Modelling of oscillatory cortisol response in horses using a Bayesian population approach for evaluation of dexamethasone suppression test protocols.

Cortisol is a steroid hormone relevant to immune function in horses and other species and shows a circadian rhythm. The glucocorticoid dexamethasone suppresses cortisol in horses. Pituitary pars intermedia dysfunction (PPID) is a disease in which the cortisol suppression mechanism through dexamethasone is challenged.