Biology subjects

Stenkula, K. G.

Publications and source records attributed to Stenkula, K. G..

6 recordsLinked to original sources

bioRxiv2026

Fixed-dose streptozotocin combined with high-fat diet induces a stable type 2 diabetes-like phenotype in C57BL/6J mice

High-fat diet (HFD) combined with streptozotocin (STZ) is widely used to model type 2 diabetes (T2D) in rodents, but is often associated with high mortality, non-responders, and inconsistent outcomes. STZ is conventionally administered using body weight-adjusted dosing (mg/kg), despite evidence that heavier animals, including HFD-fed mice, exhibit more severe glycaemic responses. Here, we performed metabolic phenotyping in chow- and HFD-fed C57BL/6J mice treated with low or high fixed doses (mg instead of mg/kg) of anomer-equilibrated STZ. HFD combined with low-dose STZ induced a stable T2D-like phenotype characterized by sustained obesity, moderate hyperglycaemia, insulin resistance, and partial {beta}-cell loss, with low inter-individual variability. In contrast, high-dose STZ induced a T1D-like phenotype with extensive {beta}-cell loss. A semi-mechanistic mathematical model was developed and validated against independent experimental data, reproducing the observed dynamics of fasting glucose in response to fixed-dose STZ. The model further predicted that weight-adjusted (mg/kg) dosing could introduce variability in glycaemic responses, particularly in HFD-fed mice. Together, these results demonstrate that fixed-dose, anomer-equilibrated STZ induces a stable T2D-like phenotype, providing an alternative to conventional weight-adjusted dosing in HFD-fed mice.

physiology↗

bioRxiv2026

Microfluidic Separation of Adipocytes

1.Adipocyte size is an independent predictor of several metabolic disorders, including type 2 diabetes, liver and cardiovascular diseases. However, technical limitations due to the fragile nature of mature adipocytes have restricted the functional analyses of size-separated adipocytes using conventional methods. Therefore, we have developed a microfluidic device, based on deterministic lateral displacement, for sorting intact, mature adipocytes. Cell-size distribution was determined from time-lapse recordings inside the device, in separate outlets, and by Coulter counter analysis of the collected cell fractions. This approach allowed size-separation with minimal size-overlap with mean diameters of (small fraction) 47 {micro}m and (large fraction) 82 {micro}m based on Coulter counter measurements. Viability of the separated cells was verified by insulin stimulation and western blotting of key insulin signaling proteins. The sample recovery, comparing input versus output material, was relatively high, 42% for the large fraction with a purity of 93%. We demonstrate that microfluidics is a suitable approach to overcome the limitations of sorting mature adipocytes according to size. Together, the high recovery rate, high throughput capacity, accurate separation and the fact that the cells maintained hormonal response after sorting provides compelling evidence of the strength and usability of the microfluidic approach for exploring adipocyte function in relation to size.

cell biology↗

bioRxiv2026

Exploring a mathematical framework for quantifying cell size- dependent glucose uptake in adipocytes

Insulin-stimulated glucose uptake (ISGU) in adipocytes is central to maintain systemic glucose homeostasis. Understanding how ISGU relates to adipocyte traits, such as cell-size, is critical for elucidating pressing questions related to metabolic dysfunction connected to adipose hypertrophy and hyperplasia. Cell size is considered a central trait reflecting multiple aspects of adipocyte metabolism. However, a robust quantitative approach to estimate ISGU for a specific cell size is currently missing. Here, in an attempt to move towards such a method, we have formulated an approach using a mathematical framework. The framework consists of a linear equation: the product of the known number of cells (calculated using coulter counter-based cell-size distributions) and the unknown ISGU/cell, compared to the absolute ISGU (measured using 14C-glucose tracer assays). To solve this equation, we formulate a minimization problem which is optimized to find the unknown ISGU/cell for the best solution. Using different formulations of the equation we can investigate the need for either cell size-dependent or independent ISGU/cell, to describe varying glucose uptake in a cell sample of various cell sizes. While the framework needs further refinement, we demonstrate that cell size-dependent uptake slightly improved the agreement between model and experimental data for some groups. Together, with further validation this could serve as a useful tool to resolve long-standing questions regarding size-dependent characteristics like adipocyte size and cellular function. Key findingsHerein we explore a method to quantify cell size-dependent glucose uptake in adipocytes

cell biology↗

bioRxiv2023

Butyrate-producing bacteria as probiotic supplement: beneficial effects on metabolism and modulation of behavior in an obesity mouse model

Obesity is a risk factor for cardio-metabolic and neurological disease. The contribution of gut microbiota to derangements of the gut-brain axis in the context of obesity has been acknowledged, particularly through physiology modulation by short-chain fatty acids (SCFAs). Thus, probiotic interventions and administration of SCFAs have been employed with the purpose of alleviating symptoms in both metabolic and neurological disease. We have tested the effects of four butyrate-producing bacteria from the Lachnospiraceae family on the development of metabolic syndrome and behavioural alterations in a mouse model of diet-induced obesity. Male mice were fed either a high-fat diet (HFD) or an ingredient-matched control diet for 2 months, and bacteria cultures or culture medium were given by gavage to HFD-fed mice every second day. Assessment of the mice through a battery of metabolic and behaviour tests revealed that one of the administered bacteria affords some degree of protection against the development of obesity and its complications.

physiology↗

bioRxiv2023

A multi-scale digital twin for adiposity-driven insulin resistance in humans: diet and drug effects

AimsThe increased prevalence of insulin resistance is one of the major health risks in society today. Insulin resistance involves both short-term dynamics, such as altered meal responses, and long-term dynamics, such as development of type 2 diabetes. Insulin resistance also occurs on different physiological levels, ranging from disease phenotypes to organ-organ communication and intracellular signaling. To better understand the progression of insulin resistance, an analysis method is needed that can combine different timescales and physiological levels. One such method is digital twins, consisting of combined mechanistic multi-scale and multi-level mathematical models. We have previously developed a multi-level model for short-term glucose homeostasis and intracellular insulin signaling, and there exists long-term weight regulation models. However, no one has combined these kinds of models into an interconnected, multi-level and multi-timescale digital twin model. Herein, we present a first such multi-scale digital twin for the progression of insulin resistance in humans. MethodsThe model is based on ordinary differential equations representing biochemical and physiological processes, in which unknown parameters were fitted to data using a MATLAB toolbox. ResultsThe connected twin correctly predicts independent data from a weight increase study, both for weight-changes, for fasting plasma insulin and glucose levels, as well as for intracellular insulin signaling. Similarly, the model can predict independent weight-change data in a weight loss study, involving diet and the weight loss drug topiramate. These independent validation tests are confirmed by a chi-square test (() = 4.8 < 21 = 2, (12,0.05)). In both these cases, the model can also predict non-measured variables, such as activity of intracellular intermediaries, glucose tolerance responses, and organ fluxes. ConclusionsWe present a first multi-level and multi-timescale model, describing dynamics on the whole-body, organ and cellular levels, ranging from minutes to years. This model constitutes the basis for a new digital twin technology, which in the future could potentially be used to aid medical pedagogics and increase motivation and compliance and thus aid in prevention and treatment of insulin resistance.

systems biology↗

bioRxiv2021

A multi-scale in silico mouse model for insulin resistance and humanoid type 2 diabetes

Insulin resistance (IR) causes compensatory insulin production, which in humans eventually progresses to beta-cell failure and type 2 diabetes (T2D). This disease progression involves multi-scale processes, ranging from intracellular signaling to organ-organ and whole-body level regulations, on timescales from minutes to years. T2D progression is commonly studied using overfed and genetically modified rodents. However, rodents do not exhibit human T2D progression, with IR-driven beta-cell failure, and available multi-scale data is too complex to fully comprehend using traditional analysis. To help resolve these issues, we here present an in silico mouse model. This is the first mathematical model that simultaneously explains multi-scale mouse IR data on all three levels - cells, organs, body - ranging from minutes to months. The model correctly predicts new independent multi-scale validation data and provides insights into non-measured processes. Finally, we present a humanoid in silico mouse exhibiting disease progression from IR to IR-driven T2D.

systems biology↗