Biology subjects

Schuster, S.

Publications and source records attributed to Schuster, S..

25 records · Page 2Linked to original sources

bioRxiv2020

Calculating the optimal hematocrit under the constraint of constant cardiac power

In humans and higher animals, a trade-off between sufficiently high erythrocyte concentrations to bind oxygen and sufficiently low blood viscosity to allow rapid blood flow has been achieved during evolution. Optimal hematocrit theory has been successful in predicting hematocrit values of about 0.3 - 0.5, in very good agreement with the normal values observed for humans and many animal species. However, according to those calculations, the optimal value should be independent of the mechanical load of the body. This is in contradiction to the exertional increase in hematocrit observed in some animals called natural blood dopers and to the illegal practice of blood boosting in high-performance sports. In this study, we calculate the optimal hematocrit under two different constraints - under a constant driving pressure and under constant cardiac power – and show that the optimal hematocrit under constant cardiac power is higher than the normal value, ranging from 0.5 to 0.7. We use this result to explain the tendency to better exertional performance at an increased hematocrit.Statement of Significance In humans and higher animals, erythrocytes comprise a volume fraction (hematocrit) of 30-50 % of the blood. Mathematical calculations based on the assumption of constant blood pressure show that the optimal hematocrit value is indeed in that range. However, this optimum should apply to both rest and physical exertion, which is in contradiction to the increase in hematocrit observed in some animals called natural blood dopers and to the illegal practice of blood boosting in sports. Here, we calculate the optimal value based on the alternative constraint of constant cardiac power. We show that this results in a higher optimal value, ranging from 50 to 70 %. In this way, we explain the better exertional performance at an increased hematocrit.Competing Interest StatementThe authors have declared no competing interest.View Full Text

physiology↗

bioRxiv2020

Influence of spatial structure on protein damage susceptibility - A bioinformatics approach

Aging research is a very popular field of research in which the gradual transformation of functional states into dysfunctional states are studied. Here we only consider the molecular level, which can also have effects on the macroscopic level. It is known that the proteinogenic amino acids differ in their modification susceptibilities and this can affect the function of proteins. For this it is important to know the distribution of amino acids between the protein surface/shell and the core. This was investigated in this study for all known structural data of peptides and proteins. As a result it is shown that the surface contains less susceptible amino acids than the core with the exception of thermophilic organisms. Furthermore, proteins could be classified according to their susceptibility. This can then be used in applications such as phylogeny, aging research, molecular medicine and synthetic biology.

bioinformatics↗

bioRxiv2019

Mapping the evolutionary landscape of Zika virus infection in immunocompromised mice.

The fundamental basis of how arboviruses evolve in nature and what regulates the adaptive process remain unclear. To address this problem, we established a Zika virus (ZIKV) vector-borne transmission system in immunocompromised mice that mimics evolutionary characteristics of ZIKV infection in humans. Using this system, we defined factors that influence the evolutionary landscape of ZIKV infection and show that transmission route and specific organ microenvironments impact viral diversity and defective viral genome (DVG) production. In addition, we identified in mice the emergence of ZIKV mutants previously seen in natural infections, including variants present in currently circulating strains, as well as mutations unique to the mouse infections. With these studies, we have established an insect-to-mouse transmission model to study ZIKV evolution. We also defined how organ microenvironments and infection route impact the ZIKV evolutionary landscape, providing a deeper understanding of the factors that regulate arbovirus evolution and emergence.

microbiology↗

bioRxiv2019

Differential equation based minimal model describing metabolic oscillations in Bacillus subtilis biofilms

Biofilms offer an excellent example of ecological interaction among bacteria. Temporal and spatial oscillations in biofilms are an emerging topic. In this paper we describe the metabolic oscillations in Bacillus subtilis biofilms by applying the smallest theoretical chemical reaction system showing Hopf bifurcation proposed by Wilhelm and Heinrich in 1995. The system involves three differential equations and a single bilinear term. We perform computer simulations and a detailed analysis of the system including bifurcation analysis and quasi-steady-state approximation. We also discuss the feedback structure of the system and the correspondence of the simulations to biological observations. We also specifically select parameters that are more suitable for the biological scenario of biofilm oscillations. Our theoretical work suggests potential scenarios about the oscillatory behaviour of biofilms and also serves as an application of a previously described chemical oscillator to a biological system.

systems biology↗

bioRxiv2019

A modification to the life cycle of the parasite Trypanosoma brucei

African trypanosomes cause sleeping sickness in humans and nagana in cattle. These unicellular parasites are transmitted by the bloodsucking tsetse fly. In the mammalian hosts circulation, tissues, and interstitium, at least two main life cycle stages exist: slender and stumpy bloodstream stages. Proliferating slender stage cells differentiate into cell cycle-arrested stumpy stage cells at high population densities. This developmental stage transition occurs in response to the quorum sensing factor SIF (stumpy induction factor), and is thought to fulfil two main functions. First, it auto-regulates the parasite load in the host. Second, the stumpy stage is regarded as pre-adapted for tsetse fly infection and the only stage capable of successful vector transmission. Here, we show that proliferating slender stage trypanosomes are able to complete the complex life cycle in the fly as successfully as the stumpy stage, and that a single parasite is sufficient for productive infection. Our findings not only propose a revision to the traditional rigid view of the trypanosome life cycle, but also suggest a solution to a long-acknowledged paradox in the transmission event: parasitaemia in chronic infections is characteristically low, and so the probability of a tsetse ingesting a stumpy cell during a bloodmeal is also low. The finding that proliferating slender parasites are infective to tsetse flies helps shed light on this enigma.

microbiology↗

bioRxiv2018

Molecular crypsis by pathogenic fungi using human factor H. A numerical model

Molecular mimicry is the formation of specific molecules by microbial pathogens to avoid recognition and attack by the immune system of the host. Several pathogenic Ascomycota and Zygomycota show such a behaviour by utilizing human complement factor H to hide in the blood stream. We call this type of mimicry molecular crypsis. Such a crypsis can reach a point where the immune system can no longer clearly distinguish between self and non-self cells. Thus, a trade-off between attacking disguised pathogens and erroneously attacking host cells has to be made, which can lead to autoreactivity. Based on signalling theory and protein-interaction modelling, we here present a mathematical model of molecular crypsis of pathogenic fungi using the example of Candida albicans. We tackle the question whether perfect crypsis is feasible, which would imply that protection of human cells by complement factors would be useless. The model identifies pathogen abundance relative to host cell abundance as the predominant factor influencing successful or unsuccessful molecular crypsis. If pathogen cells gain a (locally) quantitative advantage over host cells, even autoreactivity may occur. Our new model enables insights into the mechanisms of candidiasis-induced sepsis and complement associated autoimmune diseases.

systems biology↗

bioRxiv2017

ModuleDiscoverer: Identification of regulatory modules in protein-protein interaction networks.

The identification of disease associated modules based on protein-protein interaction networks (PPINs) and gene expression data has provided new insights into the mechanistic nature of diverse diseases. A major problem hampering their identification is the detection of protein communities within large-scale, whole-genome PPINs. Current strategies solve the maximal clique enumeration (MCE) problem, i.e., the enumeration of all non-extendable groups of proteins, where each pair of proteins is connected by an edge. The MCE problem however is non-deterministic polynomial time hard and can thus be computationally overwhelming for large-scale, whole-genome PPINs.\n\nWe present ModuleDiscoverer, a novel approach for the identification of regulatory modules from PPINs in conjunction with gene-expression data. ModuleDiscoverer is a heuristic that approximates the community structure underlying PPINs. Based on a high-confidence PPIN of Rattus norvegicus and publicly available gene expression data we apply our algorithm to identify the regulatory module of a rat-model of diet induced non-alcoholic steatohepatitis (NASH). We validate the module using single-nucleotide polymorphism data from independent genome-wide association studies. Structural analysis of the module reveals 10 sub-modules. These sub-modules are associated with distinct biological functions and pathways that are relevant to the pathological and clinical situation in NASH.\n\nModuleDiscoverer is freely available upon request from the corresponding author.

systems biology↗