Context-based generation of kinetic equations with SBMLsqueezer 1.3

The development of predictive, quantitative models constitutes a common task in today‘s systems biology. To obtain a mathematical model description for the simulation of gene-regulatory, signaling, and metabolic networks, kinetic equations are required for each reaction within the network. Deriving and assembling these formulas is a complicated, time-consuming, and error-prone process that requires knowledge about the structure of interactions, consistently choosing a rate law for each type of reaction, and assignment of appropriate units to all parameters. In many cases, thermodynamic dependencies between the parameters have to be taken into account. For multi compartment models, the concentration units of reacting species have to be converted into molecular amounts. Here we present version 1.3 of the program SBMLsqueezer that generates kinetic equations for SBML models based on the definition of the network's topology and annotations of the elements therein, i.e., Systems Biology Ontology (SBO) and Minimal Information Requested In the Annotation of Models (MIRIAM) annotations

Public health impact and cost-effectiveness of intranasal live attenuated influenza vaccination of children in Germany

Damm O, Eichner M, Rose MA, et al. Public health impact and cost-effectiveness of intranasal live attenuated influenza vaccination of children in Germany. The European Journal of Health Economics. 2015;16(5):471-488.In 2011, intranasally administered live attenuated influenza vaccine (LAIV) was approved in the EU for prophylaxis of seasonal influenza in 2-17-year-old children. Our objective was to estimate the potential epidemiological impact and cost-effectiveness of an LAIV-based extension of the influenza vaccination programme to healthy children in Germany. An age-structured dynamic model of influenza transmission was developed and combined with a decision-tree to evaluate different vaccination strategies in the German health care system. Model inputs were based on published literature or were derived by expert consulting using the Delphi technique. Unit costs were drawn from German sources. Under base-case assumptions, annual routine vaccination of children aged 2-17 years with LAIV assuming an uptake of 50 % would prevent, across all ages, 16 million cases of symptomatic influenza, over 600,000 cases of acute otitis media, nearly 130,000 cases of community-acquired pneumonia, nearly 1.7 million prescriptions of antibiotics and over 165,000 hospitalisations over 10 years. The discounted incremental cost-effectiveness ratio was a,not sign1,228 per quality-adjusted life year gained from a broad third-party payer perspective (including reimbursed direct costs and specific transfer payments), when compared with the current strategy of vaccinating primarily risk groups with the conventional trivalent inactivated vaccine. Inclusion of patient co-payments and indirect costs in terms of productivity losses resulted in discounted 10-year cost savings of a,not sign3.4 billion. In conclusion, adopting universal influenza immunisation of healthy children and adolescents would lead to a substantial reduction in influenza-associated disease at a reasonable cost to the German statutory health insurance system. On the basis of the epidemiological and health economic simulation results, a recommendation of introducing annual routine influenza vaccination of children 2-17 years of age might be taken into consideration

The epidemiological impact of childhood influenza vaccination using live-attenuated influenza vaccine (LAIV) in Germany: predictions of a simulation study

Rose MA, Damm O, Greiner W, et al. The epidemiological impact of childhood influenza vaccination using live-attenuated influenza vaccine (LAIV) in Germany: predictions of a simulation study. BMC Infectious Diseases. 2014;14(1): 40.Background Routine annual influenza vaccination is primarily recommended for all persons aged 60 and above and for people with underlying chronic conditions in Germany. Other countries have already adopted additional childhood influenza immunisation programmes. The objective of this study is to determine the potential epidemiological impact of implementing paediatric influenza vaccination using intranasally administered live-attenuated influenza vaccine (LAIV) in Germany. Methods A deterministic age-structured model is used to simulate the population-level impact of different vaccination strategies on the transmission dynamics of seasonal influenza in Germany. In our base-case analysis, we estimate the effects of adding a LAIV-based immunisation programme targeting children 2 to 17 years of age to the existing influenza vaccination policy. The data used in the model is based on published evidence complemented by expert opinion. Results In our model, additional vaccination of children 2 to 17 years of age with LAIV leads to the prevention of 23.9 million influenza infections and nearly 16 million symptomatic influenza cases within 10 years. This reduction in burden of disease is not restricted to children. About one third of all adult cases can indirectly be prevented by LAIV immunisation of children. Conclusions Our results demonstrate that vaccinating children 2–17 years of age is likely associated with a significant reduction in the burden of paediatric influenza. Furthermore, annual routine childhood vaccination against seasonal influenza is expected to decrease the incidence of influenza among adults and older people due to indirect effects of herd protection. In summary, our model provides data supporting the introduction of a paediatric influenza immunisation programme in Germany

A rapid protocol for ribosome profiling of low input samples.

Ribosome profiling provides quantitative, comprehensive, and high-resolution snapshots of cellular translation by the high-throughput sequencing of short mRNA fragments that are protected by ribosomes from nucleolytic digestion. While the overall principle is simple, the workflow of ribosome profiling experiments is complex and challenging, and typically requires large amounts of sample, limiting its broad applicability. Here, we present a new protocol for ultra-rapid ribosome profiling from low-input samples. It features a robust strategy for sequencing library preparation within one day that employs solid phase purification of reaction intermediates, allowing to reduce the input to as little as 0.1 pmol of ∼30 nt RNA fragments. Hence, it is particularly suited for the analyses of small samples or targeted ribosome profiling. Its high sensitivity and its ease of implementation will foster the generation of higher quality data from small samples, which opens new opportunities in applying ribosome profiling

SBMLsqueezer 2: context-sensitive creation of kinetic equations in biochemical networks

BACKGROUND: The size and complexity of published biochemical network reconstructions are steadily increasing, expanding the potential scale of derived computational models. However, the construction of large biochemical network models is a laborious and error-prone task. Automated methods have simplified the network reconstruction process, but building kinetic models for these systems is still a manually intensive task. Appropriate kinetic equations, based upon reaction rate laws, must be constructed and parameterized for each reaction. The complex test-and-evaluation cycles that can be involved during kinetic model construction would thus benefit from automated methods for rate law assignment. RESULTS: We present a high-throughput algorithm to automatically suggest and create suitable rate laws based upon reaction type according to several criteria. The criteria for choices made by the algorithm can be influenced in order to assign the desired type of rate law to each reaction. This algorithm is implemented in the software package SBMLsqueezer 2. In addition, this program contains an integrated connection to the kinetics database SABIO-RK to obtain experimentally-derived rate laws when desired. CONCLUSIONS: The described approach fills a heretofore absent niche in workflows for large-scale biochemical kinetic model construction. In several applications the algorithm has already been demonstrated to be useful and scalable. SBMLsqueezer is platform independent and can be used as a stand-alone package, as an integrated plugin, or through a web interface, enabling flexible solutions and use-case scenarios. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-015-0212-9) contains supplementary material, which is available to authorized users

Dirty hands: photodynamic killing of human pathogens like EHEC, MRSA and Candida within seconds

Hand hygiene is one of the most important interventions for reducing transmission of nosocomial life-threatening microorganisms, like methicillin resistant Staphylococcus aureus (MRSA), enterohemorrhagic Escherichia coli (EHEC) or Candida albicans. All three pathogens have become a leading cause of infections in hospitals. Especially EHEC is causing severe diarrhoea and, in a small percentage of cases, haemolytic-uremic syndrome (HUS) as reported for E. coli 104:H4 in Germany 2011. We revealed the possibility to inactivate very fast and efficiently MRSA, EHEC and C. albicans using the photodynamic approach. MRSA, EHEC and C. albicans were incubated in vitro with different concentrations of TMPyP for 10 s and illuminated with visible light (50 mW cm−2) for 10 and 60 s. 1 μmol l−1 of TMPyP and an applied radiant exposure of 0.5 J cm−2 achieved a photodynamic killing of ≥99.9% of MRSA and EHEC. Incubation with higher concentrations (up to 100 μmol l−1) of TMPyP caused bacteria killing of >5 log10 (≥99.999%) after illumination. Efficient Candida killing (≥99.999%) was achieved first at a higher light dose of 12 J cm−2. Different rise and decay times of singlet oxygen luminescence signals could be detected in Candida cell suspensions for the first time, indicating different oxygen concentrations in the surrounding for the photosensitizer and singlet oxygen, respectively. This confirms that TMPyP is not only found in the water-dominated cell surrounding, but also within the C. albicans cells. Applying a water–ethanol solution of TMPyP on ex vivo porcine skin, fluorescence microscopy of histology showed that the photosensitizer was exclusively localized in the stratum corneum regardless of the incubation time. TMPyP exhibited a fast and very effective killing rate of life-threatening pathogens within a couple of seconds that encourages further testing in an in vivo setting. Being fast and effective, antimicrobial photodynamic applications might become acceptable as a tool for hand hygiene procedures and also in other skin areas

Corona Health -- A Study- and Sensor-based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic

Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July, 2020) in 8 languages and attracted 7,290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures

JSBML 1.0: providing a smorgasbord of options to encode systems biology models

JSBML, the official pure Java programming library for the SBML format, has evolved with the advent of different modeling formalisms in systems biology and their ability to be exchanged and represented via extensions of SBML. JSBML has matured into a major, active open-source project with contributions from a growing, international team of developers who not only maintain compatibility with SBML, but also drive steady improvements to the Java interface and promote ease-of-use with end users

Predicting DNA-Binding Specificities of Eukaryotic Transcription Factors

Today, annotated amino acid sequences of more and more transcription factors (TFs) are readily available. Quantitative information about their DNA-binding specificities, however, are hard to obtain. Position frequency matrices (PFMs), the most widely used models to represent binding specificities, are experimentally characterized only for a small fraction of all TFs. Even for some of the most intensively studied eukaryotic organisms (i.e., human, rat and mouse), roughly one-sixth of all proteins with annotated DNA-binding domain have been characterized experimentally. Here, we present a new method based on support vector regression for predicting quantitative DNA-binding specificities of TFs in different eukaryotic species. This approach estimates a quantitative measure for the PFM similarity of two proteins, based on various features derived from their protein sequences. The method is trained and tested on a dataset containing 1 239 TFs with known DNA-binding specificity, and used to predict specific DNA target motifs for 645 TFs with high accuracy