Transcriptional and Metabolic Response of Wine-Related Lactiplantibacillus plantarum to Different Conditions of Aeration and Nitrogen Availability

Lactic acid bacteria (LAB) perform the process of malolactic fermentation (MLF) in wine. Availability of oxygen and nitrogen nutrients could influence LAB growth, malolactic activity, and other metabolic pathways, impacting the subsequent wine quality. The impact of these two factors has received limited investigation within LAB, especially on a transcriptome level. The aim of this study was to evaluate metabolic changes in the strain Lactiplantibacillus plantarum IWBT B063, growing in synthetic grape juice medium (GJM) under different oxygen exposure conditions, and with low availability of nitrogen-based nutrients. Next-generation sequencing was used to analyze expression across the transcriptome (RNA-seq), in combination with conventional microbiological and chemical analysis. L. plantarum consumed the malic acid present in all the conditions evaluated, with a slight delay and impaired growth for nitrogen limitation and for anaerobiosis. Comparison of L. plantarum transcriptome during growth in GJM with and without O-2 revealed differential expression of 148 functionally annotated genes, which were mostly involved in carbohydrate metabolism, genetic information processing, and signaling and cellular processes. In particular, genes with a protective role against oxidative stress and genes related to amino acid metabolism were differentially expressed. This study confirms the suitability of L. plantarum IWBT B063 to carry out MLF in different environmental conditions due to its potential adaption to the stress conditions tested and provides a better understanding of the genetic background of an industrially relevant strain

Uncovering the effects of heterogeneity and parameter sensitivity on within‑host dynamics of disease : malaria as a case study

CITATION: Horn, S., Snoep, J. L. & Van Niekerk, D. D. 2021. Uncovering the effects of heterogeneity and parameter sensitivity on within‑host dynamics of disease: malaria as a case study. BMC Bioinformatics, 22:384, doi:10.1186/s12859-021-04289-z.The original publication is available at https://bmcbioinformatics.biomedcentral.comPublication of this article was funded by the Stellenbosch University Open Access FundBackground: The fidelity and reliability of disease model predictions depend on accurate and precise descriptions of processes and determination of parameters. Various models exist to describe within-host dynamics during malaria infection but there is a shortage of clinical data that can be used to quantitatively validate them and establish confidence in their predictions. In addition, model parameters often contain a degree of uncertainty and show variations between individuals, potentially undermining the reliability of model predictions. In this study models were reproduced and analysed by means of robustness, uncertainty, local sensitivity and local sensitivity robustness analysis to establish confidence in their predictions. Results: Components of the immune system are responsible for the most uncertainty in model outputs, while disease associated variables showed the greatest sensitivity for these components. All models showed a comparable degree of robustness but displayed different ranges in their predictions. In these different ranges, sensitivities were well-preserved in three of the four models. Conclusion: Analyses of the effects of parameter variations in models can provide a comparative tool for the evaluation of model predictions. In addition, it can assist in uncovering model weak points and, in the case of disease models, be used to identify possible points for therapeutic intervention.https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04289-zPublisher's versio

OneStop:JWS Online's access point to SBML,SBGN and MIRIAM compliant annotation

We have developed an online model constructor and validator called OneStop, which is compliant with SBGN, SBML and MIRIAM standards. Key features of OneStop are: 1) a human readable input form (in addition to SBML upload and saving); 2) live visualization (SBGN graphics) of the reaction network during the construction phase; and 3) online access from any machine with a compatible browser. Sophisticated error feedback simplifies the debugging process during model construction significantly and guides the efforts of new users in a step by step fashion. OneStop is seamlessly integrated with the JWS Online model repository and simulator and also facilitates the importation of models from the BioModels database. In addition, OneStop is part of the SysMO-SEEK platform, which is used for data and model management in the Pan-European SysMO consortium

Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language

Background: The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools. Results: In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions. Conclusions: With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research can be accurately described and combined

BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

Background: Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description: BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions: BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License

Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language

Background: The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools. Results: In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions. Conclusions: With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research can be accurately described and combined

Transduction of intracellular and intercellular dynamics in yeast glycolytic oscillations.

AbstractUnder certain well-defined conditions, a population of yeast cells exhibits glycolytic oscillations that synchronize through intercellular acetaldehyde. This implies that the dynamic phenomenon of the oscillation propagates within and between cells. We here develop a method to establish by which route dynamics propagate through a biological reaction network. Application of the method to yeast demonstrates how the oscillations and the synchronization signal can be transduced. That transduction is not so much through the backbone of glycolysis, as via the Gibbs energy and redox coenzyme couples (ATP/ADP, and NADH/NAD), and via both intra- and intercellular acetaldehyde

Design principles of nuclear receptor signaling: how complex networking improves signal transduction

Nuclear receptors often function in the cytoplasm.A triple conveyor belt pumps ligand (signal) into the nucleus and onto the DNA.The active export of importins enhances signaling to the nucleus.Sharing a single nuclear pore may reduce rather than increase crosstalk