In the production of fermented foods, microbes play an important role. Optimization of fermentation processes or starter culture production traditionally was a trial-and-error approach inspired by expert knowledge of the fermentation process. Current developments in high-throughput 'omics' technologies allow developing more rational approaches to improve fermentation processes both from the food functionality as well as from the food safety perspective. Here, the authors thematically review typical bioinformatics techniques and approaches to improve various aspects of the microbial production of fermented food products and food safety.
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BACKGROUND: Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python.RESULTS: The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS.CONCLUSIONS: pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.
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Summary: Xpaths is a collection of algorithms that allow for the prediction of compound-induced molecular mechanisms of action by integrating phenotypic endpoints of different species; and proposes follow-up tests for model organisms to validate these pathway predictions. The Xpaths algorithms are applied to predict developmental and reproductive toxicity (DART) and implemented into an in silico platform, called DARTpaths.
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Nearly all waterborne products, such as food, beverages, pharmaceuticals, paints, biological (medical) samples, cosmetics and wood require preservation to prevent decomposition of the product due to microbial growth. Most non-food preservatives such as isothiazolinones, bronopol, and pyrithiones, are derived from oil and are increasingly more strictly regulated due to hazards such as ecotoxicity, sensibilization and development of allergies. The low legally permitted concentrations will not only become too low to realize preservation, they will also induce antimicrobial resistance. A chemical transition towards new, innovative, biobased, and eco-friendly preservatives is therefore required. Wydo NBD is dedicated to research towards sustainable ingredients for waterborne paints. For this, together with the Hanze University, non-hazardous, eco-friendly and biobased natural preservatives will be identified and further developed towards marketable products. The knowledge obtained in this project will contribute to the development of biological (paint) conservatives knowledge and improvement of current production methods of Wydo, with the potential for wider application in food and medical products. This project aims to identify natural antimicrobial additives and consists of three consecutive stages. First, an extensive, unbiased bioinformatics guided literature mining will be performed to find relationships between biological antimicrobial compounds and microbes found in paint. The most promising antimicrobials from this mining will be made available by chemical synthesis. Subsequently, the compounds will be assessed for their potential as novel natural preservatives for waterborne paints, by testing for their antimicrobial activity and stability.
Nearly all waterborne products, such as food, beverages, pharmaceuticals, paints, biological (medical) samples, cosmetics and wood require preservation to prevent decomposition of the product due to microbial growth. Most non-food preservatives such as isothiazolinones, bronopol, and pyrithiones, are derived from oil and are increasingly more strictly regulated due to hazards such as ecotoxicity, sensibilization and development of allergies. The low legally permitted concentrations will not only become too low to realize preservation, they will also induce antimicrobial resistance. A chemical transition towards new, innovative, biobased, and eco-friendly preservatives is therefore required. Wydo NBD is dedicated to research towards sustainable ingredients for waterborne paints. For this, together with the Hanze University, non-hazardous, eco-friendly and biobased natural preservatives will be identified and further developed towards marketable products. The knowledge obtained in this project will contribute to the development of biological (paint) conservatives knowledge and improvement of current production methods of Wydo, with the potential for wider application in food and medical products.This project aims to identify natural antimicrobial additives and consists of three consecutive stages. First, an extensive, unbiased bioinformatics guided literature mining will be performed to find relationships between biological antimicrobial compounds and microbes found in paint. The most promising antimicrobials from this mining will be made available by chemical synthesis. Subsequently, the compounds will be assessed for their potential as novel natural preservatives for waterborne paints, by testing for their antimicrobial activity and stability
Plastic waste is one of the largest environmental problems in the 21st century. By 2050, up to 12,000 Mt of plastic waste is estimated to be in landfills or in the natural environment. Biochemical recycling by using modified microbial enzymes have shown potentials in the back-to-monomer (BTM) recycling of polyethylene terephthalate by breaking down the polymers into re-usable monomers. These enzymes can be produced via fungal species. In order to make this biochemical BTM process viable a process integrated enzyme production is key in increasing the efficiency and reducing the cost of enzymes. For this a molecular monitoring method, such as RNA-seq (RNA-sequencing), is needed. RNA-seq can achieve a snapshot on enzyme producing process inside of the cell by semi-quantitatively measuring the volume of enzyme encoding RNAs. This information can bring hints on fungal strain improvement by promoting the desired enzymes. It also helps to instantly monitor the BTM production outcomes. However, conventional RNA-seq platforms can only be performed via service providers or startup investments reaching 2 million euros. Each round of analysis could take as long as 6 weeks turnaround time. Furthermore, the method creates huge amount of complicated datasets, only by expert skills and specialized high performance computing the data can be sorted in a comprehensive manner. To solve these problems, in this project, by combining the expertise on plastic end-of-life control, fungal enzyme production, molecular monitoring and Bioinformatics from both the UAS and SME sides, we aim to implement a novel RNA-seq based system to monitor the in-process enzyme production for plastic degradation. We will optimize the existing portable RNA-seq prototype machinery for semi-real time monitoring of the BTM recycling process. The downstream data will be handled by a tailored analysis pipeline designed with expert knowledge via an user-friendly interface.
