The Annotation and Functional Description of Non-Model Bacterial Organisms for Bio-based Engineering and Industry

Projektinformationen

HOPE-4-BEST

ID Finanzhilfevereinbarung: 101023766

DOI

10.3030/101023766

Projekt abgeschlossen

EK-Unterschriftsdatum 19 April 2021

Startdatum 1 Oktober 2021

Enddatum 14 Oktober 2023

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 174 806,40

EU-Beitrag

€ 174 806,40

Koordiniert durch

LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Germany

Periodic Reporting for period 1 - HOPE-4-BEST (The Annotation and Functional Description of Non-Model Bacterial Organisms for Bio-based Engineering and Industry)

Berichtszeitraum: 2021-10-01 bis 2023-09-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The growing human population causes numerous global challenges for modern society such as rapid depletion of non-renewable resources, increasing environmental pressure, and climate change. Hence, at least a partial transition from fossil oil-based to bio-based economy is generally considered to be an inevitable step. In this context, industrial (or white) biotechnology aims at profiting from the chemo-synthetic potential of microorganisms, especially bacteria, to convert various renewable resources into a wide range of bulk chemicals and other materials, also referred to as value added chemicals. This represents an up-and-coming approach to decrease humankind’s dependence on limited fossil feedstock. This initiative is taken very seriously in EU mainly by increasing bio-based industry sector and strategy to shift European economy towards sustainable resources and circular economy. Traditional biotechnologies nonetheless suffer from the real limitation lying in a lack of fundamental knowledge regarding regulatory and signalling pathways of various bacteria, preventing the use of novel targeted genetic modifications or other interventions of metabolic engineering necessary to establish economically feasible processes. A computational pipeline for comprehensive description of non-model bacteria and inference of biological knowledge presents the crucial step for future engineering of these microorganisms by the means of synthetic biology and their utilization in industrial biotechnology. The development of computational tools processing data from various experiments that would be utilizable in such pipeline is the overall objective of the project. Project concludes that by relatively simple adjustments of current algorithms we can perform analyses of poorly understood non-model organism that we so far possible only for well-studied model organism. Moreover, it provides a novel tool for precise functional annotation of bacterial genomes and a tool to infer how particular annotated elements interact within regulatory mechanisms present in particular bacterial cells.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

Firstly, we analyzed current algorithms for prediction of non-coding elements, i.e. genes that does not produce proteins but have regulatory functions. By simple adjustment, we showed that current algorithms designed for precise gene expression data, usually available only for model organism, can be easily adjusted to work with less precise data while overall sensitivity of the analysis remains the same. Then, we continued by proposing novel algorithm to infer gene regulatory mechanisms from less precise data that was accompanied by ready-to-use computational tool. Additionally, we analyzed current tools for functional annotation of genes and showed that comparison of results from various studies may be impossible since various tools use different versions of versatile vocabulary used for annotation of genes. To provide reproducible results we compiled a new tool producing consensus result that can secure reproducible comparison of various bacterial genomes. Finally, we used these novel tools to analyze several datasets from collaborating labs to demonstrate their usability and to show that novel knowledge utilizable in biotechnology can be inferred by proper genome annotation.

Exploitation of the results was secured by publishing two novel computational tools that are freely available to any interested user, primarily biotechnologists and synthetic biologists. Results were continuously disseminated mainly by my active participation in various scientific conferences, particularly International Work-Conference on Bioinformatics and Biomedical Engineering 2022 in Spain, Research in Computational Molecular Biology 2023 in Turkey, International Conference on Chemical Technology 2023 in Czechia, and Intelligent Systems For Molecular Biology and the European Conference on Computational Biology 2023 in France; active participation in workshops, for example de.NBI MODSIM workshop “Tools for systems biology modeling and data exchange" in Germany; or during various seminar presentations, mainly at domestic LMU Munich (Germany) but also other universities, for example Masaryk University (Czechia). The most important result were already published in two papers and additional two manuscript are currently undergoing review process in impacted journals.

Project has no dedicated website, original dedicated project website was built on ResearchGate and therefore lost when RG stopped to support projects’ websites in 2023.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Progress beyond the state of the art that the project brought can be divided into three particular conclusions: (i) older less accurate technique to measure gene expression can be used to predict small RNAs and other non-coding genomic elements with similar sensitivity to newer technology; (ii) gene regulatory networks for non-model organisms does not require single cell data and can be inferred from bulk transcriptomic datasets when expression data are supplemented by genome analysis; and (iii) results of functional annotation using the same “vocabulary” but different tools are incomparable as these tools might use different versions of “vocabulary” that should be unified, however, concensus results from various resources produce more accurate and reproducible results.

Since the project brings novel tools and findings primarily for other scientists, particularly biotechnologists and synthetic biologists, no socio-economic impact and the wider societal implications are expected in the near future. Nevertheless, improved genomic and transcriptomic analysis has a potential for selection and genome improvement of promising bacterial producers of value added chemicals. This future biotechnology advancement would imply lesser dependence on fossil feedstock.

The scope of HOPE-4-BEST in a broader context

Poster presentation during RECOMB conference