Projects / Programmes
Development of algorithms for antimicrobial drug discovery and reduction of antimicrobial resistance
| Code |
Science |
Field |
Subfield |
| 2.06.02 |
Engineering sciences and technologies |
Systems and cybernetics |
System theory and control systems |
| Code |
Science |
Field |
| B110 |
Biomedical sciences |
Bioinformatics, medical informatics, biomathematics biometrics |
| Code |
Science |
Field |
| 2.02 |
Engineering and Technology |
Electrical engineering, Electronic engineering, Information engineering |
antimicrobial resistance, drug discovery, horizontal gene transfer, metagenomics, bioinformatics, structure activity prediction, machine learning
Researchers (1)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
32446 |
PhD Jan Zrimec |
Biochemistry and molecular biology |
Head |
2016 - 2017 |
97 |
Organisations (1)
Abstract
Antimicrobial drugs either directly kill microorganisms or prevent their growth and reproduction. Microbes respond to the drugs by development of antimicrobial resistance (AMR), thereby reducing their effects. Since the genes for AMR can spread between microbes via horizontal gene transfer (HGT), the excessive use of antimicrobial drugs in the last decades has resulted in the emergence of a growing number of drug resistant microbes (e.g. MRSA). Due to the frequency of such infections, AMR is currently one of the three largest global health problems, as only in Europe 25.000 deaths occur each year. Nevertheless, pharmaceutical companies practically no longer develop new antimicrobials, which has caused a shortage of new drugs. Therefore, based on new technologies and approaches, such as metagenomics, I propose to develop algorithms to accelerate the discovery of antimicrobials among natural compounds produced by microbes themselves. Furthermore, by performing an in-depth analysis of AMR in metagenomes, I will create innovative algorithms to optimize compounds and reduce the incidence of AMR.
The findings on very large diversity () 10^6 / gram of soil) and high amount of unexplored microbial species () 99%) show that they are an unexploited resource of natural compounds. However, although the genetic data of microbes is fully accessible using metagenomics approaches, methods must be developed to process this data in order to discover antimicrobial compounds that are coded inside it. Therefore, I will develop procedures for the discovery of potential new antimicrobial compounds in data libraries of metagenomic projects. Clusters of genes that code for biosynthesis of antimicrobial compounds will be identified by analysis of specific DNA regions and their structural properties. The process of characterization of gene clusters and their biosynthetic products according to reference data will be expanded by modeling based on evolutionary principles. By adapting the above methodology, AMR systems will be characterised and analysed to determine the potential for transfer of the AMR genes by HGT and for incidence of AMR in relation to the antimicrobials used. Finally, the antimicrobial activity and AMR incidence of the discovered compounds will be predicted according to computed molecular properties on structure-activity relationships of the compounds. The expected results are (i) new antimicrobial compounds with a lower incidence of AMR than the ones currently used and (ii) validated tools that will be accessible to the general scientific community via the internet.
The proposed project is organized into three interdependent work packages (WP). In WP 1, data will be acquired and interfaces constructed for further analysis. In WP 2, the core discovery procedure and algorithms will be developed. In WP 3, analysis of AMR systems will be performed and used to optimize antimicrobial compounds.
Since the project will use of data from unexplored environments, a great number of new compounds can be accessed. Estimates indicate that less than 1% of all available microbial compounds have been identified. Consequently, I presume that there are many opportunities for the discovery of useful antimicrobials. The algorithms and procedures that will be developed are expected to have a wide applicability in the biotechnology and microbiology fields due to their flexibility and easy adaption for use not only with prokaryotic but also eukaryotic organisms, such as fungi and plants. However, the proposed analysis of AMR systems and development of strategies to lower the incidence of AMR has potentially the largest scientific as well as social impact. Such methods and strategies can help create solutions to improve healthcare and save lives in the fastest time as well as the greatest scope. The project can thus have an exceptional impact on science, the society as well as economy and is of the highest interest to Slovenia, the EU as well as globally.
Significance for science
Despite the trend in the microbiological and biotechnological fields to treat the DNA molecule as a sequence of merely four different letters, it is a much more complex and dynamic system. For the study of DNA, its conformational and physicochemical properties must analysed at the global level of several thousand to ten thousand base pairs, as well as at the local level of some ten or hundred base pairs, in order to deepen our functional insight and to distinguish new genetic products. It is important to find the intrinsic language encoded in DNA that regulates the processes of expression, replication, recombination and DNA transfer. Thus in the project I developed: (i) tools for predicting structural properties and structural representations of DNA, (ii) tools for the statistical comparison of biomolecular representations and discrimination of functional groups of molecules, (iii) the STRAST algorithm for structural alignment, which upgrades the BLAST algorithm, and (iv) algorithms for characterizing and designing motifs and gene clusters. Although the identification of regulatory regions is a large area of ??research, it is not often used to identify gene clusters when searching for antimicrobial compounds. Since predicting biomolecular properties of DNA regulatory regions is a particularly new area, algorithms based on such DNA properties present a useful expansion of tools for identifying genes in biotechnological applications and thus a significant advance in the field of (meta)genomics. Structural algorithms not only improve the functioning of existing algorithms, but also complement them, as they can be used in parallel to achieve better discrimination within the data. The developed tools enable the analysis of various representations of biomolecular properties, such as those that describe promising antimicrobial compounds in metagenomic data. We extend the functionality of new algorithms for identification of antimicrobial coding gene clusters through an optimization process that combines the analysis of non-coding and coding DNA regions, one in the structural and the other in the nucleotide representation, respectively. In addition to the above algorithms, I expect that the analysis of AMR systems will have the greatest scientific impact. The processes of horizontal transfer of mobile DNA elements that propagate AMR among deadly microbes are poorly investigated. That is why our models of the process of mobilization, analysis of origin-of-transfer regions and tools to predict potential plasmid hosts are a significant contribution to the field. Using the custom algorithm for alignment of the structural representation of DNA, STRAST, we can precisely locate the regions of mobility within plasmids and genomes. The tool therefore enables a very fast and precise forecast of the transfer properties and host repertoires of mobile elements and AMR genes. It has a high potential for analyzing newly obtained genomic and metagenomic data, since now we can predict the mobility and host repertoires in any DNA sample. As the results show a much wider mobility of AMR than has thus far been detected by existing approaches, I am convinced that our tools and database will serve basic and clinical researchers in further research and development. Based on the results of the project, completely new approaches can be developed to prevent the spread of AMR and control microbial contamination, and to develop antimicrobial compounds with a lower incidence of AMR resistance. I expect that the developed algorithms will be widely useful in the fields of biotechnology and microbiology due to their operational flexibility and development potential. For example, with minimal effort, the tools can be adapted for use with different organisms and data. They are not limited to only prokaryotic organisms, but can also be used with eukaryotic ones, such as fungi and plants, which also produce many useful compounds and medicines.
Significance for the country
The project has significantly contributed to (i) understanding the processes of horizontal gene transfer of antimicrobial drug resistance (AMR), (ii) approaches to predicting and using DNA biomolecular properties in genomic analyses, and (iii) new algorithms for finding antimicrobials and reducing AMR resistance. The project leader - postdoctoral researcher - has enabled the establishment of a new scientific field in Slovenia, in which he is building his career. In addition to the results, the postdoctoral researcher received several international awards, established numerous co-operations, visited international conferences and completed numerous educational courses. His collaboration with the very successful group for systems biology at the Chalmers University of Technology has been strengthened to the extent that he has gained a long-term research position in this respectable institution in the group, where he continues the research and development of the scientific field. Microbial infections have a major impact on health and reduce GDP due to declining productivity (AMR costs both the US and the EU € 60 million per year). Given that the results of the proposed project are algorithms for finding and optimizing antimicrobial compounds and reducing AMR resistance, they can help create solutions for improving the health and protection of citizens. Therefore, the project has a significant impact on both society and the economy. Methods for analyzing, understanding and predicting the emergence of AMR enable life saving solutions, since it is possible to develop new strategies for the use of not only new but also existing antimicrobials, which can be quickly introduced into clinical practice. Thus the methods can be used to create health care solutions that save lives in the fastest time and to the fullest extent. In addition to the importance in the health sector, the results have an impact in other industrial and environmental sectors as they contribute to solving current AMR problems and lack of antimicrobial drugs as well as enable new technological solutions for many other industries. Based on metagenomic and bioinformatic approaches, a large number of antimicrobial compounds can be detected and introduced into pharmaceutical pipelines. Antimicrobial compounds are also the basic ingredients of various industrial products that are designed to destroy or prevent the growth of microbes. Therefore, the project results have the potential to provide a basis for new antimicrobial-based products and services (e.g. algorithms used in drug development platforms), which promote the growth and development of new businesses. The proposal complies with the objectives of Slovenian policies and strategies by enabling: (i) efficient use of natural resources and development of bio based environmental technologies via platforms for exploiting natural resources for drug discovery Slovenian Industrial Policy, (ii) sustainable development with ecological products based on antimicrobials, such as ecoinnovative coatings Resolution on Research and Innovation Strategy of Slovenia 2011-2020, (iii) higher quality of life and health by helping solve AMR problems Slovenian Smart Specialisation Strategy. The results of the project can positively impact initiatives, such as the formation of public private partnerships that align public and private interests and help expedite the process of development of new antimicrobials and strategies to prevent AMR. The importance of these partnerships is outlined in the The Commission presented the communication on "Public private partnerships in Horizon 2020: a powerful tool to deliver on innovation and growth in Europe" in July 2013 (12344/13).
Most important scientific results
Interim report,
final report
Most important socioeconomically and culturally relevant results
Interim report,
final report
