Biomolecular and cell technologies

Definition

In broad terms, biomolecular technologies include mapping, measuring and using molecules such as DNA, RNA, and proteins/metabolites. An important group of technologies is formed by X-omics (Genomics/transcriptomics/ proteomics/metabolomics/glycomics, microbiomics, exposomics) which aim to quantify and characterise the set of biological entities of a particular type, such as the genome, proteome, metabolome, microbiome or exposome of an organism. This way, therapeutic or disease-prevention strategies tailored to the individual can be developed (personalised medicine), or a crop or animal can be developed that is resistant to abiotic stress (e.g. due to extreme climatic conditions) and biotic stress (due to infestation by diseases and pests). A second group involves gene editing/precise genetic engineering techniques that allow the DNA of an organism (human, animal, plant, microbe) to be altered at very specific sites. A third group comprises stem cell technology (also known as regenerative medicine), promotes the repair response of diseased, dysfunctional or damaged tissue using stem cells. Regeneration in crops is also a form of stem cell technology, creating a completely new plant from a single cell (for the purpose of propagation but also elimination of plant viral diseases). Synthetic cell technology is emerging as a technique that mimics the structure and function of living cells from scratch (minimal cell) with the aim of increasing the yield and quality of the product and preventing by-products, which improves safety. Interest in organoids is also growing rapidly: three-dimensional miniature versions of organs grown from stem cells.

Keywords (selection)

Genome analysis, Genomic engineering, Multi-omics, Integrated omics, Biomarkers,
Metabolomics, Transcriptomics, Proteomics, Glycomics High-throughput sequencing,
Next generation sequencing, Machine learning, gen-functie voorspelling, Proteome/
Genome/Metabolome analysis, Analytical chemistry, Exposome, Microbiome,
Molecules by design, Cell Surface Display Techniques, Biomarker discovery.

CRISPR-Cas, Single gene disorders, Ethics, DNA repair, Gene therapy, Genome editing,
New Genomic Techniques, Precision Breeding, Synthetic Biology, Genetic Modification,
Personalized medicine., Personalized food, Biofortification.

Regenerative medicine, Organ transplantation, Tissue repair, Gene therapy, Targeted
gene repair, Induced Pluripotent Stem Cells, In vitro Regeneration, Artificial cells,
Minimal cells, Cell therapy, Synthetic biology, Metabolic Engineering, Organoids,
Synthetic stem cells.

Definitie

Biosystemen omvat een aantal verschillende componenten. In vitro systemen en met name organoïden spelen in de medische sector een steeds belangrijker rol. Nanomedicine betreft de toepassing van nanotechnologie ten behoeve van gezondheid. Die toepassingen vinden vooral plaats in biochips en biosensoren voor diagnose of functionele karakterisatie van complexe (voedings) mengsels. Ook speelt nanotechnologie een belangrijke rol in organen-op-chips (OoC’s): systemen met gemodificeerde of natuurlijke miniatuurweefsels die in microfluïdische chips zijn gekweekt die representatief zijn voor gezonde of ongezonde humane weefsels. Andere
biosysteemtechnologieën zijn van belang in de industrie en voor milieutoepassingen
zoals bioremediation. Het gaat hier om biosystemen als microbiële consortia (darm,
bodem enz), waterplanten, biofilms, symbiotische systemen, en voor productie via
planten (vertical farms, algen).

Keywords (selectie)

Nanotechnology, Nanomaterials, Nanoelectronics, Nanofluids, Metabolic engineering,
Bioreceptor, transducer, Analytes, Microfluidics, Biosensing, Lab-on-a-chip, Organon-a-chip, Microfluidics, Biosensors, Glucose Sensors, Immunosensors, Analytic Equipment. Organoids, Primary Cell Culture, Tissue Scaffolds, Bioprinting, stem cell technology, Microelectronics, Microfabrication, Organ and/or disease models, Personalized medicine, Patient-specific Modeling, Microbia(l consortia, Biofilms, Symbiotic systems.

Definition

Biomanufacturing and bioprocess technology are important, inter alia, in industrial and food biotechnology that uses enzymes and micro-organisms to make bio-based products: sectors such as chemicals, medicine production, food and feed, healthcare, paper and pulp, textile biopolymers and bio-energy. A prominent role in this bioprocess technology is played by biocatalysis: the use of natural substances, including enzymes from biological sources or whole cells, to accelerate chemical reactions. Much attention is devoted to optimising (industrial) production conditions such as cultivation cells, culture systems and fermenters. Bioprocessing also has important environmental applications for wastewater treatment (and other biological purification techniques). A rapidly developing high-tech branch of bioproduction is biofabrication: the production of complex biological products from raw materials such as living cells, matrices, plant biomass (including residual streams), biomass from fungi (e.g. mycelium from mushroom-forming fungi), biomaterials and molecules partly stimulated by the development of 3D fabrication technologies.

Keywords (selection)

Microorganisms, Bio-based products, Bio-Based Building blocks, Biopolymer fibres,
Biodegradable plastics, Biofuels, Lubricants, Industrial enzymes, Antibiotics, Vitamins,
Amino acids and other fine chemicals, Pharmaceuticals, Vaccines or vaccine components, Diagnostics, Greenhouse gas emissions, Synthetic Biology, Metabolic
engineering, Bio process technology.

Protein Engineering, Organic solvents, Microorganism Biocatalyst, Superoxide
Reductase.

Biomaterials, fabrication, bioprinting, Tissue Scaffolds.

Tissue Engineering, Artificial organs, Patient-specific Modeling, Cell Engineering,
3D biofabrication, 3D reconstruction, tissue constructs, biological models, regenerative medicine.

Definition

Bio-informatics is the application of information sciences to biological processes. Recently, bio-informatics has received a major boost from developments in machine learning and AI that allow meaningful connections to be made from very large data sets. AI enables much faster understanding of, for example, the 3D structure of proteins, complex multigen processes in organisms, the risk factors and causes of diseases or the expected response to medical interventions or medication in animals or humans or of a crop under biotic/abiotic stress. Also important is obtaining an overview of allelic variation and variation in phenotypes, and the analysis of complex networks, including non-biological and environmental (ecosystem) data.

Keywords (selection)

Functional genomics, Structural genomics, Genome analysis, Genome-wide association studies, DNA Microarrays, Metabolome analysis, Medical Informatics, Systems biology, Artificial Intelligence, Machine learning, DNA/RNA/protein sequencing, Computational biology, Personalized medicine, Genetic diversity, Directed evolution.