Many efforts are currently underway to try and mimic the properties of single cells with the aim of designing chips that are as efficient as cells. However, cells are nature's nanotechnology engineering at the scale of atoms and molecules, and it might be better to envision a microchip that utilizes a single cell as an experimentation platform. A novel, so-called laboratory-in-a-cell concept has been described, where advantage is taken of micro-and nanotechnological tools to enable precise control of the biochemical cellular environment; these tools also offer the possibility to analyse the composition of single cells. Methods for single-cell handling and analysis are being developed and will be required for this concept to progress further.
Bioindustry is expanding to an increasing variety of food, chemical and pharmaceutical products, each requiring rapid development of a dedicated cell factory and bioprocess. Microfluidic tools are, together with tools from synthetic biology and metabolic modeling, being employed in cell factory and bioprocess development to speed up development and address new products. Recent examples of microfluidics for bioprocess development range from integrated devices for DNA assembly and transformation, to high throughput screening of cell factory libraries, and micron scale bioreactors for process optimization. These improvements act to improve the biotechnological engineering cycle with tools for building, testing and evaluating cell factories and bioprocesses by increasing throughput, parallelization and automation.
Bio-based production of chemical building blocks from renewable resources is an attractive alternative to petroleum-based platform chemicals. Metabolic pathway and strain engineering is the key element in constructing robust microbial chemical factories within the constraints of cost effective production. Here we discuss how the development of computational algorithms, novel modules and methods, omics-based techniques combined with modeling refinement are enabling reduction in development time and thus advance the field of industrial biotechnology. We further discuss how recent technological developments contribute to the development of novel cell factories for the production of the building block chemicals: adipic acid, succinic acid and 3-hydroxypropionic acid.
Recent metabolic engineering strategies for bio-based production of monomers and polymers are reviewed. In the case of monomers, we describe strategies for producing polyamide precursors, namely diamines (putrescine, cadaverine, 1,6-diaminohexane), dicarboxylic acids (succinic, glutaric, adipic, and sebacic acids), and ω-amino acids (γ-aminobutyric, 5-aminovaleric, and 6-aminocaproic acids). Also, strategies for producing diols (monoethylene glycol, 1,3-propanediol, and 1,4-butanediol) and hydroxy acids (3-hydroxypropionic and 4-hydroxybutyric acids) used for polyesters are reviewed. Furthermore, we review strategies for producing aromatic monomers, including styrene, p-hydroxystyrene, p-hydroxybenzoic acid, and phenol, and propose pathways to aromatic polyurethane precursors. Finally, in vivo production of polyhydroxyalkanoates and recombinant structural proteins having interesting applications are showcased.
Currently one of the most challenging tasks in biological and medical research is to explore and understand the function of all proteins encoded by the genome of an organism. A systematic approach based on the genome sequences is feasible because the full genome of many organisms presently is available and many more are underway. For the production of expression atlases different strategies are used. Early attempts to acquire information about protein expression levels have focused on the analysis of mRNA levels within different tissues and cell types. Recently, novel strategies to focus directly on protein levels have been developed. To assess global protein expression in a systematic and high-throughput manner, methods based on design of specific affinity ligands to recognize the proteins have been presented. By subsequently using these affinity molecules for detection of the corresponding proteins in a wide range of platforms, important information can be gained. This article focuses on strategies to profile protein levels and in particular the human protein atlas initiative and the use of microarray technologies.
Recent developments to modify enzymes for use in organic synthesis have targeted several areas. These include altering the reaction mechanism of the enzyme to catalyse new reactions, switching substrate specificity, expanding substrate specificity, and improving substrate specificity, such as enantioselectivity in kinetic resolutions. Such modifications can be achieved either by rational redesign, which requires knowledge of the enzyme structure, or by random mutagenesis methods followed by screening. Both strategies of enzyme engineering can be successful and are very useful for improving the utility of enzymes for applied catalysis. Several examples illustrating these concepts in a variety of enzyme classes have appeared recently.
Non-immunoglobulin based protein scaffolds have been reported as promising alternatives to traditional monoclonal antibodies for over a decade and are often mentioned as part of the next-generation immunotherapeutics. Today, this class of biologics is beginning to demonstrate its potential for therapeutic applications and several are currently in preclinical or clinical development. A common denominator for most of these new scaffolds is the attractive properties that differentiate them from monoclonal antibodies including small size, cysteine-free sequence, flexible pharmacokinetic properties, and ease of generating multispecific molecules. In addition to therapeutic applications, substantial evidence point to superior performance of several of these scaffolds in molecular imaging compared to full-length antibodies. Here we review the most recent progress using alternative protein scaffolds for therapy and medical imaging.
Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.