A Genome-Scale Metabolic Model of Anabaena 33047 to Guide Genetic Modifications to Overproduce Nylon Monomers

A machine learning framework for extracting information from biological pathway images in the literature

There have been significant advances in literature mining, allowing for the extraction of target information from the literature. However, biological literature often includes biological pathway images that are difficult to extract in an easily editable format. To address this challenge, this study aims to develop a machine learning framework called the "Extraction of Biological Pathway Information" (EBPI). The framework automates the search for relevant publications, extracts biological pathway information from images within the literature, including genes, enzymes, and metabolites, and generates the output in a tabular format. For this, this framework determines the direction of biochemical reactions, and detects and classifies texts within biological pathway images. Performance of EBPI was evaluated by comparing the extracted pathway information with manually curated pathway maps. EBPI will be useful for extracting biological pathway information from the literature in a high-throughput manner, and can be used for pathway studies, including metabolic engineering.

Dynamic flux balance analysis of high cell density fed-batch culture of Escherichia coli BL21 (DE3) with mass spectrometry-based spent media analysis

Dynamic flux balance analysis (FBA) allows estimation of intracellular reaction rates using organism-specific genome-scale metabolic models (GSMM) and by assuming instantaneous pseudo-steady states for processes that are inherently dynamic. This technique is well-suited for industrial bioprocesses employing complex media characterized by a hierarchy of substrate uptake and product secretion. However, knowledge of exchange rates of many components of the media would be required to obtain meaningful results. Here, we performed spent media analysis using mass spectrometry coupled with liquid and gas chromatography for a fed-batch, high-cell density cultivation of Escherichia coli BL21(DE3) expressing a recombinant protein. Time course measurements thus obtained for 246 metabolites were converted to instantaneous exchange rates. These were then used as constraints for dynamic FBA using a previously reported GSMM, thus providing insights into how the flux map evolves through the process. Changes in tri-carboxylic acid cycle fluxes correlated with the increased demand for energy during recombinant protein production. The results show how amino acids act as hubs for the synthesis of other cellular metabolites. Our results provide a deeper understanding of an industrial bioprocess and will have implications in further optimizing the process.

Synthetic biology in marine cyanobacteria: Advances and challenges

The current economic and environmental context requests an accelerating development of sustainable alternatives for the production of various target compounds. Biological processes offer viable solutions and have gained renewed interest in the recent years. For example, photosynthetic chassis organisms are particularly promising for bioprocesses, as they do not require biomass-derived carbon sources and contribute to atmospheric CO2 fixation, therefore supporting climate change mitigation. Marine cyanobacteria are of particular interest for biotechnology applications, thanks to their rich diversity, their robustness to environmental changes, and their metabolic capabilities with potential for therapeutics and chemicals production without requiring freshwater. The additional cyanobacterial properties, such as efficient photosynthesis, are also highly beneficial for biotechnological processes. Due to their capabilities, research efforts have developed several genetic tools for direct metabolic engineering applications. While progress toward a robust genetic toolkit is continuously achieved, further work is still needed to routinely modify these species and unlock their full potential for industrial applications. In contrast to the understudied marine cyanobacteria, genetic engineering and synthetic biology in freshwater cyanobacteria are currently more advanced with a variety of tools already optimized. This mini-review will explore the opportunities provided by marine cyanobacteria for a greener future. A short discussion will cover the advances and challenges regarding genetic engineering and synthetic biology in marine cyanobacteria, followed by a parallel with freshwater cyanobacteria and their current genetic availability to guide the prospect for marine species.