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      Non-natural Aldol Reactions Enable the Design and Construction of Novel One-Carbon Assimilation Pathways in vitro

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          Abstract

          Methylotrophs utilizes cheap, abundant one-carbon compounds, offering a promising green, sustainable and economical alternative to current sugar-based biomanufacturing. However, natural one-carbon assimilation pathways come with many disadvantages, such as complicated reaction steps, the need for additional energy and/or reducing power, or loss of CO 2, resulting in unsatisfactory biomanufacturing performance. Here, we predicted eight simple, novel and carbon-conserving formaldehyde (FALD) assimilation pathways based on the extended metabolic network with non-natural aldol reactions using the comb-flux balance analysis (FBA) algorithm. Three of these pathways were found to be independent of energy/reducing equivalents, and thus chosen for further experimental verification. Then, two novel aldol reactions, condensing D-erythrose 4-phosphate and glycolaldehyde (GALD) into 2 R,3 R-stereo allose 6-phosphate by DeoC or 2 S,3 R-stereo altrose 6-phosphate by TalB F178Y/Fsa, were identified for the first time. Finally, a novel FALD assimilation pathway proceeding via allose 6-phosphate, named as the glycolaldehyde-allose 6-phosphate assimilation (GAPA) pathway, was constructed in vitro with a high carbon yield of 94%. This work provides an elegant paradigm for systematic design of one-carbon assimilation pathways based on artificial aldolase (ALS) reactions, which could also be feasibly adapted for the mining of other metabolic pathways.

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          COBRApy: COnstraints-Based Reconstruction and Analysis for Python

          Background COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Results Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. Conclusion COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. Availability http://opencobra.sourceforge.net/
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            Poly(ethylene glycol) in drug delivery: pros and cons as well as potential alternatives.

            Poly(ethylene glycol) (PEG) is the most used polymer and also the gold standard for stealth polymers in the emerging field of polymer-based drug delivery. The properties that account for the overwhelming use of PEG in biomedical applications are outlined in this Review. The first approved PEGylated products have already been on the market for 20 years. A vast amount of clinical experience has since been gained with this polymer--not only benefits, but possible side effects and complications have also been found. The areas that might need consideration and more intensive and careful examination can be divided into the following categories: hypersensitivity, unexpected changes in pharmacokinetic behavior, toxic side products, and an antagonism arising from the easy degradation of the polymer under mechanical stress as a result of its ether structure and its non-biodegradability, as well as the resulting possible accumulation in the body. These possible side effects will be discussed in this Review and alternative polymers will be evaluated.
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              The MetaCyc database of metabolic pathways and enzymes

              Abstract MetaCyc (https://MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains more than 2570 pathways derived from >54 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc is strictly evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in the BioCyc (https://BioCyc.org) and other PGDB collections. This article provides an update on the developments in MetaCyc during the past two years, including the expansion of data and addition of new features.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                02 June 2021
                2021
                : 12
                : 677596
                Affiliations
                [1] 1Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences , Tianjin, China
                [2] 2Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences , Tianjin, China
                [3] 3State Key Laboratory of Food Nutrition and Safety, Tianjin University of Science and Technology , Tianjin, China
                [4] 4Key Laboratory of Systems Bioengineering (Ministry of Education), SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), School of Chemical Engineering and Technology, Tianjin University , Tianjin, China
                Author notes

                Edited by: Guodong Luan, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences (CAS), China

                Reviewed by: Steffen N. Lindner, Max Planck Institute of Molecular Plant Physiology, Germany; Xavier Garrabou Pi, ETH Zürich, Switzerland; Fei Tao, Shanghai Jiao Tong University, China

                *Correspondence: Hongwu Ma, ma_hw@ 123456tib.cas.cn

                These authors have contributed equally to this work

                This article was submitted to Microbiotechnology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.677596
                8208507
                34149668
                7ee00eb4-bbf8-469e-84aa-70ada6d59485
                Copyright © 2021 Mao, Yuan, Yang, Liu, Cheng, Luo, Liu, Yao, Sun, Cai and Ma.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 08 March 2021
                : 04 May 2021
                Page count
                Figures: 8, Tables: 2, Equations: 6, References: 46, Pages: 13, Words: 7309
                Funding
                Funded by: National Key Research and Development Program of China 10.13039/501100012166
                Award ID: 2018YFA0901400
                Award ID: 2018YFA0900300
                Funded by: Chinese Academy of Sciences 10.13039/501100002367
                Award ID: 153D31KYSB20170121
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 21908239
                Funded by: Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project
                Award ID: TSBICIP-PTJS-001
                Award ID: TSBICIP-KJGG-005
                Funded by: China Postdoctoral Science Foundation 10.13039/501100002858
                Award ID: 2018M641658
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                synthetic methylotrophy,computational pathway design,allose 6-phosphate,in vitro pathway construction,aldolase reaction,glycolaldehyde-allose 6-phosphate assimilation pathway

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