scholarly journals Back to the future: Why we need enzymology to build a synthetic metabolism of the future

2019 ◽  
Vol 15 ◽  
pp. 551-557 ◽  
Author(s):  
Tobias J Erb
Keyword(s):  
Metabolic Engineering ◽  
Metabolic Networks ◽  
Bottom Up ◽  
Theoretical Design ◽  
Enzyme Discovery ◽  
Tremendous Progress ◽  
The Future ◽  
Actual Realization

Biology is turning from an analytical into a synthetic discipline. This is especially apparent in the field of metabolic engineering, where the concept of synthetic metabolism has been recently developed. Compared to classical metabolic engineering efforts, synthetic metabolism aims at creating novel metabolic networks in a rational fashion from bottom-up. However, while the theoretical design of synthetic metabolic networks has made tremendous progress, the actual realization of such synthetic pathways is still lacking behind. This is mostly because of our limitations in enzyme discovery and engineering to provide the parts required to build synthetic metabolism. Here I discuss the current challenges and limitations in synthetic metabolic engineering and elucidate how modern day enzymology can help to build a synthetic metabolism of the future.

Square patterns formed from the directed self-assembly of block copolymers

2021 ◽  
Author(s):  
Weihua Li ◽  
Xueying Gu
Keyword(s):  
Block Copolymers ◽  
Self Assembly ◽  
Bottom Up ◽  
Tremendous Progress

Since tremendous progress has been made, directed self-assembly (DSA) of block copolymers has been regarded as one of the most promising bottom-up lithography techniques. In particular, DSA has been successfully...

Model-guided identification of novel gene amplification targets for improving succinate production in Escherichia coli NZN111

2017 ◽  
Vol 9 (10) ◽  
pp. 830-835 ◽  
Author(s):  
Xingxing Jian ◽  
Ningchuan Li ◽  
Qian Chen ◽  
Qiang Hua
Keyword(s):  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Gene Amplification ◽  
Metabolic Networks ◽  
Computational Analysis ◽  
Succinate Production ◽  
Novel Gene ◽  
Metabolic Models ◽  
Genome Scale

Reconstruction and application of genome-scale metabolic models (GEMs) have facilitated metabolic engineering by providing a platform on which systematic computational analysis of metabolic networks can be performed.

Social Interaction Technologies and the Future of Blogging

2012 ◽  
pp. 249-274 ◽  
Author(s):  
Tatyana Dumova
Keyword(s):  
Social Media ◽  
Social Interaction ◽  
Driving Forces ◽  
User Generated Content ◽  
Peer Production ◽  
Bottom Up ◽  
The Future ◽  
Grassroots Initiatives ◽  
Creativity And Innovation ◽  
The Web

In an age of user-generated content, multimedia sharing sites, and customized news aggregators, an assortment of Internet-based social interaction technologies transforms the Web and its users. A quintessential embodiment of social interaction technologies, blogs are widely used by people across diverse geographies to locate information, create and share content, initiate conversations, and collaborate and interact with others in various settings. This chapter surveys the global blogosphere landscape for the latest trends and developments in order to evaluate the overall direction that blogging might take in the future. The author posits that network-based peer production and social media convergence are the driving forces behind the current transformation of blogs. The participatory and inclusive nature of social interaction technologies makes blogging a medium of choice for disseminating user-driven content and particularly suitable for bottom-up grassroots initiatives, creativity, and innovation.

scholarly journals Engineering microbial chemical factories using metabolic models

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Debolina Sarkar ◽  
Costas D. Maranas
Keyword(s):  
Metabolic Engineering ◽  
Metabolic Networks ◽  
Reaction Rates ◽  
Control Engineering ◽  
Current Perspective ◽  
Simple Molecules ◽  
Living Organisms ◽  
Metabolic Network Modeling ◽  
And Control ◽  
Analytical Approaches

Abstract Living organisms in analogy with chemical factories use simple molecules such as sugars to produce a variety of compounds which are necessary for sustaining life and some of which are also commercially valuable. The metabolisms of simple (such as bacteria) and higher organisms (such as plants) alike can be exploited to convert low value inputs into high value outputs. Unlike conventional chemical factories, microbial production chassis are not necessarily tuned for a single product overproduction. Despite the same end goal, metabolic and industrial engineers rely on different techniques for achieving productivity goals. Metabolic engineers cannot affect reaction rates by manipulating pressure and temperature, instead they have at their disposal a range of enzymes and transcriptional and translational processes to optimize accordingly. In this review, we first highlight how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed in systems and control engineering. Specifically, how algorithmic concepts derived in operations research can help explain the structure and organization of metabolic networks. Finally, we consider the future directions and challenges faced by the field of metabolic network modeling and the possible contributions of concepts drawn from the classical fields of chemical and control engineering. The aim of the review is to offer a current perspective of metabolic engineering and all that it entails without requiring specialized knowledge of bioinformatics or systems biology.

scholarly journals A Critical Review of Bottom-Up Proteomics: The Good, the Bad, and the Future of This Field

Proteomes ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 14 ◽  
Author(s):  
Emmalyn J. Dupree ◽  
Madhuri Jayathirtha ◽  
Hannah Yorkey ◽  
Marius Mihasan ◽  
Brindusa Alina Petre ◽  
...  
Keyword(s):  
Data Analysis ◽  
Sample Preparation ◽  
Protein Interactions ◽  
Clinical Setting ◽  
Critical Review ◽  
Basic Science ◽  
Protein Protein Interactions ◽  
Bottom Up ◽  
Post Translational Modifications ◽  
The Future

Proteomics is the field of study that includes the analysis of proteins, from either a basic science prospective or a clinical one. Proteins can be investigated for their abundance, variety of proteoforms due to post-translational modifications (PTMs), and their stable or transient protein–protein interactions. This can be especially beneficial in the clinical setting when studying proteins involved in different diseases and conditions. Here, we aim to describe a bottom-up proteomics workflow from sample preparation to data analysis, including all of its benefits and pitfalls. We also describe potential improvements in this type of proteomics workflow for the future.

Liquid-phase bottom-up synthesis of graphene nanoribbons

2020 ◽  
Vol 4 (1) ◽  
pp. 29-45 ◽  
Author(s):  
Ki-Young Yoon ◽  
Guangbin Dong
Keyword(s):  
Liquid Phase ◽  
Graphene Nanoribbons ◽  
Future Outlook ◽  
Bottom Up ◽  
The Future

This review summarises the development of bottom-up synthesis of graphene nanoribbons in liquid phase and provides views on challenges in the field and the future outlook.

BU-Router: Researching on Techniques of Global Router

2014 ◽  
Vol 513-517 ◽  
pp. 539-544
Author(s):  
Chun Yang Zhang ◽  
Jun Fu Li ◽  
Qian Xu
Keyword(s):  
Cost Function ◽  
Vlsi Circuit ◽  
Long Distance ◽  
Bottom Up ◽  
Cpu Time ◽  
The Future ◽  
Global Route ◽  
Run Time ◽  
Maze Algorithm ◽  
Optimum Solution

Variety of routing approaches are employed by global routers in the VLSI circuit designs. Rip-up and reroute, as a conveniently implemented method, is widely used in most of modern global routers. Maze algorithm is always performed iteratively as the final technique to eliminate overflow. Maze algorithm and its ramifications can obtain an optimum solution. However, it will cost much CPU time if being used impertinently. In this work, we present a global router called Bottom-Up Router (BU-Router), with an optimized maze algorithm, which is based on multi-source multi-sink maze. BU-Router processes not the nets but the segments of nets in a sequence ordered by the length. In the progress, segments will be fixed on the global route graph edge, when the edge is saturated, which is as the basis, also known as bottom. Then the edge will be set as a blockage, which wont accept path goes through it any more. This means the edge will push the possible congestion in the future. Besides this, BU-Router optimized cost function in two ways: make the function adaptive and congestion center avoidable. Additionally, a specific optimized maze algorithm is proposed for routing a long distance segment so as to reduce the run-time.

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