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BioBite Student Submission: The Impact of mRNA Secondary Structures on Translation and Cell Growth

December 10, 2018

As part of our mission to inspire the next generation of Synthetic Biologists, we are featuring student submissions on our blog. These articles are written by undergraduate students with a passion for the field of Synbio and are on an article, topic or idea they find interesting! If you would like to submit a piece of your own, contact us at: 

 

The translation of mRNA sequences into polypeptides is the moment when synthetic biology creations start to come to life, where the modifications to the DNA and subsequent proteins are visualized and their impacts on the cell start to be noticed. It is known that direct modifications to the chromosomes, such as methylation and acetylation of histones and DNA, can affect the rate of transcription and translation of such genes. Previous studies have shown the importance of mRNA structures in hindering initiation by blocking ribosome binding sites and causing incomplete translation. But what is still not well-studied is the effect of secondary structures (three-dimensional conformation) of mRNA strands on translation and cell function. Knowledge of such effects can help in improving mRNA design for synthetic biology applications, such as the commercial production of enzymes and proteins, and the design of novel molecules for use in medicine and industry.  Therefore, scientists from the University of California, Berkeley and the University of Montpellier conducted a research study published in Nature to investigate how the secondary structure of mRNA strands affect cell functions and translation by ribosomes in E.coli.


The research group focused on varying different intrinsic and interdependent properties of the DNA molecule to affect the mRNA samples produced and their translation. Properties varied include the sequence nucleotide content (% A and T), hydrophobicity of coded polypeptide, stability of secondary structures in the transcript, and pattern of codon usage. The Codon Adaptation Index (CAI) was used to quantify the abundance of a codon in the DNA sample, by constructing a ratio of the presence of a codon to the maximum number of its synonymous codons. These factors were varied and combined into 244,000 synthetic sequences. Such modified sequences were then transferred to the cell via a plasmid containing a fluorescent reporter, which helps monitor protein production. The extent of the effect of different factors on mRNA transcription and cell metabolism was studied in terms of protein production, mRNA abundance and stability, distribution of ribosomes per transcript, and bacterial growth rate. 


The research group reported interesting links between secondary mRNA structure and translation efficiency. mRNA structures around the start codon have the biggest effect on translation efficiency. Higher initiation rates caused a global but non-uniform increase in protein production. Such mechanisms can be used to increase efficiency of commercial protein production in industry. Furthermore, distal mRNA secondary structures can indirectly affect translation initiation by outcompeting initiation-limiting structures in binding to the ribosomes. Weak (thermodynamically unstable) structures in the transcript, combined with high CAI, have faster initiation and unhindered elongation, increasing protein production. However, in industry, this raises concern about the costs of maintaining these cells because of the increased need for resources. Fast ribosome turnover rates ensure their redistribution towards other transcripts, lowering cellular costs. Low CAI transcripts and strong, stable transcripts are rarely translated and trap translation resources (such as ribosomes), limit cell growth. Therefore, some degree of transcript instability is required to prevent ribosome sequestration, speed up elongation and maintain translation and cell growth, reflecting the multi-dimensional, complex nature of transcript design and the need for trial-and-error in the early stages of transcript design.


The design of this experiment as a full statistical array is not usually common in biotechnology, and has various disadvantages. Designed synthetic libraries are well-suited to studying known possible mechanisms. However, this does not give enough opportunities to uncover novel mechanisms of secondary structure impacting mRNA translation, that can arise in nature and through random mutations. Also, scoring algorithms are unable to capture functionally important differences between very similar nucleotide sequences, and unrelated sequences with similar structural profiles can yield very different phenotypic results, indicating how complex this subject is because secondary structures are unpredictable emergent properties.


There is certainly room for improvement in this field of research and prospects for incorporating such findings in industrial applications. Through developments in secondary-structure prediction machine learning algorithms and more extensive research and comparison between natural and synthetic modifications, and random and planned modifications, the effect of secondary structures on translation can better be understood. This allows for more effective mRNA design that can help optimize the commercial production of enzymes designed using synthetic biology and DNA modification, as well as avoid unintended outcomes (such as slow cell proliferation) in research applications. Translation is a very energy-consuming and thermodynamically complex process, therefore, the optimization of mRNA for decreased cellular and financial costs is an aim that can be accomplished in the foreseeable future. Inspiration for more efficient translation can be obtained from natural sequences that exhibit such processes, further fueling the nature-inspired biotechnology design movement.
 

 

Nature Biotechnology Article: "Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli" 

Published: 24 September 2018

DOI: https://doi.org/10.1038/nbt.4238 

Link: https://www.nature.com/articles/nbt.4238#search-menu 

 

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© 2019 Living Computing Project.

Sponsored by National Science Foundation’s Expeditions in Computing Program

(Awards #1522074 / 1521925 / 1521759).

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