EvoMAG for genetic pathway engineering and Gene Syntheses Services

EvoMAG (Evolution Mediated Artificial Genetics) is ATG’s gene intelligence solution for multi-parametric gene and gene cluster design for metabolic engineering and optimization in diverse target organisms. It powers the company’s comparative genomics analyses and the genetic pathway operon engineering services.

EvoMAG accelerates pathway engineering for comparative genomic analyses in detail, the identification of new secondary metabolite pathways in natural product drug discovery and/or functional improvements by genetic modulation in constructive molecular projects.

Project results of multi-genes can be realized directly by ATG gene syntheses services:

Table-1. Payback or free gene mode can be choosen if a volume category of annual basepairs is passed, Then the difference in cost between two categories is compensated by either refunding or free genes.

Gene Sequence Design

The sequence space in genomics and even in genetics is enormous and was first described by Nobel Laureate Manfred Eigen.

It turns out that there is no need to search for a single needle in the haystack because the nature of molecular systems means that there are many possible solutions. The chances of finding reasonable and practicable solutions can be enhanced by using iterative improvement schemes controlled by genome statistics and Design of Experiment (DoE) techniques.

Explorative heuristic discovery strategies are experience-based techniques that help in problem solving and learning. In more precise terms, heuristics stand for strategies using readily accessible, though loosely applicable information to control problem solving.

Before the realization of an artificial gene sequence composition, multiple sequence parameters need to carefully choosen and processed in parallel.

Therefore the planning phase of a biodesign is of highest importance and a priority in identifying the relevant genetic building blocks: mostly enzyme gene entities involved in orchestrating specific catalytical cascades for constituting a pathway system or protein hetero-complexes.

In this way, the experimental space of pathway engineering can be explored in order to find advantageous parameter constellations that lie close to the intended solution.

Optimized synthesis efficiency

ATG has continuously developed its EvoMAG Gene Intelligence software based on years of engagement on customer projects and as a response to their specific requirements, to optimize constructive aspects of overall design and synthesis efficiency, along with functional aspects of expression, solubility, etc..

EvoMAG’s evolutionary genetic algorithms calculate multiple gene sequence parameters simultaneously in silico for diverse functional optimizations of formal-operational gene features.

Any gene and gene cassette cloned into ATG’s multi-gene assembly and expression systems can be adapted for optimal expression of the whole set of functionally related genes by systematically employing EvoMAG algorithms.

EvoMAG was designed to compute many relevant parameters in the gene optimization process in parallel. The gene sequence is subjected to a tournament situation where many variants compete for the best fit. Certain parameters can be given more weight than others and this will reflect in the output.

Where the aim is to improve codon bias of genes towards deploying a high expression table or production specific table but simultaneously avoid extended sequence repeats, EvoMAG can preferentially calculate the ideal pathway and find the best compromise, for example at minimal cost of suboptimal GC-content or distribution.

Heterologous gene expression regularly requires adaption of codon usage and even homologous genes can be optimized for production and regulation by using EvoMAG where needed.

Sequence Optimization

ATG offers various levels of EvoMAG sequence optimizaton, at varying degrees of parameters, genetic elements and solutions

Standard mode optimization: covering coding region/ORF of a gene with translational elongation formally optimized by adapting customer sequence using custom tables for codon frequencies.

Expert mode optimization: This will address any relevant specific customer specific details by first analyzing which additional parameters may become critical, making suggestions and then working out optimum solution in collaboration with client. This can involve up to five successive levels of optimization:

Level I: Gene Check
Level II: Gene Check + Translation Elongation with modified tables
Level III: Gene Check + Translation Elongation with modified tables + Translation Initiation
Level IV: Gene Check + Translation Elongation with modified tables + Translation Initiation + Translation Termination
Level V: like Level IV but for gene clusters

Resources

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