Multiplex Evolution
Multiplex Evolution - Related Videos
02:55
The Evidence for Evolution
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2026
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.The collection of fossils within sedimentary rocks give a record of common ancestry and often depicts the history of evolution.
01:54
Convergent Evolution
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2026
Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.The structures that arise from convergent evolution are called analogous structures. They are similar in function even if they are dissimilar in structure. Further, structures can be analogous while also...
05:08
A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution
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2024
Phage- and Robotics-assisted Near-continuous Evolution (PRANCE) is a technique for rapid, robust protein evolution. Robotics allows the parallelization of experiments, real-time monitoring, and feedback control.
12:02
Molecular Evolution of the Tre Recombinase
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Cited by 4 •
2008
Here we report the generation of Tre recombinase through directed, molecular evolution. Tre recombinase recognizes a pre-defined target sequence within the LTR sequences of the HIV-1 provirus, resulting in the excision and eradication of the provirus from infected human cells. While still in its infancy, directed molecular evolution will allow the creation of custom enzymes that will serve as tools of molecular surgery and molecular medicine.
04:21
Multiplex Cyclic Fluorescent Immunohistochemistry
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Cited by 1 •
2024
Multiplex cyclic immunohistochemistry allows in situ detection of multiple markers simultaneously using repeated antigen-antibody incubation, image scanning, and image alignment and integration. Here, we present the operating protocol for identifying immune cell substrates with this technology in lung cancer and paired brain metastasis samples.
FAQs
Its main mechanistic advantage is that it exposes interactions among mutations, regulatory elements, and pathway components. A change that appears unhelpful in isolation may contribute to a stronger overall design when combined with other changes. Evaluating coordinated variants therefore helps identify biological solutions that would remain hidden when each target is optimized separately.
Multiplex Evolution treats system performance as the result of connected design choices rather than independent parts. Varying several genes or regulatory elements together allows researchers to observe how those changes influence one another across an enzyme, pathway, or host. This systems-level view is especially relevant when modifying one component alone does not produce the desired trait.
Selection or screening identifies the variants that perform best after multiple design dimensions have been changed. The diversification step creates coordinated alternatives, while evaluation distinguishes combinations associated with improved system behavior. Linking these stages converts a broad variant library into useful candidates for further optimization of enzymes, metabolic pathways, or engineered microbial strains.
A general workflow begins by choosing several genes, regulatory elements, or pathway components connected to the target trait. Researchers then generate coordinated variants across those targets and evaluate the resulting library through selection or screening. Promising combinations can guide subsequent design cycles, enabling performance to improve through integrated changes rather than isolated substitutions.
This strategy is most useful when a desired performance trait depends on several biological components or when single-target optimization has limited effect. It can support efforts to improve enzyme function, balance a metabolic pathway, or strengthen an engineered microbial production host. The approach is also valuable when interactions among changes may determine the final phenotype.
In bioengineering, the approach can support more efficient biocatalysts, improved metabolic pathways, and microbial strains with stronger production performance. Its value extends beyond identifying an individual beneficial mutation: coordinated variants may produce a system with the desired combination of characteristics. These outcomes can help researchers develop biological platforms suited to specific engineering goals.