Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Evolution of New Traits in Microbes

Evolution of New Traits in Microbes

Microorganisms evolve rapidly due to their large population sizes and short generation times, often exhibiting measurable changes within days under laboratory conditions. Natural selection acts on standing genetic variation, enabling the retention and amplification of beneficial traits that confer fitness advantages in changing environments.Adaptive Pigment Regulation in RhodobacterIn Rhodobacter, a genus of purple non-sulfur bacteria, light-harvesting pigments such as bacteriochlorophyll and...

In-vitro Mutagenesis

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

In vitro Mutagenesis

In vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

Evolutionary Processes in Microbes

Evolutionary Processes in Microbes

Microbial evolution occurs rapidly due to short generation times and a variety of genetic processes, including horizontal gene transfer, mutation, recombination, and genetic drift. These mechanisms collectively enable microbes to adapt swiftly to changing environments.Horizontal gene transfer (HGT) allows genes to move between different species and occurs through three main mechanisms: conjugation, transformation, and transduction. Conjugation involves direct cell-to-cell contact for DNA...

Synthetic Biology

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

Bioreactor Controls-III

Bioreactor Controls-III

Strain improvement is a foundational strategy in industrial microbiology aimed at maximizing microbial productivity, particularly because natural isolates typically yield commercially valuable products in very low concentrations. Although optimizing the culture medium and environmental conditions can improve yields, these adjustments are inherently limited by the organism’s genetic potential. As a result, the focus shifts toward genetic modifications to enhance biosynthetic capacity. The...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Laparoscopic versus open pancreaticoduodenectomy for non-pancreatic periampullary adenocarcinomas: study protocol for a multicentre randomised controlled trial in China.

BMJ open·2026

Same author

Optimizing nitrogen management enhances photosynthesis and alfalfa productivity in jujube-alfalfa intercropping.

Scientific reports·2026

Same author

Diagnostic Performance of Serum AKR1B10 in Early-Stage and AFP-Negative Hepatocellular Carcinoma: A Multicentre Study.

Liver international : official journal of the International Association for the Study of the Liver·2026

Same author

Evidence supporting the role of GIGYF2 in synapse development and autism.

Molecular psychiatry·2026

Same author

Fusion prediction model for post-ERCP pancreatitis under NSAIDs prophylaxis.

Surgical endoscopy·2026

Same author

Lithio-Gel via Lithium Bonding: Mitigating Anode Failure by Blocking Crosstalk in Rechargeable Li-SOCl<sub>2</sub> Batteries.

Journal of the American Chemical Society·2026

Search research articles

Related Experiment Video

Updated: May 20, 2026

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

Published on: January 12, 2024

Harnessing Nature's Algorithm: From Test Tubes to Autonomous In Vivo Evolution.

Wenna Shang¹, Zhengbing Lyu¹, Guodong Chen^2,3

¹College of Life Sciences and Medicine, Zhejiang Provincial Key Laboratory of Silkworm Bioreactor and Biomedicine, Zhejiang Sci-Tech University, Hangzhou, China.

Biotechnology Journal

|May 19, 2026

Summary

This summary is machine-generated.

Autonomous in vivo evolution systems accelerate biomolecule engineering by overcoming traditional screening limits. Integrating machine learning with continuous evolution promises faster development of complex therapeutics.

Keywords:

continuous evolution directed evolution machine learning

More Related Videos

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

Related Experiment Videos

Last Updated: May 20, 2026

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

Published on: January 12, 2024

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

Area of Science:

Biotechnology
Molecular Engineering
Synthetic Biology

Background:

Traditional directed evolution (DE) faces throughput limitations.
Epistatic fitness landscapes in biomolecule engineering are complex.
Autonomous, continuous in vivo evolution systems are emerging.

Purpose of the Study:

Review molecular architectures and engineering principles for continuous in vivo evolution.
Evaluate strategies for genetic diversification and their trade-offs.
Analyze the integration of machine learning and future bottlenecks.

Main Methods:

Examining orthogonal replication systems (e.g., OrthoRep, T7-ORACLE).
Assessing CRISPR-guided mutagenesis (e.g., EvolvR).
Analyzing phage-assisted continuous evolution (PACE) and machine learning integration.

Main Results:

Continuous evolution systems offer higher throughput than stepwise DE.
Balancing mutational load and host viability is critical.
Machine learning, particularly protein language models (PLMs), aids in navigating complex fitness landscapes.

Conclusions:

Continuous in vivo evolution, enhanced by ML, accelerates therapeutic engineering.
Overcoming hardware and algorithmic bottlenecks is key for closed-loop biofoundries.
This transition enables more efficient navigation of complex biological systems.