Zymergen Inc.

Amyris Biotechnologies, Inc.

Amyris, Inc.

Erik Jedediah Dean

Kenneth S Bruno

Shawn Manchester

Shawn Szyjka

Aaron Kimball

Michael Flashman

Barbara Frewen

Katherine Gora

Erin Shellman

Thomas Treynor

Zach Serber

Zachariah Serber

Raymond Lowe

Kedar Patel

Patrick J Westfall

Philip Weyman

Aaron Miller

Jeffrey A Ubersax

Sunil S Chandran

Kyle Rothschild-Mancinelli

William Serber

Kunal Mehta

Youngnyun Kim

Darren M Platt

Michael W Bissell

Brian L Hawthorne

Christopher Dolan

Christy Wisnewski

Robert Haushalter

Stacy-Anne Morgan

Kenneth Toshiki Takeoka

Gregory Michael Werner

Adam Safir

Michael Blaisse

Kasia Gora

Matthew Davis

Prabha Ramakrishnan

The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

HTP genomic engineering platform

The present disclosure provides systems and methods for host cell improvement utilizing epistatic effects. The systems and methods described herein are host cell agnostic and therefore can be implemented across taxa. Furthermore, the disclosed systems and methods can be implemented to modulate or improve any host cell parameter of interest.

Systems and methods for host cell improvement utilizing epistatic effects

The present disclosure provides a microbe engineering platform that permits optimization of microbe fitness levels to optimize a microbe's suitability for industrial fermentation. The disclosed platform identifies an association between microbe properties and microbe fitness levels. The association between microbe properties and microbe fitness levels may be used to identify candidate microbes with desired fitness levels. The identified candidate microbes may be used to further optimize the industrial fermentation process.

Microbial engineering methods and systems for optimizing microbe fitness

Automated system for HTP genomic engineering

The present disclosure relates to methods of joining three or more double-stranded (ds) or single-stranded (ss) DNA molecules of interest in vitro or in vivo. The method allows the joining of a large number of DNA fragments, in a deterministic fashion. It can be used to rapidly generate nucleic acid libraries that can be subsequently used in a variety of applications that include, for example, genome editing and pathway assembly. Kits for performing the method are also disclosed.

Multiplexed deterministic assembly of DNA libraries

The present disclosure provides machine learning techniques for computationally predicting the phenotypic performance of combinations of genetic variations and for designing new improved host cells. The machine learning models and methods described herein are host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any host cell parameter of interest.

Microbial strain improvement by a HTP genomic engineering platform

Growing community of inventors

Lafayette, CA, United States of America

Erik Jedediah Dean