Zymergen Inc.

Sapphire Energy, Inc.

Shawn Szyjka

Shawn Manchester

Kenneth S Bruno

Aaron Kimball

Michael Flashman

Erik Jedediah Dean

Barbara Frewen

Katherine Gora

Thomas Treynor

Erin Shellman

Zach Serber

Michael Mendez

Zachariah Serber

Kedar Patel

Aaron Miller

Sara Da Luz Areosa Cleto

Philip Weyman

Stephen Blaskowski

Elizabeth Lauren Meier

Brian Chaikind

Patrick J Westfall

Bryan O'Neill

Solomon Henry Stonebloom

Sharon Nademanee

Colin Scott Maxwell

Kyle Rothschild-Mancinelli

Melissa Netwal

Cameron Coates

Kyle Botsch

Hendrik M Van Rossum

Paul Perkovich

Youngnyun Kim

Michael Blaisse

Kasia Gora

Erik Jedehiah Dean

Michael Flaschman

Matthew Davis

Prabha Ramakrishnan

Christy Wisnewski

Robert Haushalter

Stacy-Anne Morgan

Amy Curran

Wendy Levine

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 invention relates to methods for editing the genome of a microbial host cell in successive rounds of transformation. The method allows the introduction of genetic edits into the genome of a microbial host cell in an iterative fashion that does not require the use of functional counterselection following at least one round of transformation. It can be used to rapidly stack genetic edits in the genome of a microbial host cell. Kits for performing the methods are also disclosed.

Iterative genome editing in microbes

Automated system for HTP genomic engineering

Methods, compositions, and kits for high throughput DNA assembly reactions in vitro. Modular CRISPR DNA constructs comprising modular insert DNA parts flanked by cloning tag segments comprising pre-validated CRISPR protospacer/protospacer adjacent motif sequence combinations. High throughput methods of CRISPRi and CRISPRa.

Applications of CRISPRi in high throughput metabolic engineering

The present invention relates to methods for editing the genome of a microbial host cell in one or more rounds of transformation. The method allows the introduction of genetic edits into the genome of a microbial host cell in a pooled and/or iterative fashion that does not require the use of functional counterselection following at least one round of transformation. It can be used to rapidly stack genetic edits in the genome of a microbial host cell. Compositions and kits for performing the methods are also disclosed.

Pooled genome editing in microbes

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

Martinez, CA, United States of America

Shawn Szyjka