Automated pipetting systems and methods are disclosed for aspirating and dispensing fluids, particularly biological samples. In one aspect, a liquid dispenser includes a manifold and one or more pipette channels. The manifold includes a vacuum channel, a pressure channel, and a plurality of lanes. Each lane includes an electrical connector, a port to the pressure channel, and a port to the vacuum channel. The pipette channels can be modular. Each pipette channel includes a single dispense head and can be selectively and independently coupled to any one lane of the plurality of lanes. In some aspects, a valve in the pipette channel is in simultaneous fluid communication with a pressure port and a vacuum port of the manifold. The valve selectively diverts gas under pressure and gas under vacuum to the dispense head in response to control signals received through the electrical connector of the manifold.

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.

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.

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.

A device for immunolabeling comprising one or more solution containers with product drains through which fluid can flow; one or more valves capable controlling fluid flow through the product drains; and a sample container, wherein fluid flowing through the product drains flows into the sample container.

Methods and systems of performing an assay. A system for performing an assay includes an enclosure defining a temperature-controlled space. An imaging system, an actuator and a dispenser are disposed within the space. The actuator receives a well plate having wells. The actuator is to move the well plate relative to the imaging system to enable the imaging system to obtain image data of one of the wells. The dispenser includes a pump, an outlet and a reservoir holder to receive a reservoir containing a compound. The pump is to be fluidly coupled to the reservoir and an outlet. The pump is to pump the compound from the reservoir through the outlet into one of the wells. The system also includes a controller. The controller is to cause the dispenser to dispense the compound into the first one of the wells while the imaging system obtains the image data.

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.

The sample plate has a principal plane in which a plurality of wells is arranged. The sample plate has a plurality of through-holes each allowing a sampling needle to pass through in a region of the principal plane where the wells are not provided, and positions of the wells and positions of the through-holes are designed such that when two pieces of the sample plates are arranged up and down with a predetermined positional relationship in a state in which respective principal planes are arranged in parallel each other, the through-holes of the sample plate arranged on an upper side is arranged at positions directly above respective wells of the sample plate arranged on a lower side.

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.

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.