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 treating at least one biological cell includes at least one treatment support comprising a receiving surface enabling the adhesion of the at least one biological cell, at least one actuator capable of deforming said support in order to apply a stress to said at least one cell, and means of controlling said at least one actuator such that the actuator deforms the treatment support according to a given amplitude of deformation and for a given duration so as to generate at least one transitory pore in a membrane of the biological cell.

In an illustrative embodiment, automated multi-module cell editing instruments are provided to automate multiple edits into nucleic acid sequences inside one or more cells.

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.

Biocompatible, mechanically-dynamic thermoresponsive devices, methods for forming the devices, and exemplary applications for the devices are described. The devices include a series of wells therein and provide for temperature-controlled mechanostimulation of single cells or groups of cells that can be retained in the wells of a device. Mechanostimulation can be single instance of any duration, continuous, or regular or irregular cyclic mechanostimulation of single cells, cell clusters, cell spheroids, or organoids and may be utilized in any of a variety of biomedical applications including, without limitation, cellular engineering, cellular phenotyping, and drug discovery/screening.

Embodiments of microfluidic systems and methods of manufacturing are described herein, which utilize an automated microfluidic plumbing technology with addressable ports capable of minimally disruptive additive and subtractive (including probing) cell and/or fluid manipulation at any desired location(s) within living cultures. The addressable microfluidic ports may be integrated throughout cell cultures in microfluidic systems for microfluidic tissue scaffolds, in two- or three-dimensional spatial arrangements. The addressable microfluidic ports may be used for controlling and/or monitoring cell behavior over time at different user-selected locations within cell cultures. Also provided are methods for fabricating such microfluidic devices and microfluidic tissue scaffolds.

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.

Provided herein are methods, computer programs, and systems for automated microinjection, for example, automated Intracytoplasmic Sperm Injection (ICSI). Methods described herein include creating, by a processing unit, a first dataset of an oocyte and a holding device and a second dataset of an injection pipette; detecting the oocyte and the holding device in the first dataset and the injection pipette in the second dataset; selecting the image of the first dataset and of the second dataset where an equatorial plane of the oocyte/holding device and of the injection pipette has an improved focusing parameter; selecting images of the first and second datasets and labeling the pixels associated with the oocyte and to the injection pipette; detecting a tip of the injection pipette; detecting different morphological structures of the oocyte using artificial intelligence computer vision algorithms on the first dataset; creating an injection trajectory for the injection pipette to perform the ICSI using the detected morphological structures; detecting when the oocyte is rupturing and when the spermatozoa has been released from the injection pipette into the cytoplasm of oocyte.

Nanostraws and to methods of utilizing them in order to deliver biologically relevant molecules such as DNA, RNA, proteins etc., into non-adherent cells such as immune cells, embryos, plant cells, bacteria, yeast etc. The methods described herein are repeatedly capable of delivering biologically relevant cargo into non-adherent cells, with high cell viability, dosage control, unaffected proliferation or cellular development, and with high efficiency. Among other uses, these new delivery methods will allow to scale pre-clinical cell reprogramming techniques to clinical applications.

In an illustrative embodiment, automated multi-module cell editing instruments are provided to automate multiple edits into nucleic acid sequences inside one or more cells.