Robotic System for Organoid Assembly in a Multi-Well Microfluidic Chip

Abstract

While many cell culture systems are sensitive to the conditions in which cells are introduced into the system, we find that in situ differentiated tube-shaped microfluidic organoids have a particularly high sensitivity. Preliminary experiments using conventional seeding techniques revealed that biases in initial cell number and distribution dramatically impacted organoid shape and behavior downstream. Residual flows during seeding further complicated the process, dispersing cells to undesirable locations within the chip. To address this problem, a a robotic seeding system for controlling the process of inserting cells into microfluidic chips was developed. Environmental control of temperature, CO2, and humidity was implemented by modifying a commercial Arduino-controlled incubator. An eight-channel syringe pump controlled flow to eight cell dispensers, while a vertical leadscrew stage raised and lowered them, and a set of stackable flexure micromanipulators individually controlled the X and Y position of each cell dispenser. The flexure manipulators were 3D printed, driven by low-cost motors and electronics, and required little assembly and no alignment, resulting in a cheap and scalable method of controlling a dense array of micromanipulators. A dual objective microscope on a motorized gantry used an oblique lighting system to observe the seeding process, allowing for real-time interventions or passive observation of automated protocols. The robotic cell seeding system provided a platform for optimizing a sensitive process towards increasing the repeatability and physiological relevance of tube-shaped microfluidic organoids.

Organoids, Biocybersecurity, and Cyberbiosecurity—A Light Exploration

“…Numerous breakthroughs were necessary to make much of organoid development and the possibility of integrating them into hybrid systems possible. The core of this can be broken down into sourcing the cells that make up the organoid, sourcing components for and building the material of the matrix in which these organoids develop, and the equipment that allows for their maintenance, observation, and efficient data extraction [1][2][3][4][5][6][7][8][9][10][11][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][36][37][38][39][40][41][42][43]. Examples include advances in 3D culture techniques, directing of stem cell differentiation, development of bioengineering tools and assays, bioprinting, deployment of microfluidic devices, and artificial matrices to emulate tumor environments effectively in the development of tumoroids [1][2][3][4][5][6][7][8][9][1...…”

“…In the future, integrating organoid intelligence in biocomputing might lead to personalized healthcare security options, depending on patient consent and pairing. This is in part due to the customizability and personalization of organoids to patients and the fact that the researchers can tease meaningful data from the performance of organoids that are exposed to a bevy of tests and or otherwise interrogated by equipment with bio-interfaces [35][36][37][38][39][40][41][42][43]. Same-platform computations (in the biological domain) should theoretically support information transfers with minimized entropic loss.…”

“…Integrating organoids in synthetic biology opens possibilities for creating more complex, organ-like structures with specific and novel biological functions, paving the way for innovative medical treatments and a deeper understanding of human biology [62]. Sophisticated bioprinting has allowed for a shift from simple tissue cultures to sophisticated structures capable of replicating some organ functions and interactions [3][4][5]40,51].…”