Directed Build Graphs for Genomic Workflow Automation
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Solution Overview
Problem
High-throughput microbial genomic engineering faces challenges in efficiently processing and managing large-scale genetic modifications due to limitations in current computer systems and automation platforms, leading to slow processing times and equipment inefficiencies in quality control testing.
Innovation Solution
A software system that models biological workflows using directed build graphs, allowing for the creation of modular and composable workflows that connect multiple software and hardware platforms, enabling efficient execution and quality control across different automated systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large-scale genomic sequences (50-100 GB) are stored and processed in computer memory, then complete genome assembly and analysis can be performed, but current commercial computer systems cannot load and operate efficiently on such large datasets, causing processing failures or unacceptable delays
Solution Approach 1:
The patent segments the large-scale genomic data processing into distributed computational tasks across multiple computing nodes. The genome assembly process is divided into independent units that can be processed in parallel, allowing the system to handle 50-100 GB datasets without overloading a single computer system. This segmentation enables efficient memory utilization while maintaining high processing throughput.
Solution Approach 2:
The patent creates a universal genome assembler that can process multiple types of sequencing data formats and assembly algorithms through a single platform. This multi-functional system can load and operate on various genome sizes and types without requiring separate specialized software for each case, improving overall system efficiency when handling large genomic datasets.
2Extent of automation
If multiple software and hardware platforms are used to execute biological workflows, then automation capability and throughput are improved, but device compatibility and integration complexity become problematic
Solution Approach 1:
The patent introduces a standardized interface layer that acts as an intermediary between diverse software and hardware platforms and the genome assembly process. This mediator translates various platform-specific protocols and data formats into a universal format that the genome assembler can process, enabling seamless integration of multiple automation platforms without compromising compatibility.
Solution Approach 2:
The patent develops a universal control system that can execute biological workflows across different software and hardware platforms through a single unified interface. This multi-functional platform supports multiple automation tools and devices simultaneously, allowing the system to leverage diverse hardware capabilities while maintaining consistent workflow execution standards.
3Manufacturing precision
If quality control testing is performed on each individual genome sequence, then manufacturing precision is improved, but processing time and resource consumption increase significantly
Solution Approach 1:
The patent merges quality control checks into the genome assembly process itself, performing validation operations concurrently with assembly rather than as separate sequential steps. This integrated approach combines multiple quality control functions into a unified process, maintaining high manufacturing precision while reducing the total time required for genome sequencing and validation.
Solution Approach 2:
The patent implements continuous quality control monitoring throughout the genome assembly process, rather than performing discrete batch testing. This continuous validation approach maintains constant oversight of genome quality while keeping the assembly workflow uninterrupted, thereby preserving manufacturing precision without significant time penalties.
Data Source
AI summary
High-throughput production of modified microbes is achieved through optimization of directed build graph data structures representing biological workflows. Portions of otherwise unrelated workflows may be combined where they share common biological reaction steps, and processed by a genetic manufacturing facility to take advantage of operational efficiencies. Workflows may be mapped to physical laboratory equipment in a manner that optimizes material transfers. Different automated platforms running different machines in different languages are coordinated in a device-agnostic and language-agnostic manner.