One post tagged with "crispr"

Living cells can now be reimagined as programmable “biocomputers,” executing genetic instructions encoded in RNA and DNA to perform therapeutic and diagnostic functions. Researchers at MIT and partner institutions have pioneered languages and compilers—akin to software development tools—that translate high-level circuit descriptions into specific nucleotide sequences. These biocodes enable cells to monitor biomarkers, process logical operations, and trigger precise responses such as insulin secretion or self-destruction of cancerous cells.

High-Level Design: From Logic Diagrams to DNA Sequences​

At the core of this approach lies a software framework called Cello, often dubbed the “programming language for living cells.” Users write programs using a syntax similar to hardware description languages (e.g., Verilog), specifying desired input–output behaviors and logic gates. Cello’s compiler then selects and assembles standardized genetic parts—promoters, ribosome binding sites, terminators—and optimally arranges them into a DNA sequence that implements the logic within Escherichia coli (or other chassis organisms). The result is a plasmid that, when introduced into cells, runs the designed circuit autonomously.

Building on the original Cello, Cello 2.0 expands capabilities with a richer parts library, support for new hosts, formalized design rules, and a graphical user interface. It embraces Verilog 2005 syntax, integrates with repositories like SynBioHub, and uses mathematical models to predict dynamic behavior—streamlining design-build-test cycles in synthetic biology.

Sensor Modules: Detecting Cellular Events with RNA Switches​

Programmable cells require sensors that convert molecular cues into digital-like signals. Researchers leverage toehold switches—engineered RNA structures that remain inactive until a specific trigger RNA opens the switch, allowing translation. MIT’s team introduced eToehold sensors built on internal ribosome entry sites (IRES) that can recognize aberrant mRNAs (e.g., mutated p53) and selectively turn on therapeutic genes only in target cells.

Moreover, CRISPR-based transcriptional regulators can function as programmable logic gates. By designing guide RNAs (gRNAs) that recruit dead Cas9 (dCas9) fused to activator or repressor domains, circuits can activate or repress genes in response to multiple inputs. Data-driven models predict how gRNAs targeting different genomic loci modulate expression, enabling fine control of metabolic and therapeutic pathways.

Logic Cores: RNA- and DNA-Based Gate Architectures​

• Once inputs are sensed, the circuit’s logic core processes them through modular gates:

• RNA logic circuits combine toehold switches and aptamers to implement Boolean functions (AND, OR, NOT) at the mRNA level, ensuring rapid responses.

• Recombinase-based systems employ site-specific recombinases (e.g., Cre, Flp) that invert or excise DNA segments upon detection of triggers, creating permanent memory and enabling multi-step decision trees.

• Protein-level logic integrates transcription factors and synthetic regulators to generate graded or switch-like responses at the transcriptional level.