From Genetic Code to Cellular Fiction
Exploring how information concepts shape our understanding of biological systems from genetic codes to cellular processes
Imagine a world where microscopic messages direct the construction of organisms, where chemical codes determine destiny, and where molecules communicate with the precision of a computer program.
Researchers created the first computational model of a human cell and simulated its behavior for 15 minutes, observing how genetic information processing guides cellular function 6 .
Their simulations revealed why certain genetic components move between cellular compartments in seemingly inefficient ways—because these movements are essential for proper RNA splicing 6 .
The concept of information has acquired a strikingly prominent role in contemporary biology, particularly within genetics, evolutionary theory, and developmental biology 1 .
Many biologists view genes as carrying information about their products, much like a blueprint or instruction manual 1 .
According to philosopher Arnon Levy, informational descriptions in biology might be best understood as productive fictions rather than literal truths 5 .
This view represents a middle ground between dismissing informational talk as mere metaphor and claiming it reveals something fundamental about nature.
Biologists appear to use different concepts of "function" in different contexts—a phenomenon philosophers call function pluralism .
| Function Type | Definition | Example | Key Question |
|---|---|---|---|
| Backward-Looking (Selected Effect) | A trait's function is what it was historically selected for | The heart's function is pumping blood because ancestors with better pumping hearts had more offspring | Why did this trait evolve? |
| Forward-Looking (Causal Role) | A trait's function is its current causal contribution to a larger system | The heart's function is pumping blood within the circulatory system | What does this trait do now? |
| Organizational | A trait's function is its contribution to maintaining the organization of the system | The heart maintains blood circulation, which maintains the conditions for its own existence | How does this trait help maintain the system? |
| Intentional Design | A trait's function is what a designer intended it to do | A synthetically engineered bacterial protein's function is to digest plastic waste | What was this designed to do? |
This function pluralism becomes particularly important in the emerging field of synthetic biology, where engineers apply engineering principles to design and construct biological systems .
In the 1960s, Har Gobind Khorana, Marshall Nirenberg, and Severo Ochoa conducted groundbreaking research that revealed how the language of DNA translates into the proteins that build and run our bodies 2 .
Khorana's approach was both ingenious and methodical. He developed a chemical method to synthesize artificial RNA molecules with defined sequences 2 .
Khorana designed RNA molecules with specific repeating sequences and synthesized them nucleotide by nucleotide.
Synthetic RNA was added to a cell-free protein synthesis system containing all necessary components for translation 2 .
The system was incubated, and resulting polypeptides were analyzed to determine amino acid sequences.
| Synthetic RNA Type | RNA Sequence | Codons Produced | Amino Acids Incorporated | Significance |
|---|---|---|---|---|
| Poly-U | UUUUUU... | UUU | Phenylalanine | Established that UUU codes for phenylalanine |
| Poly-A | AAAAAA... | AAA | Lysine | Established that AAA codes for lysine |
| Poly-UC | UCUCUC... | UCU, CUC | Serine, Leucine | Proved multiple codons in repeating pattern |
| Poly-GA | GAGAGA... | GAG, AGA | Glutamate, Arginine | Demonstrated codon directionality |
| Codon | Amino Acid | Discovering Scientist | Method Used |
|---|---|---|---|
| UUU | Phenylalanine | Nirenberg | Poly-U in cell-free system |
| AAA | Lysine | Nirenberg | Poly-A in cell-free system |
| UCU, CUC | Serine, Leucine | Khorana | Poly-UC copolymer |
| Many additional codons | Various | Khorana | Various custom synthetic RNAs |
The University of Illinois team created the first computational model of a human cell, focusing on how the spatial arrangement of cellular components affects genetic processes 6 .
This approach simulates the dynamic movement of molecules through the crowded cellular environment, revealing why certain apparently inefficient processes are actually essential for proper genetic regulation 6 .
Modern functional genomics has developed innovative approaches including the concept of "lossy compression" from computer science 8 .
Researchers have created applications that identify key genetic nodes whose loss-of-function phenotypes can predict the effects of disrupting other genes 8 .
These methods demonstrate how information theory concepts can directly guide biological experimentation, enabling researchers to extract maximum knowledge from limited data.
The study of biological information relies on specialized tools and reagents that enable researchers to interrogate living systems.
| Tool/Reagent | Function | Application in Information Studies |
|---|---|---|
| CRISPR Libraries | Collections of guide RNAs for targeted gene disruption | Systematic testing of gene function and information flow |
| Cell-Free Protein Synthesis Systems | In vitro translation systems without intact cells | Deciphering genetic code and regulatory elements |
| Synthetic RNA/DNA | Artificially designed nucleic acids with specific sequences | Probing coding rules and regulatory information |
| Fluorescent Reporters | Molecules that emit light when specific genes are active | Visualizing information flow and gene expression in real-time |
| Polymerase Chain Reaction (PCR) Machines | Amplify specific DNA sequences | Increasing signal for information detection |
| Microarrays | Slides with thousands of DNA probes for parallel gene expression measurement | Global profiling of transcriptional information |
| Next-Generation Sequencers | High-throughput DNA/RNA sequencing machines | Reading genetic information at massive scale |
| Spectrophotometers | Measure concentration of nucleic acids and proteins | Quantifying biomolecules that carry information |
These tools enable the manipulation and measurement of biological information at multiple levels, from individual nucleotides to genome-wide patterns.
As synthetic biology advances, the toolkit continues to expand with increasingly sophisticated reagents for writing, editing, and reading biological information 9 .
Our exploration of information in biology reveals a rich landscape where practical experimentation intersects with deep philosophical questions.
The informational perspective has proven enormously productive, guiding everything from the deciphering of the genetic code to the engineering of synthetic organisms.
Yet there's ongoing debate about whether information represents something fundamental in nature or serves as a useful fiction that helps scientists navigate biological complexity 5 .
The evidence suggests that biology employs a plurality of concepts—different notions of function and information are useful in different contexts . This pluralism reflects the incredible complexity of living systems.
As we move further into the era of synthetic biology and computational modeling, our understanding of biological information continues to evolve. The challenge ahead lies in developing frameworks that can accommodate both the engineered functions we create and the evolved functions we discover.