21 May 2024
Eben van Tonder

Introduction

In a fascinating lecture presented by the Royal Institution of Great Britain, Philip Ball takes us on a fascinating journey through the complexities of the human genome, comparing it to a musical score. The segment, titled “Turning the Genome into Music.” Ball’s shows us how new insights challenge our traditional understanding of genes and their roles, exposing the dynamic and intricate nature of genetic information.

I am doing an article about the development of our understanding of proteins and amino acids. The talk by Philip made a huge impression on me and I wondered if there is anything we can learn from nature about how to manage complexity in our projects and organisations. But before we get there, let me give you my transcrip of the talk and some further explanatory comments. Finally I draw it together in an application to how we manage information amidst complexity.

The Central Dogma of Molecular Biology: Background and Influence

To appreciate the new thinking and discoveries, we have to see where we come from. The key concept is the Central Dogma of Molecular Biology and it is simple a linear system. The term was coined by Francis Crick in 1958, representing the understanding of genetic information flow at the time. Crick, who alongside James Watson discovered the double-helix structure of DNA, proposed this concept to describe the directional flow of genetic information: from DNA to RNA to protein. At the time it was a revolutionary thought as it was thought that proteins with their different combinations of amino acids fulfilled the role we now ascribe to DNA by encoding life in our bodies.

Crick first presented his ideas on the central dogma during a lecture in 1957, and they were formally published in a paper in 1958 in the “Symposium of the Society for Experimental Biology.” He further refined and expanded upon these ideas in a 1970 paper in the journal “Nature.” The central dogma posits three core processes: DNA replication, where genetic information is copied; transcription, where DNA is transcribed into messenger RNA (mRNA); and translation, where mRNA is translated into proteins by ribosomes, using transfer RNA (tRNA) and ribosomal RNA (rRNA).

This model profoundly influenced various fields. We now know that it is an incomplete model and could even say it is inadequate, but still, it was extremely useful. In molecular biology, it provided a foundational understanding of genetic expression and regulation. It paved the way for genetic engineering techniques, such as recombinant DNA technology, which have extensive applications in medicine, agriculture, and biotechnology. Moreover, it was instrumental in the Human Genome Project, aimed at mapping all human genes, and has significantly informed medical research into genetic disorders and diseases.

Subsequent discoveries have revealed that the flow of genetic information is more complex than initially thought which is a major part of what we discuss here and eventually apply on the management of information in any complex system.

Who is Philip Ball?

I used a talk by Philip Ball as the basis of the discussion and the question comes up who is Philip Ball and what qualifies him to talk authoritatively about these matters? Philip is a renowned British science writer, known for his ability to explain complex scientific concepts to a broad audience. He holds a degree in chemistry from the University of Oxford and a PhD in physics from the University of Bristol. Ball has worked as an editor for the prestigious scientific journal “Nature” and has authored numerous books and articles on a wide range of scientific topics, including chemistry, physics, and biology.

Why Would Philip Ball Be Discussing Advances in Understanding DNA and Proteins?

Philip Ball’s background in both chemistry and physics, combined with his extensive experience in science communication, positions him well to discuss the latest advances in molecular biology, particularly the intricacies of DNA and protein interactions. His work spans the devide between scientific research and public understanding, making complex topics accessible and engaging.

Transcription and Expansion

The lecture was hosted by the Royal Institution of Great Britain. The Royal Institution of Great Britain (RI) is one of the world’s oldest and most prestigious scientific institutions. Founded in 1799, the RI was established to promote scientific education and research. It was conceived by a group of influential figures, including the renowned scientist Sir Humphry Davy, who played a crucial role in its early development.

Let’s now delve into his lecture.

It was known by scientists that there were one of two genes who did not have corresponding proteins that was coded by it. This was strange because we thought that this was the key function of genes. Scientists now believe that the figure of genes which codes proteins is as low as “20,000 genes and by some estimates as little as 19,000 which code proteins. Did we have the wrong idea of what role genes were playing? In the 1990s, there were one or two genes that scientists could not find corresponding proteins for, and in the end, they had to conclude that there weren’t any. These genes simply make RNA, not the messenger RNA that gets translated by the ribosome into a protein. In this case, the RNA is the end in itself. It has some biochemical functions. It does the kind of thing that we thought proteins do. These RNA-encoding genes are called non-coding genes. Not because they don’t code anything, but because they don’t encode proteins, which is what we thought – we thought all genes encode proteins.” (Philip Ball)

The discovery of non-coding RNA (ncRNA) challenged the long-held belief that all genes must encode proteins. These non-coding genes produce RNA molecules that perform various biochemical functions within the cell, akin to the roles proteins were traditionally thought to play. This revelation significantly broadened our understanding of genetic functionality and regulation.

“These were not exceptions. Over the past two decades, the number of these non-coding genes kept creeping up. A few years ago, the number of non-coding genes exceeded the genes that code proteins. Current estimates suggest that this trend will continue. It seems that we will find out that non-coding genes vastly outnumber protein-coding genes.” (Philip Ball)

The increasing discovery of non-coding genes indicates that the genome’s complexity is far greater than previously understood. Non-coding RNAs are involved in various cellular processes, including gene regulation, maintenance of genome stability, and modulation of chromatin structure. These functions highlight the intricate layers of genetic regulation beyond mere protein-coding sequences.

“The picture is even more transformed. These are only the genes that code the relatively long RNA molecules that qualify as genes. It has been discovered that there are actually lots of other bits of the genome or our genome and also other large animals (called Metazoans) that encode lots of smaller RNA molecules. And there are all these different families with fancy names (housekeeping ncRNAs, regulatory ncRNAs, short ncRNAs, long ncRNAs). They do all kinds of protein-like tasks in the cell. The genome is not really what we thought it was.” (Philip Ball)

Beyond long non-coding RNAs (lncRNAs), researchers have identified numerous small non-coding RNAs (sncRNAs) that play critical roles in gene expression regulation, RNA processing, and other cellular functions. These include microRNAs (miRNAs), small interfering RNAs (siRNAs), and Piwi-interacting RNAs (piRNAs). These small RNAs add another layer of regulatory complexity, demonstrating that the genome operates through a vast network of RNA molecules in addition to proteins.

“Crick’s central dogma said that genes encode proteins, and by that, we mean that genes actually program proteins with particular shapes so that they can go and do a specific function. But this picture is now modified. It does not mean that each gene encodes a particular protein. Each of our genes can typically be used to program several different proteins. On average, each can make about six different proteins. Some genes can encode dozens or even hundreds of different proteins. We have many proteins, and no one knows how many, but many more than we have protein-coding genes.” (Philip Ball)

The central dogma of molecular biology, proposed by Francis Crick, described the flow of genetic information from DNA to RNA to protein. This concept has evolved with the discovery of alternative splicing, where a single gene can produce multiple protein variants by rearranging its exons during RNA processing. This mechanism significantly expands the proteome’s diversity, allowing organisms to generate a wide array of proteins from a limited number of genes.

“As we discovered in the 1970s, the messenger RNA that is transcribed from a gene is typically chopped up and edited before it is translated. So, there is another piece of molecular machinery. This thing called the spliceosome, made up of several different proteins, gets hold of the messenger RNA, chops it into different fractions, throws away some pieces called introns, and stitches together the remaining fractions called exons back in various orders. What decides how this splicing and editing occurs is typically information coming from a higher level of the system, for example, from the overall state of the cell in which it’s happening. So, a gene in one tissue may produce one type of protein, and in a different tissue may produce a different protein.” (Philip Ball)

The spliceosome’s role in RNA splicing underscores the importance of post-transcriptional modifications in gene expression. The regulation of alternative splicing is influenced by various factors, including the cell’s physiological state and external signals, allowing cells to adapt their protein production to specific needs and conditions. This complexity illustrates the dynamic nature of genetic information flow and its responsiveness to cellular contexts.

“The information flow here isn’t as the central dogma at least implied; it isn’t all from the bottom up, from DNA to RNA to proteins. Some crucial information for making the protein is coming from the outside, and this is just one of the ways in which, to build us and to keep us alive all these years, information doesn’t just flow upwards from the genes to higher levels of organization but flows up and down and in between and in all sorts of directions among them. It’s an open information system, not a closed one.” (Philip Ball)

The concept of an open information system in genetics highlights the bidirectional and multidirectional nature of genetic regulation. Genetic information is influenced by external signals, environmental factors, and cellular states, which feed back into the genome to modulate gene expression. This interplay between genes and their environment underscores the complexity of biological systems and the integration of multiple layers of regulatory mechanisms.

“And here’s another change to the picture. In the analogy of the genome to a musical score, we might say that the score is what prevents the orchestra from just playing a whole lot of random notes. It tells each musician which note to play and when. It is the equivalent way a protein’s gene’s encoded shape tells it what to do in the cell – which molecules to grab hold of and which to ignore. There was an earlier reference to this lock-and-key aspect, but we now know that for many of our proteins, including some with some of the most important jobs in the cell, the DNA score isn’t like this at all. It’s much more open to interpretation. Some genes encode proteins without assigning them a structure. It leaves them loose and floppy, or as biochemists say, they are intrinsically disordered. This is not a failure of the genome to give genes a proper shape. It is a deliberate feature that evolution had ‘chosen’ because there is much less of this intrinsic disorder among proteins of simpler organisms like bacteria. So, evolution was clearly fine with giving proteins a very specific structure, but it seems that it has found it useful or perhaps even necessary to give proteins disorder in order to make more complex multicellular, multi-tissue organisms like us.” (Philip Ball)

The analogy of the genome to a musical score beautifully illustrates the balance between order and flexibility in genetic regulation. Intrinsically disordered proteins (IDPs) are a prime example of this flexibility. Unlike structured proteins, IDPs lack a fixed three-dimensional structure, allowing them to interact with multiple targets and participate in various cellular processes. This structural flexibility is particularly advantageous in complex organisms, enabling versatile responses to dynamic cellular environments and facilitating the regulation of intricate biological networks. Evolution has thus favoured the presence of IDPs in multicellular organisms to support their complexity and adaptability.

Applying Biological Principles to Management

To draw management and processing design principles from Philip Ball’s talk on the emerging view of RNA, intrinsically disordered proteins (IDPs), and feedback loops, we can consider these biological processes as models for managing complexity in organizational contexts. Here’s how these concepts can be applied to structure work and the flow of information and tasks in an organization:

Adaptability of RNA – Flexibility in Roles and Responsibilities

RNA’s role in cellular mechanisms, particularly its ability to assume multiple structures and functions (e.g., mRNA, tRNA, rRNA), illustrates the value of adaptability in organizational roles. In a management context, this can translate to:

• Cross-functional Teams: Encourage staff to develop skills in multiple areas to increase flexibility and adaptability.
• Dynamic Role Assignment: Depending on the project demands, assign roles that can change, reflecting the shifting structure and function needs, much like RNA does.

IDPs and Fluidity – Embracing Uncertainty in Processes

Intrinsically disordered proteins (IDPs) do not have a fixed structure, allowing them to interact with multiple different molecules and adapt to various cellular needs. This property can be mirrored in organizational design by:

• Fluid Process Design: Create processes that are open to adaptation and change, allowing for quick pivoting and reconfiguration in response to external or internal shifts.
• Innovation Acceptance: Foster a culture that not only tolerates but encourages experimentation and accepts the inherent uncertainty and unpredictability as a source of innovation.

Feedback Loops – Responsive Decision-making

Biological feedback loops allow systems to adjust dynamically based on outputs. Similarly, in an organizational setting, effective feedback mechanisms can enhance decision-making:

• Real-time Feedback Systems: Implement technology and practices that provide immediate feedback on performance and results, allowing for quick corrections and adaptations.
• Decentralized Decision-making: Empower lower levels of the organization to make decisions based on direct feedback from operations, enhancing responsiveness and reducing bottlenecks.

Top-Down Influences – Strategic Direction and Alignment

While much of the emergent view in biology supports a bottom-up approach, the importance of influences from higher levels (e.g., regulatory proteins in genetics) can’t be ignored. In management, this translates to:

• Clear Strategic Vision: Ensure that the strategic direction from the top is clear but allows for autonomy in execution at lower levels.
• Alignment and Autonomy: Balance the need for overarching goals and policies that guide the organization with the freedom for teams to execute based on local information and conditions.

Complexity Management – Handling Interdependencies

The interplay between RNA, IDPs, and other cellular components underlines the complexity and interconnectedness of biological systems. For organizations, this suggests:

• Systems Thinking: Approach management and operational problems with an awareness of the interdependencies and the potential for complex system-wide effects from localized changes.
• Leverage Technology: Utilize advanced data analytics, AI, and other technological tools to manage and make sense of complex data and relationships within the organization.

Conclusion

By integrating these principles, inspired by the cutting-edge understanding of molecular biology, organizations can better manage complexity and enhance their adaptability and efficiency in rapidly changing environments. This approach emphasizes not just the structure, but also the flow of information and the dynamic capabilities of an organization.

References

• Ball, P. (2023). “Turning the Genome into Music.” Lecture presented at the Royal Institution of Great Britain. Royal Institution YouTube Channel
• Crick, F. (1958). “On Protein Synthesis.” Symposium of the Society for Experimental Biology, 12, 138-163.
• Crick, F. (1970). “Central Dogma of Molecular Biology.” Nature, 227(5258), 561-563. doi:10.1038/227561a0
• Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2002). Molecular Biology of the Cell. 4th edition. New York: Garland Science.
• Mattick, J. S. (2004). “RNA regulation: A new genetics?” Nature Reviews Genetics, 5(4), 316-323. doi:10.1038/nrg1321
• Esteller, M. (2011). “Non-coding RNAs in human disease.” Nature Reviews Genetics, 12(12), 861-874. doi:10.1038/nrg3074
• Uversky, V. N. (2013). “Intrinsically Disordered Proteins and Their ‘Mysterious’ (Meta)Physics.” Frontiers in Physics, 1, 37. doi:10.3389/fphy.2013.00037
• Lee, Y. S., & Dutta, A. (2009). “MicroRNAs in cancer.” Annual Review of Pathology: Mechanisms of Disease, 4, 199-227. doi:10.1146/annurev.pathol.4.110807.092222
• Singh, P., & Singh, N. (2016). “RNA Splicing: Molecular Mechanisms, Involvement in Disease and Potential Treatment by RNA Interference.” Current Pharmaceutical Biotechnology, 17(4), 332-342. doi:10.2174/1389201017666160304113833
• Kornberg, R. D. (2007). “The Central Dogma: DNA makes RNA makes protein.” Nature, 447(7146), 140-141. doi:10.1038/447140a
• The Human Genome Project. (2023). “An Overview of the Human Genome Project.” Human Genome Project Information Archive