A collection of blog posts connected to my teaching on biomedical sciences and biochemistry degrees. All views and opinions expressed are my own, and not connected to my past, present or future employers.
Over my career in bioscience, I’ve witnessed some incredible changes that have significantly changed how we do biomedical sciences and how cells work.
Recently, I was asked what I considered the most significant change in the biosciences I had seen. At first, I thought of the rise of omics technologies like genomics and proteomics, but after I thought about it some more, a few key innovations and changes in our thinking truly stood out.
In this blog post, I’ll tell you what I consider to be the major changes I have seen.
The PCR Revolution
When I first encountered PCR in the late 1980s, it seemed almost like a magic trick. The idea that you could heat a solution containing enzymes to 90°C and still get a reaction was mind-blowing. As a biochemist, the method seemed to go against what I had been taught on my degree - enzymes start to denature and stop working once you get above 40 ΒΊC.
Now, PCR is everywhere in the biosciences. It's used for research, criminal forensics, and disease diagnosis, and the ability to amplify DNA has changed the way we do science.
Another major technological leap I saw was the rise of easy-to-use mass spectrometers. Early in my career, mass spectrometry was a complex and inaccessible tool. However, the introduction of user-friendly mass spectrometers transformed lab work. Suddenly, we could easily measure the monoisotopic mass of peptides and carry out peptide mass fingerprinting to identify proteins with ease.
This shift was a game-changer for proteomics and molecular biology, enabling us to quickly identify proteins. The combination of advanced instruments and accessible databases allowed for faster, more detailed analyses that were once considered out of reach for most labs.
Bioinformatics
Bioinformatics has completely altered the way we approach science. Finding a scientific paper or sequence information in the past required extensive library work and manual searches. Now, with databases full of genetic sequences, protein structures, and published studies, the challenge has shifted from finding data to filtering and making sense of it.
When I started, labs had no computers at all. Now, every researcher has a personal computer linked to a global network of scientific knowledge and a vast array of powerful bioinformatic tools.
Adipocytes - the cells that changed
Beyond technological advances, our understanding of biology has also changed.
When I first started studying bioscience, adipocytes (fat cells) were considered passive storage units for energy. Today, they are recognised as dynamic endocrine organs that secrete a range of adipokines, influencing metabolism and overall health.
As we age, we tend to gain more fat cells, effectively adding to the number of these endocrine cells in our bodies. This shift in understanding has implications for obesity research, diabetes treatment, and metabolic health,
Mitochondria - not just a powerhouse
Our understanding of the mitochondrion—the "powerhouse" of the cell—has also changed.
Mitochondria were initially viewed as static structures within cells; however, we now know that mitochondria are dynamic organelles. They fuse, move, and interact with other cellular components, forming complex networks that help regulate cellular energy and even apoptosis (programmed cell death).
Like the mitochondria, our view of how the Golgi works has also changed. Previously, the Golgi was viewed as a series of membranes that looked like a stack of dinner plates, with the proteins being processed moving through the stack. Now, the machinery processing the proteins comes to the proteins, a radical change in our thinking.
My top picks
So, which do I view as the top change? Well, you will have to watch the video to find out!
In the lab, we often need to grow bacterial, yeast, or mammalian cells, and we use specific methods to cultivate cells in a controlled environment.
Two common cell growth approaches are batch cultures and continuous cultures.
Batch Cultures: The Standard Approach
If you’ve ever worked in a biology lab, chances are you’re familiar with batch cultures.
In a batch culture, cells are grown in a fixed space, such as a flask, dish, or plate. The culture is usually incubated for a set period, often overnight or several days, depending on the type of cells you’re growing.
During this process, the cells go through different stages of growth, represented by the bacterial growth curve:
Lag phase: Cells adapt to their environment.
Log phase: Cells rapidly divide and grow.
Stationary phase: Growth slows as nutrients deplete.
Death phase: Cells die as waste products build up and nutrients run out.
One limitation of batch cultures is that you only grow cells for a finite period. When the nutrients in the medium are exhausted, the cells stop growing, and you must start a new batch if you need more cells or products. The number of cells you can produce is limited by space and the number of available nutrients.
Continuous Cultures: Nonstop Cell Growth
In contrast to continuous cultures, cells are grown in a specialised vessel known as a bioreactor, fermentor, or chemostat.
The continuous culture method continuously adds fresh media to the vessel while an equal amount of media is removed, creating a steady flow. This keeps the cells growing indefinitely, as they are always supplied with fresh nutrients.
One of the primary advantages of continuous cultures is that they maintain cells in the growth phase, meaning they can keep dividing and producing the desired products, whether that’s proteins, enzymes, or other biological compounds. However, setting up a continuous culture can be challenging. If the flow of new media is too slow, cells will run out of nutrients, leading to stagnation and death. But, if the flow is too fast, cells won’t have time to divide, and they could be washed out of the vessel.
The challenge with a continuous culture is finding the right balance in the media flow. The goal is to keep the cells in a state of constant division while also maintaining the product yield. Achieving this balance ensures that the total number of cells in the vessel remains steady over time, which is ideal for industrial applications where continuous production is required.
Choosing the Right Method
When deciding between batch and continuous cultures, the choice depends on the specific requirements of the experiment or production process. Batch cultures are easier to set up and control, making them ideal for smaller-scale studies or experiments with a defined endpoint. Continuous cultures are more complex but offer the advantage of sustained growth and production, which is essential for large-scale manufacturing or long-term studies.
The Basics of Protein Tagging and Purification: A Lab Guide
During my career, I have had to produce and purify proteins in the lab, which can be challenging.
In the lab, we tag and purify proteins to understand what a protein does in the cell: how it works, is transported and what it interacts with, and to produce proteins for medical treatments. However, working with proteins in the lab presents some challenges. One of the biggest obstacles is that the cells that produce the protein of interest, they also make their own proteins for survival. So, how do we isolate our desired protein from the rest? The answer lies in tagging and labelling techniques, allowing easier purification and tracking.
Why Tag or Label a Protein?
When we express a protein in cells, whether for research or therapeutic purposes, it’s mixed with the cell’s proteins. Hence, we need to purify our protein of interest from this mix, and that's where tagging comes into play. Adding a specific "tag" to the protein allows us to separate it from other cellular proteins using specialised methods.
Challenges in Protein Production
Another hurdle is that producing a large amount of protein burdens the cell, slowing its growth and division. To counteract this, we use a controlled system to regulate protein production. A common approach in bacterial systems is to use an expression vector that includes regulatory elements, such as the lac operon. Therefore, by adding a chemical called IPTG, we can switch on protein production at the right time once the cells have grown to the desired number.
Methods for Protein Tagging
When it comes to purification, two main protein tags are commonly used:
Histag: This tag consists of a sequence of six or more histidine residues that can be added to either the N- or C-terminal of the protein. After the cells producing the protein are lysed, the tagged proteins can be captured using nickel affinity chromatography. The histidine residues bind to the nickel, making purifying the protein from the cell mixture easy.
GST Tag (Glutathione S-Transferase): GST is a small protein that can be fused to the target protein. The fusion protein is purified using glutathione beads. One advantage of this method is that an enzyme can later cleave the GST tag, leaving behind the pure target protein.
Alternative Tagging for Visualisation
While GFP (Green Fluorescent Protein) doesn’t assist in purification, it is often used to label proteins for visualisation. GFP is a fluorescent protein derived from jellyfish, and it allows the movement of proteins to be tracked inside living cells under a microscope. Like Histag and GST, GFP tagging involves cloning the gene for GFP alongside the gene for the protein of interest, so both are expressed as a single molecule.
The mitochondria, often called the "powerhouses" of the cell, provide the energy that keeps our bodies functioning. Interestingly, mitochondria carry their own DNA, separate from the DNA in the cell’s nucleus. This mitochondrial DNA (mtDNA) is passed down almost entirely from our mothers, and it plays a key role in producing proteins essential for the mitochondria's function.
However, mutations in mitochondrial DNA can lead to serious and sometimes life-threatening conditions, referred to as mitochondrial diseases. These diseases primarily affect high-energy tissues such as the brain, muscles, and heart, resulting in a range of debilitating symptoms.
What is Mitochondrial Replacement Therapy?
Mitochondrial replacement therapy (MRT) has been developed to combat these inherited mitochondrial conditions. This procedure aims to replace faulty mitochondria and prevent transmitting mitochondrial diseases from mother to child.
Here’s how it works:
An egg is taken from a healthy donor, and its nucleus is removed, leaving behind healthy mitochondria.
Then, the nucleus from the mother’s egg (who has mitochondrial disease) is transferred into the donor egg, essentially creating a new egg with the mother’s genetic material but the donor’s healthy mitochondria.
This egg is fertilised with the father’s sperm and implanted into the mother’s womb.
The result is a baby who inherits the vast majority of their DNA from their biological parents but receives mitochondria from a third-party donor. This process prevents the faulty mitochondria from being passed on, giving the baby a chance at a healthy life without mitochondrial disease.
Ethical Considerations of MRT
While mitochondrial replacement therapy has successfully prevented mitochondrial diseases, it comes with significant ethical considerations. Since mitochondria contain their own DNA, this procedure changes the genetic makeup of the individual born through MRT and their future offspring. This raises important questions about the long-term impact on the human gene pool and whether we should alter human genetics this way.
Despite these concerns, mitochondrial replacement therapy has already been performed in some countries, offering families the chance to have healthy children free from mitochondrial disease.
The questions raised in the comment can be broken down into four main areas of concern:
1. Understanding Unintended Consequences in Genetic Engineering
One of the central questions was about the potential unintended consequences of genetic engineering. While science has made remarkable progress, particularly with tools like CRISPR, it's essential to acknowledge that we still need to fully understand all biological systems. This incomplete picture means that, despite our best efforts, we can’t always predict every outcome of genetic modification.
For example, altering a gene in an organism may have unexpected downstream effects. In one case, when scientists genetically engineered babies to be resistant to HIV by removing the CCR5 receptor, they found off-target genetic changes that could have unintended consequences. I discuss these issues in my video - CRISPR Case Studies: Ethical Dilemmas and Revolutionary Applications.
Similarly, work in which I was involved on genetically modified potatoes showed that removing a harmful compound caused the plant to produce a different compound with potentially more harmful effects. You can get the full story in my video - Unexpected Challenges in Genetic Engineering: A Case Study on GM Crops.
The lesson? Genetic engineering requires caution. Scientists must always consider not only the intended outcomes but also the potential for unintended consequences.
2. The Incomplete Nature of Scientific Models
In the comment on the pooping pig video, I was asked whether I ever consider the incomplete nature of our understanding—whether scientific models are accurate or could fail in the long term. The simple answer is yes; I am well aware of this.
For example, at the start of my PhD studies, our understanding of insulin signalling was very basic. However, over the three years it took me to complete my PhD, scientists around the world significantly added to our knowledge and understanding. The model went from a simple black box to a complicated network involving many proteins. However, even this model is imperfect, and new discoveries are constantly reshaping our understanding.
This is true for all areas of biology, including genetic engineering. The more we experiment, the more we refine our models. However, the fact that our models are incomplete doesn’t mean we should stop pursuing genetic modification—it simply means we must proceed with caution and a sense of responsibility.
3. Ethical Concerns: Should We Be Playing God?
Another critical question raised was whether scientists are "playing God" by tinkering with nature. The concern here is that humanity might be overstepping its boundaries by altering the genetic makeup of living organisms.
Humans have indeed been manipulating nature for millennia, from selecting plants and animals for desirable traits to breeding dogs with specific characteristics. However, modern genetic engineering tools, such as CRISPR, allow us to make more precise and rapid changes, bypassing the slow process of natural selection and breeding.
While genetic engineering has the potential to solve significant problems—such as developing disease-resistant crops or addressing hereditary health issues—ethical considerations must remain at the forefront. Just because we can modify genes doesn't always mean we should.
4. Safeguards and the Role of Scientific Scrutiny
A significant factor that should be considered is the safeguards scientists put in place to prevent unintended consequences from spiralling out of control. For instance, if we genetically modify an organism, we can sequence its entire genome to ensure no other changes were made. This type of oversight is crucial when dealing with changes that could have long-term effects on ecosystems or human health.
The issue of gene drives—where genetic changes are engineered to spread through a population—is of particular concern as once released, there’s no way to reverse such changes. This makes it all the more important to thoroughly study and assess the implications before moving forward.
A Balanced Approach to Genetic Engineering
Genetic engineering holds immense promise but also carries significant risks. It is the duty of scientists to consider both the benefits and the possible dangers. By continuing to question the work, refine the models, and engaging with ethical concerns, science can harness the potential of genetic engineering in a way that’s safe and beneficial for society.
At the heart of this debate lies a critical question: how do we balance innovation with responsibility? And we should always consider the question — just because we can, should we?
In 2004, I was involved in a €3 million research project that brought together labs from Europe and China. The research team included sociologists, psychologists, biochemists, botanists, and chemists, and we were looking at food safety in genetically modified (GM) crops and people's attitudes to 'functional foods'. ('Functional foods' are foods that have been produced using genetic modifications or have added vitamins and minerals.)
The project focused on two staple foods—rice and potatoes—and our aim was to reduce harmful compounds in these crops that could pose risks to human health. Specifically, we were trying to develop a strain of rice with low levels of phytic acid and a variety of potatoes with reduced glycoalkaloid content.
Phytic acid, though naturally occurring in many plants, can bind essential nutrients like zinc, calcium, and iron, making them unavailable to the body. This is a particular problem in regions where diets heavily rely on rice, leading to widespread iron deficiency and anaemia, affecting one in four people globally. Rice produces phytic acid to store phosphate in the seed to help it grow.
Some of the different glycoalkaloids found in potatoes have been linked to health risks such as cancer. While potatoes are generally safe to eat, reducing the levels of certain glycoalkaloids could further enhance their safety. The potato produces glycoalkaloids to prevent it from rotting.
Our collaborators in China irradiated rice to introduce mutations, grew the plants and screened them for low phytic acid levels. Meanwhile, our colleagues in Aberdeen developed a potato with a gene knocked out that was responsible for producing a specific glycoalkaloid.
As with many scientific endeavours, our project encountered unexpected results.
In the case of low phytic acid rice, the mutation that blocked phytic acid production also disrupted a key component of the glycolytic pathway. This meant that the rice could only complete one turn of the TCA cycle per glucose molecule, severely stunting its growth. The rice, though low in phytic acid, grew poorly.
The potato project presented its own surprises. While the gene responsible for producing one of the glycoalkaloids was successfully knocked out, the potato plant compensated by activating another gene that produced a different glycoalkaloid. The total glycoalkaloid content remained unchanged.
For me, this project was a powerful reminder that science, particularly genetic engineering, is often unpredictable. Despite our best efforts and the involvement of many bright minds in the field, the natural complexity of these plants outsmarted us. The results we achieved were not what we had hoped for, but they were incredibly valuable in their own right. They highlighted the intricate balance of biological systems and the challenges of modifying them without unintended consequences.
The problem of phosphate pollution in the runoff from farms, particularly in pig farming, is a significant environmental concern. Animals' diets are often rich in grains, which contain phytic acid, a compound that pigs cannot digest due to the absence of a specific enzyme. The undigested phosphate-rich phytic acid is then excreted as waste, contributing to environmental issues like algal blooms and water contamination.
Phytic acid, found abundantly in grains, is a form of phosphorus that pigs—and many other animals—cannot utilise because they lack the phytase enzyme to break it down. Without this enzyme, the phosphorus passes through the pigs' digestive system and is excreted, leading to the concentration of phosphate in the environment.
To combat this issue, pigs have been engineered to contain the E. coli appA gene, which enables them to produce phytase, the enzyme needed to digest phytic acid. This modification allows the pigs to break down the phytic acid in their diet, effectively reducing the amount of phosphate in their waste.
What makes this solution particularly innovative is the way the gene is expressed. The E. coli appA gene is under a promoter from a mouse, which regulates the expression of proteins in the mouse salivary gland. This means that the pig only produces the phytase enzyme in its saliva. This targeted expression ensures that the enzyme is active exactly where it needs to be—in the pig's mouth. As the pig chews and swallows, the phytase is mixed with the grain, breaking down the phytic acid before it can pass through the digestive system.
This genetic modification significantly lowers the levels of phosphate pollution associated with pig farming by reducing the amount of undigested phytic acid excreted by pigs.