We take a deep dive into Microbiome analysis and how it improves racehorse health and performance with Chloe Hazell, Agxio’s Bioscientist & Research lead focusing on animal science and disease technologies.
The development of novel biotechnologies is transforming verticals from human health to food production, animal health to crop health. Constantly evolving through developments and breakthroughs, it is now one of the fastest-growing industries on the planet. In 2021, the global biotechnology industry was valued at over USD 1 trillion with an expected growth rate of 13.9% (CAGR) from 2022 to 2030.
One of the most exciting subsectors is animal health. This pioneering branch of biotechnology continues to advance animal health and welfare by introducing simple yet effective diagnostic techniques to make significant differences to the overall health of the animal.
Animal health and performance is affected by infinite factors including environment, nutrition, and husbandry. Many factors can be monitored, controlled, and manipulated by owners to improve the longevity, performance in the case of competition animals and livestock, and the overall health and welfare of animals. Enhancing the ability to have deeper insights using novel techniques is highly beneficial. Here we take a look at the microbiome aspect of animal health with a focus on racehorses.
The animal gut microbiome is a small but important window we can look into to help gain insightful information surrounding animal health. The gut microbiome is a population of microorganisms that lives within the gastrointestinal tract. The population is comprised of multiple kingdoms including bacteria, archea, and fungi. These microorganisms live mostly in harmony with one another, working together in nutrient breakdown to produce energy. While mostly beneficial bacteria are present, there are instances where disease-causing bacteria enter or proliferate beyond optimal levels.
The microbiome is a delicate, complex system which when disturbed can cause multiple undesirable consequences, such as dysbiosis and diarrhoea. These changes can occur due to disease, nutritional change, stress, and other causation factors. This results in a shift in the population present, disrupting the whole population mechanism and changing the pH of the environment.
Due to the delicate nature of the population, the slightest change to pH levels can cause significant issues which, if left, can lead to undesirable symptoms as described above. As such, it is vital we can monitor the gut microbiome population to help improve overall animal health but also maintain the optimum levels of each microorganism within the vast population.
In the instance of gastrointestinal disease in horses, stomach ulcers are one that majorly impact racehorses and cause unwanted side effects to both their heath and performance. Up to 90% of racehorses will have some level of ulceration in the stomach.
Gastric ulcers are a result of the mucosa wall being damaged due to an imbalance between the factors that are protective to the gastric mucosa. This painful disease can lead to many unwanted side effects including poor behavioural issues which impacts their training, ultimately reducing their performance come race day. To meet their energy requirements, racehorses are often fed diets high in starch, ingesting large meals that differ from their ancestral grazing diets so to meet calorific requirements. This can have a detrimental impact, though. High levels of carbohydrates and large meals mean the stomach capacity and small intestine are unable to cope with the overload of starch, resulting in slower gastric emptying and reaching digestive enzyme capacity.
These abrupt changes cause a shift in the microbiome population, causing rapid proliferation of streptococcus and lactobacilli in the colon and the death of fibre digesting bacteria. These changes of the microflora are accompanied with a rapid decrease in pH as endotoxins are released from dying fibre-digesting microbes, accompanied by rapid accumulation of lactobacillus’ main metabolic product, lactate. Rapid accumulation of lactate increases acidity in the gut environment, damaging the mucosa lining. These occurrences have now been linked to other metabolic diseases including colic and laminitis.
This is an excellent example of a vital point where accurate monitoring and surveillance can aid both trainers and owners to recognise when the microbiome population has shifted and when action must be taken to re-balance the gut to improve overall health and ultimately performance.
Currently, scientists can analyse the gastrointestinal microbiome using 16s rRNA sequencing. This gives an accurate and clear picture of what makes up the microbiome population of animal’s microbiome. However, interpreting and analysing this data requires significant amounts of time and effort to achieve accurate and reliable results. When facing a time-sensitive issue, we need the results straightaway, not in 8 weeks’ time.
Today we can harness automation of analysis and interpretation of this big data to achieve time-sensitive results, enabling us to make decision-led changes that can help to re-balance the microbiome population and help to alleviate the problem. The innovative use of machine learning and artificial intelligence has already been demonstrated across multiple verticals, notably human medicine for tumour detection and recognition.
The use of this revolutionary technology allows for quick analysis of big data that would usually take humans weeks of analysis. This technique can be applied to the concept of microbiome analysis, with big data being analysed within seconds, and a microbiome snapshot being presented instantly. Along with quick analytics, machine learning can aid in indicating any potential disease risks and suggesting corrective measures to re-balance the population and optimise animal health and consequently performance.
Agxio’s GALEN microbiome sequencing analytics engine is propelled by an automated, rules-based analysis of any combination of biomarkers against target ranges, enabling users to compose and modify their own rule logic and tailor their needs through a user-friendly and easily integrated platform. Combined with our automated machine learning platform Apollo, prediction models on microbiome populations can be created, allowing deep insight into the major contributing factors and to perform deep analytics. This helps not only to understand the current factors but also what impact and issues future changes could develop.
The application and progression of automated analytics of the microbiome along with disease predictive capabilities and corrective measures are speeding up current microbiome analytic techniques to provide greater insight into the animal’s gut microbiome in a timely manner, ultimately enhancing health, welfare and performance and reducing the risk of disease.