Our bodies undergo countless chemical reactions every second. These reactions are responsible for everything, from generating energy we use, conversion of the food we eat towards building the body, to the mechanisms that fight off disease. At the core of these reactions are small biological molecules called metabolites, that form the end products to carry these essential processes. They make a highly intricate, interconnected network to sustain life.

The study of these molecules, known as metabolomics, provides a relatively accurate picture of what is going on in our bodies and is increasingly being used to provide insights into diseases. Since they are influenced by many factors - such as disease, diet, and lifestyle - changes in their levels can signal shifts in our health. They are quite dynamic and sensitive to the changes taking place in and around us and thus make excellent candidates for disease diagnosis and their prediction.

The metabolome is big. Really diverse. You just won’t believe how vastly, hugely, mind- bogglingly complex it is. Metabolites form an incredibly diverse set of biomolecules and knowing the ones responsible for a condition can help in the development of targeted therapies. The sheer diversity of these chemicals, however, makes it extremely challenging to identify them and despite technological advances, we still aren’t able to categorize all metabolites in samples. Various sophisticated and advanced methods are used to know what metabolites exist under different conditions.

One such technique, called mass spectrometry (MS), is commonly used to generate characteristic patterns of “molecular fingerprints” of metabolites, just as a fingerprint can be used to uniquely identify an individual. This allows one to distinguish one metabolite from another with accuracy whereafter metabolites can be identified using these specialized setups that give characteristic patterns for a molecule. In mass spectrometry, molecules are broken down into smaller pieces called fragments, much like how a jigsaw puzzle is broken into individual pieces. Each fragment represents a portion of the original molecule. Unlike a straightforward puzzle, each molecule can produce numerous fragments, and reconstructing the complete picture is not so straightforward.

Don’t panic. To tackle this complexity, we use computational methods to decode these fragments and piece together the full picture. This process involves analyzing the raw data generated by mass spectrometry and matching the fragments to specific molecules. Scouring through metabolomics raw data is a lot like solving a complex jigsaw puzzle where there is no reference picture and there are fragments that can fit in multiple positions! Developing computational tools and algorithms to automate this process is what we strive to achieve with our work.

My work involves identifying metabolites in different diseased conditions and making optimized computational workflows for it. We also use different ways to understand the data, like making models ranging from simple linear models to more complex machine learning (ML) to help us better identify metabolites and solve the jigsaw in a more efficient way. This in turn helps translate intricate data into meaningful biological insights, allowing us to identify and understand the unique “fingerprints” of different diseases and what metabolites may be responsible for it.

Microbial hitchhikers and metabolites. Metabolomics is an indispensable technique to understand a myriad of diseases. Their diversity is further supplemented by the microbiota that dwells within us. Our bodies additionally harbour a multitude of microorganisms including bacteria, fungi and phages that increase the diversity of the metabolome. We are in a state of dynamic harmony with them wherein they actively contribute to our overall health status, perturbations to which can quickly imbalance the scales.

In addition to beneficial residing microbiota, we are continuously exposed to harmful pathogens that our resident microbiota protects us against. Colonization resistance involves the natural defences our microbiota provide against potentially pathogenic microbes. Metabolites are important in colonization resistance and are crucial in maintaining a healthy state with disruptions in the gut microbiota having been associated with numerous diseases.

These beneficial microbes occupy ecological niches, produce antimicrobial substances, and compete for resources, all of which help to keep harmful pathogens at bay. Antibiotic resistance, on the other hand, occurs when microbes evolve mechanisms to withstand the effects of drugs that once killed them or inhibited their growth. This resistance to antibiotics can lead to serious infections that are difficult to treat.

As part of the COL-RES project we are especially focused on understanding the small molecules associated with human pathogens such as bacteria involved in colonization resistance in the gut and antibiotic resistance.

The answer to the ultimate question of life, colonization resistance, and everything is metabolomics? Unlikely. But the tools offered by metabolomics have aided in understanding the underlying mechanisms involved in these processes. The complex exchange of molecules between the human host and the microbiota shapes the environment in the gut. The metabolites they produce—ranging from short-chain fatty acids to amino acids and vitamins—can have profound effects on host physiology.

Disruptions in the gut microbiota, such as an imbalance caused by diet, stress, or illness, can lead to altered metabolite profiles. For example, a reduction in beneficial bacteria may lead to lower levels of certain metabolites, contributing to inflammation and diseases. Conversely, an overgrowth of harmful bacteria can produce metabolites that promote disease states, such as those that lead to increased inflammation.

It is a mistake to think you can solve any major problems just with metabolomics. Metabolomics alone might not hold all the answers, but it equips us with valuable data that, when combined with other scientific data, contributes to a more comprehensive understanding of health and disease. It offers crucial information, offering insights that guide research and therapeutic strategies, and helping us navigate the complex landscape of human biology and microbial interactions to provide targeted therapies to patients.