Francesca Tomasi received her B.A. from the University of Chicago and currently researches tuberculosis drug targets in search for novel antibiotics.
You have probably heard words like genome or chromosome before, both of which refer to some self-contained unit of completion: chromosomes contain genetic information that all together makes up the genome, the complete set of genes within an organism. Now in the twenty-first century, the suffix -ome has been modified into a neologism, -omics, aimed at encompassing different fields that can collectively characterize (even quantify) entire pools of biological molecules. With modern tools, scientists can translate massive data sets into the inner function and dynamics of living things.
Sometimes we assume many of the “major” discoveries in science have already been made: the discovery of DNA, the identification of etiologic agents of disease through a thorough understanding of human physiology, the structure and function of viruses, bacteria, proteins, eukaryotic cells, and so on. We assume that as members of this century it is our duty instead to dig into the intimate details of a biological system to pinpoint the nuances responsible for diseases we have not been able to treat yet. As we learn repeatedly, however, this is not exactly true. Major discoveries are still made today that revolutionize anything from a small niche in research to the central dogma of medicine. Recently, for instance, the discovery of CRISPR and its simple applications to genome editing have stirred the foundation of genetics and the potential for gene therapy as a very real way to treat hereditary diseases.
Another revolution comes from the invention of tools to study entire organisms all at once. A cell is a highly complex, dynamic unit— the smallest structural and functional component of a living organism. Cells contain all sorts of biological molecules that allow them to function as single living entities. In multicellular organisms like ourselves, our cells work together to make us us. We are, to echo some biology teachers’ favorite cliché, walking chemical factories, constantly undergoing biochemical processes to maintain a functional, physiological balance.
Until now, we have predominantly studied cells and greater organisms piece by piece, by mutating, deleting, or overexpressing specific genes that encode for specific molecules, to understand the purpose of those molecules and how they come together in biochemical pathways. The goal of the omics, however, is to look at something –a single cell, organ, or an entire population of individuals – and deduce patterns that correspond to specific consequences. Let’s look at three of the main scientific omics.
GENOMICS: PUTTING TOGETHER THE GLOBAL GENETIC CODE
In 1953, Rosalind Franklin confirmed the helical structure of DNA, and her findings were published by James Watson and Francis Crick. As soon as the scientific world learned what DNA was and how it worked, the advent of genetic sequencing technology revolutionized molecular biology. As early as 1955, researchers developed ways to decode the genetic makeup of anything from a single protein to cellular organelles. By the turn of the century, DNA sequencing evolved into a rapid technique that today allows us to sequence entire genomes. In 2007, the Human Genome Project was completed: the entire genome of a single human being was published. Since then, thousands of genomes across all of life’s kingdoms have been sequenced, and thus was born the study of genomics. For example, scientists can easily compare different genomes to search for potential genes associated with different diseases. In the event of an infectious disease outbreak, sequencing pathogens can allow biologists to understand the microbe’s evolutionary pattern over the course of an outbreak. Understanding the genetic makeup of viruses and bacteria helps scientists develop vaccines, or predict mutations that will make a pathogen resistant to drugs or more contagious.
Genomics has multiple subsets. Functional genomics, for instance, attempts to describe gene functions and interactions (you will see this recurring theme as you read on about proteomics and metabolomics). This area of interest focuses on the more dynamic nature of DNA and its use as a blueprint for proteins as opposed to examining the static nature of the DNA code. For instance, scientists trying to understand how an organism coordinates its life processes on a genetic level will employ techniques in functional genomics.
Meanwhile, researchers studying structural genomics would like to elucidate the 3-dimensional structure of the proteins encoded by a genome. Like a blueprint that describes a building, moving from a 1- to 2-dimensional map to a three-dimensional building is a complex process; nonetheless, a combination of physics, structural chemistry, and genomics allows scientists to develop structure prediction algorithms to model an unknown protein’s structure. This, in turn, helps study the protein’s interactions with other proteins, and design potential molecular inhibitors of protein drug targets.
Finally, metagenomics is the study of genomes recovered from environmental samples. A major limitation in microbiology is the inability to culture over 90% of microbes. To study a community of bacteria, classical microbiology requires scientists to be able to grow and manipulate each species in the lab. However, growth media is a complex result of years of trial and error to determine the minimal necessary growth conditions for a given organism. Thus, it is difficult – and often deemed impossible – to invent and manufacture special media for any species of interest. Metagenomics helps navigate this limitation by allowing researchers to sequence entire populations and study microbial diversity by understanding the different genome sequences within a sample. It holds the power to reveal previously untapped microscopic life, allowing us to delve more deeply into hidden wonders of the world including our very own microbiomes.
PROTEOMICS: PUTTING THE “PRO” IN PROTEIN
Biochemical processes are carried out by proteins, the indispensable organic compounds that give us our body tissues, enzymes, and antibodies (amongst so many other things). Proteins are encoded for by genes, our biological blueprints. The word “proteome” furthermore describes the entire set of proteins expressed by a genome, cell, tissue, or organism at a given time. Proteomics, therefore, is the study of proteomes; a quest to understand how entire networks of proteins interact in a specific context. The proteome of a given organism, or subset of an organism, varies per the environment – stress, nutrient levels, and so on – so the amount of data one can generate through proteomic studies is massive.
Proteomic analysis is further complicated by the fact that once a protein is made, it does not necessarily remain unchanged. Proteins constantly interact with each other and are altered along with a cell’s physiological state. So-called “post-translational modifications exist to slightly alter a protein to perform a new task. An extremely common example of this is called "phosphorylation." Phosphorylation refers to the addition of a phosphate molecule to specific amino acids (the building blocks of proteins). This often happens in processes like cell signaling, where the presence or absence of a molecule causes a protein to become phosphorylated, giving it a kind of energy-rich tag that equips the protein to set off a new cascade of events in response to a change in the environment. Thus, proteomics can also involve studying variations of a specific protein in different scenarios to understand when and where it is used for a given purpose.
Suffice to say, proteomics experiments are complex tasks that require very precise planning and execution. In any biological field, proteomics has seemingly infinite applications. One such application is in drug discovery.
In the past, antimicrobial drug discovery relied heavily on serendipity. Penicillin, for instance, was only discovered when a laboratory petri dish was contaminated with mold that killed the dish’s resident bacteria. Nature is arguably Earth’s greatest pharmacist in this regard, as organisms have evolved side by side for billions of years, developing arsenals against each other. Name a bacterial species, and it is more likely than not that there exist different bacteria or fungi capable of producing their own antibiotics to outcompete that species. Nonetheless, treating bacteria within the human body has added criteria that are not necessarily met by natural antimicrobial compounds. An antibiotic used in people is, ideally, selectively toxic to a specific type of pathogen while simultaneously causing little to no harm to patients. Meanwhile, a compound produced by other microbes might be broad-spectrum, or it targets some essential biochemical process common to both a pathogen and its host. Artificial drug discovery efforts – and proteomics – step in to understand existing drugs and build novel ones.
Proteomic analyses are helpful in many subsets of drug research: namely, target identification, identification of a compound’s efficacy or toxicity, and understanding mechanisms of action. The first category requires the identification of proteins whose activities change between healthy and diseased states. Such proteins provide insight into potential novel drug targets as well as diagnostic biomarkers of a given condition. If researchers analyze a pool of extracted proteins from healthy control populations and from individuals with a given disease, they can analyze differences between both cohorts (and even along a spectrum of disease severity). With regards to compound efficacy, proteomics can aid in the identification of protein interactions and the detection of any biomarkers to assess whether an intended, theoretical target is modulated by a given compound in real life. Lastly, sometimes researchers identify chemicals that successfully treat a specific pathogen, but whose specific target(s) or mechanisms of action are not understood. In this scenario, proteomic profiling can shed light on drug targets to pinpoint what is taking place. This is often accomplished by slightly modifying a drug into a probe – that is, giving it a “handle” (usually a small chemical modification that will not change the drug’s activity) that is later detectable by a tag (such as a fluorescent molecule) that specifically binds to the handle. This in turn makes the drug discernible from other uninvolved proteins, allowing a scientist to purify specific tagged molecules and, consequently, any target protein they are bound to.
METABOLOMICS: YOU ARE WHAT YOU EAT
When researchers study new drugs to treat an infection, the obvious first question to ask when a compound is found that kills a pathogen of interest is “what is the target?” That is, what molecule or biochemical pathway within the organism is this foreign compound destroying or inhibiting that leads to the microbe’s failure to thrive? One way to address this question, besides the proteomic approach discussed above, is to compare the metabolites of untreated and treated bacterial populations. Metabolomics, the youngest of the three -omics discussed in this article, is defined as “the systematic study of the unique chemical fingerprints that specific cellular processes leave behind.” The metabolome, simply put, is a collection of all end products of cellular processes within a cell, tissue, organ, or entire organism. This physiological snapshot can provide valuable insight into the characteristics of healthy and diseased cells. In the world of drug discovery, researchers can compare the metabolic profiles over time of bacteria in a control environment with those of the same bacteria in a drug-treated environment. The distinct populations will inevitably diverge in their chemical processes, both because of metabolic disaster triggered by a foreign substance and as a potential compensatory mechanism.
Metabolomics also plays an increasingly important role in the diagnostic world, both for communicable and non-communicable diseases. Researchers are asking questions about metabolic processes that might be altered within a host, or characteristic pathogen-related metabolites that could indicate an infection. They are also asking about potential molecular predictors of a disease’s severity or state of progression.
For instance, dengue fever is a major global health concern that presents with a range of symptoms, from minor illness to organ failure. The ability for doctors to predict disease outcome on a patient-by-patient basis would aid in on-site triaging of patients in the clinic. Scientists at Colorado State University have investigated just that. In a study published last year, the researchers characterized the serum metabolome of dengue patients who experienced different disease outcomes. In this retrospective analysis of blood samples, the researchers could differentiate between different outcomes (for instance, between dengue fever and dengue shock syndrome, as well as between patients who progressed from one state to the other or ultimately succumbed to the infection) by way of different metabolites. Altogether, this study provided a proof-of-concept that metabolomics may serve as a predictive tool for infection outcome, which will help inform individualized treatment plans. Metabolomics is considered the most dynamic level of biological regulation (more so than protein modification, and much more so than any genome-level alterations), and as such a very convenient real-time method of physiological analysis.
Many times, large-scale biological projects such as antibiotic discovery efforts and environmental research do not use a single omics approach. Instead, proteomics, metabolomics, and genomics are often used together as synergistic approaches to create a more unified perspective within a given biological question. The omics do not end here, though. In fact, new omics fields are constantly popping up, from neurogenomics (the study of genetic influences on the nervous system) to nutrigenomics (understanding the relationship between the human genome, nutrition, and health). This is the era of the omics, the quantification of biology to uncover untapped questions and patterns.