Uses of Metagenomics in Pharmaceutical Development

What Is Metagenomics? 

Metagenomics is a discipline studying the genetic content of microorganisms, including fungi, bacteria, and viruses. Many metagenomic experiments seek to identify all of the microorganisms in a heterogeneous sample. This means microbes can be studied in their natural environment — making it possible to observe complex biological interactions. 

We dove into the tools and applications of metagenomics studies in our recent introductory blog post. In this article, we will focus on how metagenomics is applied to pharmaceutical research and drug development.

Monitoring Drug Resistance

How do resistance genes spread? 

Drug resistance develops when microorganisms experience changes that make medications or disinfectants less effective. There are three major ways that this resistance develops and spreads among a species: 

• A microbe independently develops drug resistance. This mutated microbe will not be impacted by the use of antimicrobials.

• A naturally drug-resistant microbe multiplies. This process of resistance spread can be sped up by human activity. In a “selective pressure” situation, an antimicrobial or antibiotic is used to kill susceptible bacteria. Non-susceptible bacteria in the environment will be unaffected, and can then continue to multiply until they are the dominant remaining bacteria type.

• Microbes share drug-resistant genetic material with each other. This gene transfer allows non-resistant bacteria to acquire resistant genes.

   

The future of resistance monitoring

Drug resistance is a challenge that will only get worse over time. In the United States, the CDC estimates that 2.8 million drug-resistant infections occur annually. Current discovery and development methods are not keeping up with antimicrobial resistance (AMR) developments worldwide. Tracking drug-resistant outbreaks and developing new treatments will be essential to prevent an increase in the spread of these microbes and the associated illnesses and fatalities. 

Metagenomic technologies are often used to track microbial resistance and spread. A project published in 2021, for example, published a global atlas of 4,728 metagenomic samples from 60 cities. Researchers used shotgun metagenomic sequencing to create profiles of microbial strains as well as their antimicrobial resistance markers. Projects like these reveal a diverse set of resistance markers that vary across cities. Results also indicate a distinct difference in the number of antimicrobial-resistant genes in different global regions, an important insight for identifying the locations most likely to play host to resistant microbes. 

Metagenomic approaches are also valuable in determining whether a drug-resistant microbe will respond to a novel compound. Methicillin-resistant Staphylococcus aureus (MRSA) is a notorious antibiotic-resistant infection. In a 2015 study, researchers identified teixobactin, a novel antibiotic produced by a previously undescribed soil microorganism. Using iChip technology, researchers grew this bacterium and isolated teixobactin. Experimental MRSA treatment in mice showed that teixobactin successfully reduced bacterial load. 

Metagenomics-powered discoveries like these will be crucial in tracking drug-resistant outbreaks, developing new therapeutics, and understanding how drug-resistant microbes may respond to those novel compounds. 

Therapeutic Developments with Metagenomics

Bacterial diversity for therapeutic discovery

With the growth of antimicrobial resistance to antibiotics, discovery of new compounds is very necessary. Metagenomic data enables researchers to hunt out novel bacterial species. This is used particularly often with environmental samples (microbial populations in the air, soil, or water). However, other environments have also proven promising. 

For example, a study on sponges off the Maharashtra Coast found that, although the sponges do not have their own defense systems, they host a large and diverse population of microorganisms. This project isolated seven bacterial species from sea sponges. These bacterial species are good candidates for isolating biologically active compounds that may be used in therapeutic development, including polyethers, terpenoids, alkaloids, macrolides and polypeptides. 

Metagenomics tools are invaluable in cases where bacterial species cannot be cultured in the lab. These unculturable species are often important in understanding disease pathogenesis, or in use for therapeutic development. For example, a study on periapical abscesses found that 13% of bacteria derived from these abscesses are unculturable. Categorizing these species is an important step in understanding disease development, as well as identifying their potential use in antimicrobial development. 

Vaccine development

Metagenomic sequencing is used to better understand the variability of pathogens. Unique strains of a disease-causing microbe may require the development of a new vaccine. In a study on COVID-19, an arsenal of metagenomic approaches were explored for strengths and limitations in characterizing zoonotic viral pathogens. Active and continuous monitoring is necessary to discover new pathogens before outbreak. 

Metagenomics is quickly becoming a critical tool in vaccine development. In traditional development, a protein-based vaccine, like the annual flu shot, often only targets a subset of the pathogen’s strains. This leaves scientists to guess which one to include in the annual vaccine. Using metagenomics, researchers were able to identify an epitope that is conserved across all eight strains of group B. streptococcus (GBS). The team used this knowledge to create a universal vaccine against GBS.

Understanding the Microbiome 

The human microbiome consists of millions of bacteria living on and in the body. The composition and balance of these microbial communities play important roles in our health. Microbiome bacteria have a proven role in immune response and in fighting off harmful microbes. When the microbiome is out of balance (dysbiosis), we are more likely to see disease states and even chronic illnesses. 

Metagenomic approaches like 16S rRNA sequencing make it possible to identify microbial species living in various parts of the body. With this information, researchers can:

• Define microbiome composition and function. By exploring microbial communities, researchers gain a better understanding of bacteria’s role in bodily functions. In the last decade, for example, researchers have begun to categorize the microbes present in the lungs (an environment traditionally presumed to be sterile). Culture-independent techniques, meaning that the microbial samples don’t have to be grown in a lab prior to sequencing, have proven that the lungs actually harbor a diverse microbial community, typically dominated by three genera. Research projects have shown the impact of conditions like asthma, COPD, cystic fibrosis, and pneumonia on these microbial populations.

• Understand impacts on drug metabolism. Some microbes are able to metabolize drugs. This can enhance or diminish those drugs’ impact on the host’s health. A study on reactive oxygen species (ROS)-based treatments in colorectal cancer, for example, showed that the gut microbe Enterococcus durans can be helpful in ROS. A critical link was identified between ROS treatment success and folate metabolism. On the other side of this spectrum, digoxin (used to treat patients with heart failure or atrial fibrillation) is metabolized by gut bacteria Eggerthella lenta into inactive dihydrodigoxin. This makes the treatment ineffective. Studies in mice indicate that a targeted diet with high protein levels may be able to limit E. lenta’s metabolism of digoxin. 

• Link disease states to dysbiosis. An imbalance in the microbiome has been linked to many disease states. Increasingly, research is linking inflammatory processes to dysbiosis in microbial communities. Microbe-microbe and microbe-host interactions make up a complex set of processes that can lead to regulatory failures on a large scale. Type 1 diabetes, for example, has been linked to microbiome imbalances in the gut. With this knowledge in mind, the challenge for Type 1 diabetes — and many other inflammatory diseases — becomes translating this microbiome data into diagnostic and  therapeutic interventions. 

• Identify influences on drug-drug interactions. Some drug interactions are influenced by the microbiome. For example, amoxicillin and aspirin administered together have a high probability of interaction. In rats, amoxicillin was found to reduce the number and diversity of intestinal microbes. At 12, 24, and 36 hour periods, levels of aspirin indicated that aspirin is metabolized by intestinal flora, and that metabolism of aspirin is slowed down after administering amoxicillin. 

• Characterize influences on the immune system. The immune system and the body’s microbiomes interact to prevent disease. When this relationship does not function as intended, diseases can develop. Recent research has even found a link between microbes, the immune system, and pregnancy hormones. These interactions assist with homeostasis and the physiological changes associated with pregnancy. However, some data indicates that these changes may make women more vulnerable to infectious disease during and after pregnancy. 

These applications make metagenomic sequencing approaches powerful tools for discovery and pharmaceutical development. Insights into host-microbe, microbe-microbe, and drug-microbe interactions lead to development of pharmaceuticals and treatments for disease states.

Applications of microbiome insights

The microbiome holds many promises for improved personalized medicine. A better understanding of an individual’s microbiome can help to understand why individuals experience different health outcomes. In lung and kidney cancers, for example, PD-1 immunotherapy was less effective in patients with low levels of Akkermansia muciniphila in the gut. Similarly, melanoma patients who responded well to PD-1 therapy had more “good” gut bacteria than non-responding patients. 

Results such as these indicate maintaining a balanced gut microbiome can help improve outcomes for some cancer treatments. Insights into helpful microbiome composition are also useful for companion diagnostics, and can help determine if an individual would benefit from a specific intervention.

Microbiome studies have also led to advancements in pre- and probiotic development. Metagenomic approaches can identify beneficial bacterial strains for use in treating gastrointestinal disorders, immune function, and dysbiosis balancing. 

For example, shotgun metagenomic sequencing was used to profile microbial communities in tempeh, an Indonesian food made from fermented soybeans. Results profiled the most abundant phyla and genera in samples from two tempeh producers, including a novel discovery that E. coli in tempeh is genetically distinct from medical E. coli isolates. An improved understanding of tempeh’s microbial communities may be a promising source for the development of paraprobiotics. 

Metagenomic sequencing capabilities have helped researchers make major strides in vaccine and therapeutic development, as well as understanding drug resistance and microbial factors that may impact the efficacy of treatments. As these technologies advance, they will play critical roles in combatting antimicrobial resistance and improving individualized medicine.