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.
Metagenomic projects often involve:
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Therapeutic development
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Disease outbreak surveillance
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Crop improvements
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Microbiome composition
Tools for Metagenomics
16S sequencing
The 16S rRNA gene is present in almost all bacterial species. It is responsible for encoding ribosomal RNA in self-replicating organisms. The ribosomes then go on to play a key role in protein synthesis.
16S rRNA genetic information has applications in:
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Clinical microbiology, in which the 16S sequence can be used to identify human bacterial pathogens. This is particularly helpful in infectious cases where traditional culturing of samples might fail. Databases of 16S sequences like GenBank make it possible for clinicians to identify microbes at the genus or species level. In projects like this one from a team of Swedish researchers, they experimented with different primers to show that the specificity and sensitivity of 16S rRNA analysis directly from clinical samples can be improved.
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Environmental microbiology, the study of microbes as they interact with each other and their environment (commonly air, soil, and water). Activated sludge, for example, is a part of the wastewater treatment process. In a 2020 study, 16S rRNA sequencing was used to better understand activity patterns and seasonal changes in microbe abundance. A better understanding of the seasonality of microbial communities in activated sludge provided insights into activities impacting wastewater treatment.
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Microbiome studies, which can profile the microbial composition of plant, animal, and human microbial communities. A study published in Beneficial Microbes analyzed 16S rRNA data to better understand the health effects of dietary fibers, probiotics, and fructans on the human gut microbiome. This data was able to identify shifts in microbiome composition related to the consumption of these groups.
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Pharmaceutical development, where 16S rRNA sequencing plays an important role in exploring bacterial compounds that may be helpful in drug development. This is particularly true of bacterial species that can’t be cultured in the lab. Sequencing these species allows researchers to identify key compounds for drug discovery. You can learn more about applications of metagenomics tools in pharmaceutical research in our most recent blog post.
ITS sequencing
The Internal Transcribed Spacer (ITS) DNA sequence is widely present in fungal species. Because it’s often present, it is used for fungal taxonomic and diversity analyses. This can be applied to work in:
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Fungal identification. Because the ITS region is highly variable, it can be used to distinguish even between very closely related fungal species. This is particularly useful in evolutionary studies, helping scientists identify possible signs of species divergence and phylogenetic relationships.
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Biodiversity studies, which analyze the rate of biodiversity in an ecosystem. In this study from the Mizoram University Departments of Biotechnology and Environmental Science, 23 wood-inhabiting fungal samples were selected for ITS sequencing. These 23 species were identified by comparing them to known species in GenBank, and represent a successful effort in understanding the biodiversity of the northeastern India region of Mizoram.
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Food safety research, where the ITS region can be used to identify potentially harmful contaminants. In grain, for example, fungal growth leads to significant loss during crop growth and storage. A study conducted in northern Uganda identified 15 genera of fungal species in household grains, many of which had toxigenic potential. This study highlighted the exposure risk and danger of mycotoxins in sub-Saharan Africa.
Shotgun metagenomics
The previous two methods for metagenomic science analyze small portions of microbial genomes. Shotgun metagenomics, by contrast, takes a much wider view. With this technology, researchers can survey the entire genomic content of microorganisms in a heterogeneous sample. Unlike 16S and ITS sequencing, which focus on bacteria and fungi (respectively), shotgun metagenomic sequencing can profile bacteria, viruses, fungi, archaea, and even eukaryotic organisms.
This methodology is valuable for characterizing interactions in high-complexity environments, and has proven uses in:
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Pathway reconstruction, in which shotgun metagenomic data is used to reconstruct metabolic pathways in microbial communities. A better understanding of how microorganisms interact with each other can assist researchers in identifying the community’s function, like decomposition, nutrient cycling, or nitrogen fixation. A 2022 study used shotgun metagenomics to reconstruct pathways for protein-creating amino acids in the human gut microbiome (HGM). The resulting analysis used 823 HGM species for predictive metabolic profiling. Data like this can be used to predict microbiome response to factors like dysbiosis and dietary changes.
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Rare species identification, made possible by shotgun genomics’ ability to detect low-abundance species in a larger sample. When partnered with advanced software as in this study out of Hannover, Germany, researchers were able to successfully identify rare species of bacteria with less than 0.2% genome coverage.
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Clinical microbiology, where shotgun sequencing can be used to identify pathogens in blood or other clinical samples. This gives a wide view of all possible pathogens contributing to an illness, and is valuable in identifying and treating complex diseases.
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Environmental ecology, particularly research conducted on water and soil communities. A better understanding of these microbial communities helps to characterize the interplay of species in an ecosystem, including nutrient cycles. It can also help us understand disruptions to an ecosystem, including effects of pollution or climate change. Shotgun metagenomic data were used in this South African study to compile metagenomic datasets for 16 samples from eutrophic and non-eutrophic lake environments. About half of the assembled genomes could not be mapped to any existing species, indicating an unexpected degree of diversity in polluted lakes.
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Drug development. Shotgun metagenomics can be used to identify enzymes with therapeutic potential or the potential for new chemical reactions. In a recent preprint, for example, shotgun metagenomics conducted on soil microbiomes was successfully used to search for naturally occurring inhibitors of cancer target HsMetAP1.
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Antibiotic resistance research. Shotgun metagenomics can profile the resistome and identify genes related to drug resistance. This is crucial to our understanding of how resistance spreads, and can inform strategies for infection management and antibiotic stewardship.
Long-read sequencing/third generation sequencing
High-throughput long-read sequencing technologies like PacBio make it possible to obtain full-length sequences of microbial samples. Longer contigs, more complete genes, and better genome binning can produce more actionable results.
In recent years, long-read sequencing has addressed major limitations of other metagenomic methods that employ short-read sequencing (<150 bp). Tests have proven that long-read sequencing provides more certainty and accuracy in metagenomic data.
In this 2024 study, long reads of the entire 16S rRNA gene provide maximum taxonomic resolution. DNA was isolated from 9 volunteers’ saliva, subgingival plaque, and fecal samples, then sequenced via short- and long-read technologies. Both technologies categorized microbes similarly at the genus level. However, PacBio long reads were more successfully categorized at the species level (55.23% for short reads, compared to 74.14% for long reads).
Similar results have been generated for fungal identification via long-read sequencing of the ITS region. Multiple pass sequencing reduced the long-read error rate to less than 1%, and full length ITS sequences revealed a taxonomically and functionally diverse community of Castanopsis carlesii mycobiome.
Exploring microbial communities enables us to better understand complex ecosystems, improve disease diagnostics, monitor environmental health, and discover novel medical treatments. As metagenomics continues to evolve with improving technology, its applications will only expand.
