What Is a Microbiome?
“Microbiome” has become incredibly popular these days. Though it may sound like a relatively new concept, it has been there in the early days of microbial ecology, since the first report of the bacteria (by Antony van Leeuwenhoek, in 1683). In 2001, a microbiologist and Nobel Laureate, Joshua Lederberg, coined the term “microbiome” to refer to the ecological system of a collection of all microorganisms that inhabit and coexist alongside other species. Today, the collection of all these microorganisms themselves is termed “microbiota”, and the collection of all microbial genomes is termed “Microbiome”.
Why Are Microbiomes So Important?
Microbes, these tiny organisms run the world and literally follow you everywhere, be it your hands, food, grass, or even hiding on your laptop like invisible bugs! They are not just a crucial part of human life, but fundamental to all forms of life on the earth. Microorganisms, including bacteria, archaea, protists, fungi, and viruses, inhabit these various ecological environments such as air, water, soil, and humans. Research on environmental microbiomes – such as those in marine and soil ecosystems emerged decades earlier than human microbiomes, where they studied the role of these in nitrogen fixation, oxygen production, bioremediation, etc. The rapid turn towards the human microbiome occurred after the Human Microbiome Project in 2007, to understand the role of the microbiome in human health and disease. Understanding the activity of the microbiome became important as studies showed the association of these microbes with general lifestyle, disease, and their applications across various environmental and industrial sectors.
How Do We Extract Microbial Information?
Sample collection: Samples are collected from the required ecological environment, and the approach varies from one environment to the other based on the required data. Basically, there are 2 approaches: a traditional approach to culturing microbes and a culture-independent approach. Historically, the culture-based method was utilized to grow microorganisms in standard laboratory conditions to identify and study microbes. But, since most of the microbes could not be cultured in the lab, they limited the study outcomes as only a small percentage of the total microbial communities would be covered in this approach. Thus, understanding the dynamics of microorganisms was limited to the culture-dependent approach, and it was a time-consuming process. As culture-independent techniques like advanced high-throughput sequencing technologies came into the picture, they allowed for the sequencing of the entire microbiome, covering a broader range of information, facilitating microbial study at a more accurate and faster rate. “Metagenomics” is one of the “omics” disciplines that focuses on analyzing the entire microbial community genome, bypassing the need for culturing microorganisms, and includes a set of comprehensive bioinformatic techniques to study microbial communities.
Figure 1: A) General approach to generating and processing the metagenomic data from various samples and bioinformatics analysis. B) Applications of microbiome across health, environmental and industrial domains.
Sequencing: Sequencing platforms produce sequence data, and two main approaches are a) marker gene/amplicon sequencing which is based on using marker genes (ribosomal regions) to characterize and analyze the presence and composition of the microbes and b) whole-genome shotgun (WGS) sequencing to sequence the entire genome of the microbes, allowing them to not just characterize but also obtain functional understanding of the microbial community.
Data processing: The first step after obtaining the raw metagenomic data is preprocessing and curation. Quality control and filtering involve sequence quality checking, trimming the adapters and bad quality reads, and removal of host DNA contamination using various software tools. This step is crucial to get high-quality data for more accurate and true insights about the microbiome.
Bioinformatics analysis: Once metagenomic data is processed, we need to extract the information of what microbes are present, how abundant they are, and what role they play in sustaining that ecology. This includes mapping the metagenomics reads to reference genomes or assembling the quality-filtered reads into contigs, binning and then mapping against the reference database to perform taxonomic classification, gene prediction, and functional annotation. Further analysis involves statistics, integration, and interpretation, which includes diversity analysis, differential abundance and prevalence analysis, microbial pathway and network analysis, comparative analysis, and microbial marker discovery.
What Do We Understand From This Microbial Data?
Diversity analysis helps us understand the spread of overall microbial species, richness, evenness, and variation in microbial compositions. Abundance and prevalence analysis help us understand variation of taxonomic composition based on relative abundance and frequency of microbes across the samples. Differential abundance analysis gives insights into the differing abundance of each microbe across the samples, after addressing the compositionality and sparsity, which helps identify the candidate microbial markers that could offer biological insights. Microbial pathways and network analysis involve understanding the role of microbial species and their functions in their habitat/ecosystem.
Major Applications of Metagenomics
- Human health:Clinical Diagnosis: In a clinical setup for pathogen detection in infectious diseases such as Tuberculosis, AIDS, metagenomics plays a crucial role in identifying and characterizing the infectious and co-infectious pathogens. Due to its comprehensive and unbiased approach, it enables broad identification of both known and rare pathogenic microbes or even novel microbes with the highest accuracy and sensitivity.Detection of Antimicrobial Resistance: Resistant gene mechanisms and identification of drug-resistant microbes are aided by functional metagenomics, which allows for the understanding of the pathogenicity of the microbes in disease/ health conditions by analyzing the genes of interest.Understanding Disease Etiology: Metagenomics helps in identifying dysbiosis conditions that drive inflammation, altered metabolism, and carcinogenesis. Sequencing tumor-associated microbes allowed for the identification of oncogenic viruses and their genomic sites that produce mutation-causing toxins. Application of other omics along with metagenomics has also been fruitful in understanding the functional capabilities of microbes and their metabolites, and their role in host gut-brain axis balance in neurodegenerative disorders. Here, the metagenomic profile would help in understanding the gut microbial taxa and their function in intestinal barrier integrity, neuroinflammation, etc.Epidemic Outbreaks: Environmental screening through metagenomics to identify the key bacterial/viral strains of outbreaks and transmission is crucial for tracking the source of the outbreak and reducing the potential risk to the general population. (i.e., Sars-Cov2 coronavirus pandemic 2020).
- Therapeutic Interventions: Microbiome, as it acts as a therapeutic marker for various disease conditions, becomes a crucial application in the clinical setup. Metagenomics not only allows for obtaining an individual’s microbial profile but also helps in developing a personalized therapeutic intervention like a customized microbial composition (probiotics & prebiotics/FMT/diet/engineered consortia) to maintain the gut microbial balance in the disease conditions. Based on the metagenomic fingerprint of the microbiome, clinics can stratify the patients and prescribe more precise medicine with microbial interventions. Metagenomic profiling defines the crucial microbial signatures associated with toxicity/response to the immune checkpoint inhibitors during the phase of cancer immunotherapy. This helps in improving the therapeutic efficacy by more precise microbial modulations, such as bacterial vaccines that can target tumor-antigens and activate the immune responses. In infectious disease conditions, early detection of pathogens and drug-resistant microbes helps in the timely initiation of anti-infective therapies.
- Food Safety and Industry: Global health concerns arising regarding the nutritional awareness and illness are reported from the consumption of contaminated foods. The presence of food-borne pathogens can be detected using metagenomic sequencing, which further contributes to the development of quality indicators and aids in improving safety assessment for food products. Rapid, sensitive and accurate methods for the detection of pathogenic microbes in food products are also facilitated by metagenomics, combined with an advanced technological approach for capturing information on potential contamination sources, microbial diversity, and even detecting pathogens at trace amounts. In the food industry, metagenomics helps in tracking the microbial community interactions and succession patterns to optimize the fermentation process and characteristic texture/flavor development of fermented food products.
- Agriculture: Metagenomic approaches greatly benefit the agroecosystems. Microbes residing in the plant roots, soil, or any agricultural environment are crucial to plant growth and sustainable yields in agriculture. A deeper understanding of functionality and interactions of these diverse microbes in soil or soilless environments helps in developing novel advancements or strategies like bio-fertilizers/pesticides, enzymes, and biocatalysts, which can increase the resistance to pathogens, improve crop productivity and soil health, and nutrient cycling and availability, further enabling sustainable agricultural practices. Metagenomics help detect pathogens in infected plants/crops. Development of genetically modified (GM) crops (i.e., Bt cotton) is also facilitated through the identification of genes associated with pest resistance and resistance genes from beneficial microbiomes and engineered to improve the agronomic traits.
- Environmental Science: Certain key environmental microbes are used to reduce pollutants such as plastics, petroleum hydrocarbons, pesticides, etc., in the environment (bioremediation) or toxic elements such as nitrogen/phosphorous elements during sewage treatment. Metagenomics facilitates the discovery of new microbial strains or functional microbes/genes with high degrading efficiency of the pollutants and having consistent expression and versatility. Pseudomonas veronii is one such bacterium containing plastic-degrading genes.
- Forensics: Microbiome found on any environmental surface or human body becomes crucial for various forensic purposes. Metagenomics helps to identify the geolocation, manner and cause of the death, identifying and distinguishing the individuals based on the microbial signatures from the body fluids, skin surface, any microbial sample from the surrounding crime spots, thus benefiting many other civil and criminal cases.
Conclusion
Metagenomics has emerged as a powerful approach for understanding and exploring the microbiome and its function across various ecosystems. Advanced sequencing technologies like NGS platforms have potential in rapid and real-time pathogen detection, improved taxonomic profiling, and strain resolution. The integration of different microbial omics (such as metagenomics, metatranscriptomics, and metaproteomics) accurately captures microbial interactions and facilitates their functional annotation. Application of metagenomics in environmental, health and industrial sectors enhances the efficiency of discovering novel enzymes, bioactive compounds, precision medicine applications, and engineered microbial products for developing sustainable management strategies.
Dr Arindam Deb, Lead Scientist (Bioinformatics) in Happiest Minds, is a profound researcher in the domain of Bioinformatics with intense research experience in academics and industry. He holds a PhD from the University of Calcutta with a national-level fellowship (RFSMS, UGC, Govt of India). He has worked in various organizations as a Senior domain expert, Principal scientist, and Assistant professor, collaborating with national and international scientific bodies. He is also involved in teaching and mentoring as an honorary member of the Doctoral reviewer committee of renowned universities. Dr Arindam has a keen research interest in the transformation and heterogeneity of gene regulation in various disease conditions. His present research focuses on exploring the complex disease microenvironment at single-cell resolution. Currently, at Happiest Minds, he is advancing fundamental research in Bioinformatics in collaboration with SKAN Research Trust.
Meghana Acharya is an Associate Data Scientist at Happiest Minds, having experience in life-science and bioinformatics research with a strong academic background in Biotechnology (B.Sc.) and Bioinformatics (M.Sc.). She is passionate about exploring the interplay between host physiology and the gut microbiome and aims to translate complex bioinformatics findings into meaningful biological interpretations that improve human health outcomes. She has also contributed to research publications in the life-science domain. Her specialization lies in metagenomic data analysis focusing on understanding the impact of gut microbiota alterations on human health. Currently, she is a part of SKAN Bioinformatics Research, working on metagenomics research and data analysis across various disease conditions to generate meaningful insights.
