Updated: Jul 19, 2022
The New Frontier: Unlocking the Opportunities of the Microbiome
July 22, 2021
By: 20/15 Visioneers, Leaders in Science and Technology A Comprehensive Microbiome Industry Perspective
Published on 22nd July 2021 “The microbiome in its extreme complexity has surrounded us all these millennia yet only recently, through our evolving understanding of biology and utilization of advanced technologies, are we beginning to unravel its applicability enabling major discoveries” - John F. Conway
1. What is the Microbiome?
2. History: Microbiome Technologies
3. Microbiome in Industry
3.1 Microbiome in Therapeutics
3.2 Opportunities for Microbiome Research in Biopharma/Drug Metabolism
3.3 Engineering Microbiome Therapeutics
3.4 Microbiome in Food, Nutrition and Wellness
3.5 Microbiome in Dermatology, Cosmetics and Personal Care
3.6 Microbiomes in Agriculture and Soil Management
3.7 Microbiomes in Aquaculture and Animal Health & Nutrition
4. Observed Challenges With Microbiome & Multi-Omics Data Management & Analysis
5. A New Generation of Scientific Data Management & Analysis Platforms for Microbiome Data & Processes are Needed
5.1 Eagle Genomics & e[datascientist]
6. Other Vendors
6.2 Illumina (BlueBee)
8. References **Acknowledgement to all the contributors to this document from both Eagle Genomics and 20/15 Visioneers. It was a highly collaborative and team effort! Executive Summary
Microbiomes are fundamental to, and interact with, every aspect of life on our planet. Despite this fact, the scientific community has, until only recently, underestimated the complexity and systems-like involvement of these highly complex microbial entities. Having now recognized their vital importance, focus has now turned towards the need to catalogue, understand, and proactively manage the microbiome. Given the multi-dimensional and complex nature of microbiome data, it is understood that this task could be a significant challenge for decades to come. Overcoming this challenge, however, will provide innumerable rewards with significant positive impact on the world and society overall, including: Accelerating the development of innovative medicines, improving food production and producing industry-leading, sustainable consumer goods, in addition to potential positive effects on already-threatened environments and ecosystems.
Common key themes and requirements have emerged repeatedly across a number of microbiome studies, including:
• The magnitude and complexity of microbiome data and data types
• Interactions between microorganisms, humans and animals
• The potential to use the microbiome to protect and improve human and animal health while reducing the impact of human related activity on the biosphere
This paper summarizes the history of microbiome exploration, understanding, and discovery to-date, and describes multiple product and market opportunities that responsible, well-informed exploitation of microbiome science could unlock. The microbiome is a perfect example of a large and complex domain that will ultimately unlock secrets in biology and hopefully improve quality of life for all beings. At the core of many large science and technology initiatives currently focused on promoting access to, handling and analysis of microbiome data, is the need for more effective data and process management. Unfortunately, today’s research and development environments have become increasingly complex, requiring forethought and planning to successfully integrate the most advanced scientific informatics, technology, and processes into established corporate cultures. Many R&D environments are riddled with inefficiencies, due to historically poor data curation and management processes that don’t comply with current FAIR data practices, relying instead on outmoded technology stacks that suffer from excessively deferred change management. This has led to a marked decrease in the rate of innovation at many organizations, as well as wasted time and effort devoted to incessant data wrangling, inconsistent reproducibility and replication of experiments, and processes that do not readily transfer and/or scale-up to further stages of development.
Top technological platform players have been addressing current challenges related to microbiome data analysis with tool stacks that can help perform contextualized data capture, curation, and reporting on microbiome experiments and data. Organizations contemplating a deeper push into advanced microbiome/multi-omics science are recommended to carefully consider and evaluate multiple partner-vendor offerings before committing resources to building a bespoke microbiome data and process environment. This paper highlights leading platforms and technologies offering the most up-to-date informatics and analytics infrastructures that have been designed to dramatically increase knowledge, understanding and discovery. A handful of microbiome software companies have developed numerous case studies that illustrate both the challenge, the approach, and the outcomes of omics-based microbiome studies. These case studies run the gamut from identifying sustainable compounds for use in consumer “everyday” products to identifying biomarker signatures for disease conditions, including the generation of prioritized and curated datasets to uncover all kinds of associations with health and disease prognosis. 1. What is the Microbiome?
The microbiome can be defined as a characteristic microbial community occupying a reasonably well-defined habitat with distinct physio-chemical properties. Therefore, the term “microbiome” refers to the microorganisms involved as well as their entire “theatre of activity,” both of which contribute to the formation of specific ecological niches. The microbiome, which forms a dynamic and interactive micro-ecosystem prone to change in time and scale, is integrated in macro-ecosystems including eukaryotic hosts, and is crucial for their functioning and health (Berg et al., 2020).
Modern medicine and consumer culture have been long on a crusade to eliminate health-threatening bacteria by using antiseptic products and antibiotics. Although this approach has delivered significant improvements in treating and controlling infectious diseases, it is becoming clear that declaring a war on Nature has come at a price. This price has rested mostly on the lack of understanding of the microbiome as well as its complex relationships with human health and wellbeing (depicted in Figure 1).
Figure 1 - The extensive impact microbiomes have on life and the planet (from Finbow, 2019) Just as modern agricultural practice now incorporates the idea that many insects together can be beneficial, rather than being considered to be harmful and unwanted pests, we are learning – or perhaps, remembering – that not all microbes are bad. It’s much more difficult to understand and manage the significant positive contributions a complex microbiome can make to the health of humans and livestock, as well as to agriculture and aquaculture, than to identify specific pathogens that unambiguously manifest in disease. The scientific community is getting more sophisticated in its understanding of the complexity of the host/microbiome relationship in the context of a symbiosis that has emerged over millions of years. This inseparable relationship continues to evolve as globalization and modern life impact the biosphere, whether in our outer environment or within our own bodies. Some have also argued that over the last seventy years or more, that this relationship has been breaking down. As a result, the microbiome has become more vulnerable to environmental changes, and hosts have also become less responsive to any microbial-related benefits.
The good news is that tools are becoming available to scientifically track, study, measure, and disentangle complex chains of causality that would otherwise be out of reach to individual researchers and/or research organizations. It seems necessary to create scientific networks and platforms whose components will benefit from shared data in a synergistic cooperation. This will allow for increasingly informed interventions, the consequence of which is that health and wellness management stands poised to reclaim its place alongside disease eradication as a critical step in the progress and evolution of living beings. 2. History: Microbiome Technologies
Ancient practice recognized the importance of the microbiome long before modern scientists defined it. The first reported use of feces with therapeutic purposes dates from the Eastern Jin Dynasty (3rd-4th century AD) where patients suffering from severe diarrhea were successfully treated with a human fecal suspension known as “the yellow soup.” Though the first formally approved microbiome therapy would not arrive for another 1500 years, technological advances have increasingly allowed us to understand and nourish beneficial microbial communities, while identifying and treating the bad. Today, novel tools are enabling us to harness the power of microbes across industries, applying and ultimately designing microbes to usher in a biological revolution.
The first Western descriptions of human-associated microbiota date back to the 1670s–1680s, when Antonie van Leeuwenhoek started using his own newly developed, handcrafted microscopes. In a letter written to the Royal Society of London in 1683, Antonie described and illustrated five different kinds of bacteria (he called them animalcules at the time) present in his own mouth and that of others. He subsequently also compared his own oral and fecal microbiota, determining that there were microbial differences between body sites as well as between health and disease. Some of the first direct observations of bacteria were therefore of human-associated microbiota.
Scientific research on the intestinal microbiome flourished at the turn of the 20th Century. In 1860, Louis Pasteur created the first reproducible artificial culture, paving the way for future research. The pivotal work of Theodor Escherich, Henry Tissier, and Ilya Metchnikov advanced the scientific foundations and clinical applications of the microorganisms found in the gut microbiome. In 1890, Koch published his famous postulates, i.e., four criteria designed to establish a causative relationship between a microorganism and a disease, and during the first half of the twentieth century, microbiology became more focused on the identification of etiological agents of disease. This was also likely due to the fact that most bacterial pathogens grow in the presence of oxygen, whereas most members of the gut microbiota cannot and therefore could not be cultured and properly studied at the time. Alfred Nissle, a German physician, isolated the Escherichia coli Nissle 1917 strain — which remains a commonly used probiotic — in 1917. During World War I, when the first gut eukaryotic microorganisms and bacteriophages were also described, Nissle noticed that one soldier did not succumb to dysentery and thought he might have a protective commensal microorganism in his gut. He isolated the strain and later showed that it antagonized other pathogens, establishing the concept of colonization resistance, whereby human-associated microorganisms prevent the establishment of pathogens in the same niche.
Following those early discoveries, a significant breakthrough in microbiome research occurred during the 1940s and 1950s when microorganisms from microbiota could be cultured in the laboratory. The next leap forward took place in the 1960s when it was demonstrated that germ-free mice (i.e., mice completely deprived of microorganisms and therefore lacking their own flora) had lost much of the normal physiology compared to conventional laboratory mice and this could be reverted by colonization with fecal bacteria. The observations made in these studies enabled many predictions that were confirmed several decades later using in-depth molecular analysis.
Despite advances in culturing microorganisms, it soon became apparent that there were significant discrepancies between the numbers of existing cells and how many could be grown in the lab, which became known as the ‘great plate count anomaly’. This key observation helped motivate the development of sequencing-based approaches to identify unculturable microorganisms. Woese, Pace, Fox and others pioneered the study of environmental microorganisms and subsequently adapted this to the analysis of human-associated communities, providing an unprecedented view into their composition. In 1977, Woese and Fox discovered a 3rd domain of life (Archaea, to sit alongside Bacteria and Eukarya) using rRNA as an evolutionary marker. Their work was further built upon in 1985 by Lane and colleagues, who developed a technique for efficient 16S rRNA gene sequencing. The introduction of pyrosequencing technology by 454 Life Sciences in 2005 began the “Next Generation Sequencing” (NGS) revolution. This ushered in a wave of technologies that offered massively parallel sequencing, delivering the kind of high throughput, scalability and speed necessary for microbiome studies, leading to an explosion in their uptake. For example, marker gene analyses (such as those using the 16S or 18S rRNA genes to evaluate the microbial taxonomic composition of a given environment) became particularly affordable utilizing NGS, and hence within the reach of most laboratories. Shotgun metagenomics, meanwhile, which can sample all genes in all organisms within a microbial sample, is becoming progressively cheaper and accessible over time, facilitating a deeper understanding of microbial ecosystems. Furthermore, bioinformatics tools have been developed that can utilize shotgun data to reconstruct metagenome assembled genomes, giving access to the representative genomes of thousands of species that have never previously been isolated and sequenced (see, for example, Almeida et al, 2021, Stewart et al, 2019 and Glendinning et al, 2020).
These technologies have enabled new and detailed insights into the microbiome in a wide range of areas, from human and animal health, through to agriculture, food manufacture, bioenergy production and marine ecology. There is no doubt that we will see this knowledge and data revolution develop further as new sequencing approaches, such as long read sequencing and single cell sequencing, become more mainstream. Real time portable sequencing, meanwhile, offers game-changing potential for tailored medicine, nutrition, personal care, and so on, based on personalized and localized microbiome analysis. We truly stand on the cusp of a new technology-driven frontier, with a multitude of associated opportunities.
Figure 2 - Microbiome: historical perspective with explosion of activity and understanding according to data published in several bibliographical sources. 3. Microbiome in Industry
The impending “Bio Revolution,” with the microbiome at its foundation, offers groundbreaking solutions to the life-threatening challenges facing our world today, from soil degradation to the rise in metabolic health conditions, to unsustainable consumer supply chains. These same solutions could also potentially unlock financial gains that will usher in a Fourth Industrial Revolution - the engineering and application of biology to transform design and production capabilities, driving sustainable innovation across numerous industries and generating up to $100 trillion for the global economy by 2040.
Companies that embrace the Bio Revolution and the concept of “Nature Codesign” will outperform their competitors by creating sustainable value chains designed to evolve with customer and environmental needs, while simultaneously generating the innovations that will rescue our planet from its greatest existential threats. Such innovations could include utilizing microbes for sanitary surveillance and water recycling; bioengineering drought- and pest-resistant crops; producing in vitro meat and alternative proteins; and new fossil-free routes to the creation of chemicals, plastics, fuels, materials, and textiles.
Microbes will be the unit of currency in this revolution, and the microbiome will provide the context through which to understand and apply these technologies. 3.1 Microbiome in Therapeutics
There is a growing appreciation for the critical role that the human microbiome plays in all aspects of health, from metabolic conditions to infectious disease, to chemotherapy response. This appreciation has led to an acceleration in the development of drug candidates attempting to harness the microbiome for therapeutic benefit.
The greatest developments in microbiome therapeutics have occurred in gut diseases. In particular, recurrent Clostridium difficile infection (CDI) has received by far the greatest experimentation with Fecal Microbiota Transplantation (FMT). This involves the transplant of fecal matter from a healthy donor to a patient experiencing gut dysbiosis in order to alter their gut microbial composition and cure them of disease. The transferred microbiota colonize the intestine and shift gut composition, ideally rebalancing the host environment and eliminating intestinal pathogens. The first known fecal microbiota transplants date back to fourth century China, where human fecal matter was delivered to patients experiencing severe diarrhea (J.-W. Wang et al., 2019). The first report in Western medical literature was not until 1958, when the same transplant technology was used to treat patients with pseudomembranous colitis. Cure rates for FMT in CDI have been high, with systematic reviews from early 2010s suggesting cure rates as high as 90% for patients of recurrent or refractory CDI, compared to only 20-30% cure rates from antimicrobials (J.-W. Wang et al., 2019). CDI is currently the only disease for which FMT is officially classified as a treatment. However, there has been a recent, rapid acceleration in the number of indications being explored for microbiome treatment. Scientists have also looked beyond FMT to increasingly specific solutions, greatly broadening the horizon of therapeutic applications of the microbiome.
Recent developments in microbiome dysbiosis treatment have focused on refining the delivered bacterial consortia and minimizing the risk from transferring entire microbial environments, which is a potential downside of FMT. For example, a defined consortium of ten bacterial isolates has been used to treat recurrent C. difficile-infected patients and provided comparable efficiency to FMT (Collins and Auchtung, 2018). Such defined consortia are cocktails of bacteria manufactured from purified samples, reducing the risk of donor contamination and matching the bacterial colonies to a patient’s specific disease. Several companies are investigating defined microbial consortia as potential therapeutics. Finch therapeutics uses ML to reverse-engineer successful fecal transplantations and other clinical datasets, identifying the microbes that drive responses in patients. This human-centric discovery model leverages clinical data to focus on in-vitro and in-vivo efforts on cocktails of microbes that have already demonstrated safety and efficacy in humans. They have a diverse and growing pipeline that includes product candidates targeting gastrointestinal diseases, such as recurrent CDI and inflammatory bowel disease, as well as product candidates aimed at conditions that go beyond the gut, such as autism spectrum disorder and chronic hepatitis B.
Sterile fecal filtrates, in comparison, remove the actual living bacteria from a sample and transfer only filtrates—including bacterial debris, proteins, antimicrobial compounds, metabolic products, and oligonucleotides—to stimulate readjustment of the gut microbiome (Ott et al., 2017). These methods reduce the risk of transferring live microorganisms from healthy donors.
In an effort to avoid similar risks, Seres Therapeutics employs rigorous purification processes to isolate the desired subset of species while weeding out pathogens and contaminants. But many are instead focusing on live therapeutics assembled from hand-picked, experimentally defined consortia of cultured microorganisms. Finch’s newer programs have shifted in this direction, and this is the strategy being employed at Vedanta and Microbiotica.
Vedanta isolates specific bacterial strains that have a specific biological effect on the microbiome that would restore balance to this internal ecosystem. The company has about a dozen patents related to its bacterial-based therapies. Its leading candidate is VE303 (is a live biotherapeutic product containing 8 clonal human commensal bacterial strains manufactured under GMP conditions), is orally administered (ClinicalTrials.gov Identifier: NCT03788434) and consists of live bacteria designed to restore gut balance and provide resistance against gut pathogens, including C. difficile.
RebiotiX, a Ferring Company, is a pioneer with its microbiota-based MRT™ drug platform, which has the potential to change the way challenging diseases are treated. Lead MRT™ drug platform product, RBX2660 is targeted at treating recurrent CDI. They are leveraging other conditions that result from disruption of the gut microbiota.
Beyond CDI, companies are exploring microbiome treatments for a range of conditions in the gut that are attributed to autoimmune disease. One critical role attributed to the gut microbiota is modulating and shaping immune responses, which is achieved by a variety of mechanisms. Among these are: the activation of the xenobiotic sensor PXR (Venkatesh, 2014) through indole metabolites exclusively produced by gut microbes; the activation of signaling receptors GPR41 and GPR43 by bacterial short chain fatty acids (SCFAs) (Ang, 2016); and the reduction in the levels of bile acids antagonizing the anti-inflammatory receptor FXR (Sayin, 2013).
Other gut conditions that are candidates for microbiome-based therapeutics include irritable bowel syndrome, Crohn’s disease, and ulcerative colitis, with technological approaches ranging from full-spectrum transfers to rationallyselected microbial consortia.
A nascent but rapidly accelerating field is the delivery of probiotics in conjunction with immuno-oncology to improve patient response like Microbiotica’s Live Bacterial Therapeutic, MB097, in development to begin clinical trials in 2022 in immuno-oncology. MB097 is a consortium of bacteria at the core of the microbiome signature predictive of patient response to immune checkpoint inhibitor therapy.
Data show potent anti-tumor efficacy in vivo and in vitro. MB097 is the first microbiome precision medicine in immuno-oncology, clinically designed in the same patient cohort in which it will be tested. Microbiotica’s platform comprises the world’s leading Reference Genome Database and Culture Collection of gut bacteria, and an unrivalled capability to culture and characterize all gut bacteria from patients at scale. This is complemented by a suite of bioinformatic and machine learning tools that enable the identification of previously undetectable gut bacterial signatures linked to patient phenotype. The company also has capabilities to develop and take such products to the clinic.
The majority of investigations in this area involve immune checkpoint inhibitors, but a more recent investigation has also demonstrated that tumor-resident intestinal bacteria can migrate to the liver following impairment of the gut-vascular barrier, creating a metastatic niche in the liver which is needed to generate metastasis (Bertocchi, 2021). Drugs specifically targeting tumor microbial signatures are in development.
There is increasing evidence of the connection between the gut and the brain, indicating that the effect of the microbiome extends far beyond the area where most bacteria reside within the human body. If the microbiome can really influence the brain, this raises intriguing questions, as well as opportunities for treatment of diseases such as Parkinson’s and disorders such as autism (Willyard, 2021). Kallyope, which closed a $112 million Series C funding round in March 2020, states “defects in the gut-brain axis have been linked to diseases including obesity, diabetes, NASH, functional gastrointestinal disorders, inflammatory disorders, depression, autism, and Parkinson's disease,” demonstrating the breadth of neurological applications for future microbiome therapeutics. 3.2 Opportunities for Microbiome Research in Biopharma/Drug Metabolism
In drug discovery, as well as for many established drugs, an important aspect of microbiomics is its consideration as a pharmacodynamic biomarker, raising the question “what are the effects of pharmacological, surgical and other interventions on the disease microbiome and health outcomes?” (Galyean, 2020).
A recent study on the general population showed that multiple drugs are associated with an altered gut microbiome composition (Jackson et al, 2018), while in vitro analysis of marketed drugs has shown that numerous non-antibiotic drugs can inhibit the growth of gut bacteria (Maier et al, 2018). Moreover, gut microbes play an active role in drug metabolism (Figure 3), digesting and transforming drugs. They can therefore influence the pharmacokinetics and pharmacodynamics of drugs in idiosyncratic ways (Zimmermann, 2019).
Figure 3 - Microbiome and drug metabolism The microbiome has a role to play in not just living therapeutics and accompanying probiotics, but drug delivery and ingredient manufacturing, as well. The future of therapeutic development will rely heavily on principles of nature co-design to target the “undruggable,” and improve existing therapies. Just as in other industries, the pharmaceutical supply chain has the potential to be transformed by the introduction of bioprocessing for chemical ingredients and microbial factories. 3.3 Engineering Microbiome Therapeutics
The next phase of microbiome therapeutics emphasizes not only optimizing existing bacterial systems to improve microbial environments but also engineering bacterial therapeutics to confer functions not naturally available (Charbonneau et al., 2020). The fundamental tools for microbial design are synthetic circuits that use basic DNA and RNA as building blocks (Riglar and Silver, 2018). Landry and Tabor (2017) describe these genetic circuits as “networks of interacting regulatory molecules, such as transcription factors and their target promoters, that perform computations such as multi-input logic or memory.” These circuits regulate actuator genes, which control cell behavior and the state of its environment. This “bottom up” engineering enables manufacturing of strains that enhance native processes, such as the assimilation of ammonia into amino acids at an increased rate, or non-native processes, such as producing effectors of human proteins (Charbonneau et al., 2020).
Manufactured microbes also allow for significantly increased specificity of delivery, including robust chassis design, “sense and control” gene expression that utilize logic circuits to control microbe activity, “memory” devices—typically toggle switches and serine integrases—which monitor the diagnosis or ongoing diseases status of a patient and enable longer-term response, and production and delivery, in which the engineered cell produces antimicrobial peptides upon reaching its intended destination (Pedrolli et al., 2019). The benefits of these highly controlled systems are multi-fold: bacteria can specifically deliver drugs to the gut that would otherwise be degraded in the bloodstream; localized delivery and colonization reduce systemic exposure; required dose of the compound is lower, because compounds are produced in situ; and production costs are significantly reduced as the therapeutic is produced directly in the human body (Pedrolli et al., 2019; Riglar and Silver, 2018).
While recombinant microorganisms have been generated for specific function or to produce some molecules, their productivity rarely reaches sufficient levels. One key barrier is metabolic burden. The synergistic combination of metabolic burden and cell stress leads to a deep drop in microbial biosynthetic performance, termed the “metabolic cliff”. When the host hovers at the edge of this cliff, even small growth/stress perturbations can cause undesired metabolic responses and loss of production yields. To minimize such problems, Division of Labor (DoL) using microbial consortia becomes an alternative strategy. Drawing inspiration from natural systems may provide one or more routes to circumvent this metabolic cliff. Eventually, entire microbial consortia may be engineered rather than single cells, leading to much wider potential applications. Network science will play a critical role identifying and designing these circuits and consortia.
These consortia can be used as live biotherapeutics for the production of molecules in the host or outside the host. When these consortia are used in the host, many factors such as host age, sex, and health, food, cross-feeding, microbiome function, and the environment need to be considered. Studying and analyzing the simultaneous effect of such multiple factors in a holistic manner is at the core of a multicausal approach which takes into consideration the vast number and types of data generated, including those available from multi-omics studies.
Network science is the key to decode theses pathways and relations for designing the functional consortia. Most of the companies today are using a top-down approach for the discovery of appropriate strains, which is time consuming and laborious. The bottom-up approach, on the other hand, takes the factors mentioned above into consideration, making it more precise, more highly targeted and less time consuming. Making the most out of the existing tools and knowledge requires integrating the multi-omics data with the application of system biology and network science. When it comes to microbiome-based therapeutics (general or personalized consortia) developers cannot rely on a limited set of data and parameters but must integrate all the existing knowledge from longitudinal data sets with appropriate mathematical calculations/statistics/predictions of perturbations/feed design for the consortia/successful engraftment. 3.4 Microbiome in Food, Nutrition and Wellness
Microbiomes constitute essential components of our bodies with roles co-evolved over millennia. Estimates of the number of bacterial cells in the human body suggest a staggering total of 3.8 x 1013 bacteria present in a 70 kg (about 154 pounds) human (Sender, 2016). Even organ environments previously thought to be devoid of bacteria, like the alveolar space in the lung, have been found to carry specific components of the microbiome, particularly when diseased (Wang, 2020;Paudel, 2020). Therefore, it should not be surprising that microbes can influence holistic body systems, including our metabolism, physiology, immune response and even our circadian clock (Brooks, 2020).
Considering the beneficial effect of microbiota in health, it seems obvious that its appropriate maintenance can be critical for preventing disease. Outside of healthcare, food has received the greatest amount of microbiome research in the area of pre- and pro-biotics, as well as the growing trend of personalized nutrition based on individual gut microbiome profiles. Some next-generation foods, such as plant-based alternative proteins and lab grown meats, have taken advantage of microbial systems to create and process food that is both healthier for humans and for the planet. However, generally healthy habits such as regular exercise and adequate diet may have a positive influence on gut flora on their own. The influence of nutrition and the impact of an appropriate diet on microbiota have been studied in the last decade and will be discussed later, but the impact of exercise on microbiota is an area of more recent research.
Pioneering studies showed differences in the composition of the gut flora for athletes with respect to that of the sedentary population, with the former being richer in carbohydrate and amino acid metabolizing species as well as in SCFA (mainly butyrate) producing species (Barton, 2018; Clarke, 2014;Velly, 2017). Likewise, studies performed with animals have demonstrated that exercise increases the levels of butyrate-producing microorganisms (Evans, 2014). On the other hand, it has been postulated that disproportionate exercise levels leading to exhaustion may induce dysbiosis that ultimately causes sarcopenia through a number of mechanisms, including the increased absorption of bacterial toxins due to an impaired mucosa (Cerda, 2016).
Although the former studies were cross-sectional, several longitudinal studies have also been conducted, demonstrating that the effects of exercise on microbiota composition are transient and reversible, and highly dependent on body mass index. For example, lean individuals have been shown to experience different changes compared to obese individuals, with the microbiome of the former being more responsive to exercise than that of the latter (Barton, 2018).
Fitbiomics, a start-up company launched by Wyss Institute, is mining the biology of the most fit people in the world and translating that information to consumer products and products aimed at promoting wellness. A proof-of-concept study was published in Nature Medicine showing that a specific bacterial strain of Veillonella bacteria, V. atypica, was amplified in the gut microbiomes of 2015 Boston Marathon runners after the race (Jonathan Scheiman et al 2019). The same strain, when given to mice, enhanced the animals' running performance on a treadmill by 13 percent. A key finding of the team’s foundational study that identified Veillonella atypica, was the bacterium’s ability to respond to the increased lactate levels produced during long-distance running. After sensing lactate, the Veillonellabacterial population expands in the intestinal lumen and synthesizes a metabolite known as propionate, a short-chain fatty acid that enters the blood circulation, is transported to various tissues, and exhibits performance-enhancing effects that remain to be further defined on the molecular and cellular level. Identifying such bacterial species that actively enhance specific physiologies, could help build a powerful collection of probiotic and nutritional strategies that may not only improve athletic performances but also general health.
Despite the overall beneficial effects, it seems that the specific effects of exercise on the microbiota can be idiosyncratic, so more studies are needed to understand the role played by the gut flora. These studies are hampered by the influence from numerous factors such as diet, age, gender, body mass index and, in the case of animal studies, the modality of exercise performed (Mailing, 2019). Teasing out causality from among these many factors calls for the use of more advanced data management, analysis, and Design of Experimentation (DoE) tools in order to discern their individual contributions to the observed outcomes. Such analysis will generate a dataset that, in addition to being vast, will be complex and multifactorial (Figure 4).
Figure 4 – Microbiome and exercise Gut microbiota is strongly influenced by the type of food consumed as well which, in turn, dictates the metabolites produced by an individual’s mix of intestinal microorganisms. Macro and micronutrients, prebiotics, probiotics, postbiotics, additives, and other minor components (including contaminants) contribute to shaping individuals’ intestinal flora, hence the beneficial or detrimental effects of their primary and secondary metabolism. However, the contribution of each dietary component remains unclear, although some progress has been achieved in recent years.
There is increasing evidence indicating that a plant-based, fiber-rich diet promotes the abundance of bacterial species producing SCFAs like butyrate or propionate that not only provide beneficial effects for the host (such as nourishment of gut epithelial cells or acting as signaling molecules in anti-inflammatory cascades (Maslowski, 2009) but also serve as fuel for other bacteria (Cockburn, 2016). Therefore, fiber intake favors the idiosyncratic structure of gut microbiota.
Regarding protein ingestion, data collected from studies performed with rodents suggest that high intake of red meat protein leads to increased levels of trimethylamine-N-oxide, a molecule related to higher risk of atherosclerosis and obesity, with a high presence of the genus Prevotella in the flora (Koeth, 2013). In contrast, consumption of plant and seafood proteins is less obesogenic, and is correlated with changes in the relative abundance of bacteria from the Bacteroidales and Costridiales genera (Danneskiold-Samsoe, 2019). The role of lipids in shaping the gut microbiota is controversial, but mouse-based studies suggest that interaction with microbiota is highly dependent on the lipid origin (whether animal or vegetable) and this interaction impacts differently on disorders like obesity, adipose tissue inflammation, and colitis (Caesar, 2015). Likewise, the composition of dietary fat influences the microbiota profile though it is unclear which factors (fatty acids composition, viscosity, saturation levels of fatty acid chains, bile acids presence) contribute the most. The consumption of prebiotics, mainly fructooligosaccharides (FOS) or galactooligosaccharides (GOS), and of polyphenols such as those present in fruit and vegetables also influence microbiota composition and have a different impact on various areas of the gastrointestinal tract (Terpend, 2013). Prebiotics are known to promote Bifidobacterium and Lactobacillus spp. and indeed GOS helps digestion of dairy products in lactose-intolerant individuals (Azcarate-Peril, 2017). Polyphenols are metabolized by gut microbiota to yield products with antioxidant, anti-inflammatory, anti-cancer, and anti-diabetes properties, and they also promote the proliferation of bacterial species with beneficial effects for the host (TomasBarberan, 2016).
The inclusion of probiotics and postbiotics in the diet has also received increasing attention in recent years, and some biotics are being studied in ongoing clinical trials (summarized in (Markowiak, 2017)). The most frequently used probiotics are bacteria of the genera Lactobacillus, Bifidobacterium, Streptococcus and Enterococcus as well as yeasts of the Saccharomyces genus (Zolkiewicz, 2020).
The available data points to a clear influence of diet on the composition of the host’s microbiota, but also suggest that microbiota modulates host physiology by metabolizing food ingredients and producing metabolites endowed with beneficial or detrimental properties. It is remarkable that such metabolites can also fuel or inhibit the proliferation of other microbial species, further shaping the host microbiota. This complex interplay needs deeper study - stressing the need for suitable informatics tools capable of mining and exploiting the vast information already available and that is expected to come.
Many big enterprises and start-ups are coming up with supplements for the healthy microbiome. Companies such as ISOThrive develop products to modulate the gut microbiome. ISOThrive produces prebiotics (nondigestible carbohydrates that act as food for probiotics) intended to promote digestive health.
To better understand the best ways of nourishing our gut, scientists from Danone Nutricia Research and the Center for Microbiome Innovation (CMI) at the University of California San Diego decided to team up with citizen scientists around the world. The Human Diets & Microbiome Initiative (THDMI) – largest international microbiome citizen science program –aims to discover the best diets and foods on the planet that can nourish our guts, by using the latest sequencing technology. Danone North America, White Plains, NY, a business unit of Danone SA, Paris, is funding a study currently underway at Rutgers University, New Brunswick, NJ, that explores the potential connection between the microbiome and COVID-19. The company’s portfolio of dairy- and plant-based fermented foods is at the core of its health strategy.
Researchers at Nestle have studied the gut microbiome for several years, looking at its composition during different life stages in both people and pets. Studies have also focused on human milk oligosaccharides, a major component of breast milk, that has been shown to influence early microbiome and immune system development. The findings were used to launch new infant formulas. Nestle Purina launched a probiotic-based supplement called Calming Care, which helps manage anxious behavior in dogs. The company is investing in the next generation of personalized nutritional solutions adapted to the individual’s microbiome.
Mark Piper, Fonterra’s Director of Group Research and Development says Fonterra, a publicly-traded dairy co-operative and the largest company in New Zealand, has proven success when it comes to probiotics and is partnering with the Universities to further understand their benefits. To date, their product, LactoB 001 (DR20TM), has been clinically proven to help treat children’s eczema, and also given some indications that it can reduce post-natal depression by 50% and gestational diabetes by 68%.” Another probiotic strain BifidoB 019 (DR10TM) can be found commercially in Symbio yogurt and Anmum. Given its proven benefits, many companies also use this strain in their food and beverage products. Everybody has a unique gut make up, so how one person reacts to a certain strain of probiotics could be quite different to how another person reacts. This makes studying the effects of these bacteria challenging.
The growing trend is for microbiome-based solutions to move towards increased precision. The term “precision microbiomics” has been coined (Mills, 2019) to define the use of the gut microbiome as a biomarker capable of predicting the effect of dietary components in a given host. It is also amenable to being used in the design of personalized diet and targeted interventions aimed at preserving and restoring overall health. Such personalized diets may include compounds known to be precursors of beneficial bacterial metabolites (e.g. tryptophan) and also exclude precursors of toxic ones (e.g. L-carnitine, choline or phenylalanine) (Kolodziejczyk, 2019) depending on the host microbiome. It can be used as auxiliary therapy in medicine, as a means of prophylaxis for individuals at risk of certain diseases, or as a tool to maximize performance e.g., of elite athletes.
There are encouraging precedents on the use of machine learning (ML) approaches to exploit microbiome information with beneficial nutritional purposes. In pioneering work, a randomized controlled trial conducted in Israel (Zeevi, 2015) and further reproduced in the US (Mendes-Soares, 2019) demonstrated that the appropriate use of microbiome data accurately predicts personalized glycemic response using ML techniques. This study has been followed by others. In 2017 Korem et. al. demonstrated that microbiome data can accurately predict the glycemic response of a given individual to the consumption of industrial white bread or artisanal whole-grain bread, therefore helping to select the best one in each case (Korem, 2017). In 2020, Berry et al. (Berry, 2020) used the data obtained in a study involving 1200 volunteers to build a ML model capable of predicting the glycemic and triglyceride responses to food intake. Likewise, Wu and coworkers (Wu, 2020) demonstrated that insulin resistance was associated with microbiota composition. Notably, in this latter study the use of ML helped to avoid the confounding effect of Metformin on the outcome, a fact known to influence microbiota composition and therefore potentially interfere with the analysis (Forslund, 2015). These are just a few examples demonstrating the value of ML approaches to microbiome data exploration for health and nutritional purposes, as well as strengthening the need for suitable tools to properly collect, catalog, and interrogate this complex information.
These studies are proof that there is no right diet for everyone. It is highly likely that the best diet is slightly different for everyone, depending on a combination of DNA, lifestyles, and the microbes living in our guts. The science of how we each individually process and respond to food is only now gaining real momentum, with the outputs being commercialized fairly rapidly. Companies like Zoe, Viome and Day Two, prescribe consumers which foods they should eat and which foods to avoid based on individual gut microbiota profiles. A personalized diet aims to steer the customer toward foods that encourage the right mix given their unique microbiome. However, at this point, these personalized diets on the market are focused on aspects of health and/or gut health and do not always provide an overarching view, for example incorporating additional claims associated with the field of nutrigenomics. Being able to tap into deeper insights provided by studying multi-dimensional data should accelerate the field and contribute to the further advancement of these therapies. 3.5 Microbiome in Dermatology, Cosmetics and Personal Care
Dermatology is one of the potential applications of advanced microbiome technology being intensively explored, applicable to two related but different markets: therapeutics and cosmetics. The skin microbiota plays a pivotal role in protecting against the infection of pathogenic microorganisms, and the number of microorganisms and their diversity varies largely between the three main skin regions: sebaceous (head, neck and trunk), wet (e.g. nare, axillary vault, popliteal fossa) and dry sites (dry forearms and legs) (Cundell, 2018; Byrd, 2018). Likewise, skin microbiota span through the different skin layers, including dermis, epidermis, adipose tissue and follicles, with notable differences in microbial composition across the layers (Nakatsuji, 2013).
Investigations on the role of skin microbiota are still in their infancy. Nonetheless, there is evidence suggesting the role of dysbiosis in promoting dermatological diseases like acne (associated with colonization of the skin by Propionibacterium acnes) and atopic dermatitis (associated with an imbalanced expansion of Staphylococcus aureus during flares, concomitant to a decrease in bacterial diversity) (Vollmer, 2018). Consequently, interventions aimed at restoring skin eubiosis are being pursued for such conditions as well as for chronic wound healing (e.g. diabetic foot ulcers) and psoriasis (Puebla-Barragan, 2021). The therapeutic approaches currently being investigated usually involve the use of probiotics like Staphylococcus epidermidis and Staphylococcus hominis for atopic dermatitis (Nakatsuji, 2017) and prebiotics like sucrose as a selective fermentation initiator improving the proliferation of Staphylocuccus epidermidis, hence impairing that of P. acnes, for acne (Wang, 2016).
The positive perspectives of using microbiome data for skin health have also propelled its use for cosmetics. The facial care segment in skincare is expected to witness the highest CAGR of 18.48% during the forecast period 2020-2030, and current forecasts indicate that the market for probiotic cosmetics specifically will grow at a 12% CAGR in the same decade. As of 2021, at least 50 types of cosmetics are being sold in the US with a claim to include probiotics: creams and sera are the most common products, but soap bars and deodorants are also included. L'Oreal S.A. currently commands the largest share of the global skin microbiome modulators market. However, a detailed examination of their components show that these products do not actually include probiotics but rather postbiotics (substances released by or produced through the metabolic activity of a microorganism, exerting a beneficial effect on the host). These can be of unproven efficacy given the lack of controlled studies endorsing their activity in restoring skin microbiota equilibrium (Puebla-Barragan, 2021).
A significant driver of innovation in this space is start-ups backed up by dominant large enterprises. Royal DSM, a global science-based company active in health, nutrition and materials, announced a collaboration and commercialization agreement with S-Biomedic. The collaboration aims to bring to market a new probiotic technology-based skin care active for the treatment of acne. DSM will be S-Biomedic’s world-wide exclusive manufacturing and go-to-market partner for this activity and plans to start commercialization of the new technology. S-Biomedic is a Belgium-based life science company working with live bacteria, exploring the unexploited cosmetic and therapeutic potential of the skin microbiome. S-Biomedic has also developed a lead program focusing on acne, where pharmaceutical applications often have severe side effects. But the possibility of restoring the microbiome in cases where it is severely diminished is promising. Simultaneously, two early-stage concept development programs have been initiated focusing on ageing and dandruff. In addition to cosmetic approaches, skin microbiota properties are also being explored for hygienic products for female personal hygiene and oral hygiene. In this regard, the toothpaste Zendium™, manufactured by Unilever, is a toothpaste designed to nurture the mouth, support a healthy microbiome and boost immune system. The ingredients are enzymes (amyloglucosidase, glucose oxidase, lactoperoxidase) to promote beneficial oral bacteria and proteins (from colostrum, lactoferrin and lysozyme) support oral immunity, and ward off dysbiotic species. Statistical analysis showed a significant increase in 12 taxa associated with gum health including Neisseria spp. and a significant decrease in 10 taxa associated with periodontal disease including Treponema spp. (Adams, 2017). Ingredient manufacturers are also following this trend. Givaudan, markets Bucovia™ as a natural bio-guided fractionated active with anti-biofilm properties against mixed fungal-bacterial biofilm. The active is said to balance the oral microbiota against opportunistic pathogens and have no biocidal activity. Their research into the Solidago virgaurea (European Goldenrod) plant extract has reported a reduction in total bacterial load, in particular species Streptococcus mutans and Candida albicans.
As explained above, the claims made by some manufacturers regarding the healthy effect of their dermatology products on microbiome have yet to be demonstrated by confirmatory studies, so there is an excellent opportunity in market positioning for companies prepared to undertake them. It is expected that some form of regulation will eventually emerge, with the establishment of specific requirements to demonstrate the presence of pre-, pro- or postbiotics and their alleged positive effects. Banning the use of such terms and claims in products failing to comply with those requirements is therefore also to be expected. In designing and interpreting these studies, companies will need to leverage appropriate informatics tools to properly mine the complex skin microbiome data.
Figure 5 – Microbiome in dermatology: the need for tools to understand complex relationships 3.6 Microbiomes in Agriculture and Soil Management
The increased evidence of the effect of human microbiota in health has led to a growing interest in learning about its origins and evolution. Genetics play a minor role in shaping the gut microbiome, with interaction with the environment being the major player in dictating that shape, and soil playing a prominent role. The influence of soil in gut microbe populations comes in different ways including direct contact, especially during early childhood, to indirect interaction through agriculture and the intake of soil-grown food. It follows that soil biodiversity clearly affects gut flora richness and ultimately human health.
Several factors, including the modern Western lifestyle and diet as well as and the deleterious negative impact of climate change, are clearly impacting and affecting soil biodiversity (Blum, 2019). Modern agricultural techniques, with the use of pesticides, hormones, and other agrochemicals as well industrial practices like the intensive use of soil for monoculture cropping, are contributing to this loss of diversity. In addition, the evolution from manual to mechanized agriculture has minimized the once intense contact of humans with soil, thus reducing the opportunities to interact with its microbial content. Evidence supporting this notion comes from recent analyses of coprolites from archeological sites in America (Tito, 2012) demonstrating that the microbiota of our ancestors, living in closer contact with nature and practicing primitive agriculture techniques, was more diverse than that of the current population. Ancient microbiota is closer to that of rural areas than to that in urban environments. Moreover, the deleterious impact on microbial diversity caused by transitioning from traditional to industrialized farming practices was illustrated by a comparative study between Amish and Hutterite communities (the former practicing traditional farming while the latter used the industrialized modality). This comparison showed that the microbiome of Amish individuals was more diverse than that of Hutterites. Most intriguingly, Amish and their children were less likely to develop autoimmune diseases, particularly asthma. This finding was corroborated by in vivostudies in a mouse model with intranasal instillation of dust extracts from homes of both communities (Stein, 2016).
To these circumstances must be added the displacement of human populations from rural areas to modern, urban environments, where the soil is less rich in microbial diversity. Altogether this is leading to a decreased microbiome alpha diversity (the one measured within each individual) concomitant to an increased beta diversity (measured between individuals) (Martinez, 2015). Likewise, horizontal gene transfer occurs more frequently in the microbiome of urban populations, suggesting that gut bacteria continuously acquire new functionality based on host lifestyle (Groussin, 2021).
These facts pose a long-term challenge to human health. Consequently, there is a growing interest in understanding the best way to manipulate and manage soil microbiomes to increase their richness and prevent further damage. Some trends in this direction include the addition of specific microorganisms to enrich the soil in damaged areas (e.g. symbionts like arbuscular mycorrhizal fungi; Rillig, 2018), the management of soil to promote the growth of beneficial microbes (e.g. by introducing probiotics; Adam, 2016) and the utilization of other microbes as bioindicators of soil condition (Fierer, 2017).
Very recently, researchers investigating groundwater, sediments, and wetland soil have discovered a new type of archaeal extrachromosomal element that they have termed “Borgs” (Al-Shayeb, 2021; preprint, not certified by peer-reviewed at the time of preparing this document). Although their origin is enigmatic (it is unknown whether they are or not archaeal viruses, or plasmids or minichromosomes), they seem to occur in association with (but not being part of) the genome of the methanotrophic Methanoperedens archaea. These Borg genes expand archaea redox and respiratory capacity, archaea ability to respond to changing environmental conditions, and likely augment archaea capacity for methane oxidation. Analysis of these Borgs have identified genes encoding proteins that may scavenge toxic NO, hydroxylamine and other byproducts from nitrate metabolism that are responsible for nitrosative stress. Likewise, other proteins encoded by Borg genes may protect from reactive oxidative species while others may increase osmotic stress tolerance by favoring the synthesis of osmolytes like β-glutamate or N-acetyl-β-lysine. These interesting discoveries may be exploited to endow soil microorganisms with tools to prevent and defend from their damage.
In recent years, a large body of research has highlighted the role of the microbiome in shaping the environmental microbes we live in and around. For instance, microbes in the soil govern crucial factors such as nutrient uptake and soil composition. Agritech startups are employing microbiome analysis to better understand the microbial communities in different soils. Companies such as Microbiome Insights – Microbial Community Analysis, Pattern, Ag – Pathogen Detection, Microomics – Functional Prebiotics, Growcentia – Agricultural Biologicals, BiomCare – Soil Health are developing the field using microbiomebased solutions for soil health and agriculture.
The Indigo team spent two years building a database on the microbiome of the most popular row crops. It compared what it found in heritage plants, and those raised through traditional agriculture, to those raised with modern tools like pesticides, fungicides, and herbicides. Ultimately, the company says it collected data on over 40,000 symbiotic microbes from 36,000 samples of more than 700 plant species. It then used machine learning techniques to identify important microbes that are less common in modern agriculture. The company claims to have grown crops within these "renewed" microbiomes over four plantings and achieved yields 10 percent higher than comparable seeds.
Another player, AgBiome discovers and develops innovative biological and trait products for crop protection. Their proprietary GENESIS™ discovery platform efficiently captures diverse, unique microbes for agriculturally relevant applications, and screens them with industry-best assays for insect, disease, and nematode control. Through its commercial subsidiaries, AgBiome develops and sells proprietary crop protection solutions.
However, it must be emphasized that the adaptability and positive influence of a microbial community on soil are highly context-dependent, the context being defined by soil abiotic factors like pH, nitrogen availability, organic carbon content, redox status, and humidity degree. It is therefore naive to consider a universal solution: microorganisms that can be beneficial in a geographical area with a given context can be detrimental in a different zone that has a very different context (Huttenhower, 2012).
Again, customized approaches must be undertaken in a similar way to personalized medicine. Such a strategy demands using and mining soil microbiome data avoiding simple metrics in a complex multidimensional approach (Shade, 2017) that should incorporate parameters like geographical area (specially discerning between areas of intensive and non-intensive cultures), the kind of soil being studied (bulk soil versus rhizosphere and for the latter which plant is defining the rhizosphere), and other relevant aspects. Ultimately, the concept of “precision microbiome” will become as prevalent as personalized medicine and require a similar level of understanding of geography and biodiversity.
Figure 6 - Microbiome Related to Soils and Healthy Food Production (from Hirt, 2020) The impact of climate change on soil microbiome is another subject of intense investigation. Higher CO2levels, thawing of permafrost soils in the Artic, increased temperatures, drought in some areas, combined with an increased frequency of precipitations and floods in others and increased fire frequencies and intensities, are different aspects of climate change that are negatively affecting the microbial composition of soil (Jansson, 2020).
The soil’s relationship with climate change is cyclical. Just as soil microbiomes are devastated by climate change, so too they may be a key to reversing it. Several approaches have been proposed to minimize or counteract the impact of climate change and many of them consist in harnessing soil microbes. To cite the most relevant ones: exploiting microorganisms’ capabilities to sequester carbon; utilizing their ability to promote growth of plants under extreme conditions like drought; managing cattle microbiome to reduce methane emissions (explained later) or promoting the metabolic activity of metanotrophs in the Artic (Hutchins, 2019). Microbiome engineering could be used to modify and promote positive interactions between microorganisms and plants, mimicking those of plants growing under strong selective pressure due to their native extreme stress conditions. This work is currently under development (Rodriguez, 2020).
Properly informed sustainability and environmental policies demand deeper study of the soil microbiome utilizing adequate informatics tools to handle and mine the large amount of data teasing out the relevant driving factors.
Figure 7 - The cyclic interplay between soil and climate change as an opportunity for sustainability 3.7 Microbiomes in Aquaculture and Animal Health & Nutrition
Not least important from a nutritional perspective is considering how modern farming techniques affect the quality of the food we eat. The negative consequences of overexploitation of wild fish catches driven by the growing demand for fish protein has propelled the development of aquaculture in the last decades. The worldwide production of fish farms has evolved from 29 metric tons of fish and shellfish in 1997 to more than 80 Mt in 2017, with more than 400 different species now being cultivated (Naylor, 2021). This continuous increase in production poses challenges, some of the most notorious being the need to find alternatives to the use of wild fish in aquafeed formulations and the control of pests, parasites, and plagues. This latter is being dealt with in several ways, with the use of antimicrobials being one of the most common approaches. However, the indiscriminate or improper use of these substances may lead to serious issues such as the emergence and transfer of antibiotics-resistance genes and bacteria (Cabello, 2013).
Like the human microbiome, there is a wide consensus that the fish microbiome influences the health status of the animals and vice versa. Moreover, studies in zebrafish (reviewed in (Wang, 2018) have demonstrated that fish microbiota play a critical role in fish primary immune response and therefore the use of prebiotics (Hoseinifar, 2015) and probiotics (Zorriehzahra, 2016) to help immune system function in aquaculture is being developed as an alternative to the use of antibiotics. Likewise, the aquaculture microbiome (i.e., the diversity of genes corresponding to microbiota present in water) is receiving increased attention since it is an area of intervention that could improve the performance of modern aquaculture (Dittmann, 2017). Indeed, a variety of commercial products including a diversity of bacterial species has been launched in recent years with the aim of promoting and controlling the growth of beneficial microbial species capable of removing and transforming detrimental products (ammonia, hydrogen sulfide, nitrites) as well as of preventing the growth of pathogens.
Therefore, the availability of suitable tools to monitor and control both fish and aquaculture microbiome is imperative not only to understand and interpret the health status of the cultured fish but also to manage fish conditions with the aim of producing animals resembling as much as possible the features of the wild species from the sea.
Investigations on cattle microbiome are also being conducted, with a critical emphasis on improving feed efficiency and reducing the environmental footprint, particularly methane emission from rumen and low gut and nitric oxide from manure (Lynch, 2019). The issues of methane production include its negative environmental impact (with methane contribution to global warmth being 28-fold that of carbon dioxide) but also its contribution to inefficient animal feed since enteric methanogenesis causes 2-12% loss of gross dietary energy (Johnson, 1995).
Several approaches are being explored to reduce methane production, most of them aimed at inhibiting the methyl coenzyme-M reductase (MCR) enzyme by products such as 3-nitroproxypropanol or bromoethanesulfonate. But these options have a transient effect and are probably impractical in the long run. An ideal solution would require intervention on the animal microbiome (Yanez-Ruiz, 2015) to achieve microbial programming of the rumen microbiota through dietary intervention during the early days or weeks of life of the animal. Interestingly, some of the recently discovered Borgs (mentioned in the previous section) encode MCR, hence demonstrating that MCR can exist as an extrachrosmosomal element and this might be exploited for the rumen microbiota to neutralize methane emissions from cattle via the reverse methanogenesis pathway, a mechanism typically exploited by anaerobic metanotrophic archaea to consume methane (Xu, 2018).
In addition to that, the extensive use of antibiotics in massive cattle farms has raised the prevalence of antimicrobial resistance as demonstrated by studies in low and middle-income countries where meat consumption is high (Van Boeckel, 2019). As in the case of aquaculture, this fact demonstrates the need for alternative techniques and practices along with a detailed monitoring of the cattle microbiome.
Figure 8 – Microbiome and livestock Metagenomic studies on animals' microbiome are expanding from cattle (Stewart, 2019) to other species and their animal husbandry practices, including poultry (Gilroy, 2021) swine (Bergamaschi, 2020), and equine (Morrison, 2018;Kauter, 2019). These analyses are intended to help understand how different factors like age, obesity, fat composition and/or life conditions affect the evolution of their intestinal flora with the ultimate goal of improving the health conditions and increasing the quality of the food they produce. The end goal is to sustainably provide better healthier food for consumers. This highlights the need for appropriate informatic tools to analyze the wide array of data being generated, which can dissect the influence of the multitude of factors being considered.
Many companies are providing microbiome-based products for the healthy livestock. With Live Biotherapeutics, Boehringer Ingelheim develops novel tools and solutions by harnessing the power of the microbiome. For both livestock and companion animals, these types of products will enable us to tackle specific diseases in a completely new way.
Similarly, Cargill will use Eagle Genomics’ e[datascientist]™ platform to digitally transform microbiome and life sciences research and development across their global locations. By revealing relationships between microbiome data entities using relevant multi-omics data, the platform will “further enable Cargill to advance the understanding of the complex association between the microbiome and digestive and immune health in humans and animals,” according to Mike Johnson, Marketing Director of Cargill Health Technologies. In the same vein, DuPont acquired Danisco, which by then was an established leader in the human probiotics market and had also developed and marketed some directfed microbials (probiotics for livestock). DuPont places a lot of emphasis on understanding the mechanism of action of a given strain as well as identifying relevant functional pathways. Doing so allows DuPont to focus on restoring the missing functions or fueling the relevant functional pathways within a given microbial ecosystem to maximize efficacy. Critically, they aim to develop not only new microbes but also molecules like prebiotics or postbiotics that only help “friendly” microbial species (helping detrimental bacterial species also grow defeats the purpose, after all). This approach is used successfully in human and animal health to develop superior ingredients modulating the microbiota and is how DuPont applies today’s Enteromix® health and nutrition science platform to screen in vitro models before moving to clinicals. 4. Observed Challenges Microbiome and Multi-Omics Data Management and Analysis
Putting complex microbiome data to work, analyzing it in context with equally large and complex multi-omics data sets in search of promising intervention opportunities, is a burgeoning R&D frontier that numerous companies are now exploring. Based on a February/March 2020 survey conducted with multi-omics personas including scientists, researchers, informaticians, and IT personnel from the biopharmaceutical industry, results showed that researchers are struggling to manage complex multi-omics data. Quality, Storage, Data and Process, FAIR compliance, Integration, and Analysis topped the list of concerns. As an example, scientists spend on average 40-80 percent of their time just finding, categorizing, organizing, and validating input data sets. This clearly speaks the need for accepted data standards, accessible data curation tools and industry-wide data management methods. When dealing with multi-omics analyses, researchers are often confronted with the challenge of incompatible data formats, measurement methods, and data transformation techniques. This leads to missed opportunities for data integration at a higher level of abstraction. Currently, there is a dearth of informatics tools to enable such data integration. Here again, the lack of standardized vocabularies, nomenclature and ontologies create bottlenecks for higher level analysis. In addition, researchers may find themselves unable to access the requisite tools and techniques for multi-omics analysis due to the gap between the biological and data science expertise that represent either end of the data generation and analysis spectrum. For example, while machine learning is a powerful tool that can provide deep insights into microbial communities and identify patterns in microbial community data, it is a specialist branch of data science that is outside of the experience of most bench biologists. Similarly, few data science professionals are fully versed in data generative processes such as biological sampling, nucleic acid extraction, sequencing, and bioinformatics analysis. This knowledge gap is likely to grow larger as more multi-modal and network-based analyses come online, with multiple disparate networks of data to integrate and interrogate and is likely to be compounded as the field moves increasingly away from observational studies to causal analyses. This will necessitate the development of specialist platforms to guide the appropriate analyses. The development and deployment of relevant visualization tools may act as a lingua franca, helping scientists from different disciplines communicate ideas and collaborate throughout the complete data journey, from data generation and preprocessing, via exploration and hypothesis generation, to communication of results. 5. A New Generation of Scientific Data Management and Analysis Platforms are Needed for Microbiome Data and Processes
This paper has highlighted the great opportunity in applications of microbiome science, but the realities of multi-omics data management demonstrate the need for technology and platforms that can handle the extreme volumes of information, process it, and provide valuable outputs. These platforms must enable consumers of data--including scientists, data scientists, product markets, researchers, members of legal and compliance, and beyond--to understand and digest the output in such a way that complex data can be productively applied to real-time solutions. Most organizations will look to outsource these platforms, as underlying data processing requirements to assist scientists in scalably aggregating, collating, and disseminating significant quantities of multi-omics data will be prohibitively expensive to build from scratch in-house.
To respond to this growing demand, an industry of multi-omics data management has arisen to enable R&D executives to meaningfully understand and apply complex data. The competitors featured below are connected by their emphasis on processing and exploration capabilities for multi-omics data, but their applications span across industries. Any organization looking to apply microbiome and multiomics data to their product design will benefit from reviewing the platform capabilities available and the data management systems that best support their innovation journeys. 5.1 Eagle Genomics & e[datascientist]
Eagle Genomics has created a next generation offering called e[datascientist]™ to support advanced microbiome data, and research processes and analyses. This is delivered via a highly curated cloud software platform that handles not only entities but also the external data sources that will be required to expand an organization’s capabilities. Eagle Genomics is establishing the essential data fabric for microbiome science and applying network data science and hypergraph technology to drive more effective innovation cross-team and throughout organizations.
e[datascientist]’s core functionalities include:
• Conversational Interface: provides the foundation for conversational learning between the data and the scientist.
• Valuation and Decision Engine: allows users to objectively measure the usefulness and relevance of their data and knowledge assets, while inferring context from metadata to prioritize data and focus on entity relationships.
• Analysis Hub: drives intelligent statistical analysis and pipeline capabilities on the cloud, which guides and informs research directions and outcomes.
• Catalog: intelligent management, analysis and sharing of multi-omics data and metadata, combined with robust governance structures, which orchestrates the journey from disparate data sources to scientifically meaningful knowledge artefacts.
• Multi-layer Hypergraph: enables users to explore complex multidimensional relationships within microbiome data. By linking, layering and nesting a network of hypergraphs, scientists are able to expose, elucidate and understand context and emergent data patterns.
These core functionalities become accessible to the user through a set of applications designed to facilitate the scientific journey. The e[datascientist] applications enable systematic data exploration and analysis, the optimization of biology workflows and the automation of key data science capabilities.
Figure 9 - The e[datascientist] platform architecture This unique platform is central to the Eagle Genomics value proposition, offering the potential to liberate scientists, data scientists and bioinformaticians from their current business process silos. 6. Other Vendors 6.1 DNANexus
DNANexus combines expertise in cloud computing and bioinformatics to create a global network for genomic medicine. Its global platform offers four major focuses, created with a range of end-users in mind from small businesses through large global enterprises. Their offering range focuses on:
• Next Generation Sequencing Data Analysis • Multi-omics Data Science Exploration, Analysis & Discovery • Customized, Private & Collaborative Environments • Regulatory Quality Services for Clinical, Manufacturing, & Laboratory Practices
Today, DNAnexus works with more than 100 large-scale customers around the world, offering a best-in-class team dedicated to customers' research goals and successes, in addition to a platform equipped to handle extreme scale and highvelocity data processing for genomics, multi-omics, and more. 6.2 Illumina (BlueBee)
Bluebee, acquired by Illumina in 2020, offers a global bio-informatics platform to process, analyze, share and store genomics data. Bluebee provides a unique cloudbased platform to enable fast, efficient and affordable processing of large volumes of genomics data. While personalized treatment comes with great opportunity, routine implementation of genome-based diagnostics is still faced with significant technological challenges including the ever-growing amounts of data generated, the inherent need for faster data processing and deep analytics, and the increasing necessity of flexibility and reliability resulting from the vastness of the application spectrum. 6.3 BigOmics
BigOmics Analytics offers a cloud-based self-service data analytics platform for the life sciences and healthcare industries.
The company tackles the challenge of big data processing, with a focus on multiomics data. It has built various self-service analytics platforms for big omics data that empower life scientists with intuitive, interactive dashboards, allowing them to explore and analyze their data themselves. These platforms also empower biologists to perform complex analyses and create visualizations on their own, without the need to learn how to code. 6.4 Metabolon
Metabolon, founded in 2000, is a leading and comprehensive health technology company that develops analytical methods and software for biomarker discovery using metabolomics. Its proprietary platforms and informatics can deliver an instantaneous snapshot of the entire physiology of a living being at a discreet point in time, as well as identify changes in that system brought about the impact of the disease, medical intervention, diet, or the environment. Metabolon’s expertise is also accelerating research and product development for clients in academia, population health, consumer products, and nutrition industries. Its platform is based on quality management and is capable of deep and wide metabolomics compound information mining, metabolite detection, reference library and metabolite types. 7. Conclusion
As seen in earlier sections, there is significant opportunity related to the microbiome, but also great complexity and diversity. The complexity embraces overarching microbiome concepts as well as resultant data, analyses and internal research processes. Given the vastness of the data and the complex multi-causal relationships that characterize the microbiome, it is evident that advanced technology will be required to manage research, development and productization workflows. Full appreciation of the microbiome has been a missing piece in humanity’s “Puzzle of Understanding,” which some argue goes back to Aristotle (384–322 BC). It is an integral component of the soil, water, and our internal ecosystem that, when disrupted, can cause knock-on effects and disturbances that ultimately compromise health of all living beings and our environment. Although the exact number is still being debated, bacteria are estimated to have a 1:1 ratio with human cells in our bodies. In addition to this, their genetic diversity is known to outnumber that of humans by several orders of magnitude. The integration of necessary multi-omics studies, including transcriptomics and genetic analysis of the human microbiome, will lead to a paradigm shift in how humans live their lives and how researchers and companies will design, manufacture, and deliver technologies in the future.
Experimental scientists, bioinformaticians and data scientists together are incorporating a whole new layer of data and information into their repertoire of analysis and discovery, using advanced tools required to handle the deluge of data and information in a coherent and organized way. These new tools and platforms, alone and in combination, are necessary to drive innovation and discovery. It is also imperative that robust systems are used to combine and manage datasets.
From a discovery and understanding perspective, the microbiome industry is still in its infancy. Ample historical precedent demonstrates that other early-stage industries that turned to rigor and detailed informatics, leveraging data and process standards, went on to deliver great rewards. Leading examples include smallmolecule drug discovery as well as semiconductor process and product development. Each benefitted greatly from the adoption of standards, best practices, and sophisticated tool stacks that were used to develop the life-saving drugs and advanced electronics now at our fingertips.
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