Microbial communities are foundational to our world, yet exceedingly diverse and complex. While modern methods for analyzing and interpreting these complex ecosystems builds on the tools available to microbiologists a decade ago, they do not enable a truly functional understanding of the role of individual strains in an environment. These methods rely upon a statistical measurement coupled to fixed assumptions around metabolism and population constants that often result in neither an optimal, nor reliable, product target.
The Native Microbials Technology Platform transforms the analysis of microbial communities with a unique, functionally descriptive approach – the result is not only a more rational and direct analysis of what takes place in these complex microbial ecosystems, but more importantly, the identification of microbial strains that are the most efficacious for desired mechanisms of commercial, health, environmental, and societal value.
Microbial populations and systems are not static—they are dynamic and constantly responding to changes in their environment. The number of cells in a microbial community can change significantly over time for any multitude of reasons within different microbe groups (e.g. bacterial, fungal, viral), and most importantly in ways that can have dramatic impacts on the analysis and interpretation of these microbial ecosystems. Measuring the absolute number of cells from one environmental condition to the next environment condition, or from one sample to another sample, is a fundamentally different measurement than the existing relative percentage measurement which makes broad assumptions about the magnitude of cells present in a microbial community.
At Native Microbials we have pioneered the incorporation of absolute cell counts into microbial community analysis as a means to more directly measure the overall system and how it shifts in response to random or induced perturbations.
Although microbial communities are incredibly diverse, only a portion of the community members will be active at any given time. The vast metabolic capabilities collectively captured by the species diversity of the community allow it to adapt rapidly and efficiently to a changing environment—this is done through the activation and deactivation of specific metabolic processes. Conventional microbial community analysis methods generally rely on DNA-based analyses, and make a broad assumption that each identified species present in that environmental condition and / or sample is relevant at that moment in time. Advancements in gene expression, protein expression, and metabolism-related measurement tools have progressed rapidly over the past 5 years.
At Native Microbials, we have pioneered the incorporation of these advancements, along with proprietary markers and tools, into our platform to focus on subpopulations and there respective chemistries, and in turn to effectively and directly assess individual members of the microbial community and where they fit in overall microbial community.
In nature, microbial communities exist as complex networks of species that interact among themselves as well as their environment. These interactions not only dictate the composition and structure of the community, but also influence the overall functionality and chemistry of the system. By using innovative approaches and mathematical methods to analyze and interpret interactions within a microbial community, and by leveraging network theory to understand how species within a community group themselves, we can gain insight into the intertwined relationships that define the overall community and the processes we observe at the environmental level. Understanding these interactions and how microorganisms within a community organize themselves enables us to create effective products that are compatible with and able to influence the naturally occurring microbial ecosystem.