Microbial dark matter^[1][2] (MDM) comprises the vast majority of microbial organisms (usually bacteria and archaea) that microbiologists are unable to culture in the laboratory, due to lack of knowledge or ability to supply the required growth conditions. Microbial dark matter is analogous to the dark matter of physics and cosmology due to its elusiveness in research and importance to our understanding of biological diversity. Microbial dark matter can be found ubiquitously and abundantly across multiple ecosystems, but remains difficult to study due to difficulties in detecting and culturing these species, posing challenges to research efforts.^[3] It is difficult to estimate its relative magnitude, but the accepted gross estimate is that as little as one percent of microbial species in a given ecological niche are culturable. In recent years, more effort has been directed towards deciphering microbial dark matter by means of recovering genome DNA sequences from environmental samples via culture independent methods such as single cell genomics^[4] and metagenomics.^[5] These studies have enabled insights into the evolutionary history and the metabolism of the sequenced genomes,^[6][7] providing valuable knowledge required for the cultivation of microbial dark matter lineages. However, microbial dark matter research remains comparatively undeveloped and is hypothesized to provide insight into processes radically different from known biology, new understandings of microbial communities, and increasing understanding of how life survives in extreme environments.^[8]

Our contemporary understanding of microbial dark matter was born from a field that still faced constraints with the cultivation of traditional microbes. One of the main constraints of this time was an over dependence on the use of culturing methods. This over reliance meant that a large amount of microbial diversity remained yet to be discovered.  However in the late 20th century new developments in molecular techniques led to a surge in discovery of uncultured microbes. Despite this newfound diversity, a large majority of microbial species remain uncharacterized.^[9] This fact was further proven by the development of advanced genomic sequencing techniques in the early 21st century which uncovered a larger amount of microbial diversity than previously thought.^[8]

Metagenomics is a technique in the field of microbial studies that enables us to sequence DNA directly from samples of microbial environments. This innovative technique allows us to identify the genetic material of unknown microbes and avoid overreliance on the use of culturing. The use of metagenomics differs from other microbial methods in that it uses a broad description through its use of bulk samples. This technique has expanded our understanding of microbial functions in ecosystems through the discovery of new genes and metabolic pathways.^[10]

Methods of single-cell genomics have shown promise in supporting metagenomics approaches by allowing the study of individual microbial cells isolated from their natural environments, a method which has been employed to uncover the genomic and functional diversity within microbial communities, particularly those that cannot be cultured. Single-cell techniques have also successfully identified numerous new branches on the tree of life, providing insight into the gaps of current phylogenetic understanding and metabolic potential of these organisms.^[11]

Despite the rise of culture-independent methods as successful methods for dark matter research, improvements in culturing techniques remain both relevant and necessary to further current understanding of MRM microbes. To this point, developments in methods such as highly specific growth media to mimic natural microbial environments and co-culturing of synergistic microbial species have shown success in studying previously unculturable microbes. These advancements also serve to facilitate the application of MRM research into biotechnological and physiological uses.^[12]

Genomic studies produce vast amounts of data to be analyzed. This analysis requires the use of advanced computational components. The scientific subdiscipline of bioinformatics used computational technology to collect genomes and conduct analysis on metabolic pathways. In recent years, research on artificial intelligence and machine learning has produced new ways to increase our ability to predict the behavior of microbial species using their genetic data.^[13] These new developments in the world of computational tools have allowed us to further understand the structure and dynamics present in microbial communities.

It has been suggested certain microbial dark matter genetic material could belong to a new (i.e., fourth) domain of life,^[14][15] although other explanations (e.g., viral origin) are also possible, which has ties with the issue of a hypothetical shadow biosphere.^[16]

• Biological dark matter
• Microbial ecology
• Microbiology

^[1]

• Microbial Dark Matter project site