Abstract
The human microbiome is an extremely complex ecosystem considering the number of bacterial species, their interactions, and its variability over space and time. Here, we untangle the complexity of the human microbiome for the Irritable Bowel Syndrome (IBS) that is the most prevalent functional gastrointestinal disorder in human populations. Based on a novel information theoretic network inference model, we detected potential species interaction networks that are functionally and structurally different for healthy and unhealthy individuals. Healthy networks are characterized by a neutral symmetrical pattern of species interactions and scale-free topology versus random unhealthy networks. We detected an inverse scaling relationship between species total outgoing information flow, meaningful of node interactivity, and relative species abundance (RSA). The top ten interacting species are also the least relatively abundant for the healthy microbiome and the most detrimental. These findings support the idea about the diminishing role of network hubs and how these should be defined considering the total outgoing information flow rather than the node degree. Macroecologically, the healthy microbiome is characterized by the highest Pareto total species diversity growth rate, the lowest species turnover, and the smallest variability of RSA for all species. This result challenges current views that posit a universal association between healthy states and the highest absolute species diversity in ecosystems. Additionally, we show how the transitory microbiome is unstable and microbiome criticality is not necessarily at the phase transition between healthy and unhealthy states. We stress the importance of considering portfolios of interacting pairs versus single node dynamics when characterizing the microbiome and of ranking these pairs in terms of their interactions (i.e., species collective behavior) that shape transition from healthy to unhealthy states. The macroecological characterization of the microbiome is useful for public health and disease diagnosis and etiognosis, while species-specific analyses can detect beneficial species leading to personalized design of pre- and probiotic treatments and microbiome engineering.
Highlights
A recent dataset with absolute abundances suggests that healthy gut microbiota have higher total abundances than diseased ones [72] but no studies exist about the universality of this abundance-health relationship
Stability is related to network topology [3], which affects diversity [77,78] and the systemic fluctuations of the microbiome, as shown by the Taylor’s law [8] that highlights how variance in relative species abundance (RSA) abundance changes with the mean
“Optimal” organization is in this case referring to the healthy state as a reference state because it has the smallest fluctuations for the highest achievable total diversity growth rate γ0 and the associated network topology is more resilient to random node removal (Figure S3)
Summary
If the ultimate goal of microbiome research is to improve human health by engineering the ecology of the gut, and other applications are of interest, we must first understand how and why our microbiota varies in time and space, whether these dynamics are consistent across humans, whether we can define stable or healthy dynamics, and how these states are associated to the environment. This line of research is primarily missing how microbial diversity is organized considering all its facets and how this diversity changes when species interaction networks change. The same level of diversity can be achieved via different network topologies that may lead to different health states [7]
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