Species gains and losses in ecological communities are inevitable given on-going global changes and reassembly may result in alternative stable states of structure and function. Microbial species gains and losses could change community structure due to extensive microbial interaction networks and mega-diversity. These features of microbial communities have hampered our ability to predict reassembly. Highly specialized interactions, either facilitative or competitive, result in nonrandom cooccurrence among taxa. Dominant and rare taxa may be differentially sensitive to cooccurrence patterns because of their degree of specialization. Rare taxa may perform unique functions with specialized interactions, while abundant members may be generalists. Alternatively, rare microbes may be functionally redundant and insensitive to cooccurrence patterns. We investigated how gains and losses of dominant and rare microbial taxa affected community structure. We simulated microbial community reassembly in two mock microbial communities based on amplicon sequencing of the human vagina microbiome and forest soil, which represent low and high richness respectively. We eliminated dominant exact sequence variants (ESVs) or rare ESVs that were either typically rare or rare in specific environments. We hypothesized that alteration of dominant members would have a larger impact on non-target ESVs than rare members.
Results/Conclusions
Species gains and losses in simulated communities affected the abundance of non-target ESVs, which was amplified in the soil microbiome compared to the vagina microbiome. Sensitivity of non-target ESVs in the forest soil microbiome suggests the soil microbial interaction network is densely interconnected. When the most dominant ESV was removed, about one-sixth of the simulated rare microbiome shifted relative abundance, which may occur because of changes in species interactions. Removing a single rare ESV that was found to be rare across all samples caused no change in dominant member relative abundance, and about one-third of the rare microbiome shifted relative abundance. On the other hand, removal of a rare ESV that was abundant in other samples, a pattern that suggests the ESV has a unique function or trait, caused 80% of the dominant members to increase relative abundance and altered relative abundance of nearly half the rare microbiome. Our simulation results suggest empirical hypotheses: 1) interaction network connectivity is related to the abiotic environment, and 2) community structure is more sensitive to changes in rare members than dominant members. Our ability to predict microbial community structure is important to predicting functions mediated by microbes under changing environmental conditions.