Human reproductive system microbiomes exhibited significantly different heterogeneity scaling with gut microbiome, but the intra‐system scaling is invariant

Abstract

Maintaining sexual reproduction in a highly competitive world is still one of the major mysteries of biology given the apparently high efficiency of asexual reproduction. Co‐evolutionary theories such as the Red Queen hypothesis would suggest that the microbiomes in human reproductive systems, specifically the microbiomes contained in semen and vaginal fluids, should reach some level of homogeneity thanks to arguably the most conspicuous microbiome transmission between two sexes. The long‐term sexual coevolution should favor the dynamic homogeneity or stability, which should also be beneficial for sexual reproduction such as sperm survival or fertilization on physiological/ecological time scale. We present a piece of quantitative evidence in the form of microbial community spatial heterogeneity to support the stability notion by analyzing three big datasets of the human vaginal, semen and gut microbiome. Methodologically, we applied a recent community‐level extension to the classic Taylor's power law, which reached the rare status of ecological law and has found applications beyond biology. Both ecological and evolutionary theories, such as hologenome/holobiont and Red Queen, as well as consideration of first principles, would predict that microbiome transmissions between two sexes should have homogenizing effects on the composition and stability of the microbiomes in human reproductive systems, and therefore have similar variance structures. This is supported by the finding that the power law analysis revealed human vaginal and semen microbiomes exhibited the same scaling parameter size in their community spatial (inter‐individual) heterogeneities, while the both exhibited significantly different heterogeneity scaling parameter size with the human gut microbiome.

Predicting the Outbreak Risks and Inflection Points of COVID‐19 Pandemic with Classic Ecological Theories

“…Note that the term aggregation at the population level can be considered as the counterpart of heterogeneity at the community level or as the counterpart of stability in temporal fluctuation (dynamics) modeling. [6,14,15,17] In the present study, the TPL analysis actually addresses the spatiotemporal aggregation (fluctuation or stability) scaling given that both temporal and spatial data were used. Table S9, Supporting Information, for the details).…”

“…Specifically, our objectives include (Figure 1): i) investigating the outbreak risk of COVID-19 by using Taylor's power law (TPL) and Ma's population aggregation critical density (PACD) for measuring the spatiotemporal aggregation scaling; [3][4][5][6] ii) evaluating the relative importance of local contagion versus regional migration in spreading the infections by approximating the metapopulation of COVID-19 infections with Hubbell's unified neutral theory of biodiversity (UNTB) implemented with Harris et al multisite neutral model (MSN); [7,8] iii) predicting the inflection (turning or tipping) points of outbreaks by establishing infection-time relationship (ITR) inspired by classic species-time relationship (STR) and Ma's diversity-time relationship (DTR) in biogeography. [9,10] First, the spatial and/or temporal distributions of many biological populations including microbes and humans follows TPL, [3,4,[11][12][13] and recent studies have also revealed its applicability at the community scale, [4,6,14,15] even beyond biology and ecology. [16][17][18][19][20] Before this study, there have already been its applications to the analyses of spatial aggregation (variation) of human population, [21] human mortality, [22] and epidemiology.…”

“…First, the spatial and/or temporal distributions of many biological populations including microbes and humans follows TPL, [ 3,4,11–13 ] and recent studies have also revealed its applicability at the community scale, [ 4,6,14,15 ] even beyond biology and ecology. [ 16–20 ] Before this study, there have already been its applications to the analyses of spatial aggregation (variation) of human population, [ 21 ] human mortality, [ 22 ] and epidemiology.…”

Ecology of Human Medical Enterprises: From Disease Ecology of Zoonoses, Cancer Ecology Through to Medical Ecology of Human Microbiomes

“…For examples, if their thresholds can be predicted in advance, we may be able to prevent the transitions from local endemic to regional epidemic, from the epidemic to ultimately global pandemic. For these arguments, power law, especially Taylor's variance-mean power law can play a critical role in measure heterogeneity (Taylor, 1961(Taylor, , 2019Ma, 2020b;Ma and Taylor, 2020). Another cross-scale metric that can be used to measure heterogeneity is Ma and Ellison (2019) dominance concept (metrics).…”

“…The Red Queen hypothesis predict that high infection rates can ultimately favor host sexual reproduction as a strategy for generating host genotypes that may resist infection by common parasite clones. It is postulated that host microbiomes may also be involved in the Red Queen hypothesis, especially in sexual selection (Ma and Taylor, 2020).…”