Host lifestyle affects human microbiota on daily timescales

By Lawrence A. David, Arne C. Materna, Jonathan Friedman, Maria I Campos-Baptista, M. Blackburn, A. Perrotta, S. Erdman, Eric J. Alm. Genome Biology, 2014

894 citations recorded by the source corpus.

Disturbance to human microbiota may underlie several pathologies. Yet, we lack a comprehensive understanding of how lifestyle affects the dynamics of human-associated microbial communities. Here, we link over 10,000 longitudinal measurements of human wellness and action to the daily gut and salivary microbiota dynamics of two individuals over the course of one year. These time series show overall microbial communities to be stable for months. However, rare events in each subjects’ life rapidly and broadly impacted microbiota dynamics. Travel from the developed to the developing world in one subject led to a nearly two-fold increase in the Bacteroidetes to Firmicutes ratio, which reversed upon return. Enteric infection in the other subject resulted in the permanent decline of most gut bacterial taxa, which were replaced by genetically similar species. Still, even during periods of overall community stability, the dynamics of select microbial taxa could be associated with specific host behaviors. Most prominently, changes in host fiber intake positively correlated with next-day abundance changes among 15% of gut microbiota members. Our findings suggest that although human-associated microbial communities are generally stable, they can be quickly and profoundly altered by common human actions and experiences.

Subfields: Infectious Diseases, Molecular Biology, Periodontics

View Paper: https://www.semanticscholar.org/paper/e7e4d8098785c9219c29a094810648ad80b25c6e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Infectious Diseases

C. Hill

In Molecular Biology

In Periodontics

Citations in the corpus

Network analysis methods for studying microbial communities: A mini review (2021, methodology): “…microbiome studies including local similarity analysis (LSA) [78], Time-decay analysis [79], Augmented Dickey Fuller test [80], Cross correlation [80], Time-varying network inference [81], Hurst exponent [82], Bistability analysis [83], as well as Extended LSA (eLSA) [84], which offers support…”
Effects of diurnal variation of gut microbes and high fat feeding on host circadian clock function and metabolism (2015, neutral): “Detecting significant oscillatory patterns in 16S rRNA amplicon sequencing data is complicated due to lack of absolute OTU abundance information and limited tools to describe nonlinear relationships in relative abundance data (Friedman and Alm, 2012; David et al., 2014).”
The human gut virome is highly diverse, stable and individual-specific (2019, background): “The bacterial component of a healthy microbiome is 39 characterized by high temporal stability but can be affected by events such as travel, sickness 40 and antibiotic usage (David et al., 2014; Jalanka-Tuovinen et al., 2011).”
Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration (2019, background): “Likewise, mouse models have indicated that manipulation of macronutrient intake can consistently shift the composition of the gut microbiota within the span of a day [5,6,18,19].”
Measuring the biodiversity of microbial communities by flow cytometry (2016, background): “…between microbial biodiversity and ecosystem function (Konopka, Lindemann & Fredrickson 2015), to monitor community stability (Prest et al. 2013; David et al. 2014) or to identify early warning signals that indicate critical ecosystem transitions (e.g. eutrophication) (Wang et al. 2012).”