Fecal Viral Community Responses to High-Fat Diet in Mice.

Alterations in diet can have significant impact on the host, with high-fat diet (HFD) leading to obesity, diabetes, and inflammation of the gut. Although membership and abundances in gut bacterial communities are strongly influenced by diet, substantially less is known about how viral communities respond to dietary changes. Examining fecal contents of mice as the mice were transitioned from normal chow to HFD, we found significant changes in the relative abundances and the diversity in the gut of bacteria and their viruses. Alpha diversity of the bacterial community was significantly diminished in response to the diet change but did not change significantly in the viral community. However, the diet shift significantly impacted the beta diversity in both the bacterial and viral communities. There was a significant shift away from the relatively abundant Siphoviridae accompanied by increases in bacteriophages from the Microviridae family. The proportion of identified bacteriophage structural genes significantly decreased after the transition to HFD, with a conserved loss of integrase genes in all four experimental groups. In total, this study provides evidence for substantial changes in the intestinal virome disproportionate to bacterial changes, and with alterations in putative viral lifestyles related to chromosomal integration as a result of shift to HFD.IMPORTANCE Prior studies have shown that high-fat diet (HFD) can have profound effects on the gastrointestinal (GI) tract microbiome and also demonstrate that bacteria in the GI tract can affect metabolism and lean/obese phenotypes. We investigated whether the composition of viral communities that also inhabit the GI tract are affected by shifts from normal to HFD. We found significant and reproducible shifts in the content of GI tract viromes after the transition to HFD. The differences observed in virome community membership and their associated gene content suggest that these altered viral communities are populated by viruses that are more virulent toward their host bacteria. Because HFD also are associated with significant shifts in GI tract bacterial communities, we believe that the shifts in the viral community may serve to drive the changes that occur in associated bacterial communities

De novo origins of multicellularity in response to predation

The transition from unicellular to multicellular life was one of a few major events in the history of life that created new opportunities for more complex biological systems to evolve. Predation is hypothesized as one selective pressure that may have driven the evolution of multicellularity. Here we show that de novo origins of simple multicellularity can evolve in response to predation. We subjected outcrossed populations of the unicellular green alga Chlamydomonas reinhardtii to selection by the filter-feeding predator Paramecium tetraurelia. Two of five experimental populations evolved multicellular structures not observed in unselected control populations within ~750 asexual generations. Considerable variation exists in the evolved multicellular life cycles, with both cell number and propagule size varying among isolates. Survival assays show that evolved multicellular traits provide effective protection against predation. These results support the hypothesis that selection imposed by predators may have played a role in some origins of multicellularity

A coevolutionary approach for understanding bacteria-phage interactions and developing enhanced phage therapeutics

For billions of years, bacteria and their viruses (termed phages) have engaged in never-ending cycles of coevolution, as bacteria evolve resistance and phages counter resistance. This process of reciprocal adaptation has fundamentally shaped the biology of bacteria and phages, as well as structured the microbial ecosystems of our planet’s oceans, soils, and organisms. In recent years, the evolution and spread of antibiotic resistant bacterial pathogens have renewed interest in phages as an alternative way to treat bacterial infections. Yet, only by understanding how phages interact and coevolve with their hosts can we devise effective treatment strategies that avoid recreating the past mistakes made with antibiotic drugs. In this dissertation, I take an applied perspective to study and better understand bacteria-phage coevolution. In the first chapter, I demonstrate that the therapeutic potential of phages can be enhanced by pre-adapting them to target pathogens via a process called coevolutionary training. In the second chapter, I evaluate how bacteria respond to trained phages compared to favored approaches in phage therapy, such as phage cocktails. In the third chapter, I study how bacteria-phage coevolution generates diversity and creates complex ecological networks. And in the fourth chapter, I use an in vivo mouse model to show that phages administered to the gut can modify the gut microbiome and affect host mouse body weight phenotypes. Altogether, this work reveals the importance of coevolution as a fundamental process that shapes the diversity of life and as a useful tool for applications such as phage therapy

Coevolutionary phage training leads to greater bacterial suppression and delays the evolution of phage resistance

The evolution of antibiotic-resistant bacteria threatens to become the leading cause of worldwide mortality. This crisis has renewed interest in the practice of phage therapy. Yet, bacteria's capacity to evolve resistance may debilitate this therapy as well. To combat the evolution of phage resistance and improve treatment outcomes, many suggest leveraging phages' ability to counter resistance by evolving phages on target hosts before using them in therapy (phage training). We found that in vitro, λtrn, a phage trained for 28 d, suppressed bacteria ∼1,000-fold for three to eight times longer than its untrained ancestor. Prolonged suppression was due to a delay in the evolution of resistance caused by several factors. Mutations that confer resistance to λtrn are ∼100× less common, and while the target bacterium can evolve complete resistance to the untrained phage in a single step, multiple mutations are required to evolve complete resistance to λtrn. Mutations that confer resistance to λtrn are more costly than mutations for untrained phage resistance. Furthermore, when resistance does evolve, λtrn is better able to suppress these forms of resistance. One way that λtrn improved was through recombination with a gene in a defunct prophage in the host genome, which doubled phage fitness. This transfer of information from the host genome is an unexpected but highly efficient mode of training phage. Lastly, we found that many other independently trained λ phages were able to suppress bacterial populations, supporting the important role training could play during phage therapeutic development

Fecal Viral Community Responses to High-Fat Diet in Mice.

Alterations in diet can have significant impact on the host, with high-fat diet (HFD) leading to obesity, diabetes, and inflammation of the gut. Although membership and abundances in gut bacterial communities are strongly influenced by diet, substantially less is known about how viral communities respond to dietary changes. Examining fecal contents of mice as the mice were transitioned from normal chow to HFD, we found significant changes in the relative abundances and the diversity in the gut of bacteria and their viruses. Alpha diversity of the bacterial community was significantly diminished in response to the diet change but did not change significantly in the viral community. However, the diet shift significantly impacted the beta diversity in both the bacterial and viral communities. There was a significant shift away from the relatively abundant Siphoviridae accompanied by increases in bacteriophages from the Microviridae family. The proportion of identified bacteriophage structural genes significantly decreased after the transition to HFD, with a conserved loss of integrase genes in all four experimental groups. In total, this study provides evidence for substantial changes in the intestinal virome disproportionate to bacterial changes, and with alterations in putative viral lifestyles related to chromosomal integration as a result of shift to HFD.IMPORTANCE Prior studies have shown that high-fat diet (HFD) can have profound effects on the gastrointestinal (GI) tract microbiome and also demonstrate that bacteria in the GI tract can affect metabolism and lean/obese phenotypes. We investigated whether the composition of viral communities that also inhabit the GI tract are affected by shifts from normal to HFD. We found significant and reproducible shifts in the content of GI tract viromes after the transition to HFD. The differences observed in virome community membership and their associated gene content suggest that these altered viral communities are populated by viruses that are more virulent toward their host bacteria. Because HFD also are associated with significant shifts in GI tract bacterial communities, we believe that the shifts in the viral community may serve to drive the changes that occur in associated bacterial communities

Figure 4

The script "Figure4.R" compiles Figure 4. It runs in R version 3.5.1 and requires the following R libraries: dplyr, reshape2, ggplot2. The data for Figure 4 are contained in the plain-text, comma-separated file "Figure4Data.csv"

Figure 5 Data

Data for Figure 5 are contained in the file "Figure5Data.csv". The file format is plain-text, comma-separated. Columns in this file are as follows: Strain: Strain idenitifier nopred1: Absorbance reading for technical replicate 1, predator absent nopred2: Absorbance reading for technical replicate 2, predator absent nopred3: Absorbance reading for technical replicate 3, predator absent nopred4: Absorbance reading for technical replicate 4, predator absent pred1: Absorbance reading for technical replicate 1, predator present pred2: Absorbance reading for technical replicate 2, predator present pred3: Absorbance reading for technical replicate 3, predator present pred4: Absorbance reading for technical replicate 4, predator present Time(h): Number of hours post-inoculation at which the absorbance readings were made MeanDiff: Mean difference between predator absent replicates and predator present replicate

Figure 4 Data

Data for Figure 4. Columns in this file are as follows: Strain: Strain identifier TechRep: Technical replicate ClusterID: Unique, arbitrary identifier per cluster Num.Cells.Progeny: The number of cells observed in a propagule after splitting from parent cluster Num.Cell.Parent: The number of cells observed in the parent cluster after releasing a propagule (determined at same time-step as Num.Cells.Progeny) RepTime.sec: The time at which reproduction (propagule splitting from parent cluster) occurred in the time-lapse. Initially this was reported in time-step, which was then converted to seconds. EntersField.sec: Time at which the cluster entered the field of vie

Figure 3

The script "Figure3.R" compiles Figure 3. It runs in R version 3.5.1 and requires the following R libraries: dplyr, reshape2, tools, ggplot2. The data for Figure 3 are contained in the folder "Figure3Data". Files in this folder are plain-text, comma-separated. The naming convention is "strain replicate", so "B2.01 01b" contains data for strain B2-01, replicate 01b. Columns in these files are as follows: ROI: Region of Interest ROI Number: The individual ROI, selected from the image based on thresholding. This typically is a single cellular cluster. Mean: Mean 8-bit brightness value for pixels within the ROI Min: Minimum 8-bit brightness value for pixels within the ROI Max: Maximum 8-bit brightness value for pixels within the ROI IntDen: The product of the area of the ROI and its mean 8-bit brightness value RawIntDen: The sum of the brightness values for all pixels in the RO