Dynamics of Microeukaryotes and Archaea in the Mammalian Gut Microbiome

The vertebrate microbiome consists of the bacteria, fungi, archaea, protozoans, and viruses that inhabit the body at diverse locations including the skin, mouth, upper airways, urogenital tract, and digestive tract. These microorganisms are known to synthesize vitamins, interact with and tone the immune system, and dramatically affect human health. A long list of diseases has been associated with imbalances in commensal microbiome communities. The work presented in this dissertation aims to characterize the microeukaryotic and archaeal components of the gut microbiome through development of wet lab techniques and in silico methods, and apply them to the study of response to antibiotics. These methods provided a picture of the healthy fungal and archaeal communities in the gut, with high prevalence of the yeast Saccharomyces and the archaeon Methanobrevibactor, along with several other species. These new tools were then used to investigate the longitudinal changes that the microbiome undergoes when treated with heavy antibiotics. Using an antibiotic cocktail containing ampicillin, neomycin, vancomycin, and metronidazole in a mouse model, we found that bacterial communities were effectively suppressed and fungi grew out by one to two orders of magnitude. After we discontinued antibiotics, bacterial and fungal cell counts returned to baseline levels within one week, but community composition was still significantly altered. Eight weeks after cessation of antibiotics, fungal community composition was not significantly different from non-treated controls, but several mice continued to have elevated levels of yeasts that had grown out during antibiotic treatment. The bacterial community composition was still significantly different from non-treated controls. Ultimately, this work demonstrated potentially deleterious long term effects of antibiotic use, and emphasizes how strong cage effects can be in mouse studies. The research performed in this dissertation will aid researchers looking to study all three domains of life and take into account the effects of commonly used antibiotics in future microbiome studies

Archaea and Fungi of the Human Gut Microbiome: Correlations with Diet and Bacterial Residents

Diet influences health as a source of nutrients and toxins, and by shaping the composition of resident microbial populations. Previous studies have begun to map out associations between diet and the bacteria and viruses of the human gut microbiome. Here we investigate associations of diet with fungal and archaeal populations, taking advantage of samples from 98 well-characterized individuals. Diet was quantified using inventories scoring both long-term and recent diet, and archaea and fungi were characterized by deep sequencing of marker genes in DNA purified from stool. For fungi, we found 66 genera, with generally mutually exclusive presence of either the phyla Ascomycota or Basiodiomycota. For archaea, Methanobrevibacter was the most prevalent genus, present in 30% of samples. Several other archaeal genera were detected in lower abundance and frequency. Myriad associations were detected for fungi and archaea with diet, with each other, and with bacterial lineages. Methanobrevibacter and Candida were positively associated with diets high in carbohydrates, but negatively with diets high in amino acids, protein, and fatty acids. A previous study emphasized that bacterial population structure was associated primarily with long-term diet, but high Candida abundance was most strongly associated with the recent consumption of carbohydrates. Methobrevibacter abundance was associated with both long term and recent consumption of carbohydrates. These results confirm earlier targeted studies and provide a host of new associations to consider in modeling the effects of diet on the gut microbiome and human health

Inter-generic relationships.

<p>The heatmaps quantify the intergeneric relationships. (A) Normalized z-score of the bacterial and fungal proportions for samples grouped according to their archaeal status (<i>Methanobrevibacter</i> positive, <i>Nitrososphaera</i> positive, or archaea negative). Asterisks indicate Kruskall-Wallis significant comparisons after FDR adjustment (FDR of 25, 20, 15, and 10% are marked with 1, 2, 3 or 4 asterisks, respectively). Domain membership is color-coded on the left. (B) Spearman correlations between Fungi and Bacteria. Asterisks in red indicate FDR adjusted significant correlations (FDR 20%) and the remaining raw p-values are shown to illustrate general patterns within the data (p-values < = 0.05, 0.01, 0.005, 0.001 are marked with 1, 2, 3 or 4 asterisks, respectively).</p

The archaeal and fungal components of the human gut microbiome.

<p>The heatmaps show the relative proportions of microbial lineages detected by pyrosequencing. The lineages are marked on the right, with Phylum (abbreviated), Class, and Genus. Archaeal genera are shown in (A), representative bacterial genera in (B), and fungal genera in (C). The top two rows show the DNA yield from PCR amplification reactions, which serves as a rough indicator of abundance. Proportions were calculated within each amplicon (archaeal 16S, bacterial 16S, or fungal ITS) for each sequencing study separately. The abbreviations for phyla were as follows (Eur: Euryarchaeota; Tha: Thaumarchaeota; Act: Actinobacteria; Bac: Bacteroidetes; Fir: Firmicutes; Asc: Ascomycota; Bas; Basidiomycota). Other Ascomycota and Other Basidiomycota are composed of genera which were detected in only one sample (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066019#pone.0066019.s010" target="_blank">Table S7</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066019#pone.0066019.s002" target="_blank">Figure S2</a> for a complete list of detected genera and their prevalence).</p

Possible syntrophic relationships in the human gut consistent with data reported in this study.

<p>Possible syntrophic relationships in the human gut consistent with data reported in this study.</p

Fungi-Diet relationships.

<p>Heatmap of Spearman correlations between nutrient clusters and the bacterial and fungal genera detected in the dataset. Correlations which were considered significant using the Usual (A) and the Recent (B) diet data are marked with asterisks as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066019#pone-0066019-g002" target="_blank">Figure 2A</a>. Domain membership is color-coded on the bottom.</p

Archaea-Diet relationships.

<p>Heatmap of normalized average means for nutrient cluster measurements of the samples classified according to the dominant archaeal genus. Usual diet (A) and recent diet (B) relationships considered significant are marked with asterisks as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066019#pone-0066019-g002" target="_blank">Figure 2A</a>.</p

Analysis of co-occurrence among microbial lineages scored using the Dice index.

<p>Dice indexes across all genera pairs present at a proportion > = 0.01 are shown as a heatmap. Clustering was carried out using Ward’s criteria, based on the Euclidian distance between each genus pair using their Dice index across all other genera. Domain membership is color-coded on the left. Data are summarized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066019#pone.0066019.s012" target="_blank">Table S9</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066019#pone.0066019.s013" target="_blank">S10</a>.</p

Molecular characterization of precise in vivo targeted gene integration in human cells using AAVHSC15.

Targeted gene integration via precise homologous recombination (HR)-based gene editing has the potential to correct genetic diseases. AAV (adeno-associated virus) can mediate nuclease-free gene integration at a disease-causing locus. Therapeutic application of AAV gene integration requires quantitative molecular characterization of the edited sequence that overcome technical obstacles such as excess episomal vector genomes and lengthy homology arms. Here we describe a novel molecular methodology that utilizes quantitative next-generation sequencing to characterize AAV-mediated targeted insertion and detects the presence of unintended mutations. The methods described here quantify targeted insertion and query the entirety of the target locus for the presence of insertions, deletions, single nucleotide variants (SNVs) and integration of viral components such as inverted terminal repeats (ITR). Using a humanized liver murine model, we demonstrate that hematopoietic stem-cell derived AAVHSC15 mediates in vivo targeted gene integration into human chromosome 12 at the PAH (phenylalanine hydroxylase) locus at 6% frequency, with no sign of co-incident random mutations at or above a lower limit of detection of 0.5% and no ITR sequences at the integration sites. Furthermore, analysis of heterozygous variants across the targeted locus using the methods described shows a pattern of strand cross-over, supportive of an HR mechanism of gene integration with similar efficiencies across two different haplotypes. Rapid advances in the application of AAV-mediated nuclease-free target integration, or gene editing, as a new therapeutic modality requires precise understanding of the efficiency and the nature of the changes being introduced to the target genome at the molecular level. This work provides a framework to be applied to homologous recombination gene editing platforms for assessment of introduced and natural sequence variation across a target site

Fungi of the Murine Gut: Episodic Variation and Proliferation during Antibiotic Treatment

<div><p>Antibiotic use in humans has been associated with outgrowth of fungi. Here we used a murine model to investigate the gut microbiome over 76 days of treatment with vancomycin, ampicillin, neomycin, and metronidazole and subsequent recovery. Mouse stool was studied as a surrogate for the microbiota of the lower gastrointestinal tract. The abundance of fungi and bacteria was measured using quantitative PCR, and the proportional composition of the communities quantified using 454/Roche pyrosequencing of rRNA gene tags. Prior to treatment, bacteria outnumbered fungi by >3 orders of magnitude. Upon antibiotic treatment, bacteria dropped in abundance >3 orders of magnitude, so that the predominant 16S sequences detected became transients derived from food. Upon cessation of treatment, bacterial communities mostly returned to their previous numbers and types after 8 weeks, though communities remained detectably different from untreated controls. Fungal communities varied substantially over time, even in the untreated controls. Separate cages within the same treatment group showed radical differences, but mice within a cage generally behaved similarly. Fungi increased ∼40-fold in abundance upon antibiotic treatment but declined back to their original abundance after cessation of treatment. At the last time point, <i>Candida</i> remained more abundant than prior to treatment. These data show that 1) gut fungal populations change radically during normal mouse husbandry, 2) fungi grow out in the gut upon suppression of bacterial communities with antibiotics, and 3) perturbations due to antibiotics persist long term in both the fungal and bacterial microbiota.</p></div