Education & Certifications
M.Sc., Kent State University, Ecology & Evolutionary Biology (2009)
B.Sc., Kent State University, Cell & Molecular Biology (2006)
Previously, we determined that genetic and environmental factors contributed equally towards rosacea in twins. To assess an environmental factor, we characterized the malar cheek bacterial microbiome from twins discordant for rosacea. We found no significant difference in facial microbiome alpha and beta diversity between related twins discordant for rosacea. However, the relative percentage abundance of Gordonia and Geobacillus, low-abundant genera, was positively and negatively associated with rosacea severity, respectively. Our data demonstrate a significant correlation between facial microbiome and severity of rosacea in genetically matched twins and importantly that overall microbiome composition is largely unchanged.
View details for DOI 10.1111/exd.13491
View details for Web of Science ID 000427009500234
View details for PubMedID 29283459
Understanding how microbial communities develop is essential for predicting and directing their future states. Ecological theory suggests that community development is often influenced by priority effects, in which the order and timing of species arrival determine how species affect one another. Priority effects can have long-lasting consequences, particularly if species arrival history varies during the early stage of community development, but their importance to the human gut microbiota and host health remains largely unknown. Here, we explore how priority effects might influence microbial communities in the gastrointestinal tract during early childhood and how the strength of priority effects can be estimated from the composition of the microbial species pool. We also discuss factors that alter microbial transmission, such as delivery mode, diet and parenting behaviours such as breastfeeding, which can influence the likelihood of priority effects. An improved knowledge of priority effects has the potential to inform microorganism-based therapies, such as prebiotics and probiotics, which are aimed at guiding the microbiota towards a healthy state.
View details for DOI 10.1038/nrgastro.2017.173
View details for PubMedID 29362469
Endogenous intestinal microbiota have wide-ranging and largely uncharacterized effects on host physiology. Here, we used reverse-phase liquid chromatography-coupled tandem mass spectrometry to define the mouse intestinal proteome in the stomach, jejunum, ileum, cecum and proximal colon under three colonization states: germ-free (GF), monocolonized with Bacteroides thetaiotaomicron and conventionally raised (CR). Our analysis revealed distinct proteomic abundance profiles along the gastrointestinal (GI) tract. Unsupervised clustering showed that host protein abundance primarily depended on GI location rather than colonization state and specific proteins and functions that defined these locations were identified by random forest classifications. K-means clustering of protein abundance across locations revealed substantial differences in host protein production between CR mice relative to GF and monocolonized mice. Finally, comparison with fecal proteomic data sets suggested that the identities of stool proteins are not biased to any region of the GI tract, but are substantially impacted by the microbiota in the distal colon.
View details for DOI 10.1038/ismej.2015.187
View details for Web of Science ID 000374377200014
View details for PubMedID 26574685
View details for PubMedCentralID PMC5029216
Fungi have developed a wide assortment of enzymes to break down pectin, a prevalent polymer in plant cell walls that is important in plant defense and structure. One enzyme family used to degrade pectin is the glycosyl hydrolase family 28 (GH28). In this study we developed primers for the amplification of GH28 coding genes from a database of 293 GH28 sequences from 40 fungal genomes. The primers were used to successfully amplify GH28 pectinases from all Ascomycota cultures tested, but only three out of seven Basidiomycota cultures. In addition, we further tested the primers in PCRs on metagenomic DNA extracted from senesced tree leaves from different forest ecosystems, followed by cloning and sequencing. Taxonomic specificity for Ascomycota GH28 genes was tested by comparing GH28 composition in leaves to internal transcribed spacer (ITS) amplicon composition using pyrosequencing. All sequences obtained from GH28 primers were classified as Ascomycota; in contrast, ITS sequences indicated that fungal communities were up to 39% Basidiomycetes. Analysis of leaf samples indicated that both forest stand and ecosystem type were important in structuring fungal communities. However, site played the prominent role in explaining GH28 composition, whereas ecosystem type was more important for ITS composition, indicating possible genetic drift between populations of fungi. Overall, these primers will have utility in understanding relationships between fungal community composition and ecosystem processes, as well as detection of potentially pathogenic Ascomycetes.
View details for DOI 10.1016/j.mimet.2016.02.013
View details for Web of Science ID 000373655300016
View details for PubMedID 26899925
Clinical diagnosis of infection in chronic wounds is currently limited to subjective clinical signs and culture-based methods that underestimate the complexity of wound microbial bioburden as revealed by DNA-based microbial identification methods. Here, we use 16S rRNA next generation sequencing and quantitative polymerase chain reaction to characterize weekly changes in bacterial load, community structure, and diversity associated with a chronic venous leg ulcer over the 15-week course of treatment and healing. Our DNA-based methods and detailed sampling scheme reveal that the bacterial bioburden of the wound is unexpectedly dynamic, including changes in the bacterial load and community structure that correlate with wound expansion, antibiotic therapy, and healing. We demonstrate that these multidimensional changes in bacterial bioburden can be summarized using swabs taken prior to debridement, and therefore, can be more easily collected serially than debridement or biopsy samples. Overall, this case illustrates the importance of detailed clinical indicators and longitudinal sampling to determine the pathogenic significance of chronic wound microbial dynamics and guide best use of antimicrobials for improvement of healing outcomes.
View details for DOI 10.1111/wrr.12309
View details for PubMedID 25902876
View details for PubMedCentralID PMC5007860
Glycosyl hydrolase family 28 (GH28) is a set of structurally related enzymes that hydrolyze glycosidic bonds in pectin, and are important extracellular enzymes for both pathogenic and saprotrophic fungi. Yet, very little is understood about the evolutionary forces driving the diversification of GH28s in fungal genomes. We reconstructed the evolutionary history of family GH28 in fungi by examining the distribution of GH28 copy number across the phylogeny of fungi, and by reconstructing the phylogeny of GH28 genes. We also examined the relationship between lineage-specific GH28 expansions and fungal ecological strategy, testing the hypothesis that GH28 evolution in fungi is driven by ecological strategy (pathogenic vs. non-pathogenic) and pathogenic niche (necrotrophic vs. biotrophic). Our results showed that GH28 phylogeny of Ascomycota and Basidiomycota sequences was structured by specific biochemical function, with endo-polygalacturonases and endo-rhamnogalacturonases forming distinct, apparently ancient clades, while exo-polygalacturonases are more widely distributed. In contrast, Mucoromycotina and Stramenopile sequences formed taxonomically-distinct clades. Large, lineage-specific variation in GH28 copy number indicates that the evolution of this gene family is consistent with the birth-and-death model of gene family evolution, where diversity of GH28 loci within genomes was generated through multiple rounds of gene duplication followed by functional diversification and loss of some gene family members. Although GH28 copy number was correlated with genome size, our findings suggest that ecological strategy also plays an important role in determining the GH28 repertoire of fungi. Both necrotrophic and biotrophic fungi have larger genomes than non-pathogens, yet only necrotrophs possess more GH28 enzymes than non-pathogens. Hence, lineage-specific GH28 expansion is the result of both variation in genome size across fungal species and diversifying selection within the necrotrophic plant pathogen ecological niche. GH28 evolution among necrotrophs has likely been driven by a co-evolutionary arms race with plants, whereas the need to avoid plant immune responses has resulted in purifying selection within biotrophic fungi.
View details for DOI 10.1016/j.gene.2011.02.009
View details for Web of Science ID 000291376300004
View details for PubMedID 21354463
The circadian input kinase A (cikA) gene encodes a protein relaying environmental signal to the central circadian oscillator in cyanobacteria. The CikA protein has a variable architecture and usually consists of four tandemly arrayed domains: GAF, histidine kinase (HisKA), histidine kinase-like ATPase (HATPase_c), and a pseudo-receiver (REC). Among them, HisKA and HATPase_c are the least polymorphic, and REC is not present in heterocystic filamentous cyanobacteria. CikA contains several conserved motifs that are likely important for circadian function. There are at least three types of circadian systems, each of which possesses a different set of circadian genes. The originally described circadian system (kaiABC system) possesses both cikA and kaiA, while the others lack either only cikA (kaiABC (Delta)) or both (kaiBC). The results we obtained allowed us to approximate the time of the cikA origin to be about 2600-2200 MYA and the time of its loss in the species with the kaiABC (Delta) or kaiBC system between 1100 and 600 MYA. Circadian specialization of CikA, as opposed to its non-circadian homologs, is a result of several factors, including the unique conserved domain architecture and high evolutionary constraints of some domains and regions, which were previously identified as critical for the circadian function of the gene.
View details for DOI 10.1007/s00239-010-9344-0
View details for Web of Science ID 000278094800005
View details for PubMedID 20437037