Biology subjects

Velsko, I. M.

Publications and source records attributed to Velsko, I. M..

4 recordsLinked to original sources

bioRxiv2018

Species Designations Belie Phenotypic and Genotypic Heterogeneity in Oral Streptococci

Health-associated oral Streptococcus species are promising probiotic candidates to protect against dental caries. Ammonia production through the arginine deiminase system (ADS), which can increase the pH of oral biofilms, and direct antagonism of caries-associated bacterial species are desirable properties for oral probiotic strains. ADS and antagonistic activities can vary dramatically among individuals, but the genetic basis for these differences is unknown. We sequenced whole genomes of a diverse set of clinical oral Streptococcus isolates and examined the genetic basis of variability in ADS and antagonistic activities. A total of 113 isolates were included and represented ten species: S. australis, A12-like, S. cristatus, S. gordonii, S. intermedius, S. mitis, S. oralis including S. oralis subsp. dentisani, S. parasanguinis, S. salivarius, and S. sanguinis. Mean ADS activity and antagonism on Streptococcus mutans UA159 were measured for each isolate, and each isolate was whole genome-shotgun sequenced on an Illumina MiSeq. Phylogenies were built of genes known to be involved in ADS activity and antagonism. Several approaches to correlate the pan-genome with phenotypes were performed. Phylogenies of genes previously identified in ADS activity and antagonism grouped isolates by species but not by phenotype. GWAS identified additional genes potentially involved in ADS activity or antagonism across all the isolates we sequenced as well as within several species. Phenotypic heterogeneity in oral streptococci is not necessarily reflected by genotype and is not species-specific. Probiotic strains must be carefully selected based on characterization of each strain, and not based on inclusion within a certain species.\n\nImportanceRepresentative type strains are commonly used to characterize bacterial species, yet species are phenotypically and genotypically heterogeneous. Conclusions about strain physiology and activity based on a single strain therefore may be inappropriate and misleading. When selecting strains for probiotic use, the assumption that all strains within a species share the same desired probiotic characteristics share those characteristics may result in selection of a strain that lacks the desired traits, and therefore makes a minimally effective or ineffective probiotic. Health-associated oral streptococci are promising candidates for anti-caries probiotics, but strains need to be carefully selected based on observed phenotypes. We characterized the genotype and anti-caries phenotypes of strains from ten species of oral Streptococci and demonstrate poor correlation between genotype and phenotype across all species.

microbiology↗

bioRxiv2018

Consistent and reproducible long-term in vitro growth of health and disease-associated oral subgingival biofilms

Background: Several in vitro oral biofilm growth systems can reliably construct oral microbiome communities in culture, yet their stability and reproducibility through time has not been well characterized. Long-term in vitro growth of natural biofilms would enable use of these biofilms in both in vitro and in vivo studies that require complex microbial communities with minimal variation over a period of time. Understanding biofilm community dynamics in continuous culture, and whether they maintain distinct signatures of health and disease, is necessary to determine the reliability and applicability of such models to broader studies. To this end, we performed next-generation sequencing on biofilms grown from healthy and disease-site subgingival plaque for 80 days to assess stability and reliability of continuous oral biofilm growth.\n\nResults: Biofilms were grown from subgingival plaque collected from periodontitis-affected sites and healthy individuals for ten eight-day long generations, using hydroxyapatite disks. The bacterial community in each generation was determined using Human Oral Microbe Identification by Next-Generation Sequencing (HOMINGS) technology, and analyzed in QIIME. Profiles were steady through the ten generations, as determined by species abundance and prevalence, Spearmans correlation coefficient, and Faiths phylogenetic distance, with slight variation predominantly in low abundance species. Community profiles were distinct between healthy and disease site-derived biofilms as demonstrated by weighted UniFrac distance throughout the ten generations. Differentially abundant species between healthy and disease site-derived biofilms were consistent throughout the generations.\n\nConclusions: Healthy and disease site-derived biofilms can reliably maintain consistent communities through ten generations of in vitro growth. These communities maintain signatures of health and disease and of individual donors despite culture in identical environments. This subgingival oral biofilm growth and perpetuation model may prove useful to studies involving oral infection or cell stimulation, or those measuring microbial interactions, which require the same biofilms over a period of time.

microbiology↗

bioRxiv2018

Selection of appropriate metagenome taxonomic classifiers for ancient microbiome research

Metagenomics enables the study of complex microbial communities from myriad sources, including the remains of oral and gut microbiota preserved in archaeological dental calculus and paleofeces, respectively. While accurate taxonomic assignment is essential to this process, DNA damage, characteristic to ancient samples (e.g. reduction in fragment size), may reduce the accuracy of read taxonomic assignment. Using a set of in silico-generated metagenomic datasets we investigated how the addition of ancient DNA (aDNA) damage patterns influences microbial taxonomic assignment by five widely-used profilers: QIIME/UCLUST, MetaPhlAn2, MIDAS, CLARK-S, and MALT (BLAST-X-mode). In silico-generated datasets were designed to mimic dental plaque, consisting of 40, 100, and 200 microbial species/strains, both with and without simulated aDNA damage patterns. Following taxonomic assignment, the profiles were evaluated for species presence/absence, relative abundance, alpha-diversity, beta-diversity, and specific taxonomic assignment biases. Unifrac metrics indicated that both MIDAS and MetaPhlAn2 provided the most accurate community structure reconstruction. QIIME/UCLUST, CLARK-S, and MALT had the highest number of inaccurate taxonomic assignments; however, filtering out species present at <0.1% abundance greatly increased the accuracy of CLARK-S and MALT. All programs except CLARK-S failed to detect some species from the input file that were in their databases. Ancient DNA damage resulted in minimal differences in species detection and relative abundance between simulated ancient and modern datasets for most programs. In conclusion, taxonomic profiling biases are program-specific rather than damage-dependent, and the choice of taxonomic classification program to use should be tailored to the research question.\n\nImportanceAncient biomolecules from oral and gut microbiome samples have been shown to preserve in the archaeological record. Studying ancient microbiome communities using metagenomic techniques offer a unique opportunity to reconstruct the evolutionary trajectories of microbial communities through time. DNA accumulates specific damage over time, which could potentially affect taxonomic classification and our ability to reconstruct community assemblages accurately. It is therefore necessary to assess whether ancient DNA (aDNA) damage patterns affect metagenomic taxonomic profiling. Here, we assessed biases in community structure, diversity, species detection, and relative abundance estimates by five popular metagenomic taxonomic classification programs using in silico-generated datasets with aDNA damage. Age-related damage patterns had minimal impact on the taxonomic profiles produced by each program, and biases were intrinsic to each program. Therefore, an appropriate classification program should be chosen that minimizes the biases related to the questions being addressed.

microbiology↗

bioRxiv2017

The dental calculus metabolome in modern and historic samples

IntroductionDental calculus is a mineralized microbial dental plaque biofilm that forms throughout life by precipitation of salivary calcium salts. Successive cycles of dental plaque growth and calcification make it an unusually well-preserved, long-term record of host-microbial interaction in the archaeological record. Recent studies have confirmed the survival of authentic ancient DNA and proteins within historic and prehistoric dental calculus, making it a promising substrate for investigating oral microbiome evolution via direct measurement and comparison of modern and ancient specimens.\n\nObjectiveWe present the first comprehensive characterization of the human dental calculus metabolome using a multi-platform approach.\n\nMethodsUltra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) quantified 285 metabolites in modern and historic (200 years old) dental calculus, including metabolites of drug and dietary origin. A subset of historic samples was additionally analyzed by high-resolution gas chromatography-MS (GC-MS) and UPLC- MS/MS for further characterization of polar metabolites and lipids, respectively. Metabolite profiles of modern and historic calculus were compared to identify patterns of persistence and loss.\n\nResultsDipeptides, free amino acids, free nucleotides, and carbohydrates substantially decrease in abundance and ubiquity in archaeological samples, with some exceptions. Lipids generally persist, and saturated and mono-unsaturated medium and long chain fatty acids appear to be well-preserved, while metabolic derivatives related to oxidation and chemical degradation are found at higher levels in archaeological dental calculus than fresh samples.\n\nConclusionsThe results of this study indicate that certain metabolite classes have higher potential for recovery over long time scales and may serve as appropriate targets for oral microbiome evolutionary studies.

microbiology↗