Biology subjects

Peter Anthony Noble

Publications and source records attributed to Peter Anthony Noble.

3 recordsLinked to original sources

bioRxiv2016

Microbial Signatures of Oral Dysbiosis, Periodontitis and Edentulism Revealed by Gene Meter Methodology

Conceptual models suggest certain microorganisms (e.g., the red complex) are indicative of a specific disease state (e.g., periodontitis); however, recent studies have questioned the validity of these models. Here, the abundances of 500+ microbial species were determined in 16 patients with clinical signs of one of the following oral conditions: periodontitis, established caries, edentulism, and oral health. Our goal was to determine if the abundances of certain microorganisms reflect dysbiosis or a specific clinical condition that could be used as a signature for dental research. Microbial abundances were determined by the analysis of 138,718 calibrated probes using Gene Meter methodology. Each 16S rRNA gene was targeted by an average of 194 unique probes (n=25 nt). The calibration involved diluting pooled gene target samples, hybridizing each dilution to a DNA microarray, and fitting the probe intensities to adsorption models. The fit of the model to the experimental data was used to assess individual and aggregate probe behavior; good fits (R2>0.90) were retained for back-calculating microbial abundances from patient samples. The abundance of a gene was determined from the median of all calibrated individual probes or from the calibrated abundance of all aggregated probes. With the exception of genes with low abundances (< 2 arbitrary units), the abundances determined by the different calibrations were highly correlated (r [~]1.0). Seventeen genera were classified as signatures of dysbiosis because they had significantly higher abundances in patients with periodontitis and edentulism when contrasted with health. Similarly, 13 genera were classified as signatures of periodontitis, and 14 genera were classified as signatures of edentulism. The signatures could be used, individually or in combination, to assess the clinical status of a patient (e.g., evaluating treatments such as antibiotic therapies). Comparisons of the same patient samples revealed high false negatives (45%) for next-generation-sequencing results and low false positives (7%) for Gene Meter results.

Microbiology↗

bioRxiv2016

Accurate Predictions of Postmortem Interval Using Linear Regression Analyses of Gene Meter Expression Data

In criminal and civil investigations, postmortem interval is used as evidence to help sort out circumstances at the time of human death. Many biological, chemical, and physical indicators can be used to determine the postmortem interval, but most are not accurate. Here, we sought to validate an experimental design to accurately predict the time of death by analyzing the expression of hundreds of upregulated genes in two model organisms, the zebrafish and mouse. In a previous study, the death of healthy adults was conducted under strictly controlled conditions to minimize the effects of confounding factors such as lifestyle and temperature. A total of 74,179 microarray probes were calibrated using the Gene Meter approach and the transcriptional profiles of 1,063 significantly upregulated genes were assembled into a time series spanning from life to 48 or 96 h postmortem. In this study, the experimental design involved splitting the gene profiles into training and testing datasets, randomly selecting groups of profiles, determining the modeling parameters of the genes to postmortem time using over- and/or perfectly- defined linear regression analyses, and calculating the fit (R2) and slope of predicted versus actual postmortem times. This design was repeated several thousand to million times to find the top predictive groups of gene transcription profiles. A group of eleven zebrafish genes yielded R2 of 1 and a slope of 0.99, while a group of seven mouse liver genes yielded a R2 of 0.98 and a slope of 0.97, and seven mouse brain genes yielded a R2 of 0.93 and a slope of 0.85. In all cases, groups of gene transcripts yielded better postmortem time predictions than individual gene transcripts. The significance of this study is two-fold: selected groups of upregulated genes provide accurate prediction of postmortem time, and the successfully validated experimental design can now be used to accurately predict postmortem time in cadavers.

Genomics↗

bioRxiv2016

Thanatotranscriptome: genes actively expressed after organismal death

A continuing enigma in the study of biological systems is what happens to highly ordered structures, far from equilibrium, when their regulatory systems suddenly become disabled. In life, genetic and epigenetic networks precisely coordinate the expression of genes -- but in death, it is not known if gene expression diminishes gradually or abruptly stops or if specific genes are involved. We investigated the unwinding of the clock by identifying upregulated genes, assessing their functions, and comparing their transcriptional profiles through postmortem time in two species, mouse and zebrafish. We found transcriptional abundance profiles of 1,063 genes were significantly changed after death of healthy adult animals in a time series spanning from life to 48 or 96 h postmortem. Ordination plots revealed non-random patterns in profiles by time. While most thanatotranscriptome (thanatos-, Greek defn. death) transcript levels increased within 0.5 h postmortem, some increased only at 24 and 48 h. Functional characterization of the most abundant transcripts revealed the following categories: stress, immunity, inflammation, apoptosis, transport, development, epigenetic regulation, and cancer. The increase of transcript abundance was presumably due to thermodynamic and kinetic controls encountered such as the activation of epigenetic modification genes responsible for unraveling the nucleosomes, which enabled transcription of previously silenced genes (e.g., development genes). The fact that new molecules were synthesized at 48 to 96 h postmortem suggests sufficient energy and resources to maintain self-organizing processes. A step-wise shutdown occurs in organismal death that is manifested by the apparent upregulation of genes with various abundance maxima and durations. The results are of significance to transplantology and molecular biology.

Systems Biology↗