While it is appreciated that global gene expression analyses can provide novel insights about complex biological processes, experiments are generally insufficiently powered to achieve this goal. Here we report the results of a robust microarray experiment of axolotl forelimb regeneration. At each of 20 post-amputation time points, we estimated gene expression for 10 replicate RNA samples that were isolated from 1 mm of heterogeneous tissue collected from the distal limb tip. We show that the limb transcription program diverges progressively with time from the non-injured state, and divergence among time adjacent samples is mostly gradual. However, punctuated episodes of transcription were identified for five intervals of time, with four of these coinciding with well-described stages of limb regeneration—amputation, early bud, late bud, and pallet. The results suggest that regeneration is highly temporally structured and regulated by mechanisms that function within narrow windows of time to coordinate transcription within and across cell types of the regenerating limb. Our results provide an integrative framework for hypothesis generation using this complex and highly informative data set.

This investigation evaluated the relationship of the oral microbiome and gingival transcriptome in health and periodontitis in nonhuman primates ( Macaca mulatta). Subgingival plaque samples and gingival biopsies were collected from healthy sites and at sites undergoing ligature-induced periodontitis. Microbial samples were analyzed with 16S amplicon sequencing to identify bacterial profiles in young (3 to 7 y) and adult (12 to 23 y) animals. The gingival transcriptome was determined with a microarray analysis and focused on the expression level of 452 genes that are associated with the development of inflammation and innate and adaptive immune responses. Of the 396 total operational taxonomic units (OTUs) identified across the samples, 81.8% were detected in the young group and 99.5% in the adult group. Nevertheless, 58 of the OTUs composed 88% of the signal in adults, and 49 OTUs covered 91% of the OTU readouts in the young group. Correlation analyses between the microbiome members and specific gingival genes showed a high number of significant bacteria-gene correlations in the young healthy tissues, which decreased by 75% in diseased tissues. In contrast, these correlations increased by 2.5-fold in diseased versus healthy tissues of adult animals. Complexes of bacteria were delineated that related to specific sets of immune genes, differing in health and disease and in the young versus adult animals. The correlated gene profiles demonstrated selected pathway overrepresentation related to particular bacterial complexes. These results provide novel insights into microbiome changes with disease and the relationship of these changes to specific gene profiles and likely biologic activities occurring in healthy and diseased gingival tissues in this human-like periodontitis model.

Young/adolescent humans demonstrate many microorganisms associated with periodontal disease in adults and substantial gingival inflammatory responses. However, younger individuals do not demonstrate the soft and hard tissue destruction that hallmark periodontitis. This study evaluated responses to the oral microbial ecology in gingival tissues from clinically healthy young Macaca mulatta (<3 years old) compared to older animals (5-23 years old). Global transcriptional profiling of four age groups revealed a subset of 159 genes that were differentially expressed at least across one of the age comparisons. Correlation metrics generated a relevance network abstraction of these genes. Partitioning of the relevance network revealed seven distinct communities comprising functionally related genes associated with host inflammatory and immune responses. A group of genes were identified that were selectively increased/decreased or positively/negatively correlated with gingival profiles in the animals. A Principal Components Analysis created metagenes of expression profiles for classifying the 23 animals. The results provide novel system-level insights into gene expression differences in healthy young tissues weighted towards host responses that were associated with anti-inflammatory biomolecules or those linked with T cell regulation of responses. The combination of the regulated microenvironment may help to explain the apparent “resistance” of younger individuals to developing periodontal disease.

Periodontal diseases are a major public health concern leading to tooth loss and also shown to be associated with several chronic systemic diseases. Smoking is a major risk factor for developing numerous systemic diseases, as well as periodontitis. While it is clear that smokers have a significantly enhanced risk for developing periodontitis leading to tooth loss, the population varies with regards to susceptibility to disease associated with smoking. This investigation focuses on identifying differences in four broad sets of variables consisting of: (a) host response molecules, (b) periodontal clinical parameters, (c) antibody measures for periodontal pathogens and oral commensal bacteria challenge, and (d) other variables of interest in a smoking population with (n = 171) and without periodontitis (n = 117). Subsequently, Bayesian network structured learning techniques (BNSL) techniques were used to investigate potential associations and cross-talk between the four broad sets of variables. BNSL revealed two broad communities with markedly different topology between the non-periodontitis and periodontitis smoking population. Confidence of the edges in the resulting network also showed marked variations within and between the periodontitis and non-periodontitis groups. The results presented validated known associations, as well as discovered new ones with minimal precedence that may warrant further investigation and novel hypothesis generation. Cross-talk between the clinical variables and antibody profiles of bacteria were especially pronounced in the case of periodontitis and mediated by the antibody response profile to P. gingivalis.