Non-coding RNAs in saliva: emerging biomarkers for molecular diagnostics.

Saliva is a complex body fluid that comprises secretions from the major and minor salivary glands, which are extensively supplied by blood. Therefore, molecules such as proteins, DNA, RNA, etc., present in plasma could be also present in saliva. Many studies have reported that saliva body fluid can be useful for discriminating several oral diseases, but also systemic diseases including cancer. Most of these studies revealed messenger RNA (mRNA) and proteomic biomarker signatures rather than specific non-coding RNA (ncRNA) profiles. NcRNAs are emerging as new regulators of diverse biological functions, playing an important role in oncogenesis and tumor progression. Indeed, the small size of these molecules makes them very stable in different body fluids and not as susceptible as mRNAs to degradation by ribonucleases (RNases). Therefore, the development of a non-invasive salivary test, based on ncRNAs profiles, could have a significant applicability to clinical practice, not only by reducing the cost of the health system, but also by benefitting the patient. Here, we summarize the current status and clinical implications of the ncRNAs present in human saliva as a source of biological information

Quantifying biosynthetic network robustness across the human oral microbiome

Metabolic interactions, such as cross-feeding, play a prominent role in microbial communitystructure. For example, they may underlie the ubiquity of uncultivated microorganisms. We investigated this phenomenon in the human oral microbiome, by analyzing microbial metabolic networks derived from sequenced genomes. Specifically, we devised a probabilistic biosynthetic network robustness metric that describes the chance that an organism could produce a given metabolite, and used it to assemble a comprehensive atlas of biosynthetic capabilities for 88 metabolites across 456 human oral microbiome strains. A cluster of organisms characterized by reduced biosynthetic capabilities stood out within this atlas. This cluster included several uncultivated taxa and three recently co-cultured Saccharibacteria (TM7) phylum species. Comparison across strains also allowed us to systematically identify specific putative metabolic interdependences between organisms. Our method, which provides a new way of converting annotated genomes into metabolic predictions, is easily extendible to other microbial communities and metabolic products.https://www.biorxiv.org/content/10.1101/392621v1First author draf

Dys-regulated Gene Expression Networks by Meta-Analysis of Microarray Data on Oral Squamous Cell Carcinoma

Background: Oral squamous cell carcinoma (OSCC) is the sixth most common type of carcinoma worldwide. Development of OSCC is a multi-step process involving genes related to cell cycle, growth control, apoptosis, DNA damage response and other cellular regulators. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of OSCC gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets has opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated.

Results: In this work we performed a meta-analysis on four microarray and four datasets of gene expression data on OSCC in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Sixteen dys-regulated pathways implicated in OSCC were mined out from the four published datasets, and most importantly three pathways were first reported. Those regulatory pathways and biological processes which are significantly enriched have been investigated by means of literatures and meanwhile, four genes of the maximally altered pathways, ECM-receptor interaction, were validated and identified by qRT-PCR as a possible candidate of aggressiveness of OSCC.

Conclusion: we have developed a robust method for analyzing pathways altered in OSCC using three expression array data sets. This study sets a stage for the further discovery of the basic mechanisms that may underlie a diseased state and would help in identifying critical nodes in the pathway that can be targeted for diagnosis and therapeutic intervention. In addition, those who are interested in our approach can obtain the software package (MATLAB platform) by email freely

Pbx loss in cranial neural crest, unlike in epithelium, results in cleft palate only and a broader midface.

Orofacial clefting represents the most common craniofacial birth defect. Cleft lip with or without cleft palate (CL/P) is genetically distinct from cleft palate only (CPO). Numerous transcription factors (TFs) regulate normal development of the midface, comprising the premaxilla, maxilla and palatine bones, through control of basic cellular behaviors. Within the Pbx family of genes encoding Three Amino-acid Loop Extension (TALE) homeodomain-containing TFs, we previously established that in the mouse, Pbx1 plays a preeminent role in midfacial morphogenesis, and Pbx2 and Pbx3 execute collaborative functions in domains of coexpression. We also reported that Pbx1 loss from cephalic epithelial domains, on a Pbx2- or Pbx3-deficient background, results in CL/P via disruption of a regulatory network that controls apoptosis at the seam of frontonasal and maxillary process fusion. Conversely, Pbx1 loss in cranial neural crest cell (CNCC)-derived mesenchyme on a Pbx2-deficient background results in CPO, a phenotype not yet characterized. In this study, we provide in-depth analysis of PBX1 and PBX2 protein localization from early stages of midfacial morphogenesis throughout development of the secondary palate. We further establish CNCC-specific roles of PBX TFs and describe the developmental abnormalities resulting from their loss in the murine embryonic secondary palate. Additionally, we compare and contrast the phenotypes arising from PBX1 loss in CNCC with those caused by its loss in the epithelium and show that CNCC-specific Pbx1 deletion affects only later secondary palate morphogenesis. Moreover, CNCC mutants exhibit perturbed rostro-caudal organization and broadening of the midfacial complex. Proliferation defects are pronounced in CNCC mutants at gestational day (E)12.5, suggesting altered proliferation of mutant palatal progenitor cells, consistent with roles of PBX factors in maintaining progenitor cell state. Although the craniofacial skeletal abnormalities in CNCC mutants do not result from overt patterning defects, osteogenesis is delayed, underscoring a critical role of PBX factors in CNCC morphogenesis and differentiation. Overall, the characterization of tissue-specific Pbx loss-of-function mouse models with orofacial clefting establishes these strains as unique tools to further dissect the complexities of this congenital craniofacial malformation. This study closely links PBX TALE homeodomain proteins to the variation in maxillary shape and size that occurs in pathological settings and during evolution of midfacial morphology

Metabolic network percolation quantifies biosynthetic capabilities across the human oral microbiome

The biosynthetic capabilities of microbes underlie their growth and interactions, playing a prominent role in microbial community structure. For large, diverse microbial communities, prediction of these capabilities is limited by uncertainty about metabolic functions and environmental conditions. To address this challenge, we propose a probabilistic method, inspired by percolation theory, to computationally quantify how robustly a genome-derived metabolic network produces a given set of metabolites under an ensemble of variable environments. We used this method to compile an atlas of predicted biosynthetic capabilities for 97 metabolites across 456 human oral microbes. This atlas captures taxonomically-related trends in biomass composition, and makes it possible to estimate inter-microbial metabolic distances that correlate with microbial co-occurrences. We also found a distinct cluster of fastidious/uncultivated taxa, including several Saccharibacteria (TM7) species, characterized by their abundant metabolic deficiencies. By embracing uncertainty, our approach can be broadly applied to understanding metabolic interactions in complex microbial ecosystems.T32GM008764 - NIGMS NIH HHS; T32 GM008764 - NIGMS NIH HHS; R01 DE024468 - NIDCR NIH HHS; R01 GM121950 - NIGMS NIH HHS; DE-SC0012627 - Biological and Environmental Research; RGP0020/2016 - Human Frontier Science Program; NSFOCE-BSF 1635070 - National Science Foundation; HR0011-15-C-0091 - Defense Advanced Research Projects Agency; R37DE016937 - NIDCR NIH HHS; R37 DE016937 - NIDCR NIH HHS; R01GM121950 - NIGMS NIH HHS; R01DE024468 - NIDCR NIH HHS; 1457695 - National Science FoundationPublished versio

Computational prediction of the human-microbial oral interactome

Background: The oral cavity is a complex ecosystem where human chemical compounds coexist with a particular microbiota. However, shifts in the normal composition of this microbiota may result in the onset of oral ailments, such as periodontitis and dental caries. In addition, it is known that the microbial colonization of the oral cavity is mediated by protein-protein interactions (PPIs) between the host and microorganisms. Nevertheless, this kind of PPIs is still largely undisclosed. To elucidate these interactions, we have created a computational prediction method that allows us to obtain a first model of the Human-Microbial oral interactome.Results: We collected high-quality experimental PPIs from five major human databases. The obtained PPIs were used to create our positive dataset and, indirectly, our negative dataset. The positive and negative datasets were merged and used for training and validation of a naïve Bayes classifier. For the final prediction model, we used an ensemble methodology combining five distinct PPI prediction techniques, namely: literature mining, primary protein sequences, orthologous profiles, biological process similarity, and domain interactions. Performance evaluation of our method revealed an area under the ROC-curve (AUC) value greater than 0.926, supporting our primary hypothesis, as no single set of features reached an AUC greater than 0.877. After subjecting our dataset to the prediction model, the classified result was filtered for very high confidence PPIs (probability ≥ 1-10-7), leading to a set of 46,579 PPIs to be further explored.Conclusions: We believe this dataset holds not only important pathways involved in the onset of infectious oral diseases, but also potential drug-targets and biomarkers. The dataset used for training and validation, the predictions obtained and the network final network are available at http://bioinformatics.ua.pt/software/oralint.info:eu-repo/semantics/publishedVersio

Characterization of Cystatin B Interactome in Saliva from Healthy Elderly and Alzheimer's Disease Patients

Cystatin B is a small, multifunctional protein involved in the regulation of inflammation, innate immune response, and neuronal protection and found highly abundant in the brains of patients with Alzheimer's disease (AD). Recently, our study demonstrated a significant association between the level of salivary cystatin B and AD. Since the protein is able to establish protein-protein interaction (PPI) in different contexts and aggregation-prone proteins and the PPI networks are relevant for AD pathogenesis, and due to the relevance of finding new AD markers in peripheral biofluids, we thought it was interesting to study the possible involvement of cystatin B in PPIs in saliva and to evaluate differences and similarities between AD and age-matched elderly healthy controls (HC). For this purpose, we applied a co-immunoprecipitation procedure and a bottom-up proteomics analysis to purify, identify, and quantify cystatin B interactors. Results demonstrated for the first time the existence of a salivary cystatin B-linked multi-protein complex composed by 82 interactors and largely expressed in the body. Interactors are involved in neutrophil activation, antimicrobial activity, modulation of the cytoskeleton and extra-cellular matrix (ECM), and glucose metabolism. Preliminary quantitative data showed significantly lower levels of triosophosphate isomerase 1 and higher levels of mucin 7, BPI, and matrix Gla protein in AD with respect to HC, suggesting implications associated with AD of altered glucose metabolism, antibacterial activities, and calcification-associated processes. Data are available via ProteomeXchange with identifiers PXD039286 and PXD030679

Protein cargo of salivary small extracellular vesicles as potential functional signature of oral squamous cell carcinoma

The early diagnosis of oral squamous cell carcinoma (OSCC) is still an investigative challenge. Saliva has been proposed as an ideal diagnostic medium for biomarker detection by mean of liquid biopsy technique. The aim of this pilot study was to apply proteomic and bioinformatic strategies to determine the potential use of saliva small extracellular vesicles (S/SEVs) as a potential tumor biomarker source. Among the twenty-three enrolled patients, 5 were free from diseases (OSCC_FREE), 6 were with OSCC without lymph node metastasis (OSCC_NLNM), and 12 were with OSCC and lymph node metastasis (OSCC_LNM). The S/SEVs from patients of each group were pooled and properly characterized before performing their quantitative proteome comparison based on the SWATH_MS (Sequential Window Acquisition of all Theoretical Mass Spectra) method. The analysis resulted in quantitative information for 365 proteins differentially characterizing the S/SEVs of analyzed clinical conditions. Bioinformatic analysis of the proteomic data highlighted that each S/SEV group was associated with a specific cluster of enriched functional network terms. Our results highlighted that protein cargo of salivary small extracellular vesicles defines a functional signature, thus having potential value as novel predict biomarkers for OSCC

Identification and Characterization of msaB Gene Involved in Biofilm Formation and Virulence in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e

Staphylococcus aureus is an important human pathogen that causes a wide variety of life-threatening infections ranging from minor skin and oral infections to severe infections, such as bacteremia, pneumonia, osteomyelitis, or endocarditis due to the presence and secretion of a large number of virulence factors that are controlled by global virulence regulators in complex networks. Furthermore, S. aureus infections have become a threat to public health because of their high potential to form biofilm, and their ability to resist a wide range of antibiotics has exacerbated further. Therefore, understanding the regulatory networks and developing a drug targeting these networks has the potential to stand as therapeutic targets for future treatment of antibiotic resistant infections. In a previous study msaC was identified as the modulator of sarA, a new global virulence regulator that controls the expression of sarA and biofilm development. Furthermore, it has also been shown that msaC is a part of four-gene operon, msaABCR operon, which includes four-genes: SAUSA300_1296 (msaA), SAUSA300_1295 (msaB), SAUSA300_1294 (msaC), and antisense RNA, msaR. The mechanism of regulation of msaABCR operon and the function of individual genes were not clearly known yet. This study defines the role of msaB, the second gene of the msaABCR operon, which will help shed some light on the regulation of msaABCR. We deleted msaB gene from USA300_LAC, and studied the major msaB phenotypes: pigmentation, protease production, biofilm formation, and rate of cell death. Deletion of msaB resulted in the similar msaC and/or msaABCR deletion mutant, thus showing the importance of this gene in this operon. The mutant showed decreased pigmentation, increased extracellular protease production, decreased biofilm formation, and increased rate of cell death. Deletion of the msaB gene also resulted in the decreased expression of some key regulators, like sarA and agr that play major roles in the regulation of virulence and biofilm formation in S. aureus, similar to msaC and msaABCR operon deletion mutant. Thus, this study identifies the role of msaB, in the msaABCR operon, that will help us define the mechanism of regulation of virulence and biofilm formation by the msaABCR operon and provides a step to investigate the stimulatory signals that the msaABCR operon responds to during pathogenesis

Metagenomics for Bacteriology

The study of bacteria, or bacteriology, has gone through transformative waves since its inception in the 1600s. It all started by the visualization of bacteria using light microscopy by Antonie van Leeuwenhoek, when he first described “animalcules.” Direct cellular observation then evolved into utilizing different wavelengths on novel platforms such as electron, fluorescence, and even near-infrared microscopy. Understanding the link between microbes and disease (pathogenicity) began with the ability to isolate and cultivate organisms through aseptic methodologies starting in the 1700s. These techniques became more prevalent in the following centuries with the work of famous scientists such as Louis Pasteur and Robert Koch, and many others since then. The relationship between bacteria and the host’s immune system was first inferred in the 1800s, and to date is continuing to unveil its mysteries. During the last century, researchers initiated the era of molecular genetics. The discovery of the first-generation sequencing technology, the Sanger method, and, later, the polymerase chain reaction technology propelled the molecular genetics field by exponentially expanding the knowledge of relationship between gene structure and function. The rise of commercially available next-generation sequencing methodologies, in the beginning of this century, is drastically allowing larger amount of information to be acquired, in a manner open to the democratization of the approach