Proteomic and Transcriptional Analysis of Interaction between Oral Microbiota Porphyromonas gingivalis and Streptococcus oralis

The polymicrobial pathogenicity of Porphyromonas gingivalis

Accumulating microbiome data and mechanistic studies in vitro and in vivo have refined our understanding of the oral microbiota as a functionally integrated polymicrobial community. Emergent properties of these communities are driven to a large extent by interspecies communication which can be based on physical association, secreted small molecules or nutritional exchange. Porphyromonas gingivalis is a consensus periodontal pathogen; however, virulence is only expressed in the context of a polymicrobial community. Multivalent fimbriae mediate attachment to other oral species which can initiate a distinct transcriptional program in both constituents of the binding pair. P. gingivalis also responds to small molecules and nutritional cues produced by partner organisms. Physiological interdependence forms the basis of complex networks of cooperating organisms which begin to resemble an organismal entity exhibiting a spectrum of pathogenic potential.

Contribution of -Omics Technologies in the Study of Porphyromonas gingivalis during Periodontitis Pathogenesis: A Minireview

Periodontitis is a non-communicable chronic inflammatory disease characterized by the progressive and irreversible breakdown of the soft periodontal tissues and resorption of teeth-supporting alveolar bone. The etiology of periodontitis involves dysbiotic shifts in the diversity of microbial communities inhabiting the subgingival crevice, which is dominated by anaerobic Gram-negative bacteria, including Porphyromonas gingivalis. Indeed, P. gingivalis is a keystone pathogen with a repertoire of attributes that allow it to colonize periodontal tissues and influence the metabolism, growth rate, and virulence of other periodontal bacteria. The pathogenic potential of P. gingivalis has been traditionally analyzed using classical biochemical and molecular approaches. However, the arrival of new techniques, such as whole-genome sequencing, metagenomics, metatranscriptomics, proteomics, and metabolomics, allowed the generation of high-throughput data, offering a suitable option for bacterial analysis, allowing a deeper understanding of the pathogenic properties of P. gingivalis and its interaction with the host. In the present review, we revise the use of the different -omics technologies and techniques used to analyze bacteria and discuss their potential in studying the pathogenic potential of P. gingivalis.

Label-free quantitative proteomic analysis of the oral bacteria Fusobacterium nucleatum and Porphyromonas gingivalis to identify protein features relevant in biofilm formation

BACKGROUND

The opportunistic pathogens Fusobacterium nucleatum and Porphyromonas gingivalis are Gram-negative bacteria associated with oral biofilm and periodontal disease. This study investigated interactions between F. nucleatum and P. gingivalis proteomes with the objective to identify proteins relevant in biofilm formation.

METHODS

We applied liquid chromatography-tandem mass spectrometry to determine the expressed proteome of F. nucleatum and P. gingivalis cells grown in biofilm or planktonic culture, and as mono- and dual-species models. The detected proteins were classified into functional categories and their label-free quantitative (LFQ) intensities statistically compared.

RESULTS

The proteomic analyses detected 1,322 F. nucleatum and 966 P. gingivalis proteins, including abundant virulence factors. Using univariate statistics, we identified significant changes between biofilm and planktonic culture (p-value ≤0.05) in 0,4% F. nucleatum, 7% P. gingivalis, and 14% of all proteins in the dual-species model. For both species, proteins involved in vitamin B2 (riboflavin) metabolism had significantly increased levels in biofilm. In both mono- and dual-species biofilms, P. gingivalis increased the production of proteins for translation, oxidation-reduction, and amino acid metabolism compared to planktonic cultures. However, when we compared LFQ intensities between mono- and dual-species, over 90% of the significantly changed P. gingivalis proteins had their levels reduced in biofilm and planktonic settings of the dual-species model.

CONCLUSIONS

The findings suggest that P. gingivalis reduces the production of multiple proteins because of the F. nucleatum presence. The results highlight the complex interactions of bacteria contributing to oral biofilms, which need to be considered in the design of prevention strategies.

Omics and interspecies interaction

Interspecies interactions are key determinants in biofilm behavior, ecology, and architecture. The cellular responses of microorganisms to each other at transcriptional, proteomic, and metabolomic levels ultimately determine the characteristics of biofilm and the corresponding implications for health and disease. Advances in omics technologies have revolutionized our understanding of microbial community composition and their activities as a whole. Large-scale analyses of the complex interaction between the many microbial species residing within a biofilm, however, are currently still hampered by technical and bioinformatics challenges. Thus, studies of interspecies interactions have largely focused on the transcriptional and proteomic changes that occur during the contact of a few prominent species, such as Porphyromonas gingivalis, Streptococcus mutans, Candida albicans, and a few others, with selected partner species. Expansion of available tools is necessary to grow the revealing, albeit limited, insight these studies have provided into a profound understanding of the nature of individual microbial responses to the presence of others. This will allow us to answer important questions including: Which intermicrobial interactions orchestrate the myriad of cooperative, synergistic, antagonistic, manipulative, and other types of relationships and activities in the complex biofilm environment, and what are the implications for oral health and disease?

Metaproteome and metabolome of oral microbial communities

The emergence of high-throughput technologies for the comprehensive measurement of biomolecules, also referred to as "omics" technologies, has helped us gather "big data" and characterize microbial communities. In this article, we focus on metaproteomic and metabolomic approaches that support hypothesis-driven investigations on various oral biologic samples. Proteomics reveals the working units of the oral milieu and metabolomics unveils the reactions taking place; and so these complementary techniques can unravel the functionality and underlying regulatory processes within various oral microbial communities. Current knowledge of the proteomic interplay and metabolic interactions of microorganisms within oral biofilm and salivary microbiome communities is presented and discussed, from both clinical and basic research perspectives. Communities indicative of, or from, health, caries, periodontal diseases, and endodontic lesions are represented. Challenges, future prospects, and examples of best practice are given.

Non-Invasive Luciferase Imaging of Type I Interferon Induction in a Transgenic Mouse Model of Biomaterial Associated Bacterial Infections: Microbial Specificity and Inter-Bacterial Species Interactions

The performance of biomaterials is often compromised by bacterial infections and subsequent inflammation. So far, the conventional analysis of inflammatory processes in vivo involves time-consuming histology and biochemical assays. The present study employed a mouse model where interferon beta (IFN-β) is monitored as a marker for non-invasive rapid detection of inflammation in implant-related infections. The mouse model comprises subcutaneous implantation of morphologically modified titanium, followed by experimental infections with four taxonomically diverse oral bacteria: Streptococcus oralis, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis and Treponema denticola (as mono culture or selected mixed-culture). IFN-β expression increased upon infections depending on the type of pathogen and was prolonged by the presence of the implant. IFN-β expression kinetics reduced with two mixed species infections when compared with the single species. Histological and confocal microscopy confirmed pathogen-specific infiltration of inflammatory cells at the implant-tissue interface. This was observed mainly in the vicinity of infected implants and was, in contrast to interferon expression, higher in infections with dual species. In summary, this non-invasive mouse model can be used to quantify longitudinally host inflammation in real time and suggests that the polymicrobial character of infection, highly relevant to clinical situations, has complex effects on host immunity.

Periodontal disease: From the lenses of light microscopy to the specs of proteomics and next-generation sequencing

Periodontal disease entails the inflammatory destruction of the tooth supporting (periodontal) tissues as a result of polymicrobial colonization of the tooth surface in the form of biofilms. Extensive data collected over the past decades on this chronic disease demonstrate that its progression is infrequent and episodic, and the susceptibility to it can vary among individuals. Physical assessments of previously occurring damage to periodontal tissues remain the cornerstone of detection and diagnosis, whereas traditionally used diagnostic procedures do neither identify susceptible individuals nor distinguish between disease-active and disease-inactive periodontal sites. Thus, more sensitive and accurate "measurable biological indicators" of periodontal diseases are needed in order to place diagnosis (e.g., the presence or stage) and management of the disease on a more rational less empirical basis. Contemporary "omics" technologies may help unlock the path to this quest. High throughput nucleic acid sequencing technologies have enabled us to examine the taxonomic distribution of microbial communities in oral health and disease, whereas proteomic technologies allowed us to decipher the molecular state of the host in disease, as well as the interactive cross-talk of the host with the microbiome. The newly established field of metaproteomics has enabled the identification of the repertoire of proteins that oral microorganisms use to compete or co-operate with each other. Vast such data is derived from oral biological fluids, including gingival crevicular fluid and saliva, which is progressively completed and catalogued as the analytical technologies and bioinformatics tools progressively advance. This chapter covers the current "omics"-derived knowledge on the microbiome, the host and their "interactome" with regard to periodontal diseases, and addresses challenges and opportunities ahead.

Proteomic Analysis of Lactobacillus nagelii in the Presence of Saccharomyces cerevisiae Isolated From Water Kefir and Comparison With Lactobacillus hordei

Water kefir is a slightly alcoholic and traditionally fermented beverage, which is prepared from sucrose, water, kefir grains, and dried or fresh fruits (e.g., figs). Lactobacillus (L.) nagelii, L. hordei, and Saccharomyces (S.) cerevisiae are predominant and stable lactic acid bacteria and yeasts, respectively, isolated from water kefir consortia. The growth of L. nagelii and L. hordei are improved in the presence of S. cerevisiae. In this work we demonstrate that quantitative comparative proteomics enables the investigation of interactions between LAB and yeast to predict real-time metabolic exchange in water kefir. It revealed 73 differentially expressed (DE) in L. nagelii TMW 1.1827 in the presence of S. cerevisiae. The presence of the yeast induced changes in the changes in the carbohydrate metabolism of L. nagelii and affected reactions involved in NAD⁺/NADH homeostasis. Furthermore, the DE enzymes involved in amino acid biosynthesis or catabolism predict that S. cerevisiae releases glutamine, histidine, methionine, and arginine, which are subsequently used by L. nagelii to ensure its survival in the water kefir consortium. In co-culture with S. cerevisiae, L. nagelii profits from riboflavin, most likely secreted by the yeast. The reaction of L. nagelii to the presence of S. cerevisiae differs from that one of the previously studied L. hordei, which displays 233 differentially expressed proteins, changes in citrate metabolism and an antidromic strategy for NAD⁺/NADH homeostasis. So far, aggregation promotion factors, i.e., formation of a specific glucan and bifunctional enzymes were only detected in L. hordei.

Tracking iron-associated proteomes in pathogens by a fluorescence approach

The high iron-dependence of Porphyromonas gingivalis, a major threat to oral health, inspired us to develop a fluorescence approach to mine its iron-associated proteome.

Microproteome of dentoalveolar tissues

Proteomic analysis of extracellular matrices (ECM) of dentoalveolar tissues can provide insights into developmental, pathological, and reparative processes. However, targeted dissection of mineralized tissues, dental cementum (DC), alveolar bone (AB), and dentin (DE), presents technical difficulties. We demonstrate an approach combining EDTA decalcification and laser capture microdissection (LCM), followed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), to analyze proteome profiles of these tissues. Using the LCM-LC-MS/MS approach, a total of 243 proteins was identified from all tissues, 193 proteins in DC, 147 in AB, and 135 proteins DE. Ninety proteins (37% of total) were common to all tissues, whereas 52 proteins (21%) were overlapping in only two. Also, 101 (42%) proteins were exclusively detected in DC (60), AB (15), or DE (26). Identification in all tissues of expected ECM proteins including collagen alpha-1(I) chain (COL1A1), collagen alpha-1(XII) chain (COL12A1), biglycan (BGN), asporin (ASPN), lumican (LUM), and fibromodulin (FMOD), served to validate the approach. Principal component analysis (PCA) and hierarchical clustering identified a high degree of similarity in DC and AB proteomes, whereas DE presented a distinct dataset. Exclusively and differentially identified proteins were detected from all three tissues. The protein-protein interaction network (interactome) of DC was notable for its inclusion of several indicators of metabolic function (e.g. mitochondrial proteins, protein synthesis, and calcium transport), possibly reflecting cementocyte activity. The DE proteome included known and novel mineralization regulators, including matrix metalloproteinase 20 (MMP-20), 5' nucleotidase (NT5E), and secreted phosphoprotein 24 (SPP-24 or SPP-2). Application of the LCM-LC-MS/MS approach to dentoalveolar tissues would be of value in many experimental designs, including developmental studies of transgenic animals, investigation of treatment effects, and identification of novel regenerative factors.

Insights into Dynamic Polymicrobial Synergy Revealed by Time-Coursed RNA-Seq

Many bacterial infections involve polymicrobial communities in which constituent organisms are synergistically pathogenic. Periodontitis, a commonly occurring chronic inflammatory disorder, is induced by multispecies bacterial communities. The periodontal keystone pathogen Porphyromonas gingivalis and the accessory pathogen Streptococcus gordonii exhibit polymicrobial synergy in animal models of disease. Mechanisms of co-adhesion and community formation by P. gingivalis and S. gordonii are well-established; however, little is known regarding the basis for increased pathogenicity. In this study we used time-coursed RNA-Seq to comprehensively and quantitatively examine the dynamic transcriptional landscape of P. gingivalis in a model consortium with S. gordonii. Genes encoding a number of potential virulence determinants had higher relative mRNA levels in the context of dual species model communities than P. gingivalis alone, including adhesins, the Type IX secretion apparatus, and tetratricopeptide repeat (TPR) motif proteins. In contrast, genes encoding conjugation systems and many of the stress responses showed lower levels of expression in P. gingivalis. A notable exception to reduced abundance of stress response transcripts was the genes encoding components of the oxidative stress-related OxyR regulon, indicating an adaptation of P. gingivalis to detoxify peroxide produced by the streptococcus. Collectively, the results are consistent with evolutionary adaptation of P. gingivalis to a polymicrobial oral environment, one outcome of which is increased pathogenic potential.

Identification and characterization of a minisatellite contained within a novel miniature inverted-repeat transposable element (MITE) of Porphyromonas gingivalis

Background

Repetitive regions of DNA and transposable elements have been found to constitute large percentages of eukaryotic and prokaryotic genomes. Such elements are known to be involved in transcriptional regulation, host-pathogen interactions and genome evolution.

Results

We identified a minisatellite contained within a miniature inverted-repeat transposable element (MITE) in Porphyromonas gingivalis. The P. gingivalis minisatellite and associated MITE, named ‘BrickBuilt’, comprises a tandemly repeating twenty-three nucleotide DNA sequence lacking spacer regions between repeats, and with flanking ‘leader’ and ‘tail’ subunits that include small inverted-repeat ends. Forms of the BrickBuilt MITE are found 19 times in the genome of P. gingivalis strain ATCC 33277, and also multiple times within the strains W83, TDC60, HG66 and JCVI SC001. BrickBuilt is always located intergenically ranging between 49 and 591 nucleotides from the nearest upstream and downstream coding sequences. Segments of BrickBuilt contain promoter elements with bidirectional transcription capabilities.

Conclusions

We performed a bioinformatic analysis of BrickBuilt utilizing existing whole genome sequencing, microarray and RNAseq data, as well as performing in vitro promoter probe assays to determine potential roles, mechanisms and regulation of the expression of these elements and their affect on surrounding loci. The multiplicity, localization and limited host range nature of MITEs and MITE-like elements in P. gingivalis suggest that these elements may play an important role in facilitating genome evolution as well as modulating the transcriptional regulatory system.

Electronic supplementary material

The online version of this article (doi:10.1186/s13100-015-0049-1) contains supplementary material, which is available to authorized users.