PrimerEvalPy: a tool for in-silico evaluation of primers for targeting the microbiome.

BACKGROUND: The selection of primer pairs in sequencing-based research can greatly influence the results, highlighting the need for a tool capable of analysing their performance in-silico prior to the sequencing process. We therefore propose PrimerEvalPy, a Python-based package designed to test the performance of any primer or primer pair against any sequencing database. The package calculates a coverage metric and returns the amplicon sequences found, along with information such as their average start and end positions. It also allows the analysis of coverage for different taxonomic levels. RESULTS: As a case study, PrimerEvalPy was used to test the most commonly used primers in the literature against two oral 16S rRNA gene databases containing bacteria and archaea. The results showed that the most commonly used primer pairs in the oral cavity did not match those with the highest coverage. The best performing primer pairs were found for the detection of oral bacteria and archaea. CONCLUSIONS: This demonstrates the importance of a coverage analysis tool such as PrimerEvalPy to find the best primer pairs for specific niches. The software is available under the MIT licence at https://gitlab.citius.usc.es/lara.vazquez/PrimerEvalPy .

Update on the Role of Cytokines as Oral Biomarkers in the Diagnosis of Periodontitis.

Periodontitis is one of the world's most common chronic human diseases and has a significant impact on oral health. Recent evidence has revealed a link between periodontitis and certain severe systemic conditions. Moreover, periodontal patients remain so for life, even following successful therapy, requiring ongoing supportive care to prevent the disease's recurrence. The first challenge in treating the condition is ensuring a timely and accurate diagnosis since the loss of periodontal bone and soft tissue is progressive and largely irreversible. Although current clinical and radiographic parameters are the best available for identifying and monitoring the disease, the scientific community has a particular interest in finding quantifiable biomarkers in oral fluids that can improve early detection rates of periodontitis and evaluations of its severity. It is widely accepted that periodontitis is associated with polymicrobial dysbiosis and a chronic inflammatory immune response in the host. This response causes the generation of mediators like cytokines. Higher concentrations of cytokines are involved in inflammation and disease progression, acting as a network of biological redundancy. Most of the cytokines investigated concerning the periodontitis pathogenesis are proinflammatory. Of all of them, interleukin (IL) 1beta has been studied the most, followed by tumor necrosis factor (TNF) alpha and IL6. In contrast, only a few papers have evaluated antiinflammatory cytokines, with the most researched being IL4 and IL10. Several systemic reviews have concluded that the specific cytokines present in patients with periodontitis have a distinctive profile, which may indicate their possible discriminatory potential. In this chapter, the focus is on analyzing studies that investigate the accuracy of diagnoses of periodontitis based on the cytokines present in gingival crevicular fluid and saliva. The findings of our research group are also described.

Accuracy of single molecular biomarkers in saliva for the diagnosis of periodontitis: A systematic review and meta-analysis.

AIM: To analyse, using a meta-analytical approach, the diagnostic accuracy of single molecular biomarkers in saliva for the detection of periodontitis in systemically healthy subjects. MATERIALS AND METHODS: Articles on molecular biomarkers in saliva providing a binary contingency table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. Searches for candidate articles were conducted in six electronic databases. The methodological quality was assessed through the tool Quality Assessment of Diagnostic Studies. Meta-analyses were performed using the Hierarchical Summary Receiver Operating Characteristic model. RESULTS: Meta-analysis was possible for 5 of the 32 biomarkers studied. The highest values of sensitivity for the diagnosis of periodontitis were obtained for IL1beta (78.7%), followed by MMP8 (72.5%), IL6 and haemoglobin (72.0% for both molecules); the lowest sensitivity value was for MMP9 (70.3%). In terms of specificity estimates, MMP9 had the best result (81.5%), followed by IL1beta (78.0%) and haemoglobin (75.2%); MMP8 had the lowest specificity (70.5%). CONCLUSIONS: MMP8, MMP9, IL1beta, IL6 and Hb were salivary biomarkers with good capability to detect periodontitis in systemically healthy subjects. MMP8 and IL1beta are the most researched biomarkers in the field, both showing clinically fair effectiveness for the diagnosis of periodontitis.

Diagnostic accuracy of IL1ß in saliva: The development of predictive models for estimating the probability of the occurrence of periodontitis in non-smokers and smokers.

AIM: To obtain salivary interleukin (IL) 1ß-based models to predict the probability of the occurrence of periodontitis, differentiating by smoking habit. MATERIALS/METHODS: A total of 141 participants were recruited, 62 periodontally healthy controls and 79 subjects affected by periodontitis. Fifty of the diseased patients were given non-surgical periodontal treatment and showed significant clinical improvement in 2 months. IL1ß was measured in the salivary samples using the Luminex instrument. Binary logistic regression models were obtained to differentiate untreated periodontitis from periodontal health (first modelling) and untreated periodontitis from treated periodontitis (second modelling), distinguishing between non-smokers and smokers. The area under the curve (AUC) and classification measures were calculated. RESULTS: In the first modelling, IL1ß presented AUC values of 0.830 for non-smokers and 0.689 for smokers (accuracy = 77.6% and 70.7%, respectively). In the second, the predictive models revealed AUC values of 0.671 for non-smokers and 0.708 for smokers (accuracy = 70.0% and 75.0%, respectively). CONCLUSION: Salivary IL1ß has an excellent diagnostic capability when it comes to distinguishing systemically healthy patients with untreated periodontitis from those who are periodontally healthy, although this discriminatory potential is reduced in smokers. The diagnostic capacity of salivary IL1ß remains acceptable for differentiating between untreated and treated periodontitis.

ABC Transporters Required for Hexose Uptake by Clostridium phytofermentans.

The mechanisms by which bacteria uptake solutes across the cell membrane broadly impact their cellular energetics. Here, we use functional genomic, genetic, and biophysical approaches to reveal how Clostridium (Lachnoclostridium) phytofermentans, a model bacterium that ferments lignocellulosic biomass, uptakes plant hexoses using highly specific, nonredundant ATP-binding cassette (ABC) transporters. We analyze the transcription patterns of its 173 annotated sugar transporter genes to find those upregulated on specific carbon sources. Inactivation of these genes reveals that individual ABC transporters are required for uptake of hexoses and hexo-oligosaccharides and that distinct ABC transporters are used for oligosaccharides versus their constituent monomers. The thermodynamics of sugar binding shows that substrate specificity of these transporters is encoded by the extracellular solute-binding subunit. As sugars are not phosphorylated during ABC transport, we identify intracellular hexokinases based on in vitro activities. These mechanisms used by Clostridia to uptake plant hexoses are key to understanding soil and intestinal microbiomes and to engineer strains for industrial transformation of lignocellulose.IMPORTANCE Plant-fermenting Clostridia are anaerobic bacteria that recycle plant matter in soil and promote human health by fermenting dietary fiber in the intestine. Clostridia degrade plant biomass using extracellular enzymes and then uptake the liberated sugars for fermentation. The main sugars in plant biomass are hexoses, and here, we identify how hexoses are taken in to the cell by the model organism Clostridium phytofermentans We show that this bacterium uptakes hexoses using a set of highly specific, nonredundant ABC transporters. Once in the cell, the hexoses are phosphorylated by intracellular hexokinases. This study provides insight into the functioning of abundant members of soil and intestinal microbiomes and identifies gene targets to engineer strains for industrial lignocellulosic fermentation.

Accuracy of single molecular biomarkers in gingival crevicular fluid for the diagnosis of periodontitis: A systematic review and meta-analysis.

AIM: To analyse, by means of a meta-analytical approach, the diagnostic accuracy of molecular biomarkers in gingival crevicular fluid (GCF) for the detection of periodontitis in systemically healthy subjects. MATERIAL AND METHODS: Studies on GCF molecular biomarkers providing a binary classification table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. The search was performed using six electronic databases. The methodological quality of studies was assessed through the tool Quality Assessment of Diagnostic Studies. Meta-analyses were performed using the Hierarchical Summary Receiver Operating Characteristic, which adjusts classification data using random effects logistic regression. RESULTS: The included papers identified 36 potential biomarkers for the detection of periodontitis and for four of them meta-analyses were performed. The median sensitivity and specificity were for MMP8, 76.7% and 92.0%; for elastase, 74.6% and 81.1%; for cathepsin, 72.8% and 67.3%, respectively. The worst estimates of sensitivity and specificity were for trypsin (71.3% and 66.1%, respectively). CONCLUSIONS: MMP8 showed good sensitivity and excellent specificity, which resulted in this biomarker being clinically the most useful or effective for the diagnosis of periodontitis in systemically healthy subjects, regardless of smoking condition.

Detection of new biased agonists for the serotonin 5-HT2A receptor: modeling and experimental validation.

Detection of biased agonists for the serotonin 5-HT2A receptor can guide the discovery of safer and more efficient antipsychotic drugs. However, the rational design of such drugs has been hampered by the difficulty detecting the impact of small structural changes on signaling bias. To overcome these difficulties, we characterized the dynamics of ligand-receptor interactions of known biased and balanced agonists using molecular dynamics simulations. Our analysis revealed that interactions with residues S5.46 and N6.55 discriminate compounds with different functional selectivity. Based on our computational predictions, we selected three derivatives of the natural balanced ligand serotonin and experimentally validated their ability to act as biased agonists. Remarkably, our approach yielded compounds promoting an unprecedented level of signaling bias at the 5-HT2A receptor, which could help interrogate the importance of particular pathways in conditions like schizophrenia.

The microwave bacteriome: biodiversity of domestic and laboratory microwave ovens.

Microwaves have become an essential part of the modern kitchen, but their potential as a reservoir for bacterial colonization and the microbial composition within them remain largely unexplored. In this study, we investigated the bacterial communities in microwave ovens and compared the microbial composition of domestic microwaves, microwaves used in shared large spaces, and laboratory microwaves, using next-generation sequencing and culturing techniques. The microwave oven bacterial population was dominated by Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes, similar to the bacterial composition of human skin. Comparison with other environments revealed that the bacterial composition of domestic microwaves was similar to that of kitchen surfaces, whereas laboratory microwaves had a higher abundance of taxa known for their ability to withstand microwave radiation, high temperatures and desiccation. These results suggest that different selective pressures, such as human contact, nutrient availability and radiation levels, may explain the differences observed between domestic and laboratory microwaves. Overall, this study provides valuable insights into microwave ovens bacterial communities and their potential biotechnological applications.

The highly differentiated gut of Pachnoda marginata hosts sequential microbiomes: microbial ecology and potential applications.

Insect gut microbiomes play a crucial role in the insect development and are shaped, among other factors, by the specialized insect diet habits as well as the morphological structure of the gut. Rose chafers (Pachnoda spp.; Coleoptera: Scarabaeidae) have a highly differentiated gut characterized by a pronounced hindgut dilation which resembles a miniaturized rumen. Specifically, the species Pachnoda marginata has not been previously studied in detail in terms of microbial ecology. Here, we show a fine scale study of the highly compartmentalized gut of P. marginata by using amplicon and metagenomic sequencing to shed light on the bacterial, archaeal and fungal communities thriving in each section of the gut. We found a microbial gradient along the gut from aerobic (foregut) to strictly anaerobic communities (hindgut). In addition, we have characterized interesting biological activities and metabolic pathways of gut microbial communities related to cellulose degradation, methane production and sulfate reduction. Taken together, our results reveal the highly diverse microbial community and the potential of P. marginata gut as a source of industrially relevant microbial diversity.

The salivary microbiome as a diagnostic biomarker of periodontitis: a 16S multi-batch study before and after the removal of batch effects.

Introduction: Microbiome-based clinical applications that improve diagnosis related to oral health are of great interest to precision dentistry. Predictive studies on the salivary microbiome are scarce and of low methodological quality (low sample sizes, lack of biological heterogeneity, and absence of a validation process). None of them evaluates the impact of confounding factors as batch effects (BEs). This is the first 16S multi-batch study to analyze the salivary microbiome at the amplicon sequence variant (ASV) level in terms of differential abundance and machine learning models. This is done in periodontally healthy and periodontitis patients before and after removing BEs. Methods: Saliva was collected from 124 patients (50 healthy, 74 periodontitis) in our setting. Sequencing of the V3-V4 16S rRNA gene region was performed in Illumina MiSeq. In parallel, searches were conducted on four databases to identify previous Illumina V3-V4 sequencing studies on the salivary microbiome. Investigations that met predefined criteria were included in the analysis, and the own and external sequences were processed using the same bioinformatics protocol. The statistical analysis was performed in the R-Bioconductor environment. Results: The elimination of BEs reduced the number of ASVs with differential abundance between the groups by approximately one-third (Before=265; After=190). Before removing BEs, the model constructed using all study samples (796) comprised 16 ASVs (0.16%) and had an area under the curve (AUC) of 0.944, sensitivity of 90.73%, and specificity of 87.16%. The model built using two-thirds of the specimens (training=531) comprised 35 ASVs (0.36%) and had an AUC of 0.955, sensitivity of 86.54%, and specificity of 90.06% after being validated in the remaining one-third (test=265). After removing BEs, the models required more ASVs (all samples=200-2.03%; training=100-1.01%) to obtain slightly lower AUC (all=0.935; test=0.947), lower sensitivity (all=81.79%; test=78.85%), and similar specificity (all=91.51%; test=90.68%). Conclusions: The removal of BEs controls false positive ASVs in the differential abundance analysis. However, their elimination implies a significantly larger number of predictor taxa to achieve optimal performance, creating less robust classifiers. As all the provided models can accurately discriminate health from periodontitis, implying good/excellent sensitivities/specificities, the salivary microbiome demonstrates potential clinical applicability as a precision diagnostic tool for periodontitis.

Impact of smoking habit on the subgingival proteome in patients with periodontitis.

BACKGROUND: Few investigations evaluated smoking's impact on the periodontal proteome. Therefore, this study aimed to analyse the influence of tobacco on the overall periodontal proteome and the differential expression of gingival crevicular fluid (GCF) proteins using sequential window acquisition of all theoretical mass spectra (SWATH-MS). METHODS: GCF samples were collected from 40 periodontitis subjects (stages III-IV). These were separated based on smoking status into smokers (17), ex-smokers (10), and non-smokers (13). Samples were analysed using SWATH-MS, and proteins were identified using the UniProt human-specific database. Data are available via ProteomeXchange with the identifier PXD043474. Principal component analysis (PCA) was employed to examine the spectral mass distribution of the proteome. Protein expression was different for a p-value <0.05 and a log2 fold change ≥0.3 (upregulated) or ≤-0.3 (downregulated). RESULTS: The distribution of overall proteome did not differ between non-smokers, smokers, and ex-smokers. Considering protein expression, 23 were differentially expressed in smokers vs. non-smokers (16 upregulated and 7 downregulated), 17 in ex-smokers vs. non-smokers (2 upregulated and 15 downregulated), and only 8 in smokers vs. ex-smokers (7 upregulated and 1 downregulated). Smoking increased the expression of proteins related to epithelial hyperkeratinization (keratins type II cytoskeletal 4, type I cytoskeletal 13 and type I cytoskeletal 19, cornulin, and fatty acid-binding protein 5). However, multiple immunoglobulins were underexpressed when comparing smokers and ex-smokers to non-smokers. CONCLUSION: Although smoking does not significantly modify the overall GCF proteome associated with periodontitis, it alters the expression of several proteins compared to never-smokers and ex-smokers. PLAIN LANGUAGE SUMMARY: Smoking is a critical risk factor for the development and progression of periodontitis. However, evidence of the effect of smoking on the subgingival proteome is scarce. Therefore, this study aimed to determine the impact of smoking on the overall proteome and differential expression of gingival crevicular fluid (GCF) proteins using the sequential window acquisition of all theoretical mass spectra (SWATH-MS) proteomic technique. For this purpose, GCF samples were collected from 40 subjects with periodontitis, of which 17 were smokers, 10 were ex-smokers, and 13 were non-smokers. These samples were analysed by SWATH-MS, and proteins were identified using the UniProt human-specific database. Analysis of the overall proteome showed that its distribution was not significantly different between smokers, ex-smokers, and non-smokers. However, several proteins were found to be differentially expressed according to the smoking status. Smoking can increase the expression of several keratins and proteins related to hyperkeratinization of the epithelium. However, in ex-smokers, these proteins return to similar levels to those of non-smokers. Moreover, smoking may induce a lower expression of proteins related to adaptive immunity, such as immunoglobulins. This immunosuppressive effect may persist in ex-smokers.

Synthesis and binding affinity of new 1,4-disubstituted triazoles as potential dopamine D(3) receptor ligands.

A series of new 1,4-disubstituted triazoles was prepared from appropriate arylacetylenes and aminoalkylazides using click chemistry methodology. These compounds were evaluated as potential ligands on several subtypes of dopamine receptors in in vitro competition assays, showing high affinity for dopamine D3 receptors, lower affinity for D2 and D4, and no affinity for the D1 receptors. Compound 18 displayed the highest affinity at the D3 receptor with a Ki value of 2.7 nM, selectivity over D2 (70-fold) and D4 (200-fold), and behaviour as a competitive antagonist in the low nanomolar range.

The Microbiome of Things: Appliances, Machines, and Devices Hosting Artificial Niche-Adapted Microbial Communities.

As it is the case with natural substrates, artificial surfaces of man-made devices are home to a myriad of microbial species. Artificial products are not necessarily characterized by human-associated microbiomes; instead, they can present original microbial populations shaped by specific environmental-often extreme-selection pressures. This review provides a detailed insight into the microbial ecology of a range of artificial devices, machines, and appliances, which we argue are specific microbial niches that do not necessarily fit in the "build environment" microbiome definition. Instead, we propose here the Microbiome of Things (MoT) concept analogous to the Internet of Things (IoT) because we believe it may be useful to shed light on human-made, but not necessarily human-related, unexplored microbial niches.

A laboratory ice machine as a cold oligotrophic artificial microbial niche for biodiscovery.

Microorganisms are ubiquitously distributed in nature and usually appear as biofilms attached to a variety of surfaces. Here, we report the development of a thick biofilm in the drain pipe of several standard laboratory ice machines, and we describe and characterise, through culture-dependent and -independent techniques, the composition of this oligotrophic microbial community. By using culturomics, 25 different microbial strains were isolated and taxonomically identified. The 16S rRNA high-throughput sequencing analysis revealed that Bacteroidota and Proteobacteria were the most abundant bacterial phyla in the sample, followed by Acidobacteriota and Planctomycetota, while ITS high-throughput sequencing uncovered the fungal community was clearly dominated by the presence of a yet-unidentified genus from the Didymellaceae family. Alpha and beta diversity comparisons of the ice machine microbial community against that of other similar cold oligotrophic and/or artificial environments revealed a low similarity between samples, highlighting the ice machine could be considered a cold and oligotrophic niche with a unique selective pressure for colonisation of particular microorganisms. The recovery and analysis of high-quality metagenome-assembled genomes (MAGs) yielded a strikingly high rate of new species. The functional profiling of the metagenome sequences uncovered the presence of proteins involved in extracellular polymeric substance (EPS) and fimbriae biosynthesis and also allowed us to detect the key proteins involved in the cold adaptation mechanisms and oligotrophic metabolic pathways. The metabolic functions in the recovered MAGs confirmed that all MAGs have the genes involved in psychrophilic protein biosynthesis. In addition, the highest number of genes for EPS biosynthesis was presented in MAGs associated with the genus Sphingomonas, which was also recovered by culture-based method. Further, the MAGs with the highest potential gene number for oligotrophic protein production were closely affiliated with the genera Chryseoglobus and Mycobacterium. Our results reveal the surprising potential of a cold oligotrophic microecosystem within a machine as a source of new microbial taxa and provide the scientific community with clues about which microorganisms are able to colonise this ecological niche and what physiological mechanisms they develop. These results pave the way to understand how and why certain microorganisms can colonise similar anthropogenic environments.

Critical review of 16S rRNA gene sequencing workflow in microbiome studies: From primer selection to advanced data analysis.

The multi-batch reanalysis approach of jointly reevaluating gene/genome sequences from different works has gained particular relevance in the literature in recent years. The large amount of 16S ribosomal ribonucleic acid (rRNA) gene sequence data stored in public repositories and information in taxonomic databases of the same gene far exceeds that related to complete genomes. This review is intended to guide researchers new to studying microbiota, particularly the oral microbiota, using 16S rRNA gene sequencing and those who want to expand and update their knowledge to optimise their decision-making and improve their research results. First, we describe the advantages and disadvantages of using the 16S rRNA gene as a phylogenetic marker and the latest findings on the impact of primer pair selection on diversity and taxonomic assignment outcomes in oral microbiome studies. Strategies for primer selection based on these results are introduced. Second, we identified the key factors to consider in selecting the sequencing technology and platform. The process and particularities of the main steps for processing 16S rRNA gene-derived data are described in detail to enable researchers to choose the most appropriate bioinformatics pipeline and analysis methods based on the available evidence. We then produce an overview of the different types of advanced analyses, both the most widely used in the literature and the most recent approaches. Several indices, metrics and software for studying microbial communities are included, highlighting their advantages and disadvantages. Considering the principles of clinical metagenomics, we conclude that future research should focus on rigorous analytical approaches, such as developing predictive models to identify microbiome-based biomarkers to classify health and disease states. Finally, we address the batch effect concept and the microbiome-specific methods for accounting for or correcting them.

Impact of 16S rRNA Gene Redundancy and Primer Pair Selection on the Quantification and Classification of Oral Microbiota in Next-Generation Sequencing.

This study aimed to evaluate the number of 16S rRNA genes in the complete genomes of the bacterial and archaeal species inhabiting the human mouth and to assess how the use of different primer pairs would affect the detection and classification of redundant amplicons and matching amplicons (MAs) from different taxa. A total of 518 oral-bacterial and 191 oral-archaeal complete genomes were downloaded from the NCBI database, and their complete 16S rRNA genes were extracted. The numbers of genes and variants per genome were calculated. Next, 39 primer pairs were used to search for matches in the genomes and obtain amplicons. For each primer, we calculated the number of gene amplicons, variants, genomes, and species detected and the percentage of coverage at the species level with no MAs (SC-NMA). The results showed that 94.09% of oral bacteria and 52.59% of oral archaea had more than one intragenomic 16S rRNA gene. From 1.29% to 46.70% of bacterial species and from 4.65% to 38.89% of archaea detected by the primers had MAs. The best primers were the following (SC-NMA; region; position for Escherichia coli [GenBank version no. J01859.1]): KP_F048-OP_R030 for bacteria (93.55%; V3 to V7; 342 to 1079), KP_F018-KP_R063 for archaea (89.63%; V3 to V9; undefined to 1506), and OP_F114-OP_R121 for both domains (92.52%; V3 to V9; 340 to 1405). In addition to 16S rRNA gene redundancy, the presence of MAs must be controlled to ensure an accurate interpretation of microbial diversity data. The SC-NMA is a more useful parameter than the conventional coverage percentage for selecting the best primer pairs. The pairs used the most in the oral microbiome literature were not among the best performers. IMPORTANCE Hundreds of publications have studied the oral microbiome through 16S rRNA gene sequencing. However, none have assessed the number of 16S rRNA genes in the genomes of oral microbes, or how the use of primer pairs targeting different regions affects the detection of MAs from different taxa. Here, we found that almost all oral bacteria and more than half of oral archaea have more than one intragenomic 16S rRNA gene. The performance of the primer pairs in not detecting MAs increases as the length of the amplicon augments. As none of those most employed in the oral literature were among the best performers, we selected a series of primers to detect bacteria and/or archaea based on their percentage of species detected without MAs. The intragenomic 16S rRNA gene redundancy and the presence of MAs between distinct taxa need to be considered to ensure an accurate interpretation of microbial diversity data.

In silico evaluation and selection of the best 16S rRNA gene primers for use in next-generation sequencing to detect oral bacteria and archaea.

BACKGROUND: Sequencing has been widely used to study the composition of the oral microbiome present in various health conditions. The extent of the coverage of the 16S rRNA gene primers employed for this purpose has not, however, been evaluated in silico using oral-specific databases. This paper analyses these primers using two databases containing 16S rRNA sequences from bacteria and archaea found in the human mouth and describes some of the best primers for each domain. RESULTS: A total of 369 distinct individual primers were identified from sequencing studies of the oral microbiome and other ecosystems. These were evaluated against a database reported in the literature of 16S rRNA sequences obtained from oral bacteria, which was modified by our group, and a self-created oral archaea database. Both databases contained the genomic variants detected for each included species. Primers were evaluated at the variant and species levels, and those with a species coverage (SC) ≥75.00% were selected for the pair analyses. All possible combinations of the forward and reverse primers were identified, with the resulting 4638 primer pairs also evaluated using the two databases. The best bacteria-specific pairs targeted the 3-4, 4-7, and 3-7 16S rRNA gene regions, with SC levels of 98.83-97.14%; meanwhile, the optimum archaea-specific primer pairs amplified regions 5-6, 3-6, and 3-6, with SC estimates of 95.88%. Finally, the best pairs for detecting both domains targeted regions 4-5, 3-5, and 5-9, and produced SC values of 95.71-94.54% and 99.48-96.91% for bacteria and archaea, respectively. CONCLUSIONS: Given the three amplicon length categories (100-300, 301-600, and >600 base pairs), the primer pairs with the best coverage values for detecting oral bacteria were as follows: KP_F048-OP_R043 (region 3-4; primer pair position for Escherichia coli J01859.1: 342-529), KP_F051-OP_R030 (4-7; 514-1079), and KP_F048-OP_R030 (3-7; 342-1079). For detecting oral archaea, these were as follows: OP_F066-KP_R013 (5-6; 784-undefined), KP_F020-KP_R013 (3-6; 518-undefined), and OP_F114-KP_R013 (3-6; 340-undefined). Lastly, for detecting both domains jointly they were KP_F020-KP_R032 (4-5; 518-801), OP_F114-KP_R031 (3-5; 340-801), and OP_F066-OP_R121 (5-9; 784-1405). The primer pairs with the best coverage identified herein are not among those described most widely in the oral microbiome literature. Video Abstract.

Epigenetic Effects of Healthy Foods and Lifestyle Habits from the Southern European Atlantic Diet Pattern: A Narrative Review.

Recent scientific evidence has shown the importance of diet and lifestyle habits for the proper functioning of the human body. A balanced and healthy diet, physical activity, and psychological well-being have a direct beneficial effect on health and can have a crucial role in the development and prognosis of certain diseases. The Southern European Atlantic diet, also named the Atlantic diet, is a unique dietary pattern that occurs in regions that present higher life expectancy, suggesting that this specific dietary pattern is associated with positive health effects. In fact, it is enriched with nutrients of high biological value, which, together with its cooking methods, physical activity promotion, reduction in carbon footprint, and promoting of family meals, promote these positive effects on health. The latest scientific advances in the field of nutri-epigenetics have revealed that epigenetic markers associated with food or nutrients and environmental factors modulate gene expression and, therefore, are involved with both health and disease. Thus, in this review, we evaluated the main aspects that define the Southern European Atlantic diet and the potential epigenetic changes associated with them based on recent studies regarding the main components of these dietary patterns. In conclusion, based on the information existing in the literature, we postulate that the Southern European Atlantic diet could promote healthy aging by means of epigenetic mechanisms. This review highlights the necessity of performing longitudinal studies to demonstrate this proposal.

His452Tyr polymorphism in the human 5-HT2A receptor affects clozapine-induced signaling networks revealed by quantitative phosphoproteomics.

Antipsychotic drugs remain the current standard for schizophrenia treatment. Although they directly recognize the orthosteric binding site of numerous monoaminergic G protein-coupled receptors (GPCRs), these drugs, and particularly second-generation antipsychotics such as clozapine, all have in common a very high affinity for the serotonin 5-HT2A receptor (5-HT2AR). Using classical pharmacology and targeted signaling pathway assays, previous findings suggest that clozapine and other atypical antipsychotics behave principally as 5-HT2AR neutral antagonists and/or inverse agonists. However, more recent findings showed that antipsychotics may also behave as pathway-specific agonists. Reversible phosphorylation is a common element in multiple signaling networks. Combining a quantitative phosphoproteomic method with signaling network analysis, we tested the effect of clozapine treatment on the overall level of protein phosphorylation and signal transduction cascades in vitro in mammalian cell lines induced to express either the human 5-HT2AR or the H452Y variant of the gene encoding the 5-HT2AR receptor. This naturally occurring variation within the 5-HT2AR gene was selected because it has been repeatedly associated with schizophrenia patients who do not respond to clozapine treatment. Our data show that short time exposure (5 or 10 min) to clozapine (10-5 M) led to phosphorylation of numerous signaling components of pathways involved in processes such as endocytosis, ErbB signaling, insulin signaling or estrogen signaling. Cells induced to express the H452Y variant showed a different basal phosphoproteome, with increases in the phosphorylation of mTOR signaling components as a translationally relevant example. However, the effect of clozapine on the functional landscape of the phosphoproteome was significantly reduced in cells expressing the 5-HT2AR-H452Y construct. Together, these findings suggest that clozapine behaves as an agonist inducing phosphorylation of numerous pathways downstream of the 5-HT2AR, and that the single nucleotide polymorphism encoding 5-HT2AR-H452Y affects these clozapine-induced phosphorylation-dependent signaling networks.

In-Silico Detection of Oral Prokaryotic Species With Highly Similar 16S rRNA Sequence Segments Using Different Primer Pairs.

Although clustering by operational taxonomic units (OTUs) is widely used in the oral microbial literature, no research has specifically evaluated the extent of the limitations of this sequence clustering-based method in the oral microbiome. Consequently, our objectives were to: 1) evaluate in-silico the coverage of a set of previously selected primer pairs to detect oral species having 16S rRNA sequence segments with ≥97% similarity; 2) describe oral species with highly similar sequence segments and determine whether they belong to distinct genera or other higher taxonomic ranks. Thirty-nine primer pairs were employed to obtain the in-silico amplicons from the complete genomes of 186 bacterial and 135 archaeal species. Each fasta file for the same primer pair was inserted as subject and query in BLASTN for obtaining the similarity percentage between amplicons belonging to different oral species. Amplicons with 100% alignment coverage of the query sequences and with an amplicon similarity value ≥97% (ASI97) were selected. For each primer, the species coverage with no ASI97 (SC-NASI97) was calculated. Based on the SC-NASI97 parameter, the best primer pairs were OP_F053-KP_R020 for bacteria (region V1-V3; primer pair position for Escherichia coli J01859.1: 9-356); KP_F018-KP_R002 for archaea (V4; undefined-532); and OP_F114-KP_R031 for both (V3-V5; 340-801). Around 80% of the oral-bacteria and oral-archaea species analyzed had an ASI97 with at least one other species. These very similar species play different roles in the oral microbiota and belong to bacterial genera such as Campylobacter, Rothia, Streptococcus and Tannerella, and archaeal genera such as Halovivax, Methanosarcina and Methanosalsum. Moreover, ~20% and ~30% of these two-by-two similarity relationships were established between species from different bacterial and archaeal genera, respectively. Even taxa from distinct families, orders, and classes could be grouped in the same possible OTU. Consequently, regardless of the primer pair used, sequence clustering with a 97% similarity provides an inaccurate description of oral-bacterial and oral-archaeal species, which can greatly affect microbial diversity parameters. As a result, OTU clustering conditions the credibility of associations between some oral species and certain health and disease conditions. This significantly limits the comparability of the microbial diversity findings reported in oral microbiome literature.