Meta-omics analysis indicates the saliva microbiome and its proteins associated with the prognosis of oral cancer patients

Saliva is a biofluid that maintains the health of oral tissues and the homeostasis of oral microbiota. Studies have demonstrated that Oral squamous cell carcinoma (OSCC) patients have different salivary microbiota than healthy individuals. However, the relationship between these microbial differences and clinicopathological outcomes is still far from conclusive. Herein, we investigate the capability of using metagenomic and metaproteomic saliva profiles to distinguish between Control (C), OSCC without active lesion (L0), and OSCC with active lesion (L1) patients. The results show that there are significantly distinct taxonomies and functional changes in L1 patients compared to C and L0 patients, suggesting compositional modulation of the oral microbiome, as the relative abundances of Centipeda, Veillonella, and Gemella suggested by metagenomics are correlated with tumor size, clinical stage, and active lesion. Metagenomics results also demonstrated that poor overall patient survival is associated with a higher relative abundance of Stenophotromonas, Staphylococcus, Centipeda, Selenomonas, Alloscordovia, and Acitenobacter. Finally, compositional and functional differences in the saliva content by metaproteomics analysis can distinguish healthy individuals from OSCC patients. In summary, our study suggests that oral microbiota and their protein abundance have potential diagnosis and prognosis value for oral cancer patients. Further studies are necessary to understand the role of uniquely detected metaproteins in the microbiota of healthy and OSCC patients as well as the crosstalk between saliva host proteins and the oral microbiome present in OSCC.     

Genetic characterization of Colombian Brahman cattle using microsatellites markers

Genetic structure and diversity of 3789 animals of the Brahman breed from 23 Colombian regions were assessed. Considering the Brahman Zebu cattle as a single population, the multilocus test based on the HW equilibrium, shows significant differences (P < 0.001). Genetic characterization made on the cattle population allowed to examine the genetic variability, calculating a H _o = 0.6621. Brahman population in Colombia was a small subdivision wthin populations (F _it = 0.045), a geographic subdivision almost non-existent or low differentiation (F _st = 0.003) and the F _is calculated (0.042) indicates no detriment to the variability in the population, despite the narrow mating takes place or there is a force that causes the variability is sustained without inbreeding actually affect the cattle population. The outcomes of multivariate analyses, Bayesian inferences and interindividual genetic distances suggested that there is no genetic sub-structure in the population, because of the high rate of animal migration among regions.     

Abscisic acid and the herbicide safener cyprosulfamide cooperatively enhance abiotic stress tolerance in rice

Plants adapt to abiotic stress by undergoing diverse biochemical and physiological changes that involve hormone-dependent signaling pathways. The effects of plant hormones can be mimicked by exogenous chemical regulators such as herbicide safeners, which not only enhance stress tolerance but also confer hormetic benefits such as increased vigor and yield. In this study, rice plants growing in normal and saline soils were exposed to abscisic acid (ABA), the safener cyprosulfamide or both compounds together. We found that cyprosulfamide, either alone or in combination with ABA, protected the plants from salinity stress and induced vigorous growth, including the formation of new tillers and early flowering. Proteomic analysis identified several proteins that were induced by stress and/or the chemical treatments, including the late embryogenesis abundant protein OsLEA3, a putative mitochondrial translocase and a putative fumarylacetoacetate hydrolase. The corresponding genes were induced by stress and/or the individual chemical treatments, but expression dropped back when the stress was removed. However, the combination of ABA and cyprosulfamide prolonged the expression of all three genes beyond the stress period, and allowed the plants to maintain their enhanced growth characteristics. These data support a model involving cooperation between the cyprosulfamide and ABA signaling pathways. Accordingly, it was found that cyprosulfamide induces ABA synthesis more robustly than salinity stress, allowing the two regulators to converge on certain downstream target genes. We discuss the impact of our results on current models for the hormonal regulation of stress response pathways in rice and other plants.     

Are all Mexican odonate species documented? An assessment of species richness

With the aim of protecting Mexican diversity, one current governmental task is to complete national biological inventories. In the case of odonate insects, several researchers have hypothesized that species richness is complete (205 dragonflies and 151 damselflies), but there has not been any formal exercise to test this. Thus, we have investigated whether odonate species richness (for Mexican endemics, dragonflies (suborder Anisoptera), damselflies (suborder Zygoptera) and total species) is complete using sample-based and coverage-based rarefaction curves. Along with this, we also showed how good distribution data are in the country. The rarefaction curves have indicated 100% completeness for all groups suggesting that the inventory is complete. However, species' distribution data is highly patchy regarding areas either well (e.g. central Mexico) or badly (e.g. coast of Guerrero and Oaxaca) collected. We encourage researchers to continue odonate sampling in order to support at least three conservation actions: (i) conservation assessment of endangered species; (ii) knowledge of range shifts given rising global temperatures; and (iii) increase public interest and awareness in protected, touristic areas.     

A disappearing oasis in the semi-arid Chaco: Deficient palm regeneration and establishment

Palm forests of Copernicia alba are a rare habitat in the semi-arid Chaco of Northwestern Argentina, are centres of high species diversity, and provide key resources for many species. Our goal was to assess the conservation status of five C. alba patches in Northwestern Argentina: Reserve; Embarcación; Palma Sola; Vinalito; and, Talar. We compared patches to identify the sites with greatest conservation needs based on four criteria: population size structure; palm density (of individuals with height >1.30 m); probability of seedlings being browsed; and, presence of potential seed dispersers. We found that three (Embarcación, Reserve, and Talar) out of five sites had palm densities greater than 200 individuals/ha and only one site (Embarcación) showed a reverse J-shaped size structure for height. Reserve and Embarcación had the greatest probability of seedlings being browsed (0.99 ± 0.01 and 0.88 ± 0.12, respectively). A total of 14 potential disperser species of mammals and birds were recorded across the five sites. Only Reserve harboured all of the potential dispersers, but at least two potential disperser species were recorded at the other sites. None of the palm patches studied had an adequate conservation status. However, Embarcación met three out of four criteria, and therefore it can be considered to have the best conservation status in the semi-arid Chaco. Palma Sola and Vinalito have the greatest conservation needs. To conserve C. alba in Northwestern Argentina, strategies are needed that ensure seedling establishment for future populations to reach an adequate density and structure.     

Polymicrobial Infection with Major Periodontal Pathogens Induced Periodontal Disease and Aortic Atherosclerosis in Hyperlipidemic ApoEnull Mice

Periodontal disease (PD) and atherosclerosis are both polymicrobial and multifactorial and although observational studies supported the association, the causative relationship between these two diseases is not yet established. Polymicrobial infection-induced periodontal disease is postulated to accelerate atherosclerotic plaque growth by enhancing atherosclerotic risk factors of orally infected Apolipoprotein E deficient (ApoE^null) mice. At 16 weeks of infection, samples of blood, mandible, maxilla, aorta, heart, spleen, and liver were collected, analyzed for bacterial genomic DNA, immune response, inflammation, alveolar bone loss, serum inflammatory marker, atherosclerosis risk factors, and aortic atherosclerosis. PCR analysis of polymicrobial-infected (Porphyromonas gingivalis [P. gingivalis], Treponema denticola [T. denticola], and Tannerella forsythia [T. forsythia]) mice resulted in detection of bacterial genomic DNA in oral plaque samples indicating colonization of the oral cavity by all three species. Fluorescent in situ hybridization detected P. gingivalis and T. denticola within gingival tissues of infected mice and morphometric analysis showed an increase in palatal alveolar bone loss (p<0.0001) and intrabony defects suggesting development of periodontal disease in this model. Polymicrobial-infected mice also showed an increase in aortic plaque area (p<0.05) with macrophage accumulation, enhanced serum amyloid A, and increased serum cholesterol and triglycerides. A systemic infection was indicated by the detection of bacterial genomic DNA in the aorta and liver of infected mice and elevated levels of bacterial specific IgG antibodies (p<0.0001). This study was a unique effort to understand the effects of a polymicrobial infection with P. gingivalis, T. denticola and T. forsythia on periodontal disease and associated atherosclerosis in ApoE^null mice.     

Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks

The ensemble modeling (EM) approach has shown promise in capturing kinetic and regulatory effects in the modeling of metabolic networks. Efficacy of the EM procedure relies on the identification of model parameterizations that adequately describe all observed metabolic phenotypes upon perturbation. In this study, we propose an optimization-based algorithm for the systematic identification of genetic/enzyme perturbations to maximally reduce the number of models retained in the ensemble after each round of model screening. The key premise here is to design perturbations that will maximally scatter the predicted steady-state fluxes over the ensemble parameterizations. We demonstrate the applicability of this procedure for an Escherichia coli metabolic model of central metabolism by successively identifying single, double, and triple enzyme perturbations that cause the maximum degree of flux separation between models in the ensemble. Results revealed that optimal perturbations are not always located close to reaction(s) whose fluxes are measured, especially when multiple perturbations are considered. In addition, there appears to be a maximum number of simultaneous perturbations beyond which no appreciable increase in the divergence of flux predictions is achieved. Overall, this study provides a systematic way of optimally designing genetic perturbations for populating the ensemble of models with relevant model parameterizations.