Informed interpretation of metagenomic data by StrainPhlAn enables strain retention analyses of the upper airway microbiome.

Shotgun metagenomic sequencing has the potential to provide bacterial strain-level resolution which is of key importance to tackle a host of clinical questions. While bioinformatic tools that achieve strain-level resolution are available, thorough benchmarking is needed to validate their use for less investigated and low biomass microbiomes like those from the upper respiratory tract. We analyzed a previously published data set of longitudinally collected nasopharyngeal samples from Bangladeshi infants (Microbiota and Health study) and a novel data set of oropharyngeal samples from Swiss children with cystic fibrosis. Data from bacterial cultures were used for benchmarking the parameters of StrainPhlAn 3, a bioinformatic tool designed for strain-level resolution. In addition, StrainPhlAn 3 results were compared with metagenomic assemblies derived from StrainGE and newly derived whole-genome sequencing data. After optimizing the analytical parameters, we compared StrainPhlAn 3 results to culture gold standard methods and achieved sensitivity values of 87% (Streptococcus pneumoniae), 80% (Moraxella catarrhalis), 75% (Haemophilus influenzae), and 57% (Staphylococcus aureus) for 420 nasopharyngeal and 75% (H. influenzae) and 46% (S. aureus) for 260 oropharyngeal samples. Comparing the phylogenetic tree of the core genome of 50 S. aureus isolates with a corresponding marker gene tree generated by StrainPhlAn 3 revealed a striking similarity in tree topology for all but three samples indicating adequate strain resolution. In conclusion, a comparison of StrainPhlAn 3 results to data from bacterial cultures revealed that strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA when parameters are carefully optimized to fit low biomass microbiomes.IMPORTANCEThe usage of 16S rRNA gene sequencing has become the state-of-the-art method for the characterization of the microbiota in health and respiratory disease. The method is reliable for low biomass samples due to prior amplification of the 16S rRNA gene but has limitations as species and certainly strain identification is not possible. However, the usage of metagenomic tools for the analyses of microbiome data from low biomass samples is not straight forward, and careful optimization is needed. In this work, we show that by validating StrainPhlAn 3 results with the data from bacterial cultures, the strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA being present when parameters are carefully optimized to fit low biomass microbiomes. This work further proposes that strain retention analyses are feasible, at least for more abundant species. This will help to better understand the longitudinal dynamics of the upper respiratory microbiome during health and disease

Tax Risk, Corporate Governance, and the Valuation of Tax Avoidance Across Philippine Firms: How Do Investors Value Corporate Tax Avoidance?

Tax avoidance has traditionally been thought to enhance firm value because it generates cash savings for reinvestment or distribution to shareholders. More recent literature, however, suggests that tax avoidance valuation may not be so simple. Desai and Dharmapala (2009) introduced the “agency perspective” on tax avoidance, arguing that investors consider the risk of tax avoidance as opening opportunities for managers to extract rents from their firms. Positive tax avoidance value would therefore be conditional on good corporate governance quality. Drake et al. (2017) introduced yet another dimension—tax risk—to the valuation of tax avoidance, arguing that tax avoidance that comes with less variability in tax outcomes (i.e., comes with lower tax risk) should be preferred to those that come with more because investors prefer stable earnings over risky earnings. This policy brief discusses our findings on how public investors in the Philippines value corporate tax avoidance in the contexts of tax risk and corporate governance quality, and policies that can be implemented to enhance firm transparency, increase tax revenues, and raise firm valuations

Introgression reshapes recombination distribution in grapevine interspecific hybrids

In grapevine interspecific hybrids, meiotic recombination is suppressed in homeologous regions and enhanced in homologous regions of recombined chromosomes, whereas crossover rate remains unchanged when chromosome pairs are entirely homeologous

Induction of the PPARγ (Peroxisome Proliferator-Activated Receptor γ)-GCM1 (Glial Cell Missing 1) syncytialization axis reduces sFLT1 (Soluble fms-Like Tyrosine Kinase 1) in the preeclamptic placenta

Preeclampsia is a hypertensive disorder of pregnancy that is a major cause of maternal-fetal morbidity and mortality worldwide. Severe preeclampsia (sPE) is mediated by pathology of the placental villi resulting in repressed PIGF (placental growth factor) production and hyper-secretion of sFLT1 (soluble fms-like tyrosine kinase 1), the net effect being wide-spread maternal endothelial dysfunction. Villous trophoblast differentiation is under control of the PPARγ (peroxisome proliferator-activated receptor γ) and GCM1 (glial cell missing 1) axis which is dysregulated in sPE. We hypothesized that disruption of trophoblast differentiation via the PPARγ-GCM1 axis is a major contribution to excess production of sFLT1 and pharmacological activation of PPARγ in the sPE placenta could reduce sFLT1 to normal levels. sPE, age-matched control placentas and first-trimester villous explants, were used to investigate the molecular relationships between PPARγ-GCM1 and sFLT1. We modulated this pathway by pharmacological activation/inhibition of PPARγ using Rosiglitazone and T0070907, respectively, and through siRNA repression of GCM1. PPARγ and GCM1 protein expressions are reduced in the sPE placenta while FLT1 protein and sFLT1 secretion are increased. GCM1 reduction in the first trimester explants significantly increased sFLT1 secretion, suggesting GCM1 as a key player in this pathway. Activation of PPARγ restored GCM1 and significantly reduced sFLT1 expression and release in first trimester and sPE placental villi. Functional integrity of the PPARγ-GCM1 axis in the villous trophoblast is critical for normal pregnancy development and is disrupted in the sPE placenta to favor excessive production of sFLT1. Pharmacological manipulation of PPARγ activity has the potential to rescue the antiangiogenic state of sPE and thereby prolong pregnancy and deliver improved clinical outcomes

A Phase 1a/1b Clinical Trial Design to Assess Safety, Acceptability, Pharmacokinetics and Tolerability of Intranasal Q-Griffithsin for COVID-19 Prophylaxis

Background: The COVID-19 pandemic remains an ongoing threat to global public health. Q-Griffithsin (Q-GRFT) is a lectin that has demonstrated potent broad-spectrum inhibitory activity in preclinical studies in models of Nipah virus and the beta coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2. Methods: Here, we propose a clinical trial design to test the safety, pharmacokinetics (PK), and tolerability of intranasally administered Q-GRFT for the prevention of SARS-CoV-2 infection as a prophylaxis strategy. The initial Phase 1a study will assess the safety and PK of a single dose of intranasally administered Q-GRFT. If found safe, the safety, PK, and tolerability of multiple doses of intranasal Q-GRFT will be assessed in a Phase 1b study. Group 1 participants will receive 3 mg of intranasal Q-GRFT (200 μL/nostril) once daily for 7 days. If this dose is tolerated, participants will be enrolled in Group 2 to receive 3 mg twice daily for 7 days. Secondary endpoints of the study will be user perceptions, acceptability, and the impact of product use on participants’ olfactory sensation and quality of life. Discussion: Results from this study will support further development of Q-GRFT as a prophylactic against respiratory viral infections in future clinical trials

Diatom DNA metabarcoding for ecological assessment: Comparison among bioinformatics pipelines used in six European countries reveals the need for standardization

Ecological assessment of lakes and rivers using benthic diatom assemblages currently requires considerable taxonomic expertise to identify species using light microscopy. This traditional approach is also time-consuming. Diatom metabarcoding is a promising alternative and there is increasing interest in using this approach for routine assessment. However, until now, analysis protocols for diatom metabarcoding have been developed and optimised by research groups working in isolation. The diversity of existing bioinformatics methods highlights the need for an assessment of the performance and comparability of results of different methods. The aim of this study was to test the correspondence of outputs from six bioinformatics pipelines currently in use for diatom metabarcoding in different European countries. Raw sequence data from 29 biofilm samples were treated by each of the bioinformatics pipelines, five of them using the same curated reference database. The outputs of the pipelines were compared in terms of sequence unit assemblages, taxonomic assignment, biotic index score and ecological assessment outcomes. The three last components were also compared to outputs from traditional light microscopy, which is currently accepted for ecological assessment of phytobenthos, as required by the Water Framework Directive. We also tested the performance of the pipelines on the two DNA markers (rbcL and 185-V4) that are currently used by the working groups participating in this study. The sequence unit assemblages produced by different pipelines showed significant differences in terms of assigned and unassigned read numbers and sequence unit numbers. When comparing the taxonomic assignments at genus and species level, correspondence of the taxonomic assemblages between pipelines was weak. Most discrepancies were linked to differential detection or quantification of taxa, despite the use of the same reference database. Subsequent calculation of biotic index scores also showed significant differences between approaches, which were reflected in the final ecological assessment. Use of the rbcL marker always resulted in better correlation among molecular datasets and also in results closer to these generated using traditional microscopy. This study shows that decisions made in pipeline design have implications for the dataset's structure and the taxonomic assemblage, which in turn may affect biotic index calculation and ecological assessment. There is a need to define best-practice bioinformatics parameters in order to ensure the best representation of diatom assemblages. Only the use of similar parameters will ensure the compatibility of data from different working groups. The future of diatom metabarcoding for ecological assessment may also lie in the development of new metrics using, for example, presence/absence instead of relative abundance data. (C) 2020 The Authors. Published by Elsevier B.V

Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using DiverseBreeds and Basal Diets

Previous shotgun metagenomic analyses of ruminal digesta identified some microbial information that might be useful as biomarkers to select cattle that emit less methane (CH4), which is a potent greenhouse gas. It is known that methane production (g/kgDMI) and to an extent the microbial community is heritable and therefore biomarkers can offer a method of selecting cattle for low methane emitting phenotypes. In this study a wider range of Bos Taurus cattle, varying in breed and diet, was investigated to determine microbial communities and genetic markers associated with high/low CH4 emissions. Digesta samples were taken from 50 beef cattle, comprising four cattle breeds, receiving two basal diets containing different proportions of concentrate and also including feed additives (nitrate or lipid), that may influence methane emissions. A combination of partial least square analysis and network analysis enabled the identification of the most significant and robust biomarkers of CH4 emissions (VIP > 0.8) across diets and breeds when comparing all potential biomarkers together. Genes associated with the hydrogenotrophic methanogenesis pathway converting carbon dioxide to methane, provided the dominant biomarkers of CH4 emissions and methanogens were the microbial populations most closely correlated with CH4 emissions and identified by metagenomics. Moreover, these genes grouped together as confirmed by network analysis for each independent experiment and when combined. Finally, the genes involved in the methane synthesis pathway explained a higher proportion of variation in CH4 emissions by PLS analysis compared to phylogenetic parameters or functional genes. These results confirmed the reproducibility of the analysis and the advantage to use these genes as robust biomarkers of CH4 emissions. Volatile fatty acid concentrations and ratios were significantly correlated with CH4, but these factors were not identified as robust enough for predictive purposes. Moreover, the methanotrophic Methylomonas genus was found to be negatively correlated with CH4. Finally, this study confirmed the importance of using robust and applicable biomarkers from the microbiome as a proxy of CH4 emissions across diverse production systems and environments

Solutions to improve targeted metagenomics studies

La métagénomique ciblée, étude de la composition et de la diversité des communautés microbiennes présentes dans différents échantillon biologiques sur la base d'un marqueur génomique, a connu un véritable essor lors de cette dernière décennie grâce à l'arrivée du séquençage haut-débit. Faisant appel à des outils de biologie moléculaire et de bioinformatique, elle a été à l’origine de substantiels progrès dans les domaines de l’évolution et de la diversité microbienne. Cependant, de nouvelles problématiques sont apparues avec le séquençage haut-débit : la génération exponentielle de données soulève des problèmes d'analyse bioinformatique, qui doit être adaptée aux plans d'expérience et aux questions biologiques associées. Cette thèse propose des solutions d'amélioration des études de métagénomique ciblée par le développement d'outils et de méthodes innovantes, apportant une meilleure compréhension des biais d'analyse inhérents à de telles études, et une meilleure conception des plans d'expérience. Tout d'abord, une expertise du pipeline d'analyse utilisé en production sur la plate-forme PEGASE-biosciences a été menée. Cette évaluation a révélé la nécessité de mettre en place une méthode d'évaluation formelle de pipelines d'analyses de données de métagénomique ciblée, qui a été développée sur la base de données simulées et réelles, et de métriques d'évaluation adaptées. Cette méthode a été utilisée sur plusieurs pipelines d'analyse couramment utilisés par la communauté, tout comme sur de nouvelles approches d'analyse jamais utilisées dans un tel contexte. Cette évaluation a permis de mieux comprendre les biais du plan d'expérience qui peuvent affecter les résultats et les conclusions biologiques associées. Un de ces biais majeurs est le choix des amorces d'amplification de la cible ; un logiciel de design d'amorces adaptées au plan d'expérience a été spécifiquement développé pour minimiser ce biais. Enfin, des recommandations de montage de plan d'expérience et d'analyse ont été émises afin d'améliorer la robustesse des études de métagénomique ciblée.Targeted metagenomics is the study of the composition of microbial communities in diverse biological samples, based on the sequencing of a genomic locus. This application has boomed over the last decade thanks to the democratisation of high-throughput sequencing, and has allowed substantial progress in the study of microbial evolution and diversity. However, new problems have emerged with high-throughput sequencing : the exponential generation of data must be properly analyzed with bioinformatics tools fitted to the experimental designs and associated biological questions. This dissertation provides solutions to improve targeted metagenomics studies, by the development of new tools and methods allowing a better understanding of analytical biases, and a better design of experiments. Firstly, an expert assessment of the analytical pipeline used on the PEGASE-biosciences plateform has been performed. This assessment revealed the need of a formal evaluation method of analytical pipelines used for targeted metagenomics analyses. This method has been developed with simulated and real datasets, and adequate evaluation metrics. It has been used on several analytical pipelines commonly used by the scientific community, as well as on new analytical methods which have never been used in such a context before. This evaluation allowed to better understand experimental design biases, which can affect the results and biological conclusions. One of those major biases is the design of amplification primers to target the genomic locus of interest. A primer design software, adaptable to different experimental designs, has been specifically developed to minimize this bias. Finally, analytical guidelines and experimental design recommendations have been formulated to improve targeted metagenomics studies