Comparison of two commercial DNA extraction kits for the analysis of nasopharyngeal bacterial communities

Characterization of microbial communities via next-generation sequencing (NGS) requires an extraction ofmicrobial DNA. Methodological differences in DNA extraction protocols may bias results and complicate inter-study comparisons. Here we compare the effect of two commonly used commercial kits (Norgen and Qiagen)for the extraction of total DNA on estimatingnasopharyngeal microbiome diversity. The nasopharynxis a reservoir for pathogens associated with respiratory illnesses and a key player in understandingairway microbial dynamics. Total DNA from nasal washes corresponding to 30 asthmatic children was extracted using theQiagenQIAamp DNA and NorgenRNA/DNA Purification kits and analyzed via IlluminaMiSeq16S rRNA V4 ampliconsequencing. The Norgen samples included more sequence reads and OTUs per sample than the Qiagen samples, but OTU counts per sample varied proportionallybetween groups (r = 0.732).Microbial profiles varied slightly between sample pairs, but alpha- and beta-diversity indices (PCoAand clustering) showed highsimilarity between Norgen and Qiagenmicrobiomes. Moreover, no significant differences in community structure (PERMANOVA and adonis tests) and taxa proportions (Kruskal-Wallis test) were observed betweenkits. Finally, aProcrustes analysis also showed low dissimilarity (M2 = 0.173; P\u3c 0.001) between the PCoAs of the two DNA extraction kits. Contrary to what has been observed in previous studies comparing DNA extraction methods, our 16S NGS analysis of nasopharyngeal washes did not reveal significant differences in community composition or structure between kits. Our findingssuggest congruence between column-based chromatography kits and supportthe comparison of microbiomeprofilesacross nasopharyngeal metataxonomic studies

Two sampling methods yield distinct microbial signatures in the nasopharynges of asthmatic children.

Background The nasopharynx is a reservoir for pathogens associated with respiratory illnesses, such as asthma. Next-generation sequencing (NGS) has been used to characterize the nasopharyngeal microbiome during health and disease. Most studies so far have surveyed the nasopharynx as a whole; however, less is known about spatial variation (biogeography) in nasal microenvironments and how sampling techniques may capture that microbial diversity. Findings We used targeted 16S rRNA MiSeq sequencing and two different sampling strategies [nasal washes (NW) and nasal brushes (NB)] to characterize the nasopharyngeal microbiota in 30 asthmatic children. Nasal brushing is more abrasive than nasal washing and targeted the inner portion of the inferior turbinate. This region is expected to be different from other nasal microenvironments. Nasal washing is not spatially specific. Our 30 × 2 nasal microbiomes generated 1,474,497 sequences, from which we identified an average of 157 and 186 OTUs per sample in the NW and NB groups, respectively. Microbiotas from NB showed significantly higher alpha-diversity than microbiotas from NW. Similarly, both nasal microbiotas were distinct from each other (PCoA) and significantly differed in their community composition and abundance in at least 9 genera (effective size ≥1 %). Conclusions Nasopharyngeal microenvironments in asthmatic children contain microbiotas with different diversity and structure. Nasal washes and brushes capture that diversity differently. Future microbial studies of the nasopharynx need to be aware of potential spatial variation (biogeography)

NKG2A inhibits TH2 cell effector function in vitro

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

VBP15, a glucocorticoid analogue, is effective at reducing allergic lung inflammation in mice

Asthma is a chronic inflammatory condition of the lower respiratory tract associated with airway hyperreactivity and mucus obstruction in which a majority of cases are due to an allergic response to environmental allergens. Glucocorticoids such as prednisone have been standard treatment for many inflammatory diseases for the past 60 years. However, despite their effectiveness, long-term treatment is often limited by adverse side effects believed to be caused by glucocorticoid receptor-mediated gene transcription. This has led to the pursuit of compounds that retain the anti-inflammatory properties yet lack the adverse side effects associated with traditional glucocorticoids. We have developed a novel series of steroidal analogues (VBP compounds) that have been previously shown to maintain anti-inflammatory properties such as NFκB-inhibition without inducing glucocorticoid receptor-mediated gene transcription. This study was undertaken to determine the effectiveness of the lead compound, VBP15, in a mouse model of allergic lung inflammation. We show that VBP15 is as effective as the traditional glucocorticoid, prednisolone, at reducing three major hallmarks of lung inflammation--NFκB activity, leukocyte degranulation, and pro-inflammatory cytokine release from human bronchial epithelial cells obtained from patients with asthma. Moreover, we found that VBP15 is capable of reducing inflammation of the lung in vivo to an extent similar to that of prednisone. We found that prednisolone--but not VBP15 shortens the tibia in mice upon a 5 week treatment regimen suggesting effective dissociation of side effects from efficacy. These findings suggest that VBP15 may represent a potent and safer alternative to traditional glucocorticoids in the treatment of asthma and other inflammatory diseases.Supported in part by grants from the NIH (1R41HL104939-01B; 1K26RR032082; 1P50AR060836-01; 1U54HD071601; 2R24HD050846-06, R01 HL033152- 25), DOD grants (W81XWH-11-1-0330; W81XWH-11-1-0782; W81XWH-10-1-0659; W81XWH-11-1-0809; W81XWH-09-1-0599) a translational research grant from MDA, pilot grant from Parent Project Muscular Dystrophy (PPMD), and a contribution from the Clark Family Foundation

Testing the Prognostic Accuracy of the Updated Pediatric Sepsis Biomarker Risk Model

Background We previously derived and validated a risk model to estimate mortality probability in children with septic shock (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl). PERSEVERE uses five biomarkers and age to estimate mortality probability. After the initial derivation and validation of PERSEVERE, we combined the derivation and validation cohorts (n = 355) and updated PERSEVERE. An important step in the development of updated risk models is to test their accuracy using an independent test cohort. Objective To test the prognostic accuracy of the updated version PERSEVERE in an independent test cohort. Methods Study subjects were recruited from multiple pediatric intensive care units in the United States. Biomarkers were measured in 182 pediatric subjects with septic shock using serum samples obtained during the first 24 hours of presentation. The accuracy of PERSEVERE 28-day mortality risk estimate was tested using diagnostic test statistics, and the net reclassification improvement (NRI) was used to test whether PERSEVERE adds information to a physiology-based scoring system. Results Mortality in the test cohort was 13.2%. Using a risk cut-off of 2.5%, the sensitivity of PERSEVERE for mortality was 83% (95% CI 62–95), specificity was 75% (68–82), positive predictive value was 34% (22–47), and negative predictive value was 97% (91–99). The area under the receiver operating characteristic curve was 0.81 (0.70–0.92). The false positive subjects had a greater degree of organ failure burden and longer intensive care unit length of stay, compared to the true negative subjects. When adding PERSEVERE to a physiology-based scoring system, the net reclassification improvement was 0.91 (0.47–1.35; p<0.001). Conclusions The updated version of PERSEVERE estimates mortality probability reliably in a heterogeneous test cohort of children with septic shock and provides information over and above a physiology-based scoring system

Asynchronous remodeling is a driver of failed regeneration in Duchenne muscular dystrophy

We sought to determine the mechanisms underlying failure of muscle regeneration that is observed in dystrophic muscle through hypothesis generation using muscle profiling data (human dystrophy and murine regeneration). We found that transforming growth factor β-centered networks strongly associated with pathological fibrosis and failed regeneration were also induced during normal regeneration but at distinct time points. We hypothesized that asynchronously regenerating microenvironments are an underlying driver of fibrosis and failed regeneration. We validated this hypothesis using an experimental model of focal asynchronous bouts of muscle regeneration in wild-type (WT) mice. A chronic inflammatory state and reduced mitochondrial oxidative capacity are observed in bouts separated by 4 d, whereas a chronic profibrotic state was seen in bouts separated by 10 d. Treatment of asynchronously remodeling WT muscle with either prednisone or VBP15 mitigated the molecular phenotype. Our asynchronous regeneration model for pathological fibrosis and muscle wasting in the muscular dystrophies is likely generalizable to tissue failure in chronic inflammatory states in other regenerative tissues

Identification of pediatric septic shock subclasses based on genome-wide expression profiling

<p>Abstract</p> <p>Background</p> <p>Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling.</p> <p>Methods</p> <p>Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization.</p> <p>Results</p> <p>Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the three putative subclasses (analysis of variance, Bonferonni correction, <it>P </it>< 0.05) identified 6,934 differentially regulated genes. K-means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the three subclasses. Leave one out cross-validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C.</p> <p>Conclusion</p> <p>Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes.</p