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There are still no highly sensitive and unique biomarkers for measurement of puberty onset. Circulating miRNAs have been shown to be promising biomarkers for diagnosis of various diseases. To identify circulating miRNAs that could be served as biomarkers for measuring chicken (Gallus gallus) puberty onset, the Solexa deep sequencing was performed to analyze the miRNA expression profiles in serum and plasma of hens from two different pubertal stages, before puberty onset (BO) and after puberty onset (AO). 197 conserved and 19 novel miRNAs (reads > 10) were identified as serum/plasma-expressed miRNAs in the chicken. The common miRNA amounts and their expression changes from BO to AO between serum and plasma were very similar, indicating the different treatments to generate serum and plasma had quite small influence on the miRNAs. 130 conserved serum-miRNAs were showed to be differentially expressed (reads > 10, P < 0.05) from BO to AO, with 68 up-regulated and 62 down-regulated. 4829 putative genes were predicted as the targets of the 40 most differentially expressed miRNAs (|log2(fold-change)|>1.0, P < 0.01). Functional analysis revealed several pathways that were associated with puberty onset. Further quantitative real-time PCR (RT-qPCR) test found that a seven-miRNA panel, including miR-29c, miR-375, miR-215, miR-217, miR-19b, miR-133a and let-7a, had great potentials to serve as novel biomarkers for measuring puberty onset in chicken. Due to highly conserved nature of miRNAs, the findings could provide cues for measurement of puberty onset in other animals as well as humans.

Onset of the rapid gonad growth is a milestone in sexual development that comprises many genes and regulatory factors. The observations in model organisms and mammals including humans have shown a potential link between miRNAs and development timing. To determine whether miRNAs play roles in this process in the chicken (Gallus gallus), the Solexa deep sequencing was performed to analyze the profiles of miRNA expression in the hypothalamus of hens from two different pubertal stages, before onset of the rapid gonad development (BO) and after onset of the rapid gonad development (AO). 374 conserved and 46 novel miRNAs were identified as hypothalamus-expressed miRNAs in the chicken. 144 conserved miRNAs were showed to be differentially expressed (reads > 10, P < 0.05) during the transition from BO to AO. Five differentially expressed miRNAs were validated by real-time quantitative RT-PCR (qRT-PCR) method. 2013 putative genes were predicted as the targets of the 15 most differentially expressed miRNAs (fold-change > 4.0, P < 0.01). Of these genes, 7 putative circadian clock genes, Per2, Bmal1/2, Clock, Cry1/2, and Star were found to be targeted multiple times by the miRNAs. qRT-PCR revealed the basic transcription levels of these clock genes were much higher (P < 0.01) in AO than in BO. Further functional analysis suggested that these 15 miRNAs play important roles in transcriptional regulation and signal transduction pathways. The results provide new insights into miRNAs functions in timing the rapid development of chicken gonads. Considering the characteristics of miRNA functional conservation, the results will contribute to the research on puberty onset in humans.

A microbial community is a dynamic system undergoing constant change in response to internal and external stimuli. These changes can have significant implications for human health. However, due to the difficulty in obtaining longitudinal samples, the study of the dynamic relationship between the microbiome and human health remains a challenge. Here, we introduce a novel computational strategy that uses massive cross-sectional sample data to model microbiome landscapes associated with chronic disease development. The strategy is based on the rationale that each static sample provides a snapshot of the disease process, and if the number of samples is sufficiently large, the footprints of individual samples populate progression trajectories, which enables us to recover disease progression paths along a microbiome landscape by using computational approaches. To demonstrate the validity of the proposed strategy, we developed a bioinformatics pipeline and applied it to a gut microbiome dataset available from a Crohn's disease study. Our analysis resulted in one of the first working models of microbial progression for Crohn's disease. We performed a series of interrogations to validate the constructed model. Our analysis suggested that the model recapitulated the longitudinal progression of microbial dysbiosis during the known clinical trajectory of Crohn's disease. By overcoming restrictions associated with complex longitudinal sampling, the proposed strategy can provide valuable insights into the role of the microbiome in the pathogenesis of chronic disease and facilitate the shift of the field from descriptive research to mechanistic studies.

BackgroundThe rupture of an intracranial aneurysm (IA) causes devastating subarachnoid hemorrhages, yet most IAs remain undiscovered until they rupture. Recently, we found an IA RNA expression signature of circulating neutrophils, and used transcriptome data to build predictive models for unruptured IAs. In this study, we evaluate the feasibility of using whole blood transcriptomes to predict the presence of unruptured IAs.MethodsWe subjected RNA from peripheral whole blood of 67 patients (34 with unruptured IA, 33 without IA) to next-generation RNA sequencing. Model genes were identified using the least absolute shrinkage and selection operator (LASSO) in a random training cohort (n = 47). These genes were used to train a Gaussian Support Vector Machine (gSVM) model to distinguish patients with IA. The model was applied to an independent testing cohort (n = 20) to evaluate performance by receiver operating characteristic (ROC) curve. Gene ontology and pathway analyses investigated the underlying biology of the model genes.ResultsWe identified 18 genes that could distinguish IA patients in a training cohort with 85% accuracy. This SVM model also had 85% accuracy in the testing cohort, with an area under the ROC curve of 0.91. Bioinformatics reflected activation and recruitment of leukocytes, activation of macrophages, and inflammatory response, suggesting that the biomarker captures important processes in IA pathogenesis.ConclusionsCirculating whole blood transcriptomes can detect the presence of unruptured IAs. Pending additional testing in larger cohorts, this could serve as a foundation to develop a simple blood-based test to facilitate screening and early detection of IAs.

OBJECTIVES:Clostridium difficile infection is a public health concern. C. difficile was found in healthy human intestine as a member of Clostridium XI. Because soluble fermentable fiber ingestion affects intestinal microbiota, we used fiber-containing diets to determine the intestinal microbial condition that could reduce the presence of Clostridium XI. METHODS:Newly weaned male mice were assigned to three published diets: Control AIN-93G purified diet with only poorly fermented cellulose; Control plus 5% purified fermentable fiber inulin; Chow with wheat, soybean and corn that provide a mixture of unpurified dietary fibers. Methods were developed to quantify 24-hour fecal microbial load and microbial DNA density. The relative abundance of bacterial genera and the bacterial diversity were determined through 16S rRNA sequence-based fecal microbiota analysis. RESULTS:Mice adjusted food intake to maintain the same energy intake and body weight under these three moderate-fat (7% w:w) diets. Chow-feeding led to higher food intake but also higher 24-h fecal output. Chow-feeding and 1-8 wk ingestion of inulin-supplemented diet increased daily fecal microbial load and density along with lowering the prevalence of Clostridium XI to undetectable. Clostridium XI remained undetectable until 4 weeks after the termination of inulin-supplemented diet. Fermentable fiber intake did not consistently increase probiotic genera such as Bifidobacterium or Lactobacillus. Chow feeding, but not inulin supplementation, increased the bacterial diversity. CONCLUSIONS:Increase fecal microbial load/density upon fermentable fiber ingestion is associated with a lower and eventually undetectable presence of Clostridium XI. Higher bacterial diversity or abundance of particular genera is not apparently essential. Future studies are needed to see whether this observation can be translated into the reduction of C. difficile at the species level in at-risk populations.

BACKGROUND:Unruptured intracranial aneurysms (IAs) are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs. METHODS:Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts. RESULTS:Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (p

[This corrects the article DOI: 10.1371/journal.pone.0166876.].

The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/∼yijunsun/lab/ESPRIT-Forest.html.

The modern Western diet is rich in advanced glycation end products (AGEs). We have previously shown an association between dietary AGEs and markers of inflammation and oxidative stress in a population of end stage renal disease (ESRD) patients undergoing peritoneal dialysis (PD). In the current pilot study we explored the effects of dietary AGEs on the gut bacterial microbiota composition in similar patients. AGEs play an important role in the development and progression of cardiovascular (CVD) disease. Plasma concentrations of different bacterial products have been shown to predict the risk of incident major adverse CVD events independently of traditional CVD risk factors, and experimental animal models indicates a possible role AGEs might have on the gut microbiota population. In this pilot randomized open label controlled trial, twenty PD patients habitually consuming a high AGE diet were recruited and randomized into either continuing the same diet (HAGE, n = 10) or a one-month dietary AGE restriction (LAGE, n = 10). Blood and stool samples were collected at baseline and after intervention. Variable regions V3-V4 of 16s rDNA were sequenced and taxa was identified on the phyla, genus, and species levels. Dietary AGE restriction resulted in a significant decrease in serum Nε-(carboxymethyl) lysine (CML) and methylglyoxal-derivatives (MG). At baseline, our total cohort exhibited a lower relative abundance of Bacteroides and Alistipes genus and a higher abundance of Prevotella genus when compared to the published data of healthy population. Dietary AGE restriction altered the bacterial gut microbiota with a significant reduction in Prevotella copri and Bifidobacterium animalis relative abundance and increased Alistipes indistinctus, Clostridium citroniae, Clostridium hathewayi, and Ruminococcus gauvreauii relative abundance. We show in this pilot study significant microbiota differences in peritoneal dialysis patients' population, as well as the effects of dietary AGEs on gut microbiota, which might play a role in the increased cardiovascular events in this population and warrants further studies.

Low temperature (LT) is one of the most important abiotic stresses that can significantly reduce crop yield. To gain insight into how Spirulina responds to LT stress, comprehensive physiological and proteomic analyses were conducted in this study. Significant decreases in growth and pigment levels as well as excessive accumulation of compatible osmolytes were observed in response to LT stress. An isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics approach was used to identify changes in protein abundance in Spirulina under LT. A total of 3,782 proteins were identified, of which 1,062 showed differential expression. Bioinformatics analysis indicated that differentially expressed proteins that were enriched in photosynthesis, carbohydrate metabolism, amino acid biosynthesis, and translation are important for the maintenance of cellular homeostasis and metabolic balance in Spirulina when subjected to LT stress. The up-regulation of proteins involved in gluconeogenesis, starch and sucrose metabolism, and amino acid biosynthesis served as coping mechanisms of Spirulina in response to LT stress. Moreover, the down-regulated expression of proteins involved in glycolysis, TCA cycle, pentose phosphate pathway, photosynthesis, and translation were associated with reduced energy consumption. The findings of the present study allow a better understanding of the response of Spirulina to LT stress and may facilitate in the elucidation of mechanisms underlying LT tolerance.

Previous studies in lower termites revealed unexpected synergies between nicotinoid insecticides and fungal entomopathogens. The present study investigated molecular mechanisms of nicotinoid-pathogen synergy in the lower termite Reticulitermes flavipes, using the nicotinoid, imidacloprid, in combination with fungal and bacterial entomopathogens. Particular focus was placed on metatranscriptome composition and microbial dynamics in the symbiont-rich termite gut, which houses diverse mixes of protists and bacteria. cDNA microarrays containing a mix of host and protist symbiont oligonucleotides were used to simultaneously assess termite and protist gene expression. Five treatments were compared that included single challenges with sublethal doses of fungi (Metharizium anisopliae), bacteria (Serratia marcescens) or imidacloprid, and dual challenges with fungi + imidacloprid or bacteria + imidacloprid. Our findings point towards protist dysbiosis and compromised social behavior, rather than suppression of stereotypical immune defense mechanisms, as the dominant factors underlying nicotinoid-pathogen synergy in termites. Also, greater impacts observed for the fungal pathogen than for the bacterial pathogen suggest that the rich bacterial symbiont community in the R. flavipes gut (>5000 species-level phylotypes) exists in an ecological balance that effectively excludes exogenous bacterial pathogens. These findings significantly advance our understanding of antimicrobial defenses in this important eusocial insect group, as well as provide novel insights into how nicotinoids can exert deleterious effects on social insect colonies.

Late onset sepsis (LOS) is a major contributor to neonatal morbidity and mortality, especially in premature infants. Distortions in the establishment of normal gut microbiota, commensal microbes that colonize the digestive tract, might increase the risk of LOS via disruption of the mucosal barrier with resultant translocation of luminal contents. Correlation of distortions of the intestinal microbiota with LOS is a necessary first step to design novel microbiota-based screening approaches that might lead to early interventions to prevent LOS in high risk infants. Using a case/control design nested in a cohort study of preterm infants, we analyzed stool samples that had been prospectively collected from ten preterm infants with LOS and from 18 matched controls. A 16S rRNA based approach was utilized to compare microbiota diversity and identify specific bacterial signatures that differed in their prevalence between cases and controls. Overall α-diversity (Chao1) was lower in cases two weeks before (p

Intestinal luminal microbiota likely contribute to the etiology of necrotizing enterocolitis (NEC), a common disease in preterm infants. Microbiota development, a cascade of initial colonization events leading to the establishment of a diverse commensal microbiota, can now be studied in preterm infants using powerful molecular tools. Starting with the first stool and continuing until discharge, weekly stool specimens were collected prospectively from infants with gestational ages ≤32 completed weeks or birth weights≤1250 g. High throughput 16S rRNA sequencing was used to compare the diversity of microbiota and the prevalence of specific bacterial signatures in nine NEC infants and in nine matched controls. After removal of short and low quality reads we retained a total of 110,021 sequences. Microbiota composition differed in the matched samples collected 1 week but not