7,915 research outputs found

    Metagenome and Metatranscriptome Analyses Using Protein Family Profiles

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    Analyses of metagenome data (MG) and metatranscriptome data (MT) are often challenged by a paucity of complete reference genome sequences and the uneven/low sequencing depth of the constituent organisms in the microbial community, which respectively limit the power of reference-based alignment and de novo sequence assembly. These limitations make accurate protein family classification and abundance estimation challenging, which in turn hamper downstream analyses such as abundance profiling of metabolic pathways, identification of differentially encoded/expressed genes, and de novo reconstruction of complete gene and protein sequences from the protein family of interest. The profile hidden Markov model (HMM) framework enables the construction of very useful probabilistic models for protein families that allow for accurate modeling of position specific matches, insertions, and deletions. We present a novel homology detection algorithm that integrates banded Viterbi algorithm for profile HMM parsing with an iterative simultaneous alignment and assembly computational framework. The algorithm searches a given profile HMM of a protein family against a database of fragmentary MG/MT sequencing data and simultaneously assembles complete or near-complete gene and protein sequences of the protein family. The resulting program, HMM-GRASPx, demonstrates superior performance in aligning and assembling homologs when benchmarked on both simulated marine MG and real human saliva MG datasets. On real supragingival plaque and stool MG datasets that were generated from healthy individuals, HMM-GRASPx accurately estimates the abundances of the antimicrobial resistance (AMR) gene families and enables accurate characterization of the resistome profiles of these microbial communities. For real human oral microbiome MT datasets, using the HMM-GRASPx estimated transcript abundances significantly improves detection of differentially expressed (DE) genes. Finally, HMM-GRASPx was used to reconstruct comprehensive sets of complete or near-complete protein and nucleotide sequences for the query protein families. HMM-GRASPx is freely available online from http://sourceforge.net/projects/hmm-graspx

    Origin and evolution of the octoploid strawberry genome.

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    Cultivated strawberry emerged from the hybridization of two wild octoploid species, both descendants from the merger of four diploid progenitor species into a single nucleus more than 1 million years ago. Here we report a near-complete chromosome-scale assembly for cultivated octoploid strawberry (Fragaria × ananassa) and uncovered the origin and evolutionary processes that shaped this complex allopolyploid. We identified the extant relatives of each diploid progenitor species and provide support for the North American origin of octoploid strawberry. We examined the dynamics among the four subgenomes in octoploid strawberry and uncovered the presence of a single dominant subgenome with significantly greater gene content, gene expression abundance, and biased exchanges between homoeologous chromosomes, as compared with the other subgenomes. Pathway analysis showed that certain metabolomic and disease-resistance traits are largely controlled by the dominant subgenome. These findings and the reference genome should serve as a powerful platform for future evolutionary studies and enable molecular breeding in strawberry

    The Human Gut and Dietary Salt: The Bacteroides/Prevotella Ratio as a Potential Marker of Sodium Intake and Beyond

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    The gut microbiota is a dynamic ecosystem that plays a pivotal role in maintaining host health. The perturbation of these microbes has been linked to several health conditions. Hence, they have emerged as promising targets for understanding and promoting good health. Despite the growing body of research on the role of sodium in health, its effects on the human gut microbiome remain under-explored. Here, using nutrition and metagenomics methods, we investigate the influence of dietary sodium intake and alterations of the human gut microbiota. We found that a high-sodium diet (HSD) altered the gut microbiota composition with a significant reduction in Bacteroides and inverse increase in Prevotella compared to a low-sodium diet (LSD). However, there is no clear distinction in the Firmicutes/Bacteroidetes (F/B) ratio between the two diet types. Metabolic pathway reconstruction revealed the presence of sodium reabsorption genes in the HSD, but not LSD. Since it is currently difficult in microbiome studies to confidently associate the F/B ratio with what is considered healthy (e.g., low sodium) or unhealthy (e.g., high sodium), we suggest that the use of a genus-based ratio such as the Bacteroides/Prevotella (B/P) ratio may be more beneficial for the application of microbiome studies in health

    Integrative high-throughput study of arsenic hyper-accumulation in Pteris vittata

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    Arsenic is a natural contaminant in the soil and ground water, which raises considerable concerns in food safety and human health worldwide. The fernPteris vittata (Chinese brake fern) is the first identified arsenic hyperaccumulator[1]. It and its close relatives have un-paralleled ability to tolerant arsenic and feature unique arsenic metabolisms. The focus of the research presented in this thesis is to elucidate the fundamentals of arsenic tolerance and hyper-accumulation in Pteris vittata through high throughput technology and bioinformatics tools. The transcriptome of the P. vittatagametophyte under arsenate stress was obtained using RNA-Seq technology and Trinity de novo assembly. Functional annotation of the transcriptome was performed in terms of blast search, Gene Ontology term assignment, Eukaryotic Orthologous Groups (KOG) classification, and pathway analysis. Differentially expressed genes induced by arsenic stress were identified, which revealed several key players in arsenic hyper-accumulation. As part of the efforts to annotate differentially expressed genes, literature of plant arsenic tolerance was collected and built into a searchable database using the Textpresso text-mining tool, which greatly facilitates the retrieval of biological facts involving arsenic related gene. In addition, an SVM-based named-entity recognition system was constructed to identify new references to genes in literature. The results provide excellent sequence resources for arsenic tolerance study in P.vittata, and establish a platform for integrative study using data of multiple types

    An integrative approach to identify hexaploid wheat miRNAome associated with development and tolerance to abiotic stress

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    Background: Wheat is a major staple crop with broad adaptability to a wide range of environmental conditions.This adaptability involves several stress and developmentally responsive genes, in which microRNAs (miRNAs) have emerged as important regulatory factors. However, the currently used approaches to identify miRNAs in this\ud polyploid complex system focus on conserved and highly expressed miRNAs avoiding regularly those that are often lineage-specific, condition-specific, or appeared recently in evolution. In addition, many environmental and biological factors affecting miRNA expression were not yet considered, resulting still in an incomplete repertoire of wheat miRNAs.\ud Results: We developed a conservation-independent technique based on an integrative approach that combines machine learning, bioinformatic tools, biological insights of known miRNA expression profiles and universal criteria of plant miRNAs to identify miRNAs with more confidence. The developed pipeline can potentially identify novel wheat miRNAs that share features common to several species or that are species specific or clade specific. It allowed the discovery of 199 miRNA candidates associated with different abiotic stresses and development stages. We also highlight from the raw data 267 miRNAs conserved with 43 miRBase families. The predicted miRNAs are highly associated with abiotic stress responses, tolerance and development. GO enrichment analysis showed that they may play biological and physiological roles associated with cold, salt and aluminum (Al) through auxin signaling pathways, regulation of gene expression, ubiquitination, transport, carbohydrates, gibberellins, lipid, glutathione and secondary metabolism, photosynthesis, as well as floral transition and flowering.\ud Conclusion: This approach provides a broad repertoire of hexaploid wheat miRNAs associated with abiotic stress responses, tolerance and development. These valuable resources of expressed wheat miRNAs will help in elucidating the regulatory mechanisms involved in freezing and Al responses and tolerance mechanisms as well as for development and flowering. In the long term, it may help in breeding stress tolerant plants

    Novel haloarchaeal viruses from Lake Retba infecting Haloferax and Halorubrum species

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    The diversity of archaeal viruses is severely undersampled compared with that of viruses infecting bacteria and eukaryotes, limiting our understanding on their evolution and environmental impacts. Here, we describe the isolation and characterization of four new viruses infecting halophilic archaea from the saline Lake Retba, located close to Dakar on the coast of Senegal. Three of the viruses, HRPV10, HRPV11 and HRPV12, have enveloped pleomorphic virions and should belong to the family Pleolipoviridae, whereas the forth virus, HFTV1, has an icosahedral capsid and a long non-contractile tail, typical of bacterial and archaeal members of the order Caudovirales. Comparative genomic and phylogenomic analyses place HRPV10, HRPV11 and HRPV12 into the genus Betapleolipovirus, whereas HFTV1 appears to be most closely related to the unclassified Halorubrum virus HRTV-4. Differently from HRTV-4, HFTV1 encodes host-derived minichromosome maintenance helicase and PCNA homologues, which are likely to orchestrate its genome replication. HFTV1, the first archaeal virus isolated on a Haloferax strain, could also infect Halorubrum sp., albeit with an eightfold lower efficiency, whereas pleolipoviruses nearly exclusively infected autochthonous Halorubrum strains. Mapping of the metagenomic sequences from this environment to the genomes of isolated haloarchaeal viruses showed that these known viruses are underrepresented in the available viromes.Peer reviewe

    Metabolic network analysis reveals microbial community interactions in anammox granules.

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    Microbial communities mediating anaerobic ammonium oxidation (anammox) represent one of the most energy-efficient environmental biotechnologies for nitrogen removal from wastewater. However, little is known about the functional role heterotrophic bacteria play in anammox granules. Here, we use genome-centric metagenomics to recover 17 draft genomes of anammox and heterotrophic bacteria from a laboratory-scale anammox bioreactor. We combine metabolic network reconstruction with metatranscriptomics to examine the gene expression of anammox and heterotrophic bacteria and to identify their potential interactions. We find that Chlorobi-affiliated bacteria may be highly active protein degraders, catabolizing extracellular peptides while recycling nitrate to nitrite. Other heterotrophs may also contribute to scavenging of detritus and peptides produced by anammox bacteria, and potentially use alternative electron donors, such as H2, acetate and formate. Our findings improve the understanding of metabolic activities and interactions between anammox and heterotrophic bacteria and offer the first transcriptional insights on ecosystem function in anammox granules
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