RAIphy: Phylogenetic classification of metagenomics samples using iterative refinement of relative abundance index profiles

Background: Computational analysis of metagenomes requires the taxonomical assignment of the genome contigs assembled from DNA reads of environmental samples. Because of the diverse nature of microbiomes, the length of the assemblies obtained can vary between a few hundred bp to a few hundred Kbp. Current taxonomic classification algorithms provide accurate classification for long contigs or for short fragments from organisms that have close relatives with annotated genomes. These are significant limitations for metagenome analysis because of the complexity of microbiomes and the paucity of existing annotated genomes. Results: We propose a robust taxonomic classification method, RAIphy, that uses a novel sequence similarity metric with iterative refinement of taxonomic models and functions effectively without these limitations. We have tested RAIphy with synthetic metagenomics data ranging between 100 bp to 50 Kbp. Within a sequence read range of 100 bp-1000 bp, the sensitivity of RAIphy ranges between 38%-81% outperforming the currently popular composition-based methods for reads in this range. Comparison with computationally more intensive sequence similarity methods shows that RAIphy performs competitively while being significantly faster. The sensitivityspecificity characteristics for relatively longer contigs were compared with the PhyloPythia and TACOA algorithms. RAIphy performs better than these algorithms at varying clade-levels. For an acid mine drainage (AMD) metagenome, RAIphy was able to taxonomically bin the sequence read set more accurately than the currently available methods, Phymm and MEGAN, and more accurately in two out of three tests than the much more computationally intensive method, PhymmBL. Conclusions: With the introduction of the relative abundance index metric and an iterative classification method, we propose a taxonomic classification algorithm that performs competitively for a large range of DNA contig lengths assembled from metagenome data. Because of its speed, simplicity, and accuracy RAIphy can be successfully used in the binning process for a broad range of metagenomic data obtained from environmental samples

Fine-Scale Bacterial Beta Diversity within a Complex Ecosystem (Zodletone Spring, OK, USA): The Role of the Rare Biosphere

The adaptation of pyrosequencing technologies for use in culture-independent diversity surveys allowed for deeper sampling of ecosystems of interest. One extremely well suited area of interest for pyrosequencing-based diversity surveys that has received surprisingly little attention so far, is examining fine scale (e.g. micrometer to millimeter) beta diversity in complex microbial ecosystems.We examined the patterns of fine scale Beta diversity in four adjacent sediment samples (1mm apart) from the source of an anaerobic sulfide and sulfur rich spring (Zodletone spring) in southwestern Oklahoma, USA. Using pyrosequencing, a total of 292,130 16S rRNA gene sequences were obtained. The beta diversity patterns within the four datasets were examined using various qualitative and quantitative similarity indices. Low levels of Beta diversity (high similarity indices) were observed between the four samples at the phylum-level. However, at a putative species (OTU(0.03)) level, higher levels of beta diversity (lower similarity indices) were observed. Further examination of beta diversity patterns within dominant and rare members of the community indicated that at the putative species level, beta diversity is much higher within rare members of the community. Finally, sub-classification of rare members of Zodletone spring community based on patterns of novelty and uniqueness, and further examination of fine scale beta diversity of each of these subgroups indicated that members of the community that are unique, but non novel showed the highest beta diversity within these subgroups of the rare biosphere.The results demonstrate the occurrence of high inter-sample diversity within seemingly identical samples from a complex habitat. We reason that such unexpected diversity should be taken into consideration when exploring gamma diversity of various ecosystems, as well as planning for sequencing-intensive metagenomic surveys of highly complex ecosystems

Novel high-rank phylogenetic lineages within a sulfur spring (Zodletone Spring, Oklahoma), revealed using a combined pyrosequencing-Sanger approach

The utilization of high-throughput sequencing technologies in 16S rRNA gene-based diversity surveys has indicated that within most ecosystems, a significant fraction of the community could not be assigned to known microbial phyla. Accurate determination of the phylogenetic affiliation of such sequences is difficult due to the short-read-length output of currently available high-throughput technologies. This fraction could harbor multiple novel phylogenetic lineages that have so far escaped detection. Here we describe our efforts in accurate assessment of the novelty and phylogenetic affiliation of selected unclassified lineages within a pyrosequencing data set generated from source sediments of Zodletone Spring, a sulfide- and sulfur-rich spring in southwestern Oklahoma. Lineage-specific forward primers were designed for 78 putatively novel lineages identified within the pyrosequencing data set, and representative nearly full-length small-subunit (SSU) rRNA gene sequences were obtained by pairing those primers with reverse universal bacterial primers. Of the 78 lineages tested, amplifiable products were obtained for 52, 32 of which had at least one nearly full-length sequence that was representative of the lineage targeted. Analysis of phylogenetic affiliation of the obtained Sanger sequences identified 5 novel candidate phyla and 10 novel candidate classes (within Fibrobacteres, Planctomycetes, and candidate phyla BRC1, GN12, TM6, TM7, LD1, WS2, and GN06) in the data set, in addition to multiple novel orders and families. The discovery of multiple novel phyla within a pilot study of a single ecosystem clearly shows the potential of the approach in identifying novel diversities within the rare biosphere.Peer reviewedMicrobiology and Molecular Genetic

Phylogenetic diversities and community structure of members of the extremely halophilic Archaea (order Halobacteriales) in multiple saline sediment habitats

We investigated the phylogenetic diversity and community structure of members of the halophilic Archaea (order Halobacteriales) in five distinct sediment habitats that experience various levels of salinity and salinity fluctuations (sediments from Great Salt Plains and Zodletone Spring in Oklahoma, mangrove tree sediments in Puerto Rico, sediment underneath salt heaps in a salt-processing plant, and sediments from the Great Salt Lake northern arm) using Halobacteriales-specific 16S rRNA gene primers. Extremely diverse Halobacteriales communities were encountered in all habitats, with 27 (Zodletone) to 37 (mangrove) different genera identified per sample, out of the currently described 38 Halobacteriales genera. With the exception of Zodletone Spring, where the prevalent geochemical conditions are extremely inhospitable to Halobacteriales survival, habitats with fluctuating salinity levels were more diverse than permanently saline habitats. Sequences affiliated with the recently described genera Halogranum, Halolamina, Haloplanus, Halosarcina, and Halorientalis, in addition to the genera Halorubrum, Haloferax, and Halobacterium, were among the most abundant and ubiquitous genera, suggesting a wide distribution of these poorly studied genera in saline sediments. The Halobacteriales sediment communities analyzed in this study were more diverse than and completely distinct from communities from typical hypersaline water bodies. Finally, sequences unaffiliated with currently described genera represented a small fraction of the total Halobacteriales communities, ranging between 2.5% (Zodletone) to 7.0% (mangrove and Great Salt Lake). However, these novel sequences were characterized by remarkably high levels of alpha and beta diversities, suggesting the presence of an enormous, yet-untapped supply of novel Halobacteriales genera within the rare biosphere of various saline ecosystems.Peer reviewedMicrobiology and Molecular Genetic

Discovery of anaerobic lithoheterotrophic haloarchaea, ubiquitous in hypersaline habitats

Hypersaline anoxic habitats harbour numerous novel uncultured archaea whose metabolic and ecological roles remain to be elucidated. Until recently, it was believed that energy generation via dissimilatory reduction of sulfur compounds is not functional at salt saturation conditions. Recent discovery of the strictly anaerobic acetotrophic Halanaeroarchaeum compels to change both this assumption and the traditional view on haloarchaea as aerobic heterotrophs. Here we report on isolation and characterization of a novel group of strictly anaerobic lithoheterotrophic haloarchaea, which we propose to classify as a new genus Halodesulfurarchaeum. Members of this previously unknown physiological group are capable of utilising formate or hydrogen as electron donors and elemental sulfur, thiosulfate or dimethylsulfoxide as electron acceptors. Using genome-wide proteomic analysis we have detected the full set of enzymes required for anaerobic respiration and analysed their substrate-specific expression. Such advanced metabolic plasticity and type of respiration, never seen before in haloarchaea, empower the wide distribution of Halodesulfurarchaeum in hypersaline inland lakes, solar salterns, lagoons and deep submarine anoxic brines. The discovery of this novel functional group of sulfur-respiring haloarchaea strengthens the evidence of their possible role in biogeochemical sulfur cycling linked to the terminal anaerobic carbon mineralisation in so far overlooked hypersaline anoxic habitats.</p

Quantification in cardiac MRI: advances in image acquisition and processing

Cardiac magnetic resonance (CMR) imaging enables accurate and reproducible quantification of measurements of global and regional ventricular function, blood flow, perfusion at rest and stress as well as myocardial injury. Recent advances in MR hardware and software have resulted in significant improvements in image quality and a reduction in imaging time. Methods for automated and robust assessment of the parameters of cardiac function, blood flow and morphology are being developed. This article reviews the recent advances in image acquisition and quantitative image analysis in CMR

Recording behaviour of indoor-housed farm animals automatically using machine vision technology: a systematic review

Large-scale phenotyping of animal behaviour traits is time consuming and has led to increased demand for technologies that can automate these procedures. Automated tracking of animals has been successful in controlled laboratory settings, but recording from animals in large groups in highly variable farm settings presents challenges. The aim of this review is to provide a systematic overview of the advances that have occurred in automated, high throughput image detection of farm animal behavioural traits with welfare and production implications. Peer-reviewed publications written in English were reviewed systematically following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After identification, screening, and assessment for eligibility, 108 publications met these specifications and were included for qualitative synthesis. Data collected from the papers included camera specifications, housing conditions, group size, algorithm details, procedures, and results. Most studies utilized standard digital colour video cameras for data collection, with increasing use of 3D cameras in papers published after 2013. Papers including pigs (across production stages) were the most common (n = 63). The most common behaviours recorded included activity level, area occupancy, aggression, gait scores, resource use, and posture. Our review revealed many overlaps in methods applied to analysing behaviour, and most studies started from scratch instead of building upon previous work. Training and validation sample sizes were generally small (mean±s.d. groups = 3.8±5.8) and in data collection and testing took place in relatively controlled environments. To advance our ability to automatically phenotype behaviour, future research should build upon existing knowledge and validate technology under commercial settings and publications should explicitly describe recording conditions in detail to allow studies to be reproduced

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

Transcriptomic analysis of lignocellulosic biomass degradation by the anaerobic fungal isolate Orpinomyces sp. strain C1A

Background: Anaerobic fungi reside in the rumen and alimentary tract of herbivores where they play an important role in the digestion of ingested plant biomass. The anaerobic fungal isolate Orpinomyces sp. strain C1A is an efficient biomass degrader, capable of simultaneous saccharification and fermentation of the cellulosic and hemicellulosic fractions in multiple types of lignocellulosic biomass. To understand the mechanistic and regulatory basis of biomass deconstruction in anaerobic fungi, we analyzed the transcriptomic profiles of C1A when grown on four different types of lignocellulosic biomass (alfalfa, energy cane, corn stover, and sorghum) versus a soluble sugar monomer (glucose).Results: A total of 468.2 million reads (70.2 Gb) were generated and assembled into 27,506 distinct transcripts. CAZyme transcripts identified included 385, 246, and 44 transcripts belonging to 44, 13, and 8 different glycoside hydrolases (GH), carbohydrate esterases, and polysaccharide lyases families, respectively. Examination of CAZyme transcriptional patterns indicates that strain C1A constitutively transcribes a high baseline level of CAZyme transcripts on glucose. Although growth on lignocellulosic biomass substrates was associated with a significant increase in transcriptional levels in few GH families, including the highly transcribed GH1 B-glucosidase, GH6 cellobiohydrolase, and GH9 endoglucanase, the transcriptional levels of the majority of CAZyme families and transcripts were not significantly altered in glucose-grown versus lignocellulosic biomass-grown cultures. Further, strain C1A co-transcribes multiple functionally redundant enzymes for cellulose and hemicellulose saccharification that are mechanistically and structurally distinct. Analysis of fungal dockerin domain-containing transcripts strongly suggests that anaerobic fungal cellulosomes represent distinct catalytic units capable of independently attacking and converting intact plant fibers to sugar monomers.Conclusions: Collectively, these results demonstrate that strain C1A achieves fast, effective biomass degradation by the simultaneous employment of a wide array of constitutively-transcribed cellulosome-bound and free enzymes with considerable functional overlap. We argue that the utilization of this indiscriminate strategy could be justified by the evolutionary history of anaerobic fungi, as well as their functional role within their natural habitat in the herbivorous gut.Peer reviewedMicrobiology and Molecular Genetic