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This article considers stochastic models for the spread of an infection in a structured community, where this structured community is itself described by a random network model. Some common network models and transmission models are defined and large population properties of them are presented. The focus is then shifted to statistical methodology: what can be estimated and how, depending on the underlying network, transmission model, and the available data? This survey article discusses several different scenarios, giving references to publications where more details can be found, and identifies important open problems.

Recently we have witnessed growing adoption of deep sequence models (e.g. LSTMs) in many application domains, including predictive health care, natural language processing, and log analysis. However, the intricate working mechanism of these models confines their accessibility to the domain experts. Their black-box nature also makes it a challenging task to incorporate domain-specific knowledge of the experts into the model. In ProtoSteer (Prototype Steering), we tackle the challenge of directly involving the domain experts to steer a deep sequence model without relying on model developers as intermediaries. Our approach originates in case-based reasoning, which imitates the common human problem-solving process of consulting past experiences to solve new problems. We utilize ProSeNet (Prototype Sequence Network), which learns a small set of exemplar cases (i.e., prototypes) from historical data. In ProtoSteer they serve both as an efficient visual summary of the original data and explanations of model decisions. With ProtoSteer the domain experts can inspect, critique, and revise the prototypes interactively. The system then incorporates user-specified prototypes and incrementally updates the model. We conduct extensive case studies and expert interviews in application domains including sentiment analysis on texts and predictive diagnostics based on vehicle fault logs. The results demonstrate that involvements of domain users can help obtain more interpretable models with concise prototypes while retaining similar accuracy.

Recently we have witnessed growing adoption of deep sequence models (e.g. LSTMs) in many application domains, including predictive health care, natural language processing, and log analysis. However, the intricate working mechanism of these models confines their accessibility to the domain experts. Their black-box nature also makes it a challenging task to incorporate domain-specific knowledge of the experts into the model. In ProtoSteer (Prototype Steering), we tackle the challenge of directly involving the domain experts to steer a deep sequence model without relying on model developers as intermediaries. Our approach originates in case-based reasoning, which imitates the common human problem-solving process of consulting past experiences to solve new problems. We utilize ProSeNet (Prototype Sequence Network), which learns a small set of exemplar cases (i.e., prototypes) from historical data. In ProtoSteer they serve both as an efficient visual summary of the original data and explanations of model decisions. With ProtoSteer the domain experts can inspect, critique, and revise the prototypes interactively. The system then incorporates user-specified prototypes and incrementally updates the model. We conduct extensive case studies and expert interviews in application domains including sentiment analysis on texts and predictive diagnostics based on vehicle fault logs. The results demonstrate that involvements of domain users can help obtain more interpretable models with concise prototypes while retaining similar accuracy.

Recently we have witnessed growing adoption of deep sequence models (e.g. LSTMs) in many application domains, including predictive health care, natural language processing, and log analysis. However, the intricate working mechanism of these models confines their accessibility to the domain experts. Their black-box nature also makes it a challenging task to incorporate domain-specific knowledge of the experts into the model. In ProtoSteer (Prototype Steering), we tackle the challenge of directly involving the domain experts to steer a deep sequence model without relying on model developers as intermediaries. Our approach originates in case-based reasoning, which imitates the common human problem-solving process of consulting past experiences to solve new problems. We utilize ProSeNet (Prototype Sequence Network), which learns a small set of exemplar cases (i.e., prototypes) from historical data. In ProtoSteer they serve both as an efficient visual summary of the original data and explanations of model decisions. With ProtoSteer the domain experts can inspect, critique, and revise the prototypes interactively. The system then incorporates user-specified prototypes and incrementally updates the model. We conduct extensive case studies and expert interviews in application domains including sentiment analysis on texts and predictive diagnostics based on vehicle fault logs. The results demonstrate that involvements of domain users can help obtain more interpretable models with concise prototypes while retaining similar accuracy.

The informally named “aervoid clade” in Amaranthaceae includes ~134 species in five genera: Ptilotus (~120 spp.), Aerva (11 spp.) and the monotypic Nothosaerva, Omegandra, and Kelita. The relationships of the small aervoid genera to the large genus Ptilotus, and relationships between major clades within Ptilotus, are poorly resolved. The aims of this study were to: (1) elucidate relationships between genera and within Ptilotus using a phylogenomic approach; (2) identify morphological characters within each genus to help delimit generic boundaries; and (3) provide an updated taxonomic framework for the aervoids. A well-supported coding DNA sequence (CDS) phylogeny was constructed for 36 aervoid and 5 outgroup species based on 69 gene sequences derived from assembled whole-plastid genomes. The CDS tree was used to constrain relationships on a larger phylogeny based on Sanger-sequenced ITS and matK for 135 taxa, comprising near-comprehensive sampling within the aervoids. Both datasets were analysed using maximum likelihood and Bayesian inference. Morphological characters were assessed from herbarium specimens. Our study demonstrates that Aerva is polyphyletic; this is resolved by reinstating Ouret and erecting a new genus, Paraerva. Kelita is found to be deeply nested within Ptilotus and is formally synonymised. The well-resolved phylogeny of Ptilotus presented here will inform future studies in biogeography and character evolution. A taxonomic treatment is provided for all aervoid genera, and new combinations are made.

DNA sequence reads contain information about the genomic variants located on a single chromosome. By extracting and extending this information using the overlaps between the reads, the haplotypes of an individual can be obtained. Using parent-offspring relationships in a population can considerably improve the quality of the haplotypes obtained from short reads, as pedigree information can be used to correct for spurious overlaps (due to sequencing errors) and insufficient overlaps (due to short read lengths, low genomic variation and shallow coverage). We developed a novel method, PopPoly, to estimate polyploid haplotypes in an F1-population from short sequence data by taking into consideration the transmission of the haplotypes from the parents to the offspring. In addition, this information is employed to improve genotype dosage estimation and to call missing genotypes in the population. Through simulations, we compare PopPoly to other haplotyping methods and show its better performance. We evaluate PopPoly by applying it to a tetraploid potato cross at nine genomic regions involved in tuber formation.

[EN] Background: Hanwoo beef is known for its marbled fat, tenderness, juiciness and characteristic flavor, as well as for its low cholesterol and high omega 3 fatty acid contents. As yet, there has been no comprehensive investigation to estimate genomic selection accuracy for carcass traits in Hanwoo cattle using dense markers. This study aimed at evaluating the accuracy of alternative statistical methods that differed in assumptions about the underlying genetic model for various carcass traits: backfat thickness (BT), carcass weight (CW), eye muscle area (EMA), and marbling score (MS). Methods: Accuracies of direct genomic breeding values (DGV) for carcass traits were estimated by applying fivefold cross-validation to a dataset including 1183 animals and approximately 34,000 single nucleotide polymorphisms (SNPs). Results: Accuracies of BayesC, Bayesian LASSO (BayesL) and genomic best linear unbiased prediction (GBLUP) methods were similar for BT, EMA and MS. However, for CW, DGV accuracy was 7% higher with BayesC than with BayesL and GBLUP. The increased accuracy of BayesC, compared to GBLUP and BayesL, was maintained for CW, regardless of the training sample size, but not for BT, EMA, and MS. Genome-wide association studies detected consistent large effects for SNPs on chromosomes 6 and 14 for CW. Conclusions: The predictive performance of the models depended on the trait analyzed. For CW, the results showed a clear superiority of BayesC compared to GBLUP and BayesL. These findings indicate the importance of using a proper variable selection method for genomic selection of traits and also suggest that the genetic architecture that underlies CW differs from that of the other carcass traits analyzed. Thus, our study provides significant new insights into the carcass traits of Hanwoo cattle.

[EN] Background: Hanwoo beef is known for its marbled fat, tenderness, juiciness and characteristic flavor, as well as for its low cholesterol and high omega 3 fatty acid contents. As yet, there has been no comprehensive investigation to estimate genomic selection accuracy for carcass traits in Hanwoo cattle using dense markers. This study aimed at evaluating the accuracy of alternative statistical methods that differed in assumptions about the underlying genetic model for various carcass traits: backfat thickness (BT), carcass weight (CW), eye muscle area (EMA), and marbling score (MS). Methods: Accuracies of direct genomic breeding values (DGV) for carcass traits were estimated by applying fivefold cross-validation to a dataset including 1183 animals and approximately 34,000 single nucleotide polymorphisms (SNPs). Results: Accuracies of BayesC, Bayesian LASSO (BayesL) and genomic best linear unbiased prediction (GBLUP) methods were similar for BT, EMA and MS. However, for CW, DGV accuracy was 7% higher with BayesC than with BayesL and GBLUP. The increased accuracy of BayesC, compared to GBLUP and BayesL, was maintained for CW, regardless of the training sample size, but not for BT, EMA, and MS. Genome-wide association studies detected consistent large effects for SNPs on chromosomes 6 and 14 for CW. Conclusions: The predictive performance of the models depended on the trait analyzed. For CW, the results showed a clear superiority of BayesC compared to GBLUP and BayesL. These findings indicate the importance of using a proper variable selection method for genomic selection of traits and also suggest that the genetic architecture that underlies CW differs from that of the other carcass traits analyzed. Thus, our study provides significant new insights into the carcass traits of Hanwoo cattle.

Here we introduce a MIxS extension to facilitate the recording and cataloguing of metadata from samples related to hydrocarbon resources. The proposed MIxS-HCR package incorporates the core features of the MIxS standard for marker gene (MIMARKS) and metagenomic (MIMS) sequences along with a hydrocarbon resources customized environmental package. Adoption of the MIxS-HCR standard will enable the comparison and better contextualization of investigations related to hydrocarbon rich environments. The insights from such standardized way of reporting could be highly beneficial for the successful development and optimization of hydrocarbon recovery processes and management of microbiological issues in petroleum production systems.

Here we introduce a MIxS extension to facilitate the recording and cataloguing of metadata from samples related to hydrocarbon resources. The proposed MIxS-HCR package incorporates the core features of the MIxS standard for marker gene (MIMARKS) and metagenomic (MIMS) sequences along with a hydrocarbon resources customized environmental package. Adoption of the MIxS-HCR standard will enable the comparison and better contextualization of investigations related to hydrocarbon rich environments. The insights from such standardized way of reporting could be highly beneficial for the successful development and optimization of hydrocarbon recovery processes and management of microbiological issues in petroleum production systems.

Real or imputed high-density SNP genotypes are routinely used for genomic prediction and genome-wide association studies. Many researchers are moving toward the use of actual or imputed next-generation sequence data in whole-genome analyses. Simulation studies are useful to mimic complex scenarios and test different analytical methods. We have developed the software tool XSim to efficiently simulate sequence data in descendants in arbitrary pedigrees. In this software, a strategy to drop-down origins and positions of chromosomal segments rather than every allele state is implemented to simulate sequence data and to accommodate complicated pedigree structures across multiple generations. Both C++ and Julia versions of XSim have been developed.

The accelerating loss of biodiversity has created a need for more effective ways to discover species. Novel algorithmic approaches for analyzing sequence data combined with rapidly expanding DNA barcode libraries provide a potential solution. While several analytical methods are available for the delineation of operational taxonomic units (OTUs), few studies have compared their performance. This study compares the performance of one morphology- based and four DNA-based (BIN, parsimony networks, ABGD, GMYC) methods on two groups of gelechioid moths. It examines 92 species of Finnish Gelechiinae and 103 species of Australian Elachistinae which were delineated by traditional taxonomy. The results reveal a striking difference in performance between the two taxa with all four DNA-based methods. OTU counts in the Elachistinae showed a wider range and a relatively low (ca. 65%) OTU match with reference species while OTU counts were more congruent and performance was higher (ca. 90%) in the Gelechiinae. Performance rose when only monophyletic species were compared, but the taxon-dependence remained. None of the DNA-based methods produced a correct match with non-monophyletic species, but singletons were handled well. A simulated test of morphospecies-grouping performed very poorly in revealing taxon diversity in these small, dull-colored moths. Despite the strong performance of analyses based on DNA barcodes, species delineated using single-locus mtDNA data are best viewed as OTUs that require validation by subsequent integrative taxonomic work.

Real or imputed high-density SNP genotypes are routinely used for genomic prediction and genome-wide association studies. Many researchers are moving toward the use of actual or imputed next-generation sequence data in whole-genome analyses. Simulation studies are useful to mimic complex scenarios and test different analytical methods. We have developed the software tool XSim to efficiently simulate sequence data in descendants in arbitrary pedigrees. In this software, a strategy to drop-down origins and positions of chromosomal segments rather than every allele state is implemented to simulate sequence data and to accommodate complicated pedigree structures across multiple generations. Both C++ and Julia versions of XSim have been developed.

Soil biodiversity is immense, with an estimated 10–100 million organisms belonging to over 5000 taxa in a handful of soil. In spite of the importance of soil biodiversity for ecosystem functions and services, information on soil species, from taxonomy to biogeographical patterns, is incomplete and there is no infrastructure to connect pre-existing or future data. Here, we propose a global platform to allow for greater access to soil biodiversity information by linking databases and repositories through a single open portal. The proposed platform would for the first time, link data on soil organisms from different global sites and biomes, and will be inclusive of all data types, from molecular sequences to morphology measurements and other supporting information. Access to soil biodiversity species records and information will be instrumental to progressing scientific research and education. Further, as demonstrated by previous biodiversity synthesis efforts, data availability is key for adapting to, and creating mitigation plans in response to global changes. With the rapid influx of soil biodiversity data, now is the time to take the first steps forward in establishing a global soil biodiversity information platform.

Soil biodiversity is immense, with an estimated 10–100 million organisms belonging to over 5000 taxa in a handful of soil. In spite of the importance of soil biodiversity for ecosystem functions and services, information on soil species, from taxonomy to biogeographical patterns, is incomplete and there is no infrastructure to connect pre-existing or future data. Here, we propose a global platform to allow for greater access to soil biodiversity information by linking databases and repositories through a single open portal. The proposed platform would for the first time, link data on soil organisms from different global sites and biomes, and will be inclusive of all data types, from molecular sequences to morphology measurements and other supporting information. Access to soil biodiversity species records and information will be instrumental to progressing scientific research and education. Further, as demonstrated by previous biodiversity synthesis efforts, data availability is key for adapting to, and creating mitigation plans in response to global changes. With the rapid influx of soil biodiversity data, now is the time to take the first steps forward in establishing a global soil biodiversity information platform.

The application of whole genome capture (WGC) methods to ancient DNA (aDNA) promises to increase the efficiency of ancient genome sequencing.We compared the performance of two recently developed WGC methods in enriching human aDNA within Illumina libraries built using both double-stranded (DSL) and single-stranded (SSL) build protocols. Although both methods effectively enriched aDNA, one consistently produced marginally better results, giving us the opportunity to further explore the parameters influencing WGC experiments.Our results suggest that bait length has an important influence on library enrichment. Moreover, we show that WGC biases against the shorter molecules that are enriched in SSL preparation protocols. Therefore application of WGC to such samples is not recommended without future optimization. Lastly, we document the effect of WGC on other features including clonality, GC composition and repetitive DNA content of captured libraries.Our findings provide insights for researchers planning to perform WGC on aDNA, and suggest future tests and optimization to improve WGC efficiency.

The application of whole genome capture (WGC) methods to ancient DNA (aDNA) promises to increase the efficiency of ancient genome sequencing.We compared the performance of two recently developed WGC methods in enriching human aDNA within Illumina libraries built using both double-stranded (DSL) and single-stranded (SSL) build protocols. Although both methods effectively enriched aDNA, one consistently produced marginally better results, giving us the opportunity to further explore the parameters influencing WGC experiments.Our results suggest that bait length has an important influence on library enrichment. Moreover, we show that WGC biases against the shorter molecules that are enriched in SSL preparation protocols. Therefore application of WGC to such samples is not recommended without future optimization. Lastly, we document the effect of WGC on other features including clonality, GC composition and repetitive DNA content of captured libraries.Our findings provide insights for researchers planning to perform WGC on aDNA, and suggest future tests and optimization to improve WGC efficiency.

The application of whole genome capture (WGC) methods to ancient DNA (aDNA) promises to increase the efficiency of ancient genome sequencing.We compared the performance of two recently developed WGC methods in enriching human aDNA within Illumina libraries built using both double-stranded (DSL) and single-stranded (SSL) build protocols. Although both methods effectively enriched aDNA, one consistently produced marginally better results, giving us the opportunity to further explore the parameters influencing WGC experiments.Our results suggest that bait length has an important influence on library enrichment. Moreover, we show that WGC biases against the shorter molecules that are enriched in SSL preparation protocols. Therefore application of WGC to such samples is not recommended without future optimization. Lastly, we document the effect of WGC on other features including clonality, GC composition and repetitive DNA content of captured libraries.Our findings provide insights for researchers planning to perform WGC on aDNA, and suggest future tests and optimization to improve WGC efficiency.

The application of whole genome capture (WGC) methods to ancient DNA (aDNA) promises to increase the efficiency of ancient genome sequencing.We compared the performance of two recently developed WGC methods in enriching human aDNA within Illumina libraries built using both double-stranded (DSL) and single-stranded (SSL) build protocols. Although both methods effectively enriched aDNA, one consistently produced marginally better results, giving us the opportunity to further explore the parameters influencing WGC experiments.Our results suggest that bait length has an important influence on library enrichment. Moreover, we show that WGC biases against the shorter molecules that are enriched in SSL preparation protocols. Therefore application of WGC to such samples is not recommended without future optimization. Lastly, we document the effect of WGC on other features including clonality, GC composition and repetitive DNA content of captured libraries.Our findings provide insights for researchers planning to perform WGC on aDNA, and suggest future tests and optimization to improve WGC efficiency.

The seagrass Halophila major (Zoll.) Miguel is reported for the first time from Vietnam. It was found growing with other seagrass species nearshore, 4-6 m deep at Tre Island, Nha Trang Bay. Leaf morphology and phylogenetic analysis based on ribosomal internal transcribed spacer sequences confirmed the identification. There was very little sequence differentiation among samples of H. major collected in Vietnam and other countries in the Western Pacific region. A very low evolutionary divergence among H. major populations was found.

Seagrasses, a unique group of submerged flowering plants, profoundly influence the physical, chemical and biological environments of coastal waters through their high primary productivity and nutrient recycling ability. They provide habitat for aquatic life, alter water flow, stabilize the ground and mitigate the impact of nutrient pollution. at the coast region. Although on a global scale seagrasses represent less than 0.1% of the angiosperm taxa, the taxonomical ambiguity in delineating seagrass species is high. Thus, the taxonomy of several genera is unsolved. While seagrasses are capable of performing both, sexual and asexual reproduction, vegetative reproduction is common and sexual progenies are always short lived and epimeral in nature. This makes species differentiation often difficult, especially for non-taxonomists since the flower as a distinct morphological trait is missing. Our goal is to develop a DNA barcoding system assisting also non-taxonomists to identify regional seagrass species. The results will be corroborated by publicly available sequence data. The main focus is on the 14 described seagrass species of India, supplemented with seagrasses from temperate regions. According to the recommendations of the Consortium for the Barcoding of Life (CBOL) rbcL and matK were used in this study. After optimization of the DNA extraction method from preserved seagrass material, the respective sequences were amplified from all species analyzed. Tree-and character-based approaches demonstrate that the rbcL sequence fragment is capable of resolving up to family and genus level. Only matK sequences were reliable in resolving species and partially the ecotype level. Additionally, a plastidic gene spacer was included in the analysis to confirm the identification level. Although the analysis of these three loci solved several nodes, a few complexes remained unsolved, even when constructing a combined tree for all three loci. Our approaches contribute to the underst

Recently diverged species are challenging for identification, yet they are frequently of special interest scientifically as well as from a regulatory perspective. DNA barcoding has proven instrumental in species identification, especially in insects and vertebrates, but for the identification of recently diverged species it has been reported to be problematic in some cases. Problems are mostly due to incomplete lineage sorting or simply lack of a ‘barcode gap’ and probably related to large effective population size and/or low mutation rate. Our objective was to compare six methods in their ability to correctly identify recently diverged species with DNA barcodes: neighbor joining and parsimony (both tree-based), nearest neighbor and BLAST (similarity-based), and the diagnostic methods DNA-BAR, and BLOG. We analyzed simulated data assuming three different effective population sizes as well as three selected empirical data sets from published studies. Results show, as expected, that success rates are significantly lower for recently diverged species (~75%) than for older species (~97%) (P

Background The best documented survival responses of organisms to past climate change on short (glacial-interglacial) timescales are distributional shifts. Despite ample evidence on such timescales for local adaptations of populations at specific sites, the long-term impacts of such changes on evolutionary significant units in response to past climatic change have been little documented. Here we use phylogenies to reconstruct changes in distribution and flowering ecology of the Cape flora - South Africa's biodiversity hotspot - through a period of past (Neogene and Quaternary) changes in the seasonality of rainfall over a timescale of several million years. Results Forty-three distributional and phenological shifts consistent with past climatic change occur across the flora, and a comparable number of clades underwent adaptive changes in their flowering phenology (9 clades; half of the clades investigated) as underwent distributional shifts (12 clades; two thirds of the clades investigated). Of extant Cape angiosperm species, 14-41% have been contributed by lineages that show distributional shifts consistent with past climate change, yet a similar proportion (14-55%) arose from lineages that shifted flowering phenology. Conclusions Adaptive changes in ecology at the scale we uncover in the Cape and consistent with past climatic change have not been documented for other floras. Shifts in climate tolerance appear to have been more important in this flora than is currently appreciated, and lineages that underwent such shifts went on to contribute a high proportion of the flora's extant species diversity. That shifts in phenology, on an evolutionary timescale and on such a scale, have not yet been detected for other floras is likely a result of the method used; shifts in flowering phenology cannot be detected in the fossil record.

Large-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of the bacterial composition in three fecal and three small intestinal samples from human individuals. As PCR remains a crucial step in sample preparation for both techniques, different forward primers were used for amplification to assess their impact on microbial profiling results. An average of 7,944 pyrosequences, spanning the V1 and V2 region of 16S rRNA genes, was obtained per sample. Although primer choice in barcoded pyrosequencing did not affect species richness and diversity estimates, detection of Actinobacteria strongly depended on the selected primer. Microbial profiles obtained by pyrosequencing and phylogenetic microarray analysis (HITChip) correlated strongly for fecal and ileal lumen samples but were less concordant for ileostomy effluent. Quantitative PCR was employed to investigate the deviations in profiling between pyrosequencing and HITChip analysis. Since cloning and sequencing of random 16S rRNA genes from ileostomy effluent confirmed the presence of novel intestinal phylotypes detected by pyrosequencing, especially those belonging to the Veillonella group, the divergence between pyrosequencing and the HITChip is likely due to the relatively low number of available 16S rRNA gene sequences of small intestinal origin in the DNA databases that were used for HITChip probe design. Overall, this study demonstrated that equivalent biological conclusions are obtained by high-throughput profiling of microbial communities, independent of technology or primer choice

Prophylactic probiotic therapy has shown beneficial effects in an experimental rat model for acute pancreatitis on the health status of the animals. Mechanisms by which probiotic therapy interferes with severity of acute pancreatitis and associated sepsis, however, are poorly understood. The aims of this study were to identify the probiotic-induced changes in the gut microbiota and to correlate these changes to disease outcome. Duodenum and ileum samples were obtained from healthy and diseased rats subjected to pancreatitis for 7 days and prophylactically treated with either a multispecies probiotic mixture or a placebo. Intestinal microbiota was characterized by terminal-restriction fragment length polymorphism (T-RFLP) analyses of PCR-amplified 16S rRNA gene fragments. These analyses showed that during acute pancreatitis the host-specific ileal microbiota was replaced by an “acute pancreatitis-associated microbiota.” This replacement was not reversed by administration of the probiotic mixture. An increase, however, was observed in the relative abundance of a novel bacterial phylotype most closely related to Clostridium lituseburense and referred to as commensal rat ileum bacterium (CRIB). Specific primers targeting the CRIB 16S rRNA gene sequence were developed to detect this phylotype by quantitative PCR. An ileal abundance of CRIB 16S rRNA genes of more than 7.5% of the total bacterial 16S rRNA gene pool was correlated with reduced duodenal bacterial overgrowth, reduced bacterial translocation to remote organs, improved pancreas pathology, and reduced proinflammatory cytokine levels in plasma. Our current findings and future studies involving this uncharacterized bacterial phylotype will contribute to unraveling one of the potential mechanisms of probiotic therapy.

The microbial electrolysis cell (MEC) is a promising system for hydrogen production. Still, expensive catalysts such as platinum are needed for efficient hydrogen evolution at the cathode. Recently, the possibility to use a biocathode as an alternative for platinum was shown. The microorganisms involved in hydrogen evolution in such systems are not yet identified. We analyzed the microbial community of a mixed culture biocathode that was enriched in an MEC bioanode. This biocathode produced 1.1 A m(-2) and 0.63 m3 H2 m(-3) cathode liquid volume per day. The bacterial population consisted of 46% Proteobacteria, 25% Firmicutes, 17% Bacteroidetes, and 12% related to other phyla. The dominant ribotype belonged to the species Desulfovibrio vulgaris. The second major ribotype cluster constituted a novel taxonomic group at the genus level, clustering within uncultured Firmicutes. The third cluster belonged to uncultured Bacteroidetes and grouped in a taxonomic group from which only clones were described before; most of these clones originated from soil samples. The identified novel taxonomic groups developed under environmentally unusual conditions, and this may point to properties that have not been considered before. A pure culture of Desulfovibrio strain G11 inoculated in a cathode of an MEC led to a current development from 0.17 to 0.76 A m(-2) in 9 days, and hydrogen gas formation was observed. On the basis of the known characteristics of Desulfovibrio spp., including its ability to produce hydrogen, we propose a mechanism for hydrogen evolution through Desulfovibrio spp. in a biocathode system

Motivation: Streptomyces is one of the best-studied genera of the order Actinomycetales due to its great importance in medical science, ecology and the biotechnology industry. A comprehensive, detailed and robust phylogeny of Streptomyces and its relatives is needed for understanding how this group emerged and maintained such a vast diversity throughout evolution and how soil-living mycelial forms (e.g., Streptomyces s. str.) are related to parasitic, unicellular pathogens (e.g., Mycobacterium tuberculosis) or marine species (e.g., Salinispora tropical). The most important application area Of such a phylogenetic analysis will be in the comparative re-annotation of genome sequences and the reconstruction of Streptomyces metabolic networks for biotechnology.Methods: Classical 16S-rRNA-based phylogenetic reconstruction does not guarantee to produce well-resolved robust trees that reflect the overall relationship between bacterial species with widespread horizontal gene transfer. Ill Our study we therefore combine three whole genome-based phylogenies with eight different, highly informative single-gene phylogenies to determine a new robust consensus tree of 45 Actinomycetales species with completely sequenced genomes.Results: None of the individual methods achieved a resolved phylogeny of Streptomyces and its relatives. Single-gene approaches failed to yield a detailed phylogeny; even though the single trees are in good agreement among each other, they show very low resolution of inner branches. The three whole genome-based methods improve resolution considerably. Only by combining the phylogenies from single gene-based and genome-based approaches we finally obtained a consensus tree with well-resolved branches for the entire set of Actinomycetales species. This phylogenetic information is stable and informative enough for application to the system-wide comparative modeling Of bacterial physiology. (C) 2009 Elsevier Inc. All rights reserved.

The role of dominant bacterial groups in the plant rhizosphere, e.g., those belonging to the phyla Acidobacteria and Verrucomicrobia, has, so far, not been elucidated, and this is mainly due to the lack of culturable representatives. This study aimed to isolate hitherto-uncultured bacteria from the potato rhizosphere by a combination of cultivation approaches. An agar medium low in carbon availability (oligotrophic agar medium) and either amended with potato root exudates or catalase or left unamended was used with the aim to improve the culturability of bacteria from the potato rhizosphere. The colony forming unit numbers based on colonies and microcolonies were compared with microscopically determined fluorescence-stained cell numbers. Taxonomical diversity of the colonies was compared with that of library clones made from rhizosphere DNA, on the basis of 16S rRNA gene comparisons. The oligotrophic media amended or not with catalase or rhizosphere extract recovered up to 33.6% of the total bacterial numbers, at least seven times more than the recovery observed on R2A. Four hitherto-uncultured Verrucomicrobia subdivision 1 representatives were recovered on agar, but representatives of this group were not found in the clone library. The use of oligotrophic medium and its modifications enabled the growth of colony numbers, exceeding those on classical agar media. Also, it led to the isolation of hitherto-uncultured bacteria from the potato rhizosphere. Further improvement in cultivation will certainly result in the recovery of other as-yet-unexplored bacteria from the rhizosphere, making these groups accessible for further investigation, e.g., with respect to their possible interactions with plants.

Molecular phylogenetics has revolutionized our understanding of the Caryophyllales, and yet many relationships have remained uncertain, particularly at deeper levels. We have performed parsimony and maximum likelihood analyses on separate and combined data sets comprising nine plastid genes (similar to 12,000 bp), two nuclear genes (similar to 5000 bp), and the plastid inverted repeat (similar to 24,000 bp), giving a combined analyzed length of 42,006 bp for 36 species of Caryophyllales and four outgroups. We have recovered strong support for deep-level relationships across the order. Two major subclades are well supported, the noncore and core Caryophyllales; Rhabdodendron followed by Simmondsia are sisters to the core Caryophyllales, Limeum and Stegnosperma are successive sisters to the "globular inclusion'' clade, Gisekia is a distinct lineage well separated from Rivina within the "raphide'' clade, and Rivina and Phytolaccaceae are disparate lineages, with Rivina sister to Nyctaginaceae. The placement of Sarcobatus and relationships within the portulacaceous cohort remain problematic. Within the latter, Halophytum is sister to Basellaceae and Didiereaceae, and the clade comprising Portulaca, Talinum, and Cactaceae is well supported. Classical hypotheses argued that the early Caryophyllales had evolved in open, dry, marginal environments at a time when pollinators were scarce, and, as such, the ancestral caryophyllid flower was wind pollinated with an undifferentiated perianth. We reevaluated these hypotheses in light of our phylogeny and find little support for anemophily as the ancestral condition; however, the early caryophyllid flower is suggested to have possessed an undifferentiated perianth. A subsequent minimum of nine origins of differentiated perianth is inferred. We discuss the evidence for independent origins of differentiated perianth and highlight the research opportunities that this pattern offers to the field of evolutionary developmental genetics.

Molecular phylogenetics has revolutionized our understanding of the Caryophyllales, and yet many relationships have remained uncertain, particularly at deeper levels. We have performed parsimony and maximum likelihood analyses on separate and combined data sets comprising nine plastid genes (similar to 12,000 bp), two nuclear genes (similar to 5000 bp), and the plastid inverted repeat (similar to 24,000 bp), giving a combined analyzed length of 42,006 bp for 36 species of Caryophyllales and four outgroups. We have recovered strong support for deep-level relationships across the order. Two major subclades are well supported, the noncore and core Caryophyllales; Rhabdodendron followed by Simmondsia are sisters to the core Caryophyllales, Limeum and Stegnosperma are successive sisters to the "globular inclusion'' clade, Gisekia is a distinct lineage well separated from Rivina within the "raphide'' clade, and Rivina and Phytolaccaceae are disparate lineages, with Rivina sister to Nyctaginaceae. The placement of Sarcobatus and relationships within the portulacaceous cohort remain problematic. Within the latter, Halophytum is sister to Basellaceae and Didiereaceae, and the clade comprising Portulaca, Talinum, and Cactaceae is well supported. Classical hypotheses argued that the early Caryophyllales had evolved in open, dry, marginal environments at a time when pollinators were scarce, and, as such, the ancestral caryophyllid flower was wind pollinated with an undifferentiated perianth. We reevaluated these hypotheses in light of our phylogeny and find little support for anemophily as the ancestral condition; however, the early caryophyllid flower is suggested to have possessed an undifferentiated perianth. A subsequent minimum of nine origins of differentiated perianth is inferred. We discuss the evidence for independent origins of differentiated perianth and highlight the research opportunities that this pattern offers to the field of evolutionary developmental genetics.

Hexachlorobenzene (HCB) has been widely used in chemical manufacturing processes and as pesticide. Due to its resistance to biological degradation, HCB mainly accumulated in fresh water bodies and agricultural soils. Dehalococcoides spp., anaerobic dechlorinating bacteria that are capable of degrading HCB, were previously isolated from river sediments. Yet there is limited knowledge about the abundance, diversity and activity of this genus in the environment. This study focused on the molecular analysis of the composition and abundance of active Dehalococcoides spp. in HCB-contaminated European river basins. 16S ribosomal RNA-based real-time quantitative PCR and denaturing gradient gel electrophoresis in combination with multivariate statistics were applied. Moreover, a functional gene array was used to determine reductive dehalogenase (rdh) gene diversity. Spatial and temporal fluctuations were observed not only in the abundance of Dehalococcoides spp. but also in the composition of the populations and rdh gene diversity. Multivariate statistics revealed that Dehalococcoides spp. abundance is primarily affected by spatial differences, whereas species composition is under the influence of several environmental parameters, such as seasonal changes, total organic carbon and/or nitrogen content and HCB contamination. This study provides new insight in the natural occurrence and dynamics of active Dehalococcoides spp. in HCB contaminated river basins

The performance of a full-scale (500 m3) sulfidogenic synthesis gas fed gas-lift reactor treating metal- and sulfate-rich wastewater was investigated over a period of 128 weeks. After startup, the reactor had a high methanogenic activity of 46 Nm3·h-1. Lowering the carbon dioxide feed rate during the first 6 weeks gradually lowered the methane production rate. Between weeks 8 and 93, less than 1% of the hydrogen supplied was used for methanogenesis. Denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified 16S rRNA gene fragments showed that the archaeal community decreased in diversity but did not disappear completely. After the carbon dioxide feed rate increased in week 88, the methane production rate also increased, confirming that methane production was carbon dioxide limited. Even though lowering the carbon dioxide feed appeared to affect part of the sulfate-reducing community, it did not prevent achieving the desired rates of sulfate reduction. The average sulfate conversion rate was 181 kg·h-1 for the first 92 weeks. After 92 weeks, the sulfate input rate was increased and from week 94 to 128, the average weekly sulfate conversion rate was 295 kg.h-1 (SD-±-87). Even higher sulfate conversion rates of up to 400 kg·h-1 could be sustained for weeks 120-128. The long-term performance and stability together with the ability to control methanogenesis demonstrates that synthesis gas fed reactor can be used successfully at full scale to treat metal and sulfate-rich wastewater

Pseudomonas putida strain P9 is a novel competent endophyte from potato. P9 causes cultivar-dependent suppression of Phytophthora infestans. Colonization of the rhizoplane and endosphere of potato plants by P9 and its rifampin-resistant derivative P9R was studied. The purposes of this work were to follow the fate of P9 inside growing potato plants and to establish its effect on associated microbial communities. The effects of P9 and P9R inoculation were studied in two separate experiments. The roots of transplants of three different cultivars of potato were dipped in suspensions of P9 or P9R cells, and the plants were planted in soil. The fate of both strains was followed by examining colony growth and by performing PCR-denaturing gradient gel electrophoresis (PCR-DGGE). Colonies of both strains were recovered from rhizoplane and endosphere samples of all three cultivars at two growth stages. A conspicuous band, representing P9 and P9R, was found in all Pseudomonas PCR-DGGE fingerprints for treated plants. The numbers of P9R CFU and the P9R-specific band intensities for the different replicate samples were positively correlated, as determined by linear regression analysis. The effects of plant growth stage, genotype, and the presence of P9R on associated microbial communities were examined by multivariate and unweighted-pair group method with arithmetic mean cluster analyses of PCR-DGGE fingerprints. The presence of strain P9R had an effect on bacterial groups identified as Pseudomonas azotoformans, Pseudomonas veronii, and Pseudomonas syringae. In conclusion, strain P9 is an avid colonizer of potato plants, competing with microbial populations indigenous to the potato phytosphere. Bacterization with a biocontrol agent has an important and previously unexplored effect on plant-associated communities.

We have characterised the northern Pacific undescribed sponge Haliclona (?gellius) sp. based on rDNA of the sponge and its associated microorganisms. The sponge is closely related to Amphimedon queenslandica from the Great Barrier Reef as the near-complete 18S rDNA sequences of both sponges were identical. The microbial fingerprint of three specimens harvested at different times and of a transplanted specimen was compared to identify stably associated microorganisms. Most bacterial phyla were detected in each sample, but only a few bacterial species were determined to be stably associated with the sponge. A sponge-specific beta- and gamma-Proteobacterium were abundant clones and both of them were present in three of the four specimens analysed. In addition, a Planctomycete and a Crenarchaea were detected in all sponge individuals. Both were closely related to operational taxonomic units that have been found in other sponges, but not exclusively in sponges. Interestingly, also a number of clones that are closely related to intracellular symbionts from insects and amoeba were detected.

Phylogenetic analyses of 46 species, representing all tribes and 14 out of 18 recognized genera of Burseraceae, are performed using nuclear ETS and plastid rps16 sequences. Boswellia madagascariensis, the only Malagasy species of this genus, is shown to belong to a clade comprising all sampled members of the current tribe Canarieae plus Triomma, whereas other species of Boswellia (including the type, B. serrata) form a clade that is strongly supported as sister to Garuga. A new genus, Ambilobea, is proposed for B. madagascariensis and the new combination A. madagascariensis is made. Ambilobea differs from Boswellia s. s. by being dioecious and by having valvate petals and, furthermore, is unique in the family by its winged tips to the petioles, by having pyrenes that remain attached to the detached valves of the fruit at dehiscence, and by its long-spinose pollen grains. Aucoumea, a monotypic central African rain forest genus, is strongly supported as sister to a clade with the arid-adapted Bursera and Commiphora. Boswellia s. s. and Garuga form a clade characterized by having hermaphroditic flowers. The relationships within Burseraceae emerging from this and previous phylogenetic studies are, on several points, in conflict with current tribal delimitation. The following suggestions for a new tribal classification of Burseraceae are made: 1) Beiselia, sister to the rest of the family, needs to be placed in a tribe of its own, Beiselieae, trib. nov., 2) Protieae should be restricted to Crepidospermum, Protium and Tetragastris, although generic rearrangements seem to be needed within this tribe, 3) Bursereae should be restricted to Aucoumea, Bursera and Commiphora, but generic rearrangements are needed in the Bursera-Commiphora complex, 4) the remaining genera, Ambilobea, Boswellia, Canarium, Dacryodes, Garuga, Haplolobus, Pseudodacryodes, Rosselia, Santiria, Scutinanthe, Trattinnickia and Triomma, are probably best placed in a broadly circumscribed Garugeae., authorCount :4

Background - Myco-heterotrophy evolved independently several times during angiosperm evolution. Although many species of myco-heterotrophic plants are highly endemic and long-distance dispersal seems unlikely, some genera are widely dispersed and have pantropical distributions, often with large disjunctions. Traditionally this has been interpreted as evidence for an old age of these taxa. However, due to their scarcity and highly reduced plastid genomes our understanding about the evolutionary histories of the angiosperm myco-heterotrophic groups is poor. Results - We provide a hypothesis for the diversification of the myco-heterotrophic family Burmanniaceae. Phylogenetic inference, combined with biogeographical analyses, molecular divergence time estimates, and diversification analyses suggest that Burmanniaceae originated in West Gondwana and started to diversify during the Late Cretaceous. Diversification and migration of the species-rich pantropical genera Burmannia and Gymnosiphon display congruent patterns. Diversification began during the Eocene, when global temperatures peaked and tropical forests occurred at low latitudes. Simultaneous migration from the New to the Old World in Burmannia and Gymnosiphon occurred via boreotropical migration routes. Subsequent Oligocene cooling and breakup of boreotropical flora ended New-Old World migration and caused a gradual decrease in diversification rate in Burmanniaceae. Conclusion - Our results indicate that extant diversity and pantropical distribution of myco-heterotrophic Burmanniaceae is the result of diversification and boreotropical migration during the Eocene when tropical rain forest expanded dramatically

AFLP markers provide a potential source of phylogenetic information for molecular systematic studies. However, there are properties of restriction fragment data that limit phylogenetic interpretation of AFLPs. These are (a) possible nonindependence of fragments, (b) problems of homology assignment of fragments, (c) asymmetry in the probability of losing and gaining fragments, and (d) problems in distinguishing heterozygote from homozygote bands. In the present study, AFLP data sets of Lactuca s.l. were examined for the presence of phylogenetic signal. An indication of this signal was provided by carrying out tree length distribution skewness (g1) tests, permutation tail probability (PTP) tests, and relative apparent synapomorphy analysis (RASA). A measure of the support for internal branches in the optimal parsimony tree (MPT) was made using bootstrap, jackknife, and decay analysis. Finally, the extent of congruence in MPTs for AFLP and internal transcribed spacer (ITS)-1 data sets for the same taxa was made using the partition homogeneity test (PHT) and the Templeton test. These analytical studies suggested the presence of phylogenetic signal in the AFLP data sets, although some incongruence was found between AFLP and ITS MPTs. An extensive literature survey undertaken indicated that authors report a general congruence of AFLP and ITS tree topologies across a wide range of taxonomic groups, suggesting that the present results and conclusions have a general bearing. In these earlier studies and those for Lactuca s.l., AFLP markers have been found to be informative at somewhat lower taxonomic levels than ITS sequences. Tentative estimates are suggested for the levels of ITS sequence divergence over which AFLP profiles are likely to be phylogenetically informative. [Amplified Fragment Length Polymorphism (AFLP) markers; congruence; Dollo parsimony; g1 statistic; internal transcribed spacer (ITS) sequences; Lactuca; partition homogeneity test (PHT); phylogenetic signal

We present Neighbor-Net, a distance based method for constructing phylogenetic networks that is based on the Neighbor-Joining (NJ) algorithm of Saitou and Nei. Neighbor-Net provides a snapshot of the data that can guide more detailed analysis. Unlike split decomposition, Neighbor-Net scales well and can quickly produce detailed and informative networks for several hundred taxa. We illustrate the method by reanalyzing three published data sets: a collection of 110 highly recombinant Salmonella multi-locus sequence typing sequences, the 135 "African Eve" human mitochondrial sequences published by Vigilant et al., and a collection of 12 Archeal chaperonin sequences demonstrating strong evidence for gene conversion. Neighbor-Net is available as part of the SplitsTree4 software package.

The aim of the GENKOMB project was to find and analyse transcription factor binding sites in the human genome, by correlating expression data for a set of genes with the nucleotide sequences in their upstream regions. This document is a technical description of tools that have been developed and results that have been obtained in the GENKOMB project. Apart from detecting transcription factor binding sites, this project has resulted in programs for matching weight matrices to DNA sequences and multiple alignment of short nucleotide sequences.

The aim of the GENKOMB project was to find and analyse transcription factor binding sites in the human genome, by correlating expression data for a set of genes with the nucleotide sequences in their upstream regions. This document is a technical description of tools that have been developed and results that have been obtained in the GENKOMB project. Apart from detecting transcription factor binding sites, this project has resulted in programs for matching weight matrices to DNA sequences and multiple alignment of short nucleotide sequences.

The analysis of consecutive ontogenetic stages, or events, introduces a new class of data to phylogenetic systematics that are distinctly different from traditional morphological characters and molecular sequence data. Ontogenetic event sequences are distinguished by varying degrees of both a collective and linear type of dependence and, therefore, violate the criterion of character independence. We applied different methods of phylogenetic reconstruction to ontogenetic data including maximum parsimony and distance (cluster) analyses. Two different data sets were investigated: (1) four simulated ontogenies with defined phylogenies of six hypothetical taxa, and (2) a set of “real” data comprising sequences of 29 ontogenetic events from 11 vertebrate taxa. We confirm that heterochronic event sequences do contain a phylogenetic signal. However, based on our results we argue that maximum parsimony is a biased method to analyze such developmental sequence data. Ontogenetic events require a special analytical algorithm that would not neglect instances of chronological (horizontal) dependence of this type of data. One coding method, “event-pairing”, appeared to fulfill this requirement in the vertebrate analyses. However, to accurately analyze ontogenetic sequence data, a more sophisticated coding method and algorithm are needed, for example, measuring distances of dependent events.

Fast similarity searching in large time-sequence databases has attracted a lot of research interest. All of them use the Euclidean distance ($L_2$), or some variation of $L_p$ metric. $L_p$ metrics lead to efficient indexing, thanks to feature extraction (e.g., by keeping the first few DFT coefficients) and subsequent use of fast spatial access methods for the points in feature space. In this work we examine a popular, field-tested dissimilarity function, the "time warping" distance function which permits local accelerations and decelerations in the rate of the signals or sequences. This function is natural and suitable for several applications, like matching of voice, audio and medical signals (e.g., electrocardiograms). However, from the indexing viewpoint it presents two major challenges: (a) it does not lead to any natural "features", precluding the use of spatial access methods (b) it is quadratic ($O(len_1 * len_2)$) on the length of the sequences involved. Here we show how to overcome both problems: for the former, we propose using a modification of the so-called "FastMap", to map sequences into points, trading off a tiny amount of "recall" (typically zero) for large gains in speed. For the latter, we provide a fast, linear test, to help us discard quickly many of the false alarms that FastMap will typically introduce. Using both ideas in cascade, our proposed method achieved up to 7.8-time speed-up over the straightforward sequential scanning, on both read and synthetic datasets.