Comparison of digestate liquid treatment technologies: mass and nitrogen balances

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A Survey on Knowledge Graphs: Representation, Acquisition and Applications

Human knowledge provides a formal understanding of the world. Knowledge graphs that represent structural relations between entities have become an increasingly popular research direction towards cognition and human-level intelligence. In this survey, we provide a comprehensive review of knowledge graph covering overall research topics about 1) knowledge graph representation learning, 2) knowledge acquisition and completion, 3) temporal knowledge graph, and 4) knowledge-aware applications, and summarize recent breakthroughs and perspective directions to facilitate future research. We propose a full-view categorization and new taxonomies on these topics. Knowledge graph embedding is organized from four aspects of representation space, scoring function, encoding models, and auxiliary information. For knowledge acquisition, especially knowledge graph completion, embedding methods, path inference, and logical rule reasoning, are reviewed. We further explore several emerging topics, including meta relational learning, commonsense reasoning, and temporal knowledge graphs. To facilitate future research on knowledge graphs, we also provide a curated collection of datasets and open-source libraries on different tasks. In the end, we have a thorough outlook on several promising research directions

Gene-gene interaction detection with deep learning

The extent to which genetic interactions affect observed phenotypes is generally unknown because current interaction detection approaches only consider simple interactions between top SNPs of genes. We introduce an open-source framework for increasing the power of interaction detection by considering all SNPs within a selected set of genes and complex interactions between them, beyond only the currently considered multiplicative relationships. In brief, the relation between SNPs and a phenotype is captured by a neural network, and the interactions are quantified by Shapley scores between hidden nodes, which are gene representations that optimally combine information from the corresponding SNPs. Additionally, we design a permutation procedure tailored for neural networks to assess the significance of interactions, which outperformed existing alternatives on simulated datasets with complex interactions, and in a cholesterol study on the UK Biobank it detected nine interactions which replicated on an independent FINRISK dataset.An open-source framework combines deep learning and permutations of gene interaction neural networks to detect complex gene-gene interactions and their significance in contributions to phenotypes.Peer reviewe

Fitness, PA, Perceived Competence, Parental Support, and Literacy Outcomes in the REACH After-School Sports Program

The purpose of this study was to assess the effectiveness of the REACH program in increasing physical activity (PA) levels, cardiorespiratory fitness, perceived competence, self-efficacy, parental support, and literacy across a year-long after-school PA intervention. Participants (N = 78) were students who volunteered from after-school program at either one of the two intervention schools or the control schools. Data are presented from two time points: Baseline (Aug/Sep 2017), and Post (end of the school year in May 2018). Data consisted of PA levels measured by PAC-Q, PACER test, Harter’s Perceived Competence questionnaire, parental support, and literacy tests. School differences in post-intervention scores were found in three (parental support, literacy, PACER) of seven intervention-related measures. Most notably parental support was higher in intervention schools over the control and PACER scores were higher in one intervention school than the control. The results demonstrate that data collection methods may need to be reconsidered in diverse low-income schools. The dramatic amount of missing data and lack of student effort points to students perhaps being overwhelmed with standardized tests and performing tasks for researchers. This leads to a dilemma in data collection in after-school programs in low-income schools: researchers need data to understand what is happening but how are students being served by the data collection process? Researchers should consider new approaches to collect data in low-income urban after-school programs to limit loss of data and to make the data collection meaningful to student participants

Bayesian modeling of recombination events in bacterial populations

Background: We consider the discovery of recombinant segments jointly with their origins within multilocus DNA sequences from bacteria representing heterogeneous populations of fairly closely related species. The currently available methods for recombination detection capable of probabilistic characterization of uncertainty have a limited applicability in practice as the number of strains in a data set increases. Results: We introduce a Bayesian spatial structural model representing the continuum of origins over sites within the observed sequences, including a probabilistic characterization of uncertainty related to the origin of any particular site. To enable a statistically accurate and practically feasible approach to the analysis of large-scale data sets representing a single genus, we have developed a novel software tool (BRAT, Bayesian Recombination Tracker) implementing the model and the corresponding learning algorithm, which is capable of identifying the posterior optimal structure and to estimate the marginal posterior probabilities of putative origins over the sites. Conclusion: A multitude of challenging simulation scenarios and an analysis of real data from seven housekeeping genes of 120 strains of genus Burkholderia are used to illustrate the possibilities offered by our approach. The software is freely available for download at URL http://web.abo.fi/fak/ mnf//mate/jc/software/brat.html

Plasmids Shaped the Recent Emergence of the Major Nosocomial Pathogen Enterococcus faecium

Enterococcus faecium is a gut commensal of humans and animals but is also listed on the WHO global priority list of multidrug-resistant pathogens. Many of its antibiotic resistance traits reside on plasmids and have the potential to be disseminated by horizontal gene transfer. Here, we present the first comprehensive population-wide analysis of the pan-plasmidome of a clinically important bacterium, by whole-genome sequence analysis of 1,644 isolates from hospital, commensal, and animal sources of E. faecium. Long-read sequencing on a selection of isolates resulted in the completion of 305 plasmids that exhibited high levels of sequence modularity. We further investigated the entirety of all plasmids of each isolate (plasmidome) using a combination of short-read sequencing and machine-learning classifiers. Clustering of the plasmid sequences unraveled different E. faecium populations with a clear association with hospitalized patient isolates, suggesting different optimal configurations of plasmids in the hospital environment. The characterization of these populations allowed us to identify common mechanisms of plasmid stabilization such as toxin-antitoxin systems and genes exclusively present in particular plasmidome populations exemplified by copper resistance, phosphotransferase systems, or bacteriocin genes potentially involved in niche adaptation. Based on the distribution of k-mer distances between isolates, we concluded that plasmidomes rather than chromosomes are most informative for source specificity of E. faecium. IMPORTANCE Enterococcus faecium is one of the most frequent nosocomial pathogens of hospital-acquired infections. E. faecium has gained resistance against most commonly available antibiotics, most notably, against ampicillin, gentamicin, and vancomycin, which renders infections difficult to treat. Many antibiotic resistance traits, in particular, vancomycin resistance, can be encoded in autonomous and extrachromosomal elements called plasmids. These sequences can be disseminated to other isolates by horizontal gene transfer and confer novel mechanisms to source specificity. In our study, we elucidated the total plasmid content, referred to as the plasmidome, of 1,644 E. faecium isolates by using short- and long-read whole-genome technologies with the combination of a machine-learning classifier. This was fundamental to investigate the full collection of plasmid sequences present in our collection (pan-plasmidome) and to observe the potential transfer of plasmid sequences between E. faecium hosts. We observed that E. faecium isolates from hospitalized patients carried a larger number of plasmid sequences compared to that from other sources, and they elucidated different configurations of plasmidome populations in the hospital environment. We assessed the contribution of different genomic components and observed that plasmid sequences have the highest contribution to source specificity. Our study suggests that E. faecium plasmids are regulated by complex ecological constraints rather than physical interaction between hosts.Peer reviewe

Population analysis of Legionella pneumophila reveals a basis for resistance to complement-mediated killing

Legionella pneumophila is the most common cause of the severe respiratory infection known as Legionnaires' disease. However, the microorganism is typically a symbiont of free-living amoeba, and our understanding of the bacterial factors that determine human pathogenicity is limited. Here we carried out a population genomic study of 902 L. pneumophila isolates from human clinical and environmental samples to examine their genetic diversity, global distribution and the basis for human pathogenicity. We find that the capacity for human disease is representative of the breadth of species diversity although some clones are more commonly associated with clinical infections. We identified a single gene (lag-1) to be most strongly associated with clinical isolates. lag-1, which encodes an O-acetyltransferase for lipopolysaccharide modification, has been distributed horizontally across all major phylogenetic clades of L. pneumophila by frequent recent recombination events. The gene confers resistance to complement-mediated killing in human serum by inhibiting deposition of classical pathway molecules on the bacterial surface. Furthermore, acquisition of lag-1 inhibits complement-dependent phagocytosis by human neutrophils, and promoted survival in a mouse model of pulmonary legionellosis. Thus, our results reveal L. pneumophila genetic traits linked to disease and provide a molecular basis for resistance to complement-mediated killing. The bacterium Legionella pneumophila can cause severe respiratory infection, but is typically a symbiont of free-living amoeba. Here, the authors analyse the genomes of 902 clinical and environmental isolates, and identify a bacterial gene that is strongly associated with human infection and confers resistance to complement-mediated killing.Peer reviewe

Ensemble approach to predict specificity determinants: benchmarking and validation

<p>Abstract</p> <p>Background</p> <p>It is extremely important and challenging to identify the sites that are responsible for functional specification or diversification in protein families. In this study, a rigorous comparative benchmarking protocol was employed to provide a reliable evaluation of methods which predict the specificity determining sites. Subsequently, three best performing methods were applied to identify new potential specificity determining sites through ensemble approach and common agreement of their prediction results.</p> <p>Results</p> <p>It was shown that the analysis of structural characteristics of predicted specificity determining sites might provide the means to validate their prediction accuracy. For example, we found that for smaller distances it holds true that the more reliable the prediction method is, the closer predicted specificity determining sites are to each other and to the ligand.</p> <p>Conclusion</p> <p>We observed certain similarities of structural features between predicted and actual subsites which might point to their functional relevance. We speculate that majority of the identified potential specificity determining sites might be indirectly involved in specific interactions and could be ideal target for mutagenesis experiments.</p

Genomic analysis of Klebsiella pneumoniae isolates from Malawi reveals acquisition of multiple ESBL determinants across diverse lineages

Objectives ESBL-producing Klebsiella pneumoniae (KPN) pose a major threat to human health globally. We carried out a WGS study to understand the genetic background of ESBL-producing KPN in Malawi and place them in the context of other global isolates. Methods We sequenced genomes of 72 invasive and carriage KPN isolates collected from patients admitted to Queen Elizabeth Central Hospital, Blantyre, Malawi. We performed phylogenetic and population structure analyses on these and previously published genomes from Kenya (n = 66) and from outside sub-Saharan Africa (n = 67). We screened for presence of antimicrobial resistance (AMR) genetic determinants and carried out association analyses by genomic sequence cluster, AMR phenotype and time. Results Malawian isolates fit within the global population structure of KPN, clustering into the major lineages of KpI, KpII and KpIII. KpI isolates from Malawi were more related to those from Kenya, with both collections exhibiting more clonality than isolates from the rest of the world. We identified multiple ESBL genes, including blaCTX-M-15, several blaSHV, blaTEM-63 and blaOXA-10, and other AMR genes, across diverse lineages of the KPN isolates from Malawi. No carbapenem resistance genes were detected; however, we detected IncFII and IncFIB plasmids that were similar to the carbapenem resistance-associated plasmid pNDM-mar. Conclusions There are multiple ESBL genes across diverse KPN lineages in Malawi and plasmids in circulation that are capable of carrying carbapenem resistance. Unless appropriate interventions are rapidly put in place, these may lead to a high burden of locally untreatable infection in vulnerable populations