scholarly journals Evolutionary Timeline and Genomic Plasticity Underlying the Lifestyle Diversity in Rhizobiales

mSystems ◽  
2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Sishuo Wang ◽  
Andrew Meade ◽  
Hon-Ming Lam ◽  
Haiwei Luo
Keyword(s):  
Nitrogen Fixation ◽  
Medical Research ◽  
Large Scale ◽  
Study Data ◽  
Time Range ◽  
Secretion Systems ◽  
Data Set ◽  
Host Interactions ◽  
Statistical Correlations ◽  
Animal Pathogens

ABSTRACT Members of the order Rhizobiales include those capable of nitrogen fixation in nodules as well as pathogens of animals and plants. This lifestyle diversity has important implications for agricultural and medical research. Leveraging large-scale genomic data, we infer that Rhizobiales originated as a free-living ancestor ∼1,500 million years ago (Mya) and that the later emergence of host-associated lifestyles broadly coincided with the rise of their eukaryotic hosts. In particular, the first nodulating lineage arose from either Azorhizobium or Bradyrhizobium 150 to 80 Mya, a time range in general concurrent with the emergence of legumes. The rates of lifestyle transitions are highly variable; nodule association is more likely to be lost than gained, whereas animal association likely represents an evolutionary dead end. We searched for statistical correlations between gene presence and lifestyle and identified genes likely contributing to the transition and adaptation to the same lifestyle in divergent lineages. Among the genes potentially promoting successful transitions to major nodulation lineages, the nod and nif clusters for nodulation and nitrogen fixation, respectively, were repeatedly acquired during each transition; the fix, dct, and phb clusters involved in energy conservation under micro-oxic conditions were present in the nonnodulating ancestors; and the secretion systems were acquired in lineage-specific patterns. Our study data suggest that increased eukaryote diversity drives lifestyle diversification of bacteria and highlight both acquired and preexisting traits facilitating the origin of host association. IMPORTANCE Bacteria form diverse interactions with eukaryotic hosts. This is well represented by the Rhizobiales, a clade of Alphaproteobacteria strategically important for their large diversity of lifestyles with implications for agricultural and medical research. To investigate their lifestyle evolution, we compiled a comprehensive data set of genomes and lifestyle information for over 1,000 Rhizobiales genomes. We show that the origins of major host-associated lineages in Rhizobiales broadly coincided with the emergences of their host plants/animals, suggesting bacterium-host interactions as a driving force in the evolution of Rhizobiales. We further found that, in addition to gene gains, preexisting traits and recurrent losses of specific genomic traits may have played underrecognized roles in the origin of host-associated lineages, providing clues to genetic engineering of microbial agricultural inoculants and prevention of the emergence of potential plant/animal pathogens.

scholarly journals Rapid inference of direct interactions in large-scale ecological networks from heterogeneous microbial sequencing data

2018 ◽  
Author(s):  
Janko Tackmann ◽  
João Frederico Matias Rodrigues ◽  
Christian von Mering
Keyword(s):  
Graphical Models ◽  
Large Scale ◽  
Study Data ◽  
Microbial Interactions ◽  
Data Sets ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Human Gut ◽  
Data Set ◽  
Seamless Integration

AbstractThe recent explosion of metagenomic sequencing data opens the door towards the modeling of microbial ecosystems in unprecedented detail. In particular, co-occurrence based prediction of ecological interactions could strongly benefit from this development. However, current methods fall short on several fronts: univariate tools do not distinguish between direct and indirect interactions, resulting in excessive false positives, while approaches with better resolution are so far computationally highly limited. Furthermore, confounding variables typical for cross-study data sets are rarely addressed. We present FlashWeave, a new approach based on a flexible Probabilistic Graphical Models framework to infer highly resolved direct microbial interactions from massive heterogeneous microbial abundance data sets with seamless integration of metadata. On a variety of benchmarks, FlashWeave outperforms state-of-the-art methods by several orders of magnitude in terms of speed while generally providing increased accuracy. We apply FlashWeave to a cross-study data set of 69 818 publicly available human gut samples, resulting in one of the largest and most diverse models of microbial interactions in the human gut to date.

scholarly journals DeepT3 2.0: improving type III secreted effector predictions by an integrative deep learning framework

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Runyu Jing ◽  
Tingke Wen ◽  
Chengxiang Liao ◽  
Li Xue ◽  
Fengjuan Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Amino Acid Sequences ◽  
Secretion Systems ◽  
Gram Negative ◽  
Type Iii ◽  
Learning Framework ◽  
Genome Wide ◽  
Type Iii Secretion Systems ◽  
Animal Pathogens

Abstract Type III secretion systems (T3SSs) are bacterial membrane-embedded nanomachines that allow a number of humans, plant and animal pathogens to inject virulence factors directly into the cytoplasm of eukaryotic cells. Export of effectors through T3SSs is critical for motility and virulence of most Gram-negative pathogens. Current computational methods can predict type III secreted effectors (T3SEs) from amino acid sequences, but due to algorithmic constraints, reliable and large-scale prediction of T3SEs in Gram-negative bacteria remains a challenge. Here, we present DeepT3 2.0 (http://advintbioinforlab.com/deept3/), a novel web server that integrates different deep learning models for genome-wide predicting T3SEs from a bacterium of interest. DeepT3 2.0 combines various deep learning architectures including convolutional, recurrent, convolutional-recurrent and multilayer neural networks to learn N-terminal representations of proteins specifically for T3SE prediction. Outcomes from the different models are processed and integrated for discriminating T3SEs and non-T3SEs. Because it leverages diverse models and an integrative deep learning framework, DeepT3 2.0 outperforms existing methods in validation datasets. In addition, the features learned from networks are analyzed and visualized to explain how models make their predictions. We propose DeepT3 2.0 as an integrated and accurate tool for the discovery of T3SEs.

scholarly journals Galaxy formation and evolution with the Dark Energy Survey

2012 ◽  
Vol 8 (S295) ◽  
pp. 137-140
Author(s):  
Diego Capozzi ◽  
Daniel Thomas ◽  
Claudia Maraston ◽  
Luke J. M. Davies
Keyword(s):  
Dark Energy ◽  
Galaxy Evolution ◽  
Galaxy Formation ◽  
Large Scale ◽  
Time Range ◽  
Data Set ◽  
Dark Energy Survey ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Energy Survey

AbstractThe Dark Energy Survey (DES) will be the new state-of the-art in large-scale galaxy imaging surveys. With 5,000 deg2, it will cover an area of the sky similar to SDSS-II, but will go over two magnitudes deeper, reaching 24th magnitude in all four optical bands (griz). DES will further provide observations in the redder Y-band and will be complemented with VISTA observations in the near-infrared bands JHK. Hence DES will furnish an unprecedented combination of sky and wavelength coverage and depth, unreached by any of the existing galaxy surveys. The very nature of the DES data set – large volume at intermediate photometric depth – allows us to probe galaxy formation and evolution within a cosmic-time range of ~ 10 Gyr and in different environments. In fact there will be many galaxy clusters available for galaxy evolution studies, given that one of the main aims of DES is to use their abundance to constrain the equation of state of dark energy. The X-ray follow up of these clusters, coupled with the use of gravitational lensing, will provide very precise measures of their masses, enabling us to study in detail the influence of the environment on galaxy formation and evolution processes. DES will leverage the study of these processes by allowing us to perform a detailed investigation of the galaxy luminosity and stellar mass functions and of the relationship between dark and baryonic matter as described by the Halo Occupation Distribution.

Collecting and evaluating large volumes of bibliographic metadata aggregated in the WorldCat database: a proposed methodology to overcome challenges

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vyacheslav I. Zavalin ◽  
Shawne D. Miksa
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Large Data ◽  
Study Data ◽  
Lessons Learned ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
Large Data Set ◽  
Smart Data

Purpose This paper aims to discuss the challenges encountered in collecting, cleaning and analyzing the large data set of bibliographic metadata records in machine-readable cataloging [MARC 21] format. Possible solutions are presented. Design/methodology/approach This mixed method study relied on content analysis and social network analysis. The study examined subject representation in MARC 21 metadata records created in 2020 in WorldCat – the largest international database of “big smart data.” The methodological challenges that were encountered and solutions are examined. Findings In this general review paper with a focus on methodological issues, the discussion of challenges is followed by a discussion of solutions developed and tested as part of this study. Data collection, processing, analysis and visualization are addressed separately. Lessons learned and conclusions related to challenges and solutions for the design of a large-scale study evaluating MARC 21 bibliographic metadata from WorldCat are given. Overall recommendations for the design and implementation of future research are suggested. Originality/value There are no previous publications that address the challenges and solutions of data collection and analysis of WorldCat’s “big smart data” in the form of MARC 21 data. This is the first study to use a large data set to systematically examine MARC 21 library metadata records created after the most recent addition of new fields and subfields to MARC 21 Bibliographic Format standard in 2019 based on resource description and access rules. It is also the first to focus its analyzes on the networks formed by subject terms shared by MARC 21 bibliographic records in a data set extracted from a heterogeneous centralized database WorldCat.

scholarly journals Infection-Blocking Genes of a Symbiotic Rhizobium leguminosarum Strain That Are Involved in Temperature-Dependent Protein Secretion

2003 ◽  
Vol 16 (1) ◽  
pp. 53-64 ◽  
Author(s):  
M. R. Bladergroen ◽  
K. Badelt ◽  
H. P. Spaink
Keyword(s):  
Nitrogen Fixation ◽  
Protein Secretion ◽  
Rhizobium Leguminosarum ◽  
Signal Sequence ◽  
Gene Clusters ◽  
Secreted Proteins ◽  
Type I ◽  
Secretion Systems ◽  
Temperature Dependent ◽  
Animal Pathogens

Rhizobium leguminosarum strain RBL5523 is able to form nodules on pea, but these nodules are ineffective for nitrogen fixation. The impairment in nitrogen fixation appears to be caused by a defective infection of the host plant and is host specific for pea. A Tn5 mutant of this strain, RBL5787, is able to form effective nodules on pea. We have sequenced a 33-kb region around the phage-transductable Tn5 insertion. The Tn5 insertion was localized to the 10th gene of a putative operon of 14 genes that was called the imp (impaired in nitrogen fixation) locus. Several highly similar gene clusters of unknown function are present in Pseudomonas aeruginosa, Vibrio cholerae, Edwardsiella ictaluri, and several other animal pathogens. Homology studies indicate that several genes of the imp locus are involved in protein phosphorylation, either as a kinase or dephosphorylase, or contain a phosphoprotein-binding module called a forkhead-associated domain. Other proteins show similarity to proteins involved in type III protein secretion. Two dimensional gel electrophoretic analysis of the secreted proteins in the supernatant fluid of cultures of RBL5523 and RBL5787 showed the absence in the mutant strain of at least four proteins with molecular masses of approximately 27 kDa and pIs between 5.5 and 6.5. The production of these proteins in the wild-type strain is temperature dependent. Sequencing of two of these proteins revealed that their first 20 amino acids are identical. This sequence showed homology to that of secreted ribose binding proteins (RbsB) from Bacilus subtilis and V. cholerae. Based on this protein sequence, the corresponding gene encoding a close homologue of RbsB was cloned that contains a N-terminal signal sequence that is recognized by type I secretion systems. Inoculation of RBL5787 on pea plants in the presence of supernatant of RBL5523 caused a reduced ability of RBL5787 to nodulate pea and fix nitrogen. Boiling of this supernatant before inoculation restored the formation of effective nodules to the original values, indicating that secreted proteins are indeed responsible for the impaired phenotype. These data suggest that the imp locus is involved in the secretion to the environment of proteins, including periplasmic RbsB protein, that cause blocking of infection specifically in pea plants.

Childhood Intelligence Predicts Adult Trait Openness

2016 ◽  
Vol 37 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Adrian Furnham ◽  
Helen Cheng
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Social Background ◽  
Study Data ◽  
Equation Modeling ◽  
Direct Effects ◽  
Data Set ◽  
National Child Development Study ◽  
Nationally Representative ◽  
The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

Computer Analyses in Preventive Health Research

1967 ◽  
Vol 06 (01) ◽  
pp. 8-14 ◽  
Author(s):  
M. F. Collen
Keyword(s):  
Medical Research ◽  
Preventive Medicine ◽  
Health Research ◽  
Large Scale ◽  
Preventive Health ◽  
New Era ◽  
Large Numbers ◽  
Normal Test ◽  
Computer Analyses

The utilization of an automated multitest laboratory as a data acquisition center and of a computer for trie data processing and analysis permits large scale preventive medical research previously not feasible. Normal test values are easily generated for the particular population studied. Long-term epidemiological research on large numbers of persons becomes practical. It is our belief that the advent of automation and computers has introduced a new era of preventive medicine.

ProGen:Provenance database generator for large-scale data set

2009 ◽  
Vol 28 (11) ◽  
pp. 2737-2740
Author(s):  
Xiao ZHANG ◽  
Shan WANG ◽  
Na LIAN
Keyword(s):  
Large Scale ◽  
Data Set ◽  
Large Scale Data ◽  
Scale Data

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

Parent and Grandparent Relationships in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Emerging Adulthood ◽  
Attachment Theory ◽  
Emerging Adults ◽  
Family Relationships ◽  
Longitudinal Research ◽  
Study Data ◽  
Family Development ◽  
Data Set ◽  
Theory Framework

Chapter 7 begins with an overview of Erikson’s ideas about intimacy and its place in the life cycle, followed by a summary of Bowlby and Ainsworth’s attachment theory framework and its relation to family development. The authors review existing longitudinal research on the development of family relationships in adolescence and emerging adulthood, focusing on evidence with regard to links to McAdams and Pals’ personality model. They discuss the evidence, both questionnaire and narrative, from the Futures Study data set on family relationships, including emerging adults’ relations with parents and, separately, with grandparents, as well as their anticipations of their own parenthood. As a way of illustrating the key personality concepts from this family chapter, the authors end with a case study of Jane Fonda in youth and her father, Henry Fonda, to illustrate these issues through the lives of a 20th-century Hollywood dynasty of actors.

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