MetaBMF: a scalable binning algorithm for large-scale reference-free metagenomic studies

Abstract Motivation Metagenomics studies microbial genomes in an ecosystem such as the gastrointestinal tract of a human. Identification of novel microbial species and quantification of their distributional variations among different samples that are sequenced using next-generation-sequencing technology hold the key to the success of most metagenomic studies. To achieve these goals, we propose a simple yet powerful metagenomic binning method, MetaBMF. The method does not require prior knowledge of reference genomes and produces highly accurate results, even at a strain level. Thus, it can be broadly used to identify disease-related microbial organisms that are not well-studied. Results Mathematically, we count the number of mapped reads on each assembled genomic fragment cross different samples as our input matrix and propose a scalable stratified angle regression algorithm to factorize this count matrix into a product of a binary matrix and a nonnegative matrix. The binary matrix can be used to separate microbial species and the nonnegative matrix quantifies the species distributions in different samples. In simulation and empirical studies, we demonstrate that MetaBMF has a high binning accuracy. It can not only bin DNA fragments accurately at a species level but also at a strain level. As shown in our example, we can accurately identify the Shiga-toxigenic Escherichia coli O104: H4 strain which led to the 2011 German E.coli outbreak. Our efforts in these areas should lead to (i) fundamental advances in metagenomic binning, (ii) development and refinement of technology for the rapid identification and quantification of microbial distributions and (iii) finding of potential probiotics or reliable pathogenic bacterial strains. Availability and implementation The software is available at https://github.com/didi10384/MetaBMF.

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Strain-level Screening of Human Gut Microbes Identifies Blautia Producta as a Novel Anti-hyperlipidemic Probiotic Via the Production of 12-methylmyristic Acid

10.21203/rs.3.rs-989302/v1 ◽

2021 ◽

Author(s):

Chongming Wu ◽

Wenyi Xu ◽

Jiaqi Yu ◽

Zhuanyu Li ◽

Yinghui Zhang ◽

...

Keyword(s):

Lipid Accumulation ◽

High Throughput Screening ◽

Large Scale ◽

Bacterial Species ◽

Strain Level ◽

Bacterial Strains ◽

Human Gut ◽

Strain Specificity ◽

Gut Microbes

Abstract Background: Compelling evidence has linked the commensal gut microbiota to human metabolic syndromes and provided new therapeutic potentials against diseases, such as hyperlipidemia. However, the precise regulatory effect of each bacterial species on human lipid homeostasis remains largely unknown.Results: We set up a cell-based high-throughput screening platform and screened 2250 human gut bacterial strains from 186 species for the lipid-decreasing activity in HepG2 cells, in which 388 strains steadily inhibited lipid accumulation. Different strains in the same species usually displayed distinct lipid-modulatory actions, revealing an obvious strain-specificity. Blautia producta, Lactobacillus gasseri, and Bifidobacterium pseudolongum contained a much higher portion of hypolipidemic strains. Among all the tested strains, the mucosal bacterium Blautia producta exhibited the most potency to suppress lipid accumulation, and gavage of live Bl. producta effectively ameliorated hyperlipidemia in mice. 12-Methylmyristic acid (12-MMA) was identified as an important active metabolite of Bl. producta by pan-genomics and comparative metabolomics, which exerted potent anti-hyperlipidemic effect in vivo and activated G protein-coupled receptor 120 (GPR120), thus stimulating white adipose tissue browning.Conclusions: Together, these data reveal a previously unreported large-scale lipid-modulatory profile of gut microbes at the strain level, and raise the possibility of developing therapeutics based on Bl. producta and microbial metabolite 12-MMA to treat hyperlipidemia.

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Phyto-fabrication of Iron Nanoparticles: Characterization and Antibacterial Capacity

Current Nanoscience ◽

10.2174/1573413716999200817105934 ◽

2020 ◽

Vol 16 ◽

Author(s):

Asma S. Algebaly ◽

Afrah E. Mohammed ◽

Mudawi M. Elobeid

Keyword(s):

Electron Microscopy ◽

Plant Extracts ◽

Large Scale ◽

Iron Nanoparticles ◽

Ethanolic Extract ◽

Green Technology ◽

Resistant Bacteria ◽

Scale Production ◽

Bacterial Strains ◽

Plant Sources

Introduction: Fabrication of iron nanoparticles (FeNPs) has recently gained a great concern for their varied applications in remediation technologies of the environment. Objective: The current study aimed to fabricate iron nanoparticles by green technology approach using different plant sources, Azadirachta indica leaf and Calligonum comosum root following two extraction methods. Methods: Currently, a mixture of FeCl2 and FeCl3 was used to react with the plant extracts which are considered as reducing and stabilizing agents for the generation of FeNPs in one step. Different techniques were used for FeNPs identification. Results: Immediately after mixing of the two reaction components, the color changed to dark brown as an indication of safe conversion of Fe ions to FeNPs, that later confirmed by zeta sizer, transmission electron microscopy (TEM) and scanning electron microscopy (SEM). FeNPs fabricated by C. comosum showed smaller size when compared by those fabricated by A. indica. Using both plant sources, FeNPs fabricated by the aqueous extract had smaller size in relation to those fabricated by ethanolic extract. Furthermore, antibacterial ability against two bacterial strains was approved. Conclusion: The current results indicated that, at room temperature plant extracts fabricated Fe ion to Fe nanoparticles, suggesting its probable usage for large scale production as well as its suitability against bacteria. It could also be recommended for antibiotic resistant bacteria.

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Bullying, School Violence, and Climate in Evolving Contexts

10.1093/oso/9780190663049.001.0001 ◽

2018 ◽

Cited By ~ 4

Author(s):

Ron Avi Astor ◽

Rami Benbenisthty

Keyword(s):

School Violence ◽

School Safety ◽

Media Coverage ◽

Large Scale ◽

Ecological Model ◽

Empirical Studies ◽

Practical Applications ◽

Teacher Student ◽

Area Of Interest ◽

New Research

Since 2005, the bullying, school violence, and school safety literatures have expanded dramatically in content, disciplines, and empirical studies. However, with this massive expansion of research, there is also a surprising lack of theoretical and empirical direction to guide efforts on how to advance our basic science and practical applications of this growing scientific area of interest. Parallel to this surge in interest, cultural norms, media coverage, and policies to address school safety and bullying have evolved at a remarkably quick pace over the past 13 years. For example, behaviors and populations that just a decade ago were not included in the school violence, bullying, and school safety discourse are now accepted areas of inquiry. These include, for instance, cyberbullying, sexting, social media shaming, teacher–student and student–teacher bullying, sexual harassment and assault, homicide, and suicide. Populations in schools not previously explored, such as lesbian, gay, bisexual, transgender, and queer students and educators and military- and veteran-connected students, become the foci of new research, policies, and programs. As a result, all US states and most industrialized countries now have a complex quilt of new school safety and bullying legislation and policies. Large-scale research and intervention funding programs are often linked to these policies. This book suggests an empirically driven unifying model that brings together these previously distinct literatures. This book presents an ecological model of school violence, bullying, and safety in evolving contexts that integrates all we have learned in the 13 years, and suggests ways to move forward.

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Large-Scale, High-Throughput Validation of Short Hairpin RNA Sequences for RNA Interference

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057105284342 ◽

2006 ◽

Vol 11 (3) ◽

pp. 236-246 ◽

Cited By ~ 6

Author(s):

Laurence H. Lamarcq ◽

Bradley J. Scherer ◽

Michael L. Phelan ◽

Nikolai N. Kalnine ◽

Yen H. Nguyen ◽

...

Keyword(s):

High Throughput ◽

Large Scale ◽

Strong Support ◽

Gc Content ◽

Rapid Identification ◽

Hairpin Rna ◽

Rna Sequences ◽

Short Hairpin ◽

Short Hairpin Rnas ◽

Interfering Rna

A method for high-throughput cloning and analysis of short hairpin RNAs (shRNAs) is described. Using this approach, 464 shRNAs against 116 different genes were screened for knockdown efficacy, enabling rapid identification of effective shRNAs against 74 genes. Statistical analysis of the effects of various criteria on the activity of the shRNAs confirmed that some of the rules thought to govern small interfering RNA (siRNA) activity also apply to shRNAs. These include moderate GC content, absence of internal hairpins, and asymmetric thermal stability. However, the authors did not find strong support for positionspecific rules. In addition, analysis of the data suggests that not all genes are equally susceptible to RNAinterference (RNAi).

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Supply chain resilience in a developing country context: a case study on the interconnectedness of threats, strategies and outcomes

Supply Chain Management An International Journal ◽

10.1108/scm-02-2017-0059 ◽

2017 ◽

Vol 22 (6) ◽

pp. 486-505 ◽

Cited By ~ 38

Author(s):

Benjamin Tukamuhabwa ◽

Mark Stevenson ◽

Jerry Busby

Keyword(s):

Supply Chain ◽

Developing Country ◽

Large Scale ◽

Empirical Studies ◽

Small Scale ◽

Supply Network ◽

Catastrophic Events ◽

Content Type ◽

Supply Chain Resilience

Purpose In few prior empirical studies on supply chain resilience (SCRES), the focus has been on the developed world. Yet, organisations in developing countries constitute a significant part of global supply chains and have also experienced the disastrous effects of supply chain failures. The purpose of this paper is therefore to empirically investigate SCRES in a developing country context and to show that this also provides theoretical insights into the nature of what is meant by resilience. Design/methodology/approach Using a case study approach, a supply network of 20 manufacturing firms in Uganda is analysed based on a total of 45 interviews. Findings The perceived threats to SCRES in this context are mainly small-scale, chronic disruptive events rather than discrete, large-scale catastrophic events typically emphasised in the literature. The data reveal how threats of disruption, resilience strategies and outcomes are inter-related in complex, coupled and non-linear ways. These interrelationships are explained by the political, cultural and territorial embeddedness of the supply network in a developing country. Further, this embeddedness contributes to the phenomenon of supply chain risk migration, whereby an attempt to mitigate one threat produces another threat and/or shifts the threat to another point in the supply network. Practical implications Managers should be aware, for example, of potential risk migration from one threat to another when crafting strategies to build SCRES. Equally, the potential for risk migration across the supply network means managers should look at the supply chain holistically because actors along the chain are so interconnected. Originality/value The paper goes beyond the extant literature by highlighting how SCRES is not only about responding to specific, isolated threats but about the continuous management of risk migration. It demonstrates that resilience requires both an understanding of the interconnectedness of threats, strategies and outcomes and an understanding of the embeddedness of the supply network. Finally, this study’s focus on the context of a developing country reveals that resilience should be equally concerned both with smaller in scale, chronic disruptions and with occasional, large-scale catastrophic events.

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“I Will Never Know the Person Who I Could Have Become”: Perceived Changes in Self-Identity Among Adult Survivors of Clergy-Perpetrated Sexual Abuse

Journal of Interpersonal Violence ◽

10.1177/0886260516650966 ◽

2016 ◽

Vol 34 (6) ◽

pp. 1139-1162 ◽

Cited By ~ 1

Author(s):

Scott D. Easton ◽

Danielle M. Leone-Sheehan ◽

Patrick J. O’Leary

Keyword(s):

Sexual Abuse ◽

Media Coverage ◽

Large Scale ◽

Clinical Sample ◽

Empirical Studies ◽

Adult Survivors ◽

Well Being ◽

Future Research ◽

Relational Self ◽

Self Identity

Clergy-perpetrated sexual abuse (CPSA) during childhood represents a tragic betrayal of trust that inflicts damage on the survivor, the family, and the parish community. Survivors often report CPSA has a disturbing impact on their self-identity. Despite intense media coverage of clergy abuse globally in the Catholic Church (and other faith communities) over several decades, relatively few empirical studies have been conducted with survivors. Beyond clinical observations and advocacy group reports, very little is known about survivors’ perceptions of how the abuse impacted their long-term self-identity. Using data collected during the 2010 Health and Well-Being Survey, this qualitative analysis represents one of the first large-scale studies with a non-clinical sample of adult male survivors of CPSA from childhood ( N = 205). The negative effects of the sexual abuse on participants were expressed across six domains of self-identity: (a) total self, (b) psychological self, (c) relational self, (d) gendered self, (e) aspirational self, and (f) spiritual self. These findings highlight the range and depth of self-suffering inflicted by this pernicious form of sexual violence. The findings are useful for developing clinical services for survivors, shaping public and institutional policies to address clergy-perpetrated sexual abuse, and guiding future research with this population.

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Identifying chironomids (Diptera: Chironomidae) for biological monitoring with PCR–RFLP

Bulletin of Entomological Research ◽

10.1079/ber2003268 ◽

2003 ◽

Vol 93 (6) ◽

pp. 483-490 ◽

Cited By ~ 28

Author(s):

M.E. Carew ◽

V. Pettigrove ◽

A.A. Hoffmann

Keyword(s):

Molecular Markers ◽

Large Scale ◽

Life Stage ◽

Biological Indicators ◽

Geographic Area ◽

Common Species ◽

Rapid Identification ◽

Chironomid Species ◽

Pcr Rflp ◽

Identification Of Species

AbstractChironomids are excellent biological indicators for the health of aquatic ecosystems, but their use at finer taxonomic levels is hindered by morphological similarity of species at each life stage. Molecular markers have the potential to overcome these problems by facilitating species identification particularly in large-scale surveys. In this study, the potential of the polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) approach was tested to rapidly distinguish among chironomids within a geographic area, by considering chironomid species from Melbourne, Australia. By comparing molecular markers with diagnostic morphological traits, RFLP profiles of the cytochrome oxidase I (COI) region were identified that were specific to genera and some common species. These profiles were used to develop an RFLP–based key, which was validated by testing the markers on samples from several wetlands and streams. As well as allowing for rapid identification of species that are difficult to separate on morphological grounds, this approach also has the potential to resolve current taxonomic ambiguities.

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DeepMAsED: evaluating the quality of metagenomic assemblies

Bioinformatics ◽

10.1093/bioinformatics/btaa124 ◽

2020 ◽

Vol 36 (10) ◽

pp. 3011-3017 ◽

Cited By ~ 5

Author(s):

Olga Mineeva ◽

Mateo Rojas-Carulla ◽

Ruth E Ley ◽

Bernhard Schölkopf ◽

Nicholas D Youngblut

Keyword(s):

Large Scale ◽

State Of The Art ◽

Ground Truth ◽

Supplementary Information ◽

Learning Approach ◽

Wide Range ◽

Metagenome Assembly ◽

Model Training ◽

Reference Genomes

Abstract Motivation Methodological advances in metagenome assembly are rapidly increasing in the number of published metagenome assemblies. However, identifying misassemblies is challenging due to a lack of closely related reference genomes that can act as pseudo ground truth. Existing reference-free methods are no longer maintained, can make strong assumptions that may not hold across a diversity of research projects, and have not been validated on large-scale metagenome assemblies. Results We present DeepMAsED, a deep learning approach for identifying misassembled contigs without the need for reference genomes. Moreover, we provide an in silico pipeline for generating large-scale, realistic metagenome assemblies for comprehensive model training and testing. DeepMAsED accuracy substantially exceeds the state-of-the-art when applied to large and complex metagenome assemblies. Our model estimates a 1% contig misassembly rate in two recent large-scale metagenome assembly publications. Conclusions DeepMAsED accurately identifies misassemblies in metagenome-assembled contigs from a broad diversity of bacteria and archaea without the need for reference genomes or strong modeling assumptions. Running DeepMAsED is straight-forward, as well as is model re-training with our dataset generation pipeline. Therefore, DeepMAsED is a flexible misassembly classifier that can be applied to a wide range of metagenome assembly projects. Availability and implementation DeepMAsED is available from GitHub at https://github.com/leylabmpi/DeepMAsED. Supplementary information Supplementary data are available at Bioinformatics online.

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Technology Acceptance in Healthcare: A Systematic Review

Applied Sciences ◽

10.3390/app112210537 ◽

2021 ◽

Vol 11 (22) ◽

pp. 10537

Author(s):

Adi A. AlQudah ◽

Mostafa Al-Emran ◽

Khaled Shaalan

Keyword(s):

Systematic Review ◽

Technology Acceptance ◽

Large Scale ◽

Empirical Studies ◽

Influential Factors ◽

Full Potential ◽

Eligibility Criteria ◽

Factors Affecting ◽

The Usa ◽

Healthcare Technologies

Understanding the factors affecting the use of healthcare technologies is a crucial topic that has been extensively studied, specifically during the last decade. These factors were studied using different technology acceptance models and theories. However, a systematic review that offers extensive understanding into what affects healthcare technologies and services and covers distinctive trends in large-scale research remains lacking. Therefore, this review aims to systematically review the articles published on technology acceptance in healthcare. From a yield of 1768 studies collected, 142 empirical studies have met the eligibility criteria and were extensively analyzed. The key findings confirmed that TAM and UTAUT are the most prevailing models in explaining what affects the acceptance of various healthcare technologies through different user groups, settings, and countries. Apart from the core constructs of TAM and UTAUT, the results showed that anxiety, computer self-efficacy, innovativeness, and trust are the most influential factors affecting various healthcare technologies. The results also revealed that Taiwan and the USA are leading the research of technology acceptance in healthcare, with a remarkable increase in studies focusing on telemedicine and electronic medical records solutions. This review is believed to enhance our understanding through a number of theoretical contributions and practical implications by unveiling the full potential of technology acceptance in healthcare and opening the door for further research opportunities.

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Accuracy and efficiency of germline variant calling pipelines for human genome data

10.1101/2020.03.27.011767 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sen Zhao ◽

Oleg Agafonov ◽

Abdulrahman Azab ◽

Tomasz Stokowy ◽

Eivind Hovig

Keyword(s):

Large Scale ◽

Variant Calling ◽

Performance Comparison ◽

Next Generation Sequencing Technology ◽

Genome Data ◽

Germline Variant ◽

Causal Variants ◽

Variant Detection ◽

Variant Analysis ◽

Human Genome Data

AbstractAdvances in next-generation sequencing technology has enabled whole genome sequencing (WGS) to be widely used for identification of causal variants in a spectrum of genetic-related disorders, and provided new insight into how genetic polymorphisms affect disease phenotypes. The development of different bioinformatics pipelines has continuously improved the variant analysis of WGS data, however there is a necessity for a systematic performance comparison of these pipelines to provide guidance on the application of WGS-based scientific and clinical genomics. In this study, we evaluated the performance of three variant calling pipelines (GATK, DRAGEN™ and DeepVariant) using Genome in a Bottle Consortium, “synthetic-diploid” and simulated WGS datasets. DRAGEN™ and DeepVariant show a better accuracy in SNPs and indels calling, with no significant differences in their F1-score. DRAGEN™ platform offers accuracy, flexibility and a highly-efficient running speed, and therefore superior advantage in the analysis of WGS data on a large scale. The combination of DRAGEN™ and DeepVariant also provides a good balance of accuracy and efficiency as an alternative solution for germline variant detection in further applications. Our results facilitate the standardization of benchmarking analysis of bioinformatics pipelines for reliable variant detection, which is critical in genetics-based medical research and clinical application.

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