scholarly journals New tools for diet analysis: nanopore sequencing of metagenomic DNA from rat stomach contents to quantify diet

2018 ◽  
Author(s):  
Nikki E. Freed ◽  
William S. Pearman ◽  
Adam N. H. Smith ◽  
Georgia Breckell ◽  
James Dale ◽  
...  
Keyword(s):  
Stomach Contents ◽  
Ground Truth ◽  
Diet Analysis ◽  
Sampling Location ◽  
Metagenomic Sequencing ◽  
Genomic Databases ◽  
Promising Alternative ◽  
Constrained Ordination ◽  
Wide Range ◽  
Long Read

AbstractBackgroundUsing metagenomics to determine animal diet offers a new and promising alternative to current methods. Here we show that rapid and inexpensive diet quantification is possible through metagenomic sequencing with the portable Oxford Nanopore Technologies (ONT) MinION. Using an amplification-free approach, we profiled the stomach contents from wild-caught rats.ResultsWe conservatively identified diet items from over 50 taxonomic orders, ranging across nine phyla that include plants, vertebrates, invertebrates, and fungi. This highlights the wide range of taxa that can be identified using this simple approach. We calibrate the accuracy of this method by comparing the characteristics of reads matching the ground-truth host genome (rat) to those matching diet items, and show that at the family-level, false positive taxon assignments are approximately 97.5% accurate. We also suggest a way to mitigate for database biases in metagenomic approaches. Finally, we implement a constrained ordination analysis and show that we can identify the sampling location of an individual rat within tens of kilometres based on diet content alone.ConclusionsThis work establishes proof-of-principle for long-read metagenomic methods in quantitative diet analysis. We show that diet content can be quantified even with limited expertise, using a simple, amplification free workflow and a relatively inexpensive and accessible next generation sequencing method. Continued increases in the accuracy and throughput of ONT sequencing, along with improved genomic databases, suggests that a metagenomic approach to quantification of animal diets will become an important method in the future.

Using stomach contents for diet analysis of carnivores through DNA barcoding

2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Teresa Santos ◽  
Carlos Fonseca ◽  
Tânia Barros ◽  
Raquel Godinho ◽  
Cristiane Bastos-Silveira ◽  
...  
Keyword(s):  
Dna Barcoding ◽  
Stomach Contents ◽  
Diet Analysis

scholarly journals Biosynthetic potential of uncultured Antarctic soil bacteria revealed through long-read metagenomic sequencing

2021 ◽  
Author(s):  
Valentin Waschulin ◽  
Chiara Borsetto ◽  
Robert James ◽  
Kevin K. Newsham ◽  
Stefano Donadio ◽  
...  
Keyword(s):  
Genome Mining ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Full Length ◽  
Metagenomic Sequencing ◽  
Short Read ◽  
Short Read Sequencing ◽  
Rich Diversity ◽  
Long Read ◽  
The Rich

AbstractThe growing problem of antibiotic resistance has led to the exploration of uncultured bacteria as potential sources of new antimicrobials. PCR amplicon analyses and short-read sequencing studies of samples from different environments have reported evidence of high biosynthetic gene cluster (BGC) diversity in metagenomes, indicating their potential for producing novel and useful compounds. However, recovering full-length BGC sequences from uncultivated bacteria remains a challenge due to the technological restraints of short-read sequencing, thus making assessment of BGC diversity difficult. Here, long-read sequencing and genome mining were used to recover >1400 mostly full-length BGCs that demonstrate the rich diversity of BGCs from uncultivated lineages present in soil from Mars Oasis, Antarctica. A large number of highly divergent BGCs were not only found in the phyla Acidobacteriota, Verrucomicrobiota and Gemmatimonadota but also in the actinobacterial classes Acidimicrobiia and Thermoleophilia and the gammaproteobacterial order UBA7966. The latter furthermore contained a potential novel family of RiPPs. Our findings underline the biosynthetic potential of underexplored phyla as well as unexplored lineages within seemingly well-studied producer phyla. They also showcase long-read metagenomic sequencing as a promising way to access the untapped genetic reservoir of specialised metabolite gene clusters of the uncultured majority of microbes.

scholarly journals Classification of unlabeled online media

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sakthi Kumar Arul Prakash ◽  
Conrad Tucker
Keyword(s):  
Social Media ◽  
Real World ◽  
Graphical Model ◽  
Ground Truth ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
Social Media Networks ◽  
Online Social Media ◽  
Wide Range

AbstractThis work investigates the ability to classify misinformation in online social media networks in a manner that avoids the need for ground truth labels. Rather than approach the classification problem as a task for humans or machine learning algorithms, this work leverages user–user and user–media (i.e.,media likes) interactions to infer the type of information (fake vs. authentic) being spread, without needing to know the actual details of the information itself. To study the inception and evolution of user–user and user–media interactions over time, we create an experimental platform that mimics the functionality of real-world social media networks. We develop a graphical model that considers the evolution of this network topology to model the uncertainty (entropy) propagation when fake and authentic media disseminates across the network. The creation of a real-world social media network enables a wide range of hypotheses to be tested pertaining to users, their interactions with other users, and with media content. The discovery that the entropy of user–user and user–media interactions approximate fake and authentic media likes, enables us to classify fake media in an unsupervised learning manner.

scholarly journals SCAPP: an algorithm for improved plasmid assembly in metagenomes

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
David Pellow ◽  
Alvah Zorea ◽  
Maraike Probst ◽  
Ori Furman ◽  
Arik Segal ◽  
...  
Keyword(s):  
Bacterial Species ◽  
Bacterial Genome ◽  
Biological Knowledge ◽  
Assessment Procedure ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Human Gut ◽  
Double Stranded Dna ◽  
Wide Range ◽  
Python Package

Abstract Background Metagenomic sequencing has led to the identification and assembly of many new bacterial genome sequences. These bacteria often contain plasmids: usually small, circular double-stranded DNA molecules that may transfer across bacterial species and confer antibiotic resistance. These plasmids are generally less studied and understood than their bacterial hosts. Part of the reason for this is insufficient computational tools enabling the analysis of plasmids in metagenomic samples. Results We developed SCAPP (Sequence Contents-Aware Plasmid Peeler)—an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. SCAPP builds on some key ideas from the Recycler algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids. We compared the performance of SCAPP to Recycler and metaplasmidSPAdes on simulated metagenomes, real human gut microbiome samples, and a human gut plasmidome dataset that we generated. We also created plasmidome and metagenome data from the same cow rumen sample and used the parallel sequencing data to create a novel assessment procedure. Overall, SCAPP outperformed Recycler and metaplasmidSPAdes across this wide range of datasets. Conclusions SCAPP is an easy to use Python package that enables the assembly of full plasmid sequences from metagenomic samples. It outperformed existing metagenomic plasmid assemblers in most cases and assembled novel and clinically relevant plasmids in samples we generated such as a human gut plasmidome. SCAPP is open-source software available from: https://github.com/Shamir-Lab/SCAPP.

scholarly journals Microdiversity and phylogeographic diversification of bacterioplankton in pelagic freshwater systems revealed through long-read amplicon sequencing

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Yusuke Okazaki ◽  
Shohei Fujinaga ◽  
Michaela M. Salcher ◽  
Cristiana Callieri ◽  
Atsushi Tanaka ◽  
...  
Keyword(s):  
16S Rrna ◽  
Regional Scale ◽  
Scale Up ◽  
Amplicon Sequencing ◽  
Freshwater Ecosystems ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Rrna Gene ◽  
Metagenomic Sequencing ◽  
Long Read

Abstract Background Freshwater ecosystems are inhabited by members of cosmopolitan bacterioplankton lineages despite the disconnected nature of these habitats. The lineages are delineated based on > 97% 16S rRNA gene sequence similarity, but their intra-lineage microdiversity and phylogeography, which are key to understanding the eco-evolutional processes behind their ubiquity, remain unresolved. Here, we applied long-read amplicon sequencing targeting nearly full-length 16S rRNA genes and the adjacent ribosomal internal transcribed spacer sequences to reveal the intra-lineage diversities of pelagic bacterioplankton assemblages in 11 deep freshwater lakes in Japan and Europe. Results Our single nucleotide-resolved analysis, which was validated using shotgun metagenomic sequencing, uncovered 7–101 amplicon sequence variants for each of the 11 predominant bacterial lineages and demonstrated sympatric, allopatric, and temporal microdiversities that could not be resolved through conventional approaches. Clusters of samples with similar intra-lineage population compositions were identified, which consistently supported genetic isolation between Japan and Europe. At a regional scale (up to hundreds of kilometers), dispersal between lakes was unlikely to be a limiting factor, and environmental factors or genetic drift were potential determinants of population composition. The extent of microdiversification varied among lineages, suggesting that highly diversified lineages (e.g., Iluma-A2 and acI-A1) achieve their ubiquity by containing a consortium of genotypes specific to each habitat, while less diversified lineages (e.g., CL500-11) may be ubiquitous due to a small number of widespread genotypes. The lowest extent of intra-lineage diversification was observed among the dominant hypolimnion-specific lineage (CL500-11), suggesting that their dispersal among lakes is not limited despite the hypolimnion being a more isolated habitat than the epilimnion. Conclusions Our novel approach complemented the limited resolution of short-read amplicon sequencing and limited sensitivity of the metagenome assembly-based approach, and highlighted the complex ecological processes underlying the ubiquity of freshwater bacterioplankton lineages. To fully exploit the performance of the method, its relatively low read throughput is the major bottleneck to be overcome in the future.

scholarly journals The draft genome sequence of the grove snail Cepaea nemoralis

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Suzanne V Saenko ◽  
Dick S J Groenenberg ◽  
Angus Davison ◽  
Menno Schilthuizen
Keyword(s):  
Genome Sequence ◽  
Draft Genome ◽  
Agricultural Pests ◽  
Shell Color ◽  
Protein Coding ◽  
Cepaea Nemoralis ◽  
Edible Species ◽  
Wide Range ◽  
In Captivity ◽  
Long Read

Abstract Studies on the shell color and banding polymorphism of the grove snail Cepaea nemoralis and the sister taxon Cepaea hortensis have provided compelling evidence for the fundamental role of natural selection in promoting and maintaining intraspecific variation. More recently, Cepaea has been the focus of citizen science projects on shell color evolution in relation to climate change and urbanization. C. nemoralis is particularly useful for studies on the genetics of shell polymorphism and the evolution of “supergenes,” as well as evo-devo studies of shell biomineralization, because it is relatively easily maintained in captivity. However, an absence of genomic resources for C. nemoralis has generally hindered detailed genetic and molecular investigations. We therefore generated ∼23× coverage long-read data for the ∼3.5 Gb genome, and produced a draft assembly composed of 28,537 contigs with the N50 length of 333 kb. Genome completeness, estimated by BUSCO using the metazoa dataset, was 91%. Repetitive regions cover over 77% of the genome. A total of 43,519 protein-coding genes were predicted in the assembled genome, and 97.3% of these were functionally annotated from either sequence homology or protein signature searches. This first assembled and annotated genome sequence for a helicoid snail, a large group that includes edible species, agricultural pests, and parasite hosts, will be a core resource for identifying the loci that determine the shell polymorphism, as well as in a wide range of analyses in evolutionary and developmental biology, and snail biology in general.

A virtual test environment for validating spacecraft optical navigation

2013 ◽  
Vol 117 (1197) ◽  
pp. 1075-1101 ◽  
Author(s):  
S. M. Parkes ◽  
I. Martin ◽  
M. N. Dunstan ◽  
N. Rowell ◽  
O. Dubois-Matra ◽  
...  
Keyword(s):  
Small Body ◽  
European Space Agency ◽  
Ground Truth ◽  
Camera Motion ◽  
Test Environment ◽  
Space Applications ◽  
Vision Guidance ◽  
Space Agency ◽  
Wide Range ◽  
And Performance

Abstract The use of machine vision to guide robotic spacecraft is being considered for a wide range of missions, such as planetary approach and landing, asteroid and small body sampling operations and in-orbit rendezvous and docking. Numerical simulation plays an essential role in the development and testing of such systems, which in the context of vision-guidance means that realistic sequences of navigation images are required, together with knowledge of the ground-truth camera motion. Computer generated imagery (CGI) offers a variety of benefits over real images, such as availability, cost, flexibility and knowledge of the ground truth camera motion to high precision. However, standard CGI methods developed for terrestrial applications lack the realism, fidelity and performance required for engineering simulations. In this paper, we present the results of our ongoing work to develop a suitable CGI-based test environment for spacecraft vision guidance systems. We focus on the various issues involved with image simulation, including the selection of standard CGI techniques and the adaptations required for use in space applications. We also describe our approach to integration with high-fidelity end-to-end mission simulators, and summarise a variety of European Space Agency research and development projects that used our test environment.

Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

2021 ◽  
Vol 143 (3) ◽  
Author(s):  
Suhui Li ◽  
Huaxin Zhu ◽  
Min Zhu ◽  
Gang Zhao ◽  
Xiaofeng Wei
Keyword(s):  
Machine Learning ◽  
Power Plant ◽  
Gas Turbine ◽  
Operating Conditions ◽  
Data Driven ◽  
Ann Model ◽  
Promising Alternative ◽  
Combustion Performance ◽  
Wide Range ◽  
Gas Turbine Power Plant

Abstract Conventional physics-based or experimental-based approaches for gas turbine combustion tuning are time consuming and cost intensive. Recent advances in data analytics provide an alternative method. In this paper, we present a cross-disciplinary study on the combustion tuning of an F-class gas turbine that combines machine learning with physics understanding. An artificial-neural-network-based (ANN) model is developed to predict the combustion performance (outputs), including NOx emissions, combustion dynamics, combustor vibrational acceleration, and turbine exhaust temperature. The inputs of the ANN model are identified by analyzing the key operating variables that impact the combustion performance, such as the pilot and the premixed fuel flow, and the inlet guide vane angle. The ANN model is trained by field data from an F-class gas turbine power plant. The trained model is able to describe the combustion performance at an acceptable accuracy in a wide range of operating conditions. In combination with the genetic algorithm, the model is applied to optimize the combustion performance of the gas turbine. Results demonstrate that the data-driven method offers a promising alternative for combustion tuning at a low cost and fast turn-around.

scholarly journals Protein dynamics revealed by NMR relaxation methods

2018 ◽  
Vol 2 (1) ◽  
pp. 93-105 ◽  
Author(s):  
Fa-An Chao ◽  
R. Andrew Byrd
Keyword(s):  
Protein Dynamics ◽  
Structural Biology ◽  
Dynamic Models ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data Bank ◽  
Biological Macromolecules ◽  
Relaxation Methods ◽  
Genomic Databases ◽  
Wide Range

Structural biology often focuses primarily on three-dimensional structures of biological macromolecules, deposited in the Protein Data Bank (PDB). This resource is a remarkable entity for the worldwide scientific and medical communities, as well as the general public, as it is a growing translation into three-dimensional space of the vast information in genomic databases, e.g. GENBANK. There is, however, significantly more to understanding biological function than the three-dimensional co-ordinate space for ground-state structures of biomolecules. The vast array of biomolecules experiences natural dynamics, interconversion between multiple conformational states, and molecular recognition and allosteric events that play out on timescales ranging from picoseconds to seconds. This wide range of timescales demands ingenious and sophisticated experimental tools to sample and interpret these motions, thus enabling clearer insights into functional annotation of the PDB. NMR spectroscopy is unique in its ability to sample this range of timescales at atomic resolution and in physiologically relevant conditions using spin relaxation methods. The field is constantly expanding to provide new creative experiments, to yield more detailed coverage of timescales, and to broaden the power of interpretation and analysis methods. This review highlights the current state of the methodology and examines the extension of analysis tools for more complex experiments and dynamic models. The future for understanding protein dynamics is bright, and these extended tools bring greater compatibility with developments in computational molecular dynamics, all of which will further our understanding of biological molecular functions. These facets place NMR as a key component in integrated structural biology.

scholarly journals A Novel Design Combining Isothermal Exponential Amplification and Gold-Nanoparticles Visualization for Rapid Detection of miRNAs

2018 ◽  
Vol 19 (11) ◽  
pp. 3374 ◽  
Author(s):  
Jiquan Jiang ◽  
Bin Zhang ◽  
Chi Zhang ◽  
Yifu Guan
Keyword(s):  
Early Phase ◽  
Color Change ◽  
Direct Detection ◽  
Colorimetric Assay ◽  
Disease Diagnosis ◽  
Dna Probes ◽  
Time Saving ◽  
Promising Alternative ◽  
Sandwich Hybridization ◽  
Wide Range

MicroRNAs (miRNAs) play important roles in a wide range of biological processes, and their aberrant expressions are associated with various diseases. The levels of miRNAs can be useful biomarkers for cellular events or disease diagnosis; thus, sensitive and selective detection of microRNAs is of great significance in understanding biological functions of miRNAs, early-phase diagnosis of cancers, and discovery of new targets for drugs. However, traditional approaches for the detection of miRNAs are usually laborious and time-consuming, with a low sensitivity. Here, we develop a simple, rapid, ultrasensitive colorimetric assay based on the combination of isothermal Exponential Amplification Reaction (EXPAR) and AuNP-labeled DNA probes for the detection of miRNAs (taking let-7a as a model analyte). In this assay, the presence of let-7a is converted to the reporter Y through EXPAR under isothermal conditions. The subsequent sandwich hybridization of the reporter Y with the AuNP-labeled DNA probes generates a red-to-purple color change. In other words, if the reporter Y is complementary to the AuNP-labeled DNA probes, the DNA-functionalized AuNPs will be aggregated, resulting in the change of solution color from red to purple/blue, while when the AuNP-labeled DNA probes are mismatched to the reporter Y, the solution remains red. This assay represents a simple, time-saving technique, and its results can be visually detected with the naked eye due to the colorimetric change. The method provides superior sensitivity, with a detection limit of 4.176 aM over a wide range from 1 nM to 1 aM under optimal conditions. The method also shows high selectivity for discriminating even single-nucleotide differences between let-7 miRNA family members. Notably, it is comparable to the most sensitive method reported to date, thus providing a promising alternative to standard approaches for the direct detection of let-7a miRNA. Importantly, through combination with specific templates, different miRNAs can be converted to the same reporter Y, which can hybridize with the same set of AuNP-labeled DNA probes to form sandwich hybrids. The color change of the solution can be observed in the presence of the target miRNA. This technique has potential as a routine method for assessing the levels of miRNAs, not only for let-7, but also for various miRNAs in the early phase of cancers. In addition, it can be a useful tool in biomedical research and clinical diagnosis, as well as diagnosis or surveillance programs in field conditions.

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