2,460 research outputs found
Steps in Metagenomics: Letâs Avoid Garbage in and Garbage Out
Is metagenomics a revolution or a new fad? Metagenomics is tightly associated with the availability of next-generation sequencing in all its implementations. The key feature of these new technologies, moving beyond the Sanger-based DNA sequencing approach, is the depth of nucleotide sequencing per sample.1 Knowing much more about a sample changes the traditional paradigms of âWhat is the most abundant?â or âWhat is the most significant?â to âWhat is present and potentially sigÂnificant that might influence the situation and outcome?â Letâs take the case of identifying proper biomarkers of disease state in the context of chronic disease prevention. Prevention has been deemed as a viable option to avert human chronic diseases and to curb healthÂcare management costs.2 The actual implementation of any effective preventive measures has proven to be rather difficult. In addition to the typically poor compliance of the general public, the vagueness of the successful validation of habit modification on the long-term risk, points to the need of defining new biomarkers of disease state. Scientists and the public are accepting the fact that humans are super-organisms, harboring both a human genome and a microbial genome, the latter being much bigger in size and diversity, and key for the health of individuals.3,4 It is time to investigate the intricate relationship between humans and their associated microbiota and how this relationship modÂulates or affects both partners.5 These remarks can be expanded to the animal and plant kingdoms, and holistically to the Earthâs biome. By its nature, the evolution and function of all the Earthâs biomes are influenced by a myriad of interactions between and among microbes (planktonic, in biofilms or host associated) and the surrounding physical environment.
The general definition of metagenomics is the cultivation-indepenÂdent analysis of the genetic information of the collective genomes of the microbes within a given environment based on its sampling. It focuses on the collection of genetic information through sequencing that can target DNA, RNA, or both. The subsequent analyses can be solely foÂcused on sequence conservation, phylogenetic, phylogenomic, function, or genetic diversity representation including yet-to-be annotated genes. The diversity of hypotheses, questions, and goals to be accomplished is endless. The primary design is based on the nature of the material to be analyzed and its primary function
Multi-camera Realtime 3D Tracking of Multiple Flying Animals
Automated tracking of animal movement allows analyses that would not
otherwise be possible by providing great quantities of data. The additional
capability of tracking in realtime - with minimal latency - opens up the
experimental possibility of manipulating sensory feedback, thus allowing
detailed explorations of the neural basis for control of behavior. Here we
describe a new system capable of tracking the position and body orientation of
animals such as flies and birds. The system operates with less than 40 msec
latency and can track multiple animals simultaneously. To achieve these
results, a multi target tracking algorithm was developed based on the Extended
Kalman Filter and the Nearest Neighbor Standard Filter data association
algorithm. In one implementation, an eleven camera system is capable of
tracking three flies simultaneously at 60 frames per second using a gigabit
network of nine standard Intel Pentium 4 and Core 2 Duo computers. This
manuscript presents the rationale and details of the algorithms employed and
shows three implementations of the system. An experiment was performed using
the tracking system to measure the effect of visual contrast on the flight
speed of Drosophila melanogaster. At low contrasts, speed is more variable and
faster on average than at high contrasts. Thus, the system is already a useful
tool to study the neurobiology and behavior of freely flying animals. If
combined with other techniques, such as `virtual reality'-type computer
graphics or genetic manipulation, the tracking system would offer a powerful
new way to investigate the biology of flying animals.Comment: pdfTeX using libpoppler 3.141592-1.40.3-2.2 (Web2C 7.5.6), 18 pages
with 9 figure
Computational approaches for improving treatment and prevention of viral infections
The treatment of infections with HIV or HCV is challenging. Thus, novel drugs and new computational approaches that support the selection of therapies are required. This work presents methods that support therapy selection as well as methods that advance novel antiviral treatments. geno2pheno[ngs-freq] identifies drug resistance from HIV-1 or HCV samples that were subjected to next-generation sequencing by interpreting their sequences either via support vector machines or a rules-based approach. geno2pheno[coreceptor-hiv2] determines the coreceptor that is used for viral cell entry by analyzing a segment of the HIV-2 surface protein with a support vector machine. openPrimeR is capable of finding optimal combinations of primers for multiplex polymerase chain reaction by solving a set cover problem and accessing a new logistic regression model for determining amplification events arising from polymerase chain reaction. geno2pheno[ngs-freq] and geno2pheno[coreceptor-hiv2] enable the personalization of antiviral treatments and support clinical decision making. The application of openPrimeR on human immunoglobulin sequences has resulted in novel primer sets that improve the isolation of broadly neutralizing antibodies against HIV-1. The methods that were developed in this work thus constitute important contributions towards improving the prevention and treatment of viral infectious diseases.Die Behandlung von HIV- oder HCV-Infektionen ist herausfordernd. Daher werden neue Wirkstoffe, sowie neue computerbasierte Verfahren benötigt, welche die Therapie verbessern. In dieser Arbeit wurden Methoden zur UnterstĂŒtzung der Therapieauswahl entwickelt, aber auch solche, welche neuartige Therapien vorantreiben. geno2pheno[ngs-freq] bestimmt, ob Resistenzen gegen Medikamente vorliegen, indem es Hochdurchsatzsequenzierungsdaten von HIV-1 oder HCV Proben mittels Support Vector Machines oder einem regelbasierten Ansatz interpretiert. geno2pheno[coreceptor-hiv2] bestimmt den HIV-2 Korezeptorgebrauch dadurch, dass es einen Abschnitt des viralen OberflĂ€chenproteins mit einer Support Vector Machine analysiert. openPrimeR kann optimale Kombinationen von Primern fĂŒr die Multiplex-Polymerasekettenreaktion finden, indem es ein MengenĂŒberdeckungsproblem löst und auf ein neues logistisches Regressionsmodell fĂŒr die Vorhersage von Amplifizierungsereignissen zurĂŒckgreift. geno2pheno[ngs-freq] und geno2pheno[coreceptor-hiv2] ermöglichen die Personalisierung antiviraler Therapien und unterstĂŒtzen die klinische Entscheidungsfindung. Durch den Einsatz von openPrimeR auf humanen Immunoglobulinsequenzen konnten PrimersĂ€tze generiert werden, welche die Isolierung von breit neutralisierenden Antikörpern gegen HIV-1 verbessern. Die in dieser Arbeit entwickelten Methoden leisten somit einen wichtigen Beitrag zur Verbesserung der PrĂ€vention und Therapie viraler Infektionskrankheiten
Biofilm-related characteristics in clinical isolates of Extraintestinal Pathogenic E. coli
The rapid increase in antibiotic resistance is one of the leading global health issues at present time. Bacteriaâs resistance to antibiotic agents can be a thousand times higher when they are embedded in an extracellular biopolymer matrix, defined as biofilm. The biofilm state is a major driver of persistent infections, offering a challenge in providing adequate treatment. Biofilm producing E. coli is a common cause of infections at extraintestinal sites, like the urinary tract or the bloodstream. By investigating the biofilm phenotype of clinical ExPEC isolates and correlating it to other phenotypic and genotypic traits, we aim to generate novel knowledge in this field, and contribute to predict the clinical manifestation, severity, and treatment of such infections.
The biofilm forming capacity of the strains was evaluated both qualitatively and quantitatively. The presence of major biofilm matrix components, curli and cellulose, was investigated by staining with Congo Red and Calcofluor. Additional quantitative measures of number of CFUs contributing to the biofilm, total biomass on pegs and in wells were conducted. Genotypic characterization of the strains ST, fimH/fumC allele, serotype, plasmids, virulence factors and resistance genes were conducted by uploading the strains genome to specific webtools. Additionally, the strains motile and haemolytic behaviour was investigated. These traits were analysed for correlation to their biofilm phenotype.
Our results display preliminary trends within biofilm formation in clinical ExPEC isolates, with a potential for further investigation. We suggest that complementation of genotypic analyses and effects of knock out mutants is further investigated with a bigger sample size, to better understand the effects these traits exhibit on biofilm formation
Gramene QTL database: development, content and applications
Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene-phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research
From bits to bites: Advancement of the Germinate platform to support prebreeding informatics for crop wild relatives
Management and distribution of experimental data from prebreeding projects
is important to ensure uptake of germplasm into breeding and research programs.
Being able to access and share this data in standard formats is essential.
The adoption of a common informatics platform for crops that may have limited
resources brings economies of scale, allowing common informatics components
to be used across multiple species. The close integration of such a platform with
commonly used breeding software, visualization, and analysis tools reduces the
barrier for entry to researchers and provides a common framework to facilitate
collaborations and data sharing. This work presents significant updates to the
Germinate platform and highlights its value in distributing prebreeding data for
14 crops as part of the project âAdapting Agriculture to Climate Change: Collecting,
Protecting and Preparing Crop Wild Relativesâ (hereafter Crop Trust Crop
Wild Relatives project) led by the Crop Trust (https://www.cwrdiversity.org). The
addition of data on these species compliments data already publicly available in
Germinate. We present a suite of updated Germinate features using examples
from these crop species and their wild relatives. The use of Germinate within the
Crop TrustCropWildRelatives project demonstrates the usefulness of the system
and the benefits a shared informatics platform provides. These data resources
provide a foundation on which breeding and research communities can develop
additional online resources for their crops, harness new data as it becomes available,
and benefit collectively from future developments of the Germinate platform
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