scholarly journals Strain-Level Metagenomic Data Analysis of Enriched In Vitro and In Silico Spiked Food Samples: Paving the Way towards a Culture-Free Foodborne Outbreak Investigation Using STEC as a Case Study

2020 ◽  
Vol 21 (16) ◽  
pp. 5688
Author(s):  
Assia Saltykova ◽  
Florence E. Buytaers ◽  
Sarah Denayer ◽  
Bavo Verhaegen ◽  
Denis Piérard ◽  
...  
Keyword(s):  
Data Analysis ◽  
In Silico ◽  
Food Samples ◽  
Strain Level ◽  
Outbreak Investigation ◽  
Metagenomic Data ◽  
Analysis Approach ◽  
Foodborne Outbreak ◽  
Metagenomic Approach

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample.

scholarly journals Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale

2017 ◽  
Author(s):  
Alex Bishara ◽  
Eli L. Moss ◽  
Ekaterina Tkachenko ◽  
Joyce B. Kang ◽  
Soumaya Zlitni ◽  
...  
Keyword(s):  
Hematopoietic Cell Transplantation ◽  
Susceptibility Testing ◽  
Mobile Element ◽  
Strain Level ◽  
Short Read Sequencing ◽  
Bacterial Competition ◽  
Structural Differences ◽  
Stool Samples ◽  
Metagenomic Approach

AbstractAlthough shotgun short-read sequencing has facilitated the study of strain-level architecture within complex microbial communities, existing metagenomic approaches often cannot capture structural differences between closely related co-occurring strains. Recent methods, which employ read cloud sequencing and specialized assembly techniques, provide significantly improved genome drafts and show potential to capture these strain-level differences. Here, we apply this read cloud metagenomic approach to longitudinal stool samples from a patient undergoing hematopoietic cell transplantation. The patient’s microbiome is profoundly disrupted and is eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allows us to predict that particular mobile element integrations result in increased antibiotic resistance, which we further support using in vitro antibiotic susceptibility testing. Thus, we find read cloud sequencing to be useful in identifying strain-level differences that underlie differential fitness.

scholarly journals Application of a strain-level shotgun metagenomics approach on food samples: resolution of the source of a Salmonella food-borne outbreak

2021 ◽  
Vol 7 (4) ◽  
Author(s):  
Florence E. Buytaers ◽  
Assia Saltykova ◽  
Wesley Mattheus ◽  
Bavo Verhaegen ◽  
Nancy H. C. Roosens ◽  
...  
Keyword(s):  
Food Samples ◽  
Strain Level ◽  
Outbreak Investigation ◽  
Reference Laboratory ◽  
Shotgun Metagenomics ◽  
Content Type ◽  
National Reference ◽  
Link Type ◽  
Food Borne ◽  
Food Isolate

Food-borne outbreak investigation currently relies on the time-consuming and challenging bacterial isolation from food, to be able to link food-derived strains to more easily obtained isolates from infected people. When no food isolate can be obtained, the source of the outbreak cannot be unambiguously determined. Shotgun metagenomics approaches applied to the food samples could circumvent this need for isolation from the suspected source, but require downstream strain-level data analysis to be able to accurately link to the human isolate. Until now, this approach has not yet been applied outside research settings to analyse real food-borne outbreak samples. In September 2019, a Salmonella outbreak occurred in a hotel school in Bruges, Belgium, affecting over 200 students and teachers. Following standard procedures, the Belgian National Reference Center for human salmonellosis and the National Reference Laboratory for Salmonella in food and feed used conventional analysis based on isolation, serotyping and MLVA (multilocus variable number tandem repeat analysis) comparison, followed by whole-genome sequencing, to confirm the source of the contamination over 2 weeks after receipt of the sample, which was freshly prepared tartar sauce in a meal cooked at the school. Our team used this outbreak as a case study to deliver a proof of concept for a short-read strain-level shotgun metagenomics approach for source tracking. We received two suspect food samples: the full meal and some freshly made tartar sauce served with this meal, requiring the use of raw eggs. After analysis, we could prove, without isolation, that Salmonella was present in both samples, and we obtained an inferred genome of a Salmonella enterica subsp. enterica serovar Enteritidis that could be linked back to the human isolates of the outbreak in a phylogenetic tree. These metagenomics-derived outbreak strains were separated from sporadic cases as well as from another outbreak circulating in Europe at the same time period. This is, to our knowledge, the first Salmonella food-borne outbreak investigation uniquely linking the food source using a metagenomics approach and this in a fast time frame.

scholarly journals Metagenomic Sequencing of Microbial Communities from Brackish Water of Pangong Lake of the Northwest Indian Himalayas

2017 ◽  
Vol 5 (40) ◽  
Author(s):  
Rashmi Rathour ◽  
Juhi Gupta ◽  
Madan Kumar ◽  
Moonmoon Hiloidhari ◽  
Anil Kumar Mehrotra ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Community Structure ◽  
Data Analysis ◽  
Brackish Water ◽  
Metagenomic Data ◽  
Metagenomic Sequencing ◽  
Water Lake ◽  
Brackish Water Lake ◽  
Metagenomic Approach ◽  
Indian Himalayas

ABSTRACT Pangong is a brackish water lake having environmental conditions that are hostile to supporting life. This is the first report unveiling the microbial diversity of sediment from Pangong Lake, Ladakh, India, using a high-throughput metagenomic approach. Metagenomic data analysis revealed a community structure of microbes in which functional genetic diversity facilitates their survival.

IN VITRO/IN SILICO CHARACTERIZATION OF ACTIVE AND PASSIVE STRESSES IN CARDIAC MUSCLE

2012 ◽  
Vol 10 (2) ◽  
pp. 171-188 ◽  
Author(s):  
Markus Boel ◽  
Oscar J. Abilez ◽  
Ahmed N Assar ◽  
Christopher K. Zarins ◽  
Ellen Kuhl
Keyword(s):  
Cardiac Muscle ◽  
In Silico ◽  
In Silico Characterization

Role of 4-O Galloylchlorogenic Acid in Lung Cancer- An Insilico Approach

2017 ◽  
Vol 9 (5) ◽  
Author(s):  
Jaynthy C. ◽  
N. Premjanu ◽  
Abhinav Srivastava
Keyword(s):  
Lung Cancer ◽  
Cell Proliferation ◽  
In Silico ◽  
Computational Study ◽  
Regulation Mechanism ◽  
Down Regulation ◽  
Fruit Extract ◽  
In Vitro Techniques ◽  
Discovery Studio

Cancer is a major disease with millions of patients diagnosed each year with high mortality around the world. Various studies are still going on to study the further mechanisms and pathways of the cancer cell proliferation. Fucosylation is one of the most important oligosaccharide modifications involved in cancer and inflammation. In cancer development increased core fucosylation by FUT8 play an important role in cell proliferation. Down regulation of FUT8 expression may help cure lung cancer. Therefore the computational study based on the down regulation mechanism of FUT8 was mechanised. Sapota fruit extract, containing 4-Ogalloylchlorogenic acid was used as the inhibitor against FUT-8 as target and docking was performed using in-silico tool, Accelrys Discovery Studio. There were several conformations of the docked result, and conformation 1 showed 80% dock score between the ligand and the target. Further the amino acids of the inhibitor involved in docking were studied using another tool, Ligplot. Thus, in-silico analysis based on drug designing parameters shows that the fruit extract can be studied further using in-vitro techniques to know its pharmacokinetics.

Discovery of New AKT1 Inhibitors by Combination of In silico Structure Based Virtual Screening Approaches and Biological Evaluations

2019 ◽  
Author(s):  
Filip Fratev ◽  
Denisse A. Gutierrez ◽  
Renato J. Aguilera ◽  
suman sirimulla
Keyword(s):  
Virtual Screening ◽  
Success Rate ◽  
Protein Interactions ◽  
In Silico ◽  
Biological Data ◽  
In Vitro Binding ◽  
Vitro Binding ◽  
Screening Protocol ◽  
Screening Approaches

AKT1 is emerging as a useful target for treating cancer. Herein, we discovered a new set of ligands that inhibit the AKT1, as shown by in vitro binding and cell line studies, using a newly designed virtual screening protocol that combines structure-based pharmacophore and docking screens. Taking together with the biological data, the combination of structure based pharamcophore and docking methods demonstrated reasonable success rate in identifying new inhibitors (60-70%) proving the success of aforementioned approach. A detail analysis of the ligand-protein interactions was performed explaining observed activities.<br>

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