"Next Generation Sequencing for Identification and Subtyping of Foodborne Pathogens" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by National Institute for Standards and Technology October 2014 by Rebecca Lindsey, PhD from Enteric Diseases Laboratory Branch of the CDC.
Presentation from the ECDC expert consultation on Whole Genome Sequencing organised by the European Centre of Disease Prevention and Control - Stockholm, 19 November 2015
Next Generation Sequencing for Identification and Subtyping of Foodborne Pat...Nathan Olson
"Next Generation Sequencing for Identification and Subtyping of Foodborne Pathogens" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by the National Institute for Standards and Technology October 2014 by Rebecca Lindsey, PhD from Enteric Diseases Laboratory Branch of the CDC.
Course: Bioinformatics for Biomedical Research (2014).
Session: 2.1.3- Next Generation Sequencing. Technologies and Applications. Part III: NGS Applications II.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
Presentation from the ECDC expert consultation on Whole Genome Sequencing organised by the European Centre of Disease Prevention and Control - Stockholm, 19 November 2015
Next Generation Sequencing for Identification and Subtyping of Foodborne Pat...Nathan Olson
"Next Generation Sequencing for Identification and Subtyping of Foodborne Pathogens" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by the National Institute for Standards and Technology October 2014 by Rebecca Lindsey, PhD from Enteric Diseases Laboratory Branch of the CDC.
Course: Bioinformatics for Biomedical Research (2014).
Session: 2.1.3- Next Generation Sequencing. Technologies and Applications. Part III: NGS Applications II.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
Building bioinformatics resources for the global communityExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Building bioinformatics resources for the global community. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management and GMI-9, 23-25 May 2016, Rome, Italy.
Presentation from the ECDC expert consultation on Whole Genome Sequencing organised by the European Centre of Disease Prevention and Control - Stockholm, 19 November 2015
Application of Whole Genome Sequencing in the infectious disease’ in vitro di...ExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Applications of WGS in industry. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
Metagenomics is the study of metagenomes, genetic material recovered directly from environmental samples. The broad field was referred to as environmental genomics, ecogenomics or community genomics. Recent studies use "shotgun" Sanger sequencing or next generation sequencing (NGS) to get largely unbiased samples of all genes from all the members of the sampled communities.
Dr. Douglas Marthaler - Use of Next Generation Sequencing for Whole Genome An...John Blue
Use of Next Generation Sequencing for Whole Genome Analysis of Pathogens - Dr. Douglas Marthaler, Veterinary Diagnostic Laboratory, College of Veterinary Medicine, University of Minnesota, from the 2016 Allen D. Leman Swine Conference, September 17-20, 2016, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2016-leman-swine-conference-material
Viral Metagenomics (CABBIO 20150629 Buenos Aires)bedutilh
This is a one-hour lecture about metagenomics, focusing on discovery of viruses and unknown sequence elements. It is part of a one-day workshop about metagenome assembly of crAssphage, a bacteriophage virus found in human gut. The hands-on workflow can be found at http://tbb.bio.uu.nl/dutilh/CABBIO/ and should be doable in one afternoon with supervision. There is also an iPython notebook about this here: https://github.com/linsalrob/CrAPy
Errors and Limitaions of Next Generation SequencingNixon Mendez
High throughput sequencing technologies has made whole genome sequencing and resequencing available to many more researchers and projects.
Cost and time have been greatly reduced.
The error profiles and limitations of the new platforms differ significantly from those of previous sequencing technologies.
The selection of an appropriate sequencing platform for particular types of experiments is an important consideration.
NGS sequencing errors focuses mainly on the following points:
1.Low quality bases
2.PCR errors
3.High Error rate
NGS has inherent limitations they are as follows :
1.Sequence properties and algorithmic challenges
2.Contamination or new insertions
3.Repeat content
4.Segmental duplications
5.Missing and fragmented genes
6.Reference index
This presents a number of case studies on the application on high-throughput sequencing (HTS), next generation sequencing (NGS), to biological problems ranging from human genome sequencing, identification of disease mutations, metagenomics, virus discovery, epidemic, transmission chains and viral populations. Presented at the University of Glasgow on Friday 26th June 2015.
Microbial Metagenomics Drives a New CyberinfrastructureLarry Smarr
06.03.03
Invited Talk
School of Biological Sciences
University of California, Irvine
Title: Microbial Metagenomics Drives a New Cyberinfrastructure
Irvine, CA
"Bacterial Pathogen Genomics at NCBI" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by National Institute for Standards and Technology October 2014 by Dr. Bill Klimke.
Presentation from the ECDC expert consultation on Whole Genome Sequencing organised by the European Centre of Disease Prevention and Control - Stockholm, 19 November 2015
WGS in public health microbiology - MDU/VIDRL Seminar - wed 17 jun 2015Torsten Seemann
How genomics is changing the practice of public health microbiology. The role of whole genome sequencing as the "one true assay". Another powerful tool for the epidemiologist.
"Microbial Genomics @NIST" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by the National Institute for Standards and Technology October 2014 by Nathan Olson from NIST.
Metagenomics research is a vast field which studies about the genetic system of the
environmental samples. Binning is a bioinformatics tool. Binning tool helps to analyses the
genomic analysis of the environmental samples.The
Building bioinformatics resources for the global communityExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Building bioinformatics resources for the global community. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management and GMI-9, 23-25 May 2016, Rome, Italy.
Presentation from the ECDC expert consultation on Whole Genome Sequencing organised by the European Centre of Disease Prevention and Control - Stockholm, 19 November 2015
Application of Whole Genome Sequencing in the infectious disease’ in vitro di...ExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Applications of WGS in industry. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
Metagenomics is the study of metagenomes, genetic material recovered directly from environmental samples. The broad field was referred to as environmental genomics, ecogenomics or community genomics. Recent studies use "shotgun" Sanger sequencing or next generation sequencing (NGS) to get largely unbiased samples of all genes from all the members of the sampled communities.
Dr. Douglas Marthaler - Use of Next Generation Sequencing for Whole Genome An...John Blue
Use of Next Generation Sequencing for Whole Genome Analysis of Pathogens - Dr. Douglas Marthaler, Veterinary Diagnostic Laboratory, College of Veterinary Medicine, University of Minnesota, from the 2016 Allen D. Leman Swine Conference, September 17-20, 2016, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2016-leman-swine-conference-material
Viral Metagenomics (CABBIO 20150629 Buenos Aires)bedutilh
This is a one-hour lecture about metagenomics, focusing on discovery of viruses and unknown sequence elements. It is part of a one-day workshop about metagenome assembly of crAssphage, a bacteriophage virus found in human gut. The hands-on workflow can be found at http://tbb.bio.uu.nl/dutilh/CABBIO/ and should be doable in one afternoon with supervision. There is also an iPython notebook about this here: https://github.com/linsalrob/CrAPy
Errors and Limitaions of Next Generation SequencingNixon Mendez
High throughput sequencing technologies has made whole genome sequencing and resequencing available to many more researchers and projects.
Cost and time have been greatly reduced.
The error profiles and limitations of the new platforms differ significantly from those of previous sequencing technologies.
The selection of an appropriate sequencing platform for particular types of experiments is an important consideration.
NGS sequencing errors focuses mainly on the following points:
1.Low quality bases
2.PCR errors
3.High Error rate
NGS has inherent limitations they are as follows :
1.Sequence properties and algorithmic challenges
2.Contamination or new insertions
3.Repeat content
4.Segmental duplications
5.Missing and fragmented genes
6.Reference index
This presents a number of case studies on the application on high-throughput sequencing (HTS), next generation sequencing (NGS), to biological problems ranging from human genome sequencing, identification of disease mutations, metagenomics, virus discovery, epidemic, transmission chains and viral populations. Presented at the University of Glasgow on Friday 26th June 2015.
Microbial Metagenomics Drives a New CyberinfrastructureLarry Smarr
06.03.03
Invited Talk
School of Biological Sciences
University of California, Irvine
Title: Microbial Metagenomics Drives a New Cyberinfrastructure
Irvine, CA
"Bacterial Pathogen Genomics at NCBI" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by National Institute for Standards and Technology October 2014 by Dr. Bill Klimke.
Presentation from the ECDC expert consultation on Whole Genome Sequencing organised by the European Centre of Disease Prevention and Control - Stockholm, 19 November 2015
WGS in public health microbiology - MDU/VIDRL Seminar - wed 17 jun 2015Torsten Seemann
How genomics is changing the practice of public health microbiology. The role of whole genome sequencing as the "one true assay". Another powerful tool for the epidemiologist.
"Microbial Genomics @NIST" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by the National Institute for Standards and Technology October 2014 by Nathan Olson from NIST.
Metagenomics research is a vast field which studies about the genetic system of the
environmental samples. Binning is a bioinformatics tool. Binning tool helps to analyses the
genomic analysis of the environmental samples.The
Course: Bioinformatics for Biomedical Research (2014).
Session: 2.1.2- Next Generation Sequencing. Technologies and Applications. Part II: NGS Applications I.
Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
Speeding up sequencing: Sequencing in an hour enables sample to answer in a w...Thermo Fisher Scientific
At this time next generation sequencing (NGS) is hindered by slow and often manual workflow procedures. Decreasing overall workflow times is critical for the widespread adoption of targeted and whole genome sequencing (WGS) for many time-sensitive applications, in particular for infectious disease analysis. To this end, we describe improvements to the four main steps of the NGS workflow: i) library preparation; ii) template preparation, iii) sequencing; iv) and data analysis. Together, these advances dramatically decrease the overall turnaround times.
Ion Torrent semiconductor-based sequencing instruments utilities flow sequencing with speed largely dependent on and the number of nucleotide flows (one flow produces ~0.5 base) and the speed of the flows (Figure 2).
QIAseq Technologies for Metagenomics and Microbiome NGS Library PrepQIAGEN
In this slide deck, learn about the innovative technologies that form the basis of QIAGEN’s portfolio of QIAseq library prep solutions for metagenomics and microbiome sequencing. Whether your research starts from single microbial cells, 16s rRNA PCR amplicons, or gDNA for whole genome analysis, QIAseq technologies offer tips and tricks for capturing the genomic diversity of your samples in the most unbiased, streamlined way possible.
The field of next-generation sequencing (NGS) has been experiencing explosive growth over the past several years and shows little sign of slowing down. The increasing capabilities and dramatically lowered costs have expanded NGS's reach beyond that of the human genome into nearly every corner of biological research. An overview of the platforms on the market today, including an assessment of their relative strengths and weaknesses, will be presented. The presentation will conclude with a peek into where the technology is going and what will be available in the future.
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
Presented at Cornell Symbiosis symposium. Workflow for processing amplicon based 16S/ITS sequences as well as whole genome shotgun sequences are described. Slides include short description and links for each tool.
DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
Exploring Spark for Scalable Metagenomics Analysis: Spark Summit East talk by...Spark Summit
Whole genome based metagenomics analyses hold the key to discover novel species from microbial communities, reveal their full metabolic potentials, and understand their interactions with each other. Metagenomics projects based on next generation sequencing typically produce 100GB to 1000GB unstructured data. Unlike many other big data problems, analysis of metagenomics data often generates temporary files with 100 to 1000 times of the original size, posing a significant challenge in both hardware infrastructure and software algorithms. Here we report our experience with evaluating Apache Spark in metagenomics data analysis for its speed, scalability, robustness, and most importantly, ease of programming. We developed a Spark-based scalable metagenomics application to deconvolute individual genomes from a complex microbial community with thousands of species. We then systematically tested its performance on synthetic and real world datasets using the Elastic MapReduce framework provided by Amazon Web Services. Our preliminary results suggest Spark provides a cost-effective solution with rapid development/deployment cycles for metagenomics data analysis. These experience likely extends to other big genomics data analyses, in both research and production settings.
The Global Micorbial Identifier (GMI) initiative - and its working groupsExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
The GMI initiative - and its working groups. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
Golden Helix’s SNP & Variation Suite (SVS) has been used by researchers around the world to do trait analysis and association testing on large cohorts of samples in both humans and other species. As Next-Generation Sequencing of whole genomes becomes more affordable, large cohorts of Whole Genome Sequencing (WGS) samples are available to search for additional trait association signals that were not found in array-based testing. In fact, recent papers have shown that WGS analysis using advanced GREML (Genomic Relatedness Restricted Maximum Likelihood) techniques is able to outperform micro-array based GWAS methods in the analysis of complex traits and proportion of the trait heritability explained.
Our latest update release of SVS has expanded the exiting maximum likelihood and GRM methods to support these new techniques. We have also enhanced various other association testing and prediction methodologies. This webcast showcases:
- Newly supported analysis workflow for whole genome variants using LD binning and enhanced GBLUP analysis
- Enhanced gender correction using REML
- Additional capabilities for genomic prediction and phenotype prediction
We are continually improving our products based on our customer’s feedback. We hope you enjoy this recording highlighting the exciting new features and select enhancements we have made.
Presentation by Justin Zook at GRC/GIAB ASHG 2017 workshop "Getting the most from the reference assembly and reference materials" on benchmarks for indels and structural variants.
We recently developed MVRSION for the purpose of using 16S to define microbiome bacterial populations from human, animal, or environmental sources. It is is a methodology that statistically leverages 8, rather than one, 16S hyper-variable regions.
GenomeTrakr: Whole-Genome Sequencing for Food Safety and A New Way Forward in...ExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
GenomeTrakr: Whole-Genome Sequencing for Food Safety and A New Way Forward in the Microbiological Testing & Traceability for Foodborne Pathogens. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
VarSeq 2.4.0: VSClinical ACMG Workflow from the User PerspectiveGolden Helix
Earlier this year, we released VarSeq 2.3.0 which brought massive updates to our VSClinical AMP interface, such as enhanced capabilities for automation and analysis of structural variants in the cancer context. Naturally, we wanted to follow that up shortly with similar advancements to our VSClinical ACMG interface, and also make our customers doing germline variant analysis happy.
Our latest software release, VarSeq 2.4.0, was therefore focused on the advancements in VSClinical ACMG, namely support for importing and clinically evaluating structural variants, long read sequencing, advanced automation with evaluation scripts in VSClinical ACMG and end-to-end automation of ACMG workflows with VSPipeline. These new and improved features were discussed in a great webcast by our VP of Product and Engineering, Gabe Rudy, last month.
This upcoming webcast by our FAS team will be a user’s perspective on the new features in VarSeq 2.4.0 and VSClinical ACMG and how our tools can precisely and efficiently enable the full spectrum NGS analysis for Mendelian disorders.
VarSeq 2.4.0: VSClinical ACMG Workflow from the User PerspectiveGolden Helix
Earlier this year, we released VarSeq 2.3.0 which brought massive updates to our VSClinical AMP interface, such as enhanced capabilities for automation and analysis of structural variants in the cancer context. Naturally, we wanted to follow that up shortly with similar advancements to our VSClinical ACMG interface, and also make our customers doing germline variant analysis happy.
Our latest software release, VarSeq 2.4.0, was therefore focused on the advancements in VSClinical ACMG, namely support for importing and clinically evaluating structural variants, long read sequencing, advanced automation with evaluation scripts in VSClinical ACMG and end-to-end automation of ACMG workflows with VSPipeline. These new and improved features were discussed in a great webcast by our VP of Product and Engineering, Gabe Rudy, last month.
This upcoming webcast by our FAS team will be a user’s perspective on the new features in VarSeq 2.4.0 and VSClinical ACMG and how our tools can precisely and efficiently enable the full spectrum NGS analysis for Mendelian disorders.
Advances and Applications Enabled by Single Cell TechnologyQIAGEN
Over the past 5 years, single-cell genomics have become a powerful technology for studying small samples and rare cells, and for dissecting complex populations such as heterogeneous tumors. Single-cell technology is enabling many new insights into diverse research areas from oncology, immunology and microbiology to neuroscience, stem cell and developmental biology. This webinar introduces single-cell technology and summarizes the newest scientific applications in various research areas, all in the context of current literature.
LIMS in Modern Molecular Pathology by Dr. Perry MaxwellCirdan
This presentation was delivered by Dr Perry Maxwell, Queen's University Belfast at Pathology Horizons 2017 in Cairns, Australia.
Pathology Horizons is an annual CPD conference organised by Cirdan on the future of pathology. You can access more information on the event at www.pathologyhorizons.com
Functional Predictions and Conservation Scores in VSClinicalGolden Helix
Computational evidence plays a vital role in the interpretation of variants using the ACMG guidelines. This includes functional prediction scores like SIFT and PolyPhen2, as well as conservation metrics such as GERP++ and PhyloP. In this webcast, we review the conservation scores and functional prediction algorithms available in VSClinical. This includes a discussion of our own implementation of these algorithms, along with a comparison to more recent variant prediction methods.
Integrating Custom Gene Panels for Variant InnovationsGolden Helix
The ability to use predefined sets of genes to isolate clinically relevant variants is an important aspect of clinical variant analysis. Golden Helix’s VarSeq product houses the tools, namely our Gene Panel Manager and Match Genes set of algorithms, that enable users to create and manage reusable gene lists within projects, incorporate the ACMG Secondary Findings v3.0 gene list for the reporting of incidental findings, make use of well validated publicly available gene panels with published evidence of disease associations and create gene panels based on specific disorders or phenotypes of interest. These capabilities were covered in a webcast “Creating and Managing Reusable Gene Lists with VSClinical” by Dr. Nathan Fortier our Director of Research. In the upcoming webcast, we will dive deeper into these capabilities, implementing our gene panel tools from the user’s perspective by focusing on two clinical use cases where custom virtual gene panels are particularly useful.
For the standard use case, users typically incorporate targeted gene panel-based data to hone in on any number of variants that fall within the scope of their targeted genes list. More recently, we have observed from the field application perspective, a trend among Golden Helix customers towards importing WES and WGS data followed by creating unique per sample gene panels. Therefore, the purpose of this webcast will be to showcase how simple it can be to construct and manage both styles of virtual gene panels within VarSeq in ways that will best suit the specific needs of your lab. We will share with you several clever shortcuts for users to implement filters on gene panels, to design and manage gene panels and calculate the coverage over these regions. We will also delve into the details of incorporating gene panel data into variant evaluation in VSClinical and bringing the relevant information into a final clinical report. Viewers tuning in to this webcast will be exposed to all the tools available in VarSeq for creating and managing their potential gene panel workflows.
2015 TriCon - Clinical Grade Annotations - Public Data Resources for Interpre...Gabe Rudy
The availability and details of using public genomic annotation sources to do clinical grade genomic diagnosis, using the exomes of myself, wife and son as the case study.
From Genomics to Medicine: Advancing Healthcare at ScaleDatabricks
With the exponential growth of genomic data sets, healthcare practitioners now have the opportunity to improve human outcomes at an unprecedented pace. These outcomes are difficult to realize in the existing ecosystem of genomic tools, where biostatisticians regularly chain together command-line interfaces based on a single-node setup on premise. The Databricks Unified Analytics Platform for Genomics empowers users to perform end-to-end analysis on our massively scalable platform in the cloud: in only minutes, a data scientist can visualize an individual’s disease risk based on their raw genomic data. Built on Apache Spark, we provide click-button implementations of accepted best practice workflows, as well as low-level Spark SQL optimizations for common genomics operations.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Next Generation Sequencing for Identification and Subtyping of Foodborne Pathogens
1. Next Generation Sequencing for
Identification and Subtyping
of Foodborne Pathogens
National Center for Emerging and Zoonotic Infectious Diseases
Division of Foodborne, Waterborne, and Environmental Diseases
Rebecca Lindsey, PhD
Enteric Diseases Laboratory Branch
NIST Workshop October 20, 2014
2. Advanced Molecular Detection (AMD) Initiative
http://www.cdc.gov/amd/
• Projects to transform Networks, programs and
systems – 8 CDC projects
• EDLB- Transforming public health microbiology with whole genome
sequencing for foodborne diseases (Salmonella, Shiga toxin-
producing Escherichia coli (STEC), and Campylobacter)
• Projects Using AMD for Specific Pathogens – 15
CDC projects
• EDLB- Maximizing the potential of real-time whole genome sequence-
based Listeria surveillance to solve outbreaks and improve food safety
No CDC consensus on how to use
WGS for identification
3.
4. Collaborating Partners
• Collaboration among the public health departments
in the states, FDA, USDA, and NCBI
• International component: Developing and refining
bioinformatics ‘pipelines’ with partners
in Belgium, Canada, Denmark, England, and France
Public Health Agency of Canada
5. Vision
for the use of WGS in the surveillance of foodborne illness
WGS is used to characterize foodborne pathogens in
public health laboratories, replacing multiple
workflows with one single efficient workflow
TAT: (2-) 3- 4 days
6. Current Methods of Characterizing Foodborne
Pathogens in a Public Health Laboratory
• Growth characteristics
• Phenotypic panels
• Agglutination reactions
• Enzyme immuno assays (EIAs)
• PCR
• DNA arrays (hybridization)
• Sanger sequencing
• DNA restriction
• Electrophoresis (PFGE, capillary)
• Each pathogen is characterized by methods that are specific to
that pathogen in multiple workflows
- Separate workflows for each pathogen
- TAT: 5 min – weeks (months)
7. Why Move Public Health
Microbiology to WGS?
Besides consolidation of workflows in the labs:
• More efficient outbreak detection, investigation & control
• Precise and flexible case definition
– More outbreaks will be detected and solved when they are
small
– Scarce epi-resources may be focused
• More efficient surveillance of sporadic infections
• Source attribution analysis of sporadic disease
• Focus on pathogens of particular public health
importance:
– Virulence – Resistance - Emerging pathogens - Rapidly
spreading clones/ traits- Vaccine preventable diseases
8. WGS in Public Health:
The tools must be
• Simple
• Public health microbiologists are NOT
bioinformaticians
• Standard desktop software
• Comprehensive
• All characterization in one workflow
• Work in a network of laboratories
• Free sharing and comparison of data between labs
• Central and local databases
9. To SNP or Not to SNP?
in public health
• Single Nucleotide Polymorphism (SNP) approaches
• Default for phylogenetic analyses of sequence data
• Comparative subtyping by nature
• Results difficult to communicate
• Computationally intensive = SLOW
• Gene- gene approach (wgMLST)
• Definitive subtyping
• Leads to naming, tracking over time, easy communication
• Computationally more simple = FAST but…
• Sufficiently discrimination?
• YES!
11. Standardization of
Methods
• Standard Operating Procedures- CLIA
certification- in EDLB
• Recommended protocols in state labs
• Sequencing quality metrics
– Qvalues – vary by machine
– Coverage – for upload to NCBI
• 20X Listeria, Campylobacter
• 30X Salmonella
• 40X STEC/Shigella
Salmonella www.cdc.gov/amd
12. NGS Standards in Progress for Clinical Labs
• The College of American Pathologists (CAP) –NGS
molecular pathology
- includes 18 laboratory accreditation checklist requirements for
the analytic “wet bench” process and “dry lab” bioinformatics
analysis processes (Aziz et al 2014).
• National Next-generation Sequencing Standardization
of Clinical Testing (Nex-StoCT) workgroup.
- developed guidelines to ensure that results from tests based
on NGS are reliable and useful for clinical decision making
(Gargis et al 2013).
• All labs submitting NGS to CLIA labs will have to
follow CLIA protocols
14. BioNumerics
• A powerful combined database and analytical
software package
– A ‘one tool fits all’ application for public health
• Highly customizable
• Used by PulseNet, CaliciNet and CryptoNet
– The public health labs are familiar with it
15. Gene – Gene Approach
• Fixed set of genes (‘loci’) leading to typing schemes
on different levels
• Concept of allelic variation, not only point mutations
• Evolutionary distance for events such as recombination
and simultaneous close-range mutations are counted as
one event
• Definitive subtyping
• Leads to nomenclature
• Requires curation
eMLST cMLST wgMLST
MLST
Genus/Species
Serotype
AR
16. Genes That May Be Targeted In a
Gene-Gene Analytical Approach
Core (c) genes (‘present
in all strains in a species’)
Housekeeping genes for MLST & eMLST
Serotyping genes
Genes for genus/species/subspecies
identification
Virulence genes
Antimicrobial resistance
genes
Pan- genome (wg) (‘all
genes in the whole
population of a species’)
17. Public Health WGS Workflow
Nomenclature server
Calculation engine
Trimming, mapping, de novo
assembly, SNP detection, allele
detection
SQL databases
End users at
CDC and in
the States
Allele databases
External storage
NCBI, ENA, BaseSpace
Sequencer
Genus/species
Serotype
Pathotype
Virulence profile
AST
Lineage
Clone
Sequence type
Allele
Raw sequences
LIMS
18. Public Health WGS Workflow
Nomenclature server
Calculation engine
Trimming, mapping, de novo
assembly, SNP detection, allele
detection
SQL databases
End users at
CDC and in
the States
Allele databases
External storage
NCBI, ENA, BaseSpace
Sequencer
Genus/species
Serotype
Pathotype
Virulence profile
AST
Lineage
Clone
Sequence type
Allele
Raw sequences
LIMS
19. The Nomenclatural Server in
the WGS Workflow
• A database with all genes and gene variants (‘alleles’)
• Function of most genes not known
but
• Genes used for reference characterization are also included
• E.g., genus/species identification, serotyping, pathotyping, virulence
characterization, antimicrobial resistance, MLST
• Alleles detected by the calculation engine are identified and NAMED
• New alleles are added to the database automatically
• Ambiguous alleles are forwarded to database managers and organism
specific SME’s for curation/confirmation before being added
Building the nomenclatural
database is an international
collaborative effort
Should ultimately be placed in
public domain
20. Building species specific allele
data bases - wgMLST
• Listeria
- 200 annotated reference genomes
- 5800 unique loci
• Campylobacteraceae
– 100 annotated reference genomes
– current BIGSdb
• Shiga toxin-producing E. coli
- 60 annotated reference genomes
- E. coli databases
21. - ResFinder
-VirulenceFinder
-SerotypeFinder
O target = wzy,
wzx, wzm and wzt
H target = flic, flka,
flla, flma and flna
Zankari E, et al., J Antimicrob
Chemother. 2012. 67(11):2640-4.
Joensen KG, et al.J. Clin.
Micobiol. 2014. 52(5): 1501-1510.
23. Public Health WGS Workflow
Nomenclature server
Calculation engine
Trimming, mapping, de novo
assembly, SNP detection, allele
detection
SQL databases
End users at
CDC and in
the States
Allele databases
External storage
NCBI, ENA, BaseSpace
Sequencer
Genus/species
Serotype
Pathotype
Virulence profile
AST
Lineage
Clone
Sequence type
Allele
Raw sequences
LIMS
24. The Calculation Engine in the
WGS Workflow
• Current: Closed - OID
Bioinformatics Core
• Potential: Public - In ‘the
cloud’ for the global public
health community
• Computationally intensive
sequence trimming,
mapping, de novo assembly,
SNP detection, allele
detection
• Slow - but a ‘one-time’
process
Calculation engine
28. Gene – Gene Approach for Naming
Subtyping in Keep with Phylogeny
(concept to be developed)
eMLST cMLST wgMLST7 gene MLST
Isolate A ST24 - e12 - c48 - w214
Isolate B ST24 - e12 - c48 - w352
Isolate C ST24 - e12 - c45 - w132
Isolate D ST31 - e15 - c60 - w582
Isolate A and B closely related
Isolate C related to A and B but not as closely as A is to B
Isolate D unrelated to all the other isolates
Providing phylogenetic information in the name is important because isolates from the
same source are more likely to be related than isolates from different sources
29. PATHOTYPE: Shiga toxin producing and Enteroaggregative E. coli (STEC & EaggEC)
VIRULENCE PROFILE: stx2a, aagR, aagA, sigA, sepA, pic, aatA, aaiC, aap
SEQUENCE TYPE: ST34
ANTIMICROBIAL RESISTANCE GENES: blaTEM-1 , blaCTX-M-15
The strain contains Shiga toxin subtype 2a typically associated with virulent STEC
It does not contain adherence and virulence factors (eae, ehxA) typically associated with virulent STEC
It contains adherence and virulence factors typically associated with virulent EaggEc (aagR, aagA, sigA, sepA,
pic, aatA, aaiC, aap)
This genotype is associated with extremely high (>10%) rates of hemolytic uremic syndrome (HUS)
All characteristics have been determined by whole genome sequencing (WGS)
GENUS/SPECIES:
30. Conclusion: Standardization of WGS
Public Health Microbiology
• No CDC consensus among the many
different organisms
• Standardization of NGS following
CAP/CLIA guidelines.
• Standardization among collaborators
-- Methods
-- Analysis
-- Nomenclature
31. Acknowledgements
National Center for Emerging and Zoonotic Infectious Diseases
Division of Foodborne, Waterborne, and Environmental Diseases
Disclaimers:
“The findings and conclusions in this presentation are those of the author and do not necessarily
represent the official position of the Centers for Disease Control and Prevention”
“Use of trade names is for identification only and does not imply endorsement by the Centers for
Disease Control and Prevention or by the U.S. Department of Health and Human Services.”
Public Health Agency of Canada
CDC: Heather Carleton, Eija Trees, Peter Gerner-Smidt, Collette Leaumont, Efrain
Ribot, Lee Katz, Nancy Strockbine
32. Questions?
For more information please contact Centers for Disease Control and Prevention
Enteric Diseases Laboratory Branch
1600 Clifton Road NE, Atlanta, GA 30333
The findings and conclusions in this report are those of the authors and do not necessarily represent the
official position of the Centers for Disease Control and Prevention.
Editor's Notes
There is no consensus at CDC for any of the above.
All labs submitting to the reference labs will have to be CLIA certified. IN the past state labs could have Molecular Pulsenet and Reference labs, now all will have to be CLIA certified so if they are all conducting NGS and they are all CLIA, they may streamline the labs into one lab. Working on EDLB and PulseNet standardized protocols which are recommended to states. Working towards CLIA certification of all steps in the process.
Need Sequencing quality metrics – Qvalues vary MiSeq vs. NextSeq vs. Pgem. For PulseNet and EDLB reference labs we have coverage recommendations.
W
High quality standard reference genomes that have been annotated would be helpful for hqSNP as well as building databases for wgMLST. Working for CLIA certification of all steps in the process.
well characterized annotated reference genomes
Pac-bio sequencing still working on the STEC database
More high quality genomes would be useful
There is no consensus at CDC for any of the above.
Want to be able to automatically name a pattern
There is no consensus at CDC for any of the above.