Toxicological Screening and Quantitation Using Liquid Chromatography/Time-of-...Annex Publishers
In recent years, an increasing number of new designer-drugs have increased the demands for general toxicological screening [1]. Limited screening based on immunoassays is commonly used in clinical toxicology, whereas more comprehensive approaches are common in forensic toxicology such as screening based on Gas or Liquid Chromatography (GC or LC) approaches [2]. The classic approach has been gas chromatography-Mass Spectrometry (GC-MS) combined with LC-diode-array detection (DAD) for systematic toxicological analysis. This setup has the advantage of covering a very broad spectrum of drugs and illicit substances when combined with library search facilities. However, the analytical sensitivity and specificity of LC-DAD may not be optimal. Thus, more sensitive and specific screening techniques based exclusively on LC combined with mass spectrometry have gained popularity. Multi-target screening and quantitation methods based on LC-tandem mass spectrometry (MS/MS) may provide detection of hundred or more compounds [3]. Using ion-trap MSn detection, several hundred compounds can be detected [4]. A more extended screening is possible using time-of-flight (TOF) mass spectrometry, which is a high-resolution mass spectrometry technique that detects drugs on the basis of their exact mass. Using this technique, scanning is performed over all masses for low molecular drugs, and detected signals can be related to a library of exact drug masses. Retention time and fragmentation pattern contribute to the identification. In principle, it is possible to screen for thousands of compounds, although issues related to software capabilities may limit the number of compounds to several hundred in daily practice [5-7].
Toxicological Screening and Quantitation Using Liquid Chromatography/Time-of-...Annex Publishers
In recent years, an increasing number of new designer-drugs have increased the demands for general toxicological screening [1]. Limited screening based on immunoassays is commonly used in clinical toxicology, whereas more comprehensive approaches are common in forensic toxicology such as screening based on Gas or Liquid Chromatography (GC or LC) approaches [2]. The classic approach has been gas chromatography-Mass Spectrometry (GC-MS) combined with LC-diode-array detection (DAD) for systematic toxicological analysis. This setup has the advantage of covering a very broad spectrum of drugs and illicit substances when combined with library search facilities. However, the analytical sensitivity and specificity of LC-DAD may not be optimal. Thus, more sensitive and specific screening techniques based exclusively on LC combined with mass spectrometry have gained popularity. Multi-target screening and quantitation methods based on LC-tandem mass spectrometry (MS/MS) may provide detection of hundred or more compounds [3]. Using ion-trap MSn detection, several hundred compounds can be detected [4]. A more extended screening is possible using time-of-flight (TOF) mass spectrometry, which is a high-resolution mass spectrometry technique that detects drugs on the basis of their exact mass. Using this technique, scanning is performed over all masses for low molecular drugs, and detected signals can be related to a library of exact drug masses. Retention time and fragmentation pattern contribute to the identification. In principle, it is possible to screen for thousands of compounds, although issues related to software capabilities may limit the number of compounds to several hundred in daily practice [5-7].
Proteomics is the study of the proteome, the full protein complement of organisms e.g. plasma, cells and tissue.
Understanding the proteome allows for:
Characterisation of proteins
Understanding protein interactions
Identification of disease biomarkers
Proteomics and its applications in phytopathologyAbhijeet Kashyap
Dear friends, I Abhijeet kashyap presenting the basics of proteomics to you all . Proteomics is the large-scale study of proteins, particularly their structures and functions.Proteomics helps in understanding the structure and function of different proteins as well as protein-protein interactions of an organism.
Proteomics is the study of the proteome, the full protein complement of organisms e.g. plasma, cells and tissue.
Understanding the proteome allows for:
Characterisation of proteins
Understanding protein interactions
Identification of disease biomarkers
Proteomics and its applications in phytopathologyAbhijeet Kashyap
Dear friends, I Abhijeet kashyap presenting the basics of proteomics to you all . Proteomics is the large-scale study of proteins, particularly their structures and functions.Proteomics helps in understanding the structure and function of different proteins as well as protein-protein interactions of an organism.
Quantitative Analysis of 30 Drugs in Whole Blood by SPE and UHPLC-TOF-MSAnnex Publishers
Abstract
An Ultra-High Pressure Liquid Chromatography Time-of-Flight Mass Spectrometry (UHPLC-TOF-MS) method for quantitative analysis of 30 drugs in whole blood was developed and validated. The method was used for screening and quantification of common drugs and drugs of abuse in whole blood received from autopsy cases and living persons. The compounds included: alprazolam, amphetamine, benzoylecgonine, bromazepam, cathine, cathinone, chlordiazepoxide, cocaine, codeine, clonazepam, 7-aminoclonazepam, diazepam, nordiazepam, flunitrazepam, 7-aminoflunitrazepam, ketamine, ketobemidone, 3,4-Methylenedioxyamphetamine (MDA), 3,4-methylenedioxymethamphetamine (MDMA), methamphetamine, methadone, morphine, 6-monoacetylmorphine, nitrazepam, 7-aminonitrazepam, oxazepam, temazepam, tramadol, O-desmethyltramadol, and zolpidem. Blood samples (200 μL) were subjected to Solid Phase Extraction (SPE). Target drugs were quantified using a Waters ACQUITY UPLC system coupled to a Waters SYNAPT G2 TOF-MS apparatus. Extraction recoveries ranged from 41% (7-aminoclonazepam) to 111% (ketamine) and matrix effects ranged from -13% (temazepam) to 50% (7-aminonitrazepam). For all compounds, a quadratic polynomial was applied for fitting the calibration curves. Lower Limits of Quantification (LOQ) ranged from 0.005 to 0.05 mg/kg. Satisfactory precisions below 15% and accuracies within 85-115% were obtained for all compounds at concentrations exceeding the LOQ. In conclusion, we present a validated UHPLC-TOF-MS method for simultaneous quantification of 30 drugs in whole blood with a run time of 15 min using 200 μL of whole blood.
Keywords: Drugs of abuse, UHPLC-TOF-MS, Whole blood, SPE, Quantification
BITS - Introduction to Mass Spec data generationBITS
This is the first presentation of the BITS training on 'Mass spec data processing'.
It reviews the basic concepts of mass spectrometry data generation.
Thanks to the Compomics Lab of the VIB for contribution.
This ppt explains the basics of mass spectrometry and in application in pharmacognosy. Hope this helps you guys. Like, comment and save. If you hav problem downloading, send your email address; i'll post it for you by mail :)
Enjoy the presentation.
(MS) is an analytical technique that produces spectra (singular spectrum) of the masses of the atoms or molecules comprising a sample of material. The spectra are used to determine the elemental or isotopic signature of a sample, the masses of particles and of molecules, and to elucidate the chemical structures of molecules, such as peptides and other chemical compounds,so it is considered one f the very important diagnostic analytical techniques .
Protein qualitative analysis based on mass spectrometry explores protein expression within organisms. Mass spectrometry offers highly efficient, robust, and accurate results and is one of the core technologies for proteomic research. Protein identification is a common topic for biochemistry research, and mass spectrometry is considered one of the most useful techniques that solve this issue. Two major strategies that are widely used for protein identification by mass spectrometry are MALDI-TOF-based protein fingerprinting and LC-MS/MS-based peptide sequencing. Meanwhile, LC-MS/MS reserved higher sensitivity and ability than MALDl-TOF and can accurately identify multiple protein components from a single sample. https://www.creative-proteomics.com/services/protein-identification.htm
Гостевая лекция Института биоинформатики. Подробнее: http://bioinformaticsinstitute.ru/lectures/1218
Несмотря на несерьезное название, на лекции разговор пойдет о важной проблеме в работе биоинформатика, почти любая реальная задача которого связана с обработкой и анализом больших данных. И решить задачу нужно не только правильно, но и эффективно. Процесс решения можно условно разделить на две части: «придумать», как решать, и «обучить» этому компьютер. И на лекции речь пойдет именно об эффективном «обучении».
Наивно реализованные алгоритмы работают неприемлемо долго, когда дело доходит до гигабайтов реальных данных. От биоинформатика уже требуются не просто базовые навыки программирования, но и знание технических нюансов. И даже у профессионального программиста уйдет немало времени, например, чтобы выгодно использовать возможности Hadoop при работе с Big Data. Так можно ли современному ученому обойтись без тщательного изучения кучи языков, библиотек и фреймворков и сосредоточиться именно на решении?
Ядерный век прошел, и становится все понятнее, что в фокусе науки 21-го века будут живые системы, медицина, и человек во всех его проявлениях. Здесь осуществляются самые масштабные финансовые вливания, и на эту отрасль человечество возлагает самые большие надежды. Все чаще слышатся предметные обсуждения тем, казавшихся еще недавно научной фантастикой: сможет ли человечество победить старение, рак, и другие смертельные заболевания? Сможет ли менять свой геном по собственному желанию? Будем ли мы хозяевами своим телам в той же мере, как мы хозяйничаем на Земле?
Многие десятилетия биология и медицина развивались как описательные науки. Однако по мере созревания и накопления информации, любая наука рано или поздно переходит на более точный язык - язык математики. Проект "Геном человека" обеспечил технологический прорыв, который будет питать науку о живом еще много лет - но который также поставил много новых глобальных вопросов перед современными учеными.
http://bioinformaticsinstitute.ru/guests
В пятницу 10 октября в 19.00 Мария Шутова (ИоГЕН РАН) выступала в Институте биоинформатики с открытой лекцией, посвященной изучению рака.
Рак -- одна из наиболее распространенных причин смерти по всему миру. В лекции рассматривается, как знания об эволюции, работе генома, репрограммировании, а также использование биоинформатических методов помогли лучше понять, как развивается раковая опухоль и предложить новые методы лечения разнообразных типов рака. Рассмотрены мышиные модели развития рака и интересные результаты, которые были получены с их помощью.
http://bioinformaticsinstitute.ru/lectures
Гостевая лекция Института биоинформатики, 9 октября 2014. Лектор -- Мария Шутова (ИоГЕН РАН).
За последние десять лет плюрипонтентные клетки стали героями двух Нобелевских премий и многих тысяч научных и научно-популярных статей. Их уникальная возможность превращаться в любую клетку взрослого организма до сих пор дает пищу для ума как биологам развития, так и ученым, ищущим способы лечения генетических заболеваний. В лекции будет рассказано о двух типах плюрипотентных клеток: "естественных" (эмбриональные стволовые клетки) и "искусственных" (индуцированные плюрипотентные стволовые клетки). Отдельно мы остановимся на том, как знания о работе транскрипционных факторов помогли репрограммировать клетки, и как эти "искусственные" плюрипотентные клетки можно использовать в медицине.
В своей лекции Андрей Афанасьев рассказал о стартапах в биотехе и биоинформатике и своем биоинформатическом проекте iBinom, разобрал несколько биотехнологических проектов глазами инноваторов и инвесторов, а также коснулся вопроса поиска инвестиций и поделился личным опытом взаимодействия с венчурными фондами и институтами развития.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
6. Proteomics
An organism’s proteome:
a catalog of all proteins
expressed throughout life
expressed under all conditions
The goals of proteomics:
to catalog all proteins
to understand their functions
to understand how they interact with
each other
7. Gel electrophoresis, northern/western
blot (fluorescence/radio active label)
X-ray crystallography
2D - mass spectrometry
Protein microarrays
Antibody Array for Protein ExpressionAntibody Array for Protein Expression
ProfilingProfiling
Methods for Protein AnalysisMethods for Protein Analysis
8. 1. High throughput
analysis of hundreds of
thousands of proteins.
2. Proteins are
immobilized on glass
chip.
3. Various probes
(protein, lipids, DNA,
peptides, etc) are used.
Part1
Protein Microarray
9. Protein Array VS DNA Microarray
Target: Proteins DNA
(Big, 3D) (Small, 2D)
Binding: 3D affinity 2D seq
Stability: Low High
Surface: Glass Glass
Printing: Arrayer Arrayer
Amplification: Cloning PCR
10. Protein Array Fabrication
Protein substratesProtein substrates
Polyacrylamide orPolyacrylamide or
agarose gelsagarose gels
GlassGlass
NanowellsNanowells
Proteins depositedProteins deposited
on chip surface byon chip surface by
robotsrobots
Benfey & Protopapas, 2005
11. Protein Attachment
Benfey & Protopapas, 2005
Diffusion
Protein suspended in
random orientation, but
presumably active
Adsorption/Absorption
Some proteins inactive
Covalent attachment
Some proteins inactive
Affinity
Orientation of protein
precisely controlled
Diffusion
Adsorption/
Absorption
Covalent
Affinity
12. Protein Interactions
Benfey & Protopapas, 2005
Different capture molecules
must be used to study
different interactions
Examples
Antibodies (or antigens) for
detection
Proteins for protein-protein
interaction
Enzyme-substrate for
biochemical function
Receptor–
ligand
Antigen–
antibody
Protein–
protein
Aptamers
Enzyme–
substrate
13. Expression Array
Probes (antibody) on surface recognize
target proteins.
Identification of expressed proteins from
samples.
Typical quantification method for large # of
expressed proteins.
14. Interaction Array
Probes (proteins, peptides, lipids) on
surface interact with target proteins.
Identification of protein interactions.
High throughput discovery of interactions.
15. Functional Array
Probes (proteins) on surface react with
target molecules .
Reaction products are detected.
Main goal of proteomics.
16. DetectionDetection
The preferred method of detection currently isThe preferred method of detection currently is
fluorescencefluorescence detection. The fluorescentdetection. The fluorescent
detection method is compatible with standarddetection method is compatible with standard
microarray scanners, the spots on the resultingmicroarray scanners, the spots on the resulting
image can be quantified by commonly usedimage can be quantified by commonly used
microarray quantification software packages.microarray quantification software packages.
However, some minor alterations to the analysisHowever, some minor alterations to the analysis
software may be needed. Other commonsoftware may be needed. Other common
detection methods include colorimetricdetection methods include colorimetric
techniques based on silver-precipitation,techniques based on silver-precipitation,
chemiluminescent and label free Surfacechemiluminescent and label free Surface
Plasmon Resonance.Plasmon Resonance.
18. Technical Challenges in Protein Chips
1. Poor control of immobilized protein activity.
2. Low yield immobilization.
3. High non-specific adsorption.
4. Fast denaturation of Protein.
5. Limited number of labels – low mutiplexing
19. “Global Analysis of Protein
Activities Using Proteome Chips”
Snyder Lab, Yale University
2101-2105, Vol 293, Science, 2001
20. Objectives
1.Construct yeast proteome chip
containing 80% of yeast proteins in
high throughput manner.
2.Study protein interactions at cell
level using the proteome chip.
“Global Analysis of Protein Activities Using Proteome Chips”
Snyder Lab, Yale University, 2101-2105, Vol 293, Science, 2001
21. Protein Immobilization on Surface
1. Cloning of 5800 ORFs.
2. Production of fusion proteins
(GST- HisX6).
3. Printing on glass chip.
4. Verification by anti-GST.
“Global Analysis of Protein Activities Using Proteome Chips”
Snyder Lab, Yale University, 2101-2105, Vol 293, Science, 2001
22. Protein-Protein Interactions
1. Calmodulin-Biotin with Ca++
.
2. Interaction checked with Cy-3-
streptavidin
3. Six calmodulin targets newly found.
4. Another six known targets could
not be detected.
“Global Analysis of Protein Activities Using Proteome Chips”
Snyder Lab, Yale University, 2101-2105, Vol 293, Science, 2001
23. Protein-Lipid Interactions
1. Phospholipids-Biotin.
2. About 150 proteins interacted with
phospholipid probes.
3. Several of them were un-known,
and some related to glucose
metabolism.
“Global Analysis of Protein Activities Using Proteome Chips”
Snyder Lab, Yale University, 2101-2105, Vol 293, Science, 2001
24. Conclusions
1. Novel tool for protein interaction
studies.
2. Concerns : * indirect interaction?
* missing proteins?
* surface chemistry?
“Global Analysis of Protein Activities Using Proteome Chips”
Snyder Lab, Yale University, 2101-2105, Vol 293, Science, 2001
25. Antibody Array for ProteinAntibody Array for Protein
Expression ProfilingExpression Profiling
http://www.youtube.com/watch?v=EeiN6bebCEwhttp://www.youtube.com/watch?v=EeiN6bebCEw
26. SELDI MS-based ProteinChip
Utilizes Surface Enhanced Laser
Desorption/Ionization Mass Spectrometry
(1993)
MALDI MS combined with
chromatography (Bioaffinity): surface-
MALDI
Part2
27. 3) Energy absorbing3) Energy absorbing
molecules are added tomolecules are added to
retained proteins.retained proteins.
Following laser desorptionFollowing laser desorption
and ionization of proteins,and ionization of proteins,
Time-of Flight (TOF) massTime-of Flight (TOF) mass
spectrometry accuratelyspectrometry accurately
determines their massesdetermines their masses
Protein Analysis by SELDI-MS
Source:http://dir.niehs.nih.gov/proteomics/emerg3.htm
1
2
3
1) Apply sample (serum,1) Apply sample (serum,
tissue extract, etc.) totissue extract, etc.) to
ProteinChip® array.ProteinChip® array.
2) Wash sample with increasing2) Wash sample with increasing
stringency to remove non-specificstringency to remove non-specific
proteins.proteins.
28. Advantages & Applications of SELDI MS
Extraction, fractionation, clean-up and amplification of
samples on surface
High throughput, high level multiplexing
Large scale/ Low sample volume
High sensitivity
Various molecules on surface to capture probes
Discover protein biomarkers
Purification of target proteins
Other fundamental proteomics research
30. Mass Spectrometry : Components
1. Ion source – sample molecules are ionized.
Chemical, Electrospray, Matrix-assisted laser
desorption ionization
2. Mass analyzer – ions are separated based on
their masses.
Time-of-flight, Quadruple, Ion trap
3. Mass detector
4. Data acquisition units
31. Ion Sources
Proteomics requires
specialized ion sources
Electrospray Ionization
(ESI)
With capillary
electrophoresis and liquid
chromatography
Matrix-assisted laser
desorption/ionization
(MALDI)
Extracts ions from sample
surface
ESI
MALDI
Benfey & Protopapas, 2005
32. Mass Analyzer
Benfey & Protopapas, 2005
Ion trap
Captures ions on the
basis of mass-to-charge
ratio
Often used with ESI
Time of flight (TOF)
Time for accelerated
ion to reach detector
indicates mass-to-
charge ratio
Frequently used with
MALDI
Also other possibilities
Ion Trap
Time of Flight
Detector
33. Mass Spectrometry for Proteins
1. ESI-Ion Trap
Sample in solution, lower mass limit.
2. MALDI-TOF
Solid state measurement, high mass
limit, most popular tool for protein
analysis.
34. Protein Identification by MS
Preparation of protein samplePreparation of protein sample
Extraction from a gelExtraction from a gel
Digestion by proteases — e.g., trypsinDigestion by proteases — e.g., trypsin
Mass spectrometer measures mass-charge ratio ofMass spectrometer measures mass-charge ratio of
peptide fragmentspeptide fragments
Identified peptides are compared with databaseIdentified peptides are compared with database
Software used to generate theoretical peptideSoftware used to generate theoretical peptide
mass fingerprint (PMF) for all proteins in databasemass fingerprint (PMF) for all proteins in database
Match of experimental readout to database PMFMatch of experimental readout to database PMF
allows researchers to identify the proteinallows researchers to identify the protein
40. “SELDIProteinChip Array Technology: Protein-Based Predictive Medicine and Drug
Discovery Applications”
Ciphergen Biosystems, Inc, 237-241, Vol 4, J. Biomed. & Biotechnol., 2003
Application 1:
Identification of HIV Replication Inhibitor
1. CAF (CD8+ antiviral factor) though to be related to AIDS
development
2. Determined the identity of CAF with SELDI techniques :
alpha-defensin -1, -2 and -3
3. Demonstrated de novo discovery of biomarker and
multimarker patterns, identification of drug candidates and
determination of protein functions
41. “SELDIProteinChip Array Technology: Protein-Based Predictive Medicine and Drug
Discovery Applications”
Ciphergen Biosystems, Inc, 237-241, Vol 4, J. Biomed. & Biotechnol., 2003
Application 2:
Multimarker Clinical Assays for Cancer
1. Early detection of cancer – critical in effective cancer
treatment
2. Cancer biomarker – massive protein expression
profiling
3. High throughput assay for multimarker provided by
SELDI array and multivariate software algorithms
produced high sensitivity and specificity.
42. “SELDIProteinChip Array Technology: Protein-Based Predictive Medicine and Drug
Discovery Applications”
Ciphergen Biosystems, Inc, 237-241, Vol 4, J. Biomed. & Biotechnol., 2003
1. SELDIProteinChip for Alzheimer’s Disease
2. Wide rage of samples
Small sample amount
3. SELDI using antibody protein array : Ab against N-
terminal sequence of target peptides (beta-amyloid)
4. Discovered candidate biomarkers, related inhibitors, &
their functions and peptide expression levels
Application 3:
Biomarker and Drug Discovery
Applications in Neurological Disorders