Live Session1: Integrating MultiomicsApproaches inProteomics Research&theChallenges of Data Analysis

01:04:00
https://www.youtube.com/watch?v=oYH2OSN7wSQ

Ringkasan

TLDRThe session was a comprehensive exploration of the integration of multiomics data—genomics, proteomics, and metabolomics—targeted at understanding complex biological questions. It focused on new technological advancements in these fields, particularly in single-cell analysis. Technologies like single-cell proteomics and genomics, proteogenomics, and metabolomics were discussed, providing insights into their applications in drug discovery and clinical research. The session demonstrated various instruments and workflows, emphasizing the progression from traditional proteomics to more advanced techniques such as single-cell proteomics and analysis of surface proteins which are crucial in drug targeting. Additionally, cutting-edge tools like mass spectrometers and data analysis software such as MS Fragger were showcased to underline the importance of accurate data interpretation in the burgeoning field of multiomics. Overall, this live session highlighted the critical role of integrating multiple omics layers to improve our understanding and treatment of diseases, offering budding scientists a glimpse into career opportunities within this rapidly advancing field.

Takeaways

  • 🔬 Single-cell proteomics is now feasible with advanced workflows.
  • 💡 Integrating multiomics data is vital for comprehensive biological insights.
  • 🧬 Genomics, proteomics, and metabolomics together offer a holistic view of biological systems.
  • 📊 Big data analytics is essential for handling and interpreting large multiomics datasets.
  • 🧪 Surface proteomics focuses on druggable cell surface proteins.
  • 🔗 Proteogenomics helps link genomic data with protein expression profiles.
  • 🚀 Emerging fields include single-cell analysis and post-translational modification studies.
  • 🔍 Data analysis tools like MS Fragger ease the handling of mass spectrometry data.
  • 💼 Growing career opportunities in multiomics fields, particularly in data analysis.
  • 📈 Advanced mass spectrometry techniques crucial for detailed proteomics analysis.

Garis waktu

  • 00:00:00 - 00:05:00

    The session starts with an introduction to the live demo, focusing on the integration of multi-omics data, specifically proteomics and genomics, to address biological questions. Single-cell proteomics is highlighted as an emerging field with advancements allowing a more comprehensive analysis at the single-cell level.

  • 00:05:00 - 00:10:00

    The speaker discusses cell surface proteomics and its significance for drug target discovery by focusing on cell surface proteins. This includes biological developments in understanding post-translational modifications like phosphorylation and glycosylation, emphasizing the importance of instruments like Orbitrap for high-resolution analysis.

  • 00:10:00 - 00:15:00

    A typical workflow for quantitative proteomics using biological samples is explained. The focus is on mass spectrometry for protein analysis, discussing sample preparation, ionization, and data acquisition. High-resolution mass spectrometry facilitates exploring proteomics in depth.

  • 00:15:00 - 00:20:00

    The session shifts to discussing Tandem Mass Tag (TMT) for proteomics, illustrating its use for sample multiplexing for quantitative analysis. This involves tagging peptides, running samples on mass spectrometry, and analyzing the data based on intensity for quantitative results.

  • 00:20:00 - 00:25:00

    The demonstration describes optimizing TMT methods to improve data accuracy. The process involves parameter settings in mass spectrometry to ensure reliable data acquisition and analysis, highlighting the importance of adequate experimental settings for effective proteomics.

  • 00:25:00 - 00:30:00

    MRM and PRM workflows for targeted proteomics are discussed, focusing on the validation of proteins using triple quadrupole instruments. These methods help confirm quantitative findings from earlier analyses, providing robust validation techniques.

  • 00:30:00 - 00:35:00

    Highlighting integration with metabolomics, the session discusses the analysis of metabolites using mass spectrometry, illustrating the potential of combining proteomic and metabolomic data from the same sample for a more comprehensive biological insight.

  • 00:35:00 - 00:40:00

    The use of next-generation sequencing in genomics is introduced for comprehensive genetic analysis using the Ion Torrent S5. The discussion includes steps for preparing libraries and amplification, enhancing genomic data integration with proteomic data for holistic insights.

  • 00:40:00 - 00:45:00

    A focus on various bioinformatics tools to analyze proteomics data is demonstrated, emphasizing the use of free and powerful tools like MS Fragger for analyzing complex mass spectrometry data efficiently, showcasing the analytical workflow from data acquisition to interpretation.

  • 00:45:00 - 00:50:00

    Discussing the integration of multiple data types (genomics, proteomics, and metabolomics), the speaker emphasizes the importance of multi-omics in understanding complex biological systems, with a drive towards precision medicine and system biology insights.

  • 00:50:00 - 00:55:00

    Demonstrations continue with insights into the statistical and computational challenges of handling large datasets in modern research environments, indicating cross-disciplinary efforts necessary for advancing biological research.

  • 00:55:00 - 01:04:00

    The session concludes by highlighting educational initiatives and career prospects in proteomics and multi-omics fields. The emphasis is on the growing demand for expertise in data analytics and the potential for integrating omics data to drive innovation and discovery in biomedicine.

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Peta Pikiran

Mind Map

Pertanyaan yang Sering Diajukan

  • What was the main theme of the live session?

    The main theme was integrating multiomics data, such as genomics, proteomics, and metabolomics, to answer biological questions.

  • What technologies are being advanced in the field of single-cell analysis?

    Single-cell genomics, mainly transcriptomics, is established. New proteomics workflows and sample preparation advancements now allow for single-cell proteome analysis.

  • What challenges exist in proteomics regarding low-abundance proteins?

    Challenges include high-abundance proteins overshadowing low-abundance ones, making sample preparation and fractionation crucial to enriching low-abundance proteins.

  • How is the field of proteomics shifting focus regarding drug target discovery?

    Proteomics is focusing more on cell surface proteins, which are potential drug targets, instead of global proteomes.

  • What tools were demonstrated in the session?

    Tools like mass spectrometers, software for mass spectrometry data analysis like MS Fragger, and NGS instruments were demonstrated.

  • What are some emerging fields within proteomics?

    Emerging fields include single-cell proteomics, surface proteomics, and analysis of post-translational modifications (PTMs) like phosphorylation and glycosylation.

  • Why is big data analysis important in the context of multiomics?

    Big data analysis is crucial for handling and integrating large datasets from genomics, proteomics, and metabolomics to build comprehensive models of biological systems.

  • What are the potential career opportunities in the field of multiomics?

    There are many opportunities, especially in data analysis, given the significance and complexity of handling multiomics datasets.

  • What were some of the technological highlights presented?

    Technologies such as high-resolution mass spectrometers, new workflows for protein and metabolite enrichment, and proteogenomics approaches were highlighted.

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Teks
en
Gulir Otomatis:
  • 00:00:15
    sir you're live now you can
  • 00:00:23
    start all right good morning everybody
  • 00:00:25
    uh welcome to today's live session uh
  • 00:00:30
    today we are going to plan to give you
  • 00:00:32
    some demonstrations from the lab uh
  • 00:00:35
    along with interacting with you life so
  • 00:00:38
    this could be your opportunity to talk
  • 00:00:39
    to us and ask questions but while you
  • 00:00:43
    are uh uh going to do that we are uh
  • 00:00:46
    going to show you some experiment in a
  • 00:00:48
    more thematic way uh today's theme is
  • 00:00:51
    going to be on integrating multix data
  • 00:00:54
    set to understand the uh different
  • 00:00:56
    biological questions and in this
  • 00:00:59
    particular session we are going to show
  • 00:01:00
    you some live experiments from different
  • 00:01:03
    type of proteomics and genomic
  • 00:01:05
    Technologies but then more Focus will be
  • 00:01:07
    how to do the data analysis and
  • 00:01:09
    integrate data from proteomics and
  • 00:01:12
    genomics so uh rather than making it
  • 00:01:15
    very theoretical uh I thought to keep it
  • 00:01:18
    very minimal in terms of talking to you
  • 00:01:19
    on the slides but we do more handson in
  • 00:01:22
    the lab uh but I'll give you very quick
  • 00:01:25
    flavor of you know where proix has
  • 00:01:27
    started making more impact understand
  • 00:01:31
    biology and addressing many clinical
  • 00:01:33
    questions right so something which is
  • 00:01:36
    coming up very new is about single cell
  • 00:01:38
    p and I thought to take this as the
  • 00:01:40
    first topic because one of the students
  • 00:01:42
    sh she asked a question about how the
  • 00:01:45
    field of single cell genomics and promic
  • 00:01:47
    is emerging are going to really make
  • 00:01:50
    impact so in this SL uh I'd like to say
  • 00:01:53
    that single cell uh genomics mainly
  • 00:01:55
    single cell transcriptomics is already
  • 00:01:58
    very established and successful approach
  • 00:02:01
    and people realize that you know they
  • 00:02:02
    can do sufficient RNA and do the transic
  • 00:02:05
    analysis with RNA seek but the challenge
  • 00:02:07
    was to look at from Singles at how to do
  • 00:02:10
    the entire proteum analysis but now with
  • 00:02:13
    the uh advancements of the new type of
  • 00:02:16
    mpic workflows and the new sample prep
  • 00:02:19
    it has really now started becoming a
  • 00:02:21
    reality that one could even look at the
  • 00:02:23
    proteum from single cell right so what I
  • 00:02:25
    showed you here on the slide think about
  • 00:02:27
    if we have to work on the cancer you
  • 00:02:30
    know to look for The Unique proteins
  • 00:02:33
    linked to given cancer uh what we do in
  • 00:02:36
    our own research which is a reality and
  • 00:02:38
    and others also do we take the tumor
  • 00:02:41
    tissue and that tumor tissue is a lump
  • 00:02:43
    of the mass of many type of cell right
  • 00:02:46
    we homogenize them Li them and in a in a
  • 00:02:49
    hope that we look at only cancer rated
  • 00:02:52
    protein but actually not no that's not
  • 00:02:54
    true because we are mixing a variety of
  • 00:02:57
    cell type in this example if you see
  • 00:02:59
    neutrophil macrofagos blood vessels t-
  • 00:03:02
    cell fibroblast all of them along with
  • 00:03:04
    the cancer cell now if you were to
  • 00:03:06
    disaggregate this tumor mass and look at
  • 00:03:09
    you know separate components of them
  • 00:03:12
    then only you know you can see you have
  • 00:03:14
    very few cancer cell but there are lot
  • 00:03:16
    of other type of abundant cells which
  • 00:03:18
    are present there so in which way we can
  • 00:03:21
    try to First Look at the cell sorting
  • 00:03:24
    and look at the Single Cell of our
  • 00:03:26
    interest which we are Keen to look at
  • 00:03:28
    the proteum or transcrip
  • 00:03:30
    to and based on that now can we do
  • 00:03:33
    sufficient ways of sample prep and
  • 00:03:36
    enrichment that we can get you know a
  • 00:03:38
    lot of peptides from that given cell and
  • 00:03:40
    one could run in the massp what you see
  • 00:03:42
    in the bottom panel to generate those
  • 00:03:44
    Mass Spectrum data and then look at the
  • 00:03:46
    data analysis and come up with lot of
  • 00:03:48
    you know different type of patterns so
  • 00:03:50
    this was definitely not possible a few
  • 00:03:52
    years back but now from last year and so
  • 00:03:55
    there's been a lot more progress being
  • 00:03:56
    made in this area that now we uh have
  • 00:03:59
    have good ability to look at the uh from
  • 00:04:02
    single cell even close to 5,000 proteins
  • 00:04:05
    3,500 to 5,000 protein is what people
  • 00:04:08
    are able to now achieve with the newer
  • 00:04:10
    uh advancements of the MPC like Tim sto
  • 00:04:13
    and estal orbit trap uh one could really
  • 00:04:16
    you know go to much deeper coverage with
  • 00:04:18
    the Single Cell as well but also like
  • 00:04:20
    sample becomes very crucial because you
  • 00:04:22
    need to make much more automated
  • 00:04:24
    processes so that you're you're not
  • 00:04:26
    losing the much peptide and also you are
  • 00:04:28
    looking at um how best to uh preserve
  • 00:04:32
    the peptides which you lost in the
  • 00:04:33
    multiple step so single po analysis
  • 00:04:36
    Scopes method there are many type of you
  • 00:04:37
    know new workflow which has emerged
  • 00:04:39
    which I'm not going to talk as a lecture
  • 00:04:41
    here but that just to give you flavor
  • 00:04:43
    that single cell genomics and proteomics
  • 00:04:46
    and soon single cell proteogenomics will
  • 00:04:48
    be a reality which is almost you know we
  • 00:04:50
    are making good advancement in this area
  • 00:04:52
    so now just another exciting thing is
  • 00:04:54
    happening in the proteum X right now to
  • 00:04:56
    look at the cell surface
  • 00:04:58
    proteum While most of the time we take
  • 00:05:00
    the again the the entire cell and try to
  • 00:05:02
    Li the cell and look at every protein
  • 00:05:04
    inside that which is the global proteum
  • 00:05:06
    but if you think about lot of drug
  • 00:05:08
    targets they work only on the surface
  • 00:05:10
    right so we should be focusing for the
  • 00:05:13
    drug Target Discovery more of the
  • 00:05:14
    membrane protein and the things are more
  • 00:05:16
    receptors and present outside the
  • 00:05:18
    membrane but when you combine everything
  • 00:05:20
    you are actually diluting with the
  • 00:05:22
    global abundant highly abundant protein
  • 00:05:24
    to these low abundant and more unique
  • 00:05:26
    targets so how to enrich only the
  • 00:05:29
    specific cell surface protein is another
  • 00:05:32
    emerging area in the proix which are
  • 00:05:35
    couple of you know good successful
  • 00:05:36
    examples shown here with also our
  • 00:05:38
    collaborator at UCSF who are developing
  • 00:05:41
    the new workflows to only enrich the
  • 00:05:42
    cell surface protein and again with the
  • 00:05:45
    these Advanced m is possible to
  • 00:05:47
    analyze thousands of protein from these
  • 00:05:50
    type of unique cell surface protein but
  • 00:05:52
    again biologically is are very important
  • 00:05:55
    development which are happening in the
  • 00:05:56
    field of proteomic right but if you
  • 00:05:59
    think about the understanding the
  • 00:06:01
    biology and looking at diseases It's
  • 00:06:03
    always important to look at the post
  • 00:06:05
    transation modification again it was
  • 00:06:07
    very difficult to look at various type
  • 00:06:09
    of PTM analysis because if you think
  • 00:06:12
    about the from the entire Global protein
  • 00:06:15
    what percentage gets phosphorated even
  • 00:06:17
    less than 1% so how to enrich those
  • 00:06:20
    phosphopeptide and then try to analyze
  • 00:06:23
    the proteum from that type of know less
  • 00:06:26
    abundant uh samples has been challenged
  • 00:06:29
    so example enrichment using different
  • 00:06:31
    type of iMac columns and different type
  • 00:06:33
    of tianium dioxide based Technologies to
  • 00:06:35
    enrich the phospho peptides followed by
  • 00:06:39
    running them in the mass spectometer
  • 00:06:40
    with very sensitive instruments and
  • 00:06:43
    acquiring all type of phosphor related
  • 00:06:45
    proteins or the phosphor map of the
  • 00:06:47
    proteum is another thing which is
  • 00:06:49
    emerging very heavily and not only like
  • 00:06:51
    you know phospho for that matter even
  • 00:06:53
    glyos are very important and very
  • 00:06:55
    complex and very
  • 00:06:56
    challenging and then think about biology
  • 00:06:58
    for UB and acation and variety of type
  • 00:07:02
    of degradation and many type of other
  • 00:07:04
    type of modifications are also equally
  • 00:07:06
    important to understand the biology and
  • 00:07:07
    disease so a lot of exciting things are
  • 00:07:10
    happening in this area of course in your
  • 00:07:12
    theoretical course of proteomics and
  • 00:07:14
    proteogenomics we did not have time to
  • 00:07:16
    touch upon all the latest advancements
  • 00:07:18
    but these are you know kind of some of
  • 00:07:20
    the quicker updates and again as I said
  • 00:07:22
    was not possible without the some of the
  • 00:07:24
    very latest high resolution mpect like
  • 00:07:27
    from the orbit trap Asal orbit trap
  • 00:07:29
    happen with the Tim stop mtic without
  • 00:07:31
    them it was not possible to go to that
  • 00:07:33
    level of depth of these very important
  • 00:07:36
    class of proteins of membrane proteins
  • 00:07:38
    and the ptms or looking at even the
  • 00:07:40
    Single Cell proteum but these are
  • 00:07:42
    started getting more and more reality
  • 00:07:43
    which actually adds lot of excitement
  • 00:07:45
    for all of you who are learning these
  • 00:07:47
    new areas and want to venture into this
  • 00:07:49
    new field by taking up the exciting
  • 00:07:51
    research problems in the future so uh
  • 00:07:55
    while this are some latest development
  • 00:07:57
    but what is the typical workflow of
  • 00:07:59
    doing protomet for all of these whatever
  • 00:08:01
    I spoke or in general if you want to do
  • 00:08:03
    qu quantity protomet a typical workflow
  • 00:08:05
    involves that you take some biological
  • 00:08:07
    sample it could be a cell line a
  • 00:08:10
    biological tissue sample or various type
  • 00:08:12
    of body fluid it could be saliva it
  • 00:08:14
    could be serum it could be C spinal
  • 00:08:15
    fluid many type of biological fluid
  • 00:08:17
    samples right all of them you stract the
  • 00:08:19
    protein you digest them with proteases
  • 00:08:23
    like a tripin choten ly make them
  • 00:08:26
    peptide form and then those peptides you
  • 00:08:28
    are ionizing them with the
  • 00:08:31
    electronization
  • 00:08:32
    ESI after ionization they are going to
  • 00:08:35
    go inside the mass spectrometer which
  • 00:08:37
    could be vary of MPS and then you are
  • 00:08:39
    acquiring their M byz and then you are
  • 00:08:42
    generating their MSS Spectra or msms
  • 00:08:44
    Spectra and going to analyze that data
  • 00:08:47
    typical pic workflow whatever type of
  • 00:08:49
    thing I'm talking they will fall in in
  • 00:08:52
    this kind of domain only thing which
  • 00:08:54
    becomes very critical is the sample
  • 00:08:55
    preparation part which we already spoke
  • 00:08:58
    in the last live session about different
  • 00:08:59
    type of sample prep how to make it more
  • 00:09:01
    unique and and and en that kind of
  • 00:09:03
    sample right but eventually as you go
  • 00:09:06
    along there are different type of
  • 00:09:07
    workflow being followed to look into the
  • 00:09:11
    quantitative type of workflows or
  • 00:09:12
    looking at a specific modification and
  • 00:09:14
    accordingly you to fine tune your
  • 00:09:16
    workflows for the data acquisition at
  • 00:09:18
    the mpect level and data analysis level
  • 00:09:21
    so uh we have this uh high resolution
  • 00:09:23
    Mass spectrometry facility at it Bombay
  • 00:09:26
    which we have established as additional
  • 00:09:27
    facility which is equipped with iy of
  • 00:09:30
    instruments uh and what we thought we
  • 00:09:32
    are going to show you some of these
  • 00:09:33
    instruments how they can be utilized for
  • 00:09:36
    different type of workflow so for
  • 00:09:37
    example here you
  • 00:09:38
    see orbit Fusion which is really
  • 00:09:41
    utilized for the D proteum type of
  • 00:09:43
    analysis or defo protom analysis utive
  • 00:09:47
    along with the HC configuration is
  • 00:09:50
    heavily utilized for metabolomics and
  • 00:09:52
    triple qurol instrument is used for the
  • 00:09:54
    targeted toomic or metabolomic based
  • 00:09:57
    analysis so we will you know take more
  • 00:10:00
    time in the lab and try to walk you
  • 00:10:01
    through with these type of workflows but
  • 00:10:04
    to begin with uh we will first talk to
  • 00:10:07
    you about one of the quantitive plumix
  • 00:10:09
    based approach which is still pretty
  • 00:10:11
    powerful which is known as the TMT or
  • 00:10:14
    tendem mass Char so idea is can you uh
  • 00:10:18
    you have three control sample and three
  • 00:10:20
    treatment samples you want to do
  • 00:10:22
    quantitative analysis quantity
  • 00:10:24
    proteom you digest the protein and after
  • 00:10:27
    that you are after digestion you have
  • 00:10:29
    these uh
  • 00:10:30
    peptides uh and those n terminal
  • 00:10:33
    peptides being labeled with these
  • 00:10:35
    isobaric tag which is having different
  • 00:10:38
    type of reporter ions for example tandom
  • 00:10:40
    Mass tag reporter 126 till TMT 131 these
  • 00:10:44
    are all reporter ions these are isobaric
  • 00:10:47
    although reporter are different but then
  • 00:10:48
    you add the carbonal group to make them
  • 00:10:50
    all same mass and then you are mixing
  • 00:10:52
    them with each of your six condition so
  • 00:10:55
    now every condition of three control and
  • 00:10:57
    three treatment they all got unique
  • 00:10:59
    barcoded right and now you can mix them
  • 00:11:02
    and after mixing them you run in the MPC
  • 00:11:05
    and then you can when you look at msms
  • 00:11:07
    level you can now segregate these
  • 00:11:09
    reporter I separately and use this
  • 00:11:11
    information of intensity to quantify the
  • 00:11:14
    signal this is one of the very powerful
  • 00:11:17
    way of doing the quantity protox other
  • 00:11:20
    way of doing quantity protx could be
  • 00:11:22
    label free quantification where every
  • 00:11:24
    sample you're not labeling but you are
  • 00:11:26
    going to run them individually in the MP
  • 00:11:29
    and then you are acquiring the data
  • 00:11:31
    which is more like you're building a
  • 00:11:32
    library of every patient is specific or
  • 00:11:34
    sample specific and then you are
  • 00:11:36
    counting the number of Spectra or the
  • 00:11:39
    relative intensity of all these abundant
  • 00:11:42
    peptide and trying to compare those
  • 00:11:43
    across your control and disease
  • 00:11:45
    condition to then come up with quantive
  • 00:11:47
    signal how much F change you can see
  • 00:11:49
    from control and treatment so two
  • 00:11:51
    different ways of doing analysis both of
  • 00:11:54
    these are coming as a part of data
  • 00:11:56
    dependent acquisition there's also new
  • 00:11:58
    emerging field known as Dia data
  • 00:12:00
    independent acquisition which I'm not
  • 00:12:01
    talking right now to keep it simple but
  • 00:12:04
    we will just you know walk you through
  • 00:12:05
    about TMT workflow and how to acquire
  • 00:12:08
    data uh in mpek uh in a live session
  • 00:12:11
    right now which will be done with uh Dr
  • 00:12:14
    ARA benergy he's going to show you the
  • 00:12:16
    workflow and talk to you about the data
  • 00:12:19
    how to acquire and analyze the data so
  • 00:12:20
    ARA please talk about TMT now so ad can
  • 00:12:24
    you help me to share the screen
  • 00:12:48
    okay so uh let me this okay so welcome
  • 00:12:52
    everyone uh welcome to the introduction
  • 00:12:55
    to the proteomic course and uh TMT based
  • 00:12:58
    proix so first of all like I will be
  • 00:13:00
    giving like what are the advantages of
  • 00:13:03
    sample multiplexing with the isic mass
  • 00:13:05
    tax though Professor has explained more
  • 00:13:08
    of it like how and where it is useful in
  • 00:13:12
    the F
  • 00:13:13
    of how and where it is useful in the
  • 00:13:15
    field of proteomics it will give you
  • 00:13:17
    increase through through uh when you are
  • 00:13:20
    using isobaric tags due to the reporters
  • 00:13:23
    and the I and
  • 00:13:28
    just yeah
  • 00:13:29
    uh when we are ISO using isobaric tax
  • 00:13:32
    where there is a very few chance like
  • 00:13:34
    the missing values will be very few as
  • 00:13:36
    compared to the level three
  • 00:13:38
    quantification we have a vast range of
  • 00:13:40
    sample flexibility whether it is from
  • 00:13:42
    human or bacteria or plant any species
  • 00:13:46
    of the samples can be originated and uh
  • 00:13:49
    like it can help us in multiplexing
  • 00:13:51
    means comparing more than two samples
  • 00:13:53
    means you can ideally now they have
  • 00:13:56
    taken out a range of 24 and 26 like one
  • 00:13:59
    go you can compare like more than two
  • 00:14:02
    samples at a time and multiple
  • 00:14:03
    comparison will help you to improve the
  • 00:14:05
    statistics now as the professor told
  • 00:14:08
    there is a mass reporter there is a mass
  • 00:14:10
    normalizer and there is a protein
  • 00:14:12
    reactive group your peptide will be your
  • 00:14:14
    peptide will be uh connected with the
  • 00:14:17
    balancer and balancer is connected with
  • 00:14:20
    the reporter this is the reporter what
  • 00:14:21
    you want to
  • 00:14:23
    see coming up to the workflow as you
  • 00:14:26
    have gone through our earlier session
  • 00:14:28
    where we we have shown you how to
  • 00:14:30
    prepare the samples we generally prepare
  • 00:14:32
    the samples we do a fraction we do a
  • 00:14:34
    labeling of the TMT TX after the
  • 00:14:37
    peptides have been uh generated and
  • 00:14:39
    followed by a cleanup followed by a
  • 00:14:41
    fractionation which can improve the
  • 00:14:43
    coverage followed by the concentration
  • 00:14:46
    data interpretation data analysis can be
  • 00:14:48
    done with the free software such as Max
  • 00:14:50
    and flf as also as the proteum discovery
  • 00:14:54
    which is one of the proprietary software
  • 00:14:56
    now when you are uh delet dealing with
  • 00:14:59
    the optimization of the TMT metods two
  • 00:15:02
    things you have to keep in mind if you
  • 00:15:04
    are using shorter gradients and shorter
  • 00:15:06
    columns that can increase a CO isolation
  • 00:15:09
    but uh if you are using 2 hours gradient
  • 00:15:12
    with a 50 cm column either you have to
  • 00:15:14
    increase the length of the column or the
  • 00:15:16
    length of the gradient a 15 cm column 1
  • 00:15:18
    hour to 1.5 hour of gradient is good
  • 00:15:21
    enough but if you are using 50 cm column
  • 00:15:24
    you can also load 500 nog to 1 microgram
  • 00:15:27
    of load which can be go to throughout
  • 00:15:29
    so this is how the gr establishment can
  • 00:15:31
    be done and as you know like this is a c
  • 00:15:35
    column so more of the hydrophobic
  • 00:15:36
    peptides will be there so this is the
  • 00:15:38
    interface how the method Edition is
  • 00:15:40
    being done so this is the method editor
  • 00:15:42
    which I am going to show you if the time
  • 00:15:45
    permits so here like in the peptide
  • 00:15:49
    quantification you can eily go to the
  • 00:15:51
    TMT ms3 and you can place it here you
  • 00:15:54
    can just drag this PMT and you can place
  • 00:15:56
    it here once that has been done you will
  • 00:15:59
    given an option like how you want to
  • 00:16:00
    analyze your ms1 data and MS2 data uh
  • 00:16:04
    the ms1 can be done in the OT mode and
  • 00:16:08
    because OT have a higher resolution and
  • 00:16:10
    MS2 mode as this orbitary Fusion what
  • 00:16:13
    Professor San showed in our facility is
  • 00:16:15
    of uh like trid Mass spectrometer is one
  • 00:16:19
    of the trid mass spectrometer it has
  • 00:16:21
    three kinds of mass analyzer qu IR graft
  • 00:16:24
    as well as the orbit the second mass
  • 00:16:26
    analyzis is a choice whether if you are
  • 00:16:28
    using a CD you can use OT mode like a
  • 00:16:30
    orbit mode and if you are using C
  • 00:16:33
    Collision induced dissociation you can
  • 00:16:35
    use the iron craft as the mass analyzer
  • 00:16:38
    and thirdly like in the DD MS2 like uh
  • 00:16:41
    which is the main for use for the
  • 00:16:42
    quantification you can use the OT so in
  • 00:16:46
    one like you can go to the 12 lakh
  • 00:16:48
    Delton like the 2 lakh Delton of the
  • 00:16:50
    Orit resolution but you can go in mass
  • 00:16:54
    in TMT Mass tax you can go to a range of
  • 00:16:56
    1 lakh 20,000
  • 00:16:59
    and severely like a multiple charge
  • 00:17:01
    State the charge State can be concluded
  • 00:17:03
    include from 2 to six because this is
  • 00:17:06
    one of the Rob which separate from the
  • 00:17:08
    mul because at a single go you can
  • 00:17:11
    monitor more than two chares monotropic
  • 00:17:15
    prepers keep it to simple pepti a full
  • 00:17:18
    msms resolution with Char Dynamic
  • 00:17:20
    exclusion and I res so these are the the
  • 00:17:23
    settings we are good to go and consider
  • 00:17:26
    selecting the most intense ion at a top
  • 00:17:29
    speed
  • 00:17:31
    mode so yeah so now this is done uh when
  • 00:17:35
    you come to the sensitivity and
  • 00:17:36
    specificity the isolation window is
  • 00:17:38
    generally from uh 7 to 2 m the choice
  • 00:17:42
    can be between 5 to 10 and for best
  • 00:17:45
    accuracy top 10 nches of the
  • 00:17:47
    prefractionated samples were taken so
  • 00:17:50
    this is how a ideal parameter or a
  • 00:17:54
    ideal Matrix of anmt workflow line so
  • 00:17:57
    this is a 2hour gradient
  • 00:17:59
    that is 120 Minutes you generally start
  • 00:18:01
    with less hydrophobic means more of the
  • 00:18:03
    Aquas to high hydrophobic which is an
  • 00:18:06
    organic solvent which is ACN and you can
  • 00:18:09
    easily obtain more than 2,000 proteins
  • 00:18:11
    in a single shot and 10,000 to 11,000
  • 00:18:15
    peptide zes in single and that can be
  • 00:18:18
    Quantified with the help of cium
  • 00:18:21
    discover okay so now let me uh let me
  • 00:18:24
    take you to the
  • 00:18:26
    original um mapping of the
  • 00:18:30
    instrument
  • 00:18:45
    just so this is the original interface
  • 00:18:48
    of the video so that 120 hour minutes
  • 00:18:50
    gradient you can see it here this is how
  • 00:18:53
    a chromatogram looks like and if I can
  • 00:18:56
    show you the total iron chromatogram
  • 00:18:59
    uh view iron map okay you can see the
  • 00:19:03
    Spectrum also this is how the Spectrum
  • 00:19:05
    looks like most of the illusion has
  • 00:19:07
    happened from 30 minutes to 110 minutes
  • 00:19:09
    so this is our gradient like the first
  • 00:19:11
    is the aqua space which I have shown you
  • 00:19:14
    5% of B then is the hydrophobic face and
  • 00:19:17
    after that again Aquas so if you zoom in
  • 00:19:20
    like
  • 00:19:26
    sorry okay this is hanging
  • 00:19:30
    is hanging a bit so if you zoom in each
  • 00:19:33
    paks represent so this is how the Crux
  • 00:19:35
    lights so you can see each Peak is a Ms
  • 00:19:38
    and the void between the two is the MS
  • 00:19:40
    Ms so this is how a peak is being seen
  • 00:19:43
    so if you click it here let this also be
  • 00:19:46
    there uh you say VI uh Spectrum okay
  • 00:19:52
    great so like you can see so this is the
  • 00:19:55
    MS so once you shift you can see if
  • 00:19:58
    between two Ms if between two Ms if the
  • 00:20:01
    fragmentation is of Ms Ms is more than
  • 00:20:04
    10 because we have selected top 10
  • 00:20:06
    abundant proteins if the transition is
  • 00:20:08
    coming more than 10 it is a very good
  • 00:20:10
    Spectrum at indeed it is a very good
  • 00:20:13
    Spectrum so this is how you can monitor
  • 00:20:16
    how the chromatogram looks
  • 00:20:18
    like once this is done you can see your
  • 00:20:22
    labeling efficiency uh TMT templex sence
  • 00:20:26
    can vary from 126 to uh 132 whatever the
  • 00:20:31
    maybe so you can simply go you can
  • 00:20:33
    simply go here you can uh go on the
  • 00:20:40
    ranges in the
  • 00:20:43
    ranges just a minute let it come in the
  • 00:20:46
    ranges you can select one more column
  • 00:20:49
    where you can select Ms sorry we have to
  • 00:20:52
    do it on the Spectrum so view
  • 00:20:55
    chromatogram once the chromatogram comes
  • 00:20:58
    you you can go on
  • 00:21:03
    the I have already done this
  • 00:21:07
    okay go to the
  • 00:21:10
    ranges once you go to the
  • 00:21:12
    ranges I will show you from
  • 00:21:16
    okay so so this is how it looks like so
  • 00:21:20
    this is a chromatogram view uh you go to
  • 00:21:24
    the ranges and suppose my labeling my
  • 00:21:28
    levels which are there are coming I will
  • 00:21:31
    click on submerge with another graph and
  • 00:21:34
    I will click on the mass range now it
  • 00:21:38
    will give you the mass of the MS
  • 00:21:40
    precursors which have been detected so
  • 00:21:43
    as we know our the labels which are
  • 00:21:47
    occurring in the uh DMT tags varies from
  • 00:21:50
    126 to 130 1 for four place or
  • 00:21:55
    132 whatever may be the ranges
  • 00:21:59
    we will just click on the same so this
  • 00:22:02
    is how you can take out the mass
  • 00:22:04
    range just click on okay it will take
  • 00:22:07
    some
  • 00:22:15
    time so it is going to tabulate and see
  • 00:22:19
    what all precursor which are present
  • 00:22:21
    here are labeled with that kind of
  • 00:22:25
    efficienc Tak a bit of time
  • 00:22:32
    by the time it comes like
  • 00:22:35
    uh uh we can show the
  • 00:22:39
    instrument comes we can show the
  • 00:22:45
    instrument all right so well these are
  • 00:22:48
    the live run which AR gu is about trying
  • 00:22:50
    to show you from
  • 00:22:52
    the uh orbit Fusion which we are
  • 00:22:54
    acquiring the data and again U to really
  • 00:22:58
    get you know proper fragmentation here
  • 00:23:00
    and looking at the uh reporter you need
  • 00:23:04
    to optimize the Collision energy and to
  • 00:23:06
    do lot optimization at the
  • 00:23:08
    chromatography level and msms
  • 00:23:10
    parameters um but eventually uh if your
  • 00:23:14
    labeling was highly efficient you have
  • 00:23:17
    done the proper labeling and if you are
  • 00:23:19
    able to now uh uh look at the data you
  • 00:23:23
    can acquire lot of good quantitative
  • 00:23:25
    accuracy uh what you see now also on the
  • 00:23:29
    um directly from the uh interface let's
  • 00:23:34
    um so AR if you can just unshare your
  • 00:23:36
    screen then we can have you on the full
  • 00:23:47
    screen see where the samples are
  • 00:23:50
    ined already loaded and it is running so
  • 00:23:53
    I cannot open the compartment box of the
  • 00:23:55
    uh Nano LC the sample is eled from here
  • 00:23:59
    and it comes to the or so this is the
  • 00:24:03
    main easy spray source of fusion and you
  • 00:24:06
    can see like this is the Trap column
  • 00:24:08
    what we are having two types of columns
  • 00:24:10
    are used before the sample is injected
  • 00:24:12
    into the instrument one is the tree
  • 00:24:14
    column or the Trap column if any debr
  • 00:24:17
    which is coming from the direct nanc it
  • 00:24:19
    will be trapped here and after that an
  • 00:24:21
    analytical column 15 cm analytical
  • 00:24:24
    column is used in which the samples is
  • 00:24:26
    in
  • 00:24:28
    sample injected so this is the ITC
  • 00:24:31
    isothermal calibration tube once the
  • 00:24:33
    sample goes inside it goes onto the uh
  • 00:24:36
    instrument and after that you can see
  • 00:24:38
    that kind of gradi so coming
  • 00:24:43
    on all right so thank you ARA this is
  • 00:24:47
    one of the workflow of doing the
  • 00:24:49
    quantitive protomet and once you have
  • 00:24:53
    identified let's say lot of protein
  • 00:24:55
    which shows you significant protein lead
  • 00:24:58
    uh which is a good hit for you so now
  • 00:25:00
    you need to validate them right
  • 00:25:02
    conventionally people used to validate
  • 00:25:04
    the targets using antibody based
  • 00:25:06
    approach like Eliza or Western broad but
  • 00:25:09
    for every protein uh we don't have uh so
  • 00:25:12
    nice antibodies available U for many it
  • 00:25:16
    is only polyon available so then how to
  • 00:25:19
    validate the target so since we are
  • 00:25:21
    acquiring data from masp which is more
  • 00:25:24
    about the peptide sequences and their
  • 00:25:26
    quantification idea came why not we only
  • 00:25:29
    validate the those peptides from
  • 00:25:31
    different type of mpect so we are let's
  • 00:25:33
    say discovering an orbit Fusion but can
  • 00:25:35
    we validate the targets of only specific
  • 00:25:38
    peptides of the proteins of Interest
  • 00:25:40
    using the triple quadrapole based
  • 00:25:42
    instrument or using another type of
  • 00:25:43
    orbit trap instrument so the two
  • 00:25:45
    different workflow which are currently
  • 00:25:46
    being heavily used one is multiple
  • 00:25:49
    reaction monitoring other is a par
  • 00:25:51
    reaction
  • 00:25:52
    monitoring multiple monitoring is one of
  • 00:25:55
    the uh triple Quadra pole based
  • 00:25:57
    configuration when you are having the
  • 00:26:00
    two set of quadr q1 and Q3 in between
  • 00:26:03
    you have Collision cell and you already
  • 00:26:05
    know that which of the specific protein
  • 00:26:08
    let's say five proteins of that 15
  • 00:26:10
    peptides of your interest you have told
  • 00:26:13
    the instrument with a hardware with a
  • 00:26:15
    spe specific software on the skyline
  • 00:26:17
    that you're only going to look at the
  • 00:26:18
    transitions of these 15 peptides and
  • 00:26:22
    only those the q1 is actually acquiring
  • 00:26:24
    data and doing fragmentation to generate
  • 00:26:26
    the relative iion uh spectrum of
  • 00:26:29
    PRM is much more powerful it can
  • 00:26:31
    actually look at all of
  • 00:26:32
    those precursors and fragment ties
  • 00:26:35
    simultaneously so then one could go much
  • 00:26:38
    higher number of transitions as compared
  • 00:26:39
    to the mrm based approach so in which
  • 00:26:43
    way these experiments can be done in the
  • 00:26:44
    lab let's have another live
  • 00:26:47
    demonstration from ainash who will walk
  • 00:26:49
    you through these workflows quickly
  • 00:26:51
    directly on the instrument so ainash
  • 00:26:54
    please show the mrm based workflow hello
  • 00:26:57
    Al so as you can see already discussed
  • 00:27:00
    about the targeted programing so this is
  • 00:27:01
    the T volage from the th scientific and
  • 00:27:05
    this has the basically the triple Quadra
  • 00:27:07
    so are the two marer and along with that
  • 00:27:10
    this is the L system connected so this
  • 00:27:12
    is the system and every LC system
  • 00:27:15
    basically multiple compartment this is
  • 00:27:18
    basically Auto sampler where we keep our
  • 00:27:20
    samples like this kind of files and so
  • 00:27:23
    these are the different kind of tray
  • 00:27:25
    where we keep our samples and from these
  • 00:27:27
    samples they go to the like like this is
  • 00:27:30
    basically the pump compartment and this
  • 00:27:32
    one is the and yeah so you can see these
  • 00:27:35
    are the pump compartment where all the
  • 00:27:37
    solvents like have been mixed and get
  • 00:27:40
    eluted during according to the our what
  • 00:27:43
    we said and this is the column
  • 00:27:46
    compartment where we keep our
  • 00:27:47
    compartment like keep our column and it
  • 00:27:50
    maintains some internal temperature for
  • 00:27:52
    the columns and these are the solventes
  • 00:27:55
    from this solvent the different gradient
  • 00:27:57
    has been prepared
  • 00:27:58
    so as you can see in the monitor so this
  • 00:28:00
    is
  • 00:28:01
    basically liquid system application so
  • 00:28:06
    this is the pump module where we can set
  • 00:28:08
    our gradient and this one is a sample
  • 00:28:10
    and we can set like set like where is
  • 00:28:13
    our sample is present and this is the
  • 00:28:14
    column compartment and we can set the
  • 00:28:16
    temperature and uh so all the method
  • 00:28:19
    file which has been used for the
  • 00:28:21
    targeted pics are set in the UN
  • 00:28:23
    application and uh and those method has
  • 00:28:26
    been like set in the X Co caliber so as
  • 00:28:27
    you can see this is a live run going on
  • 00:28:29
    so this are the chromatogram and
  • 00:28:31
    different kind of I and the
  • 00:28:34
    gradi here so as you can see like it
  • 00:28:38
    depend on the what chromat like what
  • 00:28:40
    gradiate we set according to that they
  • 00:28:41
    get uted and this kind of chatram come
  • 00:28:44
    so if I can also show so this is the one
  • 00:28:47
    of the sample R from the tumor sample so
  • 00:28:50
    this is not the Gan distribution as we
  • 00:28:52
    see the see in the global prot this is a
  • 00:28:54
    quite like like not that dense
  • 00:28:58
    because this is we are looking for the
  • 00:29:00
    only the targeted proteins and peptides
  • 00:29:03
    so that's why is not there so I can show
  • 00:29:05
    you some of the result from so after
  • 00:29:07
    that getting the raw files this kind of
  • 00:29:09
    raw file we can import those raw file in
  • 00:29:12
    the different another software which is
  • 00:29:14
    called as a Skyline and we can look for
  • 00:29:16
    the peak of the particular protein so
  • 00:29:18
    this is one of the study in the from the
  • 00:29:20
    co so as you can see so upper top top
  • 00:29:22
    panel is basically the co positive and
  • 00:29:25
    lower panel is basically the
  • 00:29:28
    so we have identified the multiple
  • 00:29:30
    protein which are basically shown the
  • 00:29:32
    differential regulation in the different
  • 00:29:34
    set of a group so as you can see the
  • 00:29:36
    also the intensity of in the like
  • 00:29:38
    negative sample and the positive sample
  • 00:29:40
    so basically this instrument has been
  • 00:29:43
    very good for the doing the targeted
  • 00:29:44
    proteomics and from the what after
  • 00:29:47
    analyzing theic global data set so yeah
  • 00:29:51
    over
  • 00:29:52
    to all right thank you Vash U so now
  • 00:29:57
    let's say say you already have looked at
  • 00:30:00
    you know your specific uh protein
  • 00:30:02
    targets and you are able to now
  • 00:30:04
    correlate that intensity what you have
  • 00:30:06
    observe the four changes they are same
  • 00:30:08
    whether you look for the discovery or
  • 00:30:10
    not in the validation stage additionally
  • 00:30:13
    from the since we're talking about mpek
  • 00:30:16
    mpek is also very powerful lcmsms
  • 00:30:18
    approach to look at the metabolites in a
  • 00:30:21
    field on as metabolomics right the way
  • 00:30:23
    we look at all the proteins and
  • 00:30:24
    proteomics likewise masp is very
  • 00:30:26
    powerful to look at all the metabolomics
  • 00:30:29
    for all the metabolites although there
  • 00:30:31
    other techniques as well like NMR can
  • 00:30:33
    also be used gcms can also be used they
  • 00:30:35
    give you very specialized proces of
  • 00:30:37
    metabolite but a global broad survey can
  • 00:30:40
    be done with the lcms based approach so
  • 00:30:43
    since let's say you think about you have
  • 00:30:45
    biological sample or tissue or cell
  • 00:30:46
    liate from which you want to do
  • 00:30:48
    proteomic you're going to extract the
  • 00:30:50
    protein out why not you know you also
  • 00:30:53
    extract the metabolite out on the same
  • 00:30:54
    sample for example you know if you're
  • 00:30:56
    doing methanol based PR reputation you
  • 00:30:59
    can even use the same sample for even
  • 00:31:00
    some part for the protein some part for
  • 00:31:02
    the metabolite analysis right how
  • 00:31:04
    powerful that could be if you are
  • 00:31:06
    integrating the data from the same
  • 00:31:07
    sample today's live session is also for
  • 00:31:10
    the broader audience talking about
  • 00:31:11
    proteogenomic and multiomic so now we
  • 00:31:14
    want to expand your view think about
  • 00:31:16
    from the same sample you are generating
  • 00:31:18
    next layer of information at the
  • 00:31:20
    metabolite level so metabolomics can be
  • 00:31:22
    done using various type of mass
  • 00:31:24
    spectometer one which we are going to
  • 00:31:26
    show you the another orbit trap Q
  • 00:31:28
    executive which is interfac with
  • 00:31:30
    uhplc and it is pretty straightforward
  • 00:31:33
    much simpler to do metabolomics as
  • 00:31:35
    compared to the proteomic of course you
  • 00:31:37
    need to optimize multiple parameter
  • 00:31:40
    which now an is going to quickly
  • 00:31:41
    demonstrate you metabolomics based
  • 00:31:44
    workflow directly from the
  • 00:31:49
    lab yeah hello everyone good morning so
  • 00:31:52
    now we will be sh you about the running
  • 00:31:55
    of the sample for the metabolite
  • 00:31:57
    identification
  • 00:31:58
    so as it was discussed that in the prot
  • 00:32:01
    there is the nanc or the Nan flow of
  • 00:32:03
    theow of the p and solution but here for
  • 00:32:07
    the metabolite what we generally use is
  • 00:32:09
    the HC here we uses the flate you can
  • 00:32:12
    see it is in the range of ml for ml per
  • 00:32:15
    minute so here is the same like in the
  • 00:32:18
    alage what a has showed there's the same
  • 00:32:20
    compartment of a and the column now
  • 00:32:23
    metabolize can be divided into three or
  • 00:32:27
    more classes on the basis of their
  • 00:32:28
    hydrophobicity so there can be
  • 00:32:30
    hydrophobic it can be in between
  • 00:32:33
    amphilic it can be hydrophilic so on
  • 00:32:34
    that basis of that the particular column
  • 00:32:37
    is used now if you are want to out only
  • 00:32:40
    the separate the identify hydrophobic so
  • 00:32:43
    then a C8 column as like it is being
  • 00:32:46
    used in the case of prot so then same
  • 00:32:49
    reverse B chromatography is being
  • 00:32:53
    principle is being followed where the in
  • 00:32:55
    the column compartment the column is
  • 00:32:57
    being added and in the solution you can
  • 00:33:00
    see that it is being made uh the
  • 00:33:03
    different layers different gradient of
  • 00:33:05
    hydrophobicity is being generated like
  • 00:33:07
    you can see here and on the basis of the
  • 00:33:11
    hydrophobicity compounds are eluted out
  • 00:33:13
    now after eluting out as it goes into
  • 00:33:17
    the mass spectrometer and this Mass
  • 00:33:19
    spectrometer is a high mass spectrometer
  • 00:33:22
    where it is consist of the quadruple and
  • 00:33:24
    the orbit trap so there in this two Mass
  • 00:33:26
    analyzers first
  • 00:33:28
    the precursor ion is getting selected at
  • 00:33:31
    ms1 level and then finally at the after
  • 00:33:34
    the fragmentation MS2 level is done so I
  • 00:33:36
    just quickly show you some runs that are
  • 00:33:40
    going on so you can see that these are
  • 00:33:42
    the Spectra at the msms level so the
  • 00:33:46
    metabolites now one thing that needs to
  • 00:33:48
    be understand that metabolites can be
  • 00:33:50
    identified at ms1 level with the
  • 00:33:53
    compound molecular weight but same
  • 00:33:54
    compound can have different molecular
  • 00:33:56
    weight so for this we need to check the
  • 00:34:00
    m to match with the known compound that
  • 00:34:03
    particular compound will have a unique
  • 00:34:05
    fragmentation picture so this is the Run
  • 00:34:07
    going on with the chromatogram on the
  • 00:34:09
    basis of the gradient the particular
  • 00:34:11
    compounds are getting analized and here
  • 00:34:14
    if you see the runs that has occurred so
  • 00:34:17
    here you can see this is the particular
  • 00:34:19
    compound that has eluted out now in the
  • 00:34:20
    case of metabolic we also need to add
  • 00:34:23
    some kind of internal standards and run
  • 00:34:26
    QC pools to check that our instrument is
  • 00:34:29
    not there's no technical variability in
  • 00:34:32
    between our run so for example this is
  • 00:34:33
    one of the standard which has the which
  • 00:34:36
    should be eluting out at any specific
  • 00:34:38
    time throughout your experiment with a
  • 00:34:41
    certain intensity and a good Pi so this
  • 00:34:44
    is in brief about the metabolomic
  • 00:34:47
    experiment Global met yeah thank
  • 00:34:52
    you all right thank you anit so again
  • 00:34:56
    some of these experiments what you see U
  • 00:34:59
    students who are live U it's not very
  • 00:35:02
    difficult to actually perform these
  • 00:35:04
    experiments right uh but what actually
  • 00:35:06
    becomes difficult to really analyze this
  • 00:35:08
    data because it takes a while to make
  • 00:35:10
    sense of these data while it actually is
  • 00:35:12
    very easy to generate these data but to
  • 00:35:15
    really get the maximum output from um
  • 00:35:19
    using these type of workflows of
  • 00:35:21
    metabolomic or proteomic you generate
  • 00:35:24
    huge amount of data and Analysis and
  • 00:35:26
    workflow that is is kind of very
  • 00:35:29
    challenging U I think know while we are
  • 00:35:33
    going to talk more about other
  • 00:35:34
    Technologies let me just take a question
  • 00:35:36
    from a student about
  • 00:35:38
    TMT uh how can we achieve High
  • 00:35:41
    sensitivity in detecting low abundance
  • 00:35:44
    protein using TMT based
  • 00:35:45
    proteomics so uh in prot is always a
  • 00:35:49
    challenge that you know
  • 00:35:51
    whatever entire complex protein we want
  • 00:35:53
    to analyze there are always some
  • 00:35:55
    abundant protein which will be having
  • 00:35:57
    more more peptides and they will always
  • 00:35:59
    mask our uh you know
  • 00:36:01
    maspic ionization followed by msms
  • 00:36:04
    analysis so you always see high abundant
  • 00:36:07
    protein much more as compared to low
  • 00:36:08
    abundant protein so it's actually you
  • 00:36:11
    know not the TMT or any quantitative
  • 00:36:14
    strategy which can enrich lot of low
  • 00:36:16
    burent protein but rather your sample
  • 00:36:18
    prep is the first place when you can
  • 00:36:20
    think about how to enrich your complex
  • 00:36:23
    proteum uh many samples like for example
  • 00:36:26
    you work on a plant sample it has the
  • 00:36:27
    plant leaf as Risco protein very
  • 00:36:29
    abundant protein you work on the saliva
  • 00:36:32
    protein you work on the plasma protein
  • 00:36:34
    all of the these samples like you know
  • 00:36:36
    amas or having the
  • 00:36:38
    Albin IGG all of these kind of abundant
  • 00:36:41
    proteins you need to remove them to then
  • 00:36:43
    try to enrich the getting the high
  • 00:36:45
    abundant protein and to be out and low
  • 00:36:48
    abundant to be seen in the m so sample
  • 00:36:50
    prep is the first step which can be
  • 00:36:52
    utilized then once you are let's say
  • 00:36:55
    done the extraction and done the uh your
  • 00:36:57
    proper ways of enrichment for lowan
  • 00:37:00
    protein then next thing is can you
  • 00:37:02
    fractionate those you know so that you
  • 00:37:04
    have from the one complex uh tube which
  • 00:37:07
    has all the 10,000 protein can you
  • 00:37:09
    separate in 10 tubes right and and with
  • 00:37:11
    different type of pH fraction other type
  • 00:37:14
    of chromatographic method or isric Point
  • 00:37:16
    method and fractionary do then each one
  • 00:37:18
    of those when you are going to run in
  • 00:37:20
    the MP you are going to see abundant
  • 00:37:22
    proteins which are low even abundant
  • 00:37:24
    will be enr now TMT will be D
  • 00:37:28
    very powerful because TMT is very
  • 00:37:30
    accurate for the quantification so if
  • 00:37:33
    you have done these kind of pre- sample
  • 00:37:35
    processing and the fractionation then
  • 00:37:37
    TMT based approaches will be able to in
  • 00:37:39
    like you know do more accurate
  • 00:37:41
    quantification of the low abundant
  • 00:37:43
    protein which you are not able to do
  • 00:37:45
    earlier but your sample preparation
  • 00:37:47
    strategy and fracturation strategy will
  • 00:37:49
    make a very important role for giving
  • 00:37:52
    you the broad
  • 00:37:53
    coverage so uh we'll be happy to take
  • 00:37:56
    more questions so please feel free to
  • 00:37:58
    ask uh on the Forum if you have more
  • 00:38:00
    query but let's just take you know kind
  • 00:38:03
    of to broaden the scope we talking about
  • 00:38:05
    multiomic I just talked about proteomic
  • 00:38:07
    and metabolomics think about genomics
  • 00:38:09
    why that is the most important like you
  • 00:38:11
    know the blueprint right so can we even
  • 00:38:13
    try to think about uh integrating the
  • 00:38:16
    data from genome and prum right and that
  • 00:38:18
    sometime especially for disease context
  • 00:38:21
    can be very important uh genomic is very
  • 00:38:23
    powerful for sure and very robust it can
  • 00:38:26
    you know very quickly with the Next
  • 00:38:27
    Generation sequencing can look at all
  • 00:38:30
    possible you know your Gene sequences
  • 00:38:32
    the various variant forms looking at
  • 00:38:34
    mutations all type of things and if you
  • 00:38:36
    were to look at from the same sample the
  • 00:38:39
    protein and the same sample the
  • 00:38:40
    metabolite you're building the layer by
  • 00:38:42
    layer information now from The genome
  • 00:38:45
    level you are able to see okay which are
  • 00:38:46
    all possible mutation from that given
  • 00:38:48
    cancer or given disease you are able to
  • 00:38:51
    see and now using protein you are able
  • 00:38:53
    to further enrich and say okay how many
  • 00:38:56
    modifications I can see what is the
  • 00:38:58
    correlation between these type of
  • 00:39:00
    genotypic changes which we see and
  • 00:39:02
    finally happening at the phenotypic
  • 00:39:03
    level by integrating the functional
  • 00:39:05
    information from the proteome and the
  • 00:39:07
    metabolome so this is where I think
  • 00:39:09
    integrating the piece of information is
  • 00:39:11
    very important and you are taking this
  • 00:39:13
    course on proteogenomics you have gone
  • 00:39:15
    through it and there is you know very
  • 00:39:17
    active effort with the proteogenomics
  • 00:39:19
    community to look at the especially for
  • 00:39:21
    the cancer program which wased by Joe
  • 00:39:23
    Biden about cancer moonshot to look at
  • 00:39:26
    integr the data of different cancer type
  • 00:39:29
    and provide much more powerful
  • 00:39:30
    information as a part of a big
  • 00:39:32
    initiative known as the ICPC
  • 00:39:34
    International cancer protogen Consortium
  • 00:39:36
    where India is also not part of the
  • 00:39:38
    cancer Moon short program so aish is
  • 00:39:41
    going to show you briefly in the lab
  • 00:39:43
    about one of the uh genome sequence and
  • 00:39:46
    and some brief overview about it then we
  • 00:39:49
    will shift to some of the Big Data
  • 00:39:50
    analysis part
  • 00:40:00
    hello everyone I Ai and I'll be giving
  • 00:40:02
    you a demo on the uh NGS instrument that
  • 00:40:05
    we have So currently we have iron
  • 00:40:08
    torrent S5 instrument that you can see
  • 00:40:10
    in your screen I'll give a brief
  • 00:40:12
    overview on the technology and then we
  • 00:40:14
    can talk about the instrumentation so if
  • 00:40:16
    anit can focus on the screen yeah so uh
  • 00:40:20
    I'm going to talk about the iron torrent
  • 00:40:21
    S5 so a brief overview on how you can
  • 00:40:24
    prepare your sample for the genomic so
  • 00:40:26
    first step is to prepare the library and
  • 00:40:29
    to prepare the library very very
  • 00:40:31
    initially you should have a good genomic
  • 00:40:33
    DNA or that or any kind of DNA that you
  • 00:40:35
    want to do for the sequencing you need
  • 00:40:38
    to have that DNA good quantity and you
  • 00:40:40
    quantify that DNA followed by the
  • 00:40:44
    amplification followed by the
  • 00:40:46
    amplification once the amplification of
  • 00:40:48
    the target is
  • 00:40:50
    done uh you have to digest the amplicons
  • 00:40:53
    digest the amplion such as that the
  • 00:40:55
    sticky end yes
  • 00:40:58
    uh I think probably your screen is
  • 00:40:59
    shared you have to stop the sharing of
  • 00:41:01
    your screen then we can see you in large
  • 00:41:04
    because right now it's very small panel
  • 00:41:05
    to really
  • 00:41:08
    view
  • 00:41:10
    okay from your system probably the Have
  • 00:41:13
    you shared the screen something that you
  • 00:41:15
    have to
  • 00:41:17
    stop I have not shared
  • 00:41:20
    anything and this Frame of anit has to
  • 00:41:23
    come on the full screen because you are
  • 00:41:25
    very
  • 00:41:27
    a small manely
  • 00:41:29
    scene
  • 00:41:33
    okay I should come on the full screen
  • 00:41:35
    right of your part then only it will be
  • 00:41:38
    visible now I I think it's
  • 00:41:41
    coming okay now you have to it's PPT is
  • 00:41:44
    coming
  • 00:41:45
    actually yeah so first I'll explain the
  • 00:41:48
    pp and then you can give a demo of the
  • 00:41:49
    instrument all
  • 00:41:51
    right yeah so uh as I was saying the
  • 00:41:55
    first step in the Next Generation
  • 00:41:57
    sequencing is to get a good quantity of
  • 00:41:59
    the DNA and once you have a good
  • 00:42:01
    quantity of the DNA next you can amplify
  • 00:42:04
    the targets there are multiple
  • 00:42:05
    techniques by which uh targets can be
  • 00:42:07
    Amplified one of the most common method
  • 00:42:09
    is the PCR and once the targets are
  • 00:42:12
    Amplified then the sticky ends are
  • 00:42:14
    created as you can see here in the
  • 00:42:16
    workflow the targets are Amplified
  • 00:42:18
    you'll get multiple copies of your
  • 00:42:20
    target DNA and the uh then the sticky
  • 00:42:23
    ends can be created using mild detergent
  • 00:42:25
    once those sticky ends are created
  • 00:42:27
    then the adapter barcodes which are
  • 00:42:30
    essential for the sequencing reaction
  • 00:42:32
    will be added to those sticky ends and
  • 00:42:34
    now these are your libraries which are
  • 00:42:36
    prepared the next step is to amplify
  • 00:42:40
    those Target libraries for that in our
  • 00:42:43
    uh iron torrent S5 we have an instrument
  • 00:42:45
    called iron OneTouch two instrument
  • 00:42:47
    which works on the principle of imulsion
  • 00:42:49
    PCR so uh this is how the instrument
  • 00:42:53
    looks like and you have to fill the
  • 00:42:54
    imulsion mixture here on this on this
  • 00:42:58
    setup and once it's there the imulsion
  • 00:43:00
    reaction will be started and the the the
  • 00:43:03
    libraries that you have prepare during
  • 00:43:05
    your first step of uh NGS will be
  • 00:43:08
    Amplified followed by The Next Step
  • 00:43:11
    would be to enrich those template
  • 00:43:13
    specific uh Target libraries for that we
  • 00:43:16
    have another instrument which is called
  • 00:43:18
    OneTouch es this is how the instrument
  • 00:43:20
    looks like so you will just enrich your
  • 00:43:23
    template specific Target libraries in
  • 00:43:25
    this step once the temp template
  • 00:43:28
    specific Target libraries are enrich in
  • 00:43:30
    this step you will remove those beads
  • 00:43:31
    which are not having any kind of uh uh
  • 00:43:34
    any kind of Library so those libraries
  • 00:43:37
    those beads will be removed in the step
  • 00:43:39
    and you will have proper um like proper
  • 00:43:42
    template specific library and those
  • 00:43:44
    libraries will be loaded onto this chip
  • 00:43:47
    like this as as it is shown here the
  • 00:43:50
    using one ml pip the libraries template
  • 00:43:53
    specific libraries will be loaded on the
  • 00:43:55
    chip I'll be giving a Dem of this chip
  • 00:43:58
    and everything in in a few minutes and
  • 00:44:01
    that's how you can once you have your
  • 00:44:03
    template specific librar are loaded you
  • 00:44:05
    can just load this chip and start the
  • 00:44:08
    sequencing run talking about the
  • 00:44:10
    principle how this iron to S5 works so
  • 00:44:13
    it works on identifying the uh this
  • 00:44:16
    proton ion which is released during the
  • 00:44:18
    formation of phosphor diaster bond so we
  • 00:44:20
    all have learned molecular biology where
  • 00:44:22
    we have learned that during the
  • 00:44:23
    formation of phosphor diester bond
  • 00:44:25
    whenever one nucleotide is added to the
  • 00:44:28
    um to the ongoing stand of DNA there is
  • 00:44:31
    formation of phosphodiester bond which
  • 00:44:32
    is something like this and there's a
  • 00:44:34
    release of proton ion so this instrument
  • 00:44:36
    basically detects this proton ion which
  • 00:44:38
    is released during this step and it
  • 00:44:40
    converts this chemical energy to the
  • 00:44:42
    electrical energy and that's how so this
  • 00:44:45
    chip has a lot of sensors here where
  • 00:44:48
    this proton ion is detected by the by
  • 00:44:51
    the sensor which is located below the
  • 00:44:53
    below the chip and it converts the
  • 00:44:55
    chemical signal to the electrical signal
  • 00:44:58
    that's how the instrument gets to know
  • 00:44:59
    that the sequencing is happening now if
  • 00:45:02
    I'm can show can show the instrument
  • 00:45:04
    I'll give a uh I'll give you the tour of
  • 00:45:07
    the uh
  • 00:45:23
    instrument right so if you can focus on
  • 00:45:26
    so this is the iron torrent S5
  • 00:45:28
    instrument where the sequencing happens
  • 00:45:31
    so before uh to start the sequencing
  • 00:45:33
    reaction you have to clean the
  • 00:45:34
    instrument so I'm going to perform that
  • 00:45:36
    step and I'll show you what all the
  • 00:45:38
    agents and what all cartridges goes
  • 00:45:40
    inside for your sequencing
  • 00:45:50
    so it will take some like just few uh
  • 00:45:54
    time so you can see here it will tell
  • 00:45:56
    you that these are all of the cartridges
  • 00:45:59
    and all of the washing Regents should
  • 00:46:01
    you should have before starting the uh
  • 00:46:03
    cleaning of the instrument and then
  • 00:46:04
    subsequently the sequencing run I'll
  • 00:46:06
    show you uh that's how the inside of the
  • 00:46:09
    instrument looks like
  • 00:46:53
    stopit so I'm not even there I have I
  • 00:46:56
    have left the meetings from
  • 00:47:17
    here all right so
  • 00:47:20
    uh she is figuring out you know way to
  • 00:47:23
    expand her screen uh what is important
  • 00:47:26
    here to think about uh the different
  • 00:47:29
    Technologies available whether for
  • 00:47:31
    looking at your complex pum or genome or
  • 00:47:34
    metabolome but can we really uh be
  • 00:47:37
    creative to look at from the same sample
  • 00:47:39
    and try to enrich that data right um and
  • 00:47:42
    how to really look at the entire thing
  • 00:47:44
    in more totality so now I think you can
  • 00:47:46
    see the IR instrument and I should
  • 00:47:48
    briefly please explain timing is as now
  • 00:47:58
    ai go ahead can
  • 00:47:59
    you okay so sorry for the glitch but now
  • 00:48:03
    I hope you can see the instrument here
  • 00:48:06
    so this is the iron torrent F5 setup
  • 00:48:08
    that we have in our phics lab and before
  • 00:48:11
    going for any sequencing back we have to
  • 00:48:13
    first clean the instrument so I'm going
  • 00:48:14
    to show you how to clean the instrument
  • 00:48:16
    and what all Regents start both inside
  • 00:48:19
    the sequencer so a you can focus on the
  • 00:48:22
    instrument now that's how the instrument
  • 00:48:24
    looks like and I can show you inside the
  • 00:48:27
    instrument where we have all these
  • 00:48:29
    cartridges and everything I'll just this
  • 00:48:31
    chip clamp where we have this chip which
  • 00:48:34
    is very important it some looks
  • 00:48:36
    something like this and there are here
  • 00:48:38
    are a lot of Bio sensors which I was
  • 00:48:40
    talking about and you have to load your
  • 00:48:42
    uh sequencing reaction onto here and
  • 00:48:45
    once your sequencing reaction is loaded
  • 00:48:48
    it will it should be equally spread
  • 00:48:50
    along this chip and then we can gently
  • 00:48:52
    place this chip um onto this chip
  • 00:48:56
    cartridge
  • 00:48:58
    like this it will go smoothly and you
  • 00:49:00
    have to close this chip clamp other than
  • 00:49:03
    chip this is the uh cartridge which is
  • 00:49:07
    the nucleotide cartridge here your all
  • 00:49:09
    the dntps are here and it will go like
  • 00:49:12
    this here like this in the instrument
  • 00:49:14
    this is the wash solution so every time
  • 00:49:16
    once your nucleotide is go uh like uh
  • 00:49:19
    goes to the goes to the instrument this
  • 00:49:21
    is a was solution so every time after
  • 00:49:24
    the one nucleotide the was solution is
  • 00:49:26
    uh will clean the tubes and everything
  • 00:49:28
    this is the cleaning solution which is
  • 00:49:30
    going to be used during the cleaning and
  • 00:49:33
    here we can also U for the um this is
  • 00:49:38
    the waste collecting uh thing where all
  • 00:49:41
    the uh waste of the sequencing reaction
  • 00:49:44
    will go here and you have to clean this
  • 00:49:46
    uh cartridge after the sequencing
  • 00:49:48
    reaction is complete so that's how you
  • 00:49:50
    have to you have to be very uh cautious
  • 00:49:53
    while checking all the things are in
  • 00:49:55
    place and once is
  • 00:49:57
    that sorry to stop you U I think we are
  • 00:50:00
    getting late thank you for this
  • 00:50:03
    demonstration um yeah so broadly now you
  • 00:50:06
    can see a lot of data can be generated
  • 00:50:08
    but how to analyze the data so timing is
  • 00:50:10
    bit short but we will give you at least
  • 00:50:13
    some flavor of uh looking at for the MPE
  • 00:50:16
    data and MPE data analysis can be very
  • 00:50:19
    complicated and the software which are
  • 00:50:22
    currently available they can take you
  • 00:50:24
    like you know good Ram of the inst your
  • 00:50:26
    MPE and it can take few days time but a
  • 00:50:30
    new software which is developed from
  • 00:50:32
    academic Lab Dr Alex's lab uh in
  • 00:50:35
    nashille uh in US Ms Fragger it is one
  • 00:50:38
    of the very highly recommended software
  • 00:50:40
    for you guys to try out even in know own
  • 00:50:43
    laptop you can run some you know complex
  • 00:50:45
    MP data and analyze that so ainash is
  • 00:50:48
    going to give you very quickly just the
  • 00:50:51
    kind of software
  • 00:50:52
    interface uh because we don't have time
  • 00:50:54
    to run the data right now uh but again
  • 00:50:56
    if you have really interest you can
  • 00:50:58
    always ask us we'll be happy to have a
  • 00:50:59
    separate session for you for the data
  • 00:51:01
    analysis part but ainash please uh
  • 00:51:04
    quickly give a demonstration of that
  • 00:51:05
    software yeah so sir can you unare your
  • 00:51:10
    screen yeah thank
  • 00:51:19
    you so uh this is a like sir I already
  • 00:51:22
    mentioned that so this is a your first
  • 00:51:24
    like after opening the software so this
  • 00:51:26
    is the frag pipe 22 version so you can
  • 00:51:29
    easily download this software by using
  • 00:51:31
    going in the Google and just type the
  • 00:51:32
    frag pipe you will easily uh get the all
  • 00:51:35
    the tutorials and the downloading links
  • 00:51:37
    so after downloading the links you will
  • 00:51:39
    get this kind of interface and this so
  • 00:51:41
    here we have to install the multiple
  • 00:51:44
    like like plugins for this software so
  • 00:51:48
    like Ms Fragger iron cont and D rure for
  • 00:51:51
    the different kind of analysis and the
  • 00:51:52
    Dian and the pythons and the and also
  • 00:51:54
    the for the different software for the
  • 00:51:56
    analysis so now we will go for the like
  • 00:51:59
    workflow like how we do the analysis so
  • 00:52:01
    after downloading all the the sessions
  • 00:52:03
    you can just click on the download and
  • 00:52:05
    you can download all the sessions after
  • 00:52:07
    downloading you can go to the workflow
  • 00:52:09
    and you can if so for this analysis I'm
  • 00:52:11
    just showing for the DDA analysis and so
  • 00:52:13
    this is the list of the different kind
  • 00:52:15
    of workflow has been given for the all
  • 00:52:17
    kind of analysis like DDA Dia tmtn you
  • 00:52:19
    can get all kind of data set So
  • 00:52:21
    currently I'm using the lfq MBR for the
  • 00:52:23
    DD files so just click on the lfq MBR
  • 00:52:25
    and you can click click on the load
  • 00:52:27
    workflow and it will get already loaded
  • 00:52:29
    and will load the all the parameters so
  • 00:52:32
    after that you can add the few files so
  • 00:52:34
    I already added here so you can just
  • 00:52:36
    click on this Ms data type you can just
  • 00:52:38
    click on ADD TI file and you can
  • 00:52:40
    download you can just select all the
  • 00:52:42
    files and you can upload here so U after
  • 00:52:45
    that after downloading the file it would
  • 00:52:47
    by default take the data type if it is
  • 00:52:50
    not taking the data type by the by
  • 00:52:52
    default you can just click on that and
  • 00:52:54
    you can change the data type and also
  • 00:52:56
    you can also add the different
  • 00:52:58
    biological group and so in this case we
  • 00:53:01
    have taken the three control and the
  • 00:53:02
    three tumor sample so likewise I have
  • 00:53:04
    annotated so you can just click on the
  • 00:53:07
    those samples and you can change by
  • 00:53:09
    using the uh conjugative Way by file
  • 00:53:12
    name and also you can do by the custom
  • 00:53:14
    way so there are multiple way of doing
  • 00:53:16
    this things so you can uh do do this
  • 00:53:18
    part in the same way you can uh if you
  • 00:53:20
    have the bio replicate and Technical
  • 00:53:23
    technical replicate you can mention this
  • 00:53:25
    part so this is the first part of
  • 00:53:26
    loading the database and after that you
  • 00:53:28
    can directly go to the uh database part
  • 00:53:31
    and you if you uh if you want to like uh
  • 00:53:34
    download or you can upload so there are
  • 00:53:36
    multiple way to uh upload your database
  • 00:53:38
    so some of the few database has been
  • 00:53:40
    already given for the human must mular
  • 00:53:42
    sensor and different other species and
  • 00:53:45
    also it was give the checkbox for the
  • 00:53:47
    review sequence add decoy and the add
  • 00:53:49
    common contamin so for this study this
  • 00:53:52
    is the human cell line so I'm just using
  • 00:53:54
    this by default one and I can just I
  • 00:53:56
    will just click on the okay so after
  • 00:53:58
    that it will be get downloaded and
  • 00:54:00
    suppose if you want to add your own
  • 00:54:02
    database you can just browse and you can
  • 00:54:04
    add your database here and after that
  • 00:54:06
    the next part is basically the all the
  • 00:54:08
    parameter the major parameter we set for
  • 00:54:10
    the analysis so the so you have already
  • 00:54:12
    selected the lfq MBR workflow and but if
  • 00:54:15
    you want to change a few parameters like
  • 00:54:17
    missing cleavage and the enzyme type you
  • 00:54:19
    can change this part so this is the like
  • 00:54:22
    showing the precursor M tolerance and
  • 00:54:24
    the fragment M tolerance so the by
  • 00:54:26
    default it give the 20 if you want you
  • 00:54:28
    can change according to your criteria so
  • 00:54:31
    and also you can also add like what kind
  • 00:54:33
    of tiation has been done so there are
  • 00:54:35
    different kind of drop down has been
  • 00:54:37
    given you can change your enzymes and
  • 00:54:39
    thetic cavage part and this section
  • 00:54:41
    basically you can add your modification
  • 00:54:43
    so by default they add like three
  • 00:54:45
    modification Al so two variable
  • 00:54:46
    modification and one fixed modification
  • 00:54:49
    so one is the oxidation methine and the
  • 00:54:52
    anal acation and the one another is a
  • 00:54:55
    fixed modification have to be quick yeah
  • 00:54:57
    yeah yeah so after that you can just
  • 00:54:59
    directly go to the qu Tams one you can
  • 00:55:01
    check just click on this part and if you
  • 00:55:03
    want to change anything you can change
  • 00:55:05
    here or otherwise you can just directly
  • 00:55:07
    go to the run and go to the browse and
  • 00:55:09
    select the directory where you want to
  • 00:55:10
    save the file and you can just start and
  • 00:55:13
    it will uh just click on the run so it
  • 00:55:15
    will get start running this way and
  • 00:55:17
    after the finishing this job it will
  • 00:55:18
    show this kind of interface to your job
  • 00:55:20
    is done and after running this file you
  • 00:55:22
    will get the output like this so this
  • 00:55:25
    will be output file and you will get the
  • 00:55:27
    combined protein peptide and anotation
  • 00:55:28
    file from this data sets now we will
  • 00:55:31
    move for the like we are rushing for the
  • 00:55:33
    time so we will move to the further
  • 00:55:34
    analysis so you can so currently they
  • 00:55:37
    have added the downstream analysis
  • 00:55:40
    analysis software as well which is the
  • 00:55:42
    track pipe anal if you just click on
  • 00:55:43
    this it will directly open up so I've
  • 00:55:46
    already opened up this software so it
  • 00:55:48
    the interface will be look like this so
  • 00:55:50
    yeah so this will be interface for the
  • 00:55:52
    frag type analyst you can just click on
  • 00:55:54
    the analysis you can select your data
  • 00:55:56
    type so our data type is lfq so we will
  • 00:55:58
    select that and if you can just browse
  • 00:56:00
    the what whatever the file was given so
  • 00:56:03
    you have to select the combined protein
  • 00:56:06
    folder combined protein so it will
  • 00:56:09
    already get uploaded after that you have
  • 00:56:11
    to give The annotation file so this is
  • 00:56:13
    our experimental annotation and after
  • 00:56:16
    that so yes is get downloaded here you
  • 00:56:18
    can select the max lfq intensity and if
  • 00:56:21
    you want to the change like various
  • 00:56:23
    other parameters like missing values and
  • 00:56:25
    the P value criteria and the full change
  • 00:56:27
    criteria and type of normalization so
  • 00:56:29
    you can check on that and also there are
  • 00:56:31
    different type of imputation method has
  • 00:56:33
    been given so Pur type K so those are
  • 00:56:36
    the basically commonly used methods and
  • 00:56:39
    also the Benjamin HB for the FDA
  • 00:56:42
    correction and you just click on the run
  • 00:56:44
    so yeah it will just take the few
  • 00:56:46
    seconds to complete this part and uh it
  • 00:56:48
    will show like all the QC parts so yeah
  • 00:56:51
    as you can see so the first part to
  • 00:56:53
    check the like uh to so these are the
  • 00:56:56
    the basically QC plot to check the data
  • 00:56:58
    quality so you can look for the PCA plot
  • 00:57:00
    sample correlation sample CVS and the
  • 00:57:02
    density plot and the missing value heat
  • 00:57:04
    map and you can also so overall you can
  • 00:57:07
    check all the type of QC plot from the
  • 00:57:09
    this data sets and after that you can
  • 00:57:11
    get the volcano plot and uh yeah so uh
  • 00:57:16
    so as you can see that in this there it
  • 00:57:19
    is showing a four five so we have not
  • 00:57:21
    added the missing value of criteria so
  • 00:57:22
    it will give you the list so you can
  • 00:57:24
    just sort on the basis of the like C
  • 00:57:26
    change criteria and uh like what F
  • 00:57:28
    change com so it is also giving the
  • 00:57:30
    volcano plot and you can download all
  • 00:57:32
    the plots and the tables which has been
  • 00:57:34
    given you can also add like what kind of
  • 00:57:37
    En enrichment you want so and also it if
  • 00:57:40
    you want you can look for the pathway
  • 00:57:41
    analysis this part so this is a very
  • 00:57:43
    convenient pathway like convenient like
  • 00:57:46
    for the all the for the downst strring
  • 00:57:48
    analysis and we can get the de is from
  • 00:57:50
    this and after that we will go for the
  • 00:57:52
    path analysis which like anit will talk
  • 00:57:56
    about that so that's all all right great
  • 00:57:59
    so uh thank you anash I think it was yes
  • 00:58:02
    quick demo but what users and the the
  • 00:58:05
    student who are joining today they can
  • 00:58:07
    see that even looking at uh please stop
  • 00:58:10
    sharing the screen yeah yes even uh now
  • 00:58:13
    analyzing the complex mpect data is very
  • 00:58:16
    much possible and earlier you know we
  • 00:58:18
    used to then look at different software
  • 00:58:20
    uh to do the plotting of the data
  • 00:58:22
    especially the u ms FR like you know
  • 00:58:25
    metab list and percs many other
  • 00:58:29
    software U but now I think you know you
  • 00:58:31
    have advantage that you can use the MS
  • 00:58:33
    frager and generate the from the same
  • 00:58:36
    software you can look at very simp of
  • 00:58:37
    output as well and very fast
  • 00:58:40
    Additionally you can always even do more
  • 00:58:42
    of the protog genomics data analysis
  • 00:58:43
    with the c bioportal and we just inst
  • 00:58:46
    you have already learned some of these
  • 00:58:47
    tools in the protog genomics course if
  • 00:58:49
    you're doing that for students of the
  • 00:58:51
    proteomic you can know that there's a
  • 00:58:53
    word Beyond this proteomic when you can
  • 00:58:55
    now start thinking about integrating
  • 00:58:57
    data and make it more multix you know
  • 00:59:00
    kind of picture and U given the short
  • 00:59:03
    time we will be uh skipping the demo of
  • 00:59:06
    other protog genomics tool U but what
  • 00:59:09
    you have to really uh understand about
  • 00:59:11
    you really want to emphasize that now
  • 00:59:13
    there is a field which is know as multix
  • 00:59:15
    or integrated omx which is now driving
  • 00:59:18
    the systems based approach of
  • 00:59:20
    understanding any complex system much
  • 00:59:22
    more
  • 00:59:23
    comprehensively that's the field which
  • 00:59:25
    is going to really make the difference
  • 00:59:26
    because in in our actual physiology
  • 00:59:30
    whether it's human or other kind of
  • 00:59:31
    living system we don't have the gene
  • 00:59:34
    protein RNA metabolite they don't work
  • 00:59:36
    separately or independently they all
  • 00:59:38
    work kind of like you know in in a very
  • 00:59:41
    relay race where every partner is very
  • 00:59:44
    important right so when we look at only
  • 00:59:46
    one side of the picture only genome or
  • 00:59:48
    only transcriptome or only proteum we
  • 00:59:50
    miss out the complete picture therefore
  • 00:59:53
    uh what is now much more with the robust
  • 00:59:55
    Technologies and instuments available
  • 00:59:57
    but is now much more possible to look at
  • 01:00:00
    different layer of information from the
  • 01:00:01
    same type of sample and that's really
  • 01:00:03
    more important for the complex disease
  • 01:00:05
    like you know for various type of human
  • 01:00:06
    cancer diabetes heart diseases now
  • 01:00:09
    people are trying to look at layer by
  • 01:00:11
    layer information and then now what you
  • 01:00:13
    realize is that since weting so much
  • 01:00:15
    amount of data it can't be only biology
  • 01:00:18
    project now we talking about the big
  • 01:00:19
    data so therefore people from the
  • 01:00:21
    statistical background becomes very
  • 01:00:23
    important to look at the significance of
  • 01:00:25
    the data people from the core
  • 01:00:27
    computational background becomes
  • 01:00:28
    important to look at the entire
  • 01:00:31
    programming and even from the chemical
  • 01:00:33
    background to look at the simulation of
  • 01:00:35
    the data and come up with the much more
  • 01:00:36
    systems modeling to understand a given
  • 01:00:39
    system much more comprehensively so all
  • 01:00:41
    this is really you know moving in the
  • 01:00:43
    direction of what we see like you know
  • 01:00:44
    the new era with the artificial
  • 01:00:46
    intelligence machine learning to really
  • 01:00:48
    make much more predictions but
  • 01:00:50
    predictions will only come if we have
  • 01:00:51
    the robust set of the data to build the
  • 01:00:53
    models so therefore right now this kind
  • 01:00:55
    of field is really uh playing an
  • 01:00:58
    important role to generate very
  • 01:01:00
    meaningful information and data sets
  • 01:01:02
    which can be utilized to make very
  • 01:01:04
    important hypothesis which can be
  • 01:01:07
    further tested with the specific type of
  • 01:01:09
    experiments I hope you got kind of a
  • 01:01:11
    gist of various technology which uh you
  • 01:01:13
    have been studying uh in bits and pieces
  • 01:01:15
    in the course but at least you had the
  • 01:01:17
    firstand opportunity today from the lab
  • 01:01:20
    to see some of these instruments and the
  • 01:01:22
    workflows so with this let me thank all
  • 01:01:24
    the t uh uh who have really given you
  • 01:01:28
    nice demonstration very limited time
  • 01:01:29
    what we had and uh also uh they have
  • 01:01:33
    been following upon all of your queries
  • 01:01:35
    on the Forum and giving you you know
  • 01:01:38
    some meaningful comments on your various
  • 01:01:40
    type of queries uh so thanks to entire
  • 01:01:43
    team and of course thanks to all of you
  • 01:01:45
    the students who are really showing good
  • 01:01:47
    interest into the course are asking some
  • 01:01:50
    very interesting questions to us and lot
  • 01:01:51
    of query which comes to us and hopefully
  • 01:01:54
    like some of you might be liking this
  • 01:01:56
    field to utilize it for your own
  • 01:01:57
    research or to take up the future job
  • 01:02:00
    opportunities and career opportunities
  • 01:02:01
    many student ask us these questions like
  • 01:02:03
    what kind of future opportunities we may
  • 01:02:05
    have in this area and of course you know
  • 01:02:07
    given the significance of this field uh
  • 01:02:10
    you will expect that okay you are going
  • 01:02:12
    to get lot of uh job opportunities in
  • 01:02:15
    this area because people who can uh
  • 01:02:17
    analyze these type of data sets will
  • 01:02:19
    been big demand uh with this I think we
  • 01:02:22
    will close today's live session which
  • 01:02:24
    was our second live session for this
  • 01:02:26
    smuk course and we really wish all of
  • 01:02:29
    you the best for your writing exams if
  • 01:02:32
    you do well in your uh this Muk course
  • 01:02:36
    you will have opportunity to come to it
  • 01:02:37
    Bombay uh spend some time in our lab or
  • 01:02:40
    do some internship or attend some
  • 01:02:41
    Workshop so uh the journey does not end
  • 01:02:45
    here with this kind of you know the
  • 01:02:46
    video courses but rather we want to have
  • 01:02:49
    to see some of you more live in the lab
  • 01:02:52
    and just you know on the lighter note
  • 01:02:53
    there has been several move propers who
  • 01:02:55
    have really you know eventually joined
  • 01:02:57
    our lab and I have been really you know
  • 01:02:59
    very proud to see their career
  • 01:03:01
    progression and our interaction with
  • 01:03:02
    them that they were virtual students who
  • 01:03:05
    you know then perform very well they
  • 01:03:07
    came to join our lab as a project
  • 01:03:09
    student or interns eventually they got
  • 01:03:11
    into the PHD programs or M tech programs
  • 01:03:14
    they finished the programs here and now
  • 01:03:15
    they're doing very well for their post
  • 01:03:16
    do and jobs in Us and other places so it
  • 01:03:19
    has been really you know remarkable uh
  • 01:03:21
    uh positive journey and experience to
  • 01:03:23
    see how the virtual interaction from all
  • 01:03:26
    over India and different parts of the
  • 01:03:27
    world brings people together and then
  • 01:03:29
    you know we are helping them to move
  • 01:03:31
    forward in their career trajectory so we
  • 01:03:34
    wish all of you the best and we'll be
  • 01:03:35
    very much available to take any other
  • 01:03:38
    query and your other kind of future uh
  • 01:03:41
    whatever you know apprehensions you may
  • 01:03:43
    have and questions you may have to give
  • 01:03:45
    you much more you know meaningful
  • 01:03:46
    insights of your query with this let me
  • 01:03:49
    thank the entire team and close today's
  • 01:03:51
    session okay bye everybody
Tags
  • multiomics
  • proteomics
  • single-cell analysis
  • biological research
  • data integration
  • genomics
  • metabolomics
  • proteogenomics
  • mass spectrometry
  • big data