Increased protein coverage for high-quality peptides with streamlined, scalable sample prep workflow

hello everyone and welcome to today's webinar increased protein coverage for highquality peptides with a streamlined scalable sample prep workflow I'm Christy jul of labots and I'll be your moderator for today's event today's educational web seminar is presented by labots and brought to you by kovarus to learn more please visit our sponsors website at covaris tocom now we encourage you to participate today by submitting as many questions as you want at any time you want during the presentation to do so simply type them into the ask a question box and click Send we will answer as many of your questions as we have time for at the end of the presentation additionally If you experience any technical questions you can submit them in that Q&A box and we will answer you directly I would now like to welcome our speakers Mo Haynes senior research associate broad proteomics broad Institute of MIT and Harvard and Deb bataria BP of Business Development emerging markets at covaris for complete biographies on our speakers visit the biography tab at the top of your screen Mo Deb welcome so happy to have you you may now begin your presentations well thanks for the nice introduction um appreciate it and also thanks to uh everyone who's attending and um who's dialing in feel free to drop your questions in we we always love to get questions so um the first part of today's talk I'm going to talk about you know streamlined scalable sample preparation workflow uh especially focused on proteins um which is something that uh is gaining a lot of traction in the market so without further Ado I'm just going to move on straight away into why we are focusing in the world protein analysis what are we doing how does our technology actually is enabling better sample preparation so um it's nothing new to the world of uh PE you know of proteomics or protein analysis folks that uh regardless of whether you are targeted or untargeted whether you are looking at Global proteins or whether you are looking at a specific protein therapeutic and monitoring Its pharmacokinetic pharmacodynamic Behavior there are a few things that are common that everybody always wants to want to uh achieve so best data data quality ensuring that you know you get highest sensitivity highest resolution and good information ability to scale um not just in terms of volume of your samples but also number of samples without spending a huge amount of time and also understanding that what can be a niche work workflow today can be implemented in a regular lab in a routine lab tomorrow so no matter where you are um all of these things are something that you know you are trying to achieve whether it's you know reduction of cost per sample whether it's uh con you know transitioning from your uh research to a routine laboratory based test uh or you are developing a particular therapeutic or you are identifying new biomarker so how we are making this world look slightly better complications complexities and challenges addressed with a little more ease um comes in the next few slides so first and foremost let me introduce our technology so it's uh an ultrasonication technology that uses acoustic energy at a specific uh subbase frequency hence very short wavelength that goes and hits the samples and creates a lot of cavitation bubbles which in due course of time coales releases an an energy that's used for uh disruption of Matrix matrices you know uh homogenization of tissues and so on and so forth so for a long long time this technology has been the go-to technology for sharing DNA and it still is as of today the main benefits are couple of things that um the pressure that comes on the sample is very equally distributed so that you are not necessarily jeopardizing the Integrity or the structure of your um sensitive vulnerable molecules whether it's like RNA or proteins and the other thing is that you can actually maintain isothermal conditions with this so there's no heat that's imparted to the sample despite the fact that you are hitting the sample with so much of energy so if I look into this the has been a long long uh history behind us where it's been the way to uh cut DNA for DNA sequencing or Shar DNA for DNA sequencing it's been also used in transcriptomics for chromatin sharing also in the world of RNA quite a lot but now we are actually focusing on the other side of the world as well which includes you know proteomic in the for the given breath of time in this particular webinar we are not going to talk about about metabolomics or lipidomics how we are also enabling those areas but in proteomics I'm going to highlight some very um nice uh published examples that would actually uh be very beneficial perhaps hopefully uh to for you to understand how uh our workflows our technology can enable every single laboratory working with proteins and after me I have got Mo who's also going to talk and share some of his own data data which I think would be even more impactful so um right off the bat there are three stages in which we have divided our workflow especially when it comes to proteins so if there is one thing that I would love for each of you to remember today is that this technology helps you address complex matrices and get highquality analytes out of it so you the first stage is where you start with whether it's tissues or or ffp samples uh cells Maman cells you know organoids you can take any one of those matrices and you could drop them in our plates or in our tubes and with the energy um we can figure out how to actually homogenize that metrix disrupt that Matrix to maximize the total yield of proteins that you're going to get it uh or get out of it in a very reliable reproducible manner from that point of time our technology also helps with protein aggregation capture as an example uh in purifying whether you are doing the pull down or and last but not the least we have options where we can also expedite the whole digestion process by exped with our energy especially if it's on be digestion we can accelerate the whole process and I will explain this a little later that how we have taken the overnight digestion and brought it down to something like 90 minutes or two hours although you can also still continue to do the overnight digestion so the next uh part um that I would love to highlight is focusing on different matrices so you can see cells fresh frozen tissues ffp which are the most obvious complex matrices that everybody uh talks about everybody wants to address and you know we have in here different in the boxes right below you can see the number of cells uh that we can address and then if you have very high concentration of cells 1 million and above it moves to a different consumable a different workflow but we do have workflows for different number of cells different amounts of fresh frozen tissues and also ffp Scrolls so at the end of the day the what I would love to highlight is that we have set workflows and towards the lat part of the presentation I will also talk about some of the kits that we have launched that are we are in the process of launching um what we are trying to do over here also is making things in a a very customizable because no two proteins are uni the same every single laboratory wherever you are your proteomic acids are focused on different groups of proteins different Technologies different Focus points so what we are trying to do is to to give you a very high starting ground and then from there on we can actually work with you to make it very custom customizable optimal for your specific uh experiments so as an example uh here is a published me some of the Publications that I'm going to go over so this came out of Cedar Sinai uh from Jenny vanites group where they looked into um doing the proteomic analysis uh for uh for proteins and peptide uh across thousands of samples um using different tissue types and they have actually created like you know a total uh curve of the total amount of proteins that they generated and also between you know segregated between you know low abundance medium abundance High abundance proteins and they are also using over here a dual trap single column configuration um which along with the afab based workflow that we have um enabled along and the mass packet assay makes it very very fast for them to analyze their protein samples so the next part is something that is very close to my heart which is like ffp and I'll again get back to it a little later in the presentation that this C actually was a collaboration work that um were you know was with Matias man's group uh and they focused on extracting samples or extracting proteins from ffp uh samples and then um automating the whole workflow where they extracted with our technology proteins across different types of metries which looked into you know pig liver heart muscle and also compared with heila cells and also showed remarkable uh High reproducibility when it comes to its peptide depth as well so um moving on some of the things that I have al already mentioned is that that we have certain process of using this particular energy in Expediting the whole workflow and this is a classic example where we have a workflow that we have developed and we've published as well where we took the whole TMT workflow and brought it down to something around 6 hours but with enabled by the AFA technology so essentially most of your reagents and workflows continue to be what it is today and enabled by the whole afab based workflow we expedite the whole process which gives you that um the luxury of completing your whole workflow within six hours so when it comes to ffp my favorite topic and I just alluded that a couple of slides back what I would love to highlight over here is that is the critical challenge for those of you who are working with ffp samples or are considering to work with ffp samples the first big obstacle is actually de paranz and most often um the workflows the options that exist out there include actually um um using harsh chemicals for deparaffinization which not only is kind of dangerous to work with it also reduces your scalability capabilities so it takes time you have to get to the fum hood and not only that um it often degrades the surface of the tissues at least that's embedded in it which means it's also compromising the Integrity of the proteins that you're trying to extract hence for Trace abundant proteins you are unlikely to get enough of it out so that you know your mass back sensitivity is good enough to catch it so uh what we are doing over here there are a couple ways but this is the only technology or AFA is the only technology along with our workflow that can actually de parapan eyesee uh an ffp sample or a scroll without use of any harsh chemicals so much so that it can be automated completely and uh as such uh on the genomic side there are quite a few of our existing users who are using our workflow for automated um automatically de parapan ising and extraction of total nucleic acid including DNA and RNA at the same time so we are taking the same first approach over here in De parapan isation with our de de parhiz buffer um and that we can start with one Scroll of 10 Micron pigness that can give you uh enough proteins and hence enough peptides for your um eventually you know bottom up analysis so you can start with the de parapan isation and in the same plate or in the same tube you can continue to have your uh next steps which is extraction of proteins purification of proteins with you know beads uh such as the protein aggregation capture or pack protocol followed by digestion so that's using a full scroll but what if you have even smaller samples if you are heading toward spatial if you have um you know laser cap micro disection so this publication came out uh as part of a collaborative Venture with Mayo Clinic last year um so what they are doing right over there uh is what they did was start with an ffp block but they used LCM which dropped the samples straight away into our 96 well plates and from there on WE homogenized the tissues we you know resulting in extraction of proteins followed by um you know the purification ation or pull down and on be digestion so as you can see towards the lower right of the screen the yellow bars where uh is what you know the standard workflows as long as it took like it was more than 20 hours was how long it was taking them and it came down to somewhere around three hours for the whole workflow so it's not just about getting quality samples quality analyze but it's also about the ability to scale it up to increasing the througho so you know it's it's actually quite nice that today uh you know within a very short period of time that we have been focused in the world of protein analysis we actually have lot of robust workflows that are not only tested internally there are quite a few users around the world who are regularly using these workflows whether it's cells um of you know different number of cells uh fresh frozen tissues or ffp samples so all of these together um along with our instruments uh we have been supporting uh different kind of protein uh Laboratories whether it's academic research whether it's biofarma uh or whether it's you know a contract research organization whether it's a clinical research environment and we also have very recently launched our uh first kit in the world of proteins which is starting with cell license kit so the true prep protein uh kit uh works with miman cells and it is a comprehensive kit that enables Lis extraction and digestion the digestion part can be done with your choice of enzymes not necessarily that you know we would provide you with an enzyme so you can continue to use your enzymes but use our workflow with our instrument and our kit to expedite um make your process a lot more efficient than what it is uh some of the results early stage that would love to highlight is that you know you can see over here the reproducibility uh which remains very consistent both for total proteins as well as for peptide yield using this particular kit so uh you there's very minimal sample handling you do not necessarily have to consider any transfer steps everything's happening in the same strip or uh in in in in a 9 to6 well plate format and the reproducibility has always been less than % for proteins and peptide yields so which is extremely beneficial whether you are trying to standardize a workflow or optimize the condition um next up I would love to highlight you know the flexibility or the scalability so as I mentioned in the meoc clinic publication it's similarly with the cells uh we also have that the standard workflow took as long as 18 hours whereas with our uh AFA enabled workflow with the kit we are down to four and a half hours so um you can start with as low as thousand cells or go up as much as you know half a million cells and you can still make it scalable because your whole workflow is actually incredibly faster compared to uh what you are normally used to so somewhere to the tune off four times faster so whether you consider it four times faster or four times increased throughput that's completely up to you but we can surely enable that um thereafter uh one other thing that I would love to highlight is that um typically we uh do not recommend and do not use a lot of detergent because your lcms instruments are not necessarily very um kind or detergents are not very kind to the LC's so this is another reason why we have a very robust cleanup process uh for the Downstream analysis that also takes care of any even Tre amount of detergent and so there is consistently low levels of reced SDS carryover so that you do not necessarily have to worry about your LC performance uh even before your sample gets to the mass spec and you know thereafter there are um cost per sample so we not only in terms of Time Savings there's also Financial savings because there are a lot of ways you can can actually increase your scalability your throughput your total capacity of working with different kinds of Mamon cells different numbers of Mamon cells and eventually resulting in lower cost for sample so uh in a nutshell this is how the true prep protein kit workflow is for the cells uh where you start with you know you know you harvest the cells uh you start with an a in lizing the cells and then you follow it up with you know cell liis and you know DNA shearing um followed by reduction and alation steps which you do not need to use any AFA for that but it can happen in the same strip format that we are providing followed by purification or your pull down and then accelerated digestion uh we also have H A workflow in the process of uh being converted to a kit but we have this workflow that we have been supporting that I already mentioned to you when it comes to ffp samples the similar approach but it has a couple of steps additional because you have to De parapan IE uh followed by tissue homogenization um then you know you have to do the whole uh reduction alation followed by purification with the pack protocol and then the digestion so all of these things are in the bag we have uh as I mentioned there are three distinct stages that we have focused on in a prot sample prep capability so from extraction to purification to digestion uh our AFA uh class leading um technology along with our workflow for proteins um and in certain cases supported by our kids can enable not only maximizing the total protein yield and you know peptide conversion or peptide depth from your perspective but also doing so in a very reliable repr uble format so that you can be rest assured that you didn't do anything wrong in your sample preparation and you can focus on where you need to focus on which is analyzing the lcms data and that too you can do the whole sample preparation faster than ever before what you've been doing until now overnight digestion can be avoided if you would love to do so so to summarize everything before I pass on the uh baton to MO is that if there is one thing once again I would love for each of you to remember from my talk today is that complex samples to high quality analyes uh this is where our technology becomes extremely beneficial extremely uh helpful a big enabler to every single laboratory thereafter the protein analysis workflows whether you're talking about extraction uh of proteins from complex matrices to purification of proteins to expedited digestion should you need that all of those St steps can be easily enabled in a customizable workflow format depending on what proteins you are going after what is your sample type that you're starting with your nature of your Matrix whether it's fresh Frozen tissue or ffp or cells or organoids and what type of proteins that you are primarily focusing on uh the true prep protein K I talked about the cells um there would be something on the ffp side um also soon uh that you would be hearing about all of these things are enabled or are designed to create uh a streamline process in your laboratory which you can further customize to cater to your specific needs so once again complex samples to high quality analyes and that's where our afab based workflow for proteins and in general protein analysis becomes extremely extremely useful so I don't want to continue any further uh because there's someone uh who's uh you know whose talk I'm actually eagerly looking forward to listen to so without further Ado next up is Mo thanks Depp for the introduction I'm very excited today to show our new ffp workflow that we've Incorporated kavaris uh into this workflow to process um FF tissue and to go over all the details in a systematic way just a little bit about um the proteomics group at the broad Institute before I get started um we do a lot of protein protein interactions um evaluations uh we're interested in what proteins are interacting together what signaling pathways are being activated and we're also looking into the PTM lens landcape we're mostly interested in ubiqutination we're interested in phosphorilation acidulation and even glycosilation another thing that we're also interested in at the Bro Institute is the multiomic and proteogenomic Analysis of different disease States and uh we do HDX mass spectrometry cross-linking mass spectrometry to understand more about protein Dynamics and drug interactions and we also do a lot of chemical proteomics and this gets me to my next point which is ffp samples as we know ffp samples are has been the long has long been the standard for tissue embedding and it presents an invaluable resource for Target of biomarker Discovery right after surgical exision or any biopsy tissue gets uh excised and then it gets uh placed in formalin which would Harden the tissue and after that that it gets embedded in a paraffin wax giving us a block that looks something similar to the picture on the left side and these blocks are very stable at room temperature and that allows any analyst to be able to analyze the same tissue multiple times by scrolling a slice out of it and then they would carry on with whatever asside they have to run such as histo staining or any kind of uh proteomic analysis and the issue with ffb examples is that they've been uh they can be stored for many years and one question remains is how stable are they but also for a proteomic application there might be some hurdles and that's because we have to deal with wax material and we need efficient cross linking as we know that formalin can diffuse through the tissue and can form a methylol um a methylol intermediate that is not stable and from that intermediate we end up with a shift base that's able to cross link between two nucleophilic groups uh whether it's DNA or protein so efficient crosslinking of our tissue is really critical to get good depth of the uh of ffp material and in a typical proteomics application we start with a sample regardless of where it's coming from whether it's tissue whether it's uh uh any fluid the idea is to lice this material and then we'd extract the proteins after they've been denatured and then these proteins get digested into smaller peptides the peptides gets cleaned up and then they get injected on an lcms setup that allows us to sequence these peptides and Trace them back to the proteins that they've originated from and M spectrometry is known to be very sensitive to many different samples however for ffp samples that will require some additional processing steps as we know that a lot of Upstream contaminants need to be eliminated such as wax otherwise we're going to end up with a lot of issues on the mpect side which can affect ID sensitivity and even peptide recovery prior ffp workflows rely on xylene out of which let's starting from an ffp block uh a scroll is taken out and then it gets St waxed using xylene which is a manual step and after that it gets rehydrated with uh an ethanol water wash multiple times and after that the tissue is kept to be dried out and then it enters uh into a Lis buffer and that's followed by the cross linking and then manual homogenization of the probe sonicator and then we carry on our typical lcms background lcms uh proteomic application of reduction alkal and digestion clean up and then mass spectrometry and as we see here uh this process is really lengthy and if you want to apply this to a clinical setting you'll have to do you'll have to process each sample individually and uh a higher throughput process is needed to allow for biomarker Discovery in a large cohort experiment so that's where the karus comes in to help us with simplifying the ffbe workflow what we've done first is we've worked with colorl and breast cancer blocks and we've done the microtome slicing out of which we've started at 10 Micron Scrolls and these scrolls are transferred immediately into a karus plate containing the tissue liis buffer and then the tissue then the kar plate is immediately transferred into the ultrasonicator for de parhiz this process takes about an hour followed by decross linking for 90 minutes at 90c in a thermal cycler and then with another round of ultrasonication to homogenize all tissue that's been DEC cross L and then we follow this up by two main proteomic applications to clean up the sample first we reduced an alkal and then we tested either the sp3 beads or the plate EST strap for proteomic digestion now uh we also add some peptide Quant before running the lcms injections to enhance reproducibility and to inject an a uniform amount and we Leverage The open trons in this case to simplify the process and make manual pipe ping much easier and then we uh then we do the analysis on the uh with an lcms system in this case it was the orbit trap explorers and the data was searched in FRP which was uploaded on Tera and Tera is another scalable solution that we're using here at the road Institute uh where we're able to upload many uh different software and that allows us to run them native on the cloud using computational uh resources I want to emphasize here that we're using Dia and that's why we need a scalable uh workflow to work with a to search our data now the first thing that we've evaluated when using the Kor ultrasonic gor whether the conditions that we're using are sufficient to extract the most amount of protein from our tissue and here what I'm showing on the left side is three different sonication parameters that we were using two factors that we changed were the duty factor which represents the total active time of sonication but we've also evaluated whether we're using whether we're using enough tial liis buffer and as we see by using 50% Duty factor and 150 microl tial liis buffer which shown in green is giving us the most amount of protein that's been extracted from the tissue so we use that condition to process all of our samples and the subsequent uh EXP experiments and then the next thing that we've evaluated was peptide yield from these tissue and the way we've designed this experiment was we started from 50 microgram of protein input and it was either processed with the estrap process in a plate format and when I say EST trap with less than 2% which is shown in yellow that means that we immediately reduce an alculated in the karus plate and then precipitated for the estra or with we evaluated whether we need more SDS to uh evaluate the srap as it requires uh 5% SDS per the manufacturers and the last thing that we've evaluated is the common sp3 bead workflow which was done by loading immediately also an sp3 from the karus play and as when we look at the yields we see uh the highest amount of peptides in the estap 2% however that was mostly shown in the coloral cancer group as shown in CRC among four different replicates for breast cancer we see peptides under five microgram slightly on the lower side and this has to do with tissue homogeneity and the nature of the tissue that we're working with but overall regardless of the choice um we found that EST strap works best for our case as we can add another wash which is uh the chloroform methanol wash during the process that allows us to further clean our samples and uh the plate format does help us in keeping uh things as fast as possible and then the other thing that we're showcasing here is the protein identifications from all these workflows when we look at uh overall we're seeing uh over 7,000 proteins identified regardless of the method that was used and that's consistent among four different replicates and in both breast and colal cancer blocks so at this point we've decided to use 50% Factor 150 microl tissue Li buffer and then we couple that with a plate asra process without adding any additional SDS and just relying on the Karis buffer reducing and alkala and carrying on the digestion as normal to as an as an optimal workflow to use now some extra stats that I wanted to go over is a peptide depth and again we don't see much of a difference in terms of peptide depth another measure that we're looking at is total Quantified tick from each experiment we see reproducibility among all the experimental replicates and the tick that's Quantified from each experiment which gives us more confidence with the automation setups that we have in house but also with the uh with the workflow itself that's being uh reproducible when it comes to processing tissue and uh des salti and last we're looking at miscleavage rate for each workflow everything falls under 16% which is also a good thing uh for a difficult proteomic experiment now that we've optimized a workflow starting from Full scroll analysis what I want to go to next is whether we how does this workflow behave in a tumor Rich environment many people who want to do uh many researchers who are interested in biomarket Discovery are interested in uh mecro dissection or smaller regions where the tumors are enriched so we'd like to see whether this trend would still hold true with when working with smaller sections so what we've done is we were using breast cancer and col rectal cancer blocks and the idea was to macro dissect the tumor rich areas and in a macro dissection experiment usually it can be lengthy given that if you want to collect a full plate one question would be how stable is a tissue in a Lis buffer and for a histologist it's preferable to transfer a tissue into a wet environment rather than into a dry environment so that you don't so that theologist wouldn't end up with any static related problems so we've done an evaluation on the stability in the cavar plate out of which four replicates from each block were split into two groups one group was transferred into the plate with tissue Lis buffer in there while the other group was transferred into a plate without any tissue liis buffer when the macro dissection was over the tissues were transferred into minus8 ADC and they were frozen until time of analysis which was sced on in the next few days using the srap process that we have in house and some automation on the opentrons and we do stage tip D salting for sample cleanup and we followed that up with the di acquisition on the uh Orbee trapic explorers 480 with a Vanquish nail and um what I'm showing here first is that when it comes to Quant IFI protein yields from all these tissue we don't see much much of a difference between uh whether having tissue liis buffer or without in each well which made us uh which which explains stability regardless of the tissue storage condition and for our case we prefer having the tissue liis buffer in the wells when doing these experiments now the other question that we had in mind is how does a depth uh change when working with full scroll an with uh with tumor in areas compared to full scroll analysis and right here we're seeing almost 8,000 IDs seen from all tissue and that means that we're still achieving this deep uh this deep proteum uh profiling while focusing these tumor rich areas and then when it comes to peptide depth it's still within the 50k which is expected based on our previous optimizations one more measure of uh reproducibility is protein CVS and what I'm plotting here is violent plots among the four different replicates from each different uh block and as we see that the median CV for each protein abundant for all proteins across all across all blocks for the replicates are are under 20% which gives us more confidence in the reproducibility and show that there isn't much variation among experimental replicas and one more question that we wanted to evaluate in a tumor Rich area is how efficient is a decross linking when we're using the kar stalis buffer and uh our digestion process and one way to do this was to create a pulled sample out of which we've combined breast and coloral cancer peptides and these peptides were analyzed by a DDA which is data dependent acquisition and two different fractions and we search that data in a PTM discovery mode and that allows us to look for any potential modifications that we're not aware of and you're not you're no longer limited to the modifications that you're using in the database and the results came back out of which we see 80% of all Pepto forms that we've seen in this open search being artifact free and that is very good for a sample of such background where it's been sitting in formalin for many years and we're able to recover a lot of these [Music] peptides another experiment that we were interested in is how does the Quant behave with this workflow when we're using different instrumentation for Dia but also how does it compare to the TMT which is multiplexing which is a very common strategy used in proteomics and we also wanted to use some some ground truth such as a positive control here and one idea was to use a genetically engineered Mouse model to evaluate the ffp um sample processing so in this experiment we're starting with two with four different blocks two blocks contain organs that were embedded from well type mice without any uh uh without any modifications and then we had two other blocks that originated from genetically engineered uh mice that had an overexpression the NCA 4 gen and we processed these samples we scroll these blocks into four different uh replicates and then the idea is to pass it through our ffb workflow and then we once we reach the peptide level that's where we split the sample for different type of mass spectrometry analysis one workflow would be using the TMT acquisition process where the peptide where individual samples get individually labeled with different tags it gets pulled again into a master mix that Master pix gets fractionated into 24 different samples and then analyzed by LC MS2 on the orbit traffic explores 480 the data gets searched in Frack pipe and Ms Fragger and even though this process is very lengthy which takes about seven days it still acquires at a slower Pace compared to the eight samples per day and then the other thing that we were compared that we were uh evaluating was how does DIA behave um compared to TMT so we've taken um each individual sample and we've desalted it into hlc vials and these samples were cleaned up immediately and uh injected into three different instrumentation the orbit trap explorers where we're using The Wide Window Dia in a variable scheme the Tim St HD which uses the ion Mobility to further enhance our reproducibility but also enhance the proteum depth of what we're working with and we're also using the newly released orbit trap astral which is all known to be very fast and also with high resolution we were able to use narrow on that as well and the data was all searched in Diane which was also uploaded on Tera and it's worthy to mention that the process of diaa would require a sample prep time of only two days compared to TMT which is seven days while the lcms acquisition time is at least twice as fast when you're using an older instrument like the Explorers 480 at almost 12 samples per day while the Tim stof HD can catch up to almost 30 samples a day and then the orbit trap astral is able to sequence at 60 samples per day and all of this can print a TMT at eight samples per [Music] day now the first thing we want to look at is how does the protein depth uh uh change between TMT and Dia and surprisingly we see orbit trap astral almost catching up to the depth that's seen by TMT even with the extensive fractionation of 24 different samples now with the with the Tim stof HD we're seeing almost 8,500 proteins as well and the Explorers 480 is still at 8,000 proteins which is still pretty impressive for uh for the for the method that's still faster than the TMT one more thing to look at when we're looking when we're working with proteomic applications is peptide Quant and peptide identifications as expected TMT would give us the deepest uh uh deepest coverage when it comes to peptides given the Deep fractionation however we see orbit trap astral also catching up at 990,000 peptides and that validates the use of Dia for uh for proteum depth as we can cut down sample prep from almost a whole week to two days but also speed up the acquisition time to 60 samples a day and we see the Tim St HD in the Explorers 480 still giving us reasonable peptide depth of 70 and 55 peptides the other the other positive control that we were interested in is the NCA 4 gen and we do see it overexpressed in all of these samples uh when compared to the Wild typ and what I'm plotting on the right side is a full change assessment of the four different groups we do see though the TMT which is shown in purple underestimating the protein full change of nca4 that was measured by Alli method that's showing the green Shades and I will get to that in the next slide as we know that TMT is relying on the concept of multiplexing so it can it can go through a process where uh interference can happen between different channels and that would suppress the observed fold changes so what I'm plotting on the left side here is a correlation Matrix where I'm showing how do all measured fold changes from all these uh from all these blocks compare between astral with respect to TMT the Tim stock HD and the explor 480 and as we see on the Y AIS where the Astro is spotted we see that both the methods which are shown in the green Shades they align very nicely in terms of f changes and exhibit peeron correlation uh over 90 which is uh pretty strong now when it comes to TMT uh when it comes to the TMT we do see that the piercing Cor corelation drops slightly to 08 and that is expected given the uh signal compression problem that I just described uh of DMT and one more metric that we're looking at here among the experimental replicates is the protein CVS for each method and as we see that we see TMT shows the least amount of variation and that is expected because you're multiplexing and you're doing relative Quant but we see Dia also being reason good and all of our CVS are within are contained under 10 or or 20% and one last thing that I want to show here is how does nca4 uh how does nca4 uh is nca4 a significant hit in our uh in our experiment and the volcano plot here shows us that nca4 is significantly upregulated as shown by volcano plot but also you see some other biomarkers that I have plotted in here and that basically serves as like a ground Truth for this workflow um given that we know that this Gene is overexpressed genetically and uh we're able to recover that piece of information out of ffp blocks with in a reproducible manner while achieving good depth and very high uh very fast um acquisition speeds so I want to go over uh what we've done so far are really the korus ultrasonic gor have really simplified the problem the problem of processing ffp samples especially elimin eliminating the need uh to use something as toxic as xylene and that sped up the process significantly especially when we're working with 96 well formats and then this workflow enables tissue to be processed real fast and we expect results to be out in almost 5 days given the speed advantage that we have now with both instrumentation and ffp IAL processing by ultrasonication and the best thing is that this workflow is compatible with different instrumentation so you don't really need the most recent instrument to get good depth as the sample prep has been really optimized to give you reasonable and impressive depth from regardless of the instrument uh that you're using as long as you're using label free analysis and then last I really want to acknowledge uh many people that that got involved in this project um from the broad really shanka John Simone Mike and uh Monty and stepen Carr uh from the kavar team we've received a lot of help in terms of uh diagnosing issues and uh getting the authenication conditions correctly uh setting up the instrumentation and any um all the assistance that we needed to build this workflow and I want to give special thanks to uh Lillian from Thermo um for helping us demo the orbit trap astral as well with these uh samples and for the bandle institute for helping us with a lot of the maccise section that we've done of these F Scrolls and of course ginden uh from Washington University in St Louis and we'll take it into questions from here Mo thank you so much for that great presentation and you too uh it is now time for our live Q&A portion of our webinar so to our audience if you haven't submitted any questions yet please do so now just type them into the ask a question box and click Send or click submit and we will answer as many of your questions as we have time for Mo Deb we have quite a few questions already coming in so I'm just going to dive in and mo let's start with you this question is two parts how was the optimization process and working with Karis to determine the ideal Duty factor in volume settings for your ffp workflow and can you please describe what the optimization process was like um kovarus has provided us with standard uh protocols where we've evaluated our tissue and we've uh tried these first however uh we were in direct communication with the kavar team and uh the way to optimize the amount of protein that was extracted from each uh sample uh was uh in tandem with our communication with cavars what we've done was looking at the duty factor and the volume settings as we did not see complete homogenization of ffp uh Scrolls and that is expected given that tissue can be different and blocks can be of different dimensions so um what we came up as a result here was 50% Duty factor and 150 microl of fuis buffer was optimal to uh achieve the greatest uh protein uh amount of protein that was extracted we've also coupled that with some ID identification um evaluations uh for both uh Duty factors and we didn't see much of a difference so it's a balance of both uh sample preparation and the optimization as well on the sonication side great thank you Mo and I'm gonna get this qu this next question over to you you mentioned scalability as one of the benefits when using kovarus have you thought about taking that further and automating your ffp workflow yes so for now we're using a semi uh we do some semi-automation by relying on the open Tron uh automated liquid handling and for many people that are involved in label free analysis and especially with tissue of such background it is challenging to do a lot of manual pip petting a 96 well format especially if you have to deal with different volumes so what we do is the open Tron helps us significantly by uh using custom CSV input files where we would assign what volume is going into each well now the other thing that we also do is we use the plate based estrap so that we can speed up the digestion and we'd be able to get away with multi- channels um however I don't see I mean I can I can see that this workflow can be fully automated if it needs to go down to that path with both Karis and uh some robotics on the [Music] side and Mo I'm going to throw another one at you this one has a few parts as well how do you think kovarus workflow compares to the traditional ffp extraction methods is it easy to follow does it require a lot of training and were results consistent end to endend from end user to end user absolutely um the traditional workflow relies on xylene so that's already a toxic chemical to work with but also um it's much more manual will work compared to what we're doing now um being able to process and transfer tissues uh transfering tissue into right into the plate is really helpful here and um for anyone who's macro dissecting it's much easier to just you know um take the regions of interest and then transfer that into a wet environment which is the kar sis buffer and then right right after the process is complete you would just seal that plate and store it at ADC um you've eliminated days of work um by just using the kar setup rather than doing the dewaxing and homogeneization of each sample [Music] individually thank you Mo dab I'm gonna jump over to you can your workflow also be used for intact protein purification uh yeah that's a good question and the answer is yes uh ideally speaking um if it is if the protein is not necessarily cross-link into a certain Matrix it is you can potentially use it use the technology for unhooking or extracting the proteins and depending on the buffer of choice you can actually put it in a um denaturing non- denaturing buffer so that you can ensure it's uh Native if not intact structure uh if it is in a matrix like ffp where it's cross-link when you decross link it it's more than likely that you not going to retain its native structure but if you're talking about intact proteins yes only the buffer section will have to be different necessarily and you do not continue forward with the whole workflow of purification and digestion thanks Deb now let's talk about kits can the kit components or methods be optimized to accommodate higher starting amount of type of protein so this these kits that I showed in my presentation will not necessarily accommodate something that is significantly different or higher but we do have workflows I also showed a one particular slide that talked about same type of Matrix but different numbers of cells or different amounts of uh fresh frows and tissues so we can address different input amounts with different workflows the kits per se ask for a range like ourselves talk about any between thousand to half a million cells if somebody's talking about doing two million cells it's probably going to go to a different workflow which we can also support great now Deb we have a few questions similar to this and we have some attendees considering several kits and workflows that exist for protein purification where and how does your AFA enabled workflow work better yeah I mean that's a particularly that's the a very overview uh kind of an answer that I can think of uh that you know to begin with most of the extraction protocols that are there and most data also testify to that that most of the extraction protocols focus on getting uh proteins out without paying attention to uh it's like a one size that fits all kind of an approach so it doesn't necessarily say that oh I don't need to hit it with this much of power if I'm trying to Li Cells versus if if I have an ffp sample or versus I have a skin tissue so that's where the ability of um controlling the power which you get when you're are operating with an a technology and then the whole workflow gives you better specific optimal uh functioning capabilities to extract as much as you can of the proteins followed by the one plate capability where you can actually do the whole workflow of protein extraction p ification and digestion in the same plate and the expedited features those are all unique capabilities and unique benefits which you're enjoying from a non-invasive uh energy thank you dub now is the kit suitable to digest peptides and Pro or proteins without changing the cality of the amino acids is the kit suitable to digest peptides without changing the chirality of uh we have not necessarily tried or tested it because essentially it's looking at H protein digestion so it Cleaves using the very standard enzymes so if you are looking at the same lysine Arginine residues that you know tripon would go after um you know I would say uh it wouldn't necessarily cause any significant changes to the chirality we haven't really gone into the depth of looking into small peptides and digesting them using this because uh that is not necessarily what most people do yeah we're past our time but I want to squeeze in a few more questions so how does AFA enable digestion ensure better reliability of digestion so the hypothesis is that um the low power pulse during the time of digestion incubation actually um opens up the hydrophobic core of the proteins making it a little easier for the enzymes to have access to the hydrophobic cores so that way it can actually do its job while it is still being active and it also in in in the sense it expedites the enhances the whole process so that's the hypothesis and that's exactly what the micromixing is supposed to be doing so um in other words these onbe or off bead digestions ensure uh not just the speed of digestion but also ensure that the enzymes do not necessarily cleave at the wrong sides and there is enough tumbling of the molecule during homogenization that exposes the right places for digestion thank you Deb and let's wrap with this final question do you also have established workflows for fresh frozen tissues yes we do have workflows for fresh Frozen tissue one of one of the slides in my presentation actually showed that um we do have fresh Frozen tissue uh where we actually have specific consumables also uh which has which comes in with the bead uh with one bead that is very capable of actually addressing up to you know 10 milligrams of tissue and homogenize it using one of our um Flagship instrument and going through the whole process of purification followed by digestion so we do not necessarily have a kit for uh fresh frozen tissues but we do have workflows that work for multiple different types of tissues thank you Deb Mo for this great Q&A I do want to thank you both for your time today and for your important contributions do either of you have any final comments for our audience I hope everybody enjoyed um the talks and I particularly enjoyed listening to more so it was very insightful lots of amazing data uh so um I hope everybody also uh enjoyed the talks and U also have a few thoughts to take back with them as to when they face their next complex Matrix and they are trying to get proteins and propeptides out of it that they would think about you know Innovative creative ways by which they can maximize efficiency and TR yeah and I'll add to that I mean it's really exciting to see that we're able to process ffb tissue um in such a high throughput fashion um we're really excited to see what biology we're going to uncover out of this workflow and um please reach out there's any questions gentlemen thank you both so much again we also want to thank clabots and our sponsor Karis for underwriting today's educational webcast now before we go I do want to thank our audience also for joining us today and their interesting questions we had quite a few questions that we weren't able to answer due to time constraint so those questions additionally along with the on demand questions they will be answered via the contact information you provided at the time of registration today's webcast can be viewed on demand and labroots will alert you via email when it's available for replay we encourage you to share that email with your colleagues who may have missed today's live event to all our friends out there thank you for joining us have a a great day everyone bye-bye thank you