Proteome Sciences Share Discussion Threads

[monte1] 11/3/2021 12:56

C’mon the PRM.

[tom barnaby] 11/3/2021 12:56

Noted monte1.


vbrs
AngelMarbles

[monte1] 11/3/2021 12:54

I think that posting regarding bombed out AIM pharma dog stocks on one woefully formatted freebb is quite enough thanks.

[elpirata] 11/3/2021 12:46

If you have been affected or traumatised by any of the issues raised in this free bb the following organisations may be able to provide help and support;

*gamblers anonymous
*tourettes helpline
*UK Mathematics Trust

[monte1] 11/3/2021 12:38

Stick with me Tom and ye will be farting through silk in next to no time.

[tom barnaby] 11/3/2021 12:37

Some posters who pay a subscription and who, therefore, I cannot moderate, are, IMO, disruptive and do not contribute to the discussion of Proteome. I have filtered them, perhaps others would like to do the same.

Monte1

[monte1] 11/3/2021 12:36

I shall commence work with other passionate holders to devise a comms strategy to extol the benefits of this wonderful stock. Hopefully I can persuade the avatar ‘muttlly’; to articulate the case for investing.

[tom barnaby] 11/3/2021 12:25

Avatars will recall that the last time monte1 threw some fruit machine money at this POS he came out a winner.

Fill yer boots folks!

[tom barnaby] 11/3/2021 12:22

Hells teeth!

[bluemango] 11/3/2021 12:10

Monte

Well done. There's a few club rules you need to be aware of, now you're in.

1. Don't tell the missus.
2. Keep going until you've staked way more than could be considered sensible.
3. Be prepared for an approximate 20 year wait/timescale.

[elpirata] 11/3/2021 11:53

hands up who has stolen monte1's log in

[monte1] 11/3/2021 11:51

This may give avatars a right larf.

For some unfathomable reason, I have just taken 40,000 shares in this shower. No. I can’t explain it either.

40k at 4.09.

Of course I am already down a ton due to a spread wider than the Clyde Tunnel.

For the avoidance of doubt, I still think this is a complete POS.

[elpirata] 11/3/2021 10:23

that didnt take long for a cache copy to appear on the net...bullish?...you decide


NEW YORK – Recently developed methods for automating isobaric labeling workflows aim to streamline multiplexing of proteomics experiments.

The approaches, developed separately by life sciences firm Calico and proteomics sample prep company PreOmics, could help drive uptake of isobaric labeling and Thermo Fisher Scientific's TMTpro label reagents in particular, which allow multiplexing of up to 16 samples.

As data-independent acquisition (DIA) mass spec workflows have advanced technically and grown in popularity, some researchers have suggested that isobaric tagging approaches like TMT labeling may see reduced uptake.

However, recent advances in mass spec instrumentation and new TMT reagents and methods have boosted the technique's utility. The ability to automate the workflow could further enhance its appeal.

Isobaric labeling (of which TMT is the most popular commercial version) uses stable isotope tags attached to peptides of interest to enable relative or absolute quantitation of proteins via tandem mass spectrometry. Digested peptides are labeled with tags that fragment during MS2 to produce signals corresponding to the amount of peptide present in a sample. The approach is commonly used to multiplex samples, which improves throughput and reduces variation.

Fiona McAllister, principal investigator, proteomics at Alphabet-subsidiary Calico, said that her lab considered using DIA for its large-scale studies but determined that "for very large cohort studies in the thousands [of samples], the time savings with TMTpro is unbeatable."

She noted that run times for a single-shot TMT experiment is longer than for a DIA experiment, but the ability to multiplex up to 16 samples in a run substantially outweighs that factor. She and her colleagues calculated that analyzing 1,000 samples would take around three months of non-stop mass spec run time using DIA methods compared to around 11 days using TMTpro.

McAllister added that the RTS-MS3 real-time search method developed by Harvard University professor Steven Gygi (in whose lab McAllister was a post-doc) and using Thermo Fisher's FAIMS ion mobility device had allowed her team to "dig much deeper" into samples without needing fractionation. She added that she considered another advantage of TMT the fact that, if fractionation is needed, "TMT samples can be easily fractionated without a huge time penalty compared to DIA."

Sample prep, however, remained a major challenge, McAllister and her colleagues noted in a January Journal of Proteome Research study detailing their development of an automated workflow for plasma proteomics using the TMTpro reagents (which Thermo Fisher licenses from UK-based proteomic firm Proteome Sciences.)

"The standard TMT sample preparation protocol is complicated, with more steps than label-free workflows," they wrote, noting that "the main barrier to performing large-scale studies using TMT is sample preparation since the labeling chemistry is very time-consuming to perform manually."

They added that, "while there have been multiple automated sample preparation platforms for label-free proteomics reported," only one such platform existed for isobaric labeling: PreOmics' PreOn system.

In fact, McAllister said that PreOmics released the PreOn system while her team was in the middle of developing its automated TMT method, meaning there were no automation options when they began their work. To address the problem, they devised a system they called the AutoMP3 platform, which uses a Hamilton Vantage liquid handler to process samples in a 96-well plate format. Using the AutoMP3 system to prep TMTpro experiments, the Calico researchers found they could prepare 96 samples in two days, five-fold faster than the 10 days they said manual preparation would have taken.

One of the biggest challenges to automating the TMT workflow, McAllister said, was the large volume of reagents involved in running a 16-plex experiment and the fact that such volumes are not compatible with 96-well plate formats.

"This was a huge barrier," she said, noting that, ultimately, Aleksandr Gaun, a senior research associate at South San Francisco-based Calico and first author on the JPR paper, devised a method in which samples were split between multiple wells to allow lower volumes per well.

"We were initially concerned that extra variability and loss could be an issue, but after extensive optimization, this performs extremely well in our hands," McAllister said.

Another challenge to automating TMT workflows is the fact that these labeling reagents "are very volatile," said Russell Golson, chief commercial officer at Martinsried, Germany-based PreOmics, which launched its PreOn proteomics sample prep platform in May 2019. Last year, the company updated the system to work with the TMTpro reagents, which upped TMT multiplexing from an 11-plex to 16-plex.

The volatility of the reagents means that the labels can't be added at the beginning of the sample prep process along with the rest of the reagents, Golson said. "So we have basically a pause step so that when the robot gets to the 'add TMT stage,' it pauses and alerts you and then you add the TMT."

The Calico researchers likewise highlighted this step as difficult to automate, and Harvard's Gygi, who was not involved in either project said that the volatility of the TMT reagents meant that "you are likely limited to semi-automated workflows where you stop the work and add the TMT reagents at that stage — usually manually."

Golson said the effort to automate the process emerged from discussions with pharmaceutical and other industry customers whose scientists were asking for increased access to mass spectrometry.

"Basically what people were saying to us more and more was that they were being pushed by biologists who wanted more access to mass spectrometry, but their cores couldn't prepare all of these samples," he said. "They wanted to be able to have a small benchtop [instrument] that they or a technician could put their samples on and run through a dedicated [sample prep] menu and press go, and then the mass spec specialist could come pick these up off the [sample prep] robot and know they were in great condition to inject into the mass spectrometer."

Golson said that a major focus of PreOmics' automation effort was paring down the number of steps involved by improving the compatibility of the different stages to eliminate as much clean-up as possible.

He noted that many proteomics workflows use "homebrew" methods developed by individual labs.

"One of the main problems with homebrew is the lack of chemical compatibility between one step and another, and that means a lot of transfer steps and clean-up steps between phases," he said. "That brings a longer cycle time, and it also means that if you have small, precious samples, you have four or five chances to lose that precious sample along the way."

He said that by reducing these gaps in compatibility, PreOmics had moved from an eight-step protocol to a three-step protocol. The PreOn system can prepare a 16-plex TMT sample in about two hours.

Golson said the company's customers for the system are largely biopharma and pharma firms doing large-scale mass spec experiments. He said that the company has also received interest from academic core facilities.

Brett Phinney, director of the proteomics core facility at the University of California, Davis, said in an email that his lab "would love to try the PreOmics kit," though he added that the cost made him reluctant.

Golson said that the PreOn platform costs around $95,000. Researchers have to use the company's reagent kits on the system, which cost around $20 per sample, not including the cost of the TMT reagents themselves.

TMT labeling has also become a key technology for single-cell proteomics, where it enables experiments using a carrier sample to boost the signal of peptides present in extremely small target samples. Neither the AutoMP3 nor the PreOn approaches are aimed at the single-cell proteomics space, but in January researchers at Brigham Young University published a study in Analytical Chemistry detailing an automated version of their previously developed nanoPOTS (nanodroplet processing in one pot for trace samples) sample prep technique.

The nanoPOTS (nanodroplet processing in one pot for trace samples) platform shrinks sample processing volumes down to less than 200 nanoliters to limit sample loss and speed trypsin digestion, which has slow kinetics at small sample volumes. The automated version, called autoPOTS, uses a robotic pipetting platform and autosampler to automate the nanoPOTS process.

Gygi said that automation becomes more important as researchers begin to move to experiments running hundreds of samples or more. He suggested that labs have not previously implemented automation for TMT sample prep in large part because they were not running such large-scale experiments.

"It seems that for most of the work we do, we are dealing with less than 16 samples — certainly less than 100," he said. "We can usually pack all of the replicates, time-series, dose-response, et cetera types of experiments into a single 16-plex. You don’t need a plate-based method for this. This even holds true for up to around 100 samples. The mass spectrometer is the bottleneck and not the prep. However, this changes as you move beyond 100 samples."

"Certainly, for large-scale studies, the automation strategies could be really important," he added.

That suggests automation could become more relevant as proteomics continues to move in the direction of larger experimental cohorts. That is particularly true of the single-cell space given the large number of cells required to collect good data on questions of interest.

Gygi also said that the development of paramagnetic bead-based single-pot solid-phase-enhanced sample preparation (SP3) methods had also allowed for improved automation of steps like protein precipitation.

The SP3 approach was first published on by researchers at the European Molecular Biology Laboratory in 2014. Last year, PreOmics entered into a licensing agreement with EMBL for the technology.

"We didn't have a good way to automate until fairly recently," he said

[elpirata] 11/3/2021 10:02

Galaxy CCRO?

whatever happened to Randy et al

[monte1] 11/3/2021 09:41

Good luck with that 1xtrader

[1xtrader] 11/3/2021 09:39

Hope one of these big American companies will see Proteome Sciences and make an offer

[colinhy] 11/3/2021 09:06

Investor Interest in Proteomics Rising on New, Improving Technologies

Mar 10, 2021 | Adam Bonislawski
Premium


NEW YORK – Investor interest in proteomics appears to be on the rise as over the last year several private firms have announced large fundraising rounds and a number of other companies have made plans to go public.

At the same time, some more established life science companies have highlighted their exposure to the space, with, for instance, Bruker making proteomics a central pillar of its growth strategy.

The factors driving this uptick in investor interest aren't entirely obvious. The mass spectrometry-based technologies that have dominated the field for the last two decades continue to steadily improve, but these improvements remain more incremental than groundbreaking. And while a number of startups are applying new technologies to the challenge of measuring proteins at proteome-scale, these technologies are for the most part still unproven.

"I can tell you that, yes, there is an increased level of interest in proteomics," said Puneet Souda, a senior research analyst at SVB Leerink covering life science tools and diagnostics.

"It's not something that I would have anticipated," he said, but he noted that the relative maturity of genomics might be driving investors to take a look at proteomics "potentially as the next frontier."

As proteins are the primary functional molecules in the body and a common drug target, the case for focusing on proteomics is compelling. The field is considerably more challenging than genomics, however, given the enormous dynamic range across which proteins are present in the body and the lack of a technology analogous to PCR that can be used to amplify low-abundance molecules.

There are around 20,000 proteins in the human body and perhaps 10 times as many different forms of those proteins. Expert proteomics lab can typically use mass spec to measure in the range of 5,000 to 10,000 proteins in cell lysate and 300 to 1,000 proteins in plasma. Affinity-based platforms from companies like Somalogic and Olink can measure, respectively, 7,000 and 1,500 proteins in blood, though in the case of the Somalogic platform there are questions about how specific its measurements are to particular proteins.

Proteomics technologies, particularly mass spec-based platforms, are also expensive and require highly expert personnel to run, which has limited the field's reach.

Souda noted that mass spec technologies are improving, with newer platforms like Bruker's timsTOF Pro offering advances in depth of coverage and throughput.

"We're getting [mass spec] technology to a point where we are delivering several hundred to maybe a thousand or so proteins in a plasma proteomics experiment," he said. "We have gotten to this point largely off of improvements in LC-MS technologies, mainly Thermo [Fisher Scientific] Orbitrap at first and now Bruker's timsTOF."

However, he said that he believes the field is really looking for "improved technologies that can in a more accessibly way deliver on the promise of the proteome."

Improvements on the mass spec side will continue to drive proteomics forward, Souda said, but, he added, "in order to really solve the proteome problem, one has to think outside the box."

That is what a series of new entrants onto the proteomics market aim to do. Companies like Seer, Nautilus, Quantum-Si, Encodia, and Erisyon are developing non-mass spec approaches to tackling the proteome. These newer firms with their novel technologies are behind much of the recent investor excitement in proteomics, suggested Hesam Motlagh, chief of staff at venture capital firm Khosla Ventures. Khosla's investments in proteomics include San Diego-based diagnostics firm Genalyte and health monitoring and early detection firm DiscernDx, which purchased the assets of Applied Proteomics, which was also backed by Khosla.

"We are much more interested in things that could make like an order of magnitude improvement, and I think that is the way a lot of venture capital firms and a lot of investors think about where they would like to park their money," he said. "Yes, there have been improvements to mass spec… but overall I would describe them as incremental, and you still need to have a fair share of technical knowledge and resident expertise to be able to do proteomics with mass spec."

"So the exciting thing that seems to have been doing well, at least on paper right now, is, ok, if not mass spec, then what?" Motlagh said.

Redwood City, California-based Seer (where Motlagh was a senior corporate strategy and finance analyst from 2019 to 2020) went public in December through a $175 million initial public offering that was accompanied by a separate private placement of $135 million of Class A common stock.

The company's Proteograph system uses nanoparticle-based enrichment of proteins in samples like human plasma to enable deeper coverage in proteomic discovery experiments. The platform is based on the observation that when incubated in a biological sample, nanoparticles collect proteins, which form a "corona." Given this, nanoparticles can serve as an enrichment tool, allowing researchers to pull proteins out of a sample, which they can then identify and quantify using technologies like mass spec or other detectors.

Seer went public at $19 a share and hit a high of $86.55 per share in January. It has since fallen back into the $40 to $50 range and Wednesday afternoon was trading on Nasdaq at $44.20 per share.

In February, Seattle-based proteomic start-up Nautilus announced that it plans to list on the Nasdaq through a merger with special purpose acquisition company Arya Sciences Acquisition Corp III. The company has entered a definitive merger agreement with Arya and is expected to receive $350 million in proceeds through the deal, including a $200 million private investment in public equity (PIPE) transaction at $10 per share from investors led by Perceptive Advisors, an affiliate of Arya III's sponsor. The company also counts among its investors Bezos Expeditions, Vulcan Capital, and Andreessen Horowitz.

Cofounded in 2016 by Patel and Chief Scientist Parag Mallick, an associate professor at Stanford University, Nautilus has disclosed little publicly about its technology beyond the fact that it uses machine learning to make protein identifications based on measurements of multiple parameters describing the target molecules.

Also in February, Quantum-Si announced plans to list on the Nasdaq via SPAC. The Guilford, Connecticut-based firm will merge with HighCape Capital Acquisition Corp and receive $425 million via a PIPE transaction from investors including Foresite Capital Management, Eldridge, accounts advised by ARK Invest, Glenview Capital Management, and Redmile Group.

Founded by next-generation sequencing pioneer Jonathan Rothberg, Quantum-Si has, like, Nautilus, provided little public detail on the specifics of its technology but said that it uses a sequencing approach it calls Quantum Si Time Domain Sequencing combined with a semiconductor sensing device to sequence proteins, including post-translational modifications, at the single-molecule level.

Of the three firms, only Seer has published peer-reviewed data on the performance of its platform. None have yet launched their systems commercially.

Souda suggested the companies were going public despite being early in development in order to take advantage of the current investing environment.

"Investor appetite for life science tools technologies is fairly robust right now," he said. "Genomics has delivered, and I think that that has given [investors] some comfort that as long as there is fundamental innovation and that innovation is supported by investment, we are going to see products that are differentiated and help solve key problems that currently challenge the [proteomics] field. So proteomics is being looked at as the next opportunity."

Souda added, though, that ultimately, "science is important and data is important, and we need to see data here in order to get more convinced that these companies are truly going to resolve the proteomics challenge."

While these newer proteomics firms are not mass spec-based (though Seer's Proteograph system will likely be used in combination with mass spec at least in the near term), they have some connections to the mass spec-based proteomics world. Seer, for instance, counts Steven Carr, senior director of proteomics at the Broad Institute among its scientific advisors. Nautilus's Mallick is one of the main developers of the ProteoWizard mass spec proteomics software platform and the company includes mass spec proteomics pioneer Ruedi Aebersold as a member of its scientific advisory board.

The move to go public isn't limited to new proteomics outfits. Last week, Swedish proteomics firm Olink filed with the US Securities and Exchange Commission for an initial public offering of American Depositary Shares (ADS) through which it will list on the Nasdaq Global Market.

Investor appetite for proteomics is also apparent in the $214 million Series A round Boulder, Colorado-based Somalogic closed in December and in a recent $250 million public stock offering by Billerica, Massachusetts-based firm Quanterix, which last month saw its stock hit an all-time high of $92.57, though it has since retreated from that peak and on Wednesday afternoon trading on Nasdaq was at $62.08 per share.

"There are some really cool tools coming out of basic science that are within striking distance of reality," Motlagh said. "It's definitely a trend, I would say. It's not just a blip on the radar."

[monte1] 11/3/2021 08:50

Good morning all btw.

[monte1] 11/3/2021 08:50

That is no way at all to ‘speak’ about the Richards, no way at all.

Nor of any avatars for that matter.

[stocktastic] 11/3/2021 08:29

"PLEASE take some notice of us? Please? Anyone?"

A grown man desperately seeking attention in the way he does, is quite telling