A busy summer for Nonlinear in Europe

The busy European summer conference season is almost upon us, so I’d just like to share with you all of the opportunities you’ll have to meet us and learn about the Progenesis range.

IMSC 2014

It all kicks off in the last week of August with the bi-annual International Mass Spectrometry Conference (IMSC), this year held in the beautiful city of Geneva at the Centre International De Conférences, Geneva (CICG). IMSC organisers are expecting around 1200 delegates to attend the week-long conference, so we’re anticipating another non-stop meeting. Once again, we’ll be busy demonstrating the new Progenesis QI range, as was the case at ASMS in Baltimore and then again at the Metabolomics 2014 conference in Japan.

Metabomeeting 2014

Shortly after IMSC, we are due to attend what’s being touted as “the metabolomics research conference of Europe”, Metabomeeting. This is being held at another prestigious venue: the Royal Institution in London. The organisers are expecting 300 attendees and are aiming to make the event as valuable as possible to both industry and academia.

Technology seminars

In September, we will be co-hosting a series of technology seminars with Waters, entitled Frontiers in metabolomics & lipidomics. These will take place at select European research hub locations, with the aim of the seminars focussed on discussing how new tools work together to provide superior workflows for lipidomics and metabolomics analyses.

Solutions will be presented from:

  • Small molecules research scientists talking about the workflows they are implementing to overcome challenges,
  • Waters separations science specialists discussing the novel analytical technologies to address these same challenges, and
  • Progenesis QI specialists showing off the objective and robust data analysis workflow designed to overcome small molecules research challenges

The first two locations of the workshops have been confirmed, with details on more venues and speakers to follow:

  1. On the 15th September, the technology roadshow will kick off at VIB department of Plant Systems in Ghent, Belgium – Geert Goeminne works in the Bioenergy group at VIB and will be delivering a talk on his work using LC-MS for metabolic profiling of plant energy systems.
  2. On the 16th September, a second seminar will be held at Aix Marseille Université for a meeting hosted by Jean-Charles Martin of the French National Institute for Agricultural Research.

We will have other meetings across Switzerland and Germany, with more information on dates and venues to come.

HUPO

The last conference of the summer/autumn for us will be the 13th Human Proteome Organisation World Congress (HUPO), in Madrid. HUPO really takes Progenesis back to its roots as this is the annual proteomics event which brings everyone in proteomics together. We attend every year as it is an ideal opportunity for us to catching up with a lot of old faces and to meet a few new ones too.

If you’re planning on attending any of these events or would like more information on how to book on to the technology seminars, please do get in touch. We hope to see you soon! :)

Progenesis QI: Big in Japan

At the end of June I headed across to Tsuruoka, Japan for the 10th Annual International Conference of the Metabolomics Society along with some of my colleagues from Nonlinear. With metabolomics still being a relatively new field for us, this was only the 2nd time we’d attended this conference so it was interesting to see how many more people are starting to associate the Progenesis name with not just proteomics, but small molecules analysis too.

IMG_20140624_103007

Interestingly for us there were a lot of talks focussed on software – something that came up was the importance of dedicated software testing, which some bespoke solutions lack; an example was made of an institute retracting 5 previously published papers due to software driven errors. One of the benefits of commercial software, such as Progenesis is the availability of a dedicated software testing team – in fact we’ve recently expanded ours.

Another recurrent theme was the challenges scientists face when identifying their metabolites, specifically sourcing suitable databases. It was therefore great to be able to talk people through the approach Progenesis QI takes, including the availability of theoretical fragmentation and the flexibility of what databases can be used.

One of the last talks of the conference was delivered by Matthew Lewis from the Phenome Centre who talked about how they’ve been putting Progenesis QI through its paces with thousands of LC-MS runs with emphasis on stabilisation for large scale experiments. One of the challenges faced is the ability for software to handle large data sets, and at Nonlinear we’ve been working hard to optimise use of the software for large scale experiments and have been pleased to work alongside the Phenome Centre to achieve this.

In the evenings we were free to explore the city of Tsuruoka and everything it had to offer, which was largely lots of games of darts(!), and as expected, some very tasty food.

A night out playing dartsEnjoying the local cuisine

In all the conference was a success, helping us to both spread the word of Progenesis QI and also a chance to listen to what the current challenges are to help guide the development of our next release. If you’d like to try Progenesis QI with your own data, get in touch and we’ll arrange a demo. Until then, sayōnara!

ASMS 2014: There and Back Again

At the end of last week, the Nonlinear team returned from ASMS 2014 in Baltimore, MD. Six of us attended: Mark and Jon from our US sales team, Ian and myself from the development team, plus Rob our Product Manager and Ronan our boss. With the exception of a spectacular thunderstorm on the evening of our arrival and a couple more on our final evening, we enjoyed fantastic weather and a great welcome in Baltimore.

It was my third ASMS after Minneapolis last year and Vancouver in 2012, but our first as part of the Waters Corporation. Being part of Waters meant a few changes: under ASMS rules, we weren’t allowed our own booth in the exhibition hall; and we attended the Waters Sales and User meetings before the conference properly started on Sunday evening. So for us, the conference started on the Saturday morning with the Users meeting which consisted of presentations by a mixture of Waters staff talking about new instruments and customers discussing their scientific endeavours. My personal highlight was a very entertaining and informative keynote talk by Jeremy Nicholson of Imperial College London on the topic of population scale phenomics and the iKnife.

On Sunday, the sales meeting gave us an opportunity to catch up with colleagues from the US and elsewhere to find out about the new developments in the wider Waters organisation whilst simultaneously informing the Waters field teams on what was going to be in the next versions of Progenesis QI and Progenesis QI for proteomics. After the sales meeting, Ian and I headed over to the hospitality suite to install our software and datasets onto the PCs, ready for Monday morning’s demos.

Our stands in the Waters hospitality suite

Monday was our first of three long days in the hospitality suite, demoing Progenesis QI and Progenesis QI for proteomics to existing and prospective customers. We had a shorter daytime session on the Monday to break early for the Waters press conference where we unveiled the exciting news of what’s coming in v2.0 of Progenesis QI for proteomics.

We also had our Scientific Advisory Board meeting during the break in the Waters hospitality meeting room in the Hilton hotel which was on the 15th floor with a fantastic view of the baseball stadium at Camden Yards:

Oriole Park at Camden Yards

The meeting was a great one, with members attending ASMS present in person and a couple of advisory board members dialling in from around the world. We had a very interesting discussion on present and future scientific advancements in the fields of proteomics and metabolomics and how Nonlinear products could help scientists with forthcoming challenges. After the Scientific Advisory Board meeting, half of us went to our customer dinner with some of the SAB members and a few other customers. Meanwhile, Jon and I went back to the hospitality suite for the evening shift, which involved a surprising number of customer demos, despite the lure of food and drink available at each of the suites!

Our three days in the hospitality suite were very busy, with a constant stream of interested scientists and existing customers wanting demonstrations of both the existing software and the new features that were coming in the next versions. On Wednesday morning, we also had a well-attended breakfast seminar on ‘Mass Spectrometry & Informatics for Molecular Phenotyping’ during which Rob and Mark talked about both Progenesis applications and how their results could be combined to give multi-omics pathways information in the next versions of the two products.

Now that we’re back in the office and over the worst of the jet lag, we need to crack on – working towards the Progenesis QI for proteomics v2 release and getting the new features we demonstrated into the hands of our customers. If you’d like to try Progenesis out for yourself, please get in touch.

Revealed: new features coming for Progenesis QI for proteomics v2.0

Yesterday, in Baltimore, Maryland, at the 62nd American Society of Mass Spectrometry (ASMS) conference we unveiled the exciting new features that we’ve been working on for the next release of Progenesis QI for proteomics. For those of you who missed the press release, here’s another chance to see what’s coming:

Pathway Analysis

Progenesis QI for proteomics v2.0 will include direct support for export to third party Pathway Analysis programs such as IMPaLA and PANTHER to allow you to put the protein differences in your data into a biological context in just a few clicks:

test

QC Metrics

No more wasting your valuable time performing data analysis on sub-optimal LC-MS data with the new QC Metrics, including chromatographic peak width, feature dynamic range, precursor mass error, missed cleavage count, peptide per fraction count, and many more:

image_5image_6

Automated Data Processing

With the new automation functionality you can set up your analysis to run right from the beginning at Import Data all the way to a completed peptide search without any user intervention – perfect for overnight processing.

“Hi-N” Quantification

The support of Hi-3 quantification for Waters MSe data has been extended to allow for absolute quantification of data from all the vendors we support as well as with the option to define the number of peptides used in quantification.

So if you’re at ASMS, come and see us in the Waters Hospitality suite, Ballroom 8 at the Hilton Baltimore where you can book a demonstration with some of the developers themselves. If you’re not at ASMS, get in touch and we can arrange a demonstration using your own data.

Talking LC/MS vs. NMR with the big cheeses of French metabolomics

standI’m pleased to report back after my first conference and first visit to France, having just attended The French Metabolomics and Fluxomics Network (RFMF) meeting. This is a key meeting for metabolomics research in France, bringing together both young and seasoned scientists to discuss methods and analysis in metabolomics research, which in France is heavily focussed on plant science.

There was a packed lecture schedule interspersed with short lunch breaks, and of course, special breaks to eat the plentiful amounts of cheese available. At the cocktail reception on the first evening my lovely colleague Agnès had great reason to laugh as she saw the look of horror on my face – the result of a combination of having just taken a bite of foreign fromage that exploded with insulting flavour and the perfect timing of Agnès commenting, “This is really special cheese, it’s 10 years old!”. There was yet more foodie fun to come…

From the research posters and chatting to delegates, it was easy to see a clear technology split between NMR and MS techniques. NMR is especially suited to analysis where sample availability is fairly generous. One of the senior scientists and organisers of the conference told me that there are around 200,000 variables (possible metabolites) in plant samples; being an NMR scientist, he mentioned that no one in his lab actually uses NMR, but rather they use LC-MS. In his opinion, other NMR metabolomics research scientists in France are going to have to look toward LC-MS if they are serious about doing research on plants, as metabolomic profiling of plants is too complex for NMR currently. Another challenge that was creeping up in my conversations with delegates was on the limited availability of suitable spectral libraries to study plants, so these researchers were pleased to hear about the capabilities of Progenesis QI being able to query existing databases, building up fragmentation databases and being able to do theoretical fragmentation analysis to gain confidence and to fill in the gaps.

On the final night, the conference committee organised a meal at Paul Bocuse’s restaurant, the prestigious L’Abbaye De Collonges. This was not a typical restaurant; in fact, it was closer to a carnival experience with musical puppets and waiters running around to a countdown… I’ll let the pictures tell the story, but it was fair to say that the food was opulent & highly calorific! We all left beyond the point of being satiated :)

Restaurant

cakeIMAG0299

The conference was a successful trip for us as we met researchers who were pleased to hear about Progenesis and how it could help them overcome some of the identification challenges they were facing in their metabolomics LC-MS analysis. If you are also finding many challenges with your LC-MS small molecule identifications, get in touch to find out whether Progenesis QI can help you too.

More new faces at Nonlinear

We’ve had a bit of a recruitment boom here at Nonlinear Dynamics over the past few months – firstly with the expansion of our software development team back in March – and now we’re pleased to announce the arrival of a new senior applications scientist and a new software tester.

DJ-2Dave Jackson has 14 years of experience in the proteomics sector, primarily in the 2D-gel field with emphases on methodological improvement, standardisation, analysis and biomarker discovery. Strictly speaking, this isn’t the first time we’ve shared an office with Dave as he used to work for Biosignatures Ltd, a spin-off company from Nonlinear who were fully separated following our acquisition by Waters, so it’s nice to have him back. :) He’ll be working in applications science with a particular focus on experimental design, analysis, and QC. When not found sampling the region’s ales, Dave likes to spend his time running, partly to work off the stress of being a Hull City supporter.

 

CM

Colin McKay has been a software tester since 1998 with experience in the electrical, financial, and health sectors. In fact, Colin is another person to fly the nest and come back, as he previously worked for us between 2002 and 2006 where he focussed on the testing of our 1D and 2D gel software applications, which are now developed and distributed by TotalLab. Nonlinear has a habit of luring people back! In his spare time Colin enjoys American football, watching films (particularly world cinema and horror) and amateur photography.

 

 

Interested in a career at Nonlinear Dynamics?

If Nonlinear Dynamics sounds like somewhere you’d like to work and you think you can strengthen our team, you might want to check out our recruitment page.

Edible oils and Progenesis QI at the AOCS annual conference

We recently attended the 105th AOCS Annual Meeting and Expo in beautiful San Antonio. Thanks to gloriously sunny weather, the San Antonio Spurs NBA basketball winning the playoff series against their instate rivals the Dallas Mavericks, The Alamo, and the Mexican-American holiday Cinco de Mayo there was plenty to see and do (aside from the conference of course!).

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Moving on from all the excitement outside of the conference, the meeting was all about the business of edibles, but with Texan flair. We focused mainly on the analytical section of the conference and met with several researchers performing oil analysis. Currently many oil scientists still perform gravimetric and spectrophotometric work, but they’re now looking for the next step in using MS techniques to not only characterise compounds, but to also look at the compounds that are changing and the differential expression.

Giuseppe Astarita of Waters gave a talk on “Novel Orthogonal Technologies in support of Mass Spectrometry based Lipid Analysis,” providing the audience with an understanding of the use of LC-MS techniques alongside Progenesis QI and how this can be used for lipid analysis to gain a greater depth of information than traditional techniques.

The AOCS annual meeting and expo gives this industry and community a chance to connect with vendors like Waters Corporation and Nonlinear Dynamics Limited and those scientists performing fats and oils analysis – it’s an exciting time for them as they begin to move into the area of MS analysis and we’re very happy to be part of it.

The next big event for us is ASMS, this year hosted in Baltimore in just over a month’s time – I’ll be there along with a number of my colleagues, so hopefully we’ll see you there :)

Peaks and valleys: coast to coast with Nonlinear Dynamics

Here at Nonlinear Dynamics, we like a challenge. So when John Renney, our Business Analyst, suggested that we cycle across Britain for charity, hands went up to volunteer!

Volunteering is central to the charity that John supports: the Tony Blair Sports Foundation (TBSF) who train adult volunteers to become sports coaches in North East schools. Amazingly, it takes only £250 to train one coach, so each of us taking part aimed to raise that amount ourselves.

After months of preparation, we assembled at Whitehaven on the Cumbrian coast, dipping our wheels into the Irish Sea as is customary on the sea to sea route, before setting off in the sunshine with the wind behind us.

Day 1 was spectacular, with breath-taking views of the English Lake District. It was a treat of a cycle ride and, despite a few of us making some wrong turns, we all made it to our stopping point for the night at Troutbeck in time for dinner.

Cycling through the Lake District

The next day was the toughest with terrible weather, having to cycle across the Pennines into a head-wind through fog and rain – conditions were tough, but we were tougher!  We had a much needed lunch at Hartside Top, England’s highest café, renowned for its views (when it is not shrouded in mist).

Hartside Summit

Then followed further descents and ascents that reminded us of mass spec peaks!

There was much joy when, dropping down out of the mist, we could see our TBSF support team in their white van, marking the end of day 2 – the hardest part was done :) The huge lasagne at The Red Brick Barn in Rookhope revived us nicely and was finished for breakfast the next day by one of our teammates who has a more unusual morning palate.

We were informed by John that, after a short, steep ascent on Day 3, it was “downhill all the way” – a statement treated with slight scepticism from the team. Well, that ascent was tough, with more rain, head-wind and mist; even the first descent to Parkhead station café required pedalling downhill in the lowest gears. John did speak the truth though: it really was downhill for miles and miles and we arrived in Tynemouth, dipping our wheels into the North Sea, once again in sunshine.

Sea at Tynemouth

The trip was a wonderful experience; it brought out real teamwork and kindness and John was a humorous leader who kept our spirits up. We had excellent support from the team at TBSF and enjoyed cycling alongside our friends at TotalLab too. We’re waiting to hear how much we raised — donations are still coming in — but hopefully we’ll reach our target, if not exceed it.

Now we need a new challenge!  Suggestions welcome :)

Improved performance for analysis of high resolution LC-MS data

Analytica 2014 saw the official launch of the new and rebranded releases of both Progenesis QI and Progenesis QI for proteomics. One of the new features shared by both products is the ability to control the noise reduction during data import – something we’ll look at in more detail here.

Big data just keeps getting bigger

One of the challenges with LC-MS data is the sheer size of the files and the demand this makes on your PC’s resources, specifically its RAM. While Progenesis is well-known for its ability to reduce this burden through its use of an intelligent peak-modelling algorithm, the advancement of PC hardware isn’t keeping pace with our demand for higher resolution instruments and the size of data they produce. Analysing such high-resolution datasets can still pose a significant challenge, but Progenesis holds an ace card in the guise of its filter strength setting:

Filter strength dialog

This setting provides the option of applying a noise filter that’s up to 20× stronger than default. While we still recommend carrying out a pilot experiment to determine the most appropriate level for your particular data, we have found that a setting of ×2 drastically improves performance while still giving good coverage of your data.

Seeing the effect in typical high-resolution data

High resolution instruments tend to produce a lot of low intensity, close-to-background signals that usually have no associated MS/MS. After peak picking, the ion map can be a dense mass of blue outlines indicating the ion locations (figure 1).

Ions found using the default filter strength Figure 1. Peak detection on data set using the default import filter strength

Ions found after double the strength of the import filter Figure 2. Peak detection on the same data set using a filter strength of ×2

Increasing the filter strength to ×2 has the effect of filtering out this background, allowing you to complete your analysis with a minimal drop-off in the number of proteins identified (figure 2).

To compare processing performance, we took a subset of files from a larger dataset and analysed them using the default import filter strength and also at a modified import filter strength of ×2. The following table shows the differences between them, giving processing time, RAM used, and the number of ions found at peak picking:

Stage Default import filter Modified import filter at ×2
Alignment (including automated reference image selection) Time taken: 5mins 14s
Peak RAM usage: 3.62GB
Time taken: 3mins 31s
Peak RAM usage: 2.29GB
Peak picking (default settings) Time taken: 27mins 46s
Peak RAM usage: 7.02GB
Time taken: 10mins 22s
Peak RAM usage: 2.97GB
Ions found 78,700 28,117

So, as you can see, both processing time and memory usage can be significantly improved by use of a filter strength more suited to your data. And while the reduction in the number of ions found may look severe at first glance, this is actually a positive thing; those were ions whose signal was at a level that should be regarded as background. Provided you’ve not increased the filter strength too far, the number of proteins identified should be practically unchanged.

Try it on your own high-resolution data

If you’ve got a data set that your PC is struggling with, why not put this to the test yourself; you can find full instructions for the tool in our FAQs. In the meantime, we’ll be busy working on other ways to improve the performance of Progenesis to keep up with the demand for analysis of increasingly complex data sets. :)

Creating custom fragmentation databases using Progenesis QI

One of the major new features in Progenesis QI (the successor to Progenesis CoMet) is the ability to create fragmentation databases from your experimental data, which can subsequently be used to assist identification. This blog post will show you how to start building your own.

Identification phase

The first step in creating a fragmentation database is to analyse an experiment where you have measured ms/ms. This might be an experiment where you have spiked in known compounds with the sole intention of gathering fragmentation data for those compounds.

When you reach the Identity compounds stage, you can search for identifications using a number of search parameters:

  • Neutral mass
  • Retention time
  • Collisional cross-sectional area

You can also use theoretical fragmentation to narrow down your possible identifications and to distinguish structural isomers:

metascope_dialog

Hopefully these search parameters and theoretical fragmentation tools will give you fairly high confidence in the identifications of your most important compounds (especially if you have known spiked compounds).

If you are confident enough with a given identification, you can accept it as the true ID, by clicking the gold star in the possible identifications table:

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The next step is to take your observed fragment spectra for compounds with accepted IDs, and export them to your fragment database.

Export phase

So now you have a set of accepted identifications for your important compounds, which you are confident are correct.

It’s a simple step to export your observed fragment spectra for those compounds to a fragment database (MSP file).

To do this, simply choose the Export fragment database… option from the File menu at the Identify Compounds screen:

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Here, I’m building a database of pain relieving drugs, and I’ve identified Phenacetin and Paracetamol. So, when I click the menu item I’m shown my two accepted IDs:

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I’ve only identified the M+H adducts, but if you’ve identified more than one adducted form, it will be shown in the Adducts column.

So once I’ve clicked Export and chosen a name for my database file, it is exported to an MSP file, which is a simple text-based format as defined by NIST. Here’s what mine shows:

Name: 46506142 (Paracetamol)
PUBCHEM_SID: 46506142
Precursor_type: [M+H]+
Comment: 5.17_152.0704m/z
Formula: C8H9NO2
Num Peaks: 5
92.05 83
93.034 163
110.0606 999
134.0606 30
152.0712 400

Name: 49854487 (Phenacetin)
PUBCHEM_SID: 49854487
Precursor_type: [M+H]+
Comment: 5.16_180.1034m/z
Formula: C10H13NO2
Num Peaks: 7
92.05 79
93.034 135
110.0606 999
138.0919 503
152.0712 67
162.0919 31
180.1025 502

When I did this search, the SDF file I used was from PubChem, so the compounds have been given a unique PUBCHEM_SID. Crucially, when I use this MSP file for searching in future experiments, the fragment information listed here will be associated with any compound that has the same PUBCHEM_SID listed in the SDF file. For example if an SDF file was used which contained a compound with PUBCHEM_SID of 46506142, that compound would be associated with the Paracetamol fragments when searching.

Augmentation phase

You may run multiple experiments, and wish to collect the MS/MS data for all of these into one MSP database.

For example, here I’ve run a second experiment, where I’ve identified Misoprostol with high confidence. Again, I choose the Export fragment database… option from the File menu:

image

Note that here I’ve identified 3 different adducted forms, which will appear in the fragment database if they have associated fragment data. When I click Export, I choose the MSP file I created before, and I’m asked if I want to overwrite the database or append to it:

fragment_export_append

I choose append in this case as I’m gradually building up my drugs database. After the export is complete, my MSP database looks like this:

Name: 46506142 (Paracetamol)
PUBCHEM_SID: 46506142
Precursor_type: [M+H]+
Comment: 5.17_152.0704m/z
Formula: C8H9NO2
Num Peaks: 5
92.05 83
93.034 163
110.0606 999
134.0606 30
152.0712 400

Name: 49854487 (Phenacetin)
PUBCHEM_SID: 49854487
Precursor_type: [M+H]+
Comment: 5.16_180.1034m/z
Formula: C10H13NO2
Num Peaks: 7
92.05 79
93.034 135
110.0606 999
138.0919 503
152.0712 67
162.0919 31
180.1025 502

Name: HMDB15064 (Misoprostol)
HMDB_ID: HMDB15064
Precursor_type: [M+Na]+
Comment: 8.55_382.2734n
Formula: C22H38O5
Num Peaks: 2
199.0733 745.9995
299.1615 581.0762

Name: HMDB15064 (Misoprostol)
HMDB_ID: HMDB15064
Precursor_type: [M+H]+
Comment: 8.55_382.2734n
Formula: C22H38O5
Num Peaks: 3
199.0733 745.9995
299.1615 581.0762
361.2362 544.4017

Note that for Misoprostol my ID has come from HMDB, so the HMDB_ID field contains the unique ID of the new compound. Also note that there are two entries for the two adducts that contained fragment data (the M+NH4 fragment had no associated fragment data).

You can continue to append to a fragment database as much as you like, until you have a complete set fragment data for your particular needs. The next step is to use that database in future searches.

Search phase

Suppose I’m now running a new discovery experiment and I’m just trying to figure out what’s in my sample; I can use my MSP fragment database by choosing it in the Fragment search method of the MetaScope search profile:

image

When I run the search, my fragment database is used:

image

Above you can see I’ve done a search and found a possible ID for Misoprostol. Now, not only have I got a mass error within the threshold, my previously measured fragmentation data also matches very well with what I’ve observed in this experiment. In fact, this ID had been given a fragmentation score of 95.1, giving me further confidence that what I have identified in this experiment is actually Misoprostol.

Summary

I hope you can see that Progenesis QI now offers a very powerful way to create and augment your own in-house fragment databases, based on the compounds you are interested in.

It then allows you to make use of these databases you have built up, to give you more confidence in your identifications in further discovery work.

For more information, see the FAQ page on fragment databases, and if you have a question about this or indeed any other feature, feel free to ask below or get in touch and one of the team here will get back to you.