Dienstag, 2. Oktober 2018

Ionic liquid matrices in MALDI MS


I know that sometimes glyercol is used a liquid matrix in IR MALDI, but I have ever heard about Ionic Liquid Matrices (ILMs) before. These type of matrices are trying to eliminate the drawbacks of commonly used MALDI matrices, which in most of the cases are organic acids, having a really pKa in order to achieved analyte protonation.

ILMs have a low melting point, low vapor pressure and high stability at AP and vacuum. They do not create dangerous fumes and are considered to be a greener technology compared to conventional MALDI Matrices. They do not display crystallization, therefore sample preparation is supposed to be really homogeneous - which is one of the biggest advantages applicational-wise. So there is no need to find the “sweet” spots on your sample anymore.

ILMs are composed of a mixture of organic salts and bases. This unique mixture leads to a high ionization performance with the analyte due to ion pairing via electrostatic or hydrogen bonding between the matrix compounds and impurities. Since the protons are originated from the salt rather than from a weak carboxylic acid group ILMs display higher proton exchange efficiencies compared to conventional matrices.
They do not cause fragmentation (even for non-covalent bonds) or cluster and alkali adduct formation. Thus, they are less prone to denaturation of biomolecules compared to acidic DHB and CHCA (pKa of 3 and 1.2) matrixes. ILM can be pH controlled by the organic base to minimize degradation, denaturation or fragmentation of labile biomolecules at low pHs.

Additionally, strength and concentration of base regulates the UV-absorbance, since a difference in charge status changes the localization of electrons within the molecule therefore changes the absorbance properties of the matrix towards lower (hypsochromic shift) or higher (bathochromic shift) wavelengths.


Source:
https://www.omicsonline.org/open-access/ionic-liquids-matrices-for-laser-assisted-desorptionionization-massspectrometry-2469-9861-1000109.php?aid=65371


Sonntag, 16. September 2018

Ultra High Pressure Column Packing


Ultra-high pressure HPLC can be one method to combat the high sample complexity of shot gun proteomics mixtures. During the years there have been an o lot of effort in optimizing the hardware setup. For example using solid core particles or longer columns.



The Coon Lab tried to reduce the van Deemter A-Term by creating an really tight and homogeneous packing bed of C18 particle utilizing pressures of over 2000bar for column packing. The packed columns turned out of display reduced backpressure and improved sequence coverage of +23%.
How this has been achieved?

Well, here a special type of pump was used. An air driven liquid pump based on pneumatic principle from heskel. This company usually operates in the hydrogen-gas fueled car industry but there multi head pump system which are able to create outlet pressures of up to 7000bar shown to be beneficial for column loading. The fittings and values used have been manufactured by HiP. Especially the connection from the slurry reservoir, having a ID of 1mm to the capillary with and OD of 0.3mm seems to be crucial to me (an modified femal to male fitting was used).

Freitag, 7. September 2018

EvoSep One nanoLC - combines low pressure sample loading and offline gradient formation for reproducible proteomics measurements


Usually reproducibility is a huge problem in nanoLC MS using an conventional 2-column setup utilizing sub-2µm solid core particles.
Due to the high pressure that is applied to achieve best efficiency, mechanical parts have reduced life time, undergo faster service intervals and obtain performance variation (pressure fluctuation).These phenomena led to an fluctuation of retention times and resolution from run to run.

Although nanoSpray displays better sensitivity researchers have been going back to microflow application because it offers a good comprise because sensitivity and reproducibility.


The new Evosep one nanoLC introduced a few concepts, which are going to overcome these limitations. The system has 4 low pressure pumps and a single high pressure pump linked by the sample loop.

The Evosep one pre-forms a gradient at low pressure and high flow and stores it within an sample loop. While sitting together with sample no mixing occurs.
Before loading into the sample loop the sample is cleaned up with an zip-tip like tip, also at low pressure. Since the loop is directly located behind the tip hydrophilic peptides won’t get lost and will be transferred entirely to the analytical column.
Since the gradient is pre-mixed only a single pump is required for eluent delivery. This is way better for reproducibility than two separately working pumps for each of the mobile phases.
Further, this unique system provides less carry over and an optimized duty cycle with less overhead time (-35% time saving compared to EASY1200 nano).
All in all this system provides great features and I am pretty sure it will become the method of choice for short gradient clinical proteomics.


Source: https://www.biorxiv.org/content/biorxiv/early/2018/05/15/323048.full.pdf

The company evosep has got a pretty cool homepage and a youtube channel, which definitely should be checked out.


Donnerstag, 6. September 2018

FUNPET - half ion funnel, half ion carpet


FUNPET is a hybrid ion funnel ion carpet MS interface. It combines the advantages on an classical stacked ring RF-only driven ion funnel and an ion carpet.
The ion carpet consists of multiple planar (isolated) metal rings with decreasing diameter stacked together. In the center there is orifice.

To each of the rings there is an RF and  DC applied. The RF (180 degrees out of phase between the rings) keeps the ions away from colliding with the rings and confines them in front of the ion carpet and its centric orifice. The DC is decreasing the closer it gets to get orifice, providing a electric gradient field for focusing the ions into the orifice and transmitting them into the next pressure stage.


Interestingly, the design includes an jet disruptor which causes dissipation of neutral gas molecules and therefore reduces the gas load for the next vacuum stage and increases ion transmission.

More information about the FUNPET and the ion carpet technology can be found at



Freitag, 17. August 2018

In-solution, In-gel, FASP and S-Traping - a voyage through protein sample preparation


When it comes sample preparation in bottom-up proteomics one likes to be as fast, as reproducible and as efficient as possible. Unfortunately, most of the sample preparations are biased towards certain peptide species. In this respect  hydrophobic proteins, such as membrane proteins can be troublesome. Also one should consider sample loss during each preparation step.

However, over the years there have been a couple of techniques established, that are widely used among proteomics researchers. Each of them has advantages and disadvantages.

During In-solution protein digestion protein precipitation in chloroform/methanol is followed by re- solubilization and digestion in 8M urea. This digestion is achieved in reasonable time compared to in-gel digestion but has the disadvantage of introducing sample loss during re-solubilization step.

Second approach is the in-gel preparation, that follows the idea to entrap the protein solution within a polyacrylamid gel matrix (usually after SDS PAGE) and subsequently washing out detergents and performing  protein digestion within the gel. In gel digestion is very time consuming but it is worth though because in most cases you are ending up with a high number of PSMs.

The third technique is called FASP, which stands for filter aided sample preparation and requires about 7h hands on time. FASP tries to combined the advantages of the previously mentioned techniques. In filter aided sample preparation proteins are denatured and kept in solution by SDS. The SDS-protein mixture is subjected onto a filter cartridge, where all proteins are bonded. After an SDS-urea exchange, digestion takes place within the molecular mass cut off filter (be aware of MWCO during selection), releasing peptides whereas undigested proteins remain within the filter and would not contaminate the peptide mixture.

Depending on the geometry of the spin filter and your centrifuge over 50% of the originally used protein amount, ranging from µg to mg, can be recovered on peptide level. I found good SDS PAGE from a nature method paper which served as a control of evaluate the recovery during each step.



A rather new technique is called S-trapping, the S stands for suspension, because the proteins are trapped within a porous network made of quartz (SiO2) while being in suspension. Contaminations and salts have no binding affinity and remain in the flow through. Sample amounts ranging from ng to µg (read somewhere that 250µg is the maximum protein capacity of the silica network)
But it all starts with a common SDS step to solubilize all proteins. Afterwards this SDS micelle is partially broken up and the proteins begin to become partially denatured. This is when the quartz networks kicks in and bonds all of these particulate proteins to prevent them from aggregating with other particulate proteins. Since all the proteins are attached onto the surface of the network proteolytic digestion enzymes have an easy job to access all cleavage sites.

Quartz is a good choice since it provides low metal content (similar to type I silica in HPLC) and low peptide background during digestion. Additionally, one is able to chemically modify the silica surface to perform enrichment of certain peptides after digestion (for example with SDPD, commonly used as crosslinker, for enrichment of cysteine containing peptides, search C-S-trapping).


A recent study comparing all of these 3 sample preparation approaches indicated that S-trapping outperforms in-solution and FASP in terms of identification of unique peptides.



The S-Trapping is commercialized by a company called Protifi. There also provide a unique protease for enhanced b-ion in MSMS fragementation. Great stuff!

Mittwoch, 8. August 2018

In vivo TMT labelling

Tandem Mass Tag (TMT) is a common technique for quantification of peptides at the MS2 level.
The TMT is based on the reaction of the Primary amine at the N-terminus and the lysine with the NHS-ester group of the isotopically labeled tag. Once successfully tagged the peptide mixture is subject to MS analysis were the TMT-peptide displays a label-specific, low mass reporter ion during MS2.

The NHS-based TMT strategy requires all peptides to be freely accessible within a lysate to obtain efficient tagging. TMT can be apply for intact proteins as well, but applying it to intact cell in vivo was new to me.
The authors investigated the labelling efficienicy among different cancer cell lines and stated that in vivo TMT labeling requires an additional enrichment step to achive decent labeling efficiencies which are still lower compared to tagging on the peptide level (roughly 50% of identified peptides were tagged with invivo TMT after enrichment). The enrichment was done using an anti-TMT antibody to pull down all labeled peptides.

Compared to TMT labelling on the peptide level which appeared to be 100% of all identified peptides in vivo labelling with subsequent
Tandem Mass Tag (TMT) is a common technique for quantification of peptides at the MS2 level.
The TMT is based on the reaction of the Primary amine at the N-terminus and the lysine with the NHS-ester group of the isotopically labeled tag. Once successfully tagged the peptide mixture is subject to MS analysis were the TMT-peptide displays a label-specific, low mass reporter ion during MS2.



The NHS-based TMT strategy requires all peptides to be freely accessible within a lysate to obtain efficient tagging. TMT can be apply for intact proteins as well, but applying it to intact cell in vivo was new to me.
The authors investigated the labelling efficienicy among different cancer cell lines and stated that in vivo TMT labeling requires an additional enrichment step to achive decent labeling efficiencies which are still lower compared to tagging on the peptide level (roughly 50% of identified peptides were tagged with invivo TMT after enrichment). The enrichment was done using an anti-TMT antibody to pull down all labeled peptides.
Compared to TMT labelling on the peptide level which appeared to be 100% of all identified peptides in vivo labelling with subsequent immunoprecipation showed rather minor efficiency. However reproducibility was definitely given. Surprisely, the in vivo labelling strategy had no specificity to the location of the proteins. Specifically, a bias towards surface protein has not been revealed.




 showed rather minor efficiency. However reproducibility was definitely given. Surprisely, the in vivo labelling strategy had no specificity to the location of the proteins. Specifically, a bias towards surface protein has not been revealed.



Freitag, 3. August 2018

New features in skyline - LC-IMS-CID-MS and contaminations library


There is a lot going on in the skyline world lately. Originally, open source software skyline from the MacCoss Lab which started out as analysis tool for label-free quantification and MRM analysis of MS data.
Over years a lot of features have been added because more comprehensive analysis was requested by the users or new instruments using new scan modes have been introduced to the market. That's why recently ion mobility functionality has been added, including the entire LC-IMS-CID-MS workflow.


However, yet another skyline feature caught my attention in the current JASMS. A contamination library has been integrated into skyline. It contains over 684 common MS contaminations, which can be used as an transition list for MS1 filtering and is also provides a approach to determine unknown contaminations via a mass-to-formula tool. The mentioned transition list can be downloaded in the public repository panorama.


CID and CIU

CID stands for collision-induced-dissociation a common fragmentation technique to create tandem MS spectra (MS2). In CID precursor ions are accelerated and subsequently injected into a ion guide filled with inert neutral gas molecules, typically N2, where the analyte of interest undergoes single or multiple collisions. The charge of the analyte, the accelerating (collisional) voltage and the gas pressure can determine the extent of collisional Impact.

Ions are vibrational excited by the collision(s) with a time frame of a few femtoseconds. Depending on the chemical bonds present the ions can break apart into charged, radical or neutral fragments. In proteomics weaker bonds, such a post-translational modification, tend to get lost during CID.
In beam type instruments a special version of CID, In Source CID, can facilitate MS3 fragmentation for deeper structural elucidation. Herein, ion guides on the front end of the MS serve as a 2nd collision device for fragmentation of all ion species injected. Out of this very complex MS2 spectrum precursors can be selected for an MS3 in the actual collision cell downstream.  

When it comes to analysis of intact proteins and protein complexes having high molecular weights, In-Source CID at elevated pressure, can be applied but in most cases it directly leads to dissociation. Secondary or high order protein structures cannot be detected easily.
Besides the dissociative nature of CID for large biomolecules there is a much elegant appoarch that utilizes collisional activation to study structures intactly. It is called CIU, which stands for collisional induced unfolding, and can be conducted with an ion mobility detector coupled to an MS.
During a CIU experiment intact biomolecules, such as antibodies, are ionzied and undergo a stepwise increase of collision heating which induces a gradual change in conformation (unfolding).
For every stepped potential an ion mobility scan, plus the nested MS scans, are recorded so that one can follow the structural changes. These multidimensional datasets (see image) help to distinguish isoforms, determine number for disulfide bonds and degree of modifications or monitor ligand binding.

Source: https://www.sciencedirect.com/science/article/pii/S1367593117301266?via%3Dihub#fig0010

Dienstag, 31. Juli 2018

CharmeRT - Chimeric spectra identification utilizing retention time prediction - Up to 50% more peptide IDs


Co-elution of peptides is a major issue in bottom-up proteomics experiments, since it can led to co-isolation and co-fragmentation of peptide ions resulting in a chimeric MS2 spectra.  A MS2 spectrum containing more than a one peptide spectrum match (PSM) is considered to be chimeric MS2 spectra.
By the way chimera is taken as an analogy from greek mythology, where it stands for a hybrid creature from two or more animals. An example would be pegasus, the winged horse, so basically a mixture of a horse and a bird. 



But now back to the problem having multiple peptides selected as MS2 precursors… According to the study a HeLa digest separated by a 3h gradient displayed over 50% chimeric MS2 spectra, 20% of these spectra showed even more than two PSMs in a single MS2.
Sounds awesome to me and really is a reason to further investigate - how the authors have done this.
Well, as it turns out they identified the chimeric spectra by performing a 2nd search, in which previously assigned PSMs have been removed from the raw data. These multiple PSMs were then validated utilizing retention time prediction model as part of Elutator software. This prediction model is based on the hydrophobicity index of the (modified) peptides. The index determines how much energy is needed to transfer molecules (or a peptide chain) from a nonpolar solvent to water.
If the polypeptide requires energy to do this it is hydrophobic. If it does not it is considered to be hydrophilic. In reverse phase liquid chromatography such an index can provide a measure of approximate elution order and time.


The special feature of Elutator is that it not only takes the hydrophobicity of the individual amino acids into account but also it considers the effect of neighbouring amino acids during its calculations. This lets Elutator predict retention times much more precise compared to other RT prediction tools.


CharmeRT using Elutator outperformed conventional proteomics workflows such as mascot and percolator by up 90% in terms of assigned PSMs and up to 65% for validated peptide IDs. It is claimed that most of these newly identified peptides are low abundant peptides.  Therefore the authors tried to investigate this hypothesis with RNA data of the identified peptides. And indeed, they showed an extension in sensitivity towards smaller peptide abundancies without increasing instrument time, well just post processing time, though.
Charme RT can also be beneficial for DIA approaches, since it works much better for wider quadrupole isolation windows.


Mittwoch, 25. Juli 2018

Temperature Gradients in on-chip LC provide an solvent saving alternative

Lately, I have been reading a lot about lab-on-chip technologies and I am beginning to admire the advantages of this technology. 

However....Temperature can be parameter targeted by method optimization to speed up liquid chromatography. Generally, it is known that temperature increase leads to an increase of brownian motion and causes faster separation (lower retention times (k) but also peak broadening and a change in selectivity due to differences in mass transfer.
Other positive side effects are lower backpressure which enables the usage of longer columns or smaller particle to increase efficiency and lower solvent consumption.


This dependency can be explained by the Horvath Rule, named after the hungarian Csaba Horvath who is known for a lot inventions in the field of LC, for instance pellicular particles. The rule points out that an temperature increase of 4-5 degree celisus has similar effects as increasing the organic modifier by 1%.

When it comes to temperature gradients in conventional LC and peak broading one has to differentiate between an radial and axial gradient. The radial gradient (in to out) causes intense peak broadening, whereas the axial gradient (front to back) leads to peak shapening and decrease retention times. In tradional LC pre-column heater and post-column cooler can prevent these effects related to the so called thermal mismatching.

If you are performing LC on chip device the interface with the heater is much larger compared to an conventional LC column and therefore one is going to have a much faster thermal response time. Solvent pre-heating is obsolate. Heat dissipation is reduced since there is no air contact. 


Due to dependency Horvath has described one does not need a solvent gradient to increase peak capacity for on chip LC temperature gradients one can be used instead. This saves ressources and reduces the ecological impact of analyical labs. 

https://pubs.acs.org/doi/abs/10.1021/acs.analchem.7b00142