Making Size Exclusion Chromatography columns

My summer student, Kalita, has been digesting oligosaccharides, derivatising them and injecting them into the mass spectrometers in an effort to derive structural information from these complex molecules. We had hoped to use acrylamide gel electrophoresis to visualise the performance of our digests, in the way of Pomin et al (2005).

Screenshot from 2016-03-03 20:30:41.png

This figure from the paper shows the effect of their hydrolysis technique upon the molecular weight of the oligomer. Note the banding patterns resulting from selective hydrolysis of certain glycosidic bonds. This produces a regular reduction in size of the fragments. We wanted to use this feature to produce polymeric fragments in the <10kDa size rage. These would be amenable to LC-MS/MS, as in Lang et al (2014), allowing us to infer the sequence, functionalisation and bonding of the monomers within the oligomer.

As it turned out our acrylamide gels got lost somewhere amidst The Great Bureaucracy and so, with time running out we cast around for alternate technologies. Enter Yang, et al (2009), who used a similar technique in their paper, but also deployed Size Exclusion Chromatography to illustrate the size-class of fragments produced.

Screenshot from 2016-03-03 21:11:31.png

The thing is we didn’t have any GPC or SEC columns.  😦

 

So we decided to try making our own!  😀

 

Fortunately or chemical store had a shelf of old bottles of dextran and other GPC or ion-exchange substrates. We dug up a protocol from an MSc thesis by Wilfred Mak in which he’d used an anion exchange substrate to determine the molecular weight of intact sulfated fucan oligosaccharides, rifled through the stores to find some substrates that looked about right and away we went!

We started out with a biuret:

IMG_20160302_172848.jpg

At the bottom, hidden by the blue compression screw, is a plug of deactivated glass wool with a few mL of sand on top of that and then the white dextran gel. This was the first addition of substrate and settling. After topping it up we have a column of about 40cm length. This type of column is purely gravity-fed. You add sample and running buffer at the top and wait for the head of fluid to pass through the column, collecting fractions through the tap at the bottom. This can take hours.

While Kalita was putting this together I was looking at some of the old silica particle LC columns I had and wondering if I might dismantle them, remove the packing and repack them with the dextran to give a real, high-pressure column. This could be plumbed into one of our conventional LC setups, allowing us to push samples through at a faster rate and giving the option of automated sample injection, data and fraction collection. I had something of a brain wave and realised that I had some Swagelok fittings which would allow me to fit a piece of 1/4″ polypropylene air line with pressure-tight caps and LC fittings at either end to fulfil exactly that function. A couple of hours later Kalita and I were the proud parents of monstrous creation on the left!

IMG_20160303_162725.jpg

The white tube held between the two clamps on the left hand retort is the air line packed with hydrated dextran. The line at the top comes from the Shimadzu LC pump on the right, which is pumping Tris buffer through the column to settle the packing material. We can get a flow of 2 mL/min through the column with a back pressure of about 5 bar. Plenty for LC!

For now our creation is parked until we can get round to doing something cool with it on Monday but watch this space to see the outcome. Our intention is to add an autosampler to the front for sample injection, a Refractive Index Detector and maybe even an electrochemical detector on the outflow to detect what came off the column and possibly even a fraction collector for downstream LC-MS/MS analysis of the fractions! Fun!

Our first goal is to validate the SEC function by injecting a range of proteins stained with Bradford Reagent. We can also try some di- and tri-saccharides along with our oligo digests.

 

References cited

Lang et al (2014). Applications of Mass Spectrometry to Structural Analysis of
Marine Oligosaccharides. Mar. Drugs 2014, 12, 4005-4030
doi:10.3390/md12074005

Pomin et al (2005). Mild acid hydrolysis of sulfated fucans: a selective 2-desulfation reaction and an alternative approach for preparing tailored sulfated oligosaccharides. Glycobiology vol. 15 no. 12 pp. 1376–1385, 2005
doi:10.1093/glycob/cwj030

Yang et al (2009). Mechanism of mild acid hydrolysis of galactan polysaccharides with highly ordered disaccharide repeats leading to a complete series of exclusively odd-numbered oligosaccharides. FEBS Journal 276 (2009) 2125–2137
doi:10.1111/j.1742-4658.2009.06947.x

nonstructural carbohydrates and FTIR

Non-structural carbohydrates [NSC] are important to tree growth and survival. Their quantification can be achieved by several analytical methodologies of varying accuracy. I am currently applying one of these – LC-MS – to elucidate the structure of algal oligosaccharides. However, these advanced analytical techniques require some fairly high-tech equipment and some careful sample preparation.

Recently it has been proposed that near-infrared spectroscopy can be used to quantify NSC with no sample preparation beyond homogenisation in a ball mill, or similar (Ramirez et al 2015). One of my students wants to try this method so I showed her how to put samples into the Fourier Transform InfraRed [FTIR] spectroscope. The referenced paper used a rigorous process of parallel biochemical analysis to determine the NSC content of the samples analysed and used these to determine the relationship between the NSC content and the FTIR properties. I have proposed a standard analytical process to eliminate this complex validation process, known as Standard Addition. Using this technique the student will add varying concentrations of the different NSC components to her samples and determine how this addition affects their FTIR properties. This should obviate the need to conduct biochemical or chemical analysis in parallel.

 

 

Ramirez et al, 2015: Near-infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree speciesMethods in Ecology and Evolution 2015, 6, 1018–1025 doi: 10.1111/2041-210X.12391

Research Update

Having meant to write several posts about exciting things that have gone on in the past couple of weeks I am now faced with combining them all, for efficiency’s sake, into another “research update”.

This week I have received an enquiry about analysing pigments and toxins found in the colourful tips of New Zealand giant springtailsHolacanthella. This could be a really cool little piece of analysis if it works. I’m going to have to head out into the Waitakeres to poke some lumps of rotting wood in the hope of finding some of these punk woodlice to play with.

After a visit from Don MacLeod of the NZ Beekeeper’s Association last week I am testing out some more extractions of neonicotinoid pesticides. A new paper was published this week in Environmental Chemistry documenting the occurrence of these pesticides in pollen and honey from hives across the US. The paper was written by Alex Chensheng Lu et al (2015), who kindly shared a copy with me. The paper reports that, during the Summer months, several neonicotinoids were present in pollen at concentrations of several ng/g; concentrations that may be acutely toxic to bees (Laycock et al 2012). The authors discovered measurable concentrations of at least one neonicotinoid pesticide in >70% of honey and pollen samples. I am hoping I can repeat their analysis in New Zealand samples to see if we have a similar issue here.

I have also been developing a method for the quantification of bile acids by LC-MS, which is causing me headaches as certain compounds won’t stay in solution (lithocholic acid, I’m looking at you), some seem to have a very low response in the instrument and others are playing hide-and-seek! The solution, as ever, is a bigger chicken.

I have also been plotting further awesome research plans for the future, submitting an application for a Summer studentship to get someone to look at polysaccharide structures, again with LC-MS. My life seems to revolve around the instrument sometimes but this week has not been all about the liquid phase. I have also been emailing around the results of some test analyses I conducted using methyl chloroformate derivatisation and GC-MS to try and expand the use of this very nice little method within the school. Consequently I found myself preparing samples of mangrove leaf extract, lamb and wagyu beef, fermented mussel liquor and hydrolysed beef protein. I was meant to have a go at some polyamines for another of the PhD students but I forgot their sample. Doh.

Apart from this mass-spectrometry-based fun I may have a student looking to measure total triacylglycerol content and fatty acid profiles of fish oocytes at some point. I’ve also had a really awesome kick-off meeting for my new PhD student, who is going to be studying plant phenology. We are kicking about ideas for the acquisition and installation of a phenocam.

Its been a crazy busy week!

Refs

Chensheng (Alex) Lu, Chi-Hsuan Chang, Lin Tao and Mei Chen (2015). Distributions of neonicotinoid insecticides in the Commonwealth of Massachusetts: a temporal and spatial variation analysis for pollen and honey samples. Environmental Chemistryhttp://dx.doi.org/10.1071/EN15064

Laycock I, Lenthall KM, Barratt AT, Cresswell JE (2012). Effects of imidacloprid, a neonicotinoid pesticide, on reproduction in worker bumble bees (Bombus terrestris). Ecotoxicology 21(7):1937-45. http://link.springer.com/article/10.1007%2Fs10646-012-0927-y

Agilent Infinity Series liquid chromatograph and 6420 triple quadrupole mass spectrometer

Here’s a picture of our LC-MS.

20150616_170729

Its a triple quadrupole instrument, so its designed for quantitative analysis of any compound you can solubilise and ionise, which includes pretty much anything relevant to metabolism, physiology, pharmacology and biochemistry.

Its a conventional pressure LC stack featuring thermostatted autosampler for 100 x 2ml vials, a thermostatted column compartment and a diode array detector at the bottom, if needed. We also have a fluorescence detector which isn’t shown.

We have two sources for the MS, a conventional electrospray ionisation [ESI] source and a Multi Mode Ionisation [MMI] source which can be set for full ESI, full Atmospheric Pressure Chemical Ionisation [APCI] or a mixture of the two, with full control over the corona current and charging voltage.

This instrument is currently analysing sugar derivatives and has previously been used to quantify phenolic compounds and anthocyanins in cherries, triglycerides in human plasma and serum and neonicotinoid pesticides. I am currently developing a method to target 15 bile acids in human samples and another to target lignin-derived phenolics in estuarine plant material and sediment.

Scraping molecular information from ChemSpider using Processing.

I’ve spent the evening knocking out this little sketch to scrape molecular information from ChemSpider to inform my mass spectrometry. Until now I’ve been doing this by hand or getting the students to, when they are able, but this is the start of my attempt to automate the process. Ultimately I will just want to feed it a text file of compound names and it will parse the output into a document.

Open a Processing window, copy the code below into it, edit the first string to contain the name of the compound of your choice and click run. Here’s an image of example output.

Processing ChemSpider sketch output

// sketch to grab molecular information from a named compound from ChemSpider
// AUT School of Applied Science
// June 2015
// drchrispook@gmail.com
// released under GPLv3 licence – https://gnu.org/licenses/quick-guide-gplv3.html

// ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~
// enter the compound name you want information for
String compound = “caffeine”;
// ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

// sketch continues
PImage webImg;

String URL = “http://www.chemspider.com//Search.aspx?q=&#8221;;
String nameURL = URL + compound;
String[] html1 = loadStrings(nameURL);

String CSID = “CSID”;
String formula = “formula”;
String MIM = “MIM”;
String solubility = “solubility”;
String logKow = “logKow”;
int imageSize = 400;
void setup() {
size(imageSize, imageSize);

for(String i:html1) { // iterate through each string in the array
// println(i);
int line = i.indexOf(“CSID:”); // identifies CSID line by searching for this string

if(line > 0) { // if you find that string
String[] trim1 = split(i, ‘,’); // split off the junk
// for(int i = 0; i < trim1.length; i++) { // println(trim[i]); // } String[] trim2 = split(trim1[0], ‘:’); // split off more junk CSID = trim2[1]; // set the CSID break; } } String imageURL = “http://www.chemspider.com//ImagesHandler.ashx?id=&#8221; + CSID + “&w=” + imageSize + “&h=” + imageSize; webImg = loadImage(imageURL, “jpg”); String CSIDURL = “http://www.chemspider.com//Chemical-Structure.&#8221; + CSID + “.html”; // use the CSID to construct the url to that molecule’s entry String[] html2 = loadStrings(CSIDURL); // grab the html //println(html2); for(String i:html2) { // this is the main part of the macro // println(i); int MIMLine = i.indexOf(“Monoisotopic mass”); // identifies MIM line int formulaLine = i.indexOf(“Molecular-Formula”); // identifies the formula line int solubilityLine = i.indexOf(“Solubility at 25 deg C (mg/L):”); // etc int logKowLine = i.indexOf(“Log Kow (KOWWIN”); // etc if(formulaLine > 0) {
String[] trim1 = split(i, ‘/’);
// for(int e = 0; e < trim1.length; e++) { // println(trim1[e]); // } String[] trim2 = split(trim1[2], ‘”‘); formula = trim2[0]; } if(MIMLine > 0) {
String[] trim1 = split(i, ‘>’);
// for(int e = 0; e < trim1.length; e++) { // println(trim1[e]); // } String[] trim2 = split(trim1[3], ‘ ‘); MIM = trim2[0]; } if(solubilityLine > 0) {
String[] trim1 = split(i, ‘ ‘);
// for(int e = 0; e < trim1.length; e++) { // println(trim1[e]); // } solubility = trim1[12]; } if(logKowLine > 0) {
String[] trim1 = split(i, ‘ ‘);
// for(int e = 0; e < trim1.length; e++) {
// println(trim1[e]);
// }
logKow = trim1[11];
}
}
print(“the formula for ” + compound + ” is “);
println(formula);

print(“the monoisotopic mass of ” + compound + ” is “);
println(MIM + ” Da”);

print(“the estimated log Kow of ” + compound + ” is “);
println(logKow);

print(“the solubility of ” + compound + ” at 25C is “);
println(solubility + ” mg/l”);
}
void draw() {
background(0);
image(webImg, 0, 0);
}

research update

I’ve been meaning to write a post for a couple of weeks detailing the state of play of my current analytical projects but I’ve been awfully busy helping my MSc student get the last of her LC-MS data on cherry anthocyanins and phenolics. We managed it in the end and she has a lovely result so I spent last week broadening my focus again and picking up some of the projects I’d had to put aside. Most of last week I also spent trying to derivatise reducing sugars for a collaboration with some lovely people from the Human Potential Centre at AUT’s Millenium Institute. This is a really exciting capability as sugars are notoriously hard targets to analyse chromatographically. We currently use a gas chromatographic method which involves a quite lengthy and fiddly acetylation procedure but I’ve found a compound that works really nicely for liquid chromatography with a relatively simple derivatisation procedure. There’s also lots of potential to push the analysis into larger oligosaccharides and glycans, with at least two exciting projects already on the table. I’m hoping this might result in two publications, the first being method development and the second an application.

I’ve also started developing a quantitative method for bile acids and have been approached to quantify lignin-derived phenolic compounds in sediment and plant material from estuarine habitats across the South Pacific. Very exotic! At some point I’d like to get some more method development done on neonicotinoid pesticides as I’ve developed a very cool and powerful extraction method which may solve the recovery and sensitivity problems. Again, definite options to present this as a method development and validation paper so no details yet.

😉

Antarctic cyanobacterial mat

Cyanobacteria are crazily robust organisms. They can thrive pretty much anywhere damp: The surface of desert rocks, oceans, in soil, lakes, the trunks of trees and even your house. Seriously, there’ll be a few squillion of them living in the biofilm that flourishes in the damp corners of the external surfaces of your house. 

I’ve been lucky enough to get to work with some of the samples of cyanobacterial mat from Antarctica that were brought back from a recent research expedition there that AUT School of Applied Sciences were involved in.

image
image

The idea is to establish what photosynthetic pigments they contain as a way of identifying them and of ground-truthing the hyperspectral data collected by the UAV Len was flying down there. So I’ve spent much of today grinding, weighing and pouring alternately liquid nitrogen and acetone. Scientific fun!

image
image
image

The extracts are in the fridge, in the dark, awaiting spectrophotometric, fluorometric and LC-DAD-FLD-MS analyses tomorrow. 

QToF

Its not every day that you get a phone call from a nice man who wants to sell you a $600K instrument for a fraction of that price, but that’s what happened to me yesterday. Because my Head of Research is a very, very nice man and a damn good scientist he didn’t laugh me out of the room when I casually dropped by to mention it. So I better get off Tumblr and work on the 200 or so words he asked me to write selling the idea to the Dean! 

😀

stability of neonicotinoid LC-MS standards
I’ve got mixed standards of six neonicotinoid pesticides for my LC-MS analysis that have been sat in the autosampler for more than six months. I’m getting ready to do some more so I thought it was time to make up a new mixed working solution and standard curve. Blow me if the response of the new standard didn’t match the old one almost perfectly! 

This is remarkable because it shows that neonicotinoids are perfectly stable in 5% acetonitrile at 6 degrees C and in brown autosampler vials. 

I love HPLC – High Pressure Liquid Chromatography

HPLC is my favourite analytical technique because it can be applied to pretty much anything soluble. Which includes, well, pretty much everything. This is in contrast to Gas Chromatography (GC), which only works for compounds which are volatile at temperature below about 350C. This is only about 5% of molecules so that’s a fairly restrictive condition, although as us scientific types are jolly clever we’ve worked out cunning ways of changing non-volatile molecules we want to analyse by GC to make them volatile.

Here’s a link to one of the HPLC systems we use in our labs, including some of the applications for this technique. In addition I’d like to present a bit of my history with this technique to provide some examples of what it can achieve.

I used HPLC during my PhD to quantify glutathione ratios in the polychaete worm I was studying. Glutahione ratios are a very useful indicator of oxidative stress as glutathione is the first line of defence against the toxic effects of many metals and is a substrate or cofactor in many antioxidant and other enzymes.

Whilst working on my PhD I also used HPLC to quantify hormones in monkey pooh! This was a quick bit of work to validate a friend’s work looking at social hierarchies in communities of monkeys in zoos. The hormones in their pooh were correlated with their health and with their place in the hierarchy!

Nowadays you tend to find HPLC systems coupled to Mass Spectrometers, harnessing the resolving power of this technology to enhance the capabilities of liquid chromatography. This allows you to identify and quantify many different compounds in very short runs and in very complex matrices such as urine, blood and cell or tissue homogenates. SoAs was lucky enough to acquire an Agilent 6420 triple quadrupole mass spectrometer and an Agilent 1200 series LC stack a couple of years ago and this has become the workhorse of our lab.

During my PhD I first managed to get time on an LC-MS instrument when I was based at Plymouth University, where I worked as Research Assistant on a project characterising the metabolism of a common biocide, 2-hydroxybiphenyl [HBP], in common shore crabs. This was incredibly valuable experience and I was lucky to have an oustanding LC-MS mentor in the form of Dr Claire Redshaw. Claire helped me develop a method to extract HBP and its metabolites from urine we collected from the crabs (that’s a post for another day). The LC-MS allowed us to confirm that the metabolites were mostly sulphate-conjugates of either the parent molecule or of a monooxygenated product of Phase 1 detoxification.

Other pieces of LC-MS work I’ve been involved in or conducted myself include the extraction and quantification of bisphenol A from human urine, profiling of triglycerides in edible oils and in human plasma and the quantification of neonicotinoid pesticides in pollen and honey. I have been working on the latter piece of work for several years now, starting with a postdoc position at Exeter University studying the toxicity of this class of pesticides to bees and continuing now here at AUT.

Hopefully these examples of HPLC and LC-MS applications illustrate why I love the technique so much. One reason which may not be obvious is that LC is a notoriously challenging technique and can be incredibly complex to get right. So much so that it is often referred to as a “Black Art”. I have a favourite joke I tell to all the students when their analysis isn’t working as it should: I ask them how big their chicken was that morning. When they look baffled or alarmed I follow up with the question: “Well, you did sacrifice a chicken this morning, didn’t you?”

LOL!