1. K-State home
  2. »Kansas Lipidomics Research Center
  3. »Analytical Laboratory
  4. »Data Handling and Policy

Kansas Lipidomics Research Center

Data/Sample Handling and Policies

  • The prices that we quote are on a fee-for-service basis, set on a "break-even" pricing schedule. Our normal practice is to send an invoice upon completion of the work. 

  • For all fee-for-service work at KLRC, the results are confidential and will not be disclosed by KLRC to anyone outside KLRC, except to the clients submitting the samples or others they authorize.  If your research is supported by public funds, we do encourage you to make the data set public at the time your work based on the data is published, via inclusion as supporting data in your publication or in a public database.

  • Samples sent to the KLRC for analysis are not returned to clients, except when a special request is made at the time of submission.http://www.k-state.edu/lipid/analytical_laboratory/klrc_policies/index.html 

  • KLRC asks that you acknowledge our grant support in publications and presentations: http://www.k-state.edu/lipid/grant_support/index.html

Information about lipid identification and quantification

Regarding compound identification for lipid profiling by ESI triple quadrupole MS

We assign compound i.d.s based on the mass (more accurately m/z) of a lipid intact ion and the mass of one fragment formed from that ion in the mass spectrometer.  Typically, for polar lipids, this is a head group fragment.  For sphingolipids, it may be a fragment characteristic of the long-chain base or sugar(s).  For neutral lipids and for specialized analyses, it may be an acyl fragment.  Typically the i.d.s indicate a head group and total acyl/alk(en)yl carbon: total carbon-carbon double bonds.  If your samples originate from a source that we are familiar with, i.e. Arabidopsis or a mammalian tissue, you can be >99% confident that the i.d.s we are providing are accurate for the most common molecular species with that mass.  Even still, there can be ambiguities and cases where molecular species with different chemical formulas share the same intact mass and fragment mass.  An Arabidopsis example is “MGDG(38:6)”, which also represents MGDG(36:4-2O), i.e. an oxidized compound with 2 fewer methylenes, 2 more double bond equivalents, and 2 extra oxygens.  These two compounds have the same nominal intact ion mass and head group fragments mass and can only be differentiated by scans in which the acyl chains are interrogated.  We will try to double annotate such molecular species, when we know of an ambiguity.

If your sample originates from an organism that we are not familiar with, e.g. a protozoan, a bacterium, or a fungus, you need to be more cautious about the i.d.s.  You need to filter the data based on your knowledge of what lipids are potentially in your organism.  One particular source of bad i.d.s is ether-linked chains vs. odd-numbered acyl chains with the same masses. We can work with you on this, but it is primarily your responsibility to make sure your data are meaningful.

Regarding amount determination for lipid profiling by ESI triple quadrupole MS 

We will report the amounts as normalized signal/(tissue metric that you provide).  This means that we are comparing the signals for the peaks in your sample to the signals for peaks of internal standards that we are adding in known amounts, and we are reporting the data so that the signal that is represented as 1 = the same signal as 1 nmol of internal standard (usually with an adjustment for variation in response with m/z).  If your compounds are diacyl or monoacyl phospholipids, the response of each compound is very close (within 5 or 10%) of the response of an internal standard of the same class.  Thus, the numbers that we report as normalized signal/(tissue metric provided by you) for diacyl or monoacyl phospholipids can be considered to be equal to nmol/(tissue metric).  However, with other compounds, including ether-linked lipids, glycolipids, and neutral lipids, there is some variation in molar response among compounds within a class and in comparison to the internal standard.  Thus, the normalized signal/(tissue metric) allows for comparison of the same compound among samples, but may not provide an accurate indicator of the relative amount of that compound compared to other compounds in the sample.  Thus, we suggest that you present those data as normalized signal/(tissue metric), as we do.

Since early 2017, we have been correcting our MGDG and DGDG values with response factors.  In other words, we have determined that the unsaturated MGDG or DGDG gives an [M + NH4]+ peak intensity that is X times (with X depending on the mass spectrometer) the size of an equimolar amount of a fully saturated MGDG or DGDG peak [M + NH4]+ intensity, and we are correcting for this, so that the results are in approximately molar amounts.  Thus, we now are including additional calculations and the data are presented as signal/(tissue metric)  and % total signal, which represent uncorrected values for polar plant lipids, AND also as nmol/(tissue metric) and mol%, which include the response factor.

TAG data

TAGs are typically identified by mass of one fatty acyl group + mass (can be translated to total acyl carbons and double bonds) of intact TAG.  This means that most of the same TAG compounds are repetitively analyzed as we scan for various fatty acyl groups.  For example: If a TAG is 16:0/18:2/18:1, it would be determined in scans for 16:0, 18:1, and 18:2.  Each time, it will appear at the intact ion m/z.  These data might also include data for other TAG species.  For example, the 16:0 scan would not differentiate 16:0/18:2/18:1 from 16:0/18:3/18:0 as these have the same m/z for each of the two both the fatty acid fragment (16:0) and the intact ion fragment (52:3).  One approach to presentation of the data that allows direct comparison of the data with those of the polar lipids is shown in Lee et al., Plant Biotechnol J., 2011, 9, 359-372, Fig. 8,  http://www.ncbi.nlm.nih.gov/pubmed/20796246.  In some cases, we are able to partially "assemble" the TAG data, resulting in identification of all three fatty acids for some or most molecular species, but you should not count on our ability to do this.