[RASMB] MW calculation question

Tue Aug 13 12:34:04 PDT 2013

Hi John S.-
One of the virtues of g(s) and c(s)-type of analysis is that there is no a priori assumption made about the number of components in the solution. The discrete models in Sedanal and Sedfit presume that you have selected the proper model (including number of components). If the model is wrong, the M will be wrong and, typically, too low. I think this is what John P and Walter have been saying, just worded a bit differently.
Best wishes,
Tom
________________________________
From: rasmb-bounces at list.rasmb.org [rasmb-bounces at list.rasmb.org] on behalf of John Sumida [jpsumida at u.washington.edu]
Sent: Tuesday, August 13, 2013 3:24 PM
To: jphilo at mailway.com; rasmb at rasmb.org
Subject: Re: [RASMB] MW calculation question

Dear John P.  Your comment regarding the effects of fitting the whole set of boundary data is very helpful.

But just to make sure I am clear on this, I believe what you are saying is to use dcdt in order to determine the dataset that is consistent with the major (80%) species observed in sedfit, and then proceed with the single species model in SEDANAL?

I will also check the single species fit in SEDFIT – I had not tried that yet – but I think that this also should only use those scans that correspond to the single species otherwise the fit could prove to be quite poor?

Thank you all for all the comments.  They are not only helpful and informative but encouraging as well.

Best regards
John Sumida
Analytical Biopharmacy Core
University of Washington.

From: John Philo [mailto:jphilo at mailway.com]
Sent: Tuesday, August 13, 2013 10:05 AM
To: rasmb at rasmb.org
Cc: 'Walter Stafford'; 'John Sumida'
Subject: RE: [RASMB] MW calculation question

John S., I agree with Walter Stafford that heterogeneity is causing the single-species fit to underestimate the mass, but I don't think there is any reason to think the primary cause is heterogeneity of monomer mass or conformation. You said yourself that the c(s) analysis gives one major peak that is only 80% of the total area. If the sample is only 80% pure, why would you expect a single-species fit to give the correct MW? If c(s) is giving one narrow main peak then it is not its ability to emulate multiple overlapping species that is primarily improving the fit quality relative to a single-species fit, it is the addition of the 20% of minor species (presumably with significantly different sedimentation coefficients).

The strength of whole-boundary analysis is that it fits all the scans, but that means that to get good results it must account for all species that are present, whether or not they are things you are interested in! That is, a weakness of whole boundary analysis is that it isn't particularly easy to exclude impurities, aggregates, fragments or other 'junk' from the data analysis, and your results simply demonstrate that problem. This is a case where a quick and simple g(s*) analysis via the dc/dt approach, and then fitting only the main peak of that distribution (excluding the junk at high and low sedimentation coefficients) would probably correctly identify the MW of your 80% major species (but always the best precision should come from whole boundary analysis).

Further, fundamentally your question is an apples vs. oranges comparison. You say you want to compare the two different analysis programs, but you are trying to compare two fundamentally different fitting models. You can easily do a single-species fit in SEDFIT and then compare that to the one from SEDANAL (and I'm sure the results will be similar).

John P.

________________________________
From: rasmb-bounces at list.rasmb.org<mailto:rasmb-bounces at list.rasmb.org> [mailto:rasmb-bounces at list.rasmb.org] On Behalf Of Walter Stafford
Sent: Monday, August 12, 2013 6:30 PM
To: John Sumida
Cc: <rasmb at rasmb.org<mailto:rasmb at rasmb.org>>
Subject: Re: [RASMB] MW calculaiton question
I think this was already answered. I think your sample is heterogeneous. Small variations on composition (I.e molar mass heterogeneity) will cause peak broadening that will appear as diffusion. If you include enough data in the fit. It should be apparent in the residuals. C(s) will add enough components to account for the heterogeneity (albeit with the same f/fo) and should give better residuals. Sedanal will not because fitting to a single species (I. E, the wrong model) should not give as good of a fit. The heterogeneity will cause Sedanal to return a value that is too large and therefore, a molar mass that is too small.

Walter Stafford
wstafford3 at walterstafford.com<mailto:wstafford3 at walterstafford.com>

On Aug 12, 2013, at 20:57, "John Sumida" <jpsumida at u.washington.edu<mailto:jpsumida at u.washington.edu>> wrote:

Dear RASMB,

The following was posted on the SEDFIT user list and it has been suggested that I also post this message to the RASMB list.  Thus I am reposting my question to RASMB and am including some edits and additional information for clarity and correctness.

Objective

I am trying to reconcile results obtained using two different approaches, SEDANAL and SEDFIT.

Observations

In SEDFIT, analysis of sed velocity FDS data returns an s20w of 8.5s and MW=1.3 MDa for the major peak, comprising >80% of the total loading concentration, determined in a c(s) fit.  Please note after checking with our collaborators this value is consistent with the MW returned from DLS and static light scattering experiments.  Thus the SEDFIT result is consistent with the DLS and static light scattering data which estimate a MW of 1.1 MDa.

In SEDANAL, the simplest model necessary to fit the data well was a single species model.  Using this model, analysis of the same data-set returns an s20w of 8.8s, similar to the value calculated in SEDFIT, but a MW of 655 kDa is calculated.

My question:

Why does the value of the MW returned for SEDANAL and SEDFIT differ by a factor of ~2 when the s20w in each case are similar (8.5s versus 8.8s).  My purpose here is that I believe the apparent difference being returned from these parallel analyses is saying something fundamentally important about the behavior of these materials in buffer and our assumptions thereof.

Background.

1.     <!--[if !supportLists]--><!--[endif]-->Rotor speed was 30 krpm, vbar=0.917 (measured), solution density = 1.00506 g/cm3 (measured), and viscosity =0.0100281 Poise (measured).  Temperature = 20oC.

2.     The material being studies is a polymer micelle with a CMC of 14 micrograms/ml.

3.     The polymer was run over a series of concentrations ranging from 0.2 mgs/ml to 1.00 mgs/ml.

1.     Thus under the conditions of the experiment I am at least 14 times the CMC at the lowest concentration.

4.     A major peak is observed in the initial c(s) distribution comprising >80% of the total loading and the position of this peak (7.7 s-exp; s20w=8.5) does not shift with concentration.

5.     From the analysis of raw SV data, SEDANAL returns an experimental sedimentation coefficient of 7.9s and a calculated s20w of 8.8s.

6.     A global analysis in SEDPHAT was performed over the entire concentration range, transforming the initial c(s) distribution into a set of 8 discrete species.

1.     Four of these 8 species survived a critical chi square analysis suggesting that these four species were important in retaining the quality of the fit.

2.     Of these four discrete species, three were grouped beneath the major peak observed in the initial c(s) analysis.

3.     <!--[if !supportLists]--><!--[endif]-->The calculated weight averaged s20w for these three species was 8.1s.

4.     The  s20w values were checked and confirmed with a manual calculation, SEDNTERP verstion 1.09, as well as the calculate “s(20,w) from s(xp) in SEDFIT.

7.     Using the ratio of s/D in the Svedberg equation and values for diffusion estimated by assuming 655 kDA, (the MW returned in SEDANAL), I calculate a MW of 655 kDa.  Thus I believe that the value for diffusion being estimated in SEDANAL is consistent with the 655 kDA molecular weight.

1.     Estimates of the diffusion coefficient in SEDFIT and SEDNTERP (and thus presumable also from SEDANAL) are not very different.

2.     The diffusion coefficient estimate in SEDFIT is 3.19E-7 cm2/sec and the value calculated in SEDNTERP 3.67E-7 cm2/sec (Teller approximation).

8.     Using the calculate M(s) function in SEDFIT and providing the experimental sedimentation coefficient noted above I need to input an ff0<1 (0.8967) in order to arrive at the 655kDA MW returned by SEDANAL.

1.     I understand that this is nonsensical as ff0 cannot be less than 1.

2.     Notably SEDNTERP version 1.09 also calculates a frictional ratio<1; namely SEDNTERP calculate ffp=0.9449.

3.     <!--[if !supportLists]--><!--[endif]-->The c(s) analysis in SEDFIT returns an ff0=1.47.

Thus to summarize:

1.     Relatively similar s20w values are determined in both SEDFIT and SEDANAL for the same data-set.

1.     <!--[if !supportLists]--><!--[endif]-->8.5s from SEDFIT

2.     <!--[if !supportLists]--><!--[endif]-->8.8s from SEDANAL

2.     SEDFIT calculates a MW almost exactly 2 times the value of the MW returned by SEDANAL for the same s20w.

3.     The estimates of diffusion in both programs are quite similar

4.     The frictional ratio ff0 in the SEDFIT analysis is 1.47 whereas the calculated ffp in SEDNTERP based on the observe MW in SEDANAL is <1.

5.     The frictional ratio calculated in SEDNTERP, assuming the MW=1.3 MDa, is 1.54

6.     There does appear to be heterogeneity in the major peak observed in the c(s) analysis.

Thank you in advance for your comments and suggestions.  I apologize for the length of this post, but in fairness, I am attempting to provide information that would enable an informed response.

Best regards

John Sumida

University of Washington

Analytical Biopharmacy Core
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