Dynamic B-cell proteome

This webpage has been designed to provide supplementary information to:

van Anken E, Romijn EP, Maggioni C, Mezghrani A, Sitia R, Braakman I & Heck AJ Sequential waves of functionally related proteins are expressed when B cells prepare for antibody secretion. Immunity 2003;18:243-53. full text pdf

Since we are still in the process of collecting more data we preferred to maintain the supplementary material at our own server. As such, we can update the site.

We would like to show the following quantitive measurements of the fraction of I.29µ+ cells that underwent differentiation towards a plasma cell phenotype upon activation with lipopolysaccharide (LPS) as supplementary information to figure 1 of Van Anken et al.

Cells were stained with anti mu and anti lambda antibodies. At every day of activation, we counted how many cells, within a population of 300 cells, displayed bright intracellular signals as a measure for synthesis of secretory IgM.

	day 0	day 1	day 2	day 3	day 4
Percentage of cells with bright intracellular IgM signal	8.7 %	24 %	38 %	58 %	78 %

Examples of anti-IgM immunofluorescence images	IF day 0	IF day 1	IF day 2	IF day 3	IF day 4

Cells were stained with anti mu antibodies and subjected to flow cytometry. Already at day 0 a strong signal was measured, as a consequence of µm surface expression (~100). Nevertheless, we arbitrarily set the threshold at 180 and calculated the percentage of cells above this threshold.

	day 0	day 1	day 2	day 3	day 4
Percentage of cells with an IgM signal above 180	11 %	27 %	56 %	57 %	66 %

Flow cytometry IgM

As a measure for morphological changes we measured both size (Forward Scatter (FSC)) and the granularity (refractivity Side Scatter (SSC)). For the FSC we uniformly set the threshold at 380 and for SSC at 300 (see fig 1D of Van Anken et al. or click below on Forward Scatter / Side Scatter). Cells first start to increase in size, which explains the increase in FSC, next cells also start to become more granular, which explains the increase in SSC. Finally, cells start to die, which might explain why the population displaying a smaller but granular phenotype (low FSC / high SSC) increases at later timepoints. Therefore, a good measure of morphological change upon activation is the decrease of the population (low FSC / low SSC), which represents the unactivated cells.

day 0

day 1

day 2

day 3

day 4

SSC	<300	>300	<300	>300	<300	>300	<300	>300	<300	>300
FSC >380	9 %	7 %	51 %	8 %	24 %	29 %	15 %	26 %	12 %	21 %
FSC <380	79 %	5 %	37 %	4 %	37 %	10 %	33 %	26 %	35 %	32 %

Forward Scatter / Side Scatter

As a supplement to fig. 1E of Van Anken et al. we give the percentages of cells that express syndecan-1 at the cell surface above the threshold level of 10.

	day 0	day 1	day 2	day 3	day 4
Percentage of cells with a syndecan-1 signal above 10	6.6 %	10 %	53 %	88 %	87 %

We followed B cell differentiation by a dynamic proteomics approach. I.29 mu+ lymphoma cells were activated with lipopolysaccharide (LPS) for various days. Cell lysates were analyzed by 2D electrophoresis. Large images of representative gels for every day of activation are given here.

2D gel day 0

2D gel day 1

2D gel day 2

2D gel day 3

2D gel day 4

Protein spots were visualized by silver staining. Spot numbering, quantification and matching of spots were performed with the PDQuestTM vs 6.0 software package. Normalization between gels was based on total protein amount (i.e. the total signal of valid spots) per gel. Background corrections were performed as follows:

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download as excel file background.xls

(note)

The 409 remaining spots were clustered according to expression kinetics as follows:

formulas

download as excel file clustering.xls

(note)

Mass spectrometry revealed the protein identities of 112 spots up to now, representing ~75 % of the total signal in the gel. We categorized identified proteins by biological function: ER resident proteins, cytoskeletal proteins etc. Most abundant proteins from six functional categories are listed in Figure 4 of Van Anken et al. The current data set of all identified spots is given in the following spreadsheet:

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download as excel file all_spots.xls

(note)

We found that biological function strongly correlated with synexpression clusters. As a supplement to figure 5A of Van Anken et al., we wish to show the expression kinetics of all spots indicated in figure 3 of Van Anken et al. Excerpts and locations of these proteins are given per functional category:

Cytoskeleton	excerpts	locations
Cytosolic & Mitochondrial chaperones	excerpts	locations
Metabolic Enzymes	excerpts	locations
Immune response	excerpts	locations
Redox balance	excerpts	locations
ER resident proteins	excerpts	locations

Because expression clusters correlated to functional groups, a picture emerged of the series of events that occur in the course of B cell differentiation. As a supplement to figure 5B of Van Anken et al., we wish to show the calculations we performed to establish the relative changes in expression of different cellular machineries. In addition, we show relative changes on a per cell basis to compare with relative changes on a total protein basis (figure 5B).

Changes on a per protein basis

Changes on a per cell basis

Calculations
Changes I	view in this browser	download as excel file	Lowry	view in this browser	download as excel file
Changes II	view in this browser	download as excel file	Per cell	view in this browser	download as excel file
Changes III	view in this browser	download as excel file
(note)			(note)

Graphs
per total protein	per cell

Last updated January 30th 2004 by Eelco van Anken
If you have any questions or comments, please contact us at folding@chem.uu.nl