1. Immunology and Inflammation
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Intravital quantification reveals dynamic calcium concentration changes across B cell differentiation stages

  1. Carolin Ulbricht
  2. Ruth Leben
  3. Asylkhan Rakhymzhan
  4. Frank Kirchhoff
  5. Lars Nitschke
  6. Helena Radbruch
  7. Raluca A Niesner
  8. Anja E Hauser  Is a corresponding author
  1. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Charitéplatz 1, Germany
  2. Immune Dynamics, Deutsches Rheuma-Forschungszentrum Berlin, ein Institut der Leibniz-Gemeinschaft, Germany
  3. Biophysical Analytics, Deutsches Rheuma-Forschungszentrum, ein Institut der Leibniz-Gemeinschaft, Germany
  4. Universität des Saarlandes, Germany
  5. Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
  6. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Germany
  7. Veterinary Medicine, Freie Universität Berlin, Germany
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Cite this article as: eLife 2021;10:e56020 doi: 10.7554/eLife.56020

Abstract

Calcium is a universal second messenger present in all eukaryotic cells. The mobilization and storage of Ca2+ ions drives a number of signaling-related processes, stress–responses, or metabolic changes, all of which are relevant for the development of immune cells and their adaption to pathogens. Here, we introduce the Förster resonance energy transfer (FRET)-reporter mouse YellowCaB expressing the genetically encoded calcium indicator TN-XXL in B lymphocytes. Calcium-induced conformation change of TN-XXL results in FRET-donor quenching measurable by two-photon fluorescence lifetime imaging. For the first time, using our novel numerical analysis, we extract absolute cytoplasmic calcium concentrations in activated B cells during affinity maturation in vivo. We show that calcium in activated B cells is highly dynamic and that activation introduces a persistent calcium heterogeneity to the lineage. A characterization of absolute calcium concentrations present at any time within the cytosol is therefore of great value for the understanding of long-lived beneficial immune responses and detrimental autoimmunity.

Introduction

During generation of humoral immunity to pathogens, calcium-mobilizing events in lymphocytes can communicate such diverse outcomes as migration, survival, stress responses, or proliferation. An elevation of cytoplasmic calcium from external space is mostly mediated through ligand binding to surface receptors (Baba et al., 2014). Especially in the germinal center (GC), where B cells fine-tune their B cell receptor (BCR) in order to become positively selected by T cells, ligand density in the form of native antigen (AG), stimuli for toll-like receptors (TLR), or chemokine receptors, is high. Selected B cells that leave the GCs fuel the pool of memory B cells and long-lived plasma cells (LLPCs). These cells produce high-affinity antibodies granting up to lifelong protection against threats such as infectious diseases, but also can account for the persistence of an autoimmune phenotype, when selection within the GC is impaired (Berek et al., 1991; da Silva et al., 1998; Hiepe et al., 2011; Victora and Nussenzweig, 2012). B cell activation by AG uptake through the BCR promotes calcium influx into B cells (Tolar et al., 2009). Calcium mobilization eventually switches on effector proteins and transcription factors like nuclear factor kappa B, nuclear factor of activated T cells, or myelocytomatosis oncogene cellular homolog, thereby inducing differentiation events and remodeling of metabolic requirements (Crabtree and Olson, 2002; Jellusova, 2018; Luo et al., 2018; Saijo et al., 2002; Su et al., 2002). Dependent on the amount of AG taken up and the quality of major histocompatibility complex II (MHCII)-mediated presentation to T follicular helper cells, B cells receive additional, costimulatory signals (Gitlin et al., 2015). Interestingly, recent studies propose that costimulatory signals have to occur within a limited period of time after initial BCR activation and that the limit is set by a calcium threshold, eventually leading to mitochondrial dysfunction (Akkaya et al., 2018). Thus, quantification of changes in absolute cytoplasmic calcium concentration tolerated by GC B cells would help to understand how B cell selection in the GC is accomplished.

In contrast to qualitative description, absolute calcium measurements in B cells have not yet been performed in vivo, partly because of the lack of internal concentration standards. Two-fluorophore genetically encoded calcium indicators (GECI) relying on Förster resonance energy transfer (FRET) can take on a calcium-saturated (quenched) and calcium-unsaturated (unquenched) condition, overcoming this issue. However, intravital application of quantitative FRET has been hampered by light distortion effects in deeper tissue. The differential scattering and photobleaching properties of the two fluorophores would lead to a false bias towards a higher quenching state. We here introduce a single-cell fluorescence lifetime imaging (FLIM) approach for absolute calcium quantification in living organisms that is tissue depth-independent. Both time-domain and frequency-domain FLIM technologies have been employed in the past 30 years to sense changes in pH, ionic strength, pO2, metabolism, and many other cellular parameters within living cells. Due to the impact of these parameters on the chemical structure, the fluorescence lifetime of the analyzed fluorophores can change (Elson et al., 2004; Lakowicz et al., 1992; Le Marois and Suhling, 2017). Particularly, the versatility of FLIM to quantify FRET quenching has been demonstrated and applied in various biological contexts (Chen et al., 2003; Levitt et al., 2020; Mossakowski et al., 2015). The enhanced cyan fluorescent protein (eCFP)/citrine-FRET pair-GECI TN-XXL is able to measure fluctuations in cytoplasmic calcium concentration through the calcium binding property of the muscle protein troponin C (TnC) (Mank et al., 2006). Calcium binding to the fluorophore-linker TnC quenches eCFP fluorescence through energy transfer to citrine (FRET), linking decreasing eCFP fluorescence lifetime to increasing calcium concentration. Whereas eCFP fluorescence lifetime changes with refractive index (Strickler and Berg, 1962) and may change upon large shifts in pH value, ionic strength, oxygenation, or temperature, these parameters hardly vary in the cytosol of living cells. Thus, we expect only changes in cytosolic calcium concentration to have an impact on the fluorescence lifetime of eCFP as donor in the TN-XXL construct. In addition, phasor analysis of FLIM data elegantly condenses multicomponent fluorescent decay curves into single vector-based information (the phasor) (Digman et al., 2008). For calcium concentration analysis in microscopic images, we first took advantage of the previously published titration curve of TN-XXL by Geiger et al., which we also confirmed in our experimental setup (Geiger et al., 2012). We further adapted the phasor-based calibration strategy to quantify calcium levels in vivo proposed by Celli and colleagues to the TN-XXL construct expressed in B lymphocytes (Celli et al., 2010). With this method, we are able to describe short- and long-term changes in absolute calcium concentrations within B cells during affinity maturation and differentiation into antibody-producing plasma cells.

We here describe the calcium reporter mouse strain ‘YellowCaB’ (termed after energy transfer to the yellow fluorescent protein citrine in case of calcium present in the cytosol of B cells). These mice express cytosolic TN-XXL in all CD19-positive cells. Intravital FLIM of adoptively transferred YellowCaB cells shows that calcium concentrations are highly dynamic in B cells involved in the GC reaction. We describe different patterns of calcium fluctuation regarding amplitude and baseline within non-activated and AG experienced cells and plasma blasts. We observe the emergence of Ca2+-high differentiated B cells and plasma blast populations, which might point to cells undergoing metabolic stress.

Results

YellowCaB: a system for FRET-based calcium analysis in B cells

Mice expressing a loxP-flanked STOP sequence followed by the TN-XXL-construct inserted into the ROSA26 locus were crossed with the CD19-Cre strain (Rickert et al., 1997). The offspring had exclusive expression of the GECI TN-XXL in CD19+ B lymphocytes, as confirmed by visualization of eCFP and citrine fluorescence by confocal microscopy after magnetic B cell isolation (Figure 1a, b). These YellowCaB cells were excited with a 405 nm laser that is capable of exciting eCFP but not citrine. The detection of yellow emission thus can be attributed to baseline FRET representing steady-state calcium levels. Expression of TN-XXL in YellowCaB mice was further confirmed by flow cytometry after excitation with the 488 nm laser and detection in a CD19+GFP+(green fluorescent protein) gate that would also detect citrine fluorescence. Citrine was found to be present in a substantial part of CD19+ B lymphocytes and was not detectable in the CD19- population (Figure 1c). Cd19cre/+ mice heterozygous for TN-XXL and Cd19cre/+ mice homozygous for TN-XXL did not differ in the proportion of cells within the CD19+GFP+ population, nor did male and female mice (Figure 1—figure supplement 1). In addition, no differences in total cell numbers and B cell numbers between Cd19cre/+Tn-xxl+/-, Cd19cre/+ Tn-xxl+/+, and wild-type mice were detected (Figure 1—figure supplement 1). We next set out to test if we could induce a FRET signal change under calcium-saturating conditions in the cytoplasm. The ionophore ionomycin is commonly used as positive control in in vitro experiments measuring calcium concentrations as it uncouples the increase of calcium concentration from the physiological entry sites of Ca2+ ions by forming holes in the cell membrane. When stimulated with ionomycin, a steep increase of the FRET level over baseline was recorded by flow cytometry in the GFP-channel after excitation with the 405 nm laser. Calcium-dependence of the signal increase was further independently confirmed by staining with the calcium sensitive dye X-Rhod-1, that shows a red fluorescence signal increase after calcium binding (Figure 1dLi et al., 2003).

Figure 1 with 1 supplement see all
The genetically encoded calcium indicator (GECI) TN-XXL is functionally expressed in CD19+ B cells of YellowCaB mice.

(a) Schematic representation of the genetically encoded calcium indicator TN-XXL with the calcium-sensitive domain troponin C (TnC) fused to donor fluorophore eCFP and acceptor fluorophore citrine. Binding of Ca2+ ions within (up to) four loops of TnC leads to quenching of eCFP and Förster resonance energy transfer (FRET) to citrine. (b) Confocal image of freshly isolated CD19+ B cells. Overlapping blue and yellow-green fluorescence of eCFP and citrine, respectively, can be detected after Cre-loxP-mediated expression of the TN-XXL vector in YellowCaB mice. (c) Flow cytometric analysis of TN-XXL expression in lymphocytes from YellowCaB mice. (d) Flow cytometric measurement of calcium flux after addition of ionomycin and phosphate buffered saline control. (e) Continuous perfusion imaging chamber for live cell imaging. (f) Confocal measurement of mean fluorescence intensity and FRET signal change after addition of ionomycin to continuously perfused YellowCaB cells. Data representative for at least 100 cells out of three independent experiments. (g) Frequency histogram of > 100 YellowCaB single cells, FRET analyzed after ionomycin stimulation. Threshold chosen for positive FRET signal change = 20% over baseline intensity.

In preparation of our intravital imaging experiments, we first tested if the YellowCaB system is stable enough for time-resolved microscopic measurements and sensitive enough for subtle cytoplasmic calcium concentration changes as they occur after store-operated calcium entry (SOCE). In SOCE, stimulation of the BCR with AG leads to drainage of intracellular calcium stores in the endoplasmic reticulum (ER), which triggers calcium influx from the extracellular space into the cytosol through specialized channels (Baba et al., 2014). We established a customizable perfusion flow chamber system to monitor and manipulate YellowCaB cells over the duration of minutes to hours (Figure 1e). Division of the fluorescence intensity of electron acceptor citrine by that of donor eCFP yields the FRET ratio (R), which is then put into relationship to baseline FRET levels. As expected, we detected a decrease of the eCFP signal, concurrent with an increased citrine fluorescence after the addition of 4 µg/ml ionomycin to continuous flow of 6 mM Krebs–Ringer solution. Overall, this resulted in a maximal elevation of ΔR/R of 50–55% over baseline (Figure 1f). Analysis of >100 cells showed that approximately in three quarters of the cells we were able to detect FRET in response to ionomycin treatment, and that the majority of these cells showed 35–40% FRET signal change. According to the two populations visible in the histogram, we defined a change of 20% ΔR/R as a relevant threshold for the positive evaluation of responsiveness (Figure 1g). In conclusion, we achieved the functional and well-tolerated expression of TN-XXL exclusively in murine CD19+ B cells for measurement of changes of cytoplasmic calcium concentrations.

Repeated BCR stimulation results in fluctuating cytoplasmic calcium concentrations

SOCE in B cells can be provoked experimentally by stimulation of the BCR with multivalent AG, for example, anti-Ig heavy chain F(ab)2 fragments. To test the functional performance of the GECI TN-XXL in YellowCaB cells, we stimulated isolated YellowCaB cells with 10 µg/ml anti-IgM F(ab)2 fragments to activate the BCR. In an open culture imaging chamber, we induced an elevated FRET signal with a peak height of >30% that lasted over 3 min (Figure 2a). The signal declines after this time span, probably due to BCR internalization or the activity of ion pumps. We tested antibody concentrations at 2, 4, 10, and 20 µg/ml. An antibody concentration of 2 µg/ml was not enough to provoke calcium flux (data not shown), whereas at 4 µg/ml anti-IgM-F(ab)2 we observed 20% an elevated ΔR/R over baseline (Figure 2b). At 20 µg/ml anti-IgM-F(ab)2, we detected no further FRET increase (Figure 2—figure supplement 1a, b). Thus, we conclude a concentration dependency of the GECI TN-XXL and saturating conditions at 10 µg/ml BCR heavy chain stimulation. Interestingly, the reaction is not completely cut off after the FRET signal has declined, but a residual FRET signal of about 7% compared to baseline values was measured for approximately 3.5 additional minutes (Figure 2a). Thus, B cells seem to be able to store extra calcium within the cytoplasm for some time. We therefore wondered if it is possible to stimulate YellowCaB cells more than once. For this purpose, we connected our imaging culture chamber to a peristaltic pump and took advantage of the fact that under continuous perfusion with Ringer solution the flow will dilute the antibody out of the chamber. This way, it is possible to stimulate B cells several times rapidly and subsequently, before BCRs are internalized, indicated by multiple peaks in ΔR/R (Figure 2b). In addition, stimulation of the BCR light chain using an anti-kappa antibody led to calcium increase within YellowCaB cells (Figure 2—figure supplement 1a). Of note, the resulting FRET peak is shaped differently, and concentrations > 150 µg/ml antibody were needed in order to generate a response.

Figure 2 with 1 supplement see all
B cell receptor (BCR) stimulation specifically leads to calcium mobilization in YellowCaB cells in vitro.

(a) Confocal measurement of Förster resonance energy transfer (FRET) duration (ΔR/R > 0) in non-perfused primary polyclonal YellowCaB cells after addition of 10 µg/ml anti-IgM-F(ab)2 (black) and ionomycin control (gray). Data representative for at least 35 single cells in four independent experiments. (b) Confocal measurement of FRET signal change after repeated addition of anti-IgM-F(ab)2 to perfused primary polyclonal YellowCaB cells. Data representative for at least 50 cells out of five independent experiments. (c) Confocal measurement of FRET signal change after addition of anti-IgM-F(ab)2 to perfused primary polyclonal YellowCaB cells following stimulation with anti-CD40 antibody and ionomycin as positive control. Examples of transient cytoplasmic (blue), intermediate (gray), and sustained calcium mobilization shown, area under the curve compared. Data representative for 26 cells out of two independent experiments. (d) Resulting FRET curve out for n = 7 primary polyclonal YellowCaB cells perfused with toll-like receptor (TLR)9 stimulator cytosine phosphate guanine (CpG) in Ringer solution and subsequent addition of anti-IgM-F(ab)2. (e) Mean FRET signal change over time after addition of TLR4 or TLR9 stimulation in combination with BCR crosslinking by anti-IgM-F(ab)2 in perfused polyclonal YellowCaB cells. n = 12 (top) and n = 8 (bottom), one-way ANOVA. Error bars: SD/mean.

Since T cell engagement and the binding of microbial targets to innate receptors like TLRs have also been described to raise cytoplasmic calcium in B cells (Ojaniemi et al., 2003; Pone et al., 2015; Ren et al., 2014), we investigated the response of YellowCaB cells after incubation with anti-CD40 antibodies, as well as the TLR4 and TLR9 stimuli lipopolysaccharide (LPS) and cytosine-phosphate-guanine-rich regions of bacterial DNA (CpG), respectively. Within the same cells, we detected no reaction to anti-CD40 treatment alone, but observed three types of shapes in post-CD40 BCR-stimulated calcium responses, which differed from anti-CD40-untreated cells (Figure 2a). These calcium flux patterns were either sustained, transient, or of an intermediate shape (Figure 2c). Sustained calcium flux even saturated the sensor at a level comparable to that achieved by ionomycin treatment. Cells that showed only intermediate flux maintained their ability to respond to ionomycin treatment at high FRET levels, as demonstrated by the ΔR/R reaching 0.4 again after stimulation (Figure 2c). Furthermore, integrated TLR and BCR stimulation affected the appearance of the calcium signal. The addition of TLR9 stimulus CpG alone had no effect on YellowCaB FRET levels; however, the subsequent FRET peak in response to anti-Ig-F(ab)2 was delayed (Figure 2d, e).

TLR4 stimulation via LPS could elevate calcium concentration of B cells, but only to a minor extent (Figure 2e). When TLR4 stimulation by LPS was performed before BCR stimulation, decreased FRET levels in response to anti-IgM-F(ab)2 were observed. We conclude that, in order to become fully activated, B cells are able to collect and integrate multiple BCR-induced calcium signals and that signaling patterns are further shaped by innate signals or T cell help. BCR inhibition abolishes a FRET signal change in response to anti-IgM-F(ab)2 (Figure 2—figure supplement 1b). Of note, we excluded the possibility that measured signal changes were related to chemokine stimulation. In vitro, we detected no FRET peak after applying CXCL12, probably because of lacking GECI sensitivity to small cytoplasmic changes (Figure 2—figure supplement 1c, d). Thus, the YellowCaB system is well suited for the detection of BCR-induced cytosolic calcium concentration changes.

Fluctuating calcium levels are observed as a result of sequential cell contacts in vivo

We next set out to investigate if the ability of B cells to collect calcium signals sequentially is also shared by GC B cells. For two-photon intravital imaging, nitrophenyl (NP)-specific B1-8hi B cells from YellowCaB mice were magnetically isolated and transferred into wild-type hosts, which were subsequently immunized with NP-chicken gamma globulin (CGG) into the right foot pad (Shih et al., 2002a). Mice were imaged at day 8 p.i. when GCs had been fully established. Activated TN-XXL+ YellowCaB cells had migrated into the GC, as confirmed by positive PNA- and anti-FP-immunofluorescence histology (Figure 3a). At this time point, mice were surgically prepared for imaging as described before (Ulbricht et al., 2017). Briefly, the right popliteal lymph node was exposed, moisturized, and flattened under a cover slip sealed against liquid drainage by an insulating compound. The temperature of the lymph node was adjusted to 37°C and monitored during the measurement. Our experiments revealed that the movement of single YellowCaB cells is traceable in vivo. Calcium fluctuations can be made visible by intensity changes in an extra channel that depicts the FRET signal, as calculated from relative quenching of TN-XXL. Color coding of intensity changes in the FRET channel showed time-dependent fluctuations of the signal and, in some particular cases, a sustained increase after prolonged contacts between two YellowCaB cells (Figure 3b, Video 1). Interestingly, FRET intensity seemed to be mostly fluctuating around low levels in moving cells, whereas sustained increase required cell arrest, as reported previously (Negulescu et al., 1996; Shulman et al., 2014), (Figure 3—figure supplement 1). The observed calcium fluctuations might therefore coincide with cell-to-cell contacts between follicular dendritic cells (FDCs) and B cells, resulting in AG-dependent BCR stimulation. To test for this, we first measured the colocalization between signals within the FDC channel and the citrine channel. The intensity of colocalization Icoloc of all cells was plotted as a function of frequency and biexponentially fitted (Figure 3c). We set the threshold for a strong and sustained colocalization of FDCs and B cells to an intensity of 150 AU within the colocalization channel. At this value, the decay of the biexponential fit was below 10%. We thus decided to term all cells with a colocalization intensity = 0 (naturally the most abundant ones) not colocalized, cells with a colocalization intensity between 1 and 150 transiently colocalized to FDCs (‘scanning’ or shortly touching the FDCs), and all cells above this intensity threshold strongly or stably colocalized. We compared the relative FRET intensity changes ΔR/R of two tracked cells (Figure 3b, cells 1 and 2), where baseline R is the lowest FRET intensity measured, and its contacts to FDCs. We detected several transient B-cell–FDC contacts in cell 1 that were followed by a gradual increase of ΔR/R, indicating an increase of cytoplasmic calcium concentration (Figure 3d). Cell 2 kept strong FDC contact over the whole imaging time and maintained elevated, mostly stable values. These experiments confirmed that GC B cells are able to collect calcium as a consequence of repeated contact events, which are mediated by B cell-to-FDC contacts in vivo.

Figure 3 with 1 supplement see all
YellowCaB cells form productive germinal centers in vivo and show active B cell receptor signaling after cell-to-cell contacts.

(a) Histological analysis of host mouse lymph nodes after adoptive transfer of YellowCaB cells. TN-XXL (green)-positive cells cluster in IgD (blue)-negative regions; a germinal center phenotype is confirmed by PNA staining (red). Scale bar 50 µm. (b) Stills of ratiometric intravital imaging of adoptively transferred YellowCaB cells. 3D surface rendering and single-cell tracking (track line in yellow) with relative color coding ranging from blue = low ΔR/R to red = high ΔR/R (c) Histogram showing segmented objects binned due to colocalization intensity within bin width of 20 AU and biexponential fit of data. Total number of objects = 6869. A curve decay of <10% was set as threshold, parting transient from strong B cell–FDC contact. All cells with colocalization intensity <1 were assigned negative. (d) Colocalization intensities of tracked cells 1 and 2 over time versus Förster resonance energy transfer signal change of cells 1 and 2 over time. Contact events to FDCs were assigned numbers #1, #2, and #3.

Video 1
Detail of intravital ratiometric imaging (day 8 p.i.) within germinal center.

YellowCaB cells had been adoptively transferred, and FDCs were in vivo-labeled with anti-CD21/35 antibody (white). 3D surface rendering and single-cell tracking (track line in yellow) with color coding ranging from blue = low ΔR/R to red = high ΔR/R. 103 frames, 7 frames per second (fps), scale bar 50 µm.

Calibration of the TN-XXL construct for in vivo quantification of cytosolic calcium in B lymphocytes using the phasor approach to FRET–FLIM

The comparison of calcium responses in different B cell subsets of multiple GCs requires normalization of TN-XXL FRET. Since this is hardly achievable in tissue due to its inherent heterogeneity, we aimed for the determination of absolute cytosolic concentration values in YellowCaB cells by calibration of TN-XXL FRET intensities. However, ratiometric calibration would require equal conditions for donor and acceptor fluorescence signals, especially in terms of scattering and photobleaching. Due to the aforementioned heterogeneous tissue composition, these requirements cannot be met in vivo (Radbruch et al., 2015). Therefore, donor FLIM is the appropriate solution as it circumvents comparative evaluation of different fluorescence signals. Fluorescence lifetime is defined as the mean time a fluorescent molecule stays in an elevated energetic state after excitation, before photon emission and relaxation to the ground state take place. As a fully calcium-quenched eCFP in the GECI TN-XXL would transfer its energy mainly to citrine, its fluorescence lifetime would be measurably shorter than that of unquenched eCFP. Time-correlated single-photon counting (TCSPC) devices offer the possibility of simultaneous photon detection and recording of the respective fluorescent lifetimes within a nanosecond scale, yielding a fluorescence lifetime decay histogram of photons. Deriving fluorescent lifetimes τ from the eCFP decay curve of photon histograms requires fitting. We decided to use the phasor analysis as it virtually transfers time-resolved fluorescence data into phase domain data by discrete Fourier transformation (Digman et al., 2008). This approach overcomes the obstacles of multicomponent exponential analysis and yields model-free, readily comparable pixel- or cell-based plots that assign a position within a semicircle to each data point, dependent on the mixture of lifetime components present (Leben et al., 2018).

Typically, data correction based on reference dyes is needed for reliable phasor analysis (Ranjit et al., 2018). We verified the reliability of our TCSPC setup to acquire high-quality fluorescence decays in an image to be evaluated using the phasor approach by measuring the instrument response function given by the second harmonic generation signal (SHG) of potassium-dihydro-phosphate crystals (laser excitation wavelength 940 nm) and the fluorescence decays of eGFP, expressed in HEK cells (laser excitation wavelength 900 nm). As shown with the phasor plots of the raw data (Figure 4a), both the SHG signal and the eGFP fluorescence are located in expected positions on the semicircle (Murakoshi et al., 2008; Rinnenthal et al., 2013). Therefore, no further correction of the data is necessary in our system.

Figure 4 with 1 supplement see all
Calibration of the TN-XXL construct using fluorescence lifetime imaging of its Förster resonance energy transfer donor.

(a) Left panel: phasor plot of second harmonic generation signal of potassium dihydrogen phosphate crystals and lifetime image (inset, scale in picoseconds) corresponding to the instrument response function (τ = 80 ± 10 ps). λexc = 940 nm, λdetection = 466±20 nm. Right panel: phasor plot of GFP fluorescence expressed in HEK cells and fluorescence lifetime image (inset, the same scale as in the left panel), corresponding to mono-exponential decay GFP fluorescence (τ = 2500 ± 100 ps). λexc = 900 nm, λdetection = 525±25 nm. (b) Left panel: fluorescence decays of CFP in TN-XXL construct from lysates of B lymphocytes at 0 nM, 602 nM, and 39 µM free calcium. Right panel: titration curve of TN-XXL resulting from the time-domain evaluation of decay curves as shown in the left panel (three independent experiments). λexc = 850 nm, λdetection = 466±20 nm. (c) Phasor plot of representative data shown in (b) – time-resolved fluorescence images 422 × 422 pixels (200 × 200 µm²); time-bin = 55 ps; time window = 12.4 ns. Blue phasor cloud (with central phase vector p free) corresponds to 0 nM free calcium, gray cloud (with central phase vector p lysate) to 602 nM free calcium, and red cloud (with central phase vector p FRET) to 39 µM free calcium. The dotted line connects the centers of the blue and red clouds, respectively, whereas the gray cloud is located on this line. The dotted line corresponds to the calibration segment as it results from measurements of TN-XXL in cell lysates. (d) Left panel: representative fluorescence decays of eCFP in two B lymphocytes (indicated by red and blue arrowheads in the inset image, right panel) expressing TN-XXL in the medullary cords of a popliteal lymph node of a YellowCaB mouse (right panel) and corresponding mono-exponential fitting curves (red fitting curve: τ = 703 ± 56 ps; blue fitting curve: τ = 1937 ± 49 ps). We measured τ = 2303 ± 53 ps in splenocytes expressing only CFP. (e) Phasor plot showing time-resolved CFP fluorescence data from three lymph nodes, in three YellowCaB mice (light gray – with central phase vector p ln3, gray – with central phase vector p p ln1, and dark gray – with central phase vector p ln2) – time-resolved fluorescence images 505 × 505 pixels (512 × 512 µm²); time-bin = 55 ps; time window = 12.4 ns. Additionally, the calibration segment (dotted line) and the phasor clouds measured in lysates of B lymphocytes expressing TN-XXL at 0 nM and 39 µM free calcium from (c) are displayed. (f) Phasor plots of the CFP fluorescence (time-resolved fluorescence images 505 × 505 pixels / 512 × 512 µm²) acquired at three different depths (100, 130, and 160 µm from the organ capsule surface) in the popliteal lymph node of a YellowCaB mouse. The red line in each phasor plot represents the calibration segment also displayed in (c) and (e). (g) Phasor plot of signal acquired in the lymph node of a non-fluorescent mouse. λexc = 850 nm, λdetection = 466±20 nm.

As the TN-XXL construct is exclusively expressed in the cytosol of B lymphocytes from YellowCaB mice, the following equilibrium holds true for Ca2+ (free cytosolic calcium), TNXXL (the calcium-free FRET construct, i.e., the unfolded tertiary structure of TnC), and Ca2+TNXXL (the FRET construct saturated by calcium, i.e., the completely folded tertiary structure of TnC):

(1) Ca2++TNXXL  Ca2+TNXXL

characterized by the dissociation constant Kd:

(2) Kd=[ Ca2+TNXXL ][ Ca2+ ][ TNXXL ]

As measured in lysate of YellowCaB B cells expressing TN-XXL, the fluorescence lifetime τ of the donor eCFP of the FRET Ca-sensitive construct TN-XXL depends on the free calcium concentration [Ca2+] following a sigmoidal function (Eq. 3).

(3) τ=τFRET+τfreeτFRET1+10(log10[Ca2+]log10Kd)Hill_slope

with τfree the fluorescence lifetime eCFP at 0 nM free calcium, and τFRET the fluorescence lifetime of completely FRET-quenched eCFP in the TN XXL-construct at 39 µM free calcium. By fitting the fluorescence lifetime of eCFP in TN-XXL excited at 850 nm and detected at 460 ± 30 nm acquired in time domain using our TCSPC system at various free calcium concentrations, we determined Kd = 475 ± 46 nM and Hill slope = −1.43 ± 0.17 (Figure 4b). Thus, we can calculate the free calcium concentration as

(4) log10[ Ca2+ ]=log10Kdlog10(τfreeτFRETττFRET1)Hill_slope

Similar to the calculation in time domain, for the phase domain we can express each phasor vector p based on the formalism proposed by Celli and colleagues (Celli et al., 2010) as

(5) p=[ Ca2+ TNXXL ]εFRETpFRET+[ TNXXL ]εfreepfree[ Ca2+ TNXXL ]εFRET+[ TNXXL ]εfree

with εfree and εFRET the relative brightness (Chen et al., 1999; Müller et al., 2000) of eCFP in TNXXL at 0 nM and saturated (39 µM) free calcium, given by the following equations:

(6) εfree=δCFPηfree=δCFPkFτfree
(7) εFRET=δCFPηFRET=δCFPkFτFRET

with δCFP the effective two-photon absorption cross section of eCFP (independent of the pathways of relaxation from the excited state), and kF the fluorescence rate of eCFP in vacuum, that is, no quenching due to surrounding molecules.

The phase vectors can be written also as complex numbers as given by the following equations:

(8) p=Re+iIm
(9) pfree=Refree+iImfree
(10) pFRET=ReFRET+iImFRET

We determined the averages and median real and imaginary values of the phasor distributions obtained by performing FRET–FLIM in lysates of YellowCaB B cells at 0 nM and 39 µM free calcium to be Refree = 0.4035 (average), 0.40326 (median); Imfree = 0.45801 (average), 0.45779 (median) and ReFRET = 0.82377 (average), 0.82203 (median); ImFRET = 0.3225 (average), 0.32093 (median), respectively, indicating that both distributions are symmetric, corresponding to normal distributions (Figure 4c).

From Eqs. (5–10) combined with Eq. (2), the free cytosolic calcium concentration is given by

(11) [Ca2+]=KdεfreeεFRETppfreepFRETp=KdτfreeτFRET(ReRefree)2+(ImImfree)2(ReFRETRe)2+(ImFRETIm)2

Thus, the free calcium concentration depends only on the Kd, tfree, tFRET as determined from the calibration curve measured in lysate and the phase vectors, describing the extreme states of eCFP in the TN-XXL construct.

Since variations in refractive index, ion strength, pH value, or temperature in the cytosol of the B lymphocytes may additionally influence the fluorescence lifetime of eCFP, as well as the phase vectors pfree and pFRET (Jameson et al., 1984; Scott et al., 1970), we verified whether the FRET trajectory of the-TN-XXL construct changes in the cytosol of B lymphocytes in cell culture (Figure 4—figure supplement 1) and under in vivo conditions, in lymph nodes (Figure 4d, e). We found that in all our measurements the phasor cloud lays on the trajectory determined in lysate solutions (Figure 4e). Measurements performed at different depths in lymph nodes led to the same result: there is no change in the slope of the trajectory at different tissue depths (Figure 4f).

To assess the impact of autofluorescence on the interpretation of the fluorescence signal in the phasor plot and, thus, on the cytosolic calcium levels, we also performed FLIM in B cell follicles of lymph nodes of non-fluorescent wild-type mice. While the acquired signal was extremely low, the phasor cloud in these measurements was located around position (0,0) in the plot, indicating that it mainly originates from detector noise (Figure 4g).

We compared the results of cytosolic free calcium concentration determined using the time-domain and the phase-domain approach and found deviations of max. 5% between the evaluation pathways using Eqs. (4) and (11) due to numerical uncertainty. We determined the calcium dynamic range of TN-XXL measured by phasor-analyzed FRET–FLIM to span between 100 nM and 4 µM free calcium, with the linear range of the titration curve in the range between 265 and 857 nM free calcium.

Comparative FLIM–FRET reveals heterogeneity of absolute calcium concentrations in B cells in vivo

Adoptively transferring AG-specific YellowCaB cells and non-AG-specific (polyclonal) YellowCaB cells (stained ex vivo) allowed us to divide GC B cells into five different populations based on their location in the imaging volume and their fluorescent appearance (Figure 5a, b). At day 8 p.i., polyclonal YellowCaB cells, identified by their red labeling, mostly lined up at the follicular mantle around the GC, with some of them having already entered into activated B cell follicles. AG-specific, citrine-positive B1-8hi:YellowCaB cells were found clustered in the GC, close to FDCs, outside of GC boundaries, or as bigger, ellipsoid cells in the extrafollicular medullary cords (MC), probably comprising plasma blasts (Figure 5b, left). Color-coded 2D- and 3D FLIM analysis of these populations confirmed that calcium concentrations were fluctuating within all of those B cell populations, and that most B cells were maintaining relatively high mean eCFP fluorescence lifetimes and therefore low calcium concentrations on average, with only few exceptions (Figure 5b, middle and right, Video 2).

Figure 5 with 1 supplement see all
Determination of absolute calcium concentration by intravital fluorescence lifetime imaging of germinal center (GC) B cell populations.

(a) Cell transfer and immunization strategy for intravital imaging of antigen (AG)-specific and polyclonal YellowCaB cells. (b) Left: maximum intensity projection of a z-stack, intravitally imaged GC, and medullary cords (MCs). B cells were distinguished as polyclonal, non-AG-specific YellowCaB cells (red), AG-specific YellowCaB cells, and AG-specific cells inside the MC. Middle: color-coded fluorescence lifetime image with lifetimes of unquenched eCFP depicted in blue and lifetimes of quenched eCFP in red. Right: 3D-rendered, color-coded z-stack showing absolute calcium concentrations in GC and MC. Yellow arrows point to cells containing high cytoplasmic calcium. (c) Bulk analysis of absolute calcium concentrations in segmented single-cell objects from B cell subsets at any given time point measured. The dynamic range of the genetically encoded calcium indicator (GECI) TN-XXL is indicated by blue dashed lines. (d) Time-resolved analysis of calcium concentrations in tracked segmented objects corresponding to B cell subsets in (c). 2 frames per minute. Non-AG-specific YellowCaB cells (left, n = 92 tracks); AG-specific YellowCaB cells (middle, n = 169 tracks); and extrafollicular AG-specific YellowCaB cells in MC (right, n = 69 tracks). The dynamic range of the GECI TN-XXL is indicated by blue dashed lines.

Video 2
Side-by-side depiction of fluorescence, fluorescence lifetime imaging, and cell-based phasor data of intravitally imaged germinal center (day 8 p.i.), single z-plane.

Left: fluorescence data with antigen (AG)-specific YellowCaB cells (green) and stained non-AG-specific YellowCaB cells transferred 1 day prior to imaging (red; autofluorescence of capsule also visible in the same channel). 4 fps, scale bar 50 µm. Middle: false color-coded presentation of fluorescence lifetime τ (0–3000 ps, see range scale in Figure 5b). 4 fps, scale bar 50 µm. Right: raw cell-based phasor plot with cells segmented according to fluorescence and spatial distribution, subsets indicated. 4 fps.

Bulk analysis of cells revealed additional calcium-intermediate and calcium-high cell subsets present among AG-specific cells and plasma blasts (Figure 5c, Video 3). Especially for plasma blasts this was somehow unexpected, given that these are thought to downregulate their surface BCR during differentiation.

Video 3
Detail of Video 2 within medullary cords and side-by-side depiction of fluorescence and fluorescence lifetime imaging data, single z-plane.

Left: fluorescence data with antigen-specific YellowCaB cells (green) and autofluorescence of capsule (red). 4 fps, scale bar 50 µm. Right: false color-coded presentation of fluorescence lifetime τ (0–3000 ps, see range scale in Figure 5b). 4 fps.

Comparison of AG-specific cells inside GCs with those outside GCs and non-AG-specific cells inside GCs as well with those outside GCs showed that the distribution of calcium concentrations of these B cells was dependent on BCR specificity and rather independent from their location within the imaging volume, despite higher fluctuation seen among AG-specific populations (Figure 5—figure supplement 1). These maxima were reached as transient fluctuation peaks, that is, periods shorter than 1 min, in which these concentrations seem to be tolerated. Calcium values exceeding the dynamic range of TN-XXL (>857 nM) were recorded for all measured subsets, but most cells >857 nM were found among intrafollicular AG-specific B cells and extrafollicular AG-specific B cells (Figure 5d). The heterogeneity in temporal calcium concentrations therefore is smallest among non-AG-specific B cells, increases with activation in AG-specific GC B cells, and is most prominent among MC-plasma blasts. The high cytoplasmic calcium levels observed in MC-plasma blasts were unlikely to be the result of chemokine-induced signaling since only a minor calcium increase was detected after CXCL12 stimulation in vitro (Figure 2—figure supplement 1d). Thus, a progressive heterogeneity of calcium signals within B cells can be seen alongside the process of activation and differentiation.

Functional relevance of increased calcium concentration among extrafollicular YellowCaB cells

We next wondered if high cytoplasmic calcium levels within certain B cell subsets could be the result of AG-mediated signals. We therefore intravenously (i.v.) injected NP-bovine serum albumine (BSA) (66 kDa) into mice that had been adoptively transferred with B1-8hi (AG-specific) YellowCaB cells and recorded absolute calcium concentrations within the GC by intravital FLIM. Antigens up to 70 kDa have been reported to be transported into the follicles via conduits in less than 5 min (Roozendaal et al., 2009). Accordingly, AG-specific GC YellowCaB cells significantly upregulated cytoplasmic calcium after AG injection within minutes (Figure 6a, top panel, Figure 6—figure supplement 1). To test if this concentration increase could be explained via BCR-dependent AG recognition, we pre-injected the inhibitor of Bruton’s tyrosine kinase (BTK) ibrutinib (Hendriks et al., 2014), which blocks BCR downstream activation, in a control group. BTK inhibition could abrogate the increase in mean cytoplasmic calcium after additional injection of NP-BSA (Figure 6a, bottom panel) and even seemed to downregulate baseline signals (Figure 6—figure supplement 1). In addition, we found that also in 48 hr LPS/ interleukin 4 (IL-4)-cultured B1-8-plasma blasts, an increase in calcium was detectable after addition of NP-BSA (Figure 6—figure supplement 2), suggesting that stimulation via AG remains possible in at least a proportion of these differentiated B cells.

Figure 6 with 3 supplements see all
Antigen dependency of calcium elevation in germinal center (GC) and extrafollicular B cells.

(a) Top panel: absolute calcium concentrations measured in antigen (AG)-specific GC B cells before and after in vivo injection of NP-BSA. Exemplary results (left) and pooled data from three imaged mice (right). Bottom panel: absolute calcium concentrations measured in AG-specific GC B cells before and after in vivo injection of the Bruton’s tyrosine kinaseinhibitor ibrutinib, followed by injection of NP-BSA. Exemplary results (left) and pooled data from three imaged mice (right). (b) z-stack of intravitally imaged lymph node with GC (white line) and subcapsular sinus (indicated by SHG, blue). CD169+ macrophages (red, contacts [yellow], YellowCaB cells [green]). Size 500 × 500 × 78 µm. Scale bar 60 µm. (c) Top: Fluorescence lifetime imaging measurement of mean absolute calcium concentration of YellowCaB cells showing no (–), transient (+), or strong (++) overlap with CD169+ signal. n = 1000, ANOVA analysis, mean and SD. Bottom: Single-cell track of a YellowCaB cell making transient contact to a macrophage; blue: colocalization intensity (AU); black: change of absolute calcium concentration.

These results led us to investigate the possible sources of AG abundance outside of GCs and their effect on calcium in B cells. Earlier studies proposed that one possible AG source in lymph nodes are subcapsular sinus macrophages (SCSM) (Junt et al., 2007; Moran et al., 2018; von Andrian and Mempel, 2003). We tested if SCSM contacts could be the cause of elevated calcium levels in extrafollicular B cells. We intravitally imaged wild-type host mice that have been adoptively transferred with B1-8hi:YellowCaB cells and received an injection of efluor660-labeled anti-CD169 antibody together with the usual FDC labeling 1 day prior to analysis. We concentrated on the area beneath the capsule, identified by second harmonic generation signals of collagen fibers in this area. Thresholds of colocalization between CD169+ macrophages and TN-XXL+ YellowCaB cells are described in Figure 6—figure supplement 3. Together, these methods led to a 3D visualization of the SCS with CD169 stained macrophages, lined up in close proximity (Figure 6b). AG-specific YellowCaB cells were detected clustering in GCs nearby. Extrafollicular YellowCaB cells crowding the SCS space were found to have multiple contact sites to SCSM. Some B cells were observed to migrate along the SCS, possibly scanning for antigenic signals (Video 4). Bulk analysis of YellowCaB cells and their colocalization with SCSM showed that the calcium concentration in YellowCaB cells with direct contact to SCSM reaches values that are more than doubled compared to values in cells that were not in contact, and that calcium concentration is positively correlated with contact strength (Figure 6c, top). Single-cell tracking and simultaneous analysis of absolute calcium concentration and colocalization intensity revealed that the increase of cytoplasmic calcium is a direct cause of B-cell-to-SCSM contacts (Figure 6c, bottom). We conclude that contacts of B cells to SCSM could induce elevation of B cell cytoplasmic calcium concentrations, presumably due to antigenic activation, with the absolute concentrations being dependent on the contact strength.

Video 4
3D projection of intravital imaging of germinal center and subcapsular sinus.

YellowCaB cells (green, with track lines) and subcapsular sinus macrophages (red), stained by CD169 in vivo labeling. White circles highlight antigen-specific B cells migrating along subcapsular space. 4 fps, scale bar 50 µm.

Discussion

Intravital imaging technologies have contributed greatly to a better understanding of the dynamic processes in GCs. AG-capture, cycling between zones, and development of clonality patterns have been made visible by two-photon microscopic techniques (Hauser et al., 2007; Suzuki et al., 2009; Tas et al., 2016; Victora et al., 2010). Furthermore, important functional in vivo data like signaling in T helper cells have been collected using a calcium-sensitive protein (Kyratsous et al., 2017; Shulman et al., 2014).

However, calcium mobilization within GC B cells was mostly investigated via ex vivo analysis of sorted cells after adoptive transfer and immunization, or BCR activation was measured using a non-reversible BCR signaling reporter like Nur77, altogether neglecting calcium flux (Khalil et al., 2012; Mueller et al., 2015). These data suggested that BCR signaling in the GC is reduced. However, no statement was made about the dynamics and timely coordination of (even small) calcium pulses and the relation to their microenvironment. In fact, a recent study confirmed that BCR signals play a central role in positive selection and display a fragile interdependence with costimulatory events (Luo et al., 2018).

BCR-regulating surface proteins like CD22 or sialic acid-binding immunoglobulin-type lectins have been related to development of autoimmunity and point out BCR-mediated calcium flux as an important component, not only during B cell development but also in their differentiation to effector cells (Hoffmann et al., 2007; Jellusova et al., 2010; Müller and Nitschke, 2014; Nitschke and Tsubata, 2004; O'Keefe et al., 1999). Apart from regulating gene transcription, cytosolic calcium mobilized has been shown to be essential for F-actin remodulation and B cell spreading on antigen presenting cells (Maus et al., 2013). Furthermore, cytosolic calcium concentration is closely linked to metabolic reprogramming of activated B cells and their cell fate (Boothby and Rickert, 2017; Caro-Maldonado et al., 2014). It has been shown that SOCE is acting directly on the mitochondrial capability to import cytosolic calcium (Shanmughapriya et al., 2016). In mitochondria, calcium is regulating ATP production through increase of glycolysis and fatty acid oxidation, processes for which activated and GC B cells have high demands, although there is controversy as to which of the two metabolic pathways predominates in GC B cells (Griffiths and Rutter, 2009; Jellusova et al., 2017; Maus et al., 2017; Weisel et al., 2020).

For flexible analysis of calcium mobilization in cells of the CD19+ lineage, we developed a novel transgenic reporter system and image processing approach, enabling quantification of cytosolic calcium concentrations. The FRET-based GECI TN-XXL can be used stably in moving, proliferating, and differentiating lymphocytes, and the reversibility of the sensor makes it suitable for longitudinal intravital measurements. Switching from ratiometric acquisition of FRET-donor and FRET-acceptor fluorescence intensities to measuring FRET-donor fluorescence lifetime enabled quantification of calcium concentrations in absolute numbers.

A first advantage of FRET–FLIM in tissue is that different photobleaching or scattering properties of the fluorophores can be neglected. We further decided to perform all analyses based on the phasor approach that circumvents the problem of multiexponential fluorescence decays we encounter measuring a two-fluorophore FRET-based GECI in tissue. For titration of TN-XXL, we used lysate of YellowCaB plasma blasts. Besides TN-XXL affinity, also eCFP fluorescence lifetime itself may be influenced by large shifts in pH value, ionic strength, oxygenation, or temperature. We ensured that these parameters were similar in lysates and cells, except for the temperature, which was at room temperature for calibration. Temperature was reported to only slightly change the fluorescence lifetime of a CFP variant (cerulean) (Laine et al., 2012). However, for accuracy purposes and in order to exclude such artifacts when determining cytosolic calcium levels in B lymphocytes within lymph nodes of YellowCaB mice, we adapted the phasor-based calibration strategy proposed by Celli et al., 2010 for the use of Calcium Green in skin samples to our data. In this way, we were able to reliably determine absolute values of cytosolic calcium concentrations in B cells within lymph nodes.

In our set-up, we have shown that TN-XXL in B cells has suitable sensitivity and fast reversibility. This key factor made it possible to observe repeated and partially sustained calcium elevation in the cytoplasm, showing that B cells are able to collect sequential signals, possibly up to a certain threshold, which determines their fate.

In support of that, B cellular calcium concentration must not constitutively exceed a certain value in order to prevent mitochondrial depolarization (Akkaya et al., 2018; Bouchon et al., 2000; Niiro and Clark, 2002). Gradual calcium elevation could be a mechanistic link for that. For example, calcium levels of >1 µM over the duration of >1 hr have been reported to be damaging to other cell types, such as neurons (Radbruch et al., 2015; Siffrin et al., 2015). Accordingly, stimulation of AG receptors via large doses of soluble AG can lead to tolerogenic apoptosis in GC B cells, which could be explained by uninhibited calcium influx (Nossal et al., 1993; Pulendran et al., 1995). Since apoptosis is the default fate for B cells in the GC reaction (Mayer et al., 2017), CD40 and TLR signaling might contribute to limiting cytoplasmic calcium concentrations, and thus promote survival of B cell clones with appropriate BCR affinity (Akkaya et al., 2018; Eckl-Dorna and Batista, 2009; Pone et al., 2015; Pone et al., 2012; Pone et al., 2010; Ruprecht and Lanzavecchia, 2006). For CD40 signaling in immature B cells, this has been confirmed (Nguyen et al., 2011). Our data does show that TLR signaling can attenuate calcium flux in stimulated B cells, while CD40 can either attenuate or augment the calcium response (Figure 2). Whether the different outcomes of CD40 stimulation are dependent on the affinity of the BCR and its efficiency in presenting AG (Schwickert et al., 2011; Shulman et al., 2013) will be subject of further studies.

Measuring absolute calcium concentration in GC B cells after administration of soluble AG in vivo, we could detect an increase of B cell calcium that is attenuated by BCR inhibitor ibrutinib, showing that BCR-mediated calcium increase is substantially contributing to calcium heterogeneity in the GC. However, the interpretation of the data should not neglect other causes of calcium elevation, given the multifaceted role of this second messenger. Therefore, it is likely that apart from BCR signaling, also other events, like binding of non-AG ligands and stress-related calcium release from internal stores, contribute to an overall cytosolic calcium increase, which needs to be regulated in order to prevent a damaging calcium overload. Causes for stress-related cytosolic calcium elevations in cells can be hypoxia, a condition reported to be present within GCs (Jellusova et al., 2017); nutrient deprivation, which mostly will affect highly proliferative cells like GC B cells; or ER-calcium release as a result of the unfolded protein response that is indispensable in plasma cells (Díaz-Bulnes et al., 2020; Høyer-Hansen and Jäättelä, 2007; Lam and Bhattacharya, 2018). The complex interaction of factors makes an exact characterization of the absolute calcium concentration in various B cell subsets crucial in order to obtain information about their regulation and containment. This characterization should preferably be done intravitally since any manipulation of cells can result in enormous non-physiological variations of cytosolic calcium levels.

For the first time, we determined absolute values of B cell cytoplasmic calcium concentrations during the GC reaction within living mice. It appears that BCR AG specificity and state of differentiation are closely related to distinct degrees of heterogeneity of calcium concentrations. Notably, heterogeneity was also evident in extrafollicular B cells in the SCS region, as well as in plasma blasts. The latter actually reach the highest calcium concentrations within the B cell compartment of the lymph node. We also observed an increase of cytoplasmic calcium in plasma blasts after stimulation with specific AG in vitro. These data are in line with a report of residual BCR signaling occurring in antibody-secreting cells (Pinto et al., 2013), which challenges the finding that B cells completely downregulate their surface BCR during differentiation to plasma cells (Manz et al., 1998). Our experiments were done in short-lived plasma blasts, not LLPC, for which the situation could be different. Therefore, an investigation of possible BCR signaling in LLPC is of high interest. Stimulation with the chemokine CXCL12, which has previously been shown to induce migration of antibody-secreting cells (Fooksman et al., 2010; Hauser et al., 2002), resulted only in a minor increase of cytoplasmic calcium in plasma blasts in our hands.

In B cells that have exited the GC, ongoing calcium flux might reflect reactivation. We confirmed that B cells in contact to SCSM had significantly higher cytosolic calcium concentrations. These are possibly attributed to BCR signaling since the SCS has been proposed as a site of reactivation of memory B cells via AG (Moran et al., 2018).

The YellowCaB system provides a tool for measuring calcium as ubiquitous, universal cellular messenger, integrating signals from various pathways, including chemokine receptor signaling and intrinsic calcium release or BCR-triggered activation. Importantly, changes in mitochondrial membrane potential and/or the integrity of the ER also lead to varying calcium concentrations within the cytoplasm since both act as major intracellular calcium buffering organelles (Kass and Orrenius, 1999) A close connection between mitochondrial calcium homeostasis, altered reactive oxygen speciesproduction, and the expression of plasma cell master transcription factor BLIMP1, as well as changes in metabolism, has been reported previously (Jang et al., 2015; Shanmugapriya et al., 2019). We have recently applied phasor-FLIM of endogenous NAD(P)H fluorescence for mapping of metabolic enzyme activities in cell cultures (Leben et al., 2019). The combination of this technique with FLIM-based intravital calcium analysis will help to further dissect immunometabolic processes in B cells, as well as in short-lived plasma cells and LLPCs in vivo.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
MouseR26CAG-TNXXLfloxMank et al., 2008-Plasmid available at addgene
(#45797)
MouseCD19 creRickert et al., 1997Stock# 004126
jaxmice
MouseB1-8highShih et al., 2002aStock# 007775
jaxmice
AntibodyRabbit
anti-GFP-Alexa488
polyclonal
Rockland, in-house coupling
DRFZ Berlin
Cat# 600-401-2151:200
AntibodyRat
anti-CD21/35-Fab-Atto590
7G6
DRFZ Berlin10 µg/mouse
AntibodyHamster
anti-IgD-Alexa594
11.26 c
DRFZ Berlin–-
AntibodyRat
anti-CD21/35-Alexa647
7G6
DRFZ Berlin
AntibodyRat
anti-CD19-Cy5
1D3
DRFZ Berlin
AntibodyRat
anti-CD40
3/23
BD PharmingenCat# 553788As indicated
AntibodyGoat
anti-IgM-F(ab)2
polyclonal
Southern BiotechCat#1023-01As indicated
AntibodyRat
anti-kappa
187.1
DRFZ BerlinAs indicated
Recombinant DNA reagentCpGTib Molbiol
Berlin
Request
#1668 and 1826
sequence ID: 1746437/8
As indicated
Peptide, recombinant proteinPeanut-agglutinin, biotinylatedVector BiolabsCat# B-1075-51:200
OtherLipopolysaccharide (LPS) from Escherichia coliSigmaCat# L4391As indicated
Peptide, recombinant proteinNP-CGG ratio > 20Biosearch TechnologiesCat#
N-5055C-5-BS
10 µg/mouse
Peptide, recombinant proteinStreptavidin-Alexa555Thermo Fisher ScientificCat# S323551:2000
OtherX-Rhod-1Molecular ProbesCat# X14210Manufacturer’s protocol
Software, algorithmPython 2.7Python Software Foundation
Software, algorithmMATLABMathWorks
Software, algorithmImarisBitplane
Software, algorithmPhasor-based-numerical analysis of eCFP lifetime dataOwn work, https://github.com/ulbrica/Phasor-FLIM.gitswh:1:rev:8ae5bfc17ec019fcc8ec7e4627442646e52cc3c5; Ulbricht, 2021.

Mice

Mice carrying a STOP cassette flanked by two loxP sites upstream of the region encoding for the TN-XXL biosensor (Mank et al., 2008) in the ROSA26 locus were obtained from F. Kirchhoff, Saarland University, Homburg. YellowCaB mice were generated by crossing those mice with the Cd19cre/cre strain (Rickert et al., 1997) and maintained on a C57Bl/6 background. Only YellowCaB mice heterozygous for Cre were used to avoid deletion of CD19. Mice with monoclonal NP-specific BCR (B1-8hi:YellowCaB) were generated by crossing of YellowCaB mice with B1-8hi mice (Shih et al., 2002b). All mice were bred in the animal facility of the DRFZ. All animal experiments were approved by Landesamt für Gesundheit und Soziales, Berlin, Germany, in accordance with institutional, state, and federal guidelines.

Cells

Primary splenocytes were isolated from whole spleens of YellowCaB mice or B1-8hi:YellowCaB mice in 1× PBS and erythrocytes lysed. B cells were negatively isolated using the Miltenyi murine B cell isolation kit via magnetic-assisted cell sorting (MACS), leaving B cells untouched in order not to pre-stimulate them.

Staining and flow cytometry

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Single-cell suspensions were prepared and stained according to the guidelines for flow cytometry and cell sorting in immunological studies (Cossarizza et al., 2019). To simultaneously assess calcium influx with a dye-based method, we stained whole splenocytes or isolated B cells with the calcium-sensitive dye X-Rhod-1 (Invitrogen). X-Rhod-1 is a single-fluorophore calcium reporter molecule that enhances its fluorescence intensity upon calcium binding in a range of 0–40 µM up to 100 times at a wavelength of 600 nm. Measurements were carried out at a BD Fortessa flow cytometer. TN-XXL expression was checked assessing positive fluorescence in a 525 ± 25 nm channel after 488 nm excitation on a MACSQuant flow cytometer.

Perfusion chamber

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All in vitro experiments were carried out in Krebs–Ringer solution containing 6 mM Ca2+ at 37°C. Cells were stimulated with anti-mouse IgM-F(ab)2 (Southern Biotech), ionomycin (4 µM, Sigma), anti-CD40 antibody (BD), LPS (20 µg/ml, Sigma), or CpG (10 µg/ml, TIB Molbiol Berlin). Cell culture imaging experiments with ionomycin stimulation were performed using an open perfusion chamber system. Buffer solution was pumped through the heated chamber containing a poly-D-lysine-coated glass slide on which freshly and sterile isolated YellowCaB cells were grown for approximately 1 hr. Ionomycin was added in the flow-through buffer supply. The lag time for the volume to arrive at the imaging volume was determined for each set-up and considered for analysis of ΔR/R over time. Anti-IgM-F(ab)2 antibody was given directly to cells within the open chamber in between acquisition time points. To visualize the reversibility of the sensor despite antibody still present, the experiment was performed in an open culture system without media exchange through a pump. To analyze if YellowCaB cells could repeatedly be stimulated, experiments were performed under continuous perfusion. Buffer flow was switched off with stimulation for several minutes and switched on again to dilute antibody out again for a second stimulation.

For analysis, regions of interest were determined based on randomly chosen single cells. Intensity density values of the raw citrine signal were divided by the intensity density values of the raw eCFP signal and related to the baseline ratio of the signals before stimulation.

Cell transfers, immunization, and surgical procedures

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B cells from spleens of YellowCaB mice were negatively isolated using the Miltenyi murine B cell isolation kit via MACS. 5 × 106 cells were transferred to a host mouse with a transgenic BCR specific for an irrelevant AG (myelin oligodendrocyte glycoprotein). When NP-specific B cells were analyzed, B cells from spleens of B1-8hiYellowCaB mice were transferred to wildtype C57Bl/6 mice. Host mice were immunized in the right footpad with 10 µg NP-CGG in complete Freund’s adjuvant 24 hr after B cell transfer. After 6–8 days p.i., FDCs were labeled with Fab-Fragment of CD21/35-Atto590 or CD21/35-Alexa647 (in-house coupling) into the right footpad. Polyclonal B cells from YellowCaB mice were stained with a red fluorescent dye (CellTracker Deep Red, Thermofisher) and adoptively transferred. 24 hr later, the popliteal lymph node was exposed for two-photon imaging as described before (Ulbricht et al., 2017). Briefly, the anesthetized mouse is fixed on a microscope stage custom-made for imaging the popliteal lymph node. The mouse is shaved and incisions are made to introduce fixators that surround the spine and the femoral bone. The mouse is thus held in a planar position to the object table. The right foot is fixed by a wire allowing to increase the tension on the leg to position the lymph node parallel to the imaging set-up. A small incision is made to the popliteal area. The lymph node is exposed after freeing it from surrounding adipose tissue. A puddle around the lymph node is formed out of insulating silicon compound, then filled with NaCl and covered bubble-free with a cover slide.

For intravital application of AG, 500 µg NP-BSA were administered i.v. after acquiring 10 time steps of baseline FLIM signal (four mice). To check for BCR specificity of calcium elevation recorded after AG injections, BTK inhibitor ibrutinib was pre-injected i.v. before AG application at 3.75 mg/kg and recorded in a control group of three mice. Technically, measurements were paused for injections for about 5 min. For accurate comparison of baseline calcium levels with calcium levels after injections, we imaged the same GC before and after. Therefore, measurements are always to be treated as separate measurements and it is not possible to track individual cells before and after an injection. However, the mean calcium elevation in the presented subset of cells can be visualized. For better comparability, we have chosen to present a time course that virtually combines two consecutive measurements in the same GC into one (Figure 5—figure supplement 1). Up to 22 individual cell tracks were randomly chosen after gating out overlapping signals from macrophages, filtering for maximum track duration and completeness of the series of events (absolute calcium value in the center of the segmented object).

Intravital and live cell imaging and image analysis

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Imaging experiments of freshly isolated B cells were carried out using a Zeiss LSM 710 confocal microscope. Images were acquired measuring 200–600 frames with one frame/3 s frame rate while simultaneously detecting eCFP and citrine signals at an excitation wavelength of 405 nm.

For intravital two-photon ratiometric imaging, z-stacks were acquired over a time period of 30–50 min with image acquisition every 30 s. eCFP and citrine were excited at 850 nm by a fs-pulsed Ti:Sa laser, and fluorescence was detected at 466 ± 30 nm or 525 ± 25 nm, respectively. Fluorescence signals of FDCs were detected in a 593 ± 20 nm channel. For experiments including macrophage staining, the fluorescence data has been unmixed for a possible overlap of the TN-XXL–citrine signal with that of the injected marker to prevent false-positive colocalization analysis between the red efluor660 coupling of anti-CD169 and the green fluorescence of TN-XXL in the 525 ± 25 nm channel (Rakhymzhan et al., 2017).

For intravital FLIM experiments, eCFP fluorescence lifetime was measured with a time-correlated single-photon counting system (LaVision Biotec, Bielefeld, Germany). The fluorescence decay curve encompassed 12.4 ns (80 MHz laser repetition rate) with a time resolution of 55 ps. The pixel dwell time was 4 × 5 µs, allowing to detect photons from 1600 laser pulses for the fluorescence decay. The fluorescence decay, while being multiexponential, may be approximated by a bi-exponential function containing the two monoexponential decays of unquenched CFP and of FRET-quenched CFP, respectively. The phasor approach allows us to display the data prior to data interpretation graphically, that is, prior to the decision on the multiexponentiality of the CFP decay function, and was primarily used for the FRET–FLIM data evaluation. Similar to fluorescence intensity two-photon experiments, we performed time-lapse FRET–FLIM measurements and repeated the described acquisition every 30 s.

Analysis of two-photon data

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For ratiometric analysis of two-photon data, fluorescence signals were corrected for spectral overlap (the eCFP to citrine ratio in 525 ± 25 nm channel is 0.52/0.48) and refined by taking into account the sensitivity of photomultiplier tubes (0.37 for 466 ± 30 nm and 0.4 for 525 ± 25 nm). Ratiometric FRET for in vivo experiments was calculated accordingly as

(12) FRET=1,2ch22,7ch1+2,5ch2100

Evaluation of FLIM data was performed using the phasor approach (Digman et al., 2008; Leben et al., 2018). Briefly, the fluorescence decay in each pixel of the image is Fourier-transformed at a frequency of 80 MHz and normalized, resulting into a phase vector, with the origin at (0|0) in a Cartesian system, pointing into a distinct direction within a half-circle centered at (0.5|0) and a radius of 0.5. For pure substances, vectors end directly on the half-circle, for mixtures of two on a connecting segment between the respective pure lifetimes and within a triangle, if three substances are present, and so on. The distance between several fluorescence lifetimes on the half-circle is naturally distributed logarithmically, with the longest lifetimes closer to the origin. In the case of TN-XXL, the extremes are the unquenched CFP fluorescence (2312 ps) and the eCFP fluorescence completely quenched by FRET (744 ps). The location of the measured lifetime on the connecting line can directly be translated into the amount of either eCFP state and thus to a corresponding calcium concentration in each pixel of the image.

At low signal-to-noise ratio values, the FLIM signal of the donor with a large contribution of electronic noise is shifted towards the origin of coordinates in the phasor plot, indicative for the infinite lifetime of noise. In non-fluorescent medium, we measured electronic noise and Gaussian-fitted the histograms of real and imaginary parts. The Gaussian fit of each part gives the mean (distribution center) as well as the full distribution width at half maximum, FWHM = 22ln2σ, which was the same for both parts. The width of electronic noise distribution gives the radius within which we expect only noise (Figure 4g). In order to increase the accuracy, we excluded all data points in an area within the radius of ¾FWHM = 0.3.

Titration of TN-XXL construct

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Sensor calibration was performed using lysate of cultured, homozygous B1-8hi:YellowCaB plasma blasts induced from isolated B1-8hi:YellowCaB cells stimulated with LPS/IL-4 for 2 days. Briefly, cells were freeze-thawed in liquid nitrogen 3–4 times and treated with ultrasound for 15 min. Lysate was filtered and cell clumps separated by high-speed centrifugation. Lysis was done at two equal shares in a sufficiently small volume of calcium-free calibration buffer (Life Technologies) or calcium-saturated (39 µM CaEGTA), respectively. Calcium buffer concentrations measured were achieved by dilution of 39 µM-buffered cell lysate with 0 µM-buffered cell lysate. Sample concentrations were loaded into glass microscope slides with recess, covered, and their fluorescence was measured at the two-photon microscope in a time-resolved manner. Focus was adjusted to a z-position with maximal photon counting numbers, as ensured by acquisition of proper decay curves. In time domain, the eCFP mean fluorescence lifetimes τ at various free calcium concentrations were determined by approximating the corresponding fluorescence decay curves F(t) acquired with our TCSPC-based FLIM detector to a monoexponential function containing background y0: F(t)=y0+Aetτ. Fitting was performed iteratively using a Levenberg–Marquardt gradient algorithm (Rinnenthal et al., 2013).

Statistical information

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Time-dependent FRET curve analysis shows representative graphs for the number of analyzed cells and independent experiments given. For multiple curve analysis, mean is shown and SD indicated in each data point. For column analysis, one-way ANOVA with Bonferroni multiple comparison test was applied with a confidence Interval of 95%.

Data availability

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All raw data and analyzed data shown here are stored on institutional servers. Imaging source data and raw Excel files have been deposited at https://datadryad.org under DOI: 10.5061/dryad.cc2fqz63d.

Data availability

Source data for flow cytometric Analysis, in vitro confocal imaging, ratiometric in vivo Imaging and fluorescence lifetime in vivo Imaging are deposited at Dryad Digital Repository 10.5061/dryad.cc2fqz63d. Analyzed absolute calcium concentration for all cells measured out of 5 experiments have also been deposited there. Source code for phasor based analysis of fluorescence lifetime data has been provided with full submission upload and is available to the public via github (https://github.com/ulbrica/Phasor-FLIM; https://archive.softwareheritage.org/swh:1:rev:8ae5bfc17ec019fcc8ec7e4627442646e52cc3c5).

The following data sets were generated
    1. Ulbricht C
    2. Leben R
    3. Rakhymzhan A
    4. Kirchhoff F
    5. Nitschke L
    6. Radbruch H
    7. Niesner RA
    8. Hauser AE
    (2021) Dryad Digital Repository
    Intravital quantification reveals dynamic calcium concentration changes across B cell differentiation stages.
    https://doi.org/10.5061/dryad.cc2fqz63d

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Decision letter

  1. Michael L Dustin
    Reviewing Editor; University of Oxford, United Kingdom
  2. Satyajit Rath
    Senior Editor; Indian Institute of Science Education and Research (IISER), India
  3. Michael L Dustin
    Reviewer; University of Oxford, United Kingdom

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

You have generated a new FLIM based reporter to follow cytoplasmic Calcium homeostasis in B cells undergoing germinal center responses and differentiation into plasma cells. You have also introduced a new analytical framework based on the phasor method, which provides a new tool for study of Calcium signals in vivo. You have also drawn attention to the heterogeneity of in vivo cytoplasmic Calcium in B cells and plasma blasts. A limitation of the study is that direct comparison to other established methods were not performed, which means that interpretation of the heterogeneity is not straight forward for others in the field and teams considering the new method will need to undertake testing to determine if this method outperforms others for a particular application. Nonetheless, the new tools developed here and initial findings should motivate further efforts to understand the role of cytoplasmic Calcium heterogeneity in, for example, vaccination responses, which we all appreciate.

Decision letter after peer review:

Thank you for sending your article entitled "Intravital quantification of cytoplasmic B cell calcium reveals dynamic signaling across B cell differentiation stages" for peer review at eLife. Your article is being evaluated by 2 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation is being overseen by Satyajit Rath as the Senior Editor.

There are technical concerns about your calibration that may be addressed without new experiments. There is a larger concern regarding the nature of the Calcium signals and evidence that these are dependent upon the BCR. It’s not felt that the observation of Ca2+ fluctuations along in GC B cells or plasma blasts is unexpected or sufficient. Can the authors demonstrate in either the of these signals is actually dependent upon the BCR? Perhaps this could be done in the setting of B1.8 setting with non-toxic versions of the hapten, that blocking the BCR can prevent Calcium signaling in either or both compartments?

Reviewer #1:

The authors establish a mouse line expressing a Fret based Calcium sensor in B cells and they perform life-time imaging to determine the cytoplasmic Ca2+ concentration in B cells activated through their antigen receptor in vitro or as part of a germinal center reaction. A strength of the approach is that the lifetime imaging gives a result that is independent of depth assuming the signal to noise ratio is adequate to acquire robust data. Using this approach they find that germinal center B cells and plasma blasts in the medullary cords both have elevated Ca2+. The non-antigen specific control cells are presumably naïve T cells, which are found everywhere in the lymph nodes and thus measurements could be made in GC or MC. The weakness of using these cells as controls for antigen recognition is that they are follicular B cells, not GC B cells or plasma blasts. So not only is their antigen receptor different, but chemokine receptors and other receptors for environmental signals will be different in these cells. This seems to mainly be written as a resource papers to illustrate the methods, establish that Ca2+ fluctuations can be measured, but is limited in the extent to which these differences can be attributed to antigen in vivo as antigen recognition is linked to both acute activation processes and differentiation into different B cell types.

1. The interpretation of any of the data as antigen specific is difficult as the antigen specific cells have distinct differentiation compared to the control polyclonal cells. In order to assess this, a way to block the antigen receptors provide a bolus of antigen to directly observe antigen dependent changes in Ca2+ in vivo could be useful.

2. The observations that the plasma blasts in the MC have high Ca2+ fluctuations is interesting, but may be related to chemokine dependent interactions with macrophages or closely associated stromal cells (see: Fooksman DR, Schwickert TA, Victora GD, Dustin ML, Nussenzweig MC, Skokos D. Development and migration of plasma cells in the mouse lymph node. Immunity. 2010;33(1):118-27 and Huang HY, Rivas-Caicedo A, Renevey F, Cannelle H, Peranzoni E, Scarpellino L, Hardie DL, Pommier A, Schaeuble K, Favre S, Vogt TK, Arenzana-Seisdedos F, Schneider P, Buckley CD, Donnadieu E, Luther SA. Identification of a new subset of lymph node stromal cells involved in regulating plasma cell homeostasis. Proc Natl Acad Sci U S A. 2018;115(29):E6826-E35.). This Calcium signaling is unlikely to be antigen dependent so they should discuss alternatives and if possible devise an experiment to directly address this issues, at least for antigen. Can they influence the signaling status of the plasma blasts with antigen at all?

Reviewer #2:

Ulbricht et al., employed a FRET-based calcium (Ca2+) sensor YellowCaB to study Ca2+ signaling in B cells. in vitro experiments using fluorescent intensities of eCFP and citrine demonstrate the ability of YellowCaB to report repeated BCR stimulation. The authors show examples of Ca2+ transients in B cells contacting FDCs and other B cells during intravital imaging. Fluorescence lifetime analysis revealed multiple lifetimes for FRET-donor eCFP. Based on the Kd of 453 nM for TN-XXL and phasor plot analysis, the authors calculate the absolute Ca2+ concentration in B cells. B cells display heterogeneity in calcium signals. Surprisingly, extrafollicular B cells displayed higher Ca2+ levels that correlated with the duration of contact with subcapsular sinus macrophage contact. However, there are important concerns.

1. Calibration. Characterizing Ca2+ signaling in B cells during immune responses will likely be important for understanding affinity maturation. However, FLIM-based analysis needs further controls to validate the claim of absolute Ca2+ concentrations reported in this study. Geiger et, al (Biophysical Journal, May 2012) cautioned for FRET-based biosensors such as TN-XXL, that calibration should be performed on the same microscope set up and the same conditions as used for imaging. It is unclear from the Methods how the lifetime of eCFP 2300ps (unquenched) vs 700ps (quenched) was determined, e.g., at what pH and temperature? Ideally, FLIM probes should have monoexponential decay curves, what is the lifetime of eCFP alone expressed in B cells?

2. Expression of TN-XXL sensor in one allele (TN-XXL+/-) vs homozygous (TN-XXL+/+) animal should be different in intensity but not in the percent of B cells positive for TN-XXL. This should be clarified.

3. Moreover, it appears that there were no new insights resulting from the calibrated Ca2+ concentrations. It is not unexpected that there is heterogeneity in the calcium responses.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Intravital quantification reveals dynamic calcium concentration changes across B cell differentiation stages" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Michael L Dustin as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Satyajit Rath as the Senior Editor.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address the validity of claims based on the data shown, clarity and presentation.

The reviewers, two of whom are new due to the unavailability of one of the original reviewers, appreciate your efforts to address the original concerns. The consensus is that you have succeeded in calibrating the lifetime measurements, with one caveat that the use of the lysate may not fully recapitulate the conditions in a live cell, but since it's difficult to clamp Calcium in a live cell your solution is acceptable. The experiments addressing the role of antigen in germinal centre B cell activation are considered helpful as a sensitivity test, but there is a consensus that your new text over-interprets the data presented. You have established BCR triggered Calcium flux in vitro (original data) and in vivo (new data with antigen injection), but this capability doesn't appear to help understand the heterogeneity of B cell's Calcium levels in the germinal centre or medullary cords. The reviewers can see a positive path and are happy to see another revision if you can respond to the new concerns, which largely relate to refining presentation of the new information introduced in your first revision.

The calibration of the lifetime data is appreciated, but some discussion should be given to limitations of the approach, which are unavoidable, but requires caution.

The NP-BSA induced Calcium elevation in vivo extends results with anti-Ig from Figure 2 and supports ability to detect BCR dependent Calcium ion elevation in vivo. NP-BSA can trigger apoptosis (Nossal, PMID 7753199) and that interactions with myeloid cells in the MC seems to limit antibody secreting cells numbers (Fooksman, PMID 24376270) such that signals leading to apoptosis may also be contributing to the Calcium signals observed in the system. This could be incorporated into the discussion of different explanations for the high Calcium subsets. It would also make sense to cite early work from Cahalan that Calcium elevation can lead to arrest of cell motility (Negulescu et al., PMID: 8630728). But it's important to point out that demonstrating that you can detect effects of BCR engagement by injecting polyvalent antigen is not the same as showing that Calcium elevation observed in germinal centre and medullary cords in the system set up by earlier immunisation is due to antigen recognition. In fact, the apparent lack of effect of the BTK inhibitor doesn't support a role for BCR signalling in the heterogeneity of Calcium.

The new data in Figure 5a is appreciated as it attempts to address the role of BCR signalling using a BTK inhibitor and injecting NP-BSA as a BCR ligand. The description of the experiments suggests that you have performed a very demanding time-course with a baseline, BTK inhibitor injection and then NP-BSA injection. Could this data be shown- similar to Figure 4g, but with breaks where the injections were performed. There are questions about how long it takes these agents to get to the lymph nodes after IV injection. The inhibitor may be fine, but I'm not sure the NP-BSA will get to the germinal centre in a lymph node by this route as it will need to leak through the vasculature into the peripheral tissues and then drain to the LN. Do the authors know of data on BSA pharmacodynamics that would suggest it gets into the germinal centre in minutes after IV injection? I know of data for peptides getting into the T cell zone rapidly, but not for an intact protein that is maintained in the blood by FcRn. I would think that marginal zone of spleen would be the main point of entry for IV protein into secondary lymphoid tissues.

As mentioned above, you need to think carefully about reasonable interpretations of these data and revise the discussion regarding possible sources of Calcium heterogeneity.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for sending your article entitled "Intravital quantification reveals dynamic calcium concentration changes across B cell differentiation stages" for peer review at eLife. Your article is being evaluated by 1 peer reviewers, and the evaluation is being overseen by a Reviewing Editor and Satyajit Rath as the Senior Editor.

Your last revision didn't appear to address the reviewers concerns, but the Reviewing Editor asked for another opinion in an attempt to pinpoint and articulate the key issues related to calibration. The opinion below agrees that the revision didn't address reviewer concerns, but suggests a different approach to the Phasor calibration that may help resolve this issue, although it would still require some adaptation from the original use with a Calcium indicator to the current use with a Calcium biosensor. The Reviewing Editor hopes that this will be helpful in focusing a final revision that can be resent to all active reviewers.

"I found this article quite confusing in regard to the calcium calibration and the proper citation of the phasor method. The authors fail to cite the paper using the phasor approach for the calcium calibration "Celli A, Sánchez SA, Behne MJ, Hazlett TL, Gratton E, Mauro TM. The epidermal Ca(2+) gradient: measurement using the phasor representation of fluorescent lifetime imaging. Biophys J. 2010; 98(5): 911-921. PMCID: PMC2830439. This paper addresses the issue of the calibration of indicators, not biosensors. It uses a different method based on the position of the data on the phasor plot rather than attempting a calibration that cannot be done due to the diversity of the calibration solutions with respect to the environment where the biosensor is located, which is a major point of the previous comments.

The only phasor plots in this paper are in figure 4, where the phasor of the biosensor is located but in my opinion the calibration method suggested in the paper by Celli et al. is not applied. This is important for the overall interpretation of the results and the conclusion of this article."

https://doi.org/10.7554/eLife.56020.sa1

Author response

There are technical concerns about your calibration that may be addressed without new experiments. There is a larger concern regarding the nature of the Calcium signals and evidence that these are dependent upon the BCR. It’s not felt that the observation of Ca2+ fluctuations along in GC B cells or plasma blasts is unexpected or sufficient. Can the authors demonstrate in either the of these signals is actually dependent upon the BCR?

We thank the reviewing editor for the honest interest in our manuscript and for the helpful suggestions, which helped us improve our research. We agree that providing a proper calibration of the TN-XXL Ca2+ sensor is indispensable for the reliability of the data. Therefore, we performed a new set of FLIM-measured calibration experiments, and also included already existing, mono- and multiexponentially analyzed lifetime data. Concerns regarding the nature of intra- and extrafollicular Ca2+ signaling events were addressed in vitro (by FLIM of stimulated LPS-induced plasma blast cultures) as well as in vivo (by injection of antigen, as suggested by the reviewers, and by adding a BCR-inhibitor while intravital imaging was performed).

Perhaps this could be done in the setting of B1.8 setting with non-toxic versions of the hapten, that blocking the BCR can prevent Calcium signaling in either or both compartments?

We followed the suggestion of measuring potential signaling events in a B1-8 (high affinity BCR for NP) setting after application of antigen. To do so, we performed intravital imaging experiments at day 7 and 8 after immunization within the popliteal lymph node, as described. This time, after acquiring basal calcium concentrations in GC B cells (identified by proximity to FDC staining with anti-CD21/35), mice received an intravenous injection of 100µl NP(7)-BSA solution, representing 500µg of antigenconjugate per animal. We were able to observe four GCs in three mice in total. In every case, injection of NP-BSA significantly increased overall Ca2+ concentrations within the GC B cell population, with a mean calcium elevation of ca. 150nM. While, due to the proposed degree of heterogeneity within the GC, this is likely not affecting all GC B cells, the single-cell data suggest a concentration-shift in a proportion of GC B cells that is sufficient to indicate a statistically significant elevation in the overall cytoplasmic calcium level. See Author response image 1.

Author response image 1
A: intravital imaging of GC B cells before and after i.

v. application of NP-BSA B: intravital imaging of GC B cells before and after i.v. application of ibtutinib, followed by NP-BSA injection. C: Cumulated data of revised intravital imaging experiments.

To address BCR-specificity of these signals further, we pre-injected ibrutinib, which is used to efficiently block BCR signaling by preventing the phosphorylation of molecules downstream of BTK, a key adaptor enzyme of the BCR signaling cascade (Herman, Blood, 2011). in vivo treatment of mice with ibrutinib (110µg/kg i.v.) before injection of NP-BSA was able to reduce Ca2+ increase, though not to completely abrogate it. We conclude that, at least in part, the calcium fluctuations observed in our in vivo data are BCR specific, but that BCR-mediated signaling is not the only source of cytoplasmic Ca2+ heterogeneity in the GC. We want to point out here that we did not aim on providing a tool for measuring BCR-specific signaling events in the first place, but rather for signaling events mediated by Ca2+ as a whole. We believe that further experiments will disseminate the nature of cytoplasmic calcium changes even further, some of them already performed in our lab (our preliminary data indicate a role for metabolic activity thresholds in Ca2+ homeostasis). We emphasized these points within the text.

Reviewer #1:

The authors establish a mouse line expressing a Fret based Calcium sensor in B cells and they perform life-time imaging to determine the cytoplasmic Ca2+ concentration in B cells activated through their antigen receptor in vitro or as part of a germinal center reaction. A strength of the approach is that the lifetime imaging gives a result that is independent of depth assuming the signal to noise ratio is adequate to acquire robust data. Using this approach they find that germinal center B cells and plasma blasts in the medullary cords both have elevated Ca2+. The non-antigen specific control cells are presumably naïve T cells, which are found everywhere in the lymph nodes and thus measurements could be made in GC or MC. The weakness of using these cells as controls for antigen recognition is that they are follicular B cells, not GC B cells or plasma blasts. So not only is their antigen receptor different, but chemokine receptors and other receptors for environmental signals will be different in these cells. This seems to mainly be written as a resource papers to illustrate the methods, establish that Ca2+ fluctuations can be measured, but is limited in the extent to which these differences can be attributed to antigen in vivo as antigen recognition is linked to both acute activation processes and differentiation into different B cell types.

We thank reviewer #1 for these comments and want to point out that indeed the non-antigen specific cells are naive, that is primary, most likely follicular B cells with polyclonal BCRs, carrying the TN-XXL construct. These cells were isolated via CD19 MACS from YellowCaB mice and adoptively transferred into wild-type recipients one day prior to imaging. One obstacle with these cells is the fact that TN-XXL fluorescence within these cells is faint due to their low amount of cytoplasm, and therefore only suboptimal signal-to-noise conditions can be met in most cases. Therefore, we decided to exclude all cells from the analysis with SNR<1 (for AG-specific cells SNR<2). It is true that these polyclonal cells also might possess differences in receptor composition. However, rather than to prove antigen-specificity of the signaling by use of these cells as control, we wanted to characterize these differences by showing the different degrees of heterogeneity among polyclonal cells in contrast to AG-specific ones. In the AG-specific subset (including B cells and plasma blasts), we see a distinct population arising that is showing elevated Ca2+ concentrations. We hypothesize that a certain Ca2+ level is associated with selection and B cell survival, which is likely the reason why naive, polyclonal B cells have relatively and uniformly low Ca2+ concentrations.

1. The interpretation of any of the data as antigen specific is difficult as the antigen specific cells have distinct differentiation compared to the control polyclonal cells. In order to assess this, a way to block the antigen receptors provide a bolus of antigen to directly observe antigen dependent changes in Ca2+ in vivo could be useful.

We thank the reviewer for this comment and feel that antigen-stimulation experiments in our system are by right an issue of strong interest. In accordance with suggestions of reviewer #1 and the reviewing editor, new in vivo data have been generated, showing i.v. injection of NP is able to increase Ca2+ in GC B cells. In addition, we performed experiments using the BCR inhibitor ibrutinib, which demonstrated that Btk-inhibition is able to restrict this cytoplasmic Ca2+ increase (see answer to the reviewing editor above).

2. The observations that the plasma blasts in the MC have high Ca2+ fluctuations is interesting, but may be related to chemokine dependent interactions with macrophages or closely associated stromal cells (see: Fooksman DR, Schwickert TA, Victora GD, Dustin ML, Nussenzweig MC, Skokos D. Development and migration of plasma cells in the mouse lymph node. Immunity. 2010;33(1):118-27 and Huang HY, Rivas-Caicedo A, Renevey F, Cannelle H, Peranzoni E, Scarpellino L, Hardie DL, Pommier A, Schaeuble K, Favre S, Vogt TK, Arenzana-Seisdedos F, Schneider P, Buckley CD, Donnadieu E, Luther SA. Identification of a new subset of lymph node stromal cells involved in regulating plasma cell homeostasis. Proc Natl Acad Sci U S A. 2018;115(29):E6826-E35.).

We agree with the reviewer’s notion that chemokine-induced Ca2+ mobilizations within lymphocytes are common and their impact should be taken into account in this system. During establishment of our ratiometric system, we already tried to address the question whether such Ca2+ changes are being detected, and these data were included in the supplementary material of the original manuscript (Figure S2c). In our hands, the ratiometric imaging approach was not sensitive enough to detect calcium mobilization in primary, polyclonal YellowCaB cells. However, this of course does not mean that the calcium fluctuations measured in our in vivo set up might not as well be a result of chemokine stimulation, at least partially. Furthermore, as pointed out by reviewer #1, AG-specific B cells and plasma blasts might have different receptor compositions than follicular B cells. Also, FLIM measurements might be more sensitive than ratiometric imaging. Therefore, and in order to investigate this issue further, we decided to repeat CXCL12-stimulated Ca2+-measurements in cultured B cells (LPS/IL-4 for 2 days) and tested if we could detect Ca2+ signaling with FLIM after direct CXCL12 stimulation. We can conclude that Ca2+ changes in YellowCaB plasmablasts are measurable with FLIM after chemokine stimulation, and that chemokine-induced Ca2+ fluctuations are thus likely to contribute to Ca2+ heterogeneity seen in our in vivo data, at least at sites with high local concentration. Figure S2 has been updated accordingly.

This Calcium signaling is unlikely to be antigen dependent so they should discuss alternatives and if possible devise an experiment to directly address this issues, at least for antigen. Can they influence the signaling status of the plasma blasts with antigen at all?

Plasmablasts and even plasma cells of the IgA and IgM isotype can carry residual BCR activity, as recently reported by the lab of L. Sollid (Spencer and Sollid, 2016). In our experiments, we could demonstrate Ca2+ elevations in B1-8-YellowCaB plasma blasts by FLIM after addition of the antigen (NP) (Author response image 2B).

Author response image 2
CXCL12 stimulation of LPS-induced B1-8 PB, B: NP stim of LPS-induced B1-8 PB.

We want to point out again that we did not aim on establishing the TN-XXL+ YellowCaB system as a readout for BCR-specific activation; rather, we wanted to provide a tool for measuring Ca2+ as ubiquitous, universal cellular messenger. In addition to alterations in the text, we have also changed the title in order to emphasize this point. The fact that we can measure absolute, that is, discrete concentrations of Ca2+ might also make it a useful tool to distinguish different Ca2+ signaling pathways, as each of these processes may be acting in a quantum-mediated manner that relies upon defined thresholds, a hypothesis that we are discussing in the revised version of the paper. However, to quantitatively dissect to what extent these differential signaling patterns affect Ca2+ levels, would go beyond the scope of our work at present.

Reviewer #2:

Ulbricht et al., employed a FRET-based calcium (Ca2+) sensor YellowCaB to study Ca2+ signaling in B cells. in vitro experiments using fluorescent intensities of eCFP and citrine demonstrate the ability of YellowCaB to report repeated BCR stimulation. The authors show examples of Ca2+ transients in B cells contacting FDCs and other B cells during intravital imaging. Fluorescence lifetime analysis revealed multiple lifetimes for FRET-donor eCFP. Based on the Kd of 453 nM for TN-XXL and phasor plot analysis, the authors calculate the absolute Ca2+ concentration in B cells. B cells display heterogeneity in calcium signals. Surprisingly, extrafollicular B cells displayed higher Ca2+ levels that correlated with the duration of contact with subcapsular sinus macrophage contact. However, there are important concerns.

1. Calibration. Characterizing Ca2+ signaling in B cells during immune responses will likely be important for understanding affinity maturation. However, FLIM-based analysis needs further controls to validate the claim of absolute Ca2+ concentrations reported in this study. Geiger et, al (Biophysical Journal, May 2012) cautioned for FRET-based biosensors such as TN-XXL, that calibration should be performed on the same microscope set up and the same conditions as used for imaging. It is unclear from the Methods how the lifetime of eCFP 2300ps (unquenched) vs 700ps (quenched) was determined, e.g., at what pH and temperature? Ideally, FLIM probes should have monoexponential decay curves, what is the lifetime of eCFP alone expressed in B cells?

We share the opinion of the reviewer that a thorough characterization of the donor (CFP) fluorescence decay in the TNXXL construct, without any quenching and under FRET-quenching, is crucial for calculating absolute Calcium values from our FRET-FLIM data. We thank the reviewer for pointing out that in the present version of the manuscript the description of the calibration is not complete and might lead to misinterpretations. In the revised version of the manuscript, we added new data and text to clarify this issue.

As suggested by the reviewer, we included FLIM data we previously acquired in spleen tissue of mice ubiquitously expressing CFP (Author response image 3C). Under two-photon excitation at 850 nm and detection with our TCSPC at 460±30 nm, we could validate its fluorescence lifetime value of 2300 ps. A corresponding fluorescence decay curve averaged over a 300x300 µm² region in spleen tissue (256 x 256 pixel) was included in the manuscript, together with exemplary close-up images of CFP-expressing splenocytes (revised Figure 4). Fitting the measured CFP fluorescence decay with a mono-exponential function with background: f(t)=yo+Aetτ led to a fluorescence lifetime τ of 2303±54 ps. Approximation with bi-exponential or tri-exponential functions did not reveal additional fluorescence lifetimes, but replicated the result of the mono-exponential fit (2303±54 ps). Thus, we conclude that the approximation of the CFP fluorescence decay with a mono-exponential curve is valid. We decided to not repeat this experiment specifically in B cells, as we do not expect the lifetime to majorly differ between lymphocyte subsets, and since we aim to pursue 3R guidelines, therefore reducing the use of laboratory animals used in experiments to a minimum.

As our FRET-FLIM calibration of the TN L15 construct (Rinnenthal et al., PLoS One, 2013) – a similar construct to TN XXL– was in very good agreement with the previously published calibration curve (Heim N., Griesbeck O., J. Biol. Chem., 2004), and since our CFP fluorescence lifetime measurements in B cells were in the same range as those published by Geiger et al. (Biophys J, 2012), we considered that using the published FRET-FLIM calibration curve for TNXXL for our data is feasible. However, to exclude any possible artifacts and to validate the published calibration curve using our own experimental setup, we performed titration FRET-FLIM experiments using lysates of B cells expressing TNXXL at various, well-defined Ca2+ concentrations. Exemplary fluorescence decay curves of CFP in the TNXXL construct from B cell lysates at 0 nM, 602 nM and 39 µM free Ca2+ have been added to the revised Figure 4, showing donor quenching with increasing Ca2+ concentration. By fitting the CFP decay curves acquired at 0 nM, 65 nM, 150 nM, 351 nM, 602 nM, 1.35 µM and 39 µM free Ca2+, we generated the corresponding titration curve of the TNXXL construct (results of three independent experiments). We approximated this calibration curve with the sigmoid function: τ (lg[Ca])=τmin+tmaxtmin1+10(lg[Kd]lg[Ca])Hillslope (revised Figure 4) and determined the parameters: Kd = 475±46 nM (lg[Kd] = -6.32±0.04) and Hill slope = 1.43±0.17. Both parameters are in very good agreement with the previously published results of Geiger et al., as differences fall within the error margins. Consequently, the resulting 4.5% difference in absolute calcium concentrations lies below our measurement accuracy. Also, the values of τ max = 2322±42 ps and τ min = 769±70 ps confirm the previously used lifetime values (unquenched: 2300 ps and FRET-quenched: 700 ps), and do not lead to any measurable differences in absolute calcium concentration.

Following the reviewer’s suggestion, we emphasized in the revised version of the manuscript that the fluorescence lifetime of fluorophores depends on the refractive index (Strickler and Berg, 1962, J. Chem. Phys. 37:814) and may be influenced by various other factors such as pH, temperature, or ionic strength. All our intracellular measurements were performed under typical intracellular conditions, i.e. pH 7.2-7.4, 37°C temperature, at the ionic strength of cytosol and refractive index of cytosol which is comparable to that of water (1.33). The extracellular measurements were performed under similar conditions as the intracellular measurements, except for the fact that they have been performed at room temperature. While Laine et al., PLoS ONE, 2012 reported a slight decrease of Cerulean fluorescence lifetime in the TN L15 construct in the range 20°C – 50°C, we did not observe such a trend as we measured the same CFP fluorescence lifetime both in spleen tissue at 37°C and in 0nM Ca2+ free buffered solutions of TN XXL, at room temperature.

Once again, we agree with the reviewer that the experimental setup may influence the results of FRET measurements. This holds true especially for ratiometric FRET, for which measuring both the fluorescence signal of the donor and of the acceptor is necessary. As detector sensitivity may vary between spectral channels and different photobleaching and scattering properties of donor and acceptor fluorophores are expected, a thorough calibration is needed not only for each experimental setup, but also for each sample type. In contrast, FRET-FLIM measures only the time-resolved fluorescence of the donor and is neither affected by the different photobleaching of donor and acceptor molecules, nor by the different scattering properties of their fluorescence. This is especially relevant in deep tissue and makes FLIM the method of choice for standardized, generally valid information on intracellular calcium concentrations, as previously shown by us in neurons (Radbruch et al., 2015, IJMS). Artifacts in fluorescence lifetime may however appear, but are mainly related to noise contribution, which – being an undamped oscillation – leads to accuracy loss. We better emphasized in the revised version of the manuscript, how we accounted for background noise impact in our phasor evaluation. We measured all fluorescence decays using TCSPC with high temporal resolution, i.e. time bin 55 ps, electronic jitter < 10 ps, and instrument response function ≈ 200 ps. Under these conditions, the fluorescence decay of unquenched CFP is best approximated by a mono-exponential function. The fluorescence decay of CFP in the TNXXL construct in the presence of Ca2+ is more complex, due to the fact that it represents the average over all CFP (donor in TNXXL) molecules dwelling within the observation volume. Each Tnroponin C molecule in the TNXXL construct has four different Ca2+-binding sites – two high-affinity and two-low-affinity binding sites, leading to different quenching levels of CFP. Accounting for the Ca2+-binding heterogeneity among the TN XXL molecules within the observation volume, the measured CFP fluorescence decay will be multi-exponential (at least fourexponential) and, as such, its numerical approximation with a correct fitting curve is challenging. By simplifying the situation and fitting the decay with a mono-exponential function, mean CFP fluorescence lifetimes which lie between 2300 ps (unquenched CFP) and 700 ps (completely FRET-quenched CFP) are expected.

Author response image 3
A: exemplary monoexponential decays for Ca2+ free (black), Ca2+ saturated (blue) and 602nM Ca2+ medium (red), and calibration curve for lysate of YellowCaB cells.

Measured concentrations (3 replicates): 0nM, 100nM, 150nM, 351nM, 602nM, 1,35μM, 39μM. B: unquenched fluorescence lifetime of eCFP was validated to be 2303+/- 53 ps in splenic tissue of mice with ubiquitous GFP expression. C: exemplary decays for plasma blasts with high (tau = 703 ps, red arrow) and lower (tau = 1937ps, white arrow) Ca2+ concentration.

In order to exclude artifacts introduced by model-based approximation algorithms, we decided to use decay visualization from the entire image, without any previous knowledge of the system (Digman M.A. et al., Biophys J., 2008). First when interpreting the evaluated data, assumptions regarding the system (especially about its molecular heterogeneity) need to be done. To validate the performance of the phasor approach in our in vivo experiments, we fitted fluorescence decay curves of plasmablasts expressing TNXXL using the Levenberg-Marquardt gradient approach to mono-exponential curves with background. The resulting fluorescence lifetimes were in good agreement with the mean fluorescence lifetime calculated using the phasor approach. We added to the revised Figure 4 representative decay curves of plasmablasts as well as their mono-exponential fits. The corresponding fluorescence lifetimes amount to 1937±49 ps and 703±56 ps. The long fluorescence lifetime indicates little FRET-quenching and, thus, a low cytosolic calcium concentration around 150 nM, however no unquenched CFP (2300 ps) indicating calcium-free medium. The short fluorescence lifetime corresponds to fully FRET-quenched CFP indicating a high calcium concentration in cytosol, above 1 µM. Additionally, these results confirm under in vivo conditions the determined τ max and τ min of CFP in the TNXXL construct, used for the calibration. The bi-exponential approximation of the exemplary decay curves led to τ1 = 563±135 ps and τ2 = 2335±180 ps (mean τ 1937±49 ps) and τ1 = 703±56 ps and τ2 > 15000 ps representing background noise (mean τ 703±56 ps).

2. Expression of TN-XXL sensor in one allele (TN-XXL+/-) vs homozygous (TN-XXL+/+) animal should be different in intensity but not in the percent of B cells positive for TN-XXL. This should be clarified.

We agree with the reviewer that the description on TNXXL sensor expression, as presented in the previous version of the manuscript, is inconclusive. We have revised the data and added some more recently generated data sets, where we paid particular attention in order to handle all cells uniformly careful (Author response image 4). We find that there is no evidence of differential expression between the genotypes. We explain the discrepancies of the original data with the fact that gating on YFP-Intensity alone is insufficient to draw conclusions about expression. This is because YFP Intensity is also a result of the amount of Ca2+ ions present within the cells, and not only of the amount of TNXXL-molecules. Within a heterogeneous population of splenic B cells, YFP-intensity comprises a spectrum rather than a uniquely assignable feature. Thus, overlaying effects like pre-activation of a proportion of cells create the impression that there are more cells in the YFP+ gate, which they can be attributed to because of their then higher YFP-intensity. On the other hand, cells not being part of this gate because of lower intensity do not equal cells that have no TNXXL expression. However, because eCFP is unquenched in these individuals, their YFP-intensity will be too low for detection in the YFP+ gate.

Author response image 4

3. Moreover, it appears that there were no new insights resulting from the calibrated Ca2+ concentrations. It is not unexpected that there is heterogeneity in the calcium responses.

The comment made us realize that we might have not spent enough effort to clarify the points of our findings and we thank the reviewer for that. There are two major advances we wanted to highlight with the manuscript. The first points we would like to make are methodological. While it is true that optical Ca2+ measurements have a certain tradition, we are the first

– to measure absolute Ca2+ amounts, not only relative changes in B cells and plasma cells

– to achieve Ca2+ quantification in vivo, and during a process that is central to immunity

– to establish the mathematical workflow based upon phasor analysis, that is simplifying the analysis of multi-component fluorescence lifetime decays.

Secondly, let us summarize the biologically relevant findings we made employing this new method:

– the mean calcium concentrations in cells of the B lineage differ dependent on the stage of affinity maturation they are in

– the interplay of different signaling cues leads to fluctuations of cytosolic Ca2+ concentrations that span several hundred nM

– a B cell subset with high cytosolic calcium is arising during GC reaction

– a subset with even higher cytosolic calcium is present among plasma blasts

Based on these findings, we propose the exciting possibility, that selection of high affinity B cell clones in the GC is coupled to distinct concentrations of Ca2+ within the cells, controlled and kept within thresholds by co-stimulation and metabolic turnover. Additionally, to unravel the interplay between signaling and other cues for calcium concentration changes, like intracellular release from ER or mitochondria, is a challenge, which we would like to meet with our research in the future. It is known that there is a link between Ca2+ as a mediator of cell-intrinsic and –extrinsic stressors, guiding vital processes like autophagy or the unfolded protein response in order to cope with environmental changes, which may be important especially in long-lived plasma cells. Taken together, we are convinced that this system will crucially contribute to our understanding of B cell activation and differentiation in vivo.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

The reviewers, two of whom are new due to the unavailability of one of the original reviewers, appreciate your efforts to address the original concerns. The consensus is that you have succeeded in calibrating the lifetime measurements, with one caveat that the use of the lysate may not fully recapitulate the conditions in a live cell, but since it's difficult to clamp Calcium in a live cell your solution is acceptable. The experiments addressing the role of antigen in germinal centre B cell activation are considered helpful as a sensitivity test, but there is a consensus that your new text over-interprets the data presented. You have established BCR triggered Calcium flux in vitro (original data) and in vivo (new data with antigen injection), but this capability doesn't appear to help understand the heterogeneity of B cell's Calcium levels in the germinal centre or medullary cords. The reviewers can see a positive path and are happy to see another revision if you can respond to the new concerns, which largely relate to refining presentation of the new information introduced in your first revision.

The calibration of the lifetime data is appreciated, but some discussion should be given to limitations of the approach, which are unavoidable, but requires caution.

We thank the reviewers and the editor for pointing out we didn’t sufficiently comment on the possible pitfalls of a fluorescence lifetime calibration of the TN-XXL construct in cell lysates, as compared to cells, in the previous version of our manuscript. In the revised version of the manuscript, we added information on the parameters which influence the fluorescence lifetime of CFP and which may differ between lysate and cytosol of a living cell. We would like to emphasize that the fluorescence lifetime of fluorophores depends on the refractive index (Strickler and Berg, 1962, J. Chem. Phys. 37:814) and may be influenced by various other factors such as pH, temperature, or ionic strength. We have paid a lot of attention to ensure that all measurements of cell lysates were performed under conditions similar to those in the cytoplasm, except for the fact that they have been performed at room temperature instead of 37°C. While Laine et al., PLoS ONE, 2012 reported a slight decrease of Cerulean fluorescence lifetime in the TN L15 construct in the range 20°C – 50°C, we did not observe such a trend as we measured the same CFP fluorescence lifetime both at 37°C and at room temperature.

The NP-BSA induced Calcium elevation in vivo extends results with anti-Ig from Figure 2 and supports ability to detect BCR dependent Calcium ion elevation in vivo. NP-BSA can trigger apoptosis (Nossal, PMID 7753199) and that interactions with myeloid cells in the MC seems to limit antibody secreting cells numbers (Fooksman, PMID 24376270) such that signals leading to apoptosis may also be contributing to the Calcium signals observed in the system.

We are pleased that the reviewer agrees that the added experiments support the detection of BCR dependent calcium elevation. We thank the reviewer for his important comment on the relation of elevated calcium and apoptosis. We would like to point out that it is not our intention to exclude the possibility of apoptosis-induction (after addition of soluble antigen) contributing to an increased calcium concentration in the cells. This mechanism is not in conflict with what causes it, namely stimulation of the BCR, but may rather contribute to selection within the GC. In fact, it supports the assumption, that high calcium concentrations after potent BCR stimulation have to be contained via costimulatory signals, as outlined and backed up with additional references within the discussion. As the reviewer pointed out, plasma blasts in the MC may also undergo apoptosis, albeit this may be triggered by different mechanisms than in GCs. In fact, preliminary data we generated using the system in a follow-up project already point to a connection between calcium concentrations, metabolic stress and autophagy in long lived plasma cells.

This could be incorporated into the discussion of different explanations for the high Calcium subsets. It would also make sense to cite early work from Cahalan that Calcium elevation can lead to arrest of cell motility (Negulescu et al., PMID: 8630728).

The authors agree. We inserted a paragraph dealing with possible sources as well as outcomes of high calcium in cells. We thank you for introducing the relevant reference we missed, and we would like to draw your attention to figure 3 —figure supplement 1, which shows a correlation between motility and calcium elevation obtained from a single cell tracked in vivo. In our hands, cell arrest seems to appear very shortly before the rise of the calcium concentration. Since calcium, as we have added in the discussion, also affects the cytoskeleton, it contributes with some certainty to cell arrest.

But it's important to point out that demonstrating that you can detect effects of BCR engagement by injecting polyvalent antigen is not the same as showing that Calcium elevation observed in germinal centre and medullary cords in the system set up by earlier immunisation is due to antigen recognition.

Thank you. We clarified in the discussion that a direct demonstration of BCR engagement does not reflect the physiologic situation of B cells taking up AG from immune complexes bound to the FDC surface.

In fact, the apparent lack of effect of the BTK inhibitor doesn't support a role for BCR signalling in the heterogeneity of Calcium.

The new data in Figure 5a is appreciated as it attempts to address the role of BCR signalling using a BTK inhibitor and injecting NP-BSA as a BCR ligand. The description of the experiments suggests that you have performed a very demanding time-course with a baseline, BTK inhibitor injection and then NP-BSA injection. Could this data be shown- similar to Figure 4g, but with breaks where the injections were performed.

Thank you for this idea and giving us the chance to present additional data (see Figure 5 —figure supplement 3): the time-dependent plots in fact are presenting two or three subsequent measurements of the same area, that is, the same GC, with breaks of about 5 min when injections were performed, indicated by interruption of the time axis. We have to add that, in our set up, it is not possible to inject during an ongoing measurement, so the cells tracked in each segment of the graph are to be treated as separate objects. We tried to be clear about this by adding text in the legend and methods, as well as to indicate the interruptions by grey dashed lines. Nevertheless, we are confident that an increase in baseline calcium levels is visible after intravenous application of NP-BSA. A slight decrease of calcium levels after ibrutinib injection, as well as a missing elevation of the calcium concentration after subsequent NP-BSA injection can also be recognized, which supports BCR stimulation with AG as one possible calcium mobilizing pathway in GC B cells.

There are questions about how long it takes these agents to get to the lymph nodes after IV injection. The inhibitor may be fine, but I'm not sure the NP-BSA will get to the germinal centre in a lymph node by this route as it will need to leak through the vasculature into the peripheral tissues and then drain to the LN. Do the authors know of data on BSA pharmacodynamics that would suggest it gets into the germinal centre in minutes after IV injection? I know of data for peptides getting into the T cell zone rapidly, but not for an intact protein that is maintained in the blood by FcRn. I would think that marginal zone of spleen would be the main point of entry for IV protein into secondary lymphoid tissues.

We appreciate this question, which brings up an important point regarding the reliability of our data. We added text citing work from Roozendaal et al., where transport of antigen into B cell follicles is characterized based on size exclusion. The study shows that small antigen is transported rapidly to the lymph node B cell follicles via conduits. The authors state that they can detect fluorescently labeled AG of less than 70kDa in the follicles within less than 2 minutes after subcutaneous injection. Since BSA has a molecular weight of about 66kDa, we can assume to achieve AG-mediated BCR simulation a few minutes after injection. For intravenous application, delivery to the LN is expected to be even faster.

As mentioned above, you need to think carefully about reasonable interpretations of these data and revise the discussion regarding possible sources of Calcium heterogeneity.

We agree and have accordingly revised the discussion. The felt bias towards BCR signaling was not our intention, instead, we tried to emphasize that calcium heterogeneity or mobilization is not to be equaled with signaling per se; and that our read-out is indirect. However, we think our data demonstrate a contribution of BCR-activated calcium flux to overall heterogeneity in cytoplasmic calcium of B lineage cells, and can serve as proof-of-principle for our system. We have substantially revised the discussion and we hope that this has contributed to make clear that we assume that intracellular calcium in B cells is influenced by many factors, some of which we discuss in more detail.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Your last revision didn't appear to address the reviewers concerns, but the Reviewing Editor asked for another opinion in an attempt to pinpoint and articulate the key issues related to calibration.

We thank the editors and the reviewers’ panel for giving us the opportunity to clarify the open issues regarding the validity of our calibration using phasor-based FRET-FLIM of the calcium-sensor TN-XXL in the cytosol of B lymphocytes, for intravital use. Especially, the comments of the new reviewer helped us to understand the issues the reviewers had with the description of our calibration method. In this way, we had the chance to improve our manuscript with the support of an expert reviewer in phasor analysis and FLIM, underlining the interdisciplinary character of the study. Following the suggestions of the new reviewer, we provide in the new version of the manuscript a thorough description of the new calibration algorithm, which resembles the features of the algorithm proposed by Celli et al., Biophys. J, 2010. Also, we provide more information on the FRET-FLIM method itself, provide pixel-based phasor plots of FRET-FLIM data acquired extracellularly, in vitro and in vivo, and elaborate more on the advantages and shortcomings of the method for intravital calcium imaging in the cytosol of B lymphocytes, in YellowCaB mice.

The opinion below agrees that the revision didn't address reviewer concerns, but suggests a different approach to the Phasor calibration that may help resolve this issue, although it would still require some adaptation from the original use with a Calcium indicator to the current use with a Calcium biosensor. The Reviewing Editor hopes that this will be helpful in focusing a final revision that can be resent to all active reviewers, but please feel free to send a revision plan if you want feedback before undertaking major work.

"I found this article quite confusing in regard to the calcium calibration and the proper citation of the phasor method. The authors fail to cite the paper using the phasor approach for the calcium calibration "Celli A, Sánchez SA, Behne MJ, Hazlett TL, Gratton E, Mauro TM. The epidermal Ca(2+) gradient: measurement using the phasor representation of fluorescent lifetime imaging. Biophys J. 2010; 98(5): 911-921. PMCID: PMC2830439. This paper addresses the issue of the calibration of indicators, not biosensors. It uses a different method based on the position of the data on the phasor plot rather than attempting a calibration that cannot be done due to the diversity of the calibration solutions with respect to the environment where the biosensor is located, which is a major point of the previous comments. The only phasor plots in this paper are in figure 4, where the phasor of the biosensor is located but in my opinion the calibration method suggested in the paper by Celli et al. is not applied. This is important for the overall interpretation of the results and the conclusion of this article."

We agree with the new and the previous reviewers that by presenting the calibration algorithm only in time-domain, may have been not sufficient to highlight the validity of our calibration for its use in living B cells and in lymph node tissue, at various tissue depths. In the revised version of the manuscript, we included a section dedicated to the calibration of the TN-XXL FRET-based Ca-sensor in B lymphocytes for its use to monitor cytosolic calcium levels in lymph nodes of YellowCaB mice in vivo.

In this section, we emphasized that the TN-XXL biosensor is exclusively expressed in the cytosol of B lymphocytes and not in other, more heterogeneous compartments such as high-Ca2+ organelles (ER, Golgi apparatus) or the extracellular space. This information is particularly important since, as already known from the pioneering work of Gregorio Weber (Jameson et al., 1984; Gordon, Jameson, 1969), fluorescence decays of fluorophores – and by that both fluorescence lifetimes in time-domain and phase vectors in frequency-domain – may change due to alterations in physical and chemical properties of the environment surrounding the fluorophore molecules. In the revised version of the manuscript, we now emphasize how refractive index, ion strength, pH value, temperature, oxygen levels may impact on the fluorescence decay of CFP in the TN-XXL construct in B lymphocyte lysates, as compared to the cytosol of these cells. We also discuss the fact that intravital imaging of lymph node tissue at different depths may also lead to changes in the CFP fluorescence decay (e.g. due to wave-front distortions, scattering or tissue autofluorescence).

In order to assess the effect of such experimental artifacts on our results, we established, next to the previously proposed time-domain formalism to calculate cytosolic calcium levels in B lymphocytes expressing TN-XXL from FRET-FLIM data (Equation (3,4)), a formalism based only on the phasor approach of the same data. This approach is similar to that published by Celli et al., 2010 for the Calcium Green dye CG5N, but adapted to FRET-FLIM of the TN-XXL construct as follows:

– Similar to the work of Celli et al., also in our case, we detect only the free calcium with our biosensor, so that the chemical equilibrium is: Ca2+ + TN-XXL↔ Ca2+TN-XXL and its dissociation (equilibrium) constant Kd can be written as [Ca2+TN-XXL]/[Ca2+][TN-XXL]. (Equation (1,2) in the manuscript). The Kd value was determined, as also proposed by Celli et al., alone from the FRET-FLIM data in lysates of defined Ca2+ concentrations. Since cytosol and lysate of B lymphocytes share a similar composition, we also consider this approach to be sufficiently accurate, as also stated by Celli et al.

– We replaced in all following equations the unbound dye state ([CG5N]) by the unquenched state of the donor CFP ([TN-XXL]) and the fully bound dye (saturated with calcium) with the fully FRET-quenched state of CFP ([Ca2+TN-XXL]). In this way, we deduced the relation between free calcium concentration and the measured phase vector in each pixel of the image (Equation (5)), which depends on the phase vectors and brightness values of CFP in the two extreme TN-XXL states, i.e. no bound calcium and fully saturated by calcium.

– We calculated the brightness values of the two extreme states of CFP, i.e. TN-XXL and Ca2+TN-XXL, as the product of their fluorescence lifetimes, fluorescence decay rate of CFP in vacuum kF, (together fluorescence quantum yield) and active two-photon absorption cross-section of CFP under excitation at 850 nm, CFP. Since neither the excitation (given by δCFP) nor the fluorescence rate kF in vacuum are influenced by the molecular surrounding of a fluorophore molecule, these values are the same for all states of CFP. In the Equation (6,7) only the fluorescence lifetime reflects the impact of the molecular environment on the brightness value. Since the exact fluorescence lifetimes of CFP in the extreme TN-XXL states (2312±54 ps and 744±90 ps, respectively), as measured in cell lysate at known free calcium concentrations, could also be measured under our in vivo conditions, in B lymphocytes in lymph nodes of YellowCaB mice, we conclude that the ratio of the brightness values for the extreme TN XXL states remains the same for lysate, B lymphocytes in culture and in live lymph node tissue.

– We show phasor plots of CFP fluorescence decays in an image:

i. In lysate solutions of YellowCaB B lymphocytes at defined free calcium concentrations (0 nM, 39 µM and 602 nM) – Figure 4c,

ii. In YellowCaB B lymphocytes in three different lymph nodes (three different animals), acquired in vivo, Figure 4e, and

iii. In YellowCaB B lymphocytes in cell culture, (Figure 4 —figure supplement 1).

In all phasor plots, we represented the extreme states measured in lysate as blue cloud (0 nM free calcium) and as red cloud (39 µM free calcium). In all three experimental setups (extracellular, cell culture and in vivo) the orientation of the calibration segment connecting the blue cloud of “no calcium” (TN-XXL) and red cloud of “full calcium saturation” (Ca2+TN-XXL) in the phasor plot remains the same. Under in vivo conditions we could not induce a complete shift of the phasor cloud, i.e. in all B lymphocytes of the popliteal lymph node, towards intracellular calcium saturation, due to animal welfare reasons. However, we repeatedly detected that parts of the phasor clouds in lymph nodes reach out to the position of calcium-saturated TN-XXL (red cloud), indicating that both orientation and length of the calibration segment determined in lysates remains valid under in vivo conditions.

– By showing the phasor plots of CFP fluorescence in B lymphocytes (Figure 4f), in different depth layers of a lymph node, encompassing B cell follicles and medullary cords (representative data of n = 3 mice), we could confirm that the data comply with the requirements imposed by the calibration, independent of tissue depth.

– We further acquired phasor plots of endogenous signal in lymph nodes of non-fluorescent C57Bl/6J mice (Figure 4g), to assess the impact of this signal on our cytosolic calcium results. Generally, the endogenous signal after excitation at 850 nm in B cell follicles and medullary cords areas was low. Its phasor cloud was located around the origin (0;0) of the phasor plot, indicating that mainly electronic noise of the device is responsible for this signal rather than optical signal originating from the sample, e.g. autofluorescence. Hence, if the excitation power is not sufficient to induce an appropriate fluorescence signal of CFP in B lymphocytes expressing TN-XXL, the phasor cloud of CFP fluorescence will be a linear combination of three reference positions: the two extreme positions of CFP fluorescence (from TN-XXL) and the origin of the phasor plot. This would result into a shift of the phasor cloud away from the calibration segment towards the origin (0;0). As shown in Figure 4c, 4e and in Figure 4 —figure supplement 1, this is not the case in our experiments.

Concluding, both Equation (5) for the phase vector in each pixel and Equation (11) for calculating free calcium concentrations, i.e. the key equations of the phasor-based formalism, are valid for extracellular (lysates) as well as cellular measurements, in vitro and in vivo, in our case.

Additionally, we now stated in the manuscript the dynamic range of the biosensor, giving the absolute Calcium concentrations that we could measure based on our FRET-FLIM data, i.e. in the range between 100 nM and 4 µM free calcium.

We further compared both formalisms (time-domain and phase-domain) in order to test whether they are equivalent. The discrepancies between the calcium level values calculated with these two formalisms (Equation 4 vs. Equation 11) were lower than 5 % in all cases, presumably due to numerical uncertainty caused by logarithmic calculation in Equation (4).

https://doi.org/10.7554/eLife.56020.sa2

Article and author information

Author details

  1. Carolin Ulbricht

    1. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Charitéplatz 1, Berlin, Germany
    2. Immune Dynamics, Deutsches Rheuma-Forschungszentrum Berlin, ein Institut der Leibniz-Gemeinschaft, Berlin, Germany
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Visualization, Methodology, Writing - original draft
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2983-6242
  2. Ruth Leben

    Biophysical Analytics, Deutsches Rheuma-Forschungszentrum, ein Institut der Leibniz-Gemeinschaft, Berlin, Germany
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  3. Asylkhan Rakhymzhan

    Biophysical Analytics, Deutsches Rheuma-Forschungszentrum, ein Institut der Leibniz-Gemeinschaft, Berlin, Germany
    Contribution
    Data curation, Software, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3152-1557
  4. Frank Kirchhoff

    Universität des Saarlandes, Saarbrücken, Germany
    Contribution
    Resources
    Competing interests
    Reviewing editor, eLife
  5. Lars Nitschke

    Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared
  6. Helena Radbruch

    Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
    Contribution
    Supervision, Funding acquisition, Writing - original draft
    Competing interests
    No competing interests declared
  7. Raluca A Niesner

    1. Biophysical Analytics, Deutsches Rheuma-Forschungszentrum, ein Institut der Leibniz-Gemeinschaft, Berlin, Germany
    2. Veterinary Medicine, Freie Universität Berlin, Berlin, Germany
    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Project administration, Writing - review and editing
    Contributed equally with
    Anja E Hauser
    Competing interests
    No competing interests declared
  8. Anja E Hauser

    1. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Rheumatology and Clinical Immunology, Charitéplatz 1, Berlin, Germany
    2. Immune Dynamics, Deutsches Rheuma-Forschungszentrum Berlin, ein Institut der Leibniz-Gemeinschaft, Berlin, Germany
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Project administration, Writing - review and editing
    Contributed equally with
    Raluca A Niesner
    For correspondence
    hauser@drfz.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7725-9526

Funding

Deutsche Forschungsgemeinschaft (TRR130 P17)

  • Helena Radbruch
  • Anja E Hauser

Deutsche Forschungsgemeinschaft (TRR130 C01)

  • Raluca A Niesner
  • Anja E Hauser

Deutsche Forschungsgemeinschaft (TRR130 P04)

  • Lars Nitschke

Deutsche Forschungsgemeinschaft (SFB1444 P14)

  • Raluca A Niesner
  • Anja E Hauser

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Patrick Thiemann, Vivien Theissig, and Manuela Ohde for animal caretaking. We thank Robert Günther for excellent surgical assistance and Peggy Mex for cell isolations and stainings. We thank Ralf Uecker for microscope facility services. We further thank Mathis Richter, who provided support with the SNR-based quality check of imaging data and their evaluation. This study has been supported by the Deutsche Forschungsgemeinschaft (DFG) TRR130, project 17 (to AEH and HR) and C01 (to AEH and RAN), and DFG SFB 1444, project 14 (to AEH and RAN).

Ethics

Animal experimentation: The study was approved by the Berlin Landesamt für Gesundheit und Soziales under the registration # G00158/16. All surgeries and experimental procedures were conducted following the principle of minimization of suffering and 3R means were used where possible.

Senior Editor

  1. Satyajit Rath, Indian Institute of Science Education and Research (IISER), India

Reviewing Editor

  1. Michael L Dustin, University of Oxford, United Kingdom

Reviewer

  1. Michael L Dustin, University of Oxford, United Kingdom

Publication history

  1. Received: February 14, 2020
  2. Accepted: March 19, 2021
  3. Accepted Manuscript published: March 22, 2021 (version 1)
  4. Version of Record published: April 21, 2021 (version 2)

Copyright

© 2021, Ulbricht et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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