Weak protein interactions quantified using a microfluidic pump

confocal image-protein interactions-microfluidic pump-elveflow

This article covers the development of an experimental method enabling Shahar Sukenik et al. to study protein interactions and detect the dissociation of GAPDH and PGK proteins in order to quantify their stoichiometry directly inside the cell by modulating the cell-volume [1].

The weakly bound protein complexes (called quinary interactions) have crucial functions in metabolic, regulatory, and signalling pathways. GAPDH and PGK proteins are two sequential enzymes in the glycolysis catalytic cycle shown to interact weakly, but the interaction has not been quantified in vivo. Their model resulted to log Kd = −9.7 ±0.3 and a 2:1 prevalent stoichiometry of the GAPDH:PGK complex.

Despite growing interest, quantification of quinary protein interactions is technically challenging because it requires detection in situ using a mildly perturbing technique. Using the Elveflow’s OB1 Mk3 Flow Controller and the MFS5 Flow Sensor, they generated a 3 mL/min precise flow rate, using hypoosmotic media and hyperosmotic media in order to induce osmolarity pressure. This flowrate was selected as an optimal value that gives fast medium switches, with little flow-related focus drifts.

Figure 1 : Representative 3D confocal images of cells subjected to volume modulation. Image at Left shows maximum xy projection. Images at Right show an xz slice before (Upper) and 1 min after (Lower) osmotic challenge. (Scale bars: xy, 20μm; xz, 10 μm)

APPLICATIONS

  • Weak protein–protein interactions characterization in live cells
  • Biomedical research on reduced scale cell components and mechanisms (RNA)
  • Complementary work to be associated with imaging phase changes inside cell
  • Study of osmolarity fluctuations consequences on mammalian cells (kidney, cartilage, blood under certain pathological conditions)

MATERIALS & METHOD

MATERIAL

OB1 Mk3 Flow Controller + MFS5 Flow Sensor

OB1-MFS-protein interactions-microfluidic pump-elveflow

FRET illumination setup

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The setup of Sukenik et al. interfaces an epifluorescence microscope with a temperature-controlled flow cell coupled to the Elveflow’s OB1 Mk3 Flow Controller, and the MFS5 Flow Sensor which flow rate range is [0 ; 5mL/min] with an accuracy of 10µL/min. The setup makes use of fluorescence resonance energy transfer (FRET) between the two light-sensitive proteins GAPDH and PGK.

METHOD

To deduce the stoichiometry of the GAPDH:PGK complex, Sukenik et al. tagged the proteins of with fluorescent protein labels (FPs), to then observe the re-equilibration process thanks to FRET mechanism and cell-volume modulation using the osmotic pressure between hypoosmotic media and hyperosmotic media (injected with the OB1 Mk3 Flow Controller).

They first tried to show that cellular crowding changes are in proportion to volume changes by using the synthetic crowding sensor fCrH2. Then, they examined two pairs of fluorescent proteins markers (FPs), AcGFP1/mCherry and mEGFP/mCherry to study which couple gives a higher fluorescence response, to finally test the best one with the GAPDH:PGK complex.

APPLICATIONS

MFS5 Flow sensor-protein interactions-microfluidic pump-elveflow

Figure 2 : (a) Representative flow profiles from 15 independent experiments showing individual flow profiles (gray) and the average (red). Flow is measured using the MFS5 Flow Sensor generated by the OB1 Flow Controller. The spikes at 10 and 160 s result from medium switching and are useful for marking the “time 0” for the osmolarity perturbation cycle.

(b) Osmolarity detected using fluorescein.  The fluorescent signal is proportional to solution osmolarity. Shown here are 6 independent measurements of a switch to 0.8 Osm (in gray) which are averaged to give the osmolarity profile (shown in red). These measurements were done independently of FRET measurements.


The OB1 Flow Controller and the MFS5 Flow Sensor used together generated an average 3mL/min flow rate with a reduced standard deviation of 0.1mL/min, namely 3,3% of the 3mL/min flow rate. By producing precise perturbation cycles, they managed to  perform fast medium switches, without flow-related focus drifts, making hypoosmotic and hyperosmotic media changes more efficient and precise.

CONCLUSION

Concerning the main results of their work, Sukenik et al. produced data showing that mEGFP does not interact with mCherry in cells. Thus, using AcGFP1/mCherry couple, their model resulted to log Kd = −9.7 ±0.3 and a 2:1 prevalent stoichiometry of the GAPDH:PGK complex. Thanks to a precise flow rate injected by the OB1 Flow Controller, they managed to perform switches of hypoosmotic and hyperosmotic media without focus drifts.

Their results finally proved that free volume modulation can be exploited to reveal the binding affinity and stoichiometry of weakly bound complexes inside the cell like GAPDH:PGK one, showing that quinary interactions quantification is from now on achievable thanks to microfluidics and Elveflow products.

RELATED PUBLICATION

[1] Shahar Sukenik, Pin Ren, and Martin Gruebele. Weak protein–protein interactions in live cells are quantified by cell-volume modulation. Proc Natl Acad Sci U S A.. (2017)