Modification of an Amplification Reaction in Recursively Dynamic Compartments Driven by Stirring

In living systems, biochemical reactions are confined to cellular or subcellular compartments, such as the plasma membrane and the organelles within a cell. These biological compartments are usually subjected to recursive changes, such as combinations of growth, fusion, and division, to constitute repeating cell cycles. In such recursively dynamic compartments, the encapsulated biochemical reaction may exhibit dynamics that differ from those of the static compartment (i.e., test tubes) used in conventional biochemistry experiments. To test this hypothesis in a simplified model, we mechanically stirred femtoliter-sized water-in-oil emulsion droplets so that individual droplets were subjected to repeated coalescence and breakage. We show that recursive dynamics appeared in the emulsion, which were measured by the exponential propagation of a water-soluble dye. The rate of the propagation, μ, was controlled by modulating the pulse-width of stirring in an electromagnetic stirrer. Within this system, we studied the dynamics of an RNA-amplification reaction in recursively increasing reaction compartments at various values of μ. We showed that there was an optimal value of μ that maximized RNA amplification. This effect was explained by the balance between the opposing effects of supply of substrate and the dilution of amplified RNA both resulting from coalescence. Moreover, when we mixed two RNA species with different kinetic properties, we found a preferential amplification for one of the species only in the recursively dynamic emulsion. This effect was partly explained by a separation effect which preferentially amplifies the number of compartments for the molecular specie that can better follow the breakage dynamics of the compartments. The present work demonstrated how the recursive dynamics of compartments modifies the internal biochemical reaction

Fluorescence micrographs showing two successive rounds of vesicle fusion (mixing), reaction, and budding/fission (aliquoting).

<p>The 5-µm scale bar in panel (a) also applies to panel (b) and to panels (e)–(h), whereas the 10-µm scale bar in panel (c) also applies to panel (d).</p

Stochasticity in Gene Expression in a Cell-Sized Compartment

The gene expression in a clonal cell population fluctuates significantly, and its relevance to various cellular functions is under intensive debate. A fundamental question is whether the fluctuation is a consequence of the complexity and redundancy in living cells or an inevitable attribute of the minute microreactor nature of cells. To answer this question, we constructed an artificial cell, which consists of only necessary components for the gene expression (<i>in vitro</i> transcription and translation system) and its boundary as a microreactor (cell-sized lipid vesicle), and investigated the gene expression noise. The variation in the expression of two fluorescent proteins was decomposed into the components that were correlated and uncorrelated between the two proteins using a method similar to the one used by Elowitz and co-workers to analyze the expression noise in <i>E. coli</i>. The observed fluctuation was compared with a theoretical model that expresses the amplitude of noise as a function of the average number of intermediate molecules and products. With the assumption that the transcripts are partly active, the theoretical model was able to well describe the noise in the artificial system. Furthermore, the same measurement for <i>E. coli</i> cells harboring an identical plasmid revealed that the <i>E. coli</i> exhibited a similar level of expression noise. Our results demonstrated that the level of fluctuation found in bacterial cells is mostly an intrinsic property that arises even in a primitive form of the cell

Brightfield micrographs showing the fusion, budding, and fission processes of GUVs.

<p>Fission (complete detachment) of daughter GUVs after budding was induced by lowering the temperature close to the <i>T_m</i> of the lipids.</p

Microscopic Examination of Cells Cultured Overnight in Three Different Media

<div><p>GFP and RFP fluorescence of cells in Medium M, N, and T were examined using an Olympus IX70 microscope and a KEYENCE VB-6010 CCD camera.</p> <p>For the GFP channel, a BA470-490 excitation filter, DM505 dichromatic beam splitter, and BA515-550 emission filter were used.</p> <p>For the RFP channel, a BA520-550 excitation filter, DM565 dichromatic beam splitter, and BA580IF emission filter were used.</p> <p>The exposure time and the sensitivity expressed as ISO values are shown in the pictures.</p> <p>Scale bar, 5 µm.</p></div

Attractor Selection in Changing Environments

<div><p> <i>E. coli</i> OSU1 cells with pALL7 were subjected to serial overnight culture with an inoculum size of 6×10⁷ cells/l every day in changing environments.</p> <p>(A) Days 1–5 in Medium N, days 6–7 in Medium T, days 8–10 in Medium N, days 11–13 in Medium M, days 14–15 in Medium N, and day 16 in Medium T.</p> <p>On the last day of serial overnight cultures in the same medium, the cells were subjected to flow cytometric analysis.</p> <p>(B) Days 1–5 in Medium N, days 6–7 in Medium M, days 8–9 in Medium T, days 10–11 in Medium N, days 12–13 in Medium M, and day 14 in Medium T.</p></div

The Three Possible Attractors Generated by the Mutual Inhibition Network under Different Conditions

<div><p>Blue dots represent the expression pattern for cells cultured overnight in Medium N, while purple dots represent that for cells that were transferred from Medium N to Medium N plus nalidixic acid and cultured for 3 days until the number of cells increased sufficiently for flow cytometric analysis.</p> <p>The diagonal correlation for purple dots was not related to any relationship of GFP and RFP expression, but was attributable to the leakage of fluorescence of GFP and RFP to the 600 nm dichroic filter and the band-pass filter at 525 nm±25 nm, respectively.</p></div

The Plasmid Structures of the Mutual Inhibition Network

<div><p>(A) The structure of the mutually inhibitory operons in pALL7.</p> <p>t₀ and <i>rrn</i>BT₁T₂ terminators terminated transcription from Operon 1 and Operon 2, respectively.</p> <p>(B) Summary of the phenotype characteristics of pALL7.</p></div

Fusion, reaction, and budding of vesicles.

<p>The upper images show GUVs before fusion. The red channel shows the marker for the substrate-containing GUV, whereas the yellow channel shows the marker for the enzyme-containing GUV. The middle images show the budding transformation process after electrofusion. The lower images show daughter GUVs after budding. The increased fluorescence in the green channel indicates the occurrence of the enzymatic reaction.</p

(a) Overview of the experimental setup.

<p>Giant vesicles are manipulated with optical tweezers and fused with an electrical pulse. (b) Schematic of the chemical-handling processes using GUVs. Reagent mixing is induced by fusion, and the reaction products are aliquoted by vesicle division. These processes are repeated for sequential (bio)chemical reactions. In the following experiments, reactions that fluoresce upon reagent mixing are used. The fluorescence in the GUV resulting from the first fusion and reaction is photobleached before the second reaction.</p