38 research outputs found
Stoichiometry of the α‑Complementation Reaction of <i>Escherichia coli</i> β‑Galactosidase As Revealed through Single-Molecule Studies
The
α-complementation reaction of β-galactosidase was
studied at single-molecule resolution using arrays of femtoliter-sized
wells. Single molecules of the complementation species were observed
to be stable for long periods of time, demonstrating that the α-complementation
reaction is irreversible. By directly counting the number of active
molecules formed in the complementation reaction when different concentrations
of enzyme acceptor (EA) and enzyme donor (ED) are used, we deduce
that the EA:ED ratio in the complementation species is 4:1
Activity traces and changes in individual β-galactosidase molecules between heat pulses.
<p>(A) Activity traces of all the individual β-galactosidase molecules taken from a single experiment. Six images were taken between each heating pulse and the activity was obtained (R<sup>2</sup> = 0.9 or greater). (B) Only four individual enzyme activity traces are shown to make it clear how the activities change after each heating pulse. The error bars correspond to linear fitting of data between heating pulses. (C, D, E, F) Histogram of the activity changes resulting from heat pulses. Negative values correspond to a decrease in the activity and positive values correspond to an increase in the activity after a heat pulse. The average changes in activity are 4 sec<sup>−1</sup>, -10 sec<sup>−1</sup>, 9 sec<sup>−1</sup>, and -15 sec<sup>−1</sup> respectively for C, D, E and F.</p
The first derivative plot of raw intensities of individual molecules with respect to time.
<p>The activities of the enzymes are relatively stable between the heating pulses. The sudden increases of the activities observed in the graph are due to the heating pulse when the solution did not have time to reach room temperature. Those frames are excluded from the analysis.</p
Single enzymes trapped in wells and raw intensities of the trajectories.
<p>(A) Image of fiber bundle with trapped active enzymes. Each enzyme generates a high local concentration of fluorescent resorufin. (B) Raw fluorescence intensities of the trajectories of individual β-galactosidase molecules.</p
Depiction of the energy landscape.
<p>An enzyme with a characteristic rate k<sub>1</sub> is trapped in a local minimum. When a heat pulse is introduced (ΔT), the enzyme changes its conformation and relaxes into a different minimum. The new conformation exhibits a different rate (k<sub>2</sub>). After sequential pulses, the enzyme can adopt different conformations leading to different rates (k<sub>3</sub>, k<sub>4</sub>).</p
Observing Single Enzyme Molecules Interconvert between Activity States upon Heating
<div><p>In this paper, we demonstrate that single enzyme molecules of β-galactosidase interconvert between different activity states upon exposure to short pulses of heat. We show that these changes in activity are the result of different enzyme conformations. Hundreds of single β-galactosidase molecules are trapped in femtoliter reaction chambers and the individual enzymes are subjected to short heating pulses. When heating pulses are introduced into the system, the enzyme molecules switch between different activity states. Furthermore, we observe that the changes in activity are random and do not correlate with the enzyme's original activity. This study demonstrates that different stable conformations play an important role in the static heterogeneity reported previously, resulting in distinct long-lived activity states of enzyme molecules in a population.</p></div
Bar graph representing the percentage of enzyme population gaining activity after each heating pulse.
<p>The error bars represent variations from four different experiments.</p
Histograms of activity distribution for single β-galactosidase molecules after each heating cycle.
<p>(A) Activity distribution of single β-galactosidase molecules before heating. The mean turnover number for the population of single β-galactosidase molecules of the enzyme population is calculated as 420 sec<sup>−1</sup>. (B,C,D,E) Activity distribution of single enzyme molecules after each sequential heating pulse. The mean turnovers numbers are 426 sec<sup>−1</sup>, 418 sec<sup>−1</sup>, 427 sec<sup>−1</sup> and 411 sec<sup>−1</sup> respectively. The bin size for all the histograms is 50 sec<sup>−1</sup>. Measurements were made at 20°C.</p
Observations of enzyme activities before and after heating.
<p>(A) Plot of the turnover number of enzymes before heating vs. turnover number after the fourth heating. No correlation between activities was observed. (B) Bar graph of sum of absolute activity changes for all enzymes after each heating pulse. No dramatic change is observed between different heating pulses.</p
Protein Counting in Single Cancer Cells
The
cell is the basic unit of biology and protein expression drives
cellular function. Tracking protein expression in single cells enables
the study of cellular pathways and behavior but requires methodologies
sensitive enough to detect low numbers of protein molecules with a
wide dynamic range to distinguish unique cells and quantify population
distributions. This study presents an ultrasensitive and automated
approach for quantifying phenotypic responses with single cell resolution
using single molecule array (SiMoA) technology. We demonstrate how
prostate specific antigen (PSA) expression varies over several orders
of magnitude between single prostate cancer cells and how PSA expression
shifts with genetic drift. Single cell SiMoA introduces a straightforward
process that is capable of detecting both high and low protein expression
levels. This technique could be useful for understanding fundamental
biology and may eventually enable both earlier disease detection and
targeted therapy