Content uploaded by Daniel J Cohen
Author content
All content in this area was uploaded by Daniel J Cohen on Jan 19, 2015
Content may be subject to copyright.
A Modified Consumer Inkjet for Spatiotemporal Control
of Gene Expression
Daniel J. Cohen
1
*, Roberto C. Morfino
2
, Michel M. Maharbiz
3
1Department of Bioengineering, University of California, Berkeley, California, United States of America, 2Department of Electrical Engineering, E
´cole Polytechnique
Fe
´de
´rale de Lausanne, Lausanne, Switzerland, 3Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of
America
Abstract
This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of
gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet
printer was adapted for chemical printing; E. coli cultures were grown on 750 mm thick agar embedded in micro-wells
machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing
of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We
demonstrate how the bistable nature of the lac operon’s feedback, when perturbed by patterning lactose (inducer) and
glucose (inhibitor), can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in
developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA
expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A
finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good
fidelity.
Citation: Cohen DJ, Morfino RC, Maharbiz MM (2009) A Modified Consumer Inkjet for Spatiotemporal Control of Gene Expression. PLoS ONE 4(9): e7086.
doi:10.1371/journal.pone.0007086
Editor: Christophe Herman, Baylor College of Medicine, United States of America
Received June 17, 2009; Accepted August 19, 2009; Published September 18, 2009
Copyright: ß2009 Cohen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The National Science Foundation and the National Defense Science and Engineering Fellowship (NDSEG). The funders had no role in study design, data
collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: dancohen@berkeley.edu
Introduction
The development of methods that introduce spatiotemporal
perturbations into developing, multi-cellular systems via soluble
molecules has a long history [1–4] and a rich, recent body of
literature. Specifically, advances in microfluidics [5–10] and
biochemistry [11–14] are beginning to open the door to direct
modulation of developmental pattern formation at the spatial and
temporal scale of the cell’s control circuitry. Such devices can
provide spatially rich, real-time input-output (I/O) signals to bias
toward developing cells into specific phenotypes. In the context of
synthetic biology, such interfaces would add a degree of control
over the pattern formation dynamics in multi-cellular structures
that are expressing genetic circuits intended to coordinate activity
through soluble molecules [15]. Initial efforts in building synthetic
multicellular constructs have already begun [15,16] and, as these
mature, a robust chemical interface will be invaluable in
addressing and biasing the development of patterns. In the context
of control theory, such devices would allow an exploration of
equilibria, stability criteria, and the non-linear dynamics of
regulatory circuits. In the context of regenerative medicine and
tissue engineering, these devices could potentially provide active,
spatiotemporal control of morphogenesis [8,17,18].
While it is clear that these applications call for systems capable
of high-resolution dosing of multiple chemicals onto ensembles of
cells, it is less clear how best to achieve this in a way that is low-
cost, versatile, and open-source. Although a number of micro-
fluidics-based attempts have been published [5,9,19,20], all have
limitations in resolution, complexity of fabrication, or ease of use.
As an alternative to microfluidics, we considered inkjet technology.
To date, inkjets have been incorporated into a variety of biological
techniques including: direct cell printing for patterning [21,22]
and tissue engineering [23–27], assorted cell factor printing to
regulate cell positioning and behavior [27–30], and DNA micro-
array fabrication [31]. This list demonstrates the versatility of the
platform, although inkjets have yet to be used for active regulation
of cellular behavior. Commercialized research-grade inkjet
systems such as the Fujifilm Dimatix system exist but cost orders
of magnitude more than consumer-grade printers and usually only
print one ink at a time.
This paper presents the adaptation of a commercial, low-cost,
piezoelectric inkjet printer and commercial compact discs (CDs)
for use as a chemical interface system designed to actively regulate
cellular development (Figure 1). The printer is capable of
addressing up to six different soluble chemicals and subsequently
delivering precise doses of these chemicals to cell cultures at
226 dots/mm. The platform can be integrated with inline
microscopy to acquire data at specific time points post-dosing.
Additionally, no custom software is required for our approach,
making the whole system simple and user-friendly. While the CD
platform is compatible with the rich toolset of polymer
microfluidics [32,33] and could be adapted into a more
sophisticated device in future work, its use here was solely as a
convenient, readily modifiable substrate that was compatible with
the printer. In this study we used the inkjet to control the
spatiotemporal reaction-diffusion dynamics of gene expression in
PLoS ONE | www.plosone.org 1 September 2009 | Volume 4 | Issue 9 | e7086
the lac regulatory system by printing specific patterns of lactose
and glucose onto a field of E. coli.
Thechoiceoflac was deliberate, in that it is commonly used in
synthetic biology and has a number of interesting control
features, including well-characterized feedback and multiple
stable states [34–36]. We were surprised by the observation that
the bistable nature of the lac operon’s feedback system, when
perturbed by patterns of lactose (inducer) and glucose (inhibitor),
can lead to coordination of cell expression patterns across a field
in ways that mimic motifs seen in developmental biology.
Examples of this behavior include sharp gene expression
boundaries and the generation of traveling waves of mRNA
expression from single ‘trigger’ patterns. In this context, lactose
and glucose are analogous to morphogens in a developing
system, with the lac operon acting as a general template for
exploring how spatially-graded perturbations generate rich
behavior in bistable circuits. This is especially interesting given
that lac, while employing positive and negative feedback and
diffusible molecules (i.e. glucose and lactose), is not usually
considered a reaction-diffusion system capable of generating
pattern. By contrast, there is a vast literature on Turing-type and
other reaction-diffusion systems and their applications to
biological pattern formation [37].
Methods
Theory and Model
The lac operon is one of the best studied regulatory pathways in
microbes [34–36,38]. In E. coli, kinetic data for the entire lac
operon is available and robust models have been developed
[34,35]. Moreover, the dynamics of the system are well
understood, and are known to exhibit multiple stable points
[34–36]. In the canonical lac system (Figure 2), extra-cellular
lactose is taken up by lactose permease, where it is converted to
allolactose by b-galactosidase. Allolactose upregulates the produc-
tion of both b-galactosidase and lactose permease by inhibiting the
repressor of the lac promoter. This lactose-based, positive feedback
loop has been shown to be bistable [34]; below a certain lactose
threshold, little lactose is converted while, above this threshold, the
system jumps to a much higher consumption rate. Glucose acts to
inhibit the conversion of lactose by lowering the transcription rate
of the lac operon via cAMP and the catabolite repressor protein
(CRP). This acts as negative feedback for the conversion of lactose.
Both lactose and glucose are soluble in the extra-cellular space. We
chose to model (Figure 2) the lac system as a set of coupled
differential equations, following models developed by [34,35] (see
Appendix S1). The well-known X-Gal assay [39] introduces the
soluble X-Gal compound, which is cleaved by b-galactosidase into
5-bromo-4-chloro-3-hydroxyindole, in turn oxidizing to 5,59-
dibromo-4,49-dichloro-indigo, finally resulting in an insoluble blue
product. This allows for b-galactosidase activity to be assayed.
Experimental overview
All experiments involved a series of four steps, detailed below.
First, bacteria were cultured in advance of an inkjet print run.
Once at the proper optical density (OD
600
), they were spread over
an agar substrate containing X-Gal and incubated until printing
time. During the incubation period, the printer was sterilized and
loaded with lactose and glucose. At the appropriate time, the
bacteria were removed from the incubator, loaded onto the
substrate CD, printed upon, and returned to the incubator.
Additional information is provided in Appendix S1.
Cell culture
E. coli strain MG1655Z1 was used in this study [40]; the strain
contained a low-copy number plasmid (pNS2-sVL) with three
reporters, one of which is GFP driven by the lac promoter. The
initial culture, suspended in LB Agar (Sigma LB at 20 g/L and
Sigma Bacteriological Agar at 14 g/L), was prepared for freezing
with the addition of 50% glycerol. Colony plates were created by
taking a sterile loop and transferring a sample from the freezer
stock to 5 mL of LB Broth (Sigma, 20 g/L) containing Kanamycin
(50 mg/mL). This culture was incubated at 37uC for 12 hours and
then spread, via sterile probe, onto the surface of an LB Agar plate
containing Kanamycin (50 mg/mL). The colony plate was incubated
at 37uC for a further 12 hours, before being transferred to a
refrigerator maintained at 4uC.
Figure 1. Overview of the printing system. (left) The dosing
method is based on the delivery of multiple chemical compounds from
piezoelectric printer heads onto specially prepared compact disk (CD)
templates modified so as to support thin layers of microbial agar
cultures, (upper-right) the printer used was the Epson R280, here shown
being loaded with a modified CD, (lower-right) close-up of a modified
CD with stand-offs for the print rollers and two LB/X-Gal agar cultures of
E. coli dosed with lactose patterns (which induce the characteristic X-Gal
blue color, see text).
doi:10.1371/journal.pone.0007086.g001 Figure 2. Graphical representation of the
lac
operon. This depicts
the model used with the simulation. See Appendix S1 for modeling and
simulation details.
doi:10.1371/journal.pone.0007086.g002
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 2 September 2009 | Volume 4 | Issue 9 | e7086
Print medium preparation
LB Agar was poured to a depth of 750 microns in Petri dishes
and chilled overnight at 4uC. Prior to plating the cells, the plates
were removed from the refrigerator, and 200 mL of X-Gal solution
(Sigma, 20 mg/ml in DMSO) was bead-spread onto the surface of
each plate. Ten minutes were allowed for the X-Gal to penetrate
the agar and for the DMSO to evaporate. Finally, 150 mLofan
overnight E. coli suspension (diluted to OD
600
0.8) was bead-spread
onto the surface and allowed to sit for 10 minutes, after which the
plates were wrapped with Parafilm and placed in a 37uC incubator
for 3.5 hours, at which point they had just entered the exponential
phase [41].
Inkjet modification and printing
As detailed descriptions of the modifications made to the Epson
R280 are included in the Appendix S1 and Movie S1, an abbreviated
summary is presented here. The necessary modifications require
commonly available tools and several hours to complete, and the
procedure should be adaptable to a number of different printer types.
Figure 3. Resolution test varying only the width of the printed region. Four bars of lactose were printed with the following widths (left to
right): 3.5 mm, 2.0 mm, 1.5 mm, and 0.75 mm. Note the abrupt transition to a low level of induction at the 0.75 mm bar. Further note the close
agreement between the empirical data and the simulation. The discrepancies at the boundaries are a result of the optical properties of the agar at the
boundaries of the sample that were not taken into account in the simulation.
doi:10.1371/journal.pone.0007086.g003
Figure 4. Half-toning demonstration of minimum feature
spacing. Half-toning was used to produce a 2-D, graded template
(left) with the feature density decreasing towards the top of the pattern.
As expected, large, closely situated features tended to blur (right), while
distinct features emerged when the feature density decreased. This
behavior can be used to modulate feature interaction as a function of
geometry and the transport properties of the medium.
doi:10.1371/journal.pone.0007086.g004
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 3 September 2009 | Volume 4 | Issue 9 | e7086
We used an Epson R280 inkjet for several reasons. Epson
printers use piezoelectric print-heads, as opposed to thermal jet
heads. While both types of print-head would probably suffice for
our experiments, the mechanical nature of piezoelectric heads
means that they can safely print a greater array of chemicals, and
they do not impose temperature fluctuations on the printed fluid.
Additionally, the R280 has the ability to print on rigid substrates
(compact discs), which is not a common feature. Finally, the whole
system is low cost (,$100) and widely available.
There are three fundamental challenges related to manipulating
a printer: loading customized inks, uniquely specifying which inks
are used during a print job, and interfacing with the biological
substrate. Using an Epson R280 printer, we were able to load our
lactose and glucose inks by interrupting the ink-charging process
and manually injecting, by syringe pump, our solutions into
specific color reservoirs (300 mM lactose, 500 mM glucose). This
technique requires no manipulation of the ink cartridges
themselves; we inject ink downstream of the cartridge, meaning
that the printer functions completely normally but prints the
injected solutions rather than ink. This is simpler, less prone to
damage of the printer, and does not require the use of third-party
hardware. Having primed the printer, the final step was to prepare
it to accept a cell-bearing substrate.
We took advantage of the R280’s ability to print directly onto
the surface of compact discs and milled 800-micron deep wells
directly into the surface of CDs. The size, geometry, and position
of these wells were selected so as not to interfere with any of the
printer’s mechanisms (feed rollers or carriage drive system). By
using a CD template in Adobe Photoshop, it was possible to create
any planar pattern, uniquely specify the inks to be used, and print
directly into the wells.
Printing of chemicals onto cultured E. coli
We used sterile shim-stock to cut out individual pieces of cell-
bearing agar and transfer them to the appropriate wells on the
surface of the CD. The CD was then loaded into the printer, and
the print job sent. No run lasted longer than two minutes, and at
no point did the cells come into contact with any components of
the printer, which had previously been sterilized with 70%
ethanol. Post-printing, the agar slices were transferred to hydrated
Petri-dishes, placed in the incubator, and observed over a period
of 15 hours.
Microscopy and image analysis
Static images were taken at 15 hours post-printing and were
captured using a fluorescent backlight and an 8 mega-pixel digital
camera (Canon A590). Time-lapse data was collected using an
Intel QX3 microscope positioned within the incubator. All images
were subsequently grey-scaled, and intensity profiles were
calculated using ImageJ. The resulting intensity profiles were
normalized so that higher intensity values imply a greater
transmittance of light. All simulation data was obtained according
to the parameter set specified in Appendix S1.
Figure 5. Cross-hatched lactose resolution testing. The printer template and corresponding induction profile are shown (left), alongside a
close-up of a junction which demonstrates the sharp drop-off in induction that occurs, despite diffusion.
doi:10.1371/journal.pone.0007086.g005
Figure 6. Transient lactose induction profiles. A single bar of lactose was printed and observed for 3 hrs. Induction profiles taken at various
time points are presented (left) alongside the corresponding rate curves. Each data point in the empirical rate curve comes from averaging the
intensity across the trough of the corresponding induction profile.
doi:10.1371/journal.pone.0007086.g006
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 4 September 2009 | Volume 4 | Issue 9 | e7086
Results and Discussion
There were three key goals for this work. First, we aimed to
demonstrate the feasibility of using a commercial inkjet printer as a
micro-dosing chemical interface for cellular systems. Second, we
wished to determine whether inclusion of diffusion terms into a
partial differential equation (PDE) model of the lac operon would
predict the gene expression patterns generated by the printer.
Lastly, we hoped to explore the types of morphogenetic-like
behaviors that could be induced solely through direct, chemical
manipulation of the lac operon.
The bistability of the lac operon generates sharp gene
expression boundaries
We first characterized the resolution and pattern-formation
capability of the printer system. As we were printing into hydrated
agar (which would allow for diffusion of any dosed molecule), we
could not rely on the resolution specifications of the print head.
Concentrated lactose (300 mM) was printed in parallel bars of
varying widths onto samples and the resulting X-Gal pattern was
recorded (Figure 3). By fitting this data (in addition to the transient
data presented below) to our finite element reaction-diffusion
model, the effective diffusion rates were calculated. The fact that
competition between diffusion and reaction rates biases the bistable
response of the lac operon is evident in Figure 3. Below a certain
width of printed inducer, diffusion reduces the peak concentration,
and the lac operon never switches to its ON state (note how the
fourth bar shows a marked, non-linear decrease in induction). For
300 mM lactose and our agar formulation, features smaller than
700 mm tended not to visibly induce. Thus, by varying the diffusion
constant of the medium and the concentration of dosed inducer, the
exact minimum width of an induced feature can be precisely
controlled. A demonstration of this involves using half-toning to
produce size-graded, two-dimensional features across a field of cells
(Figure 4). Here, we see blurring between closely spaced, large
features, but more well defined smaller features. The implication is
that, by taking the transport characteristics of a system into account,
we can modulate how features interact with each other.
Bearing this in mind, Figure 5 shows a cross-hatched pattern
used to test the uniformity of response (and resolution) across a
large field of cells. This also demonstrates how the inkjet, in
conjunction with a bistable circuit, can be readily used to produce
sharp boundaries enclosing non-induced material even in the
presence of an inter-diffusion zone. By taking advantage of
bistability in the presence of weak gradients, we can achieve fairly
sharp boundaries (see below), a motif observed in embryonic
developmental programs [42]. Given a well-tuned simulation tool,
it is possible to design and print almost any induction pattern
within the resolution constraint given above.
Inline microscopy can be used to acquire time-lapse
pattern formation data
Figure 6 shows the development of X-Gal pattern over time
subsequent to lactose induction. Time-lapse microscopy was
performed within an incubator, with images being taken every
20 minutes for a period of 3 hours (see Methods). This data was
used to fit the finite element model diffusion rates. Typically,
induction becomes visible by eye after 45 minutes, and will then
plateau at around 1.5 hours.
Inkjet printing allows for the printing of 2-D spatial
chemical gradients
Figure 7 shows results for a piece-wise continuous lactose gradient
across a field of cells. Working from a grayscale image generated on
a commercial drawing program (CorelDraw 11.0), the first bar
contains 0.24 M lactose, and each subsequent bar is 20% less
concentrated than the previous bar. Such a pattern is not easily
Figure 7. Piece-wise continuous lactose gradient profile. Here, a 5-bar (3.2 mm/bar), piece-wise continuous lactose gradient was printed,
where the numbers across the bars represent the concentration of lactose printed in that bar. Again, we see very close agreement between the
empirical data and the simulation.
doi:10.1371/journal.pone.0007086.g007
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 5 September 2009 | Volume 4 | Issue 9 | e7086
attainable without a patterning device, such as the inkjet, and
demonstrates the ability to produce customized, finely controlled
patterns, in turn allowing fine control of cellular behavior.
Patterns of multiple chemicals can be printed
We took advantage of the R280’s ability to print multiple types
of ink by creating patterns composed of both lactose and glucose.
Specifically, we first printed a large, uniform field of lactose
(300 mM) over an entire sample, immediately followed by a
narrow bar of glucose (550 mM) printed on top of the lactose.
Glucose is an exceptionally strong transcriptional inhibitor for the
lac promoter, and this effect is demonstrated both by the complete
lack of induction underneath the glucose bar, and the graded level
of induction propagating out from that region (Figure 8).
Subtle reaction-diffusion dynamics arise from patterned
activator-inhibitor dosing to a bistable system
In addition to predicting general features of X-Gal production
patterns, our model predicts two pattern formation phenomena that
arise as a result of spatial heterogeneity in the initial conditions
(Figure 9).
a)a) Size invariance in a printed field (Figure 9a). The
multi-stable nature of the lac operon [34–36] allows for counter-
gradients of glucose and lactose to generate an ON/OFF
boundary (as in Figure 8) at the same location relative to the size
of the field (Figure 9a). This is a classical motif in developmental
biology known as the French Flag problem [43]; it is interesting to
observe that, even in a regulatory system not intended for pattern
formation, such behavior arises simply as a consequence of
coupling bistable gene regulation with weak (linear) gradients.
b)b) Traveling pulses of gene expression emerge from a
single initial printed pattern (Figure 9b). The coupling
of the lac operon’s reactions and the diffusion of lactose and
glucose lead to interesting dynamical behavior at boundaries
between glucose and lactose patterns (Figure 9b). Regions dosed
with lactose above the threshold for induction will immediately
begin to uptake (and metabolize lactose); conversely, areas dosed
with high amounts of glucose will not uptake lactose until all of
the glucose is taken up. This creates a reservoir of unused lactose
in the glucose-dosed regions which begins to diffuse into the
lactose-dosed regions where it is taken up. This phenomenon
leads to the darker regions seen at the boundaries (and predicted
Figure 8. Activator-inhibitor printing with lactose and glucose. Lactose was first printed over an entire field of cells. Following this, a glucose bar,
measuring 2.2 mm wide, was printed down the center ofthe field, on top of the lactose. Glucose is an inhibitor, while lactose is an activator. The result,with
which the simulation agrees, is a region of repressed lac operon activity framed by dark boundaries. The increased induction arises because the lactose
under the glucose is not consumed and, therefore, diffuses laterally, increasing the amount of lactose available for consumption along the boundaries.
doi:10.1371/journal.pone.0007086.g008
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 6 September 2009 | Volume 4 | Issue 9 | e7086
by simulation) in Figure 8. More interestingly, as both reaction
and diffusion of glucose near the boundary deplete glucose,
inhibition for lactose uptake progressively weakens and a
traveling pulse of lac mRNA transcription arises, originating
from the lactose region and extending into the glucose-rich areas.
Conclusions
This work proposed and developed a low-cost, simple interface
for regulating spatiotemporal gene expression through the use of a
consumer-level inkjet printer. The system was successfully
demonstrated using lactose and glucose to manipulate the lac
operon in E. coli. By printing a particular chemical dosing pattern
in both space and time, the printer is able to regulate the micro-
chemical environments within a field of cells.
We note two fundamental biological observations from our work.
First, even genetic regulatory systems not used for cell signaling (lac,
in this case), can be adapted to mimic developmental, morphoge-
netic regulatory systems. As long as spatiotemporal control of
chemical dosing can be achieved, many such systems might be
manipulated to perform in a manner that mimics more traditional
developmental pathways. Second, the ability to disturb chemical
boundary conditions in space and time (especially if used in
conjunction with inline imaging) may reveal new and rich dynamics
even in classical gene circuits (like the canonical lac operon).
Moreover, apart from the ability to print simple line and dot-based
patterns, the printer allows for graded dosing profiles to be created.
Owing to the non-linearity of reaction-diffusion systems, there are
important dynamics that likely cannot be seen without graded initial
conditions. Ultimately, as the system improves, the loop can be
closed with real-time monitoring of genetic activity coupled to a
controller that can actively correct or redirect activity by regulating
the temporal aspect of the dose profiles. This system can be
informed by using computational simulations as a design tool to
obtain specific patterns (in much the way that Computer Aided
Design systems work). Our system and techniques are simple, rapid,
and inexpensive, making them an attractive option for others
interested in exploring the effects of spatiotemporal dosing.
Supporting Information
Appendix S1 Explanation of simulation methodology and
procedure for modifying the inkjet.
Found at: doi:10.1371/journal.pone.0007086.s001 (1.36 MB
DOC)
Movie S1 Demonstration of flushing the print-head. Video
details the general method for cleaning and priming the print head
of the Epson R280.
Found at: doi:10.1371/journal.pone.0007086.s002 (10.47 MB
MOV)
Acknowledgments
The authors thank Will Holtz (UC Berkeley) and Professor Jay Keasling
(UC Berkeley) for helpful biological advice, and the Maharbiz Research
Group (UC Berkeley) for support and suggestions.
Author Contributions
Conceived and designed the experiments: DJC MMM. Performed the
experiments: DJC RCM. Analyzed the data: DJC RCM MMM.
Contributed reagents/materials/analysis tools: DJC MMM. Wrote the
paper: DJC MMM.
References
1. Zicha D, Dunne GA, Brown AF (1991) A new direct-viewing chemotaxis
chamber. Journal of Cell Biology 99: 769–775.
2. Engelmann TW (1881) Neue Methode zur Untersuchung der Sauerstof-
fausscheidung pfanzlicher and tierischer Organismen. Pfluegers Arch Gesamte
Physiol Menschen Tiere 25: 285–292.
3. Boyden S (1962) The chemotactic effect of mixtures of antibody and antigen
on polymorphonuclear leucocytes. Journal of Experimental Medicine. pp
453–466.
4. Bonner JT (2000) First Signals: The Evolution of Multicellular Development.
Princeton: Princeton University Press.
Figure 9. Reaction-Diffusion Dynamics. (a) Counter-gradients of activator (lactose) and inhibitor (glucose) result in scale invariant features that
preserve proportions. This was demonstrated in simulation with three different trials where the lengths were varied. The simulated data shows the
normalized lacZ mRNA concentration as a function of the distance for three different length cases demonstrating the phenomenon of scale
invariance. (b) Plot of normalized lacZ mRNA concentration for several time steps. Here, a 2 mm long strip is simulated as having been printed with
270 mM lactose, on top of which 2 mM of glucose is printed over the region between 0 and 0.75 mm. Initially, lacZ mRNA is heavily up-regulated in
the lactose-only region (everything after 0.75 mm); as both glucose is consumed for the region before 0.75 mm and lactose is consumed for the
region after 0.75 mm, an mRNA peak emerges which travels to the left over time (arrow indicates direction).
doi:10.1371/journal.pone.0007086.g009
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 7 September 2009 | Volume 4 | Issue 9 | e7086
5. Park JH, Bansal T, Pinelis M, Maharbiz MM (2006) Electrolytic patterning of
dissolved oxygen microgradients during cell culture. Lab on a Chip 6: 611–622.
6. Jeon LN, Baskaran H, Dertinger S, Whitesides G, Water LVd, et al. (2002)
Neutrophil chemotaxis in linear and complex gradients of interleukin-8 formed
in a microfabricated device. Nature: Biotechnology 20: 826–830.
7. Ismagilov RF, Maharbiz MM (2007) Can we build synthetic, multicellular
systems by controlling developmental signaling in space and time? Current
Opinions in Chemical Biology 11: 604–611.
8. Keenan TM, Folch A (2008) Biomolecular gradients in cell culture systems. Lab
on a Chip 8: 34–57.
9. Chena D, Dua W, Liua Y, Liua W, Kuznetsovb A, et al. (2008) The
chemistrode: A droplet-based microfluidic device for stimulation and recording
with high temporal, spatial, and chemical resolutio. PNAS 105: 16843–16848.
10. Bansal T, Lenhart J, Kim T, Duan C, Maharbiz MM (2009) Patterned delivery
and expression of gene constructs into developing zebrafish embryos using
microfabricated interfaces. IEEE Biomedical Microdevices 11.
11. Mayer G, Heckel A (2006) Biologically active molecules with a ‘‘light switch’’.
Angew Chem, Int Ed 45: 4900–4921.
12. Shestopalov I, Chen J (2008) Chemial technologies for probing embryonic
development. Chemical Society Review 37: 1294–1307.
13. Chambers JJ, Banghart MR, Trauner D, Kramer RH (2006) Light-Induced
Depolarization of Neurons Using a Modified Shaker K+Channel and a
Molecular Photoswitch. J Neurophysiol 96: 2792–2796.
14. Ellis-Davies GC (2007) Caged compounds: photorelease technology for control
of cellular chemistry and physiology. Nature: Methods 4: 619–628.
15. Basu S, Gerchman Y, Collins C, Arnold F, Weiss R (2005) A synthetic
multicellular system for programmed pattern formation. Nature 434:
1130–1134.
16. Brown T, Chang C, Heinze B, Hollinger P, Kittleson J, et al. (2007)
Development of an inducible three colour bacterial water colour system. IET:
Synthetic Biology 1: 21–24.
17. Gurtner G, Werner S, Barrandon Y, Longaker M (2008) Wound repair and
regeneration. Nature 453: 314–321.
18. Lutolf M, Hubbell J (2005) Synthetic biomaterials as instructive extracellular
microenvironments for morphogenesis in tissue engineering. Nature: Biotech-
nology 23: 47–55.
19. Gu W, Zhu X, Futai N, Cho BS, Takayama S (2004) Computerized microfluidic
cell culture using elastomeric channels and Braille displays. PNAS 101 :
15861–15866.
20. Peterman MC, Noolandi J, Blumenkranz MS, Fishman HA (2004) Localized
chemical release from an artificial synapse chip. PNAS 101: 9951–9954.
21. Merrin J, Leibler S, Chuang J (2007) Printing Multistrain Bacterial Patterns with
a Piezoelectric Inkjet Printer. PLoS One 2.
22. Boland T, Xu T, Damon B, Manley B, Kesari P, et al. (2007) Drop-on-demand
printing of cells and materials for designer tissue constructs. Materials Science &
Engineering 27: 372–376.
23. Saunders RE, Gough JE, Derby B (2008) Delivery of human fibroblast cells by
piezoelectric drop-on-demand inkjet printing. Biomaterials 29: 193–203.
24. Roth EA, Xu T, Das M, Gregory C, Hickman JJ, et al. (2004) Inkjet printing for
high-throughput cell patterning. Biomaterials 25: 3707–3715.
25. Boland T, Xu T, Damon B, Cui X (2006) Appication of inkjet prining to tissue
engineering. Biotechnolog Journal 1: 910–917.
26. Cohen DL, Malone E, Lipson H, Bonassar LJ (2006) Direct freeform fabrication
of seeded hydrogels in arbitrary geometries. Tissue Engineering 12: 1325–1335.
27. Rosoff WJ, McAllister R, Esrick MA (2005) Generating controlled molecular
gradients in 3D gels. Biotechnol Bioeng 91: 754–759.
28. Ilkhanizadeh S, Teixeira AI, Hermanson O (2007) Inkjet printing of
macromolecules on hydrogels to steer neural stem cell differentiation.
Biomaterials 28: 3936–3943.
29. Campbell PG, Miller ED, Fisher GW, Walker LM, Weiss LE (2005) Engineered
spatial patterns of FGF-2 immobilized on fibrin direct cell organization.
Biomaterials 26: 6762–6770.
30. Saadi W, Rhee SW, Lin F, Vahidi B (2007) Generation of stable concentration
gradients in 2D and 3D environments using a microfluidic ladder chamber.
Biomedical Microdevices 9: 627–635.
31. Lausted C, Dahl T, Warren C, King K, Smith K, et al. (2004) POSaM: a fast,
flexible, open-source, inkjet oligonucleotide synthesize r and microarrayer.
Genome Biology 5: R58–R58.
32. Madou M, Madou M, Zoval J, Zoval J, Jia G, et al. (2006) LAB ON A CD.
Annu Rev Biomed Eng 8: 601–628.
33. Ducree J, Haeberle S, Lutz S, Pausch S, Stetten Fv, et al. (2007) The centrifugal
microfluidic Bio-Disk platform. J Micromech Microeng 17: S103–S115.
34. Yildirim N, Mackey MC (2003) Feedback Regulation in the Lactose Operon: A
Mathematical Modeling Study and Comparison with Experimental Data.
Biophysical Journal 84: 2841–2851.
35. Ozbudak EM, Thattai M, Lim HN, Shraiman BI, van Oudenaarden A (2004)
Multistability in the lactose utilization network of Escherichia coli. Nature 427:
737–740.
36. Ahmadzadeh A, Halasz A, Kumar V, Prajna S, Jadbabaie A (2005) Analysis of
the Lactose metabolism in E. coli using sum-of-squares decomposition; pp
879–884.
37. Murray JD (1993) Mathematical Biology: II: Spatial Models and Biomedical
Applications. Berlin-Heidelberg: Springer-Verlag.
38. Wong P, Gladney S Mathematical Model of the lac Operon: Inducer Exclusion,
Catabolite Repression, and Diauxic Growth on Glucose and Lactose. pp 132–
114.
39. Lehninger AL, Nelson DL, Cox MM (2004) Principles of Biochemistry.
40. Dunlop MJ, Cox RS, Levine JH, Murray RM, Elowitz MB (2008) Regulatory
activity revealed by dynamic correlations in gene expression noise. Nature:
Genetics 40.
41. Fujikawa H, Morozumi S (2005) Modeling Surface Growth of Escherichia coli
on Agar Plates. Applied Environmental Microbiology 17: 7920–7926.
42. Amonlirdviman K, Khare NA, Tree DRP, Chen W-S, Axelrod JD, et al. (2005)
Mathematical Modeling of Planar Cell Polarity to Understand Domineering
Nonautonomy. Science 307: 423–426.
43. Wolpert L (1969) Positional information and the spatial pattern of cellular
differentiation. Journal of Theoretical Biology 25: 1–47.
Inkjet Controls Gene Activity
PLoS ONE | www.plosone.org 8 September 2009 | Volume 4 | Issue 9 | e7086
