- Email: [email protected]
On-chip analysis of carbon dots effect on yeast replicative lifespan
Accepted Manuscript On-Chip Analysis of Carbon Dots Effect on Yeast Replicative Lifespan Zeinab Bagheri, Hamide Ehtesabi, Zahra Hallaji, Neda Aminoroaya, Hossein Tavana, Ebrahim Behroodi, Mahban Rahimifard, Mohammad Abdollahi, Hamid Latifi PII:
S0003-2670(18)30576-2
DOI:
10.1016/j.aca.2018.05.005
Reference:
ACA 235941
To appear in:
Analytica Chimica Acta
Received Date: 12 January 2018 Revised Date:
13 April 2018
Accepted Date: 1 May 2018
Please cite this article as: Z. Bagheri, H. Ehtesabi, Z. Hallaji, N. Aminoroaya, H. Tavana, E. Behroodi, M. Rahimifard, M. Abdollahi, H. Latifi, On-Chip Analysis of Carbon Dots Effect on Yeast Replicative Lifespan, Analytica Chimica Acta (2018), doi: 10.1016/j.aca.2018.05.005. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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On-Chip Analysis of Carbon Dots Effect on Yeast Replicative Lifespan
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Zeinab Bagheri1, Hamide Ehtesabi1, Zahra Hallaji2, Neda Aminoroaya3, Hossein Tavana4, Ebrahim Behroodi3, Mahban Rahimifard5, Mohammad Abdollahi5, Hamid Latifi3*
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Abstract Carbon dots (CDs) are promising nanomaterials for biosensing, bioimaging, and drug delivery
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due to their large surface area, excellent optical properties, and thermal and chemical stability.
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However, biosafety of CDs is still understudied, and there is not a generally accepted standard to
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evaluate the toxicity of CDs. We present a gradient network generator microfluidic device for
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dose-dependent testing of toxicity of CDs to a unicellular eukaryotic model organism, yeast
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Pichia pastoris. We fully characterized the microfluidic model and compare its performance
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with a conventional method. The gradient generator increased the contact area between the
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mixing species and enabled a high-throughput testing of CDs in a wide range of concentrations
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in cell chambers. Real time monitoring of yeast cell proliferation in the presence of CDs showed
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dose-dependent growth inhibition and various budding cell shape profiles. Comparing the result
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of microfluidic platform and conventional method revealed statistically significant differences in
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the proliferation rate of the cells between the two platforms. To understand the toxicity
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mechanism, we studied binding of CDs to P. pastoris and found increasing interactions of CDs
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with the cell surface at CDs larger concentrations. This study demonstrated the utility of the
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gradient generator microfluidic device as a convenient tool for toxicity assessment of
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nanomaterials at a cellular level.
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Faculty of Life Sciences and Biotechnology, Shahid Beheshti University G.C., Velenjak, Tehran, Iran. Protein Research Center, Shahid Beheshti University G.C., Velenjak, Tehran, Iran. Laser & Plasma Research Institute, Shahid Beheshti University G.C., Velenjak, Tehran, Iran. Department of Biomedical Engineering, The University of Akron, Akron, OH 44236, USA. The Institute of Pharmaceutical Sciences (TIPS), and Department of Toxicology and Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
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* Corresponding author. Email: [email protected] (Hamid Latifi)
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Keywords: Carbon Dots; Yeast Pichia pastoris; Microfluidics; Toxicity; Biosafety; Growth
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Inhibition
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1. Introduction Carbon dots (CDs) are a member of the carbon nanomaterials family. They are smaller than 100
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nm in size and 10 layers thick[1]. A large surface area, excellent thermal and physicochemical
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stability, and unique optical properties make CDs attractive for biological applications[2–10].
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The preparation methods of CDs are relatively simple, low cost, and easily scalable. These
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include
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electrochemical techniques [16], exfoliation-based techniques [17–19], and several others [9,20–
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23]. Although carbon is not an intrinsically toxic substance, the specific material and structural
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configuration of carbon nanomaterials may cause risks to human health. Several studies have
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evaluated toxicity of CDs in recent years [2,24–34]. However, relative to the rapid developments
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in applications of CDs, ecotoxicology and environmental hazard studies have fallen behind.
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Currently, little is known about toxic effects of CDs. Establishing new testing methods and
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technologies is expected to expedite toxicity analysis of CDs. New insights into potential
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hazardous effects of CDs in biological applications will lead to the development and design of
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safer materials.
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pyrolysis [11], oxidation techniques [12,13], hydrothermal techniques [14,15] ,
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The current approach of in vitro toxicity analysis is based on well-plate assays that require time-
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consuming manual handling of samples or costly automated robotic systems [35]. Microfluidic
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platforms are well suited for toxicity assessments due to their compatibility with high-throughput
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testing using small volumes of reagents, capability for parallel analyses, and ease of device
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fabrication. Several studies have used microfluidics for nanomaterials toxicity tests. Mahto et al.
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developed an integrated multi-compartment microfluidic device to evaluate toxicity of
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CdSe/ZnSe quantum dots (QDs) to fibroblast cells. Exposure of fibroblasts to QDs resulted in
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the production of reactive oxygen species and differences in cell morphology between static and
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flow conditions [36]. Kim et al. investigated cytotoxicity of mesoporous silica nanoparticles to
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endothelial cells lined on the surface of microchannels. Under flow and shear stress, the
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nanoparticles generated significant cytotoxicity [37]. Liu et al. developed a microfluidic device
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containing an embedded biocompatible scaffold to form hepatocyte spheroids and evaluate
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hepatotoxicity of silver nanoparticles. Treatment with the nanoparticles induced significantly
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greater membrane damage to the cells in the microfluidic device than in a conventional tissue
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culture plate [38].
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Unicellular eukaryotic model organisms are widely used to study toxicity of chemicals because
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of similarities of their biochemical structure and cellular organization to those of higher
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organisms. Yeast cells have been used in microfluidic devices to study events such as aging,
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neurotoxicity of α-synuclein protein aggregation, cell segmentation and growth, cell trapping and
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biochemical analysis [25,39–42].
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Concentration Gradient Generator (CGG) microfluidic devices offer a convenient platform to
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evaluate the toxicity of CDs to yeast cells. Due to the vast application of microfluidic gradient
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generators, various models have been introduced so far. In pressure driven models such as
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universal gradient generator, serial diluter, and tree-shaped gradient generator, mixing is
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performed through different mechanisms like parallel lamination, serial lamination and chaotic
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advection [43,44]. Some other models apply the active actuators such as micro pneumatic
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actuator, surface acoustic waves, and piezoelectric transducer to mix the solutions [45–47]. Tree-
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shaped gradient generator (also called Christmas tree) which was first proposed by the
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Whitesides group [48], is one of the most widely used models due to its simplicity in design,
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good uniformity, and robustness [49]. In Christmas tree model, two or more different solutions
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are infused into the inlets and a linear concentration gradient will be obtained at the outlets.
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Actually, the fluid streams of initial solutions are repeatedly split at the bifurcation points and
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then recombined and mixed in the mixer channels of next stages. In the serpentine mixer
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channel, molecular diffusion occurs across the interface between the laminar streams. Mixer
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channel length, solute diffusion coefficient and flow rate are the important variables to guarantee
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enough diffusive time for complete mixing at the end of each mixer branch to obtain a new
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uniformed concentration. Ultimately, the number of outlets solutions will be determined by the
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stages number and starting solutions number [48,49].
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In this study, we applied a tree network microfluidic device for dose-dependent testing of CDs
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effect on various properties of a unicellular eukaryotic model organism, yeast Pichia pastoris.
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We synthesized blue emitting CDs through a simple, safe, and inexpensive method previously
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reported [50], and characterized them using transmission electron microscopy (TEM), dynamic
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light scattering (DLS), and spectrofluorometry. We optimized the geometry of the cell
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microchamber, integrated with a tree-shaped microchannels network, to decrease potential
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effects of shear stress on budding cells [41,51]. Using this device, we measured the proliferation
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rate and morphology of yeast cells in the presence of different concentrations of CDs, and
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binding of CDs to the cell surface. This study demonstrated the potential of the microfluidic
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model for high-throughput nanomaterial biocompatibility assays with the ability of dynamic
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sampling to overcome limitations of conventional methods. In addition, the large surface-area-to-
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volume ratios and the low flow shear stress in microchambers lead to the microenvironmental
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homogeneity. These unique features enable us to find out about the toxicity of new
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nanomaterials more precisely.
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Material and Methods
2.1. Chemicals
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Anhydrous citric acid, sodium hydroxide, yeast extract, soy peptone, D-glucose, agar, quinine
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sulfate, sulfuric acid, and phosphate buffered saline (PBS) were purchased from Merck. 2′,7′
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dichlorodihydrofluorescein diacetate (DCFH-DA), was obtained from Sigma-Aldrich (GmbH
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Munich, Germany). The chemicals were all analytically pure and used as received. Milli–Q
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water was used to dilute samples to desired concentrations for experiments. SU-8 photoresist and
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polydimethylsiloxane (PDMS) were obtained from MicroChem and Dow corning, respectively.
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2.2. Synthesis and characterization of CDs
CDs were prepared using a citric acid pyrolysis method following our previous report [43].
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Briefly, 1 gr of anhydrous citric acid was heated to 160°C for 50 min and added to an NaOH
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aqueous solution (0.5 M) under continuous stirring. The sample solution was neutralized to pH
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of 7.0 with NaOH, and the stock solution of CDs was stored at 4°C until use. Optical properties
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of the CDs solution were determined using ultraviolet–visible (UV–vis) spectroscopy
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(LAMBDA 950 UV/Vis/NIR Spectrophotometer, PerkinElmer, USA). Photoluminescence (PL)
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and photoluminescence excitation (PLE) spectra were obtained using a spectrophotometer
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(Varian Cary Eclipse Fluorescence Spectrophotometer, Agilent, USA). Quantum yield (QY) of
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prepared CDs was measured using a quinine sulfate standard solution (quinine sulfate dissolved
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in 0.05 M solution of H2SO4). The particle size distribution of CDs was determined using
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dynamic light scattering (DLS) (Nanophox, Sympatec GmbH, Germany). Transmission electron
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microscopy (TEM) (Zeiss – EM10C, Germany) was performed to analyze the morphology of
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CDs.
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2.3. Microfluidic device fabrication Standard photolithography was used to pattern the concentration gradient generator (CGG)
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design on a 20 µm-thick SU-8 2025 photoresist (MicroChem Corporation). The master mold was
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cast with a 10:1 mixture of PDMS:curing agent (Dow Corning Corp., USA) [52]. After
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degassing of the PDMS, it was cured at 90°C for 30 min in an oven. The cured PDMS containing
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the design was peeled off from the master mold. The inlet and outlet reservoirs were punched at
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the ends of the microchannels using a biopsy punch of 1.25 mm diameter. The PDMS layer was
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bonded to a clean glass substrate using oxygen plasma [53].
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Fig.1 shows the design of the planar microfluidic device with two modules: a gradient-generating
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network (H1) and cell culture chamber module (H2), which their lengths are 14 and 10 mm,
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respectively. The gradient generator, which is a modified tree-shape network, consisted of six
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sinusoidal serpentine mixing stages. The length of L2 and L3 in the sinusoidal mixers are 380 and
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1300 µm respectively. Using two inlet ports and six gradient generating stages resulted in eight
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linear concentrations at the outlet ports. Each culture chamber received an equal ratio mixture of
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the cell culture medium, which entered from the inlet port below the chambers, and the solution
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from the gradient module outlets. The width and the length (L4) of rectangular cell chamber are
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480 and 650 µm, respectively.
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Fig 1. (a) The schematic shows the microfluidic channel network to generate linear
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concentrations of the test solution and the cell culture chambers, (b) mixing unit in the first stage,
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(c-e) Y-junction and the horizontal mixing unit in the cell culture chambers, and (f) the
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microfluidic chip with food coloring dyes added for visualization.
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To evaluate gradient generation in the CGG, stock solution of CDs and distilled water were
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infused through the two inlets, leading to eight linear concentrations of CDs solutions. From each
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outlet, 200 µL of the discharging solution was collected and the fluorescence intensity of the
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solution was recorded at excitation and emission wavelengths of 360 nm and 460 nm,
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respectively. The concentration of CDs of each sample was estimated based on a standard curve
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and compared with simulation results.
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2.4. Yeast cell culture and interactions with CDs using well-plate assay
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To determine the inhibition of yeast cell growth by CDs, Pichia pastoris X33 wild type was
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grown on YPD agar plates with 1% (w/v) yeast extract, 2% (w/v) peptone, 2% (w/v) dextrose,
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and 2% (w/v) agar at 30°C [53]. After 16 h of incubation, a colony was removed and added to
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sterilize YPD broth medium, and incubated at 30°C and 200 rpm under aerobic conditions. Yeast
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growth was determined through measuring the optical density at 600 nm (OD600). Linear
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concentrations of CDs solutions were prepared in a concentration range produced by the 6
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microfluidic gradient generator. Yeast cell samples with an OD600 of 0.1 were treated with CDs
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solutions at 30°C for 16 h. Finally, OD600 of the samples was measured.
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2.5. Microfluidic device operation Fabricated microfluidic devices were sterilized using collimated high power mercury light for 1
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h. Just before use, the devices were placed in a vacuum chamber to prevent air bubbles formation
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in the sinusoidal serpentine channels. All solutions were degassed prior to use. CDs solution
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were prepared by mixing 2 ml of CDs stock solution and 2 ml of 2X fresh YPD broth medium. A
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CDs gradient was established using the YPD medium and the solutions supplied continuously at
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5 µl/min from the two inlets. The YPD medium with P. pastoris were continuously infused into
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the microfluidic device from the third inlet at 10 µl/min (Fig.1 (a)). The microbial growth was
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imaged inside the microchambers using an inverted light microscope (Olympus, Japan).
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2.6. Fluorescent binding curve measurement
From the yeast grown using the above protocol, 500 µL of yeast culture medium at OD600 = 0.1
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was added to 10 ml of 2X fresh YPD broth medium. Different concentrations of CDs (from 5
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mg/ml to 25 mg/ml) in PBS (pH 7.4) were prepared and sterilized by UV radiation for 1 h before
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use. From each CDs solution, 10 ml was added into the yeast culture medium tubes. The
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yeast/CDs suspensions were kept at 30°C for 3 h while slowly shaking. After incubation, the
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yeast cells were centrifuged for 5 min at 5000 rpm and washed twice with sterilized PBS to
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remove unbound CDs. The cell pellet was collected and resuspended in 3 mL of PBS buffer
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under gentle vortex. The emission intensity of cell-treated CDs was recorded with
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spectrofluorometer.
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2.7. Measuring intracellular ROS
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The intracellular reactive oxygen species (ROS) was determined using 2',7'-dichlorofluorescin
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diacetate (DCFH-DA). The yeast cells were treated with different concentrations of CDs at 30°C
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for 16 h. in the next step, cells were gently homogenized in 20 ml of the extraction buffer and
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centrifuged. The supernatant was used for measuring ROS formation and protein content. To
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evaluate ROS production of the cells, 10 µl of DCFH-DA stock solution and 162 µl assay buffer
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were added to 50 µl of samples and incubated at 37 °C for 15 min. DCFH-DA deacetylated and
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converted to DCFH by cellular esterase. Then, cytosolic ROS oxidized this compound to 2',7'-
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dichlorofluorescein (DCF). Finally, the changes in emission were detected by 96-well microplate 7
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fluorometer every 1 min up to 60 min at 488 nm excitation and 525 nm emission [54].
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Furthermore, protein content of the samples was investigated using Bradford reagent.
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2.8. Statistical analysis At least three independent experiments were carried out for each condition. Data were presented
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as mean ± SEM. One-way ANOVA and Tukey’s multi-comparison tests were carried out to
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evaluate statistical differences. The p-value of 0.5 was considered significant [55].
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3.
Results and Discussion
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3.1. Characterization of CDs
Fig 2(a) shows the OD, photoluminescence (PL), and photoluminescence excitation (PLE) of the
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synthesized CDs. The inset illustrates the solution of CDs under visible light and UV radiation.
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The peak wavelengths for excitation and emission spectra were at 360 nm and 460 nm,
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respectively. Measurement of the PL spectra in a wide range of wavelengths showed that the
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excitation and emission wavelengths were independent (Fig 2(b)). DLS measurements showed a
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mean diameter of 3
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distribution of CDs (Fig 2(d)).
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0.4 nm for the CDs (Fig 2(c)). The TEM image showed a uniform size
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Fig 2. CDs characterization: (a) OD, PL, and PLE of CDs (inset: a solution of CDs under visible light and UV radiation), (b) emission of CDs at different excitation wavelengths, (c) DLS diagram, and (d) TEM image of prepared CDs.
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3.2. Simulation of mixing efficiency and shear stress in the microfluidic device
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The performance mixing units in CGG was quantified by calculating the variance of the mixture
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concentration in a cross section of the mixing channel perpendicular to the flow direction using:
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In Eqs 1-3,
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average color intensity, and
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efficiency [53]. Fig 3(a) shows that the concentration of CDs at each outlet of the gradient
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generator module is uniform and different from other outlets in a 0-100 µl/min range of injection
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flow rates. Fig 3(b) shows the mixing efficiency at the end point of gradient generator module.
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The mixing efficiency decreased by increase in the flow rate due to reduced time of diffusion,
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but remained as high as ~95-97% in the second to seventh channels This demonstrates the
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effectiveness of the tree network design for mixing of solutions in microchannels.
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denotes normalized color intensity,
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is the maximum standard deviation at the inlet. M is the mixing
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Fluid shear stress in the microchannel can disturb the budding process in the yeast cell and cause
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the cell morphology variation [41,51]. In this regard, the chamber module of the microfluidic
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device was designed to confine the cells to a no-flow condition and avoid shear stress on yeast
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cells. In this design, the closure of the cell chamber causes the maximum amount of fluid to flow
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through the main channels and does not perfuse into the chamber due to the convection transport,
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which provides a condition to isolate cell proliferation chamber form bulk fluid flow. According
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to Fig 3 (c), the flow velocity of 400 µm/s in the microchannels decreased to approximately zero
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in cell chambers. owing to a positive correlation between velocity and shear stress, a static
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growth condition is formed in microchamber to facilitate suitable condition for budding yeast
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cells. In this situation, the exchange between the rectangular cell chamber is supported mainly by
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diffusive transport of nutrients into the chambers, which is enough for the refreshment of the
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yeast cell microenvironment [56].
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Fig 3. Simulation of flow in the microfluidic device: (a) Outlet concentration is shown over a
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wide range of injection flow rates, (b) mixing efficiency at the end point of gradient generator
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module, (c) fluid velocity in cell chambers and their nearby microchannels. The side color bar
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shows the velocity range.
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3.3. Yeast cell culture and interactions with CDs using well-plate assay To measure the effect of CDs concentration on the yeast cells proliferation, cells were exposed to
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a linear concentration of CDs (0 to 25 mg/ml) and the growth inhibitory effect of CDs was
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determined using OD measurements (Fig 4). Measurements showed no significant cell growth
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inhibition at concentrations of CDs lower than and equal to 7.7 mg/ml. CDs at concentrations
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higher than 7.7 mg/ml reduced cell proliferation dose-dependently (p < 0.01). The largest
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decrease in the yeast cell proliferation occurred at ∼25 mg/ml concentration of CDs at which cell
proliferation was 60±5% of the negative control sample (no treatment).
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Fig 4. Calculating yeast cell number, based on proliferation assay using a conventional 96-well plate method and after 16 h of incubation with different concentrations of CDs. Data are shown as mean ± standard error of three different experiments (n = 3). * indicates significant difference from the control (no treatment) at p < 0.01.
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bacteria [31,57]. Our result establishes CDs toxicity to yeast cells and demonstrates their
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significantly lower toxicity than graphene oxide nanomaterials that were toxic to yeast cells at
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concentrations higher than 0.5 mg/ml [58]. Additionally, the CDs toxicity is significantly lower
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than QDs that exhibited marked toxicity to yeast cells at concentrations as low as 17.07 nM [59].
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The toxicity was potentially because yeast cells internalize QDs of 4.1 nm to 5.8 nm, suggesting
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that care must be taken for the design and development of aqueous QDs for biological
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applications. Low toxicity of CDs even at high concentrations makes them promising materials
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for biological applications.
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Recent studies have shown that CDs exhibit cytotoxicity toward a variety of human cells and
3.4. Microfluidic device efficiency
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The performance of the CGG was evaluated using computational fluid dynamics (CFD)
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simulations prior to experiments with CDs. A series of solutions with different concentrations of
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CDs were formed at the CGG and samples were collected (Fig 5(a)). The measured fluorescence
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intensity of the samples is shown in Fig 5(b). The concentration of collected samples was 12
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quantified using a standard curve. Results were in close agreement with the computational
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simulation simulations (inset in Fig 5(b)), indicating the reliability of experimental approach to
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generate gradients of aqueous solutions.
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Fig 5. (a) Solutions were collected from outlets using tips under visible light and UV radiation, (b) fluorescence intensity profiles of collected samples are shown. Inset shows comparison between simulation and experimental results.
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High-throughput measurements of yeast replicative lifespan in the CGG
Next, we studied the growth rate and morphology of yeast cells under different conditions using
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the microfluidic device. Light micrographs of cell culture chambers in 0 mg/ml to 25 mg/ml
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concentrations of CDs after 5 h of incubation are shown in Fig 6(a). The morphology of yeast
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cells significantly changed at larger concentrations of CDs (Fig (6(b)). While at low
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concentrations there were more aged mother cells and proliferative cells, there were more
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Schmoo cells and stationary phase cells at higher CDs concentrations. We used image processing
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and analysis in ImageJ to calculate the number of yeast cells in each chamber. The results are
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shown in Fig 6(c). Increasing the CDs concentration dose-dependently decreased the number of
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yeast cells. Decrease in cell number was fairly linear and at the largest CDs concentration of 25
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mg/ml, there was ~94% fewer cells than in control condition. In contrast to results from the
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microfluidic device, there were ~60% viable cells at the 25 mg/ml concentration of CDs with
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well plate method which require further studies to investigate the reasons underlying this
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difference.
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Fig 6. (a) Light micrographs of cell chambers in different CDs concentrations from 0 mg/ml to 25 mg/ml (numbered 1 to 8). Scale bar is 10 µm. (b) Comparison of the yeast cell shape and cell size in each chamber treated with different CDs concentrations (2X magnified). (c) Calculated yeast cell number after 5 h of incubation with different CDs concentrations. Data are shown as mean ± standard error from three different experiments (n = 3). Significant difference from control was defined at p < 0.01.
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To elucidate interactions of yeast cells with CDs, we quantitatively studied binding of CDs to the
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surface of the cells. Fig 7 shows the CDs intensity emission at 460 nm. Increasing the CDs
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concentration increased the emitted light intensity, indicating binding of CDs to the surface of
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yeast cells. CDs binding to the surface of yeast cells may induce toxicity [60]. Additionally, the
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ability of CDs to stimulate production of intracellular reactive oxygen species (ROS) beyond the
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capacity of cells to neutralize them may also be responsible for the growth inhibition of CDs at
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higher concentrations [3,60,61].
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Fig 7. Characterization of florescent CDs binding to Pichia pastoris. The curve illustrates the
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relative levels of fluorescence emission (excitation at 360 nm) induced by increasing
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concentrations of the CDs in the yeast cells suspension. Data are shown as mean ± standard error
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from three different experiments (n = 3). Significant difference from control was defined at ** p
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< 0.001 and *** p< 0.0001.
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3.6. Measuring intracellular ROS
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Administration of CDs in all concentrations showed considerable increment in cytosolic ROS
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level. At 15 and 25 mg/ ml of CDs, fulfilling increase of ROS was detected compared to the
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control group (P<0.001). As demonstrated, low concentration of CDs has also caused a
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noticeable change in ROS level of the cells (P<0.05).
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Fig 8. Effect of different CDs concentrations on intracellular reactive oxygen species (ROS) of
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yeast cells. Data are shown as mean ± standard error from three different experiments (n = 3). *
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and ** indicate significant differences from the control (no treatment) at p < 0.01 and p < 0.001,
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respectively.
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4. Conclusions We presented a microfluidic device to generate a network of gradients of carbon dots (CDs) and
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enable high-throughput testing of CDs effect on the proliferation of budding yeast cells
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maintained in integrated cell chambers. We used the gradient generator module to form eight
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linear concentrations of CDs in the 0–25 mg/ml range and evaluated the response of the yeast
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cells. Increasing the CDs concentration dose-dependently decreased the number of yeast cells.
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While 60% cell proliferation was measured with well plate method at 25 mg/ml of CDs, the
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same concentration resulted in ~6% proliferative cells in the microfluidic device and
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significantly altered morphology of the yeast cells. Our measurements showed that interactions
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of CDs with the yeast cell surface increases approximately linearly with increase in the CDs
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concentrations. This potentially inhibits the growth of yeast cells through stimulation of cells to
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produce ROS at toxic levels. This study demonstrated the potential of the microfluidic model for
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high-throughput nanomaterial biocompatibility assays with the ability of dynamic sampling to
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overcome limitations of conventional methods.
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19 Conflicts of interest
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There are no conflicts to declare
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Acknowledgements The authors are grateful to those who supported them especially Iranian Cognitive Science and
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Technologies Council.
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Highlights:
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We compared the effect of Carbon dots (CDs) on yeast growth rate in microfluidics and well-plate assay. We employed the microfluidic concentration gradient generator to produce linear concentration of CDs for nanotoxicity assessment to yeast cells. Our results showed that CDs are bound to the surface of the yeast cell.
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S0003-2670(18)30576-2
DOI:
10.1016/j.aca.2018.05.005
Reference:
ACA 235941
To appear in:
Analytica Chimica Acta
Received Date: 12 January 2018 Revised Date:
13 April 2018
Accepted Date: 1 May 2018
Please cite this article as: Z. Bagheri, H. Ehtesabi, Z. Hallaji, N. Aminoroaya, H. Tavana, E. Behroodi, M. Rahimifard, M. Abdollahi, H. Latifi, On-Chip Analysis of Carbon Dots Effect on Yeast Replicative Lifespan, Analytica Chimica Acta (2018), doi: 10.1016/j.aca.2018.05.005. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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On-Chip Analysis of Carbon Dots Effect on Yeast Replicative Lifespan
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Zeinab Bagheri1, Hamide Ehtesabi1, Zahra Hallaji2, Neda Aminoroaya3, Hossein Tavana4, Ebrahim Behroodi3, Mahban Rahimifard5, Mohammad Abdollahi5, Hamid Latifi3*
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Abstract Carbon dots (CDs) are promising nanomaterials for biosensing, bioimaging, and drug delivery
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due to their large surface area, excellent optical properties, and thermal and chemical stability.
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However, biosafety of CDs is still understudied, and there is not a generally accepted standard to
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evaluate the toxicity of CDs. We present a gradient network generator microfluidic device for
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dose-dependent testing of toxicity of CDs to a unicellular eukaryotic model organism, yeast
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Pichia pastoris. We fully characterized the microfluidic model and compare its performance
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with a conventional method. The gradient generator increased the contact area between the
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mixing species and enabled a high-throughput testing of CDs in a wide range of concentrations
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in cell chambers. Real time monitoring of yeast cell proliferation in the presence of CDs showed
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dose-dependent growth inhibition and various budding cell shape profiles. Comparing the result
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of microfluidic platform and conventional method revealed statistically significant differences in
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the proliferation rate of the cells between the two platforms. To understand the toxicity
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mechanism, we studied binding of CDs to P. pastoris and found increasing interactions of CDs
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with the cell surface at CDs larger concentrations. This study demonstrated the utility of the
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gradient generator microfluidic device as a convenient tool for toxicity assessment of
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nanomaterials at a cellular level.
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Faculty of Life Sciences and Biotechnology, Shahid Beheshti University G.C., Velenjak, Tehran, Iran. Protein Research Center, Shahid Beheshti University G.C., Velenjak, Tehran, Iran. Laser & Plasma Research Institute, Shahid Beheshti University G.C., Velenjak, Tehran, Iran. Department of Biomedical Engineering, The University of Akron, Akron, OH 44236, USA. The Institute of Pharmaceutical Sciences (TIPS), and Department of Toxicology and Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
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* Corresponding author. Email: [email protected] (Hamid Latifi)
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Keywords: Carbon Dots; Yeast Pichia pastoris; Microfluidics; Toxicity; Biosafety; Growth
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Inhibition
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1. Introduction Carbon dots (CDs) are a member of the carbon nanomaterials family. They are smaller than 100
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nm in size and 10 layers thick[1]. A large surface area, excellent thermal and physicochemical
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stability, and unique optical properties make CDs attractive for biological applications[2–10].
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The preparation methods of CDs are relatively simple, low cost, and easily scalable. These
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include
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electrochemical techniques [16], exfoliation-based techniques [17–19], and several others [9,20–
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23]. Although carbon is not an intrinsically toxic substance, the specific material and structural
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configuration of carbon nanomaterials may cause risks to human health. Several studies have
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evaluated toxicity of CDs in recent years [2,24–34]. However, relative to the rapid developments
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in applications of CDs, ecotoxicology and environmental hazard studies have fallen behind.
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Currently, little is known about toxic effects of CDs. Establishing new testing methods and
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technologies is expected to expedite toxicity analysis of CDs. New insights into potential
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hazardous effects of CDs in biological applications will lead to the development and design of
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safer materials.
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pyrolysis [11], oxidation techniques [12,13], hydrothermal techniques [14,15] ,
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The current approach of in vitro toxicity analysis is based on well-plate assays that require time-
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consuming manual handling of samples or costly automated robotic systems [35]. Microfluidic
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platforms are well suited for toxicity assessments due to their compatibility with high-throughput
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testing using small volumes of reagents, capability for parallel analyses, and ease of device
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fabrication. Several studies have used microfluidics for nanomaterials toxicity tests. Mahto et al.
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developed an integrated multi-compartment microfluidic device to evaluate toxicity of
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CdSe/ZnSe quantum dots (QDs) to fibroblast cells. Exposure of fibroblasts to QDs resulted in
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the production of reactive oxygen species and differences in cell morphology between static and
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flow conditions [36]. Kim et al. investigated cytotoxicity of mesoporous silica nanoparticles to
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endothelial cells lined on the surface of microchannels. Under flow and shear stress, the
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nanoparticles generated significant cytotoxicity [37]. Liu et al. developed a microfluidic device
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containing an embedded biocompatible scaffold to form hepatocyte spheroids and evaluate
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hepatotoxicity of silver nanoparticles. Treatment with the nanoparticles induced significantly
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greater membrane damage to the cells in the microfluidic device than in a conventional tissue
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culture plate [38].
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Unicellular eukaryotic model organisms are widely used to study toxicity of chemicals because
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of similarities of their biochemical structure and cellular organization to those of higher
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organisms. Yeast cells have been used in microfluidic devices to study events such as aging,
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neurotoxicity of α-synuclein protein aggregation, cell segmentation and growth, cell trapping and
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biochemical analysis [25,39–42].
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Concentration Gradient Generator (CGG) microfluidic devices offer a convenient platform to
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evaluate the toxicity of CDs to yeast cells. Due to the vast application of microfluidic gradient
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generators, various models have been introduced so far. In pressure driven models such as
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universal gradient generator, serial diluter, and tree-shaped gradient generator, mixing is
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performed through different mechanisms like parallel lamination, serial lamination and chaotic
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advection [43,44]. Some other models apply the active actuators such as micro pneumatic
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actuator, surface acoustic waves, and piezoelectric transducer to mix the solutions [45–47]. Tree-
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shaped gradient generator (also called Christmas tree) which was first proposed by the
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Whitesides group [48], is one of the most widely used models due to its simplicity in design,
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good uniformity, and robustness [49]. In Christmas tree model, two or more different solutions
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are infused into the inlets and a linear concentration gradient will be obtained at the outlets.
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Actually, the fluid streams of initial solutions are repeatedly split at the bifurcation points and
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then recombined and mixed in the mixer channels of next stages. In the serpentine mixer
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channel, molecular diffusion occurs across the interface between the laminar streams. Mixer
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channel length, solute diffusion coefficient and flow rate are the important variables to guarantee
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enough diffusive time for complete mixing at the end of each mixer branch to obtain a new
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uniformed concentration. Ultimately, the number of outlets solutions will be determined by the
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stages number and starting solutions number [48,49].
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In this study, we applied a tree network microfluidic device for dose-dependent testing of CDs
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effect on various properties of a unicellular eukaryotic model organism, yeast Pichia pastoris.
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We synthesized blue emitting CDs through a simple, safe, and inexpensive method previously
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reported [50], and characterized them using transmission electron microscopy (TEM), dynamic
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light scattering (DLS), and spectrofluorometry. We optimized the geometry of the cell
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microchamber, integrated with a tree-shaped microchannels network, to decrease potential
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effects of shear stress on budding cells [41,51]. Using this device, we measured the proliferation
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rate and morphology of yeast cells in the presence of different concentrations of CDs, and
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binding of CDs to the cell surface. This study demonstrated the potential of the microfluidic
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model for high-throughput nanomaterial biocompatibility assays with the ability of dynamic
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sampling to overcome limitations of conventional methods. In addition, the large surface-area-to-
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volume ratios and the low flow shear stress in microchambers lead to the microenvironmental
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homogeneity. These unique features enable us to find out about the toxicity of new
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nanomaterials more precisely.
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2.
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Material and Methods
2.1. Chemicals
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Anhydrous citric acid, sodium hydroxide, yeast extract, soy peptone, D-glucose, agar, quinine
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sulfate, sulfuric acid, and phosphate buffered saline (PBS) were purchased from Merck. 2′,7′
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dichlorodihydrofluorescein diacetate (DCFH-DA), was obtained from Sigma-Aldrich (GmbH
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Munich, Germany). The chemicals were all analytically pure and used as received. Milli–Q
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water was used to dilute samples to desired concentrations for experiments. SU-8 photoresist and
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polydimethylsiloxane (PDMS) were obtained from MicroChem and Dow corning, respectively.
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2.2. Synthesis and characterization of CDs
CDs were prepared using a citric acid pyrolysis method following our previous report [43].
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Briefly, 1 gr of anhydrous citric acid was heated to 160°C for 50 min and added to an NaOH
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aqueous solution (0.5 M) under continuous stirring. The sample solution was neutralized to pH
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of 7.0 with NaOH, and the stock solution of CDs was stored at 4°C until use. Optical properties
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of the CDs solution were determined using ultraviolet–visible (UV–vis) spectroscopy
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(LAMBDA 950 UV/Vis/NIR Spectrophotometer, PerkinElmer, USA). Photoluminescence (PL)
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and photoluminescence excitation (PLE) spectra were obtained using a spectrophotometer
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(Varian Cary Eclipse Fluorescence Spectrophotometer, Agilent, USA). Quantum yield (QY) of
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prepared CDs was measured using a quinine sulfate standard solution (quinine sulfate dissolved
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in 0.05 M solution of H2SO4). The particle size distribution of CDs was determined using
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dynamic light scattering (DLS) (Nanophox, Sympatec GmbH, Germany). Transmission electron
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microscopy (TEM) (Zeiss – EM10C, Germany) was performed to analyze the morphology of
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CDs.
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2.3. Microfluidic device fabrication Standard photolithography was used to pattern the concentration gradient generator (CGG)
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design on a 20 µm-thick SU-8 2025 photoresist (MicroChem Corporation). The master mold was
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cast with a 10:1 mixture of PDMS:curing agent (Dow Corning Corp., USA) [52]. After
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degassing of the PDMS, it was cured at 90°C for 30 min in an oven. The cured PDMS containing
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the design was peeled off from the master mold. The inlet and outlet reservoirs were punched at
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the ends of the microchannels using a biopsy punch of 1.25 mm diameter. The PDMS layer was
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bonded to a clean glass substrate using oxygen plasma [53].
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Fig.1 shows the design of the planar microfluidic device with two modules: a gradient-generating
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network (H1) and cell culture chamber module (H2), which their lengths are 14 and 10 mm,
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respectively. The gradient generator, which is a modified tree-shape network, consisted of six
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sinusoidal serpentine mixing stages. The length of L2 and L3 in the sinusoidal mixers are 380 and
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1300 µm respectively. Using two inlet ports and six gradient generating stages resulted in eight
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linear concentrations at the outlet ports. Each culture chamber received an equal ratio mixture of
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the cell culture medium, which entered from the inlet port below the chambers, and the solution
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from the gradient module outlets. The width and the length (L4) of rectangular cell chamber are
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480 and 650 µm, respectively.
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Fig 1. (a) The schematic shows the microfluidic channel network to generate linear
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concentrations of the test solution and the cell culture chambers, (b) mixing unit in the first stage,
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(c-e) Y-junction and the horizontal mixing unit in the cell culture chambers, and (f) the
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microfluidic chip with food coloring dyes added for visualization.
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To evaluate gradient generation in the CGG, stock solution of CDs and distilled water were
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infused through the two inlets, leading to eight linear concentrations of CDs solutions. From each
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outlet, 200 µL of the discharging solution was collected and the fluorescence intensity of the
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solution was recorded at excitation and emission wavelengths of 360 nm and 460 nm,
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respectively. The concentration of CDs of each sample was estimated based on a standard curve
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and compared with simulation results.
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2.4. Yeast cell culture and interactions with CDs using well-plate assay
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To determine the inhibition of yeast cell growth by CDs, Pichia pastoris X33 wild type was
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grown on YPD agar plates with 1% (w/v) yeast extract, 2% (w/v) peptone, 2% (w/v) dextrose,
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and 2% (w/v) agar at 30°C [53]. After 16 h of incubation, a colony was removed and added to
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sterilize YPD broth medium, and incubated at 30°C and 200 rpm under aerobic conditions. Yeast
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growth was determined through measuring the optical density at 600 nm (OD600). Linear
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concentrations of CDs solutions were prepared in a concentration range produced by the 6
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microfluidic gradient generator. Yeast cell samples with an OD600 of 0.1 were treated with CDs
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solutions at 30°C for 16 h. Finally, OD600 of the samples was measured.
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2.5. Microfluidic device operation Fabricated microfluidic devices were sterilized using collimated high power mercury light for 1
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h. Just before use, the devices were placed in a vacuum chamber to prevent air bubbles formation
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in the sinusoidal serpentine channels. All solutions were degassed prior to use. CDs solution
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were prepared by mixing 2 ml of CDs stock solution and 2 ml of 2X fresh YPD broth medium. A
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CDs gradient was established using the YPD medium and the solutions supplied continuously at
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5 µl/min from the two inlets. The YPD medium with P. pastoris were continuously infused into
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the microfluidic device from the third inlet at 10 µl/min (Fig.1 (a)). The microbial growth was
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imaged inside the microchambers using an inverted light microscope (Olympus, Japan).
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2.6. Fluorescent binding curve measurement
From the yeast grown using the above protocol, 500 µL of yeast culture medium at OD600 = 0.1
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was added to 10 ml of 2X fresh YPD broth medium. Different concentrations of CDs (from 5
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mg/ml to 25 mg/ml) in PBS (pH 7.4) were prepared and sterilized by UV radiation for 1 h before
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use. From each CDs solution, 10 ml was added into the yeast culture medium tubes. The
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yeast/CDs suspensions were kept at 30°C for 3 h while slowly shaking. After incubation, the
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yeast cells were centrifuged for 5 min at 5000 rpm and washed twice with sterilized PBS to
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remove unbound CDs. The cell pellet was collected and resuspended in 3 mL of PBS buffer
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under gentle vortex. The emission intensity of cell-treated CDs was recorded with
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spectrofluorometer.
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The intracellular reactive oxygen species (ROS) was determined using 2',7'-dichlorofluorescin
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diacetate (DCFH-DA). The yeast cells were treated with different concentrations of CDs at 30°C
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for 16 h. in the next step, cells were gently homogenized in 20 ml of the extraction buffer and
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centrifuged. The supernatant was used for measuring ROS formation and protein content. To
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evaluate ROS production of the cells, 10 µl of DCFH-DA stock solution and 162 µl assay buffer
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were added to 50 µl of samples and incubated at 37 °C for 15 min. DCFH-DA deacetylated and
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converted to DCFH by cellular esterase. Then, cytosolic ROS oxidized this compound to 2',7'-
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dichlorofluorescein (DCF). Finally, the changes in emission were detected by 96-well microplate 7
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fluorometer every 1 min up to 60 min at 488 nm excitation and 525 nm emission [54].
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Furthermore, protein content of the samples was investigated using Bradford reagent.
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2.8. Statistical analysis At least three independent experiments were carried out for each condition. Data were presented
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as mean ± SEM. One-way ANOVA and Tukey’s multi-comparison tests were carried out to
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evaluate statistical differences. The p-value of 0.5 was considered significant [55].
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3.
Results and Discussion
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3.1. Characterization of CDs
Fig 2(a) shows the OD, photoluminescence (PL), and photoluminescence excitation (PLE) of the
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synthesized CDs. The inset illustrates the solution of CDs under visible light and UV radiation.
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The peak wavelengths for excitation and emission spectra were at 360 nm and 460 nm,
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respectively. Measurement of the PL spectra in a wide range of wavelengths showed that the
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excitation and emission wavelengths were independent (Fig 2(b)). DLS measurements showed a
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mean diameter of 3
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distribution of CDs (Fig 2(d)).
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0.4 nm for the CDs (Fig 2(c)). The TEM image showed a uniform size
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Fig 2. CDs characterization: (a) OD, PL, and PLE of CDs (inset: a solution of CDs under visible light and UV radiation), (b) emission of CDs at different excitation wavelengths, (c) DLS diagram, and (d) TEM image of prepared CDs.
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3.2. Simulation of mixing efficiency and shear stress in the microfluidic device
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The performance mixing units in CGG was quantified by calculating the variance of the mixture
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concentration in a cross section of the mixing channel perpendicular to the flow direction using:
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In Eqs 1-3,
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average color intensity, and
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efficiency [53]. Fig 3(a) shows that the concentration of CDs at each outlet of the gradient
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generator module is uniform and different from other outlets in a 0-100 µl/min range of injection
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flow rates. Fig 3(b) shows the mixing efficiency at the end point of gradient generator module.
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The mixing efficiency decreased by increase in the flow rate due to reduced time of diffusion,
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but remained as high as ~95-97% in the second to seventh channels This demonstrates the
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effectiveness of the tree network design for mixing of solutions in microchannels.
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denotes normalized color intensity,
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is the maximum standard deviation at the inlet. M is the mixing
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Fluid shear stress in the microchannel can disturb the budding process in the yeast cell and cause
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the cell morphology variation [41,51]. In this regard, the chamber module of the microfluidic
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device was designed to confine the cells to a no-flow condition and avoid shear stress on yeast
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cells. In this design, the closure of the cell chamber causes the maximum amount of fluid to flow
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through the main channels and does not perfuse into the chamber due to the convection transport,
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which provides a condition to isolate cell proliferation chamber form bulk fluid flow. According
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to Fig 3 (c), the flow velocity of 400 µm/s in the microchannels decreased to approximately zero
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in cell chambers. owing to a positive correlation between velocity and shear stress, a static
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growth condition is formed in microchamber to facilitate suitable condition for budding yeast
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cells. In this situation, the exchange between the rectangular cell chamber is supported mainly by
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diffusive transport of nutrients into the chambers, which is enough for the refreshment of the
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yeast cell microenvironment [56].
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Fig 3. Simulation of flow in the microfluidic device: (a) Outlet concentration is shown over a
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wide range of injection flow rates, (b) mixing efficiency at the end point of gradient generator
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module, (c) fluid velocity in cell chambers and their nearby microchannels. The side color bar
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shows the velocity range.
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3.3. Yeast cell culture and interactions with CDs using well-plate assay To measure the effect of CDs concentration on the yeast cells proliferation, cells were exposed to
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a linear concentration of CDs (0 to 25 mg/ml) and the growth inhibitory effect of CDs was
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determined using OD measurements (Fig 4). Measurements showed no significant cell growth
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inhibition at concentrations of CDs lower than and equal to 7.7 mg/ml. CDs at concentrations
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higher than 7.7 mg/ml reduced cell proliferation dose-dependently (p < 0.01). The largest
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decrease in the yeast cell proliferation occurred at ∼25 mg/ml concentration of CDs at which cell
proliferation was 60±5% of the negative control sample (no treatment).
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Fig 4. Calculating yeast cell number, based on proliferation assay using a conventional 96-well plate method and after 16 h of incubation with different concentrations of CDs. Data are shown as mean ± standard error of three different experiments (n = 3). * indicates significant difference from the control (no treatment) at p < 0.01.
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bacteria [31,57]. Our result establishes CDs toxicity to yeast cells and demonstrates their
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significantly lower toxicity than graphene oxide nanomaterials that were toxic to yeast cells at
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concentrations higher than 0.5 mg/ml [58]. Additionally, the CDs toxicity is significantly lower
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than QDs that exhibited marked toxicity to yeast cells at concentrations as low as 17.07 nM [59].
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The toxicity was potentially because yeast cells internalize QDs of 4.1 nm to 5.8 nm, suggesting
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that care must be taken for the design and development of aqueous QDs for biological
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applications. Low toxicity of CDs even at high concentrations makes them promising materials
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for biological applications.
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Recent studies have shown that CDs exhibit cytotoxicity toward a variety of human cells and
3.4. Microfluidic device efficiency
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The performance of the CGG was evaluated using computational fluid dynamics (CFD)
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simulations prior to experiments with CDs. A series of solutions with different concentrations of
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CDs were formed at the CGG and samples were collected (Fig 5(a)). The measured fluorescence
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intensity of the samples is shown in Fig 5(b). The concentration of collected samples was 12
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quantified using a standard curve. Results were in close agreement with the computational
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simulation simulations (inset in Fig 5(b)), indicating the reliability of experimental approach to
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generate gradients of aqueous solutions.
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Fig 5. (a) Solutions were collected from outlets using tips under visible light and UV radiation, (b) fluorescence intensity profiles of collected samples are shown. Inset shows comparison between simulation and experimental results.
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High-throughput measurements of yeast replicative lifespan in the CGG
Next, we studied the growth rate and morphology of yeast cells under different conditions using
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the microfluidic device. Light micrographs of cell culture chambers in 0 mg/ml to 25 mg/ml
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concentrations of CDs after 5 h of incubation are shown in Fig 6(a). The morphology of yeast
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cells significantly changed at larger concentrations of CDs (Fig (6(b)). While at low
14
concentrations there were more aged mother cells and proliferative cells, there were more
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Schmoo cells and stationary phase cells at higher CDs concentrations. We used image processing
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and analysis in ImageJ to calculate the number of yeast cells in each chamber. The results are
17
shown in Fig 6(c). Increasing the CDs concentration dose-dependently decreased the number of
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yeast cells. Decrease in cell number was fairly linear and at the largest CDs concentration of 25
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mg/ml, there was ~94% fewer cells than in control condition. In contrast to results from the
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microfluidic device, there were ~60% viable cells at the 25 mg/ml concentration of CDs with
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well plate method which require further studies to investigate the reasons underlying this
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difference.
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Fig 6. (a) Light micrographs of cell chambers in different CDs concentrations from 0 mg/ml to 25 mg/ml (numbered 1 to 8). Scale bar is 10 µm. (b) Comparison of the yeast cell shape and cell size in each chamber treated with different CDs concentrations (2X magnified). (c) Calculated yeast cell number after 5 h of incubation with different CDs concentrations. Data are shown as mean ± standard error from three different experiments (n = 3). Significant difference from control was defined at p < 0.01.
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To elucidate interactions of yeast cells with CDs, we quantitatively studied binding of CDs to the
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surface of the cells. Fig 7 shows the CDs intensity emission at 460 nm. Increasing the CDs
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concentration increased the emitted light intensity, indicating binding of CDs to the surface of
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yeast cells. CDs binding to the surface of yeast cells may induce toxicity [60]. Additionally, the
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ability of CDs to stimulate production of intracellular reactive oxygen species (ROS) beyond the
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capacity of cells to neutralize them may also be responsible for the growth inhibition of CDs at
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higher concentrations [3,60,61].
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Fig 7. Characterization of florescent CDs binding to Pichia pastoris. The curve illustrates the
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relative levels of fluorescence emission (excitation at 360 nm) induced by increasing
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concentrations of the CDs in the yeast cells suspension. Data are shown as mean ± standard error
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from three different experiments (n = 3). Significant difference from control was defined at ** p
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< 0.001 and *** p< 0.0001.
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3.6. Measuring intracellular ROS
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Administration of CDs in all concentrations showed considerable increment in cytosolic ROS
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level. At 15 and 25 mg/ ml of CDs, fulfilling increase of ROS was detected compared to the
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control group (P<0.001). As demonstrated, low concentration of CDs has also caused a
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noticeable change in ROS level of the cells (P<0.05).
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Fig 8. Effect of different CDs concentrations on intracellular reactive oxygen species (ROS) of
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yeast cells. Data are shown as mean ± standard error from three different experiments (n = 3). *
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and ** indicate significant differences from the control (no treatment) at p < 0.01 and p < 0.001,
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respectively.
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4. Conclusions We presented a microfluidic device to generate a network of gradients of carbon dots (CDs) and
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enable high-throughput testing of CDs effect on the proliferation of budding yeast cells
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maintained in integrated cell chambers. We used the gradient generator module to form eight
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linear concentrations of CDs in the 0–25 mg/ml range and evaluated the response of the yeast
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cells. Increasing the CDs concentration dose-dependently decreased the number of yeast cells.
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While 60% cell proliferation was measured with well plate method at 25 mg/ml of CDs, the
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same concentration resulted in ~6% proliferative cells in the microfluidic device and
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significantly altered morphology of the yeast cells. Our measurements showed that interactions
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of CDs with the yeast cell surface increases approximately linearly with increase in the CDs
15
concentrations. This potentially inhibits the growth of yeast cells through stimulation of cells to
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produce ROS at toxic levels. This study demonstrated the potential of the microfluidic model for
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high-throughput nanomaterial biocompatibility assays with the ability of dynamic sampling to
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overcome limitations of conventional methods.
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There are no conflicts to declare
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Acknowledgements The authors are grateful to those who supported them especially Iranian Cognitive Science and
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Technologies Council.
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We compared the effect of Carbon dots (CDs) on yeast growth rate in microfluidics and well-plate assay. We employed the microfluidic concentration gradient generator to produce linear concentration of CDs for nanotoxicity assessment to yeast cells. Our results showed that CDs are bound to the surface of the yeast cell.
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