Ki-Bum Lee

Design, Synthesis, and Characterization of Graphene–Nanoparticle Hybrid Materials for Bioapplications

Graphene is composed of single-atom thick sheets of sp2 bonded carbon atoms that are arranged in a perfect two-dimensional (2D) honeycomb lattice. Because of this structure, graphene is characterized by a number of unique and exceptional structural, optical, and electronic properties.1 Specifically, these extraordinary properties include, but are not limited to, a high planar surface area that is calculated to be 2630 m2 g−1,2 superior mechanical strength with a Young’s modulus of 1100 GPa,3 unparalleled thermal conductivity (5000 W m−1 K−1),4 remarkable electronic properties (e.g., high carrier mobility [10 000 cm2 V−1 s−1] and capacity),5 and alluring optical characteristics (e.g., high opacity [~97.7%] and the ability to quench fluorescence).6 As such, it should come as no surprise that graphene is currently, without any doubt, the most intensively studied material for a wide range of applications that include electronic, energy, and sensing outlets.1c Moreover, because of these unique chemical and physical properties, graphene and graphene-based nanomaterials have attracted increasing interest, and, arguably, hold the greatest promise for implementation into a wide array of bioapplications.7 In the last several years, numerous studies have utilized graphene in bioapplications ranging from the delivery of chemotherapeutics for the treatment of cancer8 to biosensing applications for a host of medical conditions9 and even for the differentiation and imaging of stem cells.10 While promising and exciting, recent reports have demonstrated that the combination of graphene with nanomaterials such as nanoparticles, thereby forming graphene–nanoparticle hybrid structures, offers a number of additional unique physicochemical properties and functions that are both highly desirable and markedly advantageous for bioapplications when compared to the use of either material alone (Figure 1).11 These graphene–nanoparticle hybrid structures are especially alluring because not only do they display the individual properties of the nanoparticles, which can already possess beneficial optical, electronic, magnetic, and structural properties that are unavailable in bulk materials, and of graphene, but they also exhibit additional advantageous and often synergistic properties that greatly augment their potential for bioapplications. Open in a separate window Figure 1 Graphene nanoparticle hybrids exist in two forms, as graphene–nanoparticle composites and graphene-encapsulated nanoparticles, and can be used for various bioapplications including biosensors, photothermal therapies, stem cell/tissue engineering, drug/gene delivery, and bioimaging. Panel (A) reprinted with permission from ref 110. Copyright 2012 Wiley. Panel (B) reprinted with permission from ref 211. Copyright 2013 Elsevier. Panel (C) reprinted with permission from ref 244. Copyright 2013 Wiley.

GRAPHENE-ENCAPSULATED NANOPARTICLE-BASED BIOSENSOR FOR THE SELECTIVE DETECTION OF BIOMARKERS

Nanomaterials such as silicon nanowires (SiNWs), [ 1 , 2 ] carbon nanotubes (CNTs), [ 3–6 ] and graphene, [ 7,8 ] have gained much attention for use in electrical biosensors due to their nanoscopic and electrical properties. For instance, SiNWs and CNTs can be integrated into fi eld-effect transistors (FETs) to detect small amounts of target biomolecules with high sensitivity and selectivity by measuring electrical disturbances induced by the binding of these biomolecules to the surface of the nanostructure. [ 9,10 ] The detection of biomarker proteins with high sensitivity and selectivity is vital for the early diagnosis of many diseases including cancer and HIV. For this purpose, carbonbased nanomaterials such as CNTs and graphene have attracted signifi cant attention for fabricating highly sensitive FET-based biosensors. [ 6 , 8,9 , 11–15 ] In particular, the use of graphene in FETbased biosensors is becoming more and more appealing not only due to its unique properties, such as higher 2D electrical conductivity, superb mechanical fl exibility, large surface area, and high chemical and thermal stability, but also due to its ability to overcome the limitations of CNTs, such as variations in electrical properties of CNT-based devices and the limited surface area of CNTs. [ 16–24 ] Nevertheless, there have been only a few reports on the development of graphene FET-based biosensors, [ 14 , 25 ] and their potential as biosensors has not been fully explored. It is therefore critical to develop nanoscopic graphenebased biosensors that are simple in device structure, small in size, and allow label-free detection and real-time monitoring of biomarkers, all of which are essential criteria for biosensors. A key challenge in the above requirements is the achievement of both, well-organized 2D or 3D graphene structures, in microscopic and nanoscopic biosensing devices and well-defi ned bioconjugation chemistry on graphene.

Phosphoproteomic Analysis of Human Embryonic Stem Cells

Protein phosphorylation, while critical to cellular behavior, has been undercharacterized in pluripotent cells. Therefore, we performed phosphoproteomic analyses of human embryonic stem cells (hESCs) and their differentiated derivatives. A total of 2546 phosphorylation sites were identified on 1602 phosphoproteins; 389 proteins contained more phosphorylation site identifications in undifferentiated hESCs, whereas 540 contained more such identifications in differentiated derivatives. Phosphoproteins in receptor tyrosine kinase (RTK) signaling pathways were numerous in undifferentiated hESCs. Cellular assays corroborated this observation by showing that multiple RTKs cooperatively supported undifferentiated hESCs. In addition to bFGF, EGFR, VEGFR, and PDGFR activation was critical to the undifferentiated state of hESCs. PDGF-AA complemented a subthreshold bFGF concentration to maintain undifferentiated hESCs. Also consistent with phosphoproteomics, JNK activity participated in maintenance of undifferentiated hESCs. These results support the utility of phosphoproteomic data, provide guidance for investigating protein function in hESCs, and complement transcriptomics/epigenetics for broadening our understanding of hESC fate determination.

Nanotechnology for regenerative medicine: nanomaterials for stem cell imaging

Although stem cells hold great potential for the treatment of many injuries and degenerative diseases, several obstacles must be overcome before their therapeutic application can be realized. These include the development of advanced techniques to understand and control functions of microenvironmental signals and novel methods to track and guide transplanted stem cells. The application of nanotechnology to stem cell biology would be able to address those challenges. This review details the current challenges in regenerative medicine, the current applications of nanoparticles in stem cell biology and further potential of nanotechnology approaches towards regenerative medicine, focusing mainly on magnetic nanoparticle- and quantum dot-based applications in stem cell research.

Selective Inhibition of Human Brain Tumor Cells through Multifunctional Quantum‐Dot‐Based siRNA Delivery

One of the most promising new chemotherapeutic strategies is the RNA interference (RNAi)-based approach, wherein small double-stranded RNA molecules can sequence-specifically inhibit the expression of targeted oncogenes.[1] In principle, this method has high specificity and broad applicability for chemotherapy. For example, the small interfering RNA (siRNA) strategy enables manipulation of key oncogenes that modulate signaling pathways and thereby regulate the behavior of malignant tumor cells. To harness the full potential of this approach, the prime requirements are to deliver the siRNA molecules with high selectivity and efficiency into tumor cells and to monitor both siRNA delivery and the resulting knock-down effects at the single cell level. Although several approaches such as polymer- and nanomaterial-based methods[2] have been attempted, limited success has been achieved for delivering siRNA into the target tumor cells. Moreover, these types of approaches mainly focus on the enhancement of transfection efficiency, knock-down of non-oncogenes (e.g. green fluorescent protein (GFP)), and the use of different nanomaterials such as quantum dots (QDs), iron oxide nanoparticles, and gold nanoparticles.[3,4] Therefore, to narrow the gap between current nanomaterial-based siRNA delivery and chemotherapies, there is a clear need to develop methods for target-oriented delivery of siRNA [5], for further monitoring the effects of siRNA-mediated target gene silencing via molecular imaging probes[4], and for investigating the corresponding up/down regulation of signaling cascades.[6] Perhaps most importantly, to begin the development of the necessary treatment modalities, the nanomaterial-based siRNA delivery strategies must be demonstrated on oncogenes involved in cancer pathogenesis.

Guiding Stem Cell Differentiation into Oligodendrocytes Using Graphene‐Nanofiber Hybrid Scaffolds

Damage to the central nervous system (CNS) from degenerative diseases or traumatic injuries is particularly devastating due the limited regenerative capabilities of the CNS. Among the current approaches, stem cell-based regenerative medicine has shown great promise in achieving significant functional recovery by taking advantage of the self-renewal and differentiation capabilities of stem cells, which include pluripotent stem cells (PSCs), mesenchymal stem cells (MSCs) and neural stem cells (NSCs).[1] However, the low survival rate upon transplantation has been a longstanding barrier for scientists and clinicians to overcome.[2] To this end, numerous types of natural and synthetic biomaterial scaffolds have been developed, the two main classes being hydrogels and nanofibers, in an attempt to mimic the cellular microenvironment, support cellular growth and improve cellular viability.[3] Yet, designing scaffolds with defined properties to selectively guide stem cell differentiation towards a specific neural cell lineage is still an ongoing challenge.

Versatile fluorescence resonance energy transfer-based mesoporous silica nanoparticles for real-time monitoring of drug release.

We describe the development of a versatile fluorescence resonance energy transfer (FRET)-based real-time monitoring system, consisting of (a) coumarin-labeled-cysteine tethered mesoporous silica nanoparticles (MSNs) as the drug carrier, (b) a fluorescein isothiocyanate-β-cyclodextrin (FITC-β-CD) as redox-responsive molecular valve blocking the pores, and (c) a FRET donor-acceptor pair of coumarin and FITC integrated within the pore-unlocking event, thereby allowing for monitoring the release of drugs from the pores in real-time. Under nonreducing conditions, when the disulfide bond is intact, the close proximity between coumarin and FITC on the surface of MSNs results in FRET from coumarin to FITC. However, in the presence of the redox stimuli like glutathione (GSH), the disulfide bond is cleaved which leads to the removal of molecular valve (FITC-β-CD), thus triggering drug release and eliminating FRET. By engineering such a FRET-active donor-acceptor structure within the redox-responsive molecular valve, we can monitor the release of the drugs entrapped within the pores of the MSN nanocarrier, following the change in the FRET signal. We have demonstrated that, any exogenous or endogenous change in the GSH concentration will result in a change in the extent of drug release as well as a concurrent change in the FRET signal, allowing us to extend the applications of our FRET-based MSNs for monitoring the release of any type of drug molecule in real-time.

Axonal alignment and enhanced neuronal differentiation of neural stem cells on graphene-nanoparticle hybrid structures.

Human neural stem cells (hNSCs) cultured on graphene-nanoparticle hybrid structures show a unique behavior wherein the axons from the differentiating hNSCs show enhanced growth and alignment. We show that the axonal alignment is primarily due to the presence of graphene and the underlying nanoparticle monolayer causes enhanced neuronal differentiation of the hNSCs, thus having great implications of these hybrid-nanostructures for neuro-regenerative medicine.

Exocytosis of nanoparticles from cells: Role in cellular retention and toxicity

Over the past decade, nanoparticles (NPs) have been increasingly developed in various biomedical applications such as cell tracking, biosensing, contrast imaging, targeted drug delivery, and tissue engineering. Their versatility in design and function has made them an attractive, alternative choice in many biological and biomedical applications. Cellular responses to NPs, their uptake, and adverse biological effects caused by NPs are rapidly-growing research niches. However, NP excretion and its underlying mechanisms and cell signaling pathways are yet elusive. In this review, we present an overview of how NPs are handled intracellularly and how they are excreted from cells following the uptake. We also discuss how exocytosis of nanomaterials impacts both the therapeutic delivery of nanoscale objects and their nanotoxicology.

A Microfluidic Platform for Systems Pathology: Multiparameter Single-Cell Signaling Measurements of Clinical Brain Tumor Specimens

The clinical practice of oncology is being transformed by molecular diagnostics that will enable predictive and personalized medicine. Current technologies for quantitation of the cancer proteome are either qualitative (e.g., immunohistochemistry) or require large sample sizes (e.g., flow cytometry). Here, we report a microfluidic platform-microfluidic image cytometry (MIC)-capable of quantitative, single-cell proteomic analysis of multiple signaling molecules using only 1,000 to 2,800 cells. Using cultured cell lines, we show simultaneous measurement of four critical signaling proteins (EGFR, PTEN, phospho-Akt, and phospho-S6) within the oncogenic phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway. To show the clinical application of the MIC platform to solid tumors, we analyzed a panel of 19 human brain tumor biopsies, including glioblastomas. Our MIC measurements were validated by clinical immunohistochemistry and confirmed the striking intertumoral and intratumoral heterogeneity characteristic of glioblastoma. To interpret the multiparameter, single-cell MIC measurements, we adapted bioinformatic methods including self-organizing maps that stratify patients into clusters that predict tumor progression and patient survival. Together with bioinformatic analysis, the MIC platform represents a robust, enabling in vitro molecular diagnostic technology for systems pathology analysis and personalized medicine.