Bachelor of Science, University Of Sydney (2004)
Doctor of Philosophy, Carnegie Mellon University (2012)
Yunzhi Peter Yang, Postdoctoral Faculty Sponsor
Project 1: Deer Antler Biology
Deer antlers are bone tissues that grow at astounding rates. I am studying various genes that are involved in rapid antler growth and differentiation.
Project 2:Biomaterials for Tendon Repair
Rotator cuff tears among the most common cause of shoulder pain with over 200,000 surgical procedures performed annually. I am developing a novel biomaterial to mimic the mechanical and biochemical properties of the native bone-tendon interface to aid in tendon repair.
Success with bone morphogenetic protein-2 (BMP-2) has been widely reported in the osseous reconstruction of large calvarial defects. These efforts have required enormous doses of BMP-2 and are not sufficiently refined to facilitate the detail-oriented repair required for intricate craniofacial structures. We have previously shown that inkjet-based bioprinting technologies allow for precisely customized low-dose protein patterns to induce spatially regulated osteogenesis. Here, we investigate the importance of direct contact between bioprinted BMP-2 and the dura mater (a source of osteoprogenitors) in mediating calvarial healing.Five-millimeter osseous defects were trephinated in mouse parietal bones (N=8). Circular acellular dermal matrix (ADM) implants were prepared such that 1 semicircle of 1 face per implant was printed with BMP-2 bio-ink. These implants were then placed ink-toward (N=3) or ink-away (N=5) from the underlying dura mater. After 4 weeks, osteogenesis was assessed in each of the 4 possible positions (BMP-2-printed area toward dura, BMP-2-printed area away from dura, unprinted area toward dura, and unprinted area away from dura) by faxitron.The BMP-2-printed portion of the ADM generated bone covering an average of 66.5% of its surface area when it was face-down (printed surface directly abutting dura mater). By comparison, the BMP-2-printed portion of the ADM generated bone covering an average of only 21.3% of its surface area when it was face-up (printed surface away from dura). Similarly, the unprinted portion of the ADM generated an average of only 18.6% osseous coverage when face-down and 18.4% when face-up.We have previously shown that inkjet-based bioprinting has the potential to significantly enhance the role of regenerative therapies in craniofacial surgery. This technology affords the precise control of osteogenesis necessary to reconstruct this region's intricate anatomical architecture. In the present study, we demonstrate that direct apposition of BMP-2-printed ADM to a source of osteoprogenitor cells (in this case dura mater) is necessary for bio-ink-directed osteogenesis to occur. These results have important implications for the design of more complex bioprinted osseous structures.
View details for DOI 10.1097/SAP.0b013e31824cfe64
View details for Web of Science ID 000308866500038
View details for PubMedID 22972553
Polyploidization can precede the development of aneuploidy in cancer. Polyploidization in megakaryocytes (Mks), in contrast, is a highly controlled developmental process critical for efficient platelet production via unknown mechanisms. Using primary cells, we demonstrate that the guanine exchange factors GEF-H1 and ECT2, which are often overexpressed in cancer and are essential for RhoA activation during cytokinesis, must be downregulated for Mk polyploidization. The first (2N-4N) endomitotic cycle requires GEF-H1 downregulation, whereas subsequent cycles (>4N) require ECT2 downregulation. Exogenous expression of both GEF-H1 and ECT2 prevents endomitosis, resulting in proliferation of 2N Mks. Furthermore, we have shown that the mechanism by which polyploidization is prevented in Mks lacking Mkl1, which is mutated in megakaryocytic leukemia, is via elevated GEF-H1 expression; shRNA-mediated GEF-H1 knockdown alone rescues this ploidy defect. These mechanistic insights enhance our understanding of normal versus malignant megakaryocytopoiesis, as well as aberrant mitosis in aneuploid cancers.
View details for DOI 10.1016/j.devcel.2011.12.019
View details for Web of Science ID 000301701600012
View details for PubMedID 22387001
The detection of apoptosis, or programmed cell death, is important to understand the underlying mechanism of cell development. At present, apoptosis detection resorts to fluorescence or colorimetric assays, which may affect cell behavior and thus not allow long-term monitoring of intact cells. In this work, we present an image analysis method to detect apoptosis in time-lapse phase-contrast microscopy, which is nondestructive imaging. The method first detects candidates for apoptotic cells based on the optical principle of phase-contrast microscopy in connection with the properties of apoptotic cells. The temporal behavior of each candidate is then examined in its neighboring frames in order to determine if the candidate is indeed an apoptotic cell. When applied to three C2C12 myoblastic stem cell populations, which contain more than 1000 apoptosis, the method achieved around 90% accuracy in terms of average precision and recall.
View details for PubMedID 23285568
View details for DOI 10.1109/ISBI.2012.6235566
Current cell culture practices are dependent upon human operators and remain laborious and highly subjective, resulting in large variations and inconsistent outcomes, especially when using visual assessments of cell confluency to determine the appropriate time to subculture cells. Although efforts to automate cell culture with robotic systems are underway, the majority of such systems still require human intervention to determine when to subculture. Thus, it is necessary to accurately and objectively determine the appropriate time for cell passaging. Optimal stem cell culturing that maintains cell pluripotency while maximizing cell yields will be especially important for efficient, cost-effective stem cell-based therapies. Toward this goal we developed a real-time computer vision-based system that monitors the degree of cell confluency with a precision of 0.791±0.031 and recall of 0.559±0.043. The system consists of an automated phase-contrast time-lapse microscope and a server. Multiple dishes are sequentially imaged and the data is uploaded to the server that performs computer vision processing, predicts when cells will exceed a pre-defined threshold for optimal cell confluency, and provides a Web-based interface for remote cell culture monitoring. Human operators are also notified via text messaging and e-mail 4 hours prior to reaching this threshold and immediately upon reaching this threshold. This system was successfully used to direct the expansion of a paradigm stem cell population, C2C12 cells. Computer-directed and human-directed control subcultures required 3 serial cultures to achieve the theoretical target cell yield of 50 million C2C12 cells and showed no difference for myogenic and osteogenic differentiation. This automated vision-based system has potential as a tool toward adaptive real-time control of subculturing, cell culture optimization and quality assurance/quality control, and it could be integrated with current and developing robotic cell cultures systems to achieve complete automation.
View details for DOI 10.1371/journal.pone.0027672
View details for Web of Science ID 000297555400080
View details for PubMedID 22110715
The capability to spatially control stem cell orientation and differentiation simultaneously using a combination of geometric cues that mimic structural aspects of native extracellular matrix (ECM) and biochemical cues such as ECM-bound growth factors (GFs) is important for understanding the organization and function of musculoskeletal tissues. Herein, oriented sub-micron fibers, which are morphologically similar to musculoskeletal ECM, were spatially patterned with GFs using an inkjet-based bioprinter to create geometric and biochemical cues that direct musculoskeletal cell alignment and differentiation in vitro in registration with fiber orientation and printed patterns, respectively. Sub-micron polystyrene fibers (diameter ~ 655 nm) were fabricated using a Spinneret-based Tunable Engineered Parameters (STEP) technique and coated with serum or fibrin. The fibers were subsequently patterned with tendon-promoting fibroblast growth factor-2 (FGF-2) or bone-promoting bone morphogenetic protein-2 (BMP-2) prior to seeding with mouse C2C12 myoblasts or C3H10T1/2 mesenchymal fibroblasts. Unprinted regions of STEP fibers showed myocyte differentiation while printed FGF-2 and BMP-2 patterns promoted tenocyte and osteoblast fates, respectively, and inhibited myocyte differentiation. Additionally, cells aligned along the fiber length. Functionalizing oriented sub-micron fibers with printed GFs provides instructive cues to spatially control cell fate and alignment to mimic native tissue organization and may have applications in regenerative medicine.
View details for DOI 10.1016/j.biomaterials.2011.07.025
View details for Web of Science ID 000295241200007
View details for PubMedID 21820736
The capability to engineer microenvironmental cues to direct a stem cell population toward multiple fates, simultaneously, in spatially defined regions is important for understanding the maintenance and repair of multi-tissue units. We have previously developed an inkjet-based bioprinter to create patterns of solid-phase growth factors (GFs) immobilized to an extracellular matrix (ECM) substrate, and applied this approach to drive muscle-derived stem cells toward osteoblasts 'on-pattern' and myocytes 'off-pattern' simultaneously. Here this technology is extended to spatially control osteoblast, tenocyte and myocyte differentiation simultaneously. Utilizing immunofluorescence staining to identify tendon-promoting GFs, fibroblast growth factor-2 (FGF-2) was shown to upregulate the tendon marker Scleraxis (Scx) in C3H10T1/2 mesenchymal fibroblasts, C2C12 myoblasts and primary muscle-derived stem cells, while downregulating the myofibroblast marker α-smooth muscle actin (α-SMA). Quantitative PCR studies indicated that FGF-2 may direct stem cells toward a tendon fate via the Ets family members of transcription factors such as pea3 and erm. Neighboring patterns of FGF-2 and bone morphogenetic protein-2 (BMP-2) printed onto a single fibrin-coated coverslip upregulated Scx and the osteoblast marker ALP, respectively, while non-printed regions showed spontaneous myotube differentiation. This work illustrates spatial control of multi-phenotype differentiation and may have potential in the regeneration of multi-tissue units.
View details for DOI 10.1016/j.biomaterials.2011.01.036
View details for Web of Science ID 000288884800008
View details for PubMedID 21316755
Due to the enormous potential and impact that stem cells may have on regenerative medicine, there has been a rapidly growing interest for tools to analyze and characterize the behaviors of these cells in vitro in an automated and high throughput fashion. Among these behaviors, mitosis, or cell division, is important since stem cells proliferate and renew themselves through mitosis. However, current automated systems for measuring cell proliferation often require destructive or sacrificial methods of cell manipulation such as cell lysis or in vitro staining. In this paper, we propose an effective approach for automated mitosis detection using phase-contrast time-lapse microscopy, which is a nondestructive imaging modality, thereby allowing continuous monitoring of cells in culture. In our approach, we present a probabilistic model for event detection, which can simultaneously 1) identify spatio-temporal patch sequences that contain a mitotic event and 2) localize a birth event, defined as the time and location at which cell division is completed and two daughter cells are born. Our approach significantly outperforms previous approaches in terms of both detection accuracy and computational efficiency, when applied to multipotent C3H10T1/2 mesenchymal and C2C12 myoblastic stem cell populations.
View details for DOI 10.1109/TMI.2010.2089384
View details for Web of Science ID 000287862300005
View details for PubMedID 21356609
View details for Web of Science ID 000305885000032
Stem cell expansion culture aims to generate sufficient number of clinical-grade cells for cell-based therapies. One challenge for ex vivo expansion is to decide the appropriate time to perform subculture. Traditionally, this decision has been reliant on human estimation of cell confluency and predicting when confluency will approach a desired threshold. However, the use of human operators results in highly subjective decision-making and is prone to inter- and intra-operator variability. Using a real-time cell image analysis system, we propose a data-driven approach to model the cell growth process and predict the cell confluency levels, signaling times to subculture. This approach has great potential as a tool for adaptive real-time control of subculturing, and it can be integrated with robotic cell culture systems to achieve complete automation.
View details for Web of Science ID 000298810002323
View details for PubMedID 22255112