Archive for the ‘Deirdre Meldrum’s Lab’ Category

Project 3 Team Members

Monday, November 7th, 2011

Project Lead: Deirdre R. Meldrum

  • Deirdre R. Meldrum is ASU Senior Scientist, Director of the Biosignature Initiative and Director of the Center for Biosignature Discovery Automation (CBDA) in the Biodesign Institute and Professor of Electrical Engineering in the School of Electrical, Computer, and Energy Engineering. She is also Director and Principal Investigator of the NIH Center of Excellence in Genomic Sciences: Microscale Life Sciences Center (MLSC). Her research interests include probing heterogeneity by live single cell analyses, nuclear organization in cancer, microscale systems for biological applications, robotics and control systems for applications to human health and disease and the oceans. She served on the National Advisory Council for Human Genome Research. More Info

  • Team Members

  • Roger H. Johnson is a Research Scientist and Laboratory Manager in the Center for Biosignatures Discovery Automation in ASU’s Biodesign Institute. Roger is responsible for overall management of daily research activities in the Center, and leads the cell CT research. He has over twenty years’ experience in 3D micro CT, and is an expert in CT scanner design and construction, image reconstruction algorithms, and 3D image processing and analysis. Roger is co-inventor of the cell CT and has seven patents including two on x-ray and two on optical microtomography.

  • Laimonas Kelbauskas is an Assistant Research Professor in the Center for Biosignatures Discovery Automation. He has an PhD in physics and his major research interests are in methods for early cancer detection, the role of intercellular interactions and cell-to-cell variability in pre-neoplastic to neoplastic progression, and changes in gene transcription levels in individual cells in carcinogenesis.

  • Brain Ashcroft received his PhD in physics from ASU for his work on fast DNA sequencing with an AFM/rotaxane system. He worked as a postdoctoral scholar at Leiden university for three years where he explored growth disorders with nanoindention. In addition, he worked on a microfluidics system to do cancer detection and monitoring from blood plasma, and studied the formation of scars in heart tissue. He is currently a postdoctoral scholar at the Center for Biosignatures Discovery Automation. His research is focused on software development for high quality 3D reconstructions in absorption and fluorescent modalities with fixed and live cells.

  • Thai Tran received his Ph.D. in molecular biology from Purdue University and was trained a as a postdoctoral fellow with Dr. Hallgeir Rui at the Kimmel Cancer Center, Thomas Jefferson University. Dr. Tran has background in molecular and cellular biology of cancer. His research focus is to investigate the molecular functions that govern cancer cell development and progression.

  • Jiangxin Wang received a Ph.D. in molecular genetics. Currently he is an assistant research scientist for the Center for Biosignatures Discovery Automation at the Biodesign Institute at Arizona State University. His research interests include single cell transcriptomics, live single cell analyses, and gene signatures as prognostic markers in diseases.

  • Kimberly J. Bussey is an Assistant Professor in the Clinical Translational Research Division of the Translational Genomics Research Institute (TGen), Co-Director of the Adrenocortical Carcinoma Research Program at TGen, and an Adjunct Associate Research Scientist with the Center for Biosignatures Discovery Automation at the Biodesign Institute at Arizona State University. Her research interests lie in exploiting intra-tumor heterogeneity in cancer for treatment. Dr. Bussey has a background in medical and molecular genetics, rare tumors, cancer cytogenetics, and applied bioinformatics.

  • Vivek Nandakumar is a graduate research associate at the Center for Biosignatures Discovery Automation in the biodesign institute. His research is centered around quantitative three-dimensional morphometric biosignatures for early cancer detection using the Cell-CT.

  • Kathryn Hernandez is an undergraduate research assistant at the Center for Biosignatures Discovery Automation. She is a senior majoring in Biological Sciences at Arizona State University and has extensive prior work experience in clinical and reference laboratories. She works on single cell imaging with Cell-CT.

  • Miranda Slaydon is an undergraduate majoring in Geology. She assists with sample preparation and imaging for Cell-CT

  • Stephanie Helland is an undergraduate student worker at CBDA. She is a sophomore at ASU pursuing bachelor of science degrees in Biochemistry and Molecular Biosciences. She assists with sample preparation and imaging for Cell-CT

  • Beatriz Rodolpho is a visiting scholar at the Center for Biosignatures Discovery Automation in the Biodesign Institute. She is currently pursuing her MS degree at Universidade Nova de Lisboa in Portugal. Her research includes Cell-CT imaging and development of metrics to assess quality of 3D reconstruction algorithms.

Meldrum’s Publications

Thursday, February 17th, 2011

Publications 2013

A Physical Sciences Network Characterization of Non-tumorigenic and Metastatic Cells. Sci Rep. 2013
A physical sciences network characterization of non-tumorigenic and metastatic cells.

Publications 2012

‘Isotropic 3D Nuclear Morphometry of normal, fibrocystic and malignant breast epithelial cells reveals novel structural alterations’ with Vivek Nandakumar, Laimonas Kelbauskas, Kathryn Hernandez, Kelly Lintecum, Patti Senechal, Kimberly Bussey, Roger Johnson and Deirdre Meldrum, PLoS ONE (2012).
Isotropic 3D Nuclear Morphometry of normal, fibrocystic and malignant breast epithelial cells reveals novel structural alterations PDF

Publications 2011

Vivek Nandakumar, Deirdre Meldrum and Roger Johnson publish “Quantitative Characterization of Preneoplastic Progression Using Single-Cell Computed Tomography and Three-Dimensional Karyometry”
Quantitative characterization of preneoplastic progression using single-cell computed tomography and three-dimensional karyometry.

A hallmark of cancer is that the cell nucleus changes shape and size as the cell transforms from healthy to premalignant to malignant, and cancer researchers suspect that an accurate method of quantifying those changes could serve as an early diagnostic test for cancer. Now, a team of investigators at Arizona State University have given cancer researchers an imaging tool that should enable them to determine if that suspicion is correct.

Deirdre Meldrum and Roger Johnson, both members of the Arizona State University Physical Sciences-Oncology Center (PS-OC), led the team that used high-resolution optical absorption tomographic imaging and mathematical reconstruction to create detailed three-dimensional images of the cell nucleus. They then took those images and used an automated analytical technique they developed to compute 41 quantitative descriptions of a cell’s nuclear structure. The investigators also developed mathematical tools to quantify the spatial distribution of DNA within the cell nucleus from the reconstructed optical images.

Using these techniques, the Arizona PS-OC team compared the three-dimensional architecture of malignant, premalignant, and malignant esophageal epithelial cells and identified quantitative differences in cell shape among the three cell types. Moreover, the researchers were able to clearly distinguish between the three different types of cells using those quantitative measures. The researchers published the results of their study in the journal Cytometry Part A.

This work, which is detailed in a paper titled, “Quantitative Characterization of Preneoplastic Progression Using Single-Cell Computed Tomography and Three-Dimensional Karyometry,” was supported by the National Cancer Institute’s Physical Sciences-Oncology Centers program that aims to foster the development of innovative ideas and new fields of study based on knowledge of the biological and physical laws and principles that define both normal and tumor systems. An abstract of this paper is available at the journal’s Web site.


Automated Selection and Placement of Single Cells Using Vision-Based Feedback Control (pdf)

Tuesday, April 6th, 2010

Automated Selection and Placement of Single Cells Using Vision-Based Feedback Control

We present a robotic manipulation system for automated selection and transfer of individual living cells to analysis locations. We begin with a commonly used cell transfer technique using glass capillary micropipettes to aspirate and release living cells suspended in liquid growth media. Using vision-based feedback and closed-loop process control, two individual three-axis robotic stages position the micropipette tip in proximity to the cell of interest. The cell is aspirated and the tip is moved to a target location where the cell is dispensed. Computer vision is used to monitor and inspect the success of the dispensing process. In our initial application, the target cell destination is a microwell etched in a fused silica substrate. The system offers a robust and flexible technology for cell selection and manipulation. Applications for this technology include embryonic stem cells transfer, blastomere biopsy, cell patterning, and cell surgery.

Characterization of deep wet etching of fused silica glass for single cell and optical sensor deposition (pdf)

Tuesday, April 6th, 2010

Characterization of deep wet etching of fused silica glass for single cell and optical sensor deposition

The development of a high-throughput single-cell metabolic rate monitoring system relies onthe use of transparent substrate material for a single cell-trapping platform. The high opticaltransparency, high chemical resistance, improved surface quality and compatibility with thesilicon micromachining process of fused silica make it very attractive and desirable for thisapplication. In this paper, we report the results from the development and characterization of ahydrofluoric acid (HF) based deep wet-etch process on fused silica. The pin holes andnotching defects of various single-coated masking layers during the etching are characterizedand the most suitable masking materials are identified for different etch depths. Thedependence of the average etch rate and surface roughness on the etch depth, impurityconcentration and HF composition are also examined. The resulting undercut from the deepHF etch using various masking materials is also investigated. The developed and characterizedprocess techniques have been successfully implemented in the fabrication of micro-well arraysfor single cell trapping and sensor deposition. Up to 60 μm deep micro-wells have beenetched in a fused silica substrate with over 90{236bd5e292587b885399ce1fe93b84c86ca4f34851d3c4bf06f3f0da35a3ccbb} process yield and repeatability. To ourknowledge, such etch depth has never been achieved in a fused silica substrate by using anon-diluted HF etchant and a single-coated masking layer at room temperature.

A New Approach for Measuring Single-Cell Oxygen Consumption Rates (pdf)

Tuesday, April 6th, 2010

A New Approach for Measuring Single-Cell Oxygen Consumption Rates

A novel system that has enabled the measurement of single-cell oxygen consumption rates is presented. The experimental apparatus includes a temperature controlled environmental chamber, an array of microwells etched in glass, and a lid actuator used to seal cells in the microwells. Each microwell contains an oxygen sensitive platinum phosphor sensor used to monitor the cellular metabolic rates. Custom automation software controls the digital image data collection for oxygen sensor measurements, which are analyzed using an image-processing program to yield the oxygen concentration within each microwell versus time. Two proof-of-concept experiments produced oxygen consumption rate measurements for A549 human epithelial lung cancer cells of 5.39 and 5.27 fmol/min/cell, closely matching published oxygen consumption rates for bulk A549 populations.

Life-on-a-chip (pdf)

Tuesday, April 6th, 2010


Mechanistic studies of cellular processes are usually carried out with large populations of cells. However, parameters that are measured as averages of large populations can be misleading. For instance, an apparently linear response to a signal could, in fact, reflect an increasing number of cells in the population that have switched from ‘off’ to ‘on’, rather than a graded increase in response by all the cells. At present, the study of single cells is challenging, but new technologies mean it might soon be a reality.

Poster: “Single Cell Tomography for Early Cancer Detection” Vivek Nandakumar, Laimonas Kelbauskas, Roger Johnson, Deirdre Meldrum

Wednesday, March 17th, 2010

Vivek Nandakumar, a graduate student working withDeirdre Meldrum, presented a poster of his work to the Arizona Microscopy and Microanalysis Society  (AIMS) annual meeting in March 2010.

viveknandakumar aims2010 PSOC (jpg)

Poster(Powerpoint): Single Cell Tomography for Early Cancer Detection

Poster (JPG):  Single Cell Tomography for Early Cancer Detection