2022 Suddath Award Winners

2022 SUDDATH AWARDS
The F.L. "Bud" Suddath Memorial Award was established by Bud Suddath's family, friends, and colleagues in memory of his contributions to Georgia Tech. The award is given annually to graduate students at Georgia Tech who have demonstrated significant bio-research accomplishments while conducting biological or biochemical research at the molecular or cellular level.

• Yan Zhang - 1st Place - Ph.D. Candidate, Chemical and Biomolecular Engineering, Georgia Tech - Mark Styczynski, Advisor - "New Interfaces for Cell-free Biosensors to Enable Multiplexed Analyte Detection and Analyte Quantification at Point of Care" – Yan will present her work on the opening day of the 2022 Suddath Symposium, January 13, 2022 - Register here
  • Yan’s research group creates low-cost, low-resource diagnostics for the developing world. They use synthetic biology to engineer biological systems to sense biomarkers and then produce visual readouts that do not require complex or expensive equipment (or ideally even electricity) to be interpreted. A recent emphasis has been in cell-free systems, which are bacterial extracts that allow for execution of essentially arbitrary genetic programs via in vitro transcription and translation in field-friendly conditions. Yan has also written two book chapters (in press), was second author on a project on the systems biology of our cell-free systems (published at ACS Synthetic Biology), was a middle author in a collaboration published in PLOS Biology, was an NSF GRFP honorable mention, and led contribution to a COVID diagnostic collaboration with two other Georgia Tech investigators.
• Penghao Xu - 2nd Place - Ph.D. Candidate, Bioinformatics, Georgia Tech – Francesca Storici, Advisor - "Applications of Bioinformatics to Uncover Features and Functions of Ribonucleotides Embedded in Eukaryotic DNA"
  • Penghao developed a heatmap analysis to determine the frequency of the deoxyribonucleotides that surround the rNMPs embedded in genomic DNA all on his own. These dinucleotide or trinucleotide-preference heatmaps have led us to discover a fundamental rule of rNMP incorporation in DNA, namely that the deoxyribonucleotide immediately upstream of an rNMP site is a major determinant for incorporation of the rNMPs by DNA polymerases in specific genomic loci. This finding markedly increased the significance of our work, and it is reflected in the title of our recently published study ‘Ribonucleotide incorporation in yeast genomic DNA shows preference for cytosine and guanosine preceded by deoxyadenosine’ in Nature Communications, 2020. Penghao is co-first author in this large study by Balachander, Gombolay, Yang, Xu et al.The mono- and di-nucleotide heatmap analyses of ribonucleotides embedded in genomic DNA developed by Penghao represent a central part of the recently published manuscript in iScience, in which Penghao applied his heatmap analysis to rNMPs embedded in genomic DNA of the photosynthetic green alga Chlamydomonas reinhardtii. The study is entitled ‘Disproportionate presence of adenosine in mitochondrial and chloroplast DNA of Chlamydomonas reinhardtii’. Penghao is co-second author in this study.
• Shivesh Chaudhary - 3rd Place - Ph.D. Candidate, Chemical and Biomolecular Engineering, Georgia Tech – Hang Lu, Advisor
  • Shivesh’s latest paper describes a method to identify cells by matching data to atlases. This is a very difficult task due to incomplete information present in the data and perturbations (imperfections) with the biological system. Shivesh very cleverly developed a graphical-model framework inspired by natural language processing algorithms to do this task, which has several advantages as the paper laid out. He did a large set of experiments to produce training and test data sets to validate the algorithm and demonstrate the utility of the method. (His data set has already been used by other labs.) He collaborated with a molecular biologist lab to develop a set of reagents to further improve the accuracy of the neuron identity assignments.