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Arguello-Miranda, Orlando

Assitant Professor Plant and Microbial Biology
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Orlando Argüello-Miranda grew up in Costa Rica and engaged in intercultural experiences since a young age, which led him to participate in the world youth parliament (Paris France, 1999), the ITU global submit (Hong Kong, 2005), and to work with environmental and human right organizations such as Humane Society international (Nicaragua, 2006). As a product of these experiences, Orlando decided to pursue a scientific career focused on improving human health or human nutrition through experimental research. After receiving a B.Sc. from the National University of Costa Rica, Orlando moved to Germany to pursue doctoral studies at the Max Planck Institute for Cell Biology and Genetics and the Max Planck Institute of Biochemistry. His doctoral work revealed how E3-ubiquitin-ligase-mediated proteolysis controls cellular decision-making between cell division programs, such as mitosis or meiosis. For his postdoctoral work, Orlando joined the Doncic and Danuser Laboratories at the University of Texas Southwestern Medical Center (UTSW, USA), where he developed single-cell imaging approaches based on data science, spectral microscopy, and microfluidics. In 2020, he was awarded a K99/R00 Pathway to Independence Award (NIGMS) to continue his work on combining data science tools to elucidate new biochemical pathways in single living cells. Orlando is now a new assistant professor in the Plant and Microbial Biology department at North Carolina State University (NCSU, USA) and plans to leverage data science tools to understand cellualr dormancy, with an emphasis on fungal pathogens.

Bioinformatics | Biochemistry | Microbiology | Molecular Biology | Plant Pathology
Country(s) of experience:
Costa Rica | United States
Type(s) of International Experience:

Research Focus:

My laboratory wants to understand how cells divide. We want to discover new biochemical mechanisms that help cells divide when needed. In the same manner, we want to learn how cells stop whenever cell division is too dangerous and could result in irreversible cellular damage. In humans, problems in the control of cell division cause diseases such as cancer and can interfere with wound healing or the maintenance of adult stem cells. In addition, for many bacteria, parasitic organisms, and agricultural pests, the capacity to stop cell division and enter dormant or quiescent states is critical for becoming resistant to antibiotics and pesticides. Thus, understanding how cells activate or stop their machinery for cell division promises to advance both biomedical and agricultural knowledge.

To analyze dividing and non-dividing cells, we use a unique combination of biochemical methods with machine learning approaches. We track individual cells as they enter or exit from cell division using custom-made algorithms for image analysis. The information derived from monitoring single cells is processed using machine learning algorithms to cluster data sets, identify correlations, and infer causality in intracellular biological networks. Machine learning-inspired hypotheses are then tested using biochemical and genetic tools in model organisms such as the yeast Saccharomyces cerevisiae.

Our current projects aim at:

  • Understanding how cells stop their cell cycle machinery and enter an intriguing state called “cellular quiescence”
  • Developing new sensors to track intracellular processes during entry and exit from cell division
  • Engineering experimental setups for observing entire signaling pathways or protein networks in single cells

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