Office of Undergraduate Research

Permanent URI for this communityhttp://hdl.handle.net/1903/20157

Emphasizing equitable and inclusive access to research opportunities, the University of Maryland's Office of Undergraduate Research (OUR) empowers undergraduates and faculty to engage and succeed in inquiry, creative activity, and scholarship. This collection includes materials shared by undergraduate researchers during OUR events. It also encompasses materials from Undergraduate Research Day 2020, Undergraduate Research Day 2021, and Undergraduate Research Day 2022, which were organized by the Maryland Center for Undergraduate Research.

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Subject: search.filters.subject.Cell Biology

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    Novel Computational Methods for the Comparison of Leishmania Genomes and Transcriptomes
    (2024-04) Klimes, Daniel; Belew, Trey; El-Sayed, Najib
    Leishmania is a genus of protozoan parasites and the causative agent of Leishmaniasis. Twenty-one infectious species have been identified, with many previously being investigated by DNA and RNA-sequencing. However, significant genetic variation has prevented the comparison of this data across Leishmania species. Gene orthology grouping fails to compare over 70% of Leishmania genes’ expression across multiple species because of this variation. Here, we describe a novel method to reliably compare the genomes and transcriptomes of multiple Leishmania. This method produces a hybrid genome from the genetic sequence of any Leishmania species, while containing the rich sequence annotations of the L. major reference genome. In a demonstrative analysis, our approach allowed the comparison of 87% of genes in L. major against 5 other Leishmania species. Significant genetic variation was found to prevent comparison of many virulence-implicated genes, including surface antigens (e.g. amastins), cysteine proteases, and HSP-83. Within genes that could be compared, parasite transcriptomes segregated primarily by developmental stage (promastigote and amastigote). Transcriptomes secondarily separated by species. Genes upregulated in infection across all Leishmania were identified and included surface amastins, methyltransferases, and an apoptosis inhibition factor. Downregulated genes showed significantly greater sequence conservation than upregulated genes and comprised paraflagellar, flagellar, and HSP-70 proteins among others. The transcriptome differences between the clinical manifestations of leishmaniasis were additionally characterized. Taken together, these results provide much needed insight into the shared Leishmania pathway of infection and survival.
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    Automated Workflow for Advanced Single Cell and Bacterium Tracking in Host-Pathogen Interactions
    (2024) Augenstreich, Jacques; Poddar, Anushka; Belew, Ashton T.; El-Sayed, Najib; Briken, Volker; Briken, Volker
    In the study of intracellular pathogens like Mycobacterium tuberculosis, time-lapse microscopy is a valuable tool for understanding dynamic cellular processes involved in host cell defense. Quantification of signals at localized compartments within the cell and around bacteria can provide even deeper insight into interactions between bacteria and host cell organelles. However, existing quantitative analysis at a single-bacterial level remains limited and dependent on manual tracking methods. We developed a near-fully automated workflow that performs unbiased, high-throughput cell segmentation and quantitative tracking of both single cells and single bacteria/phagosomes within multi-channel, z-stack, time-lapse confocal microscopy videos. We took advantage of the PyImageJ library to bring Fiji functionality into a Python environment and combined deep-learning-based segmentation from Cellpose with tracking algorithms from Trackmate and visualization within ImageJ. Following both cell and bacteria tracking, our workflow provides a versatile toolkit of functions for measuring relevant signal parameters at the single-cell level (such as velocity or bacterial burden) and at the single-bacteria level (for assessment of phagosome maturation). Ultimately, our workflow’s capabilities in both single-cell and single-bacteria quantification can help decipher the virulence factors of pathogens and pave the way for the development of innovative therapeutic approaches. The customizable nature of the methods extends the applications of the workflow far beyond the field of mycobacteria and presents opportunities for advancement in host-pathogen interaction research in a variety of systems.