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Lopez, B. A.

Publications and source records attributed to Lopez, B. A..

2 recordsLinked to original sources

Aquavert: Imaging and Microfluidics for Vertical Swimming of Microorganisms

Investigating aquatic microorganisms swimming and feeding behaviors under well-controlled conditions is of great interest across multiple disciplines. Thus, broader access to resources that enable these investigations is desirable. Given the organisms microscopic dimensions, an ideal system should combine microscopy to visualize and fluidics to control and modulate their environments. We report an integrated device (Aquavert) that combines DIY microscopy and microfluidics for biomechanical investigations of marine microorganisms, emphasizing vertical swimming. The DIY microscope was developed for modularity, and imaging chambers were secured in vertical orientations (either in portrait or landscape mode). Fluid channels were used to introduce flow and fluid segmentation while remaining upright. Fluid segmentation established two distinct environments (e.g., with and without algae) in neighboring regions inside a chamber. System application with multiple marine larvae (sand dollars, sea urchins, and starfish) and introduction of unicellular algae were demonstrated. Finally, the devices capabilities were extended to fluorescence imaging to visualize tracer beads. The role of gravity is often ignored in conventional plate or microfluidic experiments. Beyond the current application, Aquavert enables investigations of the behavior and physiology of microorganisms where the role of gravity is critical.

biophysics↗

Identification of transcriptional regulators using a combined disease module identification and prize-collecting Steiner tree approach

Transcription factors play important roles in maintaining normal biological function, and their dys-regulation can lead to the development of diseases. Identifying candidate transcription factors involved in disease pathogenesis is thus an important task for deriving mechanistic insights from gene expression data. We developed Transcriptional Regulator Identification using Prize-collecting Steiner trees (TRIPS), a workflow for identifying candidate transcriptional regulators from case-control expression data. In the first step, TRIPS combines the results of differential expression analysis with a disease module identification step to retrieve perturbed subnetworks comprising an expanded gene list. TRIPS then solves a prize-collecting Steiner tree problem on a gene regulatory network, thereby identifying candidate transcriptional modules and transcription factors. We compare TRIPS to relevant methods using publicly available disease datasets and show that the proposed workflow can recover known disease-associated transcription factors with high precision. Network perturbation analyses demonstrate the reliability of TRIPS results. We further evaluate TRIPS on Alzheimers disease, diabetic kidney disease, and prostate cancer single-cell omics datasets. Overall, TRIPS is a useful approach for prioritizing transcriptional mechanisms for further downstream analyses.

bioinformatics↗