Research
Investigating mechanisms that regulate reproductive fitness in Drosophila
A fundamental requirement for animal reproduction is the development and maintenance of the germline, the set of highly specialized cells responsible for passing on genetic material to the following generation. Recent discoveries have revealed that germline function requires the formation of highly conserved ribonucleoprotein (RNP) granules called germ granules. Germ granules have essential roles in germline differentiation, proliferation, and post-transcriptional gene regulation. In animals such as Drosophila, germ cell specification occurs through the inheritance of germ granules that reside at a specific location within the egg. In humans, where germline fate is induced through signaling interactions, similar germ granules form de novo after germline differentiation. Regardless of their origin, germ granules contain highly conserved components such as mRNA encoding the translational repressor nanos (nos). Evidence supporting the conserved role of germ granules comes from the effect of mutations that eliminate conserved germ granule components in Drosophila, Xenopus, zebrafish, and mouse, which result in the loss of the germline. In humans, mutations in the nos ortholog, NANOS1, are associated with defects in spermatogenesis that result in a lack of germ cells in the testes, while mutations in NANOS3 are linked to premature ovarian failure. Despite the conserved function of germ granules, it is unclear how fertility may be affected by changes in germ granule composition. Elucidating how granule mRNA content affects fertility and the mechanisms that yield germ granule diversity should provide insight into defects such as infertility and sterility. In the Niepielko Lab, we take advantage of the natural variation of fertility found in Drosophila species to investigate the role germ granules have in reproductive robustness.
Capturing 3D pollen images using confocal micrscopy
Seasonal allergic rhinitis (SAR) is a common inflammatory condition caused by pollen grains released by trees, grasses, weeds, or molds. Many people are affected by the cold-like symptoms caused by these various pollen species. Therefore, streamlining the distribution of real-time pollen conditions is important because it can provide allergy sufferers with useful information to help reduce pollen exposure. AI can be used to automate the process of identifying and quantifying real time pollen conditions. It is hypothesized that confocal microscopy images can serve as sufficient training data for this AI program. Whereas other types of microscopes can only allow the external characteristics of samples to be seen, confocal microscopy allows a sample to be imaged in slices along its z-axis which are then used to create 3D and cross-sectional images. This allows the images to not only display the external morphologies and characteristics that are unique to each pollen species, but also the internal morphologies and characteristics. During this study, several 3D images of various pollen species were captured at various magnifications. The images were able to show and distinguish each pollen species by their distinctive characteristics. The study found that confocal microscopy can be used to produce detailed images of pollen grain species. The next step in this research would be to develop an AI program that can identify and quantify pollen on an unmodified slide of current pollen conditions. This information can then be made public online or added to a pollen database.
Tissue Patterning: a window into gene regulation and morphological evolution
A vast amount of morphological diversity can be observed in nature and a growing body of evidence suggests that this diversity is driven by changes in the location and timing of gene expression within a developing animal. However, the evolutionary and molecular mechanisms underlying the patterns of gene expression in a developing tissue, known as tissue patterning, remain poorly understood. To understand how changes in tissue patterning drive morphological evolution, we use the Drosophila eggshell, a well established system for studying developmental signaling and tissue patterning. The eggshells of different species of Drosophila are morphologically diverse, and by employing a computational approach that transforms tissue patterning data into a digital format, our research investigates how eggshell diversity is mediated by changes in the pattern of Epidermal Growth Factor Receptor (EGFR) and the Bone Morphogenetic Protein (BMP) pathways. Our research program aims to identify the regulatory DNA sequences that are required for gene activation in morphologically diverse species.
