Biology subjects

Axelrod, J. D.

Publications and source records attributed to Axelrod, J. D..

4 recordsLinked to original sources

bioRxiv2023

Cell autonomous polarization by the planar cell polarity signaling pathway

As epithelial cells polarize in the tissue plane, the Planar Cell Polarity (PCP) signaling module segregates two distinct molecular subcomplexes to opposite sides of cells. Homodimers of the atypical cadherin Flamingo form bridges linking opposite complexes in neighboring cells, coordinating their direction of polarization. Feedback is required for cell polarization, but whether feedback requires intercellular and/or intracellular pathways is unknown. Using novel tools, we show that cells lacking Flamingo, or bearing a homodimerization-deficient Flamingo, polarize autonomously, indicating that functional PCP subcomplexes form and segregate cell-autonomously. Furthermore, we identify feedback pathways and propose an asymmetry amplifying mechanism that operate cell-autonomously. The intrinsic logic of PCP signaling is therefore more similar to that in single cell systems than was previously recognized.

developmental biology↗

bioRxiv2023

Flamingo participates in multiple models of cell competition

The growth and survival of cells with different fitness, such as those with a proliferative advantage or a deleterious mutation, is controlled through cell competition. During development, cell competition enables healthy cells to eliminate less fit cells that could jeopardize tissue integrity, and facilitates the elimination of pre-malignant cells by healthy cells as a surveillance mechanism to prevent oncogenesis. Malignant cells also benefit from cell competition to promote their expansion. Despite its ubiquitous presence, the mechanisms governing cell competition, particularly those common to developmental competition and tumorigenesis, are poorly understood. Here, we show that in Drosophila, the planar cell polarity (PCP) protein Flamingo (Fmi) is required by winners to maintain their status during cell competition in malignant tumors to overtake healthy tissue, in early pre-malignant cells when they overproliferate among wildtype cells, in healthy cells when they later eliminate pre-malignant cells, and by supercompetitors as they compete to occupy excessive territory within wildtype tissues. "Would-be" winners that lack Fmi are unable to over-proliferate, and instead become losers. We demonstrate that the role of Fmi in cell competition is independent of PCP, and that it uses a distinct mechanism that may more closely resemble one used in other less well-defined functions of Fmi.

developmental biology↗

bioRxiv2023

Protein phosphatase 1 regulates core PCP signaling

AbstractPCP signaling polarizes epithelial cells within the plane of an epithelium. Core PCP signaling components adopt asymmetric subcellular localizations within cells to both polarize and coordinate polarity between cells. Achieving subcellular asymmetry requires additional effectors, including some mediating post-translational modifications of core components. Identification of such proteins is challenging due to pleiotropy. We used mass spectrometry-based proximity labeling proteomics to identify such regulators in the Drosophila wing. We identified the catalytic subunit of Protein Phosphatase1, Pp1-87B, and show that it regulates core protein polarization. Pp1-87B interacts with the core protein Van Gogh and at least one Serine/Threonine kinase, Dco/CKIc, that is known to regulate PCP. Pp1-87B modulates Van Gogh subcellular localization and directs its dephosphorylation in vivo. PNUTS, a Pp1 regulatory subunit, also modulates PCP. While the direct substrate(s) of Pp1-87B in control of PCP is not known, our data support the model that cycling between phosphorylated and unphosphorylated forms of one or more core PCP components may regulate acquisition of asymmetry. Finally, our screen serves as a resource for identifying additional regulators of PCP signaling.

developmental biology↗

bioRxiv2023

Automated counting of Drosophila imaginal disc cell nuclei

Automated image quantification workflows have dramatically improved over the past decade, enriching image analysis and enhancing the ability to achieve statistical power. These analyses have proved especially useful for studies in organisms such as Drosophila melanogaster, where it is relatively simple to obtain high sample numbers for downstream analyses. However, the developing wing, an intensively utilized structure in developmental biology, has eluded efficient cell counting workflows due to its highly dense cellular population. Here, we present efficient automated cell counting workflows capable of quantifying cells in the developing wing. Our workflows can count the total number of cells or count cells in clones labeled with a fluorescent nuclear marker in imaginal discs. Moreover, by training a machine-learning algorithm we have developed a workflow capable of segmenting and counting twin-spot labeled nuclei, a challenging problem requiring distinguishing heterozygous and homozygous cells in a background of regionally varying intensity. Our workflows could potentially be applied to any tissue with high cellular density, as they are structure-agnostic, and only require a nuclear label to segment and count cells.

developmental biology↗