Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the Molecular Biology of the Cell Ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,384 genes, 753 SCPs and 19,180 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed SCP networks for predictive modeling of emergent whole cell functions.

We present a technical platform that allows us to monitor and measure cortex and membrane dynamics during bleb-based chemotaxis. Using D. discoideum cells expressing LifeAct-GFP and crawling under agarose containing RITC-dextran, we were able to simultaneously visualize the actin cortex and the cell membrane throughout bleb formation. Using these images, we then applied edge detect to generate points on the cell boundary with coordinates in a coordinate plane. Then we fitted these points to a curve with known x and y coordinate functions. The result was to parameterize the cell outline. With the parameterization, we demonstrate how to compute data for geometric features such as cell area, bleb area and edge curvature. This allows us to collect vital data for the analysis of blebbing.

Abstract:Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the "Molecular Biology of the Cell" ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,385 genes, 753 SCPs and 19,180 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed multidimensional SCP networks for predictive modeling of emergent whole cell functions.

We present a technical platform that allows us to monitor and measure cortex and membrane dynamics during bleb-based chemotaxis. Using D. discoideum cells expressing LifeAct-GFP and crawling under agarose containing RITC-dextran, we were able to simultaneously visualize the actin cortex and the cell membrane throughout bleb formation. Using these images, we then applied edge detect to generate points on the cell boundary with coordinates in a coordinate plane. Then we fitted these points to a curve with known x and y coordinate functions. The result was to parameterize the cell outline. With the parameterization, we demonstrate how to compute data for geometric features such as cell area, bleb area and edge curvature. This allows us to collect vital data for the analysis of blebbing. Introduction1 Cells must modify their motile behavior when encountering varying conditions. They 2 must travel through multiple environments as they participate in a variety of biological 3 phenomena including foraging for food, embryogenesis, development, wound healing, 4 immune response, and cancer metastasis. There are two distinct modes of motility cells 5 utilize depending on their environment [1], [2]. When crawling on top of a substrate 6 with limited resistance to movement, a two dimensional environment, cells use filopodia, 7 lamellipodia, or pseudopodia as their main mode(s) of motility where actin is 8 continuously cycled to the front of the cell, pushing the cell's membrane forward in the 9 direction of movement. When crawling through a substrate or between cells where 10resistance is higher, a three dimensional environment, cells use blebs as their main mode 11 of motility. During bleb-based motility, the front of the cell makes a series of blister-like 12 protrusions in the direction of movement where the cell's membrane detaches from the 13 actin cortex [3]. This is driven in part by the increased intracellular pressure associated 14 with moving through a three dimensional environment. A variety of cell types have been 15 shown to utilize bleb-based motility in three dimensional environments: skeletal muscle 16 stem cells, zebrafish primordial germ cells, cancer cells, Entamoeba histolytica and 17 Dictyostelium discoideum [4], [5], [6], [7], [8], [9] and [10]. 18 PLOS 1/18 The formation of a bleb follows three general steps with distinct membrane and 19 cortex characteristics (Fig 1): 1) the membrane detaches from the cortex, making a 20 blister-like protrusion at the cell front; 2) the new cortex begins forming at the new 21 position of the membrane while the original cortex behind the detachment begins to 22 disassemble; and 3) the original cortex vanishes where the new cortex is fully assembled 23 and associated with the membrane. 24 Fig 1. Bleb formation can be identified by cortex-to-membrane 25 positioning. 26 At T 1 , the membrane detaches from the cortex, initiating a bleb. At T 2 , an actin 27 scar in the original location of the cortex disassembles as the cortex begins to reform at 28 the new location...