EdgeProps: A Computational Platform for Correlative Analysis of Cell Dynamics and Near-Edge Protein Activity

Real-time semantic segmentation and anomaly detection of functional images for cell therapy manufacturing

BACKGROUND AIMS

Cell therapy is a promising treatment method that uses living cells to address a variety of diseases and conditions, including cardiovascular diseases, neurologic disorders and certain cancers. As interest in cell therapy grows, there is a need to shift to a more efficient, scalable and automated manufacturing process that can produce high-quality products at a lower cost.

METHODS

One way to achieve this is using non-invasive imaging and real-time image analysis techniques to monitor and control the manufacturing process. This work presents a machine learning-based image analysis pipeline that includes semantic segmentation and anomaly detection capabilities.

RESULTS/CONCLUSIONS

This method can be easily implemented even when given a limited dataset of annotated images, is able to segment cells and debris and can identify anomalies such as contamination or hardware failure.

Quantifying protrusions as tumor-specific biophysical predictors of cancer invasion in in vitro tumor micro-spheroid models

An important hallmark in cancer research is the discovery of suitable features capable to reliably predict tumor invasiveness, and consequently, their metastatic potential at an early stage. Current methods are based on molecular biomarker screening and imaging that may not reveal the altered properties of tumor cells, being also labor-intensive and costly. Biophysical-based methodologies provide a new framework assessing-and even predicting-the invasion potential of tumors with improved accuracy. In particular, the stochastic fluctuations of cancer invasive protrusions can be used as a tumor-specific biophysical indicator of its aggressiveness. In this methodology, tumor micro-spheroids with different metastatic capabilities were employed as in vitro models to analyze protrusion activity. It is described the procedure for extracting the descriptive biophysical parameters characteristic of protrusion activity, which magnitude depends on the invasion capability of tumors. Next, a simple mathematical approach is employed to define a predictive index that correlates with tumor invasiveness. Overall, this innovative approach may provide a simple method for unveiling cancer invasiveness and complement existing diagnosis methodologies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44164-022-00020-1.

Methods for assessment of membrane protrusion dynamics

Membrane protrusions are a critical facet of cell function. Mediating fundamental processes such as cell migration, cell-cell interactions, phagocytosis, as well as assessment and remodeling of the cell environment. Different protrusion types and morphologies can promote different cellular functions and occur downstream of distinct signaling pathways. As such, techniques to quantify and understand the inner workings of protrusion dynamics are critical for a comprehensive understanding of cell biology. In this chapter, we describe approaches to analyze cellular protrusions and correlate physical changes in cell morphology with biochemical signaling processes. We address methods to quantify and characterize protrusion types and velocity, mathematical approaches to predictive models of cytoskeletal changes, and implementation of protein engineering and biosensor design to dissect cell signaling driving protrusive activity. Combining these approaches allows cell biologists to develop a comprehensive understanding of the dynamics of membrane protrusions.

Regulation of local GTP availability controls RAC1 activity and cell invasion

Physiological changes in GTP levels in live cells have never been considered a regulatory step of RAC1 activation because intracellular GTP concentration (determined by chromatography or mass spectrometry) was shown to be substantially higher than the in vitro RAC1 GTP dissociation constant (RAC1-GTP Kd). Here, by combining genetically encoded GTP biosensors and a RAC1 activity biosensor, we demonstrated that GTP levels fluctuating around RAC1-GTP Kd correlated with changes in RAC1 activity in live cells. Furthermore, RAC1 co-localized in protrusions of invading cells with several guanylate metabolism enzymes, including rate-limiting inosine monophosphate dehydrogenase 2 (IMPDH2), which was partially due to direct RAC1-IMPDH2 interaction. Substitution of endogenous IMPDH2 with IMPDH2 mutants incapable of binding RAC1 did not affect total intracellular GTP levels but suppressed RAC1 activity. Targeting IMPDH2 away from the plasma membrane did not alter total intracellular GTP pools but decreased GTP levels in cell protrusions, RAC1 activity, and cell invasion. These data provide a mechanism of regulation of RAC1 activity by local GTP pools in live cells.

Changes in intracellular GTP levels are not considered as a regulatory event in RAC1 activation in live cells since total GTP levels are substantially higher than the RAC1 GTP dissociation constant determined in vitro. Here, the authors demonstrate that the availability of free GTP in live cells controls the activity of RAC1 and cell invasion.

Light-regulated allosteric switch enables temporal and subcellular control of enzyme activity

Engineered allosteric regulation of protein activity provides significant advantages for the development of robust and broadly applicable tools. However, the application of allosteric switches in optogenetics has been scarce and suffers from critical limitations. Here, we report an optogenetic approach that utilizes an engineered Light-Regulated (LightR) allosteric switch module to achieve tight spatiotemporal control of enzymatic activity. Using the tyrosine kinase Src as a model, we demonstrate efficient regulation of the kinase and identify temporally distinct signaling responses ranging from seconds to minutes. LightR-Src off-kinetics can be tuned by modulating the LightR photoconversion cycle. A fast cycling variant enables the stimulation of transient pulses and local regulation of activity in a selected region of a cell. The design of the LightR module ensures broad applicability of the tool, as we demonstrate by achieving light-mediated regulation of Abl and bRaf kinases as well as Cre recombinase.