Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing

Integrating machine learning and biosensors in microfluidic devices: A review

Microfluidic devices are increasingly widespread in the literature, being applied to numerous exciting applications, from chemical research to Point-of-Care devices, passing through drug development and clinical scenarios. Setting up these microenvironments, however, introduces the necessity of locally controlling the variables involved in the phenomena under investigation. For this reason, the literature has deeply explored the possibility of introducing sensing elements to investigate the physical quantities and the biochemical concentration inside microfluidic devices. Biosensors, particularly, are well known for their high accuracy, selectivity, and responsiveness. However, their signals could be challenging to interpret and must be carefully analysed to carry out the correct information. In addition, proper data analysis has been demonstrated even to increase biosensors' mentioned qualities. To this regard, machine learning algorithms are undoubtedly among the most suitable approaches to undertake this job, automatically learning from data and highlighting biosensor signals' characteristics at best. Interestingly, it was also demonstrated to benefit microfluidic devices themselves, in a new paradigm that the literature is starting to name "intelligent microfluidics", ideally closing this benefic interaction among these disciplines. This review aims to demonstrate the advantages of the triad paradigm microfluidics-biosensors-machine learning, which is still little used but has a great perspective. After briefly describing the single entities, the different sections will demonstrate the benefits of the dual interactions, highlighting the applications where the reviewed triad paradigm was employed.

Apoptosis Detection by Quantification of Cell Debris in Bright-Field Microscopy Images

We describe a simple protocol for quantification of apoptosis by counting subcellular debris particles in bright-field microscopy images of cell culture media samples. The only necessary equipment is a bright-field microscope (fitted with a digital camera) and a computer for image processing and analysis. The method gives comparable results to established fluorescence markers in several different applications and is, in principle, compatible with any culture format. Given its simplicity, accessibility, and inexpensive nature, the method can complement or provide an alternative to other methods for apoptosis detection.

An Apoptotic Caspase Network Safeguards Cell Death Induction in Pyroptotic Macrophages

Pyroptosis has emerged as a key mechanism by which inflammasomes promote host defense against microbial pathogens and sterile inflammation. Gasdermin D (GSDMD)-mediated cell lysis is a hallmark of pyroptosis, but our understanding of cell death signaling during pyroptosis is fragmented. Here, we show that independently of GSDMD-mediated plasma membrane permeabilization, inflammasome receptors engage caspase-1 and caspase-8, both of which redundantly promote activation of apoptotic executioner caspase-3 and caspase-7 in pyroptotic macrophages. Impaired GSDMD pore formation downstream of caspase-1 and caspase-8 activation suffices to unmask the apoptotic phenotype of pyroptotic macrophages. Combined inactivation of initiator caspase-1 and caspase-8, or executioner caspase-3 and caspase-7, is required to abolish inflammasome-induced DEVDase activity during pyroptosis and in apoptotic Gsdmd^-/- cells. Collectively, these results unveil a robust apoptotic caspase network that is activated in parallel to GSDMD-mediated plasma membrane permeabilization and safeguards cell death induction in pyroptotic macrophages.

Novel Insights into the Roles of Bcl-2 Homolog Nr-13 (vNr-13) Encoded by Herpesvirus of Turkeys in the Virus Replication Cycle, Mitochondrial Networks, and Apoptosis Inhibition

The Bcl-2 (B cell lymphoma 2)-related protein Nr-13 plays a major role in the regulation of cell death in developing avian B cells. With over 65% sequence similarity to the chicken Nr-13, herpesvirus of turkeys (HVT) vNr-13, encoded by the HVT079 and HVT096 genes, is the first known alphaherpesvirus-encoded Bcl-2 homolog. HVT-infected cells were reported to be relatively more resistant to serum starvation, suggested that vNr-13 could be involved in protecting the cells. Here, we describe CRISPR/Cas9-based editing of exon 1 of the HVT079 and HVT096 genes from the HVT genome to generate the mutant HVT-ΔvNr-13 to gain insights into its functional roles. Overall, wild-type HVT and HVT-ΔvNr-13 showed similar growth kinetics; however, at early time points, HVT-ΔvNr-13 showed 1.3- to 1.7-fold-lower growth of cell-associated virus and 3- to 6.2-fold-lower growth of cell-free virus. In transfected cells, HVT vNr-13 showed a mainly diffuse cytoplasmic distribution with faint nuclear staining. Further, vNr-13 localized to the mitochondria and endoplasmic reticulum (ER) and disrupted mitochondrial network morphology in the transfected cells. In the wild-type HVT-infected cells, vNr-13 expression appeared to be directly involved in the disruption of the mitochondrial network, as the mitochondrial network morphology was substantially restored in the HVT-ΔvNr-13-infected cells. IncuCyte S3 real-time apoptosis monitoring demonstrated that vNr-13 is unequivocally involved in the apoptosis inhibition, and it is associated with an increase of PFU, especially under serum-free conditions in the later stages of the viral replication cycle. Furthermore, HVT blocks apoptosis in infected cells but activates apoptosis in noninfected bystander cells.IMPORTANCE B cell lymphoma 2 (Bcl-2) family proteins play important roles in regulating apoptosis during homeostasis, tissue development, and infectious diseases. Several viruses encode homologs of cellular Bcl-2-proteins (vBcl-2) to inhibit apoptosis, which enable them to replicate and persist in the infected cells and to evade/modulate the immune response of the host. Herpesvirus of turkeys (HVT) is a nonpathogenic alphaherpesvirus of turkeys and chickens that is widely used as a live vaccine against Marek's disease and as recombinant vaccine viral vectors for protecting against multiple avian diseases. Identical copies of the HVT genes HVT079 and HVT096 encode the Bcl-2 homolog vNr-13. While previous studies have identified the potential ability of vNr-13 in inhibiting apoptosis induced by serum deprivation, there have been no detailed investigations on the functions of vNr-13. Using CRISPR/Cas9-based ablation of the vNr-13 gene, we demonstrated the roles of HVT vNr-13 in early stages of the viral replication cycle, mitochondrial morphology disruption, and apoptosis inhibition in later stages of viral replication.

Hep G2 cell culture confluence measurement in phase-contrast micrographs - a user-friendly, open-source software-based approach

Phase-contrast micrographs are often used for confirmation of proliferation and viability assays. However, they are usually only a qualitative tool and fail to exclude with certainty the presence of assay interference by test substances. The complexity of image analysis workflows hinders life scientists from routinely utilizing micrograph data. Here, we present an open-source software-based, combined ilastik segmentation/ImageJ measurement of area (ISIMA) approach for cell monolayer segmentation and confluence percentage measurement of phase-contrast micrographs of Hep G2 cells. The aim of this study is to test whether the proposed approach is suitable for quantitative confirmation of proliferation data, acquired by the 3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. Our results show that ISIMA is user-friendly and provides reproducible data, which strongly correlates to the results of the MTT assay. In conclusion, ISIMA is an affordable, simple, and fast approach for confluence quantification by researchers without image analysis background.

COMBImage2: a parallel computational framework for higher-order drug combination analysis that includes automated plate design, matched filter based object counting and temporal data mining

BACKGROUND

Pharmacological treatment of complex diseases using more than two drugs is commonplace in the clinic due to better efficacy, decreased toxicity and reduced risk for developing resistance. However, many of these higher-order treatments have not undergone any detailed preceding in vitro evaluation that could support their therapeutic potential and reveal disease related insights. Despite the increased medical need for discovery and development of higher-order drug combinations, very few reports from systematic large-scale studies along this direction exist. A major reason is lack of computational tools that enable automated design and analysis of exhaustive drug combination experiments, where all possible subsets among a panel of pre-selected drugs have to be evaluated.

RESULTS

Motivated by this, we developed COMBImage2, a parallel computational framework for higher-order drug combination analysis. COMBImage2 goes far beyond its predecessor COMBImage in many different ways. In particular, it offers automated 384-well plate design, as well as quality control that involves resampling statistics and inter-plate analyses. Moreover, it is equipped with a generic matched filter based object counting method that is currently designed for apoptotic-like cells. Furthermore, apart from higher-order synergy analyses, COMBImage2 introduces a novel data mining approach for identifying interesting temporal response patterns and disentangling higher- from lower- and single-drug effects. COMBImage2 was employed in the context of a small pilot study focused on the CUSP9v4 protocol, which is currently used in the clinic for treatment of recurrent glioblastoma. For the first time, all 246 possible combinations of order 4 or lower of the 9 single drugs consisting the CUSP9v4 cocktail, were evaluated on an in vitro clonal culture of glioma initiating cells.

CONCLUSIONS

COMBImage2 is able to automatically design and robustly analyze exhaustive and in general higher-order drug combination experiments. Such a versatile video microscopy oriented framework is likely to enable, guide and accelerate systematic large-scale drug combination studies not only for cancer but also other diseases.

Image-Based Quantification of Cell Debris as a Measure of Apoptosis

Apoptosis is a controlled form of cell death that can be induced by various diseases and exogenous toxicants. Common apoptosis-detection methods rely on fluorescent markers, which necessitate the use of costly reagents and time-consuming labeling procedures. Label-free methods avoid these problems, but often require specialized instruments instead. Here, we utilize apoptotic-cell disintegration to develop a novel label-free detection method based on the quantification of subcellular debris particles in bright-field-microscopy images. Debris counts show strong correlations with fluorescence-based annexin V staining and can be used to study concentration-dependent and temporal apoptosis activation. The method is rapid, low-cost, and easy to apply, as the only experimental step comprises bright-field imaging of culture-media samples followed by automated image processing. The late-stage nature of the debris measurement means that the method can complement other, established apoptosis assays, and its accessibility will allow a wider community of researchers to study apoptotic cell death.

A single-cell micro-trench platform for automatic monitoring of cell division and apoptosis after chemotherapeutic drug administration

Cells vary in their dynamic response to external stimuli, due to stochastic fluctuations and non-uniform progression through the cell cycle. Hence, single-cell studies are required to reveal the range of heterogeneity in their responses to defined perturbations, which provides detailed insight into signaling processes. Here, we present a time-lapse study using arrays of micro-trenches to monitor the timing of cell division and apoptosis in non-adherent cells at the single-cell level. By employing automated cell tracking and division detection, we precisely determine cell cycle duration and sister-cell correlations for hundreds of individual cells in parallel. As a model application we study the response of leukemia cells to the chemostatic drug vincristine as a function of cell cycle phase. The time-to-death after drug addition is found to depend both on drug concentration and cell cycle phase. The resulting timing and dose-response distributions were reproduced in control experiments using synchronized cell populations. Interestingly, in non-synchronized cells, the time-to-death intervals for sister cells appear to be correlated. Our study demonstrates the practical benefits of micro-trench arrays as a platform for high-throughput, single-cell time-lapse studies on cell cycle dependence, correlations and cell fate decisions in general.

Institutional profile: the national Swedish academic drug discovery & development platform at SciLifeLab

The Science for Life Laboratory Drug Discovery and Development Platform (SciLifeLab DDD) was established in Stockholm and Uppsala, Sweden, in 2014. It is one of ten platforms of the Swedish national SciLifeLab which support projects run by Swedish academic researchers with large-scale technologies for molecular biosciences with a focus on health and environment. SciLifeLab was created by the coordinated effort of four universities in Stockholm and Uppsala: Stockholm University, Karolinska Institutet, KTH Royal Institute of Technology and Uppsala University, and has recently expanded to other Swedish university locations. The primary goal of the SciLifeLab DDD is to support selected academic discovery and development research projects with tools and resources to discover novel lead therapeutics, either molecules or human antibodies. Intellectual property developed with the help of SciLifeLab DDD is wholly owned by the academic research group. The bulk of SciLifeLab DDD's research and service activities are funded from the Swedish state, with only consumables paid by the academic research group through individual grants.

Time-Resolved Study of Nanoparticle Induced Apoptosis Using Microfabricated Single Cell Arrays

Cell fate decisions like apoptosis are heterogeneously implemented within a cell population and, consequently, the population response is recognized as sum of many individual dynamic events. Here, we report on the use of micro-patterned single-cell arrays for real-time tracking of nanoparticle-induced (NP) cell death in sets of thousands of cells in parallel. Annexin (pSIVA) and propidium iodide (PI), two fluorescent indicators of apoptosis, are simultaneously monitored after exposure to functionalized polystyrene (PS - NH 2) nanobeads as a model system. We find that the distribution of Annexin onset times shifts to later times and broadens as a function of decreasing NP dose. We discuss the mean time-to-death as a function of dose, and show how the EC 50 value depends both on dose and time of measurement. In addition, the correlations between the early and late apoptotic markers indicate a systematic shift from apoptotic towards necrotic cell death during the course of the experiment. Thus, our work demonstrates the potential of array-based single cell cytometry for kinetic analysis of signaling cascades in a high-throughput format.

A direct role for ATP1A1 in unconventional secretion of fibroblast growth factor 2

Previous studies proposed a role for the Na/K-ATPase in unconventional secretion of fibroblast growth factor 2 (FGF2). This conclusion was based upon pharmacological inhibition of FGF2 secretion in the presence of ouabain. However, neither independent experimental evidence nor a potential mechanism was provided. Based upon an unbiased RNAi screen, we now report the identification of ATP1A1, the α1-chain of the Na/K-ATPase, as a factor required for efficient secretion of FGF2. As opposed to ATP1A1, down-regulation of the β1- and β3-chains (ATP1B1 and ATP1B3) of the Na/K-ATPase did not affect FGF2 secretion, suggesting that they are dispensable for this process. These findings indicate that it is not the membrane potential-generating function of the Na/K-ATPase complex but rather a so far unidentified role of potentially unassembled α1-chains that is critical for unconventional secretion of FGF2. Consistently, in the absence of β-chains, we found a direct interaction between the cytoplasmic domain of ATP1A1 and FGF2 with submicromolar affinity. Based upon these observations, we propose that ATP1A1 is a recruitment factor for FGF2 at the inner leaflet of plasma membranes that may control phosphatidylinositol 4,5-bisphosphate-dependent membrane translocation as part of the unconventional secretory pathway of FGF2.