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Zebrafish are a powerful vertebrate model for many avenues of biological research including developmental biology and pathology. Due to their small size and optical clarity they are uniquely amendable to imaging studies. In this webinar we will describe how automated digital microscopy and quantitative image analysis can be applied to zebrafish research focusing on three common areas of study including angiogenesis, toxicology and cell death.

In this webinar, we’ll describe how automated digital microscopy methods and high content image analysis tools frequently used in mammalian cell studies are applied to an array of microbial cell models common to bacteriology, virology, mycology, and mixed cell type co-cultures. Using live and fixed microorganisms, and a variety of stains, fluorescent probes and a label-free technique to demonstrate how downstream qualitative and quantitative data outcomes, such as cell counting and unit volume conversion, metabolic activity, strain differentiation, and morphology characterization, are obtained for each of a group of individual case studies. Our goal is to provide tips and insights that can be broadly applied in microbial imaging applications beyond the examples shown.

Three dimensional (3D) spheroidal cell models have become a mainstay in life science research to provide the most in vivo-like environment. Performing media exchanges and washes with unattached spheroids can be problematic due to the risk of accidental spheroid removal. In this webinar we will introduce the MultiFlo™ FX's new AMX™ Automated Media Exchange Module, a novel automated, peristaltic pump-based tool that allows these procedures to be carried out in a controlled and consistent manner that eliminates spheroid disruption and removal, simplifying long-term 3D experimental procedures.

Nucleic acids are the building blocks of life in all living things, from plants and animals to bacteria and viruses. In research, it’s important to quantify nucleic acids prior to downstream processes like sequencing, restriction enzyme digestions and ligations, PCR and qPCR along with many other applications. Along with determining nucleic acid concentrations, it’s also important to calculate the ratio of nucleic acid to protein to ascertain the purity of the nucleic acid before using the sample in subsequent analyses.

Phenotypic cellular analysis is a critical area of biological research. Numerous applications require quantifying the number of “spots” per cell, including DNA damage, autophagosomes, endosomes, and mitochondria. These evaluations are often done by hand, which is highly subjective and can be tedious. In this webinar we will describe using an automated image based approach for rapid, objective quantification of various assays that use object spot counting analysis including autophagy, mitochondria membrane potential, genotoxicity, and others.

Enzyme-linked immunosorbent assay (ELISA) is an antibody-based reaction that allows the detection and quantitation of numerous analytes with the same basic assay process. The reaction uses a solid surface, typically a microplate, to immobilize the analyte. Once immobilized, unwanted materials can be removed by washing and the remaining analyte quantitated. The assay technology uses antibodies in conjunction with enzyme-catalyzed amplification to provide high specificity and high sensitivity. Here we will describe the basic process steps of ELISA, best laboratory practices along with troubleshooting tips for common problems. In addition, some of the devices and instrumentation used with this assay technology will be described.

The use of cells cultured into a three-dimensional (3D) configuration continues to gain acceptance within multiple areas of life science research and drug discovery. Assay procedures commonly performed with two-dimensional (2D) cultured cells are rapidly migrating to 3D because of the reestablishment of cell-cell and cell-extracellular matrix (ECM) interactions, and in vivo-like results these cell models afford. Examples include cell migration studies, stem cell differentiation, and toxicity assessments.

Characterizing cell proliferation is a crucial aspect of biological research and therapeutic drug development. Most current cell proliferation assays rely on indirect biochemical metrics that are limited by artifacts or imaging-based endpoint measures. In this webinar, we will describe a continuous live-cell assay for determining cell proliferation profiles using high contrast brightfield imaging. This fully automated method enables long-term quantitative analysis of cell growth using non-invasive methods to directly count cells or assess % confluence.

The science of cell biology relies heavily on microscopy to visualize structure and function of cells. Qualitative assessments can be made with traditional microscopes that rely on oculars to visualize cells and how they behave in homeostasis or under stress. To quantify these processes, it is necessary to digitize images so processing and analysis routines can be employed.

BioTek's Lionheart™ FX Automated Live Cell Imager simplifies live cell imaging by providing a fully integrated solution. While the sample environment is effectively controlled to maintain cell health, all optical components are kept in separate conditions optimal for high resolution microscopy. The Lionheart FX also possesses versatile software allowing the easy creation of time-lapse movies and powerful image analysis enabling quantitative phenotypic assays. These capabilities will be demonstrated in the webinar by several applications including perfusion and wound healing assays.

In this webinar we will demonstrate imaging and analysis procedures using the CometAssay® from Trevigen®. Following staining, automated imaging of each well is performed using the Cytation cell imaging multi-mode reader. Built in Gen5 software, used for analysis and instrument control, then carries out commonly accepted calculations; such as % DNA in the comet tail and tail moment. The combined process can then be used to generate automated, high throughput comet-based genotoxicity data.