Join this year's poster presenters in the Poster Hall during the Poster Discussion, Wednesday, September 18th, from 1:00pm –2:00pm PDT, to chat live about their posters and latest research and findings.

This webinar is designed to explore the fundamental characteristics of reverse transcriptases and the essential factors that play a pivotal role in achieving high-quality cDNA synthesis from samples with limited input. Furthermore, the session will provide valuable insights into the significance of template switching reverse transcription and highlight the advantages of direct cDNA synthesis from cell lysates. These advancements contribute to more streamlined and effective workflows, ultimately enabling researchers to analyze single cells with greater efficiency and accuracy.

Key Learning:

• Discuss reverse transcriptase attributes
• Analyze important considerations for working with limited sample sources
• Evaluate benefits of direct cDNA synthesis
• Discuss advantages and applications of template-switching reverse transcription

The quest to decipher the complex molecular events underpinning cell polarity and organelle segregation during eukaryotic cell division presents a formidable challenge. A predominant focus on metazoans, fungi, and microbial eukaryotes risks neglecting evolutionary insights and unique features inherent to diverse organisms. This narrow scope could impede the broader understanding of protein functions across the eukaryotic kingdom. Our research aims to bridge this gap by exploring universal mechanisms of cell division in an apicomplexan protist. Building on our previous work, which utilized 3D super-resolution expansion microscopy, we have hypothesized that dynamic tethers to the nucleus are key to the cellularization of multinucleated cells. We will further this investigation by scrutinizing the molecular composition and architecture of the centriolar plaque, particularly its role in establishing cell polarity and driving organelle segregation in atypical eukaryotic cell division. Our approach integrates genetic, biochemical, and advanced expansion microscopy assays to pinpoint critical proteins and map their interactions in these vital processes. This research not only promises to broaden the imaging toolkit for microorganism studies but also seeks to uncover novel cell division mechanisms involving conserved nuclear proteins and Microtubule Organizing Centers (MTOCs). This project has the potential to significantly advance basic scientific knowledge and contribute to global health innovations, offering insights into the universality and diversity of cell division processes across the eukaryotic spectrum.

Learning Objectives: 

1. Discuss atypical cell division of a singled cell eurokaryote.

2. Explain advanced imaging for microorganisms - What is Expansion Microscopy.

3. Analyze the new avenues of basic research to contribute to Malaria eradication.

The disposition of antibody-based therapeutics is generally determined by both target-mediated and non-target processes, the latter being an often-overlooked aspect. Target-independent liabilities can significantly increase the elimination rate of a candidate protein, which could lead to reduced efficacy and attrition during drug development. However, the ability to identify at-risk proteins via in vitro techniques has remained challenging. This presentation will highlight key mechanisms causing pharmacokinetic shortfalls for antibody-based therapeutics. Additionally, it will demonstrate how cell-based assays can successfully predict target-independent problems to identify candidates with the most optimal pharmacokinetic properties.

Learning Objectives:

• Discuss the factors important for poor pharmacokinetics of antibody-based proteins

• Explain how cellular assays can be used to detect pharmacokinetic liabilities during large molecule drug development 

• Apply Knowledge to Drug Development: Participants will be able to apply the knowledge gained to propose strategies for incorporating cellular assays into their own drug development processes to identify and mitigate potential pharmacokinetic issues.

Super-resolution microscopy, or nanoscopy, enables the use of fluorescent-based molecular localization tools to study molecular structure at the nanoscale level in the intact cell. Analysis of super-resolution data by artificial intelligence (AI), or machine learning, offers tremendous potential for discovery of new biology, that, by definition, is not known and lacks ground truth. Application of weakly supervised paradigms to super-resolution microscopy has the potential to enable the accelerated exploration of the nanoscale architecture of subcellular macromolecules and organelles.

Single molecule localization microscopy (SMLM) approaches are based on analysis of stochastic blinking of isolated fluorophores and generate an event list of localizations, or a point cloud, essentially a network of connections between localizations or nodes. Application of a computational pipeline, SuperResNET, to SMLM point cloud data for the coat protein of caveolae, caveolin-1, identified not only caveolae but also three non-caveolar scaffold domains, including the smallest corresponding to the 11-mer caveolin-1 8S complex as well as 8S complex dimers and larger hemispherical S2 scaffold domains.

MCS-DETECT detects contact sites between organelles, separated by sub-pixel distances of 10-60 nm, from stimulated emission depletion (STED) microscopy volumes. MCS-DETECT uses Laplacian detection of local intensity changes to identify regions in 3D STED super-resolution images where the intensity of ER and mitochondria change in tandem. We tuned MCS-DETECT using a group label comparison of HT-1080 cells, expressing ribosome-studded mitochondria-ER contacts (riboMERCs) and COS-7 cells that do not express riboMERCs. riboMERCs present complex tubular shapes intercalating between multiple mitochondria whose formation is dependent on the riboMERC tether protein RRBP1 and size modulated by the Gp78 E3 ubiquitin ligase.

Learning Objectives:

1. Explain the principles of super-resolution microscopy (nanoscopy) and its use in studying subcellular structures at the nanoscale level within intact cells.

2. Analyze the application of artificial intelligence (AI) and machine learning in processing super-resolution microscopy data, specifically focusing on the SuperResNET computational pipeline and its role in identifying nanoscale structures such as caveolin-1 domains.

3. Evaluate the MCS-DETECT tool for detecting organelle contact sites from super-resolution images, and understand its application in distinguishing ribosome-studded mitochondria-ER contacts (riboMERCs) based on sub-pixel intensity variations.

Numerous biomedical applications have been described for liver-humanized mouse models, such as in drug metabolism or drug-drug interaction (DDI) studies. However, the strong enlargement of the bile acid (BA) pool due to lack of recognition of murine intestine-derived fibroblast growth factor-15 by human hepatocytes and a resulting upregulation in the rate-controlling enzyme for BA synthesis, cytochrome P450 (CYP) 7A1, may pose a challenge in interpreting the results obtained from such mice. To address this challenge, the human fibroblast growth factor-19 (FGF19) gene was inserted into the Fah-/- , Rag2-/- , Il2rg-/- NOD (FRGN) mouse model, allowing repopulation with human hepatocytes capable of responding to FGF19. While a decrease in CYP7A1 expression in human hepatocytes from humanized FRGN19 mice (huFRGN19) and a concomitant reduction in BA production was previously shown, a detailed analysis of the BA pool in these animals has not been elucidated. Furthermore, there are sparse data on the use of this model to assess potential clinical DDI. In the present work, the change in BA composition in huFRGN19 compared with huFRGN control animals was systematically evaluated, and the ability of the model to recapitulate a clinically described CYP3A4-mediated DDI was assessed. In addition to a massive reduction in the total amount of BA, FGF19 expression in huFRGN19 mice resulted in significant changes in the profile of various primary, secondary, and sulfated BAs in serum and feces. Moreover, as observed clinically, administration of the pregnane X receptor agonist rifampicin reduced the oral exposure of the CYP3A4 substrate triazolam. SIGNIFICANCE STATEMENT: Transgenic expression of FGF19 normalizes the unphysiologically high level of bile acids in a chimeric liver-humanized mouse model and leads to massive changes in bile acid composition. These adaptations could overcome one of the potential impediments in the use of these mouse models for drug-drug interaction studies.

Learning Objectives

1. Describe the role of fibroblast growth factor 19 (FGF19) expression in liver-humanized mouse models and its impact on bile acid composition and metabolism.

2. Evaluate the significance of bile acid pool normalization in liver-humanized mouse models and how it improves the interpretation of drug metabolism and drug-drug interaction (DDI) studies.

3. Analyze the effectiveness of the huFRGN19 model in recapitulating clinically relevant CYP3A4-mediated drug-drug interactions, using the example of rifampicin and triazolam interaction.

One of the primary limitations in drug discovery and toxicology research is the lack of good model systems between the single cell level and animal or human systems. This is especially true for neurodegenerative diseases such as ALS and Alzheimer’s as well as spinal cord injury. In addition, with the banning of animals for toxicology testing in many industries body-on-a-chip systems to replace animals with human mimics is essential for product development and safety testing. Our research focus is on the establishment of functional in vitro systems to address this deficit where we seek to create organs and subsystems to model motor control, muscle function, myelination and cognitive function, as well as cardiac and liver subsystems. The idea is to integrate microsystems fabrication technology and surface modifications with protein and cellular components, for initiating and maintaining self-assembly and growth into biologically, mechanically and electronically interactive functional multi-component systems. Specific embodiments of this technology are the creation of a functional human NMJ system to understand ALS and a long-term potentiation (LTP) for AD utilizing clinically relevant functional readouts. We have investigated four mutations found in ALS patients; SOD1, FUS, TDP43 and C9ORF72. The models have demonstrated variations of the disease phenotype compared to WT for NMJ stability and functional dynamics. We have also demonstrated the LTP model can reproduce Aβ pathology and tauopathy in human cortical neurons and demonstrated how AD therapeutics can recover these effects Examples will be given of some of the other human-on-a-chip systems being developed for CNS and PNS disease applications as well as the results Sanofi has used as efficacy data from one of our models to file the first IND only from MPS data that has enabled a clinical trial (#NCT04658472) and has now proceeded to a Phase III trial.

Learning Objectives

1. Explain the development and applications of human-on-a-chip systems as alternatives to animal models for drug discovery and toxicity testing, with a focus on neurodegenerative diseases such as ALS and Alzheimer’s.

2. Evaluate the integration of microsystems technology, surface modifications, and cellular components in creating functional in vitro models to mimic human organ systems, including motor control, cognitive function, and cardiac subsystems.

3. Analyze the use of human-on-a-chip models for therapeutic efficacy, focusing on their impact in preclinical drug discovery, including case studies such as the ALS and Alzheimer’s models, and their role in advancing clinical trials.

Organisms sense and respond to changes in the environment through signal transduction pathways. Pathways like highly conserved Mitogen-Activated Protein Kinase (MAPK) pathways are composed of sensor proteins, cytosolic relay proteins, and transcription factors. A mysterious feature of MAPK pathways is they contain common or shared components that function in multiple pathways. The question of signal specificity is important because mis-regulation of pathways, such as by cross talk, and cause diseases like cancer in humans. A priority is to understand how specificity is achieved between MAPK and other pathways that share components. A type of sensor protein for MAPK pathways are members of the mucin family of proteins. Mucins are highly glycosylated transmembrane proteins that function at the cell surface. In humans, mucins are mis-regulated in cancers, being markers for poor prognosis and targets of immunotherapies. Mucins remain poorly characterized because of their ill-defined mechano-sensory properties, the unknown effects of various types of glycosylation on signaling, and their poorly explored connections to cytosolic relay proteins. The lack of understanding in mucin biology is highlighted when compared to the common G-protein coupled receptors (GPCRs), whose ligands are well defined, structures resolved, and connections to effector proteins firmly established. In the genetic model yeast, two mucins regulate different MAPK pathways, providing an opportunity to define how mucins regulate signaling specificity. Mucins work with relay proteins including G-proteins like the Rho GTPase Cdc42. This regulator of signaling and polarity interacts with effector kinases to regulate MAPK pathways. We have identified a member of the Ral GDS family that binds Cdc42 and may direct it to a specific pathway. Because mucins, Ral GDS proteins and Cdc42 are conserved throughout eukaryotes, studying specificity mechanisms in a model system can teach us about related pathways important for human health.

Learning Objectives: 

1. Discuss how signaling mucins regulate MAPK pathways.

2. Demonstrate knowledge of signal specificity by scaffolds.

3. Demonstrate knowledge of signal integration in networks.