BackgroundRecent studies of transcription activator-like (TAL) effector domains fused to nucleases (TALENs) demonstrate enormous potential for genome editing. Effective design of TALENs requires a combination of selecting appropriate genetic features, finding pairs of binding sites based on a consensus sequence, and, in some cases, identifying endogenous restriction sites for downstream molecular genetic applications.ResultsWe present the web-based program Mojo Hand for designing TAL and TALEN constructs for genome editing applications (http://www.talendesign.org). We describe the algorithm and its implementation. The features of Mojo Hand include (1) automatic download of genomic data from the National Center for Biotechnology Information, (2) analysis of any DNA sequence to reveal pairs of binding sites based on a user-defined template, (3) selection of restriction-enzyme recognition sites in the spacer between the TAL monomer binding sites including options for the selection of restriction enzyme suppliers, and (4) output files designed for subsequent TALEN construction using the Golden Gate assembly method.ConclusionsMojo Hand enables the rapid identification of TAL binding sites for use in TALEN design. The assembly of TALEN constructs, is also simplified by using the TAL-site prediction program in conjunction with a spreadsheet management aid of reagent concentrations and TALEN formulation. Mojo Hand enables scientists to more rapidly deploy TALENs for genome editing applications.

Transcription activator-like effectors (TALEs) are extremely effective, single-molecule DNA-targeting molecular cursors used for locus-specific genome science applications, including high-precision molecular medicine and other genome engineering applications. TALEs are used in genome engineering for locus-specific DNA editing and imaging, as artificial transcriptional activators and repressors, and for targeted epigenetic modification. TALEs as nucleases (TALENs) are effective editing tools and offer high binding specificity and fewer sequence constraints toward the targeted genome than other custom nuclease systems. One bottleneck of broader TALE use is reagent accessibility. For example, one commonly deployed method uses a multitube, 5-day assembly protocol. Here we describe FusX, a streamlined Golden Gate TALE assembly system that (1) is backward compatible with popular TALE backbones, (2) is functionalized as a single-tube 3-day TALE assembly process, (3) requires only commonly used basic molecular biology reagents, and (4) is cost-effective. More than 100 TALEN pairs have been successfully assembled using FusX, and 27 pairs were quantitatively tested in zebrafish, with each showing high somatic and germline activity. Furthermore, this assembly system is flexible and is compatible with standard molecular biology laboratory tools, but can be scaled with automated laboratory support. To demonstrate, we use a highly accessible and commercially available liquid-handling robot to rapidly and accurately assemble TALEs using the FusX TALE toolkit. Together, the FusX system accelerates TALE-based genomic science applications from basic science screening work for functional genomics testing and molecular medicine applications.

Cigarette smoking remains the most preventable cause of death and excess health care costs in the United States, and is a leading cause of death among alcoholics. Long-term tobacco abstinence rates are low, and pharmacotherapeutic options are limited. Repositioning medications approved by the U.S. Food and Drug Administration (FDA) may efficiently provide clinicians with new treatment options. We developed a drug-repositioning paradigm using larval zebrafish locomotion and established predictive clinical validity using FDA-approved smoking cessation therapeutics. We evaluated 39 physician-vetted medications for nicotine-induced locomotor activation blockade. We further evaluated candidate medications for altered ethanol response, as well as in combination with varenicline for nicotine-response attenuation. Six medications specifically inhibited the nicotine response. Among this set, apomorphine and topiramate blocked both nicotine and ethanol responses. Both positively interact with varenicline in the Bliss Independence test, indicating potential synergistic interactions suggesting these are candidates for translation into Phase II clinical trials for smoking cessation.

zfishbook is an internet-based openly accessible database of revertible protein trap gene-breaking transposon (GBT) insertional mutants in the zebrafish, Danio rerio. In these lines, a monomeric red fluorescent protein (mRFP) is encoded by an artificial 3′ exon, resulting in a translational fusion to endogenous loci. The natural transparency of the zebrafish embryo and larvae greatly facilitates the expression annotation of tagged loci using new capillary-based SCORE imaging methods. Molecular annotation of each line is facilitated by cloning methods such as 5′-Rapid Amplification of cDNA Ends (RACE) and inverse polymerase chain reaction (PCR). zfishbook (http://zfishbook.org) represents a central hub for molecular, expression and mutational information about GBT lines from the International Zebrafish Protein Trap Consortium (IZPTC) that includes researchers from around the globe. zfishbook is open to community-wide contributions including expression and functional annotation. zfishbook also represents a central location for information on how to obtain these lines from diverse members of the IZPTC and integration within other zebrafish community databases including Zebrafish Information Network (ZFIN), Ensembl and National Center for Biotechnology Information.

Background: The patient/caregiver experience during CAR-T therapy is stressful, overwhelming, terrifying, and often a patient’s last treatment option. The Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery Innovation and Design team has worked with the CAR-T therapy clinical team to develop a patient experience that provides patients with a sense of caring, supportive environment, timely knowledge, and realistic expectations. Using a human-centered design approach, the Innovation and Design team worked with patients and caregivers to understand latent and unspoken needs in order to develop an ideal CAR-T therapy patient journey. Methods: With qualitative interviewing techniques, patient observation, and low fidelity experimentation, 21 patients/caregiver pairs were interviewed throughout their CAR-T therapy experience in 2018. Patients were interviewed at several touch points as well as encouraged to reach out to the Innovation and Design team at any point with reflections on their experiences. Patients were recruited as they began their evaluation phase for CAR-T therapy. The interviews were unscripted to allow for a breadth of discovery by not constraining the conversations to previously developed themes. As themes emerged from patient/caregiver interviews, artifacts and interventions were designed to alleviate pain points and improve the patient/caregiver experience. These artifacts and interventions were integrated into the clinical processes in real time and patient/caregivers were interviewed to understand the impact of these activities. Results: Several themes emerged from qualitative interviews with patients and caregivers. From the themes, interventions were developed. We were able to demonstrate a qualitative improvement in patient/caregiver experience through these interventions (Figure 1). Conclusions: Patients/caregivers undergoing CAR-T therapy have unique issues surrounding the logistics of care, emotional burden, and physical effects of treatment. We implemented processes to address these issues and observed a qualitative improvement via patient interviews/feedback. Ongoing work includes optimizing remote monitoring, digital platforms for patient education, and a quantitative study looking at patient reported outcomes (PROs) in such patients. To our knowledge, this is the first report for care delivery optimization in real-world practice for this new therapy.