Performance evaluation of three DNA sample tracking tools in a whole exome sequencing workflow

Next-generation sequencing applications are becoming the building blocks for clinical diagnostics. These experiments require numerous wet- and drylab steps, each one increasing the probability of a sample swap and/or contamination. Therefore, an identity confirmation at the end of the process is required to ensure the right data is used for each patient. We tested three commercially available, SNP bases sample tracking kits in a diagnostic workflow to evaluate their performance. The coverage uniformity, on-target specificity, sample identification and genotyping performance were determined to measure the reliability and estimate the cost-effectiveness of each kit. Our findings showed that the kit from Swift did not perform up to standards as only 20 out of the 46 samples were correctly genotyped. The kit provided by Nimagen identified all but one sample and the kit from pxlence unambiguously identified all samples, making it the most reliable and robust kit of this evaluation. The kit from Nimagen showed poor on-target rates, resulting in deeper sequencing needs and higher sequencing costs compared to the other two kits.

Laser Capture Microdissection (LCM) and 3D Sample Tracking Protocol

This protocol demonstrates the use of Laser Capture Microdissection (LCM), a precise cell isolation technique, for acquiring single neurons from right atrial ganglionated plexus (RAGP) porcine heart tissue in sync with image acquisition to enable 3D location tracking of collected samples. Fresh frozen RAGP tissue sectioned and stained for neurons (Nissl stain) is processed through LCM for sample collection. The LCM workflow is comprised of four steps: instrument setup, slide loading and tissue inspection, microdissection and image acquisition and sample processing and storage. LCM collected samples were processed for gene expression experiments : High-throughput-qRT-PCR or Single cell RNA sequencing. Gene expression data along with 3D sample tracking was used to generate a functional map of porcine RAGP. The techniques described in this protocol can be adapted to a wide variety of sample and tissue types with minor modifications. This protocol is a part of a protocol pipeline that includes cryosectioning and staining protocols upstream and Tissue Mapper protocol, High-Throughput q-RT-PCR and RNA Seq protocols downstream.

Complete Digital Pathology for Routine Histopathology Diagnosis in a Multicenter Hospital Network

Context.— Complete digital pathology and whole slide imaging for routine histopathology diagnosis is currently in use in few laboratories worldwide. Granada University Hospitals, Spain, which comprises 4 hospitals, adopted full digital pathology for primary histopathology diagnosis in 2016. Objective.— To describe the methodology adopted and the resulting experience at Granada University Hospitals in transitioning to full digital diagnosis. Design.— All histopathology glass slides generated for routine diagnosis were digitized at ×40 using the Philips IntelliSite Pathology Solution, which includes an ultrafast scanner and an image management system. All hematoxylin-eosin–stained preparations and immunohistochemistry and histochemistry slides were digitized. The existing sample-tracking software and image management system were integrated to allow data interchange through the Health Level 7 protocol. Results.— Circa 160 000 specimens have been signed out using digital pathology for primary diagnosis. This comprises more than 800 000 digitized glass slides. The scanning error rate during the implementation phase was below 1.5%, and subsequent workflow optimization rendered this rate negligible. Since implementation, Granada University Hospitals pathologists have signed out 21% more cases per year on average. Conclusions.— Digital pathology is an adequate medium for primary histopathology diagnosis. Successful digitization relies on existing sample tracking and integration of the information technology infrastructure. Rapid and reliable scanning at ×40 equivalent was key to the transition to a fully digital workflow. Digital pathology resulted in efficiency gains in the preanalytical and analytical phases, and created the basis for computational pathology: the use of computer-assisted tools to aid diagnosis.