T cell fate and clonality inference from single-cell transcriptomes

Advanced Methodologies in High-Throughput Sequencing of Immune Repertoires

In recent years, major efforts have been made to develop sophisticated experimental and bioinformatic workflows for sequencing adaptive immune repertoires. The immunological insight gained has been applied to fields as varied as lymphocyte biology, immunodiagnostics, vaccines, cancer immunotherapy, and antibody engineering. In this review, we provide a detailed overview of these advanced methodologies, focusing specifically on strategies to reduce sequencing errors and bias and to achieve high-throughput pairing of variable regions (e.g., heavy-light or alpha-beta chains). In addition, we highlight recent technologies for single-cell transcriptome sequencing that can be integrated with immune repertoires. Finally, we provide a perspective on advanced immune repertoire sequencing and its ability to impact basic immunology, biopharmaceutical drug discovery and development, and cancer immunotherapy.

Rapid identification and expression of human TCRs in retrogenic mice

Single-cell paired TCR identification is a powerful tool, but has been limited in its previous incompatibility with further functional analysis. The current protocol describes a method to clone and functionally evaluate in vivo TCRs derived from single antigen-responsive human T cells and monoclonal T cell lines. We have improved upon current PCR-based TCR sequencing protocols by developing primers that allow amplification of human TCRα and TCRβ variable regions, while incorporating specific restriction cut sites for direct subcloning into the template retroviral vector. This streamlined approach for generating human:mouse chimeric TCR vectors allows for rapid TCR expression in humanized-retrogenic (hu-Rg) mice through retroviral mediated stem cell gene transfer. Using widely available techniques and equipment, this method is easily adaptable by most laboratories. This is the first TCR identification protocol that is efficiently combined with subsequent in vivo TCR expression.

Single-cell TCRseq: paired recovery of entire T-cell alpha and beta chain transcripts in T-cell receptors from single-cell RNAseq

Accurate characterization of the repertoire of the T-cell receptor (TCR) alpha and beta chains is critical to understanding adaptive immunity. Such characterization has many applications across such fields as vaccine development and response, clone-tracking in cancer, and immunotherapy. Here we present a new methodology called single-cell TCRseq (scTCRseq) for the identification and assembly of full-length rearranged V(D)J T-cell receptor sequences from paired-end single-cell RNA sequencing reads. The method allows accurate identification of the V(D)J rearrangements for each individual T-cell and has the novel ability to recover paired alpha and beta segments. Source code is available at https://github.com/ElementoLab/scTCRseq.

Inflammation Thread Runs across Medical Laboratory Specialities

We work on the assumption that four major specialities or sectors of medical laboratory assays, comprising clinical chemistry, haematology, immunology, and microbiology, embraced by genome sequencing techniques, are routinely in use. Medical laboratory markers for inflammation serve as model: they are allotted to most fields of medical lab assays including genomics. Incessant coding of assays aligns each of them in the long lists of big data. As exemplified with the complement gene family, containing C2, C3, C8A, C8B, CFH, CFI, and ITGB2, heritability patterns/risk factors associated with diseases with genetic glitch of complement components are unfolding. The C4 component serum levels depend on sufficient vitamin D whilst low vitamin D is inversely related to IgG1, IgA, and C3 linking vitamin sufficiency to innate immunity. Whole genome sequencing of microbial organisms may distinguish virulent from nonvirulent and antibiotic resistant from nonresistant varieties of the same species and thus can be listed in personal big data banks including microbiological pathology; the big data warehouse continues to grow.

Genetics and immunity in the era of single-cell genomics

Recent developments in the field of single-cell genomics (SCG) are changing our understanding of how functional phenotypes of cell populations emerge from the behaviour of individual cells. Some of the applications of SCG include the discovery of new gene networks and novel cell subpopulations, fine mapping of transcription kinetics, and the relationships between cell clonality and their functional phenotypes. Immunology is one of the fields that is benefiting the most from such advancements, providing us with completely new insights into mammalian immunity. In this review, we start by covering new immunological insights originating from the use of single-cell genomic tools, specifically single-cell RNA-sequencing. Furthermore, we discuss how new genetic study designs are starting to explain inter-individual variation in the immune response. We conclude with a perspective on new multi-omics technologies capable of integrating several readouts from the same single cell and how such techniques might push our biological understanding of mammalian immunity to a new level.

search.bioPreprint: a discovery tool for cutting edge, preprint biomedical research articles

The time it takes for a completed manuscript to be published traditionally can be extremely lengthy. Article publication delay, which occurs in part due to constraints associated with peer review, can prevent the timely dissemination of critical and actionable data associated with new information on rare diseases or developing health concerns such as Zika virus. Preprint servers are open access online repositories housing preprint research articles that enable authors (1) to make their research immediately and freely available and (2) to receive commentary and peer review prior to journal submission. There is a growing movement of preprint advocates aiming to change the current journal publication and peer review system, proposing that preprints catalyze biomedical discovery, support career advancement, and improve scientific communication. While the number of articles submitted to and hosted by preprint servers are gradually increasing, there has been no simple way to identify biomedical research published in a preprint format, as they are not typically indexed and are only discoverable by directly searching the specific preprint server websites. To address this issue, we created a search engine that quickly compiles preprints from disparate host repositories and provides a one-stop search solution. Additionally, we developed a web application that bolsters the discovery of preprints by enabling each and every word or phrase appearing on any web site to be integrated with articles from preprint servers. This tool, search.bioPreprint, is publicly available at http://www.hsls.pitt.edu/resources/preprint.