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VDJ sequencing in mice, DNA or RNA?

VDJ sequencing in mice, DNA or RNA?



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I am wondering if anyone who is well versed with VDJ sequencing for TCR repertoire analysis (specifically CDR3) would know if DNA or RNA is a better starting material? We are looking at the effects of radiation therapy on immune system of mice. Thanks


Immunoglobulin heavy chain gene replacement: A mechanism of receptor editing

We have generated a site-directed transgenic (sd-tg) mouse model in which the JH locus has been replaced with a rearranged VDJ coding for the heavy chain of an anti-DNA antibody. In these mice, B cells expressing the anti-dsDNA specificity are negatively regulated. We observe a novel mechanism for B cell tolerance, receptor editing at the heavy chain locus. In most sd-tg B cells, the inserted anti-DNA VH gene has been replaced by the upstream endogenous VH, or DH, or both genes through recombination with the heptamer embedded at the 3′ end of most VH genes. Three types of recombination events have been identified: VH-to-VDJ, DH-to-VDJ, and VH-to-DH-VDJ. Analysis of the junctional sequences revealed features of classical V(D)J rearrangement, namely N sequence addition and nucleotide deletion. A conserved nonamer was found 12 by upstream of the embedded heptamer. This nonamer may represent a novel recombination signal sequence used for VH editing. The sd-tg model thus provides direct evidence for secondary rearrangement at VH-D-JH. This process may play a role in tolerance by editing autoreactive receptors and may also serve to diversity the VH repertoire.


"To see this dramatic response in our progeria mouse model is one of the most exciting therapeutic developments I have been part of in 40 years as a physician-scientist."

- Francis Collins, Director of the National Institutes of Health and Senior Investigator at the National Human Genome Research Institute

Cohorts of mice were given a single injection three days or 14 days after birth with adeno-associated viruses that encoded the base editor. By six weeks of age, the gene correction was found in multiple organs at levels ranging from about 10 to 60 percent.

By six months, key organs including the heart of animals injected with base editor contained much lower levels of progerin than the saline-injected control mice with progeria. In addition, while the aorta of control mice showed extensive loss of vascular smooth muscle cells and high levels of adventitial fibrosis — the accumulation of fibrotic cells around the aorta — the aorta of mice injected with the base editor appeared similar to samples from healthy mice.

“We saw this unexpected, nearly complete, rescue of pathology in the aorta,” said Liu. “We did a number of follow-up experiments to make sure we weren't being misled. The aorta samples were nearly indistinguishable from normal mouse samples, which was stunning. Cells from the base-edited mice were making the corrected human lamin A protein instead of progerin.”

The base editing injection also greatly extended the lifespan of the treated mice and improved their vitality. A healthy mouse lives for about two years. The treated mice survived to a median of 510 days, which corresponds to the beginning of old age — and is more than double the length of time that the untreated mice lived.

The dramatic extension in lifespan in the treated mice “was a really profound result,” Brown said, “because kids with progeria die early from vascular disease. They suffer from heart attacks and strokes.”

”When my research lab identified the genetic cause of progeria in 2003, we hoped that someday this might lead to a way to help these children,” said Collins. “Along the way, we’ve made some progress with drug therapy, but the potential of actually correcting the fundamental cause at the DNA level is beyond anything we could have imagined back then. To see this dramatic response in our progeria mouse model is one of the most exciting therapeutic developments I have been part of in 40 years as a physician-scientist.”

“As a physician-scientist, it’s incredibly exciting to think that an idea you’ve been working on in the laboratory might actually have a therapeutic impact,” said Brown. “Ultimately, our goal will be to try to develop this approach for humans, although there are remaining questions that we need to address first in these model systems.”

While the team did not observe significant off-target edits from the base editor, a number of the longest-living treated mice developed liver tumors — a known long-term complication when using adeno-associated viruses to deliver genes into mice.

Additional safety and efficacy studies are underway to further examine these results and investigate potential ways to mitigate the risks. The results of the work are being taken forward into further preclinical studies, with the eventual goal of launching a clinical trial.

“This work also provides a blueprint for the potential treatment of other genetic diseases that can be addressed with base editing,” says Liu. “It amplifies not only our excitement, but also our sense of responsibility to continue to do careful science while offering patients the best possible chance to benefit.”

This research was supported in part by the Progeria Research Foundation, National Institutes of Health (U01AI142756, UG3AI150551, UG3TR002636, RM1HG009490, R01EB022376, R35GM118062, Z01HG200305, R01HL146654, R01HL126784), intramural support from project ZIA HG 200-305-18, and the Howard Hughes Medical Institute.

Paper cited: Koblan LW, Erdos MR, et al. In vivo adenine base editing rescues Hutchinson-Gilford progeria syndrome. Nature. Online January 6, 2021. DOI: 10.1038/s41586-020-03086-7


VDJ sequencing in mice, DNA or RNA? - Biology

Antigen presentation and recognition is central to immunology. HLA genes encode the proteins that present antigens. VDJ genes encode the receptors: T cell receptors (TCRs) in T cells and the repertoires of antibodies/immunoglobulins in B cells.

Here, researchers can find links to tools and resources for computational analysis of HLA and VDJ data.

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Table of Contents

Robson, K. J., Ooi, J. D., Holdsworth, S. R., Rossjohn, J. & Kitching, A. R. HLA and kidney disease: from associations to mechanisms. Nat. Rev. Nephrol. 14, 636–655 (2018)

La Gruta, N. L., Gras, S., Daley, S. R., Thomas, P. G. & Rossjohn, J. Understanding the drivers of MHC restriction of T cell receptors. Nat. Rev. Immunol. 18, 467–478 (2018)

Adaptive Immune Receptor Repertoire (AIRR) Community

The Adaptive Immune Receptor Repertoire (AIRR) Community of The Antibody Society is a research-driven group that is organizing and coordinating stakeholders in the use of next-generation sequencing technologies to study antibody/B-cell and T-cell receptor repertoires. Recent advances in sequencing technology have made it possible to sample the immune repertoire in exquisite detail. AIRR sequencing (AIRR-seq) has enormous promise for understanding the dynamics of the immune repertoire in vaccinology, infectious diseases, autoimmunity, and cancer biology, but also poses substantial challenges. The AIRR Community was established to meet these challenges.

A Public Database of Memory and Naive B-Cell Receptor Sequences

We present a public database of more than 37 million unique BCR sequences from three healthy adult donors that is many fold deeper than any existing resource, together with a set of online tools designed to facilitate the visualization and analysis of the annotated data.

Coronavirus-Binding Antibody Sequences & Structures

The Oxford Protein Informatics Group (Dept. of Statistics, University of Oxford) is collaborating in efforts to understand the immune response to SARS-CoV2 infection and vaccination. As part of our investigations, we are releasing and maintaining this public database to document all published/patented binding antibodies and nanobodies to coronaviruses, including SARS-CoV2, SARS-CoV1, and MERS-CoV.

Human Vaccines Project (Human Immunome Program)

The Human Immunome Program (HIP) is open-source effort with the goal sequencing all of the adaptive receptors on the surface of human B and T cells. Under a targeted 7-to-10-year effort, the program will sequence these receptors from a group of globally diverse individuals, and determine the structure and function of a key subset of receptors. Through an open-source approach, this data will be made available to researchers across the world.

Dive into the world’s largest collection of TCR and BCR sequences. Easily incorporate millions of sequences worth of public data into your next papers and projects using immunoSEQ Analyzer. Construct your own projects, draw your own conclusions, and freely publish new discoveries.

See these instructions for tips on how to download data from immuneACCESS.

iReceptor facilitates the curation, analysis and sharing of antibody/B-cell and T-cell receptor repertoires (Adaptive Immune Receptor Repertoire or AIRR-seq data) from multiple labs and institutions. We are committed to providing a platform for researchers to increase the value of their data through sharing with the community. This will greatly increase the amount of data available to answer complex questions about the adaptive immune response, accelerating the development of vaccines, therapeutic antibodies against autoimmune diseases, and cancer immunotherapies.

McPAS-TCR: A manually curated catalogue of pathology associated T-cell receptor sequences

McPAS-TCR is a manually curated catalogue of T cell receptor (TCR) sequences that were found in T cells associated with various pathological conditions in humans and in mice. It is meant to link TCR sequences to their antigen target or to the pathology and organ with which they are associated.

PIRD: Pan immune repertoire database

Pan immune repertoire database (PIRD) collects raw and processed sequences of immunoglobulins (IGs) and T cell receptors (TCRs) of human and other vertebrate species with different phenotypes. You can check the detailed information of each sample in the database, choose samples to analyze according to your need, and upload data to analyze. Your analysis results will be auto-saved, so you can return to check them at any time. PIRD is developed by the immune and health lab of BGI-research.

Zhang, W. et al. PIRD: Pan Immune Repertoire Database. Bioinformatics 36, 897–903 (2020)

STCRDab: The Structural T-Cell Receptor Database

An automated, curated set of T-Cell Receptor structural data from the PDB.

TCR3d: T cell receptor structural repertoire database

Welcome to the T cell receptor (TCR) structural repertoire database. Here we provide an easy-to-use interface to view all experimentally determined T cell receptor structures and their complexes. This includes complementarity determining region loops and analysis of interfaces with antigenic peptide and MHC.

We have also assembled a set of known TCR sequences from recent studies including TCR repertoire sequencing efforts.

The major goal of this site is to enable insights into the basis of TCR structure and recognition, to assist efforts in predictive modeling of this key component of the adaptive immune response, and to facilitate rational engineering of improved and novel immunotherapeutics.

VDJDB: A curated database of T-cell receptor sequences of known antigen specificity

The primary goal of VDJdb is to facilitate access to existing information on T-cell receptor antigen specificities, i.e. the ability to recognize certain epitopes in certain MHC contexts.

Our mission is to both aggregate the scarce TCR specificity information available so far and to create a curated repository to store such data.

ALICE: Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences

Detecting TCR involved in immune responses from single RepSeq datasets.

CONGA: Clonotype Neighbor Graph Analysis

Python scripts and C++ code

CONGA was developed to detect correlation between T cell gene expression profile and TCR sequence in single-cell datasets.

ClusTCR: a Python interface for rapid clustering of large sets of CDR3 sequences with unknown antigen specificity

CDR3 clustering module providing a new method for fast and accurate clustering of large data sets of CDR3 amino acid sequences, and offering functionalities for downstream analysis of clustering results.

A two-step clustering approach that combines the speed of the Faiss Clustering Library with the accuracy of Markov Clustering Algorithm On a standard machine*, clusTCR can cluster 1 million CDR3 sequences in under 5 minutes.

DeepTCR: Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data

DeepTCR is a python package that has a collection of unsupervised and supervised deep learning methods to parse TCRSeq data. It has the added functionality of being able to analyze paired alpha/beta chain inputs as well as also being able to take in v/d/j gene usage and the contextual HLA information the TCR-Sequences were seen in (i.e. HLA alleles for a repertoire from a given human sample).

dkm: Dynamic Kernel Matching

DKM is analogous to a convolutional network, but for sequences. Consider the problem of classifying a sequence. Because some sequences are longer than others, the number of features is irregular. Given a specific sequence, the challenge is to determine the appropriate permutation of features with weights, allowing us to run the features through the statistical classifier to generate a prediction. To find the permutation of features that exhibit the maximal response, like how max-pooling identifies the image patch that exhibit the maximal response, we use a sequence alignment algorithm.

enclone is standalone software (primarily written in Rust) developed by 10x Genomics for analysis of single cell TCR and BCR sequences. enclone performs SHM-aware clonotyping, phylogenetic/lineage analysis, multiple sequence alignment, and provides an extremely fast interface to analyze, display, and export VDJ, gene expression, and feature barcoding (REAP-seq, CITE-seq, ECCITE-seq, LIBRA-seq, PERTURB-seq, etc.) data.

immunarch: An R Package for Painless Bioinformatics Analysis of T-cell and B-cell Immune Repertoire Data

immunarch is an R package designed to analyse T-cell receptor (TCR) and B-cell receptor (BCR) repertoires, aimed at medical scientists and bioinformaticians. The mission of immunarch is to make immune sequencing data analysis as effortless as possible and help you focus on research instead of coding. Follow us on Twitter for news and updates.

immuneSIM: Tunable Simulation of B- And T-Cell Receptor Repertoires

Simulate full B-cell and T-cell receptor repertoires using an in silico recombination process that includes a wide variety of tunable parameters to introduce noise and biases. Additional post-simulation modification functions allow the user to implant motifs or codon biases as well as remodeling sequence similarity architecture. The output repertoires contain records of all relevant repertoire dimensions and can be analyzed using provided repertoire analysis functions. Preprint is available at bioRxiv (Weber et al., 2019 doi:10.1101/759795).

ImReP: Rapid and accurate profiling of the adaptive immune repertoires from regular RNA-Seq data

ImReP is a method to quantify individual immune response based on a recombination landscape of genes encoding B and T cell receptors (BCR and TCR). ImReP is able to efficiently extract TCR and BCR reads from the RNA-Seq data and assemble clonotypes (defined as clones with identical CDR3 amino acid sequences) and detect corresponding V(D)J recombinations. Using CAST clustering technique, ImReP is able to correct assembled clonotypes for PCR and sequencing errors.

IMSEQ: IMmunogenetic SEQuence Analysis

IMSEQ is a fast, PCR and sequencing error aware tool to analyze high throughput data from recombined T-cell receptor or immunoglobolin gene sequencing experiments. It derives immune repertoires from sequencing data in FASTA / FASTQ format.

MiGMAP: mapper for full-length T- and B-cell repertoire sequencing

In a nutshell, this software is a smart wrapper for IgBlast V-(D)-J mapping tool designed to facilitate analysis immune receptor libraries profiled using high-throughput sequencing. This package includes additional experimental modules for contig assembly, error correction and immunoglobulin lineage tree construction.

MiXCR: a universal tool for fast and accurate analysis of T- and B- cell receptor repertoire sequencing data

MiXCR is a universal framework that processes big immunome data from raw sequences to quantitated clonotypes. MiXCR efficiently handles paired- and single-end reads, considers sequence quality, corrects PCR errors and identifies germline hypermutations. The software supports both partial- and full-length profiling and employs all available RNA or DNA information, including sequences upstream of V and downstream of J gene segments.

Python scripts and Jupyter notebooks

A multi-view Variational Autoencoder (mvTCR) to jointly embed transcriptomic and TCR sequence information at a single-cell level to better capture the phenotypic behavior of T cells.

PRESTO: The REpertoire Sequencing TOolkit

pRESTO is a toolkit for processing raw reads from high-throughput sequencing of B cell and T cell repertoires.

The REpertoire Sequencing TOolkit (pRESTO) is composed of a suite of utilities to handle all stages of sequence processing prior to germline segment assignment. pRESTO is designed to handle either single reads or paired-end reads. It includes features for quality control, primer masking, annotation of reads with sequence embedded barcodes, generation of unique molecular identifier (UMI) consensus sequences, assembly of paired-end reads and identification of duplicate sequences. Numerous options for sequence sorting, sampling and conversion operations are also included.

pyIR: An IgBLAST wrapper and parser

PyIR is a minimally-dependent high-speed wrapper for the IgBLAST immunoglobulin and T-cell analyzer. This is achieved through chunking the input data set and running IgBLAST single-core in parallel to better utilize modern multi-core and hyperthreaded processors.

Recon: Reconstruction of Estimated Communities from Observed Numbers

Recon uses the distribution of species counts in a sample to estimate the distribution of species counts in the population from which the sample was drawn.

scirpy: A scanpy extension to analyse single-cell TCR data.

Scirpy is a scalable python-toolkit to analyse T cell receptor (TCR) repertoires from single-cell RNA sequencing (scRNA-seq) data. It seamlessly integrates with the popular scanpy library and provides various modules for data import, analysis and visualization.

scRepertoire: A toolkit for single-cell immune profiling

scRepertoire v1.0.0 added the functionality of the powerTCR approach to comparing clone size distribution, please cite the manuscript if using the clonesizeDistribution() function. Similiarly, the application of novel indices for single-cell clonotype dynamics in the StartracDiversity() function is based on the work from Lei Zhang et al.

Software tools for the analysis of epitope-specific T cell receptor (TCR) repertoires

TRUST4: TCR and BCR assembly from RNA-seq data

Tcr Receptor Utilities for Solid Tissue (TRUST) is a computational tool to analyze TCR and BCR sequences using unselected RNA sequencing data, profiled from solid tissues, including tumors. TRUST4 performs de novo assembly on V, J, C genes including the hypervariable complementarity-determining region 3 (CDR3) and reports consensus of BCR/TCR sequences. TRUST4 then realigns the contigs to IMGT reference gene sequences to report the corresponding information. TRUST4 supports both single-end and paired-end sequencing data with any read length.

Song L, Cohen D, Ouyang Z, Cao Y, Hu X, Shirley Liu X. TRUST4: immune repertoire reconstruction from bulk and single-cell RNA-seq data. Nat Methods. Nature Publishing Group 2021 May 131–4.

vampire: Deep generative models for TCR sequences

Fit and test variational autoencoder (VAE) models for T cell receptor sequences.

A comprehensive analysis framework for T-cell and B-cell repertoire sequencing data

IEDB: Immune Epitope Database and Analysis Resource

The Immune Epitope Database (IEDB) is a freely available resource funded by NIAID. It catalogs experimental data on antibody and T cell epitopes studied in humans, non-human primates, and other animal species in the context of infectious disease, allergy, autoimmunity and transplantation. The IEDB also hosts tools to assist in the prediction and analysis of epitopes.

The IPD-IMGT/HLA Database provides a specialist database for sequences of the human major histocompatibility complex (MHC) and includes the official sequences named by the WHO Nomenclature Committee For Factors of the HLA System. The IPD-IMGT/HLA Database is part of the international ImMunoGeneTics project (IMGT).

The database uses the 2010 naming convention for HLA alleles in all tools herein. To aid in the adoption of the new nomenclature, all search tools can be used with both the current and pre-2010 allele designations. The pre-2010 nomenclature designations are only used where older reports or outputs have been made available for download.

arcasHLA: Fast and accurate in silico inference of HLA genotypes from RNA-seq

arcasHLA performs high resolution genotyping for HLA class I and class II genes from RNA sequencing, supporting both paired and single-end samples.

HATK: HLA Analysis Toolkit

HATK(HLA Analysis Tool-Kit) is a collection of tools and modules to perform HLA fine-mapping analysis, which is to identify which HLA allele or amino acid position of the HLA gene is driving the disease.

HLA-LA: Fast HLA type inference from whole-genome data

HLA typing based on a population reference graph and employs a new linear projection method to align reads to the graph.

HLA-TAPAS: HLA-Typing At Protein for Association Studies

An HLA-focused pipeline that can handle HLA reference panel construction (MakeReference), HLA imputation (SNP2HLA), and HLA association (HLAassoc). It is an updated version of the SNP2HLA.

HLAProfiler: Using k-mers to call HLA alleles in RNA sequencing data

HLAProfiler uses the k-mer content of next generation sequencing reads to call HLA types in a sample. Based on the k-mer content each each read pair is assigned to an HLA gene and the aggregate k-mer profile for the gene is compared to reference k-mer profiles to determin the HLA type. Currently HLAProfiler only supports paired-end RNA-seq data.

MATER: Minimizer RNAseq HLA typer

Python scripts and C code

MATER is a minimizer-based HLA typer for RNAseq read dataset. In a typical RNAseq dataset, the reads sampled from HLA genes are less uniform and may miss regions that makes assembly or variant calling base methods for HLA typing more challenge. Here we adopt a slight different approach. We try to assign each reads to possible HLA types by using minimizers. Namely, we will generate dense minimizer for each reads and compare to those from the HLA type seqeunces.

We annotate each each reads to possible HLA serotype or 4 digit type sequence according the minimizer matches. Some reads may be able to assign to single HLA type-sequence, some other may be more ambiguous. We derive a simple score to summarize the results from all reads that are mapped to HLA-type sequences for each HLA allele.

MultiHLA: WES HLA Typing based on multiple alternative tools

This workflow enables the concurrent analysis of WES or WGS data using publicly available software to derive HLA haplotypes from this type of data. It includes automated Snakemake workflows for the following tools: xHLA, HLA-VBSeq, OptiType, HLA-LA, arcasHLA

OptiType: Precision HLA typing from next-generation sequencing data

OptiType is a novel HLA genotyping algorithm based on integer linear programming, capable of producing accurate 4-digit HLA genotyping predictions from NGS data by simultaneously selecting all major and minor HLA Class I alleles.

PHLAT: Inference of High Resolution HLA Types

PHLAT is a bioinformatics algorithm that offers HLA typing at four-digit resolution (or higher) using genome-wide transcriptome and exome sequencing data over a wide range of read lengths and sequencing depths.

seq2HLA: HLA typing from RNA-Seq sequence reads

In-silico method written in Python and R to determine HLA genotypes of a sample. seq2HLA takes standard RNA-Seq sequence reads in fastq format as input, uses a bowtie index comprising all HLA alleles and outputs the most likely HLA class I and class II genotypes (in 4 digit resolution), a p-value for each call, and the expression of each class.

SNP2HLA: Imputation of Amino Acid Polymorphisms in Human Leukocyte Antigens

SNP2HLA is a tool to impute amino acid polymorphisms and single nucleotide polymorphisms in human luekocyte antigenes (HLA) within the major histocompatibility complex (MHC) region in chromosome 6.


Generation of gene-modified mice via Cas9/RNA-mediated gene targeting

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) adaptive immune systems are found in bacteria and archaea to protect the hosts against the invasion of viruses and plasmids 1,2,3 . Three types (I-III) of CRISPR systems with different features have been identified. The CRISPR-associated protein Cas9 that belongs to the type II CRISPR/Cas system has attracted much attention due to its potential use in genomic engineering. Cas9 contains one HNH motif and three RuvC-like motifs, homologous to HNH and RuvC endonucleases, respectively (Supplementary information, Figure S1) 4,5,6,7,8 . Recent studies showed that Cas9 displayed strong DNA cleavage activity in bacteria and in test tubes. Its nuclease activity is guided by two non-coding RNA elements of the system one is crRNA (CRISPR RNA) that contains about 20 base pairs (bp) of unique target sequence (called spacer sequence) and the other is tracrRNA (trans-activating crRNA). These two RNA elements form a crRNA:tracrRNA duplex that directs Cas9 to target DNA via complementary base pairing between the spacer on the crRNA and the complementary sequence (called protospacer) on the target DNA. The 3 nucleotides (nt) located immediately at the 3′ side next to the protospacer sequence constitute the protospacer adjacent motif (PAM) that is required to ensure the cleavage specificity in target sequences 9,10 .

Theoretically, CRISPR systems can be used in higher eukaryotes through ectopically expressing the enzyme (Cas9) and the RNAs, much like the zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) (Figure 1A). To test this, we first asked whether Cas9 could perform DNA cleavage in zebrafish. We generated codon-optimized Cas9 (Supplementary information, Table S1 and Data S2) and cloned it into an expression vector. A chimeric RNA that is a single engineered RNA molecule combining features of both crRNA and tracrRNA 9 was designed to target one of the two sites (EGFP-A and -B) in the pEGFP-N1 plasmid (Figure 1B, Supplementary information, Figures S2 and S3). DNA fragments corresponding to Cas9 and the chimeric RNA were transcribed to RNAs in vitro by the T7 RNA polymerase and the Cas9 RNA was further modified by adding a translation-required cap at the 5′-end and a poly-A tail at the 3′-end to make it resemble an authentic mRNA. The Cas9 mRNA, chimeric RNA, and pEGFP-N1 plasmid were co-injected into one-cell zebrafish embryos. Similar strategies have previously been employed to test ZFN and TALEN activity 11,12 . The embryos were cultured for 12 h before being harvested for total DNA extraction.

Cas9/RNA-mediated gene targeting. (A) Schematic diagram of Cas9/RNA-mediated gene targeting. Chimeric RNA, a single engineered RNA molecule combining crRNA and tracrRNA, can guide Cas9 to cleave the target site of ∼ 20 nt. PAM, an NGG motif shown in purple, is essential for the activity of the complex. (B) Schematic representation of EGFP-A chimeric RNA (chiRNA) binding to pEGFP-N1 plasmid through spacer sequence. PAM is highlighted in purple. (C) Chimeric RNA guides Cas9 to cleave pEGFP-N1 at the target site in zebrafish. Four hundred nanograms per litre of Cas9 mRNA, 100 ng/μl of EGFP-A chimeric RNA, and pEGFP-N1 plasmid were co-injected into one-cell zebrafish embroys. Cleavage assays were performed 12 h after injection. Arrowheads indicate that two cleavage bands (about 295 bp and 198 bp) were detected in zygotes treated with Cas9 and non-annealed EGFP-A chimeric RNA. The Cas9 and chimeric RNA were added as indicated. (D) Sequencing results of T-A colonies of targeted fragments amplified from the sample of lane 4 in C. Two colonies with 1-bp insertion were detected in 48 colonies. Target sequence is capitalized and highlighted in red. Red lower case represents insert sequence. (E) PCR amplification of targeted fragment in the EGFP gene in founder mice treated with Cas9/RNA microinjection. Founder mice were generated as described in Supplementary information, Data S1. PCR amplification of the targeted fragment was performed using genomic DNA extracted from the tails of the founders as templates. Primers used were listed in Supplementary information, Figure S2. Arrowhead indicates a truncated band in founder #5. Ng, negative control. (F) The PCR products from founder #5 were subjected to T-A cloning. Twenty colonies were randomly selected for DNA sequencing. A 108-bp deletion was detected in nine colonies. Target sequence is capitalized and highlighted in red.

The targeted region on the EGFP plasmid was amplified from the extracted DNA the purified PCR products were then denatured and reannealed to form hybridized DNA, followed by digestion with the T7 endonuclease 1 (T7EN1) 13 that can recognize and cleave mismatched DNA (Supplementary information, Figure S4). Gel electrophoresis of T7EN1-digestion products clearly showed two smaller fragments besides the amplicon of the targeted region, which were not observed in the control (Figure 1C and Supplementary information, Figure S3), suggesting that the target DNA was cleaved by Cas9. To precisely locate the site of cleavage, we cloned the PCR products and analyzed the clones by DNA sequencing. There were 2 mutant clones out of 48 sequenced. The cutting occurred about 4 nt away from the PAM (Figure 1D). These results demonstrate that Cas9/RNA can site-specifically cut DNA in eukaryotic cells.

To improve the cutting efficiency of the Cas9 and chimeric RNA module, we annealed the chimeric RNA before injection to facilitate its correct folding. Indeed, T7EN1 cleavage assay showed that using preannealed chimeric RNA in the Cas9 system generated stronger cleavage bands. Consistently, more mutants (3 out of 46 PCR clones) were detected by DNA sequencing. Similarly, the cutting occurred about 4 nt away from the PAM (Supplementary information, Figure S5). These results suggest that the conformation of the chimeric RNA probably affects the activity of the Cas9 complex.

Different from prokaryotes, targeting eukaryotic DNA requires nuclear translocation of the nucleases. As expected, when expressed in the mammalian cell line 293T, the prokaryote-derived Cas9 was only detected in cytoplasm despite the addition of an SV40 nuclear localization signal (NLS) to the N- or both the N- and C-termini of Cas9. Even the addition of a triple NLS to the N-terminus did not work (Supplementary information, Figure S6). The reason might be that the NLS peptide was buried or shielded during the folding of the Cas9 protein. To circumvent this, we added a linker (32 amino acids) between the NLS and Cas9, which resulted in the successful nuclear localization of Cas9 (Supplementary information, Figure S6). We tested the cleavage activity of all tagged-Cas9s and found that, as expected, NLS-flag-linker-Cas9 displayed enhanced cleavage activity (Supplementary information, Figure S7).

The cleavage of exogenous DNA in zebrafish embryos encouraged us to test whether Cas9/RNA could be used to site-specifically disrupt endogenous genes in mice, as has been achieved with ZFN and TALEN. We first used the Pouf5-IRES-EGFP knock-in mouse line that carries one copy of the EGFP gene incorporated into the mouse genome. Twenty nanograms per microlitre of NLS-flag-linker-Cas9 mRNA and 20 ng/μl preannealed EGFP-A chimeric RNA were co-injected into one-cell mouse embryos obtained from the crosses between male homozygous Pouf5-IRES-EGFP knock-in mice and superovulated C57BL/6J female mice. Twenty-four injected embryos were transferred into pseudopregnant CD1 female mice and five live animals were born so far. As the Pouf5-IRES-EGFP male mice that we used were homozygous for the knock-in gene, all five founder mice were, as expected, genotyped as heterozygous, indicated by PCR amplification of a knock-in fragment using genomic DNA extracted from the tails of the founders 5 days after birth (Supplementary information, Figure S8). Site-specific cleavage of the endogenous EGFP locus was first analyzed by PCR amplification of the target site using the same tail genomic DNA as used in genotyping. As shown in Figure 1E, a smaller amplicon appeared in founder #5, whereas no mutant bands were detected in the PCR products of founders #1-4. Twenty T-A colonies of the PCR products from founder #5 were randomly picked for DNA sequencing. A 108-bp deletion was detected in nine colonies (Figure 1F). No mutations were detected in the remaining 11 colonies (data not shown). Further analyses by the T7EN1 cleavage assay and DNA sequencing did not detect mutations of the target region in founders #1-4 (data not shown). These results indicate that the Cas9/RNA system induced a site-specific cleavage on endogenous single-copied EGFP. Given the presence of the wild-type amplicon besides the mutant one, fonder #5 is mosaic for the mutant EGFP, which suggests that the cleavage and subsequent repair occurred after the first division of the injected one-cell embryo. It is noteworthy that similar to ZFN and TALEN, Cas9/RNA-induced double-stranded break leads to nonhomologous end joining-mediated repair, which generates indels (insertions or deletions) of different sizes around the DNA break site. The 108-bp deletion within the EGFP gene in the mouse model only represents one case it is likely that more indels of different sizes would be found upon screenings of more founder mice treated with Cas9/RNA.

Next, we tested the efficiency of the same targeting strategy in another EGFP mouse line (CAG-EGFP, with multiple copies of the transgene). Seven pups were born from 51 injected embryos and one of them (#4) contained disrupted EGFP as shown by the T7EN1 cleavage assay (Supplementary information, Figure S9). PCR products from #4 were cloned and sequenced. Eleven out of 50 clones contained mutations. Interestingly, we detected six mutant forms, indicating that Cas9/RNA-mediated cleavage had occurred multiple times on different copies of the EGFP transgene in the same embryo (Supplementary information, Figure S9). Taken together, we demonstrated that Cas9/RNA can induce site-specific cleavage of chromosomal loci in the mouse genome.

In summary, our findings demonstrate that Cas9/RNA can site-specifically cut DNA in zebrafish and mouse embryos, paving the way for its use in the generation of gene-disrupted animals. During the preparation of this manuscript, two papers were published in Science, reporting the use of the Cas9/RNA system in mammalian cells 14,15 . Our study goes beyond cultured cells and shows the utility of the Cas9/RNA as a genetic tool in generating genetically engineered mice and, potentially, other mammals. Different from ZFN and TALEN, the Cas9/RNA system is RNA-guided and easy to engineer, offering better flexibility as a genomic engineering tool. The fact that this system uses RNA to guide DNA cleavage points to its potential use in large-scale genetic screenings, as a library of guide RNAs can be constructed.


Human chromosome 7: DNA sequence and biology

DNA sequence and annotation of the entire human chromosome 7, encompassing nearly 158 million nucleotides of DNA and 1917 gene structures, are presented. To generate a higher order description, additional structural features such as imprinted genes, fragile sites, and segmental duplications were integrated at the level of the DNA sequence with medical genetic data, including 440 chromosome rearrangement breakpoints associated with disease. This approach enabled the discovery of candidate genes for developmental diseases including autism.

Figures

DNA sequence comparison of CRA_TCAGchr7.v1…

DNA sequence comparison of CRA_TCAGchr7.v1 against NCBI Build 31. Black circles represent the…

Six mouse chromosomes with synteny…

Six mouse chromosomes with synteny to human chromosome 7, 12 syntenic breakpoints overlapping…

Distribution of 1917 gene structures…

Distribution of 1917 gene structures and 20 putative gene deserts on chromosome 7.

Recent segmental duplications on chromosome…

Recent segmental duplications on chromosome 7. Graphical views (using GenomePixelizer) of paralogous relationships…

The distribution of 1570 cytogenetic…

The distribution of 1570 cytogenetic rearrangement breakpoints (850 constitutional and 720 malignancy-associated) from…

The SHFM1 region at 7q21.3,…

The SHFM1 region at 7q21.3, as an example of information in the chromosome…


THE GENERATION OF ANTIBODY REPERTOIRE: A RISKY DIVERSITY

The error-prone V(D)J recombination process

Ig genes are good candidates to study nonsense RNA surveillance because the generation of primary Ig repertoire in early B-cell development and the process of somatic hypermutations (SHM) in germinal center B cells frequently generate PTCs (1). The V(D)J recombination process of Ig genes takes place in the bone marrow and assembles the variable region from germline variable (V), diversity (D), and joining (J) gene segments. Control of V(D)J recombination occurs at several levels, including cell-type specificity, intra-and inter-locus sequential rearrangements, and allelic exclusion (17). Although DNA rearrangements in the Ig heavy (IgH) and light (i.e. Igκ and Igλ) loci occur in a precise order, the selection of gene segments within each locus is random. It allows for combinatorial diversity. The mechanism used by lymphoid cells to successfully rearrange their antigen (Ag) receptor genes requires the use of recombinase enzymes RAG1 & RAG2 that are only active in lymphocytes (18, 19). Recombinases act at early stages of lymphoid cell development in order to bring two segments into close proximity, forming a loop of intervening DNA which can then be excised. The ends of these segments are annealed to form a newly rearranged DNA sequence. To increase diversity, joining of V, D, and J segments is imprecise with nucleotide deletions or insertions. Non-template (N) nucleotide additions are introduced by terminal deoxynucleotidyl transferase (TdT). Palindromic (P) insertions occur after asymmetric hairpin opening. Random N-additions cannot be attributed to any other genomic sequences. They rarely exceed a dozen nucleotides (20, 21). They are polymerized by TdT which is the third lymphoid-specific protein involved in V(D)J recombination besides RAG1 and RAG2 (22�). P insertions rarely exceed two nucleotides and form a palindrome with respect to the sequence at the end of the coding strand (26�). Although nucleotide deletions and insertions greatly enlarge the diversity of the Ig repertoire, only one third of all V(D)J junctions are in-frame, while the other two thirds are out-of-frame due to frameshift mutations that create PTCs.

Frequency of PTC-containing Ig genes in B-lineage cells

Clonal selection implies that each B cell clone expresses a unique receptor. Hence, one of the two inherited Ig alleles is functionally rearranged. This allelic exclusion associates asynchronous V(D)J recombination events at Ig loci with receptor-mediated inhibitory feedback control (29). At the pro-B cell stage, VDJ recombination is initiated by biallelic D to J rearrangements at IgH loci, followed by a monoallelic V to DJ recombination. A productive VDJ junction encodes the variable (V) region of the μ heavy chain that can associate with the surrogate light chain to form pre-BCR (pre-B cell receptor). Regulatory mechanisms mediated by pre-BCR signaling prevent further V to DJ rearrangements on the second IgH allele and initiates VJ recombination at Ig light chain loci lacking D segments. By contrast, when the VDJ junction on the first IgH allele is nonproductive, the lack of the pre-BCR inhibitory signal allows V to DJ recombination on the second allele. If this second attempt is successful, a pre-BCR-mediated proliferation wave will generate abundant B cell clones with biallelic VDJ rearrangements. Roughly half of mature B cells harbor biallelic VDJ-rearrangements with a nonproductively-recombined IgH allele (30�). If another nonproductive VDJ junction occurs on the second IgH allele, cells are eliminated through apoptosis. As mentioned above, pre-BCR signaling stimulates recombination of Ig light chain genes. The presence of two Igκ and Igλ light chain isotypes permits multiple VJ recombination events. Again, the expression of a functional BCR precludes further recombination in immature B cells. In humans,

50% of mature B cells express Igλ. However, in mice, recombination takes places preferentially at the Igκ locus and only 5% of B cells express Igλ isotypes (32). Hence, B cells harbor numerous nonproductive VJ-recombined Ig light chain alleles ( Fig. 1 ).

Abundance of nonproductive V(D)J rearrangements in B-lineage cells. (A) Schematic representation of productive and nonproductive V(D)J rearrangements during the generation of primary antibody repertoire. V(D)J recombination is initiated by a monoallelic V to DJ recombination at the IgH locus (biallelic D–J rearrangements are not depicted). If successful, then V to J recombination occurs at Ig light chain (IgL) loci. Successive IgL rearrangements are possible due to the fact that there are two Igκ and two Igλ alleles (not depicted). Pre-B cell receptor (pre-BCR) or BCR-mediated feedback signalling upon in-frame rearrangement of one IgH or IgL allele (i.e., VDJ+ or VJ+) prevents V(D)J recombination on the second allele (32). By contrast, a nonproductive V(D)J recombination on one Ig allele (i.e. VDJ− or VJ−) induces rearrangement on the second allele. The imprecise nature of V(D)J junctions generates

2/3 of nonproductive V(D)J-rearranged alleles. Hence, most B-lineage cells harbour nonproductively-recombined Ig alleles in their genome (red parts in pie charts). If the two attempts on both Ig alleles are unsuccessful, the cell is programmed to die by apoptosis (dashed circles). (B) PTCs introduced during the error-prone V(D)J recombination process (red stars) or by somatic hypermutations (SHM yellow stars) can activate different modes of NMD degradation. Frameshift V(D)J junctions can lead to the appearance of PTCs in the variable (V) exon or in the downstream adjacent constant exon. SHM can lead to the appearance of PTCs in the first leader exon (L1: L-part1) or in the V exon, with a greater abundance in the complement-determining regions (CDRs). For IgH mRNAs, PTC introduced by SHM or during V(D)J recombination can elicit exon junction complex (EJC)-dependent NMD. EJCs that remain bound to mRNAs after a pioneer round of translation are depicted (blue ovals). As good NMD candidates, PTC-containing IgH mRNAs are strongly degraded by NMD (up to 100-fold) (1, 9, 59). However, it has been demonstrated that some nonsense codons in the 5′-half of the VDJ exon could not elicit strong NMD degradation (73). Similarly, PTCs close to the initiation codon are NMD resistant in other models likely due to a critical interaction between PABPC1 with the translation initiation complex (74, 75). For nonproductive Igκ alleles, PTCs are located at the end of the V exon or within the last constant Cκ exon. Hence, these PTC-containing IgL mRNAs could not elicit EJC-dependent NMD degradation, although they are likely to be targeted by a PTC-PABC1 distance-dependent mode of NMD which induces a less efficient degradation (

After their exit from the bone marrow, alternative splicing of constant Cμ and Cδ exons ensures co-expression of IgM and IgD at the surface of naïve B cells (33). Upon antigen encounter, IgD expression is downregulated and activated B cells are subjected to a second wave of Ig gene diversification by SHM in germinal centers (GCs). Frequent nonsense mutations can arise during this affinity maturation process that requires transcription of the target region and enzymatic activity of B-cell-specific activation-induced deaminase AID (34). This process leads to the introduction of multiple nucleotide changes in the V exon (i.e., VDJ or VJ) and a few hundred base pairs in the downstream intron (35). Nucleotide insertions and deletions (indels) have also been observed (36, 37). SHM leads to the expression of a secondary repertoire from which B cells carrying a mutated BCR with improved Ag-binding affinity can be selected (38). We have previously observed that SHM occurs at similar levels on productive and nonproductive VDJ-rearranged IgH alleles (39). If a nonsense codon appears on the productive allele, the lack of Ag-binding activity provokes a rapid elimination of mutated B cell clones within GCs (40�). The occurrence of SHM on nonproductive Ig alleles can introduce additional nonsense codons, modifying the PTC position within the V exon. Class switch recombination (CSR) also occurs in germinal centers. This second round of IgH intragenic rearrangements replaces the Cμ exons with a downstream constant gene (43). GC B cells can differentiate into memory cells or terminally differentiated PCs that secrete substantial amounts of antibody (44). The PC transcriptional program induces major changes including a transcriptional boost of Ig gene transcription and the activation of unfolded protein response (UPR) to ensure proper Ig folding (45). In PCs, the use of secreted polyadenylation signal (PAS) instead of downstream membrane PAS allows alternative IgH pre-mRNA processing to switch from membrane to secreted Ig isoforms (46). Taken together, the vast majority of B-lineage cells harbor PTC+ Ig alleles in their genome with nonsense codons introduced in the V exon or in the adjacent constant exon during the V(D)J recombination process or SHM ( Fig. 1 ).

Transcriptional control of PTC-containing Ig genes

The high frequency of PTC+ V(D)J-rearranged Ig alleles in B-lineage cells needs additional mechanisms to downregulate these nonsense transcripts. A transcriptional silencing of PTC+ Ig genes has been proposed as a primary mechanism preventing their expression. This mechanism is called “nonsense-mediated transcriptional gene silencing” (NMTGS). It involves chromatin remodelling and “heterochromatinization” of the PTC+ DNA sequence. NMTGS can be inhibited by the overexpression of exonuclease. However, the involvement of siRNA like molecules has not been elucidated yet (4). NMTGS is also impaired upon knock-down of the main NMD factor UPF1, suggesting a mechanistic link between NMD and NMTGS (47). Although NMTGS has been demonstrated in Hela cells transfected with minigene constructs, the occurrence of such a quality control mechanism needs to be determined in B cells. Instead of active silencing, many studies including ours have shown a biallelic transcription pattern for productive and nonproductive Ig alleles in B cells (9, 39, 48�). To study the transcription and RNA surveillance of PTC+ IgH alleles during B cell development, we introduced a nonsense V exon in the IgH locus to specifically mark each allele in heterozygous mutants. Consistent with previous observations in a pro-B cell line (52), productive and nonproductive IgH alleles exhibited equivalent transcription rates with similar RNAPII loading in LPS-stimulated B cells (9, 48). This also confirms our earlier study in germinal center B cells, demonstrating that the frequency of transcription-dependent SHM is similar for productive and nonproductive VDJ-recombined IgH alleles (39).


Memory deficits, gait ataxia and neuronal loss in the hippocampus and cerebellum in mice that are heterozygous for Pur-alpha

Pur-alpha is a highly conserved sequence-specific DNA and RNA binding protein with established roles in DNA replication, RNA translation, cell cycle regulation, and maintenance of neuronal differentiation. Prior studies have shown that mice lacking Pur-alpha (-/-) display decreased neurogenesis and impaired neuronal differentiation. We sought to examine for the first time, the behavioral phenotype and brain histopathology of mice that are heterozygous (+/-) for Pur-alpha. Standardized behavioral phenotyping revealed a decreased escape response to touch, limb and abdominal hypotonia, and gait abnormalities in heterozygous Pur-alpha (+/-) mice, compared to wild-type (+/+) littermates. Footprint pattern analyses showed wider-based steps, increased missteps and more outwardly rotated hindpaws in heterozygous Pur-alpha (+/-) mice, suggestive of cerebellar pathology. The Barnes maze and novel object location testing revealed significant memory deficits in heterozygous Pur-alpha mice, suggestive of hippocampal pathology. Quantitative immunohistochemical assays of the vermal region of the cerebellum and CA1-3 regions of the hippocampus revealed reduced numbers of neurons in general, as well as reduced numbers of Pur-alpha+-immunopositive neurons and dendrites in heterozygous Pur-alpha mice, compared to wild-type littermates. Past studies have implicated mutations in Pur-alpha in several diseases of brain development and neurodegeneration. When combined with these new findings, the Pur-alpha heterozygous knockout mice may provide an animal model to study mechanisms of and treatments for Pur-alpha-related cognitive deficiencies and neuropathology.

Keywords: PURA animals brain pathology knockout mice puralpha.

Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Figures

Select results (neural reflexes and…

Select results (neural reflexes and open field activities) from a general health screen.…

Gait abnormalities were evident in…

Gait abnormalities were evident in heterozygous Pur-alpha (+/−) mice during forward walking. (A)…

Assessment of memory abilities in…

Assessment of memory abilities in novel object location and novel object recognition assays…

Assessment of memory abilities in…

Assessment of memory abilities in a Barnes maze test at 24 hours after…

Further assessment of memory abilities…

Further assessment of memory abilities in Barnes maze tests. Animals were trained for…

Reduced Pur-alpha immunostained neurons and…

Reduced Pur-alpha immunostained neurons and dendrites in hippocampus and cerebellum of mature (11…

Reduced numbers of Pur-alpha immunostained…

Reduced numbers of Pur-alpha immunostained neurons and dendrites in hippocampus, cerebellum and amygdala…


DNA methylation alters transcriptional rates of differentially expressed genes and contributes to pathophysiology in mice fed a high fat diet

Objective: Overnutrition can alter gene expression patterns through epigenetic mechanisms that may persist through generations. However, it is less clear if overnutrition, for example a high fat diet, modifies epigenetic control of gene expression in adults, or by what molecular mechanisms, or if such mechanisms contribute to the pathology of the metabolic syndrome. Here we test the hypothesis that a high fat diet alters hepatic DNA methylation, transcription and gene expression patterns, and explore the contribution of such changes to the pathophysiology of obesity.

Methods: RNA-seq and targeted high-throughput bisulfite DNA sequencing were used to undertake a systematic analysis of the hepatic response to a high fat diet. RT-PCR, chromatin immunoprecipitation and in vivo knockdown of an identified driver gene, Phlda1, were used to validate the results.

Results: A high fat diet resulted in the hypermethylation and decreased transcription and expression of Phlda1 and several other genes. A subnetwork of genes associated with Phlda1 was identified from an existing Bayesian gene network that contained numerous hepatic regulatory genes involved in lipid and body weight homeostasis. Hepatic-specific depletion of Phlda1 in mice decreased expression of the genes in the subnetwork, and led to increased oil droplet size in standard chow-fed mice, an early indicator of steatosis, validating the contribution of this gene to the phenotype.

Conclusions: We conclude that a high fat diet alters the epigenetics and transcriptional activity of key hepatic genes controlling lipid homeostasis, contributing to the pathophysiology of obesity.

Keywords: DNA methylation High fat diet Liver Phlda1 RNA-seq Transcription.


DNA repair is essential for cell vitality, cell survival, and cancer prevention, yet cells’ ability to patch up damaged DNA declines with age for reasons not fully understood.

Now, research led by scientists at Harvard Medical School (HMS) reveals a critical step in a molecular chain of events that allows cells to mend their broken DNA.

The findings, to be published March 24 in Science, offer a critical insight into how and why the body’s ability to fix DNA dwindles over time and point to a previously unknown role for the signaling molecule NAD as a key regulator of protein-to-protein interactions in DNA repair. NAD, identified a century ago, is already known for its role as a controller of cell-damaging oxidation.

Additionally, experiments conducted in mice show that treatment with the NAD precursor NMN mitigates age-related DNA damage and wards off DNA damage from radiation exposure.

Unraveling the mysteries of aging

The scientists caution that the effects of many therapeutic substances are often profoundly different in mice and humans owing to critical differences in biology. However, if affirmed in further animal studies and in humans, the findings can help pave the way to therapies that prevent DNA damage associated with aging and with cancer treatments that involve radiation exposure and some types of chemotherapy, which, along with killing tumors, can cause considerable DNA damage in healthy cells. Human trials with NMN are expected to begin within six months, the researchers said.

“Our results unveil a key mechanism in cellular degeneration and aging, but beyond that they point to a therapeutic avenue to halt and reverse age-related and radiation-induced DNA damage,” said senior author David Sinclair, professor in the Department of Genetics at HMS, co-director of the Paul F. Glenn Center for the Biology of Aging, and professor at the University of New South Wales School of Medicine in Sydney.

A previous study led by Sinclair showed that NMN reversed muscle aging in mice.

A plot with many characters

The investigators started by looking at a cast of proteins and molecules suspected to play a part in the cellular aging process. Some of them were well-known characters, others more enigmatic figures.

The researchers already knew that NAD, which declines steadily with age, boosts the activity of the SIRT1 protein, which delays aging and extends life in yeast, flies, and mice. Both SIRT1 and PARP1, a protein known to control DNA repair, consume NAD in their work.

Another protein, DBC1, one of the most abundant proteins in humans and found across life forms from bacteria to plants and animals, was a far murkier presence. Because DBC1 previously had been shown to inhibit vitality-boosting SIRT1, the researchers suspected DBC1 may also somehow interact with PARP1, given the similar roles PARP1 and SIRT1 play.

“We thought if there is a connection between SIRT1 and DBC1, on one hand, and between SIRT1 and PARP1 on the other, then maybe PARP1 and DBC1 were also engaged in some sort of intracellular game,” said Jun Li, first author on the study and a research fellow in the Department of Genetics at HMS.

To get a better sense of the chemical relationship among the three proteins, the scientists measured the molecular markers of protein-to-protein interaction inside human kidney cells. DBC1 and PARP1 bound powerfully to each other. However, when NAD levels increased, that bond was disrupted. The more NAD was present inside cells, the fewer molecular bonds PARP1 and DBC1 could form. When researchers inhibited NAD, the number of PARP1-DBC1 bonds went up. In other words, when NAD is plentiful, it prevents DBC1 from binding to PARP1 and meddling with its ability to mend damaged DNA.

What this suggests, the researchers said, is that as NAD declines with age, fewer and fewer NAD molecules are around to stop the harmful interaction between DBC1 and PARP1. The result: DNA breaks go unrepaired and, as these breaks accumulate over time, precipitate cell damage, cell mutations, cell death, and loss of organ function.

Averting mischief

Next, to understand how exactly NAD prevents DBC1 from binding to PARP1, the team homed in on a region of DBC1 known as NHD, a pocket-like structure found in some 80,000 proteins across life forms and species whose function has eluded scientists. The team’s experiments showed that NHD is an NAD binding site and that in DBC1, NAD blocks this specific region to prevent DBC1 from locking in with PARP1 and interfering with DNA repair.

Sinclair said that since NHD is so common across species, the finding suggests that by binding to it, NAD may play a similar role averting harmful protein interactions across many species to control DNA repair and other cell survival processes.

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Keywords: T cell receptor repertoire, RNA sequencing, single cell analysis, bioinformatics, immune system

Citation: De Simone M, Rossetti G and Pagani M (2018) Single Cell T Cell Receptor Sequencing: Techniques and Future Challenges. Front. Immunol. 9:1638. doi: 10.3389/fimmu.2018.01638

Received: 09 April 2018 Accepted: 03 July 2018
Published: 18 July 2018

Fabio Luciani, University of New South Wales, Australia

Avinash Bhandoola, National Institutes of Health (NIH), United States
John Stephen Bridgeman, Cellular Therapeutics Ltd., United Kingdom

Copyright: © 2018 De Simone, Rossetti and Pagani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.


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