A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

Background Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual’s ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics. Methods Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires. Results We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients’ immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude. Conclusions Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.ISSN:1756-994

An overview of bioinformatics workflow and statistical analysis performed on antibody HTS datasets.

<p>(A) Bioinformatics steps following the HTS of antibody libraries and preceding the data analysis. Sequences were pre-processed and IMGT-annotated reads were filtered for (i) CDR3s of minimal length of 4 amino acids and (ii) CDR3 and VDJ regions present with a minimal abundance of 2 in order to exclude errors introduced during library preparation or HTS reaction. Abundances were calculated based on occurrence of exact amino acid sequences (100% identity, see <i>Methods</i>). (B) Statistical analysis detailing the principle of reliable detection as applied in this study. CDR3 clones were ranked in decreasing order of frequency and tested for simultaneous presence in the other dataset(s). The principle is demonstrated using two hypothetical datasets of 10 different (unique) CDR3s with an exemplary reliable detection cut-off of 85% (throughout this study 95% was used). Specifically, from each dataset a list of reliably detected clones was generated (clones in green box) by sequentially adding the highest frequency clones to a list, until the addition of the next clone would reduce the percentage of clones present in the other dataset(s) below the set threshold (marked by the red dashed line). All further clones of lower rank were not included in the list and therefore not reliably detected (red color). Orange indicates clones that are not present in the other dataset(s) but were nevertheless included in the list of reliably detected CDR3s via the 85% detection cut-off. The list of reliably detected CDR3s allowed downstream analyses such as the determination of the range of reliable detection (frequency and abundance ranges), the calculation of the percentage of total reads corresponding to the reliably detected CDR3s, and the comparison of CDR3 rankings.</p

The relative advantages and disadvantages of the three investigated adapter addition methods (Ligation/DA/PE) for antibody HTS.

<p>The relative advantages and disadvantages of the three investigated adapter addition methods (Ligation/DA/PE) for antibody HTS.</p

Overview of the different methods used for adapter addition to antibody variable heavy chain amplicon libraries.

<p>All methods required the reverse transcription of antibody mRNA into cDNA (step 1), which served as template for the following IgG gene-specific amplification by PCR. (A) The ligation method required a pre-amplified library as starting material, with a 3′ A-overhang added by the Taq DNA Polymerase (step 2). The stem-loop adapters containing a 5′ T-overhang were then attached in an enzymatic ligation reaction and cleaved in order to create a double-stranded form (step 3) that served as template for a final amplification step (step 4) in which the full-length Illumina TruSeq universal and index adapter sequences were incorporated into the library. (B) The direct addition method combined antibody library amplification and sequencing adapter addition into one PCR step (step 2) by attaching the Illumina adapter sequences 5′ of the gene-specific primers used for library preparation. (C) The primer extension method incorporated a GC-rich overhang into the library in PCR1 (step 2). This resulted in uniformly high amplification in a second PCR by using primers specific for the GC-rich overhang and containing the full-length Illumina sequencing adapters (step 3). UTR: untranslated region, L: leader sequence, V: variable region, C: constant region, RT: reverse transcription, fw: forward, rv: reverse, x: barcode/index allowing multiplexed sequencing runs.</p

PCR and HTS statistics for ligation, DA, and PE.

<p>Display of performance differences of tested methods and conditions in terms of library preparation and HTS results. Please refer to the <i>Methods</i> section for library preparation details.</p><p>*DA1 and DA2 are technical replicates.</p>#<p>Phred scores range between 0 and 40 and reflect the quality of Illumina base calling.</p

Comparison of HTS datasets from the RNA titration experiment (500–5 ng) using the PE method.

<p>Spearman’s rank correlation of reliably detected CDR3s decreased with decreasing RNA input (r = 0.95–0.69). Antibody amplicon libraries prepared using PE and differing amounts of RNA input (500–5 ng) were sequenced (see <i>Methods</i>). CDR3 ranks were determined as detailed in Fig. 3. Average numbers of reliably detected CDR3s, frequency and abundance ranges, and the percentage of reads corresponding to reliably detected CDR3s are summarized in Table S1 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096727#pone.0096727.s001" target="_blank">File S1</a>.</p

Comprehensive Evaluation and Optimization of Amplicon Library Preparation Methods for High-Throughput Antibody Sequencing

<div><p>High-throughput sequencing (HTS) of antibody repertoire libraries has become a powerful tool in the field of systems immunology. However, numerous sources of bias in HTS workflows may affect the obtained antibody repertoire data. A crucial step in antibody library preparation is the addition of short platform-specific nucleotide adapter sequences. As of yet, the impact of the method of adapter addition on experimental library preparation and the resulting antibody repertoire HTS datasets has not been thoroughly investigated. Therefore, we compared three standard library preparation methods by performing Illumina HTS on antibody variable heavy genes from murine antibody-secreting cells. Clonal overlap and rank statistics demonstrated that the investigated methods produced equivalent HTS datasets. PCR-based methods were experimentally superior to ligation with respect to speed, efficiency, and practicality. Finally, using a two-step PCR based method we established a protocol for antibody repertoire library generation, beginning from inputs as low as 1 ng of total RNA. In summary, this study represents a major advance towards a standardized experimental framework for antibody HTS, thus opening up the potential for systems-based, cross-experiment meta-analyses of antibody repertoires.</p></div