ClonoMatch: a tool for identifying homologous immunoglobulin and T-cell receptor sequences in large databases.

SUMMARY: B-cell receptor (BCR) and T-cell receptor (TCR) repertoires are generated through somatic DNA rearrangements and are responsible for the molecular basis of antigen recognition in the immune system. Next-generation sequencing (NGS) of DNA and the falling cost of sequencing due to continued development of these technologies have made sequencing assays an affordable way to characterize the repertoire of adaptive immune receptors (sometimes termed the 'immunome'). Many new workflows have been developed to take advantage of NGS and have placed the resulting immunome datasets in the public domain. The scale of these NGS datasets has made it challenging to search through the Complementarity-determining region 3 (CDR3), which is responsible for imparting specific antibody-antigen interactions. Thus, there is an increasing demand for sequence analysis tools capable of searching through CDR3s from immunome data collections containing millions of sequences. To address this need, we created a software package called ClonoMatch that facilitates rapid searches in bulk immunome data for BCR or TCR sequences based on their CDR3 sequence or V3J clonotype. AVAILABILITY AND IMPLEMENTATION: Documentation, software support and the codebase are all available at https://github.com/crowelab/clonomatch. This software is distributed under the GPL v3 license.

PyIR: a scalable wrapper for processing billions of immunoglobulin and T cell receptor sequences using IgBLAST.

BACKGROUND: Recent advances in DNA sequencing technologies have enabled significant leaps in capacity to generate large volumes of DNA sequence data, which has spurred a rapid growth in the use of bioinformatics as a means of interrogating antibody variable gene repertoires. Common tools used for annotation of antibody sequences are often limited in functionality, modularity and usability. RESULTS: We have developed PyIR, a Python wrapper and library for IgBLAST, which offers a minimal setup CLI and API, FASTQ support, file chunking for large sequence files, JSON and Python dictionary output, and built-in sequence filtering. CONCLUSIONS: PyIR offers improved processing speed over multithreaded IgBLAST (version 1.14) when spawning more than 16 processes on a single computer system. Its customizable filtering and data encapsulation allow it to be adapted to a wide range of computing environments. The API allows for IgBLAST to be used in customized bioinformatics workflows.

Diverse patterns of antibody variable gene repertoire disruption in patients with amyloid light chain (AL) amyloidosis.

Immunoglobulin light chain amyloidosis is the most common form of systemic amyloidosis. AL amyloidosis is caused by a misfolded light chain produced by a clonal population of plasma cells. Disease status currently is defined by measuring the absolute quantity of serum free light chain protein, but this measurement often fails to identify the subclinical presence of clonal cells that may merit additional therapy. Next generation sequencing has the sensitivity to measure the relative amount of dominating light chains within the repertoire of a patient, and this technique is in clinical use to identify clonal populations of plasma cells for multiple myeloma, a related disorder. In this proof-of-concept study, we used bone marrow aspirates of AL amyloidosis positive patients and used reverse transcription of the antibody transcriptome followed by next generation sequencing to identify antibody variable-diversity-joining gene sequences for patients with immunoglobulin light chain amyloidosis, and demonstrate that this technology can be used to identify the dominant clone. The data also reveal differing patterns of overall antibody repertoire disruption in different patients. This method merits further study in larger prospective studies to establish its utility in detecting residual disease for patients with immunoglobulin light chain amyloidosis.

High Frequency of Shared Clonotypes in Human T Cell Receptor Repertoires.

The collection of T cell receptors (TCRs) generated by somatic recombination is large but unknown. We generate large TCR repertoire datasets as a resource to facilitate detailed studies of the role of TCR clonotypes and repertoires in health and disease. We estimate the size of individual human recombined and expressed TCRs by sequence analysis and determine the extent of sharing between individual repertoires. Our experiments reveal that each blood sample contains between 5 million and 21 million TCR clonotypes. Three individuals share 8% of TCRß- or 11% of TCRα-chain clonotypes. Sorting by T cell phenotypes in four individuals shows that 5% of naive CD4+ and 3.5% of naive CD8+ subsets share their TCRß clonotypes, whereas memory CD4+ and CD8+ subsets share 2.3% and 0.4% of their clonotypes, respectively. We identify the sequences of these shared TCR clonotypes that are of interest for studies of human T cell biology.

Representation over time: the effects of temporal distance on similarity.

Similarity is central in human cognition, playing a role in a wide range of cognitive processes. In three studies, we demonstrate that subjective similarity may change as a function of temporal distance, with some events seeming more similar when considered in the near future, while others increase in similarity as temporal distance increases. Given the ubiquity of inter-temporal thought, and the fundamental role of similarity, these results have important implications for cognition in general.

The Cognitive Costs of Context: The Effects of Concreteness and Immersiveness in Instructional Examples.

Prior research has established that while the use of concrete, familiar examples can provide many important benefits for learning, it is also associated with some serious disadvantages, particularly in learners' ability to recognize and transfer their knowledge to new analogous situations. However, it is not immediately clear whether this pattern would hold in real world educational contexts, in which the role of such examples in student engagement and ease of processing might be of enough importance to overshadow any potential negative impact. We conducted two experiments in which curriculum-relevant material was presented in natural classroom environments, first with college undergraduates and then with middle-school students. All students in each study received the same relevant content, but the degree of contextualization in these materials was varied between students. In both studies, we found that greater contextualization was associated with poorer transfer performance. We interpret these results as reflecting a greater degree of embeddedness for the knowledge acquired from richer, more concrete materials, such that the underlying principles are represented in a less abstract and generalizable form.

Analogical transfer from a simulated physical system.

Previous research has consistently found that spontaneous analogical transfer is strongly tied to concrete and contextual similarities between the cases. However, that work has largely failed to acknowledge that the relevant factor in transfer is the similarity between individuals' mental representations of the situations rather than the overt similarities between the cases themselves. Across several studies, we found that participants were able to transfer strategies learned from a perceptually concrete simulation of a physical system to a task with very dissimilar content and appearance. This transfer was reflected in better performance on the transfer task when its underlying dynamics were consistent rather than inconsistent with the preceding training task. Our data indicate that transfer in these tasks relies on the perceptual and spatial nature of the training task but does not depend on direct interaction with the system, with participants performing equally well after simply observing the concrete simulation. We argue that participants generated a spatial, dynamic, and force-based mental model while interacting with the training simulation and tended to spontaneously interpret the transfer task according to this primed model. Unexpectedly, our data consistently show that transfer was independent of reported recognition of the analogy between tasks: Although such recognition was associated with better overall performance, it was not associated with better transfer (in terms of applying an appropriate strategy). Together, these findings suggest that analogical transfer between overtly dissimilar cases may be much more common--and much more relevant to our cognitive processing--than is generally assumed.

Nonintentional analogical inference in text comprehension.

We present findings suggesting that analogical inference processes can play a role in fluent comprehension and interpretation. Participants were found to use information from a prior relationally similar example in understanding the content of a later example, but they reported that they were not aware of having done so. These inference processes were sensitive to structural mappings between the two instances, ruling out explanations based solely on more general kinds of activation, such as priming. Reading speed measures were consistent with the possibility that these inferences had taken place during encoding of the target rather than during the later recognition test. These findings suggest that analogical mapping, though often viewed as an explicit deliberative process, can sometimes operate without intent or even awareness.