Aaron M. Rosenfeld

NBC: The Naïve Bayes Classification Tool Webserver for Taxonomic Classification of Metagenomic Reads

Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads. Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign next-generation sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss. Availability: Publicly available at: http://nbc.ece.drexel.edu. Contact: gailr@ece.drexel.edu

An atlas of B-cell clonal distribution in the human body

B-cell responses result in clonal expansion, and can occur in a variety of tissues. To define how B-cell clones are distributed in the body, we sequenced 933,427 B-cell clonal lineages and mapped them to eight different anatomic compartments in six human organ donors. We show that large B-cell clones partition into two broad networks—one spans the blood, bone marrow, spleen and lung, while the other is restricted to tissues within the gastrointestinal (GI) tract (jejunum, ileum and colon). Notably, GI tract clones display extensive sharing of sequence variants among different portions of the tract and have higher frequencies of somatic hypermutation, suggesting extensive and serial rounds of clonal expansion and selection. Our findings provide an anatomic atlas of B-cell clonal lineages, their properties and tissue connections. This resource serves as a foundation for studies of tissue-based immunity, including vaccine responses, infections, autoimmunity and cancer.

VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements

BackgroundThe genes that produce antibodies and the immune receptors expressed on lymphocytes are not germline encoded; rather, they are somatically generated in each developing lymphocyte by a process called V(D)J recombination, which assembles specific, independent gene segments into mature composite genes. The full set of composite genes in an individual at a single point in time is referred to as the immune repertoire. V(D)J recombination is the distinguishing feature of adaptive immunity and enables effective immune responses against an essentially infinite array of antigens. Characterization of immune repertoires is critical in both basic research and clinical contexts. Recent technological advances in repertoire profiling via high-throughput sequencing have resulted in an explosion of research activity in the field. This has been accompanied by a proliferation of software tools for analysis of repertoire sequencing data. Despite the widespread use of immune repertoire profiling and analysis software, there is currently no standardized format for output files from V(D)J analysis. Researchers utilize software such as IgBLAST and IMGT/High V-QUEST to perform V(D)J analysis and infer the structure of germline rearrangements. However, each of these software tools produces results in a different file format, and can annotate the same result using different labels. These differences make it challenging for users to perform additional downstream analyses.ResultsTo help address this problem, we propose a standardized file format for representing V(D)J analysis results. The proposed format, VDJML, provides a common standardized format for different V(D)J analysis applications to facilitate downstream processing of the results in an application-agnostic manner. The VDJML file format specification is accompanied by a support library, written in C++ and Python, for reading and writing the VDJML file format.ConclusionsThe VDJML suite will allow users to streamline their V(D)J analysis and facilitate the sharing of scientific knowledge within the community. The VDJML suite and documentation are available from https://vdjserver.org/vdjml/. We welcome participation from the community in developing the file format standard, as well as code contributions.

ImmuneDB: a system for the analysis and exploration of high-throughput adaptive immune receptor sequencing data

Summary: As high-throughput sequencing of B cells becomes more common, the need for tools to analyze the large quantity of data also increases. This article introduces ImmuneDB, a system for analyzing vast amounts of heavy chain variable region sequences and exploring the resulting data. It can take as input raw FASTA/FASTQ data, identify genes, determine clones, construct lineages, as well as provide information such as selection pressure and mutation analysis. It uses an industry leading database, MySQL, to provide fast analysis and avoid the complexities of using error prone flat-files. Availability and Implementation: ImmuneDB is freely available at http://immunedb.com A demo of the ImmuneDB web interface is available at: http://immunedb.com/demo Contact: Uh25@drexel.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Computational Evaluation of B-Cell Clone Sizes in Bulk Populations

B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data.

A comparison of group-based data persistence techniques in MANETs

Maintaining a consistent set of state information across applications in tactical edge, mobile ad-hoc networks (MANETs) is a challenging, yet mission-critical task. This paper analyzes the performance and effectiveness of eight approaches to data persistence with three different persistence requirements. This is done by introducing COPE, a middleware framework for reliable data delivery that allows different protocols to be configured at runtime. Our empirical results provide a roadmap for selecting the best protocol for a given scenario.

ImmuneDB, a Novel Tool for the Analysis, Storage, and Dissemination of Immune Repertoire Sequencing Data

ImmuneDB is a system for storing and analyzing high-throughput immune receptor sequencing data. Unlike most existing tools, which utilize flat-files, ImmuneDB stores data in a well-structured MySQL database, enabling efficient data queries. It can take raw sequencing data as input and annotate receptor gene usage, infer clonotypes, aggregate results, and run common downstream analyses such as calculating selection pressure and constructing clonal lineages. Alternatively, pre-annotated data can be imported and analyzed data can be exported in a variety of common Adaptive Immune Receptor Repertoire (AIRR) file formats. To validate ImmuneDB, we compare its results to those of another pipeline, MiXCR. We show that the biological conclusions drawn would be similar with either tool, while ImmuneDB provides the additional benefits of integrating other common tools and storing data in a database. ImmuneDB is freely available on GitHub at https://github.com/arosenfeld/immunedb, on PyPi at https://pypi.org/project/ImmuneDB, and a Docker container is provided at https://hub.docker.com/r/arosenfeld/immunedb. Full documentation is available at http://immunedb.com.

Human Lymph Nodes Maintain TCF-1hi Memory T Cells with High Functional Potential and Clonal Diversity throughout Life

Translating studies on T cell function and modulation from mouse models to humans requires extrapolating in vivo results on mouse T cell responses in lymphoid organs (spleen and lymph nodes [LN]) to human peripheral blood T cells. However, our understanding of T cell responses in human lymphoid sites and their relation to peripheral blood remains sparse. In this study, we used a unique human tissue resource to study human T cells in different anatomical compartments within individual donors and identify a subset of memory CD8+ T cells in LN, which maintain a distinct differentiation and functional profile compared with memory CD8+ T cells in blood, spleen, bone marrow, and lungs. Whole-transcriptome and high-dimensional cytometry by time-of-flight profiling reveals that LN memory CD8+ T cells express signatures of quiescence and self-renewal compared with corresponding populations in blood, spleen, bone marrow, and lung. LN memory T cells exhibit a distinct transcriptional signature, including expression of stem cell–associated transcription factors TCF-1 and LEF-1, T follicular helper cell markers CXCR5 and CXCR4, and reduced expression of effector molecules. LN memory T cells display high homology to a subset of mouse CD8+ T cells identified in chronic infection models that respond to checkpoint blockade immunotherapy. Functionally, human LN memory T cells exhibit increased proliferation to TCR-mediated stimulation and maintain higher TCR clonal diversity compared with memory T cells from blood and other sites. These findings establish human LN as reservoirs for memory T cells with high capacities for expansion and diverse recognition and important targets for immunotherapies.

AIRR Community Standardized Representations for Annotated Immune Repertoires

Increased interest in the immune systems involvement in pathophysiological phenomena coupled with decreased DNA sequencing costs have led to an explosion of antibody and T cell receptor sequencing data collectively termed “adaptive immune receptor repertoire sequencing” (AIRR-seq or Rep-Seq). The AIRR Community has been actively working to standardize protocols, metadata, formats, APIs, and other guidelines to promote open and reproducible studies of the immune repertoire. In this paper, we describe the work of the AIRR Communitys Data Representation Working Group to develop standardized data representations for storing and sharing annotated antibody and T cell receptor data. Our file format emphasizes ease-of-use, accessibility, scalability to large data sets, and a commitment to open and transparent science. It is composed of a tab-delimited format with a specific schema. Several popular repertoire analysis tools and data repositories already utilize this AIRR-seq data format. We hope that others will follow suit in the interest of promoting interoperable standards.

Dynamic Selection of Persistence and Transport Layer Protocols in Challenged Networks

This work applies a distributed algorithm utilizing Markov Random Fields (MRFs) to the problem of dynamically selecting Session and Transport layer protocols in challenged networks such as mobile ad-hoc networks. It motivates the problem by identifying the primary network properties which affect Message Delivery Ratio (MDR) in networks with varying degrees of connectivity and traffic load. Using this information, local and remote observations are used to select a set of protocols which should perform the best. Analysis shows that dynamically selecting a set of protocols can deliver up to 50% more messages in challenged environments, and never under-performs statically choosing protocols.