Sequence-Signature Optimization Enables Improved Identification of Human HV6-1-Derived Class Antibodies That Neutralize Diverse Influenza A Viruses

Sequence signatures of multidonor broadly neutralizing influenza antibodies can be used to quantify the prevalence of B cells with virus-neutralizing potential to accelerate development of broadly protective vaccine strategies. Antibodies of the same class share similar recognition modes and developmental pathways, and several antibody classes have been identified that neutralize diverse group 1- and group 2-influenza A viruses and have been observed in multiple human donors. One such multidonor antibody class, the HV6-1-derived class, targets the stem region of hemagglutinin with extraordinary neutralization breadth. Here, we use an iterative process to combine informatics, biochemical, and structural analyses to delineate an improved sequence signature for HV6-1-class antibodies. Based on sequence and structure analyses of known HV6-1 class antibodies, we derived a more inclusive signature (version 1), which we used to search for matching B-cell transcripts from published next-generation sequencing datasets of influenza vaccination studies. We expressed selected antibodies, evaluated their function, and identified amino acid-level requirements from which to refine the sequence signature (version 2). The cryo-electron microscopy structure for one of the signature-identified antibodies in complex with hemagglutinin confirmed motif recognition to be similar to known HV6-1-class members, MEDI8852 and 56.a.09, despite differences in recognition-loop length. Threading indicated the refined signature to have increased accuracy, and signature-identified heavy chains, when paired with the light chain of MEDI8852, showed neutralization comparable to the most potent members of the class. Incorporating sequences of additional class members thus enables an improved sequence signature for HV6-1-class antibodies, which can identify class members with increased accuracy

The how and why of lncRNA function: An innate immune perspective.

Next-generation sequencing has provided a more complete picture of the composition of the human transcriptome indicating that much of the "blueprint" is a vastness of poorly understood non-protein-coding transcripts. This includes a newly identified class of genes called long noncoding RNAs (lncRNAs). The lack of sequence conservation for lncRNAs across species meant that their biological importance was initially met with some skepticism. LncRNAs mediate their functions through interactions with proteins, RNA, DNA, or a combination of these. Their functions can often be dictated by their localization, sequence, and/or secondary structure. Here we provide a review of the approaches typically adopted to study the complexity of these genes with an emphasis on recent discoveries within the innate immune field. Finally, we discuss the challenges, as well as the emergence of new technologies that will continue to move this field forward and provide greater insight into the biological importance of this class of genes. This article is part of a Special Issue entitled: ncRNA in control of gene expression edited by Kotb Abdelmohsen

Optimization and clinical validation of a pathogen detection microarray

New design and optimization of pathogen detection microarrays is shown to allow robust and accurate detection of a range of pathogens. The customized microarray platform includes a method for reducing PCR bias during DNA amplification

Salmonella Degrades the Host Glycocalyx Leading to Altered Infection and Glycan Remodeling.

Complex glycans cover the gut epithelial surface to protect the cell from the environment. Invasive pathogens must breach the glycan layer before initiating infection. While glycan degradation is crucial for infection, this process is inadequately understood. Salmonella contains 47 glycosyl hydrolases (GHs) that may degrade the glycan. We hypothesized that keystone genes from the entire GH complement of Salmonella are required to degrade glycans to change infection. This study determined that GHs recognize the terminal monosaccharides (N-acetylneuraminic acid (Neu5Ac), galactose, mannose, and fucose) and significantly (p < 0.05) alter infection. During infection, Salmonella used its two GHs sialidase nanH and amylase malS for internalization by targeting different glycan structures. The host glycans were altered during Salmonella association via the induction of N-glycan biosynthesis pathways leading to modification of host glycans by increasing fucosylation and mannose content, while decreasing sialylation. Gene expression analysis indicated that the host cell responded by regulating more than 50 genes resulting in remodeled glycans in response to Salmonella treatment. This study established the glycan structures on colonic epithelial cells, determined that Salmonella required two keystone GHs for internalization, and left remodeled host glycans as a result of infection. These data indicate that microbial GHs are undiscovered virulence factors

Genomic Signature-Based Identification of Influenza A Viruses Using RT-PCR/Electro-Spray Ionization Mass Spectrometry (ESI-MS) Technology

BACKGROUND: The emergence and rapid spread of the 2009 H1N1 pandemic influenza A virus (H1N1pdm) in humans highlights the importance of enhancing the capability of existing influenza surveillance systems with tools for rapid identification of emerging and re-emerging viruses. One of the new approaches is the RT-PCR electrospray ionization mass spectrometry (RT-PCR/ESI-MS) technology, which is based on analysis of base composition (BC) of RT-PCR amplicons from influenza "core" genes. Combination of the BC signatures represents a "genomic print" of an influenza A virus. METHODOLOGY/PRINCIPAL FINDINGS: Here, 757 samples collected between 2006 and 2009 were tested, including 302 seasonal H1N1, 171 H3N2, 7 swine triple reassortants, and 277 H1N1pdm viruses. Of the 277 H1N1pdm samples, 209 were clinical specimens (throat, nasal and nasopharyngeal swabs, nasal washes, blood and sputum). BC signatures for the clinical specimen from one of the first cases of the 2009 pandemic, A/California/04/2009, confirmed it as an unusual, previously unrecognized influenza A virus, with "core" genes related to viruses of avian, human and swine origins. Subsequent analysis of additional 276 H1N1pdm samples revealed that they shared the genomic print of A/California/04/2009, which differed from those of North American swine triple reassortant viruses, seasonal H1N1 and H3N2 and other viruses tested. Moreover, this assay allowed distinction between "core" genes of co-circulating groups of seasonal H1N1, such as clades 2B, 2C, and their reassortants with dual antiviral resistance to adamantanes and oseltamivir. CONCLUSIONS/SIGNIFICANCE: The RT-PCR/ESI-MS assay is a broad range influenza identification tool that can be used directly on clinical specimens for rapid and accurate detection of influenza virus genes. The assay differentiates the H1N1pdm from seasonal and other nonhuman hosts viruses. Although not a diagnostic tool, this assay demonstrates its usefulness and robustness in influenza virus surveillance and detection of novel and unusual viruses with previously unseen genomic prints

Identifying Influenza Viruses with Resequencing Microarrays

Resequencing microarrays rapidly identify influenza viruses

Biochip sensors for the rapid and sensitive detection of viral disease

Recent advances in DNA and protein microarray methodology and the emerging technology of cell-based sensors have massively increased the speed and sensitivity with which we can detect viral infections. The advantages of the multi-parameter microarray technologies could be combined with the speed and sensitivity of cell-based systems to give 'cell-omic' sensors

Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity in order to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic and (iv) machine learning methods applied to dissect, quantify and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology towards coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.Comment: 27 pages, 2 figure

T Cell Epitope Redundancy: Cross-conservation of the TCR face between Pathogens and Self and its Implications for Vaccines and Auto-immunity

T cells are extensively trained on ‘self’ in the thymus and then move to the periphery, where they seek out and destroy infections and regulate immune response to self-antigens. T cell receptors (TCR) on T cells’ surface recognize T cell epitopes, short linear strings of amino acids presented by antigen-presenting cells. Some of these epitopes activate T effectors, while others activate regulatory T cells. It was recently discovered that T cell epitopes that are highly conserved on their TCR face with human genome sequences are often associated with T cells that regulate immune response. These TCR-cross-conserved or ‘redundant epitopes’ are more common in proteins found in pathogens that have co-evolved with humans than in other non-commensal pathogens. Epitope redundancy might be the link between pathogens and autoimmune disease. This article reviews recently published data and addresses epitope redundancy, the “elephant in the room” for vaccine developers and T cell immunologists