Dataset Information

Playing hide and seek: how glycosylation of the influenza virus hemagglutinin can modulate the immune response to infection.

ABSTRACT: Seasonal influenza A viruses (IAV) originate from pandemic IAV and have undergone changes in antigenic structure, including addition of glycans to the hemagglutinin (HA) glycoprotein. The viral HA is the major target recognized by neutralizing antibodies and glycans have been proposed to shield antigenic sites on HA, thereby promoting virus survival in the face of widespread vaccination and/or infection. However, addition of glycans can also interfere with the receptor binding properties of HA and this must be compensated for by additional mutations, creating a fitness barrier to accumulation of glycosylation sites. In addition, glycans on HA are also recognized by phylogenetically ancient lectins of the innate immune system and the benefit provided by evasion of humoral immunity is balanced by attenuation of infection. Therefore, a fine balance must exist regarding the optimal pattern of HA glycosylation to offset competing pressures associated with recognition by innate defenses, evasion of humoral immunity and maintenance of virus fitness. In this review, we examine HA glycosylation patterns of IAV associated with pandemic and seasonal influenza and discuss recent advancements in our understanding of interactions between IAV glycans and components of innate and adaptive immunity.

SUBMITTER: Tate MD

PROVIDER: S-EPMC3970151 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Playing hide and seek: how glycosylation of the influenza virus hemagglutinin can modulate the immune response to infection.

Tate Michelle D MD Job Emma R ER Deng Yi-Mo YM Gunalan Vithiagaran V Maurer-Stroh Sebastian S Reading Patrick C PC

Viruses 20140314 3

Seasonal influenza A viruses (IAV) originate from pandemic IAV and have undergone changes in antigenic structure, including addition of glycans to the hemagglutinin (HA) glycoprotein. The viral HA is the major target recognized by neutralizing antibodies and glycans have been proposed to shield antigenic sites on HA, thereby promoting virus survival in the face of widespread vaccination and/or infection. However, addition of glycans can also interfere with the receptor binding properties of HA a ...[more]

PMID: 24638204

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Project description:BACKGROUND:The main challenge in de novo genome assembly of DNA-seq data is certainly to deal with repeats that are longer than the reads. In de novo transcriptome assembly of RNA-seq reads, on the other hand, this problem has been underestimated so far. Even though we have fewer and shorter repeated sequences in transcriptomics, they do create ambiguities and confuse assemblers if not addressed properly. Most transcriptome assemblers of short reads are based on de Bruijn graphs (DBG) and have no clear and explicit model for repeats in RNA-seq data, relying instead on heuristics to deal with them. RESULTS:The results of this work are threefold. First, we introduce a formal model for representing high copy-number and low-divergence repeats in RNA-seq data and exploit its properties to infer a combinatorial characteristic of repeat-associated subgraphs. We show that the problem of identifying such subgraphs in a DBG is NP-complete. Second, we show that in the specific case of local assembly of alternative splicing (AS) events, we can implicitly avoid such subgraphs, and we present an efficient algorithm to enumerate AS events that are not included in repeats. Using simulated data, we show that this strategy is significantly more sensitive and precise than the previous version of KisSplice (Sacomoto et al. in WABI, pp 99-111, 1), Trinity (Grabherr et al. in Nat Biotechnol 29(7):644-652, 2), and Oases (Schulz et al. in Bioinformatics 28(8):1086-1092, 3), for the specific task of calling AS events. Third, we turn our focus to full-length transcriptome assembly, and we show that exploring the topology of DBGs can improve de novo transcriptome evaluation methods. Based on the observation that repeats create complicated regions in a DBG, and when assemblers try to traverse these regions, they can infer erroneous transcripts, we propose a measure to flag transcripts traversing such troublesome regions, thereby giving a confidence level for each transcript. The originality of our work when compared to other transcriptome evaluation methods is that we use only the topology of the DBG, and not read nor coverage information. We show that our simple method gives better results than Rsem-Eval (Li et al. in Genome Biol 15(12):553, 4) and TransRate (Smith-Unna et al. in Genome Res 26(8):1134-1144, 5) on both real and simulated datasets for detecting chimeras, and therefore is able to capture assembly errors missed by these methods.

Dataset Information

Playing hide and seek: how glycosylation of the influenza virus hemagglutinin can modulate the immune response to infection.

Publications

Playing hide and seek: how glycosylation of the influenza virus hemagglutinin can modulate the immune response to infection.

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