Bettina Budeus

The amino acid substitutions rtP177G and rtF249A in the reverse transcriptase domain of hepatitis B virus polymerase reduce the susceptibility to tenofovir

Long term antiviral therapy with nucleoside/nucleotide analogs have been routinely used to treat chronic hepatitis B virus (HBV) infection but may lead to the emergence of drug-resistant viral mutants. However, the HBV resistance mutations for tenofovir (TDF) remain controversial. It is speculated that the genetic barrier for TDF resistance may be high for HBV. We asked whether selected amino acid substitutions in HBV polymerase may reduce susceptibility to TDF. A series of amino acids in HBV polymerase were selected based on bioinformatics analysis for mutagenesis. The replication competence and susceptibility to TDF of the mutated HBV clones were determined both in vitro and in vivo. nineteen mutations in HBV polymerase were included and impaired the replication competence of HBV genome in different degrees. The mutations at rtL77F (sS69C), rtF88L (sF80Y), and rtP177G (sR169G) also significantly affected HBsAg expression. The HBV mutants with rtP177G and rtF249A were found to have reduced susceptibility to TDF in vitro with a resistance index of 2.53 and 12.16, respectively. The testing in in vivo model based on the hydrodynamic injection revealed the antiviral effect of TDF against wild type and mutated HBV genomes and confirmed the reduced the susceptibility of mutant HBV to TDF.

Adaptation of the hepatitis B virus core protein to CD8(+) T-cell selection pressure.

Activation of hepatitis B virus (HBV)–specific CD8 T cells by therapeutic vaccination may promote sustained control of viral replication by clearance of covalently closed circular DNA from infected hepatocytes. However, little is known about the exact targets of the CD8 T‐cell response and whether HBV reproducibly evades CD8 T‐cell immune pressure by mutation. The aim of this study was to address if HBV reproducibly selects substitutions in CD8 T‐cell epitopes that functionally act as immune escape mutations. The HBV core gene was amplified and sequenced from 148 patients with chronic HBV infection, and the human leukocyte antigen (HLA) class I genotype (A and B loci) was determined. Residues under selection pressure in the presence of particular HLA class I alleles were identified by a statistical approach utilizing the novel analysis package SeqFeatR. With this approach we identified nine residues in HBV core under selection pressure in the presence of 10 different HLA class I alleles. Additional immunological experiments confirmed that seven of the residues were located inside epitopes targeted by patients with chronic HBV infection carrying the relevant HLA class I allele. Consistent with viral escape, the selected substitutions reproducibly impaired recognition by HBV‐specific CD8 T cells. Conclusion: Viral sequence analysis allows identification of HLA class I–restricted epitopes under reproducible selection pressure in HBV core; the possibility of viral escape from CD8 T‐cell immune pressure needs attention in the context of therapeutic vaccination against HBV. (Hepatology 2015;62:47‐56)

Complexity of the human memory B-cell compartment is determined by the versatility of clonal diversification in germinal centers.

Significance The complexity of the human memory B-lymphocyte compartment is a key component to depict and understand adaptive immunity. Despite numerous prior investigations, the generation of certain memory B-cell subsets, the dependency on T-cell help, and the composition, size, and diversity of clonal expansions are either poorly understood or debated. Here we provide an extensive and tightly controlled immunoglobulin heavy chain variable (IGHV) gene repertoire analysis of four main human memory B-cell subpopulations, revealing that an ordered diversification in germinal centers determines a highly versatile memory B-cell compartment in humans with surprisingly many very large B-cell clones. Our knowledge about the clonal composition and intraclonal diversity of the human memory B-cell compartment and the relationship between memory B-cell subsets is still limited, although these are central issues for our understanding of adaptive immunity. We performed a deep sequencing analysis of rearranged immunoglobulin (Ig) heavy chain genes from biological replicates, covering more than 100,000 memory B lymphocytes from two healthy adults. We reveal a highly similar B-cell receptor repertoire among the four main human IgM+ and IgG+ memory B-cell subsets. Strikingly, in both donors, 45% of sequences could be assigned to expanded clones, demonstrating that the human memory B-cell compartment is characterized by many, often very large, B-cell clones. Twenty percent of the clones consisted of class switched and IgM+(IgD+) members, a feature that correlated significantly with clone size. Hence, we provide strong evidence that the vast majority of Ig mutated B cells—including IgM+IgD+CD27+ B cells—are post-germinal center (GC) memory B cells. Clone members showed high intraclonal sequence diversity and high intraclonal versatility in Ig class and IgG subclass composition, with particular patterns of memory B-cell clone generation in GC reactions. In conclusion, GC produce amazingly large, complex, and diverse memory B-cell clones, equipping the human immune system with a versatile and highly diverse compartment of IgM+(IgD+) and class-switched memory B cells.

AmpliconDuo: A Split-Sample Filtering Protocol for High-Throughput Amplicon Sequencing of Microbial Communities

High throughput sequencing (HTSeq) of small ribosomal subunit amplicons has the potential for a comprehensive characterization of microbial community compositions, down to rare species. However, the error-prone nature of the multi-step experimental process requires that the resulting raw sequences are subjected to quality control procedures. These procedures often involve an abundance cutoff for rare sequences or clustering of sequences, both of which limit genetic resolution. Here we propose a simple experimental protocol that retains the high genetic resolution granted by HTSeq methods while effectively removing many low abundance sequences that are likely due to PCR and sequencing errors. According to this protocol, we split samples and submit both halves to independent PCR and sequencing runs. The resulting sequence data is graphically and quantitatively characterized by the discordance between the two experimental branches, allowing for a quick identification of problematic samples. Further, we discard sequences that are not found in both branches (“AmpliconDuo filter”). We show that the majority of sequences removed in this way, mostly low abundance but also some higher abundance sequences, show features expected from random modifications of true sequences as introduced by PCR and sequencing errors. On the other hand, the filter retains many low abundance sequences observed in both branches and thus provides a more reliable census of the rare biosphere. We find that the AmpliconDuo filter increases biological resolution as it increases apparent community similarity between biologically similar communities, while it does not affect apparent community similarities between biologically dissimilar communities. The filter does not distort overall apparent community compositions. Finally, we quantitatively explain the effect of the AmpliconDuo filter by a simple mathematical model.

Genotypic Prediction of Co-receptor Tropism of HIV-1 Subtypes A and C.

Antiretroviral treatment of Human Immunodeficiency Virus type-1 (HIV-1) infections with CCR5-antagonists requires the co-receptor usage prediction of viral strains. Currently available tools are mostly designed based on subtype B strains and thus are in general not applicable to non-B subtypes. However, HIV-1 infections caused by subtype B only account for approximately 11% of infections worldwide. We evaluated the performance of several sequence-based algorithms for co-receptor usage prediction employed on subtype A V3 sequences including circulating recombinant forms (CRFs) and subtype C strains. We further analysed sequence profiles of gp120 regions of subtype A, B and C to explore functional relationships to entry phenotypes. Our analyses clearly demonstrate that state-of-the-art algorithms are not useful for predicting co-receptor tropism of subtype A and its CRFs. Sequence profile analysis of gp120 revealed molecular variability in subtype A viruses. Especially, the V2 loop region could be associated with co-receptor tropism, which might indicate a unique pattern that determines co-receptor tropism in subtype A strains compared to subtype B and C strains. Thus, our study demonstrates that there is a need for the development of novel algorithms facilitating tropism prediction of HIV-1 subtype A to improve effective antiretroviral treatment in patients.

Differential selection in HIV-1 gp120 between subtype B and East Asian variant B’

HIV-1 evolves strongly and undergoes geographic differentiation as it spreads in diverse host populations around the world. For instance, distinct genomic backgrounds can be observed between the pandemic subtype B, prevalent in Europe and North-America, and its offspring clade B’ in East Asia. Here we ask whether this differentiation affects the selection pressure experienced by the virus. To answer this question we evaluate selection pressure on the HIV-1 envelope protein gp120 at the level of individual codons using a simple and fast estimation method based on the ratio ka/ks of amino acid changes to synonymous changes. To validate the approach we compare results to those from a state-of-the-art mixed-effect method. The agreement is acceptable, but the analysis also demonstrates some limitations of the simpler approach. Further, we find similar distributions of codons under stabilizing and directional selection pressure in gp120 for subtypes B and B’ with more directional selection pressure in variable loops and more stabilizing selection in the constant regions. Focusing on codons with increased ka/ks values in B’, we show that these codons are scattered over the whole of gp120, with remarkable clusters of higher density in regions flanking the variable loops. We identify a significant statistical association of glycosylation sites and codons with increased ka/ks values.

SeqFeatR for the Discovery of Feature-Sequence Associations

Specific selection pressures often lead to specifically mutated genomes. The open source software SeqFeatR has been developed to identify associations between mutation patterns in biological sequences and specific selection pressures (“features”). For instance, SeqFeatR has been used to discover in viral protein sequences new T cell epitopes for hosts of given HLA types. SeqFeatR supports frequentist and Bayesian methods for the discovery of statistical sequence-feature associations. Moreover, it offers novel ways to visualize results of the statistical analyses and to relate them to further properties. In this article we demonstrate various functions of SeqFeatR with real data. The most frequently used set of functions is also provided by a web server. SeqFeatR is implemented as R package and freely available from the R archive CRAN (http://cran.r-project.org/web/packages/SeqFeatR/index.html). The package includes a tutorial vignette. The software is distributed under the GNU General Public License (version 3 or later). The web server URL is https://seqfeatr.zmb.uni-due.de.

Quantitative Comparison of Abundance Structures of Generalized Communities: From B-Cell Receptor Repertoires to Microbiomes

The community, the assemblage of organisms co-existing in a given space and time, has the potential to become one of the unifying concepts of biology, especially with the advent of high-throughput sequencing experiments that reveal genetic diversity exhaustively. In this spirit we show that a tool from community ecology, the Rank Abundance Distribution (RAD), can be turned by the new MaxRank normalization method into a generic, expressive descriptor for quantitative comparison of communities in many areas of biology. To illustrate the versatility of the method, we analyze RADs from various generalized communities, i.e. assemblages of genetically diverse cells or organisms, including human B cells, gut microbiomes under antibiotic treatment and of different ages and countries of origin, and other human and environmental microbial communities. We show that normalized RADs enable novel quantitative approaches that help to understand structures and dynamics of complex generalized communities.