Larger mammalian body size leads to lower retroviral activity

Retroviruses have been infecting mammals for at least 100 million years, leaving descendants in host genomes known as endogenous retroviruses (ERVs). The abundance of ERVs is partly determined by their mode of replication, but it has also been suggested that host life history traits could enhance or suppress their activity. We show that larger bodied species have lower levels of ERV activity by reconstructing the rate of ERV integration across 38 mammalian species. Body size explains 37% of the variance in ERV integration rate over the last 10 million years, controlling for the effect of confounding due to other life history traits. Furthermore, 68% of the variance in the mean age of ERVs per genome can also be explained by body size. These results indicate that body size limits the number of recently replicating ERVs due to their detrimental effects on their host. To comprehend the possible mechanistic links between body size and ERV integration we built a mathematical model, which shows that ERV abundance is favored by lower body size and higher horizontal transmission rates. We argue that because retroviral integration is tumorigenic, the negative correlation between body size and ERV numbers results from the necessity to reduce the risk of cancer, under the assumption that this risk scales positively with body size. Our model also fits the empirical observation that the lifetime risk of cancer is relatively invariant among mammals regardless of their body size, known as Peto's paradox, and indicates that larger bodied mammals may have evolved mechanisms to limit ERV activity

Persistence of frequently transmitted drug-resistant HIV-1 variants can be explained by high viral replication capacity

Background: In approximately 10% of newly diagnosed individuals in Europe, HIV-1 variants harboring transmitted drug resistance mutations (TDRM) are detected. For some TDRM it has been shown that they revert to wild type while other mutations persist in the absence of therapy. To understand the mechanisms explaining persistence we investigated the in vivo evolution of frequently transmitted HIV-1 variants and their impact on in vitro replicative capacity. Results: We selected 31 individuals infected with HIV-1 harboring frequently observed TDRM such as M41L or K103N in reverse transcriptase (RT) or M46L in protease. In all these samples, polymorphisms at non-TDRM positions were present at baseline (median protease: 5, RT: 6). Extensive analysis of viral evolution of protease and RT demonstrated that the majority of TDRM (51/55) persisted for at least a year and even up to eight years in the plasma. D

The Global Spread of Hepatitis C Virus 1a and 1b: A Phylodynamic and Phylogeographic Analysis

Using phylodynamic and phylogeographic methods, Angelos Hatzakis and colleagues find that the global spread of Hepatitis C virus coincided with widespread use of transfused blood and with the expansion of intravenous drug use

Rationale for our approach.

<p>Rationale for our approach.</p

Presumed evolution of the <i>deltaretrovirus</i> pX region.

<p>The deltaretrovirus phylogeny is shown as a cladogram. Conventions are the same as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003162#pcbi-1003162-g003" target="_blank">Figure 3</a>.</p

Prediction of the ancestral frame in overlapping genes from the benchmark dataset.

(1)<p>The last two overlaps have entered their genome by horizontal transfer and are not taken into account for calculations of specificity and sensitivity of the method.</p><p>Abbreviations and conventions are the same as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003162#pcbi-1003162-t002" target="_blank">Table 2</a>. A frame is predicted ancestral if its <i>r_s</i> is positive and significantly higher than the <i>r_s</i> of the other frame (P<0.05, corresponding to t-Hotelling >1.70). If no prediction is possible, the field is left blank. Numerical values are the same as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003162#pcbi-1003162-t003" target="_blank">Table 3</a> for actual frames, but are reproduced here for clarity.</p

Benchmark dataset of 27 overlapping genes with known genealogy.

(1)<p>gene overlaps described previously (see reference <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003162#pcbi.1003162-Rancurel1" target="_blank">[3]</a>).</p>(2)<p>additional overlaps collected for this study.</p>(3)<p>The function is that of the overlapping region of the protein; if it is not known, the field is left blank.</p>(4)<p>The NS2 proteins of <i>brevidensoviruses</i> and that of <i>densoviruses</i> are not homologous (they are encoded in different frames relative to NS1).</p>(5)<p>The <i>alphacarmotetravirus</i> polymerase and <i>machlomovirus</i> capsid have originated by horizontal transfer and thus the two corresponding overlaps are not part of the benchmark dataset, although we perform the same analyses on them than on other overlaps(see text).</p><p>Abbreviations: AAP, assembly-activating protein; dsRNA, double-stranded RNA; C-term, C-terminal; L, large envelope protein; MP, movement protein; NABP, nucleic-acid binding protein; NS, non-structural protein; NSs, non-structural protein of the small RNA segment; N-term, N-terminal; Pog, predicted overlapping gene; Pol, Polymerase; SAT, small alternatively translated protein; ssDNA, single-stranded DNA; ssRNA, single-stranded RNA (+, positive or −, negative); TGBp2, Triple Gene Block protein 2; TGBp3, Triple Gene Block protein 3; VP, viral protein.</p

A genomic hotspot of origination of silencing suppressors in plus-strand RNA viruses.

<p>The replicases of <i>Nodaviridae</i> and <i>Bromoviridae</i> contain C-terminal extensions predicted disordered (thin boxes) downstream of their homologous polymerase (RdRP) domain. These extensions encode structurally unrelated suppressors of RNA silencing, B2 and 2b (PDB accession codes respectively 2AZ2 and 2ZI0) in different reading frames. Neither the C-terminal extensions nor the suppressors of RNA silencing have detectable sequence similarity, even between closely related genera. Which region is ancestral in each overlap could not be determined (see text).</p

Analysis of the codon usage of overlapping frames from the benchmark dataset.

<p>Abbreviations are the same as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003162#pcbi-1003162-t001" target="_blank">Table 1</a>. The last two overlaps have entered their genome by horizontal transfer (see text).</p><p><i>r_sA</i> is the Spearman rank correlation coefficient <i>r_s</i> between the codon usage of the ancestral frame and that of its genome. <i>r_sN</i> is the equivalent coefficient for the <i>de novo</i> frame. N_A and N_N are the number of codons on which <i>r_sA</i> and <i>r_sN</i> were calculated. The first row indicates whether calculations are presented for the actual overlapping frames or for the corresponding simulated frames. The calculation of P for the actual frames is based on Hotelling's t-test, whereas for simulated frames P is based on the distribution of the simulated <i>d₂₁</i> (see text). Agreement between t-Hotelling and simulation is calculated on the basis of whether corresponding P-values are both <0.05 or >0.05.</p

Prediction, by codon usage, of the ancestral frame in overlapping reading frames with identical phylogenetic distribution.

<p>Conventions are the same as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003162#pcbi-1003162-t003" target="_blank">Table 3</a>. A frame is predicted ancestral if its <i>r_s</i> is positive and significantly higher than the <i>r_s</i> of the other frame (P<0.05, corresponding to t-Hotelling>1.70).</p