Mutational Correlates of Virological Failure in Individuals Receiving a WHO-Recommended Tenofovir-Containing First-Line Regimen: An International Collaboration

Tenofovir disoproxil fumarate (TDF) genotypic resistance defined by K65R/N and/or K70E/Q/G occurs in 20% to 60% of individuals with virological failure (VF) on a WHO-recommended TDF-containing first-line regimen. However, the full spectrum of reverse transcriptase (RT) mutations selected in individuals with VF on such a regimen is not known. To identify TDF regimen-associated mutations (TRAMs), we compared the proportion of each RT mutation in 2873 individuals with VF on a WHO-recommended first-line TDF-containing regimen to its proportion in a cohort of 50,803 antiretroviral-naïve individuals. To identify TRAMs specifically associated with TDF-selection pressure, we compared the proportion of each TRAM to its proportion in a cohort of 5805 individuals with VF on a first-line thymidine analog-containing regimen. We identified 83 TRAMs including 33 NRTI-associated, 40 NNRTI-associated, and 10 uncommon mutations of uncertain provenance. Of the 33 NRTI-associated TRAMs, 12 - A62V, K65R/N, S68G/N/D, K70E/Q/T, L74I, V75L, and Y115F - were more common among individuals receiving a first-line TDF-containing compared to a first-line thymidine analog-containing regimen. These 12 TDF-selected TRAMs will be important for monitoring TDF-associated transmitted drug-resistance and for determining the extent of reduced TDF susceptibility in individuals with VF on a TDF-containing regimen.

Hydrocephalus secondary to obstruction of the lateral apertures in two dogs

BACKGROUND

Traditionally, hydrocephalus is divided into communicating or non-communicating (obstructive) based on the identification of a blockage of cerebrospinal fluid (CSF) flow through the ventricular system. Hydrocephalus ex vacuo refers to ventricular enlargement as a consequence of neuroparenchymal loss. Hydrocephalus related to obstruction of the lateral apertures of the fourth ventricles has rarely been described.

CASE REPORT

The clinicopathologic findings in two dogs with hydrocephalus secondary to obstruction of the lateral apertures of the fourth ventricle are reported. Signs were associated with a caudal cervical spinal cord lesion in one dog and a caudal brain stem lesion in the other dog. Magnetic resonance imaging (MRI) disclosed dilation of the ventricular system, including the lateral recesses of the fourth ventricle. In one dog, postmortem ventriculography confirmed obstruction of the lateral apertures. Microscopic changes were identified in the choroid plexus in both dogs, yet a definitive cause of the obstructions was not identified. The MRI findings in both dogs are similar to membranous occlusion of the lateral and median apertures in human patients.

CONCLUSION

MRI detection of dilation of the entire ventricular system in the absence of an identifiable cause should prompt consideration of an obstruction of the lateral apertures. In future cases, therapeutic interventions aimed at re-establishing CSF flow or ventriculoperitoneal catheterisation should be considered.

DADA2: High-resolution sample inference from Illumina amplicon data

We present the open-source software package DADA2 for modeling and correcting Illumina-sequenced amplicon errors (https://github.com/benjjneb/dada2). DADA2 infers sample sequences exactly and resolves differences of as little as 1 nucleotide. In several mock communities, DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or nonparametric. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests and nonparametric testing using community networks and the ggnetwork package.

Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, whether parametric or nonparametric. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests and nonparametric testing using community networks and the ggnetwork package.

Interpreting Prevotella and Bacteroides as biomarkers of diet and lifestyle

BACKGROUND

In a series of studies of the gut microbiome, "enterotypes" have been used to classify gut microbiome samples that cluster together in ordination analyses. Initially, three distinct enterotypes were described, although later studies reduced this to two clusters, one dominated by Bacteroides or Clostridiales species found more commonly in Western (American and Western European) subjects and the other dominated by Prevotella more often associated with non-Western subjects. The two taxa, Bacteroides and Prevotella, have been presumed to represent consistent underlying microbial communities, but no one has demonstrated the presence of additional microbial taxa across studies that can define these communities.

RESULTS

We analyzed the combined microbiome data from five previous studies with samples across five continents. We clearly demonstrate that there are no consistent bacterial taxa associated with either Bacteroides- or Prevotella-dominated communities across the studies. By increasing the number and diversity of samples, we found gradients of both Bacteroides and Prevotella and a lack of the distinct clusters in the principal coordinate plots originally proposed in the "enterotypes" hypothesis. The apparent segregation of the samples seen in many ordination plots is due to the differences in the samples' Prevotella and Bacteroides abundances and does not represent consistent microbial communities within the "enterotypes" and is not associated with other taxa across studies. The projections we see are consistent with a continuum of values created from a simple mixture of Bacteroides and Prevotella; these two biomarkers are significantly correlated to the projection axes. We suggest that previous findings citing Bacteroides- and Prevotella-dominated clusters are the result of an artifact caused by the greater relative abundance of these two taxa over other taxa in the human gut and the sparsity of Prevotella abundant samples.

CONCLUSIONS

We believe that the term "enterotypes" is misleading because it implies both an underlying consistency of community taxa and a clear separation of sets of human gut samples, neither of which is supported by the broader data. We propose the use of "biomarker" as a more accurate description of these and other taxa that correlate with diet, lifestyle, and disease state.

More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1

In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistance mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here, we use 6717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely.

DOI:http://dx.doi.org/10.7554/eLife.10670.001

In the early days of HIV therapy, the strains of the virus that infected patients frequently evolved drug resistance and the therapies would often eventually fail. These treatments generally involved using a single anti-viral drug. Nowadays, better therapies involving combinations of several anti-viral drugs are available and drug resistance in HIV is a much rarer occurrence. This means that now a particular therapy may be an effective treatment for an HIV-infected individual over much longer periods of time.

A theory of population genetics predicts that when it is easy for a population to acquire a beneficial genetic mutation – like one that provides drug resistance – multiple versions of that mutation may spread in the population at the same time. This is called a soft selective sweep. However, when beneficial mutations occur only rarely, it is expected that only one version of that mutation will take over in a population, which is known as a hard selective sweep.

Here, Feder et al. test this theory using data from 6717 patients with HIV who were treated between 1989 and 2013 using a variety of different drug therapies. The experiments aimed to find out whether the transition from the older drug therapies –where the virus frequently acquired resistance – to the newer, more effective drugs was associated with a transition from soft to hard sweeps.

Feder et al. find that HIV more often evolved drug resistance via soft sweeps in patients treated with the less effective drug combinations (like those given in the early days of HIV treatment), while hard sweeps were more common with the more effective drug combinations. This suggests that good drug combinations may allow fewer drug resistance mutations to occur in the HIV population within a patient. This may be because there are fewer virus particles in these patients, or because the specific combinations of mutations that provide resistance occur less often. Feder et al.’s findings are a step towards understanding why modern HIV treatments work so well, which will ultimately help us find better treatments for other infectious diseases.

DOI:http://dx.doi.org/10.7554/eLife.10670.002

Marine mammals harbor unique microbiotas shaped by and yet distinct from the sea

Marine mammals play crucial ecological roles in the oceans, but little is known about their microbiotas. Here we study the bacterial communities in 337 samples from 5 body sites in 48 healthy dolphins and 18 healthy sea lions, as well as those of adjacent seawater and other hosts. The bacterial taxonomic compositions are distinct from those of other mammals, dietary fish and seawater, are highly diverse and vary according to body site and host species. Dolphins harbour 30 bacterial phyla, with 25 of them in the mouth, several abundant but poorly characterized Tenericutes species in gastric fluid and a surprisingly paucity of Bacteroidetes in distal gut. About 70% of near-full length bacterial 16S ribosomal RNA sequences from dolphins are unique. Host habitat, diet and phylogeny all contribute to variation in marine mammal distal gut microbiota composition. Our findings help elucidate the factors structuring marine mammal microbiotas and may enhance monitoring of marine mammal health.

Variation in Taxonomic Composition of the Fecal Microbiota in an Inbred Mouse Strain across Individuals and Time

Genetics, diet, and other environmental exposures are thought to be major factors in the development and composition of the intestinal microbiota of animals. However, the relative contributions of these factors in adult animals, as well as variation with time in a variety of important settings, are still not fully understood. We studied a population of inbred, female mice fed the same diet and housed under the same conditions. We collected fecal samples from 46 individual mice over two weeks, sampling four of these mice for periods as long as 236 days for a total of 190 samples, and determined the phylogenetic composition of their microbial communities after analyzing 1,849,990 high-quality pyrosequencing reads of the 16S rRNA gene V3 region. Even under these controlled conditions, we found significant inter-individual variation in community composition, as well as variation within an individual over time, including increases in alpha diversity during the first 2 months of co-habitation. Some variation was explained by mouse membership in different cage and vendor shipment groups. The differences among individual mice from the same shipment group and cage were still significant. Overall, we found that 23% of the variation in intestinal microbiota composition was explained by changes within the fecal microbiota of a mouse over time, 12% was explained by persistent differences among individual mice, 14% by cage, and 18% by shipment group. Our findings suggest that the microbiota of controlled populations of inbred laboratory animals may not be as uniform as previously thought, that animal rearing and handling may account for some variation, and that as yet unidentified factors may explain additional components of variation in the composition of the microbiota within populations and individuals over time. These findings have implications for the design and interpretation of experiments involving laboratory animals.

Genetically dictated change in host mucus carbohydrate landscape exerts a diet-dependent effect on the gut microbiota

We investigate how host mucus glycan composition interacts with dietary carbohydrate content to influence the composition and expressed functions of a human gut community. The humanized gnotobiotic mice mimic humans with a nonsecretor phenotype due to knockout of their α1-2 fucosyltransferase (Fut2) gene. The fecal microbiota of Fut2(-) mice that lack fucosylated host glycans show decreased alpha diversity relative to Fut2(+) mice and exhibit significant differences in community composition. A glucose-rich plant polysaccharide-deficient (PD) diet exerted a strong effect on the microbiota membership but eliminated the effect of Fut2 genotype. Additionally fecal metabolites predicted host genotype in mice on a polysaccharide-rich standard diet but not on a PD diet. A more detailed mechanistic analysis of these interactions involved colonization of gnotobiotic Fut2(+) and Fut2(-) mice with Bacteroides thetaiotaomicron, a prominent member of the human gut microbiota known to adaptively forage host mucosal glycans when dietary polysaccharides are absent. Within Fut2(-) mice, the B. thetaiotaomicron fucose catabolic pathway was markedly down-regulated, whereas BT4241-4247, an operon responsive to terminal β-galactose, the precursor that accumulates in the Fut2(-) mice, was significantly up-regulated. These changes in B. thetaiotaomicron gene expression were only evident in mice fed a PD diet, wherein B. thetaiotaomicron relies on host mucus consumption. Furthermore, up-regulation of the BT4241-4247 operon was also seen in humanized Fut2(-) mice. Together, these data demonstrate that differences in host genotype that affect the carbohydrate landscape of the distal gut interact with diet to alter the composition and function of resident microbes in a diet-dependent manner.

PRC2/EED-EZH2 complex is up-regulated in breast cancer lymph node metastasis compared to primary tumor and correlates with tumor proliferation in situ

BACKGROUND

Lymph node metastasis is a key event in the progression of breast cancer. Therefore it is important to understand the underlying mechanisms which facilitate regional lymph node metastatic progression.

METHODOLOGY/PRINCIPAL FINDINGS

We performed gene expression profiling of purified tumor cells from human breast tumor and lymph node metastasis. By microarray network analysis, we found an increased expression of polycomb repression complex 2 (PRC2) core subunits EED and EZH2 in lymph node metastatic tumor cells over primary tumor cells which were validated through real-time PCR. Additionally, immunohistochemical (IHC) staining and quantitative image analysis of whole tissue sections showed a significant increase of EZH2 expressing tumor cells in lymph nodes over paired primary breast tumors, which strongly correlated with tumor cell proliferation in situ. We further explored the mechanisms of PRC2 gene up-regulation in metastatic tumor cells and found up-regulation of E2F genes, MYC targets and down-regulation of tumor suppressor gene E-cadherin targets in lymph node metastasis through GSEA analyses. Using IHC, the expression of potential EZH2 target, E-cadherin was examined in paired primary/lymph node samples and was found to be significantly decreased in lymph node metastases over paired primary tumors.

CONCLUSIONS/SIGNIFICANCE

This study identified an over expression of the epigenetic silencing complex PRC2/EED-EZH2 in breast cancer lymph node metastasis as compared to primary tumor and its positive association with tumor cell proliferation in situ. Concurrently, PRC2 target protein E-cadherin was significant decreased in lymph node metastases, suggesting PRC2 promotes epithelial mesenchymal transition (EMT) in lymph node metastatic process through repression of E-cadherin. These results indicate that epigenetic regulation mediated by PRC2 proteins may provide additional advantage for the outgrowth of metastatic tumor cells in lymph nodes. This opens up epigenetic drug development possibilities for the treatment and prevention of lymph node metastasis in breast cancer.

Denoising PCR-amplified metagenome data

Background

PCR amplification and high-throughput sequencing theoretically enable the characterization of the finest-scale diversity in natural microbial and viral populations, but each of these methods introduces random errors that are difficult to distinguish from genuine biological diversity. Several approaches have been proposed to denoise these data but lack either speed or accuracy.

Results

We introduce a new denoising algorithm that we call DADA (Divisive Amplicon Denoising Algorithm). Without training data, DADA infers both the sample genotypes and error parameters that produced a metagenome data set. We demonstrate performance on control data sequenced on Roche’s 454 platform, and compare the results to the most accurate denoising software currently available, AmpliconNoise.

Conclusions

DADA is more accurate and over an order of magnitude faster than AmpliconNoise. It eliminates the need for training data to establish error parameters, fully utilizes sequence-abundance information, and enables inclusion of context-dependent PCR error rates. It should be readily extensible to other sequencing platforms such as Illumina.

Magnetic resonance imaging for the differentiation of neoplastic, inflammatory, and cerebrovascular brain disease in dogs

BACKGROUND

The reliability and validity of magnetic resonance imaging (MRI) for detecting neoplastic, inflammatory, and cerebrovascular brain lesions in dogs are unknown.

OBJECTIVES

To estimate sensitivity, specificity, and inter-rater agreement of MRI for classifying histologically confirmed neoplastic, inflammatory, and cerebrovascular brain disease in dogs.

ANIMALS

One hundred and twenty-one client-owned dogs diagnosed with brain disease (n = 77) or idiopathic epilepsy (n = 44).

METHODS

Retrospective, multi-institutional case series; 3 investigators analyzed MR images for the presence of a brain lesion with and without knowledge of case clinical data. Investigators recorded most likely etiologic category (neoplastic, inflammatory, cerebrovascular) and most likely specific disease for all brain lesions. Sensitivity, specificity, and inter-rater agreement were calculated to estimate diagnostic performance.

RESULTS

MRI was 94.4% sensitive (95% confidence interval [CI] = 88.7, 97.4) and 95.5% specific (95% CI = 89.9, 98.1) for detecting a brain lesion with similarly high performance for classifying neoplastic and inflammatory disease, but was only 38.9% sensitive for classifying cerebrovascular disease (95% CI = 16.1, 67.0). In general, high specificity but not sensitivity was retained for MR diagnosis of specific brain diseases. Inter-rater agreement was very good for overall detection of structural brain lesions (κ = 0.895, 95% CI = 0.792, 0.998, P < .001) and neoplastic lesions, but was only fair for cerebrovascular lesions (κ = 0.299, 95% CI = 0, 0.761, P = .21).

CONCLUSIONS AND CLINICAL IMPORTANCE

MRI is sensitive and specific for identifying brain lesions and classifying disease as inflammatory or neoplastic in dogs. Cerebrovascular disease in general and specific inflammatory, neoplastic, and cerebrovascular brain diseases were frequently misclassified.

Magnetic resonance imaging enhancement of intervertebral disc disease in 30 dogs following chemical fat saturation

OBJECTIVE

To describe the patterns of enhancement of extradural intervertebral disc on chemically fat saturated gadolinium-enhanced magnetic resonance images and to investigate the clinical and pathological associations with enhancement.

METHODS

Medical records and magnetic resonance images were reviewed from 30 dogs with histopathologically confirmed disc disease and enhancement on a T1-weighted postcontrast fat saturated sequence.

RESULTS

Median duration of neurological signs was 4 days and the most common grade of severity was II, seen in 46·6% of dogs. Homogeneous, heterogeneous and peripheral patterns of disc enhancement were described, with peripheral enhancement most commonly identified (57% of dogs). There were no clinical or pathological differences between the dogs with each of the patterns. The mean signal intensity of a region of interest within the extruded disc material and contrast-to-noise ratio of the disc material were significantly higher on postcontrast T1-weighted fat saturated images (P=<0·0001 each).

CLINICAL SIGNIFICANCE

The use of fat saturated gadolinium-enhanced magnetic resonance imaging can detect enhancement of extradural disc material. Patterns of enhancement are not associated with the clinical presentation or pathological features.

A multifaceted analysis of HIV-1 protease multidrug resistance phenotypes

Background

Great strides have been made in the effective treatment of HIV-1 with the development of second-generation protease inhibitors (PIs) that are effective against historically multi-PI-resistant HIV-1 variants. Nevertheless, mutation patterns that confer decreasing susceptibility to available PIs continue to arise within the population. Understanding the phenotypic and genotypic patterns responsible for multi-PI resistance is necessary for developing PIs that are active against clinically-relevant PI-resistant HIV-1 variants.

Results

In this work, we use globally optimal integer programming-based clustering techniques to elucidate multi-PI phenotypic resistance patterns using a data set of 398 HIV-1 protease sequences that have each been phenotyped for susceptibility toward the nine clinically-approved HIV-1 PIs. We validate the information content of the clusters by evaluating their ability to predict the level of decreased susceptibility to each of the available PIs using a cross validation procedure. We demonstrate the finding that as a result of phenotypic cross resistance, the considered clinical HIV-1 protease isolates are confined to ~6% or less of the clinically-relevant phenotypic space. Clustering and feature selection methods are used to find representative sequences and mutations for major resistance phenotypes to elucidate their genotypic signatures. We show that phenotypic similarity does not imply genotypic similarity, that different PI-resistance mutation patterns can give rise to HIV-1 isolates with similar phenotypic profiles.

Conclusion

Rather than characterizing HIV-1 susceptibility toward each PI individually, our study offers a unique perspective on the phenomenon of PI class resistance by uncovering major multidrug-resistant phenotypic patterns and their often diverse genotypic determinants, providing a methodology that can be applied to understand clinically-relevant phenotypic patterns to aid in the design of novel inhibitors that target other rapidly evolving molecular targets as well.

Adaptive importance sampling for network growth models

Network Growth Models such as Preferential Attachment and Duplication/Divergence are popular generative models with which to study complex networks in biology, sociology, and computer science. However, analyzing them within the framework of model selection and statistical inference is often complicated and computationally difficult, particularly when comparing models that are not directly related or nested. In practice, ad hoc methods are often used with uncertain results. If possible, the use of standard likelihood-based statistical model selection techniques is desirable. With this in mind, we develop an Adaptive Importance Sampling algorithm for estimating likelihoods of Network Growth Models. We introduce the use of the classic Plackett-Luce model of rankings as a family of importance distributions. Updates to importance distributions are performed iteratively via the Cross-Entropy Method with an additional correction for degeneracy/over-fitting inspired by the Minimum Description Length principle. This correction can be applied to other estimation problems using the Cross-Entropy method for integration/approximate counting, and it provides an interpretation of Adaptive Importance Sampling as iterative model selection. Empirical results for the Preferential Attachment model are given, along with a comparison to an alternative established technique, Annealed Importance Sampling.

A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads

MOTIVATION

G → A hypermutation is an innate antiviral defense mechanism, mediated by host enzymes, which leads to the mutational impairment of viruses. Sensitive and specific identification of host-mediated G → A hypermutation is a novel sequence analysis challenge, particularly for viral deep sequencing studies. For example, two of the most common hepatitis B virus (HBV) reverse transcriptase (RT) drug-resistance mutations, A181T and M204I, arise from G → A changes and are routinely detected as low-abundance variants in nearly all HBV deep sequencing samples.

RESULTS

We developed a classification model using measures of G → A excess and predicted indicators of lethal mutation and applied this model to 325 920 unique deep sequencing reads from plasma virus samples from 45 drug treatment-naïve HBV-infected individuals. The 2.9% of sequence reads that were classified as hypermutated by our model included most of the reads with A181T and/or M204I, indicating the usefulness of this model for distinguishing viral adaptive changes from host-mediated viral editing.

AVAILABILITY

Source code and sequence data are available at http://hivdb.stanford.edu/pages/resources.html.

CONTACT

ereuman@stanfordalumni.org

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Constrained patterns of covariation and clustering of HIV-1 non-nucleoside reverse transcriptase inhibitor resistance mutations

Objectives

We characterized pairwise and higher order patterns of non-nucleoside reverse transcriptase inhibitor (NNRTI)-selected mutations because multiple mutations are usually required for clinically significant resistance to second-generation NNRTIs.

Patients and methods

We analysed viruses from 13 039 individuals with sequences containing at least one of 52 published NNRTI-selected mutations, including 1133 viruses from individuals who received efavirenz but no other NNRTI and 1510 viruses from individuals who received nevirapine but no other NNRTI. Of the 17 reported etravirine resistance-associated mutations (RAMs), Y181C/I/V, L100I, K101P and M230L were considered major based on published in vitro susceptibility data.

Results

Efavirenz preferentially selected for 16 mutations, including L100I (14% versus 0.1%, P < 0.001), K101P (3.3% versus 0.4%, P < 0.001) and M230L (2.8% versus 1.3%, P = 0.004), whereas nevirapine preferentially selected for 12 mutations, including Y181C/I/V (48% versus 6.9%, P < 0.001). Twenty-nine pairs of NNRTI-selected mutations covaried significantly, including Y181C with seven other mutations (A98G, K101E/H, V108I, G190A/S and H221Y), L100I with K103N, and K101P with K103S. Two pairs (Y181C + V179F and Y181C + G190S) were predicted to confer >10-fold decreased etravirine susceptibility. Seventeen percent of sequences had three or more NNRTI-selected mutations, mostly in clusters of covarying mutations. Many clusters had Y181C plus a non-major etravirine RAM; few had more than one major etravirine RAM.

Conclusions

Although major etravirine RAMs rarely occur in combination, 2 of 29 pairs of covarying mutations were associated with >10-fold decreased etravirine susceptibility. Viruses with three or more NNRTI-selected mutations often contained Y181C in combination with one or more minor etravirine RAMs; however, phenotypic and clinical correlates for most of these higher order combinations have not been published.

Ultra-deep pyrosequencing of hepatitis B virus quasispecies from nucleoside and nucleotide reverse-transcriptase inhibitor (NRTI)-treated patients and NRTI-naive patients

The dynamics of emerging nucleoside and nucleotide reverse-transcriptase inhibitor (NRTI) resistance in hepatitis B virus (HBV) are not well understood because standard dideoxynucleotide direct polymerase chain reaction (PCR) sequencing assays detect drug-resistance mutations only after they have become dominant. To obtain insight into NRTI resistance, we used a new sequencing technology to characterize the spectrum of low-prevalence NRTI-resistance mutations in HBV obtained from 20 plasma samples from 11 NRTI-treated patients and 17 plasma samples from 17 NRTI-naive patients, by using standard direct PCR sequencing and ultra-deep pyrosequencing (UDPS). UDPS detected drug-resistance mutations that were not detected by PCR in 10 samples from 5 NRTI-treated patients, including the lamivudine-resistance mutation V173L (in 5 samples), the entecavir-resistance mutations T184S (in 2 samples) and S202G (in 1 sample), the adefovir-resistance mutation N236T (in 1 sample), and the lamivudine and adefovir-resistance mutations V173L, L180M, A181T, and M204V (in 1 sample). G-to-A hypermutation mediated by the apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like family of cytidine deaminases was estimated to be present in 0.6% of reverse-transcriptase genes. Genotype A coinfection was detected by UDPS in each of 3 patients in whom genotype G virus was detected by direct PCR sequencing. UDPS detected low-prevalence HBV variants with NRTI-resistance mutations, G-to-A hypermutation, and low-level dual genotype infection with a sensitivity not previously possible.

Natural variation of HIV-1 group M integrase: implications for a new class of antiretroviral inhibitors

HIV-1 integrase is the third enzymatic target of antiretroviral (ARV) therapy. However, few data have been published on the distribution of naturally occurring amino acid variation in this enzyme. We therefore characterized the distribution of integrase variants among more than 1,800 published group M HIV-1 isolates from more than 1,500 integrase inhibitor (INI)-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the central core domain positions, 42% of the C-terminal domain positions, and 50% of the N-terminal domain positions. Among 727 ARV-naïve individuals in whom the complete pol gene was sequenced, integrase displayed significantly decreased inter- and intra-subtype diversity and a lower Shannon's entropy than protease or RT. All primary INI-resistance mutations with the exception of E157Q--which was present in 1.1% of sequences--were nonpolymorphic. Several accessory INI-resistance mutations including L74M, T97A, V151I, G163R, and S230N were also polymorphic with polymorphism rates ranging between 0.5% to 2.0%.

HIV-1 subtype B protease and reverse transcriptase amino acid covariation

Despite the high degree of HIV-1 protease and reverse transcriptase (RT) mutation in the setting of antiretroviral therapy, the spectrum of possible virus variants appears to be limited by patterns of amino acid covariation. We analyzed patterns of amino acid covariation in protease and RT sequences from more than 7,000 persons infected with HIV-1 subtype B viruses obtained from the Stanford HIV Drug Resistance Database (http://hivdb.stanford.edu). In addition, we examined the relationship between conditional probabilities associated with a pair of mutations and the order in which those mutations developed in viruses for which longitudinal sequence data were available. Patterns of RT covariation were dominated by the distinct clustering of Type I and Type II thymidine analog mutations and the Q151M-associated mutations. Patterns of protease covariation were dominated by the clustering of nelfinavir-associated mutations (D30N and N88D), two main groups of protease inhibitor (PI)-resistance mutations associated either with V82A or L90M, and a tight cluster of mutations associated with decreased susceptibility to amprenavir and the most recently approved PI darunavir. Different patterns of covariation were frequently observed for different mutations at the same position including the RT mutations T69D versus T69N, L74V versus L74I, V75I versus V75M, T215F versus T215Y, and K219Q/E versus K219N/R, and the protease mutations M46I versus M46L, I54V versus I54M/L, and N88D versus N88S. Sequence data from persons with correlated mutations in whom earlier sequences were available confirmed that the conditional probabilities associated with correlated mutation pairs could be used to predict the order in which the mutations were likely to have developed. Whereas accessory nucleoside RT inhibitor-resistance mutations nearly always follow primary nucleoside RT inhibitor-resistance mutations, accessory PI-resistance mutations often preceded primary PI-resistance mutations.

Down-regulation of the interferon signaling pathway in T lymphocytes from patients with metastatic melanoma

BACKGROUND

Dysfunction of the immune system has been documented in many types of cancers. The precise nature and molecular basis of immune dysfunction in the cancer state are not well defined.

METHODS AND FINDINGS

To gain insights into the molecular mechanisms of immune dysfunction in cancer, gene expression profiles of pure sorted peripheral blood lymphocytes from 12 patients with melanoma were compared to 12 healthy controls. Of 25 significantly altered genes in T cells and B cells from melanoma patients, 17 are interferon (IFN)-stimulated genes. These microarray findings were further confirmed by quantitative PCR and functional responses to IFNs. The median percentage of lymphocytes that phosphorylate STAT1 in response to interferon-alpha was significantly reduced (Delta = 16.8%; 95% confidence interval, 0.98% to 33.35%) in melanoma patients (n = 9) compared to healthy controls (n = 9) in Phosflow analysis. The Phosflow results also identified two subgroups of patients with melanoma: IFN-responsive (33%) and low-IFN-response (66%). The defect in IFN signaling in the melanoma patient group as a whole was partially overcome at the level of expression of IFN-stimulated genes by prolonged stimulation with the high concentration of IFN-alpha that is achievable only in IFN therapy used in melanoma. The lowest responders to IFN-alpha in the Phosflow assay also showed the lowest gene expression in response to IFN-alpha. Finally, T cells from low-IFN-response patients exhibited functional abnormalities, including decreased expression of activation markers CD69, CD25, and CD71; TH1 cytokines interleukin-2, IFN-gamma, and tumor necrosis factor alpha, and reduced survival following stimulation with anti-CD3/CD28 antibodies compared to controls.

CONCLUSIONS

Defects in interferon signaling represent novel, dominant mechanisms of immune dysfunction in cancer. These findings may be used to design therapies to counteract immune dysfunction in melanoma and to improve cancer immunotherapy.

Rapid assessment of recognition efficiency and functional capacity of antigen-specific T-cell responses

It is increasingly recognized that cells within an antigen-specific CD8 T-cell population may be diverse in recognition efficiency for target, which may significantly affect the overall efficacy of the response in clinical settings such as viral infections and cancer. CD8 T cells with seemingly identical antigen specificity, particularly those elicited by cancer vaccines, may be heterogeneous for sensitivity and recognition efficiency for the cognate peptide and functional state in vivo. Analysis of individual T-cell clones derived from an antigen-specific T-cell population would provide an accurate assessment of the overall response; however, this is time- and labor-intensive, preventing rapid and routine assessment of patient samples from clinical trials. By stimulating antigen-specific T cells that otherwise appear homogeneous on tetramer staining with graded amounts of cognate peptides, the authors show that individual cells downmodulate surface T-cell receptors (TCR) and thus lose tetramer reactivity with variable dynamics within the T-cell population. The dynamics of TCR downregulation represent an accurate assessment of an individual cell's antigen sensitivity, recognition efficiency, and relative functional state within an antigen-specific population and have direct correlation to killing capacity by chromium release as well as degranulation by CD107 mobilization. Furthermore, despite correlation of average T-cell function by all three techniques, TCR downregulation uncovered heterogeneity in T-cell responses after vaccination among patient samples directly ex vivo. When examined using this novel technique, antigen-specific T cells elicited by vaccination with heteroclitic peptides exhibited significantly different recognition efficiencies for the heteroclitic versus native peptides, translating into differences in functional responses. With advancing cancer vaccine trials, the capacity to detect and functionally characterize antigen-specific T-cell responses in detail is critical. Techniques, as presented here, that rapidly assess the overall antigen sensitivity, recognition efficiency, and functional status of patients' T-cell responses will guide future vaccine trials and immunotherapies.