Nod1-dependent NF-kB activation initiates hematopoietic stem cell specification in response to small Rho GTPases

Uncovering the mechanisms regulating hematopoietic specification not only would overcome current limitations related to hematopoietic stem and progenitor cell (HSPC) transplantation, but also advance cellular immunotherapies. However, generating functional human induced pluripotent stem cell (hiPSC)-derived HSPCs and their derivatives has been elusive, necessitating a better understanding of the developmental mechanisms that trigger HSPC specification. Here, we reveal that early activation of the Nod1-Ripk2-NF-kB inflammatory pathway in endothelial cells (ECs) primes them to switch fate towards definitive hemogenic endothelium, a pre-requisite to specify HSPCs. Our genetic and chemical embryonic models show that HSPCs fail to specify in the absence of Nod1 and its downstream kinase Ripk2 due to a failure on hemogenic endothelial (HE) programming, and that small Rho GTPases coordinate the activation of this pathway. Manipulation of NOD1 in a human system of definitive hematopoietic differentiation indicates functional conservation. This work establishes the RAC1-NOD1-RIPK2-NF-kB axis as a critical intrinsic inductor that primes ECs prior to HE fate switch and HSPC specification. Manipulation of this pathway could help derive a competent HE amenable to specify functional patient specific HSPCs and their derivatives for the treatment of blood disorders.

An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species

Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set of genes known to confer resistance was able to accurately predict isolate resistance on average (mean F1 score = 98.0%, SD = 2.3%, mean accuracy = 98.2%, SD = 2.7%). However, fitted models sometimes varied for antibiotics in the same class and for the same antibiotic across animal hosts, suggesting heterogeneity in the genetic determinants of AMR resistance. We conclude that an interpretable AMR prediction model can be used to accurately predict resistance phenotypes across multiple host species and reveal testable hypotheses about how the mechanism of resistance may vary across antibiotics within the same class and across animal hosts for the same antibiotic.

Unsupervised contrastive peak caller for ATAC-seq

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is a common assay to identify chromatin accessible regions by using a Tn5 transposase that can access, cut, and ligate adapters to DNA fragments for subsequent amplification and sequencing. These sequenced regions are quantified and tested for enrichment in a process referred to as "peak calling." Most unsupervised peak calling methods are based on simple statistical models and suffer from elevated false positive rates. Newly developed supervised deep learning methods can be successful, but they rely on high quality labeled data for training, which can be difficult to obtain. Moreover, though biological replicates are recognized to be important, there are no established approaches for using replicates in the deep learning tools, and the approaches available for traditional methods either cannot be applied to ATAC-seq, where control samples may be unavailable, or are post hoc and do not capitalize on potentially complex, but reproducible signal in the read enrichment data. Here, we propose a novel peak caller that uses unsupervised contrastive learning to extract shared signals from multiple replicates. Raw coverage data are encoded to obtain low-dimensional embeddings and optimized to minimize a contrastive loss over biological replicates. These embeddings are passed to another contrastive loss for learning and predicting peaks and decoded to denoised data under an autoencoder loss. We compared our replicative contrastive learner (RCL) method with other existing methods on ATAC-seq data, using annotations from ChromHMM genomic labels and transcription factor ChIP-seq as noisy truth. RCL consistently achieved the best performance.

Predicting allosteric pockets in protein biological assemblages

MOTIVATION

Allostery enables changes to the dynamic behavior of a protein at distant positions induced by binding. Here, we present APOP, a new allosteric pocket prediction method, which perturbs the pockets formed in the structure by stiffening pairwise interactions in the elastic network across the pocket, to emulate ligand binding. Ranking the pockets based on the shifts in the global mode frequencies, as well as their mean local hydrophobicities, leads to high prediction success when tested on a dataset of allosteric proteins, composed of both monomers and multimeric assemblages.

RESULTS

Out of the 104 test cases, APOP predicts known allosteric pockets for 92 within the top 3 rank out of multiple pockets available in the protein. In addition, we demonstrate that APOP can also find new alternative allosteric pockets in proteins. Particularly interesting findings are the discovery of previously overlooked large pockets located in the centers of many protein biological assemblages; binding of ligands at these sites would likely be particularly effective in changing the protein's global dynamics.

AVAILABILITY AND IMPLEMENTATION

APOP is freely available as an open-source code (https://github.com/Ambuj-UF/APOP) and as a web server at https://apop.bb.iastate.edu/.

Accurate estimation of molecular counts from amplicon sequence data with unique molecular identifiers

MOTIVATION

Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, plus errors during polymerase chain reaction (PCR) and sequencing. One solution attaches unique molecular identifiers (UMIs) to sample sequences before amplification. Counting UMIs instead of sequences provides unbiased estimates of abundance. While modern methods improve over naïve counting by UMI identity, most do not account for UMI reuse or collision, and they do not adequately model PCR and sequencing errors in the UMIs and sample sequences.

RESULTS

We introduce Deduplication and Abundance estimation with UMIs (DAUMI), a probabilistic framework to detect true biological amplicon sequences and accurately estimate their deduplicated abundance. DAUMI recognizes UMI collision, even on highly similar sequences, and detects and corrects most PCR and sequencing errors in the UMI and sampled sequences. DAUMI performs better on simulated and real data compared to other UMI-aware clustering methods.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/DormanLab/AmpliCI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CAPG: comprehensive allopolyploid genotyper

MOTIVATION

Genotyping by sequencing is a powerful tool for investigating genetic variation in plants, but many economically important plants are allopolyploids, where homoeologous similarity obscures the subgenomic origin of reads and confounds allelic and homoeologous SNPs. Recent polyploid genotyping methods use allelic frequencies, rate of heterozygosity, parental cross or other information to resolve read assignment, but good subgenomic references offer the most direct information. The typical strategy aligns reads to the joint reference, performs diploid genotyping within each subgenome, and filters the results, but persistent read misassignment results in an excess of false heterozygous calls.

RESULTS

We introduce the Comprehensive Allopolyploid Genotyper (CAPG), which formulates an explicit likelihood to weight read alignments against both subgenomic references and genotype individual allopolyploids from whole-genome resequencing data. We demonstrate CAPG in allotetraploids, where it performs better than Genome Analysis Toolkit's HaplotypeCaller applied to reads aligned to the combined subgenomic references.

AVAILABILITY AND IMPLEMENTATION

Code and tutorials are available at https://github.com/Kkulkarni1/CAPG.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Coarse-graining protein structures into their dynamic communities with DCI, a dynamic community identifier

SUMMARY

A new dynamic community identifier (DCI) is presented that relies upon protein residue dynamic cross-correlations generated by Gaussian elastic network models to identify those residue clusters exhibiting motions within a protein. A number of examples of communities are shown for diverse proteins, including GPCRs. It is a tool that can immediately simplify and clarify the most essential functional moving parts of any given protein. Proteins usually can be subdivided into groups of residues that move as communities. These are usually densely packed local sub-structures, but in some cases can be physically distant residues identified to be within the same community. The set of these communities for each protein are the moving parts. The ways in which these are organized overall can aid in understanding many aspects of functional dynamics and allostery. DCI enables a more direct understanding of functions including enzyme activity, action across membranes and changes in the community structure from mutations or ligand binding. The DCI server is freely available on a web site (https://dci.bb.iastate.edu/).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Retrospective evaluation of a dose-dependent effect of angiotensin-converting enzyme inhibitors on long-term outcome in dogs with cardiac disease

Background

Angiotensin‐converting enzyme inhibitors (ACEIs) are commonly prescribed in dogs, but the ideal dosage is unknown.

Hypothesis/Objectives

In dogs with cardiac disease, a dose‐response relationship exists for ACEIs with respect to long‐term outcome.

Animals

One hundred forty‐four dogs with cardiac disease, 63 with current or prior congestive heart failure.

Methods

Retrospective medical record review. Cox proportional hazards models were used to determine variables associated with 2‐year survival or survival from first‐onset congestive heart failure (CHF).

Results

Median initial ACEI dosage was 0.84 (interquartile range [IQR], 0.56‐0.98) mg/kg/day, and 108/144 (75%) of dogs received q12h dosing. No clinically relevant changes in renal function test results, serum electrolyte concentrations, or blood pressure occurred between initial prescription of ACEI and first reevaluation (median, 14 days later). In univariable analysis, higher ACEI dose was associated with increased survival from first‐onset CHF (P = .005), and within the subgroup of dogs in CHF at the time of ACEI prescription, higher ACEI dose was associated with improved survival at 2 years (P = .04). In multivariable analysis, q12h dose frequency of ACEI (hazard ratio [HR], 0.30; 95% CI, 0.10‐0.88; P = .03) and higher serum potassium concentration at visit 1 (HR, 0.39; 95% CI, 0.16‐0.97; P = .04) were predictive of 2‐year survival. The ACEIs were well‐tolerated, with only 8/144 (5.6%) dogs having ACEI dose decreased or discontinued because of adverse effects.

Conclusions and Clinical Importance

Twice daily dose frequency might optimize the cardioprotective benefit of ACEIs.

AmpliCI: a high-resolution model-based approach for denoising Illumina amplicon data

Motivation

Next-generation amplicon sequencing is a powerful tool for investigating microbial communities. A main challenge is to distinguish true biological variants from errors caused by amplification and sequencing. In traditional analyses, such errors are eliminated by clustering reads within a sequence similarity threshold, usually 97%, and constructing operational taxonomic units, but the arbitrary threshold leads to low resolution and high false-positive rates. Recently developed ‘denoising’ methods have proven able to resolve single-nucleotide amplicon variants, but they still miss low-frequency sequences, especially those near more frequent sequences, because they ignore the sequencing quality information.

Results

We introduce AmpliCI, a reference-free, model-based method for rapidly resolving the number, abundance and identity of error-free sequences in massive Illumina amplicon datasets. AmpliCI considers the quality information and allows the data, not an arbitrary threshold or an external database, to drive conclusions. AmpliCI estimates a finite mixture model, using a greedy strategy to gradually select error-free sequences and approximately maximize the likelihood. AmpliCI has better performance than three popular denoising methods, with acceptable computation time and memory usage.

Availability and implementation

Source code is available at https://github.com/DormanLab/AmpliCI.

Supplementary information

Supplementary material are available at Bioinformatics online.

Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

Dietary Soluble and Insoluble Fiber With or Without Enzymes Altered the Intestinal Microbiota in Weaned Pigs Challenged With Enterotoxigenic E. coli F18

Post-weaning diarrhea caused by enterotoxigenic E. coli (ETEC) causes significant economic losses for pig producers. This study was to test the hypotheses that an ETEC challenge disrupts intestinal microbial homeostasis and the inclusion of dietary soluble (10% sugar beet pulp) or insoluble fiber (15% corn distillers dried grains with solubles) with or without exogenous carbohydrases will protect or restore the gut microbial homeostasis in weaned pigs. Sixty crossbred piglets (6.9 ± 0.1 kg) were blocked by body weight and randomly assigned to one of six treatments (n = 10), including a non-challenged control (NC), ETEC F18-challenged positive control (PC), ETEC-challenged soluble fiber without (SF-) or with carbohydrases (SF+), and ETEC-challenged insoluble fiber without (IF-) or with carbohydrases (IF+). Pigs were housed individually and orally received either ETEC inoculum or PBS-sham inoculum on day 7 post-weaning. Intestinal contents were collected on day 14 or 15. The V4 region of the bacterial 16S rRNA was amplified and sequenced. High-quality reads (total 6,671,739) were selected and clustered into 3,330 OTUs. No differences were observed in α-diversity among treatments. The ileal microbiota in NC and PC had modest separation in the weighted PCoA plot; the microbial structures were slightly altered by SF+ and IF- compared with PC. The PC increased ileal Escherichia-Shigella (P < 0.01) and numerically decreased Lactobacillus compared to NC. Predicted functional pathways enriched in the ileal microbiota of PC pigs indicated enhanced activity of Gram-negative bacteria, in agreement with increased Escherichia-Shigella. The SF+ tended to decrease (P < 0.10) ileal Escherichia-Shigella compared to PC. Greater abundance of ileal Streptococcus, Turicibacter, and Roseburia and colonic Prevotella were observed in SF- and SF+ than PC (P < 0.05). Pigs fed IF + had greater Lactobacillus and Roseburia than PC pigs (P < 0.05). The ETEC challenge reduced total volatile fatty acid (VFA) compared with NC (P < 0.05). The SF+ tended to increase (P < 0.10) and SF- significantly increased (P < 0.05) colonic total VFA compared with PC. Collectively, ETEC challenge disrupted gut microbial homeostasis and impaired microbial fermentation capacity. Soluble fiber improved VFA production. Dietary fiber and carbohydrases altered microbiota composition to maintain or restore microbial homeostasis.

Dynamics of lentiviral infection in vivo in the absence of adaptive immune responses

Understanding the dynamics of acute viral infection is crucial for developing strategies to prevent and control infection. In this study, lentiviral dynamics in a host without adaptive immunity were examined in order to determine kinetic parameters of infection and quantify the effect of neutralizing antibodies in preventing infection, using mathematical modeling of data from equine infectious anemia virus (EIAV) infection of horses with severe combined immunodeficiency (SCID). Estimated parameters were used to calculate the basic reproductive number and virus doubling time and found that the rate that antibodies neutralized virus was ~18 times greater than the virus clearance rate. These results establish EIAV replication kinetics in SCID horses and the minimal efficacy of antibodies that blocked infection. Furthermore, they indicate that EIAV is at most mildly cytopathic. This study advances our understanding of EIAV infection and may have important implications for the control of other viral infections, including HIV.

Identification of a homogenous structural basis for oligomerization by retroviral Rev-like proteins

Background

Rev-like proteins are post-transcriptional regulatory proteins found in several retrovirus genera, including lentiviruses, betaretroviruses, and deltaretroviruses. These essential proteins mediate the nuclear export of incompletely spliced viral RNA, and act by tethering viral pre-mRNA to the host CRM1 nuclear export machinery. Although all Rev-like proteins are functionally homologous, they share less than 30% sequence identity. In the present study, we computationally assessed the extent of structural homology among retroviral Rev-like proteins within a phylogenetic framework.

Results

We undertook a comprehensive analysis of overall protein domain architecture and predicted secondary structural features for representative members of the Rev-like family of proteins. Similar patterns of α-helical domains were identified for Rev-like proteins within each genus, with the exception of deltaretroviruses, which were devoid of α-helices. Coiled-coil oligomerization motifs were also identified for most Rev-like proteins, with the notable exceptions of HIV-1, the deltaretroviruses, and some small ruminant lentiviruses. In Rev proteins of primate lentiviruses, the presence of predicted coiled-coil motifs segregated within specific primate lineages: HIV-1 descended from SIVs that lacked predicted coiled-coils in Rev whereas HIV-2 descended from SIVs that contained predicted coiled-coils in Rev. Phylogenetic ancestral reconstruction of coiled-coils for all Rev-like proteins predicted a single origin for the coiled-coil motif, followed by three losses of the predicted signal. The absence of a coiled-coil signal in HIV-1 was associated with replacement of canonical polar residues with non-canonical hydrophobic residues. However, hydrophobic residues were retained in the key ‘a’ and ‘d’ positions, and the α-helical region of HIV-1 Rev oligomerization domain could be modeled as a helical wheel with two predicted interaction interfaces. Moreover, the predicted interfaces mapped to the dimerization and oligomerization interfaces in HIV-1 Rev crystal structures. Helical wheel projections of other retroviral Rev-like proteins, including endogenous sequences, revealed similar interaction interfaces that could mediate oligomerization.

Conclusions

Sequence-based computational analyses of Rev-like proteins, together with helical wheel projections of oligomerization domains, reveal a conserved homogeneous structural basis for oligomerization by retroviral Rev-like proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-017-0366-1) contains supplementary material, which is available to authorized users.

The genomic evolution of H1 influenza A viruses from swine detected in the United States between 2009 and 2016

Transmission of influenza A virus (IAV) from humans to swine occurs with relative frequency and is a critical contributor to swine IAV diversity. Subsequent to the introduction of these human seasonal lineages, there is often reassortment with endemic viruses and antigenic drift. To address whether particular genome constellations contributed to viral persistence following the introduction of the 2009 H1N1 human pandemic virus to swine in the USA, we collated and analysed 616 whole genomes of swine H1 isolates. For each gene, sequences were aligned, the best-known maximum likelihood phylogeny was inferred, and each virus was assigned a clade based upon its evolutionary history. A time-scaled Bayesian approach was implemented for the haemagglutinin (HA) gene to determine the patterns of genetic diversity over time. From these analyses, we observed an increase in genome diversity across all H1 lineages and clades, with the H1-γ and H1-δ1 genetic clades containing the greatest number of unique genome patterns. We documented 74 genome patterns from 2009 to 2016, of which 3 genome patterns were consistently detected at a significantly higher level than others across the entire time period. Eight genome patterns increased significantly, while five genome patterns were shown to decline in detection over time. Viruses with genome patterns identified as persisting in the US swine population may possess a greater capacity to infect and transmit in swine. This study highlights the emerging genetic diversity of US swine IAV from 2009 to 2016, with implications for swine and public health and vaccine control efforts.

Complete genome sequence of T'Ho virus, a novel putative flavivirus from the Yucatan Peninsula of Mexico

Background

We previously reported the discovery of a novel, putative flavivirus designated T’Ho virus in Culex quinquefasciatus mosquitoes in the Yucatan Peninsula of Mexico. A 1358-nt region of the NS5 gene was amplified and sequenced but an isolate was not recovered.

Results

The complete genome of T’Ho virus was sequenced using a combination of unbiased high-throughput sequencing, 5′ and 3′ rapid amplification of cDNA ends, reverse transcription-polymerase chain reaction and Sanger sequencing. The genome contains a single open reading frame of 10,284 nt which is flanked by 5′ and 3′ untranslated regions of 97 and 556-nt, respectively. Genome sequence alignments revealed that T’Ho virus is most closely related to Rocio virus (67.4% nucleotide identity) and Ilheus virus (65.9%), both of which belong to the Ntaya group, followed by other Ntaya group viruses (58.8–63.3%) and Japanese encephalitis group viruses (62.0–63.7%). Phylogenetic inference is in agreement with these findings.

Conclusions

This study furthers our understanding of flavivirus genetics, phylogeny and diagnostics. Because the two closest known relatives of T’Ho virus are human pathogens, T’Ho virus could be an unrecognized cause of human disease. It is therefore important that future studies investigate the public health significance of this virus.

Identification of a novel subtype of South River virus (family Bunyaviridae)

We previously reported the isolation of South River virus (SORV) from a pool of mosquitoes collected in the Yucatan Peninsula of Mexico (Farfan-Ale et al. in Vector Borne Zoonotic Dis 10:777-783, 5). The isolate (designated SORV-252) was identified as SORV after a 197-nucleotide region of its small RNA genome segment was sequenced. In the present study, the complete small and medium RNA genome segments and part of the large RNA genome segment of SORV-252 were sequenced and shown to have 92%, 85% and 90% nucleotide sequence identity, respectively, to the homologous regions of the prototype SORV isolate (NJO-94F). To determine the antigenic relationship between SORV-252 and NJO-94F, cross-plaque reduction neutralization tests (PRNTs) were performed using sera from mice inoculated with these viruses. SORV-252 and NJO-94F were distinguishable in the cross-neutralization assays; there was a twofold difference in the PRNT titers in one direction and a fourfold difference in the other direction, suggesting that SORV-252 represents a novel subtype of SORV. Additionally, SORV-252 and NJO-94F have distinct plaque morphologies in African green monkey kidney (Vero) cells. In conclusion, we provide evidence that a novel subtype of SORV is present in the Yucatan Peninsula of Mexico.

Two new complete genome sequences offer insight into host and tissue specificity of plant pathogenic Xanthomonas spp

Xanthomonas is a large genus of bacteria that collectively cause disease on more than 300 plant species. The broad host range of the genus contrasts with stringent host and tissue specificity for individual species and pathovars. Whole-genome sequences of Xanthomonas campestris pv. raphani strain 756C and X. oryzae pv. oryzicola strain BLS256, pathogens that infect the mesophyll tissue of the leading models for plant biology, Arabidopsis thaliana and rice, respectively, were determined and provided insight into the genetic determinants of host and tissue specificity. Comparisons were made with genomes of closely related strains that infect the vascular tissue of the same hosts and across a larger collection of complete Xanthomonas genomes. The results suggest a model in which complex sets of adaptations at the level of gene content account for host specificity and subtler adaptations at the level of amino acid or noncoding regulatory nucleotide sequence determine tissue specificity.

Repeat-aware modeling and correction of short read errors

Background

High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content.

Results

We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. Availability: The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at “http://aluru-sun.ece.iastate.edu/doku.php?id=redeem”.

Conclusions

We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors for genomes with high repeat content.

Rev variation during persistent lentivirus infection

The ability of lentiviruses to continually evolve and escape immune control is the central impediment in developing an effective vaccine for HIV-1 and other lentiviruses. Equine infectious anemia virus (EIAV) is considered a useful model for immune control of lentivirus infection. Virus-specific cytotoxic T lymphocytes (CTL) and broadly neutralizing antibody effectively control EIAV replication during inapparent stages of disease, but after years of low-level replication, the virus is still able to produce evasion genotypes that lead to late re-emergence of disease. There is a high rate of genetic variation in the EIAV surface envelope glycoprotein (SU) and in the region of the transmembrane protein (TM) overlapped by the major exon of Rev. This review examines genetic and phenotypic variation in Rev during EIAV disease and a possible role for Rev in immune evasion and virus persistence.

Detection of flaviviruses and orthobunyaviruses in mosquitoes in the Yucatan Peninsula of Mexico in 2008

A total of 191,244 mosquitoes from 24 species were collected in the Yucatan Peninsula of Mexico from January to December 2008, and tested for the presence of cytopathic virus by virus isolation in Vero cells. Eighteen virus isolates were obtained, all of which were orthobunyaviruses. These were identified by reverse transcription-polymerase chain reaction (RT-PCR) and nucleotide sequencing as Cache Valley virus (n=17) and South River virus (n=1). A subset (n=20,124) of Culex quinquefasciatus collected throughout the year was further tested by RT-PCR using flavivirus-specific primers. Flavivirus RNA was present in this mosquito species year-round. The overall flavivirus minimal infection rate, expressed as the number of positive mosquito pools per 1000 mosquitoes tested, was 7.7 and the monthly flavivirus minimal infection rates ranged from 4.3 to 16.6. Approximately one-third of the RT-PCR products were sequenced and all corresponded to Culex flavivirus, a recently discovered insect-specific flavivirus.

Reptile: representative tiling for short read error correction

MOTIVATION

Error correction is critical to the success of next-generation sequencing applications, such as resequencing and de novo genome sequencing. It is especially important for high-throughput short-read sequencing, where reads are much shorter and more abundant, and errors more frequent than in traditional Sanger sequencing. Processing massive numbers of short reads with existing error correction methods is both compute and memory intensive, yet the results are far from satisfactory when applied to real datasets.

RESULTS

We present a novel approach, termed Reptile, for error correction in short-read data from next-generation sequencing. Reptile works with the spectrum of k-mers from the input reads, and corrects errors by simultaneously examining: (i) Hamming distance-based correction possibilities for potentially erroneous k-mers; and (ii) neighboring k-mers from the same read for correct contextual information. By not needing to store input data, Reptile has the favorable property that it can handle data that does not fit in main memory. In addition to sequence data, Reptile can make use of available quality score information. Our experiments show that Reptile outperforms previous methods in the percentage of errors removed from the data and the accuracy in true base assignment. In addition, a significant reduction in run time and memory usage have been achieved compared with previous methods, making it more practical for short-read error correction when sampling larger genomes.

AVAILABILITY

Reptile is implemented in C++ and is available through the link: http://aluru-sun.ece.iastate.edu/doku.php?id=software

CONTACT

aluru@iastate.edu.

Universal primers for the amplification and sequence analysis of actin-1 from diverse mosquito species

We report the development of universal primers for the reverse-transcription polymerase chain reaction (RT-PCR) amplification and nucleotide sequence analysis of actin cDNAs from taxonomically diverse mosquito species. Primers specific to conserved regions of the invertebrate actin-1 gene were designed after actin cDNA sequences of Anopheles gambiae, Bombyx mori, Drosophila melanogaster, and Caenorhabditis elegans. The efficacy of these primers was determined by RT-PCR with the use of total RNA from mosquitoes belonging to 30 species and 8 genera (Aedes, Anopheles, Culex, Deinocerites, Mansonia, Psorophora, Toxorhynchites, and Wyeomyia). The RT-PCR products were sequenced, and sequence data were used to design additional primers. One primer pair, denoted as Act-2F (5'-ATGGTCGGYATGGGNCAGAAGGACTC-3') and Act-8R (5'-GATTCCATACCCAGGAAGGADGG-3'), successfully amplified an RT-PCR product of the expected size (683-nt) in all mosquito spp. tested. We propose that this primer pair can be used as an internal control to test the quality of RNA from mosquitoes collected in vector surveillance studies. These primers can also be used in molecular experiments in which the detection, amplification or silencing of a ubiquitously expressed mosquito housekeeping gene is necessary. Sequence and phylogenetic data are also presented in this report.

Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection

Computer models of disease take a systems biology approach toward understanding host-pathogen interactions. In particular, data driven computer model calibration is the basis for inference of immunological and pathogen parameters, assessment of model validity, and comparison between alternative models of immune or pathogen behavior. In this paper we describe the calibration and analysis of an agent-based model of Leishmania major infection. A model of macrophage loss following uptake of necrotic tissue is proposed to explain macrophage depletion following peak infection. Using Gaussian processes to approximate the computer code, we perform a sensitivity analysis to identify important parameters and to characterize their influence on the simulated infection. The analysis indicates that increasing growth rate can favor or suppress pathogen loads, depending on the infection stage and the pathogen's ability to avoid detection. Subsequent calibration of the model against previously published biological observations suggests that L. major has a relatively slow growth rate and can replicate for an extended period of time before damaging the host cell.

Genomic sequence and phylogenetic analysis of Culex flavivirus, an insect-specific flavivirus, isolated from Culex pipiens (Diptera: Culicidae) in Iowa

Adult mosquitoes (Diptera: Culicidae) were collected in 2007 and tested for specific viruses, including West Nile virus, as part of the ongoing arbovirus surveillance efforts in the state of Iowa. A subset of these mosquitoes (6,061 individuals in 340 pools) was further tested by reverse transcription-polymerase chain reaction (RT-PCR) using flavivirus universal primers. Of the 211 pools of Culex pipiens (L.) tested, 50 were positive. One of 51 pools of Culex tarsalis Coquillet was also positive. The flavivirus minimum infection rates (expressed as the number of positive mosquito pools per 1,000 mosquitoes tested) for Cx. pipiens and Cx. tarsalis were 10.3 and 1.2, respectively. Flavivirus RNA was not detected in Aedes triseriatus (Say) (52 pools), Culex erraticus (Dyar & Knab) (25 pools), or Culex territans Walker (one pool). Sequence analysis of all RT-PCR products revealed that the mosquitoes had been infected with Culex flavivirus (CxFV), an insect-specific virus previously isolated in Japan, Indonesia, Texas, Mexico, Guatemala and Trinidad. The complete genome of one isolate was sequenced, as were the envelope protein genes of eight other isolates. Phylogenetic analysis revealed that CxFV isolates from the United States (Iowa and Texas) are more closely related to CxFV isolates from Asia than those from Mexico, Guatemala, and Trinidad.

Detection of RNA from a novel West Nile-like virus and high prevalence of an insect-specific flavivirus in mosquitoes in the Yucatan Peninsula of Mexico

As part of our ongoing surveillance efforts for West Nile virus (WNV) in the Yucatan Peninsula of Mexico, 96,687 mosquitoes collected from January through December 2007 were assayed by virus isolation in mammalian cells. Three mosquito pools caused cytopathic effect. Two isolates were orthobunyaviruses (Cache Valley virus and Kairi virus) and the identity of the third infectious agent was not determined. A subset of mosquitoes was also tested by reverse transcription-polymerase chain reaction (RT-PCR) using WNV-, flavivirus-, alphavirus-, and orthobunyavirus-specific primers. A total of 7,009 Culex quinquefasciatus in 210 pools were analyzed. Flavivirus RNA was detected in 146 (70%) pools, and all PCR products were sequenced. The nucleotide sequence of one PCR product was most closely related (71-73% identity) with homologous regions of several other flaviviruses, including WNV, St. Louis encephalitis virus, and Ilheus virus. These data suggest that a novel flavivirus (tentatively named T'Ho virus) is present in Mexico. The other 145 PCR products correspond to Culex flavivirus, an insect-specific flavivirus first isolated in Japan in 2003. Culex flavivirus was isolated in mosquito cells from approximately one in four homogenates tested. The genomic sequence of one isolate was determined. Surprisingly, heterogeneous sequences were identified at the distal end of the 5' untranslated region.

mlegp: statistical analysis for computer models of biological systems using R

Gaussian processes (GPs) are flexible statistical models commonly used for predicting output from complex computer codes. As such, GPs are well suited for the analysis of computer models of biological systems, which have been traditionally difficult to analyze due to their high-dimensional, non-linear and resource-intensive nature. We describe an R package, mlegp, that fits GPs to computer model outputs and performs sensitivity analysis to identify and characterize the effects of important model inputs.

AVAILABILITY

http://www.biomath.org/mlegp

Naturally arising point mutations in non-essential domains of equine infectious anemia virus Rev alter Rev-dependent nuclear-export activity

Equine infectious anemia virus (EIAV) exhibits a high rate of genetic variation in vivo, and results in a clinically variable disease in infected horses. In vivo populations of EIAV have been characterized by the presence of distinct, genetic subpopulations of Rev that differ in phenotype and fluctuate in dominance in a manner coincident with each clinical stage of disease. This study examined the specific mutations that arose in vivo and altered the phenotype. The Rev protein was found to be highly conserved, and only 10 aa mutations were observed at a frequency greater than 10 % in the sample population. Nine of these mutations were capable of significantly altering Rev activity, either as single mutations in the context of the founder variant, or in the context of cumulatively fixed mutations. The results indicated that limited genetic variation outside the essential functional domains of Rev can alter the phenotype and may confer a selective advantage in vivo.

StepBrothers: inferring partially shared ancestries among recombinant viral sequences

Phylogeneticists have developed several statistical methods to infer recombination among molecular sequences that are evolutionarily related. Of these methods, Markov change-point models currently provide the most coherent framework. Yet, the Markov assumption is faulty in that the inferred relatedness of homologous sequences across regions divided by recombinant events is not independent, particularly for nonrecombinant sequences as they share the same history. To correct this limitation, we introduce a novel random tips (RT) model. The model springs from the idea that a recombinant sequence inherits its characters from an unknown number of ancestral full-length sequences, of which one only observes the incomplete portions. The RT model decomposes recombinant sequences into their ancestral portions and then augments each portion onto the data set as unique partially observed sequences. This data augmentation generates a random number of sequences related to each other through a single inferable tree with the same random number of tips. While intuitively pleasing, this single tree corrects the independence assumptions plaguing previous methods while permitting the detection of recombination. The single tree also allows for inference of the relative times of recombination events and generalizes to incorporate multiple recombinant sequences. This generalization answers important questions with which previous models struggle. For example, we demonstrate that a group of human immunodeficiency type 1 recombinant viruses from Argentina, previously thought to have the same recombinant history, actually consist of 2 groups: one, a clonal expansion of a reference sequence and another that predates the formation of the reference sequence. In another example, we demonstrate that 2 hepatitis B virus recombinant strains share similar splicing locations, suggesting a common descent of the 2 viruses. We implement and run both examples in a software package called StepBrothers, freely available to interested parties.

Molecular cloning and sequencing of MHC class II beta 1 domain of turkey reveals high sequence identity with chicken

We report the nucleotide sequences of turkey (Meleagris gallopavo) major histocompatibility complex (MHC) class II loci (beta 1 domain or exon 2 encoding the peptide-binding region). In the present investigation, three distinct sequences from the beta 1 domain of turkey MHC class II were isolated. A BLAST search and phylogenetic analysis revealed that turkey MHC sequences are most similar to chicken and peacock MHC. There was no strong evidence of recombination among the turkey MHC sequences or with other avian MHC, but diversity was high. The diversity in this peptide-binding region may be the result of point mutation and balancing selection or frequent gene conversion within turkey. However, more work and data are needed to understand the evolution of turkey and other avian MHC. Moreover, polymerase chain reaction-restriction fragment-length polymorphism analysis of exon 2 using the Hinf I restriction enzyme demonstrated three restriction patterns and a preliminary evidence of multiple beta loci in turkey. PCR-RFLP analysis of turkey MHC class II loci could be a promising method of MHC genotyping, when more sequences are available. Turkey MHC haplotypes identified earlier by RFLP analysis should be sequenced to standardize turkey MHC nomenclature and to develop DNA based method of haplotyping.

Identifying dramatic selection shifts in phylogenetic trees

Background

The rate of evolution varies spatially along genomes and temporally in time. The presence of evolutionary rate variation is an informative signal that often marks functional regions of genomes and historical selection events. There exist many tests for temporal rate variation, or heterotachy, that start by partitioning sampled sequences into two or more groups and testing rate homogeneity among the groups. I develop a Bayesian method to infer phylogenetic trees with a divergence point, or dramatic temporal shifts in selection pressure that affect many nucleotide sites simultaneously, located at an unknown position in the tree.

Results

Simulation demonstrates that the method is most able to detect divergence points when rate variation and the number of affected sites is high, but not beyond biologically relevant values. The method is applied to two viral data sets. A divergence point is identified separating the B and C subtypes, two genetically distinct variants of HIV that have spread into different human populations with the AIDS epidemic. In contrast, no strong signal of temporal rate variation is found in a sample of F and H genotypes, two genetic variants of HBV that have likely evolved with humans during their immigration and expansion into the Americas.

Conclusion

Temporal shifts in evolutionary rate of sufficient magnitude are detectable in the history of sampled sequences. The ability to detect such divergence points without the need to specify a prior hypothesis about the location or timing of the divergence point should help scientists identify historically important selection events and decipher mechanisms of evolution.

Phylogenetic mapping of recombination hotspots in human immunodeficiency virus via spatially smoothed change-point processes

We present a Bayesian framework for inferring spatial preferences of recombination from multiple putative recombinant nucleotide sequences. Phylogenetic recombination detection has been an active area of research for the last 15 years. However, only recently attempts to summarize information from several instances of recombination have been made. We propose a hierarchical model that allows for simultaneous inference of recombination breakpoint locations and spatial variation in recombination frequency. The dual multiple change-point model for phylogenetic recombination detection resides at the lowest level of our hierarchy under the umbrella of a common prior on breakpoint locations. The hierarchical prior allows for information about spatial preferences of recombination to be shared among individual data sets. To overcome the sparseness of breakpoint data, dictated by the modest number of available recombinant sequences, we a priori impose a biologically relevant correlation structure on recombination location log odds via a Gaussian Markov random field hyperprior. To examine the capabilities of our model to recover spatial variation in recombination frequency, we simulate recombination from a predefined distribution of breakpoint locations. We then proceed with the analysis of 42 human immunodeficiency virus (HIV) intersubtype gag recombinants and identify a putative recombination hotspot.

cBrother: relaxing parental tree assumptions for Bayesian recombination detection

Bayesian multiple change-point models accurately detect recombination in molecular sequence data. Previous Java-based implementations assume a fixed topology for the representative parental data. cBrother is a novel C language implementation that capitalizes on reduced computational time to relax the fixed tree assumption. We show that cBrother is 19 times faster than its predecessor and the fixed tree assumption can influence estimates of recombination in a medically-relevant dataset.

AVAILABILITY

cBrother can be freely downloaded from http://www.biomath.org/dormanks/ and can be compiled on Linux, Macintosh and Windows operating systems. Online documentation and a tutorial are also available at the site.

Quantitative exposure assessment for confinement of maize biogenic systems

The development of transgenic crops as production platforms for biogenic agents will largely depend on the success of efforts to confine the genes and their expressed proteins in field environments. We have used quantitative exposure assessment to evaluate how management practices affect materials escape due to outcrossing by pollen flow or grain loss during harvest operations. Specifically, we study the use of maize to produce biogenic agents within field-confined systems. Decision trees representing simplified schemes of fully conforming (designed to comply with current regulatory standards for field confined trials), partially conforming, and non-conforming management practices were developed. Exemplifying assumptions and published data for conformance and material fate probabilities were used in Monte Carlo simulations to forecast materials escape by pollen outcrossing and harvest operations from a 1 ha source field. Deterministic analyses showed fully conforming confinement management restricted materials loss to low levels (for this example, outcrossing produced <1 in 10(6) kernels in receptor fields). The corresponding high-end (90th percentile) probabilistic result was 16- and 4333-fold higher (relative to deterministic outcrossing = 1) for outcrossing and harvest loss, respectively. For partially conforming practice, high-end outcrossing ranged from 100- to >15000-fold over the base result in receptor fields, and harvest loss was >10000-fold over the base result. For non-conforming practice, high-end outcrossing produced >15000-fold greater kernels in receptor fields and high-end harvest loss was at least 19000-fold greater. Deterministic estimates of off-field loss by machine transfer are as much as 30000-fold higher for non-conforming operations relative to the base case of pollen outcrossing. Better knowledge of failure frequencies for confinement management practices, improved physical models of materials flows, refined analysis of confinement loss probabilities using quantitative tools, and decision analysis to improve and audit management system performance are all needed to extend understanding of confinement integrity beyond the exemplifying case used here.

Dual multiple change-point model leads to more accurate recombination detection

MOTIVATION

We introduce a dual multiple change-point (MCP) model for recombination detection among aligned nucleotide sequences. The dual MCP model is an extension of the model introduced previously by Suchard and co-workers. In the original single MCP model, one change-point process is used to model spatial phylogenetic variation. Here, we show that using two change-point processes, one for spatial variation of tree topologies and the other for spatial variation of substitution process parameters, increases recombination detection accuracy. Statistical analysis is done in a Bayesian framework using reversible jump Markov chain Monte Carlo sampling to approximate the joint posterior distribution of all model parameters.

RESULTS

We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model.

Subpopulations of equine infectious anemia virus Rev coexist in vivo and differ in phenotype

Lentiviruses exist in vivo as a population of related, nonidentical genotypes, commonly referred to as quasispecies. The quasispecies structure is characteristic of complex adaptive systems and contributes to the high rate of evolution in lentiviruses that confounds efforts to develop effective vaccines and antiviral therapies. Here, we describe analyses of genetic data from longitudinal studies of genetic variation in a lentivirus regulatory protein, Rev, over the course of disease in ponies experimentally infected with equine infectious anemia virus. As observed with other lentivirus data, the Rev variants exhibited a quasispecies character. Phylogenetic and partition analyses suggested that the Rev quasispecies comprised two distinct subpopulations that coexisted during infection. One subpopulation appeared to accumulate changes in a linear, time-dependent manner, while the other evolved radially from a common variant. Over time, the two subpopulations cycled in predominance coincident with changes in the disease state, suggesting that the two groups differed in selective advantage. Transient expression assays indicated the two populations differed significantly in Rev nuclear export activity. Chimeric proviral clones containing Rev genotypes representative of each population differed in rate and overall level of virus replication in vitro. The coexistence of genetically distinct viral subpopulations that differ in phenotype provides great adaptability to environmental changes within the infected host. A quasispecies model with multiple subpopulations may provide additional insight into the nature of lentivirus reservoirs and the evolution of antigenic and drug-resistant variants.

Are you my mother? Bayesian phylogenetic inference of recombination among putative parental strains

Reconstructing evolutionary relationships using Bayesian inference has become increasingly popular due to the ability of Bayesian inference to handle complex models of evolution. In this review we concentrate on inference of recombination events between strains of viruses when these events are sporadic, ie rare relative to point mutations. Bayesian inference is especially attractive in the detection of recombination events because it allows for simultaneous inferences about the presence, number and location of crossover points and the identification of parental sequences. Current frequentist recombination identification falls into a sequential testing trap. The most likely parental sequences and crossover points are identified using the data and then the certainty of recombination is assessed conditional on this identification. After briefly outlining basic phylogenetic models, Bayesian inference and Markov chain Monte Carlo (MCMC) computation, we summarise three different approaches to recombination detection and discuss current challenges in applying Bayesian phylogenetic inference of recombination.

Oh brother, where art thou? A Bayes factor test for recombination with uncertain heritage

Current methods to identify recombination between subtypes of human immunodeficiency virus 1 (HIV-1) fall into a sequential testing trap, in which significance is assessed conditional on parental representative sequences and crossover points (COPs) that maximize the same test statistic. We overcame this shortfall by testing for recombination while inferring parental heritage and COPs using an extended Bayesian multiple change-point model. The model assumes that aligned molecular sequence data consist of an unknown number of contiguous segments that may support alternative topologies or varying evolutionary pressures. We allowed for heterogeneity in the substitution process and specifically tested for intersubtype recombination using Bayes factors. We also developed a new class of priors to assess significance across a wide range of support for recombination in the data. We applied our method to three putative gag gene recombinants. HIV-1 isolate RW024 decisively supported recombination with an inferred parental heritage of AD and a COP 95% Bayesian credible interval of (1,152, 1,178) using the HXB2 numbering scheme. HIV-1 isolate VI557 barely supported recombination. HIV-1 isolate RF decisively rejected recombination as expected, given that the sequence is commonly used as a reference sequence for subtype B. We employed scaled regeneration quantile plots to assess convergence and found this approach convenient to use even for our variable dimensional model parameter space.

Bootstrap confidence levels for HIV-1 recombination

Recombination has been invoked to explain the disparate evolutionary relationships observed for different genes or sequence segments of a single HIV-1 genome. We present a new method of assessing confidence in HIV-1 recombination as an alternative to the segment-by-segment nonparametric bootstrap commonly applied to confirm HIV-1 recombinant data. Our new method uses the bias-corrected accelerated percentile interval (BCa) bootstrap method as applied to the "problem of regions" (Efron and Tibshirani 1998). It is an extension of the BCa method used in the inference of evolutionary relationships (Efron et al. 1996). This method has two advantages over the traditional bootstrap procedure: (1) it gives a single overall confidence measure rather than segment-by-segment results, and (2) it is more accurate. We test our method on 61 sequences, including 16 with ambiguous recombinant status.

Primate DAX1, SRY, and SOX9: evolutionary stratification of sex-determination pathway

The molecular evolution of DAX1, SRY, and SOX9, genes involved in mammalian sex determination, was examined in six primate species. DAX1 and SRY have been added to the X and Y chromosomes, respectively, during mammalian evolution, whereas SOX9 remains autosomal. We determined the genomic sequences of DAX1, SRY, and SOX9 in all six species, and calculated K(a), the number of nonsynonymous substitutions per nonsynonymous site, and compared this with the K(s), the number of synonymous substitutions per synonymous site. Phylogenetic trees were constructed by means of the DAX1, SRY, and SOX9 coding sequences, and phylogenetic analysis was performed using maximum likelihood. Overall measures of gene and protein similarity were closer for DAX1 and SOX9, but DAX1 exhibited nonsynonymous amino acid substitutions at an accelerated frequency relative to synonymous changes, similar to SRY and significantly higher than SOX9. We conclude that, at the protein level, DAX1 and SRY are under less selective pressure to remain conserved than SOX9, and, therefore, diverge more across species than does SOX9. These results are consistent with evolutionary stratification of the mammalian sex determination pathway, analogous to that for sex chromosomes.

Mutation takes no vacation: can structured treatment interruptions increase the risk of drug-resistant HIV-1?

We use a mathematical model to study the dynamics of HIV-1 replication during structured treatment interruptions (STIs) in infected patients. The model predicts rapid viral rebound, restoration of a latently infected cell pool, and critically, partially resistant mutant rebound that may be missed because of high levels of wild type virus. Because partially resistant viruses are capable of mutating to full resistance, a substantial increase in their numbers represents a threat to therapeutic response durability. Compared with continued treatment, STIs may increase the chance of mutation to full resistance by several thousandfold.

[Molecular epidemiology of the human immunodeficiency virus type 1 in Santiago, Chile]

BACKGROUND

Most of the studies of HIV-1 infection in South America have been limited to Brazil and little is known about the viral variants that are causing disease elsewhere in the continent.

AIM

To determine the characteristics of the viral variants present in Chile as well as patterns of viral transmission.

MATERIAL AND METHODS

Viral sequences were obtained from 21 HIV-1 infected people from Santiago, Chile who were infected either via sexual contact or intravenous drug use. Cloned sequences obtained from both the third variable and conserved regions of the envelope as well as the viral protease were evaluated.

RESULTS

We found only clade B subtype viruses in Santiago. An evaluation of the envelope gene revealed no evidence that the sequences were monophyletic by risk group. A number of the protease sequences were predicted to encode amino acid substitutions commonly found during selection for protease inhibitor resistance.

CONCLUSIONS

The HIV-1 strains studied in Chile, belong to the subtype B. There is no molecular evidence of separate introductions of the virus into the different risk groups. A number of substitutions in the protease gene that may confer resistance to protease inhibitors were found in patients with no previous exposure to this class of drugs.