Genomic surveillance uncovers a pandemic clonal lineage of the wheat blast fungus.

Wheat, one of the most important food crops, is threatened by a blast disease pandemic. Here, we show that a clonal lineage of the wheat blast fungus recently spread to Asia and Africa following two independent introductions from South America. Through a combination of genome analyses and laboratory experiments, we show that the decade-old blast pandemic lineage can be controlled by the Rmg8 disease resistance gene and is sensitive to strobilurin fungicides. However, we also highlight the potential of the pandemic clone to evolve fungicide-insensitive variants and sexually recombine with African lineages. This underscores the urgent need for genomic surveillance to track and mitigate the spread of wheat blast outside of South America and to guide preemptive wheat breeding for blast resistance.

Correction: Genomic surveillance uncovers a pandemic clonal lineage of the wheat blast fungus.

[This corrects the article DOI: 10.1371/journal.pbio.3002052.].

Burden of human metapneumovirus infections among children with acute respiratory tract infections attending a Tertiary Care Hospital, Kathmandu.

BACKGROUND: Acute respiratory infections (ARIs) are one of the most common causes of mortality and morbidity worldwide. Every year millions of children suffer from viral respiratory tract infections (RTIs) ranging from mild to severe illnesses. Human Metapneumovirus (HMPV) is among the most frequent viruses responsible for RTIs. However, HMPV infections and their severity among children have not been explored yet in Nepal. PURPOSE: Therefore, the study was focused on HMPV infections and other potential viral etiologies or co-infections using multiplex PCR among children attending Kanti Children's Hospital and assessed the clinical characteristics of the infections as well as found the co-infections. A hospital-based cross-sectional study was designed and a convenience sampling method was used to enroll children of less than 15 years with flu-like symptoms from both outpatients and inpatients departments over three months of the study period. RESULTS: HMPV infection (13.3%) was the most predominant infection among the different viral infections in children with ARIs in Kanti Children's Hospital. The HMPV was more prevalent in the age group less than three years (21.8%). Cough and fever were the most common clinical features present in all children infected with HMPV followed by rhinorrhea, sore throat, and wheezing. HMPV-positive children were diagnosed with pneumonia (42.9%), bronchiolitis (28.5%), upper respiratory tract infections (14.3%), and asthma (14.3%). The prevalence of HMPV was high in late winter (14.3%) followed by early spring (13.5%). CONCLUSIONS: This study provides the baseline information on HMPV and associated co-infection with other respiratory viruses for the differential diagnosis based on molecular methods and also the comparison of clinical presentations among the different respiratory syndromes.

High-resolution expression profiling of selected gene sets during plant immune activation.

The plant immune system involves detection of pathogens via both cell-surface and intracellular receptors. Both receptor classes can induce transcriptional reprogramming that elevates disease resistance. To assess differential gene expression during plant immunity, we developed and deployed quantitative sequence capture (CAP-I). We designed and synthesized biotinylated single-strand RNA bait libraries targeted to a subset of defense genes, and generated sequence capture data from 99 RNA-seq libraries. We built a data processing pipeline to quantify the RNA-CAP-I-seq data, and visualize differential gene expression. Sequence capture in combination with quantitative RNA-seq enabled cost-effective assessment of the expression profile of a specified subset of genes. Quantitative sequence capture is not limited to RNA-seq or any specific organism and can potentially be incorporated into automated platforms for high-throughput sequencing.

Extended spectrum beta-lactamase and metallo beta-lactamase production among Escherichia coli and Klebsiella pneumoniae isolated from different clinical samples in a tertiary care hospital in Kathmandu, Nepal.

BACKGROUND: Extended spectrum beta-lactamase (ESBL) and metallo beta-lactamase (MBL) production in Klebsiella pneumoniae and Escherichia coli are the commonest modes of drug resistance among these commonly isolated bacteria from clinical specimens. So the main purpose of our study was to determine the burden of ESBL and MBL production in E. coli and K. pneumoniae isolated from clinical samples. Further, the antimicrobial susceptibility patterns of E. coli and K. pneumoniae were also determined. METHODS: A cross-sectional study was conducted at Om Hospital and Research Centre, Kathmandu, Nepal by using the E. coli and K. pneumoniae isolated from different clinical samples (urine, pus, body fluids, sputum, blood) from May 2015 to December 2015. Antimicrobial susceptibility testing was performed by Kirby-Bauer disc diffusion technique. Extended spectrum beta-lactamase production was detected by combined disc method using ceftazidime and ceftazidime/clavulanic acid discs and cefotaxime and cefotaxime/clavulanic acid discs. Similarly, metallo beta-lactamase production was detected by combined disc assay using imipenem and imipenem/ethylenediaminetetracetate discs. Bacteria showing resistance to at least three different classes of antibiotics were considered multidrug resistant (MDR). RESULTS: Of total 1568 different clinical samples processed, 268 (17.1%) samples were culture positive. Among which, E. coli and K. pneumoniae were isolated from 138 (51.5%) and 39 (14.6%) samples respectively. Of the total isolates 61 (34.5%) were ESBL producers and 7 (4%) isolates were found to be MBL producers. High rates of ESBL production (35.9%) was noted among the clinical isolates from outpatients, however no MBL producing strains were isolated from outpatients. Among 138 E. coli and 39 K. pneumoniae, 73 (52.9%) E. coli and 23 (59%) K. pneumoniae were multidrug resistant. The lowest rates of resistance was seen toward imipenem followed by piperacillin/tazobactam, amikacin and cefoperazone/sulbactam. CONCLUSIONS: High rate of ESBL production was found in the E. coli and K. pneumoniae isolated from outpatients suggesting the dissemination of ESBL producing isolates in community. This is very serious issue and can't be neglected. Regular monitoring of rates of ESBL and MBL production along with multidrug resistance among clinical isolates is very necessary.

QTrim: a novel tool for the quality trimming of sequence reads generated using the Roche/454 sequencing platform.

BACKGROUND: Many high throughput sequencing (HTS) approaches, such as the Roche/454 platform, produce sequences in which the quality of the sequence (as measured by a Phred-like quality scores) decreases linearly across a sequence read. Undertaking quality trimming of this data is essential to enable confidence in the results of subsequent downstream analysis. Here, we have developed a novel, highly sensitive and accurate approach (QTrim) for the quality trimming of sequence reads generated using the Roche/454 sequencing platform (or any platform with long reads that outputs Phred-like quality scores). RESULTS: The performance of QTrim was evaluated against all other available quality trimming approaches on both poor and high quality 454 sequence data. In all cases, QTrim appears to perform equally as well as the best other approach (PRINSEQ) with these two methods significantly outperforming all other methods. Further analysis of the trimmed data revealed that the novel trimming approach implemented in QTrim ensures that the prevalence of low quality bases in the resulting trimmed data is substantially lower than PRINSEQ or any of the other approaches tested. CONCLUSIONS: QTrim is a novel, highly sensitive and accurate algorithm for the quality trimming of Roche/454 sequence reads. It is implemented both as an executable program that can be integrated with standalone sequence analysis pipelines and as a web-based application to enable individuals with little or no bioinformatics experience to quality trim their sequence data.

Extensive immune receptor repertoire diversity in disease-resistant rice landraces.

Plants have powerful defense mechanisms and extensive immune receptor repertoires, yet crop monocultures are prone to epidemic diseases. Rice (Oryza sativa) is susceptible to many diseases, such as rice blast caused by Magnaporthe oryzae. Varietal resistance of rice to blast relies on intracellular nucleotide binding, leucine-rich repeat (NLR) receptors that recognize specific pathogen molecules and trigger immune responses. In the Yuanyang terraces in southwest China, rice landraces rarely show severe losses to disease whereas commercial inbred lines show pronounced field susceptibility. Here, we investigate within-landrace NLR sequence diversity of nine rice landraces and eleven modern varieties using complexity reduction techniques. We find that NLRs display high sequence diversity in landraces, consistent with balancing selection, and that balancing selection at NLRs is more pervasive in landraces than modern varieties. Notably, modern varieties lack many ancient NLR haplotypes that are retained in some landraces. Our study emphasizes the value of standing genetic variation that is maintained in farmer landraces as a resource to make modern crops and agroecosystems less prone to disease. The conservation of landraces is, therefore, crucial for ensuring food security in the face of dynamic biotic and abiotic threats.

Solanum americanum genome-assisted discovery of immune receptors that detect potato late blight pathogen effectors.

Potato (Solanum tuberosum) and tomato (Solanum lycopersicon) crops suffer severe losses to late blight caused by the oomycete pathogen Phytophthora infestans. Solanum americanum, a relative of potato and tomato, is globally distributed and most accessions are highly blight resistant. We generated high-quality reference genomes of four S. americanum accessions, resequenced 52 accessions, and defined a pan-NLRome of S. americanum immune receptor genes. We further screened for variation in recognition of 315P. infestans RXLR effectors in 52 S. americanum accessions. Using these genomic and phenotypic data, we cloned three NLR-encoding genes, Rpi-amr4, R02860 and R04373, that recognize cognate P. infestans RXLR effectors PITG_22825 (AVRamr4), PITG_02860 and PITG_04373. These genomic resources and methodologies will support efforts to engineer potatoes with durable late blight resistance and can be applied to diseases of other crops.

Appraising the performance of genotyping tools in the prediction of coreceptor tropism in HIV-1 subtype C viruses.

BACKGROUND: In human immunodeficiency virus type 1 (HIV-1) infection, transmitted viruses generally use the CCR5 chemokine receptor as a coreceptor for host cell entry. In more than 50% of subtype B infections, a switch in coreceptor tropism from CCR5- to CXCR4-use occurs during disease progression. Phenotypic or genotypic approaches can be used to test for the presence of CXCR4-using viral variants in an individual's viral population that would result in resistance to treatment with CCR5-antagonists. While genotyping approaches for coreceptor-tropism prediction in subtype B are well established and verified, they are less so for subtype C. METHODS: Here, using a dataset comprising V3 loop sequences from 349 CCR5-using and 56 CXCR4-using HIV-1 subtype C viruses we perform a comparative analysis of the predictive ability of 11 genotypic algorithms in their prediction of coreceptor tropism in subtype C. We calculate the sensitivity and specificity of each of the approaches as well as determining their overall accuracy. By separating the CXCR4-using viruses into CXCR4-exclusive (25 sequences) and dual-tropic (31 sequences) we evaluate the effect of the possible conflicting signal from dual-tropic viruses on the ability of a of the approaches to correctly predict coreceptor phenotype. RESULTS: We determined that geno2pheno with a false positive rate of 5% is the best approach for predicting CXCR4-usage in subtype C sequences with an accuracy of 94% (89% sensitivity and 99% specificity). Contrary to what has been reported for subtype B, the optimal approaches for prediction of CXCR4-usage in sequence from viruses that use CXCR4 exclusively, also perform best at predicting CXCR4-use in dual-tropic viral variants. CONCLUSIONS: The accuracy of genotyping approaches at correctly predicting the coreceptor usage of V3 sequences from subtype C viruses is very high. We suggest that genotyping approaches can be used to test for coreceptor tropism in HIV-1 group M subtype C with a high degree of confidence that they will identify CXCR4-usage in both CXCR4-exclusive and dual tropic variants.

Etiology of Coinfections in Children with Influenza during 2015/16 Winter Season in Nepal.

Acute respiratory infections (ARIs) are one of the major public health problems in developing countries like Nepal. Besides the influenza, several other pathogens are responsible for acute respiratory infection in children. Etiology of infections is poorly characterized at the course of clinical management, and hence empirical antimicrobial agents are used. The objective of this study was to characterize the influenza and other respiratory pathogens by real-time PCR assay. A total of 175 throat swab specimens of influenza-positive cases collected at National Influenza Center, Nepal, during the 2015/16 winter season were selected for detecting other respiratory copathogens. Total nucleic acid was extracted using Pure Link viral RNA/DNA mini kit (Invitrogen), and multiplex RT-PCR assays were performed. Influenza A and B viruses were found in 120 (68.6%) and 55 (31.4%) specimens, respectively, among which coinfections were found in 106 (60.6%) specimens. Among the influenza A-positive cases, 25 (20.8%) were A/H1N1 pdm09 and 95 (79.2%) were A/H3 subtypes. Viruses coinfected frequently with influenza virus in children were rhinovirus (26; 14.8%), respiratory syncytial virus A/B (19; 10.8%), adenovirus (14; 8.0%), coronavirus (CoV)-HKU1 (14; 8.0%), CoV-OC43 (5; 2.9%), CoV-229E (2; 1.1%), metapneumovirus A/B (5; 2.9%), bocavirus (6; 3.4%), enterovirus (5; 2.9%), parainfluenza virus-1 (3; 1.7%), and parainfluenza virus-3 (2; 1.1%). Coinfection of Mycoplasma pneumoniae with influenza virus was found in children (5; 2.8%). Most of the viral infection occurred in young children below 5 years of age. In addition to influenza virus, nine different respiratory pathogens were detected, of which coinfections of rhinovirus and respiratory syncytial virus A/B were predominantly found in children. This study gives us better information on the respiratory pathogen profile and coinfection combinations which are important for diagnosis and treatment of ARIs.

A workflow for simplified analysis of ATAC-cap-seq data in R.

Background: Assay for Transposase-Accessible Chromatin (ATAC)-cap-seq is a high-throughput sequencing method that combines ATAC-seq with targeted nucleic acid enrichment of precipitated DNA fragments. There are increased analytical difficulties arising from working with a set of regions of interest that may be small in number and biologically dependent. Common statistical pipelines for RNA sequencing might be assumed to apply but can give misleading results on ATAC-cap-seq data. A tool is needed to allow a nonspecialist user to quickly and easily summarize data and apply sensible and effective normalization and analysis. Results: We developed atacR to allow a user to easily analyze their ATAC enrichment experiment. It provides comprehensive summary functions and diagnostic plots for studying enriched tag abundance. Application of between-sample normalization is made straightforward. Functions for normalizing based on user-defined control regions, whole library size, and regions selected from the least variable regions in a dataset are provided. Three methods for detecting differential abundance of tags from enriched methods are provided, including bootstrap t, Bayes factor, and a wrapped version of the standard exact test in the edgeR package. We compared the precision, recall, and F-score of each detection method on resampled datasets at varying replicate, significance threshold, and genes changed and found that the Bayes factor method had the greatest overall detection power, though edgeR was slightly stronger in simulations with lower numbers of genes changed. Conclusions: Our package allows a nonspecialist user to easily and effectively apply methods appropriate to the analysis of ATAC-cap-seq in a reproducible manner. The package is implemented in pure R and is fully interoperable with common workflows in Bioconductor.