The first complete genome of the simian malaria parasite Plasmodium brasilianum.

Naturally occurring human infections by zoonotic Plasmodium species have been documented for P. knowlesi, P. cynomolgi, P. simium, P. simiovale, P. inui, P. inui-like, P. coatneyi, and P. brasilianum. Accurate detection of each species is complicated by their morphological similarities with other Plasmodium species. PCR-based assays offer a solution but require prior knowledge of adequate genomic targets that can distinguish the species. While whole genomes have been published for P. knowlesi, P. cynomolgi, P. simium, and P. inui, no complete genome for P. brasilianum has been available. Previously, we reported a draft genome for P. brasilianum, and here we report the completed genome for P. brasilianum. The genome is 31.4 Mb in size and comprises 14 chromosomes, the mitochondrial genome, the apicoplast genome, and 29 unplaced contigs. The chromosomes consist of 98.4% nucleotide sites that are identical to the P. malariae genome, the closest evolutionarily related species hypothesized to be the same species as P. brasilianum, with 41,125 non-synonymous SNPs (0.0722% of genome) identified between the two genomes. Furthermore, P. brasilianum had 4864 (82.1%) genes that share 80% or higher sequence similarity with 4970 (75.5%) P. malariae genes. This was demonstrated by the nearly identical genomic organization and multiple sequence alignments for the merozoite surface proteins msp3 and msp7. We observed a distinction in the repeat lengths of the circumsporozoite protein (CSP) gene sequences between P. brasilianum and P. malariae. Our results demonstrate a 97.3% pairwise identity between the P. brasilianum and the P. malariae genomes. These findings highlight the phylogenetic proximity of these two species, suggesting that P. malariae and P. brasilianum are strains of the same species, but this could not be fully evaluated with only a single genomic sequence for each species.

New Histoplasma Diagnostic Assays Designed via Whole Genome Comparisons.

Histoplasmosis is a systemic fungal disease caused by the pathogen Histoplasma spp. that results in significant morbidity and mortality in persons with HIV/AIDS and can also affect immunocompetent individuals. Although some PCR and antigen-detection assays have been developed, conventional diagnosis has largely relied on culture, which can take weeks. Our aim was to provide a proof of principle for rationally designing and standardizing PCR assays based on Histoplasma-specific genomic sequences. Via automated comparisons of aligned genome contigs/scaffolds and gene (sub)sequences, we identified protein-coding genes that are present in existing sequences of Histoplasma strains but not in other genera. Two of the genes, PPK and CFP4, were used for designing primer sets for conventional and real-time PCR assays. Both resulted in a 100% analytical specificity in vitro and detected 62/62 H. capsulatum isolates using purified DNA. We also obtained positive detections of 2/2 confirmed H. capsulatum clinical FFPE (formalin-fixed paraffin-embedded) samples using both primer sets. Positive control plasmid 10-fold serial dilutions confirmed the analytical sensitivity of the assays. The findings suggest that these novel primer sets should allow for detection sensitivity and reduce false positive results/cross-reactions. New assays for detecting pathogenic fungi, constructed along these lines, could be simple and affordable to implement.

Using earth mover's distance for viral outbreak investigations.

BACKGROUND: RNA viruses mutate at extremely high rates, forming an intra-host viral population of closely related variants, which allows them to evade the host's immune system and makes them particularly dangerous. Viral outbreaks pose a significant threat for public health, and, in order to deal with it, it is critical to infer transmission clusters, i.e., decide whether two viral samples belong to the same outbreak. Next-generation sequencing (NGS) can significantly help in tackling outbreak-related problems. While NGS data is first obtained as short reads, existing methods rely on assembled sequences. This requires reconstruction of the entire viral population, which is complicated, error-prone and time-consuming. RESULTS: The experimental validation using sequencing data from HCV outbreaks shows that the proposed algorithm can successfully identify genetic relatedness between viral populations, infer transmission direction, transmission clusters and outbreak sources, as well as decide whether the source is present in the sequenced outbreak sample and identify it. CONCLUSIONS: Introduced algorithm allows to cluster genetically related samples, infer transmission directions and predict sources of outbreaks. Validation on experimental data demonstrated that algorithm is able to reconstruct various transmission characteristics. Advantage of the method is the ability to bypass cumbersome read assembly, thus eliminating the chance to introduce new errors, and saving processing time by allowing to use raw NGS reads.

Ribonucleotide incorporation in yeast genomic DNA shows preference for cytosine and guanosine preceded by deoxyadenosine.

Despite the abundance of ribonucleoside monophosphates (rNMPs) in DNA, sites of rNMP incorporation remain poorly characterized. Here, by using ribose-seq and Ribose-Map techniques, we built and analyzed high-throughput sequencing libraries of rNMPs derived from mitochondrial and nuclear DNA of budding and fission yeast. We reveal both common and unique features of rNMP sites among yeast species and strains, and between wild type and different ribonuclease H-mutant genotypes. We demonstrate that the rNMPs are not randomly incorporated in DNA. We highlight signatures and patterns of rNMPs, including sites within trinucleotide-repeat tracts. Our results uncover that the deoxyribonucleotide immediately upstream of the rNMPs has a strong influence on rNMP distribution, suggesting a mechanism of rNMP accommodation by DNA polymerases as a driving force of rNMP incorporation. Consistently, we find deoxyadenosine upstream from the most abundant genomic rCMPs and rGMPs. This study establishes a framework to better understand mechanisms of rNMP incorporation in DNA.

A spontaneous complex structural variant in rcan-1 increases exploratory behavior and laboratory fitness of Caenorhabditis elegans.

Over long evolutionary timescales, major changes to the copy number, function, and genomic organization of genes occur, however, our understanding of the individual mutational events responsible for these changes is lacking. In this report, we study the genetic basis of adaptation of two strains of C. elegans to laboratory food sources using competition experiments on a panel of 89 recombinant inbred lines (RIL). Unexpectedly, we identified a single RIL with higher relative fitness than either of the parental strains. This strain also displayed a novel behavioral phenotype, resulting in higher propensity to explore bacterial lawns. Using bulk-segregant analysis and short-read resequencing of this RIL, we mapped the change in exploration behavior to a spontaneous, complex rearrangement of the rcan-1 gene that occurred during construction of the RIL panel. We resolved this rearrangement into five unique tandem inversion/duplications using Oxford Nanopore long-read sequencing. rcan-1 encodes an ortholog to human RCAN1/DSCR1 calcipressin gene, which has been implicated as a causal gene for Down syndrome. The genomic rearrangement in rcan-1 creates two complete and two truncated versions of the rcan-1 coding region, with a variety of modified 5' and 3' non-coding regions. While most copy-number variations (CNVs) are thought to act by increasing expression of duplicated genes, these changes to rcan-1 ultimately result in the reduction of its whole-body expression due to changes in the upstream regions. By backcrossing this rearrangement into a common genetic background to create a near isogenic line (NIL), we demonstrate that both the competitive advantage and exploration behavioral changes are linked to this complex genetic variant. This NIL strain does not phenocopy a strain containing an rcan-1 loss-of-function allele, which suggests that the residual expression of rcan-1 is necessary for its fitness effects. Our results demonstrate how colonization of new environments, such as those encountered in the laboratory, can create evolutionary pressure to modify gene function. This evolutionary mismatch can be resolved by an unexpectedly complex genetic change that simultaneously duplicates and diversifies a gene into two uniquely regulated genes. Our work shows how complex rearrangements can act to modify gene expression in ways besides increased gene dosage.

Development of anthracycline-induced dilated cardiomyopathy due to mutation on LMNA gene in a breast cancer patient: a case report.

BACKGROUND: Anthracyclines are highly effective anticancer medication prescribed for the treatment of breast cancer. Nevertheless, the use of anthracyclines as chemotherapeutic agents involves a risk for development of cardiac toxicity which may cause restrictive and dilated cardiomyopathy. Currently, genetic predisposition is not considered as a risk factor for cardiotoxicity associated to the use of anthracyclines. CASE PRESENTATION: We report the case of a 37-years old Panamanian female patient diagnosed with breast cancer who developed clinical signs of severe heart failure after treatment with doxorubicin. A diagnosis of anthracycline induced cardiomyopathy was made and treatment was initiated accordingly. A whole exome sequencing study performed to the patient showed the presence of a missense mutation in LMNA gene, which codifies for lamin A/C. Our results points to a correlation between the LMNA variant and the anthracycline cardiotoxicity developed by the woman. Improvement of the clinical symptoms and the left ventricle ejection fraction was observed after proper treatment. CONCLUSIONS: This case report suggests for the first time a potential genetic predisposition for anthracyclines induced cardiomyopathy in patients with mutations in LMNA gene. Perhaps chemotherapies accelerate or deliver the "second-hit" in the development of DCM in patients with genetic mutations. More data is needed to understand the contribution of LMNA variants that predispose to DCM in patients receiving cardiotoxic therapies.

Ribose-Map: a bioinformatics toolkit to map ribonucleotides embedded in genomic DNA.

Recent advances in high-throughput sequencing techniques have made it possible to tag ribonucleoside monophosphates (rNMPs) embedded in genomic DNA for sequencing. rNMP sequencing experiments generate large, complex datasets that require efficient, scalable software that can accurately map embedded rNMPs independently of the particular sequencing technique used. Current computational pipelines designed to map rNMPs embedded in genomic DNA are customized for data generated using only one type of rNMP sequencing technique. To standardize the processing and analysis of rNMP sequencing experiments, we developed Ribose-Map. Through a series of analytical modules, Ribose-Map transforms raw sequencing data into summary datasets and publication-ready visualizations of results, allowing biologists to identify sites of embedded rNMPs, study the nucleotide sequence context of these rNMPs and explore their genome-wide distribution. By accommodating data from any of the available rNMP sequencing techniques, Ribose-Map can increase the reproducibility of rNMP sequencing experiments and enable a head-to-head comparison of these experiments.

Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual patient tumors. Machine learning (ML) is a computational method particularly suited to the establishment of predictive models of drug response based on genomic profiles of targeted cells. We report here on the application of our previously established open-source support vector machine (SVM)-based algorithm to predict the responses of 175 individual cancer patients to a variety of standard-of-care chemotherapeutic drugs from the gene-expression profiles (RNA-seq or microarray) of individual patient tumors. The models were found to predict patient responses with >80% accuracy. The high PPV of our algorithms across multiple drugs suggests a potential clinical utility of our approach, particularly with respect to the identification of promising second-line treatments for patients failing standard-of-care first-line therapies.

Next-Generation Sequencing and Bioinformatics Protocol for Malaria Drug Resistance Marker Surveillance.

The recent advances in next-generation sequencing technologies provide a new and effective way of tracking malaria drug-resistant parasites. To take advantage of this technology, an end-to-end Illumina targeted amplicon deep sequencing (TADS) and bioinformatics pipeline for molecular surveillance of drug resistance in P. falciparum, called malaria resistance surveillance (MaRS), was developed. TADS relies on PCR enriching genomic regions, specifically target genes of interest, prior to deep sequencing. MaRS enables researchers to simultaneously collect data on allele frequencies of multiple full-length P. falciparum drug resistance genes (crt, mdr1, k13, dhfr, dhps, and the cytochrome b gene), as well as the mitochondrial genome. Information is captured at the individual patient level for both known and potential new single nucleotide polymorphisms associated with drug resistance. The MaRS pipeline was validated using 245 imported malaria cases that were reported to the Centers for Disease Control and Prevention (CDC). The chloroquine resistance crt CVIET genotype (mutations underlined) was observed in 42% of samples, the highly pyrimethamine-resistant dhpsIRN triple mutant in 92% of samples, and the sulfadoxine resistance dhps mutation SGEAA in 26% of samples. The mdr1 NFSND genotype was found in 40% of samples. With the exception of two cases imported from Cambodia, no artemisinin resistance k13 alleles were identified, and 99% of patients carried parasites susceptible to atovaquone-proguanil. Our goal is to implement MaRS at the CDC for routine surveillance of imported malaria cases in the United States and to aid in the adoption of this system at participating state public health laboratories, as well as by global partners.

Mapping-free variant calling using haplotype reconstruction from k-mer frequencies.

Motivation: The standard protocol for detecting variation in DNA is to map millions of short sequence reads to a known reference and find loci that differ. While this approach works well, it cannot be applied where the sample contains dense variants or is too distant from known references. De novo assembly or hybrid methods can recover genomic variation, but the cost of computation is often much higher. We developed a novel k-mer algorithm and software implementation, Kestrel, capable of characterizing densely packed SNPs and large indels without mapping, assembly or de Bruijn graphs. Results: When applied to mosaic penicillin binding protein (PBP) genes in Streptococcus pneumoniae, we found near perfect concordance with assembled contigs at a fraction of the CPU time. Multilocus sequence typing (MLST) with this approach was able to bypass de novo assemblies. Kestrel has a very low false-positive rate when applied to the whole genome, and while Kestrel identified many variants missed by other methods, limitations of a purely k-mer based approach affect overall sensitivity. Availability and implementation: Source code and documentation for a Java implementation of Kestrel can be found at https://github.com/paudano/kestrel. All test code for this publication is located at https://github.com/paudano/kescases. Contact: paudano@gatech.edu or fredrik.vannberg@biology.gatech.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

TLR-exosomes exhibit distinct kinetics and effector function.

The innate immune system is vital to rapidly responding to pathogens and Toll-like receptors (TLRs) are a critical component of this response. Nanovesicular exosomes play a role in immunity, but to date their exact contribution to the dissemination of the TLR response is unknown. Here we show that exosomes from TLR stimulated cells can largely recapitulate TLR activation in distal cells in vitro. We can abrogate the action-at-a-distance signaling of exosomes by UV irradiation, demonstrating that RNA is crucial for their effector function. We are the first to show that exosomes derived from poly(I:C) stimulated cells induce in vivo macrophage M1-like polarization within murine lymph nodes. These poly(I:C) exosomes demonstrate enhanced trafficking to the node and preferentially recruit neutrophils as compared to control exosomes. This work definitively establishes the differential effector function for exosomes in communicating the TLR activation state of the cell of origin.

First Full Draft Genome Sequence of Plasmodium brasilianum.

Plasmodium malariae is a protozoan parasite that can cause human malaria. The simian parasite Plasmodium brasilianum infects New World monkeys from Latin America and is morphologically indistinguishable from P. malariae Here, we report the first full draft genome sequence for P. brasilianum.

Molecular Epidemiology of Plasmodium falciparum kelch13 Mutations in Senegal Determined by Using Targeted Amplicon Deep Sequencing.

The emergence of Plasmodium falciparum resistance to artemisinin in Southeast Asia threatens malaria control and elimination activities worldwide. Multiple polymorphisms in the P. falciparum kelch gene found in chromosome 13 (Pfk13) have been associated with artemisinin resistance. Surveillance of potential drug resistance loci within a population that may emerge under increasing drug pressure is an important public health activity. In this context, P. falciparum infections from an observational surveillance study in Senegal were genotyped using targeted amplicon deep sequencing (TADS) for Pfk13 polymorphisms. The results were compared to previously reported Pfk13 polymorphisms from around the world. A total of 22 Pfk13 propeller domain polymorphisms were identified in this study, of which 12 have previously not been reported. Interestingly, of the 10 polymorphisms identified in the present study that were also previously reported, all had a different amino acid substitution at these codon positions. Most of the polymorphisms were present at low frequencies and were confined to single isolates, suggesting they are likely transient polymorphisms that are part of naturally evolving parasite populations. The results of this study underscore the need to identify potential drug resistance loci existing within a population, which may emerge under increasing drug pressure.

Chocó, Colombia: a hotspot of human biodiversity.

OBJECTIVE: Chocó is a state located on the Pacific coast of Colombia that has a majority Afro-Colombian population. The objective of this study was to characterize the genetic ancestry, admixture and diversity of the population of Chocó, Colombia. METHODOLOGY: Genetic variation was characterized for a sample of 101 donors (61 female and 40 male) from the state of Chocó. Genotypes were determined for each individual via the characterization of 610,545 single nucleotide polymorphisms genome-wide. Haplotypes for the uniparental mitochondrial DNA (female) and Y-DNA (male) chromosomes were also determined. These data were used for comparative analyses with a number of worldwide populations, including putative ancestral populations from Africa, the Americas and Europe, along with several admixed American populations. RESULTS: The population of Chocó has predominantly African genetic ancestry (75.8%) with approximately equal parts European (13.4%) and Native American (11.1%) ancestry. Chocó shows relatively high levels of three-way genetic admixture, and far higher levels of Native American ancestry, compared to other New World African populations from the Caribbean and the United States. There is a striking pattern of sex-specific ancestry in Chocó, with Native American admixture along the female lineage and European admixture along the male lineage. The population of Chocó is also characterized by relatively high levels of overall genetic diversity compared to both putative ancestral populations and other admixed American populations. CONCLUSION: These results suggest a unique genetic heritage for the population of Chocó and underscore the profound human genetic diversity that can be found in the region.

Lymphatic transport of exosomes as a rapid route of information dissemination to the lymph node.

It is well documented that cells secrete exosomes, which can transfer biomolecules that impact recipient cells' functionality in a variety of physiologic and disease processes. The role of lymphatic drainage and transport of exosomes is as yet unknown, although the lymphatics play critical roles in immunity and exosomes are in the ideal size-range for lymphatic transport. Through in vivo near-infrared (NIR) imaging we have shown that exosomes are rapidly transported within minutes from the periphery to the lymph node by lymphatics. Using an in vitro model of lymphatic uptake, we have shown that lymphatic endothelial cells actively enhanced lymphatic uptake and transport of exosomes to the luminal side of the vessel. Furthermore, we have demonstrated a differential distribution of exosomes in the draining lymph nodes that is dependent on the lymphatic flow. Lastly, through endpoint analysis of cellular distribution of exosomes in the node, we identified macrophages and B-cells as key players in exosome uptake. Together these results suggest that exosome transfer by lymphatic flow from the periphery to the lymph node could provide a mechanism for rapid exchange of infection-specific information that precedes the arrival of migrating cells, thus priming the node for a more effective immune response.

Advanced Molecular Detection of Malarone Resistance.

The rapid emergence of drug-resistant malaria parasites during the course of an infection remains a major challenge for providing accurate treatment guidelines. This is particularly important in cases of malaria treatment failure. Using a previously well-characterized case of malaria treatment failure, we show the utility of using next-generation sequencing for early detection of the rise and selection of a previously reported atovaquone-proguanil (malarone) drug resistance-associated mutation.

Whole-Genome Sequencing to Determine Origin of Multinational Outbreak of Sarocladium kiliense Bloodstream Infections.

We used whole-genome sequence typing (WGST) to investigate an outbreak of Sarocladium kiliense bloodstream infections (BSI) associated with receipt of contaminated antinausea medication among oncology patients in Colombia and Chile during 2013-2014. Twenty-five outbreak isolates (18 from patients and 7 from medication vials) and 11 control isolates unrelated to this outbreak were subjected to WGST to elucidate a source of infection. All outbreak isolates were nearly indistinguishable (<5 single-nucleotide polymorphisms), and >21,000 single-nucleotide polymorphisms were identified from unrelated control isolates, suggesting a point source for this outbreak. S. kiliense has been previously implicated in healthcare-related infections; however, the lack of available typing methods has precluded the ability to substantiate point sources. WGST for outbreak investigation caused by eukaryotic pathogens without reference genomes or existing genotyping methods enables accurate source identification to guide implementation of appropriate control and prevention measures.

Ligation of RNA Oligomers by the Schistosoma mansoni Hammerhead Ribozyme in Frozen Solution.

The interstitial liquid phase within frozen aqueous solutions is an environment that minimizes RNA degradation and facilitates reactions that may have relevance to the RNA World hypothesis. Previous work has shown that frozen solutions support condensation of activated nucleotides into RNA oligomers, RNA ligation by the hairpin ribozyme, and RNA synthesis by a RNA polymerase ribozyme. In the current study, we examined the activity of a hammerhead ribozyme (HHR) in frozen solution. The Schistosoma mansoni hammerhead ribozyme, which predominantly cleaves RNA, can ligate its cleaved products (P1 and P2) with yields up to ~23 % in single turnover experiments at 25 °C in the presence of Mg(2+). Our studies show that this HHR ligates RNA oligomers in frozen solution in the absence of divalent cations. Citrate and other anions that exhibit strong ion-water affinity enhanced ligation. Yields up to 43 % were observed in one freeze-thaw cycle and a maximum of 60 % was obtained after several freeze-thaw cycles using wild-type P1 and P2. Truncated and mutated P1 substrates were ligated to P2 with yields of 14-24 % in one freeze-thaw cycle. A pool of P2 substrates with mixtures of all four bases at five positions were ligated with P1 in frozen solution. High-throughput sequencing indicated that 70 of the 1024 possible P2 sequences were represented in ligated products at 1000 or more read counts per million reads. The results indicate that the HHR can ligate a range of short RNA oligomers into an ensemble of diverse sequences in ice.

KAnalyze: a fast versatile pipelined k-mer toolkit.

MOTIVATION: Converting nucleotide sequences into short overlapping fragments of uniform length, k-mers, is a common step in many bioinformatics applications. While existing software packages count k-mers, few are optimized for speed, offer an application programming interface (API), a graphical interface or contain features that make it extensible and maintainable. We designed KAnalyze to compete with the fastest k-mer counters, to produce reliable output and to support future development efforts through well-architected, documented and testable code. Currently, KAnalyze can output k-mer counts in a sorted tab-delimited file or stream k-mers as they are read. KAnalyze can process large datasets with 2 GB of memory. This project is implemented in Java 7, and the command line interface (CLI) is designed to integrate into pipelines written in any language. RESULTS: As a k-mer counter, KAnalyze outperforms Jellyfish, DSK and a pipeline built on Perl and Linux utilities. Through extensive unit and system testing, we have verified that KAnalyze produces the correct k-mer counts over multiple datasets and k-mer sizes. AVAILABILITY AND IMPLEMENTATION: KAnalyze is available on SourceForge: https://sourceforge.net/projects/kanalyze/.