Chemical-Genetic Approaches for Exploring Mode of Action of Antifungal Compounds in the Fungal Pathogen Candida albicans.

Candida albicans is a prevalent fungal pathogen of humans that can cause both superficial and life-threatening disease, primarily in immunocompromised populations. Currently, antifungal drug classes available to treat fungal infections remain limited and the emergence of drug-resistant strains threatens antifungal efficacy, necessitating the discovery and development of additional therapeutics. The construction of the C. albicans double-barcoded heterozygous deletion collection (DBC) enables the rapid and systematic assessment of haploinsufficiency phenotypes in a pooled format. Specifically, this functional genomics resource can be used to identify heterozygous deletion mutants that are hypersensitive to compounds in order to define putative cellular targets and/or other modifiers of compound activity. Here, we describe protocols to characterize the mode of action of small molecules using the C. albicans DBC, including how to prepare compound-treated cultures, isolate genomic DNA, amplify strain-specific barcodes, and prepare DNA libraries for high-throughput sequencing. This technique provides a powerful approach to elucidate the compound mechanism of action in order to bolster the antifungal pipeline.

Using unique molecular identifiers to improve allele calling in low-template mixtures.

PCR artifacts are an ever-present challenge in sequencing applications. These artifacts can seriously limit the analysis and interpretation of low-template samples and mixtures, especially with respect to a minor contributor. In medicine, molecular barcoding techniques have been employed to decrease the impact of PCR error and to allow the examination of low-abundance somatic variation. In principle, it should be possible to apply the same techniques to the forensic analysis of mixtures. To that end, several short tandem repeat loci were selected for targeted sequencing, and a bioinformatic pipeline for analyzing the sequence data was developed. The pipeline notes the relevant unique molecular identifiers (UMIs) attached to each read and, using machine learning, filters the noise products out of the set of potential alleles. To evaluate this pipeline, DNA from pairs of individuals were mixed at different ratios (1-1, 1-9) and sequenced with different starting amounts of DNA (10, 1 and 0.1 ng). Naïvely using the information in the molecular barcodes led to increased performance, with the machine learning resulting in an additional benefit. In concrete terms, using the UMI data results in less noise for a given amount of drop out. For instance, if thresholds are selected that filter out a quarter of the true alleles, using read counts accepts 2381 noise alleles and using raw UMI counts accepts 1726 noise alleles, while the machine learning approach only accepts 307.

MuA-based Molecular Indexing for Rare Mutation Detection by Next-Generation Sequencing.

Detection of low-frequency mutations in cancer genomes or other heterogeneous cell populations requires high-fidelity sequencing. Molecular barcoding is one of the key technologies that enables the differentiation of true mutations from errors, which can be caused by sequencing or library preparation processes. However, current approaches where barcodes are introduced via primer extension or adaptor ligation do not utilize the full power of barcoding, due to complicated library preparation workflows and biases. Here we demonstrate the remarkable tolerance of MuA transposase to the presence of multiple replacements in transposon sequence, and explore this unique feature to engineer the MuA transposome complex with randomised nucleotides in 12 transposon positions, which can be introduced as a barcode into the target molecule after transposition event. We applied the approach of Unique MuA-based Molecular Indexing (UMAMI) to assess the power of rare mutation detection by shortgun sequencing on the Illumina platform. Our results show that UMAMI allows detection of rare mutations readily and reliably, and in this paper we report error rate values for the number of thermophilic DNA polymerases measured by using UMAMI.

UMIc: A Preprocessing Method for UMI Deduplication and Reads Correction.

A recent refinement in high-throughput sequencing involves the incorporation of unique molecular identifiers (UMIs), which are random oligonucleotide barcodes, on the library preparation steps. A UMI adds a unique identity to different DNA/RNA input molecules through polymerase chain reaction (PCR) amplification, thus reducing bias of this step. Here, we propose an alignment free framework serving as a preprocessing step of fastq files, called UMIc, for deduplication and correction of reads building consensus sequences from each UMI. Our approach takes into account the frequency and the Phred quality of nucleotides and the distances between the UMIs and the actual sequences. We have tested the tool using different scenarios of UMI-tagged library data, having in mind the aspect of a wide application. UMIc is an open-source tool implemented in R and is freely available from https://github.com/BiodataAnalysisGroup/UMIc.

Reducing noise and stutter in short tandem repeat loci with unique molecular identifiers.

Unique molecular identifiers (UMIs) are a promising approach to contend with errors generated during PCR and massively parallel sequencing (MPS). With UMI technology, random molecular barcodes are ligated to template DNA molecules prior to PCR, allowing PCR and sequencing error to be tracked and corrected bioinformatically. UMIs have the potential to be particularly informative for the interpretation of short tandem repeats (STRs). Traditional MPS approaches may simply lead to the observation of alleles that are consistent with the hypotheses of stutter, while with UMIs stutter products bioinformatically may be re-associated with their parental alleles and subsequently removed. Herein, a bioinformatics pipeline named strumi is described that is designed for the analysis of STRs that are tagged with UMIs. Unlike other tools, strumi is an alignment-free machine learning driven algorithm that clusters individual MPS reads into UMI families, infers consensus super-reads that represent each family and provides an estimate the resulting haplotype's accuracy. Super-reads, in turn, approximate independent measurements not of the PCR products, but of the original template molecules, both in terms of quantity and sequence identity. Provisional assessments show that naïve threshold-based approaches generate super-reads that are accurate (∼97 % haplotype accuracy, compared to ∼78 % when UMIs are not used), and the application of a more nuanced machine learning approach increases the accuracy to ∼99.5 % depending on the level of certainty desired. With these features, UMIs may greatly simplify probabilistic genotyping systems and reduce uncertainty. However, the ability to interpret alleles at trace levels also permits the interpretation, characterization and quantification of contamination as well as somatic variation (including somatic stutter), which may present newfound challenges.

Poor performance of DNA barcoding and the impact of RAD loci filtering on the species delimitation of an Iberian ant-eating spider.

Genomic data provide unprecedented power for species delimitation. However, current implementations are still time and resource consuming. In addition, bioinformatic processing is contentious and its impact on downstream analyses is insufficiently understood. Here we employ ddRAD sequencing and a thorough sampling for species delimitation in Zodarion styliferum, a widespread Iberian ant-eating spider. We explore the influence of the loci filtering strategy on the downstream phylogenetic analyses, genomic clustering and coalescent species delimitation. We also assess the accuracy of one mitochondrial (COI) and one nuclear (ITS) barcode for fast and inexpensive species delineation in the group. Our genomic data strongly support two morphologically cryptic but ecologically divergent lineages, mainly restricted to the central-eastern and western parts of the Iberian Peninsula, respectively. Larger matrices with more missing data showed increased genomic diversity, supporting that bioinformatic strategies to maximize matrix completion disproportionately exclude loci with the highest mutation rates. Moderate loci filtering gave the best results across analyses: although larger matrices returned concatenated phylogenies with higher support, middle-sized matrices performed better in genetic structure analyses. COI displayed high diversity and a conspicuous barcode gap, revealing 13 mitochondrial lineages. Mitonuclear discordance is consistent with ancestral isolation in multiple groups, probably in glacial refugia, followed by range expansion and secondary contact that produced genomic homogenization. Several apparently (unidirectionally) introgressed specimens further challenge the accuracy of species identification through mitochondrial barcodes in the group. Conversely, ITS failed to separate both lineages of Z. styliferum. This study shows an extreme case of mitonuclear discordance that highlights the limitations of single molecular barcodes for species delimitation, even in presence of distinct barcode gaps, and brings new light on the effects of parameterization on shallow-divergence studies using RAD data.

Investigation of Somatic Mutations in Human Brains Targeting Genes Associated With Parkinson's Disease.

Background: Somatic single nucleotide variant (SNV) mutations occur in neurons but their role in synucleinopathies is unknown. Aim: We aimed to identify disease-relevant low-level somatic SNVs in brains from sporadic patients with synucleinopathies and a monozygotic twin carrying LRRK2 G2019S, whose penetrance could be explained by somatic variation. Methods and Results: We included different brain regions from 26 Parkinson's disease (PD), one Incidental Lewy body, three multiple system atrophy cases, and 12 controls. The whole SNCA locus and exons of other genes associated with PD and neurodegeneration were deeply sequenced using molecular barcodes to improve accuracy. We selected 21 variants at 0.33-5% allele frequencies for validation using accurate methods for somatic variant detection. Conclusions: We could not detect disease-relevant somatic SNVs, however we cannot exclude their presence at earlier stages of degeneration. Our results support that coding somatic SNVs in neurodegeneration are rare, but other types of somatic variants may hold pathological consequences in synucleinopathies.

Molecular validation of anthropophilic Phlebotominae sandflies (Diptera: Psychodidae) in Central Panama

Six Phlebotominae sand fly species are incriminated as biological vectors of human pathogens in Panama, but molecular corroboration is still needed. We aim at confirming the identity of Phlebotominae species documented as anthropophilic in Panama. Adult sandflies were collected from August 2010 to February 2012 in Central Panama using CDC light traps. Species confirmation was accomplished through molecular barcodes and allied sequences from GenBank. A total of 53,366 sand fly specimens representing 18 species were collected. Five species were validated molecularly as single phylogenetic clusters, but Psychodopygus thula depicted two genetically divergent lineages, which may be indicative of cryptic speciation.

Using Barcoded HIV Ensembles (B-HIVE) for Single Provirus Transcriptomics.

The latent HIV reservoir is the main barrier to curing AIDS, because infected cells escape the immune system and antiretroviral therapies. Developing new treatment strategies requires technologies to trace latent proviruses. Here, we describe a genome-wide technique called Barcoded HIV Ensembles (B-HIVE) to measure HIV expression at the single provirus level. The principle of B-HIVE is to tag the genome of HIV with DNA barcodes to trace viral transcripts produced by single proviruses in an infected cell population. This in turn reveals which proviruses are active and which are latent or expressed at low level. B-HIVE is a high-throughput method to identify and quantify thousands of individual viral transcripts per round of infection. It can be applied in different conditions, characterizing the response of single proviruses to different treatments. Overall, B-HIVE gives unprecedented insight into the expression of single proviruses in populations of HIV-infected cells. © 2018 by John Wiley & Sons, Inc.

Seasonal dynamics of freshwater pathogens as measured by microarray at Lake Sapanca, a drinking water source in the north-eastern part of Turkey.

Monitoring drinking water quality is an important public health issue. Two objectives from the 4 years, six nations, EU Project µAqua were to develop hierarchically specific probes to detect and quantify pathogens in drinking water using a PCR-free microarray platform and to design a standardised water sampling program from different sources in Europe to obtain sufficient material for downstream analysis. Our phylochip contains barcodes (probes) that specifically identify freshwater pathogens that are human health risks in a taxonomic hierarchical fashion such that if species is present, the entire taxonomic hierarchy (genus, family, order, phylum, kingdom) leading to it must also be present, which avoids false positives. Molecular tools are more rapid, accurate and reliable than traditional methods, which means faster mitigation strategies with less harm to humans and the community. We present microarray results for the presence of freshwater pathogens from a Turkish lake used drinking water and inferred cyanobacterial cell equivalents from samples concentrated from 40 into 1 L in 45 min using hollow fibre filters. In two companion studies from the same samples, cyanobacterial toxins were analysed using chemical methods and those dates with highest toxin values also had highest cell equivalents as inferred from this microarray study.

NanoString, a novel digital color-coded barcode technology: current and future applications in molecular diagnostics.

INTRODUCTION: Formalin-fixed, paraffin-embedded (FFPE) tissue sample is a gold mine of resources for molecular diagnosis and retrospective clinical studies. Although molecular technologies have expanded the range of mutations identified in FFPE samples, the applications of existing technologies are limited by the low nucleic acids yield and poor extraction quality. As a result, the routine clinical applications of molecular diagnosis using FFPE samples has been associated with many practical challenges. NanoString technologies utilize a novel digital color-coded barcode technology based on direct multiplexed measurement of gene expression and offer high levels of precision and sensitivity. Each color-coded barcode is attached to a single target-specific probe corresponding to a single gene which can be individually counted without amplification. Therefore, NanoString is especially useful for measuring gene expression in degraded clinical specimens. Areas covered: This article describes the applications of NanoString technologies in molecular diagnostics and challenges associated with its applications and the future development. Expert commentary: Although NanoString technology is still in the early stages of clinical use, it is expected that NanoString-based cancer expression panels would play more important roles in the future in classifying cancer patients and in predicting the response to therapy for better personal therapeutic care.

Microarray (phylochip) analysis of freshwater pathogens at several sites along the Northern German coast transecting both estuarine and freshwaters.

Monitoring the quality of drinking water is an important issue for public health. Two of the main objectives of the European Project µAQUA were (i) the development of specific probes to detect and quantify pathogens in drinking water and (ii) the design of standardized sampling programs of water from different sources in Europe in order to obtain sufficient material for downstream analysis. Our phylochip contains barcodes that specifically identify freshwater pathogens for enabling the detection of organisms that can be risks for human health. Monitoring for organisms with molecular tools is rapid, more accurate and more reliable than traditional methods. Rapid detection means that mitigation strategies come into play faster with less harm to the community and to humans. Samples were collected from several waters in France, Germany, Ireland, Italy and Turkey over 2 years. We present microarray results for the presence of freshwater pathogens from brackish and freshwater sites in Northern Germany, and cyanobacterial cell numbers inferred from these sites. In a companion study from the same samples, cyanobacterial toxins were analyzed using two methods and those sites with highest toxin values also had highest cell numbers as inferred from this microarray study.

Two new Korean earthworms (Annelida, Oligochaeta, Megadrilacea, Megascolecidae).

Two Korean endemic pheretimoid Amynthas Kinberg, 1867 species belonging in family Megascolecidae s. stricto are sketched, dissected and described. Amynthas daeari Blakemore sp. n. has spermathecae in 6/7/8 complying with an Amynthas tokioensis spp-group, whilst Amynthas jinburi Blakemore sp. n. has spermathecal pores in 5 & 6 strictly complying with Sims and Easton's (1972)Amynthas canaliculatus-group. A definitive COI gene barcode is provided for the holotype of Amynthas daeari but the age since collection or preservation of the Amynthas jinburi type in 2000 precluded its mtDNA extraction at this time.