ProDeGe: a computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.Recent technological advancements have enabled the large-scale sampling of genomes from uncultured microbial taxa, through the high-throughput sequencing of single amplified genomes (SAGs; Rinke et al., 2013; Swan et al., 2013) and assembly and binning of genomes from metagenomes (GMGs; Cuvelier et al., 2010; Sharon and Banfield, 2013). The importance of these products in assessing community structure and function has been established beyond doubt (Kalisky and Quake, 2011). Multiple Displacement Amplification (MDA) and sequencing of single cells has been immensely successful in capturing rare and novel phyla, generating valuable references for phylogenetic anchoring. However, efforts to conduct MDA and sequencing in a high-throughput manner have been heavily impaired by contamination from DNA introduced by the environmental sample, as well as introduced during the MDA or sequencing process (Woyke et al., 2011; Engel et al., 2014; Field et al., 2014). Similarly, metagenome binning and assembly often carries various errors and artifacts depending on the methods used (Nielsen et al., 2014). Even cultured isolate genomes have been shown to lack immunity to contamination with other species (Parks et al., 2014; Mukherjee et al., 2015). As sequencing of these genome product types rapidly increases, contaminant sequences are finding their way into public databases as reference sequences. It is therefore extremely important to define standardized and automated protocols for quality control and decontamination, which would go a long way towards establishing quality standards for all microbial genome product types.Current procedures for decontamination and quality control of genome sequences in single cells and metagenome bins are heavily manual and can consume hours/megabase when performed by expert biologists. Supervised decontamination typically involves homology-based inspection of ribosomal RNA sequences and protein coding genes, as well as visual analysis of k-mer frequency plots and guanine–cytosine content (Clingenpeel, 2015). Manual decontamination is also possible through the software SmashCell (Harrington et al., 2010), which contains a tool for visual identification of contaminants from a self-organizing map and corresponding U-matrix. Another existing software tool, DeconSeq (Schmieder and Edwards, 2011), automatically removes contaminant sequences, however, the contaminant databases are required input. The former lacks automation, whereas the latter requires prior knowledge of contaminants, rendering both applications impractical for high-throughput decontamination.Here, we introduce ProDeGe, the first fully automated computational protocol for decontamination of genomes. ProDeGe uses a combination of homology-based and sequence composition-based approaches to separate contaminant sequences from the target genome draft. It has been pre-calibrated to discard at least 84% of the contaminant sequence, which results in retention of a median 84% of the target sequence. The standalone software is freely available at http://prodege.jgi-psf.org//downloads/src and can be run on any system that has Perl, R (R Core Team, 2014), Prodigal (Hyatt et al., 2010) and NCBI Blast (Camacho et al., 2009) installed. A graphical viewer allowing further exploration of data sets and exporting of contigs accompanies the web application for ProDeGe at http://prodege.jgi-psf.org, which is open to the wider scientific community as a decontamination service (Supplementary Figure S1).The assembly and corresponding NCBI taxonomy of the data set to be decontaminated are required inputs to ProDeGe (Figure 1a). Contigs are annotated with genes following which, eukaryotic contamination is removed based on homology of genes at the nucleotide level using the eukaryotic subset of NCBI''s Nucleotide database as the reference. For detecting prokaryotic contamination, a curated database of reference contigs from the set of high-quality genomes within the Integrated Microbial Genomes (IMG; Markowitz et al., 2014) system is used as the reference. This ensures that errors in public reference databases due to poor quality of sequencing, assembly and annotation do not negatively impact the decontamination process. Contigs determined as belonging to the target organism based on nucleotide level homology to sequences in the above database are defined as ‘Clean'', whereas those aligned to other organisms are defined as ‘Contaminant''. Contigs whose origin cannot be determined based on alignment are classified as ‘Undecided''. Classified clean and contaminated contigs are used to calibrate the separation in the subsequent 5-mer based binning module, which classifies undecided contigs as ‘Clean'' or ‘Contaminant'' using principal components analysis (PCA) of 5-mer frequencies. This parameter can also be specified by the user. When data sets do not have taxonomy deeper than phylum level, or a single confident taxonomic bin cannot be detected using sequence alignment, solely 9-mer based binning is used due to more accurate overall classification. In the absence of a user-defined cutoff, a pre-calibrated cutoff for 80% or more specificity separates the clean contigs from contaminated sequences in the resulting PCA of the 9-mer frequency matrix. Details on ProDeGe''s custom database, evaluation of the performance of the system and exploration of the parameter space to calibrate ProDeGe for a high accurate classification rate are provided in the Supplementary Material.Open in a separate windowFigure 1(a) Schematic overview of the ProDeGe engine. (b) Features of data sets used to validate ProDeGe: SAGs from the Arabidopsis endophyte sequencing project, MDM project, public data sets found in IMG but not sequenced at the JGI, as well as genomes from metagenomes. All the data and results can be found in Supplementary Table S3.The performance of ProDeGe was evaluated using 182 manually screened SAGs (Figure 1b,Supplementary Table S1) from two studies whose data sets are publicly available within the IMG system: genomes of 107 SAGs from an Arabidopsis endophyte sequencing project and 75 SAGs from the Microbial Dark Matter (MDM) project* (only 75/201 SAGs from the MDM project had 1:1 mapping between contigs in the unscreened and the manually screened versions, hence these were used; Rinke et al., 2013). Manual curation of these SAGs demonstrated that the use of ProDeGe prevented 5311 potentially contaminated contigs in these data sets from entering public databases. Figure 2a demonstrates the sensitivity vs specificity plot of ProDeGe results for the above data sets. Most of the data points in Figure 2a cluster in the top right of the box reflecting a median retention of 89% of the clean sequence (sensitivity) and a median rejection of 100% of the sequence of contaminant origin (specificity). In addition, on average, 84% of the bases of a data set are accurately classified. ProDeGe performs best when the target organism has sequenced homologs at the class level or deeper in its high-quality prokaryotic nucleotide reference database. If the target organism''s taxonomy is unknown or not deeper than domain level, or there are few contigs with taxonomic assignments, a target bin cannot be assessed and thus ProDeGe removes contaminant contigs using sequence composition only. The few samples in Figure 2a that demonstrate a higher rate of false positives (lower specificity) and/or reduced sensitivity typically occur when the data set contains few contaminant contigs or ProDeGe incorrectly assumes that the largest bin is the target bin. Some data sets contain a higher proportion of contamination than target sequence and ProDeGe''s performance can suffer under this condition. However, under all other conditions, ProDeGe demonstrates high speed, specificity and sensitivity (Figure 2). In addition, ProDeGe demonstrates better performance in overall classification when nucleotides are considered than when contigs are considered, illustrating that longer contigs are more accurately classified (Supplementary Table S1).Open in a separate windowFigure 2ProDeGe accuracy and performance scatterplots of 182 manually curated single amplified genomes (SAGs), where each symbol represents one SAG data set. (a) Accuracy shown by sensitivity (proportion of bases confirmed ‘Clean'') vs specificity (proportion of bases confirmed ‘Contaminant'') from the Endophyte and Microbial Dark Matter (MDM) data sets. Symbol size reflects input data set size in megabases. Most points cluster in the top right of the plot, showing ProDeGe''s high accuracy. Median and average overall results are shown in Supplementary Table S1. (b) ProDeGe completion time in central processing unit (CPU) core hours for the 182 SAGs. ProDeGe operates successfully at an average rate of 0.30 CPU core hours per megabase of sequence. Principal components analysis (PCA) of a 9-mer frequency matrix costs more computationally than PCA of a 5-mer frequency matrix used with blast-binning. The lack of known taxonomy for the MDM data sets prevents blast-binning, thus showing longer finishing times than the endophyte data sets, which have known taxonomy for use in blast-binning.All SAGs used in the evaluation of ProDeGe were assembled using SPAdes (Bankevich et al., 2012). In-house testing has shown that reads assembled with SPAdes from different strains or even slightly divergent species of the same genera may be combined into the same contig (Personal communications, KT and Robert Bowers). Ideally, the DNA in a well that gets sequenced belongs to a single cell. In the best case, contaminant sequences need to be at least from a different species to be recognized as such by the homology-based screening stage. In the absence of closely related sequenced organisms, contaminant sequences need to be at least from a different genus to be recognized as such by the composition-based screening stage (Supplementary Material). Thus, there is little risk of ProDeGe separating sequences from clonal populations or strains. We have found species- and genus-level contamination in MDA samples to be rare.To evaluate the quality of publicly available uncultured genomes, ProDeGe was used to screen 185 SAGs and 14 GMGs (Figure 1b). Compared with CheckM (Parks et al., 2014), a tool which calculates an estimate of genome sequence contamination using marker genes, ProDeGe generally marks a higher proportion of sequence as ‘Contaminant'' (Supplementary Table S2). This is because ProDeGe has been calibrated to perform at high specificity levels. The command line version of ProDeGe allows users to conduct their own calibration and specify a user-defined distance cutoff. Further, CheckM only outputs the proportion of contamination, but ProDeGe actually labels each contig as ‘Clean'' or ‘Contaminant'' during the process of automated removal.The web application for ProDeGe allows users to export clean and contaminant contigs, examine contig gene calls with their corresponding taxonomies, and discover contig clusters in the first three components of their k-dimensional space. Non-linear approaches for dimensionality reduction of k-mer vectors are gaining popularity (van der Maaten and Hinton, 2008), but we observed no systematic advantage of using t-Distributed Stochastic Neighbor Embedding over PCA (Supplementary Figure S2).ProDeGe is the first step towards establishing a standard for quality control of genomes from both cultured and uncultured microorganisms. It is valuable for preventing the dissemination of contaminated sequence data into public databases, avoiding resulting misleading analyses. The fully automated nature of the pipeline relieves scientists of hours of manual screening, producing reliably clean data sets and enabling the high-throughput screening of data sets for the first time. ProDeGe, therefore, represents a critical component in our toolkit during an era of next-generation DNA sequencing and cultivation-independent microbial genomics.     

Alkaline-sulfite pretreatment and use of surfactants during enzymatic hydrolysis to enhance ethanol production from sugarcane bagasse

Sugarcane bagasse is a by-product from the sugar and ethanol industry which contains approximately 70 % of its dry mass composed by polysaccharides. To convert these polysaccharides into fuel ethanol it is necessary a pretreatment step to increase the enzymatic digestibility of the recalcitrant raw material. In this work, sugarcane bagasse was pretreated by an alkaline-sulfite chemithermomechanical process for increasing its enzymatic digestibility. Na₂SO₃ and NaOH ratios were fixed at 2:1, and three increasing chemical loads, varying from 4 to 8 % m/m Na₂SO₃, were used to prepare the pretreated materials. The increase in the alkaline-sulfite load decreased the lignin content in the pretreated material up to 35.5 % at the highest chemical load. The pretreated samples presented enhanced glucose yields during enzymatic hydrolysis as a function of the pretreatment severity. The maximum glucose yield (64 %) was observed for the samples pretreated with the highest chemical load. The use of 2.5 g l^?1 Tween 20 in the hydrolysis step further increased the glucose yield to 75 %. Semi-simultaneous hydrolysis and fermentation of the pretreated materials indicated that the ethanol yield was also enhanced as a function of the pretreatment severity. The maximum ethanol yield was 56 ± 2 % for the sample pretreated with the highest chemical load. For the sample pretreated with the lowest chemical load (2 % m/m NaOH and 4 % m/m Na₂SO₃), adding Tween 20 during the hydrolysis process increased the ethanol yield from 25 ± 3 to 39.5 ± 1 %.     

Trypanosoma cruzi Needs a Signal Provided by Reactive Oxygen Species to Infect Macrophages

Background

During Trypanosoma cruzi infection, macrophages produce reactive oxygen species (ROS) in a process called respiratory burst. Several works have aimed to elucidate the role of ROS during T. cruzi infection and the results obtained are sometimes contradictory. T. cruzi has a highly efficiently regulated antioxidant machinery to deal with the oxidative burst, but the parasite macromolecules, particularly DNA, may still suffer oxidative damage. Guanine (G) is the most vulnerable base and its oxidation results in formation of 8-oxoG, a cellular marker of oxidative stress.

Methodology/Principal Findings

In order to investigate the contribution of ROS in T. cruzi survival and infection, we utilized mice deficient in the gp91^phox (Phox KO) subunit of NADPH oxidase and parasites that overexpress the enzyme EcMutT (from Escherichia coli) or TcMTH (from T. cruzi), which is responsible for removing 8-oxo-dGTP from the nucleotide pool. The modified parasites presented enhanced replication inside murine inflammatory macrophages from C57BL/6 WT mice when compared with control parasites. Interestingly, when Phox KO macrophages were infected with these parasites, we observed a decreased number of all parasites when compared with macrophages from C57BL/6 WT. Scavengers for ROS also decreased parasite growth in WT macrophages. In addition, treatment of macrophages or parasites with hydrogen peroxide increased parasite replication in Phox KO mice and in vivo.

Conclusions

Our results indicate a paradoxical role for ROS since modified parasites multiply better inside macrophages, but proliferation is significantly reduced when ROS is removed from the host cell. Our findings suggest that ROS can work like a signaling molecule, contributing to T. cruzi growth inside the cells.     

Metabolic profile and antioxidant responses during drought stress recovery in sugarcane treated with humic acids and endophytic diazotrophic bacteria

Water deficit is the major yield‐limiting factor for sugarcane crop production that can be enhanced by inoculating with plant growth promoting bacteria (PGPB) combined with humic substances. The aim of this work was to examine changes to the metabolic profile and antioxidant enzyme activity of sugarcane treated with PGPB and humic acid (HA) after drought and then rehydration. The drought was imposed by withholding irrigation for 21 days thereby measuring enzyme activity, metabolic profile and photosynthetic rate 1 week after rehydratation. Growth of plants treated with HA, PGPB and with both treatments combined (PGPB + HA) was higher than control plants. The antioxidant enzymes superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activities remained higher after rehydration only in plants treated with HA. Plants treated with HA and PGPB + HA exhibited increased transpiration, stomatal conductance and net photosynthesis than plants treated with PGPB. The PGPB‐treated plants exhibited drought resistance that resembled ‘delayed stress onset’, which is a new term for preserving water in the plants tissues. Water preservation in plants treated with PGPB was corroborated by higher relative water content (RWC) than control plants at the end of the drought period. Plants treated with HA + PGPB exhibited the highest water potential after rehydration and high RWC. Osmotic adjustment in the other treatments (control, HA and PGPB) was indicated by a new pattern of metabolic response after rehydration, including generally enhanced carbohydrates and proteins and specific changes induced by HA‐enhancing aromatic compounds, whereas PGPB exhibited enhanced fatty acids and other aliphatic H species. Humic acids assist with drought stress recovery by inducing antioxidant enzyme activity whereas PGPB induced preservation of leaf water potential and RWC by closing stomata efficiently, resulting in plant water preservation.     

Immobilized Metal Affinity Chromatography Coupled to Multiple Reaction Monitoring Enables Reproducible Quantification of Phospho-signaling

A major goal in cell signaling research is the quantification of phosphorylation pharmacodynamics following perturbations. Traditional methods of studying cellular phospho-signaling measure one analyte at a time with poor standardization, rendering them inadequate for interrogating network biology and contributing to the irreproducibility of preclinical research. In this study, we test the feasibility of circumventing these issues by coupling immobilized metal affinity chromatography (IMAC)-based enrichment of phosphopeptides with targeted, multiple reaction monitoring (MRM) mass spectrometry to achieve precise, specific, standardized, multiplex quantification of phospho-signaling responses. A multiplex immobilized metal affinity chromatography- multiple reaction monitoring assay targeting phospho-analytes responsive to DNA damage was configured, analytically characterized, and deployed to generate phospho-pharmacodynamic curves from primary and immortalized human cells experiencing genotoxic stress. The multiplexed assays demonstrated linear ranges of ≥3 orders of magnitude, median lower limit of quantification of 0.64 fmol on column, median intra-assay variability of 9.3%, median inter-assay variability of 12.7%, and median total CV of 16.0%. The multiplex immobilized metal affinity chromatography- multiple reaction monitoring assay enabled robust quantification of 107 DNA damage-responsive phosphosites from human cells following DNA damage. The assays have been made publicly available as a resource to the community. The approach is generally applicable, enabling wide interrogation of signaling networks.Cell signaling research is faced with the challenging task of interrogating increasingly large numbers of analytes in “systems biology” approaches, while maintaining the high standards of integrity and reproducibility traditionally associated with the scientific approach. For example, studies interrogating complex systems, such as protein signaling networks, require quantification technologies capable of sensitive, specific, multiplexable, and reproducible application. However, recent reports have highlighted alarmingly high rates of irreproducibility in fundamental biological and pre-clinical studies (1, 2), as well as poor performance of affinity reagents used in traditional proteomic assay and detection platforms (3, 4). There is an imminent need for high quality assays, including highly characterized standards and detailed documentation of processes and procedures (5). To improve the translation of cell signaling discoveries into clinical application, we need reproducible and transferable technologies that enable higher throughput quantification of protein phosphorylation.Signaling dynamics through post-translational modifications (e.g. phosphorylation) are predominantly measured by Western blotting. Although this technique has led to many discoveries and is the de facto “gold standard,” it suffers from many drawbacks. Western blotting is a low throughput approach applied to individual analytes (i.e. no multiplexing) and is susceptible to erroneous interpretation when applied quantitatively (6). Alternative immunoassay platforms have emerged (e.g. immunohistochemistry, ELISA, mass cytometry, and bead-based or planar arrays), but suffer from similar limitations, namely specificity issues (because of cross-reactivity of antibodies), poor standardization, and difficulties in multiplexing.One alternative for quantifying phosphorylation is targeted, multiple reaction monitoring (MRM)¹ MS, a widely deployed technique in clinical laboratories for quantification of small molecules (7, 8). MRM is now also well established for precise and specific quantification of endogenous, proteotypic peptides relative to spiked-in stable isotope-labeled internal standards (9–11), and MRM can be applied to phosphopeptides (12–18). MRM assays can be run at high multiplex levels (19–21) and can be standardized to be highly reproducible across laboratories (22–24), even on an international stage (25). Because phosphorylation typically occurs at sub-stoichiometric levels and because phosphopeptides must compete for ionization with more abundant peptides, mass spectrometry-based analysis of phosphorylation requires an analyte enrichment step. Immuno-affinity enrichment approaches using anti-phospho-tyrosine antibodies (26) or panels of antibodies targeting signaling nodes (27) have been implemented with shotgun mass spectrometry. Although anti-peptide antibodies can also be used to enrich individual phosphopeptides upstream of MRM (28), the generation of these reagents is time-consuming and costly, limiting widespread uptake.Phosphopeptide enrichment based on metal affinity chromatography has recently matured into a reproducible approach (29). Immobilized metal affinity chromatography (IMAC) is widely used in discovery phosphoproteomic studies to enrich phosphopeptides upstream of shotgun-based mass spectrometry (30, 31). We hypothesized that a subset of the cellular phosphoproteome with favorable binding characteristics to the IMAC resin might be reproducibly recovered for quantification when coupled with quantitative MRM mass spectrometry, enabling robust IMAC-MRM assays without the need for an antibody.In this report, we: (1) demonstrate the feasibility of generating analytically robust, multiplex IMAC-MRM assays for quantifying cellular phospho-signaling, (2) present a semi-automated, 96-well format magnetic bead-based protocol for IMAC enrichment, (3) provide a catalogue of phosphopeptides that are highly amenable to IMAC-MRM quantification, and (4) make publicly available standard operating protocols (SOP) and fit-for-purpose analytical validation data for IMAC-MRM assays targeting 107 phospho-analytes, providing a community resource for study of the DNA damage response. The data suggest that the IMAC-MRM approach is generally applicable to signaling pathways, enabling wider interrogation of signaling networks.     

IL-22 Restrains Tapeworm-Mediated Protection against Experimental Colitis via Regulation of IL-25 Expression

Interleukin (IL)-22, an immune cell-derived cytokine whose receptor expression is restricted to non-immune cells (e.g. epithelial cells), can be anti-inflammatory and pro-inflammatory. Mice infected with the tapeworm Hymenolepis diminuta are protected from dinitrobenzene sulphonic acid (DNBS)-induced colitis. Here we assessed expulsion of H. diminuta, the concomitant immune response and the outcome of DNBS-induced colitis in wild-type (WT) and IL-22 deficient mice (IL-22^-/-) ± infection. Interleukin-22^-/- mice had a mildly impaired ability to expel the worm and this correlated with reduced or delayed induction of TH2 immunity as measured by splenic and mesenteric lymph node production of IL-4, IL-5 and IL-13 and intestinal Muc-2 mRNA and goblet cell hyperplasia; in contrast, IL-25 increased in the small intestine of IL-22^-/- mice 8 and 12 days post-infection compared to WT mice. In vitro experiments revealed that H. diminuta directly evoked epithelial production of IL-25 that was inhibited by recombinant IL-22. Also, IL-10 and markers of regulatory T cells were increased in IL-22^-/- mice that displayed less DNBS (3 mg, ir. 72h)-induced colitis. Wild-type mice infected with H. diminuta were protected from colitis, as were infected IL-22^-/- mice and the latter to a degree that they were almost indistinguishable from control, non-DNBS treated mice. Finally, treatment with anti-IL-25 antibodies exaggerated DNBS-induced colitis in IL-22^-/- mice and blocked the anti-colitic effect of infection with H. diminuta. Thus, IL-22 is identified as an endogenous brake on helminth-elicited TH2 immunity, reducing the efficacy of expulsion of H. diminuta and limiting the effectiveness of the anti-colitic events mobilized following infection with H. diminuta in a non-permissive host.     

The Protective Association between Pet Ownership and Depression among Street-involved Youth: A Cross-sectional Study

Street-involved youth represent a particularly vulnerable subsection of the homeless population and are at increased risk of health problems, substance abuse, and depression. Qualitative research has demon- strated that animal companions help homeless youth cope with loneliness, are motivators for positive change, such as decreasing drug or alcohol use, provide unconditional love without judgement, and improve youths’ sense of health. To quantitatively investigate the association between depression and pet ownership among street-involved youth, a cross-sectional study was per- formed with a convenience sample of 189 street-involved youths who were surveyed in four cities in Ontario, Canada, 89 of whom were pet owners and 100 of whom were not. Logistic regression modelling found pet ownership to be negatively associated with depression in the study population (controlling for gender, regular use of drugs, and time since youth left home), with the odds of being depressed three times greater for youths who did not own pets. While pet ownership among street-involved youth has many liabilities, includ- ing impairing youths’ ability to access shelter, services, and housing and employment opportunities, companion animals may offer both physical and psychosocial benefits that youth have difficult attaining. This finding highlights the importance of increased awareness among youth service providers of the potential impacts of pet ownership for street-involved youth.