Geert Trooskens

Transcriptional reprogramming by root knot and migratory nematode infection in rice

Rice is one of the most important staple crops worldwide, but its yield is compromised by different pathogens, including plant-parasitic nematodes. In this study we have characterized specific and general responses of rice (Oryza sativa) roots challenged with two endoparasitic nematodes with very different modes of action. Local transcriptional changes in rice roots upon root knot (Meloidogyne graminicola) and root rot nematode (RRN, Hirschmanniella oryzae) infection were studied at two time points (3 and 7 d after infection, dai), using mRNA-seq. Our results confirm that root knot nematodes (RKNs), which feed as sedentary endoparasites, stimulate metabolic pathways in the root, and enhance nutrient transport towards the induced root gall. The migratory RRNs, on the other hand, induce programmed cell death and oxidative stress, and obstruct the normal metabolic activity of the root. While RRN infection causes up-regulation of biotic stress-related genes early in the infection, the sedentary RKNs suppress the local defense pathways (e.g. salicylic acid and ethylene pathways). Interestingly, hormone pathways mainly involved in plant development were strongly induced (gibberellin) or repressed (cytokinin) at 3 dai. These results uncover previously unrecognized nematode-induced expression profiles related to their specific infection strategy.

Transcriptional analysis through RNA sequencing of giant cells induced by Meloidogyne graminicola in rice roots

One of the reasons for the progressive yield decline observed in aerobic rice production is the rapid build-up of populations of the rice root knot nematode Meloidogyne graminicola. These nematodes induce specialized feeding cells inside root tissue, called giant cells. By injecting effectors in and sipping metabolites out of these cells, they reprogramme normal cell development and deprive the plant of its nutrients. In this research we have studied the transcriptome of giant cells in rice, after isolation of these cells by laser-capture microdissection. The expression profiles revealed a general induction of primary metabolism inside the giant cells. Although the roots were shielded from light induction, we detected a remarkable induction of genes involved in chloroplast biogenesis and tetrapyrrole synthesis. The presence of chloroplast-like structures inside these dark-grown cells was confirmed by confocal microscopy. On the other hand, genes involved in secondary metabolism and more specifically, the majority of defence-related genes were strongly suppressed in the giant cells. In addition, significant induction of transcripts involved in epigenetic processes was detected inside these cells 7 days after infection.

Detection of High-grade Prostate Cancer Using a Urinary Molecular Biomarker-Based Risk Score.

BACKGROUND To reduce overdiagnosis and overtreatment, a test is urgently needed to detect clinically significant prostate cancer (PCa). OBJECTIVE To develop a multimodal model, incorporating previously identified messenger RNA (mRNA) biomarkers and traditional risk factors that could be used to identify patients with high-grade PCa (Gleason score ≥7) on prostate biopsy. DESIGN, SETTING, AND PARTICIPANTS In two prospective multicenter studies, urine was collected for mRNA profiling after digital rectal examination (DRE) and prior to prostate biopsy. The multimodal risk score was developed on a first cohort (n=519) and subsequently validated clinically in an independent cohort (n=386). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The mRNA levels were measured using reverse transcription quantitative polymerase chain reaction. Logistic regression was used to model patient risk and combine risk factors. Models were compared using the area under the curve (AUC) of the receiver operating characteristic, and clinical utility was evaluated with a decision curve analysis (DCA). RESULTS AND LIMITATIONS HOXC6 and DLX1 mRNA levels were shown to be good predictors for the detection of high-grade PCa. The multimodal approach reached an overall AUC of 0.90 (95% confidence interval [CI], 0.85-0.95) in the validation cohort (AUC 0.86 in the training cohort), with the mRNA signature, prostate-specific antigen (PSA) density, and previous cancer-negative prostate biopsies as the strongest, most significant components, in addition to nonsignificant model contributions of PSA, age, and family history. For another model, which included DRE as an additional risk factor, an AUC of 0.86 (95% CI, 0.80-0.92) was obtained (AUC 0.90 in the training cohort). Both models were successfully validated, with no significant change in AUC in the validation cohort, and DCA indicated a strong net benefit and the best reduction in unnecessary biopsies compared with other clinical decision-making tools, such as the Prostate Cancer Prevention Trial risk calculator and the PCA3 assay. CONCLUSIONS The risk score based on the mRNA liquid biopsy assay combined with traditional clinical risk factors identified men at risk of harboring high-grade PCa and resulted in a better patient risk stratification compared with current methods in clinical practice. Therefore, the risk score could reduce the number of unnecessary prostate biopsies. PATIENT SUMMARY This study evaluated a novel urine-based assay that could be used as a noninvasive diagnostic aid for high-grade prostate cancer (PCa). When results of this assay are combined with traditional clinical risk factors, risk stratification for high-grade PCa and biopsy decision making are improved.

Combining in silico prediction and ribosome profiling in a genome-wide search for novel putatively coding sORFs

BackgroundIt was long assumed that proteins are at least 100 amino acids (AAs) long. Moreover, the detection of short translation products (e.g. coded from small Open Reading Frames, sORFs) is very difficult as the short length makes it hard to distinguish true coding ORFs from ORFs occurring by chance. Nevertheless, over the past few years many such non-canonical genes (with ORFs < 100 AAs) have been discovered in different organisms like Arabidopsis thaliana, Saccharomyces cerevisiae, and Drosophila melanogaster. Thanks to advances in sequencing, bioinformatics and computing power, it is now possible to scan the genome in unprecedented scrutiny, for example in a search of this type of small ORFs.ResultsUsing bioinformatics methods, we performed a systematic search for putatively functional sORFs in the Mus musculus genome. A genome-wide scan detected all sORFs which were subsequently analyzed for their coding potential, based on evolutionary conservation at the AA level, and ranked using a Support Vector Machine (SVM) learning model. The ranked sORFs are finally overlapped with ribosome profiling data, hinting to sORF translation. All candidates are visually inspected using an in-house developed genome browser. In this way dozens of highly conserved sORFs, targeted by ribosomes were identified in the mouse genome, putatively encoding micropeptides.ConclusionOur combined genome-wide approach leads to the prediction of a comprehensive but manageable set of putatively coding sORFs, a very important first step towards the identification of a new class of bioactive peptides, called micropeptides.

Phylogenetic trees: visualizing, customizing and detecting incongruence

SUMMARY TreeIllustrator is a user-friendly application to visualize and customize phylogenetic trees. It has a broad range of functions and capabilities, such as dragging of nodes, different tree shapes, zooming and searching capabilities, and support for large trees. It acts as a solution that integrates the specificity of visualizing phylogenetic trees and the customization options of a drawing program. It also contains a simple and effective method that compares a custom tree with the Tree of Life, by detecting incongruence.

Food-derived opioid peptides inhibit cysteine uptake with redox and epigenetic consequences☆

Dietary interventions like gluten-free and casein-free diets have been reported to improve intestinal, autoimmune and neurological symptoms in patients with a variety of conditions; however, the underlying mechanism of benefit for such diets remains unclear. Epigenetic programming, including CpG methylation and histone modifications, occurring during early postnatal development can influence the risk of disease in later life, and such programming may be modulated by nutritional factors such as milk and wheat, especially during the transition from a solely milk-based diet to one that includes other forms of nutrition. The hydrolytic digestion of casein (a major milk protein) and gliadin (a wheat-derived protein) releases peptides with opioid activity, and in the present study, we demonstrate that these food-derived proline-rich opioid peptides modulate cysteine uptake in cultured human neuronal and gastrointestinal (GI) epithelial cells via activation of opioid receptors. Decreases in cysteine uptake were associated with changes in the intracellular antioxidant glutathione and the methyl donor S-adenosylmethionine. Bovine and human casein-derived opioid peptides increased genome-wide DNA methylation in the transcription start site region with a potency order similar to their inhibition of cysteine uptake. Altered expression of genes involved in redox and methylation homeostasis was also observed. These results illustrate the potential of milk- and wheat-derived peptides to exert antioxidant and epigenetic changes that may be particularly important during the postnatal transition from placental to GI nutrition. Differences between peptides derived from human and bovine milk may contribute to developmental differences between breastfed and formula-fed infants. Restricted antioxidant capacity, caused by wheat- and milk-derived opioid peptides, may predispose susceptible individuals to inflammation and systemic oxidation, partly explaining the benefits of gluten-free or casein-free diets.

Quality evaluation of methyl binding domain based kits for enrichment DNA-methylation sequencing.

DNA-methylation is an important epigenetic feature in health and disease. Methylated sequence capturing by Methyl Binding Domain (MBD) based enrichment followed by second-generation sequencing provides the best combination of sensitivity and cost-efficiency for genome-wide DNA-methylation profiling. However, existing implementations are numerous, and quality control and optimization require expensive external validation. Therefore, this study has two aims: 1) to identify a best performing kit for MBD-based enrichment using independent validation data, and 2) to evaluate whether quality evaluation can also be performed solely based on the characteristics of the generated sequences. Five commercially available kits for MBD enrichment were combined with Illumina GAIIx sequencing for three cell lines (HCT15, DU145, PC3). Reduced representation bisulfite sequencing data (all three cell lines) and publicly available Illumina Infinium BeadChip data (DU145 and PC3) were used for benchmarking. Consistent large-scale differences in yield, sensitivity and specificity between the different kits could be identified, with Diagenodes MethylCap kit as overall best performing kit under the tested conditions. This kit could also be identified with the Fragment CpG-plot, which summarizes the CpG content of the captured fragments, implying that the latter can be used as a tool to monitor data quality. In conclusion, there are major quality differences between kits for MBD-based capturing of methylated DNA, with the MethylCap kit performing best under the used settings. The Fragment CpG-plot is able to monitor data quality based on inherent sequence data characteristics, and is therefore a cost-efficient tool for experimental optimization, but also to monitor quality throughout routine applications.

Next-generation technologies and data analytical approaches for epigenomics.

Epigenetics refers to the collection of heritable features that modulate the genome–environment interaction without being encoded in the actual DNA sequence. While being mitotically and sometimes even meiotically transmitted, epigenetic traits often demonstrate extensive flexibility. This allows cells to acquire diverse gene expression patterns during differentiation, but also to adapt to a changing environment. However, epigenetic alterations are not always beneficial to the organism, as they are, for example, frequently identified in human diseases such as cancer. Accurate and cost‐efficient genome‐scale profiling of epigenetic features is thus of major importance to pinpoint these “epimutations,” for example, to monitor the epigenetic impact of environmental exposure. Over the last decade, the field of epigenetics has been revolutionized by several innovative “epigenomics” technologies exactly addressing this need. In this review, we discuss and compare widely used next‐generation methods to assess DNA methylation and hydroxymethylation, noncoding RNA expression, histone modifications, and nucleosome positioning. Although recent methods are typically based on “second‐generation” sequencing, we also pay attention to still commonly used array‐ and PCR‐based methods, and look forward to the additional advantages of single‐molecule sequencing. As the current bottleneck in epigenomics research is the analysis rather than generation of data, the basic difficulties and problem‐solving strategies regarding data preprocessing and statistical analysis are introduced for the different technologies. Finally, we also consider the complications associated with epigenomic studies of species with yet unsequenced genomes and possible solutions. Environ. Mol. Mutagen. 55:155–170, 2014.

Interaction of the tobacco lectin with histone proteins

The tobacco (Nicotiana tabacum) agglutinin or Nictaba is a member of a novel class of plant lectins residing in the nucleus and the cytoplasm of tobacco cells. Since tobacco lectin expression is only observed after the plant has been subjected to stress situations such as jasmonate treatment or insect attack, Nictaba is believed to act as a signaling protein involved in the stress physiology of the plant. In this paper, a nuclear proteomics approach was followed to identify the binding partners for Nictaba in the nucleus and the cytoplasm of tobacco cv Xanthi cells. Using lectin affinity chromatography and pull-down assays, it was shown that Nictaba interacts primarily with histone proteins. Binding of Nictaba with histone H2B was confirmed in vitro using affinity chromatography of purified calf thymus histone proteins on a Nictaba column. Elution of Nictaba-interacting histone proteins was achieved with 1 m N-acetylglucosamine (GlcNAc). Moreover, mass spectrometry analyses indicated that the Nictaba-interacting histone proteins are modified by O-GlcNAc. Since the lectin-histone interaction was shown to be carbohydrate dependent, it is proposed that Nictaba might fulfill a signaling role in response to stress by interacting with O-GlcNAcylated proteins in the plant cell nucleus.

Methylation-specific digital karyotyping of HPV16E6E7-expressing human keratinocytes identifies novel methylation events in cervical carcinogenesis.

Transformation of epithelial cells by high‐risk human papillomavirus (hrHPV) types can lead to anogenital carcinomas, particularly cervical cancer, and oropharyngeal cancers. This process is associated with DNA methylation alterations, often affecting tumour suppressor gene expression. This study aimed to comprehensively unravel genome‐wide DNA methylation events linked to a transforming hrHPV‐infection, which is driven by deregulated expression of the viral oncogenes E6 and E7 in dividing cells. Primary human keratinocytes transduced with HPV16E6E7 and their untransduced counterparts were subjected to methylation‐specific digital karyotyping (MSDK) to screen for genome‐wide DNA‐methylation changes at different stages of HPV‐induced transformation. Integration of the obtained methylation profiles with genome‐wide gene expression patterns of cervical carcinomas identified 34 genes with increased methylation in HPV‐transformed cells and reduced expression in cervical carcinomas. For 12 genes (CLIC3, CREB3L1, FAM19A4, LFNG, LHX1, MRC2, NKX2‐8, NPTX‐1, PHACTR3, PRDM14, SOST and TNFSF13) specific methylation in HPV‐containing cell lines was confirmed by semi‐quantitative methylation‐specific PCR. Subsequent analysis of FAM19A4, LHX1, NKX2‐8, NPTX‐1, PHACTR3 and PRDM14 in cervical tissue specimens showed increasing methylation levels for all genes with disease progression. All six genes were frequently methylated in cervical carcinomas, with highest frequencies (up to 100%) seen for FAM19A4, PHACTR3 and PRDM14. Analysis of hrHPV‐positive cervical scrapes revealed significantly increased methylation levels of the latter three genes in women with high‐grade cervical disease compared to controls. In conclusion, MSDK analysis of HPV16‐transduced keratinocytes at different stages of HPV‐induced transformation resulted in the identification of novel DNA methylation events, involving FAM19A4, LHX1, NKX2‐8, PHACTR3 and PRDM14 genes in cervical carcinogenesis. These genes may provide promising triage markers to assess the presence of (pre)cancerous cervical lesions in hrHPV‐positive women. Copyright