101 research outputs found

    Expression of the Stress Response Oncoprotein LEDGF/p75 in Human Cancer: A Study of 21 Tumor Types

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    Oxidative stress-modulated signaling pathways have been implicated in carcinogenesis and therapy resistance. The lens epithelium derived growth factor p75 (LEDGF/p75) is a transcription co-activator that promotes resistance to stress-induced cell death. This protein has been implicated in inflammatory and autoimmune conditions, HIV-AIDS, and cancer. Although LEDGF/p75 is emerging as a stress survival oncoprotein, there is scarce information on its expression in human tumors. The present study was performed to evaluate its expression in a comprehensive panel of human cancers. Transcript expression was examined in the Oncomine cancer gene microarray database and in a TissueScan Cancer Survey Panel quantitative polymerase chain reaction (Q-PCR) array. Protein expression was assessed by immunohistochemistry (IHC) in cancer tissue microarrays (TMAs) containing 1735 tissues representing single or replicate cores from 1220 individual cases (985 tumor and 235 normal tissues). A total of 21 major cancer types were analyzed. Analysis of LEDGF/p75 transcript expression in Oncomine datasets revealed significant upregulation (tumor vs. normal) in 15 out of 17 tumor types. The TissueScan Cancer Q-PCR array revealed significantly elevated LEDGF/p75 transcript expression in prostate, colon, thyroid, and breast cancers. IHC analysis of TMAs revealed significant increased levels of LEDGF/p75 protein in prostate, colon, thyroid, liver and uterine tumors, relative to corresponding normal tissues. Elevated transcript or protein expression of LEDGF/p75 was observed in several tumor types. These results further establish LEDGF/p75 as a cancer-related protein, and provide a rationale for ongoing studies aimed at understanding the clinical significance of its expression in specific human cancers

    Transient and sustained incentive effects on electrophysiological indices of cognitive control in younger and older adults

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    Preparing for upcoming events, separating task-relevant from task-irrelevant information and efficiently responding to stimuli all require cognitive control. The adaptive recruitment of cognitive control depends on activity in the dopaminergic reward system as well as the frontoparietal control network. In healthy aging, dopaminergic neuromodulation is reduced, resulting in altered incentive-based recruitment of control mechanisms. In the present study, younger adults (18–28 years) and healthy older adults (66–89 years) completed an incentivized flanker task that included gain, loss, and neutral trials. Event-related potentials (ERPs) were recorded at the time of incentive cue and target presentation. We examined the contingent negative variation (CNV), implicated in stimulus anticipation and response preparation, as well as the P3, which is involved in the evaluation of visual stimuli. Both younger and older adults showed transient incentive-based modulation of CNV. Critically, cue-locked and target-locked P3s were influenced by transient and sustained effects of incentives in younger adults, while such modulation was limited to a sustained effect of gain incentives on cue-P3 in older adults. Overall, these findings are in line with an age-related reduction in the flexible recruitment of preparatory and target-related cognitive control processes in the presence of motivational incentives

    Diversity and dynamics of rare and of resident bacterial populations in coastal sands

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    Coastal sands filter and accumulate organic and inorganic materials from the terrestrial and marine environment, and thus provide a high diversity of microbial niches. Sands of temperate climate zones represent a temporally and spatially highly dynamic marine environment characterized by strong physical mixing and seasonal variation. Yet little is known about the temporal fluctuations of resident and rare members of bacterial communities in this environment. By combining community fingerprinting via pyrosequencing of ribosomal genes with the characterization of multiple environmental parameters, we disentangled the effects of seasonality, environmental heterogeneity, sediment depth and biogeochemical gradients on the fluctuations of bacterial communities of marine sands. Surprisingly, only 3–5% of all bacterial types of a given depth zone were present at all times, but 50–80% of them belonged to the most abundant types in the data set. About 60–70% of the bacterial types consisted of tag sequences occurring only once over a period of 1 year. Most members of the rare biosphere did not become abundant at any time or at any sediment depth, but varied significantly with environmental parameters associated with nutritional stress. Despite the large proportion and turnover of rare organisms, the overall community patterns were driven by deterministic relationships associated with seasonal fluctuations in key biogeochemical parameters related to primary productivity. The maintenance of major biogeochemical functions throughout the observation period suggests that the small proportion of resident bacterial types in sands perform the key biogeochemical processes, with minimal effects from the rare fraction of the communities

    Differential Encoding of Factors Influencing Predicted Reward Value in Monkey Rostral Anterior Cingulate Cortex

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    Background: The value of a predicted reward can be estimated based on the conjunction of both the intrinsic reward value and the length of time to obtain it. The question we addressed is how the two aspects, reward size and proximity to reward, influence the responses of neurons in rostral anterior cingulate cortex (rACC), a brain region thought to play an important role in reward processing. Methods and Findings: We recorded from single neurons while two monkeys performed a multi-trial reward schedule task. The monkeys performed 1–4 sequential color discrimination trials to obtain a reward of 1–3 liquid drops. There were two task conditions, a valid cue condition, where the number of trials and reward amount were associated with visual cues, and a random cue condition, where the cue was picked from the cue set at random. In the valid cue condition, the neuronal firing is strongly modulated by the predicted reward proximity during the trials. Information about the predicted reward amount is almost absent at those times. In substantial subpopulations, the neuronal responses decreased or increased gradually through schedule progress to the predicted outcome. These two gradually modulating signals could be used to calculate the effect of time on the perception of reward value. In the random cue condition, little information about the reward proximity or reward amount is encoded during the course of the trial before reward delivery, but when the reward is actually delivered the responses reflect both the reward proximity and reward amount

    Roles of glial cells in synapse development

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    Brain function relies on communication among neurons via highly specialized contacts, the synapses, and synaptic dysfunction lies at the heart of age-, disease-, and injury-induced defects of the nervous system. For these reasons, the formation—and repair—of synaptic connections is a major focus of neuroscience research. In this review, I summarize recent evidence that synapse development is not a cell-autonomous process and that its distinct phases depend on assistance from the so-called glial cells. The results supporting this view concern synapses in the central nervous system as well as neuromuscular junctions and originate from experimental models ranging from cell cultures to living flies, worms, and mice. Peeking at the future, I will highlight recent technical advances that are likely to revolutionize our views on synapse–glia interactions in the developing, adult and diseased brain

    Cancer Biomarker Discovery: The Entropic Hallmark

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    Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

    The Use of Genus-Specific Amplicon Pyrosequencing to Assess Phytophthora Species Diversity Using eDNA from Soil and Water in Northern Spain

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    [EN] Phytophthora is one of the most important and aggressive plant pathogenic genera in agriculture and forestry. Early detection and identification of its pathways of infection and spread are of high importance to minimize the threat they pose to natural ecosystems. eDNA was extracted from soil and water from forests and plantations in the north of Spain. Phytophthora-specific primers were adapted for use in high-throughput Sequencing (HTS). Primers were tested in a control reaction containing eight Phytophthora species and applied to water and soil eDNA samples from northern Spain. Different score coverage threshold values were tested for optimal Phytophthora species separation in a custom-curated database and in the control reaction. Clustering at 99% was the optimal criteria to separate most of the Phytophthora species. Multiple Molecular Operational Taxonomic Units (MOTUs) corresponding to 36 distinct Phytophthora species were amplified in the environmental samples. Pyrosequencing of amplicons from soil samples revealed low Phytophthora diversity (13 species) in comparison with the 35 species detected in water samples. Thirteen of the MOTUs detected in rivers and streams showed no close match to sequences in international sequence databases, revealing that eDNA pyrosequencing is a useful strategy to assess Phytophthora species diversity in natural ecosystems.This project has been supported by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (EUPHRESCO-CEP: "Current and Emerging Phytophthoras: Research Supporting Risk Assessment And Risk Management"). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Català, S.; Pérez Sierra, AM.; Abad Campos, P. (2015). The Use of Genus-Specific Amplicon Pyrosequencing to Assess Phytophthora Species Diversity Using eDNA from Soil and Water in Northern Spain. PLoS ONE. 10(3):1-14. doi:10.1371/journal.pone.0119311S114103REICHARD, S. H., & WHITE, P. (2001). Horticulture as a Pathway of Invasive Plant Introductions in the United States. BioScience, 51(2), 103. doi:10.1641/0006-3568(2001)051[0103:haapoi]2.0.co;2Brasier, C. M. (2008). The biosecurity threat to the UK and global environment from international trade in plants. Plant Pathology, 57(5), 792-808. doi:10.1111/j.1365-3059.2008.01886.xTABERLET, P., COISSAC, E., HAJIBABAEI, M., & RIESEBERG, L. H. (2012). Environmental DNA. Molecular Ecology, 21(8), 1789-1793. doi:10.1111/j.1365-294x.2012.05542.xSogin, M. L., Morrison, H. G., Huber, J. A., Welch, D. M., Huse, S. M., Neal, P. R., … Herndl, G. J. (2006). Microbial diversity in the deep sea and the underexplored «rare biosphere». Proceedings of the National Academy of Sciences, 103(32), 12115-12120. doi:10.1073/pnas.0605127103Roesch, L. F. W., Fulthorpe, R. R., Riva, A., Casella, G., Hadwin, A. K. M., Kent, A. D., … Triplett, E. W. (2007). Pyrosequencing enumerates and contrasts soil microbial diversity. The ISME Journal, 1(4), 283-290. doi:10.1038/ismej.2007.53Acosta-Martínez, V., Dowd, S., Sun, Y., & Allen, V. (2008). Tag-encoded pyrosequencing analysis of bacterial diversity in a single soil type as affected by management and land use. Soil Biology and Biochemistry, 40(11), 2762-2770. doi:10.1016/j.soilbio.2008.07.022Jumpponen, A., & Jones, K. L. (2009). Massively parallel 454 sequencing indicates hyperdiverse fungal communities in temperateQuercus macrocarpaphyllosphere. New Phytologist, 184(2), 438-448. doi:10.1111/j.1469-8137.2009.02990.xNilsson, R. H., Ryberg, M., Abarenkov, K., Sjökvist, E., & Kristiansson, E. (2009). The ITS region as a target for characterization of fungal communities using emerging sequencing technologies. FEMS Microbiology Letters, 296(1), 97-101. doi:10.1111/j.1574-6968.2009.01618.xCoince, A., Caël, O., Bach, C., Lengellé, J., Cruaud, C., Gavory, F., … Buée, M. (2013). Below-ground fine-scale distribution and soil versus fine root detection of fungal and soil oomycete communities in a French beech forest. Fungal Ecology, 6(3), 223-235. doi:10.1016/j.funeco.2013.01.002Vannini, A., Bruni, N., Tomassini, A., Franceschini, S., & Vettraino, A. M. (2013). Pyrosequencing of environmental soil samples reveals biodiversity of thePhytophthoraresident community in chestnut forests. FEMS Microbiology Ecology, 85(3), 433-442. doi:10.1111/1574-6941.12132Jerde, C. L., Mahon, A. R., Chadderton, W. L., & Lodge, D. M. (2011). «Sight-unseen» detection of rare aquatic species using environmental DNA. Conservation Letters, 4(2), 150-157. doi:10.1111/j.1755-263x.2010.00158.xMonchy, S., Sanciu, G., Jobard, M., Rasconi, S., Gerphagnon, M., Chabé, M., … Sime-Ngando, T. (2011). Exploring and quantifying fungal diversity in freshwater lake ecosystems using rDNA cloning/sequencing and SSU tag pyrosequencing. Environmental Microbiology, 13(6), 1433-1453. doi:10.1111/j.1462-2920.2011.02444.xJobard, M., Rasconi, S., Solinhac, L., Cauchie, H.-M., & Sime-Ngando, T. (2012). Molecular and morphological diversity of fungi and the associated functions in three European nearby lakes. Environmental Microbiology, 14(9), 2480-2494. doi:10.1111/j.1462-2920.2012.02771.xLivermore, J. A., & Mattes, T. E. (2013). Phylogenetic detection of novel Cryptomycota in an Iowa (United States) aquifer and from previously collected marine and freshwater targeted high-throughput sequencing sets. Environmental Microbiology, 15(8), 2333-2341. doi:10.1111/1462-2920.12106NAKAYAMA, J., JIANG, J., WATANABE, K., CHEN, K., NINXIN, H., MATSUDA, K., … LEE, Y.-K. (2013). Up to Species-level Community Analysis of Human Gut Microbiota by 16S rRNA Amplicon Pyrosequencing. Bioscience of Microbiota, Food and Health, 32(2), 69-76. doi:10.12938/bmfh.32.69CREER, S., & SINNIGER, F. (2012). Cosmopolitanism of microbial eukaryotes in the global deep seas. Molecular Ecology, 21(5), 1033-1035. doi:10.1111/j.1365-294x.2012.05437.xDavey, M. L., Heegaard, E., Halvorsen, R., Kauserud, H., & Ohlson, M. (2012). Amplicon-pyrosequencing-based detection of compositional shifts in bryophyte-associated fungal communities along an elevation gradient. Molecular Ecology, 22(2), 368-383. doi:10.1111/mec.12122Weber, C. F., Vilgalys, R., & Kuske, C. R. (2013). Changes in Fungal Community Composition in Response to Elevated Atmospheric CO2 and Nitrogen Fertilization Varies with Soil Horizon. Frontiers in Microbiology, 4. doi:10.3389/fmicb.2013.00078Bergmark, L., Poulsen, P. H. B., Al-Soud, W. A., Norman, A., Hansen, L. H., & Sørensen, S. J. (2012). Assessment of the specificity of Burkholderia and Pseudomonas qPCR assays for detection of these genera in soil using 454 pyrosequencing. FEMS Microbiology Letters, 333(1), 77-84. doi:10.1111/j.1574-6968.2012.02601.xLi, L., Abu Al-Soud, W., Bergmark, L., Riber, L., Hansen, L. H., Magid, J., & Sørensen, S. J. (2013). Investigating the Diversity of Pseudomonas spp. in Soil Using Culture Dependent and Independent Techniques. Current Microbiology, 67(4), 423-430. doi:10.1007/s00284-013-0382-xSCHENA, L., HUGHES, K. J. D., & COOKE, D. E. L. (2006). Detection and quantification ofPhytophthora ramorum,P. kernoviae,P. citricolaandP. quercinain symptomatic leaves by multiplex real-time PCR. Molecular Plant Pathology, 7(5), 365-379. doi:10.1111/j.1364-3703.2006.00345.xTooley, P. W., Martin, F. N., Carras, M. M., & Frederick, R. D. (2006). Real-Time Fluorescent Polymerase Chain Reaction Detection ofPhytophthora ramorumandPhytophthora pseudosyringaeUsing Mitochondrial Gene Regions. Phytopathology, 96(4), 336-345. doi:10.1094/phyto-96-0336Pavón, C. F., Babadoost, M., & Lambert, K. N. (2008). Quantification of Phytophthora capsici Oospores in Soil by Sieving-Centrifugation and Real-Time Polymerase Chain Reaction. Plant Disease, 92(1), 143-149. doi:10.1094/pdis-92-1-0143Than, D. J., Hughes, K. J. D., Boonhan, N., Tomlinson, J. A., Woodhall, J. W., & Bellgard, S. E. (2013). A TaqMan real-time PCR assay for the detection ofPhytophthora‘taxon Agathis’ in soil, pathogen of Kauri in New Zealand. Forest Pathology, 43(4), 324-330. doi:10.1111/efp.12034Chen, W., Djama, Z. R., Coffey, M. D., Martin, F. N., Bilodeau, G. J., Radmer, L., … Lévesque, C. A. (2013). Membrane-Based Oligonucleotide Array Developed from Multiple Markers for the Detection of Many Phytophthora Species. Phytopathology, 103(1), 43-54. doi:10.1094/phyto-04-12-0092-rScibetta, S., Schena, L., Chimento, A., Cacciola, S. O., & Cooke, D. E. L. (2012). A molecular method to assess Phytophthora diversity in environmental samples. Journal of Microbiological Methods, 88(3), 356-368. doi:10.1016/j.mimet.2011.12.012Català S, Pérez-Sierra A, Berbegal M, Abad-Campos P. First approach into the knowledge of the Phytophthora species diversity in Mediterranean holm oak forests based on 454 parallel amplicon pyrosequencing of soil samples. Phytophthora in Forest and Natural Ecosystems 6th International IUFRO Working Party 7.02.09 Meeting, Córdoba, Spain, pp 34; 2012.Català S, Pérez-Sierra A, Beltrán A, Abad-Campos P. Next Generation Sequencing shows Phytophthora species diversity in soil samples of Macaronesian laurel forests from the Canary Islands. Phytophthora in Forest and Natural Ecosystems 6th International IUFRO Working Party 7.02.09 Meeting, Córdoba, Spain, pp. 86; 2012.Cooke, D. E. L., Drenth, A., Duncan, J. M., Wagels, G., & Brasier, C. M. (2000). A Molecular Phylogeny of Phytophthora and Related Oomycetes. Fungal Genetics and Biology, 30(1), 17-32. doi:10.1006/fgbi.2000.1202Andrews S. FastQC: a quality control tool for high throughput sequence data. Available: http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/Chou, H.-H., & Holmes, M. H. (2001). DNA sequence quality trimming and vector removal. Bioinformatics, 17(12), 1093-1104. doi:10.1093/bioinformatics/17.12.1093Altschul, S. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389-3402. doi:10.1093/nar/25.17.3389Edgar, R. C. (2004). MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32(5), 1792-1797. doi:10.1093/nar/gkh340Gouy, M., Guindon, S., & Gascuel, O. (2009). SeaView Version 4: A Multiplatform Graphical User Interface for Sequence Alignment and Phylogenetic Tree Building. Molecular Biology and Evolution, 27(2), 221-224. doi:10.1093/molbev/msp259Park, J., Park, B., Veeraraghavan, N., Jung, K., Lee, Y.-H., Blair, J. E., … Kang, S. (2008). Phytophthora Database: A Forensic Database Supporting the Identification and Monitoring of Phytophthora. Plant Disease, 92(6), 966-972. doi:10.1094/pdis-92-6-0966Vettraino, A. M., Bonants, P., Tomassini, A., Bruni, N., & Vannini, A. (2012). Pyrosequencing as a tool for the detection ofPhytophthoraspecies: error rate and risk of false Molecular Operational Taxonomic Units. Letters in Applied Microbiology, 55(5), 390-396. doi:10.1111/j.1472-765x.2012.03310.xJung, T., & Burgess, T. I. (2009). Re-evaluation of Phytophthora citricola isolates from multiple woody hosts in Europe and North America reveals a new species, Phytophthora plurivora sp. nov. Persoonia - Molecular Phylogeny and Evolution of Fungi, 22(1), 95-110. doi:10.3767/003158509x442612Deagle, B. E., Eveson, J. P., & Jarman, S. N. (2006). Quantification of damage in DNA recovered from highly degraded samples – a case study on DNA in faeces. Frontiers in Zoology, 3(1). doi:10.1186/1742-9994-3-11Dejean, T., Valentini, A., Duparc, A., Pellier-Cuit, S., Pompanon, F., Taberlet, P., & Miaud, C. (2011). Persistence of Environmental DNA in Freshwater Ecosystems. PLoS ONE, 6(8), e23398. doi:10.1371/journal.pone.0023398Guha Roy S, Grunwald NJ. The plant destroyer genus Phytophthora in the 21st century. In book: Review of Plant Pathology, Edition: Volume 6, Publisher: Scientific Publishers (India), Jodhpur, Editors: B.N.Chakraborty, B.B.L.Thakore, pp. In press; 2014.Brasier, C. M., Cooke, D. E. L., Duncan, J. M., & Hansen, E. M. (2003). Multiple new phenotypic taxa from trees and riparian ecosystems in Phytophthora gonapodyides-P. megasperma ITS Clade 6, which tend to be high-temperature tolerant and either inbreeding or sterile. Mycological Research, 107(3), 277-290. doi:10.1017/s095375620300738xHüberli, D., Hardy, G. E. S. J., White, D., Williams, N., & Burgess, T. I. (2013). Fishing for Phytophthora from Western Australia’s waterways: a distribution and diversity survey. Australasian Plant Pathology, 42(3), 251-260. doi:10.1007/s13313-012-0195-6Jung, T., Stukely, M. J. C., Hardy, G. E. S. J., White, D., Paap, T., Dunstan, W. A., & Burgess, T. I. (2011). Multiple new Phytophthora species from ITS Clade 6 associated with natural ecosystems in Australia: evolutionary and ecological implications. Persoonia - Molecular Phylogeny and Evolution of Fungi, 26(1), 13-39. doi:10.3767/003158511x557577Brasier, C. M., Sanchez-Hernandez, E., & Kirk, S. A. (2003). Phytophthora inundata sp. nov., a part heterothallic pathogen of trees and shrubs in wet or flooded soils. Mycological Research, 107(4), 477-484. doi:10.1017/s0953756203007548Hansen, E. M., Reeser, P. W., & Sutton, W. (2012). PhytophthoraBeyond Agriculture. Annual Review of Phytopathology, 50(1), 359-378. doi:10.1146/annurev-phyto-081211-172946Reeser, P. W., Sutton, W., Hansen, E. M., Remigi, P., & Adams, G. C. (2011). Phytophthora species in forest streams in Oregon and Alaska. Mycologia, 103(1), 22-35. doi:10.3852/10-013Nechwatal, J., Bakonyi, J., Cacciola, S. O., Cooke, D. E. L., Jung, T., Nagy, Z. Á., … Brasier, C. M. (2012). The morphology, behaviour and molecular phylogeny ofPhytophthorataxon Salixsoil and its redesignation asPhytophthora lacustrissp. nov. Plant Pathology, 62(2), 355-369. doi:10.1111/j.1365-3059.2012.02638.xHuai, W. -x., Tian, G., Hansen, E. M., Zhao, W. -x., Goheen, E. M., Grünwald, N. J., & Cheng, C. (2013). Identification ofPhytophthoraspecies baited and isolated from forest soil and streams in northwestern Yunnan province, China. Forest Pathology, 43(2), 87-103. doi:10.1111/efp.12015Oh, E., Gryzenhout, M., Wingfield, B. D., Wingfield, M. J., & Burgess, T. I. (2013). Surveys of soil and water reveal a goldmine of Phytophthora diversity in South African natural ecosystems. IMA Fungus, 4(1), 123-131. doi:10.5598/imafungus.2013.04.01.1
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