The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications.

UNITE (https://unite.ut.ee/) is a web-based database and sequence management environment for the molecular identification of fungi. It targets the formal fungal barcode-the nuclear ribosomal internal transcribed spacer (ITS) region-and offers all ∼1 000 000 public fungal ITS sequences for reference. These are clustered into ∼459 000 species hypotheses and assigned digital object identifiers (DOIs) to promote unambiguous reference across studies. In-house and web-based third-party sequence curation and annotation have resulted in more than 275 000 improvements to the data over the past 15 years. UNITE serves as a data provider for a range of metabarcoding software pipelines and regularly exchanges data with all major fungal sequence databases and other community resources. Recent improvements include redesigned handling of unclassifiable species hypotheses, integration with the taxonomic backbone of the Global Biodiversity Information Facility, and support for an unlimited number of parallel taxonomic classification systems.

Platelets harbor prostate cancer biomarkers and the ability to predict therapeutic response to abiraterone in castration resistant patients.

BACKGROUND: Novel therapies for castration resistant prostate cancer (CRPC) have been introduced in the clinic with possibilities for individualized treatment plans. Best practice of those expensive drugs requires predictive biomarker monitoring. This study used circulating biomarker analysis to follow cancer-derived transcripts implicated in therapy resistance. METHOD: The isolated platelet population of blood samples and digital-PCR were used to identify selected biomarker transcripts in patients with CRPC prior chemo- or androgen synthesis inhibiting therapy. RESULTS: Fifty patients received either docetaxel (n = 24) or abiraterone (n = 26) therapy, with therapy response rates of 54% and 48%, respectively. Transcripts for the PC-associated biomarkers kallikrein-related peptidase-2 and -3 (KLK2, KLK3), folate hydrolase 1 (FOLH1), and neuropeptide-Y (NPY) were uniquely present within the platelet fraction of cancer patients and not detected in healthy controls (n = 15). In the abiraterone treated cohort, the biomarkers provided information on therapy outcome, demonstrating an association between detectable biomarkers and short progression free survival (PFS) (FOLH1, P < 0.01; KLK3, P < 0.05; and NPY, P < 0.05). Patients with biomarker-negative platelets had the best outcome, while FOLH1 (P < 0.05) and NPY (P = 0.05) biomarkers provided independent predictive information in a multivariate analysis regarding PFS. KLK2 (P < 0.01), KLK3 (P < 0.001), and FOLH1 (P < 0.05) biomarkers were associated with short overall survival (OS). Combining three biomarkers in a panel (KLK3, FOLH1, and NPY) made it possible to separate long-term responders from short-term responders with 87% sensitivity and 82% specificity. CONCLUSION: Analyzing tumor-derived biomarkers in platelets of CRPC patients enabled prediction of the outcome after abiraterone therapy with higher accuracy than baseline serum PSA or PSA response.

Blood plasma reference material: a global resource for proteomic research.

There is an ever-increasing awareness and interest within the clinical research field, creating a large demand for blood fraction samples as well as other clinical samples. The translational research area is another field that is demanding for blood samples, used widely in proteomics, genomics, as well as metabolomics. Blood samples are globally the most common biological samples that are used in a broad variety of applications in life science. We hereby introduce a new reference blood plasma standard (heparin) that is aimed as a global resource for the proteomics community. We have developed these reference plasma standards by defining the Control group as those with C-reactive protein levels <3 mg/L and a Disease group with C-reactive protein ranges >30 mg/L. In these references we have used both newborn children 1-2 weeks, as well as youngsters 15-30 years, and middle aged 30-50 years, and elderly patients at the ages of 65+. In total, there were 80 patients in each group in the reference plasma pools. We provide data on the developments and characteristics of the reference blood plasma standards, as well as what is used by the team members at the respective laboratories. The standards have been evaluated by pilot sample processing in biobanking operations and are currently a resource that allows the Proteomic society to perform quantitative proteomic studies. By the use of high quality reference plasma samples, global initiatives, such as the Chromosome Human Proteome Project (C-HPP), will benefit as one scientific program when the entire human proteome is mapped and linked to human diseases. The plasma reference standards are a global resource and can be accessed upon request.

Impact of lactose starvation on the physiology of Lactobacillus casei GCRL163 in the presence or absence of tween 80.

The global proteomic response of the nonstarter lactic acid bacteria Lactobacillus casei strain GCRL163 under carbohydrate depletion was investigated to understand aspects of its survival following cessation of fermentation. The proteome of L. casei GCRL163 was analyzed quantitatively after growth in modified MRS (with and without Tween 80) with different levels of lactose (0% lactose, starvation; 0.2% lactose, growth limiting; 1% lactose, non-growth-limited control) using gel-free proteomics. Results revealed that carbohydrate starvation lead to suppression of lactose and galactose catabolic pathways as well as pathways for nucleotide and protein synthesis. Enzymes of the glycolysis/gluconeogenesis pathway, amino acid synthesis, and pyruvate and citrate metabolism become more abundant as well as other carbohydrate catabolic pathways, suggesting increased optimization of intermediary metabolism and scavenging. Tween 80 did not affect growth yield; however, proteins related to fatty acid biosynthesis were repressed in the presence of Tween 80. The data suggest that L. casei adeptly switches to a scavenging mode, using both citrate and Tween 80, and efficiently adjusts energetic requirements when carbohydrate starved and thus can sustain survival for weeks to months. Explaining the adaptation of L. casei during lactose starvation will assist efforts to maintain viability of L. casei and extend its utility as a beneficial dietary adjunct and fermentation processing aid.

Phenotypic and transcriptomic acclimation of the green microalga Raphidocelis subcapitata to high environmental levels of the herbicide diflufenican.

Herbicide pollution poses a worldwide threat to plants and freshwater ecosystems. However, the understanding of how organisms develop tolerance to these chemicals and the associated trade-off expenses are largely unknown. This study aims to investigate the physiological and transcriptional mechanisms underlying the acclimation of the green microalgal model species Raphidocelis subcapitata (Selenastraceae) towards the herbicide diflufenican, and the fitness costs associated with tolerance development. Algae were exposed for 12 weeks (corresponding to 100 generations) to diflufenican at the two environmental concentrations 10 and 310 ng/L. The monitoring of growth, pigment composition, and photosynthetic performance throughout the experiment revealed an initial dose-dependent stress phase (week 1) with an EC50 of 397 ng/L, followed by a time-dependent recovery phase during weeks 2 to 4. After week 4, R. subcapitata was acclimated to diflufenican exposure with a similar growth rate, content of carotenoids, and photosynthetic performance as the unexposed control algae. This acclimation state of the algae was explored in terms of tolerance acquisition, changes in the fatty acids composition, diflufenican removal rate, cell size, and changes in mRNA gene expression profile, revealing potential fitness costs associated with acclimation, such as up-regulation of genes related to cell division, structure, morphology, and reduction of cell size. Overall, this study demonstrates that R. subcapitata can quickly acclimate to environmental but toxic levels of diflufenican; however, the acclimation is associated with trade-off expenses that result in smaller cell size.

Investigation of the Listeria monocytogenes Scott A acid tolerance response and associated physiological and phenotypic features via whole proteome analysis.

The global proteomic responses of the foodborne pathogen Listeria monocytogenes strain Scott A, during active growth and transition to the stationary growth phase under progressively more acidic conditions, created by addition of lactic acid and HCl, were investigated using label-free liquid chromatography/tandem mass spectrometry. Approximately 56% of the Scott A proteome was quantitatively assessable, and the data provides insight into its acquired acid tolerance response (ATR) as well as the relation of the ATR to the growth phase transition. Alterations in protein abundance due to acid stress were focused in proteins belonging to the L. monocytogenes common genome, with few strain-dependent proteins involved. However, one of the two complete prophage genomes appeared to enter lysogeny. During progressive acidification, the growth rate and yield were reduced 55% and 98%, respectively, in comparison to nonacidified control cultures. The maintenance of the growth rate was determined to be connected to activation of cytoplasmic pH homeostatic mechanisms while cellular reproductive-related and cell component turnover proteins were markedly more abundant in acid stressed cultures. Cell biomass accumulation was impeded predominantly due to repression of phosphodonor-linked enzymes involved with sugar phosphotransfer, glycolysis, and cell wall polymer biosynthesis. Acidification caused a shift from heterofermentation to an oxidatively stressed state in which ATP appears to be generated mainly through the pyruvate dehydrogenase/pyruvate oxidase/phosphotransacetylase/acetate kinase and branched chain acid dehydrogenase pathways. Analysis of regulons indicated energy conservation occurs due to repression by the GTP/isoleucine sensor CodY and also the RelA mediated stringent response. Whole proteome analysis proved to be an effective way to highlight proteins involved with the acquisition of the ATR.

MudPIT analysis of alkaline tolerance by Listeria monocytogenes strains recovered as persistent food factory contaminants.

Alkaline solutions are used to clean food production environments but the role of alkaline resistance in persistent food factory contamination by Listeria monocytogenes is unknown. We used shotgun proteomics to characterise alkaline adapted L. monocytogenes recovered as persistent and transient food factory contaminants. Three unrelated strains were studied including two persistent and a transient food factory contaminant determined using multilocus sequence typing (MLST). The strains were adapted to growth at pH 8.5 and harvested in exponential phase. Protein extracts were analysed using multidimensional protein identification technology (MudPIT) and protein abundance compared by spectra counting. The strains elicited core responses to alkaline growth including modulation of intracellular pH, stabilisation of cellular processes and reduced cell-division, independent to lineage, MLST or whether the strains were transient or persistent contaminants. Alkaline adaptation by all strains corresponded to that expected in stringent-response induced cells, with protein expression supporting metabolic shifts concordant with elevated alarmone production and indicating that the alkaline-stringent response results from energy rather than nutrient limitation. We believe this is the first report describing induction of a stringent response in different L. monocytogenes strains by alkaline pH under non-limiting growth conditions. The work emphasises the need for early intervention to avoid persistent food factory contamination by L. monocytogenes.

Clinical and biological relevance of the transcriptomic-based prostate cancer metastasis subtypes MetA-C.

To improve treatment of metastatic prostate cancer, the biology of metastases needs to be understood. We recently described three subtypes of prostate cancer bone metastases (MetA-C), based on differential gene expression. The aim of this study was to verify the clinical relevance of these subtypes and to explore their biology and relations to genetic drivers. Freshly-frozen metastasis samples were obtained as hormone-naive (n = 17), short-term castrated (n = 21), or castration-resistant (n = 65) from a total of 67 patients. Previously published sequencing data from 573 metastasis samples were also analyzed. Through transcriptome profiling and sample classification based on a set of predefined MetA-C-differentiating genes, we found that most metastases were heterogeneous for the MetA-C subtypes. Overall, MetA was the most common subtype, while MetB was significantly enriched in castration-resistant samples and in liver metastases, and consistently associated with poor prognosis. By gene set enrichment analysis, the phenotype of MetA was described by high androgen response, protein secretion and adipogenesis, MetB by high cell cycle activity and DNA repair, and MetC by epithelial-to-mesenchymal transition and inflammation. The MetB subtype demonstrated single nucleotide variants of RB transcriptional corepressor 1 (RB1) and loss of 21 genes at chromosome 13, including RB1, but provided independent prognostic value to those genetic aberrations. In conclusion, a distinct set of gene transcripts can be used to classify prostate cancer metastases into the subtypes MetA-C. The MetA-C subtypes show diverse biology, organ tropism, and prognosis. The MetA-C classification may be used independently, or in combination with genetic markers, primarily to identify MetB patients in need of complementary therapy to conventional androgen receptor-targeting treatments.

Utility of gel-free, label-free shotgun proteomics approaches to investigate microorganisms.

This review will examine the current situation with label-free, quantitative, shotgun-oriented proteomics technology and discuss the advantages and limitations associated with its capability in capturing and quantifying large portions of proteomes of microorganisms. Such an approach allows (1) comparisons between physiological or genetic states of organisms at the protein level, (2) 'painting' of proteomic data onto genome data-based metabolic maps, (3) enhancement of the utility of genomic data and finally (4) surveying of non-genome sequenced microorganisms by taking advantage of available inferred protein data in order to gain new insights into strain-dependent metabolic or physiological capacities. The technology essentially is a powerful addition to systems biology with a capacity to be used to ask hypothesis-driven 'top-down' questions or for more empirical 'bottom-up' exploration.

Advancing biodiversity assessments with environmental DNA: Long-read technologies help reveal the drivers of Amazonian fungal diversity.

Fungi are a key component of tropical biodiversity. However, due to their inconspicuous and largely subterranean nature, they are usually neglected in biodiversity inventories. The goal of this study was to identify the key determinants of fungal richness, community composition, and turnover in tropical rainforests. We tested specifically for the effect of soil properties, habitat, and locality in Amazonia. For these analyses, we used high-throughput sequencing data of short and long reads of fungal DNA present in soil and organic litter samples, combining existing and novel genomic data. Habitat type (phytophysiognomy) emerges as the strongest factor explaining fungal community composition. Naturally open areas-campinas-are the richest habitat overall. Soil properties have different effects depending on the soil layer (litter or mineral soil) and the choice of genetic marker. We suggest that campinas could be a neglected hotspot of fungal diversity. An underlying cause for their rich diversity may be the overall low soil fertility, which increases the reliance on biotic interactions essential for nutrient absorption in these environments, notably ectomycorrhizal fungi-plant associations. Our results highlight the advantages of using both short and long DNA reads produced through high-throughput sequencing to characterize fungal diversity. While short reads can suffice for diversity and community comparison, long reads add taxonomic precision and have the potential to reveal population diversity.

Fungal functional ecology: bringing a trait-based approach to plant-associated fungi.

Fungi play many essential roles in ecosystems. They facilitate plant access to nutrients and water, serve as decay agents that cycle carbon and nutrients through the soil, water and atmosphere, and are major regulators of macro-organismal populations. Although technological advances are improving the detection and identification of fungi, there still exist key gaps in our ecological knowledge of this kingdom, especially related to function. Trait-based approaches have been instrumental in strengthening our understanding of plant functional ecology and, as such, provide excellent models for deepening our understanding of fungal functional ecology in ways that complement insights gained from traditional and -omics-based techniques. In this review, we synthesize current knowledge of fungal functional ecology, taxonomy and systematics and introduce a novel database of fungal functional traits (FunFun ). FunFun is built to interface with other databases to explore and predict how fungal functional diversity varies by taxonomy, guild, and other evolutionary or ecological grouping variables. To highlight how a quantitative trait-based approach can provide new insights, we describe multiple targeted examples and end by suggesting next steps in the rapidly growing field of fungal functional ecology.

METAXA2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data.

The ribosomal rRNA genes are widely used as genetic markers for taxonomic identification of microbes. Particularly the small subunit (SSU; 16S/18S) rRNA gene is frequently used for species- or genus-level identification, but also the large subunit (LSU; 23S/28S) rRNA gene is employed in taxonomic assignment. The METAXA software tool is a popular utility for extracting partial rRNA sequences from large sequencing data sets and assigning them to an archaeal, bacterial, nuclear eukaryote, mitochondrial or chloroplast origin. This study describes a comprehensive update to METAXA - METAXA2 - that extends the capabilities of the tool, introducing support for the LSU rRNA gene, a greatly improved classifier allowing classification down to genus or species level, as well as enhanced support for short-read (100 bp) and paired-end sequences, among other changes. The performance of METAXA2 was compared to other commonly used taxonomic classifiers, showing that METAXA2 often outperforms previous methods in terms of making correct predictions while maintaining a low misclassification rate. METAXA2 is freely available from http://microbiology.se/software/metaxa2/.

MudPIT profiling reveals a link between anaerobic metabolism and the alkaline adaptive response of Listeria monocytogenes EGD-e.

Listeria monocytogenes is a foodborne human pathogen capable of causing life-threatening disease in susceptible populations. Previous proteomic analysis we performed demonstrated that different strains of L. monocytogenes initiate a stringent response when subjected to alkaline growth conditions. Here, using multidimensional protein identification technology (MudPIT), we show that in L. monocytogenes EGD-e this response involves an energy shift to anaerobic pathways in response to the extracellular pH environment. Importantly we show that this supports a reduction in relative lag time following an abrupt transition to low oxygen tension culture conditions. This has important implications for the packaging of fresh and ready-to-eat foods under reduced oxygen conditions in environments where potential exists for alkaline adaptation.

Significant and persistent impact of timber harvesting on soil microbial communities in Northern coniferous forests.

Forest ecosystems have integral roles in climate stability, biodiversity and economic development. Soil stewardship is essential for sustainable forest management. Organic matter (OM) removal and soil compaction are key disturbances associated with forest harvesting, but their impacts on forest ecosystems are not well understood. Because microbiological processes regulate soil ecology and biogeochemistry, microbial community structure might serve as indicator of forest ecosystem status, revealing changes in nutrient and energy flow patterns before they have irreversible effects on long-term soil productivity. We applied massively parallel pyrosequencing of over 4.6 million ribosomal marker sequences to assess the impact of OM removal and soil compaction on bacterial and fungal communities in a field experiment replicated at six forest sites in British Columbia, Canada. More than a decade after harvesting, diversity and structure of soil bacterial and fungal communities remained significantly altered by harvesting disturbances, with individual taxonomic groups responding differentially to varied levels of the disturbances. Plant symbionts, like ectomycorrhizal fungi, and saprobic taxa, such as ascomycetes and actinomycetes, were among the most sensitive to harvesting disturbances. Given their significant ecological roles in forest development, the fate of these taxa might be critical for sustainability of forest ecosystems. Although abundant bacterial populations were ubiquitous, abundant fungal populations often revealed a patchy distribution, consistent with their higher sensitivity to the examined soil disturbances. These results establish a comprehensive inventory of bacterial and fungal community composition in northern coniferous forests and demonstrate the long-term response of their structure to key disturbances associated with forest harvesting.

Large scale biobanking of blood - the importance of high density sample processing procedures.

OBJECTIVE: The aim of this study is a novel automated sample-processing concept for future proteomics and clinical research, performing patient studies from resulting blood fractions in various disease areas. Another aim is biobank storage of small sample volumes, where each sample aliquot can be used for a dedicated clinical analysis and end-point measurement in order to preserve sample integrity and value over time. METHODS: 96 and 384 format sample storage tube systems were utilized for preservation and archiving of clinical patient samples. Automated sample processing and aliquoting were achieved using robotic liquid handling instrumentation, followed by biomarker assay quantitations. Sample workflow was documented and tracked by Nautilus LIMS. RESULTS: Validation by repetitive processing and analysis confirmed the reliability of automated high density 384 format aliquoting. This high density scaling allows for reproducible aliquoting of 70-µL volumes of blood. Plasma with EDTA, Li-heparin, and citrate, as anti-coagulants, fractioned along with the buffy coat (leukocytes) and the erythrocyte fraction. Large scale processing of 11,000 sample aliquots resulted in a 99.8% process fulfillment. CONCLUSION: Our results demonstrate that robust results can be generated from an automated sample processing strategy, isolating plasma, buffy coat, erythrocytes, serum and whole blood, proven by quantitation of 23 common markers used in everyday healthcare around the world. This article is part of a Special Issue entitled: Integrated omics.

Variability in biofilm production by Listeria monocytogenes correlated to strain origin and growth conditions.

This study aimed to identify factors that influence the development of biofilm by Listeria monocytogenes strains and to determine the extent to which biofilm production protects against quaternary ammonium compound (QAC) disinfectant challenge. A total of 95 L. monocytogenes strains were studied and biofilm production was assessed as a function of incubation temperature, media pH, strain origin, serotype, and environmental persistence status. Attachment and biofilm development (inferred by the level of attached biomass) were measured in vitro using a colourimetric 96-well microtitre plate method in nutritive media (Brain-Heart Infusion). Increased biofilm production correlated with increasing temperature and the most acidic, or most alkaline, growth conditions tested. Clinical and environmental (food factory) strains were observed to increase biofilm production at higher and lower incubation temperatures respectively, independent of their rate of planktonic growth. Serotype 1/2a strains produced significantly more biofilm. Biofilm maturity, rather than strain, was correlated with resistance to QAC. Carbohydrate containing exopolymeric material could not be detected in the biofilm of representative strains, and no correlation between strains recovered as persistent food factory contaminants and biofilm production was identified. Although limited to in vitro inference based on the assay system used, our results suggest that environmental conditions determine the level of biofilm production by L. monocytogenes strains, independent of the rate of planktonic growth, and that this may manifest from selection pressures to which a given strain grows optimally.

The ITS region as a target for characterization of fungal communities using emerging sequencing technologies.

The advent of new high-throughput DNA-sequencing technologies promises to redefine the way in which fungi and fungal communities--as well as other groups of organisms--are studied in their natural environment. With read lengths of some few hundred base pairs, massively parallel sequencing (pyrosequencing) stands out among the new technologies as the most apt for large-scale species identification in environmental samples. Although parallel pyrosequencing can generate hundreds of thousands of sequences at an exceptional speed, the limited length of the reads may pose a problem to the species identification process. This study explores whether the discrepancy in read length between parallel pyrosequencing and traditional (Sanger) sequencing will have an impact on the perceived taxonomic affiliation of the underlying species. Based on all 39,200 publicly available fungal environmental DNA sequences representing the nuclear ribosomal internal transcribed spacer (ITS) region, the results show that the two approaches give rise to quite different views of the diversity of the underlying samples. Standardization of which subregion from the ITS region should be sequenced, as well as a recognition that the composition of fungal communities as depicted through different sequencing methods need not be directly comparable, appear crucial to the integration of the new sequencing technologies with current mycological praxis.