| 1. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Metaxa2 Database Builder: enabling taxonomic identification from metagenomic or metabarcoding data using any genetic marker
- 2018
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Ingår i: Bioinformatics (Oxford, England). - : Oxford University Press (OUP). - 1367-4811 .- 1367-4803. ; 34:23, s. 4027-4033
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Tidskriftsartikel (refereegranskat)abstract
- Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, no genetic marker gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. This has led to the adoption of a range of genetic markers for DNA metabarcoding. While many taxonomic classification software tools can be re-trained on these genetic markers, they are often designed with assumptions that impair their utility on genes other than the SSU and LSU rRNA. Here, we present an update to Metaxa2 that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data.We evaluated the Metaxa2 Database Builder on eleven commonly used barcoding regions and found that while there are wide differences in performance between different genetic markers, our software performs satisfactorily provided that the input taxonomy and sequence data are of high quality.Freely available on the web as part of the Metaxa2 package at http://microbiology.se/software/metaxa2/.Supplementary data are available at Bioinformatics online.
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| 2. |
- Sepehri, Sobhan, 1986, et al.
(författare)
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Characterization of Binding of Magnetic Nanoparticles to Rolling Circle Amplification Products by Turn-On Magnetic Assay
- 2019
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Ingår i: Biosensors-Basel. - : MDPI AG. ; 9:3
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Tidskriftsartikel (refereegranskat)abstract
- The specific binding of oligonucleotide-tagged 100 nm magnetic nanoparticles (MNPs) to rolling circle products (RCPs) is investigated using our newly developed differential homogenous magnetic assay (DHMA). The DHMA measures ac magnetic susceptibility from a test and a control samples simultaneously and eliminates magnetic background signal. Therefore, the DHMA can reveal details of binding kinetics of magnetic nanoparticles at very low concentrations of RCPs. From the analysis of the imaginary part of the DHMA signal, we find that smaller MNPs in the particle ensemble bind first to the RCPs. When the RCP concentration increases, we observe the formation of agglomerates, which leads to lower number of MNPs per RCP at higher concentrations of RCPs. The results thus indicate that a full frequency range of ac susceptibility observation is necessary to detect low concentrations of target RCPs and a long amplification time is not required as it does not significantly increase the number of MNPs per RCP. The findings are critical for understanding the underlying microscopic binding process for improving the assay performance. They furthermore suggest DHMA is a powerful technique for dynamically characterizing the binding interactions between MNPs and biomolecules in fluid volumes.
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| 3. |
- Norinder, Ulf, 1956-, et al.
(författare)
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Conformal prediction to define applicability domain : A case study on predicting ER and AR binding
- 2016
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Ingår i: SAR and QSAR in environmental research (Print). - : Taylor & Francis. - 1062-936X .- 1029-046X. ; 27:4, s. 303-316
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Tidskriftsartikel (refereegranskat)abstract
- A fundamental element when deriving a robust and predictive in silico model is not only the statistical quality of the model in question but, equally important, the estimate of its predictive boundaries. This work presents a new method, conformal prediction, for applicability domain estimation in the field of endocrine disruptors. The method is applied to binders and non-binders related to the oestrogen and androgen receptors. Ensembles of decision trees are used as statistical method and three different sets (dragon, rdkit and signature fingerprints) are investigated as chemical descriptors. The conformal prediction method results in valid models where there is an excellent balance in quality between the internally validated training set and the corresponding external test set, both in terms of validity and with respect to sensitivity and specificity. With this method the level of confidence can be readily altered by the user and the consequences thereof immediately inspected. Furthermore, the predictive boundaries for the derived models are rigorously defined by using the conformal prediction framework, thus no ambiguity exists as to the level of similarity needed for new compounds to be in or out of the predictive boundaries of the derived models where reliable predictions can be expected.
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| 4. |
- Norinder, Ulf, 1956-, et al.
(författare)
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Conformal prediction of HDAC inhibitors
- 2019
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Ingår i: SAR and QSAR in environmental research (Print). - : Taylor & Francis. - 1062-936X .- 1029-046X. ; 30:4, s. 265-277
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Tidskriftsartikel (refereegranskat)abstract
- The growing interest in epigenetic probes and drug discovery, as revealed by several epigenetic drugs in clinical use or in the lineup of the drug development pipeline, is boosting the generation of screening data. In order to maximize the use of structure-activity relationships there is a clear need to develop robust and accurate models to understand the underlying structure-activity relationship. Similarly, accurate models should be able to guide the rational screening of compound libraries. Herein we introduce a novel approach for epigenetic quantitative structure-activity relationship (QSAR) modelling using conformal prediction. As a case study, we discuss the development of models for 11 sets of inhibitors of histone deacetylases (HDACs), which are one of the major epigenetic target families that have been screened. It was found that all derived models, for every HDAC endpoint and all three significance levels, are valid with respect to predictions for the external test sets as well as the internal validation of the corresponding training sets. Furthermore, the efficiencies for the predictions are above 80% for most data sets and above 90% for four data sets at different significant levels. The findings of this work encourage prospective applications of conformal prediction for other epigenetic target data sets.
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| 5. |
- Lebreton, Sebastien, et al.
(författare)
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A Drosophila female pheromone elicits species-specific long-range attraction via an olfactory channel with dual specificity for sex and food
- 2017
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Ingår i: BMC Biology. - : Springer Science and Business Media LLC. - 1741-7007. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Mate finding and recognition in animals evolves during niche adaptation and involves social signals and habitat cues. Drosophila melanogaster and related species are known to be attracted to fermenting fruit for feeding and egg-laying, which poses the question of whether species-specific fly odours contribute to long-range premating communication. Results: We have discovered an olfactory channel in D. melanogaster with a dual affinity to sex and food odorants. Female flies release a pheromone, (Z)-4-undecenal (Z4-11Al), that elicits flight attraction in both sexes. Its biosynthetic precursor is the cuticular hydrocarbon (Z,Z)-7,11-heptacosadiene (7,11-HD), which is known to afford reproductive isolation between the sibling species D. melanogaster and D. simulans during courtship. Twin olfactory receptors, Or69aB and Or69aA, are tuned to Z4-11Al and food odorants, respectively. They are co-expressed in the same olfactory sensory neurons, and feed into a neural circuit mediating species-specific, long-range communication; however, the close relative D. simulans, which shares food resources with D. melanogaster, does not respond to Z4-11Al. Conclusion: The Or69aA and Or69aB isoforms have adopted dual olfactory traits. The underlying gene yields a collaboration between natural and sexual selection, which has the potential to drive speciation.
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| 6. |
- Memedi, Mevludin, 1983-, et al.
(författare)
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Automatic Spiral Analysis for Objective Assessment of Motor Symptoms in Parkinson's Disease
- 2015
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 15:9, s. 23727-23744
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Tidskriftsartikel (refereegranskat)abstract
- A challenge for the clinical management of advanced Parkinson's disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.
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| 7. |
- Nystedt, Björn, et al.
(författare)
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The Norway spruce genome sequence and conifer genome evolution
- 2013
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Ingår i: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 497:7451, s. 579-584
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Tidskriftsartikel (refereegranskat)abstract
- Conifers have dominated forests for more than 200 million years and are of huge ecological and economic importance. Here we present the draft assembly of the 20-gigabase genome of Norway spruce (Picea abies), the first available for any gymnosperm. The number of well-supported genes (28,354) is similar to the >100 times smaller genome of Arabidopsis thaliana, and there is no evidence of a recent whole-genome duplication in the gymnosperm lineage. Instead, the large genome size seems to result from the slow and steady accumulation of a diverse set of long-terminal repeat transposable elements, possibly owing to the lack of an efficient elimination mechanism. Comparative sequencing of Pinus sylvestris, Abies sibirica, Juniperus communis, Taxus baccata and Gnetum gnemon reveals that the transposable element diversity is shared among extant conifers. Expression of 24-nucleotide small RNAs, previously implicated in transposable element silencing, is tissue-specific and much lower than in other plants. We further identify numerous long (>10,000 base pairs) introns, gene-like fragments, uncharacterized long non-coding RNAs and short RNAs. This opens up new genomic avenues for conifer forestry and breeding.
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| 8. |
- Sahin, Cagla, et al.
(författare)
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Structural Basis for Dityrosine-Mediated Inhibition of α-Synuclein Fibrillization
- 2022
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Ingår i: Journal of the American Chemical Society. - : American Chemical Society (ACS). - 0002-7863 .- 1520-5126. ; 144:27, s. 11949-11954
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Tidskriftsartikel (refereegranskat)abstract
- α-Synuclein (α-Syn) is an intrinsically disordered protein which self-assembles into highly organized β-sheet structures that accumulate in plaques in brains of Parkinson’s disease patients. Oxidative stress influences α-Syn structure and self-assembly; however, the basis for this remains unclear. Here we characterize the chemical and physical effects of mild oxidation on monomeric α-Syn and its aggregation. Using a combination of biophysical methods, small-angle X-ray scattering, and native ion mobility mass spectrometry, we find that oxidation leads to formation of intramolecular dityrosine cross-linkages and a compaction of the α-Syn monomer by a factor of √2. Oxidation-induced compaction is shown to inhibit ordered self-assembly and amyloid formation by steric hindrance, suggesting an important role of mild oxidation in preventing amyloid formation.
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| 9. |
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- 2019
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Tidskriftsartikel (refereegranskat)
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| 10. |
- Allison, Timothy M., et al.
(författare)
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Complementing machine learning‐based structure predictions with native mass spectrometry
- 2022
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Ingår i: Protein Science. - : John Wiley & Sons. - 0961-8368 .- 1469-896X. ; 31:6
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Tidskriftsartikel (refereegranskat)abstract
- The advent of machine learning-based structure prediction algorithms such as AlphaFold2 (AF2) and RoseTTa Fold have moved the generation of accurate structural models for the entire cellular protein machinery into the reach of the scientific community. However, structure predictions of protein complexes are based on user-provided input and may require experimental validation. Mass spectrometry (MS) is a versatile, time-effective tool that provides information on post-translational modifications, ligand interactions, conformational changes, and higher-order oligomerization. Using three protein systems, we show that native MS experiments can uncover structural features of ligand interactions, homology models, and point mutations that are undetectable by AF2 alone. We conclude that machine learning can be complemented with MS to yield more accurate structural models on a small and large scale.
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