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Background: Leishmania tarentolae, a unicellular eukaryotic protozoan, has been established as a novel host for recombinant protein production in recent years. Current protocols for protein expression in Leishmania are, however, time consuming and require extensive lab work in order to identify well-expressing cell lines. Here we established an alternative protein expression work-flow that employs recently engineered infrared fluorescence protein (IFP) as a suitable and easy-to-handle reporter protein for recombinant protein expression in Leishmania. As model proteins we tested three proteins from the plant Arabidopsis thaliana, including a NAC and a type-B ARR transcription factor.
Results: IFP and IFP fusion proteins were expressed in Leishmania and rapidly detected in cells by deconvolution microscopy and in culture by infrared imaging of 96-well microtiter plates using small cell culture volumes (2 mu L - 100 mu L). Motility, shape and growth of Leishmania cells were not impaired by intracellular accumulation of IFP. In-cell detection of IFP and IFP fusion proteins was straightforward already at the beginning of the expression pipeline and thus allowed early pre-selection of well-expressing Leishmania clones. Furthermore, IFP fusion proteins retained infrared fluorescence after electrophoresis in denaturing SDS-polyacrylamide gels, allowing direct in-gel detection without the need to disassemble cast protein gels. Thus, parameters for scaling up protein production and streamlining purification routes can be easily optimized when employing IFP as reporter.
Conclusions: Using IFP as biosensor we devised a protocol for rapid and convenient protein expression in Leishmania tarentolae. Our expression pipeline is superior to previously established methods in that it significantly reduces the hands-on-time and work load required for identifying well-expressing clones, refining protein production parameters and establishing purification protocols. The facile in-cell and in-gel detection tools built on IFP make Leishmania amenable for high-throughput expression of proteins from plant and animal sources.
Background: Leishmania tarentolae, a unicellular eukaryotic protozoan, has been established as a novel host for recombinant protein production in recent years. Current protocols for protein expression in Leishmania are, however, time consuming and require extensive lab work in order to identify well-expressing cell lines. Here we established an alternative protein expression work-flow that employs recently engineered infrared fluorescence protein (IFP) as a suitable and easy-to-handle reporter protein for recombinant protein expression in Leishmania. As model proteins we tested three proteins from the plant Arabidopsis thaliana, including a NAC and a type-B ARR transcription factor. Results: IFP and IFP fusion proteins were expressed in Leishmania and rapidly detected in cells by deconvolution microscopy and in culture by infrared imaging of 96-well microtiter plates using small cell culture volumes (2 μL - 100 μL). Motility, shape and growth of Leishmania cells were not impaired by intracellular accumulation of IFP. In-cell detection of IFP and IFP fusion proteins was straightforward already at the beginning of the expression pipeline and thus allowed early pre-selection of well-expressing Leishmania clones. Furthermore, IFP fusion proteins retained infrared fluorescence after electrophoresis in denaturing SDS-polyacrylamide gels, allowing direct in-gel detection without the need to disassemble cast protein gels. Thus, parameters for scaling up protein production and streamlining purification routes can be easily optimized when employing IFP as reporter. Conclusions: Using IFP as biosensor we devised a protocol for rapid and convenient protein expression in Leishmania tarentolae. Our expression pipeline is superior to previously established methods in that it significantly reduces the hands-on-time and work load required for identifying well-expressing clones, refining protein production parameters and establishing purification protocols. The facile in-cell and in-gel detection tools built on IFP make Leishmania amenable for high-throughput expression of proteins from plant and animal sources.
Although the use of stable transformation technology has led to great insight into gene function, its application in high-throughput studies remains arduous. Agro-infiltration have been widely used in species such as Nicotiana benthamiana for the rapid detection of gene expression and protein interaction analysis, but this technique does not work efficiently in other plant species, including Arabidopsis thaliana. As an efficient high-throughput transient expression system is currently lacking in the model plant species A. thaliana, we developed a method that is characterized by high efficiency, reproducibility, and suitability for transient expression of a variety of functional proteins in A. thaliana and 7 other plant species, including Brassica oleracea, Capsella rubella, Thellungiella salsuginea, Thellungiella halophila, Solanum tuberosum, Capsicum annuum, and N. benthamiana. Efficiency of this method was independently verified in three independent research facilities, pointing to the robustness of this technique. Furthermore, in addition to demonstrating the utility of this technique in a range of species, we also present a case study employing this method to assess protein-protein interactions in the sucrose biosynthesis pathway in Arabidopsis.
Although the use of stable transformation technology has led to great insight into gene function, its application in high-throughput studies remains arduous. Agro-infiltration have been widely used in species such as Nicotiana benthamiana for the rapid detection of gene expression and protein interaction analysis, but this technique does not work efficiently in other plant species, including Arabidopsis thaliana. As an efficient high-throughput transient expression system is currently lacking in the model plant species A. thaliana, we developed a method that is characterized by high efficiency, reproducibility, and suitability for transient expression of a variety of functional proteins in A. thaliana and 7 other plant species, including Brassica oleracea, Capsella rubella, Thellungiella salsuginea, Thellungiella halophila, Solanum tuberosum, Capsicum annuum, and N. benthamiana. Efficiency of this method was independently verified in three independent research facilities, pointing to the robustness of this technique. Furthermore, in addition to demonstrating the utility of this technique in a range of species, we also present a case study employing this method to assess protein-protein interactions in the sucrose biosynthesis pathway in Arabidopsis.
Motivation: Full-length DNA and protein sequences that span the entire length of a gene are ideally used for multiple sequence alignments (MSAs) and the subsequent inference of their relationships. Frequently, however, MSAs contain a substantial amount of missing data. For example, expressed sequence tags (ESTs), which are partial sequences of expressed genes, are the predominant source of sequence data for many organisms. The patterns of missing data typical for EST-derived alignments greatly compromise the accuracy of estimated phylogenies. Results: We present a statistical method for inferring phylogenetic trees from EST-based incomplete MSA data. We propose a class of hierarchical models for modeling pairwise distances between the sequences, and develop a fully Bayesian approach for estimation of the model parameters. Once the distance matrix is estimated, the phylogenetic tree may be constructed by applying neighbor-joining (or any other algorithm of choice). We also show that maximizing the marginal likelihood from the Bayesian approach yields similar results to a pro. le likelihood estimation. The proposed methods are illustrated using simulated protein families, for which the true phylogeny is known, and one real protein family.
To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes.
The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times.
Using the system, a single researcher can phenotype up to 7000 plants d(-1). Technical variance is very low (typically < 2%). We show quantitative results for the growth-impaired starch-excessmutant sex4-3 and the growth-enhancedmutant grf9.
We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.
Plants located adjacent to agricultural fields are important for maintaining biodiversity in semi-natural landscapes. To avoid undesired impacts on these plants due to herbicide application on the arable fields, regulatory risk assessments are conducted prior to registration to ensure proposed uses of plant protection products do not present an unacceptable risk. The current risk assessment approach for these non-target terrestrial plants (NTTPs) examines impacts at the individual-level as a surrogate approach for protecting the plant community due to the inherent difficulties of directly assessing population or community level impacts. However, modelling approaches are suitable higher tier tools to upscale individual-level effects to community level. IBC-grass is a sophisticated plant community model, which has already been applied in several studies. However, as it is a console application software, it was not deemed sufficiently user-friendly for risk managers and assessors to be conveniently operated without prior expertise in ecological models. Here, we present a user-friendly and open source graphical user interface (GUI) for the application of IBC-grass in regulatory herbicide risk assessment. It facilitates the use of the plant community model for predicting long-term impacts of herbicide applications on NTTP communities. The GUI offers two options to integrate herbicide impacts: (1) dose responses based on current standard experiments (acc. to testing guidelines) and (2) based on specific effect intensities. Both options represent suitable higher tier options for future risk assessments of NTTPs as well as for research on the ecological relevance of effects.
Our goal was to reconstruct the late eighteenth century forest vegetation of the Prignitz region (NE Germany) at a scale of 1:50,000. We also wanted to relate the historical forest vegetation to the actual and potential natural vegetation. For these purposes, we selected 15 woody species and transferred relevant data found in historical records from various sources together with the recent localities of (very) old individuals belonging to these woody species into ArcView GIS. Following multi-step data processing including the generation of a point density layer using a moving window with kernel estimation and derivation of vegetation units applying Boolean algebra rules together with information on site conditions, we derived 17 forest communities corresponding to the potential natural vegetation. We were able to reconstruct the historical forest vegetation for 90% of the forest area ca. 1780. Only two of the 17 forest communities covered large parts of the forested area. The oak forest with Agrostis capillaris covered about 44% of the total forest area, and alder forests on fenland made up about 37%. Oak-hornbeam forests with Stellaria holostea comprised slightly less than 6% of the forest area, while all other forest communities comprised less than 1%. The historical forest vegetation is more similar to the potential forest vegetation and quite different from the actual forest vegetation because coniferous tree species currently cover approximately two-thirds of the actual forest area. The most beneficial result of this study is the map of high-resolution historical vegetation units that may serve as the basis for various further studies, e.g., modelling long-term changes in biodiversity at the landscape scale.
Ophiostomatoid fungi are vectored by their bark-beetle associates and colonize different host tree species. To survive and proliferate in the host, they have evolved mechanisms for detoxification and elimination of host defence compounds, efficient nutrient sequestration, and, in pathogenic species, virulence towards plants. Here, we assembled a draft genome of the spruce pathogen Ophiostoma bicolor. For our comparative and phylogenetic analyses, we mined the genomes of closely related species (Ophiostoma piceae, Ophiostoma ulmi, Ophiostoma novo-ulmi, and Grosmannia clavigera). Our aim was to acquire a genomic and evolutionary perspective of gene families important in host colonization. Genome comparisons showed that both the nuclear and mitochondrial genomes in our assembly were largely complete. Our O. bicolor 25.3 Mbp draft genome had 10 018 predicted genes, 6041 proteins with gene ontology (GO) annotation, 269 carbohydrate-active enzymes (CAZymes), 559 peptidases and inhibitors, and 1373 genes likely involved in pathogen-host interactions. Phylogenetic analyses of selected protein families revealed core sets of cytochrome P450 genes, ABC transporters and backbone genes involved in secondary metabolite (SM) biosynthesis (polyketide synthases (PKS) and non-ribosomal synthases), and species-specific gene losses and duplications. Phylogenetic analyses of protein families of interest provided insight into evolutionary adaptations to host biochemistry in ophiostomatoid fungi.
Liverwort Blasia pusilla L. recruits soil nitrogen-fixing cyanobacteria of genus Nostoc as symbiotic partners. In this work we compared Nostoc community composition inside the plants and in the soil around them from two distant locations in Northern Norway. STRR fingerprinting and 16S rDNA phylogeny reconstruction showed a remarkable local diversity among isolates assigned to several Nostoc clades. An extensive web of negative allelopathic interactions was recorded at an agricultural site, but not at the undisturbed natural site. The cell extracts of the cyanobacteria did not show antimicrobial activities, but four isolates were shown to be cytotoxic to human cells. The secondary metabolite profiles of the isolates were mapped by MALDI-TOF MS, and the most prominent ions were further analyzed by Q-TOF for MS/MS aided identification. Symbiotic isolates produced a great variety of small peptide-like substances, most of which lack any record in the databases. Among identified compounds we found microcystin and nodularin variants toxic to eukaryotic cells. Microcystin producing chemotypes were dominating as symbiotic recruits but not in the free-living community. In addition, we were able to identify several novel aeruginosins and banyaside-like compounds, as well as nostocyclopeptides and nosperin.