Efficient Segmental Isotope Labeling of Integral Membrane Proteins for High-Resolution NMR Studies.

High-resolution structural NMR analyses of membrane proteins are challenging due to their large size, resulting in broad resonances and strong signal overlap. Among the isotope labeling methods that can remedy this situation, segmental isotope labeling is a suitable strategy to simplify NMR spectra and retain high-resolution structural information. However, protein ligation within integral membrane proteins is complicated since the hydrophobic protein fragments are insoluble, and the removal of ligation side-products is elaborate. Here, we show that a stabilized split-intein system can be used for rapid and high-yield protein trans-splicing of integral membrane proteins under denaturing conditions. This setup enables segmental isotope labeling experiments within folded protein domains for NMR studies. We show that high-quality NMR spectra of markedly reduced complexity can be obtained in detergent micelles and lipid nanodiscs. Of note, the nanodisc insertion step specifically selects for the ligated and correctly folded membrane protein and simultaneously removes ligation byproducts. Using this tailored workflow, we show that high-resolution NMR structure determination is strongly facilitated with just two segmentally isotope-labeled membrane protein samples. The presented method will be broadly applicable to structural and dynamical investigations of (membrane-) proteins and their complexes by solution and solid-state NMR but also other structural methods where segmental labeling is beneficial.

Multiple instance learning framework can facilitate explainability in murmur detection.

OBJECTIVE: Cardiovascular diseases (CVDs) account for a high fatality rate worldwide. Heart murmurs can be detected from phonocardiograms (PCGs) and may indicate CVDs. Still, they are often overlooked as their detection and correct clinical interpretation require expert skills. In this work, we aim to predict the presence of murmurs and clinical outcomes from multiple PCG recordings employing an explainable multitask model. APPROACH: Our approach consists of a two-stage multitask model. In the first stage, we predict the murmur presence in single PCGs using a multiple instance learning (MIL) framework. MIL also allows us to derive sample-wise classifications (i.e. murmur locations) while only needing one annotation per recording ("weak label") during training. In the second stage, we fuse explainable hand-crafted features with features from a pooling-based artificial neural network (PANN) derived from the MIL framework. Finally, we predict the presence of murmurs and the clinical outcome for a single patient based on multiple recordings using a simple feed-forward neural network. MAIN RESULTS: We show qualitatively and quantitatively that the MIL approach yields useful features and can be used to detect murmurs on multiple time instances and may thus guide a practitioner through PCGs. We analyze the second stage of the model in terms of murmur classification and clinical outcome. We achieved a weighted accuracy of 0.714 and an outcome cost of 13612 when using the PANN model and demographic features on the CirCor dataset (hidden test set of the George B. Moody PhysioNet challenge 2022, team "Heart2Beat", rank 12 / 40). SIGNIFICANCE: To the best of our knowledge, we are the first to demonstrate the usefulness of MIL in PCG classification. Also, we showcase how the explainability of the model can be analyzed quantitatively, thus avoiding confirmation bias inherent to many post-hoc methods. Finally, our overall results demonstrate the merit of employing MIL combined with handcrafted features for the generation of explainable features as well as for a competitive classification performance.

New Scale-up Technologies for Hydrogenation Reactions in Multipurpose Pharmaceutical Production Plants.

The classical scale-up approach for hydrogenation reaction processes usually includes numerous laboratory- and pilot-scale experiments. With a novel scale-up strategy, a significant number of these experiments may be replaced by modern computational simulations in combination with scale-down experiments. With only a few laboratory-scale experiments and information about the production-scale reactor, a chemical process model is developed. This computational model can be used to simulate the production-scale process with a range of different process parameters. Those simulations are then validated by only a few experiments in an advanced scale-down reactor. The scale-down reactor has to be geometrically identical to the corresponding production-scale reactor and should show a similar mass transfer behaviour. Closest similarity in terms of heat transfer behaviour is ensured by a sophisticated 3D-printed heating/cooling finger, offering the same heat exchange area per volume and overall heat-transfer coefficient as in production-scale. The proposed scale-up strategy and the custom-designed scale-down reactor will be tested by proof of concept with model reactions. Those results will be described in a future publication. This project is an excellent example of a collaboration between academia and industry, which was funded by the Aargau Research Fund. The interest of academia is to study and understand all physical and chemical processes involved, whereas industry is interested in generating a robust and simple to use tool to improve scale-up and make reliable predictions.

YBa2Cu3O7 nano superconducting quantum interference devices on MgO bicrystal substrates.

We report on nanopatterned YBa2Cu3O7-δ (YBCO) direct current superconducting quantum interference devices (SQUIDs) based on grain boundary Josephson junctions. The nanoSQUIDs are fabricated by epitaxial growth of 120 nm-thick films of the high-transition temperature cuprate superconductor YBCO via pulsed laser deposition on MgO bicrystal substrates with 24° misorientation angle, followed by sputtering of dAu = 65 nm thick Au. Nanopatterning is performed by Ga focused ion beam (FIB) milling. The SQUID performance is comparable to devices on SrTiO3 (STO), as demonstrated by electric transport and noise measurements at 4.2 K. MgO has orders of magnitude smaller dielectric permittivity than STO; i.e., one may avoid Au as a resistively shunting layer to reduce the intrinsic thermal flux noise of the nanoSQUIDs. However, we find that the Au layer is important for avoiding degradation during FIB milling. Hence, we compare devices with different dAu produced by thinning the Au layer via Ar ion milling after FIB patterning. We find that the reduction of dAu yields an increase in junction resistance, however at the expense of a reduction of the critical current and increase in SQUID inductance. This results in an estimated thermal flux noise that is almost independent of dAu. However, for two devices on MgO with 65 nm-thick Au, we find an order of magnitude lower low-frequency excess noise as compared to nanoSQUIDs on STO or those on MgO with reduced dAu. For one of those devices we obtain with bias-reversal readout ultra-low flux noise of ∼175 nΦ0 Hz-1/2 down to ∼10 Hz.

Overexpression of SUMO1 located predominately to euchromatin of dividing cells affects reproductive development in maize.

Post-translational modification of proteins by small ubiquitin-like modifier (SUMO) plays essential roles in a large variety of cellular and developmental processes. While SUMO conjugation to target proteins has been reported in numerous studies in animals and human, and partly also in the model plant Arabidopsis, little is known about the specific roles of SUMO in crop plants. Here, we report about the maize SUMO family and show that the highly conserved core isoform SUMO1 predominately locates to the nucleus where it marks euchromatin rather than heterochromatin. Moreover, SUMO1 is especially present in nuclei of small dividing cells. Strong overexpression of SUMO1 caused a severe dwarf phenotype and abnormalities in floral organ structures. Defects in anther development and female gametogenesis occurred similar to null-mutant phenotypes reported in Arabidopsis. Taken together, these studies imply that precise and fine-tuned conjugation of the highly conserved plant SUMO1 isoform to target proteins is required for vegetative and reproductive development. Mis-regulation by overexpression or knock-out is deleterious, strongly affecting fertility in both dicots and monocots, including the crop plant maize.

The role of KDEL-tailed cysteine endopeptidases of Arabidopsis (AtCEP2 and AtCEP1) in root development.

Plants encode a unique group of papain-type cysteine endopeptidases (CysEP) characterized by a C-terminal KDEL endoplasmic reticulum retention signal (KDEL-CysEP) and an unusually broad substrate specificity. The three Arabidopsis KDEL-CysEPs (AtCEP1, AtCEP2, and AtCEP3) are differentially expressed in vegetative and generative tissues undergoing programmed cell death (PCD). While KDEL-CysEPs have been shown to be implicated in the collapse of tissues during PCD, roles of these peptidases in processes other than PCD are unknown. Using mCherry-AtCEP2 and EGFP-AtCEP1 reporter proteins in wild type versus atcep2 or atcep1 mutant plants, we explored the participation of AtCEP in young root development. Loss of AtCEP2, but not AtCEP1 resulted in shorter primary roots due to a decrease in cell length in the lateral root (LR) cap, and impairs extension of primary root epidermis cells such as trichoblasts in the elongation zone. AtCEP2 was localized to root cap corpses adherent to epidermal cells in the rapid elongation zone. AtCEP1 and AtCEP2 are expressed in root epidermis cells that are separated for LR emergence. Loss of AtCEP1 or AtCEP2 caused delayed emergence of LR primordia. KDEL-CysEPs might be involved in developmental tissue remodeling by supporting cell wall elongation and cell separation.

Real-Space Probing of the Local Magnetic Response of Thin-Film Superconductors Using Single Spin Magnetometry.

We report on direct, real-space imaging of the stray magnetic field above a micro-scale disc of a thin film of the high-temperature superconductor YBa2Cu3O7-δ (YBCO) using scanning single spin magnetometry. Our experiments yield a direct measurement of the sample's London penetration depth and allow for a quantitative reconstruction of the supercurrents flowing in the sample as a result of Meissner screening. These results show the potential of scanning single spin magnetometry for studies of the nanoscale magnetic properties of thin-film superconductors, which could be readily extended to elevated temperatures or magnetic fields.

DiSUMO-LIKE Interacts with RNA-Binding Proteins and Affects Cell-Cycle Progression during Maize Embryogenesis.

Embryogenesis in flowering plants is initiated by an asymmetric zygote division, generating two daughter cells that are the precursors of different cell lineages. Little is known about the molecular players regulating activation and progression of zygote development, establishment of asymmetry, and the plant-specific process of cell-plate formation. Here, we report the function of the ubiquitin-like modifier DiSUMO-LIKE (DSUL) for early embryo development in maize. Introducing a DSUL-RNAi construct by sperm cells affects cytokinesis generating non-separated zygotic daughter nuclei or multinucleate embryonic cells lacking cell plates. DSUL accumulates in the cytoplasm partly in granules, in the nucleus, as well as in the cell division zone. The enzymatic DSULyation cascade involves maturation and the same enzymatic machinery for activation and conjugation as was previously shown for SUMO1. Identification of DSUL targets suggests predominant roles of DSULylation in regulation of cytoplasmic RNA metabolism as well as in cell-cycle progression and cell-plate formation. A comparison of DSUL and SUMO1 localization during the cell cycle and of their substrates indicates strong functional diversification between these two SUMO family modifiers.

The long and winding road: transport pathways for amino acids in Arabidopsis seeds.

KEY MESSAGE: Pathways for assimilates. During their life cycle, plants alternate between a haploid stage, the gametophyte, and a diploid stage, the sporophyte. In higher plants, meiosis generates the gametophyte deeply embedded in the maternal tissue of the flower. The megaspore mother cell undergoes meiosis, and then, the surviving megaspore of the four megaspores produced undergoes mitotic divisions and finally gives rise to the female gametophyte, consisting of the egg cell, two synergids, the central cell, which due to the fusion of two nuclei is diploid (double haploid) in Arabidopsis and most angiosperms and the antipods, whose number is not fixed and varies significantly between species (Yadegari and Drews in Plant Cell 16(Suppl):S133-S141, 2004). The maternal tissues that harbor the female gametophyte and the female gametophyte are referred to as the ovule (Fig. 1). Double fertilization of the egg cell and the central cell by the two generative nuclei of the pollen leads to the diploid embryo and the endosperm, respectively (Hamamura et al. in Curr Opin Plant Biol 15:70-77, 2012). Upon fertilization, the ovule is referred to as the seed. Seeds combine two purposes: to harbor storage compounds for use by the embryo upon germination and to protect the embryo until the correct conditions for germination are encountered. As a consequence, seeds are the plant tissue that is of highest nutritional value and the human diet, by a considerable amount, consists of seeds or seed-derived products. Amino acids are of special interest, because plants serve as the main source for the so-called essential amino acids, that animals cannot synthesize de novo and are therefore often a limiting factor for human growth and development (WHO in Protein and amino acid requirements in human nutrition. WHO technical report series, WHO, Geneva, 2007). The plant embryo needs amino acids for general protein synthesis, and additionally they are used to synthesize storage proteins in the seeds of certain plants, e.g., legumes as a resource to support the growth of the seedling after germination. The support of the embryo depends on transport processes that occur between the mother plant and the seed tissues including the embryo. In this review, we will focus on the processes of unloading amino acids from the phloem and their post-phloem transport. We will further highlight similarities between amino acid transport and the transport of the main assimilate and osmolyte, sucrose. Finally, we will discuss similarities and differences between different plant species in terms of structural aspects but for the molecular aspects we are almost exclusively focusing on Arabidopsis. Fig. 1 Vascularization of the Arabidopsis ovule and seed. Plants expressing ER-localized mCherry under control of the companion cell-specific SUC2 promoter and ER-localized GFP under control of the sieve element marker PD1 as described (Müller et al. 2015) are shown to visualize the phloem in the funiculus and the chalazal regions. a Overview over an ovule. FG: female gametophyte. b A magnification of the region marked by a square in panel a. c Overview over a seed. ES: endosperm; E: embryo. d A magnification of the region marked by a square in panel c. The arrows in b and d point to the terminal companion cell and arrowheads to terminal sieve elements.

Tumor Cell Load and Heterogeneity Estimation From Diffusion-Weighted MRI Calibrated With Histological Data: an Example From Lung Cancer.

Diffusion-weighted magnetic resonance imaging (DWI) is a key non-invasive imaging technique for cancer diagnosis and tumor treatment assessment, reflecting Brownian movement of water molecules in tissues. Since densely packed cells restrict molecule mobility, tumor tissues produce usually higher signal (a.k.a. less attenuated signal) on isotropic maps compared with normal tissues. However, no general quantitative relation between DWI data and the cell density has been established. In order to link low-resolution clinical cross-sectional data with high-resolution histological information, we developed an image processing and analysis chain, which was used to study the correlation between the diffusion coefficient (D value) estimated from DWI and tumor cellularity from serial histological slides of a resected non-small cell lung cancer tumor. Color deconvolution followed by cell nuclei segmentation was performed on digitized histological images to determine local and cell-type specific 2d (two-dimensional) densities. From these, the 3d cell density was inferred by a model-based sampling technique, which is necessary for the calculation of local and global 3d tumor cell count. Next, DWI sequence information was overlaid with high-resolution CT data and the resected histology using prominent anatomical hallmarks for co-registration of histology tissue blocks and non-invasive imaging modalities' data. The integration of cell numbers information and DWI data derived from different tumor areas revealed a clear negative correlation between cell density and D value. Importantly, spatial tumor cell density can be calculated based on DWI data. In summary, our results demonstrate that tumor cell count and heterogeneity can be predicted from DWI data, which may open new opportunities for personalized diagnosis and therapy optimization.

An individual-based model for collective cancer cell migration explains speed dynamics and phenotype variability in response to growth factors.

Collective cell migration is a common phenotype in epithelial cancers, which is associated with tumor cell metastasis and poor patient survival. However, the interplay between physiologically relevant pro-migratory stimuli and the underlying mechanical cell-cell interactions are poorly understood. We investigated the migratory behavior of different collectively migrating non-small cell lung cancer cell lines in response to motogenic growth factors (e.g. epidermal growth factor) or clinically relevant small compound inhibitors. Depending on the treatment, we observed distinct behaviors in a classical lateral migration assay involving traveling fronts, finger-shapes or the development of cellular bridges. Particle image velocimetry analysis revealed characteristic speed dynamics (evolution of the average speed of all cells in a frame) in all experiments exhibiting initial acceleration and subsequent deceleration of the cell populations. To better understand the mechanical properties of individual cells leading to the observed speed dynamics and the phenotypic differences we developed a mathematical model based on a Langevin approach. This model describes intercellular forces, random motility, and stimulation of active migration by mechanical interaction between cells. Simulations show that the model is able to reproduce the characteristic spatio-temporal speed distributions as well as most migratory phenotypes of the studied cell lines. A specific strength of the proposed model is that it identifies a small set of mechanical features necessary to explain all phenotypic and dynamical features of the migratory response of non-small cell lung cancer cells to chemical stimulation/inhibition. Furthermore, all processes included in the model can be associated with potential molecular components, and are therefore amenable to experimental validation. Thus, the presented mathematical model may help to predict which mechanical aspects involved in non-small cell lung cancer cell migration are affected by the respective therapeutic treatment.

TTCA: an R package for the identification of differentially expressed genes in time course microarray data.

BACKGROUND: The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for detecting significant expression dynamics often fail when the expression dynamics show a large heterogeneity. Moreover, these methods often cannot cope with irregular and sparse measurements. RESULTS: The method proposed here is specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and transient dynamics as well as slow expression changes, and performs well in the presence of low replicate numbers and irregular sampling times. The results are given in the form of tables including links to figures showing the expression dynamics of the respective transcript. These allow to quickly recognise the relevance of detection, to identify possible false positives and to discriminate early and late changes in gene expression. An extension of the method allows the analysis of the expression dynamics of functional groups of genes, providing a quick overview of the cellular response. The performance of this package was tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor (EGF). CONCLUSION: Here we describe a new, efficient method for the analysis of sparse and heterogeneous time course data with high detection sensitivity and transparency. It is implemented as R package TTCA (transcript time course analysis) and can be installed from the Comprehensive R Archive Network, CRAN. The source code is provided with the Additional file 1.

Three-Axis Vector Nano Superconducting Quantum Interference Device.

We present the design, realization, and performance of a three-axis vector nano superconducting quantum interference device (nanoSQUID). It consists of three mutually orthogonal SQUID nanoloops that allow distinguishing the three components of the vector magnetic moment of individual nanoparticles placed at a specific position. The device is based on Nb/HfTi/Nb Josephson junctions and exhibits line widths of ∼250 nm and inner loop areas of 600 × 90 and 500 × 500 nm(2). Operation at temperature T = 4.2 K under external magnetic fields perpendicular to the substrate plane up to ∼50 mT is demonstrated. The experimental flux noise below [Formula: see text] in the white noise limit and the reduced dimensions lead to a total calculated spin sensitivity of [Formula: see text] and [Formula: see text] for the in-plane and out-of-plane components of the vector magnetic moment, respectively. The potential of the device for studying three-dimensional properties of individual nanomagnets is discussed.

Expression analysis of KDEL-CysEPs programmed cell death markers during reproduction in Arabidopsis.

KEY MESSAGE: CEP cell death markers. Programmed cell death (PCD) is essential for proper plant growth and development. Plant-specific papain-type KDEL-tailed cysteine endopeptidases (KDEL-CysEPs or CEPs) have been shown to be involved in PCD during vegetative development as executors for the last step in the process. The Arabidopsis genome encodes three KDEL-CysEPs: AtCEP1, AtCEP2 and AtCEP3. With the help of fluorescent fusion reporter lines, we report here a detailed expression analysis of KDEL-CysEP (pro)proteins during reproductive processes, including flower organ and germline development, fertilization and seed development. AtCEP1 is highly expressed in different reproductive tissues including nucellus cells of mature ovule and the connecting edge of anther and filament. After fertilization, AtCEP1 marks integument cell layers of the seeds coat as well as suspensor and columella cells of the developing embryo. Promoter activity of AtCEP2 is detected in the style of immature and mature pistils, in other floral organs including anther, sepal and petal. AtCEP2 mainly localizes to parenchyma cells next to xylem vessels. Although there is no experimental evidence to demonstrate that KDEL-CysEPs are involved in PCD during fertilization, the expression pattern of AtCEPs, which were previously shown to represent cell death markers during vegetative development, opens up new avenues to investigate PCD in plant reproduction.

Inferring Growth Control Mechanisms in Growing Multi-cellular Spheroids of NSCLC Cells from Spatial-Temporal Image Data.

We develop a quantitative single cell-based mathematical model for multi-cellular tumor spheroids (MCTS) of SK-MES-1 cells, a non-small cell lung cancer (NSCLC) cell line, growing under various nutrient conditions: we confront the simulations performed with this model with data on the growth kinetics and spatial labeling patterns for cell proliferation, extracellular matrix (ECM), cell distribution and cell death. We start with a simple model capturing part of the experimental observations. We then show, by performing a sensitivity analysis at each development stage of the model that its complexity needs to be stepwise increased to account for further experimental growth conditions. We thus ultimately arrive at a model that mimics the MCTS growth under multiple conditions to a great extent. Interestingly, the final model, is a minimal model capable of explaining all data simultaneously in the sense, that the number of mechanisms it contains is sufficient to explain the data and missing out any of its mechanisms did not permit fit between all data and the model within physiological parameter ranges. Nevertheless, compared to earlier models it is quite complex i.e., it includes a wide range of mechanisms discussed in biological literature. In this model, the cells lacking oxygen switch from aerobe to anaerobe glycolysis and produce lactate. Too high concentrations of lactate or too low concentrations of ATP promote cell death. Only if the extracellular matrix density overcomes a certain threshold, cells are able to enter the cell cycle. Dying cells produce a diffusive growth inhibitor. Missing out the spatial information would not permit to infer the mechanisms at work. Our findings suggest that this iterative data integration together with intermediate model sensitivity analysis at each model development stage, provide a promising strategy to infer predictive yet minimal (in the above sense) quantitative models of tumor growth, as prospectively of other tissue organization processes. Importantly, calibrating the model with two nutriment-rich growth conditions, the outcome for two nutriment-poor growth conditions could be predicted. As the final model is however quite complex, incorporating many mechanisms, space, time, and stochastic processes, parameter identification is a challenge. This calls for more efficient strategies of imaging and image analysis, as well as of parameter identification in stochastic agent-based simulations.

Amino Acid Export in Developing Arabidopsis Seeds Depends on UmamiT Facilitators.

Essential amino acids cannot be synthesized by humans and animals. They often are limiting in plant-derived foods and determine the nutritional value of a given diet. Seeds and fruits often represent the harvestable portion of plants. In order to improve the amino acid composition of these tissues, it is indispensable to understand how these substrates are transported within the plant. Amino acids result from nitrogen assimilation, which often occurs in leaves, the source tissue. They are transported via the vasculature, the xylem, and the phloem into the seeds, the so-called sink tissue, where they are stored or consumed. In seeds, several tissues are symplasmically isolated, i.e., not connected by plasmodesmata, channels in the cell walls that enable a cytoplasmic continuum in plants. Consequently, amino acids must be exported from cells into the apoplast and re-imported many times to support seed development. Several amino acid importers are known, but exporters remained elusive. Here, we characterize four members of the plant-specific UmamiT transporter family from Arabidopsis, related to the amino acid facilitator SIAR1 and the vacuolar auxin transporter WAT1. We show that the proteins transport amino acids along their (electro)chemical potential across the plasma membrane. In seeds, they are found in tissues from which amino acids are exported. Loss-of-function mutants accumulate high levels of free amino acids in fruits and produce smaller seeds. Our results strongly suggest a crucial role for the UmamiTs in amino acid export and possibly a means to improve yield quality.

Concomitant expression of far upstream element (FUSE) binding protein (FBP) interacting repressor (FIR) and its splice variants induce migration and invasion of non-small cell lung cancer (NSCLC) cells.

Transcription factors integrate a variety of oncogenic input information, facilitate tumour growth and cell dissemination, and therefore represent promising therapeutic target structures. Because over-expression of DNA-interacting far upstream element binding protein (FBP) supports non-small cell lung cancer (NSCLC) migration, we asked whether its repressor, FBP-interacting repressor (FIR) is functionally inactivated and how FIR might affect NSCLC cell biology. Different FIR splice variants were highly expressed in the majority of NSCLCs, with the highest levels in tumours carrying genomic gains of chromosome 8q24.3, which contained the FIR gene locus. Nuclear FIR expression was significantly enriched at the invasion front of primary NSCLCs, but this did not correlate with tumour cell proliferation. FIR accumulation was associated with worse patient survival and tumour recurrence; in addition, FIR over-expression significantly correlated with lymph node metastasis in squamous cell carcinomas (SCCs). In vitro, we applied newly developed methods and modelling approaches for the quantitative and time-resolved description of the pro-migratory and pro-invasive capacities of SCC cells. siRNA-mediated silencing of all FIR variants significantly reduced the speed and directional movement of tumour cells in all phases of migration. Furthermore, sprouting efficiency and single cell invasiveness were diminished following FIR inhibition. Interestingly, the silencing of FIR isoforms lacking exon 2 (FIR(Δexon2)) alone was sufficient to reduce lateral migration and invasion. In summary, by using scale-spanning data derived from primary human tissues, quantitative cellular analyses and mathematical modelling, we have demonstrated that concomitant over-expression of FIR and its splice variants drives NSCLC migration and dissemination.

Stathmin regulates keratinocyte proliferation and migration during cutaneous regeneration.

Cutaneous regeneration utilizes paracrine feedback mechanisms to fine-tune the regulation of epidermal keratinocyte proliferation and migration. However, it is unknown how fibroblast-derived hepatocyte growth factor (HGF) affects these mutually exclusive processes in distinct cell populations. We here show that HGF stimulates the expression and phosphorylation of the microtubule-destabilizing factor stathmin in primary human keratinocytes. Quantitative single cell- and cell population-based analyses revealed that basal stathmin levels are important for the migratory ability of keratinocytes in vitro; however, its expression is moderately induced in the migration tongue of mouse skin or organotypic multi-layered keratinocyte 3D cultures after full-thickness wounding. In contrast, clearly elevated stathmin expression is detectable in hyperproliferative epidermal areas. In vitro, stathmin silencing significantly reduced keratinocyte proliferation. Automated quantitative and time-resolved analyses in organotypic cocultures demonstrated a high correlation between Stathmin/phospho-Stathmin and Ki67 positivity in epidermal regions with proliferative activity. Thus, activation of stathmin may stimulate keratinocyte proliferation, while basal stathmin levels are sufficient for keratinocyte migration during cutaneous regeneration.

Belowground neighbor perception in Arabidopsis thaliana studied by transcriptome analysis: roots of Hieracium pilosella cause biotic stress.

Root-root interactions are much more sophisticated than previously thought, yet the mechanisms of belowground neighbor perception remain largely obscure. Genome-wide transcriptome analyses allow detailed insight into plant reactions to environmental cues. A root interaction trial was set up to explore both morphological and whole genome transcriptional responses in roots of Arabidopsis thaliana in the presence or absence of an inferior competitor, Hieracium pilosella. Neighbor perception was indicated by Arabidopsis roots predominantly growing away from the neighbor (segregation), while solitary plants placed more roots toward the middle of the pot. Total biomass remained unaffected. Database comparisons in transcriptome analysis revealed considerable similarity between Arabidopsis root reactions to neighbors and reactions to pathogens. Detailed analyses of the functional category "biotic stress" using MapMan tools found the sub-category "pathogenesis-related proteins" highly significantly induced. A comparison to a study on intraspecific competition brought forward a core of genes consistently involved in reactions to neighbor roots. We conclude that beyond resource depletion roots perceive neighboring roots or their associated microorganisms by a relatively uniform mechanism that involves the strong induction of pathogenesis-related proteins. In an ecological context the findings reveal that belowground neighbor detection may occur independently of resource depletion, allowing for a time advantage for the root to prepare for potential interactions.