The fungal endophyte Epichloë typhina improves photosynthesis efficiency of its host orchard grass (Dactylis glomerata)

According to the results presented in this paper the fungal endophyteEpichloë typhinasignificantly improves the growth, PSII photochemistry and C assimilation efficiency of its hostDactylis glomerata. In this paper, we present a comprehensive study of the impact of the endophytic fungi Epichloë typhina on its plant hosts’ photosynthesis apparatus. Chlorophyll a fluorescence, gas exchange, immuno-blotting and spectrophotometric measurements were employed to assess photosynthetic performance, changes in pigment content and mechanisms associated with light harvesting, carbon assimilation and energy distribution in Dactylis glomerata colonized with Epichloë typhina. According to the results presented in this study, colonization of D. glomerata results in improved photosynthesis efficiency. Additionally, we propose a new mechanism allowing plants to cope with the withdrawal of a significant fraction of its energy resources by the endophytic fungi. The abundance of LHCI, LHCII proteins as well as chlorophyll b was significantly higher in E+ plants. Malate export out of the chloroplast was shown to be increased in colonized plants. To our knowledge, we are the first to report this phenomenon. Epichloë colonization improved PSII photochemistry and C assimilation efficiency. Elevated energy demands of E+ D. glomerata plants are met by increasing the rate of carbon assimilation and PSII photochemistry. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00425-015-2337-x) contains supplementary material, which is available to authorized users

Molecular spectroscopic markers of abnormal protein aggregation

Abnormal protein aggregation has been intensively studied for over 40 years and broadly discussed in the literature due to its significant role in neurodegenerative diseases etiology. Structural reorganization and conformational changes of the secondary structure upon the aggregation determine aggregation pathways and cytotoxicity of the aggregates, and therefore, numerous analytical techniques are employed for a deep investigation into the secondary structure of abnormal protein aggregates. Molecular spectroscopies, including Raman and infrared ones, are routinely applied in such studies. Recently, the nanoscale spatial resolution of tip-enhanced Raman and infrared nanospectroscopies, as well as the high sensitivity of the surface-enhanced Raman spectroscopy, have brought new insights into our knowledge of abnormal protein aggregation. In this review, we order and summarize all nano- and micro-spectroscopic marker bands related to abnormal aggregation. Each part presents the physical principles of each particular spectroscopic technique listed above and a concise description of all spectral markers detected with these techniques in the spectra of neurodegenerative proteins and their model systems. Finally, a section concerning the application of multivariate data analysis for extraction of the spectral marker bands is included

Combined analytical approach empowers precise spectroscopic interpretation of subcellular components of pancreatic cancer cells

The lack of specific and sensitive early diagnostic options for pancreatic cancer (PC) results in patients being largely diagnosed with late-stage disease, thus inoperable and burdened with high mortality. Molecular spectroscopic methodologies, such as Raman or infrared spectroscopies, show promise in becoming a leader in screening for early-stage cancer diseases, including PC. However, should such technology be introduced, the identification of differentiating spectral features between various cancer types is required. This would not be possible without the precise extraction of spectra without the contamination by necrosis, inflammation, desmoplasia, or extracellular fluids such as mucous that surround tumor cells. Moreover, an efficient methodology for their interpretation has not been well defined. In this study, we compared different methods of spectral analysis to find the best for investigating the biomolecular composition of PC cells cytoplasm and nuclei separately. Sixteen PC tissue samples of main PC subtypes (ductal adenocarcinoma, intraductal papillary mucinous carcinoma, and ampulla of Vater carcinoma) were collected with Raman hyperspectral mapping, resulting in 191,355 Raman spectra and analyzed with comparative methodologies, specifically, hierarchical cluster analysis, non-negative matrix factorization, T-distributed stochastic neighbor embedding, principal components analysis (PCA), and convolutional neural networks (CNN). As a result, we propose an innovative approach to spectra classification by CNN, combined with PCA for molecular characterization. The CNN-based spectra classification achieved over 98% successful validation rate. Subsequent analyses of spectral features revealed differences among PC subtypes and between the cytoplasm and nuclei of their cells. Our study establishes an optimal methodology for cancer tissue spectral data classification and interpretation that allows precise and cognitive studies of cancer cells and their subcellular components, without mixing the results with cancer-surrounding tissue. As a proof of concept, we describe findings that add to the spectroscopic understanding of PC

Context and strain-dependent behavioral response to stress

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

The role of strigolactone in the cross-talk between Arabidopsis thaliana and the endophytic fungus Mucor sp.

Over the last years the role of fungal endophytes in plant biology has been extensively studied. A number of species were shown to positively affect plant growth and fitness, thus attempts have been made to utilize these microorganisms in agriculture and phytoremediation. Plant-fungi symbiosis requires multiple metabolic adjustments of both of the interacting organisms. The mechanisms of these adaptations are mostly unknown, however, plant hormones seem to play a central role in this process. The plant hormone strigolactone (SL) was previously shown to activate hyphae branching of mycorrhizal fungi and to negatively affect pathogenic fungi growth. Its role in the plant–endophytic fungi interaction is unknown. The effect of the synthetic SL analog GR24 on the endophytic fungi Mucor sp. growth, respiration, H2O2 production and the activity of antioxidant enzymes was evaluated. We found fungi colony growth rate was decreased in a GR24 concentration dependent manner. Additionally, the fungi accumulated more H2O2 what was accompanied by an altered activity of antioxidant enzymes. Symbiosis with Mucor sp. positively affected Arabidopsis thaliana growth, but SL was necessary for the establishment of the beneficial interaction. A. thaliana biosynthesis mutants max1 and max4, but not the SL signaling mutant max2 did not develop the beneficial phenotype. The negative growth response was correlated with alterations in SA homeostasis and a significant upregulation of genes encoding selected plant defensins. The fungi were also shown to be able to decompose SL in planta and to downregulate the expression of SL biosynthesis genes. Additionally, we have shown that GR24 treatment with a dose of 1 μM activates the production of SA in A. thaliana. The results presented here provide evidence for a role of SL in the plant–endophyte cross-talk during the mutualistic interaction between Arabidopsis thaliana and Mucor sp

Variabilities in global DNA methylation and β\beta-sheet richness establish spectroscopic landscapes among subtypes of pancreatic cancer

Purpose: Knowledge about pancreatic cancer (PC) biology has been growing rapidly in recent decades. Nevertheless, the survival of PC patients has not greatly improved. The development of a novel methodology suitable for deep investigation of the nature of PC tumors is of great importance. Molecular imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman hyperspectral mapping (RHM) combined with advanced multivariate data analysis, were useful in studying the biochemical composition of PC tissue. Methods: Here, we evaluated the potential of molecular imaging in differentiating three groups of PC tumors, which originate from different precursor lesions. Specifically, we comprehensively investigated adenocarcinomas (ACs): conventional ductal AC, intraductal papillary mucinous carcinoma, and ampulla of Vater AC. FTIR microspectroscopy and RHM maps of 24 PC tissue slides were obtained, and comprehensive advanced statistical analyses, such as hierarchical clustering and nonnegative matrix factorization, were performed on a total of 211,355 Raman spectra. Additionally, we employed deep learning technology for the same task of PC subtyping to enable automation. The so-called convolutional neural network (CNN) was trained to recognize spectra specific to each PC group and then employed to generate CNN-prediction-based tissue maps. To identify the DNA methylation spectral markers, we used differently methylated, isolated DNA and compared the observed spectral differences with the results obtained from cellular nuclei regions of PC tissues. Results: The results showed significant differences among cancer tissues of the studied PC groups. The main findings are the varying content of β-sheet-rich proteins within the PC cells and alterations in the relative DNA methylation level. Our CNN model efficiently differentiated PC groups with 94% accuracy. The usage of CNN in the classification task did not require Raman spectral data preprocessing and eliminated the need for extensive knowledge of statistical methodologies. Conclusions: Molecular spectroscopy combined with CNN technology is a powerful tool for PC detection and subtyping. The molecular fingerprint of DNA methylation and β-sheet cytoplasmic proteins established by our results is different for the main PC groups and allowed the subtyping of pancreatic tumors, which can improve patient management and increase their survival. Our observations are of key importance in understanding the variability of PC and allow translation of the methodology into clinical practice by utilizing liquid biopsy testing

Clinical course and outcome of SARS-CoV-2 infection in multiple sclerosis patients treated with disease-modifying therapies — the Polish experience

Introduction. The aim of this study was to report the course and outcome of SARS-CoV-2 infection in multiple sclerosis (MS) patients treated with disease-modifying therapies (DMTs) in Poland. A major concern for neurologists worldwide is the course and outcome of SARS-CoV-2 infection in patients with MS treated with different DMTs. Although initial studies do not suggest an unfavourable course of infection in this group of patients, the data is limited.Materials and methods. This study included 396 MS patients treated with DMTs and confirmed SARS-CoV-2 infection from 28 Polish MS centres. Information concerning patient demographics, comorbidities, clinical course of MS, current DMT use, as well as symptoms of SARS-CoV-2 infection, need for pharmacotherapy, oxygen therapy, and/or hospitalisation, and short-term outcomes was collected up to 30 January 2021. Additional data about COVID-19 cases in the general population in Poland was obtained from official reports of the Polish Ministry of Health.Results. There were 114 males (28.8%) and 282 females (71.2%). The median age was 39 years (IQR 13). The great majority of patients with MS exhibited relapsing-remitting course (372 patients; 93.9%). The median EDSS was 2 (SD 1.38), and the mean disease duration was 8.95 (IQR 8) years. Most of the MS patients were treated with dimethyl fumarate (164; 41.41%). Other DMTs were less frequently used: interferon beta (82; 20.70%), glatiramer acetate (42; 10.60%), natalizumab (35;8.84%), teriflunomide (25; 6.31%), ocrelizumab (20; 5.05%), fingolimod (16; 4.04), cladribine (5; 1.26%), mitoxantrone (3; 0.76%), ozanimod (3; 0.76%), and alemtuzumab (1; 0.25%). The overall hospitalisation rate due to COVID-19 in the cohort was 6.81% (27 patients). Only one patient (0.3%) died due to SARS-CoV-2 infection, and three (0.76%) patients were treated with mechanical ventilation; 106 (26.8%) patients had at least one comorbid condition. There were no significant differences in the severity of SARS-CoV-2 infection regarding patient age, duration of the disease, degree of disability (EDSS), lymphocyte count, or type of DMT used.Conclusions and clinical implications. Most MS patients included in this study had a favourable course of SARS-CoV-2 infection. The hospitalisation rate and the mortality rate were not higher in the MS cohort compared to the general Polish population. Continued multicentre data collection is needed to increase the understanding of SARS-CoV-2 infection impact on the course of MS in patients treated with DMTs

Many Labs 5:Testing pre-data collection peer review as an intervention to increase replicability

Replication studies in psychological science sometimes fail to reproduce prior findings. If these studies use methods that are unfaithful to the original study or ineffective in eliciting the phenomenon of interest, then a failure to replicate may be a failure of the protocol rather than a challenge to the original finding. Formal pre-data-collection peer review by experts may address shortcomings and increase replicability rates. We selected 10 replication studies from the Reproducibility Project: Psychology (RP:P; Open Science Collaboration, 2015) for which the original authors had expressed concerns about the replication designs before data collection; only one of these studies had yielded a statistically significant effect (p < .05). Commenters suggested that lack of adherence to expert review and low-powered tests were the reasons that most of these RP:P studies failed to replicate the original effects. We revised the replication protocols and received formal peer review prior to conducting new replication studies. We administered the RP:P and revised protocols in multiple laboratories (median number of laboratories per original study = 6.5, range = 3?9; median total sample = 1,279.5, range = 276?3,512) for high-powered tests of each original finding with both protocols. Overall, following the preregistered analysis plan, we found that the revised protocols produced effect sizes similar to those of the RP:P protocols (?r = .002 or .014, depending on analytic approach). The median effect size for the revised protocols (r = .05) was similar to that of the RP:P protocols (r = .04) and the original RP:P replications (r = .11), and smaller than that of the original studies (r = .37). Analysis of the cumulative evidence across the original studies and the corresponding three replication attempts provided very precise estimates of the 10 tested effects and indicated that their effect sizes (median r = .07, range = .00?.15) were 78% smaller, on average, than the original effect sizes (median r = .37, range = .19?.50)