Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

TREM2 deficiency exacerbates tau pathology through dysregulated kinase signaling in a mouse model of tauopathy

Background

Genetic variants of the Triggering Receptor Expressed on Myeloid Cells-2 (TREM2) confer increased risk of developing late-onset Alzheimer’s Disease (LOAD) and other neurodegenerative disorders. Recent studies provided insight into the multifaceted roles of TREM2 in regulating extracellular β-amyloid (Aβ) pathology, myeloid cell accumulation, and inflammation observed in AD, yet little is known regarding the role of TREM2 in regulating intracellular microtubule associated protein tau (MAPT; tau) pathology in neurodegenerative diseases and in AD, in particular.

Results

Here we report that TREM2 deficiency leads to accelerated and exacerbated hyperphosphorylation and aggregation of tau in a humanized mouse model of tauopathy. TREM2 deficiency also results, indirectly, in dramatic widespread dysregulation of neuronal stress kinase pathways.

Conclusions

Our results suggest that deficiency of microglial TREM2 leads to heightened tau pathology coupled with widespread increases in activated neuronal stress kinases. These findings offer new insight into the complex, multiple roles of TREM2 in regulating Aβ and tau pathologies.

     

CrypticIBDcheck: an R package for checking cryptic relatedness in nominally unrelated individuals

Background

In population association studies, standard methods of statistical inference assume that study subjects are independent samples. In genetic association studies, it is therefore of interest to diagnose undocumented close relationships in nominally unrelated study samples.

Results

We describe the R package CrypticIBDcheck to identify pairs of closely-related subjects based on genetic marker data from single-nucleotide polymorphisms (SNPs). The package is able to accommodate SNPs in linkage disequibrium (LD), without the need to thin the markers so that they are approximately independent in the population. Sample pairs are identified by superposing their estimated identity-by-descent (IBD) coefficients on plots of IBD coefficients for pairs of simulated subjects from one of several common close relationships.

Conclusions

The methods implemented in CrypticIBDcheck are particularly relevant to candidate-gene association studies, in which dependent SNPs cluster in a relatively small number of genes spread throughout the genome. The accommodation of LD allows the use of all available genetic data, a desirable property when working with a modest number of dependent SNPs within candidate genes. CrypticIBDcheck is available from the Comprehensive R Archive Network (CRAN).

     

Metabolic profiling of <Emphasis Type="Italic">Daphnia magna</Emphasis> exposed to environmental stressors by GC–MS and chemometric tools

Introduction

Climate change is a major concern for the scientific community, demanding novel information about the effects of environmental stressors on living organisms. Metabolic profiling is required for achieving the most extensive possible range of compounds and their concentration changes on stressed conditions.

Objectives

Individuals of the crustacean species Daphnia magna were exposed to three different abiotic factors linked to global climate change: high salinity, high temperature levels and hypoxia. Advanced chemometric tools were used to characterize the metabolites affected by the exposure.

Method

An exploratory analysis of gas chromatography-mass spectrometry (GC–MS) data was performed to discriminate between control and exposed daphnid samples. Due to the complexity of these GC–MS data sets, a comprehensive untargeted analysis of the full scan data was performed using multivariate curve resolution-alternating least squares (MCR-ALS) method. This approach enabled to resolve most of the metabolite signals from interference peaks caused by derivatization reactions. Metabolites with significant changes in their peak areas were tentatively identified and the involved metabolic pathways explored.

Results

D. magna metabolic biomarkers are proposed for the considered physical factors. Metabolites related with energy metabolic pathways including some amino acids, carbohydrates, organic acids and nucleosides were identified as potential biomarkers of the investigated treatments.

Conclusions

The proposed untargeted GC–MS metabolomics strategy and multivariate data analysis tools were useful to investigate D. magna metabolome under environmental stressed conditions.

     

Metabolomics-guided analysis of isocoumarin production by <Emphasis Type="Italic">Streptomyces</Emphasis> species MBT76 and biotransformation of flavonoids and phenylpropanoids

Introduction

Actinomycetes produce the majority of the antibiotics currently in clinical use. The efficiency of antibiotic production is affected by multiple factors such as nutrients, pH, temperature and growth phase. Finding the optimal harvesting time is crucial for successful isolation of the desired bioactive metabolites from actinomycetes, but for this conventional chemical analysis has limitations due to the metabolic complexity.

Objectives

This study explores the utility of NMR-based metabolomics for (1) optimizing fermentation time for the production of known and/or unknown bioactive compounds produced by actinomycetes; (2) elucidating the biosynthetic pathway for microbial natural products; and (3) facilitating the biotransformation of nature-abundant chemicals.

Method

The aqueous culture broth of actinomycete Streptomyces sp. MBT76 was harvested every 24 h for 5 days and each broth was extracted by ethyl acetate. The extracts were analyzed by ¹H NMR spectroscopy and the data were compared with principal component analysis (PCA) and orthogonal projection to latent structures (OPLS) analysis. Antimicrobial test were performed by agar diffusion assay.

Results

The secondary metabolites production by Streptomyces sp. MBT76 was growth phase-dependent. Isocoumarins (1–9), undecylprodiginine (10), streptorubin B (11), 1H-pyrrole-2-carboxamide (12), acetyltryptamine (13), and fervenulin (14) were identified, and their optimal production time was determined in crude extracts without tedious chromatographic fractionation. Of these compounds, 5,6,7,8-tetramethoxyl-3-methyl-isocoumarin (9) is as a novel compound, which was most likely synthesized by a type I iterative polyketide synthase (PKS) encoded by the icm gene cluster. Multivariate data analysis of the ¹H NMR spectra showed that acetyltryptamine (13) and tri-methoxylated isocoumarins (7 and 8) were the major determinants of antibiotic activity during later time points. The methoxylation was exploited to allow bioconversion of exogenously added genistein into a suite of methoxylated isoflavones (15–18). Methoxylation increased the antimicrobial efficacy of isocoumarins, but decreased that of the isoflavones.

Conclusion

Our results show the applicability of NMR-based metabolic profiling to streamline microbial biotransformation and to determine the optimal harvesting time of actinomycetes for antibiotic production.

     

A context-free encoding scheme of protein sequences for predicting antigenicity of diverse influenza A viruses

Background

The evolution of influenza A viruses leads to the antigenic changes. Serological diagnosis of the antigenicity is usually labor-intensive, time-consuming and not suitable for early-stage detection. Computational prediction of the antigenic relationship between emerging and old strains of influenza viruses using viral sequences can facilitate large-scale antigenic characterization, especially for those viruses requiring high biosafety facilities, such as H5 and H7 influenza A viruses. However, most computational models require carefully designed subtype-specific features, thereby being restricted to only one subtype.

Methods

In this paper, we propose a Context-FreeEncoding Scheme (CFreeEnS) for pairs of protein sequences, which encodes a protein sequence dataset into a numeric matrix and then feeds the matrix into a downstream machine learning model. CFreeEnS is not only free from subtype-specific selected features but also able to improve the accuracy of predicting the antigenicity of influenza. Since CFreeEnS is subtype-free, it is applicable to predicting the antigenicity of diverse influenza subtypes, hopefully saving the biologists from conducting serological assays for highly pathogenic strains.

Results

The accuracy of prediction on each subtype tested (A/H1N1, A/H3N2, A/H5N1, A/H9N2) is over 85%, and can be as high as 91.5%. This outperforms existing methods that use carefully designed subtype-specific features. Furthermore, we tested the CFreeEnS on the combined dataset of the four subtypes. The accuracy reaches 84.6%, much higher than the best performance 75.1% reported by other subtype-free models, i.e. regional band-based model and residue-based model, for predicting the antigenicity of influenza. Also, we investigate the performance of CFreeEnS when the model is trained and tested on different subtypes (i.e. transfer learning). The prediction accuracy using CFreeEnS is 84.3% when the model is trained on the A/H1N1 dataset and tested on the A/H5N1, better than the 75.2% using a regional band-based model.

Conclusions

The CFreeEnS not only improves the prediction of antigenicity on datasets with only one subtype but also outperforms existing methods when tested on a combined dataset with four subtypes of influenza viruses.

     

Quinic acid derivatives inhibit dengue virus replication in vitro

Background

Dengue is the most prevalent arboviral disease in tropical and sub-tropical areas of the world. The incidence of infection is estimated to be 390 million cases and 25,000 deaths per year. Despite these numbers, neither a specific treatment nor a preventive vaccine is available to protect people living in areas of high risk.

Results

With the aim of seeking a treatment that can mitigate dengue infection, we demonstrated that the quinic acid derivatives known as compound 2 and compound 10 were effective against all four dengue virus serotypes and safe for use in a human hepatoma cell line (Huh7.5). Both compounds were non-virucidal to dengue virus particles and did not interfere with early steps of the dengue virus life cycle, including binding and internalization. Experiments using a replicon system demonstrated that compounds 2 and 10 impaired dengue virus replication in Huh7.5 cells. Additionally, the anti-dengue virus effects of the quinic acid derivatives were preserved in human peripheral blood mononuclear cells.

Conclusions

Taken together, these data suggest that quinic acid derivatives represent a novel chemical class of active compounds that could be used to combat dengue virus infection.

     

Volatile organic compounds (VOCs) drive nutrient foraging in the clonal woodland strawberry, <Emphasis Type="Italic">Fragaria vesca</Emphasis>

Background and Aims

It was previously demonstrated that stolons of Fragaria vesca respond to patches of varying nutrient quality; however, the mechanism of patch-detection remained unknown. Here we provide support for a process by which F. vesca perceives nutrient-rich patches, consistent with nutrient foraging prior to rooting.

Methods

Volatile organic compounds (VOCs) emitted from unsterilized and sterilized field substrates were collected and analyzed by stir-bar headspace extraction gas chromatography-mass spectrometry using a method modified for soil and litter systems. Selected compounds were chosen to represent unsterilized and sterilized field substrates. These synthetic volatile compound mixtures were then applied to neutral substrate to test the ability of F. vesca to choose between unsterilized versus sterilized substrates.

Results

Primary stolons exhibited chemotropism towards unsterilized (natural) substrates and grew away from the sterilized volatile substrates when the alternate choice was a negative control. We conclude that the presence of carboxylic acids tends to stimulate stolon elongation and chemotropism while aldehydes, ketones and monoterpenes tend to suppress it.

Conclusions

We provide evidence that developing stolons of F. vesca forage for nutrient-rich patches via volatile cues similar to those emitted from the soil through microflora activity.

     

An empirical comparison of knowledge and skill in the context of traditional ecological knowledge

Background

We test whether traditional ecological knowledge (TEK) about how to make an item predicts a person’s skill at making it among the Tsimane’ (Bolivia). The rationale for this research is that the failure to distinguish between knowledge and skill might account for some of the conflicting results about the relationships between TEK, human health, and economic development.

Methods

We test the association between a commonly-used measure of individual knowledge (cultural consensus analysis) about how to make an arrow or a bag and a measure of individual skill at making these items, using ordinary least-squares regression. The study consists of 43 participants from 3 villages.

Results

We find no association between our measures of knowledge and skill (core model, p?>?0.5,?R ² ?=?.132).

Conclusions

While we cannot rule out the possibility of a real association between these phenomena, we interpret our findings as support for the claim that researchers should distinguish between methods to measure knowledge and skill when studying trends in TEK.

     

Design,molecular docking,synthesis, characterization,biological activity evaluation (against MES model), <Emphasis Type="Italic">in-silico</Emphasis> biological activity spectrum (PASS analysis), toxicological and predicted oral rat LD<Subscript>50</Subscript> studies of novel sulphonamide derivatives

Background

Among the reported potential agents to treat the epilepsy, sulphonamides are important and their significance cannot be ignored. A series of substituted 4-amino-benzene sulfonamides were designed, keeping in view the structural requirement of pharmacophore.

Methods

Lipinski rule of five has been calculated; failure to Lipinski rule was not observed. Docking was performed through AutoDock Vina. Molecules have been screened out through docking. Compounds were synthesized and characterized through IR, ¹HNMR, ¹³C NMR, Mass and elemental analysis. The anticonvulsant activity of the synthesized compounds was assessed using the Maximal Electroshock Seizure (MES) model. In-silico biological activity spectrum, toxicological studies, predicted oral rats LD50 were performed.

Results

Docking studies showed good interaction with lyase (Oxo-acid) - human carbonic anhydrase-I (1AZM). The in-silico studies proved them to be with good drug-likeness properties, especially 4-(3-Acetyl-phenylamino)-methyl)-benzenesulfonamide (2g). These results revealed that the synthesized compounds (1a-1c, 2a-2q) exhibited promising anticonvulsant effect against MES model for inhibition of Lyase- Human Carbonic Anhydrase-I.

Conclusion

After investigating all the results, the compound 4-(3-Acetyl-phenylamino)-methyl)-benzenesulfonamide (2g) is found to be best in the series. A comparatively good activity of compound 2g suggests us that sulphonamide can be leads to further optimization for building potent and chemically diversified anti-convulsant agents.

     

Highly enantioselective production of a chiral intermediate of sitagliptin by a novel isolate of <Emphasis Type="Italic">Pseudomonas pseudoalcaligenes</Emphasis>

Objective

To produce (S)-3-hydroxy-1-(3-(trifluoromethyl)-5,6-dihydro[1,2,4]triazolo[4,3-a]pyrazin-7(8H)-yl]-4-(2,4,5-trifluorophenyl)butan-1-one (S)-1 from 4-oxo-4-[3-(trifluoromethyl)-5,6-dihydro [1,2,4]triazolo[4,3-a]pyrazin-7(8H)-yl)-1-(2,4,5-trifluorophenyl)butan-2-one (2) by microbial bioreduction.

Results

A new isolate of Pseudomonas pseudoalcaligenes reduced enantioselectively prochiral ketone 2 to chiral alcohol (S)-1. Whole cells of the bacterium were tolerant towards 20 % (v/v) DMSO and 10 g 2/l. Under the optimal conditions, the preparative-scale bioreduction yielded (S)-1 at 90 % yield and >99 % ee. Cells could be re-used with the yield and ee of product being 45 % and >99 %, respectively, after five cycles.

Conclusion

Bioreduction using whole cells of P. pseudoalcaligenes is an attractive approach to produce (S)-1, as a chiral intermediate of the anti-diabetic drug, sitagliptin.

     

Substantial fibrin amyloidogenesis in type 2 diabetes assessed using amyloid-selective fluorescent stains

Background

We have previously shown that many chronic, inflammatory diseases are accompanied, and possibly partly caused or exacerbated, by various coagulopathies, manifested as anomalous clots in the form of ‘dense matted deposits’. More recently, we have shown that these clots can be amyloid in nature, and that the plasma of healthy controls can be induced to form such clots by the addition of tiny amounts of bacterial lipopolysaccharide or lipoteichoic acid. Type 2 diabetes (T2D) is also accompanied by raised levels of LPS.

Methods

We use superresolution and confocal microscopies to investigate the amyloid nature of clots from healthy and T2D individuals.

Results

We show here, with the established stain thioflavin T and the novel stains Amytracker? 480 and 680, that the clotting of plasma from type 2 diabetics is also amyloid in nature, and that this may be prevented by the addition of suitable concentrations of LPS-binding protein.

Conclusion

This implies strongly that there is indeed a microbial component to the development of type 2 diabetes, and suggests that LBP might be used as treatment for it and its sequelae.

     

Mangrove root: adaptations and ecological importance

Key message

This review gives a comprehensive overview of adaptations of mangrove root system to the adverse environmental conditions and summarizes the ecological importance of mangrove root to the ecosystem.

Abstract

In plants, the first line of defense against abiotic stress is in their roots. If the soil surrounding the plant root is healthy and biologically diverse, the plant will have a higher chance to survive in stressful conditions. Different plant species have unique adaptations when exposed to a variety of abiotic stress conditions. None of the responses are identical, even though plants have become adapted to the exact same environment. Mangrove plants have developed complex morphological, anatomical, physiological, and molecular adaptations allowing survival and success in their high-stress habitat. This review briefly depicts adaptive strategies of mangrove roots with respect to anatomy, physiology, biochemistry and also the major advances recently made at the genetic and genomic levels. Results drawn from the different studies on mangrove roots have further indicated that specific patterns of gene expression might contribute to adaptive evolution of mangroves under high salinity. We also review crucial ecological contributions provided by mangrove root communities to the ecosystem including marine fauna.

     

Genetic diversity of <Emphasis Type="Italic">Escherichia coli</Emphasis> in gut microbiota of patients with Crohn’s disease discovered using metagenomic and genomic analyses

Background

Crohn’s disease is associated with gut dysbiosis. Independent studies have shown an increase in the abundance of certain bacterial species, particularly Escherichia coli with the adherent-invasive pathotype, in the gut. The role of these species in this disease needs to be elucidated.

Methods

We performed a metagenomic study investigating the gut microbiota of patients with Crohn’s disease. A metagenomic reconstruction of the consensus genome content of the species was used to assess the genetic variability.

Results

The abnormal shifts in the microbial community structures in Crohn’s disease were heterogeneous among the patients. The metagenomic data suggested the existence of multiple E. coli strains within individual patients. We discovered that the genetic diversity of the species was high and that only a few samples manifested similarity to the adherent-invasive varieties. The other species demonstrated genetic diversity comparable to that observed in the healthy subjects. Our results were supported by a comparison of the sequenced genomes of isolates from the same microbiota samples and a meta-analysis of published gut metagenomes.

Conclusions

The genomic diversity of Crohn’s disease-associated E. coli within and among the patients paves the way towards an understanding of the microbial mechanisms underlying the onset and progression of the Crohn’s disease and the development of new strategies for the prevention and treatment of this disease.

     

Rhizosphere processes induce changes in dissimilatory iron reduction in a tidal marsh soil: a rhizobox study

Background and aims

Although the role of microbial iron respiration in tidal marshes has been recognized for decades, the effect of rhizosphere processes on dissimilatory ferric iron reduction (FeR) is poorly known. Herein, we examined the FeR surrounding the root zone of three tidal marsh plants.

Methods

Using in situ rhizoboxes, we accurately separated rhizobox soil as one rhizosphere zone, and three bulk soil zones. Dissimilatory and sulfidic-mediated FeR were quantified by accumulation of non-sulfidic Fe(II) and Fe sulfides over time, respectively.

Results

The rates of dissimilatory FeR attained 42.5 μmol Fe g^?1 d^?1 in the rhizosphere, and logarithmically declined by up to 19.1 μmol Fe g^?1 d^?1 in the outer bulk soil. The rates of sulfidic-mediated FeR were less than 2 μmol Fe g^?1 d^?1 among all zones. Poorly crystalline Fe(III), DOC and DON, porewater Fe²⁺, and SO₄^2? were all enriched in the rhizosphere, whereas non-sulfidic Fe(II) and Fe sulfides gradually accumulated away from the roots. Iron reducers (Geobacter, Bacillus, Shewanella, and Clostridium) had higher populations in the rhizosphere than in the bulk soil. Higher rates of dissimilatory FeR were observed in the Phragmites australis and Spartina alterniflora rhizoboxes than in the Cyperus malaccensis rhizoboxes.

Conclusions

The radial change pattern of dissimilatory FeR rates were determined by allocation of poorly crystalline Fe(III) and dissolved organic carbon. The interspecies difference of rhizosphere dissimilatory FeR was associated with the root porosity and aerenchyma of the tidal marsh plants.

     

High efficiency of targeted mutagenesis in arabidopsis via meiotic promoter-driven expression of Cas9 endonuclease

Key message

The use of a meiosis I-specific promoter increased the efficiency of targeted mutagenesis and will facilitate the manipulation of homologous recombination.

Abstract

The CRISPR/Cas9 system has been harnessed for targeted engineering of eukaryotic genomes, including plants; however, CRISPR/Cas9 efficiency varies considerably in different plant tissues and species. In Arabidopsis, the generation of homozygous or bi-allelic mutants in the first (T1) generation is inefficient. Here, we used specific promoters to drive the expression of Cas9 during meiosis to maximize the efficiency of recovering heritable mutants in T1 plants. Our data reveal that the use of a promoter active in meiosis I resulted in high-efficiency (28 %) recovery of targeted mutants in the T1 generation. Moreover, this method enabled efficient simultaneous targeting of three genes for mutagenesis. Taken together, our results show that the use of meiosis-specific promoters will improve methods for functional genomic analysis and studying the molecular underpinnings of homologous recombination.

     

Anti-BCMA CAR-T cells for treatment of plasma cell dyscrasia: case report on POEMS syndrome and multiple myeloma

Background

POEMS (polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy, and skin changes) syndrome still has no standard treatment. On the basis that both POEMS syndrome and myeloma have an underlying plasma cell dyscrasia, anti-myeloma therapy can be expected to be useful for POEMS syndrome. Chimeric antigen receptor T (CAR-T) cells targeting B cell maturation antigen (BCMA) has been used in the treatment of relapsed and refractory multiple myeloma (RRMM). No POEMS syndrome cases treated with anti-BCMA CAR-T cells have been reported.

Case presentation

Here, we, for the first time, report a POEMS syndrome case treated with anti-BCMA CAR-T cells. A 49-year-old female with incapacitating POEMS syndrome that progressed on lenalidomide treatment was enrolled in a phase I study involving anti-BCMA CAR-T cells (ChiCTR-OPC-16009113). Another patient with RRMM who had undergone six prior lines treatments was also enrolled in the study. They received infusions of anti-BCMA CAR-T cells. Both patients achieved a stringent complete response. Complete remission persisted in the patient with POEMS syndrome and lasted for 7.6 months before a relapse in RRMM patient. Both patients had toxicity consistent with the grade 1 cytokine release syndrome.

Conclusions

This is the first report of treatment by anti-BCMA CAR-T cells in POEMS syndrome. Our findings demonstrate the anti-BCMA CAR-T cell treatment may be a feasible therapeutic option for patients with POEMS syndrome and RRMM who do not respond well to traditional therapies.

Trial registration

ChiCTR-OPC, ChiCTR-OPC-16009113. Registered 29 August 2016.

     

Assessment of urban microbiome assemblies with the help of targeted in silico gold standards

Background

Microbial communities play a crucial role in our environment and may influence human health tremendously. Despite being the place where human interaction is most abundant we still know little about the urban microbiome. This is highlighted by the large amount of unclassified DNA reads found in urban metagenome samples. The only in silico approach that allows us to find unknown species, is the assembly and classification of draft genomes from a metagenomic dataset. In this study we (1) investigate the applicability of an assembly and binning approach for urban metagenome datasets, and (2) develop a new method for the generation of in silico gold standards to better understand the specific challenges of such datasets and provide a guide in the selection of available software.

Results

We applied combinations of three assembly (Megahit, SPAdes and MetaSPAdes) and three binning tools (MaxBin, MetaBAT and CONCOCT) to whole genome shotgun datasets from the CAMDA 2017 Challenge. Complex in silico gold standards with a simulated bacterial fraction were generated for representative samples of each surface type and city. Using these gold standards, we found the combination of SPAdes and MetaBAT to be optimal for urban metagenome datasets by providing the best trade-off between the number of high-quality genome draft bins (MIMAG standards) retrieved, the least amount of misassemblies and contamination. The assembled draft genomes included known species like Propionibacterium acnes but also novel species according to respective ANI values.

Conclusions

In our work, we showed that, even for datasets with high diversity and low sequencing depth from urban environments, assembly and binning-based methods can provide high-quality genome drafts. Of vital importance to retrieve high-quality genome drafts is sequence depth but even more so a high proportion of the bacterial sequence fraction too achieve high coverage for bacterial genomes. In contrast to read-based methods relying on database knowledge, genome-centric methods as applied in this study can provide valuable information about unknown species and strains as well as functional contributions of single community members within a sample. Furthermore, we present a method for the generation of sample-specific highly complex in silico gold standards.

Reviewers

This article was reviewed by Craig Herbold, Serghei Mangul and Yana Bromberg.