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.

     

Three-dimensional co-culture microfluidic model and its application for research on cancer stem-like cells inducing migration of endothelial cells

Objectives

To build a three-dimensional co-culture model in a microfluidic device for cancer research and evaluate its feasibility by investigating cancer stem-like cells (SCs) induced migration of human umbilical vein endothelial cells (ECs).

Results

The microfluidic device provided two-dimensional and three-dimensional (2D/3D) culture and co-culture environments without affecting cell viability. The device also provided an effective concentration for the chemiotaxis of cells, and to support real-time monitoring of cell behavior. In this model, SCs significantly increased the migration area of ECs with a hepatocarcinoma cell line (MHCC97H; MCs). The presence of ECs also induced both MCs and SCs invasion into Matrigel. The migration area of MCs and SCs significantly increased when co-cultured with ECs.

Conclusions

This 3D co-culture microfluidic model is a suitable model in cancer research. Compared with MCs, SCs had greater potential in inducing EC migration and interacting with ECs.

     

Novel microbial photobioelectrochemical cell using an invasive ultramicroelectrode array and a microfluidic chamber

Objective

To fabricate a novel microbial photobioelectrochemical cell using silicon microfabrication techniques.

Results

High-density photosynthetic cells were immobilized in a microfluidic chamber, and ultra-microelectrodes in a microtip array were inserted into the cytosolic space of the cells to directly harvest photosynthetic electrons. In this way, the microbial photobioelectrochemical cell operated without the aid of electron mediators. Both short circuit current and open circuit voltage of the microbial photobioelectrochemical cell responded to light stimuli, and recorded as high as 250 pA and 45 mV, respectively.

Conclusion

A microbial photobioelectrochemical cell was fabricated with potential use in next-generation photosynthesis-based solar cells and sensors.

     

Minimal variation of the plasma lipidome after delayed processing of neonatal cord blood

Background

Cord blood lipids are potential disease biomarkers. We aimed to determine if their concentrations were affected by delayed blood processing.

Method

Refrigerated cord blood from six healthy newborns was centrifuged every 12 h for 4 days. Plasma lipids were analysed by liquid chromatography/mass spectroscopy.

Results

Of 262 lipids identified, only eight varied significantly over time. These comprised three dihexosylceramides, two phosphatidylserines and two phosphatidylethanolamines whose relative concentrations increased and one sphingomyelin that decreased.

Conclusion

Delay in separation of plasma from refrigerated cord blood has minimal effect overall on the plasma lipidome.

     

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

Background

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening.

Results

Herein, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, and proteogenic and metabolic output analysis.

Conclusions

Taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Forecasting infectious disease emergence subject to seasonal forcing

Background

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models.

Methods

We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic.

Results

Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly.

Conclusions

Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Nonlinear analysis of biomagnetic signals recorded from uterine myomas

Objective

To determine if there is any non-linearity in the biomagnetic recordings of uterine myomas and to find any differences that may be present in the mechanisms underlying their signal dynamics.

Methods

Twenty-four women were included in the study. Sixteen of them were characterised with large myomas and 8 with small ones. Uterine artery waveform measurements were evaluated by use of Pulsatility Index (PI) (normal value PI<1.45).

Results

Applying nonlinear analysis to the biomagnetic signals of the uterine myomas, we observed a clear saturation value for the group of large ones (mean = 11.35 ± 1.49) and no saturation for the small ones.

Conclusion

The comparison of the saturation values in the biomagnetic recordings of large and small myomas may be a valuable tool in the evaluation of functional changes in their dynamic behavior.

     

Pig tissue factor pathway inhibitor α fusion immunoglobulin inhibits pig tissue factor activity in human plasma moderately more efficiently than the human counterpart

Objective

To determine the efficacy of soluble pig tissue factor pathway inhibitor fusion immunoglobulin (TFPI-Ig) in blocking pig to human xenogeneic blood coagulation.

Results

To generate pig TFPI-Ig or human TFPI-Ig, expression vector containing cDNA encoding pig TFPIα or human TFPIα combined with human constant Ig heavy chain region was cloned and introduced into CHO cells. After purification of pig TFPI-Ig and human TFPI-Ig, the inhibition of each recombinant protein on pig tissue factor (TF)-mediated blood coagulation was examined in human plasma. Compared to human TFPI-Ig, pig TFPI-Ig inhibited pig TF activity and thrombin generation in human plasma more efficiently at certain concentrations.

Conclusions

Pig TFPI-Ig will be be useful as a therapeutic protein to treat pig to human xenogeneic blood coagulation.

     

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Introduction

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

Objectives

In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

Methods

Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using ¹H nuclear magnetic resonance (¹H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

Results

The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

Conclusion

PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

     

Application of β-glucuronidase-immobilised silica gel formulation to microfluidic platform for biotransformation of β-glucuronides

Objective

To improve the efficiency of reactions of β-glucuronidase (GUS)-assisted glucuronic acid (GluA) removal within a microfluidic system.

Results

β-glucuronidase from Helix pomatia was immobilised and characterised in silica-based sol–gel monoliths. Efficiency of the GUS-doped silica monoliths was tested for hydrolysis of p-Nitrophenyl-β-d-glucuronide (pNP–GluA) in both ml-scaled medium via batch reactions and microfluidic environment via continuous-flow reactions. In the microfluidic platform, within a duration of 150 min of continuous operation (flow rate: 1 µL/min), the obtained highest pNP yield was almost 50% higher than that of the corresponding batchwise reaction. However, increased flow rates (3, 5, and 10 µL/min) resulted in lower conversion yields compared to 1 µL/min. The microfluidic platform demonstrated continuous hydrolytic activity for 7 days with considerable reaction yields while using a small amount of the enzyme.

Conclusion

These results revealed that usage of the microreactors has considerable potential to efficiently obtain bioactive GluA-free aglycons from various plant-derived β-glucuronides for pharmaceutical applications.

Graphical Abstract

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Buckyballs conjugated with nucleic acid sequences identifies microorganisms in live cell assays

Background

Rapid identification of bacteria can play an important role at the point of care, evaluating the health of the ecosystem, and discovering spatiotemporal distributions of a bacterial community. We introduce a method for rapid identification of bacteria in live cell assays based on cargo delivery of a nucleic acid sequence and demonstrate how a mixed culture can be differentiated using a simple microfluidic system.

Methods

C60 Buckyballs are functionalized with nucleic acid sequences and a fluorescent reporter to show that a diversity of microorganisms can be detected and identified in live cell assays. The nucleic acid complexes include an RNA detector, targeting a species-specific sequence in the 16S rRNA, and a complementary DNA with an attached fluorescent reporter. As a result, each bacterium can be detected and visualized at a specific emission frequency through fluorescence microscopy.

Results

The C60 probe complexes can detect and identify a diversity of microorganisms that include gram-position and negative bacteria, yeast, and fungi. More specifically, nucleic-acid probes are designed to identify mixed cultures of Bacillus subtilis and Streptococcus sanguinis, or Bacillus subtilis and Pseudomonas aeruginosa. The efficiency, cross talk, and accuracy for the C60 probe complexes are reported. Finally, to demonstrate that mixed cultures can be separated, a microfluidic system is designed that connects a single source-well to multiple sinks wells, where chemo-attractants are placed in the sink wells. The microfluidic system allows for differentiating a mixed culture.

Conclusions

The technology allows profiling of bacteria composition, at a very low cost, for field studies and point of care.

     

High-resolution mass spectrometry metabolomics of grape chemical markers to reveal use of not-allowed varieties in the production of Amarone and Recioto wines

Introduction

Grape varieties allowed to produce Amarone della Valpolicella and Recioto DOCG wines are strictly regulated by their disciplinary of production. These are Corvina Veronese and Corvinone grapes, to a lesser extent also Rondinella can be used. The use of other varieties, is not allowed.

Objectives

To identify chemical markers suitable to reveal addition of two not allowed grape varieties to the Corvina/Corvinone blend, such as Primitivo or Negro Amaro.

Methods

The identification of the secondary metabolites of the four grape varieties was conducted by high-resolution mass spectrometry (HRMS) metabolomics. By using the signals of these metabolites the indexes able to identify the presence of Primitivo or Negro Amaro grapes in the Corvina/Corvinone 1:1 blend were calculated.

Results

Indexes of laricitrin (Lr), delphinidin (Dp), and petunidin (Pt) signals were effective to identify the use of 10% Primitivo, while α-terpineol pentosyl-hexoside and linalool pentosyl-hexoside reveal the presence of Negro Amaro in the grape blend.

Conclusions

Varietal markers useful to detect the presence of Primitivo and Negro Amaro in the grape blend were identified by HRMS metabolomics, a method suitable to check the identity of grapes on arrival at the winery, as well as the fermenting musts. The effectiveness of the identified markers in the final wines have to be confirmed. Potentially, a similar approach can be used to reveal analogous frauds performed on other high-quality wines.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Metabolomics approach for predicting response to neoadjuvant chemotherapy for colorectal cancer

Introduction

Colorectal cancer (CRC) is a clinically heterogeneous disease, which necessitates a variety of treatments and leads to different outcomes. Only some CRC patients will benefit from neoadjuvant chemotherapy (NACT).

Objectives

An accurate prediction of response to NACT in CRC patients would greatly facilitate optimal personalized management, which could improve their long-term survival and clinical outcomes.

Methods

In this study, plasma metabolite profiling was performed to identify potential biomarker candidates that can predict response to NACT for CRC. Metabolic profiles of plasma from non-response (n?=?30) and response (n?=?27) patients to NACT were studied using UHPLC–quadruple time-of-flight)/mass spectrometry analyses and statistical analysis methods.

Results

The concentrations of nine metabolites were significantly different when comparing response to NACT. The area under the receiver operating characteristic curve value of the potential biomarkers was up to 0.83 discriminating the non-response and response group to NACT, superior to the clinical parameters (carcinoembryonic antigen and carbohydrate antigen 199).

Conclusion

These results show promise for larger studies that could result in more personalized treatment protocols for CRC patients.

     

Differential elemental uptake in three pseudo-metallophyte C<Subscript>4</Subscript> grasses in situ in the eastern USA

Background and aims

Elemental uptake in serpentine floras in eastern North America is largely unknown. The objective of this study was to determine major and trace element concentrations in soil and leaves of three native pseudo-metallophyte C₄ grasses in situ at five sites with three very different soil types, including three serpentine sites, in eastern USA.

Methods

Pseudo-total and extractible concentrations of 15 elements were measured and correlated from the soils and leaves of three species at the five sites.

Results

Element concentrations in soils of pseudo-metallophytes varied up to five orders of magnitude. Soils from metalliferous sites exhibited higher concentrations of their characteristic elements than non-metalliferous. In metallicolous populations, elemental concentrations depended on the element. Concentrations of major elements (Ca, Mg, K) in leaves were lower than typical toxicity thresholds, whereas concentrations of Zn were higher.

Conclusions

In grasses, species can maintain relatively low metal concentrations in their leaves even when soil concentrations are richer. However, in highly Zn-contaminated soil, we found evidence of a threshold concentration above which Zn uptake increases drastically. Finally, absence of main characteristics of serpentine soil at one site indicated the importance of soil survey and restoration to maintain serpentinophytes communities and avoid soil encroachment.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.