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.

     

Modification of fatty acid selectivity of <Emphasis Type="Italic">Candida antarctica</Emphasis> lipase A by error-prone PCR

Objective

To generate Candida antarctica lipase A (CAL-A) mutants with modified fatty acid selectivities and improved lipolytic activities using error-prone PCR (epPCR).

Results

A Candida antarctica lipase A mutant was obtained in three rounds of epPCR. This mutant showed a 14 times higher ability to hydrolyze triacylglycerols containing conjugated linoleic acids, and was 12 and 14 times more selective towards cis-9, trans-11 and trans-10, cis-12 isomers respectively, compared to native lipase. Lipolytic activities towards fatty acid esters were markedly improved, in particular towards butyric, lauric, stearic and palmitic esters.

Conclusion

Directed molecular evolution is an efficient method to generate lipases with desirable selectivity towards CLA isomers and improved lipolytic activities towards esters of fatty acids.

     

Biotherapeutic protein formulation variables influence protein integrity and can promote post-translational modifications as shown using chicken egg white lysozyme as a model system

Objectives

The effect of different formulations variables on protein integrity were investigated using lysozyme as a model protein for the development of biotherapeutic protein formulations for use in the clinic.

Results

Buffer composition/concentration was the key variable of formulation reagents investigated in determining lysozyme stability and authenticity independent of protein concentration whilst the storage temperature and time, not surprisingly, were also key variables. Tryptic peptide mapping of the protein showed that the modifications occurred when formulated under specific conditions but not others. A model peptide system was developed that reflected the same behavior under formulation conditions as intact lysozyme.

Conclusions

Peptide models may mirror the stability of proteins, or regions of proteins, in the same formulations and be used to help develop a rapid screen of formulations for stabilisation of biotherapeutic proteins.

     

Tissue-engineered smooth muscle cell and endothelial progenitor cell bi-level cell sheets prevent progression of cardiac dysfunction,microvascular dysfunction,and interstitial fibrosis in a rodent model of type 1 diabetes-induced cardiomyopathy

Background

Diabetes mellitus is a risk factor for coronary artery disease and diabetic cardiomyopathy, and adversely impacts outcomes following coronary artery bypass grafting. Current treatments focus on macro-revascularization and neglect the microvascular disease typical of diabetes mellitus-induced cardiomyopathy (DMCM). We hypothesized that engineered smooth muscle cell (SMC)-endothelial progenitor cell (EPC) bi-level cell sheets could improve ventricular dysfunction in DMCM.

Methods

Primary mesenchymal stem cells (MSCs) and EPCs were isolated from the bone marrow of Wistar rats, and MSCs were differentiated into SMCs by culturing on a fibronectin-coated dish. SMCs topped with EPCs were detached from a temperature-responsive culture dish to create an SMC-EPC bi-level cell sheet. A DMCM model was induced by intraperitoneal streptozotocin injection. Four weeks after induction, rats were randomized into 3 groups: control (no DMCM induction), untreated DMCM, and treated DMCM (cell sheet transplant covering the anterior surface of the left ventricle).

Results

SMC-EPC cell sheet therapy preserved cardiac function and halted adverse ventricular remodeling, as demonstrated by echocardiography and cardiac magnetic resonance imaging at 8 weeks after DMCM induction. Myocardial contrast echocardiography demonstrated that myocardial perfusion and microvascular function were preserved in the treatment group compared with untreated animals. Histological analysis demonstrated decreased interstitial fibrosis and increased microvascular density in the SMC-EPC cell sheet-treated group.

Conclusions

Treatment of DMCM with tissue-engineered SMC-EPC bi-level cell sheets prevented cardiac dysfunction and microvascular disease associated with DMCM. This multi-lineage cellular therapy is a novel, translatable approach to improve microvascular disease and prevent heart failure in diabetic patients.

     

Statin resistance in <Emphasis Type="Italic">Candida glabrata</Emphasis>

Objectives

Reduced efficacy of statins has been observed in people but the mechanism of this resistance is unclear and no statin-resistance mutations in the catalytic domain of HMGCR have been reported. The present study focused on looking for statin-resistance mutations and examining the mechanism of statin resistance using Candida glabrata as a model organism.

Results

C. glabrata was cultured in media containing lovastatin, simvastatin or atorvastatin to obtain lovastatin-, simvastatin- and atorvastatin-resistant mutants. A single mutant from each was purified for further analysis. In each mutant, gene sequencing showed there were no changes in the catalytic domain of HMGCR. HMGCR was overexpressed in two resistant isolates suggesting that increased production of HMGCR can lead to resistance. In a third mutant, HMGCR activity was unaltered, suggesting a non-HMGCR related mechanism, such as increased drug efflux, could be operating.

Conclusions

Candida glabrata is a useful model organism for examining resistance to statins. Further studies are warranted to examine the precise molecular mechanisms of statin resistance.

     

Metabolic engineering of <Emphasis Type="Italic">Klebsiella pneumoniae</Emphasis> and in silico investigation for enhanced 2,3-butanediol production

Objectives

To improve the production of 2,3-butanediol (2,3-BD) in Klebsiella pneumoniae, the genes related to the formation of lactic acid, ethanol, and acetic acid were eliminated.

Results

Although the cell growth and 2,3-BD production rates of the K. pneumoniae ΔldhA ΔadhE Δpta-ackA strain were lower than those of the wild-type strain, the mutant produced a higher titer of 2,3-BD and a higher yield in batch fermentation: 91 g 2,3-BD/l with a yield of 0.45 g per g glucose and a productivity of 1.62 g/l.h in fed-batch fermentation. The metabolic characteristics of the mutants were consistent with the results of in silico simulation.

Conclusions

K. pneumoniae knockout mutants developed with an aid of in silico investigation could produce higher amounts of 2,3-BD with increased titer, yield, and productivity.

     

Regioselective C-H hydroxylation of omeprazole sulfide by <Emphasis Type="Italic">Bacillus megaterium</Emphasis> CYP102A1 to produce a human metabolite

Objectives

To find a simple enzymatic strategy for the efficient synthesis of the expensive 5′-hydroxyomeprazole sulfide, a recently identified minor human metabolite, from omeprazole sulfide, which is an inexpensive substrate.

Results

The practical synthetic strategy for the 5′-OH omeprazole sulfide was accomplished with a set of highly active CYP102A1 mutants, which were obtained by blue colony screening from CYP102A1 libraries with a high conversion yield. The mutant and even the wild-type enzyme of CYP102A1 catalyzed the high regioselective (98 %) C-H hydroxylation of omeprazole sulfide to 5′-OH omeprazole sulfide with a high conversion yield (85–90 %).

Conclusions

A highly efficient synthesis of 5′-OH omeprazole sulfide was developed using CYP102A1 from Bacillus megaterium as a biocatalyst.

     

Generation of lycopene-overproducing strains of the fungus <Emphasis Type="Italic">Mucor circinelloides</Emphasis> reveals important aspects of lycopene formation and accumulation

Objectives

To generate lycopene-overproducing strains of the fungus Mucor circinelloides with interest for industrial production and to gain insight into the catalytic mechanism of lycopene cyclase and regulatory process during lycopene overaccumulation.

Results

Three lycopene-overproducing mutants were generated by classic mutagenesis techniques from a β-carotene-overproducing strain. They carried distinct mutations in the carRP gene encoding lycopene cyclase that produced loss of enzymatic activity to different extents. In one mutant (MU616), the lycopene cyclase was completely destroyed, and a 43.8% (1.1 mg/g dry mass) increase in lycopene production was observed in comparison to that by the previously existing lycopene overproducer. In addition, feedback regulation of the end product was suggested in lycopene-overproducing strains.

Conclusions

A lycopene-overaccumulating strain of the fungus M. circinelloides was generated that could be an alternative for the industrial production of lycopene. Vital catalytic residues for lycopene cyclase activity and the potential mechanism of lycopene formation and accumulation were identified.

     

Accumulation of Fascin<Superscript>+</Superscript> cells during experimental autoimmune neuritis

Background

Experimental autoimmune neuritis (EAN) is a well-known animal model of human demyelinating polyneuropathies and is characterized by inflammation and demyelination in the peripheral nervous system. Fascin is an evolutionarily highly conserved cytoskeletal protein of 55 kDa containing two actin binding domains that cross-link filamentous actin to hexagonal bundles.

Methods

Here we have studied by immunohistochemistry the spatiotemporal accumulation of Fascin?+?cells in sciatic nerves of EAN rats.

Results

A robust accumulation of Fascin?+?cell was observed in the peripheral nervous system of EAN which was correlated with the severity of neurological signs in EAN.

Conclusion

Our results suggest a pathological role of Fascin in EAN.

Virtual slides

The virtual slides for this article can be found here: http://www.diagnosticphatology.diagnomx.eu/vs/6734593451114811

     

ClpXP affects the cell metabolism of <Emphasis Type="Italic">Salmonella typhimurium</Emphasis> partially in an RpoS-dependent manner

Introduction

ClpXP protease is an important proteolytic system in Salmonella enterica serovar typhimurium (S. typhimurium). Inactivation of ClpXP by deletion of clpP resulted in overproduction of RpoS and a growth defect phenotype. Only one report has indicated that deleting rpoS can restore the growth of a S. typhimurium clpP mutant to the wild-type level. Whether overproduction of RpoS is responsible for the growth deficiency resulting from clpP disruption and how ClpXP affects the cell metabolism of S. typhimurium remain to be elucidated.

Objectives

The aim of this study is to investigate the effect of ClpXP on cell metabolism of S. typhimurium and explore the possible co-effect of RpoS associated with ClpXP in cell metabolism.

Method

We constructed a clpP rpoS double deletion mutant TT-19 (ΔclpP ΔrpoS TT-1) using a two-step phage transduction technique. We then compared the metabolite fingerprints of Salmonella rpoS deletion mutant TT-14 (ΔrpoS TT-1), clpP deletion mutant TT-16 (ΔclpP TT-1), and clpP rpoS double deletion mutant TT-19 (ΔclpP ΔrpoS TT-1) with those of the wild-type strain TT-1 by using gas chromatography coupled with mass spectrometry (GC–MS).

Results

Deletion of rpoS recovered only a part of the growth of Salmonella clpP mutant. Further metabolome analysis indicated that clpP disruption changed the levels of 16 extra- and 19 intracellular substances, while the extracellular concentrations of 4 compounds (serine, l-5-oxoproline, l-glutamic acid, and l-tryptophan) and intracellular concentrations of 10 compounds (l-isoleucine, glycine, serine, l-methionine, l-phenylalanine, malic acid, citric acid, urea, putrescine, and 6-hydroxypurine) returned to their wild-type levels when rpoS was also deleted.

Conclusion

ClpXP affects the cell metabolism of S. typhimurium partially in an RpoS-dependent manner.

     

PROPER: Performance visualization for optimizing and comparing ranking classifiers in MATLAB

Background

One of the recent challenges of computational biology is development of new algorithms, tools and software to facilitate predictive modeling of big data generated by high-throughput technologies in biomedical research.

Results

To meet these demands we developed PROPER - a package for visual evaluation of ranking classifiers for biological big data mining studies in the MATLAB environment.

Conclusion

PROPER is an efficient tool for optimization and comparison of ranking classifiers, providing over 20 different two- and three-dimensional performance curves.

     

Soft sensor for monitoring biomass subpopulations in mammalian cell culture processes

Objectives

Biomass subpopulations in mammalian cell culture processes cause impurities and influence productivity, which requires this critical process parameter to be monitored in real-time.

Results

For this reason, a novel soft sensor concept for estimating viable, dead and lysed cell concentration was developed, based on the robust and cheap in situ measurements of permittivity and turbidity in combination with a simple model. It could be shown that the turbidity measurements contain information about all investigated biomass subpopulations. The novelty of the developed soft sensor is the real-time estimation of lysed cell concentration, which is directly correlated to process-related impurities such as DNA and host cell protein in the supernatant. Based on data generated by two fed-batch processes the developed soft sensor is described and discussed.

Conclusions

The presented soft sensor concept provides a tool for viable, dead and lysed cell concentration estimation in real-time with adequate accuracy and enables further applications with respect to process optimization and control.

     

Removing the bottlenecks of cell culture metabolomics: fast normalization procedure,correlation of metabolites to cell number,and impact of the cell harvesting method

Introduction

Although cultured cells are nowadays regularly analyzed by metabolomics technologies, some issues in study setup and data processing are still not resolved to complete satisfaction: a suitable harvesting method for adherent cells, a fast and robust method for data normalization, and the proof that metabolite levels can be normalized to cell number.

Objectives

We intended to develop a fast method for normalization of cell culture metabolomics samples, to analyze how metabolite levels correlate with cell numbers, and to elucidate the impact of the kind of harvesting on measured metabolite profiles.

Methods

We cultured four different human cell lines and used them to develop a fluorescence-based method for DNA quantification. Further, we assessed the correlation between metabolite levels and cell numbers and focused on the impact of the harvesting method (scraping or trypsinization) on the metabolite profile.

Results

We developed a fast, sensitive and robust fluorescence-based method for DNA quantification showing excellent linear correlation between fluorescence intensities and cell numbers for all cell lines. Furthermore, 82–97 % of the measured intracellular metabolites displayed linear correlation between metabolite concentrations and cell numbers. We observed differences in amino acids, biogenic amines, and lipid levels between trypsinized and scraped cells.

Conclusion

We offer a fast, robust, and validated normalization method for cell culture metabolomics samples and demonstrate the eligibility of the normalization of metabolomics data to the cell number. We show a cell line and metabolite-specific impact of the harvesting method on metabolite concentrations.

     

OptPipe - a pipeline for optimizing metabolic engineering targets

Background

We propose OptPipe - a Pipeline for Optimizing Metabolic Engineering Targets, based on a consensus approach. The method generates consensus hypotheses for metabolic engineering applications by combining several optimization solutions obtained from distinct algorithms. The solutions are ranked according to several objectives, such as biomass and target production, by using the rank product tests corrected for multiple comparisons.

Results

OptPipe was applied in a genome-scale model of Corynebacterium glutamicum for maximizing malonyl-CoA, which is a valuable precursor for many phenolic compounds. In vivo experimental validation confirmed increased malonyl-CoA level in case of ΔsdhCAB deletion, as predicted in silico.

Conclusions

A method was developed to combine the optimization solutions provided by common knockout prediction procedures and rank the suggested mutants according to the expected growth rate, production and a new adaptability measure. The implementation of the pipeline along with the complete documentation is freely available at https://github.com/AndrasHartmann/OptPipe.

     

Enhanced stochastic optimization algorithm for finding effective multi-target therapeutics

Background

For treating a complex disease such as cancer, we need effective means to control the biological network that underlies the disease. However, biological networks are typically robust to external perturbations, making it difficult to beneficially alter the network dynamics by controlling a single target. In fact, multi-target therapeutics is often more effective compared to monotherapies, and combinatory drugs are commonly used these days for treating various diseases. A practical challenge in combination therapy is that the number of possible drug combinations increases exponentially, which makes the prediction of the optimal drug combination a difficult combinatorial optimization problem. Recently, a stochastic optimization algorithm called the Gur Game algorithm was proposed for drug optimization, which was shown to be very efficient in finding potent drug combinations.

Results

In this paper, we propose a novel stochastic optimization algorithm that can be used for effective optimization of combinatory drugs. The proposed algorithm analyzes how the concentration change of a specific drug affects the overall drug response, thereby making an informed guess on how the concentration should be updated to improve the drug response. We evaluated the performance of the proposed algorithm based on various drug response functions, and compared it with the Gur Game algorithm.

Conclusions

Numerical experiments clearly show that the proposed algorithm significantly outperforms the original Gur Game algorithm, in terms of reliability and efficiency. This enhanced optimization algorithm can provide an effective framework for identifying potent drug combinations that lead to optimal drug response.

     

Reliable RT-qPCR-based titration of retroviral and lentiviral vectors via quantification of residual vector plasmid DNA in samples

Objectives

To develop a method for reliable quantification of viral vectors, which is necessary for determining the optimal dose of vector particles in clinical trials to obtain the desired effects without severe unwanted immune responses.

Results

A significant level of vector plasmid remained in retroviral and lentiviral vector samples, which led to overestimation of viral titers when using the conventional RT-qPCR-based genomic titration method. To address this problem, we developed a new method in which the residual plasmid was quantified by an additional RT-qPCR step, and standard molecules and primer sets were optimized. The obtained counts were then used to correct the conventionally measured genomic titers of viral samples. While the conventional method produced significantly higher genomic titers for mutant retroviral vectors than for wild-type vectors, our method produced slightly higher or equivalent titers, corresponding with the general idea that mutation of viral components mostly results in reduced or, at best, retained titers.

Conclusion

Subtraction of the number of residual vector plasmid molecules from the conventionally measured genomic titer can yield reliable quantification of retroviral and lentiviral vector samples, a prerequisite to advancing the safety of gene therapy applications.