Mitochondrial aconitase is a key regulator of energy production for growth and protein expression in Chinese hamster ovary cells

Introduction

Mammalian cells like Chinese hamster ovary (CHO) cells are routinely used for production of recombinant therapeutic proteins. Cells require a continuous supply of energy and nutrients to sustain high cell densities whilst expressing high titres of recombinant proteins. Cultured mammalian cells are primarily dependent on glucose and glutamine metabolism for energy production.

Objectives

The TCA cycle is the main source of energy production and its continuous flow is essential for cell survival. Modulated regulation of TCA cycle can affect ATP production and influence CHO cell productivity.

Methods

To determine the key metabolic reactions of the cycle associated with cell growth in CHO cells, we transiently silenced each gene of the TCA cycle using RNAi.

Results

Silencing of at least four TCA cycle genes was detrimental to CHO cell growth. With an exception of mitochondrial aconitase (or Aco2), all other genes were associated with ATP production reactions of the TCA cycle and their resulting substrates can be supplied by other anaplerotic and cataplerotic reactions. This study is the first of its kind to have established key role of aconitase gene in CHO cells. We further investigated the temporal effects of aconitase silencing on energy production, CHO cell metabolism, oxidative stress and recombinant protein production.

Conclusion

Transient silencing of mitochondrial aconitase inhibited cell growth, reduced ATP production, increased production of reactive oxygen species and reduced cell specific productivity of a recombinant CHO cell line by at least twofold.

     

Efficacy of repeated intrathecal triamcinolone acetonide application in progressive multiple sclerosis patients with spinal symptoms

Background

There are controversial results on the efficacy of the abandoned, intrathecal predominant methylprednisolone application in multiple sclerosis (MS) in contrast to the proven effectiveness in intractable postherpetic neuralgia.

Methods

We performed an analysis of the efficacy of the application of 40 mg of the sustained release steroid triamcinolone acetonide (TCA). We intrathecally injected in sterile saline dissolved TCA six times within three weeks on a regular basis every third day in 161 hospitalized primary and predominant secondary progressive MS patients with spinal symptoms. The MS patients did not experience an acute onset of exacerbation or recent distinct increased progression of symptoms. We simultaneously scored the MS patients with the EDSS and the Barthel index, estimated the walking distance and measured somatosensory evoked potentials. Additionally the MS patients received a standardized rehabilitation treatment.

Results

EDSS score and Barthel index improved, walking distance increased, latencies of somatosensory evoked potentials of the median and tibial nerves shortened in all MS patients with serial evaluation (p < 0.0001 for all variables). Side effects were rare, five patients stopped TCA application due to onset of a post lumbar puncture syndrome.

Conclusions

Repeated intrathecal TCA application improves spinal symptoms, walking distance and SSEP latencies in progressive MS patients in this uncontrolled study. Future trials should evaluate the long-term benefit of this invasive treatment.

     

Untargeted and stable isotope-assisted metabolomic analysis of MDA-MB-231 cells under hypoxia

Introduction

Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.

Objectives

Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.

Methods

Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.

Results

Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.

Conclusion

The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.

     

Noninvasive characterization of metabolites secreted in culture media by bovine embryos during in vitro production

Introduction

Secreted molecules could be correlated with the potential of embryonic development. The development of new technologies, such as mass spectrometry (MS), has enabled analyzes in culture medium to favor the determination of embryos viability in order to improve embryo selection.

Objectives

To perform a non-invasive characterization of the secretome of in vitro produced embryos with different kinetics of cleavage and in different stages of development to obtain specific patterns based on embryonic phenotype through MALDI–TOF–MS.

Methods

Bovine embryos were produced in vitro by standard protocols. The zygotes were transferred to individual culture medium and divided into two groups: Fast [4 cells-22 hours past the beginning of culture (hpc)] and Slow (2 cells-22 hpc). Culture media drops were collected at 22, 96 and 168 hpc. Analysis of embryonic secretome was made by MALDI–TOF–MS after extractions of the metabolites. Spectra were acquired in positive ionization mode. Univariate (Fold-change) and multivariate (Partial Least Squares Discriminants Analysis) analyses were performed by the online software Metaboanalyst.

Results

It was demonstrated that embryos with different kinetics have different spectrometric profiles during embryonic development. Moreover, secreted molecules in each developmental stage are differentially represented in embryos with different kinetics, and are related to specific pathways such as lipid and amino acids metabolism and cell proliferation.

Conclusion

We propose that the analysis of culture media by MALDI–TOF–MS can be used for qualitative characterization of bovine embryos, allowing the identification of key molecules during in vitro culture.

     

Echocardiographic chamber quantification in a healthy Dutch population

Aim

For accurate interpretation of echocardiographic measurements normative data are required, which are provided by guidelines. For this article, the hypothesis was that these cannot be extrapolated to the Dutch population, since in Dutch clinical practice often higher values are found, which may not be pathological but physiological. Therefore this study aimed to 1) obtain and propose normative values for cardiac chamber quantification in a healthy Dutch population and 2) determine influences of baseline characteristics on these measurements.

Methods

Prospectively recruited healthy subjects, aged 20–72 years (at least 28 subjects per age decade, equally distributed for gender) underwent physical examination and 2D and 3D echocardiography. Both ventricles and atria were assessed and volumes were calculated.

Results

147 subjects were included (age 44 ± 14 years, 50% female). Overall, feasibility was good for both linear and volumetric measurements. Linear and volumetric parameters were consistently higher than current guidelines recommend, while functional parameters were in line with the guidelines. This was more so in the older population. 3D volumes were higher than 2D volumes. Gender dependency was seen in all body surface area (BSA) corrected volumes and with increasing age, ejection fractions decreased.

Conclusion

This study provides 2D and 3D echocardiographic reference ranges for both ventricles and atria derived from a healthy Dutch population. BSA indexed volumes are gender-dependent, age did not influence ventricular volumes and a rise in blood pressure was independently associated with increased right ventricular volumes. The higher volumes found may be indicative for the Dutch population being the tallest in the world.

     

A metabolomics approach to uncover effects of different exercise modalities in type 1 diabetes

Introduction

Exercise-associated metabolism in type 1 diabetes (T1D) remains under-studied due to the complex interplay between exogenous insulin, counter-regulatory hormones and insulin-sensitivity.

Objective

To identify the metabolic differences induced by two exercise modalities in T1D using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HRMS) based metabolomics.

Methods

Twelve T1D adults performed intermittent high-intensity (IHE) and continuous-moderate-intensity (CONT) exercise. Serum samples were analysed by UHPLC–HRMS.

Results

Metabolic profiling of IHE and CONT highlighted exercise-induced changes in purine and acylcarnitine metabolism.

Conclusion

IHE may increase beta-oxidation through higher ATP-turnover. UHPLC–HRMS based metabolomics as a data-driven approach without an a priori hypothesis may help uncover distinctive metabolic effects during exercise in T1D.Clinical trial registration number is www.clinicaltrials.gov: NCT02068638.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Amelioration of patients with chronic spontaneous urticaria in treatment with vitamin D supplement

Background

Spontaneous urticaria is a common allergic skin condition affecting 0.5–1% of individuals and may burden on health care expenditure or may be associated with remarkable morbidity.

Aim

In this study, we measured the effect of vitamin D supplementation in patients with a diagnosis of CSU. Furthermore, quality of life and cytokine changes were evaluated.

Methods

The clinical trial was conducted on 20 patients with idiopathic chronic urticaria. Vitamin D was administered orally for 8 weeks and disease activity was measured pre- and post-treatment using USS and DLQI. On the other hand expressions of IL-17, IL-10, Foxp3, and TGF-β by Real-time RT-PCR were assessed.

Results

USS questionnaire showed that severity of idiopathic urticaria after the intervention, which compared with the first day reached a significant 55% reduction. The DLQI quality of life questionnaire 2 months after treatment showed 55% improvement. Along with the significant improvement of clinical symptoms, use of vitamin D increase FOXP3 gene expression and downregulation of IL-10, TGF-B, and FOXP3, IL-17, but these changes were not statistically significant.

Limitation

These might happen due to lack of enrolled population in the investigation.

Conclusion

Vitamin D can be used along with standard medical care and it’s a safe and cost-effective method for the treatment of chronic urticaria with deficiency of vitamin D.

     

Identification and characterization of a novel antioxidant peptide from feather keratin hydrolysate

Objectives

To improve the potential value of feather, which is a valuable protein resource, we have separated and identified antioxidant peptide(s) from feather hydrolysate.

Results

Feather hydrolysate was prepared by fermentation with Bacillus subtilis S1–4. Antioxidative peptides were separated by sequential acid precipitation, cation exchange, and reversed-phase fast performance liquid chromatography. Finally, a peptide with antioxidative activity was identified as Ser-Asn-Leu-Cys-Arg-Pro-Cys-Gly by MALDI time-of-flight (TOF)/TOF analysis, and determined to represent a portion of feather keratin near its N-terminal. A synthesized peptide with the same sequence was used to characterize its antioxidative properties, including scavenging free radicals, reducing power, and Fe²⁺ chelation. In terms of the peptide’s amino acid composition, the antioxidative activity might be mainly attributed to Cys and other amino acid residues.

Conclusion

Feather keratin is a good source for the quantitative preparation of antioxidative peptides.

     

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.

     

Type 2 diabetes increases oocyte mtDNA mutations which are eliminated in the offspring by bottleneck effect

Background

Diabetes induces many complications including reduced fertility and low oocyte quality, but whether it causes increased mtDNA mutations is unknown.

Methods

We generated a T2D mouse model by using high-fat-diet (HFD) and Streptozotocin (STZ) injection. We examined mtDNA mutations in oocytes of diabetic mice by high-throughput sequencing techniques.

Results

T2D mice showed glucose intolerance, insulin resistance, low fecundity compared to the control group. T2D oocytes showed increased mtDNA mutation sites and mutation numbers compared to the control counterparts. mtDNA mutation examination in F1 mice showed that the mitochondrial bottleneck could eliminate mtDNA mutations.

Conclusions

T2D mice have increased mtDNA mutation sites and mtDNA mutation numbers in oocytes compared to the counterparts, while these adverse effects can be eliminated by the bottleneck effect in their offspring. This is the first study using a small number of oocytes to examine mtDNA mutations in diabetic mothers and offspring.

     

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.

     

Quantifying and filtering knowledge generated by literature based discovery

Background

Literature based discovery (LBD) automatically infers missed connections between concepts in literature. It is often assumed that LBD generates more information than can be reasonably examined.

Methods

We present a detailed analysis of the quantity of hidden knowledge produced by an LBD system and the effect of various filtering approaches upon this. The investigation of filtering combined with single or multi-step linking term chains is carried out on all articles in PubMed.

Results

The evaluation is carried out using both replication of existing discoveries, which provides justification for multi-step linking chain knowledge in specific cases, and using timeslicing, which gives a large scale measure of performance.

Conclusions

While the quantity of hidden knowledge generated by LBD can be vast, we demonstrate that (a) intelligent filtering can greatly reduce the number of hidden knowledge pairs generated, (b) for a specific term, the number of single step connections can be manageable, and (c) in the absence of single step hidden links, considering multiple steps can provide valid links.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

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.

     

An effective hybrid of hill climbing and genetic algorithm for 2D triangular protein structure prediction

Background

Proteins play fundamental and crucial roles in nearly all biological processes, such as, enzymatic catalysis, signaling transduction, DNA and RNA synthesis, and embryonic development. It has been a long-standing goal in molecular biology to predict the tertiary structure of a protein from its primary amino acid sequence. From visual comparison, it was found that a 2D triangular lattice model can give a better structure modeling and prediction for proteins with short primary amino acid sequences.

Methods

This paper proposes a hybrid of hill-climbing and genetic algorithm (HHGA) based on elite-based reproduction strategy for protein structure prediction on the 2D triangular lattice.

Results

The simulation results show that the proposed HHGA can successfully deal with the protein structure prediction problems. Specifically, HHGA significantly outperforms conventional genetic algorithms and is comparable to the state-of-the-art method in terms of free energy.

Conclusions

Thanks to the enhancement of local search on the global search, the proposed HHGA achieves promising results on the 2D triangular protein structure prediction problem. The satisfactory simulation results demonstrate the effectiveness of the proposed HHGA and the utility of the 2D triangular lattice model for protein structure prediction.

     

Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics

Introduction

Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput ‘omics’ technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.

Objectives

We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.

Methods

Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC–TOF–MS). For each batch OPLS-DA^® was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.

Results

A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.

Conclusion

Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

Structural MRI correlates of PASAT performance in multiple sclerosis

Background

The Paced Auditory Serial Addition Test (PASAT) is a useful cognitive test in patients with multiple sclerosis (MS), assessing sustained attention and information processing speed. However, the neural underpinnings of performance in the test are controversial. We aimed to study the neural basis of PASAT performance by using structural magnetic resonance imaging (MRI) in a series of 242 patients with MS.

Methods

PASAT (3-s) was administered together with a comprehensive neuropsychological battery. Global brain volumes and total T2-weighted lesion volumes were estimated. Voxel-based morphometry and lesion symptom mapping analyses were performed.

Results

Mean PASAT score was 42.98?±?10.44; results indicated impairment in 75 cases (31.0%). PASAT score was correlated with several clusters involving the following regions: bilateral precuneus and posterior cingulate, bilateral caudate and putamen, and bilateral cerebellum. Voxel-based lesion symptom mapping showed no significant clusters. Region of interest–based analysis restricted to white matter regions revealed a correlation with the left cingulum, corpus callosum, bilateral corticospinal tracts, and right arcuate fasciculus. Correlations between PASAT scores and global volumes were weak.

Conclusion

PASAT score was associated with regional volumes of the posterior cingulate/precuneus and several subcortical structures, specifically the caudate, putamen, and cerebellum. This emphasises the role of both cortical and subcortical structures in cognitive functioning and information processing speed in patients with MS.

     

Automatic infection detection based on electronic medical records

Background

Making accurate patient care decision, as early as possible, is a constant challenge, especially for physicians in the emergency department. The increasing volumes of electronic medical records (EMRs) open new horizons for automatic diagnosis. In this paper, we propose to use machine learning approaches for automatic infection detection based on EMRs. Five categories of information are utilized for prediction, including personal information, admission note, vital signs, diagnose test results and medical image diagnose.

Results

Experimental results on a newly constructed EMRs dataset from emergency department show that machine learning models can achieve a decent performance for infection detection with area under the receiver operator characteristic curve (AUC) of 0.88. Out of all the five types of information, admission note in text form makes the most contribution with the AUC of 0.87.

Conclusions

This study provides a state-of-the-art EMRs processing system to automatically make medical decisions. It extracts five types of features associated with infection and achieves a decent performance on automatic infection detection based on machine learning models.