DEApp: an interactive web interface for differential expression analysis of next generation sequence data

Background

A growing trend in the biomedical community is the use of Next Generation Sequencing (NGS) technologies in genomics research. The complexity of downstream differential expression (DE) analysis is however still challenging, as it requires sufficient computer programing and command-line knowledge. Furthermore, researchers often need to evaluate and visualize interactively the effect of using differential statistical and error models, assess the impact of selecting different parameters and cutoffs, and finally explore the overlapping consensus of cross-validated results obtained with different methods. This represents a bottleneck that slows down or impedes the adoption of NGS technologies in many labs.

Results

We developed DEApp, an interactive and dynamic web application for differential expression analysis of count based NGS data. This application enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface.

Conclusions

DEApp enables labs with no access to full time bioinformaticians to exploit the advantages of NGS applications in biomedical research. This application is freely available at https://yanli.shinyapps.io/DEAppand https://gallery.shinyapps.io/DEApp.

     

Identification of trunk mutations in gastric carcinoma: a case study

Background

Intratumor heterogeneity (ITH) poses an urgent challenge for cancer precision medicine because it can cause drug resistance against cancer target therapy and immunotherapy. The search for trunk mutations that are present in all cancer cells is therefore critical for each patient.

Case presentation

In this study, we aimed to evaluate the efficiency of multiregional sequencing for the identification of trunk mutations present in all regions of a tumor as a case study. We applied multiregional whole-exome sequencing (WES) to investigate the genetic heterogeneity and homogeneity of a case of gastric carcinoma. Approximately 83% of common missense mutations present in two samples and approximately 89% of common missense mutations present in three samples were trunk mutations. Notably, trunk mutations appeared to have higher variant allele frequencies (VAFs) than non-trunk mutations.

Conclusions

Our results indicate that small-scale multiregional sampling and subsequent screening of low VAF somatic mutations might be a cost-effective strategy for identifying the majority of trunk mutations in gastric carcinoma.

     

High-throughput pyrosequencing used for the discovery of a novel cellulase from a thermophilic cellulose-degrading microbial consortium

Objectives

To analyze the microbial diversity and gene content of a thermophilic cellulose-degrading consortium from hot springs in Xiamen, China using 454 pyrosequencing for discovering cellulolytic enzyme resources.

Results

A thermophilic cellulose-degrading consortium, XM70 that was isolated from a hot spring, used sugarcane bagasse as sole carbon and energy source. DNA sequencing of the XM70 sample resulted in 349,978 reads with an average read length of 380 bases, accounting for 133,896,867 bases of sequence information. The characterization of sequencing reads and assembled contigs revealed that most microbes were derived from four phyla: Geobacillus (Firmicutes), Thermus, Bacillus, and Anoxybacillus. Twenty-eight homologous genes belonging to 15 glycoside hydrolase families were detected, including several cellulase genes. A novel hot spring metagenome-derived thermophilic cellulase was expressed and characterized.

Conclusions

The application value of thermostable sugarcane bagasse-degrading enzymes is shown for production of cellulosic biofuel. The practical power of using a short-read-based metagenomic approach for harvesting novel microbial genes is also demonstrated.

     

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.

     

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.

     

Identification of a urine metabolite constellation characteristic for kidney allograft rejection

Introduction

Allograft rejection is still an important complication after kidney transplantation. Currently, monitoring of these patients mostly relies on the measurement of serum creatinine and clinical evaluation. The gold standard for diagnosing allograft rejection, i.e. performing a renal biopsy is invasive and expensive. So far no adequate biomarkers are available for routine use.

Objectives

We aimed to develop a urine metabolite constellation that is characteristic for acute renal allograft rejection.

Methods

NMR-Spectroscopy was applied to a training cohort of transplant recipients with and without acute rejection.

Results

We obtained a metabolite constellation of four metabolites that shows promising performance to detect renal allograft rejection in the cohorts used (AUC of 0.72 and 0.74, respectively).

Conclusion

A metabolite constellation was defined with the potential for further development of an in-vitro diagnostic test that can support physicians in their clinical assessment of a kidney transplant patient.

     

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.

     

Lateral flow strip for visual detection of K-ras mutations based on allele-specific PCR

Objectives

To develop a convenient and sensitive point-of-care test for detecting gene mutations based on allele-specific PCR.

Results

To develop a lateral flow strip for visual detection of K-ras mutations based on a modified PCR, a specific DNA tag was covalently linked to the 5′-end of each primer by a nine-carbon linker to produce a sticky end. One of the sticky ends of the PCR products bound to gold nano-particles, while the other sticky end was captured onto a nitrocellulose membrane of lateral flow strips. The lateral flow strip showed a great sensitivity, which detected mutations in as low as 10 tumor cells. The positive rate and accuracy of the lateral flow strip for blood samples were over 92 and 96 %, respectively.

Conclusions

The lateral flow strip provides an easy method for sensitive detection of gene mutations based on allele specific-PCR.

     

Challenging popular tools for the annotation of genetic variations with a real case,pathogenic mutations of lysosomal alpha-galactosidase

Background

Severity gradation of missense mutations is a big challenge for exome annotation. Predictors of deleteriousness that are most frequently used to filter variants found by next generation sequencing, produce qualitative predictions, but also numerical scores. It has never been tested if these scores correlate with disease severity.

Results

wANNOVAR, a popular tool that can generate several different types of deleteriousness-prediction scores, was tested on Fabry disease. This pathology, which is caused by a deficit of lysosomal alpha-galactosidase, has a very large genotypic and phenotypic spectrum and offers the possibility of associating a quantitative measure of the damage caused by mutations to the functioning of the enzyme in the cells. Some predictors, and in particular VEST3 and PolyPhen2 provide scores that correlate with the severity of lysosomal alpha-galactosidase mutations in a statistically significant way.

Conclusions

Sorting disease mutations by severity is possible and offers advantages over binary classification. Dataset for testing and training in silico predictors can be obtained by transient transfection and evaluation of residual activity of mutants in cell extracts. This approach consents to quantitative data for severe, mild and non pathological variants.

     

Hypocapnia is a biological marker for orthostatic intolerance in some patients with chronic fatigue syndrome

Context

Patients with chronic fatigue syndrome and those with orthostatic intolerance share many symptoms, yet questions exist as to whether CFS patients have physiological evidence of orthostatic intolerance.

Objective

To determine if some CFS patients have increased rates of orthostatic hypotension, hypertension, tachycardia, or hypocapnia relative to age-matched controls.

Design

Assess blood pressure, heart rate, respiratory rate, end tidal CO2 and visual analog scales for orthostatic symptoms when supine and when standing for 8 minutes without moving legs.

Setting

Referral practice and research center.

Participants

60 women and 15 men with CFS and 36 women and 4 men serving as age matched controls with analyses confined to 62 patients and 35 controls showing either normal orthostatic testing or a physiological abnormal test.

Main outcome measures

Orthostatic tachycardia; orthostatic hypotension; orthostatic hypertension; orthostatic hypocapnia or combinations thereof.

Results

CFS patients had higher rates of abnormal tests than controls (53% vs 20%, p < .002), but rates of orthostatic tachycardia, orthostatic hypotension, and orthostatic hypertension did not differ significantly between patients and controls (11.3% vs 5.7%, 6.5% vs 2.9%, 19.4% vs 11.4%, respectively). In contrast, rates of orthostatic hypocapnia were significantly higher in CFS than in controls (20.6% vs 2.9%, p < .02). This CFS group reported significantly more feelings of illness and shortness of breath than either controls or CFS patients with normal physiological tests.

Conclusion

A substantial number of CFS patients have orthostatic intolerance in the form of orthostatic hypocapnia. This allows subgrouping of patients with CFS and thus reduces patient pool heterogeneity engendered by use of a clinical case definition.

     

Pranlukast,a novel binding ligand of human Raf1 kinase inhibitory protein

Objectives

To study the binding of pranlukast to hRKIP and its regulatory role in the Raf1/MEK/ERK signal pathway.

Results

NMR and fluorescence experiments demonstrated hRKIP could bind pranlukast with a binding constant of 1016 mM^?1. Residues (Y81, S109 and Y181) on the conserved ligand-binding pocket of hRKIP played a crucial role in binding pranlukast, and their mutations reduced the binding affinity more than 85 %. Furthermore, 25 μM pranlukast could up-regulate the ERK phosphorylation by about 17 %.

Conclusion

Pranlukast may be used as a potential drug precursor for treating hRKIP involved diseases.

     

Sex differences in the prognostic significance of KRAS codons 12 and 13, and BRAF mutations in colorectal cancer: a cohort study

Background

Activating KRAS and BRAF mutations predict unresponsiveness to EGFR-targeting therapies in colorectal cancer (CRC), but their prognostic value needs further validation. In this study, we investigated the impact of KRAS codons 12 and 13, and BRAF mutations on survival from CRC, overall and stratified by sex, in a large prospective cohort study.

Methods

KRAS codons 12 and 13, and BRAF mutations were analysed by pyrosequencing of tumours from 525 and 524 incident CRC cases in The Malmö Diet and Cancer Study. Associations with cancer-specific survival (CSS) were explored by Cox proportional hazards regression, unadjusted and adjusted for age, TNM stage, differentiation grade, vascular invasion and microsatellite instability (MSI) status.

Results

KRAS and BRAF mutations were mutually exclusive. KRAS mutations were found in 191/ 525 (36.4%) cases, 82.2% of these mutations were in codon 12, 17.3% were in codon 13, and 0.5% cases had mutations in both codons. BRAF mutations were found in 78/524 (14.9%) cases. Overall, mutation in KRAS codon 13, but not codon 12, was associated with a significantly reduced CSS in unadjusted, but not in adjusted analysis, and BRAF mutation did not significantly affect survival. However, in microsatellite stable (MSS), but not in MSI tumours, an adverse prognostic impact of BRAF mutation was observed in unadjusted, but not in adjusted analysis. While KRAS mutation status was not significantly associated with sex, BRAF mutations were more common in women. BRAF mutation was not prognostic in women; but in men, BRAF mutation was associated with a significantly reduced CSS in overall adjusted analysis (HR = 3.50; 95% CI = 1.41–8.70), but not in unadjusted analysis. In men with MSS tumours, BRAF mutation was an independent factor of poor prognosis (HR = 4.91; 95% CI = 1.99–12.12). KRAS codon 13 mutation was associated with a significantly reduced CSS in women, but not in men in unadjusted, but not in adjusted analysis.

Conclusions

Results from this cohort study demonstrate sex-related differences in the prognostic value of BRAF mutations in colorectal cancer, being particularly evident in men. These findings are novel and merit further validation.

     

Development of a recombinant immunotoxin for the immunotherapy of autoreactive lymphocytes expressing MOG-specific BCRs

Objective

Myelin oligodendrocyte glycoprotein (MOG) is one of the major autoantigens in multiple sclerosis (MS), therefore selective depletion of autoreactive lymphocytes exposing MOG-specific B cell receptors (BCRs) would be beneficial in terms of MS treatment.

Results

Using E. coli we generated an efficient protocol for the purification of the recombinant immunotoxin DT-MOG composed of the extracellular Ig-like domain of MOG fused in frame with the catalytic and translocation subunits of diphtheria toxin (DT, Corynebacterium diphtheriae) under native conditions with a final yield of 1.5 mg per liter of culture medium. Recombinant DT-MOG was recognized in vitro by MOG-reactive antibodies and has catalytic activity comparable with wild-type DT.

Conclusion

Enhanced pharmacokinetics (mean residence time in the bloodstream of 61 min) and minimized diminished nonspecific toxicity (LD₅₀ = 1.76 mg/kg) of the DT-MOG makes it a potential candidate for the immunotherapy of MS.

     

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.

     

Association of a novel point mutation in MSH2 gene with familial multiple primary cancers

Background

Multiple primary cancers (MPC) have been identified as two or more cancers without any subordinate relationship that occur either simultaneously or metachronously in the same or different organs of an individual. Lynch syndrome is an autosomal dominant genetic disorder that increases the risk of many types of cancers. Lynch syndrome patients who suffer more than two cancers can also be considered as MPC; patients of this kind provide unique resources to learn how genetic mutation causes MPC in different tissues.

Methods

We performed a whole genome sequencing on blood cells and two tumor samples of a Lynch syndrome patient who was diagnosed with five primary cancers. The mutational landscape of the tumors, including somatic point mutations and copy number alternations, was characterized. We also compared Lynch syndrome with sporadic cancers and proposed a model to illustrate the mutational process by which Lynch syndrome progresses to MPC.

Results

We revealed a novel pathologic mutation on the MSH2 gene (G504 splicing) that associates with Lynch syndrome. Systematical comparison of the mutation landscape revealed that multiple cancers in the proband were evolutionarily independent. Integrative analysis showed that truncating mutations of DNA mismatch repair (MMR) genes were significantly enriched in the patient. A mutation progress model that included germline mutations of MMR genes, double hits of MMR system, mutations in tissue-specific driver genes, and rapid accumulation of additional passenger mutations was proposed to illustrate how MPC occurs in Lynch syndrome patients.

Conclusion

Our findings demonstrate that both germline and somatic alterations are driving forces of carcinogenesis, which may resolve the carcinogenic theory of Lynch syndrome.

     

TarMet: a reactive GUI tool for efficient and confident quantification of MS based targeted metabolic and stable isotope tracer analysis

Introduction

Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately.

Objectives

TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface.

Methods

TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically.

Results

TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well.

Conclusion

TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.

     

COGcollator: a web server for analysis of distant relationships between homologous protein families

Background

The Clusters of Orthologous Groups (COGs) of proteins systematize evolutionary related proteins into specific groups with similar functions. However, the available databases do not provide means to assess the extent of similarity between the COGs.

Aim

We intended to provide a method for identification and visualization of evolutionary relationships between the COGs, as well as a respective web server.

Results

Here we introduce the COGcollator, a web tool for identification of evolutionarily related COGs and their further analysis. We demonstrate the utility of this tool by identifying the COGs that contain distant homologs of (i) the catalytic subunit of bacterial rotary membrane ATP synthases and (ii) the DNA/RNA helicases of the superfamily 1.

Reviewers

This article was reviewed by Drs. Igor N. Berezovsky, Igor Zhulin and Yuri Wolf.

     

Constraint-based perturbation analysis with cluster Newton method: a case study of personalized parameter estimations with irinotecan whole-body physiologically based pharmacokinetic model

Background

Drug development considering individual varieties among patients becomes crucial to improve clinical development success rates and save healthcare costs. As a useful tool to predict individual phenomena and correlations among drug characteristics and individual varieties, recently, whole-body physiologically based pharmacokinetic (WB- PBPK) models are getting more attention. WB-PBPK models generally have a lot of drug-related parameters that need to be estimated, and the estimations are difficult because the observed data are limited. Furthermore, parameter estimation in WB-PBPK models may cause overfitting when applying to individual clinical data such as urine/feces drug excretion for each patient in which Cluster Newton Method (CNM) is applicable for parameter estimation. In order to solve this issue, we came up with the idea of constraint-based perturbation analysis of the CNM. The effectiveness of our approach is demonstrated in the case of irinotecan WB-PBPK model using common organ-specific tissue-plasma partition coefficients (Kp) among the patients as constraints in WB-PBPK parameter estimation.

Results

We find strong correlations between age, renal clearance and liver functions in irinotecan WB-PBPK model with personalized physiological parameters by observing the distributions of optimized values of strong convergence drug-related parameters using constraint-based perturbation analysis on CNM. The constraint-based perturbation analysis consists of the following three steps: (1) Estimation of all drug-related parameters for each patient; the parameters include organ-specific Kp. (2) Fixing suitable values of Kp for each organ among all patients identically. (3) Re-estimation of all drug-related parameters other than Kp by using the fixed values of Kp as constraints of CNM.

Conclusions

Constraint-based perturbation analysis could yield new findings when using CNM with appropriate constraints. This method is a new technique to find suitable values and important insights that are masked by CNM without constraints.

     

Effect of experimental gingivitis induction and erythritol on the salivary metabolome and functional biochemistry of systemically healthy young adults

Introduction

Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.

Objectives

To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.

Methods

In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.

Results

Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.

Conclusions

The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.

     

rDolphin: a GUI R package for proficient automatic profiling of 1D <Superscript>1</Superscript>H-NMR spectra of study datasets

Introduction

Adoption of automatic profiling tools for ¹H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.

Objectives

To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.

Methods

rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.

Results

The information and quality achieved in two public datasets of complex matrices are maximized.

Conclusion

rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.