Simulating pedigrees ascertained for multiple disease-affected relatives

Background

Studies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.

Results

We present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.

Conclusions

Through simulation, we show that affected members of a family segregating a rare disease variant tend to be more numerous and cluster in relationships more closely than those for sporadic disease. We also show that the family ascertainment process can lead to apparent anticipation in the age of onset. Finally, we use simulation to gain insight into the limit on the proportion of ascertained families segregating a causal variant. SimRVPedigree should be useful to investigators seeking insight into the family-based study design through simulation.

     

The gene family-free median of three

Background

The gene family-free framework for comparative genomics aims at providing methods for gene order analysis that do not require prior gene family assignment, but work directly on a sequence similarity graph. We study two problems related to the breakpoint median of three genomes, which asks for the construction of a fourth genome that minimizes the sum of breakpoint distances to the input genomes.

Methods

We present a model for constructing a median of three genomes in this family-free setting, based on maximizing an objective function that generalizes the classical breakpoint distance by integrating sequence similarity in the score of a gene adjacency. We study its computational complexity and we describe an integer linear program (ILP) for its exact solution. We further discuss a related problem called family-free adjacencies for k genomes for the special case of \(k \le 3\) and present an ILP for its solution. However, for this problem, the computation of exact solutions remains intractable for sufficiently large instances. We then proceed to describe a heuristic method, FFAdj-AM, which performs well in practice.

Results

The developed methods compute accurate positional orthologs for genomes comparable in size of bacterial genomes on simulated data and genomic data acquired from the OMA orthology database. In particular, FFAdj-AM performs equally or better when compared to the well-established gene family prediction tool MultiMSOAR.

Conclusions

We study the computational complexity of a new family-free model and present algorithms for its solution. With FFAdj-AM, we propose an appealing alternative to established tools for identifying higher confidence positional orthologs.

     

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.

     

Accurate flexible refinement of atomic models against medium-resolution cryo-EM maps using damped dynamics

Background

Dramatic progress has recently been made in cryo-electron microscopy technologies, which now make possible the reconstruction of a growing number of biomolecular structures to near-atomic resolution. However, the need persists for fitting and refinement approaches that address those cases that require modeling assistance.

Methods

In this paper, we describe algorithms to optimize the performance of such medium-resolution refinement methods. These algorithms aim to automatically optimize the parameters that define the density shape of the flexibly fitted model, as well as the time-dependent damper cutoff distance. Atomic distance constraints can be prescribed for cases where extra containment of parts of the structure is helpful, such as in regions where the density map is poorly defined. Also, we propose a simple stopping criterion that estimates the probable onset of overfitting during the simulation.

Results

The new set of algorithms produce more accurate fitting and refinement results, and yield a faster rate of convergence of the trajectory toward the fitted conformation. The latter is also more reliable due to the overfitting warning provided to the user.

Conclusions

The algorithms described here were implemented in the new Damped-Dynamics Flexible Fitting simulation tool “DDforge” in the Situs package.

     

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.

     

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

     

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.

     

Structure elucidation of metabolite x17299 by interpretation of mass spectrometric data

Introduction

A major bottleneck in metabolomic studies is metabolite identification from accurate mass spectrometric data. Metabolite x17299 was identified in plasma as an unknown in a metabolomic study using a compound-centric approach where the associated ion features of the compound were used to determine the true molecular mass.

Objectives

The aim of this work is to elucidate the chemical structure of x17299, a new compound by de novo interpretation of mass spectrometric data.

Methods

An Orbitrap Elite mass spectrometer was used for acquisition of mass spectra up to MS⁴ at high resolution. Synthetic standards of N,N,N-trimethyl-l-alanyl-l-proline betaine (l,l-TMAP), a diastereomer, and an enantiomer were chemically prepared.

Results

The planar structure of x17299 was successfully proposed by de novo mechanistic interpretation of mass spectrometric data without any laborious purification and nuclear magnetic resonance spectroscopic analysis. The proposed structure was verified by deuterium exchanged mass spectrometric analysis and confirmed by comparison to a synthetic standard. Relative configuration of x17299 was determined by direct chromatographic comparison to a pair of synthetic diastereomers. Absolute configuration was assigned after derivatization of x17299 with a chiral auxiliary group followed by its chromatographic comparison to a pair of synthetic standards.

Conclusion

The chemical structure of metabolite x17299 was determined to be l,l-TMAP.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

Robust dose-response curve estimation applied to high content screening data analysis

Background and method

Successfully automated sigmoidal curve fitting is highly challenging when applied to large data sets. In this paper, we describe a robust algorithm for fitting sigmoid dose-response curves by estimating four parameters (floor, window, shift, and slope), together with the detection of outliers. We propose two improvements over current methods for curve fitting. The first one is the detection of outliers which is performed during the initialization step with correspondent adjustments of the derivative and error estimation functions. The second aspect is the enhancement of the weighting quality of data points using mean calculation in Tukey’s biweight function.

Results and conclusion

Automatic curve fitting of 19,236 dose-response experiments shows that our proposed method outperforms the current fitting methods provided by MATLAB®;’s nlinfit nlinfit function and GraphPad’s Prism software.

     

Serum metabolomic study for detecting biomarkers of non-traumatic osteonecrosis of the femoral head

Introduction

Non-traumatic osteonecrosis of the femoral head (NTONFH) is a progressive disease, always leading to hip dysfunction if no early intervention was applied. The difficulty for early diagnosis of NTONFH is due to the slight symptoms at early stages as well as the high cost for screening patients by using magnetic resonance imaging.

Objective

The aim was to detect biomarkers of early-stage NTONFH, which was beneficial to the exploration of a cost-effective approach for the early diagnose of the disease.

Methods

Metabolomic approaches were employed in this study to detect biomarkers of early-stage NTONFH (22 patients, 23 controls), based on the platform of ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and the uses of multivariate statistic analysis, putative metabolite identification, metabolic pathway analysis and biomarker analysis.

Results

In total, 33 serum metabolites were found altered between NTONFH group and control group. In addition, glycerophospholipid metabolism and pyruvate metabolism were highly associated with the disease.

Conclusion

The combination of LysoPC (18:3), l-tyrosine and l-leucine proved to have a high diagnostic value for early-stage NTONFH. Our findings may contribute to the protocol for early diagnosis of NTONFH and further elucidate the underlying mechanisms of the disease.

     

Furosemide enhances the sensitivity of urinary metabolomics for assessment of kidney function

Introduction

The ability of urinary metabolomics to detect meaningful, tissue-specific, biological effects (i.e., toxicity, disease) is compounded by high background variability. We hypothesize that sensitivity can be enhanced by imposing a tissue-targeted metabolic stressor.

Objective

We tested whether the sensitivity of metabolomics to assess kidney function is improved under the diuretic stress of furosemide.

Methods

To mildly compromise kidney, rats were given a sub-acute dose of d-serine. Then at 24 h postdose, we administered vehicle solution (control) or the diuretic drug, furosemide, and conducted NMR-based urinary metabolomics.

Results

Principal Components and OPLS discriminant analyses showed no effects on urinary profiles in rats receiving d-serine alone. However, the effects of d-serine were observable under furosemide-induced stress, as urinary profiles classified separately from rats receiving furosemide alone or vehicle-treated controls (p?<?0.001). Furthermore, this profile was uniquely different from a co-treatment effect observed following co-administration of d-serine?+?furosemide. We identified 24 metabolites to classify the effects of furosemide in normal rats vs. d-serine-compromised rats. Most notably, a furosemide-induced increase in urinary excretion of α-ketoglutarate, creatinine, trigonelline, and tryptophan in control rats, was significantly reduced in d-serine exposed rats (p?<?0.05). Interestingly, increased tryptophan metabolism has been shown to correlate with the severity of kidney transplant failure and chronic kidney disease.

Conclusions

We attribute these effects to differences in kidney function, which were only detectable under the stress imposed by furosemide. This technique may extend to other organ systems and may provide improved sensitivity for assessment of tissue function or early detection of disease.

     

The PAM domain,a multi-protein complex-associated module with an all-alpha-helix fold

Background

Multimeric protein complexes have a role in many cellular pathways and are highly interconnected with various other proteins. The characterization of their domain composition and organization provides useful information on the specific role of each region of their sequence.

Results

We identified a new module, the PAM domain (P CI/PINT a ssociated m odule), present in single subunits of well characterized multiprotein complexes, like the regulatory lid of the 26S proteasome, the COP-9 signalosome and the Sac3-Thp1 complex. This module is an around 200 residue long domain with a predicted TPR-like all-alpha-helical fold.

Conclusions

The occurrence of the PAM domain in specific subunits of multimeric protein complexes, together with the role of other all-alpha-helical folds in protein-protein interactions, suggest a function for this domain in mediating transient binding to diverse target proteins.

     

Individualized,discrete event,simulations provide insight into inter- and intra-subject variability of extended-release,drug products

Objective

Develop and validate particular, concrete, and abstract yet plausible in silico mechanistic explanations for large intra- and interindividual variability observed for eleven bioequivalence study participants. Do so in the face of considerable uncertainty about mechanisms.

Methods

We constructed an object-oriented, discrete event model called subject (we use small caps to distinguish computational objects from their biological counterparts). It maps abstractly to a dissolution test system and study subject to whom product was administered orally. A subject comprises four interconnected grid spaces and event mechanisms that map to different physiological features and processes. Drugs move within and between spaces. We followed an established, Iterative Refinement Protocol. Individualized mechanisms were made sufficiently complicated to achieve prespecified Similarity Criteria, but no more so. Within subjects, the dissolution space is linked to both a product-subject Interaction Space and the GI tract. The GI tract and Interaction Space connect to plasma, from which drug is eliminated.

Results

We discovered parameterizations that enabled the eleven subject simulation results to achieve the most stringent Similarity Criteria. Simulated profiles closely resembled those with normal, odd, and double peaks. We observed important subject-by-formulation interactions within subjects.

Conclusion

We hypothesize that there were interactions within bioequivalence study participants corresponding to the subject-by-formulation interactions within subjects. Further progress requires methods to transition currently abstract subject mechanisms iteratively and parsimoniously to be more physiologically realistic. As that objective is achieved, the approach presented is expected to become beneficial to drug development (e.g., controlled release) and to a reduction in the number of subjects needed per study plus faster regulatory review.

     

An efficient biocatalytic synthesis of imidazole-4-acetic acid

Objective

To develop a new and efficient biocatalytic synthesis method of imidazole-4-acetic acid (IAA) from l-histidine (l-His).

Results

l-His was converted to imidazole-4-pyruvic acid (IPA) by an Escherichia coli whole-cell biocatalyst expressing membrane-bound l-amino acid deaminase (ml-AAD) from Proteus vulgaris firstly. The obtained IPA was subsequently decarboxylated to IAA under the action of H₂O₂. Under optimum conditions, 34.97 mM IAA can be produced from 50 mM l-His, with a yield of 69.9%.

Conclusions

Compared to the traditional chemical synthesis, this biocatalytic method for IAA production is not only environmentally friendly, but also more cost effective, thus being promising for industrial IAA production.

     

Algorithms for computing the double cut and join distance on both gene order and intergenic sizes

Background

Combinatorial works on genome rearrangements have so far ignored the influence of intergene sizes, i.e. the number of nucleotides between consecutive genes, although it was recently shown decisive for the accuracy of inference methods (Biller et al. in Genome Biol Evol 8:1427–39, 2016; Biller et al. in Beckmann A, Bienvenu L, Jonoska N, editors. Proceedings of Pursuit of the Universal-12th conference on computability in Europe, CiE 2016, Lecture notes in computer science, vol 9709, Paris, France, June 27–July 1, 2016. Berlin: Springer, p. 35–44, 2016). In this line, we define a new genome rearrangement model called wDCJ, a generalization of the well-known double cut and join (or DCJ) operation that modifies both the gene order and the intergene size distribution of a genome.

Results

We first provide a generic formula for the wDCJ distance between two genomes, and show that computing this distance is strongly NP-complete. We then propose an approximation algorithm of ratio 4/3, and two exact ones: a fixed-parameter tractable (FPT) algorithm and an integer linear programming (ILP) formulation.

Conclusions

We provide theoretical and empirical bounds on the expected growth of the parameter at the center of our FPT and ILP algorithms, assuming a probabilistic model of evolution under wDCJ, which shows that both these algorithms should run reasonably fast in practice.

     

Importing statistical measures into Artemis enhances gene identification in the <Emphasis Type="Italic">Leishmania</Emphasis> genome project

Background

Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces.

Results

Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODON USAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence.

Conclusion

An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.