DTL reconciliation repair

Background

Maximum parsimony phylogenetic tree reconciliation is an important technique for reconstructing the evolutionary histories of hosts and parasites, genes and species, and other interdependent pairs. Since the problem of finding temporally feasible maximum parsimony reconciliations is NP-complete, current methods use either exact algorithms with exponential worst-case running time or heuristics that do not guarantee optimal solutions.

Results

We offer an efficient new approach that begins with a potentially infeasible maximum parsimony reconciliation and iteratively “repairs” it until it becomes temporally feasible.

Conclusions

In a non-trivial number of cases, this approach finds solutions that are better than those found by the widely-used Jane heuristic.

     

An improved probability mapping approach to assess genome mosaicism

Background

Maximum likelihood and posterior probability mapping are useful visualization techniques that are used to ascertain the mosaic nature of prokaryotic genomes. However, posterior probabilities, especially when calculated for four-taxon cases, tend to overestimate the support for tree topologies. Furthermore, because of poor taxon sampling four-taxon analyses suffer from sensitivity to the long branch attraction artifact. Here we extend the probability mapping approach by improving taxon sampling of the analyzed datasets, and by using bootstrap support values, a more conservative tool to assess reliability.

Results

Quartets of orthologous proteins were complemented with homologs from selected reference genomes. The mapping of bootstrap support values from these extended datasets gives results similar to the original maximum likelihood and posterior probability mapping. The more conservative nature of the plotted support values allows to focus further analyses on those protein families that strongly disagree with the majority or plurality of genes present in the analyzed genomes.

Conclusion

Posterior probability is a non-conservative measure for support, and posterior probability mapping only provides a quick estimation of phylogenetic information content of four genomes. This approach can be utilized as a pre-screen to select genes that might have been horizontally transferred. Better taxon sampling combined with subtree analyses prevents the inconsistencies associated with four-taxon analyses, but retains the power of visual representation. Nevertheless, a case-by-case inspection of individual multi-taxon phylogenies remains necessary to differentiate unrecognized paralogy and shared phylogenetic reconstruction artifacts from horizontal gene transfer events.

     

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.

     

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

Introduction

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

Objectives

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

Methods

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

Results

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

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

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.

     

Maximum likelihood models and algorithms for gene tree evolution with duplications and losses

Background

The abundance of new genomic data provides the opportunity to map the location of gene duplication and loss events on a species phylogeny. The first methods for mapping gene duplications and losses were based on a parsimony criterion, finding the mapping that minimizes the number of duplication and loss events. Probabilistic modeling of gene duplication and loss is relatively new and has largely focused on birth-death processes.

Results

We introduce a new maximum likelihood model that estimates the speciation and gene duplication and loss events in a gene tree within a species tree with branch lengths. We also provide an, in practice, efficient algorithm that computes optimal evolutionary scenarios for this model. We implemented the algorithm in the program DrML and verified its performance with empirical and simulated data.

Conclusions

In test data sets, DrML finds optimal gene duplication and loss scenarios within minutes, even when the gene trees contain sequences from several hundred species. In many cases, these optimal scenarios differ from the lca-mapping that results from a parsimony gene tree reconciliation. Thus, DrML provides a new, practical statistical framework on which to study gene duplication.

     

Models and algorithms for genome rearrangement with positional constraints

Background

Traditionally, the merit of a rearrangement scenario between two gene orders has been measured based on a parsimony criteria alone; two scenarios with the same number of rearrangements are considered equally good. In this paper, we acknowledge that each rearrangement has a certain likelihood of occurring based on biological constraints, e.g. physical proximity of the DNA segments implicated or repetitive sequences.

Results

We propose optimization problems with the objective of maximizing overall likelihood, by weighting the rearrangements. We study a binary weight function suitable to the representation of sets of genome positions that are most likely to have swapped adjacencies. We give a polynomial-time algorithm for the problem of finding a minimum weight double cut and join scenario among all minimum length scenarios. In the process we solve an optimization problem on colored noncrossing partitions, which is a generalization of the Maximum Independent Set problem on circle graphs.

Conclusions

We introduce a model for weighting genome rearrangements and show that under simple yet reasonable conditions, a fundamental distance can be computed in polynomial time. This is achieved by solving a generalization of the Maximum Independent Set problem on circle graphs. Several variants of the problem are also mentioned.

     

RNA binding protein Lin28A promotes osteocarcinoma cells progression by associating with the long noncoding RNA MALAT1

Objectives

To explore the effects of Lin28A on progression of osteocarcinoma (OS) cells.

Results

Lin28A mRNA and protein expressions were significantly increased in OS tissues compared with that in normal adjacent tissues. Expressions of Lin28A and long noncoding RNA MALAT1 were positively correlated. Patients with higher Lin28A expression had shorter overall survival. Moreover, Lin28A knockdown inhibited OS cells proliferation, migration, invasion and promoted cell apoptosis; Lin28A was found to harbor binding sites on MALAT1 sequences and associated with MALAT1, and increased MALAT1 stability and expression. Notably, the inhibition of Lin28A knockdown was attenuated or even reversed by MALAT1 overexpression.

Conclusions

RNA binding protein Lin28A could facilitate OS cells progression by associating with the long noncoding RNA MALAT1.

     

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.

     

Retrieving hidden atrial repolarization waves from standard surface ECGs

Background

This study estimates atrial repolarization activities (Ta waves), which are typically hidden most of the time from body surface electrocardiography when diagnosing cardiovascular diseases. The morphology of Ta waves has been proven to be an important marker for the early sign of inferior injury, such as acute atrial infarction, or arrhythmia, such as atrial fibrillation. However, Ta waves are usually unseen except during conduction system malfunction, such as long QT interval or atrioventricular block. Therefore, justifying heart diseases based on atrial repolarization becomes impossible in sinus rhythm.

Methods

We obtain TMPs in the atrial part of the myocardium which reflects the correct excitation sequence starting from the atrium to the end of the apex.

Results

The resulting TMP shows the hidden atrial part of ECG waves.

Conclusions

This extraction makes many diseases, such as acute atrial infarction or arrhythmia, become easily diagnosed.

     

Inferring angiosperm phylogeny from EST data with widespread gene duplication

Background

Most studies inferring species phylogenies use sequences from single copy genes or sets of orthologs culled from gene families. For taxa such as plants, with very high levels of gene duplication in their nuclear genomes, this has limited the exploitation of nuclear sequences for phylogenetic studies, such as those available in large EST libraries. One rarely used method of inference, gene tree parsimony, can infer species trees from gene families undergoing duplication and loss, but its performance has not been evaluated at a phylogenomic scale for EST data in plants.

Results

A gene tree parsimony analysis based on EST data was undertaken for six angiosperm model species and Pinus, an outgroup. Although a large fraction of the tentative consensus sequences obtained from the TIGR database of ESTs was assembled into homologous clusters too small to be phylogenetically informative, some 557 clusters contained promising levels of information. Based on maximum likelihood estimates of the gene trees obtained from these clusters, gene tree parsimony correctly inferred the accepted species tree with strong statistical support. A slight variant of this species tree was obtained when maximum parsimony was used to infer the individual gene trees instead.

Conclusion

Despite the complexity of the EST data and the relatively small fraction eventually used in inferring a species tree, the gene tree parsimony method performed well in the face of very high apparent rates of duplication.

     

High-throughput extraction and quantification method for targeted metabolomics in murine tissues

Introduction

Global metabolomics analyses using body fluids provide valuable results for the understanding and prediction of diseases. However, the mechanism of a disease is often tissue-based and it is advantageous to analyze metabolomic changes directly in the tissue. Metabolomics from tissue samples faces many challenges like tissue collection, homogenization, and metabolite extraction.

Objectives

We aimed to establish a metabolite extraction protocol optimized for tissue metabolite quantification by the targeted metabolomics AbsoluteIDQ? p180 Kit (Biocrates). The extraction method should be non-selective, applicable to different kinds and amounts of tissues, monophasic, reproducible, and amenable to high throughput.

Methods

We quantified metabolites in samples of eleven murine tissues after extraction with three solvents (methanol, phosphate buffer, ethanol/phosphate buffer mixture) in two tissue to solvent ratios and analyzed the extraction yield, ionization efficiency, and reproducibility.

Results

We found methanol and ethanol/phosphate buffer to be superior to phosphate buffer in regard to extraction yield, reproducibility, and ionization efficiency for all metabolites measured. Phosphate buffer, however, outperformed both organic solvents for amino acids and biogenic amines but yielded unsatisfactory results for lipids. The observed matrix effects of tissue extracts were smaller or in a similar range compared to those of human plasma.

Conclusion

We provide for each murine tissue type an optimized high-throughput metabolite extraction protocol, which yields the best results for extraction, reproducibility, and quantification of metabolites in the p180 kit. Although the performance of the extraction protocol was monitored by the p180 kit, the protocol can be applicable to other targeted metabolomics assays.

     

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.

     

SProt: sphere-based protein structure similarity algorithm

Background

Similarity search in protein databases is one of the most essential issues in computational proteomics. With the growing number of experimentally resolved protein structures, the focus shifted from sequences to structures. The area of structure similarity forms a big challenge since even no standard definition of optimal structure similarity exists in the field.

Results

We propose a protein structure similarity measure called SProt. SProt concentrates on high-quality modeling of local similarity in the process of feature extraction. SProt’s features are based on spherical spatial neighborhood of amino acids where similarity can be well-defined. On top of the partial local similarities, global measure assessing similarity to a pair of protein structures is built. Finally, indexing is applied making the search process by an order of magnitude faster.

Conclusions

The proposed method outperforms other methods in classification accuracy on SCOP superfamily and fold level, while it is at least comparable to the best existing solutions in terms of precision-recall or quality of alignment.

     

Cationic antimicrobial peptide: LL-37 and its role in periodontitis

Background

Periodontitis i.e. inflammation of the periodontium is a multifactorial disease. Antimicrobial peptides (AMPs) which demonstrate a broad-spectrum of activity against varied number of bacteria, fungi, viruses, and parasites, and cancerous cells have been linked to periodontitis. The AMPs even possess the caliber of immunomodulation, and are significantly responsive to innate immuno-stimulation and infections. LL-37 plays a salubrious role by preventing and in treatment of chronic forms of periodontitis.

Objective

In the present work we will review the role of antimicrobial peptide LL-37 in periodontitis.

Methods

A systematic search was carried out from the beginning till August, 2016 using the Pubmed search engine. The keywords included “LL-37,” “periodontitis,” “Papillon–Lefevre syndrome,” “Morbus Kostmann,” “Haim-Munk syndrome” along with use of Boolean operator “and.”

Results

The search resulted in identifying 67 articles which included articles linking LL-37 with periodontitis, articles on Papillon–Lefevre syndrome, Morbus Kostmann, Haim-Munk syndrome, LL-37 and periodontitis and articles on pathogenicity of periodontitis.

Conclusion

The literature search concluded that LL-37 plays a pivotal role in preventing and treatment of severe form of periodontitis.

     

The degradation of nucleotide triphosphates extracted under boiling ethanol conditions is prevented by the yeast cellular matrix

Introduction

Boiling ethanol extraction is a frequently used method for metabolomics studies of biological samples. However, the stability of several central carbon metabolites, including nucleotide triphosphates, and the influence of the cellular matrix on their degradation have not been addressed.

Objectives

To study how a complex cellular matrix extracted from yeast (Saccharomyces cerevisiae) may affect the degradation profiles of nucleotide triphosphates extracted under boiling ethanol conditions.

Methods

We present a double-labelling LC–MS approach with a ¹³C-labeled yeast cellular extract as complex surrogate matrix, and ¹³C¹⁵N-labeled nucleotides as internal standards, to study the effect of the yeast matrix on the degradation of nucleotide triphosphates.

Results

While nucleotide triphosphates were degraded to the corresponding diphosphates in pure solutions, degradation was prevented in the presence of the yeast matrix under typical boiling ethanol extraction conditions.

Conclusions

Extraction of biological samples under boiling ethanol extraction conditions that rapidly inactivate enzyme activity are suitable for labile central energy metabolites such as nucleotide triphosphates due to the stabilizing effect of the yeast matrix. The basis of this phenomenon requires further study.

Graphical abstract

Open image in new window

     

Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

Background

With the development of sequencing technology, more and more long non-coding RNAs (lncRNAs) have been identified. Some lncRNAs have been confirmed that they play an important role in the process of development through the dosage compensation effect, epigenetic regulation, cell differentiation regulation and other aspects. However, the majority of the lncRNAs have not been functionally characterized. Explore the function of lncRNAs and the regulatory network has become a hot research topic currently.

Methods

In the work, a network-based model named BiRWLGO is developed. The ultimate goal is to predict the probable functions for lncRNAs at large scale. The new model starts with building a global network composed of three networks: lncRNA similarity network, lncRNA-protein association network and protein-protein interaction (PPI) network. After that, it utilizes bi-random walk algorithm to explore the similarities between lncRNAs and proteins. Finally, we can annotate an lncRNA with the Gene Ontology (GO) terms according to its neighboring proteins.

Results

We compare the performance of BiRWLGO with the state-of-the-art models on a manually annotated lncRNA benchmark with known GO terms. The experimental results assert that BiRWLGO outperforms other methods in terms of both maximum F-measure (F_max) and coverage.

Conclusions

BiRWLGO is a relatively efficient method to predict the functions of lncRNA. When protein interaction data is integrated, the predictive performance of BiRWLGO gains a great improvement.

     

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.