Improved de novo peptide sequencing using LC retention time information

Background

Liquid chromatography combined with tandem mass spectrometry is an important tool in proteomics for peptide identification. Liquid chromatography temporally separates the peptides in a sample. The peptides that elute one after another are analyzed via tandem mass spectrometry by measuring the mass-to-charge ratio of a peptide and its fragments. De novo peptide sequencing is the problem of reconstructing the amino acid sequences of a peptide from this measurement data. Past de novo sequencing algorithms solely consider the mass spectrum of the fragments for reconstructing a sequence.

Results

We propose to additionally exploit the information obtained from liquid chromatography. We study the problem of computing a sequence that is not only in accordance with the experimental mass spectrum, but also with the chromatographic retention time. We consider three models for predicting the retention time and develop algorithms for de novo sequencing for each model.

Conclusions

Based on an evaluation for two prediction models on experimental data from synthesized peptides we conclude that the identification rates are improved by exploiting the chromatographic information. In our evaluation, we compare our algorithms using the retention time information with algorithms using the same scoring model, but not the retention time.

     

New eight genes identified at the clinical multidrug-resistant <Emphasis Type="Italic">Acinetobacter baumannii</Emphasis> DMS06669 strain in a Vietnam hospital

Background

Acinetobacter baumannii is an important nosocomial pathogen that can develop multidrug resistance. In this study, we characterized the genome of the A. baumannii strain DMS06669 (isolated from the sputum of a male patient with hospital-acquired pneumonia) and focused on identification of genes relevant to antibiotic resistance.

Methods

Whole genome analysis of A. baumannii DMS06669 from hospital-acquired pneumonia patients included de novo assembly; gene prediction; functional annotation to public databases; phylogenetics tree construction and antibiotics genes identification.

Results

After sequencing the A. baumannii DMS06669 genome and performing quality control, de novo genome assembly was carried out, producing 24 scaffolds. Public databases were used for gene prediction and functional annotation to construct a phylogenetic tree of the DMS06669 strain with 21 other A. baumannii strains. A total of 18 possible antibiotic resistance genes, conferring resistance to eight distinct classes of antibiotics, were identified. Eight of these genes have not previously been reported to occur in A. baumannii.

Conclusions

Our results provide important information regarding mechanisms that may contribute to antibiotic resistance in the DMS06669 strain, and have implications for treatment of patients infected with A. baumannii.

     

Genomic analysis of membrane protein families: abundance and conserved motifs

Background

Polytopic membrane proteins can be related to each other on the basis of the number of transmembrane helices and sequence similarities. Building on the Pfam classification of protein domain families, and using transmembrane-helix prediction and sequence-similarity searching, we identified a total of 526 well-characterized membrane protein families in 26 recently sequenced genomes. To this we added a clustering of a number of predicted but unclassified membrane proteins, resulting in a total of 637 membrane protein families.

Results

Analysis of the occurrence and composition of these families revealed several interesting trends. The number of assigned membrane protein domains has an approximately linear relationship to the total number of open reading frames (ORFs) in 26 genomes studied. Caenorhabditis elegans is an apparent outlier, because of its high representation of seven-span transmembrane (7-TM) chemoreceptor families. In all genomes, including that of C. elegans, the number of distinct membrane protein families has a logarithmic relation to the number of ORFs. Glycine, proline, and tyrosine locations tend to be conserved in transmembrane regions within families, whereas isoleucine, valine, and methionine locations are relatively mutable. Analysis of motifs in putative transmembrane helices reveals that GxxxG and GxxxxxxG (which can be written GG4 and GG7, respectively; see Materials and methods) are among the most prevalent. This was noted in earlier studies; we now find these motifs are particularly well conserved in families, however, especially those corresponding to transporters, symporters, and channels.

Conclusions

We carried out a genome-wide analysis on patterns of the classified polytopic membrane protein families and analyzed the distribution of conserved amino acids and motifs in the transmembrane helix regions in these families.

     

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.

     

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

Background

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening.

Results

Herein, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, and proteogenic and metabolic output analysis.

Conclusions

Taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.

     

Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction

Background

RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily combine different sources of information that can be expressed probabilistically, such as an evolutionary model of comparative RNA sequence analysis and a biophysical model of structure plausibility. However, the number of free parameters in an integrated model for consensus RNA structure prediction can become untenable if the underlying SCFG design is too complex. Thus a key question is, what small, simple SCFG designs perform best for RNA secondary structure prediction?

Results

Nine different small SCFGs were implemented to explore the tradeoffs between model complexity and prediction accuracy. Each model was tested for single sequence structure prediction accuracy on a benchmark set of RNA secondary structures.

Conclusions

Four SCFG designs had prediction accuracies near the performance of current energy minimization programs. One of these designs, introduced by Knudsen and Hein in their PFOLD algorithm, has only 21 free parameters and is significantly simpler than the others.

     

Role of <Emphasis Type="Italic">PUF60</Emphasis> gene in Verheij syndrome: a case report of the first Chinese Han patient with a de novo pathogenic variant and review of the literature

Background

Verheij syndrome is a rare microdeletion syndrome of chromosome 8q24.3 that harbors PUF60, SCRIB, and NRBP2 genes. Subsequently, loss of function mutations in PUF60 have been found in children with clinical features significantly overlapping with Verheij.

Case presentation

Here we present the first Chinese Han patient with a de novo nonsense variant (c.1357C?>?T, p.Gln453*) in PUF60 by clinical whole exome sequencing. The 5-year-old boy presents with dysmorphic facial features, intellectual disability, and growth retardation but without apparent cardiac, renal, ocular, and spinal anomalies.

Conclusions

Our finding contributes to the understanding of the genotype and phenotype in PUF60 related disorder.

     

An Initial Investigation of an Alternative Model to Study rat Primordial Germ Cell Epigenetic Reprogramming

Background

Primordial germ cells (PGC) are the precursors of the gametes. During pre-natal development, PGC undergo an epigenetic reprogramming when bulk DNA demethylation occurs and is followed by sex-specific de novo methylation. The de novo methylation and the maintenance of the methylation patterns depend on DNA methyltransferases (DNMTs). PGC reprogramming has been widely studied in mice but not in rats. We have previously shown that the rat might be an interesting model to study germ cell development. In face of the difficulties of getting enough PGC for molecular studies, the aim of this study was to propose an alternative method to study rat PGC DNA methylation. Rat embryos were collected at 14, 15 and 19 days post-coitus (dpc) for the analysis of 5mC, 5hmC, DNMT1, DNMT3a and DNMT3b expression or at 16dpc for treatment 5-Aza-CdR, a DNMT inhibitor, in vitro.

Methods

Once collected, the gonads were placed in 24-well plates previously containing 45μm pore membrane and medium with or without 5-Aza-CdR. The culture was kept for five days and medium was changed daily. The gonads were either fixed or submitted to RNA extraction.

Results

5mC and DNMTs labelling suggests that PGC are undergoing epigenetic reprogramming around 14/15dpc. The in vitro treatment of rat embryonic gonads with 1 μM of 5-Aza-CdR lead to a loss of 5mC labelling and to the activation of Pax6 expression in PGC, but not in somatic cells, suggesting that 5-Aza-CdR promoted a PGC-specific global DNA hypomethylation.

Conclusions

This study suggests that the protocol used here can be a potential method to study the wide DNA demethylation that takes place during PGC reprogramming.

     

Consensus structural models for the amino terminal domain of the retrovirus restriction gene <Emphasis Type="Italic">Fv1</Emphasis> and the Murine Leukaemia Virus capsid proteins

Background

The mouse Fv1 (friend virus) susceptibility gene inhibits the development of the murine leukaemia virus (MLV) by interacting with its capsid (CA) protein. As no structures are available for these proteins we have constructed molecular models based on distant sequence similarity to other retroviral capsid proteins.

Results

Molecular models were constructed for the amino terminal domains of the probable capsid-like structure for the mouse Fv1 gene product and the capsid protein of the MLV. The models were based on sequence alignments with a variety of other retrovirus capsid proteins. As the sequence similarity of these proteins with MLV and especially Fv1 is very distant, a threading method was employed that incorporates predicted secondary structure and multiple sequence information. The resulting models were compared with equivalent models constructed using the sequences of the capsid proteins of known structure.

Conclusions

These comparisons suggested that the MLV model should be accurate in the core but with significant uncertainty in the loop regions. The Fv1 model may have some additional errors in the core packing of its helices but the resulting model gave some support to the hypothesis that it adopts a capsid-like structure.

     

Expression and purification of classical swine fever virus E2 protein from Sf9 cells using a modified vector

Objective

To develop a simple method for efficient expression of classical swine fever virus (CSFV) E2 protein.

Results

The pFastBac HT B vector (pFastHTB-M1) was modified by adding a melittin signal peptide sequence. The E2 gene fragment without the transmembrane region was cloned into pFastHTB-M1. The modified vector has clear advantage over the original one, as evidenced by the purified recombinant E2 protein that was detected significantly by SDS-PAGE.

Conclusions

The modified vector has the potential for large-scale production and easy purification of the CSFV E2 protein or other proteins of interests.

     

IMP/GTP balance modulates cytoophidium assembly and IMPDH activity

Background

Inosine monophosphate dehydrogenase (IMPDH), the rate-limiting enzyme in de novo GTP biosynthesis, plays an important role in cell metabolism and proliferation. It has been demonstrated that IMPDH can aggregate into a macrostructure, termed the cytoophidium, in mammalian cells under a variety of conditions. However, the regulation and function of the cytoophidium are still elusive.

Results

In this study, we report that spontaneous filamentation of IMPDH is correlated with rapid cell proliferation. Intracellular IMP accumulation promoted cytoophidium assembly, whereas elevated GTP level triggered disassociation of aggregates. By using IMPDH2 CBS domain mutant cell models, which are unable to form the cytoophidium, we have determined that the cytoophidium is of the utmost importance for maintaining the GTP pool and normal cell proliferation in the condition that higher IMPDH activity is required.

Conclusions

Together, our results suggest a novel mechanism whereby cytoophidium assembly upregulates IMPDH activity and mediates guanine nucleotide homeostasis.

     

Medium chain fatty acids in intrauterine growth restricted and small for gestational age pregnancies

Introduction

Low birth weight is associated with an increased risk of heart disease, high blood pressure and diabetes in adult life. Fetal growth is determined by nutrient availability, which is related to placenta nutrient transport. Medium chain fatty acids (MCFAs) are a particular class of nutrients, known to be a readily available energy source. Until now no data are reported on these MCFAs in low birth weight fetus.

Aim

This is a prospective study conducted in a tertiary center of prenatal diagnosis to investigate the maternal and fetal MCFAs levels in appropriate for gestational age (AGA), intrauterine growth restricted (IUGR), and small for gestational age (SGA) pregnancies.

Method

The plasmatic levels of MCFAs in AGA, IUGR and SGA mother–infant pairs were quantified by gas chromatography–mass spectrometry. The analytical method had a linearity range of 0.1–50 mg/L and a limit of quantification of 0.03 mg/L. Reduced fetal growth was defined as an estimated fetal weight below the 3rd–10th percentile for gestational age, with (IUGR) or without (SGA) fetal Doppler abnormalities.

Result

Maternal and fetal MCFAs plasma levels were significantly different among SGA, IUGR and AGA groups. Additionally, the observed MCFAs fetal to maternal ratio is >1 for IUGR group, whilst for SGA and AGA the fetal to maternal ratio is less than one.

Conclusion

Changes in MCFAs levels in fetal and maternal plasma are not related to placental functionality or nutrients availability, suggesting the presence of a de novo biosynthesis.

     

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.

     

Reengineering substrate specificity of <Emphasis Type="Italic">E. coli</Emphasis> glutamate dehydrogenase using a position-based prediction method

Objective

To re-engineer the active site of proteins for non-natural substrates using a position-based prediction method (PBPM).

Results

The approach has been applied to re-engineer the E. coli glutamate dehydrogenase to alter its substrate from glutamate to homoserine for a de novo 1,3-propanediol biosynthetic pathway. After identification of key residues that determine the substrate specificity, residue K92 was selected as a candidate site for mutation. Among the three mutations (K92V, K92C, and K92M) suggested by PBPM, the specific activity of the best mutant (K92 V) was increased from 171 ± 35 to 1328 ± 71 μU mg^?1.

Conclusion

The PBPM approach has a high efficiency for re-engineering the substrate specificity of natural enzymes for new substrates.

     

A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction

Background

Elucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured.

Methods

We propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima.

Results and conclusions

Results show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions.

     

Prediction of heme binding residues from protein sequences with integrative sequence profiles

Background

The heme-protein interactions are essential for various biological processes such as electron transfer, catalysis, signal transduction and the control of gene expression. The knowledge of heme binding residues can provide crucial clues to understand these activities and aid in functional annotation, however, insufficient work has been done on the research of heme binding residues from protein sequence information.

Methods

We propose a sequence-based approach for accurate prediction of heme binding residues by a novel integrative sequence profile coupling position specific scoring matrices with heme specific physicochemical properties. In order to select the informative physicochemical properties, we design an intuitive feature selection scheme by combining a greedy strategy with correlation analysis.

Results

Our integrative sequence profile approach for prediction of heme binding residues outperforms the conventional methods using amino acid and evolutionary information on the 5-fold cross validation and the independent tests.

Conclusions

The novel feature of an integrative sequence profile achieves good performance using a reduced set of feature vector elements.

     

Harnessing Whole Genome Sequencing in Medical Mycology

Purpose of Review

Comparative genome sequencing studies of human fungal pathogens enable identification of genes and variants associated with virulence and drug resistance. This review describes current approaches, resources, and advances in applying whole genome sequencing to study clinically important fungal pathogens.

Recent Findings

Genomes for some important fungal pathogens were only recently assembled, revealing gene family expansions in many species and extreme gene loss in one obligate species. The scale and scope of species sequenced is rapidly expanding, leveraging technological advances to assemble and annotate genomes with higher precision. By using iteratively improved reference assemblies or those generated de novo for new species, recent studies have compared the sequence of isolates representing populations or clinical cohorts. Whole genome approaches provide the resolution necessary for comparison of closely related isolates, for example, in the analysis of outbreaks or sampled across time within a single host.

Summary

Genomic analysis of fungal pathogens has enabled both basic research and diagnostic studies. The increased scale of sequencing can be applied across populations, and new metagenomic methods allow direct analysis of complex samples.

     

Transient decrease of hepatic NAD<Superscript>+</Superscript> and amino acid alterations during treatment with valproate: new insights on drug-induced effects in vivo using targeted MS-based metabolomics

Background

Therapeutic administration of the drug valproate (VPA) results in metabolic changes at the hepatic level that have not been fully characterized. Interference of this branched-chain fatty acid with the oxidative metabolism of amino acids may have consequences for the downstream biosynthesis of essential cofactors.

Objectives

We aimed to evaluate the effect of VPA on amino acid and NAD⁺ metabolism using targeted MS-based metabolite profiling.

Methods

Plasma samples from patients under chronic treatment with VPA were analyzed. VPA was administered to Wistar rats mimicking prolonged and acute treatment, the latter with two different doses. Plasma and liver samples were collected for targeted metabolomics studies using UPLC-MS/MS and GC-FID.

Results

Analysis of amino acids in rat plasma and liver and in human plasma demonstrated that drug intake is associated with a particularly significant drop in the levels of tryptophan, and increased levels of glycine and lysine. The lowered plasma tryptophan levels prompted us to study the intracellular content of tryptophan and various nicotinamide adenine dinucleotides. A significant decrease of NAD⁺ and NADP⁺ was observed in the liver of rats after the single administration of VPA at two different doses, but not after repeated administration.

Conclusion

The observed accumulation of kynurenine intermediates in rat liver tissue suggests a drug-induced interference with the de novo pathway of NAD⁺ biosynthesis. These findings provide novel insights into the mechanisms of VPA associated hepatocellular dysfunction and/or toxicity, but with possible major relevance to the anticancer effects of the drug.