Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment

<p>Abstract</p> <p>Background</p> <p>A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution.</p> <p>Results</p> <p>Our experimentation with <it>E. coli </it>and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms; this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives.</p> <p>Conclusion</p> <p>Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influences the prediction accuracy of the PPC approach. We note that the predictive power of the PPC approach, especially in eukaryotes, is heavily influenced by the primary endosymbiosis and subsequent bacterial contributions. The over-representation of parasitic unicellular eukaryotes and vertebrates additionally make eukaryotes less useful in the reference sets. Reference sets composed of highly non-redundant set of genomes from all three super-kingdoms fare better with pathways showing considerable vertical inheritance and strong conservation (e.g. translation apparatus), while reference sets solely composed of prokaryotic genomes fare better for more variable pathways like carbohydrate metabolism. Differential performance of the PPC approach on various pathways, and a weak positive correlation between functional and profile similarities suggest that caution should be exercised while interpreting functional linkages inferred from genome-wide large-scale profile comparisons using a single reference set.</p

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Recessive Robinow syndrome, allelic to dominant brachydactyly type B, is caused by mutation of ROR2

The autosomal recessive form of Robinow syndrome (RRS; MIM 268310) is a severe skeletal dysplasia with generalized limb bone shortening, segmental defects of the spine, brachydactyly and a dysmorphic facial appearance(1-3). We previously mapped the gene mutated in RRS to chromosome 9q22 (ref. 4), a region that overlaps the locus for autosomal dominant brachydactyly type B (refs 5,6). The recent identification of ROR2, encoding an orphan receptor tyrosine kinase, as the gene mutated in brachydactyly type B (BDB1; ref. 7) and the mesomelic dwarfing in mice homozygous for a lacZ and/or a neo insertion into Ror2 (refs 8.9) made this gene a candidate for RRS. Here we report homozygous missense mutations in both intracellular and extracellular domains of ROR2 in affected individuals from 3 unrelated consanguineous families, and a nonsense mutation that removes the tyrosine kinase domain and all subsequent 3' regions of the gene in 14 patients from 7 families from Oman. The nature of these mutations suggests that RRS is caused by loss of ROR2 activity. The identification of mutations in three distinct domains (containing Frizzled-like, kringle and tyrosine kinase motifs) indicates that these are all essential for ROR2 function

Photodegradation kinetics and transformation products of ketoprofen, diclofenac and atenolol in pure water and treated wastewater

Pharmaceutical compounds such as ketoprofen, diclofenac and atenolol are frequently detected at relatively high concentrations in secondary effluents from wastewater treatment plants. Therefore, it is important to assess their transformation kinetics and intermediates in subsequent disinfection processes, such as direct ultraviolet (UV) irradiation. The photodegradation kinetics of these compounds using a medium pressure (MP) lamp was assessed in pure water, as well as in filtered and unfiltered treated wastewater. Ketoprofen had the highest time- and fluence-based rate constants in all experiments, whereas atenolol had the lowest values, which is consistent with the corresponding decadic molar absorption coefficient and quantum yield. The fluence-based rate constants of all compounds were evaluated in filtered and unfiltered wastewater matrices as well as in pure water. Furthermore, transformation products of ketoprofen, diclofenac and atenolol were identified and monitored throughout the irradiation experiments, and photodegradation pathways were proposed for each compound. This enabled the identification of persistent transformation products, which are potentially discharged from WWTP disinfection works employing UV photolysis

Spinocerebellar ataxia type 10: common haplotype and disease progression rate in Peru and Brazil

Background and purpose: Spinocerebellar ataxia type 10 is a neurodegenerative disorder that is due to an expanded ATTCT repeat tract in the ATXN10 gene. Our aim was to describe clinical characteristics and intragenic haplotypes of patients with spinocerebellar ataxia type 10 from Brazil and Peru. Methods: Expanded alleles were detected by repeat-primed polymerase chain reaction. Disease progression was measured by the Scale for the Assessment and Rating of Ataxia, and the Neurological Examination Score for Spinocerebellar Ataxias when possible. Haplotypes were constructed based on polymorphic markers within and outside the gene. Results: Thirteen new families were diagnosed (three from Peru). Patients from three Brazilian families diagnosed previously were also reassessed. In total, 25 individuals (16 families) were evaluated. Mean (+/-SD) age at onset and disease duration were 34.8 +/- 10.2 and 12 +/- 8 years, respectively. Common findings were ataxia, dysarthria/dysphagia, nystagmus, pyramidal signs, ophthalmoparesis and seizures. No associations were found between clinical findings and geographical origins. Twelve patients living in remote regions were examined only once. In the remaining individuals, the Scale for the Assessment and Rating of Ataxia score, and Neurological Examination Score for Spinocerebellar Ataxias worsened by 0.444 (95% CI, -0.088 to 0.800) and 0.287 (95% CI, -0.061 to 0.635) points/year, respectively. A common haplotype, 19CGGC14, was found in 11/13 of Brazilian and in 1/3 of Peruvian families. Conclusions: The progression rate was slower than in other spinocerebellar ataxias. A consistently recurrent intragenic haplotype was found, suggesting a common ancestry for most, if not all, patients.Conselho Nacional de Desenvolvimento Cientifico e TecnologicoInstituto Nacional de Genetica Medica PopulacionalFundacao de Amparo a Pesquisa do Estado do Rio Grande do SulFundo de Incentivo a Pesquisa e Eventos do HCPACNPqCtr Pesquisa Expt HCPA, Lab Identificacao Genet, Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Programa Posgrad Genet & Biol Mol, Porto Alegre, RS, BrazilHCPA, Serv Genet Med, Porto Alegre, RS, BrazilINAGEMP, Inst Genet Med Populac, Porto Alegre, RS, BrazilUniv Fed Sao Paulo, Dept Neurol, Div Neurol Geral, Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Neurol, Unidade Ataxia, Sao Paulo, BrazilUniv Fed Rio Grande do Norte, Natal, RN, BrazilCtr Reabilitacao Dr Henrique Santillo, Goiania, Go, BrazilUniv Fed Santa Catarina, Florianopolis, SC, BrazilUniv Sao Paulo, Ribeirao Preto, BrazilUniv Porto, Inst Biol Mol & Celular, UnIGENe, Oporto, PortugalInst Nacl Ciencias Neurol, Neurogenet Res Ctr, Lima, PeruUniv Fed Rio Grande do Sul, Dept Estat, Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Dept Med Interna, Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Dept Bioquim, Porto Alegre, RS, BrazilUniv Fed Sao Paulo, Dept Neurol, Div Neurol Geral, Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Neurol, Unidade Ataxia, Sao Paulo, BrazilCNPqINaGeMPFAPERGSFIPE-HCPACNPqWeb of Scienc