Diversifying Selection Underlies the Origin of Allozyme Polymorphism at the Phosphoglucose Isomerase Locus in Tigriopus californicus

The marine copepod Tigriopus californicus lives in intertidal rock pools along the Pacific coast, where it exhibits strong, temporally stable population genetic structure. Previous allozyme surveys have found high frequency private alleles among neighboring subpopulations, indicating that there is limited genetic exchange between populations. Here we evaluate the factors responsible for the diversification and maintenance of alleles at the phosphoglucose isomerase (Pgi) locus by evaluating patterns of nucleotide variation underlying previously identified allozyme polymorphism. Copepods were sampled from eleven sites throughout California and Baja California, revealing deep genetic structure among populations as well as genetic variability within populations. Evidence of recombination is limited to the sample from Pescadero and there is no support for linkage disequilibrium across the Pgi locus. Neutrality tests and codon-based models of substitution suggest the action of natural selection due to elevated non-synonymous substitutions at a small number of sites in Pgi. Two sites are identified as the charge-changing residues underlying allozyme polymorphisms in T. californicus. A reanalysis of allozyme variation at several focal populations, spanning a period of 26 years and over 200 generations, shows that Pgi alleles are maintained without notable frequency changes. Our data suggest that diversifying selection accounted for the origin of Pgi allozymes, while McDonald-Kreitman tests and the temporal stability of private allozyme alleles suggests that balancing selection may be involved in the maintenance of amino acid polymorphisms within populations

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.Jon Agirre is a Royal Society University Research Fellow (UF160039 and URF\R\221006). Mihaela Atanasova is funded by the UK Engineering and Physical Sciences Research Council (EPSRC; EP/R513386/1). Haroldas Bagdonas is funded by The Royal Society (RGF/R1/181006). Jose´ Javier Burgos-Ma´rmol and Daniel J. Rigden are supported by the BBSRC (BB/S007105/1). Robbie P. Joosten is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 871037 (iNEXTDiscovery) and by CCP4. This work was supported by the Medical Research Council as part of United Kingdom Research and Innovation, also known as UK Research and Innovation: MRC file reference No. MC_UP_A025_1012 to Garib N. Murshudov, which also funded Keitaro Yamashita, Paul Emsley and Fei Long. Robert A. Nicholls is funded by the BBSRC (BB/S007083/1). Soon Wen Hoh is funded by the BBSRC (BB/T012935/1). Kevin D. Cowtan and Paul S. Bond are funded in part by the BBSRC (BB/S005099/1). John Berrisford and Sameer Velankar thank the European Molecular Biology Laboratory–European Bioinformatics Institute, who supported this work. Andrea Thorn was supported in the development of AUSPEX by the German Federal Ministry of Education and Research (05K19WWA and 05K22GU5) and by Deutsche Forschungsgemeinschaft (TH2135/2-1). Petr Kolenko and Martin Maly´ are funded by the MEYS CR (CZ.02.1.01/0.0/0.0/16_019/0000778). Martin Maly´ is funded by the Czech Academy of Sciences (86652036) and CCP4/STFC (521862101). Anastassis Perrakis acknowledges funding from iNEXT (grant No. 653706), iNEXT-Discovery (grant No. 871037), West-Life (grant No. 675858) and EOSC-Life (grant No. 824087) funded by the Horizon 2020 program of the European Commission. Robbie P. Joosten has been the recipient of a Veni grant (722.011.011) and a Vidi grant (723.013.003) from the Netherlands Organization for Scientific Research (NWO). Maarten L. Hekkelman, Robbie P. Joosten and Anastassis Perrakis thank the Research High Performance Computing facility of the Netherlands Cancer Institute for providing and maintaining computation resources and acknowledge the institutional grant from the Dutch Cancer Society and the Dutch Ministry of Health, Welfare and Sport. Tarik R. Drevon is funded by the BBSRC (BB/S007040/1). Randy J. Read is supported by a Principal Research Fellowship from the Wellcome Trust (grant 209407/Z/17/Z). Atlanta G. Cook is supported by a Wellcome Trust SRF (200898) and a Wellcome Centre for Cell Biology core grant (203149). Isabel Uso´n acknowledges support from STFC-UK/CCP4: ‘Agreement for the integration of methods into the CCP4 software distribution, ARCIMBOLDO_LOW’ and Spanish MICINN/AEI/FEDER/UE (PID2021-128751NB-I00). Pavol Skubak and Navraj Pannu were funded by the NWO Applied Sciences and Engineering Domain and CCP4 (grant Nos. 13337 and 16219). Bernhard Lohkamp was supported by the Ro¨ntgen A˚ ngstro¨m Cluster (grant 349-2013-597). Nicholas Pearce is currently funded by the SciLifeLab and Wallenberg Data Driven Life Science Program (grant KAW 2020.0239) and has previously been funded by a Veni Fellowship (VI.Veni.192.143) from the Dutch Research Council (NWO), a Long-term EMBO fellowship (ALTF 609-2017) and EPSRC grant EP/G037280/1. David M. Lawson received funding from BBSRC Institute Strategic Programme Grants (BB/P012523/1 and BB/P012574/1). Lucrezia Catapano is the recipient of an STFC/CCP4-funded PhD studentship (Agreement No: 7920 S2 2020 007).Peer reviewe

The CCP4 suite : integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world

Normalization to Specific Gravity Prior to Analysis Improves Information Recovery from High Resolution Mass Spectrometry Metabolomic Profiles of Human Urine

Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets

Adductomic signatures of benzene exposure provide insights into cancer induction

Although benzene has long been recognized as a cause of human leukemia, the mechanism by which this simple molecule causes cancer has been problematic. A complicating factor is benzene metabolism, which produces many reactive intermediates, some specific to benzene and others derived from redox processes. Using archived serum from 20 nonsmoking Chinese workers, 10 with and 10 without occupational exposure to benzene (exposed: 3.2-88.9 ppm, controls: 0.002-0.020 ppm), we employed an adductomic pipeline to characterize protein modifications at Cys34 of human serum albumin, a nucleophilic hotspot in extracellular fluids. Of the 47 measured human serum albumin modifications, 39 were present at higher concentrations in benzene-exposed workers than in controls and many of the exposed-control differences were statistically significant. Correlation analysis identified three prominent clusters of adducts, namely putative modifications by benzene oxide and a benzene diolepoxide that grouped with other measures of benzene exposure, adducts of reactive oxygen and carbonyl species, and Cys34 disulfides of small thiols that are formed following oxidation of Cys34. Benzene diolepoxides are potent mutagens and carcinogens that have received little attention as potential causes of human leukemia. Reactive oxygen and carbonyl species-generated by redox processes involving polyphenolic benzene metabolites and by Cyp2E1 regulation following benzene exposure-can modify DNA and proteins in ways that contribute to cancer. The fact that these diverse human serum albumin modifications differed between benzene-exposed and control workers suggests that benzene can increase leukemia risks via multiple pathways involving a constellation of reactive molecules

Cys34 Adductomes Differ between Patients with Chronic Lung or Heart Disease and Healthy Controls in Central London

Oxidative stress generates reactive species that modify proteins, deplete antioxidant defenses, and contribute to chronic obstructive pulmonary disease (COPD) and ischemic heart disease (IHD). To determine whether protein modifications differ between COPD or IHD patients and healthy subjects, we performed untargeted analysis of adducts at the Cys34 locus of human serum albumin (HSA). Biospecimens were obtained from nonsmoking participants from London, U.K., including healthy subjects (<i>n</i> = 20) and patients with COPD (<i>n</i> = 20) or IHD (<i>n</i> = 10). Serum samples were digested with trypsin and analyzed by liquid chromatography-high resolution mass spectrometry. Effects of air pollution on adduct levels were also investigated based on estimated residential exposures to PM_2.5, O₃ and NO₂. For the 39 adducts with sufficient data, levels were essentially identical in blood samples collected from the same subjects on two consecutive days, consistent with the 28 day residence time of HSA. Multivariate linear regression revealed 21 significant associations, mainly with the underlying diseases but also with air-pollution exposures (<i>p</i>-value < 0.05). Interestingly, most of the associations indicated that adduct levels decreased with the presence of disease or increased pollutant concentrations. Negative associations of COPD and IHD with the Cys34 disulfide of glutathione and two Cys34 sulfoxidations, were consistent with previous results from smoking and nonsmoking volunteers and nonsmoking women exposed to indoor combustion of coal and wood

Aspirin-triggered 15-epi-lipoxin A 4 predicts cyclooxygenase-2 in the lungs of LPS-treated mice but not in the circulation: implications for a clinical test A. Aspirin- triggered 15-epi-lipoxin A 4 predicts cyclooxygenase-2 in the lungs of LPS-treated mic

ABSTRACT Inhibition of cyclooxygenase (COX)

compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC–MS Data Sets

A long-standing challenge of untargeted metabolomic profiling by ultrahigh-performance liquid chromatography–high-resolution mass spectrometry (UHPLC–HRMS) is efficient transition from unknown mass spectral features to confident metabolite annotations. The <i>compMS</i>²<i>Miner</i> (Comprehensive MS² Miner) package was developed in the R language to facilitate rapid, comprehensive feature annotation using a peak-picker-output and MS² data files as inputs. The number of MS² spectra that can be collected during a metabolomic profiling experiment far outweigh the amount of time required for pain-staking manual interpretation; therefore, a degree of software workflow autonomy is required for broad-scale metabolite annotation. <i>CompMS</i>²<i>Miner</i> integrates many useful tools in a single workflow for metabolite annotation and also provides a means to overview the MS² data with a Web application GUI <i>compMS</i>²<i>Explorer</i> (Comprehensive MS² Explorer) that also facilitates data-sharing and transparency. The automatable <i>compMS</i>²<i>Miner</i> workflow consists of the following steps: (i) matching unknown MS¹ features to precursor MS² scans, (ii) filtration of spectral noise (dynamic noise filter), (iii) generation of composite mass spectra by multiple similar spectrum signal summation and redundant/contaminant spectra removal, (iv) interpretation of possible fragment ion substructure using an internal database, (v) annotation of unknowns with chemical and spectral databases with prediction of mammalian biotransformation metabolites, wrapper functions for <i>in silico</i> fragmentation software, nearest neighbor chemical similarity scoring, random forest based retention time prediction, text-mining based false positive removal/true positive ranking, chemical taxonomic prediction and differential evolution based global annotation score optimization, and (vi) network graph visualizations, data curation, and sharing are made possible via the <i>compMS</i>²<i>Explorer</i> application. Metabolite identities and comments can also be recorded using an interactive table within <i>compMS</i>²<i>Explorer</i>. The utility of the package is illustrated with a data set of blood serum samples from 7 diet induced obese (DIO) and 7 nonobese (NO) C57BL/6J mice, which were also treated with an antibiotic (streptomycin) to knockdown the gut microbiota. The results of fully autonomous and objective usage of <i>compMS</i>²<i>Miner</i> are presented here. All automatically annotated spectra output by the workflow are provided in the Supporting Information and can alternatively be explored as publically available <i>compMS</i>²<i>Explorer</i> applications for both positive and negative modes (https://wmbedmands.shinyapps.io/compMS2_mouseSera_POS and https://wmbedmands.shinyapps.io/compMS2_mouseSera_NEG). The workflow provided rapid annotation of a diversity of endogenous and gut microbially derived metabolites affected by both diet and antibiotic treatment, which conformed to previously published reports. Composite spectra (<i>n</i> = 173) were autonomously matched to entries of the Massbank of North America (MoNA) spectral repository. These experimental and virtual (lipidBlast) spectra corresponded to 29 common endogenous compound classes (e.g., 51 lysophosphatidylcholines spectra) and were then used to calculate the ranking capability of 7 individual scoring metrics. It was found that an average of the 7 individual scoring metrics provided the most effective weighted average ranking ability of 3 for the MoNA matched spectra in spite of potential risk of false positive annotations emerging from automation. Minor structural differences such as relative carbon–carbon double bond positions were found in several cases to affect the correct rank of the MoNA annotated metabolite. The latest release and an example workflow is available in the package vignette (https://github.com/WMBEdmands/compMS2Miner) and a version of the published application is available on the shinyapps.io site (https://wmbedmands.shinyapps.io/compMS2Example)

Profiling the Serum Albumin Cys34 Adductome of Solid Fuel Users in Xuanwei and Fuyuan, China

Xuanwei and Fuyuan counties in China have the highest lung cancer rates in the world due to household air pollution from combustion of smoky coal for cooking and heating. To discover potential biomarkers of indoor combustion products, we profiled adducts at the Cys34 locus of human serum albumin (HSA) in 29 nonsmoking Xuanwei and Fuyuan females who used smoky coal, smokeless coal, or wood and 10 local controls who used electricity or gas fuel. Our untargeted “adductomics” method detected 50 tryptic peptides of HSA, containing Cys34 and prominent post-translational modifications. Putative adducts included Cys34 oxidation products, mixed disulfides, rearrangements, and truncations. The most significant differences in adduct levels across fuel types were observed for <i>S</i>-glutathione (<i>S</i>-GSH) and <i>S</i>-γ-glutamylcysteine (<i>S</i>-γ-GluCys), both of which were present at lower levels in subjects exposed to combustion products than in controls. After adjustment for age and personal measurements of airborne benzo­(<i>a</i>)­pyrene, the largest reductions in levels of <i>S</i>-GSH and <i>S</i>-γ-GluCys relative to controls were observed for users of smoky coal, compared to users of smokeless coal and wood. These results point to possible depletion of GSH, an essential antioxidant, and its precursor γ-GluCys in nonsmoking females exposed to indoor-combustion products in Xuanwei and Fuyuan, China