Applicability of tandem affinity purification MudPIT to pathway proteomics in yeast

A combined multidimensional chromatography-mass spectrometry approach known as "MudPIT" enables rapid identification of proteins that interact with a tagged bait while bypassing some of the problems associated with analysis of polypeptides excised from SDS-polyacrylamide gels. However, the reproducibility, success rate, and applicability of MudPIT to the rapid characterization of dozens of proteins have not been reported. We show here that MudPIT reproducibly identified bona fide partners for budding yeast Gcn5p. Additionally, we successfully applied MudPIT to rapidly screen through a collection of tagged polypeptides to identify new protein interactions. Twenty-five proteins involved in transcription and progression through mitosis were modified with a new tandem affinity purification (TAP) tag. TAP-MudPIT analysis of 22 yeast strains that expressed these tagged proteins uncovered known or likely interacting partners for 21 of the baits, a figure that compares favorably with traditional approaches. The proteins identified here comprised 102 previously known and 279 potential physical interactions. Even for the intensively studied Swi2p/Snf2p, the catalytic subunit of the Swi/Snf chromatin remodeling complex, our analysis uncovered a new interacting protein, Rtt102p. Reciprocal tagging and TAP-MudPIT analysis of Rtt102p revealed subunits of both the Swi/Snf and RSC complexes, identifying Rtt102p as a common interactor with, and possible integral component of, these chromatin remodeling machines. Our experience indicates it is feasible for an investigator working with a single ion trap instrument in a conventional molecular/cellular biology laboratory to carry out proteomic characterization of a pathway, organelle, or process (i.e. "pathway proteomics") by systematic application of TAP-MudPIT

Myocardial Dysfunction in an Animal Model of Cancer Cachexia

Aims Fatigue is a common occurrence in cancer patients regardless of tumor type or anti-tumor therapies and is an especially problematic symptom in persons with incurable tumor disease. In rodents, tumor-induced fatigue is associated with a progressive loss of skeletal muscle mass and increased expression of biomarkers of muscle protein degradation. The purpose of the present study was to determine if muscle wasting and expression of biomarkers of muscle protein degradation occur in the hearts of tumor-bearing mice, and if these effects of tumor growth are associated with changes in cardiac function. Main methods The colon26 adenocarcinoma cell line was implanted into female CD2F1 mice and skeletal muscle wasting, in vivo heart function, in vitro cardiomyocyte function, and biomarkers of muscle protein degradation were determined. Key findings Expression of biomarkers of protein degradation were increased in both the gastrocnemius and heart muscle of tumor-bearing mice and caused systolic dysfunction in vivo. Cardiomyocyte function was significantly depressed during both cellular contraction and relaxation. Significance These results suggest that heart muscle is directly affected by tumor growth, with myocardial function more severely compromised at the cellular level than what is observed using echocardiography

Bandt-Pompe symbolization dynamics for time series with tied values: A data-driven approach

In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which the permutation entropy can be evaluated. Equalities in the analyzed sequence, for example, repeated equal values, deserve special attention and treatment as was shown recently by Zunino and co-workers [Phys. Lett. A 381, 1883 (2017)]. A significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. In the present contribution, we review the different existing methodologies for treating time series with tied values by classifying them according to their different strategies. In addition, a novel data-driven imputation is presented that proves to outperform the existing methodologies and avoid the false conclusions pointed by Zunino and co-workers.Fil: Traversaro Varela, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Lanús; ArgentinaFil: Redelico, Francisco Oscar. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; ArgentinaFil: Risk, Marcelo. Hospital Italiano; Argentina. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Frery, Alejandro César. Universidade Federal de Alagoas; BrasilFil: Rosso, Osvaldo Aníbal. Hospital Italiano; Argentina. Universidade Federal de Alagoas; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Los Andes; Chil

Alternative global Cretaceous paleogeography

Plate tectonic reconstructions for the Cretaceous have assumed that the major continental blocks—Eurasia, Greenland, North America, South America, Africa, India, Australia, and Antarctica—had separated from one another by the end of the Early Cretaceous, and that deep ocean passages connected the Pacific, Tethyan, Atlantic, and Indian Ocean basins. North America, Eurasia, and Africa were crossed by shallow meridional seaways. This classic view of Cretaceous paleogeography may be incorrect. The revised view of the Early Cretaceous is one of three large continental blocks— North America–Eurasia, South America–Antarctica-India-Madagascar-Australia; and Africa—with large contiguous land areas surrounded by shallow epicontinental seas. There was a large open Pacific basin, a wide eastern Tethys, and a circum- African Seaway extending from the western Tethys (“Mediterranean”) region through the North and South Atlantic into the juvenile Indian Ocean between Madagascar-India and Africa. During the Early Cretaceous the deep passage from the Central Atlantic to the Pacific was blocked by blocks of northern Central America and by the Caribbean plate. There were no deep-water passages to the Arctic. Until the Late Cretaceous the Atlantic-Indian Ocean complex was a long, narrow, sinuous ocean basin extending off the Tethys and around Africa. Deep passages connecting the western Tethys with the Central Atlantic, the Central Atlantic with the Pacific, and the South Atlantic with the developing Indian Ocean appeared in the Late Cretaceous. There were many island land areas surrounded by shallow epicontinental seas at high sea-level stands

Globally sparse PLS regression

Volume 56 ; Print ISBN : 978-1-4614-8282-6Partial least squares (PLS) regression combines dimensionality reduction and prediction using a latent variable model. It provides better predictive ability than principle component analysis by taking into account both the independent and re- sponse variables in the dimension reduction procedure. However, PLS suffers from over-fitting problems for few samples but many variables. We formulate a new criterion for sparse PLS by adding a structured sparsity constraint to the global SIMPLS optimization. The constraint is a sparsity-inducing norm, which is useful for selecting the important variables shared among all the components. The optimization is solved by an augmented Lagrangian method to obtain the PLS components and to perform variable selection simultaneously. We propose a novel greedy algorithm to overcome the computation difficulties. Experiments demonstrate that our approach to PLS regression attains better performance with fewer selected predictor

Multi-target genome editing reduces polyphenol oxidase activity in wheat (Triticum aestivum L.) grains

Introduction: Polyphenol oxidases (PPO) are dual activity metalloenzymes that catalyse the production of quinones. In plants, PPO activity may contribute to biotic stress resistance and secondary metabolism but is undesirable for food producers because it causes the discolouration and changes in flavour profiles of products during post-harvest processing. In wheat (Triticum aestivum L.), PPO released from the aleurone layer of the grain during milling results in the discolouration of flour, dough, and end-use products, reducing their value. Loss-of-function mutations in the PPO1 and PPO2 paralogous genes on homoeologous group 2 chromosomes confer reduced PPO activity in the wheat grain. However, limited natural variation and the proximity of these genes complicates the selection of extremely low-PPO wheat varieties by recombination. The goal of the current study was to edit all copies of PPO1 and PPO2 to drive extreme reductions in PPO grain activity in elite wheat varieties. Results: A CRISPR/Cas9 construct with one single guide RNA (sgRNA) targeting a conserved copper binding domain was used to edit all seven PPO1 and PPO2 genes in the spring wheat cultivar ‘Fielder’. Five of the seven edited T1 lines exhibited significant reductions in PPO activity, and T2 lines had PPO activity up to 86.7% lower than wild-type. The same construct was transformed into the elite winter wheat cultivars ‘Guardian’ and ‘Steamboat’, which have five PPO1 and PPO2 genes. In these varieties PPO activity was reduced by >90% in both T1 and T2 lines. In all three varieties, dough samples from edited lines exhibited reduced browning. Discussion: This study demonstrates that multi-target editing at late stages of variety development could complement selection for beneficial alleles in cropbreeding programs by inducing novel variation in loci inaccessible to recombinatio

Predicting Crystal Structures with Data Mining of Quantum Calculations

Predicting and characterizing the crystal structure of materials is a key problem in materials research and development. It is typically addressed with highly accurate quantum mechanical computations on a small set of candidate structures, or with empirical rules that have been extracted from a large amount of experimental information, but have limited predictive power. In this letter, we transfer the concept of heuristic rule extraction to a large library of ab-initio calculated information, and demonstrate that this can be developed into a tool for crystal structure prediction.Comment: 4 pages, 3 pic

Magnetic ordering of the antiferromagnet Cu2MnSnS4 from magnetization and neutron-scattering measurements

Magnetization and neutron-diffraction measurements were performed on a single crystal of Cu2MnSnS4. This quartenary magnetic semiconductor has the stannite structure (derived from the zinc-blende structure which is common to many II-VI dilute magnetic semiconductors), and it orders antiferromagnetically at low temperature. The neutron data for the nuclear structure confirm that the space group is I42̄m. Both the neutron and magnetization data give TN=8.8 K for the Néel temperature. The neutron data show a collinear antiferromagnetic (AF) structure with a propagation vector k=[1/2,0,1/2], in agreement with earlier neutron data on a powder. However, the deduced angle θ between the spin axis and the crystallographic c direction is between 6° and 16°, in contrast to the earlier value of 40°. The magnetization curve at T≪TN shows the presence of a spin rotation (analogous to a spin flop), which indicates that the spin axis is indeed close to the c direction. The deduced magnetic anisotropy gives an anisotropy field HA≅2 kOe. At high magnetic fields the magnetization curve at T≪TN shows the transition between the canted (spin-flop) phase and the paramagnetic phase. The transition field, H=245.5 kOe, yields an intersublattice exchange field HE= 124 kOe. The exchange constants deduced from HE and the Curie-Weiss temperature Θ=-25 K show that the antiferromagnetic interactions are an order of magnitude smaller than in II-VI dilute magnetic semiconductors (DMS's). The much weaker antiferromagnetic interactions are expected from the difference in the crystal structures (stannite versus zincblende). A more surprising result is that the exchange constant which controls the AF order below TN is not between Mn ions with the smallest separation. This result contrasts with a prediction made for the related II-VI DMS, according to which the exchange constants decrease rapidly with distance.The work at Tufts University was partially supported by NSF Grant No. DMR-9219727. The research in Zaragoza was supported by CICYT Grant No. MAT94-0043. The work at Brown University was supported by NSF Grant No. DMR-9221141. The Francis Bitter National Magnet Laboratory was supported by NSF.Peer Reviewe

The genotype-phenotype relationship in multicellular pattern-generating models - the neglected role of pattern descriptors

Background: A deep understanding of what causes the phenotypic variation arising from biological patterning processes, cannot be claimed before we are able to recreate this variation by mathematical models capable of generating genotype-phenotype maps in a causally cohesive way. However, the concept of pattern in a multicellular context implies that what matters is not the state of every single cell, but certain emergent qualities of the total cell aggregate. Thus, in order to set up a genotype-phenotype map in such a spatiotemporal pattern setting one is actually forced to establish new pattern descriptors and derive their relations to parameters of the original model. A pattern descriptor is a variable that describes and quantifies a certain qualitative feature of the pattern, for example the degree to which certain macroscopic structures are present. There is today no general procedure for how to relate a set of patterns and their characteristic features to the functional relationships, parameter values and initial values of an original pattern-generating model. Here we present a new, generic approach for explorative analysis of complex patterning models which focuses on the essential pattern features and their relations to the model parameters. The approach is illustrated on an existing model for Delta-Notch lateral inhibition over a two-dimensional lattice. Results: By combining computer simulations according to a succession of statistical experimental designs, computer graphics, automatic image analysis, human sensory descriptive analysis and multivariate data modelling, we derive a pattern descriptor model of those macroscopic, emergent aspects of the patterns that we consider of interest. The pattern descriptor model relates the values of the new, dedicated pattern descriptors to the parameter values of the original model, for example by predicting the parameter values leading to particular patterns, and provides insights that would have been hard to obtain by traditional methods. Conclusion: The results suggest that our approach may qualify as a general procedure for how to discover and relate relevant features and characteristics of emergent patterns to the functional relationships, parameter values and initial values of an underlying pattern-generating mathematical model

Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter

In this study, the ability to predict N-uptake in winter wheat crops using NIR-spectroscopy on soil samples was evaluated. Soil samples were taken in unfertilized plots in one winter wheat field during three years (1997-1999) and in another winter wheat field nearby in one year (2000). Soil samples were analyzed for organic C content and their NIR-spectra. N-uptake was measured as total N-content in aboveground plant materials at harvest. Models calibrated to predict N-uptake were internally cross validated and validated across years and across fields. Cross-validated calibrations predicted N-uptake with an average error of 12.1 to 15.4 kg N ha-1. The standard deviation divided by this error (RPD) ranged between 1.9 and 2.5. In comparison, the corresponding calibrations based on organic C alone had an error from 11.7 to 28.2 kg N ha-1 and RPDs from 1.3 to 2.5. In three of four annual calibrations within a field, the NIR-based calibrations worked better than the organic C based calibrations. The prediction of N-uptake across years, but within a field, worked slightly better with an organic C based calibration than with a NIR based one, RPD = 1.9 and 1.7 respectively. Across fields, the corresponding difference was large in favour of the NIR-calibration, RPD = 2.5 for the NIR-calibration and 1.5 for the organic C calibration. It was concluded that NIR-spectroscopy integrates information about organic C with other relevant soil components and therefore has a good potential to predict complex functions of soils such as N-mineralization. A relatively good agreement of spectral relationships to parameters related to the N-mineralization of datasets across the world suggests that more general models can be calibrated