Summary goodness‐of‐fit statistics for binary generalized linear models with noncanonical link functions

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness‐of‐fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer–Lemeshow () and Pigeon–Heyse (J²) statistics can be applied directly. In a simulation study, , , and J² were used to evaluate the fit of probit, log–log, complementary log–log, and log models, all calculated with a common grouping method. The statistic consistently maintained Type I error rates, while those of and J² were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, had more power than or J².     

New insights into the interaction of proteins and disaccharides—The effect of pH and concentration

To gain new insights into the interaction of proteins and disaccharides, we investigated the hydrodynamic radii, , of lysozyme molecules in solution and in a ternary protein‐sugar‐water system by PFG‐NMR. Our approach is based on the assumption that the anhydrobiotic properties of disaccharides like trehalose are based on aggregation of sugar molecules to the proteins, i.e., accumulation of sugar molecules close to the protein, and that this process can be investigated by the experimentally detectable value of the protein. The R_h values are calculated from the experimentally determined diffusion coefficients and the application of a viscosity correction using the inert molecule dioxane as an internal viscosity reference. The experiments were performed as a function of sugar concentration, the overall particle concentration and the pH value. We investigated the disaccharides trehalose and sucrose, mainly for the reason that trehalose has well know cryptobiotic properties while sucrose, which is similar in size and structure, lacks these properties. The results show the formation of a protective sugar shell around the proteins over a wider range of concentrations and pH values in the case of trehalose.     

speed‐ne: Software to simulate and estimate genetic effective population size (Ne) from linkage disequilibrium observed in single samples

The genetic effective population size, N_e, can be estimated from the average gametic disequilibrium () between pairs of loci, but such estimates require evaluation of assumptions and currently have few methods to estimate confidence intervals. speed‐ne is a suite of matlab computer code functions to estimate from with a graphical user interface and a rich set of outputs that aid in understanding data patterns and comparing multiple estimators. speed‐ne includes functions to either generate or input simulated genotype data to facilitate comparative studies of estimators under various population genetic scenarios. speed‐ne was validated with data simulated under both time‐forward and time‐backward coalescent models of genetic drift. Three classes of estimators were compared with simulated data to examine several general questions: what are the impacts of microsatellite null alleles on , how should missing data be treated, and does disequilibrium contributed by reduced recombination among some loci in a sample impact . Estimators differed greatly in precision in the scenarios examined, and a widely employed estimator exhibited the largest variances among replicate data sets. speed‐ne implements several jackknife approaches to estimate confidence intervals, and simulated data showed that jackknifing over loci and jackknifing over individuals provided ~95% confidence interval coverage for some estimators and should be useful for empirical studies. speed‐ne provides an open‐source extensible tool for estimation of from empirical genotype data and to conduct simulations of both microsatellite and single nucleotide polymorphism (SNP) data types to develop expectations and to compare estimators.     

Effective size of density‐dependent populations in fluctuating environments

Reliable estimates of effective population size are of central importance in population genetics and evolutionary biology. For populations that fluctuate in size, harmonic mean population size is commonly used as a proxy for (multi‐) generational effective size. This assumes no effects of density dependence on the ratio between effective and actual population size, which limits its potential application. Here, we introduce density dependence on vital rates in a demographic model of variance effective size. We derive an expression for the ratio in a density‐regulated population in a fluctuating environment. We show by simulations that yearly genetic drift is accurately predicted by our model, and not proportional to as assumed by the harmonic mean model, where N is the total population size of mature individuals. We find a negative relationship between and N. For a given N, the ratio depends on variance in reproductive success and the degree of resource limitation acting on the population growth rate. Finally, our model indicate that environmental stochasticity may affect not only through fluctuations in N, but also for a given N at a given time. Our results show that estimates of effective population size must include effects of density dependence and environmental stochasticity.     

Effects of chronic elevated nitrate concentrations on the structure and function of river biofilms

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Archaea S‐layer nanotube from a “black smoker” in complex with cyclo‐octasulfur (S8) rings

Elemental sulfur exists primarily as an ring and serves as terminal electron acceptor for a variety of sulfur‐fermenting bacteria. Hyperthermophilic archaea from black smoker vents are an exciting research tool to advance our knowledge of sulfur respiration under extreme conditions. Here, we use a hybrid method approach to demonstrate that the proteinaceous cavities of the S‐layer nanotube of the hyperthermophilic archaeon Staphylothermus marinus act as a storage reservoir for cyclo‐octasulfur . Fully atomistic molecular dynamics (MD) simulations were performed and the method of multiconfigurational thermodynamic integration was employed to compute the absolute free energy for transferring a ring of elemental sulfur from an aqueous bath into the largest hydrophobic cavity of a fragment of archaeal tetrabrachion. Comparisons with earlier MD studies of the free energy of hydration as a function of water occupancy in the same cavity of archaeal tetrabrachion show that the sulfur ring is energetically favored over water.     

Comparative effects of ammonium,nitrate and urea on growth and photosynthetic efficiency of three bloom‐forming cyanobacteria

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Particle tracking microrheology of purified gastrointestinal mucins

The rheological characteristics of gastric and duodenal mucin solutions, the building blocks of the mucus layer that covers the epithelia of the two organs, were investigated using particle tracking microrheology. We used biochemically well characterized purified porcine mucins (MUC5AC and MUC2) as models for human mucins, to probe their viscoelasticity as a function of mucin concentration and pH. Furthermore, we used both reducing (dithiothreitol, DTT) and chaotropic agents (guanidinium chloride and urea) to probe the mesoscopic forces that mediate the integrity of the polymer network. At neutral pH both gastric and duodenal mucins formed self‐assembled semi‐dilute networks above a certain critical mucin concentration (c*) with the viscosity (η) scaling as for MUC5AC and for MUC2, where c is the mucin concentration. Above an even higher mucin concentration threshold (c_e, the entanglement concentration) reptation occurs and there is a dramatic increase in the viscosity scaling, for MUC5AC and for MUC2. The dynamics of the self‐assembled comb polymers is examined in terms of a scaling model for flexible polyelectrolyte combs. Both duodenum and gastric mucin are found to be pH switchable gels, gelation occurring at low pHs. There is a hundred‐fold increase in the elastic shear modulus once the pH is decreased. The addition of DTT, guanidinium chloride and urea disassembles both the semi‐dilute and gel structures causing a large increase in the compliance (decrease in their shear moduli). Addition of the polyphenol EGCG has a reverse effect on mucin viscoelasticity, that is, it triggers a sol–gel transition in semi‐dilute mucin solutions at neutral pH. © 2013 The Authors. Biopolymers published by Wiley Periodicals, Inc. Biopolymers 101: 366–377, 2014.     

Biotransformation of β‐hydroxypyruvate and glycolaldehyde to l‐erythrulose by Pichia pastoris strain GS115 overexpressing native transketolase

Transketolase is a proven biocatalytic tool for asymmetric carbon‐carbon bond formation, both as a purified enzyme and within bacterial whole‐cell biocatalysts. The performance of Pichia pastoris as a host for transketolase whole‐cell biocatalysis was investigated using a transketolase‐overexpressing strain to catalyze formation of l ‐erythrulose from β‐hydroxypyruvic acid and glycolaldehyde substrates. Pichia pastoris transketolase coding sequence from the locus PAS_chr1‐4_0150 was subcloned downstream of the methanol‐inducible AOX1 promoter in a plasmid for transformation of strain GS115, generating strain TK150. Whole and disrupted TK150 cells from shake flasks achieved 62% and 65% conversion, respectively, under optimal pH and methanol induction conditions. In a 300 μL reaction, TK150 samples from a 1L fed‐batch fermentation achieved a maximum l ‐erythrulose space time yield (STY) of 46.58 g L^?1 h^?1, specific activity of 155 U , product yield on substrate (Y_p/s) of 0.52 mol mol^?1 and product yield on catalyst (Y_p/x) of 2.23g . We have successfully exploited the rapid growth and high biomass characteristics of Pichia pastoris in whole cell biocatalysis. At high cell density, the engineered TK150 Pichia pastoris strain tolerated high concentrations of substrate and product to achieve high STY of the chiral sugar l ‐erythrulose. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:99–106, 2018     

A practical approach in bioreactor scale‐up and process transfer using a combination of constant P/V and vvm as the criterion

Bioreactor scale‐up is a critical step in the production of therapeutic proteins such as monoclonal antibodies (MAbs). With the scale‐up criterion such as similar power input per volume or O₂ volumetric mass transfer coefficient ( ), adequate oxygen supply and cell growth can be largely achieved. However, CO₂ stripping in the growth phase is often inadequate. This could cascade down to increased base addition and osmolality, as well as residual lactate increase and compromised production and product quality. Here we describe a practical approach in bioreactor scale‐up and process transfer, where bioreactor information may be limited. We evaluated the sparger and (CO₂ volumetric mass transfer coefficient) from a range of bioreactor scales (3–2,000 L) with different spargers. Results demonstrated that for oxygen is not an issue when scaling from small‐scale to large‐scale bioreactors at the same gas flow rate per reactor volume (vvm). Results also showed that sparging CO₂ stripping, , is dominated by the gas throughput. As a result, a combination of a minimum constant vvm air or N₂ flow with a similar specific power was used as the general scale‐up criterion. An equation was developed to determine the minimum vvm required for removing CO₂ produced from cell respiration. We demonstrated the effectiveness of using such scale‐up criterion with five MAb projects exhibiting different cell growth and metabolic characteristics, scaled from 3 to 2,000 L bioreactors across four sites. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1146–1159, 2017     

Contemporary effective population and metapopulation size (Ne and meta‐Ne): comparison among three salmonids inhabiting a fragmented system and differing in gene flow and its asymmetries

We estimated local and metapopulation effective sizes ( and meta‐) for three coexisting salmonid species (Salmo salar, Salvelinus fontinalis, Salvelinus alpinus) inhabiting a freshwater system comprising seven interconnected lakes. First, we hypothesized that might be inversely related to within‐species population divergence as reported in an earlier study (i.e., F_ST: S. salar> S. fontinalis> S. alpinus). Using the approximate Bayesian computation method implemented in ONeSAMP, we found significant differences in () between species, consistent with a hierarchy of adult population sizes (). Using another method based on a measure of linkage disequilibrium (LDNE: ), we found more finite values for S. salar than for the other two salmonids, in line with the results above that indicate that S. salar exhibits the lowest among the three species. Considering subpopulations as open to migration (i.e., removing putative immigrants) led to only marginal and non‐significant changes in , suggesting that migration may be at equilibrium between genetically similar sources. Second, we hypothesized that meta‐ might be significantly smaller than the sum of local s (null model) if gene flow is asymmetric, varies among subpopulations, and is driven by common landscape features such as waterfalls. One ‘bottom‐up’ or numerical approach that explicitly incorporates variable and asymmetric migration rates showed this very pattern, while a number of analytical models provided meta‐ estimates that were not significantly different from the null model or from each other. Our study of three species inhabiting a shared environment highlights the importance and utility of differentiating species‐specific and landscape effects, not only on dispersal but also in the demography of wild populations as assessed through local s and meta‐s and their relevance in ecology, evolution and conservation.     

High‐throughput identification of protein mutant stability computed from a double mutant fitness landscape

The effect of a mutation on protein stability is traditionally measured by genetic construction, expression, purification, and physical analysis using low‐throughput methods. This process is tedious and limits the number of mutants able to be examined in a single study. In contrast, functional fitness effects can be measured in a high‐throughput manner by various deep mutational scanning tools. Using protein GB 1, we have recently demonstrated the feasibility of estimating the mutational stability effect ( G) of single‐substitution based on the functional fitness profile of all double‐substitutions. The principle is to identify genetic backgrounds that have an exhausted stability margin. The functional effect of an additional substitution on these genetic backgrounds can then be used to compute the mutational G based on the biophysical relationship between functional fitness and thermodynamic stability. However, to identify such genetic backgrounds, the approach described in our previous study required a benchmark dataset, which is a set of known mutational G. In this study, a benchmark‐independent approach is developed. The genetic backgrounds of interest are identified using k‐means clustering with the integration of structural information. We further demonstrated that a reasonable approximation of G can also be obtained without taking structural information into account. In summary, this study describes a novel method for computing G from double‐substitution functional fitness profiles alone, without relying on any known mutational G as a benchmark.     

SEX RATIO AND DENSITY AFFECT SEXUAL SELECTION IN A SEX‐ROLE REVERSED FISH

Understanding how demographic processes influence mating systems is important to decode ecological influences on sexual selection in nature. We manipulated sex ratio and density in experimental populations of the sex‐role reversed pipefish Syngnathus typhle. We quantified sexual selection using the Bateman gradient (), the opportunity for selection (I), and sexual selection (I_s), and the maximum standardized sexual selection differential (). We also measured selection on body length using standardized selection differentials (s′) and mating differentials (m′), and tested whether the observed I and I_s differ from values obtained by simulating random mating. We found that I, I_s, and , but not , were higher for females under female than male bias and the opposite for males, but density did not affect these measures. However, higher density decreased sexual selection (m′ but not s′) on female length, but selection on body length was not affected by sex ratio. Finally, I_s but not I was higher than expected from random mating, and only for females under female bias. This study demonstrates that both sex ratio and density affect sexual selection and that disentangling interrelated demographic processes is essential to a more complete understanding of mating behavior and the evolution of mating systems.     

Isotope labeling to determine the dynamics of metabolic response in CHO cell perfusion bioreactors using MALDI‐TOF‐MS

The steady‐state operation of Chinese hamster ovary (CHO) cells in perfusion bioreactors requires the equilibration of reactor dynamics and cell metabolism. Accordingly, in this work we investigate the transient cellular response to changes in its environment and their interactions with the bioreactor hydrodynamics. This is done in a benchtop perfusion bioreactor using MALDI‐TOF MS through isotope labeling of complex intracellular nucleotides (ATP, UTP) and nucleotide sugars (UDP‐Hex, UDP‐HexNAc). By switching to a ¹³C₆ glucose containing feed media during constant operation at 20 × 10⁶ cells and a perfusion rate of 1 reactor volume per day, isotopic steady state was studied. A step change to the ¹³C₆ glucose medium in spin tubes allowed the determination of characteristic times for the intracellular turnover of unlabeled metabolites pools, (≤0.56 days), which were confirmed in the bioreactor. On the other hand, it is shown that the reactor residence time (1 day) and characteristic time for glucose uptake (0.33 days), representative of the bioreactor dynamics, delayed the consumption of ¹³C₆ glucose in the bioreactor and thus the intracellular ¹³C enrichment. The proposed experimental approach allowed the decoupling of bioreactor hydrodynamics and intrinsic dynamics of cell metabolism in response to a change in the cell culture environment. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1630–1639, 2017     

pKa predictions for proteins,RNAs, and DNAs with the Gaussian dielectric function using DelPhi pKa

We developed a Poisson‐Boltzmann based approach to calculate the values of protein ionizable residues (Glu, Asp, His, Lys and Arg), nucleotides of RNA and single stranded DNA. Two novel features were utilized: the dielectric properties of the macromolecules and water phase were modeled via the smooth Gaussian‐based dielectric function in DelPhi and the corresponding electrostatic energies were calculated without defining the molecular surface. We tested the algorithm by calculating values for more than 300 residues from 32 proteins from the PPD dataset and achieved an overall RMSD of 0.77. Particularly, the RMSD of 0.55 was achieved for surface residues, while the RMSD of 1.1 for buried residues. The approach was also found capable of capturing the large shifts of various single point mutations in staphylococcal nuclease (SNase) from ‐cooperative dataset, resulting in an overall RMSD of 1.6 for this set of pKa's. Investigations showed that predictions for most of buried mutant residues of SNase could be improved by using higher dielectric constant values. Furthermore, an option to generate different hydrogen positions also improves predictions for buried carboxyl residues. Finally, the calculations on two RNAs demonstrated the capability of this approach for other types of biomolecules. Proteins 2015; 83:2186–2197. © 2015 Wiley Periodicals, Inc.     

Soil moisture variations affect short‐term plant‐microbial competition for ammonium,glycine, and glutamate

We tested whether the presence of plant roots would impair the uptake of ammonium (), glycine, and glutamate by microorganisms in a deciduous forest soil exposed to constant or variable moisture in a short‐term (24‐h) experiment. The uptake of ¹⁵NH₄ and dual labeled amino acids by the grass Festuca gigantea L. and soil microorganisms was determined in planted and unplanted soils maintained at 60% WHC (water holding capacity) or subject to drying and rewetting. The experiment used a design by which competition was tested in soils that were primed by plant roots to the same extent in the planted and unplanted treatments. Festuca gigantea had no effect on microbial N uptake in the constant moist soil, but its presence doubled the microbial uptake in the dried and rewetted soil compared with the constant moist. The drying and rewetting reduced by half or more the uptake by F. gigantea, despite more than 60% increase in the soil concentration of . At the same time, the amino acid and ‐ N became equally valued in the plant uptake, suggesting that plants used amino acids to compensate for the lower acquisition. Our results demonstrate the flexibility in plant‐microbial use of different N sources in response to soil moisture fluctuations and emphasize the importance of including transient soil conditions in experiments on resource competition between plants and soil microorganisms. Competition between plants and microorganisms for N is demonstrated by a combination of removal of one of the potential competitors, the plant, and subsequent observations of the uptake of N in the organisms in soils that differ only in the physical presence and absence of the plant during a short assay. Those conditions are necessary to unequivocally test for competition.     

Deep soil carbon dynamics are driven more by soil type than by climate: a worldwide meta‐analysis of radiocarbon profiles

The response of soil carbon dynamics to climate and land‐use change will affect both the future climate and the quality of ecosystems. Deep soil carbon (>20 cm) is the primary component of the soil carbon pool, but the dynamics of deep soil carbon remain poorly understood. Therefore, radiocarbon activity (C), which is a function of the age of carbon, may help to understand the rates of soil carbon biodegradation and stabilization. We analyzed the published C contents in 122 profiles of mineral soil that were well distributed in most of the large world biomes, except for the boreal zone. With a multivariate extension of a linear mixed‐effects model whose inference was based on the parallel combination of two algorithms, the expectation–maximization (EM) and the Metropolis–Hasting algorithms, we expressed soil C profiles as a four‐parameter function of depth. The four‐parameter model produced insightful predictions of soil C as dependent on depth, soil type, climate, vegetation, land‐use and date of sampling (). Further analysis with the model showed that the age of topsoil carbon was primarily affected by climate and cultivation. By contrast, the age of deep soil carbon was affected more by soil taxa than by climate and thus illustrated the strong dependence of soil carbon dynamics on other pedologic traits such as clay content and mineralogy.     

Purging putative siblings from population genetic data sets: a cautionary view

Interest has surged recently in removing siblings from population genetic data sets before conducting downstream analyses. However, even if the pedigree is inferred correctly, this has the potential to do more harm than good. We used computer simulations and empirical samples of coho salmon to evaluate strategies for adjusting samples to account for family structure. We compared performance in full samples and sibling‐reduced samples of estimators of allele frequency (), population differentiation () and effective population size (). Results: (i) unless simulated samples included large family groups together with a component of unrelated individuals, removing siblings generally reduced precision of and ; (ii) based on the linkage disequilibrium method was largely unbiased using full random samples but became increasingly upwardly biased under aggressive purging of siblings. Under nonrandom sampling (some families over‐represented), using full samples was downwardly biased; removing just the right ‘Goldilocks’ fraction of siblings could produce an unbiased estimate, but this sweet spot varied widely among scenarios; (iii) weighting individuals based on the inferred pedigree (to produce a best linear unbiased estimator, BLUE) maximized precision of when the inferred pedigree was correct but performed poorly when the pedigree was wrong; (iv) a variant of sibling removal that leaves intact small sibling groups appears to be more robust to errors in inferences about family structure. Our results illustrate the complex challenges posed by presence of family structure, suggest that no single optimal solution exists and argue for caution in adjusting population genetic data sets for the presence of putative siblings without fully understanding the consequences.     

Nucleotide‐dependent structural fluctuations and regulation of microtubule‐binding affinity of KIF1A

Molecular motors such as kinesin regulate affinity to a rail protein during the ATP hydrolysis cycle. The regulation mechanism, however, is yet to be determined. To understand this mechanism, we investigated the structural fluctuations of the motor head of the single‐headed kinesin called KIF1A in different nucleotide states using molecular dynamics simulations of a Gō‐like model. We found that the helix at the microtubule (MT) binding site intermittently exhibits a large structural fluctuation when MT is absent. Frequency of this fluctuation changes systematically according to the nucleotide states and correlates strongly with the experimentally observed binding affinity to MT. We also showed that thermal fluctuation enhances the correlation and the interaction with the nucleotide suppresses the fluctuation of the helix . These results suggest that KIF1A regulates affinity to MT by changing the flexibility of the helix during the ATP hydrolysis process: the binding site becomes more flexible in the strong binding state than in the weak binding state. Proteins 2015; 83:809–819. © 2015 Wiley Periodicals, Inc.     

Stable carbon isotopes of methane for real‐time process monitoring in anaerobic digesters

Efficient operation and stability of biogas plants requires continuous monitoring of the digester content. Traditional laboratory analysis of digester sludge is often complex and time‐consuming and shows a delayed response to disruptions within the fermentation process. As a new approach, we applied an online measurement technique (laser absorption spectroscopy) for real‐time monitoring of stable carbon isotopes of methane () in a pilot‐scale biogas digester (3500 L) regularly fed with maize silage. Generally, isotopic composition of methane gives information about specific substrate degradation, that is, methanogenic pathways that reflect the actual digester state. First results of a 2‐wk monitoring experiment show that stable carbon isotopes of methane respond promptly and highly dynamic to changes in the process state of the digester. In combination with other monitoring parameters (methane production rate, concentration of volatile fatty acids, and pH) the fluctuations in can be interpreted as a change in methanogenic pathways due to a high organic loading rate. In this context, might be used as a new parameter tool for monitoring and characterization of the process state of the digester.