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     

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     

Exploring the capabilities of fluorometric online monitoring on chinese hamster ovary cell cultivations producing a monoclonal antibody

Online monitoring of Chinese hamster ovary fed‐batch cell cultures via two‐dimensional fluorescence spectroscopy (2DFS) was evaluated in this work. Particular attention was directed toward different process strategies regarding the use of nutrient‐rich feed media and temperature shifts. These intentionally performed process manipulations broadened the variances in the obtained fluorescence spectra and this was suspected to hamper the generation of reliable soft sensors. Principal component analysis of the obtained fluorescence data showed that temperature shift and feeding strategy had a considerable impact on the fluorescence signals. Partial least square regression models were calculated for the prediction of glucose, lactate, monoclonal antibody (mAb), and viable cell concentrations (VCC). It was aimed to integrate all 2DFS datasets in the respective calibration models regardless of the process‐strategy‐dependent diversity. Contrary to the expectations, it was feasible to calibrate soft sensors for the online prediction of glucose (7 latent variables (LVs), = 0.97, rout mean squared error of prediction (RMSEP) = 1.1 g L^?1), lactate (5 LV; = 0.96; RMSEP = 0.5 g L^?1) and mAb concentrations (4 LV; = 0.99; RMSEP = 11.4 mg L^?1). Feeding and temperature shifts had the highest impact on the VCC model (3 LV; = 0.94; RMSEP 3.8 × 10⁵ mL^?1), nevertheless the prediction of VCC from the fed‐batch 2DFS data was feasible. The results strongly indicate that variances in the datasets due to the process strategy can be tolerated to some extent by the respective soft sensors. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1592–1600, 2016     

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     

Variance component tests of multivariate mediation effects under composite null hypotheses

Mediation effects of multiple mediators are determined by two associations: one between an exposure and mediators (‐) and the other between the mediators and an outcome conditional on the exposure (‐). The test for mediation effects is conducted under a composite null hypothesis, that is, either one of the ‐ and ‐ associations is zero or both are zeros. Without accounting for the composite null, the type 1 error rate within a study containing a large number of multimediator tests may be much less than the expected. We propose a novel test to address the issue. For each mediation test , , we examine the ‐ and ‐ associations using two separate variance component tests. Assuming a zero‐mean working distribution with a common variance for the element‐wise ‐ (and ‐) associations, score tests for the variance components are constructed. We transform the test statistics into two normally distributed statistics under the null. Using a recently developed result, we conduct hypothesis tests accounting for the composite null hypothesis by adjusting for the variances of the normally distributed statistics for the ‐ and ‐ associations. Advantages of the proposed test over other methods are illustrated in simulation studies and a data application where we analyze lung cancer data from The Cancer Genome Atlas to investigate the smoking effect on gene expression through DNA methylation in 15 114 genes.     

Biophysical analysis of the dynamics of calmodulin interactions with neurogranin and Ca2+/calmodulin‐dependent kinase II

Calmodulin (CaM) functions depend on interactions with CaM‐binding proteins, regulated by . Induced structural changes influence the affinity, kinetics, and specificities of the interactions. The dynamics of CaM interactions with neurogranin (Ng) and the CaM‐binding region of /calmodulin‐dependent kinase II (CaMKII_290−309) have been studied using biophysical methods. These proteins have opposite dependencies for CaM binding. Surface plasmon resonance biosensor analysis confirmed that and CaM interact very rapidly, and with moderate affinity ( ). Calmodulin‐CaMKII_290−309 interactions were only detected in the presence of , exhibiting fast kinetics and nanomolar affinity ( ). The CaM–Ng interaction had higher affinity under ‐depleted ( and k ₋₁ = 1.6 × 10⁻¹s⁻¹) than ‐saturated conditions ( ). The IQ motif of Ng (Ng₂₇₋₅₀) had similar affinity for CaM as Ng under ‐saturated conditions ( ), but no interaction was seen under ‐depleted conditions. Microscale thermophoresis using fluorescently labeled CaM confirmed the surface plasmon resonance results qualitatively, but estimated lower affinities for the Ng ( ) and CaMKII_290−309( ) interactions. Although CaMKII_290−309 showed expected interaction characteristics, they may be different for full‐length CaMKII. The data for full‐length Ng, but not Ng₂₇₋₅₀, agree with the current model on Ng regulation of /CaM signaling.     

Nitrate or ammonium: Influences of nitrogen source on the physiology of a green alga

In freshwaters, algal species are exposed to different inorganic nitrogen (N_i) sources whose incorporation varies in biochemical energy demand. We hypothesized that due to the lesser energy requirement of ammonium ()‐use, in contrast to nitrate ()‐use, more energy remains for other metabolic processes, especially under CO₂‐ and phosphorus (P_i) limiting conditions. Therefore, we tested differences in cell characteristics of the green alga Chlamydomonas acidophila grown on or under covariation of CO₂ and P_i‐supply in order to determine limitations, in a full‐factorial design. As expected, results revealed higher carbon fixation rates for ‐grown cells compared to growth with under low CO₂ conditions. ‐grown cells accumulated more of the nine analyzed amino acids, especially under P_i‐limited conditions, compared to cells provided with . This is probably due to a slower protein synthesis in cells provided with . In contrast to our expectations, compared to ‐grown cells ‐grown cells had higher photosynthetic efficiency under P_i‐limitation. In conclusion, growth on the N_i‐source did not result in a clearly enhanced C_i‐assimilation, as it was highly dependent on P_i and CO₂ conditions (replete or limited). Results are potentially connected to the fact that C. acidophila is able to use only CO₂ as its inorganic carbon (C_i) source.     

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.     

MATERNAL INHERITANCE AND ITS EFFECT ON ADAPTIVE EVOLUTION: A QUANTITATIVE GENETIC ANALYSIS OF MATERNAL EFFECTS IN A NATURAL PLANT POPULATION

A mother can influence a trait in her offspring both by the genes she transmits (Mendelian inheritance) and by maternal attributes that directly affect that trait in her offspring (maternal inheritance). Maternal inheritance can alter the direction, rate, and duration of adaptive evolution from standard Mendelian models and its impact on adaptive evolution is virtually unexplored in natural populations. In a hierarchical quantitative genetic analysis to determine the magnitude and structure of maternal inheritance in the winter annual plant, Collinsia verna, I consider three potential models of inheritance. These range from a standard Mendelian model estimating only direct (i.e., Mendelian) additive and environmental variance components to a maternal inheritance model estimating six additive and environmental variance components: direct additive and environmental variances; maternal additive and environmental variances; and the direct-maternal additive () and environmental covariances. The structure of maternal inheritance differs among the 10 traits considered at four stages in the life cycle. Early in the life cycle, seed weight and embryo weight display substantial , a negative , and a positive . Subsequently, cotyledon diameter displays and of roughly the same magnitude and negative . For fall rosettes, leaf number and length are best described by a Mendelian model. In the spring, leaf length displays maternal inheritance with significant and and a negative . All maternally inherited traits show significant negative . Predicted response to selection under maternal inheritance depends on and as well as . Negative results in predicted responses in the opposite direction to selection for seed weight and embryo weight and predicted responses near zero for all subsequent maternally inherited traits. Maternal inheritance persists through the life cycle of this annual plant for a number of size-related traits and will alter the direction and rate of evolutionary response in this population.     

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.     

Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups

Accurate estimates of heritability () are necessary to assess adaptive responses of populations and evolution of fitness‐related traits in changing environments. For plants, estimates generally rely on maternal progeny designs, assuming that offspring are either half‐sibs or unrelated. However, plant mating systems often depart from half‐sib assumptions, this can bias estimates. Here, we investigate how to accurately estimate in nonmodel species through the analysis of sibling designs with a moderate genotyping effort. We performed simulations to investigate how microsatellite marker information available for only a subset of offspring can improve estimates based on maternal progeny designs in the presence of nonrandom mating, inbreeding in the parental population or maternal effects. We compared the basic family method, considering or not adjustments based on average relatedness coefficients, and methods based on the animal model. The animal model was used with average relatedness information, or with hybrid relatedness information: associating one‐generation pedigree and family assumptions, or associating one‐generation pedigree and average relatedness coefficients. Our results highlighted that methods using marker‐based relatedness coefficients performed as well as pedigree‐based methods in the presence of nonrandom mating (i.e. unequal male reproductive contributions, selfing), offering promising prospects to investigate in situ heritabilities in natural populations. In the presence of maternal effects, only the use of pairwise relatednesses through pedigree information improved the accuracy of estimates. In that case, the amount of father‐related offspring in the sibling design is the most critical. Overall, we showed that the method using both one‐generation pedigree and average relatedness coefficients was the most robust to various ecological scenarios.     

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.     

The Arabidopsis root stele transporter NPF2.3 contributes to nitrate translocation to shoots under salt stress

In most plants, constitutes the major source of nitrogen, and its assimilation into amino acids is mainly achieved in shoots. Furthermore, recent reports have revealed that reduction of translocation from roots to shoots is involved in plant acclimation to abiotic stress. NPF2.3, a member of the NAXT (nitrate excretion transporter) sub‐group of the NRT1/PTR family (NPF) from Arabidopsis, is expressed in root pericycle cells, where it is targeted to the plasma membrane. Transport assays using NPF2.3‐enriched Lactococcus lactis membranes showed that this protein is endowed with transport activity, displaying a strong selectivity for against Cl^?. In response to salt stress, translocation to shoots is reduced, at least partly because expression of the root stele transporter gene NPF7.3 is decreased. In contrast, NPF2.3 expression was maintained under these conditions. A loss‐of‐function mutation in NPF2.3 resulted in decreased root‐to‐shoot translocation and reduced shoot content in plants grown under salt stress. Also, the mutant displayed impaired shoot biomass production when plants were grown under mild salt stress. These mutant phenotypes were dependent on the presence of Na⁺ in the external medium. Our data indicate that NPF2.3 is a constitutively expressed transporter whose contribution to translocation to the shoots is quantitatively and physiologically significant under salinity.     

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

相似文献   

Expression and purification of the matrix protein of Nipah virus in baculovirus insect cell system

Nipah virus (NiV) causes fatal respiratory illness and encephalitis in humans and animals. The matrix (M) protein of NiV plays an important role in the viral assembly and budding process. Thus, an access to the NiV M protein is vital to the design of viral antigens as diagnostic reagents. In this study, recombinant DNA technology was successfully adopted in the cloning and expression of NiV M protein. A recombinant expression cassette (baculovirus expression vector) was used to encode an N‐terminally His‐tagged NiV M protein in insect cells. A time‐course study demonstrated that the highest yield of recombinant M protein (400–500 μg) was expressed from infected cells 3 days after infection. A single‐step purification method based on metal ion affinity chromatography was established to purify the NiV M protein, which successfully yielded a purity level of 95.67% and a purification factor of 3.39. The Western blotting and enzyme‐linked immunosorbent assay (ELISA) showed that the purified recombinant M protein (48 kDa) was antigenic and reacted strongly with the serum of a NiV infected pig. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:171–177, 2016     

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.     

Variation of photoautotrophic fatty acid production from a highly CO2 tolerant alga,Chlorococcum littorale,with inorganic carbon over narrow ranges of pH

Photoautotrophic fatty acid production of a highly CO₂‐tolerant green alga Chlorococcum littorale in the presence of inorganic carbon at 295 K and light intensity of 170 µmol‐photon m^?2 s^?1 was investigated. CO₂ concentration in the bubbling gas was adjusted by mixing pure gas components of CO₂ and N₂ to avoid photorespiration and β‐oxidation of fatty acids under O₂ surrounding conditions. Maximum content of total fatty acid showed pH‐dependence after nitrate depletion of the culture media and increased with the corresponding inorganic carbon ratio. Namely, [HCO₃^?]/([CO₂]+n[ ]) ratio in the culture media was found to be a controlling factor for photoautotrophic fatty acid production after the nitrate limitation. At a CO₂ concentration of 5% (vol/vol) and a pH of 6.7, the fatty acid content was 47.8 wt % (dry basis) at its maximum that is comparable with land plant seed oils. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1053–1057, 2015     

THE MAINTENANCE OF POLYGENIC VARIATION IN FINITE POPULATIONS

Models of the maintenance of genetic variance in a polygenic trait have usually assumed that population size is infinite and that selection is weak. Consequently, they will overestimate the amount of variation maintained in finite populations. I derive approximations for the equilibrium genetic variance, in finite populations under weak stabilizing selection for triallelic loci and for an infinite “rare alleles” model. These are compared to results for neutral characters, to the “Gaussian allelic” model, and to Wright's approximation for a biallelic locus under arbitrary selection pressures. For a variety of parameter values, the three-allele, Gaussian, and Wrightian approximations all converge on the neutral model when population size is small. As expected, far less equilibrium genetic variance can be maintained if effective population size, N, is on the order of a few hundred than if N is infinite. All of the models predict that comparisons among populations with N less than about 10⁴ should show substantial differences in . While it is easier to maintain absolute when alleles interact to yield dominance or overdominance for fitness, less additivity also makes more susceptible to differences in N. I argue that experimental data do not seem to reflect the predicted degree of relationship between N and . This calls into question the ability of mutation-selection balance or simple balancing selection to explain observed . The dependence of on N could be used to test the adequacy of mutation-selection balance models.     

Differential responses of two wetland graminoids to high ammonium at different pH values

Enhanced soil ammonium () concentrations in wetlands often lead to graminoid dominance, but species composition is highly variable. Although is readily taken up as a nutrient, several wetland species are known to be sensitive to high concentrations or even suffer toxicity, particularly at low soil pH. More knowledge about differential graminoid responses to high availability in relation to soil pH can help to better understand vegetation changes. The responses of two wetland graminoids, Juncus acutiflorus and Carex disticha, to high (2 mmol·l^?1) versus control (20 μmol·l^?1) concentrations were tested in a controlled hydroponic set up, at two pH values (4 and 6). A high concentration did not change total biomass for these species at either pH, but increased C allocation to shoots and increased P uptake, leading to K and Ca limitation, depending on pH treatment. More than 50% of N taken up by C. disticha was invested in N‐rich amino acids with decreasing C:N ratio, but only 10% for J. acutiflorus. Although both species appeared to be well adapted to high loadings in the short term, C. disticha showed higher classic detoxifying responses that are early warning indicators for decreased tolerance in the long term. In general, the efficient aboveground biomass allocation, P uptake and N detoxification explain the competitive strength of wetland graminoids at the expense of overall biodiversity at high loading. In addition, differential responses to enhanced affect interspecific competition among graminoids and lead to a shift in vegetation composition.