Lipid synthesized by micro‐algae grown in laboratory‐ and industrial‐scale bioreactors

Tetraselmis sp. and Nannochloropsis oculata, cultivated in industrial‐scale bioreactors, produced 2.33 and 2.44% w/w lipid (calculated as the sum of fatty acid methyl esters) in dry biomass, respectively. These lipids contained higher amounts of neutral lipids and glycolipids plus sphingolipids, than phospholipids. Lipids of Tetraselmis sp. were characterized by the presence of eicosapentaenoic acid (that was located mainly in phospholipids), and octadecatetraenoic acid (that was equally distributed among lipid fractions), while these fatty acids were completely absent in N. oculata lipids. Additionally, lipids produced by 16 newly isolated strains from Greek aquatic environments (cultivated in flask reactors) were studied. The highest percentage of lipids was found in Prorocentrum triestinum (3.69% w/w) while the lowest in Prymnesium parvum (0.47% w/w). Several strains produced lipids rich in eicosapentaenoic and docosahexaenoic acids. For instance, docosahexaenoic acid was found in high percentages in lipids of Amphidinium sp. S1, P. parvum, Prorocentrum minimum and P. triestinum, while lipids produced by Asterionella sp. (?) S2 contained eicosapentaenoic acid in high concentration. These lipids, containing ω‐3‐long‐chain polyunsaturated fatty acids, have important applications in the food and pharmaceutical industries and in aquaculture.     

Meta‐Omics‐ and Metabolic Modeling‐Assisted Deciphering of Human Microbiota Metabolism

The human microbiota is a complex community of commensal, symbiotic, and pathogenic microbes that play a crucial role in maintaining the homeostasis of human health. Such a homeostasis is maintained through the collective functioning of enzymatic genes responsible for the production of metabolites, enabling the interaction and signaling within microbiota as well as between microbes and the human host. Understanding microbial genes, their associated chemistries and functions would be valuable for engineering systemic metabolic pathways within the microbiota to manage human health and diseases. Given that there are many unknown gene metabolic functions and interactions, increasing efforts have been made to gain insights into the underlying functions of microbiota metabolism. This can be achieved through culture‐independent metagenomic approaches and metabolic modeling to simulate the microenvironment of human microbiota. In this article, the recent advances in metagenome mining and functional profiling for the discovery of the genetic and biochemical links in human microbiota metabolism as well as metabolic modeling for simulation and prediction of metabolic fluxes in the human microbiota are reviewed. This review provides useful insights into the understanding, reconstruction, and modulation of the human microbiota guided by the knowledge acquired from the basic understanding of the human microbiota metabolism.     

Development,characterization, and application of a 2‐Compartment system to investigate the impact of pH inhomogeneities in large‐scale CHO‐based processes

Large‐scale bioreactors for the production of monoclonal antibodies reach volumes of up to 25 000 L. With increasing bioreactor size, mixing is however affected negatively, resulting in the formation of gradients throughout the reactor. These gradients can adversely affect process performance at large scale. Since mammalian cells are sensitive to changes in pH, this study investigated the effects of pH gradients on process performance. A 2‐Compartment System was established for this purpose to expose only a fraction of the cell population to pH excursions and thereby mimicking a large‐scale bioreactor. Cells were exposed to repeated pH amplitudes of 0.4 units (pH 7.3), which resulted in decreased viable cell counts, as well as the inhibition of the lactate metabolic shift. These effects were furthermore accompanied by increased absolute lactate levels. Continuous assessment of molecular attributes of the expressed target protein revealed that subunit assembly or N‐glycosylation patterns were only slightly influenced by the pH excursions. The exposure of more cells to the same pH amplitudes further impaired process performance, indicating this is an important factor, which influences the impact of pH inhomogeneity. This knowledge can aid in the design of pH control strategies to minimize the effects of pH inhomogeneity in large‐scale bioreactors.     

Scale‐down simulators for mammalian cell culture as tools to access the impact of inhomogeneities occurring in large‐scale bioreactors

During the scale‐up of a bioprocess, not all characteristics of the process can be kept constant throughout the different scales. This typically results in increased mixing times with increasing reactor volumes. The poor mixing leads in turn to the formation of concentration gradients throughout the reactor and exposes cells to varying external conditions based on their location in the bioreactor. This can affect process performance and complicate process scale‐up. Scale‐down simulators, which aim at replicating the large‐scale environment, expose the cells to changing environmental conditions. This has the potential to reveal adaptation mechanisms, which cells are using to adjust to rapidly fluctuating environmental conditions and can identify possible root causes for difficulties maintaining similar process performance at different scales. This understanding is of utmost importance in process validation. Additionally, these simulators also have the potential to be used for selecting cells, which are most robust when encountering changing extracellular conditions. The aim of this review is to summarize recent work in this interesting and promising area with the focus on mammalian bioprocesses, since microbial processes have been extensively reviewed.     

Prediction of Rate‐Limiting Reactions for Growth‐Associated Production Using a Constraint‐Based Approach

Identification of a rate‐limiting step in pathways is a key challenge in metabolic engineering. Although the prediction of rate‐limiting steps using a kinetic model is a powerful approach, there are several technical hurdles for developing a kinetic model. In this study, an in silico screening algorithm of key enzyme for metabolic engineering is developed to identify the possible rate‐limiting reactions for the growth‐coupled target production using a stoichiometric model without any experimental data and kinetic parameters. In this method, for each reaction, an upper‐bound flux constraint is imposed and the target production is predicted by linear programming. When the constraint decreases the target production at the optimal growth state, the reaction is thought to be a possible rate‐limiting step. For validation, this method is applied to the production of succinate or 1,4‐butanediol (1,4‐BDO) in Escherichia coli, in which the experimental engineering for eliminating rate‐limiting steps has been previously reported. In succinate production from glycerol, nine reactions including phosphoenolpyruvate carboxylase are predicted as the rate‐limiting steps. In 1,4‐BDO production from glucose, eight reactions including pyruvate dehydrogenase are predicted as the rate‐limiting steps. These predictions include experimentally identified rate‐limiting steps, which would contribute to metabolic engineering as a practical tool for screening candidates of rate‐limiting reactions.     

Model‐Based Quality Assessment and Base‐Calling for Second‐Generation Sequencing Data

Summary Second‐generation sequencing (sec‐gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads—strings of A,C,G, or T's, between 30 and 100 characters long—which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base‐calling. The complexity of the base‐calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across‐sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec‐gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base‐calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base‐calling allowing for informative and easily interpretable metrics that capture the variability in sequencing quality. Our model provides these informative estimates readily usable in quality assessment tools while significantly improving base‐calling performance.     

Multi‐Length‐Scale Morphologies in PCPDTBT/PCBM Bulk‐Heterojunction Solar Cells

Additives are known to improve the performance of organic photovoltaic devices based on mixtures of a low bandgap polymer, poly[2,6‐(4,4‐bis(2‐ethylhexyl)‐4H‐cyclopenta[2,1‐b;3,4‐b′]‐dithiophene)‐alt‐4,7‐(2,1,3‐benzothiadiazole)] (PCPDTBT) and [6,6]‐phenyl C61‐butyric acid methyl ester (PCBM). The evolution of the morphology during the evaporation of the mixed solvent, which comprises additive and chlorobenzene (CB), is investigated by in‐situ grazing incidence X‐ray scattering, providing insight into the key role the additive plays in developing a multi‐length‐scale morphology. Provided the additive has a higher vapor pressure and a selective solubility for PCBM, as the host solvent (CB) evaporates, the mixture of the primary solvent and additive becomes less favorable for the PCPDTBT, while completely solubilizing the PCBM. During this process, the PCPDTBT first crystallizes into fibrils and then the PCBM, along with the remaining PCPDTBT, is deposited, forming a phase‐separated morphology comprising domains of pure, crystalline PCPDTBT fibrils and another domain that is a PCBM‐rich mixture with amorphous PCPDTBT. X‐ray/neutron scattering and diffraction methods, in combination with UV–vis absorption spectroscopy and transmission electron microscopy, are used to determine the crystallinity and phase separation of the resultant PCPDTBT/PCBM thin films processed with or without additives. Additional thermal annealing is carried out and found to change the packing of the PCPDTBT. The two factors, degree of crystallinity and degree of phase separation, control the multi‐length‐scale morphology of the thin films and significantly influence device performance.     

Scale dependence of sex‐specific movement in a small‐bodied stream fish

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High Energy Density Sodium‐Ion Battery with Industrially Feasible and Air‐Stable O3‐Type Layered Oxide Cathode

Extensive effort is being made into cathode materials for sodium‐ion battery to address several fatal issues, which restrict their future application in practical sodium‐ion full cell system, such as their unsatisfactory initial Coulombic efficiency, inherent deficiency of cyclable sodium content, and poor industrial feasibility. A novel air‐stable O3‐type Na[Li_0.05Mn_0.50Ni_0.30Cu_0.10Mg_0.05]O₂ is synthesized by a coprecipitation method suitable for mass production followed by high‐temperature annealing. The microscale secondary particle, consisting of numerous primary nanocrystals, can efficiently facilitate sodium‐ion transport due to the short diffusion distance, and this cathode material also has inherent advantages for practical application because of its superior physical properties. It exhibits a reversible capacity of 172 mA h g^?1 at 0.1 C and remarkable capacity retention of 70.4% after 1000 cycles at 20 C. More importantly, it offers good compatibility with pristine hard carbon as anode in the sodium‐ion full cell system, delivering a high energy density of up to 215 W h kg^?1 at 0.1 C and good rate performance. Owing to the high industrial feasibility of the synthesis process, good compatibility with pristine hard carbon anode, and excellent electrochemical performance, it can be considered as a promising active material to promote progress toward sodium‐ion battery commercialization.     

Millimeter‐scale genetic gradients and community‐level molecular convergence in a hypersaline microbial mat

To investigate the extent of genetic stratification in structured microbial communities, we compared the metagenomes of 10 successive layers of a phylogenetically complex hypersaline mat from Guerrero Negro, Mexico. We found pronounced millimeter‐scale genetic gradients that were consistent with the physicochemical profile of the mat. Despite these gradients, all layers displayed near‐identical and acid‐shifted isoelectric point profiles due to a molecular convergence of amino‐acid usage, indicating that hypersalinity enforces an overriding selective pressure on the mat community.     

High‐Quality Graphene Microflower Design for High‐Performance Li–S and Al‐Ion Batteries

Poor quality and insufficient productivity are two main obstacles for the practical application of graphene in electrochemical energy storage. Here, high‐quality crumpled graphene microflower (GmF) for high‐performance electrodes is designed. The GmF possesses four advantages simultaneously: highly crystallized defect‐free graphene layers, low stacking degree, sub‐millimeter continuous surface, and large productivity with low cost. When utilized as carbon host for sulfur cathode, the GmF‐sulfur hybrid delivers decent areal capacities of 5.2 mAh cm^?2 at 0.1 C and 3.8 mAh cm^?2 at 0.5 C. When utilized as cathode of Al‐ion battery, the GmF affords a high capacity of 100 mAh g^?1 with 100% capacity retention after 5000 cycles and excellent rate capability from 0.1 to 20 A g^?1. This facile and large‐scale producible GmF represents a meaningful high‐quality graphene powder for practical energy storage technology. Meanwhile, this unique high‐quality graphene design provides an effective route to improve electrochemical properties of graphene‐based electrodes.     

Considerations for the process development of insect‐derived antimicrobial peptide production

Antimicrobial peptides (AMPs) could evolve into new therapeutic lead molecules against multi‐resistant bacteria. As insects are a rich source of AMP, the identification and characterization of insect‐derived AMPs is particularly emphasized. One challenge of bringing these molecules into market, e.g., as a drug, is to develop a cost‐efficient large‐scale production process. Due to the fact that a direct AMP isolation from insects is not economical and that chemical synthesis is recommended for peptide sizes below 40 amino acids, a viable option is heterologous AMP production. Therefore, previous knowledge concerning the expression of larger proteins can be adapted, but due to the AMP nature (e.g., small size, bactericide) additional challenges have to be faced during up and downstream processing. Nonetheless the bottleneck for large‐scale AMP production is the same as for proteins; mainly the downstream process. This review introduces opportunities for insect‐derived AMP production, like the choice of the expression system (based on previously derived data), depending on the AMP nature, as well as new purification strategies like elastin‐like peptide/intein based purification strategies. All of these aspects are discussed with regard to large‐scale processes and costs. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 31:1–11, 2015     

Zonal rate model for axial and radial flow membrane chromatography,part II: Model‐based scale‐up

Membrane chromatography (MC) systems are finding increasing use in downstream processing trains for therapeutic proteins due to the unique mass‐transfer characteristics they provide. As a result, there is increased need for model‐based methods to scale‐up MC units using data collected on a scaled‐down unit. Here, a strategy is presented for MC unit scale‐up using the zonal rate model (ZRM). The ZRM partitions an MC unit into virtual flow zones to account for deviations from ideal plug‐flow behavior. To permit scale‐up, it is first configured for the specific device geometry and flow profiles within the scaled‐down unit so as to achieve decoupling of flow and binding related non‐idealities. The ZRM is then configured for the preparative‐scale unit, which typically utilizes markedly different flow manifolds and membrane architecture. Breakthrough is first analyzed in both units under non‐binding conditions using an inexpensive tracer to independently determine unit geometry related parameters of the ZRM. Binding related parameters are then determined from breakthrough data on the scaled‐down MC capsule to minimize sample requirements. Model‐based scale‐up may then be performed to predict band broadening and breakthrough curves on the preparative‐scale unit. Here, the approach is shown to be valid when the Pall XT140 and XT5 capsules serve as the preparative and scaled‐down units, respectively. In this case, scale‐up is facilitated by our finding that the distribution of linear velocities through the membrane in the XT140 capsule is independent of the feed flow rate and the type of protein transmitted. Introduction of this finding into the ZRM permits quantitative predictions of breakthrough over a range of industrially relevant operating conditions. Biotechnol. Bioeng. 2014;111: 1587–1594. © 2014 Wiley Periodicals, Inc.     

Validation of a landscape‐scale planning tool for cavity‐dependent wildlife

Tree cavities provide important habitat for wildlife. Effective landscape‐scale management of cavity‐dependent wildlife requires an understanding of where cavities occur, but tree cavities can be cryptic and difficult to survey. We assessed whether a landscape‐scale map of mature forest habitat availability, derived from aerial photographs, reflected the relative availability of mature trees and tree cavities. We assessed cavities for their suitability for use by wildlife, and whether the map reflected the availability of such cavities. There were significant differences between map categories in several characteristics of mature trees that can be used to predict cavity abundance (i.e. tree form and diameter at breast height). There were significant differences between map categories in the number of potential cavity bearing trees and potential cavities per tree. However, the index of cavity abundance based on observations made from the ground provided an overestimate of true cavity availability. By climbing a sample of mature trees we showed that only 5.1% of potential tree cavities detected from the ground were suitable for wildlife, and these were found in only 12.5% of the trees sampled. We conclude that management tools developed from remotely sensed data can be useful to guide decision‐making in the conservation management of tree cavities but stress that the errors inherent in these data limit the scale at which such tools can be applied. The rarity of tree cavities suitable for wildlife in our study highlights the need to conserve the tree cavity resource across the landscape, but also the importance of increasing the accuracy of management tools for decision‐making at different scales. Mapping mature forest habitat availability at the landscape scale is a useful first step in managing habitat for cavity‐dependent wildlife, but the potential for overestimating actual cavity abundance in a particular area highlights the need for complementary on‐ground surveys.     

Actinomycetes scale‐up for the production of the antibacterial,nocathiacin

An Amycolatopsis fastidiosa culture, which produces the nocathiacin class of antibacterial compounds, was scaled up to the 15,000 L working volume. Lower volume pilot fermentations (600, 900, and 1,500 L scale) were conducted to determine process feasibility at the 15,000 L scale. The effects of inoculum volume, impeller tip speed, volumetric gas flow rate, superficial gas velocity, backpressure, and sterilization heat stress were examined to determine optimal scale‐up operating conditions. Inoculum volume (6 vs. 2 vol %) and medium sterilization (R_o of 68 vs. 92 min^?1) had no effect on productivity or titer, and higher impeller tip speeds (2.1 vs. 2.9 m/s) had a slight effect (20% decrease). In contrast, higher backpressure, incorporating increased head pressure at the 15,000 L scale (1.2 vs. 0.7 kg/cm²) and low gas flow rates (0.25 vs. 0.8 vvm), appeared to be problematic (40–50% decrease). High off‐gas CO₂ levels were likely reasons for observed lower productivity. Consequently, air flow rate for this 25‐fold scale‐up (600–15,000 L) was controlled to match off‐gas CO₂ profiles of acceptable smaller scale batches to maintain levels below 0.5%. The 15,000 L‐scale fermentation achieved an expected nocathiacin I titer of 310 mg/L after 7 days. Other on‐line data (i.e., pH, oxygen uptake rate, and CO₂ evolution rate) and off‐line data (i.e., analog production, glucose utilization, ammonium production, and dry cell weight) at the 15,000 L scale also tracked similarly to the smaller scale, demonstrating successful fermentation scale‐up. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Transformation of cover‐abundance values for appropriate numerical treatment ‐ Alternatives to the proposals by Podani

Abstract. Two alternatives are offered to Podani's proposals, based on the claim that Braun‐Blanquet cover‐abundance estimates cannot be properly analysed by conventional mul‐tivariate methods. 1. The ordinal transform scale, based on an extended Braun‐Blanquet cover‐abundance scale, comes close to a metric cover percentage scale after (1) the abundance values r (very few individuals), + (few ind.), 1 (abundant) and 2m (very abundant, cover < 5%) are replaced by cover percentage estimates and (2) the higher Braun‐Blanquet values, notably 4 and 5, with cover intervals 50‐75% and 75‐100%, respectively, are interpreted as estimates of considerably higher cover values than the usual visual projection on the ground (because of the position of stems and leaves in several layers). I propose the equation ln C= (OTV ?2) /a, where C= Cover%, OTV is the 1 to 9 Ordinal Transfer Value and a is a factor weighting the cover values. With this equation cover values in a geometric series are achieved for the nine values in the extended Braun‐Blanquet scale from 0.5 % (OTV 1) to 140% (OTV 9) for a= 1.415, and for a= 1.380 from 0.6 % to 160%. 2. This makes use of an earlier developed ‘optimum‐transformation’ of cover‐abundance values. For each species a frequency distribution of cover‐abundance values is determined for a large data set, i.e. of dune slack vegetation. Tiny species have low values (OTVs 1–3) with high frequencies and hardly occur with higher OTV values; here all scores are considered ‘optimal’. In dominant species OTVs 7 to 9 have the highest frequencies and only these values are considered optimal. Species with intermediate OTV ranges have optimum ranges with low‐bound OTV = 2, 3, 4 and 5, respectively. No species were found in the dune slack data set with a frequency distribution justifying an optimum range with low‐bound OTV = 6. For mathematically correct numerical treatments’ optimum scores’ can be converted to 1 and sub‐optimal scores to 0 in order to approach a presence/absence situation. Both alternatives are suggested to be acceptable approximations to a metric basis for numerical analyses.