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.     

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.     

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.     

Scaling‐up biodiversity‐ecosystem functioning research

A rich body of knowledge links biodiversity to ecosystem functioning (BEF), but it is primarily focused on small scales. We review the current theory and identify six expectations for scale dependence in the BEF relationship: (1) a nonlinear change in the slope of the BEF relationship with spatial scale; (2) a scale‐dependent relationship between ecosystem stability and spatial extent; (3) coexistence within and among sites will result in a positive BEF relationship at larger scales; (4) temporal autocorrelation in environmental variability affects species turnover and thus the change in BEF slope with scale; (5) connectivity in metacommunities generates nonlinear BEF and stability relationships by affecting population  synchrony at local and regional scales; (6) spatial scaling in food web structure and diversity will generate scale dependence in ecosystem functioning. We suggest directions for synthesis that combine approaches in metaecosystem and metacommunity ecology and integrate cross‐scale feedbacks. Tests of this theory may combine remote sensing with a generation of networked experiments that assess effects at multiple scales. We also show how anthropogenic land cover change may alter the scaling of the BEF relationship. New research on the role of scale in BEF will guide policy linking the goals of managing biodiversity and ecosystems.     

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

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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.     

Scaling‐up of complex whole‐cell bioconversions in conventional and non‐conventional media

The use of whole cells is becoming a more common approach in pharmaceutical and agrochemical industries in order to obtain pure compounds with fewer production steps, higher yields, and cleaner processes, as compared to those achieved with traditional strategies. Whole cells are often used as enzymes pools, in particular when multi‐step reactions and/or co‐factor regeneration are envisaged. Nonetheless, published information on the scale‐up of such systems both in aqueous and in two‐phase aqueous–organic systems is relatively scarce. The present work aims to evaluate suitable scale‐up criteria in conventional and non‐conventional medium for a whole‐cell bioconversion that uses resting cells of Mycobacterium sp. NRRL B‐3805 to cleave the side chain of β‐sitosterol, a poorly water‐soluble substrate. The experiments were performed in 24‐well microtiter plates and in 250 mL shaken flasks as orbital stirred systems, and in 300 mL stirred tanks as mechanically stirred systems. Results show that productivity yields were similar in all scales tested, when maintaining oxygen mass transfer coefficients constant in aqueous systems, or when maintaining constant volumetric power consumption in aqueous–organic two‐phase systems. Biotechnol. Bioeng. 2010;106: 619–626. © 2010 Wiley Periodicals, Inc.     

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.     

Phosphatidylinositol 4‐phosphate on Rab7‐positive autophagosomes revealed by the freeze‐fracture replica labeling

Phosphatidylinositol 4‐phophate (PtdIns(4)P) is an essential signaling molecule in the Golgi body, endosomal system, and plasma membrane and functions in the regulation of membrane trafficking, cytoskeletal organization, lipid metabolism and signal transduction pathways, all mediated by direct interaction with PtdIns(4)P‐binding proteins. PtdIns(4)P was recently reported to have functional roles in autophagosome biogenesis. LC3 and GABARAP subfamilies and a small GTP‐binding protein, Rab7, are localized on autophagosomal membranes and participate at each stage of autophagosome formation and maturation. To better understand autophagosome biogenesis, it is essential to determine the localization of PtdIns(4)P and to examine its relationship with LC3 and GABARAP subfamilies and Rab7. To analyze PtdIns(4)P distribution, we used an electron microscopy technique that labels PtdIns(4)P on the freeze‐fracture replica of intracellular biological membranes, which minimizes the possibility of artificial perturbation because molecules in the membrane are physically immobilized in situ. Using this technique, we found that PtdIns(4)P is localized on the cytoplasmic, but not the luminal (exoplasmic), leaflet of the inner and outer membranes of autophagosomes. Double labeling revealed that PtdIns(4)P mostly colocalizes with Rab7, but not with LC3B, GABARAP, GABARAPL1 and GABARAPL2. Rab7 plays essential roles in autophagosome maturation and in autophagosome‐lysosome fusion events. We suggest that PtdIns(4)P is localized to the cytoplasmic leaflet of the autophagosome at later stages, which may illuminate the importance of PtdIns(4)P at the later stages of autophagosome formation.      

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.     

The shifting phenological landscape: Within‐ and between‐species variation in leaf emergence in a mixed‐deciduous woodland

Many organisms rely on synchronizing the timing of their life‐history events with those of other trophic levels—known as phenological matching—for survival or successful reproduction. In temperate deciduous forests, the extent of matching with the budburst date of key tree species is of particular relevance for many herbivorous insects and, in turn, insectivorous birds. In order to understand the ecological and evolutionary forces operating in these systems, we require knowledge of the factors influencing leaf emergence of tree communities. However, little is known about how phenology at the level of individual trees varies across landscapes, or how consistent this spatial variation is between different tree species. Here, we use field observations, collected over 2 years, to characterize within‐ and between‐species differences in spring phenology for 825 trees of six species (Quercus robur, Fraxinus excelsior, Fagus sylvatica, Betula pendula, Corylus avellana, and Acer pseudoplatanus) in a 385‐ha woodland. We explore environmental predictors of individual variation in budburst date and bud development rate and establish how these phenological traits vary over space. Trees of all species showed markedly consistent individual differences in their budburst timing. Bud development rate also varied considerably between individuals and was repeatable in oak, beech, and sycamore. We identified multiple predictors of budburst date including altitude, local temperature, and soil type, but none were universal across species. Furthermore, we found no evidence for interspecific covariance of phenology over space within the woodland. These analyses suggest that phenological landscapes are highly complex, varying over small spatial scales both within and between species. Such spatial variation in vegetation phenology is likely to influence patterns of selection on phenology within populations of consumers. Knowledge of the factors shaping the phenological environments experienced by animals is therefore likely to be key in understanding how these evolutionary processes operate.     

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.     

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.     

Ultra scale‐down approaches for clarification of mammalian cell culture broths in disc‐stack centrifuges

Ultra‐scale down (USD) methodology developed by University College London for cell broth clarification with industrial centrifuges was applied to two common cell lines (NS0 and GS‐CHO) expressing various therapeutic monoclonal antibodies. A number of centrifuges at various scales were used with shear devices operating either by high speed rotation or flow‐through narrow channels. The USD methodology was found effective in accounting for both gravitational and shear effects on clarification performance with three continuous centrifuges at pilot and manufacturing scales. Different shear responses were observed with the two different cell lines and even with the same cell line expressing different products. Separate particle size analysis of the treated broths seems consistent with the shear results. Filterability of the centrifuged solutions was also evaluated to assess the utility of the USD approach for this part of the clarification operation. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009