Growth of E. coli in a stirred tank and in an air lift tower reactor with an outer loop

E. coli ATCC 11105 was cultivated in a 10-1 stirred tank reactor and in a 60-1 tower loop reactor in batch and continuous operation. By on-line measurements of O₂ and CO₂ concentrations in the outlet gas, pH, temperature, cell mass concentration X as well as dissolved O₂ concentration along the tower in the broth, gas holdup, broth recirculation rate through the loop and by offline measurements of substrate concentration DOC and cell mass concentration along the tower, the maximum specific growth rate _m , yield coefficients Y _X/S. Y _X/DOC and were evaluated in stirred tank and tower loop in batch and continuous cultures with and without motionless mixers in the tower and at different broth circulation rates through the loop. To control the accuracy of the measurements the C balance was calculated and 95% of the C content was covered.The biological parameters determined depend on the mode of operation as well as on the reactor used. Furthermore, they depend on the recirculation rate of the broth and built-ins in the tower. The unstructured cell and reactor models are unable to explain these differences. Obviously, structured cell and reactor models are needed. The cell mass concentration can be determined on line by NADH fluorescence in balanced growth, if the model parameters are determined under the same operational conditions in the same reactor.List of Symbols a, b empirical parameters in Eq. (1) - CPR kg/(m³ h) CO₂ production rate - C kg/m³ concentration - D l/h dilution rate - DOC kg/m³ dissolved organic carbon - I net. fluorescence intensity - K _S kg/m³ Monod constant - k _L a l/h volumetric mass transfer coefficient - OTR kg/(m³ h) oxygen transfer rate - OUR kg/(m³ h) oxygen utilization rate - RQ = CPR/OUR respiratory quotient - S kg/m³ substrate concentration - t h,min, s time - t _u min recirculation time - t _M min mixing time - v m³/h volumetric flow rate through the loop - X kg/m³ (dry) cell mass concentration - Y _X/S yield coefficient of cell mass with regard to the consumed substrate - Y _X/DOC yield coefficient of the cell mass with regard to the consumed DOC - Y _X/O yield coefficient of the cell mass with regard to the consumed oxygen - Z relative distance in the tower from the aerator with regard to the height of the aerated broth - l/h specific growth rate - _m l/h maximum specific growth rate Indices f feed - e outlet     

The Electrical Conductivity of Bovine Milk in Mastitis Diagnosis

The electrical conductivity (EC) of milk is mainly a function of the electrolyte concentration in the milk and therefore raised in mastitis. The present investigation was aimed at elaborating, if possible, a diagnostic model for screening purposes based on EC determinations and consistent with the diagnostic procedures and interpretations commonly used in laboratory milk diagnosis in the Nordic countries (Klastrup 1975). According to this diagnosis (here called reference diagnosis) cell numbers above 300,000/ml (cell count or the corresponding CMT-score) in foremilk quarter samples during the main part of the lactation period and significantly above the lowest value on within-udder comparison during late lactation are considered indicative of mastitis and bacteriological examinations are made when called for.     

On the role of Ca2+-calmodulin-dependent and cAMP-dependent protein phosphorylation in the circadian rhythm ofNeurospora crassa

Summary Pulses of some Ca²⁺ channel blockers (dantrolene, Co²⁺, nifedipine) and calmodulin inhibitors (chlorpromazine) lead to medium (maximally 5–9 h) phase shifts of the circadian conidiation rhythm ofNeurospora crassa. Pulses of high Ca²⁺, or of low Ca²⁺, a Ca²⁺ ionophore (A23187) together with Ca²⁺, and other Ca²⁺ channel blockers (La³⁺, diltiazem), however, caused only minor phase shifts. The effect of these substances (A 23187) and of different temperatures on the Ca²⁺ release from isolated vacuoles was analyzed by using the fluorescent dye Fura-2. A 23187 and higher temperatures increased the release drastically, whereas dantrolene decreased the permeation of Ca²⁺ (Cornelius et al., 1989).Pulses of 8-PCTP-cAMP, IBMX and of the cAMP antagonist RP-cAMPS, also caused medium (maximally 6–9 h) phase shifts of the conidiation rhythm. The phase response curve of the agonist was almost 180° out of phase with the antagonist PRC. In spite of some variability in the PRCs of these series of experiments all showed maximal shifts during ct 0–12. The variability of the response may be due to circadian changes in the activity of phosphodiesterases: After adding cAMP to mycelial extracts HPLC analysis of cAMP metabolites showed significant differences during a circadian period with a maximum at ct 0.Protein phosphorylation was tested mainly in an in vitro phosphorylation system (with³⁵S-thio -ATP). The results showed circadian rhythmic changes predominantly in proteins of 47/48 kDa. Substances and treatments causing phase-shifts of the conidiation rhythm also caused changes in the phosphorylation of these proteins: an increase was observed when Ca²⁺ or cAMP were added, whereas a decrease occurred upon addition of a calmodulin inhibitor (TFP) or pretreatment of the mycelia with higher (42° C) temperatures.Altogether, the results indicate that Ca²⁺-calmodulin-dependent and cAMP-dependent processes play an important, but perhaps not essential, role in the clock mechanism ofNeurospora. Ca²⁺ calmodulin and the phosphorylation state of the 47/48-kDa proteins may have controlling or essential functions for this mechanism.     

Genetic analysis of two tomato mutants affected in the regulation of iron metabolism

Iron is one of the most important micronutrients for plants. Like other organisms, plants have developed active mechanisms for the acquisition of sufficient iron from the soil. Nevertheless, very little is known about the genetic mechanisms that control the active uptake. In tomato, two spontaneously derived mutants are available, which are defective in key steps that control this process. The recessive mutationchloronerva (chln) affects a gene which controls the synthesis of the non-protein amino acid nicotianamine (NA), a key component in the iron physiology of plants. The root system of the recessive mutantfer is unable to induce any of the characteristic responses to iron deficiency and iron uptake is thus completely blocked. We present a characterization of the double mutant, showing that thefer gene is epistatic over thechln gene and thus very likely to be one of the major genetic elements controlling iron physiology in tomato. In order to gain access to these two genes at the molecular level, both mutants were precisely mapped onto the high density RFLP map of tomato. Thechln gene is located on chromosome 1 and thefer gene is on chromosome 6 of tomato. Using this high-resolution map, a chromosome walk has been started to isolate thefer gene by map-based cloning. The isolation of thefer gene will provide new insights into the molecular mechanisms of iron uptake control in plants.     

Suppression of fungal β-glucan-induced plant defence in soybean (Glycine max L.) by cyclic 1,3-1,6-β-glucans from the symbiont Bradyrhizobium japonicum

The production of antimicrobial phytoalexins is one of the best-known inducible defence responses following microbial infection of plants or treatment with elicitors. In the legume soybean (Glycine max L.), 1,3-1,6--glucans derived from the fungal pathogen Phytophthora sojae have been identified as potent elicitors of the synthesis of the phytoalexin, glyceollin. Recently it has been reported that during symbiotic interaction between soybean and the nitrogen-fixing bacterium Bradyrhizobium japonicum USDA 110 the bacteria synthesize cyclic 1,3-1,6--glucans. Here we demonstrate that both the fungal and the bacterial -glucans are ligands of -glucan-binding sites which are putative receptors for the elicitor signal compounds in soybean roots. Whereas the fungal -glucans stimulate phytoalexin synthesis at low concentrations, the bacterial cyclic 1,3-1,6--glucans appear to be inactive even at relatively high concentrations. Competition studies indicate that increasing concentrations of the bacterial 1,3-1,6--glucans progressively inhibit stimulation of phytoalexin synthesis in a bioassay induced by the fungal 1,3-1,6--glucans. Another type of cyclic -glucan, a 1,2--glucan from Rhizobium meliloti, that does not nodulate on soybean, seems to be inactive as elicitor and as ligand of the -glucan-binding sites. These results may indicate a novel mechanism for a successful plant-symbiont interaction by suppressing the plant's defence response.Abbreviations HG-APEA 1-[2-(4-aminophenyl)ethyl]amino-l-[hexaglucosyl]deoxyglucitol - HG-AzPEA l-[2-(4-azidophenyl)-ethyl]amino-l-[hexaglucosyl]deoxyglucitol - IC₅₀ concentration for half-maximal displacement We thank Ines Arlt for excellent technical assistance. This work was supported by the Deutsche Forschungsgemeinschaft (SFB 369), the Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie, Fonds der Chemischen Industrie (J.E.), and USDA CSRS NRI Competitive Research grant 93373059233 (A.A.B.).     

Comparative studies on the dynamics of crosslinked insulin

Molecular dynamics simulations were carried out on an insulin crosslinked between the N-terminal A chain and the C-terminal B chain to form a so-called mini-proinsulin: N -^A1-N -^B29-diaminosuberoyl insulin (DASI). To investigate the influence of crosslinking on the dynamics of the insulin moiety, the bridge was removed from a transient DASI structure and simulation was carried on independently with the then unlinked (ULKI) as well as with the crosslinked species. The effects of crystal packing and quaternary interactions were checked by simulating both types of monomers and dimers known from the hexamer structure. All simulations were compared to previous ones of native insulin. DASI shows general similarity to the native simulations in most parts of the structure. Deviations are visible in the segments to which the bridge is directly connected, i.e. their flexibility is reduced. Upon removal of the bridge the ULKI simulations reapproach those of native insulin. The influence of the bridge spreads over the whole molecule, but all of its main structural features remain intact. The simulations suggest that the displacement of the C-terminal B chain of native insulin, considered important for receptor interaction, is prevented by the bridge, which also partially shields some binding residues. This is in accordance with the poor biological potency of A1-B29-crosslinked insulins.Abbreviations DASI-insulin(DASI) bovineN -^A1-N -^B29-di-aminosuberoyl insulin - ULK-insulin (ULKI) Native beef insulin with the bridge of DASI removed     

Phylogenetic relationships among eutherian orders estimated from inferred sequences of mitochondrial proteins: Instability of a tree based on a single gene

The phylogenetic relationships among Primates (human), Artiodactyla (cow), Cetacea (whale), Carnivora (seal), and Rodentia (mouse and rat) were estimated from the inferred amino acid sequences of the mitochondrial genomes using Marsupialia (opossum), Aves (chicken), and Amphibia (Xenopus) as an outgroup. The overall evidence of the maximum likelihood analysis suggests that Rodentia is an outgroup to the other four eutherian orders and that Cetacea and Artiodactyla form a clade with Carnivora as a sister taxon irrespective of the assumed model for amino acid substitutions. Although there remains an uncertainty concerning the relation among Artiodactyla, Cetacea, and Carnivora, the existence of a clade formed by these three orders and the outgroup status of Rodentia to the other eutherian orders seems to be firmly established. However, analyses of individual genes do not necessarily conform to this conclusion, and some of the genes reject the putatively correct tree with nearly 5% significance. Although this discrepancy can be due to convergent or parallel evolution in the specific genes, it was pointed out that, even without a particular reason, such a discrepancy can occur in 5% of the cases if the branching among the orders in question occurred within a short period. Due to uncertainty about the assumed model underlying the phylogenetic inference, this can occur even more frequently. This demonstrates the importance of analyzing enough sequences to avoid the danger of concluding an erroneous tree.