Analysis of kinetic,stoichiometry and regulation of glucose and glutamine metabolism in hybridoma batch cultures using logistic equations

Batch cultures were carried out to study the kinetic, stoichiometry, and regulation of glucose and glutamine metabolism of a murine hybridoma line. Asymmetric logistic equations (ALEs) were used to fit total and viable cell density, and nutrient and metabolite/product concentrations. Since these equations were analytically differentiable, specific rates and yield coefficients were readily calculated. Asymmetric logistic equations described satisfactorily uncontrolled batch cultures, including death phase. Specific growth rate showed a Monod-type dependence on initial glucose and glutamine concentrations. Yield coefficients of cell and lactate from glucose, and cell and ammonium from glutamine were all found to change dramatically at low residual glucose and glutamine concentrations. Under stoichiometric glucose limitation, the glucose-to-cell yield increased and glucose-to-lactate yield decreased, indicating a metabolic shift. Under stoichiometric glutamine limitation the glutamine-to-cell and glutamine-to-ammonium yields increased, but also glucose-to-cell yield increased and the glucose-to-lactate yield decreased. Monoclonal antibody production was mainly non-growth associated, independently of glucose and glutamine levels.     

Hydrophobic interaction between contiguous residues in the S6 transmembrane segment acts as a stimuli integration node in the BK channel

Large-conductance Ca²⁺- and voltage-activated K⁺ channel (BK) open probability is enhanced by depolarization, increasing Ca²⁺ concentration, or both. These stimuli activate modular voltage and Ca²⁺ sensors that are allosterically coupled to channel gating. Here, we report a point mutation of a phenylalanine (F380A) in the S6 transmembrane helix that, in the absence of internal Ca²⁺, profoundly hinders channel opening while showing only minor effects on the voltage sensor active–resting equilibrium. Interpretation of these results using an allosteric model suggests that the F380A mutation greatly increases the free energy difference between open and closed states and uncouples Ca²⁺ binding from voltage sensor activation and voltage sensor activation from channel opening. However, the presence of a bulky and more hydrophobic amino acid in the F380 position (F380W) increases the intrinsic open–closed equilibrium, weakening the coupling between both sensors with the pore domain. Based on these functional experiments and molecular dynamics simulations, we propose that F380 interacts with another S6 hydrophobic residue (L377) in contiguous subunits. This pair forms a hydrophobic ring important in determining the open–closed equilibrium and, like an integration node, participates in the communication between sensors and between the sensors and pore. Moreover, because of its effects on open probabilities, the F380A mutant can be used for detailed voltage sensor experiments in the presence of permeant cations.     

Effects of combining biological treatment and activated carbon on hexavalent chromium reduction

The objectives of the present work were: (a) to analyze the Cr(VI) removal by combining activated sludge (AS) with powdered activated carbon (PAC), (b) to analyze the effect of PAC and Cr(VI) on the growth kinetics of activated sludge, and (c) to determine if the combined method (AS-PAC) for Cr(VI) removal can be considered additive or synergistic with respect to the individual processes. Chromate removal was improved by increasing PAC concentrations in both PAC and AS-PAC systems. Cr(VI) removal using the AS-PAC system was higher than using AS or PAC. The increase of Cr(VI) caused longer lag phase and lower observed specific growth rate (μ_obs), biomass yield (Y_X/S), and specific growth substrate consumption rate (q_S) of activated sludge; additionally, PAC did not enhance the growth kinetic parameters (μ_obs, Y_X/S, q_S). Cr(VI) reduction in AS-PAC system was the result of the additive effect of each individual Cr(VI) removal process.     

Salmonella bongori provides insights into the evolution of the Salmonellae

The genus Salmonella contains two species, S. bongori and S. enterica. Compared to the well-studied S. enterica there is a marked lack of information regarding the genetic makeup and diversity of S. bongori. S. bongori has been found predominantly associated with cold-blooded animals, but it can infect humans. To define the phylogeny of this species, and compare it to S. enterica, we have sequenced 28 isolates representing most of the known diversity of S. bongori. This cross-species analysis allowed us to confidently differentiate ancestral functions from those acquired following speciation, which include both metabolic and virulence-associated capacities. We show that, although S. bongori inherited a basic set of Salmonella common virulence functions, it has subsequently elaborated on this in a different direction to S. enterica. It is an established feature of S. enterica evolution that the acquisition of the type III secretion systems (T3SS-1 and T3SS-2) has been followed by the sequential acquisition of genes encoding secreted targets, termed effectors proteins. We show that this is also true of S. bongori, which has acquired an array of novel effector proteins (sboA-L). All but two of these effectors have no significant S. enterica homologues and instead are highly similar to those found in enteropathogenic Escherichia coli (EPEC). Remarkably, SboH is found to be a chimeric effector protein, encoded by a fusion of the T3SS-1 effector gene sopA and a gene highly similar to the EPEC effector nleH from enteropathogenic E. coli. We demonstrate that representatives of these new effectors are translocated and that SboH, similarly to NleH, blocks intrinsic apoptotic pathways while being targeted to the mitochondria by the SopA part of the fusion. This work suggests that S. bongori has inherited the ancestral Salmonella virulence gene set, but has adapted by incorporating virulence determinants that resemble those employed by EPEC.     

Specificity of Intramembrane Protein–Lipid Interactions

Our concept of biological membranes has markedly changed, from the fluid mosaic model to the current model that lipids and proteins have the ability to separate into microdomains, differing in their protein and lipid compositions. Since the breakthrough in crystallizing membrane proteins, the most powerful method to define lipid-binding sites on proteins has been X-ray and electron crystallography. More recently, chemical biology approaches have been developed to analyze protein–lipid interactions. Such methods have the advantage of providing highly specific cellular probes. With the advent of novel tools to study functions of individual lipid species in membranes together with structural analysis and simulations at the atomistic resolution, a growing number of specific protein–lipid complexes are defined and their functions explored. In the present article, we discuss the various modes of intramembrane protein–lipid interactions in cellular membranes, including examples for both annular and nonannular bound lipids. Furthermore, we will discuss possible functional roles of such specific protein–lipid interactions as well as roles of lipids as chaperones in protein folding and transport.Our concept of biological membranes has markedly changed in the last two decades, from the fluid mosaic model (Singer and Nicolson 1972), in which the membrane was thought to be formed by a homogenous lipid fluid phase with proteins embedded, to the current model that lipids and proteins are not homogenously distributed, but have the ability to separate into microdomains, differing in their protein and lipid compositions. A well established example of domains are lipid rafts (see Box 1 for definitions). Raft domains are described as dynamic domain structures enriched in cholesterol, sphingolipids, and membrane proteins (Brown and London 1998; Simons and Ikonen 1997) that have an important role in different cellular processes (Lingwood and Simons 2010). Formation of domains within cellular membranes has been extensively investigated over the past years leading to various models that differ in the primary forces involved in the formation and the recruitment of surrounding membrane components into such domains.

BOX 1.

Definitions

Annular Lipids/Lipid Shell

An annular lipid shell is formed when selected lipid classes or molecular species bind preferentially to the hydrophobic and/or hydrophilic surfaces of a membrane protein. Per definition these lipids show markedly reduced residence times at the protein–lipid interface as compared to bulk lipids.

Bulk Lipids

Lipids within the membrane that diffuse rapidly in the bilayer plane and show a low residence time at the protein–lipid interface following random collisions. Typical diffusion coefficients for bulk lipids in a liquid disordered phase are in the range of D_L = 7×10⁻¹² m²/sec (DOPC) (Filippov et al. 2003).

Hydrophobic Mismatch

A term to describe any deviation from the compatibility of the hydrophobic surface of membrane proteins (their TMDs) to the vertically and laterally encountered hydrophobic surfaces of the lipid bilayer in biological membranes. In the case of a hydrophobic mismatch, the resulting energy penalty may cause the recruitment of a suitable local lipid environment, the deformation of the membrane and/or in conformational changes of the protein to achieve a status of hydrophobic match (for advanced reading, see Killian 1998).

Lateral Pressure Field/Profile of Membranes

Biological membranes can be considered as the “solvent” for membrane proteins that are embedded in them. The lateral pressure profile (Ω(z)) describes the force or pressure that is exerted by the membrane on the matter residing inside it. This pressure is modulated by different extents of lipid–lipid interactions and asymmetries across and within the bilayer, which in turn results in varying lateral pressures that may locally correspond to several hundreds of atmospheres.

Lipid Rafts

Sterol and sphingolipid-dependent microdomains that form a network of lipid–lipid, protein–protein, and protein–lipid interactions; involved in the compartmentalization of processes such as signaling within biological membranes.

Liquid-Disordered Phase (I_d)

A predominantly fluid phase of lipids, characterized by a high degree of mobility (cis-gauche flexibility of acyl chains; lateral diffusion) and a high content of short and/or unsaturated fatty acyl chains.

Liquid-Ordered Phase (I_o)

A liquid crystalline phase (that displays physical properties of both liquids and of solid crystals), characterized by a high degree of acyl chain order (“packing”), a reduced lateral mobility of lipid and protein molecules, and a reduction in the elasticity of the membrane as a result of specific interactions between sterols and phospholipids containing long, saturated acyl chains and/or glycosphingolipids.

Microdomains

Membrane compartments of distinct lipid and protein composition that may modulate the enzymatic functions of membrane proteins.

Molecular Lipid Species

Individual members of a lipid class that differ in their fatty acid composition.

Nonannular Lipids

Lipids that specifically interact with membrane proteins are neither bulk lipids, nor do they belong to the shell/annulus of lipids that surround the membrane protein. These nonannular lipids often reside within membrane protein complexes, in which they may fulfill diverse functions ranging from structural building blocks to allosteric effectors of enzymatic activity (see text). Nonannular lipids bind to distinct hydrophobic sites of membrane proteins or membrane protein complexes.According to one model, membrane domains can form by specific protein–protein interactions (Douglass and Vale 2005). This model is based on single-molecule microscopy experiments. In these studies, single fluorophores were chemically attached to specific proteins, and the dynamics of individual proteins was tracked by monitoring the fluorescent probe. In this kind of set up, a dynamic behavior of lipids is not assessed. Here, proteins involved in signaling processes are trapped within interconnected microdomains created by specific protein–protein interactions, probably involving additional scaffolding proteins. The proteins of such domains can exchange with the surrounding membrane area at individual kinetics, some components are immobile over minutes, and others can diffuse rapidly.Another model emphasizes the importance of lipid–lipid interactions, initiating the formation of subdomains of defined lipid compositions. Transmembrane proteins then can be attracted to such subdomains via various specific interactions with lipids. The resulting lipid–protein complexes then eventually coalesce to form larger lipid–protein assemblies (Anderson and Jacobson 2002).The idea of lipid-dependent domain formation is inherent to the biophysical properties and therefore to the complex lipid composition of cellular membranes that include up to a thousand lipids that vary in structure (van Meer et al. 2008). This wide range of lipid species has been proposed to facilitate the “solvation” of membrane proteins. Taken into account the sum of lipid species present in a cellular membrane, it is important to understand the different interactions and affinities within the bilayer between different lipids. Molecular dynamics simulations have been successfully employed to investigate lipid interactions between different lipid species and found specific interactions of various lipid classes and molecular species (Hofsass et al. 2003; Niemela et al. 2004, 2006, 2009; Pandit et al. 2004; Zaraiskaya and Jeffrey 2005; Bhide et al. 2007). These results are supported and expanded by recent data from our group that suggest a specific order of interactions of sphingomyelin species with cholesterol in membranes (A.M. Ernst, F. Wieland, and B. Brügger, unpubl.). At low cholesterol concentrations, some sphingomyelin species preferentially interact with cholesterol, whereas others prefer their kin. At higher cholesterol concentrations, all sphingomyelin species investigated display an increased affinity for the sterol. These findings open the possibility of differentiated pathways of self-assembly of microdomains, dependent on molecular lipid species.In the present article the various modes of intramembrane protein–lipid interactions in cellular membranes (Fig. 1) will be discussed. This includes possible functional roles of such specific protein–lipid interactions.Open in a separate windowFigure 1.Intramembrane protein–lipid interactions within a cell membrane. (A) Bulk lipids; (B) annular lipids; (C) nonannular lipids/lipid ligands. For details see text.     

Structure of the human gastric bacterial community in relation to Helicobacter pylori status

The human stomach is naturally colonized by Helicobacter pylori, which, when present, dominates the gastric bacterial community. In this study, we aimed to characterize the structure of the bacterial community in the stomach of patients of differing H. pylori status. We used a high-density 16S rRNA gene microarray (PhyloChip, Affymetrix, Inc.) to hybridize 16S rRNA gene amplicons from gastric biopsy DNA of 10 rural Amerindian patients from Amazonas, Venezuela, and of two immigrants to the United States (from South Asia and Africa, respectively). H. pylori status was determined by PCR amplification of H. pylori glmM from gastric biopsy samples. Of the 12 patients, 8 (6 of the 10 Amerindians and the 2 non-Amerindians) were H. pylori glmM positive. Regardless of H. pylori status, the PhyloChip detected Helicobacteriaceae DNA in all patients, although with lower relative abundance in patients who were glmM negative. The G2-chip taxonomy analysis of PhyloChip data indicated the presence of 44 bacterial phyla (of which 16 are unclassified by the Taxonomic Outline of the Bacteria and Archaea taxonomy) in a highly uneven community dominated by only four phyla: Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. Positive H. pylori status was associated with increased relative abundance of non-Helicobacter bacteria from the Proteobacteria, Spirochetes and Acidobacteria, and with decreased abundance of Actinobacteria, Bacteroidetes and Firmicutes. The PhyloChip detected richness of low abundance phyla, and showed marked differences in the structure of the gastric bacterial community according to H. pylori status.     

EXTRAFLORAL NECTARIES IN EBENACEAE: ANATOMY,MORPHOLOGY, AND DISTRIBUTION

Previous superficial reports, but only one anatomical study of one species, have supported the view that extrafloral nectaries (EFNs) of the unusual Benincasa type (i.e., with several layers of small nectariferous cells) of “Flachnektarien” (surface nectary) are common in Ebenaceae. An anatomical survey was made of 107 species (24% of the 450 species) of the four genera commonly accepted (Diospyros—73, Euclea—13, Maba— 12, Royena—9). There are 1–15 abaxial EFNs per leaf (two species each of Euclea and Royena had none). They were all of the Benincasa type, subtended by an irregularly 1–2-layered sheath of cells with extremely thick radial walls. The pattern of minor vein association allowed recognition of two subtypes: apovascular (two or more subglandular layers between vein and sheath) and paravascular (one subglandular separating layer). Apovascular EFNs are smaller but more numerous per leaf, paravascular EFNs are larger but fewer per leaf. The apovascular subtype is most common in North America and Asia; a mixture of both subtypes occurs elsewhere; Euclea has only the latter subtype. Both subtypes have the most extensive vascular association yet described for Flachnektarien. They appear to have become specialized early in the family's evolution, before extensive migration occurred.