Regulatory role of monoamine neurotransmitters in <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis> cells

Proliferation of Saccharomyces cerevisiae EPF cells on solid maltose-peptone-yeast extract (MPY) medium was stimulated by the addition of monoamine neurotransmitters. Dopamine turned out to be the most efficient among them: it caused ∼8-fold growth stimulation at 1 μM concentration. The dopamine effect was partly mimicked by apomorphine, a dopamine receptor agonist. Serotonin and histamine produced less significant (1.5–2-fold) effects, and norepinephrine virtually failed to stimulate yeast culture growth. These data point to a specific, apparently receptor-dependent mode of action of the tested neurotransmitters on S. cerevisiae cells. Using high performance liquid chromatography, serotonin, catecholamines (dopamine and norepinephrine), catecholamine precursor dioxyphenylamine, and oxidized amine products (homovanilic acid, dihydrophenylacetic acid, and 5-hydroxyindolacetic acid) were established to be accumulated in yeast cells up to (sub)micromolar concentrations without their release into the culture fluid supernatant (CFS). The results obtained suggest that the tested amine neurotransmitters and related compounds do not serve as autoregulators in the yeast population. Nevertheless, they may be involved in the regulation of yeast population development by other ecosystem components.     

Flora Europaea Notulae Systematicae ad Floram Europaeam spectantes No. 20 Corrigenda et Addenda

Following the publication of the last of the series of Flora Europaea Notulae, No. 20 in the Botanical Journal of the Linnean Society , 76: 297–384 (1978), a number of additions or alterations have been drawn to our attention. These are published in continuation.     

Use of inert gas jets to measure the forces required for mechanical gene transfection

Background

Abnormal blood glucose (BG) concentrations have been associated with increased morbidity and mortality in both critically ill adults and infants. Furthermore, hypoglycaemia and glycaemic variability have both been independently linked to mortality in these patients. Continuous Glucose Monitoring (CGM) devices have the potential to improve detection and diagnosis of these glycaemic abnormalities. However, sensor noise is a trade-off of the high measurement rate and must be managed effectively if CGMs are going to be used to monitor, diagnose and potentially help treat glycaemic abnormalities.

Aim

To develop a tool that will aid clinicians in identifying unusual CGM behaviour and highlight CGM data that potentially need to be interpreted with care.

Methods

CGM data and BG measurements from 50 infants at risk of hypoglycaemia were used. Unusual CGM measurements were classified using a stochastic model based on the kernel density method and historical CGM measurements from the cohort. CGM traces were colour coded with very unusual measurements coloured red, highlighting areas to be interpreted with care. A 5-fold validation of the model was Monte Carlo simulated 25 times to ensure an adequate model fit.

Results

The stochastic model was generated using ~67,000 CGM measurements, spread across the glycaemic range ~2-10?mmol/L. A 5-fold validation showed a good model fit: the model 80% confidence interval (CI) captured 83% of clinical CGM data, the model 90% CI captured 91% of clinical CGM data, and the model 99% CI captured 99% of clinical CGM data. Three patient examples show the stochastic classification method in use with 1) A stable, low variability patient which shows no unusual CGM measurements, 2) A patient with a very sudden, short hypoglycaemic event (classified as unusual), and, 3) A patient with very high, potentially un-physiological, glycaemic variability after day 3 of monitoring (classified as very unusual).

Conclusions

This study has produced a stochastic model and classification method capable of highlighting unusual CGM behaviour. This method has the potential to classify important glycaemic events (e.g. hypoglycaemia) as true clinical events or sensor noise, and to help identify possible sensor degradation. Colour coded CGM traces convey the information quickly and efficiently, while remaining computationally light enough to be used retrospectively or in real-time.     

Cortical potential imaging using L-curve and GCV method to choose the regularisation parameter

Background

The electroencephalography (EEG) is an attractive and a simple technique to measure the brain activity. It is attractive due its excellent temporal resolution and simple due to its non-invasiveness and sensor design. However, the spatial resolution of EEG is reduced due to the low conducting skull. In this paper, we compute the potential distribution over the closed surface covering the brain (cortex) from the EEG scalp potential. We compare two methods – L-curve and generalised cross validation (GCV) used to obtain the regularisation parameter and also investigate the feasibility in applying such techniques to N170 component of the visually evoked potential (VEP) data.

Methods

Using the image data set of the visible human man (VHM), a finite difference method (FDM) model of the head was constructed. The EEG dataset (256-channel) used was the N170 component of the VEP. A forward transfer matrix relating the cortical potential to the scalp potential was obtained. Using Tikhonov regularisation, the potential distribution over the cortex was obtained.

Results

The cortical potential distribution for three subjects was solved using both L-curve and GCV method. A total of 18 cortical potential distributions were obtained (3 subjects with three stimuli each – fearful face, neutral face, control objects).

Conclusions

The GCV method is a more robust method compared to L-curve to find the optimal regularisation parameter. Cortical potential imaging is a reliable method to obtain the potential distribution over cortex for VEP data.

     

Role of Neurochemicals in the Interaction between the Microbiota and the Immune and the Nervous System of the Host Organism

This work is concerned with the role of evolutionary conserved substances, neurotransmitters, and neurohormones, within the complex framework of the microbial consortium–immune system–nervous system axis in the human or animal organism. Although the operation of each of these systems per se is relatively well understood, their combined effects on the host organism still await further research. Drawing on recent research on host-produced and microbial low-molecular-weight neurochemicals such as biogenic amines, amino acids, and short-chain fatty acids (SCFAs), we suggest that these mediators form a part of a universal neurochemical “language.” It mediates the whole gamut of harmonious and disharmonious interactions between (a) the intestinal microbial consortium, (b) local and systemic immune cells, and (c) the central and peripheral nervous system. Importantly, the ongoing microbiota–host interactivity is bidirectional. We present evidence that a large number of microbially produced low-molecular-weight compounds are identical or homologous to mediators that are synthesized by immune or nervous cells and, therefore, can bind to the corresponding host receptors. In addition, microbial cells specifically respond to host-produced neuromediators/neurohormones because they have adapted to them during the course of many millions of years of microbiota–host coevolution. We emphasize that the terms “microbiota” and “microbial consortium” are to be used in the broadest sense, so as to include, apart from bacteria, also eukaryotic microorganisms. These are exemplified by the mycobiota whose role in the microbial consortium–immune system–nervous system axis researchers are only beginning to elucidate. In light of the above, it is imperative to reform the current strategies of using probiotic microorganisms and their metabolites for treating and preventing dysbiosis-related diseases. The review demonstrates, in the example of novel probiotics (psychobiotics), that many target-oriented probiotic preparations produce important side effects on a wide variety of processes in the host organism. In particular, we should take into account probiotics’ capacity to produce mediators that can considerably modify the operation of the microecological, immune, and nervous system of the human organism.     

Programmed cell death

This paper reviews data on programmed cell death (apoptosis) in animals and plants. Necrosis is a pathological scenario of cell death, which entails an inflammatory response in animal tissues. Apoptosis results in the disintegration of animal/plant cells into membrane vesicles enclosing the intracellular content, which are thereupon engulfed by adjacent or specialized cells (phagocytes) in animals. Plants lack such specialized cells, and plant cell walls prevent phagocytosis. The paper considers the main molecular mechanisms of apoptosis in animals and the pathways of activation of caspases, evolutionarily conserved cysteine proteases. A self-contained section concerns itself with the process of programmed cell death (PCD) in microorganisms including: 1) cell death in the myxomycete Dictyostelium discoideum and the parasitic flagellate Trypanosoma cruzi; 2) PCD in genetically manipulated yeast expressing the proapoptotic Bax and Bak proteins; 3) the death of a part of a prokaryotic cell population upon the depletion of nutrient resources or under stress; 4) the elimination of cells after a loss of a plasmid encoding a stable cytotoxic agent in combination with an unstable antidote; and 5) PCD in phage-infected bacterial cells.     

Nonglutamate pore residues in ion selection and conduction in voltage-gated Ca(2+) channels

High-affinity, intrapore binding of Ca(2+) over competing ions is the essential feature in the ion selectivity mechanism of voltage-gated Ca(2+) channels. At the same time, several million Ca(2+) ions can travel each second through the pore of a single open Ca(2+) channel. How such high Ca(2+) flux is achieved in the face of tight Ca(2+) binding is a current area of inquiry, particularly from a structural point of view. The ion selectivity locus comprises four glutamate residues within the channel's pore. These glutamates make unequal contributions to Ca(2+) binding, underscoring a role for neighboring residues in pore function. By comparing two Ca(2+) channels (the L-type alpha(1C), and the non-L-type alpha(1A)) that differ in their pore properties but only differ at a single amino acid position near the selectivity locus, we have identified the amino-terminal neighbor of the glutamate residue in motif III as a determinant of pore function. This position is more important in the function of alpha(1C) channels than in alpha(1A) channels. For a systematic series of mutations at this pore position in alpha(1C), both unitary Ba(2+) conductance and Cd(2+) block of Ba(2+) current varied with residue volume. Pore mutations designed to make alpha(1C) more like alpha(1A) and vice versa revealed that relative selectivity for Ba(2+) over K(+) depended almost solely on pore sequence and not channel type. Analysis of thermodynamic mutant cycles indicates that the motif III neighbor normally interacts in a cooperative fashion with the locus, molding the functional behavior of the pore.     

Colonial organization and intercellular communication in microorganisms

This review covers the modern concepts and recent data demonstrating the integrity and coherence of microbial populations (colonies, biofilms, etc.) as peculiar “superorganisms.” Special attention is given to such relevant phenomena as apoptosis, bacterial altruism, quorum effects, collective differentiation of microbial cells, and the formation of population-level structures such as an extracellular matrix. Emphasis is placed on the channels and agents of intercellular communication in microbial populations. The involvement of a large number of evolutionarily conserved communicational facilities and patterns of intercellular interactions is underscored. Much attention is also given to the role of colonial organization and intercellular communication in parasite/commensal/symbiont-multicellular host organism systems.