Flow Cytometry Pulse Width Data Enables Rapid and Sensitive Estimation of Biomass Dry Weight in the Microalgae Chlamydomonas reinhardtii and Chlorella vulgaris

Dry weight biomass is an important parameter in algaculture. Direct measurement requires weighing milligram quantities of dried biomass, which is problematic for small volume systems containing few cells, such as laboratory studies and high throughput assays in microwell plates. In these cases indirect methods must be used, inducing measurement artefacts which vary in severity with the cell type and conditions employed. Here, we utilise flow cytometry pulse width data for the estimation of cell density and biomass, using Chlorella vulgaris and Chlamydomonas reinhardtii as model algae and compare it to optical density methods. Measurement of cell concentration by flow cytometry was shown to be more sensitive than optical density at 750 nm (OD₇₅₀) for monitoring culture growth. However, neither cell concentration nor optical density correlates well to biomass when growth conditions vary. Compared to the growth of C. vulgaris in TAP (tris-acetate-phosphate) medium, cells grown in TAP + glucose displayed a slowed cell division rate and a 2-fold increased dry biomass accumulation compared to growth without glucose. This was accompanied by increased cellular volume. Laser scattering characteristics during flow cytometry were used to estimate cell diameters and it was shown that an empirical but nonlinear relationship could be shown between flow cytometric pulse width and dry weight biomass per cell. This relationship could be linearised by the use of hypertonic conditions (1 M NaCl) to dehydrate the cells, as shown by density gradient centrifugation. Flow cytometry for biomass estimation is easy to perform, sensitive and offers more comprehensive information than optical density measurements. In addition, periodic flow cytometry measurements can be used to calibrate OD₇₅₀ measurements for both convenience and accuracy. This approach is particularly useful for small samples and where cellular characteristics, especially cell size, are expected to vary during growth.     

Modeling Hermissenda: II. Effects of variations in type-B cell excitability, synaptic strength, and network architecture

Because the Hermissenda eye is relatively simple and its cells well characterized, it provides an attractive preparation for detailed computational analysis. To examine the neural mechanisms of learning in this system, we developed multicompartmental models of the type-A and type-B photoreceptors, simulated the eye, and asked three questions: First, how do conductance changes affect cells in a network as compared with those in isolation; second, what are the relative contributions of increases in B-cell excitability and synaptic strength to network output; and third, how do these contributions vary as a function of network architecture? We found that reductions in the type-B cells of two K⁺ currents, I _A and I _C, differentially affected the type-B cells themselves, with I _C reductions increasing firing rate (excitability) in response to light, and I _A reductions increasing quantal output (synaptic strength) onto postsynaptic targets. Increases in either type-B cell excitability or synaptic strength, induced directly or indirectly, each suppressed A-cell photoresponses, and the combined effect of both changes occurring together was greater than either alone. To examine the effects of network architecture, we compared the full network with a simple feedforward B-A pair and intermediate configurations. Compared with a feedforward pair, the complete network exhibited greater A-cell sensitivity to B-cell changes. This was due to many factors, including an increased number of B-cells (which increased B-cell impact on A-cells), A-B feedback inhibition (which slowed both cell types and altered spike timing relationships), and B-B lateral inhibition (which reduced B-cell sensitivity to intrinsic biophysical modifications). These results suggest that an emergent property of the network is an increase both in the rate of information acquisition (“learning”) and in the amount of information that can be stored (“memory”).     

Matching–centrality decomposition and the forecasting of new links in networks

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network.     

Modeling the quorum sensing regulatory network of human-pathogenic Pseudomonas aeruginosa

The biochemical network underlying quorum sensing in human-pathogenic Pseudomonas aeruginosa is one of the best characterized. Mathematical modeling is required to untangle the complexity of its architecture and dynamics. We present a qualitative model of the P. aeruginosa quorum-sensing network including interactions between the las and rhl modules, the signaling molecule PQS and the regulatory proteins Mvfr and VfR. Simulations exemplify the model to reproduce natural network behavior and suggest quorum-sensing responses to pharmacological interference.     

The influence of salicylic acid elicitation of shoots, callus, and cell suspension cultures on production of naphtodianthrones and phenylpropanoids in Hypericum perforatum L.

Hypericum perforatum is a well known medicinal plant. The main pharmacological properties are due to the presence of naphtodianthrones such as hypericin and pseudohypericin. Unfortunately the levels of these compounds vary under different environmental conditions. Elicitation of in vitro cultures is a useful approach to enhance and extend production of desirable products. Therefore, the effects of salicylic acid were characterized on different explants of H. perforatum L. (cells, calli and shoots) cultured in vitro. It appears at first that salicylic acid did not affect growth and development of these explants. In addition, the production of both hypericin and pseudohypericin has doubled in elicited cell suspension cultures but not in the two other cultures. Furthermore, phenylpropanoids that are among the most frequently observed metabolites affected upon treatment of in vitro culture material with elicitors, were produced and the enzymatic activities of phenylalanine ammonia lyase and of chalcone isomerase were stimulated upon elicitation. These effects were dependant of the type of in vitro culture, the concentration of salicylic acid and the duration post-elicitation. The H. perforatum cells were globally more sensitive to salicylic acid elicitation when maintained in an undifferentiated state and particularly in cell suspension cultures. In the absence of glands considered as the sites of naphtodianthrones biosynthesis, cells and calli were capable of producing these compounds. This implies that salicylic acid could act at biosynthesis level but not for the accumulation of both hypericin and pseudohypericin. Consequently, the regulation of this process is more complex than cited in the literature involving the responsibility of only Hyp-1 gene, encoding a hypericin biosynthetic enzyme, cloned and characterized from H. perforatum.     

Wingless signaling and the control of cell shape in Drosophila wing imaginal discs

The control of cell morphology is important for shaping animals during development. Here we address the role of the Wnt/Wingless signal transduction pathway and two of its target genes, vestigial and shotgun (encoding E-cadherin), in controlling the columnar shape of Drosophila wing disc cells. We show that clones of cells mutant for arrow (encoding an essential component of the Wingless signal transduction pathway), vestigial or shotgun undergo profound cell shape changes and are extruded towards the basal side of the epithelium. Compartment-wide expression of a dominant-negative form of the Wingless transducer T-cell factor (TCF/Pangolin), or double-stranded RNA targeting vestigial or shotgun, leads to abnormally short cells throughout this region, indicating that these genes act cell autonomously to maintain normal columnar cell shape. Conversely, overexpression of Wingless, a constitutively-active form of the Wingless transducer β-catenin/Armadillo, or Vestigial, results in precocious cell elongation. Co-expression of Vestigial partially suppresses the abnormal cell shape induced by dominant-negative TCF. We conclude that Wingless signal transduction plays a cell-autonomous role in promoting and maintaining the columnar shape of wing disc cells. Furthermore, our data suggest that Wingless controls cell shape, in part, through maintaining vestigial expression.     

A Model for Visual Memory Encoding

Memory encoding engages multiple concurrent and sequential processes. While the individual processes involved in successful encoding have been examined in many studies, a sequence of events and the importance of modules associated with memory encoding has not been established. For this reason, we sought to perform a comprehensive examination of the network for memory encoding using data driven methods and to determine the directionality of the information flow in order to build a viable model of visual memory encoding. Forty healthy controls ages 19–59 performed a visual scene encoding task. FMRI data were preprocessed using SPM8 and then processed using independent component analysis (ICA) with the reliability of the identified components confirmed using ICASSO as implemented in GIFT. The directionality of the information flow was examined using Granger causality analyses (GCA). All participants performed the fMRI task well above the chance level (>90% correct on both active and control conditions) and the post-fMRI testing recall revealed correct memory encoding at 86.33±5.83%. ICA identified involvement of components of five different networks in the process of memory encoding, and the GCA allowed for the directionality of the information flow to be assessed, from visual cortex via ventral stream to the attention network and then to the default mode network (DMN). Two additional networks involved in this process were the cerebellar and the auditory-insular network. This study provides evidence that successful visual memory encoding is dependent on multiple modules that are part of other networks that are only indirectly related to the main process. This model may help to identify the node(s) of the network that are affected by a specific disease processes and explain the presence of memory encoding difficulties in patients in whom focal or global network dysfunction exists.     

Information routing driven by background chatter in a signaling network

Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity -or chatter- that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios.     

Design and utility of CCN2 anchor peptide aptamers

CCN family protein 2/connective tissue growth factor (CCN2/CTGF) consists of 4 conserved modules that are highly interactive with a number of biomolecules. With such interaction, CCN2 exerts multiple functions by forming an extracellular information network. In the present study, we screened for dodecapeptide sequences that bound to each module of human CCN2 by using a bacteriophage display library. Thereafter, consensus amino acid sequences for the binding to individual modules were extracted in silico and utilized to design anchor peptide aptamers that would facilitate the interaction between CCN2 and other molecules. Direct binding of a few peptides to CCN2 was confirmed by surface plasmon resonance analysis. Subsequent biological assay indicated that one such peptide was capable of promoting the proliferation of CCN2-producing chondrocytic cells. This cell biological activity was found to be sequence specific and CCN2 dependent. Since CCN2/CTGF was shown to be effective in articular cartilage/bone regeneration in vivo, utility of such peptide aptamers in CCN2-associated regenerative therapeutics is suggested herein.     

Dose-response aligned circuits in signaling systems

Cells use biological signal transduction pathways to respond to environmental stimuli and the behavior of many cell types depends on precise sensing and transmission of external information. A notable property of signal transduction that was characterized in the Saccharomyces cerevisiae yeast cell and many mammalian cells is the alignment of dose-response curves. It was found that the dose response of the receptor matches closely the dose responses of the downstream. This dose-response alignment (DoRA) renders equal sensitivities and concordant responses in different parts of signaling system and guarantees a faithful information transmission. The experimental observations raise interesting questions about the nature of the information transmission through DoRA signaling networks and design principles of signaling systems with this function. Here, we performed an exhaustive computational analysis on network architectures that underlie the DoRA function in simple regulatory networks composed of two and three enzymes. The minimal circuits capable of DoRA were examined with Michaelis-Menten kinetics. Several motifs that are essential for the dynamical function of DoRA were identified. Systematic analysis of the topology space of robust DoRA circuits revealed that, rather than fine-tuning the network's parameters, the function is primarily realized by enzymatic regulations on the controlled node that are constrained in limiting regions of saturation or linearity.     

Social Evolution Selects for Redundancy in Bacterial Quorum Sensing

Quorum sensing is a process of chemical communication that bacteria use to monitor cell density and coordinate cooperative behaviors. Quorum sensing relies on extracellular signal molecules and cognate receptor pairs. While a single quorum-sensing system is sufficient to probe cell density, bacteria frequently use multiple quorum-sensing systems to regulate the same cooperative behaviors. The potential benefits of these redundant network structures are not clear. Here, we combine modeling and experimental analyses of the Bacillus subtilis and Vibrio harveyi quorum-sensing networks to show that accumulation of multiple quorum-sensing systems may be driven by a facultative cheating mechanism. We demonstrate that a strain that has acquired an additional quorum-sensing system can exploit its ancestor that possesses one fewer system, but nonetheless, resume full cooperation with its kin when it is fixed in the population. We identify the molecular network design criteria required for this advantage. Our results suggest that increased complexity in bacterial social signaling circuits can evolve without providing an adaptive advantage in a clonal population.     

Integrated analysis of co-expressed MAP kinase substrates in Arabidopsis thaliana

MAP kinase (MAPK) signal transduction cascades are conserved eukaryotic pathways that modulate stress responses and developmental processes. In a recent report we have identified novel Arabidopsis MAPKK/MAPK/Substrate signaling pathways using microarrays containing 2,158 unique Arabidopsis proteins. Subsequently, several WRKY and TGA targets phosphorylated by MAPKs were verified in planta. We have also reported that specific MAPKK/MAPK modules expressed in Nicotiana benthamiana induced a cell death phenotype related to the immune response. We have generated a MAPK phosphorylation network based on our protein microarray experimental data. Here we further analyze our network by integrating phosphorylation and gene expression information to identify biologically relevant signaling modules. We have identified 108 phosphorylation events that occur among 96 annotated genes with highly similar pairwise expression profiles. Our analysis brings a new perspective on MAPK signaling by revealing new relationships between components of signaling pathways.Key words: MAPK, protein microarray, network, cell death, co-expression, signaling     

Yeast Protein Interactome topology provides framework for coordinated-functionality

The architecture of the network of protein–protein physical interactions in Saccharomyces cerevisiae is exposed through the combination of two complementary theoretical network measures, betweenness centrality and ‘Q-modularity’. The yeast interactome is characterized by well-defined topological modules connected via a small number of inter-module protein interactions. Should such topological inter-module connections turn out to constitute a form of functional coordination between the modules, we speculate that this coordination is occurring typically in a pairwise fashion, rather than by way of high-degree hub proteins responsible for coordinating multiple modules. The unique non-hub-centric hierarchical organization of the interactome is not reproduced by gene duplication-and-divergence stochastic growth models that disregard global selective pressures.     

Computer modeling of mechanisms of the information processing in the olfactory bulb. I. Model of the structure-functional organizations of neuronal elements in the olfactory bulb and receptor epithelium

A computer model of the olfactory bulb was constructed. The paper describes: 1) the general architecture of a model neuron network that reflects the neurophysiological experimental and theoretical data on the structural and functional organization of the peripheral part of the olfactory system, the olfactory bulb with inputs from olfactory receptor neurons; 2) the organization of each of three levels of the model: receptors, olfactory glomeruli, and basic neurons; and 3) a scenario of the computer model work. In some aspects, in particular, in the principle of information presentation, the treatment of the role of basic neurons (mitral and tufted cells), and their interrelations in modules, the model favorably differs from the available olfactory bulb models. The model is basic and provides further refinement of the architecture, an increase in the number of modules, and the modeling of the learning process.     

The availability of filament ends modulates actin stochastic dynamics in live plant cells

A network of individual filaments that undergoes incessant remodeling through a process known as stochastic dynamics comprises the cortical actin cytoskeleton in plant epidermal cells. From images at high spatial and temporal resolution, it has been inferred that the regulation of filament barbed ends plays a central role in choreographing actin organization and turnover. How this occurs at a molecular level, whether different populations of ends exist in the array, and how individual filament behavior correlates with the overall architecture of the array are unknown. Here we develop an experimental system to modulate the levels of heterodimeric capping protein (CP) and examine the consequences for actin dynamics, architecture, and cell expansion. Significantly, we find that all phenotypes are the opposite for CP-overexpression (OX) cells compared with a previously characterized cp-knockdown line. Specifically, CP OX lines have fewer filament–filament annealing events, as well as reduced filament lengths and lifetimes. Further, cp-knockdown and OX lines demonstrate the existence of a subpopulation of filament ends sensitive to CP concentration. Finally, CP levels correlate with the biological process of axial cell expansion; for example, epidermal cells from hypocotyls with reduced CP are longer than wild-type cells, whereas CP OX lines have shorter cells. On the basis of these and other genetic studies in this model system, we hypothesize that filament length and lifetime positively correlate with the extent of axial cell expansion in dark-grown hypocotyls.