Announcement

Collapse
No announcement yet.

Communication shapes sensory response in multicellular networks

Collapse
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • CT Communication shapes sensory response in multicellular networks

    http://www.pnas.org/content/113/37/10334.abstract

    Significance

    Cells routinely sense and respond to their environment, and they also communicate with each other. Exactly how communication impacts sensing remains poorly understood. We study a population of fibroblast cells that responds to a chemical stimulus (ATP) and communicates by molecule exchange. Combining experiments and mathematical modeling, we find that cells exhibit calcium oscillations in response to not only the ATP stimulus but also, increased cell–cell communication. Our results show that, when cells are together, their sensory responses reflect not just the stimulus level but also, the degree of communication within the population.
    Abstract
    Collective sensing by interacting cells is observed in a variety of biological systems, and yet, a quantitative understanding of how sensory information is collectively encoded is lacking. Here, we investigate the ATP-induced calcium dynamics of monolayers of fibroblast cells that communicate via gap junctions. Combining experiments and stochastic modeling, we find that increasing the ATP stimulus increases the propensity for calcium oscillations, despite large cell-to-cell variability. The model further predicts that the oscillation propensity increases with not only the stimulus, but also the cell density due to increased communication. Experiments confirm this prediction, showing that cell density modulates the collective sensory response. We further implicate cell–cell communication by coculturing the fibroblasts with cancer cells, which we show act as “defects” in the communication network, thereby reducing the oscillation propensity. These results suggest that multicellular networks sit at a point in parameter space where cell–cell communication has a significant effect on the sensory response, allowing cells to simultaneously respond to a sensory input and the presence of neighbors.
    cell–cell communication calcium oscillations gap junctions cellular sensing collective behavior



    Acting without Central Agent - Considerations for a Self-Model at the Cellular Level
    http://journal.frontiersin.org/artic...017.00191/full

    Acting without Central Agent - Considerations for a Self-Model at the Cellular Level

    Abstract
    Single-celled organisms existed already one billion years before multi-cellularity emerged – and they still do. Although these cells do not have a nervous system they are able to live in a challenging environment responding to stimuli by complex behaviour. In this paper we give examples showing that single-celled organisms can solve complex tasks and have a short-term memory buffer. Some authors consider these capabilities as a form of basal intelligence. It seems likely that in multicellular organisms some of the qualities of single cells are still present and that solving complex tasks is not restricted to a central nervous system. Here we propose a self-model at the cellular level, similar to the phenomenal self-model which allows planned action of the organism as a whole. According to our model, the sensory input produces a cellular self-model that makes predictions about the future. This concept has implications on how we understand disease and therapy on the cellular level.
    Life on Earth - the Nervous System
    Fossil discoveries suggest that life began on earth about 3.8 billion years ago. At first there were single-celled organisms with no nuclei (prokaryotes), later approximately 2.7 billion years ago, protozoa developed which are cells with a nucleus (eukaryotes). Only since about 800 Mio years have multicellular organisms (eumetazoa) emerged and with that the ability to evolve specialized cells, such as nerve cells. The function of nerve cells is to receive information from both the internal and external environment, interpret and translate it into body reactions e.g. muscle contractions which change the body´s position. In radially symmetric multicellular organisms such as jellyfish, there is a loose network of nerves which condenses in higher organisms with bilateral symmetry to a central nervous system. In bilateria the main axis is mostly in the direction of movement, where, at the front, uptake of nutrients takes place. This defines the starting point for cephalisation with the emergence of a cerebral ganglion. Later in evolution the number and interconnections of ganglia increased forming a brain, the place where we assume cognition and intelligence is located. The everyday neuro-fixation ignores indications that already single cells show complex behaviour patterns with a kind of basal intelligence and the ability to memorize. How do single cells accomplish this? In the following we hypothesize that cells may have a kind of self-model, a representation of themselves.
    Phenomenal Self-Model
    For planned action, the presence of a brain is a prerequisite. After a philosophical theory, for which there is increasingly reliable experimental data, the brain produces a phenomenal self-model (PSM), which creates a representation of one's body in which its upper layers are functionally anchored (Lenggenhager et al., 2007; Metzinger, 2003, 2008). The PSM creates the feeling of “mineness” and of being a self. Arbitrary and controlled acts, i.e. movements for which we possess a veto control and which are initiated by a conscious act, will be simulating within the PSM before implementation: Hence we know which motor co-ordination is necessary to grasp an object by directing the introspective attention to the process of action planning. Within a certain time frame the action can be cancelled or modified. The PSM - or virtual self – enables the holder to interact with the environment in a particularly flexible and context-sensitive manner. This is especially necessary when complex environmental conditions arise that require new strategies: a dog that lacks a limb is still able to walk, but has to develop a new co-ordination pattern for the remaining limbs. This is done in the repetitive interaction between self-model and environment. This procedure has proven its versatility in the development of robots with artificial intelligence. A walking robot equipped with a self-model can compensate the shutdown of a limb by developing a new style of locomotion (Bongard et al., 2006).
    Self-Model at the Cellular Level?
    The presence of a nervous system is not a conditio sine qua non to receive environmental stimuli and to translate them into appropriate responses. Single-celled organisms such as amoebae or paramecia move actively and purposefully in their environment without even having a nervous system. In the following we will provide a few examples showing the impressive behaviour of organisms which we call “simple”. In an experiment, a labyrinth was evenly colonized with the unicellular slime mould Physarum polycephalum. Then, oat flakes, the preferred food of Physarum, were placed at the entry and exit. Within a few hours Physarum retracted all branches only leaving a linear connection of the shortest distance between entry and exit (Nakagaki et al., 2000). In a similar experiment, Physarum was grown on a circular agar plate. Three oat flakes were placed at the corners of a triangle; the fungus found a link corresponding to the mathematically shortest route (Steiner's minimum tree) (Nakagaki et al., 2004). In addition, Physarium can solve the complex traveling-salesman-problem by linking eight points with the shortest distances (Zhu et al., 2013). Moreover, there is evidence for learning and memory in single-celled organisms. After irritating Physarum with dry air it slows its running speed. After three irritations the cell anticipates further stimuli and slows down the running speed without drying stimulus. When irritations were permanently turned off, the memory disappeared (Saigusa et al., 2008). Also in Paramecium caudatum, a single-celled aquatic organism, there is evidence for learning: the cells were trained with electric shocks to discriminate the difference between light and dark (Armus et al., 2006). Tetrahymena, another ciliate, was held in minute water droplets, after release to a larger area it recapitulates the circular swimming trajectories from the confinement for a while (Kunita et al., 2016).
    These examples suggest a form of primitive intelligence and the presence of a self-model already at the cellular level. Since every multicellular individual organism starts as a single cell, from which during ontogenesis various cell species emerge, the question arises whether cells of our body use something like a self-model. The "large" self-model which was discussed above generates a kind of body map, which sometimes is in conflict with body sensations. An impressive example are the so-called "rubber hand" experiments where a virtual limb, a rubber hand looking like connected to the body, becomes part of the body map (Armel and Ramachandran, 2003). These experiments were proven with different experimental settings and recently extended to a whole body representation. By using a virtual reality device representing one´s own body from the rear standing 2 m in front, the visual-somatosensory input becomes disrupted and the spatial unity between the self and the body becomes separated (Lenggenhager et al., 2007). A clinical example for conflict between body map and real world is the phantom limb pain which is frequently perceived after limb amputation (Ramachandran and Hirstein, 1998).
    Is there a match for a self-model already at the cellular level? How does a cell recognize its extent and size? In the human body there are cells of different sizes, from the denucleated erythrocyte, the smallest cell, with 7.5μm, to the oocyte with 250µm and the nerve cell, with cell processes up to 1m. Do these cells have a kind of self-model in order to calibrate their size? What happens in an experiment where one repeatedly cuts pieces from the cytoplasm?, does the cell compensate for the missing volume? In apocrine secretion (e.g., mammary gland, apocrine sweat gland) liquid-filled vesicles are extruded from the cell, which thereby loses volume. Thus, the cell becomes initially smaller. In merocrine secretion (e.g., pancreas), the cell loses volume by exocytosis, which causes an increase of cell membrane. Since in both types of secretion there is no permanent change in volume observed, cells seem to measure their size and also actively adjust to a set value - with a self-model?
    Last edited by Jo Bowyer; 01-04-2017, 08:43 PM.
    Jo Bowyer
    Chartered Physiotherapist Registered Osteopath.
    "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

  • #2
    Unexpected Discovery Gives Rise to New Model For Brain Network Studies

    http://neurosciencenews.com/brain-ne...oscience-8986/
    Jo Bowyer
    Chartered Physiotherapist Registered Osteopath.
    "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

    Comment

    Working...
    X