What Makes Neurons Contract to Generate Tension?

BPJ_111_7.c1.inddWhen preparing for the cover image for the October 4 issue of Biophysical Journal, we started with an image that resembled an art painting, probably something between Monet and Pollock (not claiming that it’s up to their standards). It was pretty, at least to us, but we thought that it didn’t tell a story. So we thought to ourselves, “What is the message that we want to tell if we have the chance?”

This is how the current version of our cover image came about. On the left, it has a bunch of curved green and red lines, while on the right there is the same set of lines but straightened. These are actually real experimental images achieved by genetically encoding the neuronal membrane to fluoresce in green—thanks to the technology enabled by the late Roger Tsien, while staining the cytoskeleton, in this case microtubules, in red. The implication is that buckled (curved) neurons would always contract and become straight again in less than 5 minutes with the contraction vs. time profile following an exponential decay. We used genetic and pharmaceutical tools to study this phenomenon and found that the acto-myosin machinery was the active driver, while microtubules contributed in a resistive/dissipative role.

The neurons contracted because the machineries were trying to build up a mechanical tension, which was shown to be critical for vesicle clustering, a process central to signal propagation across neurons. Yet, we do not know how tension leads to clustering. It’s like we know that we can drive from New York to Los Angeles, but we do not know the path. Unfortunately, there isn’t an app for that in our case. Knowing the players (tension generators) involved is the first step to answer this question.

There are quite a few implications, mostly to our understanding of mechanics in neuroscience. A better understanding always leads to new ideas and approaches to solve problems, which, in the context of nervous system health, are usually costly and sometimes a matter of life and death.

– Alireza Tofangchi, Anthony Fan, Taher Saif

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Domain Organization in the 54kDa Chloroplast Signal Recognition Particle

BPJ_111_6.c1.inddPlanes, trains, ships, and automobiles — all machines that transport goods and materials from where they are found or made to where they are needed and used. Much the way these modern transport machines are essential to complex trade around the world, the biological world relies on transport machines to move materials and goods at the cellular level. Nanoscale transport machinery has evolved the ability to pick up and carry biological cargo, such as newly synthesized proteins, from places in the cell where proteins are made to cellular sites where the proteins must function.  The image on the cover of this issue of the Biophysical Journal depicts a cellular transport machine in chloroplasts, a chloroplast signal recognition particle (cpSRP).  Its job is to bind newly made components of the light harvesting complexes and direct them to the thylakoid membrane where they are assembled with chlorophyll to efficiently capture light energy for photosynthesis.

Understanding how these nanoscale machines operate may make it possible to design bioinspired machines that can be used to build or repair artificial solar energy conversion devices.  But ”seeing” a nanoscale machine operate presents a tremendous challenge.  We have used a wide array of techniques including bioinformatics, molecular dynamics, Small Angle X-ray Scattering (SAXS), and single-molecule Fluorescence Resonance Energy Transfer (smFRET)  to produce ”movies” of how one of the components of this molecular machine – the protein cpSRP54, a 54 kDa subunit of cpSRP – moves during its operation. Bioinformatics and molecular dynamics use structural data from similar proteins and physical theories to predict the multiple structures that the protein can adopt and how they interconvert between each other. These structural predictions are then tested using SAXS and smFRET experiments. The idea of smFRET — also depicted on the cover —employs the use of two fluorescent dyes placed at distinct sites on cpSRP54, shown in red and green. By exciting only the green dye of a single molecule that is within the confocal volume of a microscope (which is a tightly focused beam of laser light in an hourglass shape, as seen in the cover image), it is possible to transfer some of this energy to the red dye molecule on that same molecule if the two dyes are in close proximity. In fact, we can quantify exactly how much energy is transferred by measuring the brightness of the green versus red colors emitted. If there is more green light emitted, the dyes are far apart and if there is more red light emitted, the dyes are close together. This allows us to accurately measure the distance between the dye attachment sites on the single protein molecule, which is then compared to the structural predictions that we obtained from the other techniques. These data were combined and used to produce the model of cpSRP54 shown in the center of the confocal volume of the cover image.  Furthermore, since smFRET is measured at the single-molecule level, it is possible to directly show that each protein can adopt a range of different structures, which all depend on what else the protein is interacting with during the transport process. The findings show that cpSRP54 goes through multiple structural states that can interconvert between each other – a finding that is supported by the SAXS data. Importantly, the model is predictive of structural states required to load cpSRP with LHC cargo and deliver it to the chloroplast thylakoid membrane.  A small site-specific mutation predicted from the model to adversely affect the transport activity of cpSRP54 was verified in functional assays, providing a high degree of confidence in our structural models.

—Rory Henderson, Feng Gao, Srinivas Jayanthi, Alicia Kight, Priyanka Sharma, Robyn Goforth, Colin Heyes, Ralph Henry, Thallapuranam Suresh Kumar

A Screw-like Mechanism of Bacterial Motion

BPJ_111_5.c1.inddBacterial gliding is defined as steady movement of bacteria that have neither flagella nor pili, over a surface. It is an active process that requires a constant influx of energy. Using a mobile adhesin, SprB, and a powerful rotary motor that is fuelled by a proton motive force, gliding bacteria can move over surfaces with speeds reaching about 2 µm/s.

Adhesion to a surface and gliding motility are important during the development of some early biofilms. Gliding bacteria form biofilms over diverse surfaces. The human oral cavity (gingival region), scales of fishes, and plant roots are examples of environmental niches where some gliding bacteria colonize. The exact mechanism of gliding is not clear. To help understand gliding, we tracked both the motion of SprB and of a gliding bacterium in three-dimensional (3D) space.

Our cover image for the September 6 issue of Biophysical Journal shows the 3D track of SprB moving along the surface of a cell. A gold nanoparticle was coated with anti-SprB antibody and was attached to SprB. The nanoparticle was imaged using an evanescent field. An arrow and a dot represent the beginning and end of the track, respectively. As is evident from the track, SprB moves along an irregular right-handed spiral. The color of the track represents the position of SprB along the long axis of the cell. The track was plotted using MATLAB and was converted to an image file. Further, we showed that the spiral motion of SprB resulted in the screw-like motion of a gliding bacterium (i.e., cells rolled along their long axis as they moved forward). This information was used to propose a mechanism for gliding. While we need to learn more about the molecular details that govern gliding, we now know by 3D tracking that an adhesive external thread, which is localized as a right-handed spiral on the surface of a gliding cell, enables the movement of the cell in a screw-like fashion.

– Abhishek Shrivastava, Thibault Roland, Howard C. Berg

Epithelial Folding: How Planar Cell Polarity Regulates 3D Organogenesis

BPJ_111_3.c1.inddIt is a nice season to enjoy the river by canoeing or kayaking. But do you know that mammalian eggs also drift over a deep channel? This channel, or epithelial folds, is in a tubular organ named the oviduct, or Fallopian tube in humans, connecting the ovary and the uterus.

Viewing the cover image, you too can experience going through the oviduct from the point of view of an egg. The epithelium of the oviduct in the image was obtained by a mathematical simulation. The epithelial folds are straight and align longitudinally along the ovarian-uterine axis in mice and other species of animals. Previously, we reported that a Planar Cell Polarity (PCP) factor Celsr1 regulates fold patterning in mice. But the mechanisms connecting PCP with the well-patterned alignment of the epithelial folds are still unknown.

Here, we analyzed the mechanical regulation of the epithelial fold patterning by mathematical modeling where the epithelium was defined as an elastic sheet. We found that PCP could mechanically regulate the three-dimensional morphogenesis via the polarized cell array. Furthermore, our model scheme is also useful for analyzing mechanical effects on epithelial morphology generally. Our simulation could recapitulate the morphology of various types of epithelial folds, some of which can be found in other organs in vivo.

A sophisticated three-dimensional morphology is important for the organ’s function, but we are still far from a comprehensive understanding of the mechanism to build it.  The oviduct is not only where we come from, but is also a good place to start our scientific journey.

-Dongbo Shi, Hiroshi Koyama, Toshihiko Fujimori

Microtubules form dynamic network with help from motors

BPJ_111_2.c1.inddThe cytoskeletal network is of vital importance in proper cellular functions. Microtubules, one of the major cytoskeletal components, interact with various associated proteins and generate hierarchical network structures spanning tens of micrometers to millimeters. The network dynamically varies during a cell cycle according to physiological roles in the cell.

To gain the integrative perspectives of network formation and its dynamics, we have extensively surveyed the pattern formation of microtubule-motor mixtures in vitro and found the bundling and sliding of microtubules are the key to pattern formation.

This cover image, acquired with a confocal microscope, shows the network spontaneously formed in the mixture of microtubules (magenta) and a member of the kinesin-5 family, Eg5 (cyan). Radial microtubule structures (asters) are formed through the clustering of plus-ends of microtubules by Eg5, and these asters form a global network spanning up to several millimeters. The sliding activity of Eg5 finally induces the contraction of the network.

The experimental system exhibited various distinct spatiotemporal patterns according to mixing ratios of motors to microtubules. A coarse-grained numerical model we developed can explain these experimentally observed dynamics and demonstrate how bundling and sliding activities of motors determined these spatiotemporal dynamics. Now, together with the model, our system will provide a beneficial platform for the investigation of dynamics and mechanical properties of cytoskeletal architecture.

– Takayuki Torisawa, Daisuke Taniguchi, Shuji Ishihara and Kazuhiro Oiwa

An Interview with Ayyalusamy Ramamoorthy

BJ: How did you compose the image on the July 12 issue of Biophysical Journal?

AR: We used Visual Molecular Dynamics software (http://www.ks.uiuc.edu/Research/vmd/) and the program Persistence of Vision Raytracer (http://www.povray.org/) to create the image.BPJ_111_1.c1.indd

BJ: How does this image reflect your scientific research?

AR: This image represents our molecular vision of the role of cholesterol in amylin-mediated membrane damage.

BJ: Can you please provide a real-world example of how your research might be applied?

AR: Is hypercholesterolemia related to an increased risk to develop type 2 diabetes? The main goal of our research is to provide a molecular framework for the relationship between diet and lifestyle and proteinopathies.

BJ: How does your research apply to those who are not working in your specific field?

AR: Clinicians will find this study to be useful to gain insights into the molecular mechanisms underlying type 2 diabetes development. In particular, this may help them to better correlate symptoms with lifestyle.

BJ: Do you have a website where our readers can view your recent research?

AR: https://www.researchgate.net/profile/Carmelo_La_Rosa and http://rams.biop.lsa.umich.edu/, https://www.researchgate.net/profile/Danilo_Milardi.

– Michele Sciacca, Fabio Lolicato, Giacomo Di Mauro, Danilo Milardi, Luisa D’Urso, Cristina Satriano, Carmelo La Rosa, Ayyalusamy Ramamoorthy

Interview with Dr. Raz Jelinek

BPJ_110_9.c1.inddBJ: How did you compose the cover image for Biophysical Journal 110/9?

RJ: The image is designed to highlight the thrust of our paper; the C-dot-phospholipid conjugates are seamlessly embedded within the lipid bilayer “carpet” representing the cell membrane.  The fluorescence of the protruding C-dots (green spheres) , constituting the core property of the C-dots and the primary analytical tool, is represented by the “hallows” around the spheres.

BJ: How does this image reflect your scientific research?

RJ: We are deeply interested in cellular membranes, and have been active over the years trying to decipher fundamental structural and functional properties of membranes, primarily as related to their lipid bilayer scaffolding.   The image reflects the research presented in the paper—development of a new analytical platform for studying membranes and membrane processes.

BJ: Can you please provide a few real-world examples of your research?

RJ: An important research program in my lab focuses on the relationship between membranes and amyloid diseases, particularly Alzheimer’s disease.  While amyloid diseases are incurable, there is a growing evidence for the intimate roles of cellular membranes in the onset and pathogenicity of the diseases.  We aim to elucidate these putative relationships and assess the relevance of membrane interactions toward development of therapeutic treatments.

BJ: How does your research apply to those who are not working in your specific field?

RJ: We believe that introduction of new tools for imaging membranes and analysis of membrane dynamics could aid research efforts of scientists in other disciplines, including biologists, biochemists, and bioengineers.

BJ: Do you have a website where our readers can view your recent research?

RJ: http://www.bgu.ac.il/~razj/

– Sukhendu Nandi, Ravit Malishev, Susanta Bhunia, Sofiya Kolusheva, Jurgen Jopp, Raz Jelinek