Unraveling the genome biophysics puzzle

BPJ_112_3.c1.inddWhile digitizing the human genome is one of the recent major scientific achievements, unraveling genome structure and, more importantly, structure–function relationships has been a major preoccupation for many scientific teams worldwide. Indeed, the understanding of structure from the DNA level to nucleosomes, chromatin fibers, genes, and chromosomes holds the key to interpreting many of the associated genome functions from DNA repair and duplication to gene transcription.

To celebrate the anniversary of Biophysical Journal‘s newest section Nucleic Acids and Genome Biophysics, we present this Special Issue devoted to Genome Biophysics.

The cover image for this issue conveys the excitement in the field, as many techniques are being developed and applied by both experimentalists and modelers to decipher aspects of the genome puzzle. Specifically, the cover image highlights the genome puzzle from multiple scales and viewpoints. The illustration, created by G. Bascom and T. Schlick, features images from the contributions by A. Onufriev and colleagues on partially assembled nucleosomes (left top puzzle piece), B. Zhang and P. Wolynes on chromosomal domains (right bottom puzzle piece), and G. Bascom and T. Schlick on looping networks in fibers and genes (central image and background fibers).

We hope BJ readers will enjoy the excellent contributions in this issue that reflect an exciting range of topics, as well as the breadth and depth of this fascinating subject.

– Tamar Schlick

Three Coexisting Phases of Lipid Membranes

BPJ_112_2.c1.inddWhile there has been a large amount of research into the phase behavior of lipid membranes in the past decade driven by the biological relevance of ordered micro-domains (often termed “lipid-rafts”), images of three coexisting phases are very rare. Researchers have difficulties preparing samples with a high proportion of ordered phase, and finding reliable methods to sufficiently discriminate the phases as fluorescent dyes often prefer one phase and are excluded from the remaining two. The cover image of the January 24th issue of the Biophysical Journal shows a collection of atomic force micrographs (AFM) exhibiting three-phase coexistence in a model cell membrane under water.

Three phases are found in lipid compositions. They lie in a narrow triangle below the more commonly studied two-phase micro-domain region, which contains the liquid disordered (Ld – yellow/red) and liquid ordered (Lo – magenta) phases, together with a gel phase (Lb – blue/green). Each phase has a different degree of chain packing order leading to varying depths. A surprising and counterintuitive finding of this study is that the gel phase, while definitely solid, is more disordered and slightly lower in height than Lo. It is also structurally very weak. This is explained by the small but significant quantity of cholesterol that disrupts the ordered solid phase, while being insufficient to form the Lo phase. Relative proportions of the three phases are governed by their position in the three-phase triangle. Domain morphology is controlled by the mechanism of phase separation. We observed examples of both spinodal and nucleated domains of each phase, and in some cases both mechanisms in the same image An example of this can be seen in the cover image where a nucleated gel phase (green) is surrounded by a percolated Lo/Ld  structure (yellow/magenta). Another interesting finding was the signature of a radially varying composition across the nucleated gel domains, reflecting the kinetically trapped solid state in the process of separating from a compositionally varying melt. This effect has been commonly observed in metallurgy, but not in lipids.

Each image was produced within the standard AFM analysis software, Bruker Nanoscope v1.5. Manual coloring in Photoshop has not been used, rather a standard color look-up table (No 9) is mapped directly to the topography data. The contrast was adjusted so that the lowest phase is on the yellow/red transition, and the highest phase is magenta, resulting in a blue/green middle phase. A problem with this approach is the tiny 0.6 nm difference in height between the highest and lowest phases, which calls for accurate levelling to remove image bowing artefacts common in AFM, provide defined peaks in the depth histogram, and  a uniform color across each phase. This task was made even more painstaking by the presence of three phases interfering with the thresholding and masking approach normally used. The final composite was created simply in Powerpoint.

Our work is part of an EPSRC (Engineering and Physical Sciences Research Council) Program entitled CAPiTALS, which is based around the fundamental understanding of the physics governing lipid membrane curvature, asymmetry, and patterning, and the technological uses arising from this new knowledge.

–  Simon Connell, Anders Aufderhorst-Roberts, Udayan Chandra.

What drives immune cells to engulf pathogens?

BPJ_111_12.c1.inddMacrophages and neutrophils (phagocytes) are the front-line defenders in your body’s immune system. They seek out, ingest, and destroy pathogens and other debris through a process called phagocytosis.  Typically, phagocytosis is initiated when receptors on the immune cell surface bind to ligands which have coated a pathogen particle. Once the cell’s receptors have found their target ligands, they initiate a chemical cascade within the cell which recruits the biochemical machinery necessary to drive the cell to envelop its target, forming a vacuole in which the pathogen can be degraded.

On a small scale, nearly every cell type in your body internalizes nutrients and various signals through a similar engulfment process called endocytosis What makes immune cells and phagocytosis unique is the relative size of the internalized particle. During endocytosis, cells internalize small objects, typically no larger than 100 nanometers, a fraction of the cell’s size (usually 10-30 micrometers). However, during phagocytosis, immune cells need to be able to internalize very large particles such as bacteria, which could be several microns long, and debris like dead cells, which could be larger than the immune cell itself.

Phagocytes accomplish this seemingly heroic feat by leveraging the biomechanical machinery typically involved with cellular migration, specifically the actin cytoskeleton and myosin molecular motors. Once phagocytosis has been initiated, actin monomers within the cell begin to polymerize near the location of the bound particle. As the polymerized network forms, it pushes the cell’s membrane around the particle, forming what is called a phagocytic cup. Interestingly, as a particle is internalized, the leading edge of the phagocytic cup constricts, pinching down on the particle.

Earlier studies have shown that actin tends to accumulate in a dense ring at the point of constriction. Unfortunately, due to limitations of the microscopy techniques available at the time, the precise structural organization of actin filaments within this ring could not be resolved. Consequently, exactly how the actin ring facilitates constriction remained elusive.

Using super-resolution fluorescent imaging (Structured Illumination Microscopy) we sought to illuminate how actin is reorganized during phagocytosis, with the goal of providing insight as to how phagocytes constrict around their targets.  One of the challenges in using microscopy to study phagocytosis is that particle internalization is three-dimensional, yet nearly all microscopy techniques are inherently two-dimensional. To side-step this issue, we turned to a planar technique called Frustrated Phagocytosis. Instead of presenting immune cells with pathogen particles, we deposited cells onto glass coverslips functionalized with antibodies. When the immune cells contact the surface, they perceive it as a giant pathogen and begin to flatten and spread as if trying to phagocytose the entire plane, yielding an unfolded view of what’s happening at the cell-target interface.

The cover image in the December 20th issue of the Biophysical Journal shows several macrophage cells at various stages of the frustrated phagocytic process. In the image, each cell’s actin cytoskeleton is shown in green (using Atto488-phalloidin) and the nuclei are shown in blue (using DAPI). During the early stages of phagocytosis (top left), actin polymerizes at the leading edge of the cell, forming a dense zone. This is similar to the structure formed at the leading edge of migrating cells. As actin polymerizes at the edge, it pushes the membrane outward causing the cell to spread. As the cell nears its maximum contact area, the actin zone begins to dissociate (top center) and actin-filaments throughout the body of the cell bundle to form fibers (middle right). As the cell enters the later stages of phagocytosis those bundles reorient, surrounding the perimeter of the cell (bottom center and middle left). With actin bundles surrounding the cell, myosin motor proteins exert tension between adjacent bundles. This tension causes the network to contract, forcing the cell to pinch down on the substrate. For frustrated phagocytosis, this constriction drives the cell to retract from the surface, leaving fragments of actin and tethered membrane in its trail (spinney protrusions around bottom center and middle left cells).

The mechanism that triggers the bundles to form and reorganize around the cell perimeter remains a mystery; although, there is mounting evidence that mechanical factors such as the cell’s membrane tension are involved in signaling transitions to late-stage phagocytic behavior.  These images, along with other studies of phagocyte mechanics, illustrate the robust and dynamical processes that unfold when immune cells carry out their essential task of clearing debris and eliminating pathogens.

– Wenbin Wei, Patrick Chang, Jan-Simon Toro, Ruth Fogg Beach, Dwight Chambers, Karen Porter, Doyeon Koo, Jennifer Curtis, Daniel Kovari

Probing Water and DMSO near Lipid Membrane Surfaces

BPJ_111_11.c1.inddDimethyl sulfoxide (DMSO) is a powerful anti-freezing agent and has been used in biology as a cryoprotectant of cells. Thanks to a series of experiments and computer simulations  bulk properties of DMSO solution are reasonably well understood, yet the effects of DMSO on water molecules near lipid membrane surfaces, which are more relevant for elucidating the underlying physical chemistry of DMSO as a cryoprotectant, still remain elusive.

The consensus from a number of different experiments is that DMSO dehydrates phospholipid bilayer surfaces, which our study confirms. However, the DMSO-enhanced water diffusivity at solvent-bilayer interfaces, was not confirmed in our simulations. In order to resolve this discrepancy, we explicitly modeled Tempo-PC by appending Tempos to a few choline groups and conducted simulations and analyses.

Our cover image for the December 6th Issue of the Biophysical Journal depicts a snapshot from the molecular dynamics simulation of POPC phospholipid bilayer in 7.5 mol% DMSO solution. The lipid tails are rendered in grey, and the regions corresponding to phosphatidylcholine head groups are depicted in pale blue. Four Tempo-PCs, in the upper and lower leaflets are highlighted with the tail domain in yellow and the Tempo appended to the choline group in blue. Of particular note is that in contrast to the original intent of Overhauser Dynamic Nuclear Polarization (ODNP) measurements using Tempo-PC lipids to probe the surface water dynamics, the Tempo moieties are predominantly equilibrated at 8 − 10 Å below the solvent-bilayer interface, probing the water dynamics in the interior of bilayer. The water and DMSO molecules around the Tempo moieties are depicted in stick and surface representations, respectively. The inset magnifies the snapshot of water and DMSO molecules around Tempo. The image was produced using the molecular visualization system, PyMOL.

DMSO deposited beneath the PC head group, where Tempo moieties are equilibrated, increases the area per lipid slightly, and hence water diffusion probed by Tempo is detected to increase with increasing DMSO. Our study suggests that the experimentally detected signal of water using Tempo, stems from the interior of lipid bilayers, not from the interface. The only viable tool for the direct probe of water dynamics on biological surfaces at present is ODNP measurements using a Tempo spin label. Given its significance, the equilibrated location of Tempo moiety in lipid bilayers revealed here calls for adequate interpretation of data and careful re-evaluation of the technique.

—Yuno Lee, Philip A. Pincus, Changbong Hyeon

Toward Modeling More Realistic Cell Geometries

BPJ_COVER-1Nowadays, computer-driven numerical simulation is becoming increasingly popular as an integral part of all areas of research and engineering. Simulations can often be performed faster, cheaper, and in a potentially safer manner than benchtop experiments. Describing the real-world with systems of equations also helps us to verify the existence of different phenomena, predict future behavior, and discover new idiosyncrasies in complex systems.

In our work, we study how biological cells respond to externally-applied electric fields using numerical simulations based on the finite element method (FEM) for the specific purpose of cancer treatment. FEMs are based on the concept of approximating the geometry of a real-world problem using smaller two-dimensional shapes (often triangles or quadrilaterals) or three-dimensional solids (often tetrahedra). A complex global problem may be reduced to a number of local problems on each of these smaller geometries—called elements—and each of these elements is related to those surrounding it, forming a mesh of elements representing the global geometry and a large system of coupled equations. For the specific application reported here, the geometries of biological cells are described in two dimensions using triangles that are refined around high-aspect ratio features, such as at the cell and nuclear membranes. The cells in our simulation need to be described mathematically as accurately as possible, to render appropriate spatial, temporal, and physical characteristics. Typically, many simplifications are made to a cell’s morphology in order to more easily represent it computationally, which include simple shapes in the form of circles/spheres and ellipses/ellipsoids and a limited amount of physical phenomena. However, biological cells are complex structures with ever-changing geometry and physics that span many length and time scales. To truly capture and explore physical phenomena in such a system requires accounting for more of the complexities of a biological cell, such as its irregular geometry.

Our cover image for the November 15 issue of Biophysical Journal was created during a project where we showed the importance of using realistic cell shapes when studying electric field exposure. We used fluorescence microscopy images to extract realistic cell shapes and convert them into a two-dimensional numerical model. The image shows a triangular FEM mesh, fit to the cell boundaries, where each system of equations is generated on each triangular element that describes their relation to other neighboring elements. Each element is also assigned material parameters, such as electrical conductivity and permittivity. The cell and nuclear membrane boundaries are discretized using numerous boundary nodes to resolve the irregular geometry and minimize the numerical error introduced into the calculation, while retaining sufficient solution efficiency. Conversely, fewer nodes are needed in the middle of the nuclear regions for example, where material boundaries are not present. The above mesh consists of almost one million triangles in a rectangular computational domain that measures around 200 microns across. The image is a zoom of a large model system with realistic cell geometries, containing 91 tightly packed cells and nuclei. The nuclei were highlighted in blue during the assignment of parameters to the nuclear regions in the software used. A glowing effect was added during post-processing for a bit of a dramatic flare.

These types of simulations are not just for research purposes though. Historically, we have utilized robust FEM models to predict how electric currents will propagate in a tissue. Such models are also utilized during treatment planning for tumor ablation procedures in which a series of electrical pulses are delivered to the tumor via two or more electrodes to maximally destroy malignant cells while preserving critical stromal components, such as vasculature. More realistic models of biological cells allows treatments to be delivered to the appropriate malignant region and further limit the damage to the surrounding healthy tissue.

More simulations like this are sure to follow that include detailed geometries, extend these and similar models to three dimensions, and account for additional relevant biophysical phenomena. Though simplifications must be made to any simulation, the trend of increasing computer power and performance enables many of these inhibitions to be overcome by simulations that achieve a greater predictive capacity and come ever closer to simulating precise experimental and clinical conditions.

—Tomo Murovec and Daniel C. Sweeney

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

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