Systems analysis of RNA trafficking in neural cells

In neural cells, certain RNAs are targeted to dendrites by a specific RNA trafficking pathway, termed the A2 pathway, mediated by the trans-acting trafficking factor, heterogeneous nuclear ribonucleoprotein (hnRNP) A2, which binds to an 11 nucleotide cis-acting trafficking sequence, termed the hnRNP A2 response element (A2RE). RNAs containing A2RE-like sequences are recognized by hnRNP A2 in the nucleus and exported to the cytoplasm where they assemble into trafficking intermediates, termed granules, which also contain components of the translation machinery and molecular motors (cytoplasmic dynein and conventional kinesin). RNA granules move along microtubules to the cell periphery where they become localized and where the encoded protein is translated. Intracellular trafficking of RNA molecules by the A2 pathway is mediated by a complex system consisting of five different subsystems, approximately 35 different molecules and approximately 45 different molecular interactions. Specificity in the A2 pathway is provided by specific interactions of hnRNP A2 with different molecular partners in different subsystems. Polarity of RNA trafficking is controlled by transitions of trafficking intermediates between different subsystems. Comprehensive understanding of the A2 RNA trafficking pathway will require quantitative analysis of concentrations and diffusion constants for each of the different molecules, on rates and off rates for each of the different interactions, relevant conditional operators controlling specific interactions, and interactions of different subsystems. Once the necessary quantitative data are available, mathematical models for the different RNA trafficking subsystems can be developed using computational platforms such as the 'Virtual Cell'. Here we describe how each of the subsystems in the A2 system functions and how the different subsystems interact to regulate RNA trafficking.     

Detecting Protein Complexes in Living Cells from Laser Scanning Confocal Image Sequences by the Cross Correlation Raster Image Spectroscopy Method

We describe a general method for detecting molecular complexes based on the analysis of single molecule fluorescence fluctuations from laser scanning confocal images. The method detects and quantifies complexes of two different fluorescent proteins noninvasively in living cells. Because in a raster scanned image successive pixels are measured at different times, the spatial correlation of the image contains information about dynamic processes occurring over a large time range, from the microseconds to seconds. The correlation of intensity fluctuations measured simultaneously in two channels detects protein complexes that carry two molecules of different colors. This information is obtained from the entire image. A map of the spatial distribution of protein complexes in the cell and their diffusion and/or binding properties can be constructed. Using this cross correlation raster image spectroscopy method, specific locations in the cell can be visualized where dynamics of binding and unbinding of fluorescent protein complexes occur. This fluctuation imaging method can be applied to commercial laser scanning microscopes thereby making it accessible to a large community of scientists.     

Constructing structural networks of signaling pathways on the proteome scale

Proteins function through their interactions, and the availability of protein interaction networks could help in understanding cellular processes. However, the known structural data are limited and the classical network node-and-edge representation, where proteins are nodes and interactions are edges, shows only which proteins interact; not how they interact. Structural networks provide this information. Protein-protein interface structures can also indicate which binding partners can interact simultaneously and which are competitive, and can help forecasting potentially harmful drug side effects. Here, we use a powerful protein-protein interactions prediction tool which is able to carry out accurate predictions on the proteome scale to construct the structural network of the extracellular signal-regulated kinases (ERK) in the mitogen-activated protein kinase (MAPK) signaling pathway. This knowledge-based method, PRISM, is motif-based, and is combined with flexible refinement and energy scoring. PRISM predicts protein interactions based on structural and evolutionary similarity to known protein interfaces.     

Pair bond characteristics and maintenance in free‐flying jackdaws Corvus monedula: effects of social context and season

Most birds rely on cooperation between pair partners for breeding. In long‐term monogamous species, pair bonds are considered the basic units of social organization, albeit these birds often form foraging, roosting or breeding groups in which they repeatedly interact with numerous conspecifics. Focusing on jackdaws Corvus monedula, we here investigated 1) the interplay between pair bond and group dynamics in several social contexts and 2) how pair partners differ in individual effort of pair bond maintenance. Based on long‐term data on free‐flying birds, we quantified social interactions between group members within three positive contexts (spatial proximity, feeding and sociopositive interactions) for different periods of the year (non‐breeding, pre‐breeding, parental care). On the group level, we found that the number of interaction partners was highest in the spatial proximity context while in the feeding and sociopositive contexts the number of interaction partners was low and moderately low, respectively. Interactions were reciprocated within almost all contexts and periods. Investigating subgrouping within the flock, results showed that interactions were preferentially directed towards the respective pair partner compared to unmated adults. When determining pair partner effort, both sexes similarly invested most into mutual proximity during late winter, thereby refreshing their bond before the onset of breeding. Paired males fed their mates over the entire year at similar rates while paired females hardly fed their mates at all but engaged in sociopositive behaviors instead. We conclude that jackdaws actively seek out positive social ties to flock members (close proximity, sociopositive behavior), at certain times of the year. Thus, the group functions as a dynamic social unit, nested within are highly cooperative pair bonds. Both sexes invested into the bond with different social behaviors and different levels of effort, yet these are likely male and female proximate mechanisms aimed at maintaining and perpetuating the pair bond.     

Measuring the flow of molecules in cells

No methods proposed thus far have the capability to measure molecular flow in live cells at the single molecule level. Here, we review the potentiality of a newly established method based on the spatial correlation of fluorescence fluctuations at a pair of points in the sample (pair correlation method). The pair correlation function (pCF) offers a unique tool to probe the directionality of intracellular traffic, by measuring the accessibility of the cellular landscape and its role in determining the diffusive routes adopted by molecules. The sensitivity of the pCF method toward detection of barriers means that different structural elements of the cell can be tested in terms of penetrability and mechanisms of regulation imparted on molecular flow. This has been recently demonstrated in a series of studies looking at molecular transport inside live cells. Here, we will review the theory behind detection of barriers to molecular flow, the rules to interpret pCF data, and relevant applications to intracellular transport.     

Imaging Barriers to Diffusion by Pair Correlation Functions

Molecular diffusion and transport are fundamental processes in physical, chemical, biochemical, and biological systems. However, current approaches to measure molecular transport in cells and tissues based on perturbation methods such as fluorescence recovery after photobleaching are invasive, fluctuation correlation methods are local, and single-particle tracking requires the observation of isolated particles for relatively long periods of time. We propose to detect molecular transport by measuring the time cross-correlation of fluctuations at a pair of locations in the sample. When the points are farther apart than two times the size of the point spread function, the maximum of the correlation is proportional to the average time a molecule takes to move from a specific location to another. We demonstrate the method by simulations, using beads in solution, and by measuring the diffusion of molecules in cellular membranes. The spatial pair cross-correlation method detects barriers to diffusion and heterogeneity of diffusion because the time of the correlation maximum is delayed in the presence of diffusion barriers. This noninvasive, sensitive technique follows the same molecule over a large area, thereby producing a map of molecular flow. It does not require isolated molecules, and thus many molecules can be labeled at the same time and within the point spread function.     

PATHWAYS TO SOCIAL EVOLUTION: RECIPROCITY,RELATEDNESS, AND SYNERGY

Many organisms live in populations structured by space and by class, exhibit plastic responses to their social partners, and are subject to nonadditive ecological and fitness effects. Social evolution theory has long recognized that all of these factors can lead to different selection pressures but has only recently attempted to synthesize how these factors interact. Using models for both discrete and continuous phenotypes, we show that analyzing these factors in a consistent framework reveals that they interact with one another in ways previously overlooked. Specifically, behavioral responses (reciprocity), genetic relatedness, and synergy interact in nontrivial ways that cannot be easily captured by simple summary indices of assortment. We demonstrate the importance of these interactions by showing how they have been neglected in previous synthetic models of social behavior both within and between species. These interactions also affect the level of behavioral responses that can evolve in the long run; proximate biological mechanisms are evolutionarily stable when they generate enough responsiveness relative to the level of responsiveness that exactly balances the ecological costs and benefits. Given the richness of social behavior across taxa, these interactions should be a boon for empirical research as they are likely crucial for describing the complex relationship linking ecology, demography, and social behavior.     

On the dynamics of T-cell activation in lymph nodes

The immune system is a complex network comprising many different organs and cell types, all of which have to work together in a highly accurate manner to exert their function. How is it, then, that the key players of adaptive immunity, T cells, B cells and dendritic cells (DC) move through this network? How is compartmentalization maintained and how do they interact? Over the past decade much attention has been paid to how and where T-cell/DC interactions take place, but only recently--with the advent of new techniques--has research been directed to investigate 'live' T-cell/DC interactions ex vivo and in situ. Whereas the overall sequence of events leading to T-cell activation is largely undisputed, many of the cellular and molecular details of early T-cell priming remain undefined or controversial. This review will focus on recent findings and discuss their implications for T-cell activation.     

Accessing molecular dynamics in cells by fluorescence correlation spectroscopy

Fluorescence correlation spectroscopy (FCS) analyzes spontaneous fluctuations in the fluorescence emission of small molecular ensembles, thus providing information about a multitude of parameters, such as concentrations, molecular mobility and dynamics of fluorescently labeled molecules. Performed within diffraction-limited confocal volume elements, FCS provides an attractive alternative to photobleaching recovery methods for determining intracellular mobility parameters of very low quantities of fluorophores. Due to its high sensitivity sufficient for single molecule detection, the method is subject to certain artifact hazards that must be carefully controlled, such as photobleaching and intramolecular dynamics, which introduce fluorescence flickering. Furthermore, if molecular mobility is to be probed, nonspecific interactions of the labeling dye with cellular structures can introduce systematic errors. In cytosolic measurements, lipophilic dyes, such as certain rhodamines that bind to intracellular membranes, should be avoided. To study free diffusion, genetically encoded fluorescent labels such as green fluorescent protein (GFP) or DsRed are preferable since they are less likely to nonspecifically interact with cellular substructures.     

Physiological importance of RNA and protein mobility in the cell nucleus

Trafficking of proteins and RNAs is essential for cellular function and homeostasis. While it has long been appreciated that proteins and RNAs move within cells, only recently has it become possible to visualize trafficking events in vivo. Analysis of protein and RNA motion within the cell nucleus have been particularly intriguing as they have revealed an unanticipated degree of dynamics within the organelle. These methods have revealed that the intranuclear trafficking occurs largely by energy-independent mechanisms and is driven by diffusion. RNA molecules and non-DNA binding proteins undergo constrained diffusion, largely limited by the spatial constraint imposed by chromatin, and chromatin binding proteins move by a stop-and-go mechanism where their free diffusion is interrupted by random association with the chromatin fiber. The ability and mode of motion of proteins and RNAs has implications for how they find nuclear targets on chromatin and in nuclear subcompartments and how macromolecular complexes are assembled in vivo. Most importantly, the dynamic nature of proteins and RNAs is emerging as a means to control physiological cellular responses and pathways.     

Photocrosslinkers illuminate interactions in living cells

Transient and low-affinity interactions among macromolecules underlie many physiological events. Often, these interactions are difficult to study because they are not maintained when the participating molecules are removed from their cellular context. To circumvent this challenge, crosslinking reagents can be used to introduce covalent bonds between interacting macromolecules. Photoactivatable crosslinkers are particularly attractive because they allow crosslinking to proceed in time- and location-specific ways. Once the interacting partners have been crosslinked, they can be isolated and then analyzed by mass spectrometry or other analytical techniques to determine the identity of the interacting molecules and to pinpoint the interacting regions. This review highlights recent methodological developments that make it possible to introduce photocrosslinking groups into polypeptides or glycans as they are synthesized in cells. We also describe how these methods offer a non-invasive way to study macromolecular interactions in a native context.     

Global dynamics of microbial communities emerge from local interaction rules

Most microbes live in spatially structured communities (e.g., biofilms) in which they interact with their neighbors through the local exchange of diffusible molecules. To understand the functioning of these communities, it is essential to uncover how these local interactions shape community-level properties, such as the community composition, spatial arrangement, and growth rate. Here, we present a mathematical framework to derive community-level properties from the molecular mechanisms underlying the cell-cell interactions for systems consisting of two cell types. Our framework consists of two parts: a biophysical model to derive the local interaction rules (i.e. interaction range and strength) from the molecular parameters underlying the cell-cell interactions and a graph based model to derive the equilibrium properties of the community (i.e. composition, spatial arrangement, and growth rate) from these local interaction rules. Our framework shows that key molecular parameters underlying the cell-cell interactions (e.g., the uptake and leakage rates of molecules) determine community-level properties. We apply our model to mutualistic cross-feeding communities and show that spatial structure can be detrimental for these communities. Moreover, our model can qualitatively recapitulate the properties of an experimental microbial community. Our framework can be extended to a variety of systems of two interacting cell types, within and beyond the microbial world, and contributes to our understanding of how community-level properties emerge from microscopic interactions between cells.     

Beyond species: why ecological interaction networks vary through space and time

Community ecology is tasked with the considerable challenge of predicting the structure, and properties, of emerging ecosystems. It requires the ability to understand how and why species interact, as this will allow the development of mechanism‐based predictive models, and as such to better characterize how ecological mechanisms act locally on the existence of inter‐specific interactions. Here we argue that the current conceptualization of species interaction networks is ill‐suited for this task. Instead, we propose that future research must start to account for the intrinsic variability of species interactions, then scale up from here onto complex networks. This can be accomplished simply by recognizing that there exists intra‐specific variability, in traits or properties related to the establishment of species interactions. By shifting the scale towards population‐based processes, we show that this new approach will improve our predictive ability and mechanistic understanding of how species interact over large spatial or temporal scales. Synthesis Although species interactions are the backbone of ecological communities, we have little insights on how (and why) they vary through space and time. In this article, we build on existing empirical literature to show that the same species may happen to interact in different ways when their local abundances vary, their trait distribution changes, or when the environment affects either of these factors. We discuss how these findings can be integrated in existing frameworks for the analysis and simulation of species interactions.     

The anatomy of predator-prey dynamics in a changing climate

Humans are increasingly influencing global climate and regional predator assemblages, yet a mechanistic understanding of how climate and predation interact to affect fluctuations in prey populations is currently lacking. Here we develop a modelling framework to explore the effects of different predation strategies on the response of age-structured prey populations to a changing climate. We show that predation acts in opposition to temporal correlation in climatic conditions to suppress prey population fluctuations. Ambush predators such as lions are shown to be more effective at suppressing fluctuations in their prey than cursorial predators such as wolves, which chase down prey over long distances, because they are more effective predators on prime-aged adults. We model climate as a Markov process and explore the consequences of future changes in climatic autocorrelation for population dynamics. We show that the presence of healthy predator populations will be particularly important in dampening prey population fluctuations if temporal correlation in climatic conditions increases in the future.     

Alternative modes of binding of proteins with tandem SH2 domains

The issue of specificity in tyrosine kinase intracellular signaling mediated by src homology 2 (SH2) domains has great importance in the understanding how individual signals maintain their mutual exclusivity and affect downstream responses. Several proteins contain tandem SH2 domains that, on interacting with their ligand, provide a higher level of specificity than can be afforded by the interaction of a single SH2 domain. In this study, we focus on the comparison of two proteins ZAP70 and the p85 subunit of PI 3-kinase, which although distinctly different in function and general structure, possess tandem SH2 domains separated by a linker region and which bind to phosphorylated receptor molecules localized to the cell membrane. Binding studies using isothermal titration calorimetry show that these two proteins interact with peptides mimicking their physiological ligands in very different ways. In the case of the SH2 domains from ZAP70, they interact with a stoichiometry of unity, while p85 is able to make two distinct interactions, one with a stoichiometry of 1:1 and the other with two p85 molecules interacting with one receptor. The observation of two different modes of binding of p85 might be important in providing different cellular responses based on fluctuating intracellular concentration regimes of this protein. Thermodynamic data on both proteins suggest that a conformational change occurs on binding. On investigation of this structural change using a truncated form of p85 (including just the two SH2 domains and the inter-SH2 region), both NMR and circular dichroism spectroscopic studies failed to show significant changes in secondary structure. This suggests that any conformational change associated with binding is small and potentially limited to loop regions of the protein.     

Design and implementation of bimolecular fluorescence complementation (BiFC) assays for the visualization of protein interactions in living cells

Bimolecular fluorescence complementation (BiFC) analysis enables direct visualization of protein interactions in living cells. The BiFC assay is based on the discoveries that two non-fluorescent fragments of a fluorescent protein can form a fluorescent complex and that the association of the fragments can be facilitated when they are fused to two proteins that interact with each other. BiFC must be confirmed by parallel analysis of proteins in which the interaction interface has been mutated. It is not necessary for the interaction partners to juxtapose the fragments within a specific distance of each other because they can associate when they are tethered to a complex with flexible linkers. It is also not necessary for the interaction partners to form a complex with a long half-life or a high occupancy since the fragments can associate in a transient complex and un-associated fusion proteins do not interfere with detection of the complex. Many interactions can be visualized when the fusion proteins are expressed at levels comparable to their endogenous counterparts. The BiFC assay has been used for the visualization of interactions between many types of proteins in different subcellular locations and in different cell types and organisms. It is technically straightforward and can be performed using a regular fluorescence microscope and standard molecular biology and cell culture reagents.