Chaperones as integrators of cellular networks: changes of cellular integrity in stress and diseases

The complex integrity of the cells and its sudden, but often predictable changes can be described and understood by the topology and dynamism of cellular networks. All these networks undergo both local and global rearrangements during stress and development of diseases. Here, we illustrate this by showing the stress-induced structural rearrangement of the yeast protein-protein interaction network (interactome). In an unstressed state, the yeast interactome is highly compact, and the centrally organized modules have a large overlap. During stress, several original modules became more separated, and a number of novel modules also appear. A few basic functions such as theproteasome preserve their central position; however, several functions with high energy demand, such the cell-cycle regulation loose their original centrality during stress. A number of key stress-dependent protein complexes, such as the disaggregation-specific chaperone, Hsp104 gain centrality in the stressed yeast interactome. Molecular chaperones, heat shock, or stress proteins became established as key elements in our molecular understanding of the cellular stress response. Chaperones form complex interaction networks (the chaperome) with each other and their partners. Here, we show that the human chaperome recovers the segregation of protein synthesis-coupled and stress-related chaperones observed in yeast recently. Examination of yeast and human interactomes shows that chaperones 1) are intermodular integrators of protein-protein interaction networks, which 2) often bridge hubs and 3) are favorite candidates for extensive phosphorylation. Moreover, chaperones 4) become more central in the organization of the isolated modules of the stressed yeast protein-protein interaction network, which highlights their importance in the decoupling and recoupling of network modules during and after stress. Chaperone-mediated evolvability of cellular networks may play a key role in cellular adaptation during stress and various polygenic and chronic diseases, such as cancer, diabetes or neurodegeneration.     

Analyzing protein–protein interactions in the post-interactomic era. Are we ready for the endgame?

Mapping protein–protein interactions in genome-wide scales revealed thousands of novel binding partners in each of the explored model organisms. Organizing these hits in comprehensive ways is becoming increasingly important for systems biology approaches to understand complex cellular processes and diseases. However, proteome wide interaction techniques and their resulting global networks are not revealing the topologies of networks that are truly operating in the cell. In this short review I will discuss which prerequisites have to be fulfilled and which experimental methods might be practicable to translate primary protein interaction data into network presentations that help in understanding cellular processes.     

Shugoshins: from protectors of cohesion to versatile adaptors at the centromere

Sister chromatids are held together by a protein complex named cohesin. Shugoshin proteins protect cohesin from cleavage by separase during meiosis I in eukaryotes and from phosphorylation-mediated removal during mitosis in vertebrates. This protection is crucial for chromosome segregation during mitosis and meiosis. Mechanistically, shugoshins shield cohesin by forming a complex with the phosphatase PP2A, which dephosphorylates cohesin, leading to its retention at centromeres during the onset of meiotic anaphase and vertebrate mitotic prophase I. In addition to this canonical function, shugoshins have evolved novel, species-specific cellular functions, the mechanisms of which remain a subject of intense debate, but are likely to involve spatio-temporally coordinated interactions with the chromosome passenger complex, the spindle checkpoint and the anaphase promoting complex. Here, we compare and contrast these remarkable features of shugoshins in model organisms and humans.     

The intracellular antibody capture technology: towards the high-throughput selection of functional intracellular antibodies for target validation

Several approaches have been developed over the past decade to study the complex interactions that occur in biological system. The ability to carry out a comprehensive genetic analysis of an organism becomes more limited and difficult as the complexity of the organism increases because complex organisms are likely to have not only more genes than simple organisms but also more elaborate networks of interactions among those genes. The development of technologies to systematically disrupt protein networks at the genomic scale would greatly accelerate the comprehensive understanding of the cell as molecular machinery. Intracellular antibodies (intrabodies) can be targeted to different intracellular compartments to specifically interfere with function of selected intracellular gene products in mammalian cells. This technique should prove important for studies of mammalian cells, where genetic approaches are more difficult. In the context of large-scale protein interaction mapping projects, intracellular antibodies (ICAbs) promise to be an important tool to knocking out protein function inside the cell. In this context, however, the need for speed and high throughput requires the development of simple and robust methods to derive antibodies which function within cells, without the need for optimization of each individual ICAb. The successful inhibition of biological processes by intrabodies has been demonstrated in a number of different cells. The performance of antibodies that are intracellularly expressed is, however, somewhat unpredictable, because the reducing environment of the cell cytoplasm in which they are forced to work prevents some antibodies, but not others, to fold properly. For this reason, we have developed an in vivo selection procedure named Intracellular Antibody Capture Technology (IACT) that allows the isolation of functional intrabodies. The IAC technology has been used for the rapid identification of antigen-antibody pairs in intracellular compartments and for the in vivo identification of epitopes recognized by the selected intracellular antibodies. Several optimizations of the IAC technology for protein knock-out have been developed so far. This system offers a powerful and versatile proteomic tool to dissect diverse functional properties of cellular proteins in different cell lines.     

A journey from reductionist to systemic cell biology aboard the schooner Tara

In this essay I describe my personal journey from reductionist to systems cell biology and describe how this in turn led to a 3-year sea voyage to explore complex ocean communities. In describing this journey, I hope to convey some important principles that I gleaned along the way. I realized that cellular functions emerge from multiple molecular interactions and that new approaches borrowed from statistical physics are required to understand the emergence of such complex systems. Then I wondered how such interaction networks developed during evolution. Because life first evolved in the oceans, it became a natural thing to start looking at the small organisms that compose the plankton in the world's oceans, of which 98% are … individual cells-hence the Tara Oceans voyage, which finished on 31 March 2012 in Lorient, France, after a 60,000-mile around-the-world journey that collected more than 30,000 samples from 153 sampling stations.     

Job contenders: roles of the β‐barrel assembly machinery and the translocation and assembly module in autotransporter secretion

Billions of years of evolution have yielded today's complex metabolic networks driven by efficient and highly specialized enzymes. In contrast, the metabolism of the earliest cellular life forms was likely much simpler with only a few enzymes of comparatively low activity. It has been speculated that these early enzymes had low specificities and in turn were able to perform multiple functions. In this issue of Molecular Microbiology, Ferla et al. describe examples of enzymes that catalyze chemically distinct reactions while using the same active site. Most importantly, the authors demonstrated that the comparatively weak activities of these multifunctional enzymes are each physiologically relevant. These findings contrast with simply promiscuous enzyme activities, which have been described numerous times but are not physiologically relevant. Ferla et al. elegantly combined initial bioinformatics searches for enzyme candidates with sound kinetic measurements, evolutionary considerations and even structural discussions. The phenomenon of multifunctionality appears to be a mechanism for bacteria with reduced genomes to compensate for their lack of certain enzymes. In the broader context of evolution, these organisms could be considered living model systems to study features of long‐extinct early cellular life.     

Role of multiheme cytochromes involved in extracellular anaerobic respiration in bacteria

Heme containing proteins are involved in a broad range of cellular functions, from oxygen sensing and transport to catalyzing oxidoreductive reactions. The two major types of cytochrome (b‐type and c‐type) only differ in their mechanism of heme attachment, but this has major implications for their cellular roles in both localization and mechanism. The b‐type cytochromes are commonly cytoplasmic, or are within the cytoplasmic membrane, while c‐type cytochromes are always found outside of the cytoplasm. The mechanism of heme attachment allows for complex c‐type multiheme complexes, having the capacity to hold multiple electrons, to be assembled. These are increasingly being identified as secreted into the extracellular environment. For organisms that respire using extracellular substrates, these large multiheme cytochromes allow for electron transfer networks from the cytoplasmic membrane to the cell exterior for the reduction of extracellular electron acceptors. In this review the structures and functions of these networks and the mechanisms by which electrons are transferred to extracellular substrates is described.     

Time zones: a comparative genetics of circadian clocks

The circadian clock is a widespread cellular mechanism that underlies diverse rhythmic functions in organisms from bacteria and fungi, to plants and animals. Intense genetic analysis during recent years has uncovered many of the components and molecular mechanisms comprising these clocks. Although autoregulatory genetic networks are a consistent feature in the design of all clocks, the weight of evidence favours their independent evolutionary origins in different kingdoms.     

Heat shock proteins: Molecules with assorted functions

Heat shock proteins (Hsps) or molecular chaperones, are highly conserved protein families present in all studied organisms. Following cellular stress, the intracellular concentration of Hsps generally increases several folds. Hsps undergo ATP-driven conformational changes to stabilize unfolded proteins or unfold them for translocation across membranes or mark them for degradation. They are broadly classified in several families according to their molecular weights and functional properties. Extensive studies during the past few decades suggest that Hsps play a vital role in both normal cellular homeostasis and stress response. Hsps have been reported to interact with numerous substrates and are involved in many biological functions such as cellular communication, immune response, protein transport, apoptosis, cell cycle regulation, gametogenesis and aging. The present review attempts to provide a brief overview of various Hsps and summarizes their involvement in diverse biological activities.     

The statistical mechanics of complex signaling networks: nerve growth factor signaling

The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'     

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.     

Structural aspects of microRNA biogenesis

One of the biggest surprises at the beginning of the 'post-genome era' was the discovery of numerous genes encoding microRNAs. They were found in genomes of such diverse organisms as Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, and Homo sapiens which implies their important role in multicellular life evolution. The number of microRNA genes is estimated to be nearly 1% of that of protein-coding genes. Their products, tiny RNAs, are thought to regulate gene expression during development, organogenesis, and very likely during many other processes, by hybridizing to their target mRNAs. The cellular functions of mRNAs that are regulated by microRNAs are only beginning to be revealed, and details of this regulation mechanism are still poorly understood. In this article we discuss the possible mechanisms of microRNA biogenesis with special emphasis on their structural aspects. We have focused on the factors and effects that may be responsible for the existing length differences between different microRNAs, and for the observed length heterogeneity within some individual microRNA species.     

Phenotypic and dynamical transitions in model genetic networks. I. Emergence of patterns and genotype-phenotype relationships

SUMMARY Genotype–phenotype interactions during the evolution of form in multicellular organisms is a complex problem but one that can be aided by computational approaches. We present here a framework within which developmental patterns and their underlying genetic networks can be simulated. Gene networks were chosen to reflect realistic regulatory circuits, including positive and negative feedback control, and the exchange of a subset of gene products between cells, or within a syncytium. Some of these networks generate stable spatial patterns of a subset of their molecular constituents, and can be assigned to categories (e.g., "emergent" or "hierarchic") based on the topology of molecular circuitry. These categories roughly correspond to what has been discussed in the literature as "self-organizing" and "programmed" processes of development. The capability of such networks to form patterns of repeating stripes was studied in network ensembles in which parameters of gene-gene interaction were caused to vary in a manner analogous to genetic mutation. The evolution under mutational change of individual representative networks of each category was also simulated. We have found that patterns with few stripes (≤3) are most likely to originate in the form of a hierarchic network, whereas those with greater numbers of stripes (≥4) originate most readily as emergent networks. However, regardless of how many stripes it contains, once a pattern is established, there appears to be an evolutionary tendency for emergent mechanisms to be replaced by hierarchic mechanisms. These results have potential significance for the understanding of genotype-phenotype relationships in the evolution of metazoan form.     

Scaling of differentiation in networks: nervous systems,organisms, ant colonies,ecosystems, businesses,universities, cities,electronic circuits,and Legos

Nodes in networks are often of different types, and in this sense networks are differentiated. Here we examine the relationship between network differentiation and network size in networks under economic or natural selective pressure, such as electronic circuits (networks of electronic components), Legos (networks of Lego pieces), businesses (networks of employees), universities (networks of faculty), organisms (networks of cells), ant colonies (networks of ants), and nervous systems (networks of neurons). For each of these we find that (i) differentiation increases with network size, and (ii) the relationship is consistent with a power law. These results are explained by a hypothesis that, because nodes are costly to build and maintain in such "selected networks", network size is optimized, and from this the power-law relationship may be derived. The scaling exponent depends on the particular kind of network, and is determined by the degree to which nodes are used in a combinatorial fashion to carry out network-level functions. We find that networks under natural selection (organisms, ant colonies, and nervous systems) have much higher combinatorial abilities than the networks for which human ingenuity is involved (electronic circuits, Legos, businesses, and universities). A distinct but related optimization hypothesis may be used to explain scaling of differentiation in competitive networks (networks where the nodes themselves, rather than the entire network, are under selective pressure) such as ecosystems (networks of organisms).     

Modular approaches to expanding the functions of living matter

The synthesis of increasingly complex unnatural networks embedded in living matter is an emerging theme in synthetic biology. Synthetic networks have allowed the creation of organisms endowed with toggle switches, logic gates, pattern-forming systems, oscillators, cellular sensors, new modes of gene regulation and expanded genetic codes. A common challenge of this work is the addition of specific new functions to complex living organisms. This requires spatial and temporal control of molecular interactions and fluxes to achieve the desired outcomes. Here we review recent successes in this emerging field and discuss strategies for addressing the challenges of increasing network complexity.