Interactomics aims to characterize all interactions formed between molecules that comprise our body. Although it emerged from quantitative biophysics, it has devolved into a predominantly qualitative field of science over the past decades. Due to technical limitations at its onset, almost all tools in interactomics are qualitative, which persists in defining the discipline. Here, we argue that interactomics needs to return to a quantitative direction because the technical achievements of the last decade have overcome the original limitations that forced its (...) current path. In contrast to qualitative interactomics which is constrained to charting lists of observed interactions, quantitative interactomics can also uncover answers to key questions such as the strength of interactions or how many of certain complexes can form in cells, thus providing researchers with more immediate proxies for understanding and predicting biological processes. (shrink)

During the last few months, several pioneer genome‐wide transcriptomic, proteomic and metabolomic studies have revolutionised the understanding of bacterial biological processes, leading to a picture that resembles eukaryotic complexity. Technological advances such as next‐generation high‐throughput sequencing and high‐density oligonucleotide microarrays have allowed the determination, in several bacteria, of the entire boundaries of all expressed transcripts. Consequently, novel RNA‐mediated regulatory mechanisms have been discovered including multifunctional RNAs. Moreover, resolution of bacterial proteome organisation (interactome) and global protein localisation (localizome) have unveiled (...) an unanticipated complexity that highlights the significance of protein multifunctionality and localisation in the cell. Also, analysis of a complete bacterial metabolic network has again revealed a high fraction of multifunctional enzymes and an unexpectedly high level of metabolic responses and adaptation. Altogether, these novel approaches have permitted the deciphering of the entire physiological landscape of one of the smallest bacteria, Mycoplasma pneumoniae. Here, we summarise and discuss recent findings aimed at defining the blueprint of any prokaryote. (shrink)

The key assumption behind evolutionary epistemology is that animals are active learners or ‘knowers’. In the present study, I updated the concept of natural learning, developed by Henry Plotkin and John Odling-Smee, by expanding it from the animal-only territory to the biosphere-as-a-whole territory. In the new interpretation of natural learning the concept of biological information, guided by Peter Corning’s concept of “control information”, becomes the ‘glue’ holding the organism–environment interactions together. The control information guides biological systems, from bacteria to ecosystems, (...) in the process of natural learning executed by the universal algorithm. This algorithm, summarized by the acronym IGPT (information-gain-process-translate) incorporates natural cognitive methods including sensing/perception, memory, communication, and decision-making. Finally, the biosphere becomes the distributed network of communicative interactions between biological systems termed the interactome. The concept of interactome is based on Gregory Bateson’s natural epistemology known as the “ecology of mind”. Mimicking Bateson’s approach, the interactome may also be designated “physiology of mind”—the principle behind regulating the biosphere homeostasis. (shrink)

A categorical, higher dimensional algebra and generalized topos framework for Łukasiewicz–Moisil Algebraic–Logic models of non-linear dynamics in complex functional genomes and cell interactomes is proposed. Łukasiewicz–Moisil Algebraic–Logic models of neural, genetic and neoplastic cell networks, as well as signaling pathways in cells are formulated in terms of non-linear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable ‘next-state functions’ is extended to a Łukasiewicz–Moisil (...) Topos with an n-valued Łukasiewicz–Moisil Algebraic Logic subobject classifier description that represents non-random and non-linear network activities as well as their transformations in developmental processes and carcinogenesis. The unification of the theories of organismic sets, molecular sets and Robert Rosen’s (M,R)-systems is also considered here in terms of natural transformations of organismal structures which generate higher dimensional algebras based on consistent axioms, thus avoiding well known logical paradoxes occurring with sets. Quantum bionetworks, such as quantum neural nets and quantum genetic networks, are also discussed and their underlying, non-commutative quantum logics are considered in the context of an emerging Quantum Relational Biology. (shrink)

The complexity of intracellular molecular pathways can be simplified by the use of Network Biology that breaks down the intricacy of biological processes into components and interactions among them. In the paper we show that any complex interactome, that is, a biological network representing protein-protein, protein-DNA and DNA-RNA interactions, can be decomposed into a conjunction of logical theorems expressed in terms of Zsyntax, a formal language which allows representing biological pathways. This result, illustrated with the case study of melanoma (...) network, opens the possibility for a computable model of the cell expressed in a logical language and shows how a formal way of intending philosophy can be useful to cope with the complexity of the biological world. (shrink)

A categorical, higher dimensional algebra and generalized topos framework for Łukasiewicz–Moisil Algebraic–Logic models of non-linear dynamics in complex functional genomes and cell interactomes is proposed. Łukasiewicz–Moisil Algebraic–Logic models of neural, genetic and neoplastic cell networks, as well as signaling pathways in cells are formulated in terms of non-linear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable ‘next-state functions’ is extended to a Łukasiewicz–Moisil (...) Topos with an n-valued Łukasiewicz–Moisil Algebraic Logic subobject classifier description that represents non-random and non-linear network activities as well as their transformations in developmental processes and carcinogenesis. The unification of the theories of organismic sets, molecular sets and Robert Rosen’s (M,R)-systems is also considered here in terms of natural transformations of organismal structures which generate higher dimensional algebras based on consistent axioms, thus avoiding well known logical paradoxes occurring with sets. Quantum bionetworks, such as quantum neural nets and quantum genetic networks, are also discussed and their underlying, non-commutative quantum logics are considered in the context of an emerging Quantum Relational Biology. (shrink)

During tumor evolution, cancer cells use the tumor‐stroma crosstalk to reorganize the microenvironment for maximum robustness of the tumor. The success of immune checkpoint therapy foretells a new cancer therapy paradigm: an effective cancer treatment should not aim to influence the individual components of super complex intracellular interactomes (molecular targeting), but try to disrupt the intercellular interactions between cancer and stromal cells, thus breaking the tumor as a whole. Arguments are provided in favor of a hypothesis that such interactions include (...) formation of synapse‐like structures (interfaces) where the interacting cells are located at a distance of ∼10–15 nm. Within these interfaces, molecules initiating and strengthening the interaction are organized, and allow optimum cross‐signaling; a very confined intercellular space facilitates the concentration of secreted cytokines, enhancing the paracrine cross‐communication. These features of tumors form a druggable cancer hallmark the tumor‐stroma symbiotic crosstalk—which represents a new target for efficient cancer drug discovery. (shrink)

G protein‐coupled receptors (GPCRs) constitute the largest family of transmembrane proteins and play a crucial role in regulating diverse cellular functions. They transmit their signaling via binding to intracellular signal transducers and effectors, such as G proteins, GPCR kinases, and β‐arrestins. To influence specific GPCR signaling behaviors, β‐arrestins recruit effectors to form larger signaling complexes. Intriguingly, they facilitate divergent functions for the binding to different receptors. Recent studies relying on advanced structural approaches, novel biosensors and interactome analyses bring us (...) closer to understanding how this specificity is achieved. In this article, we share our hypothesis of how active GPCRs induce specific conformational rearrangements within β‐arrestins to reveal distinct binding interfaces, enabling the recruitment of a subset of effectors to foster specialized signaling complexes. Furthermore, we discuss methods of how to comprehensively assess β‐arrestin conformational states and present the current state of research regarding the functionality of these multifaceted scaffolding proteins. (shrink)

Constructive Neutral Evolution is an evolutionary mechanism that can explain much molecular inter-dependence and organismal complexity without assuming positive selection favoring such dependency or complexity, either directly or as a byproduct of adaptation. It differs from but complements other non-selective explanations for complexity, such as genetic drift and the Zero Force Evolutionary Law, by being ratchet-like in character. With CNE, purifying selection maintains dependencies or complexities that were neutrally evolved. Preliminary treatments use it to explain specific genetic and molecular structures (...) or processes, such as retained gene duplications, the spliceosome, and RNA editing. Here we aim to expand the scope of such explanation beyond the molecular level, integrating CNE with Multi-Level Selection theory, and arguing that several popular higher-level selection scenarios are in fact instances of CNE. Suitably contextualized, CNE occurs at any level in the biological hierarchy at which natural selection as normally construed occurs. As examples, we focus on modularity in protein–protein interaction networks or “interactomes,” the origin of eukaryotic cells and the evolution of co-dependence in microbial communities—a variant of the “Black Queen Hypothesis” which we call the “Gray Queen Hypothesis”. (shrink)

New concepts may prove necessary to profit from the avalanche of sequence data on the genome, transcriptome, proteome and interactome and to relate this information to cell physiology. Here, we focus on the concept of large activity-based structures, or hyperstructures, in which a variety of types of molecules are brought together to perform a function. We review the evidence for the existence of hyperstructures responsible for the initiation of DNA replication, the sequestration of newly replicated origins of replication, cell (...) division and for metabolism. The processes responsible for hyperstructure formation include changes in enzyme affinities due to metabolite-induction, lipid-protein affinities, elevated local concentrations of proteins and their binding sites on DNA and RNA, and transertion. Experimental techniques exist that can be used to study hyperstructures and we review some of the ones less familiar to biologists. Finally, we speculate on how a variety of in silico approaches involving cellular automata and multi-agent systems could be combined to develop new concepts in the form of an Integrated cell (I-cell) which would undergo selection for growth and survival in a world of artificial microbiology. (shrink)

With decades of research seeking to generalize sterile alpha motif (SAM) biology, many outstanding questions remain regarding this multi‐tool protein module. Recent data from structural and molecular/cell biology has begun to reveal new SAM modes of action in cell signaling cascades and biomolecular condensation. SAM‐dependent mechanisms underlie blood‐related (hematologic) diseases, including myelodysplastic syndromes and leukemias, prompting our focus on hematopoiesis for this review. With the increasing coverage of SAM‐dependent interactomes, a hypothesis emerges that SAM interaction partners and binding affinities work (...) to fine tune cell signaling cascades in developmental and disease contexts, including hematopoiesis and hematologic disease. This review discusses what is known and remains unknown about the standard mechanisms and neoplastic properties of SAM domains and what the future might hold for developing SAM‐targeted therapies. (shrink)

A novel conceptual framework is introduced for the Complexity Levels Theory in a Categorical Ontology of Space and Time. This conceptual and formal construction is intended for ontological studies of Emergent Biosystems, Super-complex Dynamics, Evolution and Human Consciousness. A claim is defended concerning the universal representation of an item’s essence in categorical terms. As an essential example, relational structures of living organisms are well represented by applying the important categorical concept of natural transformations to biomolecular reactions and relational structures that (...) emerge from the latter in living systems. Thus, several relational theories of living systems can be represented by natural transformations of organismic, relational structures. The ascent of man and other living organisms through adaptation, is viewed in novel categorical terms, such as variable biogroupoid representations of evolving species. Such precise but flexible evolutionary concepts will allow the further development of the unifying theme of local-to-global approaches to highly complex systems in order to represent novel patterns of relations that emerge in super- and ultra-complex systems in terms of compositions of local procedures. Solutions to such local-to-global problems in highly complex systems with ‘broken symmetry’ might be possible to be reached with the help of higher homotopy theorems in algebraic topology such as the generalized van Kampen theorems (HHvKT). Categories of many-valued, Łukasiewicz-Moisil (LM) logic algebras provide useful concepts for representing the intrinsic dynamic ‘asymmetry’ of genetic networks in organismic development and evolution, as well as to derive novel results for (non-commutative) Quantum Logics. Furthermore, as recently pointed out by Baianu and Poli (Theory and applications of ontology, vol 1. Springer, Berlin, in press), LM-logic algebras may also provide the appropriate framework for future developments of the ontological theory of levels with its complex/entangled/intertwined ramifications in psychology, sociology and ecology. As shown in the preceding two papers in this issue, a paradigm shift towards non-commutative, or non-Abelian, theories of highly complex dynamics—which is presently unfolding in physics, mathematics, life and cognitive sciences—may be implemented through realizations of higher dimensional algebras in neurosciences and psychology, as well as in human genomics, bioinformatics and interactomics. (shrink)

RNAs have emerged as a major target for diagnostics and therapeutics approaches. Regulatory nonprotein‐coding RNAs (ncRNAs) in particular display remarkable versatility. They can fold into complex structures and interact with proteins, DNA, and other RNAs, thus modulating activity, localization, or interactome of multi‐protein complexes. Thus, ncRNAs confer regulatory plasticity and represent a new layer of regulatory control. Interestingly, long noncoding RNAs (lncRNAs) tend to acquire complex secondary and tertiary structures and their function—in many cases—is dependent on structural conservation rather (...) than primary sequence conservation.Whereas for many proteins, structure and its associated function are closely connected, for lncRNAs, the structural domains that determine functionality and its interactome are still not well understood. Numerous approaches for analyzing the structural configuration of lncRNAs have been developed recently. Here, will provide an overview of major experimental approaches used in the field, and discuss the potential benefit of using combinatorial strategies to analyze lncRNA modes of action based on structural information. (shrink)

The noncoding RNA 7SK is a critical regulator of transcription by adjusting the activity of the kinase complex P‐TEFb. Release of P‐TEFb from 7SK stimulates transcription at many genes by promoting productive elongation. Conversely, P‐TEFb sequestration by 7SK inhibits transcription. Recent studies have shown that 7SK functions are particularly important for neuron development and maintenance and it can thus be hypothesized that 7SK is at the center of many signaling pathways contributing to neuron function. 7SK activates neuronal gene expression programs (...) that are key for terminal differentiation of neurons. Proteomics studies revealed a complex protein interactome of 7SK that includes several RNA‐binding proteins. Some of these novel 7SK subcomplexes exert non‐canonical cytosolic functions in neurons by regulating axonal mRNA transport and fine‐tuning spliceosome production in response to transcription alterations. Thus, a picture emerges according to which 7SK acts as a multi‐functional RNA scaffold that is integral for neuron homeostasis. (shrink)

Sex steroids, through their receptors, have potent effects on the signal pathways involved in osteogenic or myogenic differentiation. However, a considerable segment of those signal pathways has a prominent role in epithelial neoplastic transformation. The capability to intervene locally has focused on specific ligands for the receptors. Nevertheless, many signals are mapped to interactions of steroid receptor motifs with heterologous regulatory proteins. Some of those proteins interact with the glucocorticoid receptor and other factors essential to cell fate. Interactions of steroid (...) receptor domain motifs with heterologous proteins affect specific target pathways; consequently, manipulation of specified protein modules complexed with steroid receptors may be a next major step for enhancing molecular targeted therapeutics. In the future, intervention at specific sections of receptor primary sequence may prove therapeutically more efficient in targeting pathways of choice than ligand selectivity can be. (shrink)

A novel conceptual framework is introduced for the Complexity Levels Theory in a Categorical Ontology of Space and Time. This conceptual and formal construction is intended for ontological studies of Emergent Biosystems, Super-complex Dynamics, Evolution and Human Consciousness. A claim is defended concerning the universal representation of an item’s essence in categorical terms. As an essential example, relational structures of living organisms are well represented by applying the important categorical concept of natural transformations to biomolecular reactions and relational structures that (...) emerge from the latter in living systems. Thus, several relational theories of living systems can be represented by natural transformations of organismic, relational structures. The ascent of man and other living organisms through adaptation, is viewed in novel categorical terms, such as variable biogroupoid representations of evolving species. Such precise but flexible evolutionary concepts will allow the further development of the unifying theme of local-to-global approaches to highly complex systems in order to represent novel patterns of relations that emerge in super- and ultra-complex systems in terms of compositions of local procedures. Solutions to such local-to-global problems in highly complex systems with ‘broken symmetry’ might be possible to be reached with the help of higher homotopy theorems in algebraic topology such as the generalized van Kampen theorems (HHvKT). Categories of many-valued, Łukasiewicz-Moisil (LM) logic algebras provide useful concepts for representing the intrinsic dynamic ‘asymmetry’ of genetic networks in organismic development and evolution, as well as to derive novel results for (non-commutative) Quantum Logics. Furthermore, as recently pointed out by Baianu and Poli (Theory and applications of ontology, vol 1. Springer, Berlin, in press), LM-logic algebras may also provide the appropriate framework for future developments of the ontological theory of levels with its complex/entangled/intertwined ramifications in psychology, sociology and ecology. As shown in the preceding two papers in this issue, a paradigm shift towards non-commutative, or non-Abelian, theories of highly complex dynamics—which is presently unfolding in physics, mathematics, life and cognitive sciences—may be implemented through realizations of higher dimensional algebras in neurosciences and psychology, as well as in human genomics, bioinformatics and interactomics. (shrink)

RNA binding proteins (RBPs) are key factors for the regulation of gene expression by binding to cis elements, i.e. short sequence motifs in RNAs. Recent studies demonstrate that cooperative binding of multiple RBPs is important for the sequence‐specific recognition of RNA and thereby enables the regulation of diverse biological activities by a limited set of RBPs. Cross‐linking immuno‐precipitation (CLIP) and other recently developed high‐throughput methods provide comprehensive, genome‐wide maps of protein‐RNA interactions in the cell. Structural biology gives detailed insights into (...) molecular mechanisms and principles of RNA recognition by RBPs, but has so far focused on single RNA binding proteins and often on single RNA binding domains. The combination of high‐throughput methods and detailed structural biology studies is expected to greatly advance our understanding of the code for protein‐RNA recognition in gene regulation, as we review in this article. (shrink)