Ligand-receptor promiscuity enables cellular addressing

Engineering Sequestration-Based Biomolecular Classifiers with Shared Resources

Constructing molecular classifiers that enable cells to recognize linear and nonlinear input patterns would expand the biocomputational capabilities of engineered cells, thereby unlocking their potential in diagnostics and therapeutic applications. While several biomolecular classifier schemes have been designed, the effects of biological constraints such as resource limitation and competitive binding on the function of those classifiers have been left unexplored. Here, we first demonstrate the design of a sigma factor-based perceptron as a molecular classifier working based on the principles of molecular sequestration between the sigma factor and its antisigma molecule. We then investigate how the output of the biomolecular perceptron, i.e., its response pattern or decision boundary, is affected by the competitive binding of sigma factors to a pool of shared and limited resources of core RNA polymerase. Finally, we reveal the influence of sharing limited resources on multilayer perceptron neural networks and outline design principles that enable the construction of nonlinear classifiers using sigma-based biomolecular neural networks in the presence of competitive resource-sharing effects.

Principles of Computation by Competitive Protein Dimerization Networks

Many biological signaling pathways employ proteins that competitively dimerize in diverse combinations. These dimerization networks can perform biochemical computations, in which the concentrations of monomers (inputs) determine the concentrations of dimers (outputs). Despite their prevalence, little is known about the range of input-output computations that dimerization networks can perform (their "expressivity") and how it depends on network size and connectivity. Using a systematic computational approach, we demonstrate that even small dimerization networks (3-6 monomers) are expressive, performing diverse multi-input computations. Further, dimerization networks are versatile, performing different computations when their protein components are expressed at different levels, such as in different cell types. Remarkably, individual networks with random interaction affinities, when large enough (≥8 proteins), can perform nearly all (~90%) potential one-input network computations merely by tuning their monomer expression levels. Thus, even the simple process of competitive dimerization provides a powerful architecture for multi-input, cell-type-specific signal processing.

Protocol to identify receptors of secreted proteins through CRISPR-Cas9 whole-genome screening technology

The interaction between cell surface receptors and their ligands is crucial for intercellular communication. However, current techniques for identifying direct receptor-ligand interactions remain limited. Here, we present a protocol to identify receptors of secreted proteins using a genome-scale CRISPR-Cas9 knockout genetic screening approach. We describe steps for creating a single-guide RNA (sgRNA) lentivirus library, infecting stable Cas9-MCF7 cells, staining with tagged Cholesin, and sorting non-binding cells via flow cytometry. We then detail procedures for extracting DNA, amplifying sgRNAs, and sequencing. For complete details on the use and execution of this protocol, please refer to Hu et al.1.

Reducing Uncertainty Through Mutual Information in Structural and Systems Biology

Systems biology models are useful models of complex biological systems that may require a large amount of experimental data to fit each model's parameters or to approximate a likelihood function. These models range from a few to thousands of parameters depending on the complexity of the biological system modeled, potentially making the task of fitting parameters to the model difficult - especially when new experimental data cannot be gathered. We demonstrate a method that uses structural biology predictions to augment systems biology models to improve systems biology models' predictions without having to gather more experimental data. Additionally, we show how systems biology models' predictions can help evaluate novel structural biology hypotheses, which may also be expensive or infeasible to validate.

Intercellular Communication in Shoot Meristems

The shoot meristem of land plants maintains the capacity for organ generation throughout its lifespan due to a group of undifferentiated stem cells. Most meristems are shaped like a dome with a precise spatial arrangement of functional domains, and, within and between these domains, cells interact through a network of interconnected signaling pathways. Intercellular communication in meristems is mediated by mobile transcription factors, small RNAs, hormones, and secreted peptides that are perceived by membrane-localized receptors. In recent years, we have gained deeper insight into the underlying molecular processes of the shoot meristem, and we discuss here how plants integrate internal and external inputs to control shoot meristem activities.

The diversification of methods for studying cell-cell interactions and communication

No cell lives in a vacuum, and the molecular interactions between cells define most phenotypes. Transcriptomics provides rich information to infer cell-cell interactions and communication, thus accelerating the discovery of the roles of cells within their communities. Such research relies heavily on algorithms that infer which cells are interacting and the ligands and receptors involved. Specific pressures on different research niches are driving the evolution of next-generation computational tools, enabling new conceptual opportunities and technological advances. More sophisticated algorithms now account for the heterogeneity and spatial organization of cells, multiple ligand types and intracellular signalling events, and enable the use of larger and more complex datasets, including single-cell and spatial transcriptomics. Similarly, new high-throughput experimental methods are increasing the number and resolution of interactions that can be analysed simultaneously. Here, we explore recent progress in cell-cell interaction research and highlight the diversification of the next generation of tools, which have yielded a rich ecosystem of tools for different applications and are enabling invaluable discoveries.

Comparative cofactor screens show the influence of transactivation domains and core promoters on the mechanisms of transcription

Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors used by nine different TFs and core promoters in human cells. Using this dataset, we associate TFs with cofactors, classify cofactors as ubiquitous or specific and discover transcriptional co-dependencies. Through a reductionistic, comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF depends on a unique combination of cofactors, which influences distinct steps in transcription. By contrast, the influence of core promoters appears relatively discrete. Different promoter classes are constrained by either initiation or pause-release, which influences their dynamic range and compatibility with cofactors. Overall, our comparative cofactor screens characterize the interplay between TFs, cofactors and core promoters, identifying general principles by which they influence transcription.

Control of neuronal excitation-inhibition balance by BMP-SMAD1 signalling

Throughout life, neuronal networks in the mammalian neocortex maintain a balance of excitation and inhibition, which is essential for neuronal computation1,2. Deviations from a balanced state have been linked to neurodevelopmental disorders, and severe disruptions result in epilepsy3-5. To maintain balance, neuronal microcircuits composed of excitatory and inhibitory neurons sense alterations in neural activity and adjust neuronal connectivity and function. Here we identify a signalling pathway in the adult mouse neocortex that is activated in response to increased neuronal network activity. Overactivation of excitatory neurons is signalled to the network through an increase in the levels of BMP2, a growth factor that is well known for its role as a morphogen in embryonic development. BMP2 acts on parvalbumin-expressing (PV) interneurons through the transcription factor SMAD1, which controls an array of glutamatergic synapse proteins and components of perineuronal nets. PV-interneuron-specific disruption of BMP2-SMAD1 signalling is accompanied by a loss of glutamatergic innervation in PV cells, underdeveloped perineuronal nets and decreased excitability. Ultimately, this impairment of the functional recruitment of PV interneurons disrupts the cortical excitation-inhibition balance, with mice exhibiting spontaneous epileptic seizures. Our findings suggest that developmental morphogen signalling is repurposed to stabilize cortical networks in the adult mammalian brain.

Liebig's law of the minimum in the TGF-β/SMAD pathway

Cells use signaling pathways to sense and respond to their environments. The transforming growth factor-β (TGF-β) pathway produces context-specific responses. Here, we combined modeling and experimental analysis to study the dependence of the output of the TGF-β pathway on the abundance of signaling molecules in the pathway. We showed that the TGF-β pathway processes the variation of TGF-β receptor abundance using Liebig's law of the minimum, meaning that the output-modifying factor is the signaling protein that is most limited, to determine signaling responses across cell types and in single cells. We found that the abundance of either the type I (TGFBR1) or type II (TGFBR2) TGF-β receptor determined the responses of cancer cell lines, such that the receptor with relatively low abundance dictates the response. Furthermore, nuclear SMAD2 signaling correlated with the abundance of TGF-β receptor in single cells depending on the relative expression levels of TGFBR1 and TGFBR2. A similar control principle could govern the heterogeneity of signaling responses in other signaling pathways.

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Bone morphogenetic protein signaling: the pathway and its regulation

In the mid-1960s, bone morphogenetic proteins (BMPs) were first identified in the extracts of bone to have the remarkable ability to induce heterotopic bone. When the Drosophila gene decapentaplegic (dpp) was first identified to share sequence similarity with mammalian BMP2/BMP4 in the late-1980s, it became clear that secreted BMP ligands can mediate processes other than bone formation. Following this discovery, collaborative efforts between Drosophila geneticists and mammalian biochemists made use of the strengths of their respective model systems to identify BMP signaling components and delineate the pathway. The ability to conduct genetic modifier screens in Drosophila with relative ease was critical in identifying the intracellular signal transducers for BMP signaling and the related transforming growth factor-beta/activin signaling pathway. Such screens also revealed a host of genes that encode other core signaling components and regulators of the pathway. In this review, we provide a historical account of this exciting time of gene discovery and discuss how the field has advanced over the past 30 years. We have learned that while the core BMP pathway is quite simple, composed of 3 components (ligand, receptor, and signal transducer), behind the versatility of this pathway lies multiple layers of regulation that ensures precise tissue-specific signaling output. We provide a sampling of these discoveries and highlight many questions that remain to be answered to fully understand the complexity of BMP signaling.

Computational cell-cell interaction technologies drive mechanistic and biomarker discovery in the tumor microenvironment

Complex networks of cell-cell interactions (CCIs) within the tumor microenvironment (TME) play a crucial role in cancer persistence. These communication axes represent prime targets for therapeutic intervention, but our incomplete understanding of the cellular heterogeneity and interacting partners within the TME remains a stubborn barrier to complete drug responses. This review outlines recent advances in the study of CCIs that leverage single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies that can clarify TME dynamics. We anticipate that these strategies will promote discovery of CCIs critical to the tumor-immune interface and will, by extension, expand the repertoire of druggable tumor biomarkers.

Unmasking Chemokine-Inducing Specificity in Oligosaccharide Biomaterial to Promote Hair Growth

Hair loss affects over 50 million people worldwide with limited therapeutic options. Despite evidence highlighting the vital role of local immune cells in regulating the life cycle of hair follicles (HFs), accurate regulation of immunocytes to directly promote hair growth remains unachieved. Here, inspired by the physiological feedback in the skin immunity to suppress microbe-triggered inflammation, an oligosaccharide biomaterial with "unmasked" specific activity is developed to recruit regulatory T (Treg ) cells around HFs, leading to accelerated hair growth in mice. By processing the glucomannan polysaccharide via controllable enzymatic cleavage, a series of oligosaccharide fractions with more specific chemokine-inducing functions is obtained. Notably, a hexasaccharide-based fraction (OG6) stimulates macrophages to selectively express Treg -chemoattractant C-C Motif Chemokine Ligand 5 (CCL5) through a mannose receptor-mediated endocytosis and NOD1/2-dependent signaling, as evidenced by molecular docking, inhibition assays, and a Foxp3-reporter mouse model. Intradermal delivery of OG6 to the depilated mouse skin promotes Treg mobilization around HFs and stimulates de novo regeneration of robust hairs. This study demonstrates that unmasking precise immunomodulatory functions in oligosaccharides from their parental polysaccharide can potentially solve the long-lasting dilemma with polysaccharide biomaterials that are widely renowned for versatile activities yet high heterogeneity, opening new avenues to designing glycan-based therapeutic tools with improved specificity and safety.

The roles and regulatory mechanisms of TGF-β and BMP signaling in bone and cartilage development, homeostasis and disease

Transforming growth factor-βs (TGF-βs) and bone morphometric proteins (BMPs) belong to the TGF-β superfamily and perform essential functions during osteoblast and chondrocyte lineage commitment and differentiation, skeletal development, and homeostasis. TGF-βs and BMPs transduce signals through SMAD-dependent and -independent pathways; specifically, they recruit different receptor heterotetramers and R-Smad complexes, resulting in unique biological readouts. BMPs promote osteogenesis, osteoclastogenesis, and chondrogenesis at all differentiation stages, while TGF-βs play different roles in a stage-dependent manner. BMPs and TGF-β have opposite functions in articular cartilage homeostasis. Moreover, TGF-β has a specific role in maintaining the osteocyte network. The precise activation of BMP and TGF-β signaling requires regulatory machinery at multiple levels, including latency control in the matrix, extracellular antagonists, ubiquitination and phosphorylation in the cytoplasm, nucleus-cytoplasm transportation, and transcriptional co-regulation in the nuclei. This review weaves the background information with the latest advances in the signaling facilitated by TGF-βs and BMPs, and the advanced understanding of their diverse physiological functions and regulations. This review also summarizes the human diseases and mouse models associated with disordered TGF-β and BMP signaling. A more precise understanding of the BMP and TGF-β signaling could facilitate the development of bona fide clinical applications in treating bone and cartilage disorders.

Modes and motifs in multicellular communication

Signaling pathways feature multiple interacting ligand and receptor variants, which are thought to act in a combinatorial manner to elicit different cellular responses. Transcriptome analyses now suggest that many signaling pathways use their components in combinations that are surprisingly often shared between otherwise dissimilar cell states.

Multiorgan locked-state model of chronic diseases and systems pharmacology opportunities

With increasing human life expectancy, the global medical burden of chronic diseases is growing. Hence, chronic diseases are a pressing health concern and will continue to be in decades to come. Chronic diseases often involve multiple malfunctioning organs in the body. An imminent question is how interorgan crosstalk contributes to the etiology of chronic diseases. We conceived the locked-state model (LoSM), which illustrates how interorgan communication can give rise to body-wide memory-like properties that 'lock' healthy or pathological conditions. Next, we propose cutting-edge systems biology and artificial intelligence strategies to decipher chronic multiorgan locked states. Finally, we discuss the clinical implications of the LoSM and assess the power of systems-based therapies to dismantle pathological multiorgan locked states while improving treatments for chronic diseases.

Small transcriptional differences among cell clones lead to distinct NF-κB dynamics

Transcription factor dynamics is fundamental to determine the activation of accurate transcriptional programs and yet is heterogeneous at a single-cell level, even within homogeneous populations. We asked how such heterogeneity emerges for the nuclear factor κB (NF-κB). We found that clonal populations of immortalized fibroblasts derived from a single mouse embryo display robustly distinct NF-κB dynamics upon tumor necrosis factor ɑ (TNF-ɑ) stimulation including persistent, oscillatory, and weak activation, giving rise to differences in the transcription of its targets. By combining transcriptomics and simulations we show how less than two-fold differences in the expression levels of genes coding for key proteins of the signaling cascade and feedback system are predictive of the differences of the NF-κB dynamic response of the clones to TNF-ɑ and IL-1β. We propose that small transcriptional differences in the regulatory circuit of a transcription factor can lead to distinct signaling dynamics in cells within homogeneous cell populations and among different cell types.

Context-dependent TGFβ family signalling in cell fate regulation

The transforming growth factor-β (TGFβ) family are a large group of evolutionarily conserved cytokines whose signalling modulates cell fate decision-making across varying cellular contexts at different stages of life. Here we discuss new findings in early embryos that reveal how, in contrast to our original understanding of morphogen interpretation, robust cell fate specification can originate from a noisy combination of signalling inputs and a broad range of signalling levels. We compare this evidence with novel findings on the roles of TGFβ family signalling in tissue maintenance and homeostasis during juvenile and adult life, spanning the skeletal, haemopoietic and immune systems. From these comparisons, it emerges that in contrast to robust developing systems, relatively small perturbations in TGFβ family signalling have detrimental effects at later stages in life, leading to aberrant cell fate specification and disease, for example in cancer or congenital disorders. Finally, we highlight novel strategies to target and amend dysfunction in signalling and discuss how gleaning knowledge from different fields of biology can help in the development of therapeutics for aberrant TGFβ family signalling in disease.

Recent advances in glucose oxidase-based nanocarriers for tumor targeting therapy

Glucose oxidase (GOx) can specifically catalyze the conversion of β-d-glucose into gluconic acid and hydrogen peroxide (H2O2) in the presence of oxygen, making it promising for tumor starvation therapy and oxidative therapy. However, GOx's immunogenicity, poor in vivo stability, short half-life, and potential systemic toxicity, limit its application in cancer therapy. Nanocarriers are capable of improving the pharmacological properties of therapeutic drugs (e.g. stability, circulating half-life, and tumor accumulation) and lower toxicity, hence resolving GOx issues and enhancing its efficacy. Although the application of targeted nanocarriers based on GOx has recently flourished, this field has not yet been reviewed and evaluated. Herein, we initially examined the mechanism of GOx-based nanocarriers for enhanced tumor therapy. Also, we present a comprehensive and up-to-date review that highlights GOx-based nanocarriers for tumor targeting therapy. This review expands on GOx-based nano-targeted combination therapies from both passive and active targeting perspectives, meanwhile, active targeting is further classified into ligand-mediated targeting and physical-mediated targeting. Furthermore, this review also emphasizes the present challenges and promising advancements.

BMPR2 as a Novel Predisposition Gene for Hereditary Colorectal Polyposis

BACKGROUND & AIMS

Colorectal cancer (CRC) is one of the most prevalent tumors worldwide, with incidence quickly increasing (particularly in the context of early-onset cases), despite important prevention efforts, mainly in the form of population-wide screening programs. Although many cases present a clear familial component, the current list of hereditary CRC genes leaves a considerable proportion of the cases unexplained.

METHODS

In this work, we used whole-exome sequencing approaches on 19 unrelated patients with unexplained colonic polyposis to identify candidate CRC predisposition genes. The candidate genes were then validated in an additional series of 365 patients. CRISPR-Cas9 models were used to validate BMPR2 as a potential candidate for CRC risk.

RESULTS

We found 8 individuals carrying 6 different variants in the BMPR2 gene (approximately 2% of our cohort of patients with unexplained colonic polyposis). CRISPR-Cas9 models of 3 of these variants showed that the p.(Asn442Thrfs∗32) truncating variant completely abrogated BMP pathway function in a similar way to the BMPR2 knockout. Missense variants p.(Asn565Ser), p.(Ser967Pro) had varying effects on cell proliferation levels, with the former impairing cell control inhibition via noncanonical pathways.

CONCLUSIONS

Collectively, these results support loss-of-function BMPR2 variants as candidates to be involved in CRC germline predisposition.

The computational capabilities of many-to-many protein interaction networks

Many biological circuits comprise sets of protein variants that interact with one another in a many-to-many, or promiscuous, fashion. These architectures can provide powerful computational capabilities that are especially critical in multicellular organisms. Understanding the principles of biochemical computations in these circuits could allow more precise control of cellular behaviors. However, these systems are inherently difficult to analyze, due to their large number of interacting molecular components, partial redundancies, and cell context dependence. Here, we discuss recent experimental and theoretical advances that are beginning to reveal how promiscuous circuits compute, what roles those computations play in natural biological contexts, and how promiscuous architectures can be applied for the design of synthetic multicellular behaviors.

pYtags enable spatiotemporal measurements of receptor tyrosine kinase signaling in living cells

Receptor tyrosine kinases (RTKs) are major signaling hubs in metazoans, playing crucial roles in cell proliferation, migration, and differentiation. However, few tools are available to measure the activity of a specific RTK in individual living cells. Here, we present pYtags, a modular approach for monitoring the activity of a user-defined RTK by live-cell microscopy. pYtags consist of an RTK modified with a tyrosine activation motif that, when phosphorylated, recruits a fluorescently labeled tandem SH2 domain with high specificity. We show that pYtags enable the monitoring of a specific RTK on seconds-to-minutes time scales and across subcellular and multicellular length scales. Using a pYtag biosensor for epidermal growth factor receptor (EGFR), we quantitatively characterize how signaling dynamics vary with the identity and dose of activating ligand. We show that orthogonal pYtags can be used to monitor the dynamics of EGFR and ErbB2 activity in the same cell, revealing distinct phases of activation for each RTK. The specificity and modularity of pYtags open the door to robust biosensors of multiple tyrosine kinases and may enable engineering of synthetic receptors with orthogonal response programs.

Cell Decision Making through the Lens of Bayesian Learning

Cell decision making refers to the process by which cells gather information from their local microenvironment and regulate their internal states to create appropriate responses. Microenvironmental cell sensing plays a key role in this process. Our hypothesis is that cell decision-making regulation is dictated by Bayesian learning. In this article, we explore the implications of this hypothesis for internal state temporal evolution. By using a timescale separation between internal and external variables on the mesoscopic scale, we derive a hierarchical Fokker-Planck equation for cell-microenvironment dynamics. By combining this with the Bayesian learning hypothesis, we find that changes in microenvironmental entropy dominate the cell state probability distribution. Finally, we use these ideas to understand how cell sensing impacts cell decision making. Notably, our formalism allows us to understand cell state dynamics even without exact biochemical information about cell sensing processes by considering a few key parameters.

Recent Developments in Oral Delivery of Vaccines Using Nanocarriers

As oral administration of vaccines is the preferred route due to its high patient compliance and ability to stimulate both cellular and humoral immune responses, it is also associated with several challenges that include denaturation of vaccine components in the acidic environment of the stomach, degradation from proteolytic enzymes, and poor absorption through the intestinal membrane. To achieve effective delivery of such biomolecules, there is a need to investigate novel strategies of formulation development that can overcome the barriers associated with conventional vaccine delivery systems. Nanoparticles are advanced drug delivery carriers that provide target-oriented delivery by encapsulating vaccine components within them, thus making them stable against unfavorable conditions. This review provides a detailed overview of the different types of nanocarriers and various approaches that can enhance oral vaccine delivery.

Mass Spectrometry-Driven Discovery of Neuropeptides Mediating Nictation Behavior of Nematodes

Neuropeptides regulate animal physiology and behavior, making them widely studied targets of functional genetics research. While the field often relies on differential -omics approaches to build hypotheses, no such method exists for neuropeptidomics. It would nonetheless be valuable for studying behaviors suspected to be regulated by neuropeptides, especially when little information is otherwise available. This includes nictation, a phoretic strategy of Caenorhabditis elegans dauers that parallels host-finding strategies of infective juveniles of many pathogenic nematodes. We here developed a targeted peptidomics method for the model organism C. elegans and show that 161 quantified neuropeptides are more abundant in its dauer stage compared with L3 juveniles. Many of these have orthologs in the commercially relevant pathogenic nematode Steinernema carpocapsae, in whose infective juveniles, we identified 126 neuropeptides in total. Through further behavioral genetics experiments, we identify flp-7 and flp-11 as novel regulators of nictation. Our work advances knowledge on the genetics of nictation behavior and adds comparative neuropeptidomics as a tool to functional genetics workflows.

FKBP12 is a major regulator of ALK2 activity in multiple myeloma cells

BACKGROUND

The immunophilin FKBP12 binds to TGF-β family type I receptors, including the BMP type I receptor ALK2. FKBP12 keeps the type I receptor in an inactive state and controls signaling activity. Removal of FKBP12 with drugs such as the FKBP-ligand FK506 enhances BMP activity in various cell types. In multiple myeloma cells, activation of SMAD1/5/8 leads to apoptosis. We hypothesized that removing FKBP12 from ALK2 in myeloma cells would potentiate BMP-induced ALK2-SMAD1/5/8 activity and in consequence cell death.

METHODS

Multiple myeloma cell lines were treated with FK506, or other FKBP-binding compounds, combined with different BMPs before analyzing SMAD1/5/8 activity and cell viability. SMAD1/5/8 activity was also investigated using a reporter cell line, INA-6 BRE-luc. To characterize the functional signaling receptor complex, we genetically manipulated receptor expression by siRNA, shRNA and CRISPR/Cas9 technology.

RESULTS

FK506 potentiated BMP-induced SMAD1/5/8 activation and apoptosis in multiple myeloma cell lines. By using FKBP-binding compounds with different affinity profiles, and siRNA targeting FKBP12, we show that the FK506 effect is mediated by binding to FKBP12. Ligands that typically signal via ALK3 in myeloma cells, BMP2, BMP4, and BMP10, did not induce apoptosis in cells lacking ALK3. Notably, BMP10 competed with BMP6 and BMP9 and antagonized their activity via ALK2. However, upon addition of FK506, we saw a surprising shift in specificity, as the ALK3 ligands gained the ability to signal via ALK2 and induce apoptosis. This indicates that the receptor complex can switch from an inactive non-signaling complex (NSC) to an active one by adding FK506. This gain of activity was also seen in other cell types, indicating that the observed effects have broader relevance. BMP2, BMP4 and BMP10 depended on BMPR2 as type II receptor to signal, which contrasts with BMP6 and BMP9, that activate ALK2 more potently when BMPR2 is knocked down.

CONCLUSIONS

In summary, our data suggest that FKBP12 is a major regulator of ALK2 activity in multiple myeloma cells, partly by switching an NSC into an active signaling complex. FKBP12 targeting compounds devoid of immunosuppressing activity could have potential in novel treatment strategies aiming at reducing multiple myeloma tumor load. Video Abstract.

Molecular versatility during pluripotency progression

A challenge during development is to ensure lineage segregation while preserving plasticity. Using pluripotency progression as a paradigm, we review how developmental transitions are coordinated by redeployments, rather than global resettings, of cellular components. We highlight how changes in response to extrinsic cues (FGF, WNT, Activin/Nodal, Netrin-1), context- and stoichiometry-dependent action of transcription factors (Oct4, Nanog) and reconfigurations of epigenetic regulators (enhancers, promoters, TrxG, PRC) may confer robustness to naïve to primed pluripotency transition. We propose the notion of Molecular Versatility to regroup mechanisms by which molecules are repurposed to exert different, sometimes opposite, functions in close stem cell configurations.

Non-complementary strand commutation as a fundamental alternative for information processing by DNA and gene regulation

The discovery of the DNA double helix has revolutionized our understanding of data processing in living systems, with the complementarity of the two DNA strands providing a reliable mechanism for the storage of hereditary information. Here I reveal the 'strand commutation' phenomenon-a fundamentally different mechanism of information storage and processing by DNA/RNA based on the reversible low-affinity interactions of essentially non-complementary nucleic acids. I demonstrate this mechanism by constructing a memory circuit, a 5-min square-root circuit for 4-bit inputs comprising only nine processing ssDNAs, simulating a 572-input AND gate (surpassing the bitness of current electronic computers), and elementary algebra systems with continuously changing variables. Most importantly, I show potential pathways of gene regulation with strands of maximum non-complementarity to the gene sequence that may be key to the reduction of off-target therapeutic effects. This Article uncovers the information-processing power of the low-affinity interactions that may underlie major processes in an organism-from short-term memory to cancer, ageing and evolution.

Spatial range, temporal span, and promiscuity of CLE-RLK signaling

CLAVATA3/EMBRYO SURROUNDING REGION-RELATED (CLE) signaling through receptor-like kinases (RLKs) regulates developmental transitions and responses to biotic and abiotic inputs by communicating the physiological state of cells and tissues. CLE peptides have varying signaling ranges, which can be defined as the distance between the source, i.e., the cells or tissue that secrete the peptide, and their destination, i.e., cells or tissue where the RLKs that bind the peptide and/or respond are expressed. Case-by-case analysis substantiates that CLE signaling is predominantly autocrine or paracrine, and rarely endocrine. Furthermore, upon CLE reception, the ensuing signaling responses extend from cellular to tissue, organ and whole organism level as the downstream signal gets amplified. CLE-RLK-mediated effects on tissue proliferation and differentiation, or on subsequent primordia and organ development have been widely studied. However, studying how CLE-RLK regulates different stages of proliferation and differentiation at cellular level can offer additional insights into these processes. Notably, CLE-RLK signaling also mediates diverse non-developmental effects, which are less often observed; however, this could be due to biased experimental approaches. In general, CLEs and RLKs, owing to the sequence or structural similarity, are prone to promiscuous interactions at least under experimental conditions in which they are studied. Importantly, there are regulatory mechanisms that suppress CLE-RLK cross-talk in vivo, thereby eliminating the pressure for co-evolving binding specificity. Alternatively, promiscuity in signaling may also offer evolutionary advantages and enable different CLEs to work in combination to activate or switch off different RLK signaling pathways.