Multiscale networks in multiple sclerosis.

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Shared Proteins and Pathways of Cardiovascular and Cognitive Diseases: Relation to Vascular Cognitive Impairment.

One of the primary goals of systems medicine is the detection of putative proteins and pathways involved in disease progression and pathological phenotypes. Vascular cognitive impairment (VCI) is a heterogeneous condition manifesting as cognitive impairment resulting from vascular factors. The precise mechanisms underlying this relationship remain unclear, which poses challenges for experimental research. Here, we applied computational approaches like systems biology to unveil and select relevant proteins and pathways related to VCI by studying the crosstalk between cardiovascular and cognitive diseases. In addition, we specifically included signals related to oxidative stress, a common etiologic factor tightly linked to aging, a major determinant of VCI. Our results show that pathways associated with oxidative stress are quite relevant, as most of the prioritized vascular cognitive genes and proteins were enriched in these pathways. Our analysis provided a short list of proteins that could be contributing to VCI: DOLK, TSC1, ATP1A1, MAPK14, YWHAZ, CREB3, HSPB1, PRDX6, and LMNA. Moreover, our experimental results suggest a high implication of glycative stress, generating oxidative processes and post-translational protein modifications through advanced glycation end-products (AGEs). We propose that these products interact with their specific receptors (RAGE) and Notch signaling to contribute to the etiology of VCI.

Parametric modeling of mechanical effects on circadian oscillators.

Circadian rhythms are archetypal examples of nonlinear oscillations. While these oscillations are usually attributed to circuits of biochemical interactions among clock genes and proteins, recent experimental studies reveal that they are also affected by the cell's mechanical environment. Here, we extend a standard biochemical model of circadian rhythmicity to include mechanical effects in a parametric manner. Using experimental observations to constrain the model, we suggest specific ways in which the mechanical signal might affect the clock. Additionally, a bifurcation analysis of the system predicts that these mechanical signals need to be within an optimal range for circadian oscillations to occur.

Single-cell Bayesian deconvolution.

Individual cells exhibit substantial heterogeneity in protein abundance and activity, which is frequently reflected in broad distributions of fluorescently labeled reporters. Since all cellular components are intrinsically fluorescent to some extent, the observed distributions contain background noise that masks the natural heterogeneity of cellular populations. This limits our ability to characterize cell-fate decision processes that are key for development, immune response, tissue homeostasis, and many other biological functions. It is therefore important to separate the contributions from signal and noise in single-cell measurements. Addressing this issue rigorously requires deconvolving the noise distribution from the signal, but approaches in that direction are still limited. Here, we present a non-parametric Bayesian formalism that performs such a deconvolution efficiently on multidimensional measurements, providing unbiased estimates of the resulting confidence intervals. We use this approach to study the expression of the mesodermal transcription factor Brachyury in mouse embryonic stem cells undergoing differentiation.

On time: developmental timing within and across species.

Organisms across species differ in the relative size and complexity of their tissues to serve the specific purposes of the host. Correct timing is a crucial ingredient in the development of tissues, as reaching the right size and complexity requires a careful balance between cellular proliferation and differentiation. Premature or delayed differentiation, for instance, can result in tissue imbalance, malformation or malfunction. Despite seemingly rigid constraints on development, however, there is flexibility in both the timing and differentiation trajectories within and between species. In this Spotlight, we discuss how time is measured and regulated in development, and question whether developmental timing is in fact different between species.

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.

Mechanical control of the mammalian circadian clock via YAP/TAZ and TEAD.

Autonomous circadian clocks exist in nearly every mammalian cell type. These cellular clocks are subjected to a multilayered regulation sensitive to the mechanochemical cell microenvironment. Whereas the biochemical signaling that controls the cellular circadian clock is increasingly well understood, mechanisms underlying regulation by mechanical cues are largely unknown. Here we show that the fibroblast circadian clock is mechanically regulated through YAP/TAZ nuclear levels. We use high-throughput analysis of single-cell circadian rhythms and apply controlled mechanical, biochemical, and genetic perturbations to study the expression of the clock gene Rev-erbα. We observe that Rev-erbα circadian oscillations are disrupted with YAP/TAZ nuclear translocation. By targeted mutations and overexpression of YAP/TAZ, we show that this mechanobiological regulation, which also impacts core components of the clock such as Bmal1 and Cry1, depends on the binding of YAP/TAZ to the transcriptional effector TEAD. This mechanism could explain the impairment of circadian rhythms observed when YAP/TAZ activity is upregulated, as in cancer and aging.

Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks.

Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.

A Genome-Wide Functional Screen Identifies Enhancer and Protective Genes for Amyloid Beta-Peptide Toxicity.

Alzheimer's disease (AD) is known to be caused by amyloid ß-peptide (Aß) misfolded into ß-sheets, but this knowledge has not yet led to treatments to prevent AD. To identify novel molecular players in Aß toxicity, we carried out a genome-wide screen in Saccharomyces cerevisiae, using a library of 5154 gene knock-out strains expressing Aß1-42. We identified 81 mammalian orthologue genes that enhance Aß1-42 toxicity, while 157 were protective. Next, we performed interactome and text-mining studies to increase the number of genes and to identify the main cellular functions affected by Aß oligomers (oAß). We found that the most affected cellular functions were calcium regulation, protein translation and mitochondrial activity. We focused on SURF4, a protein that regulates the store-operated calcium channel (SOCE). An in vitro analysis using human neuroblastoma cells showed that SURF4 silencing induced higher intracellular calcium levels, while its overexpression decreased calcium entry. Furthermore, SURF4 silencing produced a significant reduction in cell death when cells were challenged with oAß1-42, whereas SURF4 overexpression induced Aß1-42 cytotoxicity. In summary, we identified new enhancer and protective activities for Aß toxicity and showed that SURF4 contributes to oAß1-42 neurotoxicity by decreasing SOCE activity.

Comparison between an exact and a heuristic neural mass model with second-order synapses.

Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that the output firing rate of a neural population can be described by a static nonlinear transfer function (NMM1). However, a recent exact mean-field theory for quadratic integrate-and-fire (QIF) neurons challenges this view by showing that the mean firing rate is not a static function of the neuronal state but follows two coupled nonlinear differential equations (NMM2). Here we analyze and compare these two descriptions in the presence of second-order synaptic dynamics. First, we derive the mathematical equivalence between the two models in the infinitely slow synapse limit, i.e., we show that NMM1 is an approximation of NMM2 in this regime. Next, we evaluate the applicability of this limit in the context of realistic physiological parameter values by analyzing the dynamics of models with inhibitory or excitatory synapses. We show that NMM1 fails to reproduce important dynamical features of the exact model, such as the self-sustained oscillations of an inhibitory interneuron QIF network. Furthermore, in the exact model but not in the limit one, stimulation of a pyramidal cell population induces resonant oscillatory activity whose peak frequency and amplitude increase with the self-coupling gain and the external excitatory input. This may play a role in the enhanced response of densely connected networks to weak uniform inputs, such as the electric fields produced by noninvasive brain stimulation.

Proteomic signatures of synergistic interactions in antimicrobials.

Mounting evidence has shown that antimicrobial agents can interfere synergistically with bacterial viability and proliferation when acting together at both the planktonic and biofilm levels without clear underlying molecular mechanisms. Here, multiplexed proteomics by iTRAQ was used to study the interplay between two biocides, the isothiazolone 1,2-benzisothiazolin-3-one (BIT) and the chelating agent disodium ethylenediaminetetraacetic acid (EDTA-2Na), employing the Citrobacter werkmanii as a model system. We first confirmed that these two biocides act synergistically on this bacterial species and then extracted the proteomic profiles of C. werkmanii cells in the presence of BIT, EDTA-2Na, and their combinations. In particular, we identified 43 core proteins that are differentially expressed in all three conditions simultaneously. Meanwhile, we found that these core proteins are consistently up-regulated when these two biocides are present, but not for single biocides, where we found a balanced mix of up- and down-regulation. Meanwhile, most of the deletion mutants of the core DEPs exhibited biofilm growth inhibition under joint biocide action, while their response was very heterogenous, with respect to the wild-type strain. Together, our results show that while BIT and EDTA-2Na act on multiple protein targets, they interact synergistically at the protein level in a very consistent manner. SIGNIFICANCE: Our preliminary experiments have demonstrated that a combination of 1,2-benzisothiazolin-3-one (BIT) and EDTA-2Na shows higher inhibitory effects on planktonic growth and biofilm formation in both C. werkmanii and Staphylococcus aureus than when these two biocides act alone. However, the mechanistic basis of such synergistic interaction is still unknown. Therefore, the key proteins involved in the above-mentioned enhanced antimicrobial synergy were elucidated using multiplexed proteomics analysis by isobaric tags for relative and absolute quantification (iTRAQ). Our results reveal that the joint action of BIT and EDTA-2Na induces consistent protein expression alteration in a set of core proteins of C. werkmanii, which underlies a strong synergistic antimicrobial effect, which increase our understanding of the action modes of BIT and EDTA-2Na as well as their combinations.

Periodic spatial patterning with a single morphogen.

During multicellular development, periodic spatial patterning systems generate repetitive structures, such as digits, vertebrae, and teeth. Turing patterning provides a foundational paradigm for understanding such systems. The simplest Turing systems are believed to require at least two morphogens to generate periodic patterns. Here, using mathematical modeling, we show that a simpler circuit, including only a single diffusible morphogen, is sufficient to generate long-range, spatially periodic patterns that propagate outward from transient initiating perturbations and remain stable after the perturbation is removed. Furthermore, an additional bistable intracellular feedback or operation on a growing cell lattice can make patterning robust to noise. Together, these results show that a single morphogen can be sufficient for robust spatial pattern formation and should provide a foundation for engineering pattern formation in the emerging field of synthetic developmental biology.

Electrochemical potential enables dormant spores to integrate environmental signals.

The dormant state of bacterial spores is generally thought to be devoid of biological activity. We show that despite continued dormancy, spores can integrate environmental signals over time through a preexisting electrochemical potential. Specifically, we studied thousands of individual Bacillus subtilis spores that remain dormant when exposed to transient nutrient pulses. Guided by a mathematical model of bacterial electrophysiology, we modulated the decision to exit dormancy by genetically and chemically targeting potassium ion flux. We confirmed that short nutrient pulses result in step-like changes in the electrochemical potential of persistent spores. During dormancy, spores thus gradually release their stored electrochemical potential to integrate extracellular information over time. These findings reveal a decision-making mechanism that operates in physiologically inactive cells.

Differential regulation of insulin signalling by monomeric and oligomeric amyloid beta-peptide.

Alzheimer's disease and Type 2 diabetes are pathological processes associated to ageing. Moreover, there are evidences supporting a mechanistic link between Alzheimer's disease and insulin resistance (one of the first hallmarks of Type 2 diabetes). Regarding Alzheimer's disease, amyloid ß-peptide aggregation into ß-sheets is the main hallmark of Alzheimer's disease. At monomeric state, amyloid ß-peptide is not toxic but its function in brain, if any, is unknown. Here we show, by in silico study, that monomeric amyloid ß-peptide 1-40 shares the tertiary structure with insulin and is thereby able to bind and activate insulin receptor. We validated this prediction experimentally by treating human neuroblastoma cells with increasing concentrations of monomeric amyloid ß-peptide 1-40. Our results confirm that monomeric amyloid ß-peptide 1-40 activates insulin receptor autophosphorylation, triggering downstream enzyme phosphorylations and the glucose Transporter 4 translocation to the membrane. On the other hand, neuronal insulin resistance is known to be associated to Alzheimer's disease since early stages. We thus modelled the docking of oligomeric amyloid ß-peptide 1-40 to insulin receptor. We found that oligomeric amyloid ß-peptide 1-40 blocks insulin receptor, impairing its activation. It was confirmed in vitro by observing the lack of insulin receptor autophosphorylation, and also the impairment of insulin-induced intracellular enzyme activations and the glucose Transporter 4 translocation to the membrane. By biological system analysis, we have carried out a mathematical model recapitulating the process that turns amyloid ß-peptide binding to insulin receptor from the physiological to the pathophysiological regime. Our results suggest that monomeric amyloid ß-peptide 1-40 contributes to mimic insulin effects in the brain, which could be good when neurons have an extra requirement of energy beside the well-known protective effects on insulin intracellular signalling, while its accumulation and subsequent oligomerization blocks the insulin receptor producing insulin resistance and compromising neuronal metabolism and protective pathways.

Signaling oscillations: Molecular mechanisms and functional roles.

Mounting evidence shows that oscillatory activity is widespread in cell signaling. Here, we review some of this recent evidence, focusing on both the molecular mechanisms that potentially underlie such dynamical behavior, and the potential advantages that signaling oscillations might have in cell function. The biological processes considered include cellular differentiation and tissue maintenance, intermittent responses in pluripotent stem cells, and collective cell migration during wound healing. With the aid of mathematical modeling, we review recent examples in which delayed negative feedback has been seen to act as a unifying principle that underpins this wide variety of phenomena.

Localized electrical stimulation triggers cell-type-specific proliferation in biofilms.

Biological systems ranging from bacteria to mammals utilize electrochemical signaling. Although artificial electrochemical signals have been utilized to characterize neural tissue responses, the effects of such stimuli on non-neural systems remain unclear. To pursue this question, we developed an experimental platform that combines a microfluidic chip with a multielectrode array (MiCMA) to enable localized electrochemical stimulation of bacterial biofilms. The device also allows for the simultaneous measurement of the physiological response within the biofilm with single-cell resolution. We find that the stimulation of an electrode locally changes the ratio of the two major cell types comprising Bacillus subtilis biofilms, namely motile and extracellular-matrix-producing cells. Specifically, stimulation promotes the proliferation of motile cells but not matrix cells, even though these two cell types are genetically identical and reside in the same microenvironment. Our work thus reveals that an electronic interface can selectively target bacterial cell types, enabling the control of biofilm composition and development.

Blood Neutrophil Counts Define Specific Clusters of Bronchiectasis Patients: A Hint to Differential Clinical Phenotypes.

We sought to investigate differential phenotypic characteristics according to neutrophil counts, using a biostatistics approach in a large-cohort study from the Spanish Online Bronchiectasis Registry (RIBRON). The 1034 patients who met the inclusion criteria were clustered into two groups on the basis of their blood neutrophil levels. Using the Mann-Whitney U test to explore potential differences according to FACED and EFACED scores between the two groups, a neutrophil count of 4990 cells/µL yielded the most balanced cluster sizes: (1) above-threshold (n = 337) and (2) below-threshold (n = 697) groups. Patients above the threshold showed significantly worse lung function parameters and nutritional status, while systemic inflammation levels were higher than in the below-threshold patients. In the latter group, the proportions of patients with mild disease were greater, while a more severe disease was present in the above-threshold patients. According to the blood neutrophil counts using biostatistics analyses, two distinct clinical phenotypes of stable patients with non-CF bronchiectasis were defined. Patients falling into the above-threshold cluster were more severe. Severity was characterized by a significantly impaired lung function parameters and nutritional status, and greater systemic inflammation. Phenotypic profiles of bronchiectasis patients are well defined as a result of the cluster analysis of combined systemic and respiratory variables.

Evaluation of Ravindran et al.: Real-time detection of signaling pulses in vivo: making cells monitor themselves.

One snapshot of the peer review process for "A synthetic gene circuit for imaging-free detection of signaling pulses" (Ravindran et al., 2022) appears below.

Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study.

Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort (n = 1092). Clusters #1-3 were named as mild, moderate, and severe on the basis of disease severity scores. Patients in cluster #3 were significantly more severe (FEV1, age, colonization, extension, dyspnea (FACED), exacerbation (EFACED), and bronchiectasis severity index (BSI) scores) than patients in clusters #1 and #2. Exacerbation and hospitalization numbers, Charlson index, and blood inflammatory markers were significantly greater in cluster #3 than in clusters #1 and #2. Chronic colonization by Pseudomonas aeruginosa and COPD prevalence were higher in cluster # 3 than in cluster #1. Airflow limitation and diffusion capacity were reduced in cluster #3 compared to clusters #1 and #2. Multivariate ordinal logistic regression analysis further confirmed these results. Similar results were obtained after excluding COPD patients. Clustering analysis offers a powerful tool to better characterize patients with bronchiectasis. These results have clinical implications in the management of the complexity and heterogeneity of bronchiectasis patients.

Synthetic multistability in mammalian cells.

In multicellular organisms, gene regulatory circuits generate thousands of molecularly distinct, mitotically heritable states through the property of multistability. Designing synthetic multistable circuits would provide insight into natural cell fate control circuit architectures and would allow engineering of multicellular programs that require interactions among distinct cell types. We created MultiFate, a naturally inspired, synthetic circuit that supports long-term, controllable, and expandable multistability in mammalian cells. MultiFate uses engineered zinc finger transcription factors that transcriptionally self-activate as homodimers and mutually inhibit one another through heterodimerization. Using a model-based design, we engineered MultiFate circuits that generate as many as seven states, each stable for at least 18 days. MultiFate permits controlled state switching and modulation of state stability through external inputs and can be expanded with additional transcription factors. These results provide a foundation for engineering multicellular behaviors in mammalian cells.