Mor Nitzan

Dynamics of the Type III Secretion System Activity of Enteropathogenic Escherichia coli

ABSTRACT Type III secretion systems (TTSSs) are employed by pathogens to translocate host cells with effector proteins, which are crucial for virulence. The dynamics of effector translocation, behavior of the translocating bacteria, translocation temporal order, and relative amounts of each of the translocated effectors are all poorly characterized. To address these issues, we developed a microscopy-based assay that tracks effector translocation. We used this assay alongside a previously described real-time population-based translocation assay, focusing mainly on enteropathogenic Escherichia coli (EPEC) and partly comparing it to Salmonella. We found that the two pathogens exhibit different translocation behaviors: in EPEC, a subpopulation that formed microcolonies carried out most of the translocation activity, while Salmonella executed protein translocation as planktonic bacteria. We also noted variability in host cell susceptibility, with some cells highly resistant to translocation. We next extended the study to determine the translocation dynamics of twenty EPEC effectors and found that all exhibited distinct levels of translocation efficiency. Further, we mapped the global effects of key TTSS-related components on TTSS activity. Our results provide a comprehensive description of the dynamics of the TTSS activity of EPEC and new insights into the mechanisms that control the dynamics. IMPORTANCE EPEC and the closely related enterohemorrhagic Escherichia coli (EHEC) represent a global public health problem. New strategies to combat EPEC and EHEC infections are needed, and development of such strategies requires better understanding of their virulence machinery. The TTSS is a critical virulence mechanism employed by these pathogens, and by others, including Salmonella. In this study, we aimed at elucidating new aspects of TTSS function. The results obtained provide a comprehensive description of the dynamics of TTSS activity of EPEC and new insights into the mechanisms that control these changes. This knowledge sets the stage for further analysis of the system and may accelerate the development of new ways to treat EPEC and EHEC infections. Further, the newly described microscopy-based assay can be readily adapted to study the dynamics of TTSS activity in other pathogens. EPEC and the closely related enterohemorrhagic Escherichia coli (EHEC) represent a global public health problem. New strategies to combat EPEC and EHEC infections are needed, and development of such strategies requires better understanding of their virulence machinery. The TTSS is a critical virulence mechanism employed by these pathogens, and by others, including Salmonella. In this study, we aimed at elucidating new aspects of TTSS function. The results obtained provide a comprehensive description of the dynamics of TTSS activity of EPEC and new insights into the mechanisms that control these changes. This knowledge sets the stage for further analysis of the system and may accelerate the development of new ways to treat EPEC and EHEC infections. Further, the newly described microscopy-based assay can be readily adapted to study the dynamics of TTSS activity in other pathogens.

Bundle-forming pilus retraction enhances enteropathogenic Escherichia coli infectivity.

Enteropathogenic Escherichia coli (EPEC) and other pathogenic bacteria use dynamic type IV pili to adhere to the host. Here we show that the capacity of the EPEC type IV pili to retract is required for the breakdown of the host epithelial tight-junction barrier, efficient actin-pedestal formation, and translocation of effectors via the type III secretion system.

Reversible functional connectivity disturbances during transient global amnesia.

Transient global amnesia (TGA), an abrupt occurrence of severe anterograde episodic amnesia accompanied by repetitive questioning, has been known for more than 50 years. Despite extensive research, there is no clear evidence for the underlying pathophysiological basis of TGA. Moreover, there is no neuroimaging method to evaluate TGA in real time.

Interactions between Distant ceRNAs in Regulatory Networks

Competing endogenous RNAs (ceRNAs) were recently introduced as RNA transcripts that affect each other’s expression level through competition for their microRNA (miRNA) coregulators. This stems from the bidirectional effects between miRNAs and their target RNAs, where a change in the expression level of one target affects the level of the miRNA regulator, which in turn affects the level of other targets. By the same logic, miRNAs that share targets compete over binding to their common targets and therefore also exhibit ceRNA-like behavior. Taken together, perturbation effects could propagate in the posttranscriptional regulatory network through a path of coregulated targets and miRNAs that share targets, suggesting the existence of distant ceRNAs. Here we study the prevalence of distant ceRNAs and their effect in cellular networks. Analyzing the network of miRNA-target interactions deciphered experimentally in HEK293 cells, we show that it is a dense, intertwined network, suggesting that many nodes can act as distant ceRNAs of one another. Indeed, using gene expression data from a perturbation experiment, we demonstrate small, yet statistically significant, changes in gene expression caused by distant ceRNAs in that network. We further characterize the magnitude of the propagated perturbation effect and the parameters affecting it by mathematical modeling and simulations. Our results show that the magnitude of the effect depends on the generation and degradation rates of involved miRNAs and targets, their interaction rates, the distance between the ceRNAs and the topology of the network. Although demonstrated for a miRNA-mRNA regulatory network, our results offer what to our knowledge is a new view on various posttranscriptional cellular networks, expanding the concept of ceRNAs and implying possible distant cross talk within the network, with consequences for the interpretation of indirect effects of gene perturbation.

Integration of Bacterial Small RNAs in Regulatory Networks

Small RNAs (sRNAs) are central regulators of gene expression in bacteria, controlling target genes posttranscriptionally by base pairing with their mRNAs. sRNAs are involved in many cellular processes and have unique regulatory characteristics. In this review, we discuss the properties of regulation by sRNAs and how it differs from and combines with transcriptional regulation. We describe the global characteristics of the sRNA-target networks in bacteria using graph-theoretic approaches and review the local integration of sRNAs in mixed regulatory circuits, including feed-forward loops and their combinations, feedback loops, and circuits made of an sRNA and another regulator, both derived from the same transcript. Finally, we discuss the competition effects in posttranscriptional regulatory networks that may arise over shared targets, shared regulators, and shared resources and how they may lead to signal propagation across the network.

A defense-offense multi-layered regulatory switch in a pathogenic bacterium

Cells adapt to environmental changes by efficiently adjusting gene expression programs. Staphylococcus aureus, an opportunistic pathogenic bacterium, switches between defensive and offensive modes in response to quorum sensing signal. We identified and studied the structural characteristics and dynamic properties of the core regulatory circuit governing this switch by deterministic and stochastic computational methods, as well as experimentally. This module, termed here Double Selector Switch (DSS), comprises the RNA regulator RNAIII and the transcription factor Rot, defining a double-layered switch involving both transcriptional and post-transcriptional regulations. It coordinates the inverse expression of two sets of target genes, immuno-modulators and exotoxins, expressed during the defensive and offensive modes, respectively. Our computational and experimental analyses show that the DSS guarantees fine-tuned coordination of the inverse expression of its two gene sets, tight regulation, and filtering of noisy signals. We also identified variants of this circuit in other bacterial systems, suggesting it is used as a molecular switch in various cellular contexts and offering its use as a template for an effective switching device in synthetic biology studies.

Evidence for functional networks within the human brain's white matter.

Investigation of the functional macro-scale organization of the human cortex is fundamental in modern neuroscience. Although numerous studies have identified networks of interacting functional modules in the gray-matter, limited research was directed to the functional organization of the white-matter. Recent studies have demonstrated that the white-matter exhibits blood oxygen level-dependent signal fluctuations similar to those of the gray-matter. Here we used these signal fluctuations to investigate whether the white-matter is organized as functional networks by applying a clustering analysis on resting-state functional MRI (RSfMRI) data from white-matter voxels, in 176 subjects (of both sexes). This analysis indicated the existence of 12 symmetrical white-matter functional networks, corresponding to combinations of white-matter tracts identified by diffusion tensor imaging. Six of the networks included interhemispheric commissural bridges traversing the corpus callosum. Signals in white-matter networks correlated with signals from functional gray-matter networks, providing missing knowledge on how these distributed networks communicate across large distances. These findings were replicated in an independent subject group and were corroborated by seed-based analysis in small groups and individual subjects. The identified white-matter functional atlases and analysis codes are available at http://mind.huji.ac.il/white-matter.aspx. Our results demonstrate that the white-matter manifests an intrinsic functional organization as interacting networks of functional modules, similarly to the gray-matter, which can be investigated using RSfMRI. The discovery of functional networks within the white-matter may open new avenues of research in cognitive neuroscience and clinical neuropsychiatry. SIGNIFICANCE STATEMENT In recent years, functional MRI (fMRI) has revolutionized all fields of neuroscience, enabling identifications of functional modules and networks in the human brain. However, most fMRI studies ignored a major part of the brain, the white-matter, discarding signals from it as arising from noise. Here we use resting-state fMRI data from 176 subjects to show that signals from the human white-matter contain meaningful information. We identify 12 functional networks composed of interacting long-distance white-matter tracts. Moreover, we show that these networks are highly correlated to resting-state gray-matter networks, highlighting their functional role. Our findings enable reinterpretation of many existing fMRI datasets, and suggest a new way to explore the white-matter role in cognition and its disturbances in neuropsychiatric disorders.

Revealing physical interaction networks from statistics of collective dynamics

Recording only the statistics of driven, asynchronous dynamics reveals a network’s interaction structure. Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems.

Model-free inference of direct network interactions from nonlinear collective dynamics

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.Network dynamical systems can represent the interactions involved in the collective dynamics of gene regulatory networks or metabolic circuits. Here Casadiego et al. present a method for inferring these types of interactions directly from observed time series without relying on their model.

Degradation of Ndd1 by APC/C Cdh1 generates a feed forward loop that times mitotic protein accumulation

Ndd1 activates the Mcm1-Fkh2 transcription factor to transcribe mitotic regulators. The anaphase-promoting complex/cyclosome activated by Cdh1 (APC/C(Cdh1)) mediates the degradation of proteins throughout G1. Here we show that the APC/C(Cdh1) ubiquitinates Ndd1 and mediates its degradation, and that APC/C(Cdh1) activity suppresses accumulation of Ndd1 targets. We confirm putative Ndd1 targets and identify novel ones, many of them APC/C(Cdh1) substrates. The APC/C(Cdh1) thus regulates these proteins in a dual manner—both pretranscriptionally and post-translationally, forming a multi-layered feedforward loop (FFL). We predict by mathematical modelling and verify experimentally that this FFL introduces a lag between APC/C(Cdh1) inactivation at the end of G1 and accumulation of genes transcribed by Ndd1 in G2. This regulation generates two classes of APC/C(Cdh1) substrates, early ones that accumulate in S and late ones that accumulate in G2. Our results show how the dual state APC/C(Cdh1) activity is converted into multiple outputs by interactions between its substrates.