Landscape context mediates the relationship between plant functional traits and decomposition

Aims: It has been well demonstrated that several interacting endogenous and exogenous factors influence decomposition. However, teasing apart the direct and indirect effects of these factors to predict decomposition patterns in heterogenous landscapes remains a key challenge. Methods: At 157 locations in a temperate forest, we measured decomposition of a standard substrate (filter paper) over two years, the landscape context in which decomposition took place, and the functional composition of the woody species that contributed leaf litter to the forest floor where litter bags were placed. We tested for direct and indirect effects of landscape context and direct effects of forest functional composition on decay using structural equation modelling. Results: We found that landscape context had direct effects on decay and indirect effects on decay via its influence on the functional composition of the surrounding forest. Forest functional composition also had direct effects on decay, but these effects decreased or disappeared completely over time. Moreover, community weighted mean trait values were better predictors of decay than functional dispersion of leaf traits, and leaf nitrogen content and carbon content were better predictors of decay than leaf dry matter content or leaf toughness. Conclusions: Our results highlight the importance of an integrative approach that examines the direct and indirect effects of multiple factors for understanding and predicting decomposition patterns across heterogenous landscapes

Trade-off between Responsiveness and Noise Suppression in Biomolecular System Responses to Environmental Cues

When living systems detect changes in their external environment their response must be measured to balance the need to react appropriately with the need to remain stable, ignoring insignificant signals. Because this is a fundamental challenge of all biological systems that execute programs in response to stimuli, we developed a generalized time-frequency analysis (TFA) framework to systematically explore the dynamical properties of biomolecular networks. Using TFA, we focused on two well-characterized yeast gene regulatory networks responsive to carbon-source shifts and a mammalian innate immune regulatory network responsive to lipopolysaccharides (LPS). The networks are comprised of two different basic architectures. Dual positive and negative feedback loops make up the yeast galactose network; whereas overlapping positive and negative feed-forward loops are common to the yeast fatty-acid response network and the LPS-induced network of macrophages. TFA revealed remarkably distinct network behaviors in terms of trade-offs in responsiveness and noise suppression that are appropriately tuned to each biological response. The wild type galactose network was found to be highly responsive while the oleate network has greater noise suppression ability. The LPS network appeared more balanced, exhibiting less bias toward noise suppression or responsiveness. Exploration of the network parameter space exposed dramatic differences in system behaviors for each network. These studies highlight fundamental structural and dynamical principles that underlie each network, reveal constrained parameters of positive and negative feedback and feed-forward strengths that tune the networks appropriately for their respective biological roles, and demonstrate the general utility of the TFA approach for systems and synthetic biology

Reliability of Transcriptional Cycles and the Yeast Cell-Cycle Oscillator

A recently published transcriptional oscillator associated with the yeast cell cycle provides clues and raises questions about the mechanisms underlying autonomous cyclic processes in cells. Unlike other biological and synthetic oscillatory networks in the literature, this one does not seem to rely on a constitutive signal or positive auto-regulation, but rather to operate through stable transmission of a pulse on a slow positive feedback loop that determines its period. We construct a continuous-time Boolean model of this network, which permits the modeling of noise through small fluctuations in the timing of events, and show that it can sustain stable oscillations. Analysis of simpler network models shows how a few building blocks can be arranged to provide stability against fluctuations. Our findings suggest that the transcriptional oscillator in yeast belongs to a new class of biological oscillators

Thermodynamic State Ensemble Models of cis-Regulation

A major goal in computational biology is to develop models that accurately predict a gene's expression from its surrounding regulatory DNA. Here we present one class of such models, thermodynamic state ensemble models. We describe the biochemical derivation of the thermodynamic framework in simple terms, and lay out the mathematical components that comprise each model. These components include (1) the possible states of a promoter, where a state is defined as a particular arrangement of transcription factors bound to a DNA promoter, (2) the binding constants that describe the affinity of the protein–protein and protein–DNA interactions that occur in each state, and (3) whether each state is capable of transcribing. Using these components, we demonstrate how to compute a cis-regulatory function that encodes the probability of a promoter being active. Our intention is to provide enough detail so that readers with little background in thermodynamics can compose their own cis-regulatory functions. To facilitate this goal, we also describe a matrix form of the model that can be easily coded in any programming language. This formalism has great flexibility, which we show by illustrating how phenomena such as competition between transcription factors and cooperativity are readily incorporated into these models. Using this framework, we also demonstrate that Michaelis-like functions, another class of cis-regulatory models, are a subset of the thermodynamic framework with specific assumptions. By recasting Michaelis-like functions as thermodynamic functions, we emphasize the relationship between these models and delineate the specific circumstances representable by each approach. Application of thermodynamic state ensemble models is likely to be an important tool in unraveling the physical basis of combinatorial cis-regulation and in generating formalisms that accurately predict gene expression from DNA sequence

Epithelial p38α Controls Immune Cell Recruitment in the Colonic Mucosa

Intestinal epithelial cells (IECs) compose the first barrier against microorganisms in the gastrointestinal tract. Although the NF-κB pathway in IECs was recently shown to be essential for epithelial integrity and intestinal immune homeostasis, the roles of other inflammatory signaling pathways in immune responses in IECs are still largely unknown. Here we show that p38α in IECs is critical for chemokine expression, subsequent immune cell recruitment into the intestinal mucosa, and clearance of the infected pathogen. Mice with p38α deletion in IECs suffer from a sustained bacterial burden after inoculation with Citrobacter rodentium. These animals are normal in epithelial integrity and immune cell function, but fail to recruit CD4+ T cells into colonic mucosal lesions. The expression of chemokines in IECs is impaired, which appears to be responsible for the impaired T cell recruitment. Thus, p38α in IECs contributes to the host immune responses against enteric bacteria by the recruitment of immune cells

Monotone and near-monotone biochemical networks

Monotone subsystems have appealing properties as components of larger networks, since they exhibit robust dynamical stability and predictability of responses to perturbations. This suggests that natural biological systems may have evolved to be, if not monotone, at least close to monotone in the sense of being decomposable into a “small” number of monotone components, In addition, recent research has shown that much insight can be attained from decomposing networks into monotone subsystems and the analysis of the resulting interconnections using tools from control theory. This paper provides an expository introduction to monotone systems and their interconnections, describing the basic concepts and some of the main mathematical results in a largely informal fashion

Early Secreted Antigen ESAT-6 of Mycobacterium tuberculosis Promotes Protective T Helper 17 Cell Responses in a Toll-Like Receptor-2-dependent Manner

Despite its relatively poor efficacy, Bacillus Calmette-Guérin (BCG) has been used as a tuberculosis (TB) vaccine since its development in 1921. BCG induces robust T helper 1 (Th1) immune responses but, for many individuals, this is not sufficient for host resistance against Mycobacterium tuberculosis (M. tb) infection. Here we provide evidence that early secreted antigenic target protein 6 (ESAT-6), expressed by the virulent M. tb strain H37Rv but not by BCG, promotes vaccine-enhancing Th17 cell responses. These activities of ESAT-6 were dependent on TLR-2/MyD88 signalling and involved IL-6 and TGF-β production by dendritic cells. Thus, animals that were previously infected with H37Rv or recombinant BCG containing the RD1 region (BCG::RD1) exhibited improved protection upon re-challenge with virulent H37Rv compared with mice previously infected with BCG or RD1-deficient H37Rv (H37RvΔRD1). However, TLR-2 knockout (TLR-2-/-) animals neither showed Th17 responses nor exhibited improved protection in response to immunization with H37Rv. Furthermore, H37Rv and BCG::RD1 infection had little effect on the expression of the anti-inflammatory microRNA-146a (miR146a) in dendritic cells (DCs), whereas BCG and H37RvΔRD1 profoundly induced its expression in DCs. Consistent with these findings, ESAT-6 had no effect on miR146a expression in uninfected DCs, but dramatically inhibited its upregulation in BCG-infected or LPS-treated DCs. Collectively, our findings indicate that, in addition to Th1 immunity induced by BCG, RD1/ESAT-6-induced Th17 immune responses are essential for optimal vaccine efficacy

Elevation of IL-6 in the allergic asthmatic airway is independent of inflammation but associates with loss of central airway function

<p>Abstract</p> <p>Background</p> <p>Asthma is a chronic inflammatory disease of the airway that is characterized by a Th2-type of immune response with increasing evidence for involvement of Th17 cells. The role of IL-6 in promoting effector T cell subsets suggest that IL-6 may play a functional role in asthma. Classically IL-6 has been viewed as an inflammatory marker, along with TNFα and IL-1β, rather than as regulatory cytokine.</p> <p>Objective</p> <p>To investigate the potential relationship between IL-6 and other proinflammatory cytokines, Th2/Th17 cytokines and lung function in allergic asthma, and thus evaluate the potential role of IL-6 in this disease.</p> <p>Methods</p> <p>Cytokine levels in induced sputum and lung function were measured in 16 healthy control and 18 mild-moderate allergic asthmatic subjects.</p> <p>Results</p> <p>The levels of the proinflammatory biomarkers TNFα and IL-1β were not different between the control and asthmatic group. In contrast, IL-6 levels were specifically elevated in asthmatic subjects compared with healthy controls (p < 0.01). Hierarchical regression analysis in the total study cohort indicates that the relationship between asthma and lung function could be mediated by IL-6. Among Th2 cytokines only IL-13 (p < 0.05) was also elevated in the asthmatic group, and positively correlated with IL-6 levels (r_S= 0.53, p < 0.05).</p> <p>Conclusions</p> <p>In mild-moderate asthma, IL-6 dissociates from other proinflammatory biomarkers, but correlates with IL-13 levels. Furthermore, IL-6 may contribute to impaired lung function in allergic asthma.</p

IL-22 Production Is Regulated by IL-23 During Listeria monocytogenes Infection but Is Not Required for Bacterial Clearance or Tissue Protection

Listeria monocytogenes (LM) is a gram-positive bacterium that is a common contaminant of processed meats and dairy products. In humans, ingestion of LM can result in intracellular infection of the spleen and liver, which can ultimately lead to septicemia, meningitis, and spontaneous abortion. Interleukin (IL)-23 is a cytokine that regulates innate and adaptive immune responses by inducing the production of IL-17A, IL-17F, and IL-22. We have recently demonstrated that the IL-23/IL-17 axis is required for optimal recruitment of neutrophils to the liver, but not the spleen, during LM infection. Furthermore, these cytokines are required for the clearance of LM during systemic infection. In other infectious models, IL-22 induces the secretion of anti-microbial peptides and protects tissues from damage by preventing apoptosis. However, the role of IL-22 has not been thoroughly investigated during LM infection. In the present study, we show that LM induces the production of IL-22 in vivo. Interestingly, IL-23 is required for the production of IL-22 during primary, but not secondary, LM infection. Our findings suggest that IL-22 is not required for clearance of LM during primary or secondary infection, using both systemic and mucosal models of infection. IL-22 is also not required for the protection of LM infected spleens and livers from organ damage. Collectively, these data indicate that IL-22 produced during LM infection must play a role other than clearance of LM or protection of tissues from pathogen- or immune-mediated damage