The molecular mechanism of induction of unfolded protein response by Chlamydia

The unfolded protein response (UPR) contributes to chlamydial pathogenesis, as a source of lipids and ATP during replication, and for establishing the initial anti-apoptotic state of host cell that ensures successful inclusion development. The molecular mechanism(s) of UPR induction by Chlamydia is unknown. Chlamydia use type III secretion system (T3SS) effector proteins (e.g, the Translocated Actin-Recruiting Phosphoprotein (Tarp) to stimulate host cell's cytoskeletal reorganization that facilitates invasion and inclusion development. We investigated the hypothesis that T3SS effector-mediated assembly of myosin-II complex produces activated non-muscle myosin heavy chain II (NMMHC-II), which then binds the UPR master regulator (BiP) and/or transducers to induce UPR. Our results revealed the interaction of the chlamydial effector proteins (CT228 and Tarp) with components of the myosin II complex and UPR regulator and transducer during infection. These interactions caused the activation and binding of NMMHC-II to BiP and IRE1α leading to UPR induction. In addition, specific inhibitors of myosin light chain kinase, Tarp oligomerization and myosin ATPase significantly reduced UPR activation and Chlamydia replication. Thus, Chlamydia induce UPR through T3SS effector-mediated activation of NMMHC-II components of the myosin complex to facilitate infectivity. The finding provides greater insights into chlamydial pathogenesis with the potential to identify therapeutic targets and formulations.     

A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens

1. Download high-res image (279KB)
2. Download full-size image

     

Inhibition of CYP2E1 attenuates myocardial dysfunction in a murine model of insulin resistance through NLRP3-mediated regulation of mitophagy

Insulin resistance leads to myocardial contractile dysfunction and deranged autophagy although the underlying mechanism or targeted therapeutic strategy is still lacking. This study was designed to examine the impact of inhibition of the cytochrome P450 2E1 (CYP2E1) enzyme on myocardial function and mitochondrial autophagy (mitophagy) in an Akt2 knockout model of insulin resistance. Adult wild-type (WT) and Akt2^?/? mice were treated with the CYP2E1 inhibitor diallyl sulfide (100?mg/kg/d, i.p.) for 4?weeks. Cardiac geometry and function were assessed using echocardiographic and IonOptix systems. Western blot analysis was used to evaluate autophagy, mitophagy, inducible NOS (iNOS), and the NLRP3 inflammasome, a multi-protein intracellular pattern recognition receptor complex. Akt2 deletion triggered insulin resistance, compromised cardiac contractile and intracellular Ca²⁺ property, mitochondrial ultrastructural damage, elevated O2^– production, as well as suppressed autophagy and mitophagy, accompanied with elevated levels of NLRP3 and iNOS, the effects of which were significantly attenuated or ablated by diallyl sulfide. In vitro studies revealed that the NLRP3 activator nigericin nullified diallyl sulfide-offered benefit against Akt2 knockout on cardiomyocyte mechanical function and mitophagy (using Western blot and colocalization of GFP-LC3 and MitoTracker Red). Moreover, inhibition of iNOS but not mitochondrial ROS production attenuated Akt2 deletion-induced activation of NLRP3, substantiating a role for iNOS-mediated NLRP3 in insulin resistance-induced changes in mitophagy and cardiac dysfunction. In conclusion, these data depict that insulin resistance through CYP2E1 may contribute to the pathogenesis of myopathic changes including myocardial contractile dysfunction, oxidative stress and mitochondrial injury, possibly through activation of iNOS and NLRP3 signaling.     

Use of behavioral measures to assess reproductive status in maned wolves (Chrysocyon brachyurus)

Captive breeding efforts of the threatened maned wolf (Chrysocyon brachyurus) have been plagued by a lack of reliable reproduction and a high rate of neonatal mortality. A particular problem for animal managers has been the ability to detect pregnancy in a noninvasive manner. Pseudopregnancies are common, and many staff hours are expended preparing for a birth that may not occur. The objectives of our study were to document changes in behavior during the breeding season in captive maned wolves in order to determine if behaviors other than sexual (i.e., copulation) could be used to distinguish nonbreeding from breeding pairs and, further, whether successful breeding pairs (young born) could be distinguished behaviorally from breeding pairs that did not produce young (pseudopregnant). Between 1988 and 1994, behavioral data were collected during the annual reproductive season from 52 maned wolf pairings (27 males, 26 females) housed at 17 North American institutions. Breeding animals showed significant increases in rates of affiliative behaviors (approach, friendly) and the amount of time spent in close association (social) during the estrous period, compared to pre- and post-estrous periods. In contrast, the behavior of nonbreeding pairs varied little throughout the breeding season. Discriminant function analysis (DFA) showed that several behavioral measurements during certain reproductive periods were useful in discriminating between nonbreeding and breeding animals (rates of friendly and social behavior for males, marking and social behavior for females). Unsuccessful (pseudopregnant) and successful breeding pairs could be further distinguished on the basis of agonistic and approach behavior frequencies (successful females showed higher rates of agonistic and lower rates of approach behavior during certain periods; successful males had higher rates of both behaviors). Discriminant equations for key behavioral measurements and examples of their practical application are presented. DFA provides animal managers with an effective, noninvasive technique for assessing the reproductive status of maned wolf pairs. © 1996 Wiley-Liss, Inc.     

Classifying behavior from short‐interval biologging data: An example with GPS tracking of birds

1. Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.
2. We apply a framework for using K‐means clustering to classify bird behavior using points from short time interval GPS tracks. K‐means clustering is a well‐known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K‐means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free‐flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life‐stage‐ and age‐related variation in behavior.
3. After filtering for data quality, the K‐means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non‐moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.
4. The K‐means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short‐interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high‐dimensional movement data, it provides insight into small‐scale variation in behavior that would not be possible with many other analytical approaches.

     

Pharmacological and genetic activation of cAMP synthesis disrupts cholesterol utilization in Mycobacterium tuberculosis

There is a growing appreciation for the idea that bacterial utilization of host-derived lipids, including cholesterol, supports Mycobacterium tuberculosis (Mtb) pathogenesis. This has generated interest in identifying novel antibiotics that can disrupt cholesterol utilization by Mtb in vivo. Here we identify a novel small molecule agonist (V-59) of the Mtb adenylyl cyclase Rv1625c, which stimulates 3’, 5’-cyclic adenosine monophosphate (cAMP) synthesis and inhibits cholesterol utilization by Mtb. Similarly, using a complementary genetic approach that induces bacterial cAMP synthesis independent of Rv1625c, we demonstrate that inducing cAMP synthesis is sufficient to inhibit cholesterol utilization in Mtb. Although the physiological roles of individual adenylyl cyclase enzymes in Mtb are largely unknown, here we demonstrate that the transmembrane region of Rv1625c is required during cholesterol metabolism. Finally, the pharmacokinetic properties of Rv1625c agonists have been optimized, producing an orally-available Rv1625c agonist that impairs Mtb pathogenesis in infected mice. Collectively, this work demonstrates a role for Rv1625c and cAMP signaling in controlling cholesterol metabolism in Mtb and establishes that cAMP signaling can be pharmacologically manipulated for the development of new antibiotic strategies.