Wild-type Caenorhabditis elegans isolates exhibit distinct gene expression profiles in response to microbial infection

The soil-dwelling nematode Caenorhabditis elegans serves as a model system to study innate immunity against microbial pathogens. C. elegans have been collected from around the world, where they, presumably, adapted to regional microbial ecologies. Here we use survival assays and RNA-sequencing to better understand how two isolates from disparate climates respond to pathogenic bacteria. We found that, relative to N2 (originally isolated in Bristol, UK), CB4856 (isolated in Hawaii), was more susceptible to the Gram-positive microbe, Staphylococcus epidermidis, but equally susceptible to Staphylococcus aureus as well as two Gram-negative microbes, Providencia rettgeri and Pseudomonas aeruginosa. We performed transcriptome analysis of infected worms and found gene-expression profiles were considerably different in an isolate-specific and microbe-specific manner. We performed GO term analysis to categorize differential gene expression in response to S. epidermidis. In N2, genes that encoded detoxification enzymes and extracellular matrix proteins were significantly enriched, while in CB4856, genes that encoded detoxification enzymes, C-type lectins, and lipid metabolism proteins were enriched, suggesting they have different responses to S. epidermidis, despite being the same species. Overall, discerning gene expression signatures in an isolate by pathogen manner can help us to understand the different possibilities for the evolution of immune responses within organisms

The C. elegans CHP1 homolog, pbo-1, functions in innate immunity by regulating the pH of the intestinal lumen

This work is licensed under a Creative Commons Attribution 4.0 International License.Caenorhabditis elegans are soil-dwelling nematodes and models for understanding innate immunity and infection. Previously, we developed a novel fluorescent dye (KR35) that accumulates in the intestine of C. elegans and reports a dynamic wave in intestinal pH associated with the defecation motor program. Here, we use KR35 to show that mutations in the Ca2+-binding protein, PBO-1, abrogate the pH wave, causing the anterior intestine to be constantly acidic. Surprisingly, pbo-1 mutants were also more susceptible to infection by several bacterial pathogens. We could suppress pathogen susceptibility in pbo-1 mutants by treating the animals with pH-buffering bicarbonate, suggesting the pathogen susceptibility is a function of the acidity of the intestinal pH. Furthermore, we use KR35 to show that upon infection by pathogens, the intestinal pH becomes neutral in a wild type, but less so in pbo-1 mutants. C. elegans is known to increase production of reactive oxygen species (ROS), such as H2O2, in response to pathogens, which is an important component of pathogen defense. We show that pbo-1 mutants exhibited decreased H2O2 in response to pathogens, which could also be partially restored in pbo-1 animals treated with bicarbonate. Ultimately, our results support a model whereby PBO-1 functions during infection to facilitate pH changes in the intestine that are protective to the host

Adenosine-5′-phosphosulfate - a multifaceted modulator of bifunctional 3′-phospho-adenosine-5′-phosphosulfate synthases and related enzymes

All sulfation reactions rely on active sulfate in the form of 3′-phosphoadenosine-5′-phosphosulfate (PAPS). In fungi, bacteria, and plants, the enzymes responsible for PAPS synthesis, ATP sulfurylase and adenosine-5′-phosphosulfate (APS) kinase, reside on separate polypeptide chains. In metazoans, however, bifunctional PAPS synthases catalyze the consecutive steps of sulfate activation by converting sulfate to PAPS via the intermediate APS. This intricate molecule and the related nucleotides PAPS and 3′-phospho-adenosine-5′-phosphate modulate the function of various enzymes from sulfation pathways, and these effects are summarized in this review. On the ATP sulfurylase domain that initially produces APS from sulfate and ATP, APS acts as a potent product inhibitor, being competitive with both ATP and sulfate. For the APS kinase domain that phosphorylates APS to PAPS, APS is an uncompetitive substrate inhibitor that can bind both at the ATP/ADP binding site and the PAPS/APS-binding site. For human PAPS synthase 1, the steady-state concentration of APS has been modelled to be 1.6 lM, but this may increase up to 60 lM under conditions of sulfate excess. It is noteworthy that the APS concentration for maximal APS kinase activity is 15 lM. Finally, we recognized APS as a highly specific stabilizer of bifunctional PAPS synthases. APS most likely stabilizes the APS kinase part of these proteins by forming a dead-end enzyme–ADP–APS complex at APS concentrations between 0.5 and 5 lM; at higher concentrations, APS may bind to the catalytic centers of ATP sulfurylase. Based on the assumption that cellular concentrations of APS fluctuate within this range, APS can therefore be regarded as a key modulator of PAPS synthase functions

Variations in Porosity and Permeability of the Sundance Formation, Northeast Wyoming

The Sundance Formation covers an area from Northern Montana to Northern Colorado and from Eastern Wyoming to Western Wyoming. The formation is fine- to medium- grained sandstone composed of quartz and is Upper Jurassic in age. This research focuses on the formation in the Devil’s Tower area of Northeast Wyoming. Within the formation are various facies deposited under different depositional environments, including the Stockdale Beaver Shale overlain by the Hulett Sandstone. The Stockdale Beaver Shale, primarily slope forming, is roughly 30 meters thick and was deposited in a lacustrine setting. The Hulett Sandstone, cliff forming, in roughly 15 meters thick and was deposited under a series of tidal inlet sequences. The differences in depositional environments suggest that there could be variations in the physical properties of the rock. This research focuses on porosity and permeability, how much void space, by volume, is within the rock and how connected the void spaces are, respectively. To find these two properties of the rock, samples were taken from the formation and are currently being analyzed via thin section petrography. Porosity and permeability are important characteristics. They determine how much of a fluid can be stored in the rock, and how easily a fluid can move through the rock. Knowing something about these characteristics can give insight on how the formation could function as an aquifer, and how to make decisions about drilling water and/or oil wells

Determinants of Individuals' Levels of Knowledge, Attitudes, and Decisions Regarding a Health Innovation in Maine.

Ph.D.Public administrationUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/157475/1/7619170.pd

GEFS+ mutants lack homeostatic sleep regulation.

<p><b>(A)</b> The 24 hr sleep profiles of baseline day and recovery day following 24 hr sleep deprivation in control (<i>n</i> = 81) and GEFS+ mutants (<i>n</i> = 86). <b>(B)</b> The percentage of time asleep over the 24 hr period and <b>(C)</b> subjective sleep latencies for baseline and recovery days; ANOVA on Ranks, Dunn’s compared to baseline data within genotype. <b>(D)</b> Cumulative sleep loss during 24 hr sleep deprivation and recovery. Sleep debt is presented relative to baseline sleep for each genotype. <b>(E)</b> Percent change in 24 hr sleep compared between before and after sleep deprivation; Rank Sum Test. Data presented as averages with SEM <b>(A, D)</b> or boxplot with means (“X”) <b>(B, C, E)</b>; ***p < 0.001.</p

Effect of constant and acute light during the scotophase on GEFS+ and control sleep.

<p><b>(A)</b> Sleep profiles of control (<i>n</i> = 83) and GEFS+ (<i>n</i> = 95) flies under constant light/light (LL) exposure. <b>(B)</b> Total sleep and <b>(C)</b> sleep latency during subjective night under LD and LL conditions; Rank Sum Tests. <b>(D)</b> Sleep and <b>(E)</b> activity profiles of control (<i>n</i> = 52) and GEFS+ (<i>n</i> = 59) flies subjected to a 1 hr scotophase light pulse; repeated measures ANOVA on Ranks. <b>(F)</b> Sleep latencies of control and GEFS+ flies after normal lights off (12 hr and 36 hr) and the scotophase pulse (42 hr); ANOVA on Ranks, Dunn’s vs 12 hr control. Data presented as averages with SEM (<b>A</b>, <b>D</b> and <b>E</b>) or boxplots with means (“X”) (<b>B</b>, <b>C</b> and <b>F</b>); ***p < 0.001.</p

GEFS+ mutation affects sleep/wake behavior.

<p><b>(A)</b> The 24 hr activity profiles, <b>(B)</b> 12 hr LD activity counts, and <b>(C)</b> 24 hr sleep profiles of virgin females (☿), mated females (♀), and males (♂) for knock-in controls (<i>n</i> = 85, 93, 95) and GEFS+ mutants (<i>n</i> = 88, 87, 94). <b>(D)</b> Nighttime 12 hr sleep/activity parameters of mated females for control (<i>n</i> = 93), GEFS+ heterozygotes (<i>n</i> = 44), and GEFS+ homozygotes (<i>n</i> = 87). Data are presented as averages with SEM for <b>(A, C)</b> or boxplots with means (“X”) for <b>(B, D)</b>. ANOVA on Ranks, Dunn’s compared to control; *p < 0.05, ***p < 0.001.</p

Exaggerated Nighttime Sleep and Defective Sleep Homeostasis in a <i>Drosophila</i> Knock-In Model of Human Epilepsy

<div><p>Despite an established link between epilepsy and sleep behavior, it remains unclear how specific epileptogenic mutations affect sleep and subsequently influence seizure susceptibility. Recently, Sun <i>et al</i>. (2012) created a fly knock-in model of human generalized epilepsy with febrile seizures plus (GEFS+), a wide-spectrum disorder characterized by fever-associated seizing in childhood and lifelong affliction. GEFS+ flies carry a disease-causing mutation in their voltage-gated sodium channel (VGSC) gene and display semidominant heat-induced seizing, likely due to reduced GABAergic inhibitory activity at high temperature. Here, we show that at room temperature the GEFS+ mutation dominantly modifies sleep, with mutants exhibiting rapid sleep onset at dusk and increased nighttime sleep as compared to controls. These characteristics of GEFS+ sleep were observed regardless of sex, mating status, and genetic background. GEFS+ mutant sleep phenotypes were more resistant to pharmacologic reduction of GABA transmission by carbamazepine (CBZ) than controls, and were mitigated by reducing GABA_A receptor expression specifically in wake-promoting pigment dispersing factor (PDF) neurons. These findings are consistent with increased GABAergic transmission to PDF neurons being mainly responsible for the enhanced nighttime sleep of GEFS+ mutants. Additionally, analyses under other light conditions suggested that the GEFS+ mutation led to reduced buffering of behavioral responses to light on and off stimuli, which contributed to characteristic GEFS+ sleep phenotypes. We further found that GEFS+ mutants had normal circadian rhythms in free-running dark conditions. Interestingly, the mutants lacked a homeostatic rebound following mechanical sleep deprivation, and whereas deprivation treatment increased heat-induced seizure susceptibility in control flies, it unexpectedly reduced seizure activity in GEFS+ mutants. Our study has revealed the sleep architecture of a <i>Drosophila</i> VGSC mutant that harbors a human GEFS+ mutation, and provided unique insight into the relationship between sleep and epilepsy.</p></div

<i>Rdl</i> GABA_A knockdown in PDF-positive neurons differentially influences sleep latency in GEFS+ mutants.

<p><b>(A, B)</b><i>Rdl</i> knockdown in PDF neurons of control and heterozygous GEFS+ mutants; +<i>/Rdl-RNAi</i> (<i>n</i> = 55), <i>pdf-GAL4/Rdl-RNAi</i> (<i>n</i> = 49), <i>GEFS+/+;</i> +<i>/Rdl-RNAi</i> (<i>n</i> = 56), <i>GEFS+/+; pdf-GAL4/Rdl-RNAi</i> (<i>n</i> = 38). <b>(A)</b><i>Rdl</i> knockdown in PDF neurons reduced sleep to the same extent in both control and GEFS+ flies. <b>(B)</b><i>Rdl</i> knockdown in PDF neurons specifically increased sleep latencies in heterozygous GEFS+ mutants (but not in control flies), restoring the GEFS+ short sleep latencies to control levels; ANOVA on Ranks, Dunn’s Multiple Comparisons. To determine the extent of change caused by <i>Rdl</i> knockdown, differences within a genotype were calculated by subtracting experimental data to the averages of RNAi only controls; Rank Sum Test. All data presented as boxplots with means (“X”); **p < 0.01, ***p < 0.001.</p