A screen for nuclear transcripts identifies two linked noncoding RNAs associated with SC35 splicing domains

BACKGROUND: Noncoding RNA species play a diverse set of roles in the eukaryotic cell. While much recent attention has focused on smaller RNA species, larger noncoding transcripts are also thought to be highly abundant in mammalian cells. To search for large noncoding RNAs that might control gene expression or mRNA metabolism, we used Affymetrix expression arrays to identify polyadenylated RNA transcripts displaying nuclear enrichment. RESULTS: This screen identified no more than three transcripts; XIST, and two unique noncoding nuclear enriched abundant transcripts (NEAT) RNAs strikingly located less than 70 kb apart on human chromosome 11: NEAT1, a noncoding RNA from the locus encoding for TncRNA, and NEAT2 (also known as MALAT-1). While the two NEAT transcripts share no significant homology with each other, each is conserved within the mammalian lineage, suggesting significant function for these noncoding RNAs. NEAT2 is extraordinarily well conserved for a noncoding RNA, more so than even XIST. Bioinformatic analyses of publicly available mouse transcriptome data support our findings from human cells as they confirm that the murine homologs of these noncoding RNAs are also nuclear enriched. RNA FISH analyses suggest that these noncoding RNAs function in mRNA metabolism as they demonstrate an intimate association of these RNA species with SC35 nuclear speckles in both human and mouse cells. These studies show that one of these transcripts, NEAT1 localizes to the periphery of such domains, whereas the neighboring transcript, NEAT2, is part of the long-sought polyadenylated component of nuclear speckles. CONCLUSION: Our genome-wide screens in two mammalian species reveal no more than three abundant large non-coding polyadenylated RNAs in the nucleus; the canonical large noncoding RNA XIST and NEAT1 and NEAT2. The function of these noncoding RNAs in mRNA metabolism is suggested by their high levels of conservation and their intimate association with SC35 splicing domains in multiple mammalian species

Reply to van Hoorn: Converging lines of evidence

We agree with the comments by van Hoorn (1) on our critique (2): testing causal hypotheses about human behavior is a challenge (1, 3). Making progress requires specifying alternative hypotheses and then testing these hypotheses using diverse and converging lines of evidence. We have defended the hypothesis that social norms, which culturally coevolved with the institutions of large-scale societies including markets, influence economic decision-making. This hypothesis emerged from a larger set that we developed both at the outset of our project and as we went along. Our interdisciplinary team’s initial list of hypotheses included the idea that experimental games might spark an innate reciprocity module that would yield little variation across populations

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

From Many Hosts, One Accidental Pathogen: The Diverse Protozoan Hosts of Legionella

The 1976 outbreak of Legionnaires' disease led to the discovery of the intracellular bacterial pathogen Legionella pneumophila. Given their impact on human health, Legionella species and the mechanisms responsible for their replication within host cells are often studied in alveolar macrophages, the primary human cell type associated with disease. Despite the potential severity of individual cases of disease, Legionella are not spread from person-to-person. Thus, from the pathogen's perspective, interactions with human cells are accidents of time and space—evolutionary dead ends with no impact on Legionella's long-term survival or pathogenic trajectory. To understand Legionella as a pathogen is to understand its interaction with its natural hosts: the polyphyletic protozoa, a group of unicellular eukaryotes with a staggering amount of evolutionary diversity. While much remains to be understood about these enigmatic hosts, we summarize the current state of knowledge concerning Legionella's natural host range, the diversity of Legionella-protozoa interactions, the factors influencing these interactions, the importance of avoiding the generalization of protozoan-bacterial interactions based on a limited number of model hosts and the central role of protozoa to the biology, evolution, and persistence of Legionella in the environment

Some of the pathogenic characteristics explored by laboratory passage models.

<p>Examples of the application of experimental evolution to the study of pathogens include modeling the evolution of drug resistance <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Almahmoud1" target="_blank">[18]</a>–<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Wong1" target="_blank">[20]</a>, trade-offs between generalist versus specialist adaptations to the host <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Ensminger1" target="_blank">[9]</a>, <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Deardorff1" target="_blank">[12]</a>, pathogen transmission <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Herfst1" target="_blank">[13]</a>, <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Imai1" target="_blank">[14]</a>, and biofilm formation <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003340#ppat.1003340-Traverse1" target="_blank">[17]</a>.</p

Considerations in designing a laboratory passage experiment.

<p>Considerations in designing a laboratory passage experiment.</p

Type I-F CRISPR-Cas Distribution and Array Dynamics in Legionella pneumophila

In bacteria and archaea, several distinct types of CRISPR-Cas systems provide adaptive immunity through broadly similar mechanisms: short nucleic acid sequences derived from foreign DNA, known as spacers, engage in complementary base pairing with invasive genetic elements setting the stage for nucleases to degrade the target DNA. A hallmark of type I CRISPR-Cas systems is their ability to acquire spacers in response to both new and previously encountered invaders (naïve and primed acquisition, respectively). Our phylogenetic analyses of 43 L. pneumophila type I-F CRISPR-Cas systems and their resident genomes suggest that many of these systems have been horizontally acquired. These systems are frequently encoded on plasmids and can co-occur with nearly identical chromosomal loci. We show that two such co-occurring systems are highly protective and undergo efficient primed acquisition in the lab. Furthermore, we observe that targeting by one system’s array can prime spacer acquisition in the other. Lastly, we provide experimental and genomic evidence for a model in which primed acquisition can efficiently replenish a depleted type I CRISPR array following a mass spacer deletion event

Legionella pneumophila Philadelphia-1 clinical genome (GenBank format)

GenBank formatted file derived from editing NC_002942 (Legionella pneumophila subsp. pneumophila str. Philadelphia 1). Corrects several discrepancies between the 1976 Philadelphia isolate given to the Isberg laboratory by Barry Fields and the original sequence