Genome wide analysis of the complete GlnR nitrogen-response regulon in Mycobacterium smegmatis

BACKGROUND: Nitrogen is an essential element for bacterial growth and an important component of biological macromolecules. Consequently, responding to nitrogen limitation is critical for bacterial survival and involves the interplay of signalling pathways and transcriptional regulation of nitrogen assimilation and scavenging genes. In the soil dwelling saprophyte Mycobacterium smegmatis the OmpR-type response regulator GlnR is thought to mediate the transcriptomic response to nitrogen limitation. However, to date only ten genes have been shown to be in the GlnR regulon, a vastly reduced number compared to other organisms. RESULTS: We investigated the role of GlnR in the nitrogen limitation response and determined the entire GlnR regulon, by combining expression profiling of M. smegmatis wild type and glnR deletion mutant, with GlnR-specific chromatin immunoprecipitation and high throughput sequencing. We identify 53 GlnR binding sites during nitrogen limitation that control the expression of over 100 genes, demonstrating that GlnR is the regulator controlling the assimilation and utilisation of nitrogen. We also determine a consensus GlnR binding motif and identify key residues within the motif that are required for specific GlnR binding. CONCLUSIONS: We have demonstrated that GlnR is the global nitrogen response regulator in M. smegmatis, directly regulating the expression of more than 100 genes. GlnR controls key nitrogen stress survival processes including primary nitrogen metabolism pathways, the ability to utilise nitrate and urea as alternative nitrogen sources, and the potential to use cellular components to provide a source of ammonium. These studies further our understanding of how mycobacteria survive nutrient limiting conditions

Marine Copepods, The Wildebeest of the Ocean

Copepods are amongst the most abundant animals on our planet. Who knew?! These small (typically 1–10 mm) crustaceans are found in all of the world’s oceans and play an important role in regulating Earth’s climate. Like wildebeest in the Serengeti graze on grasslands and are food for lions, herbivorous copepods represent a vital link in oceanic food chains between microscopic algae and higher predators, such as fish, birds, and whales. A group of copepods called Calanus are particularly important in the Northern Hemisphere. These tiny-but-mighty animals also share the wildebeest’s need to make a large annual migration—but in their case, they sink thousands of meters downwards to spend the winter in the deep, dark ocean. Understanding the lives of marine copepods, and how their populations will respond to climate change, is crucial for predicting the future health of the marine environment and how it helps our planet

Halo Mass Functions in Early Dark Energy Cosmologies

We examine the linear density contrast at collapse time, $\delta_c$ for large-scale structure in dynamical dark energy cosmologies, including models with early dark energy. Contrary to previous results, we find that as long as dark energy is homogeneous on small scales, $\delta_c$ is insensitive to dark energy properties for parameter values fitting current data, including the case of early dark energy. This is significant since using the correct $\delta_c$ is crucial for accurate Press-Schechter prediction of the halo mass function. Previous results have found an apparent failing of the extended Press-Schechter approach (Sheth-Tormen) for early dark energy. Our calculations demonstrate that with the correct $\delta_c$ the accuracy of this approach is restored. We discuss the significance of this result for the halo mass function and examine what dark energy physics would be needed to cause significant change in $\delta_c$, and the observational signatures this would leave.Comment: 5 pages, 2 figures. Accepted for MNRAS Letter

Can Early Dark Energy be Detected in Non-Linear Structure?

We present the first study of early dark energy cosmologies using N-body simulations to investigate the formation of non-linear structure. In contrast to expectations from semi-analytic approaches, we find that early dark energy does not imprint a unique signature on the statistics of non-linear structures. Investigating the non-linear power spectra and halo mass functions, we show that universal mass functions hold for early dark energy, making its presence difficult to distinguish from $\Lambda$CDM. Since early dark energy biases the baryon acoustic oscillation scale, the lack of discriminating power is problematic.Comment: 11 pages, 19 figures. Minor changes to match version accepted to MNRA

Detection and extraction of signals from the epoch of reionization using higher-order one-point statistics

Detecting redshifted 21-cm emission from neutral hydrogen in the early Universe promises to give direct constraints on the epoch of reionization (EoR). It will, though, be very challenging to extract the cosmological signal (CS) from foregrounds and noise which are orders of magnitude larger. Fortunately, the signal has some characteristics which differentiate it from the foregrounds and noise, and we suggest that using the correct statistics may tease out signatures of reionization. We generate mock data cubes simulating the output of the Low Frequency Array (LOFAR) EoR experiment. These cubes combine realistic models for Galactic and extragalactic foregrounds and the noise with three different simulations of the CS. We fit out the foregrounds, which are smooth in the frequency direction, to produce residual images in each frequency band. We denoise these images and study the skewness of the one-point distribution in the images as a function of frequency. We find that, under sufficiently optimistic assumptions, we can recover the main features of the redshift evolution of the skewness in the 21-cm signal. We argue that some of these features ¿ such as a dip at the onset of reionization, followed by a rise towards its later stages ¿ may be generic, and give us a promising route to a statistical detection of reionization

Growth and retreat of the last British–Irish Ice Sheet, 31 000 to 15 000 years ago: the BRITICE-CHRONO reconstruction

The BRITICE-CHRONO consortium of researchers undertook a dating programme to constrain the timing of advance, maximum extent and retreat of the British–Irish Ice Sheet between 31 000 and 15 000 years before present. The dating campaign across Ireland and Britain and their continental shelves, and across the North Sea included 1500 days of field investigation yielding 18 000 km of marine geophysical data, 377 cores of sea floor sediments, and geomorphological and stratigraphical information at 121 sites on land; generating 690 new geochronometric ages. These findings are reported in 28 publications including synthesis into eight transect reconstructions. Here we build ice sheet-wide reconstructions consistent with these findings and using retreat patterns and dates for the inter-transect areas. Two reconstructions are presented, a wholly empirical version and a version that combines modelling with the new empirical evidence. Palaeoglaciological maps of ice extent, thickness, velocity, and flow geometry at thousand-year timesteps are presented. The maximum ice volume of 1.8 m sea level equivalent occurred at 23 ka. A larger extent than previously defined is found and widespread advance of ice to the continental shelf break is confirmed during the last glacial. Asynchrony occurred in the timing of maximum extent and onset of retreat, ranging from 30 to 22 ka. The tipping point of deglaciation at 22 ka was triggered by ice stream retreat and saddle collapses. Analysis of retreat rates leads us to accept our hypothesis that the marine-influenced sectors collapsed rapidly. First order controls on ice-sheet demise were glacio-isostatic loading triggering retreat of marine sectors, aided by glaciological instabilities and then climate warming finished off the smaller, terrestrial ice sheet. Overprinted on this signal were second order controls arising from variations in trough topographies and with sector-scale ice geometric readjustments arising from dispositions in the geography of the landscape. These second order controls produced a stepped deglaciation. The retreat of the British–Irish Ice Sheet is now the world’s most well-constrained and a valuable data-rich environment for improving ice-sheet modelling.publishedVersio

Understanding and managing patchy data in the UK museum sector

It is well accepted that the museum sector has a longstanding problem with data collection and management. This article begins by exploring problems with gaining access to data, poor archiving and coverage, and the absence of data. We then explain how the Mapping Museums research team set out to remedy the lack of longitudinal data on the UK museum sector in the period between 1960 and 2020. Initially we collated and supplemented existing information on UK museums but it was impossible to fill some gaps or resolve some inconsistencies in the data. Here we discuss how we designed a database that was sensitive to the patchiness of the material, and that could model uncertain and absent data in computational terms. To close, we briefly comment on how our data enables research on museum history and on how the problems with data collection in the sector might be remedied in the longer term

Inflammatory phenotypes in patients with severe asthma are associated with distinct airway microbiology

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Background Asthma pathophysiology and treatment responsiveness are predicted by inflammatory phenotype. However, the relationship between airway microbiology and asthma phenotype is poorly understood. Objective We aimed to characterize the airway microbiota in patients with symptomatic stable asthma and relate composition to airway inflammatory phenotype and other phenotypic characteristics. Methods The microbial composition of induced sputum specimens collected from adult patients screened for a multicenter randomized controlled trial was determined by using 16S rRNA gene sequencing. Inflammatory phenotypes were defined by sputum neutrophil and eosinophil cell proportions. Microbiota were defined by using α- and β-diversity measures, and interphenotype differences were identified by using similarity of percentages, network analysis, and taxon fold change. Phenotypic predictors of airway microbiology were identified by using multivariate linear regression. Results Microbiota composition was determined in 167 participants and classified as eosinophilic (n = 84), neutrophilic (n = 14), paucigranulocytic (n = 60), or mixed neutrophilic-eosinophilic (n = 9) asthma phenotypes. Airway microbiology was significantly less diverse (P = .022) and more dissimilar (P = .005) in neutrophilic compared with eosinophilic participants. Sputum neutrophil proportions, but not eosinophil proportions, correlated significantly with these diversity measures (α-diversity: Spearman r = −0.374, P < .001; β-diversity: r = 0.238, P = .002). Interphenotype differences were characterized by a greater frequency of pathogenic taxa at high relative abundance and reduced Streptococcus, Gemella, and Porphyromonas taxa relative abundance in patients with neutrophilic asthma. Multivariate regression confirmed that sputum neutrophil proportion was the strongest predictor of microbiota composition. Conclusions Neutrophilic asthma is associated with airway microbiology that is significantly different from that seen in patients with other inflammatory phenotypes, particularly eosinophilic asthma. Differences in microbiota composition might influence the response to antimicrobial and steroid therapies and the risk of lung infection

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects