Genetic Basis of Ammonium Toxicity Resistance in a Sake Strain of Yeast: A Mendelian Case.

High concentrations of ammonium at physiological concentrations of potassium are toxic for the standard laboratory strain of Saccharomyces cerevisiae In the original description of this metabolic phenotype, we focused on the standard laboratory strains of Saccharomyces In this study, we screened a large collection of S. cerevisiae natural isolates and identified one strain that is resistant to high concentrations of ammonium. This strain, K12, was isolated in sake breweries. When the K12 strain was crossed to the standard laboratory strain (FY4), the resulting tetrads displayed 2:2 segregation of the resistance phenotype, suggesting a single gene trait. Using a bulk segregant analysis strategy, we mapped this trait to a 150-kb region on chromosome X containing the TRK1 gene. This gene encodes a transporter required for high-affinity potassium transport in S. cerevisiae Data from reciprocal hemizygosity experiments with TRK1 deletion strains in K12 and BY backgrounds, as well as analysis of the deletion of this gene in the K12 strain, demonstrate that the K12 allele of TRK1 is responsible for ammonium toxicity resistance. Furthermore, we determined the minimal amount of potassium required for both the K12 and laboratory strain needed for growth. These results demonstrate that the gene encoded by the K12 allele of TRK1 has a greater affinity for potassium than the standard allele of TRK1 found in Saccharomyces strains. We hypothesize that this greater-affinity allele of the potassium transporter reduces the flux of ammonium into the yeast cells under conditions of ammonium toxicity. These findings further refine our understanding of ammonium toxicity in yeast and provide an example of using natural variation to understand cellular processes

Anisotropy and periodicity in the density distribution of electrons in a quantum-well

We use low temperature near-field optical spectroscopy to image the electron density distribution in the plane of a high mobility GaAs quantum well. We find that the electrons are not randomly distributed in the plane, but rather form narrow stripes (width smaller than 150 nm) of higher electron density. The stripes are oriented along the [1-10 ] crystal direction, and are arranged in a quasi-periodic structure. We show that elongated structural mounds, which are intrinsic to molecular beam epitaxy, are responsible for the creation of this electron density texture.Comment: 10 pages, 3 figure

Near-field spectroscopy of a gated electron gas: a direct evidence for electrons localization

The near-field photoluminescence of a gated two-dimensional electron gas is measured. We use the negatively charged exciton, formed by binding of an electron to a photo-excited electron-hole pair, as an indicator for the local presence of charge. Large spatial fluctuations in the luminescence intensity of the negatively charged exciton are observed. These fluctuations are shown to be due to electrons localized in the random potential of the remote ionized donors. We use these fluctuations to image the electrons and donors distribution in the plane.Comment: 10 pages, 5 figures, to be published in PR

74 MHz Discrete HII Absorption Regions Towards The Inner Galaxy

At low radio frequencies (< 100 MHz), classical HII regions may become optically thick (optical depth > 1) and can be observed as discrete absorption regions against the Galactic nonthermal background emission created by Galactic cosmic ray electrons spiraling around magnetic fields. In this work we present 74 MHz observations in the region 26>l>-15, -5<b<5, and report the detection of 92 absorption features associated with known HII regions, and derive the brightness temperature of the Galactic cosmic ray electron synchrotron emission emanating from the column behind these regions. For the 42 HII regions with known distances, the average emissivity of the column behind the HII region is derived. 74 MHz emissivity values range between 0.3 and 1.0 Kelvin per parsec for a model assuming uniform distribution of emissivity. Methods for utilizing this type of data to model the 3-dimensional distribution of cosmic ray emissivity and the possibility of using this method to break the HII region kinematic distance degeneracy are discussed.Comment: Accepted, The Astronomical Journa

Abnormal social reward processing in autism as indexed by pupillary responses to happy faces

Background: Individuals with Autism Spectrum Disorders (ASD) typically show impaired eye contact during social interactions. From a young age, they look less at faces than typically developing (TD) children and tend to avoid direct gaze. However, the reason for this behavior remains controversial; ASD children might avoid eye contact because they perceive the eyes as aversive or because they do not find social engagement through mutual gaze rewarding. Methods: We monitored pupillary diameter as a measure of autonomic response in children with ASD (n = 20, mean age = 12.4) and TD controls (n = 18, mean age = 13.7) while they looked at faces displaying different emotions. Each face displayed happy, fearful, angry or neutral emotions with the gaze either directed to or averted from the subjects. Results: Overall, children with ASD and TD controls showed similar pupillary responses; however, they differed significantly in their sensitivity to gaze direction for happy faces. Specifically, pupillary diameter increased among TD children when viewing happy faces with direct gaze as compared to those with averted gaze, whereas children with ASD did not show such sensitivity to gaze direction. We found no group differences in fixation that could explain the differential pupillary responses. There was no effect of gaze direction on pupil diameter for negative affect or neutral faces among either the TD or ASD group. Conclusions: We interpret the increased pupillary diameter to happy faces with direct gaze in TD children to reflect the intrinsic reward value of a smiling face looking directly at an individual. The lack of this effect in children with ASD is consistent with the hypothesis that individuals with ASD may have reduced sensitivity to the reward value of social stimuli

Ammonium Toxicity and Potassium Limitation in Yeast

DNA microarray analysis of gene expression in steady-state chemostat cultures limited for potassium revealed a surprising connection between potassium and ammonium: potassium limits growth only when ammonium is the nitrogen source. Under potassium limitation, ammonium appears to be toxic for Saccharomyces cerevisiae. This ammonium toxicity, which appears to occur by leakage of ammonium through potassium channels, is recapitulated under high-potassium conditions by over-expression of ammonium transporters. Although ammonium toxicity is well established in metazoans, it has never been reported for yeast. To characterize the response to ammonium toxicity, we examined the filtrates of these cultures for compounds whose excretion might serve to detoxify the ammonium (such as urea in mammals). Using liquid chromatography–tandem mass spectrometry to assay for a wide array of metabolites, we detected excreted amino acids. The amounts of amino acids excreted increased in relation to the severity of growth impairment by ammonium, suggesting that amino acid excretion is used by yeast for ammonium detoxification

Objective assessment of stored blood quality by deep learning

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans’ assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis

S-Nitrosylation of Surfactant Protein-D Controls Inflammatory Function

The pulmonary collectins, surfactant proteins A and D (SP-A and SP-D) have been implicated in the regulation of the innate immune system within the lung. In particular, SP-D appears to have both pro- and anti-inflammatory signaling functions. At present, the molecular mechanisms involved in switching between these functions remain unclear. SP-D differs in its quaternary structure from SP-A and the other members of the collectin family, such as C1q, in that it forms large multimers held together by the N-terminal domain, rather than aligning the triple helix domains in the traditional “bunch of flowers” arrangement. There are two cysteine residues within the hydrophobic N terminus of SP-D that are critical for multimer assembly and have been proposed to be involved in stabilizing disulfide bonds. Here we show that these cysteines exist within the reduced state in dodecameric SP-D and form a specific target for S-nitrosylation both in vitro and by endogenous, pulmonary derived nitric oxide (NO) within a rodent acute lung injury model. S-nitrosylation is becoming increasingly recognized as an important post-translational modification with signaling consequences. The formation of S-nitrosothiol (SNO)-SP-D both in vivo and in vitro results in a disruption of SP-D multimers such that trimers become evident. SNO-SP-D but not SP-D, either dodecameric or trimeric, is chemoattractive for macrophages and induces p38 MAPK phosphorylation. The signaling capacity of SNO-SP-D appears to be mediated by binding to calreticulin/CD91. We propose that NO controls the dichotomous nature of this pulmonary collectin and that posttranslational modification by S-nitrosylation causes quaternary structural alterations in SP-D, causing it to switch its inflammatory signaling role. This represents new insight into both the regulation of protein function by S-nitrosylation and NO's role in innate immunity

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts