A simian hemorrhagic fever virus isolate from persistently infected baboons efficiently induces hemorrhagic fever disease in Japanese macaques

Simian hemorrhagic fever virus is an arterivirus that naturally infects species of African nonhuman primates causing acute or persistent asymptomatic infections. Although it was previously estimated that 1% of baboons are SHFV-positive, more than 10% of wild-caught and captive-bred baboons tested were SHFV positive and the infections persisted for more than 10 years with detectable virus in the blood (100–1000 genomes/ml). The sequences of two baboon SHFV isolates that were amplified by a single passage in primary macaque macrophages showed a very high degree of identity to each other as well as to the genome of SHFV-LVR, a laboratory strain isolated in the 1960s. Infection of Japanese macaques with 100 PFU of a baboon isolate consistently produced high level viremia, pro-inflammatory cytokines, elevated tissue factor levels and clinical signs indicating coagulation defects. The baboon virus isolate provides a reliable BSL2 model of viral hemorrhagic fever disease in macaques

A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division

Upstream events that trigger initiation of cell division, at a point called START in yeast, determine the overall rates of cell proliferation. The identity and complete sequence of those events remain unknown. Previous studies relied mainly on cell size changes to identify systematically genes required for the timely completion of START. Here, we evaluated panels of non-essential single gene deletion strains for altered DNA content by flow cytometry. This analysis revealed that most gene deletions that altered cell cycle progression did not change cell size. Our results highlight a strong requirement for ribosomal biogenesis and protein synthesis for initiation of cell division. We also identified numerous factors that have not been previously implicated in cell cycle control mechanisms. We found that CBS, which catalyzes the synthesis of cystathionine from serine and homocysteine, advances START in two ways: by promoting cell growth, which requires CBS's catalytic activity, and by a separate function, which does not require CBS's catalytic activity. CBS defects cause disease in humans, and in animals CBS has vital, non-catalytic, unknown roles. Hence, our results may be relevant for human biology. Taken together, these findings significantly expand the range of factors required for the timely initiation of cell division. The systematic identification of non-essential regulators of cell division we describe will be a valuable resource for analysis of cell cycle progression in yeast and other organisms

Comparative Genomic Analysis of Human Fungal Pathogens Causing Paracoccidioidomycosis

Paracoccidioides is a fungal pathogen and the cause of paracoccidioidomycosis, a health-threatening human systemic mycosis endemic to Latin America. Infection by Paracoccidioides, a dimorphic fungus in the order Onygenales, is coupled with a thermally regulated transition from a soil-dwelling filamentous form to a yeast-like pathogenic form. To better understand the genetic basis of growth and pathogenicity in Paracoccidioides, we sequenced the genomes of two strains of Paracoccidioides brasiliensis (Pb03 and Pb18) and one strain of Paracoccidioides lutzii (Pb01). These genomes range in size from 29.1 Mb to 32.9 Mb and encode 7,610 to 8,130 genes. To enable genetic studies, we mapped 94% of the P. brasiliensis Pb18 assembly onto five chromosomes. We characterized gene family content across Onygenales and related fungi, and within Paracoccidioides we found expansions of the fungal-specific kinase family FunK1. Additionally, the Onygenales have lost many genes involved in carbohydrate metabolism and fewer genes involved in protein metabolism, resulting in a higher ratio of proteases to carbohydrate active enzymes in the Onygenales than their relatives. To determine if gene content correlated with growth on different substrates, we screened the non-pathogenic onygenale Uncinocarpus reesii, which has orthologs for 91% of Paracoccidioides metabolic genes, for growth on 190 carbon sources. U. reesii showed growth on a limited range of carbohydrates, primarily basic plant sugars and cell wall components; this suggests that Onygenales, including dimorphic fungi, can degrade cellulosic plant material in the soil. In addition, U. reesii grew on gelatin and a wide range of dipeptides and amino acids, indicating a preference for proteinaceous growth substrates over carbohydrates, which may enable these fungi to also degrade animal biomass. These capabilities for degrading plant and animal substrates suggest a duality in lifestyle that could enable pathogenic species of Onygenales to transfer from soil to animal hosts.National Institute of Allergy and Infectious Diseases (U.S.)National Institutes of Health. Department of Health and Human Services (contract HHSN266200400001C)National Institutes of Health. Department of Health and Human Services(contract HHSN2722009000018C)Brazil. National Council for Scientific and Technological Developmen

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Decreased fitness correlates with altered cell cycle progression.

<p>The y-axis shows the fitness values of Giaever et al <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Giaever1" target="_blank">[33]</a>. Higher values indicate reduced fitness. The cutoff for reduced fitness was about <85% of the wild type in that study <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Giaever1" target="_blank">[33]</a>. Thus, strains with possible small reductions in fitness have been assigned a “WT-like” fitness score of 1. Giaever et al <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Giaever1" target="_blank">[33]</a> evaluated fitness of the same strains we used, during growth in rich (YPD-2%Dextrose) liquid media, allowing for a direct comparison with our dataset. We used the non-parametric Spearman test to obtain the correlation (<i>r</i>) values we show. The correlation coefficient for all the strains (<i>r</i>_T) is shown at the bottom right of the graph. We colored the r values for the sub-groups as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen-1002590-g002" target="_blank">Figure 2</a>. For every gene we included in this analysis, the values we used in this correlation are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s001" target="_blank">Dataset S1</a>.</p

Schematic overview of our approach.

<p>For a detailed description of all the protocols we used, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#s4" target="_blank">Methods</a>.</p

Network representation of the “Low G1” group.

<p>The interactions shown are from the gold-standard reference database BioGRID <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Stark1" target="_blank">[54]</a>. The network was constructed with Cytoscape <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Smoot1" target="_blank">[83]</a>, and displayed using an unbiased, force-generated layout. Only the factors that showed interactions (physical or functional) are included. We also included the essential gene <i>CDC28</i> (shown in red), encoding the major yeast Cdk.</p

Cys4p advances START both by promoting cell growth and by a separate function, which does not require CBS's catalytic activity.

<p>A, Rate of cell size increase (shown as growth rate, in fl/min) for the indicated strains was measured assuming linear growth from synchronous elutriated cultures in media that contain galactose and induce expression of the <i>P_GAL</i> alleles (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#s4" target="_blank">Methods</a>). The average value for each strain is shown with a horizontal bar (± sd). Where indicated, the <i>P</i> values shown were calculated from two-tailed <i>t</i> tests. The data used to calculate the values shown in A and B are in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s009" target="_blank">Figure S8</a>. B, The critical cell size of the indicated strains (shown in fl), was measured from the same elutriation experiments shown in A (see also <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s010" target="_blank">Figure S9</a>). The analogous experiments in non-inducing, glucose containing, medium are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590.s010" target="_blank">Figure S9</a>.</p

Interactions among the factors of the “High G1” group.

<p>The network of interactions was constructed and displayed as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen-1002590-g007" target="_blank">Figure 7</a>. We also included factors with known roles at START (shown in red), which were not identified in our study. Among the G1 cyclins, we only included Cln3p, which is responsible for initiating the positive feedback loop of the large G1/S transcriptional program <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Skotheim1" target="_blank">[10]</a>–<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002590#pgen.1002590-Doncic1" target="_blank">[12]</a>. The other G1 cyclins, Cln1p and Cln2p, are important for this feedback, once it is initiated by Cln3p, but they were not included in this network. 60S ribosomal proteins are in yellow, while 40S ribosomal proteins are in orange. The most highly connected factors among the ones we identified are in green, and Cys4p is in blue.</p