The diverse chemistry of protoplanetary disks as revealed by JWST

Early results from the JWST-MIRI guaranteed time programs on protostars (JOYS) and disks (MINDS) are presented. Thanks to the increased sensitivity, spectral and spatial resolution of the MIRI spectrometer, the chemical inventory of the planet-forming zones in disks can be investigated with unprecedented detail across stellar mass range and age. Here data are presented for five disks, four around low-mass stars and one around a very young high-mass star. The mid-infrared spectra show some similarities but also significant diversity: some sources are rich in CO2, others in H2O or C2H2. In one disk around a very low-mass star, booming C2H2 emission provides evidence for a ``soot'' line at which carbon grains are eroded and sublimated, leading to a rich hydrocarbon chemistry in which even di-acetylene (C4H2) and benzene (C6H6) are detected (Tabone et al. 2023). Together, the data point to an active inner disk gas-phase chemistry that is closely linked to the physical structure (temperature, snowlines, presence of cavities and dust traps) of the entire disk and which may result in varying CO2/H2O abundances and high C/O ratios >1 in some cases. Ultimately, this diversity in disk chemistry will also be reflected in the diversity of the chemical composition of exoplanets.Comment: 17 pages, 8 figures. Author's version of paper submitted to Faraday Discussions January 18 2023, Accepted March 16 202

BNP controls early load-dependent regulation of SERCA through calcineurin

Heart failure is characterised by reduced expression of sarcoplasmic reticulum calcium-ATPase (SERCA) and increased expression of B-type natriuretic peptide (BNP). The present study was performed to investigate causality of this inverse relationship under in vivo conditions in the transversal aortic constriction mouse model (TAC). Left ventricular SERCA-mRNA expression was significantly upregulated in TAC by 32% after 6 h, but not different from sham after 24 h. Serum proANP and BNP levels were increased in TAC after 24 h (BNP +274%, p < 0.01; proANP +60%, p < 0.05), but only proANP levels were increased after 6 h (+182%, p < 0.01). cGMP levels were only increased 24 h after TAC (+307%, p < 0.01), but not 6 h after TAC. BNP infusion inhibited the increase in SERCA expression 6 h after TAC. In BNP-receptor-knockout animals (GC-A), the expression of SERCA was still significantly increased 24 h after TAC at the mRNA level by 35% (p < 0.05), as well as at the protein level by 25% (p < 0.05). MCIP expression as an indicator of calcineurin activity was regulated in parallel to SERCA after 6 and 24 h. MCIP-mRNA was increased by 333% 6 h after TAC, but not significantly different from sham after 24 h. In the GC-A-KO mice, MCIP-mRNA was significantly increased in TAC compared to WT after 24 h. In mice with BNP infusion, MCIP was significantly lower 6 h after TAC compared to control animals. In conclusion, mechanical load leads to an upregulation of SERCA expression. This is followed by upregulation of natriuretic peptides with subsequent suppression of SERCA upregulation. Elevated natriuretic peptides may suppress SERCA expression by inhibition of calcineurin activity via activation of GC-A

The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology

<p>Abstract</p> <p>Background</p> <p>High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently.</p> <p>Results</p> <p>We developed the Annotation, Mapping, Expression and Network (AMEN) software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i) uploading and pre-processing data from microarray expression profiling experiments, (ii) detecting groups of significantly co-expressed genes, and (iii) searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human.</p> <p>Conclusion</p> <p>AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.</p

Which clustering algorithm is better for predicting protein complexes?

<p>Abstract</p> <p>Background</p> <p>Protein-Protein interactions (PPI) play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks.</p> <p>Results</p> <p>In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H) and Tandem Affinity Purification (TAP) methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases.</p> <p>Conclusions</p> <p>While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: <url>http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm</url></p

Cardiac contractile dysfunction in insulin-resistant rats fed a high-fat diet is associated with elevated CD36-mediated fatty acid uptake and esterification

Changes in cardiac substrate utilisation leading to altered energy metabolism may underlie the development of diabetic cardiomyopathy. We studied cardiomyocyte substrate uptake and utilisation and the role of the fatty acid translocase CD36 in relation to in vivo cardiac function in rats fed a high-fat diet (HFD).Rats were exposed to an HFD or a low-fat diet (LFD). In vivo cardiac function was monitored by echocardiography. Substrate uptake and utilisation were determined in isolated cardiomyocytes.Feeding an HFD for 8 weeks induced left ventricular dilation in the systolic phase and decreased fractional shortening and the ejection fraction. Insulin-stimulated glucose uptake and proline-rich Akt substrate 40 phosphorylation were 41% (p <0.001) and 45% (p <0.05) lower, respectively, in cardiomyocytes from rats on the HFD. However, long-chain fatty acid (LCFA) uptake was 1.4-fold increased (p <0.001) and LCFA esterification into triacylglycerols and phospholipids was increased 1.4- and 1.5-fold, respectively (both p <0.05), in cardiomyocytes from HFD compared with LFD hearts. In the presence of the CD36 inhibitor sulfo-N-succinimidyloleate, LCFA uptake and esterification were similar in LFD and HFD cardiomyocytes. In HFD hearts CD36 was relocated to the sarcolemma, and basal phosphorylation of a mediator of CD36-trafficking, i.e. protein kinase B (PKB/Akt), was increased.Feeding rats an HFD induced cardiac contractile dysfunction, which was accompanied by the relocation of CD36 to the sarcolemma, and elevated basal levels of phosphorylated PKB/Akt. The permanent presence of CD36 at the sarcolemma resulted in enhanced rates of LCFA uptake and myocardial triacylglycerol accumulation, and may contribute to the development of insulin resistance and diabetic cardiomyopathy

Women's job quality across family life stages: An analysis of female employees across 27 European countries

There is little empirical evidence on how working conditions affect women’s employment and fertility choices, despite a number of studies on the impact of individual-level and institutional factors. The article addresses this gap by examining how family life stages are related to particular aspects of job quality among employed women in 27 European countries. The central argument of the analysis is that high-quality jobs are conducive to both transitions to motherhood and employment after childbirth as women select into these roles. Accordingly, mothers of young children, if employed, are expected to have relatively better quality jobs. Four dimensions of job quality are considered: job security, career progression, working time and intrinsic job quality. The results indicate that mothers with young children are more likely to hold high-quality jobs than women at other life stages with respect to working time quality and job security, but with some variation across countries for job security. The findings highlight the importance of high-quality jobs for women’s fertility decisions and labour market attachment after childbirth, with implications for European employment policy

Deciphering Diseases and Biological Targets for Environmental Chemicals using Toxicogenomics Networks

Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types