Modulation of bacterial membrane proteins activity by clustering into plasma membrane nanodomains

Recent research has demonstrated specific protein clustering within membrane subdomains in bacteria, challenging the long-held belief that prokaryotes lack these subdomains. This mini review provides examples of bacterial membrane protein clustering, discussing the benefits of protein assembly in membranes and highlighting how clustering regulates protein activity.

CustOmics: A versatile deep-learning based strategy for multi-omics integration

The availability of patient cohorts with several types of omics data opens new perspectives for exploring the disease's underlying biological processes and developing predictive models. It also comes with new challenges in computational biology in terms of integrating high-dimensional and heterogeneous data in a fashion that captures the interrelationships between multiple genes and their functions. Deep learning methods offer promising perspectives for integrating multi-omics data. In this paper, we review the existing integration strategies based on autoencoders and propose a new customizable one whose principle relies on a two-phase approach. In the first phase, we adapt the training to each data source independently before learning cross-modality interactions in the second phase. By taking into account each source's singularity, we show that this approach succeeds at taking advantage of all the sources more efficiently than other strategies. Moreover, by adapting our architecture to the computation of Shapley additive explanations, our model can provide interpretable results in a multi-source setting. Using multiple omics sources from different TCGA cohorts, we demonstrate the performance of the proposed method for cancer on test cases for several tasks, such as the classification of tumor types and breast cancer subtypes, as well as survival outcome prediction. We show through our experiments the great performances of our architecture on seven different datasets with various sizes and provide some interpretations of the results obtained. Our code is available on (https://github.com/HakimBenkirane/CustOmics).

The Physcomitrium (Physcomitrella) patens PpKAI2L receptors for strigolactones and related compounds function via MAX2-dependent and -independent pathways

In angiosperms, the α/β hydrolase DWARF14 (D14), along with the F-box protein MORE AXILLARY GROWTH2 (MAX2), perceives strigolactones (SL) to regulate developmental processes. The key SL biosynthetic enzyme CAROTENOID CLEAVAGE DIOXYGENASE8 (CCD8) is present in the moss Physcomitrium patens, and PpCCD8-derived compounds regulate moss extension. The PpMAX2 homolog is not involved in the SL response, but 13 PpKAI2LIKE (PpKAI2L) genes homologous to the D14 ancestral paralog KARRIKIN INSENSITIVE2 (KAI2) encode candidate SL receptors. In Arabidopsis thaliana, AtKAI2 perceives karrikins and the elusive endogenous KAI2-Ligand (KL). Here, germination assays of the parasitic plant Phelipanche ramosa suggested that PpCCD8-derived compounds are likely noncanonical SLs. (+)-GR24 SL analog is a good mimic for PpCCD8-derived compounds in P. patens, while the effects of its enantiomer (-)-GR24, a KL mimic in angiosperms, are minimal. Interaction and binding assays of seven PpKAI2L proteins pointed to the stereoselectivity toward (-)-GR24 for a single clade of PpKAI2L (eu-KAI2). Enzyme assays highlighted the peculiar behavior of PpKAI2L-H. Phenotypic characterization of Ppkai2l mutants showed that eu-KAI2 genes are not involved in the perception of PpCCD8-derived compounds but act in a PpMAX2-dependent pathway. In contrast, mutations in PpKAI2L-G, and -J genes abolished the response to the (+)-GR24 enantiomer, suggesting that PpKAI2L-G, and -J proteins are receptors for moss SLs.

Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies

BACKGROUND

We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D).

METHODS AND FINDINGS

Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist.

CONCLUSIONS

In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.

Energy Deregulation Precedes Alteration in Heart Energy Balance in Young Spontaneously Hypertensive Rats: A Non Invasive In Vivo31P-MR Spectroscopy Follow-Up Study

Introduction

Gradual alterations in cardiac energy balance, as assessed by the myocardial PCr/ATP-ratio, are frequently associated with the development of cardiac disease. Despite great interest for the follow-up of myocardial PCr and ATP content, cardiac MR-spectroscopy in rat models in vivo is challenged by sensitivity issues and cross-contamination from other organs.

Methods

Here we combined MR-Imaging and MR-Spectroscopy (Bruker BioSpec 9.4T) to follow-up for the first time in vivo the cardiac energy balance in the SHR, a genetic rat model of cardiac hypertrophy known to develop early disturbances in cytosolic calcium dynamics.

Results

We obtained consistent ³¹P-spectra with high signal/noise ratio from the left ventricle in vivo by using a double-tuned (³¹P/¹H) surface coil. Reasonable acquisition time (<3.2min) allowed assessing the PCr/ATP-ratio comparatively in SHR and age-matched control rats (WKY): i) weekly from 12 to 21 weeks of age; ii) in response to a bolus injection of the ß-adrenoreceptor agonist isoproterenol at age 21 weeks.

Discussion

Along weeks, the cardiac PCr/ATP-ratio was highly reproducible, steady and similar (2.35±0.06) in SHR and WKY, in spite of detectable ventricular hypertrophy in SHR.

At the age 21 weeks, PCr/ATP dropped more markedly (-17.1%±0.8% vs. -3,5%±1.4%, P<0.001) after isoproterenol injection in SHR and recovered slowly thereafter (time constant 21.2min vs. 6.6min, P<0.05) despite similar profiles of tachycardia among rats.

Conclusion

The exacerbated PCr/ATP drop under ß-adrenergic stimulation indicates a defect in cardiac energy regulation possibly due to calcium-mediated abnormalities in the SHR heart. Of note, defects in energy regulation were present before detectable abnormalities in cardiac energy balance at rest.