Improved Bipolar Properties of Ester-Functionalized Discotic Diimine-Dithiolene Complexes

A series of platinum diimine-dithiolene complexes with a 5,6-dihydro-1,4-dithiin-2,3-dithiolato (dddt2- ) dithiolene ligand and a bipyridine carrying tris-alkoxyphenyl fragments connected through an ester linker (bpyCn, n=8, 12, 16, 10(s), 20) (Scheme 1) has been developed. The mesomorphic properties of the ligands and of the platinum complexes have been investigated by a combination of DSC, POM and SAXS analyses. The platinum complexes were found to self-organize into columnar mesophases of hexagonal symmetry over large temperature range including room temperature. Their electronic properties were also characterized by a combination of electrochemistry, absorption and emission spectroscopy measurements and TD-DFT calculations. Besides being liquid crystalline, these compounds can undergo two oxidation processes and two reduction processes in a fully reversible manner, allowing the isolation of stable dicationic and dianionic species. Such a behavior is highly promising for the development of ambipolar semiconducting soft materials.

Cristae shaping and dynamics in mitochondrial function

Mitochondria are multifunctional organelles of key importance for cell homeostasis. The outer mitochondrial membrane (OMM) envelops the organelle, and the inner mitochondrial membrane (IMM) is folded into invaginations called cristae. As cristae composition and functions depend on the cell type and stress conditions, they recently started to be considered as a dynamic compartment. A number of proteins are known to play a role in cristae architecture, such as OPA1, MIC60, LETM1, the prohibitin (PHB) complex and the F1FO ATP synthase. Furthermore, phospholipids are involved in the maintenance of cristae ultrastructure and dynamics. The use of new technologies, including super-resolution microscopy to visualize cristae dynamics with superior spatiotemporal resolution, as well as high-content techniques and datasets have not only allowed the identification of new cristae proteins but also helped to explore cristae plasticity. However, a number of open questions remain in the field, such as whether cristae-resident proteins are capable of changing localization within mitochondria, or whether mitochondrial proteins can exit mitochondria through export. In this Review, we present the current view on cristae morphology, stability and composition, and address important outstanding issues that might pave the way to future discoveries.

Genomic disturbance of vitellogenin 2 (vtg2) leads to vitellin membrane deficiencies and significant mortalities at early stages of embryonic development in zebrafish (Danio rerio)

The specific functions and essentiality of type II vitellogenin (Vtg2) in early zebrafish development were investigated in this study. A vtg2-mutant zebrafish line was produced and effects of genomic disturbance were observed in F2 females and F3 offspring. No change in vtg2 transcript has been detected, however, Vtg2 abundance in F2 female liver was 5×, and in 1 hpf F3 vtg2-mutant embryos was 3.8× less than Wt (p < 0.05). Fecundity was unaffected while fertilization rate was more than halved in F2 vtg2-mutant females (p < 0.05). Hatching rate was significantly higher in F3 vtg2-mutant embryos in comparison to Wt embryos. Survival rate declined drastically to 29% and 18% at 24 hpf and 20 dpf, respectively, in F3 vtg2-mutant embryos. The introduced mutation caused vitelline membrane deficiencies, significant mortalities at early embryonic stages, and morphological abnormalities in the surviving F3 vtg2-mutant larvae. Overrepresentation of histones, zona pellucida proteins, lectins, and protein degradation related proteins in F3 vtg2-mutant embryos provide evidence to impaired mechanisms involved in vitellin membrane formation. Overall findings imply a potential function of Vtg2 in acquisition of vitellin membrane integrity, among other reproductive functions, and therefore, its essentiality in early zebrafish embryo development.

Predicting enzymatic function of protein sequences with attention

MOTIVATION

There is a growing number of available protein sequences, but only a limited amount has been manually annotated. For example, only 0.25% of all entries of UniProtKB are reviewed by human annotators. Further developing automatic tools to infer protein function from sequence alone can alleviate part of this gap. In this article, we investigate the potential of Transformer deep neural networks on a specific case of functional sequence annotation: the prediction of enzymatic classes.

RESULTS

We show that our EnzBert transformer models, trained to predict Enzyme Commission (EC) numbers by specialization of a protein language model, outperforms state-of-the-art tools for monofunctional enzyme class prediction based on sequences only. Accuracy is improved from 84% to 95% on the prediction of EC numbers at level two on the EC40 benchmark. To evaluate the prediction quality at level four, the most detailed level of EC numbers, we built two new time-based benchmarks for comparison with state-of-the-art methods ECPred and DeepEC: the macro-F1 score is respectively improved from 41% to 54% and from 20% to 26%. Finally, we also show that using a simple combination of attention maps is on par with, or better than, other classical interpretability methods on the EC prediction task. More specifically, important residues identified by attention maps tend to correspond to known catalytic sites. Quantitatively, we report a max F-Gain score of 96.05%, while classical interpretability methods reach 91.44% at best.

AVAILABILITY AND IMPLEMENTATION

Source code and datasets are respectively available at https://gitlab.inria.fr/nbuton/tfpc and https://doi.org/10.5281/zenodo.7253910.