Subcellular localization is a critical aspect of protein function and the potential application of proteins either as drugs or drug targets, or in industrial and domestic applications. However, the experimental determination of protein localization is time consuming and expensive. Therefore, various localization predictors have been developed for particular groups of species. Intriguingly, despite their major representation amongst biotechnological cell factories and pathogens, a meta-predictor based on sorting signals and specific for Gram-positive bacteria was still lacking. Here we present GP4, a protein subcellular localization meta-predictor mainly for Firmicutes, but also Actinobacteria, based on the combination of multiple tools, each specific for different sorting signals and compartments. Novelty elements include improved cell-wall protein prediction, including differentiation of the type of interaction, prediction of non-canonical secretion pathway target proteins, separate prediction of lipoproteins and better user experience in terms of parsability and interpretability of the results. GP4 aims at mimicking protein sorting as it would happen in a bacterial cell. As GP4 is not homology based, it has a broad applicability and does not depend on annotated databases with homologous proteins. Non-canonical usage may include little studied or novel species, synthetic and engineered organisms, and even re-use of the prediction data to develop custom prediction algorithms. Our benchmark analysis highlights the improved performance of GP4 compared to other widely used subcellular protein localization predictors. A webserver running GP4 is available at http//gp4.hpc.rug.nl/.A promoter is a region in the DNA sequence that defines where the transcription of a gene by RNA polymerase initiates, which is typically located proximal to the transcription start site (TSS). How to correctly identify the gene TSS and the core promoter is essential for our understanding of the transcriptional regulation of genes. As a complement to conventional experimental methods, computational techniques with easy-to-use platforms as essential bioinformatics tools can be effectively applied to annotate the functions and physiological roles of promoters. Epigenetics inhibitor In this work, we propose a deep learning-based method termed Depicter (Deep learning for predicting promoter), for identifying three specific types of promoters, i.e. promoter sequences with the TATA-box (TATA model), promoter sequences without the TATA-box (non-TATA model), and indistinguishable promoters (TATA and non-TATA model). Depicter is developed based on an up-to-date, species-specific dataset which includes Homo sapiens, Mus musculus, Drosophila melanogaster and Arabidopsis thaliana promoters. A convolutional neural network coupled with capsule layers is proposed to train and optimize the prediction model of Depicter. Extensive benchmarking and independent tests demonstrate that Depicter achieves an improved predictive performance compared with several state-of-the-art methods. The webserver of Depicter is implemented and freely accessible at https//depicter.erc.monash.edu/.Heterozygous de novo missense variants of SRP54 were recently identified in patients with congenital neutropenia (CN) who display symptoms that overlap with Shwachman-Diamond syndrome (SDS). Here, we investigate srp54 knockout zebrafish as the first in vivo model of SRP54 deficiency. srp54-/- zebrafish experience embryonic lethality and display multisystemic developmental defects along with severe neutropenia. In contrast, srp54+/- zebrafish are viable, fertile, and show only mild neutropenia. Interestingly, injection of human SRP54 messenger RNAs (mRNAs) that carry mutations observed in patients (T115A, T117Δ, and G226E) aggravated neutropenia and induced pancreatic defects in srp54+/- fish, mimicking the corresponding human clinical phenotypes. These data suggest that the various phenotypes observed in patients may be a result of mutation-specific dominant-negative effects on the functionality of the residual wild-type SRP54 protein. Overexpression of mutated SRP54 also consistently induced neutropenia in wild-type fish and impaired the granulocytic maturation of human promyelocytic HL-60 cells and healthy cord blood-derived CD34+ hematopoietic stem and progenitor cells. Mechanistically, srp54-mutant fish and human cells show impaired unconventional splicing of the transcription factor X-box binding protein 1 (Xbp1). Moreover, xbp1 morphants recapitulate phenotypes observed in srp54 deficiency and, importantly, injection of spliced, but not unspliced, xbp1 mRNA rescues neutropenia in srp54+/- zebrafish. Together, these data indicate that SRP54 is critical for the development of various tissues, with neutrophils reacting most sensitively to the loss of SRP54. The heterogenic phenotypes observed in patients that range from mild CN to SDS-like disease may be the result of different dominant-negative effects of mutated SRP54 proteins on downstream XBP1 splicing, which represents a potential therapeutic target.

Body composition assessment in breast cancer survivors (BCSs) is essential to plan feasible dietary strategies for sarcopenic obesity prevention.

Studying the effect of an individualized nutrition intervention according to socioeconomic status and grocery shopping behavior on BCSs relative fat mass (RFM).

BCSs attending an academic medical center were studied; participants saved all 1-week supermarket tickets and answered a grocery shopping consumer preference survey. RFM was assessed at baseline and after the 3-month nutrition intervention. Nutrition plans were based on the dynamic macronutrient meal-equivalent menu method (MEM) and dietary guidelines for BCSs.

Thirty-three BCSs completed the study and 91% of them presented obesity or overweight at baseline. After the intervention, BCSs lost 1.6 kg (p < 0.01) of body weight, 1.8 kg (p < 0.01) of RFM, 3 cm (p < 0.01) of waist circumference, and 2.4 cm (p < 0.01) of hip circumference, while no changes were observed in fat-free mass (p = 0.6) and arm bone-free muscle area (p = 0.7).

RFM and body weight in breast cancer survivors decreased after an individualized nutrition intervention according to socioeconomic status and grocery shopping consumer behavior. Based on the participants’ food preferences and consumer behavior, plant-based protein diet plans cost less than the animal-based protein diet plans.

RFM and body weight in breast cancer survivors decreased after an individualized nutrition intervention according to socioeconomic status and grocery shopping consumer behavior. Based on the participants’ food preferences and consumer behavior, plant-based protein diet plans cost less than the animal-based protein diet plans.