Analysis of Gut Characteristics and Microbiota Changes with Maternal Supplementation in a Neural Tube Defect Mouse Model.

Adequate nutrient supply is crucial for the proper development of the embryo. Although nutrient supply is determined by maternal diet, the gut microbiota also influences nutrient availability. While currently there is no cure for neural tube defects (NTDs), their prevention is largely amenable to maternal folic acid and inositol supplementation. The gut microbiota also contributes to the production of these nutrients, which are absorbed by the host, but its role in this context remains largely unexplored. In this study, we performed a functional and morphological analysis of the intestinal tract of loop-tail mice (Vangl2 mutants), a mouse model of folate/inositol-resistant NTDs. In addition, we investigated the changes in gut microbiota using 16S rRNA gene sequencing regarding (1) the host genotype; (2) the sample source for metagenomics analysis; (3) the pregnancy status in the gestational window of neural tube closure; (4) folic acid and (5) D-chiro-inositol supplementation. We observed that Vangl2+/Lp mice showed no apparent changes in gastrointestinal transit time or fecal output, yet exhibited increased intestinal length and cecal weight and gut dysbiosis. Moreover, our results showed that the mice supplemented with folic acid and D-chiro-inositol had significant changes in their microbiota composition, which are changes that could have implications for nutrient absorption.

Analysis of Serial Neuroblastoma PDX Passages in Mice Allows the Identification of New Mediators of Neuroblastoma Aggressiveness.

Neuroblastoma is a neural crest cell-derived pediatric tumor characterized by high inter- and intra-tumor heterogeneity, and by a poor outcome in advanced stages. Patient-derived xenografts (PDXs) have been shown to be useful models for preserving and expanding original patient biopsies in vivo, and for studying neuroblastoma biology in a more physiological setting. The maintenance of genetic, histologic, and phenotypic characteristics of the original biopsy along serial PDX passages in mice is a major concern regarding this model. Here we analyze consecutive PDX passages in mice, at both transcriptomic and histological levels, in order to identify potential changes or highlight similarities to the primary sample. We studied temporal changes using mRNA and miRNA expression and correlate those with neuroblastoma aggressiveness using patient-derived databases. We observed a shortening of tumor onset and an increase in proliferative potential in the PDXs along serial passages. This behavior correlates with changes in the expression of genes related to cell proliferation and neuronal differentiation, including signaling pathways described as relevant for neuroblastoma malignancy. We also identified new genes and miRNAs that can be used to stratify patients according to survival, and which could be potential new players in neuroblastoma aggressiveness. Our results highlight the usefulness of the PDX neuroblastoma model and reflect phenotypic changes that might be occurring in the mouse environment. These findings could be useful for understanding the progression of tumor aggressiveness in this pathology.

Molecular epidemiology of paediatric invasive pneumococcal disease in Andalusia, Spain.

This study aimed to assess the impact of the introduction of pneumococcal conjugate vaccine 13 (PCV13) on the molecular epidemiology of invasive pneumococcal disease (IPD) in children from Andalusia. A population-based prospective surveillance study was conducted on IPD in children aged <14 years from Andalusia (2018-2020). Pneumococcal invasive isolates collected between 2006 and 2009 in the two largest tertiary hospitals in Andalusia were used as pre-PCV13 controls for comparison of serotype/genotype distribution. Overall IPD incidence rate was 3.55 cases per 100 000 in 2018; increased non-significantly to 4.20 cases per 100 000 in 2019 and declined in 2020 to 1.69 cases per 100 000 (incidence rate ratio 2020 vs. 2019: 0.40, 95% confidence interval (CI) 0.20-0.89, P = 0.01). Proportion of IPD cases due to PCV13 serotypes in 2018-2020 was 28% (P = 0.0001 for comparison with 2006-2009). Serotypes 24F (15%) and 11A (8.3%) were the most frequently identified non-PCV13 serotypes (NVT) in 2018-2020. Penicillin- and/or ampicillin-resistant clones mostly belonged to clonal complex 156 (serotype 14-ST156 and ST2944 and serotype 11A-ST6521). The proportion of IPD cases caused by PCV13 serotypes declined significantly after the initiation of the PCV13 vaccination programme in 2016. Certain NVT, such as serotypes 24F and 11A, warrant future monitoring in IPD owing to invasive potential and/or antibiotic resistance rates.

A DNA damage repair gene-associated signature predicts responses of patients with advanced soft-tissue sarcoma to treatment with trabectedin.

Predictive biomarkers of trabectedin represent an unmet need in advanced soft-tissue sarcomas (STS). DNA damage repair (DDR) genes, involved in homologous recombination or nucleotide excision repair, had been previously described as biomarkers of trabectedin resistance or sensitivity, respectively. The majority of these studies only focused on specific factors (ERCC1, ERCC5, and BRCA1) and did not evaluate several other DDR-related genes that could have a relevant role for trabectedin efficacy. In this retrospective translational study, 118 genes involved in DDR were evaluated to determine, by transcriptomics, a predictive gene signature of trabectedin efficacy. A six-gene predictive signature of trabectedin efficacy was built in a series of 139 tumor samples from patients with advanced STS. Patients in the high-risk gene signature group showed a significantly worse progression-free survival compared with patients in the low-risk group (2.1 vs 6.0 months, respectively). Differential gene expression analysis defined new potential predictive biomarkers of trabectedin sensitivity (PARP3 and CCNH) or resistance (DNAJB11 and PARP1). Our study identified a new gene signature that significantly predicts patients with higher probability to respond to treatment with trabectedin. Targeting some genes of this signature emerges as a potential strategy to enhance trabectedin efficacy.

The Roles of Imprinted SLC22A18 and SLC22A18AS Gene Overexpression Caused by Promoter CpG Island Hypomethylation as Diagnostic and Prognostic Biomarkers for Non-Small Cell Lung Cancer Patients.

Genomic imprinting is a process that involves one gene copy turned-off in a parent-of-origin-dependent manner. The regulation of imprinted genes is broadly dependent on promoter methylation marks, which are frequently associated with both oncogenes and tumor suppressors. The purpose of this study was to assess the DNA methylation patterns of the imprinted solute-carrier family 22 member 18 (SLC22A18) and SLC22A18 antisense (SLC22A18AS) genes in non-small cell lung cancer (NSCLC) patients to study their relevance to the disease. We found that both genes were hypomethylated in adenocarcinoma and squamous cell carcinoma patients. Due to this imprinting loss, SLC22A18 and SLC22A18AS were found to be overexpressed in NSCLC tissues, which is significantly more evident in lung adenocarcinoma patients. These results were validated through analyses of public databases of NSCLC patients. The reversed gene profile of both genes was achieved in vitro by treatment with ademetionine. We then showed that high SLC22A18 and SLC22A18AS expression levels were significantly associated with worsening disease progression. In addition, low levels of SLC22A18AS were also correlated with better overall survival for lung adenocarcinoma patients. We found that SLC22A18 and SLC22A18AS knockdown inhibits cell proliferation in vitro. All these results suggest that both genes may be useful as diagnostic and prognostic biomarkers in NSCLC, revealing novel therapeutic opportunities.

Phenotype inference in an Escherichia coli strain panel.

Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Combining high-throughput gene function assays with mechanistic models of the impact of genetic variants is a promising alternative to genome-wide association studies. Here we have assembled a large panel of 696 Escherichia coli strains, which we have genotyped and measured their phenotypic profile across 214 growth conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across all strains. Finally, we combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to compute the growth defects of each strain. Not only could we reliably predict these defects in up to 38% of tested conditions, but we could also directly identify the causal variants that were validated through complementation assays. Our work demonstrates the power of forward predictive models and the possibility of precision genetic interventions.