Changes in the genetic requirements for microbial interactions with increasing community complexity.

Microbial community structure and function rely on complex interactions whose underlying molecular mechanisms are poorly understood. To investigate these interactions in a simple microbiome, we introduced E. coli into an experimental community based on a cheese rind and identified the differences in E. coli's genetic requirements for growth in interactive and non-interactive contexts using Random Barcode Transposon Sequencing (RB-TnSeq) and RNASeq. Genetic requirements varied among pairwise growth conditions and between pairwise and community conditions. Our analysis points to mechanisms by which growth conditions change as a result of increasing community complexity and suggests that growth within a community relies on a combination of pairwise and higher-order interactions. Our work provides a framework for using the model organism E. coli as a readout to investigate microbial interactions regardless of the genetic tractability of members of the studied ecosystem

Cardiovascular autonomic dysfunction in insomnia patients with objective short sleep duration.

Two phenotypes have been proposed: insomnia with objective near-normal sleep duration, related to increased psychological symptoms, and insomnia with objective short sleep duration, associated with cardiometabolic morbidity. Reduced heart rate variability has also been implicated in the pathophysiology of cardiometabolic disease; however, there are little data on whether cardiovascular function differs between patients with objective short sleep duration and near-normal sleep duration. Participants (Mage  = 49.9 ± 11.3 years; 62.8% female) were 180 adults with chronic insomnia (Mduration  = 15.7 ± 13.6). Objective sleep duration was based on total sleep time averaged across two consecutive nights of polysomnography and subjective sleep duration was based on 2-week sleep diaries. The sample was divided into two groups, with sleep duration shorter (polysomnography-total sleep time: n = 46; sleep diary: n = 95) or equal/longer (polysomnography-total sleep time: n = 134; sleep diary: n = 85) than 6 hr. Electrocardiogram data derived from polysomnography were used to obtain heart rate and heart rate variability during stage 2 (N2) and rapid eye movement sleep. Heart rate variability measures included absolute and normalized high-frequency component, an index of parasympathetic activation, and the ratio of low- to high-frequency (LF/HF ratio), an index of sympathovagal balance. After controlling for covariates (e.g., co-morbidity), patients with objective short sleep duration had reduced high-frequency (p < .05) and elevated low-frequency/high-frequency ratio (p = .036) and heart rate (p = .051) compared with patients with near-normal sleep duration. No differences were observed between phenotypes when subjective sleep duration was used. Insomnia patients with objective short sleep duration showed significantly dampened parasympathetic activation and increased sympathovagal imbalance relative to their counterparts with near-normal sleep duration. These findings highlight the importance of treating insomnia, as treatment may reduce the risk of cardiovascular disease

Reactive oxygen species-dependent Toll/ NF-kB activation in the Drosophila hematopoietic niche confers resistance to wasp parasitism

International audienceHematopoietic stem/progenitor cells in the adult mammalian bone marrow ensure blood cell renewal. Their cellular microenvironment, called 'niche', regulates hematopoiesis both under homeostatic and immune stress conditions. In the Drosophila hematopoietic organ, the lymph gland, the posterior signaling center (PSC) acts as a niche to regulate the hematopoietic response to immune stress such as wasp parasitism. This response relies on the differentiation of lamellocytes, a cryptic cell type, dedicated to pathogen encapsulation and killing. Here, we establish that Toll/NF-kB pathway activation in the PSC in response to wasp parasitism non-cell autonomously induces the lymph gland immune response. Our data further establish a regulatory network where co-activation of Toll/NF-kB and EGFR signaling by ROS levels in the PSC/niche controls lymph gland hematopoiesis under parasitism. Whether a similar regulatory network operates in mammals to control emergency hematopoiesis is an open question

The Csr System Regulates Escherichia coli Fitness by Controlling Glycogen Accumulation and Energy Levels

International audienceIn the bacterium Escherichia coli, the posttranscriptional regulatory system Csr was postulated to influence the transition from glycolysis to gluconeogene-sis. Here, we explored the role of the Csr system in the glucose-acetate transition as a model of the glycolysis-to-gluconeogenesis switch. Mutations in the Csr system influence the reorganization of gene expression after glucose exhaustion and disturb the timing of acetate reconsumption after glucose exhaustion. Analysis of me-tabolite concentrations during the transition revealed that the Csr system has a major effect on the energy levels of the cells after glucose exhaustion. This influence was demonstrated to result directly from the effect of the Csr system on glycogen accumulation. Mutation in glycogen metabolism was also demonstrated to hinder metabolic adaptation after glucose exhaustion because of insufficient energy. This work explains how the Csr system influences E. coli fitness during the glycolysis-gluconeogenesis switch and demonstrates the role of glycogen in maintenance of the energy charge during metabolic adaptation. IMPORTANCE Glycogen is a polysaccharide and the main storage form of glucose from bacteria such as Escherichia coli to yeasts and mammals. Although its function as a sugar reserve in mammals is well documented, the role of glycogen in bacteria is not as clear. By studying the role of posttranscriptional regulation during metabolic adaptation, for the first time, we demonstrate the role of sugar reserve played by glycogen in E. coli. Indeed, glycogen not only makes it possible to maintain sufficient energy during metabolic transitions but is also the key component in the capacity of cells to resume growth. Since the essential posttranscriptional regulatory system Csr is a major regulator of glycogen accumulation, this work also sheds light on the central role of posttranscriptional regulation in metabolic adaptation

Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics

Introduction There is a cumulative risk of 20-40% of developing brain metastases (BM) in solid cancers. Stereotactic radiotherapy (SRT) enables the application of high focal doses of radiation to a volume and is often used for BM treatment. However, SRT can cause adverse radiation effects (ARE), such as radiation necrosis, which sometimes cause irreversible damage to the brain. It is therefore of clinical interest to identify patients at a high risk of developing ARE. We hypothesized that models trained with radiomics features, deep learning (DL) features, and patient characteristics or their combination can predict ARE risk in patients with BM before SRT. Methods Gadolinium-enhanced T1-weighted MRIs and characteristics from patients treated with SRT for BM were collected for a training and testing cohort (N = 1,404) and a validation cohort (N = 237) from a separate institute. From each lesion in the training set, radiomics features were extracted and used to train an extreme gradient boosting (XGBoost) model. A DL model was trained on the same cohort to make a separate prediction and to extract the last layer of features. Different models using XGBoost were built using only radiomics features, DL features, and patient characteristics or a combination of them. Evaluation was performed using the area under the curve (AUC) of the receiver operating characteristic curve on the external dataset. Predictions for individual lesions and per patient developing ARE were investigated. Results The best-performing XGBoost model on a lesion level was trained on a combination of radiomics features and DL features (AUC of 0.71 and recall of 0.80). On a patient level, a combination of radiomics features, DL features, and patient characteristics obtained the best performance (AUC of 0.72 and recall of 0.84). The DL model achieved an AUC of 0.64 and recall of 0.85 per lesion and an AUC of 0.70 and recall of 0.60 per patient. Conclusion Machine learning models built on radiomics features and DL features extracted from BM combined with patient characteristics show potential to predict ARE at the patient and lesion levels. These models could be used in clinical decision making, informing patients on their risk of ARE and allowing physicians to opt for different therapies

Automated detection and segmentation of non-small cell lung cancer computed tomography images.

peer reviewedDetection and segmentation of abnormalities on medical images is highly important for patient management including diagnosis, radiotherapy, response evaluation, as well as for quantitative image research. We present a fully automated pipeline for the detection and volumetric segmentation of non-small cell lung cancer (NSCLC) developed and validated on 1328 thoracic CT scans from 8 institutions. Along with quantitative performance detailed by image slice thickness, tumor size, image interpretation difficulty, and tumor location, we report an in-silico prospective clinical trial, where we show that the proposed method is faster and more reproducible compared to the experts. Moreover, we demonstrate that on average, radiologists & radiation oncologists preferred automatic segmentations in 56% of the cases. Additionally, we evaluate the prognostic power of the automatic contours by applying RECIST criteria and measuring the tumor volumes. Segmentations by our method stratified patients into low and high survival groups with higher significance compared to those methods based on manual contours