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A major gap in diagnosis, classification, risk stratification, and prediction of therapeutic response exists in pulmonary arterial hypertension (PAH), driven in part by a lack of functional biomarkers that are also disease-specific. In this regard, leveraging big data -omics analyses using innovative approaches that integrate network medicine and machine learning correlated with clinically useful indices or risk stratification scores is an approach well-positioned to advance PAH precision medicine. For example, machine learning applied to a panel of 48 cytokines, chemokines, and growth factors could prognosticate PAH patients with immune-dominant subphenotypes at elevated or low-risk for mortality. Here, we discuss strengths and weaknesses of the most current studies evaluating omics-derived biomarkers in PAH. Progress in this field is offset by studies with small sample size, pervasive limitations in bioinformatics, and lack of standardized methods for data processing and interpretation. Future success in this field, in turn, is likely to hinge on mechanistic validation of data outputs in order to couple functional biomarker data with target-specific therapeutics in clinical practice.

Lipidomics is an emerging and promising omic that analyzes different lipid molecules in a biological sample. It is considered as a branch of metabolomics, which is defined as the comprehensive analysis of metabolites in a biological specimen. Nonetheless, in recent years lipidomics is being considered a distinct discipline in the biomedicine field. Lipids play important roles in many biological pathways and could work as biomarkers of disease or as therapeutic targets for treatment diseases. The major lipidomics strategies are shotgun lipidomics and liquid chromatography coupled with mass spectrometry. Gastrointestinal diseases such as irritable bowel syndrome or inflammatory bowel disease are chronic diseases that need non-invasive biomarkers for prognosis and diagnosis. Even more, patients with inflammatory bowel disease are at a significantly increased risk of colorectal cancer, principally resulting from the pro-neoplastic effects of chronic intestinal inflammation. Current screening methods utilized globally include sigmoidoscopy, or standard colonoscopy but it is important to develop non-invasive and accurate screening tools to facilitate early detection and precise staging of colorectal cancer. Disease progression and response to treatment may benefit also from the application of these potential new tools. This review is focused on studies that use lipidomics approaches to discover potential biomarkers for monitoring the mentioned intestinal diseases and, particularly, tumour progression.

Although decades of the reductionist approach achieved great milestones in optimizing the immunosuppres-sion therapy, traditional clinical parameters still fail in predicting both acute and chronic (mainly) rejection events leading to higher rates across all solid organ transplants. To clarify the underlying immune-related cel-lular and molecular mechanisms, current biomedical research is increasingly focusing on "transplantomics" which relies on a huge quantity of big data deriving from genomics, transcriptomics, epigenomics, proteomics, and metabolomics platforms. The AlloMap (gene expression) and the AlloSure (donor-derived cell-free DNA) tests represent two successful examples of how omics and liquid biopsy can really improve the precision med-icine of heart and kidney transplantation. One of the major challenges in translating big data in clinically useful biomarkers is the integration and interpretation of the different layers of omics datasets. Network Medicine offers advanced bioinformatic-molecular strategies which were widely used to integrate large omics datasets and clinical information in end-stage patients to prioritize potential biomarkers and drug targets. The applica-tion of network-oriented approaches to clarify the complex nature of graft rejection is still in its infancy. Here, we briefly discuss the real-life clinical applications derived from omics datasets as well as novel opportunities for establishing predictive tests in solid organ transplantation. Also, we provide an original "graft rejection interactome" and propose network-oriented strategies which can be useful to improve precision medicine of solid organ transplantation.

Background Metastases are the major cause of cancer-related morbidity and mortality. By the time cancer cells detach from their primary site to eventually spread to distant sites, they need to acquire the ability to survive in non-adherent conditions and to proliferate within a new microenvironment in spite of stressing conditions that may severely constrain the metastatic process. In this study, we gained insight into the molecular mechanisms allowing cancer cells to survive and proliferate in an anchorage-independent manner, regardless of both tumor-intrinsic variables and nutrient culture conditions. Methods 3D spheroids derived from lung adenocarcinoma (LUAD) and breast cancer cells were cultured in either nutrient-rich or -restricted culture conditions. A multi-omics approach, including transcriptomics, proteomics, and metabolomics, was used to explore the molecular changes underlying the transition from 2 to 3D cultures. Small interfering RNA-mediated loss of function assays were used to validate the role of the identified differentially expressed genes and proteins in H460 and HCC827 LUAD as well as in MCF7 and T47D breast cancer cell lines. Results We found that the transition from 2 to 3D cultures of H460 and MCF7 cells is associated with significant changes in the expression of genes and proteins involved in metabolic reprogramming. In particular, we observed that 3D tumor spheroid growth implies the overexpression of ALDOC and ENO2 glycolytic enzymes concomitant with the enhanced consumption of glucose and fructose and the enhanced production of lactate. Transfection with siRNA against both ALDOC and ENO2 determined a significant reduction in lactate production, viability and size of 3D tumor spheroids produced by H460, HCC827, MCF7, and T47D cell lines. Conclusions Our results show that anchorage-independent survival and growth of cancer cells are supported by changes in genes and proteins that drive glucose metabolism towards an enhanced lactate production. Notably, this finding is valid for all lung and breast cancer cell lines we have analyzed in different nutrient environmental conditions. broader Validation of this mechanism in other cancer cells of different origin will be necessary to broaden the role of ALDOC and ENO2 to other tumor types. Future in vivo studies will be necessary to assess the role of ALDOC and ENO2 in cancer metastasis.

Circadian oscillations play a fundamental role in many biological processes including cell metabolism and cell cycle. As such, interest in understanding these molecular oscillations has generated an increasingly large collection of circadian omic data. These studies have demonstrated the remarkable plasticity with which the set of oscillating molecular species within a cell are selected. These large shifts in oscillating species are known as circadian reprogramming events. These events have been observed across experimental condition, tissue, and species. While many of these studies have made tissue or condition specific conclusions, a consolidated framework of software tools and a central repository of data has become necessary to answer questions about the orchestration of these reprogramming events.By combining the largest repository for circadian omic data with improved methods for the detection of circadian oscillation and regulation in omic studies, a model for the transcriptomic organization of circadian rhythms can be identified. Results are presented from a collection of specific reprogramming studies utilizing these new methods, as well as a high through-put analysis of a large collection of comparable transcriptomic datasets from mouse tissue. The identified model can be viewed as a deep hierarchical network of circadian regulation that originates from the core circadian clock to over 95% of oscillating transcripts.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Objetivo: O presente estudo avaliou metabólitos circulantes no plasma de pacientes com e sem leiomiomas, buscando definir um perfil metabolômico de tais pacientes e compará-las metabolomicamente entre si, de acordo com a presença de leiomioma e o volume uterino. Métodos: Estudo observacional, transversal, incluindo mulheres divididas em três grupos: 37 com leiomiomas e útero acima de 500 cm3, 17 com leiomiomas e útero de até 150 cm3 e 21 mulheres sem leiomiomas. As pacientes foram submetidas à coleta de sangue periférico seguida de avaliação metabólica global por cromatografia gasosa acoplada a espectrômetro de massa. Resultados: Os três grupos de pacientes foram semelhantes estatisticamente no que diz respeito a características antropométricas e demográficas e exames laboratoriais. Encontramos diferenças estatísticas entre os grupos para o volume do útero (p

Aims/hypothesis Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. Methods We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. Results The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p−16]). Conclusions/interpretation Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html). Graphical abstract

The core microbiome, which refers to a set of consistent microbial features across populations, is of major interest in microbiome research and has been addressed by numerous studies. Understanding the core microbiome can help identify elements that lead to dysbiosis, and lead to treatments for microbiome-related health states. However, defining the core microbiome is a complex task at several levels. In this review, we consider the current state of core human microbiome research. We consider the knowledge that has been gained, the factors limiting our ability to achieve a reliable description of the core human microbiome, and the fields most likely to improve that ability. DNA sequencing technologies and the methods for analyzing metagenomics and amplicon data will most likely facilitate higher accuracy and resolution in describing the microbiome. However, more effort should be invested in characterizing the microbiome’s interactions with its human host, including the immune system and nutrition. Other components of this holobiontic system should also be emphasized, such as fungi, protists, lower eukaryotes, viruses, and phages. Most importantly, a collaborative effort of experts in microbiology, nutrition, immunology, medicine, systems biology, bioinformatics, and machine learning is probably required to identify the traits of the core human microbiome.

Microbial communities interact with us and affect our health in ways that are only beginning to be understood. Microorganisms have been detected in every ecosystem on Earth, as well as in any built environment that has been investigated. Drinking water sources, drinking water treatment plants and distribution systems provide peculiar microbial ecological niches, dismantling the belief of the “biological simplicity” of drinking water. Nevertheless, drinking water microbiomes are understudied compared to other microbiomes. Recent DNA sequencing and meta-omics advancements allow a deeper understanding of drinking water microbiota. Thus, moving beyond the limits of day-to-day testing for specific pathogenic microbes, new approaches aim at predicting microbiome changes driven by disturbances at the macro-scale and overtime. This will foster an effective and proactive management of water sources, improving the drinking water supply system and the monitoring activities to lower public health risk. Here, we want to give a new angle on drinking water microbiome research. Starting from a selection of 231 scientific publications on this topic, we emphasize the value of biodiversity in drinking water ecosystems and how it can be related with industrialization. We then discuss how microbiome research can support sustainable drinking water management, encouraging collaborations across sectors and involving the society through responsible research and innovation.

En: Allergy e-ISSN:1398-9995, 2021, nov. 2, 14 pp Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force “Omics technologies in allergic research” broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients’ stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Background Omics data, driven by rapid advances in laboratory techniques, have been generated very quickly during the COVID-19 pandemic. Our aim is to use omics data to highlight the involvement of specific pathways, as well as that of cell types and organs, in the pathophysiology of COVID-19, and to highlight their links with clinical phenotypes of SARS-CoV-2 infection. Methods The analysis was based on the domain model, where for domain it is intended a conceptual repository, useful to summarize multiple biological pathways involved at different levels. The relevant domains considered in the analysis were: virus, pathways and phenotypes. An interdisciplinary expert working group was defined for each domain, to carry out an independent literature scoping review. Results The analysis revealed that dysregulated pathways of innate immune responses, (i.e., complement activation, inflammatory responses, neutrophil activation and degranulation, platelet degranulation) can affect COVID-19 progression and outcomes. These results are consistent with several clinical studies. Conclusions Multi-omics approach may help to further investigate unknown aspects of the disease. However, the disease mechanisms are too complex to be explained by a single molecular signature and it is necessary to consider an integrated approach to identify hallmarks of severity.

Summary In an attempt to explore the role of the gut microbiome during recent canine evolutionary history, we sequenced the metagenome of 13 canine coprolites dated ca. 3,600–3,450 years ago from the Bronze Age archaeological site of Solarolo (Italy), which housed a complex farming community. The microbiome structure of Solarolo dogs revealed continuity with that of modern dogs, but it also shared some features with the wild wolf microbiome, as a kind of transitional state between them. The dietary niche, as also inferred from the microbiome composition, was omnivorous, with evidence of consumption of starchy agricultural foods. Of interest, the Solarolo dog microbiome was particularly enriched in sequences encoding alpha-amylases and complemented a low copy number of the host amylase gene. These findings suggest that Neolithic dogs could have responded to the transition to a starch-rich diet by expanding microbial functionalities devoted to starch catabolism, thus compensating for delayed host response., Graphical abstract, Highlights • Ancient DNA of Bronze Age canine coprolites from Solarolo was sequenced • Solarolo dogs share gut microbiome features with modern wolves and dogs • The gut microbiome of Solarolo dogs shows high number of reads for alpha-amylase • Neolithic canine gut microbiome complemented delay in host genome adaptation, Biological sciences; Microbiome; Evolutionary biology; Evolutionary processes; Phylogenetics; Phylogeny; Evolutionary history; Genomic analysis; Sequence analysis; Omics; Genomics

For many years the one-size-fits-all approach has been the only one available to manage patients affected by primary biliary cholangitis. The introduction of obeticholic acid in 2016 as a second-line treatment, together with the creation and validation of several biochemically based scores to stratify the risk of progressive disease, has opened up the need to redefine clinical practice by changing the actual paradigm. The precision medicine initiative is a model of patient-centered health care that aims to improve medicine based on genotypic and molecular characteristics that correlate to specific phenotypic, individual characteristics. In summary, the aim of the precision medicine is to define the right treatment for the right person at the right time. The availability of a second-line disease-modifying drug and new molecules in phase 2 or 3 trials makes this an exciting time for the precision medicine initiative in primary biliary cholangitis. In this review we describe the current risk stratification tools and we track a possible path towards the application of precision medicine in clinical daily life.

Mineral elements are essential for plant growth and development and strongly affect crop yield and quality. To cope with an everchanging environment, plants have developed specific responses to combined nutrient variations. In this work, we investigated the effects of multifactorial treatments with three macrocations (K, Ca, and Mg) on lettuce (Lactuca sativa L.) varieties that strongly diverge in leaf pigmentation (full red or green). Specifically, we monitored main leaf parameters and metabolomics profiles of hydroponically grown plants fed with isosmotic nutrient solutions that have different proportions of macroelements. The result revealed a high biochemical plasticity of lettuce, significantly affected by the genotype, the nutrient solution, and their interaction. Our work also provided evidence and insights into the different intraspecific responses to multifactorial variation of macrocations, with two varieties having distinct strategies to metabolically respond to nutrient variation. Overall, plant adaptive mechanisms increased the phytochemical diversity between the varieties both among and within the main classes of plant secondary metabolites. Finally, our work also implies that the interaction of a pre-existing phytochemical diversity with the management of multiple mineral elements can offer added health-related benefits to the edible product specific to the variety.

Dissertation, RWTH Aachen University, 2021; Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen (2022). = Dissertation, RWTH Aachen University, 2021, Environmental pollution through industrial chemicals or pesticides has emerged as a major health issue for humans and the environment. While several of these chemicals were shown to adversely affect nervous system development, the estimated number of potential neurotoxicants is likely to be much higher. Such developmental perturbations cost society billions of dollars and result in IQ loss in children and several other neurological disorders. As there is currently no cure for such disorders, prevention is essential. Yet, the mechanisms leading to developmental neurotoxicity (DNT) are poorly understood, making prevention difficult. Consequently, methods and strategies are required that allow for a fast and reliable screening of potentially neurotoxic or -active substances. With regards to this the zebrafish (Danio rerio) embryo has emerged as a model organism. The embryos provide multiple advantageous features, promoting its use in DNT investigations as a non-mammal in vivo test system.In the work at hand, it was hypothesised that zebrafish embryos can be used to generate comprehensive insights into the mechanisms underlying DNT. To reveal these mechanisms, this thesis defined several objectives. First, to assess the applicability of zebrafish embryo behaviour for DNT screens. Therefore, six different insecticides and four endocrine disruptors (EDs) were used. Subsequently, observed behavioural deficits were to be investigated on multiple molecular levels to clarify underlying mechanisms, thus presenting the second goal. Thirdly the applicability of the embryos to lipidome investigations and their relevance for DNT-testing was to be assessed.To accomplish the first goal, it was aimed to increase the information output of one of the most commonly used behaviour assays, the light/ dark transition (LDT) test. Data evaluation was done by integrating multiple parameters at once, thereby retrieving additional information that was indicative for underlying (neuro-) toxic mechanisms. Furthermore, the experimental implementation of the spontaneous movement assay was improved. This resulted in a detailed description of this behaviour and highlighted new endpoints beneficial for DNT screens. As the increasing number of environmental toxicants makes rapid DNT screens necessary, the applicability of zebrafish embryos for such screens was assessed. An optimised battery of different behaviour assays, covering the entire early embryonic development showed that the embryos behaviour was able to indicate DNT. At the same time, this approach dramatically reduced the number of required test organisms. Hence, zebrafish embryo behaviour was recommended for broad DNT screenings in relevance of an Integrated Approach to Testing and Assessment (IATA). The second aim was accomplished by utilising multiple OMIC techniques (transcriptomics, proteomics, metabolomics). Exposure to acetylcholinesterase (AChE) inhibiting substances resulted in similar effects that were, however, not identical. For instance, dichlorvos exerted muscle apparatus and visual system perturbations while exposure to paraoxon-methyl lead to neurotoxic outcomes (e.g., serotonin dysregulation). On a higher level of organisation (locomotion) both substances decreased embryonic activity. Nervous system dysregulations (e.g., increased GABA levels) were further noticed after expo-sure to the EDs TDCPP, MEHP and 4-NP. Employing lipidomic analysis on exposed zebrafish embryos indicated effects on lipids involved in energy storing, cholesterol homeostasis or lipid-based signalling. A dysregulation of the lipidome can be associated with human-like diseases, demonstrating the relevance of including lipidome investigation into environmental exposure considerations for DNT. The thesis presented here demonstrated how environmental toxicants act on multiple levels of organisation in the zebrafish embryo. Due to the high conservation between e.g., the endocrine or the neuronal system of mammals and lower vertebrates, the results obtained from this research likely possess general relevance for both human and environmental DNT risk assessment. However, further research will be necessary to identify causal relationships. This work further established the applicability of zebrafish embryos as a non-mammal in vivo test system for DNT screens, suitable for a DNT-IATA. Overall, this thesis contributed approaches for addressing and understanding DNT as well as emphasised the need for new strategies, which increase the transferability of this knowledge to eco(toxico)logical research questions., Published by RWTH Aachen University, Aachen

Parallel to the dramatic rise of pediatric obesity, estimates reported an increased prevalence of type 2 diabetes (T2D) already in childhood. The close relationship between obesity and T2D in children is mainly sustained by insulin resistance (IR). In addition, the cardiometabolic burden of T2D including nonalcoholic fatty liver disease, cardiovascular disease and metabolic syndrome is also strictly related to IR. Although T2D pathophysiology has been largely studied in an attempt to improve therapeutic options, molecular mechanisms are still not fully elucidated. In this perspective, omics approaches (including lipidomics, metabolomics, proteomics and metagenomics) are providing the most attractive therapeutic options for T2D. In particular, distinct both lipids and metabolites are emerging as potential therapeutic tools. Of note, among lipid classes, the pathogenic role of ceramides in T2D context has been supported by several data. Thus, selective changes of ceramides expression might represent innovative therapeutic strategies for T2D treatment. More, distinct metabolomics pathways have been also found to be associated with higher T2D risk, by providing novel potential T2D biomarkers. Taken together, omics data are responsible for the expanding knowledge of T2D pathophysiology, by providing novel insights to improve therapeutic strategies for this tangled disease. We aimed to summarize the most recent evidence in the intriguing field of the omics approaches in T2D both in adults and children.

Cephalopods such as the cuttlefish Sepia officinalis, despite their short lifespan, have been found in the oceans for millions of years. In these atypical animals, few pathologies have been observed, revealing the presence of an effective but little studied immune system based on innate processes. The study of the cuttlefish's immune system has been carried out on the white body, a haematopoietic organ; on the circulating cells, the haemocytes; and on the skin, the first barrier with the external environment. At the white body level, the transcriptomic and proteomic study highlighted the presence of factors linked to haematopoiesis, including members of the JAK-STAT signalling pathway. Immune factors have also been identified, revealing a possible multifunctionality of the white body. The immune response to Vibrio splendidus could be apprehended from a comparative transcriptomic analysis of haemocytes. However, as the latter did not allow the clear identification of antimicrobial peptides, an original in silico analysis was developed to select five candidate peptides, three of which revealed a targeted antibacterial activity against bacteria of the Vibrio genus. Finally, a study of the skin and its mucus was initiated. This study using -omic approaches enabled the identification of factors related to pathogen recognition and immune response. In addition, twelve strains were isolated and identified at the level of the skin microbiome. All these results represent a major contribution concerning the immune system in cuttlefish, making it possible to initiate functional studies during an infection or at the end of life. These studies would make it possible to understand the mode of action of the identified immune factors, the involvement of each entity in the immune response or in the establishment and maintenance of the microbiome.; Les Céphalopodes comme la seiche Sepia officinalis, malgré une durée de vie courte, sont retrouvés dans les océans depuis des millions d’années. Chez ces animaux atypiques, peu de pathologies ont été observées révélant la présence d’un système immunitaire efficace mais peu étudié qui repose sur des processus innés. L’étude du système immunitaire de la seiche a été menée au niveau du corps blanc, organe hématopoïétique ; des cellules circulantes, les hémocytes et au niveau de la peau, première barrière avec le milieu extérieur. Au niveau du corps blanc, l’étude transcriptomique et protéomique a mis en évidence la présence de facteurs en lien avec l’hématopoïèse dont des membres de la voie de signalisation JAK-STAT. Des facteurs immunitaires ont également été identifiés révélant une possible multifonctionnalité du corps blanc. La réponse immunitaire face à Vibrio splendidus a pu être appréhendées à partir d’une analyse transcriptomique comparative sur les hémocytes. Toutefois cette dernière n’ayant pas permis d’identifier clairement des peptides antimicrobiens, une analyse in silico originale a été développée permettant de sélectionner cinq peptides candidats dont trois ont révélé une activité antibactérienne ciblée contre des bactéries du genre Vibrio. Enfin, une étude au niveau de la peau et de son mucus a été initiée. Cette étude par des approches -omiques a permis l’identification de facteurs en lien avec la reconnaissance des pathogènes et la réponse immunitaire. Par ailleurs, douze souches ont pu être isolées et identifiées au niveau du microbiome cutané. L’ensemble de ces résultats représente un apport majeur concernant le système immunitaire chez la seiche permettant d’initier des études fonctionnelles lors d’une infection ou en fin de vie. Ces études permettraient de comprendre le mode d’action des facteurs immunitaires identifiés, l’implication de chaque entité dans la réponse immunitaire ou dans la mise en place et la maintenance du microbiome.

Advanced age is the major risk factor for idiopathic Parkinson's disease (PD), but to date the biological relationship between PD and ageing remains elusive. Here we describe the rationale and the design of the H2020 funded project "PROPAG-AGEING", whose aim is to characterize the contribution of the ageing process to PD development. We summarize current evidences that support the existence of a continuum between ageing and PD and justify the use of a Geroscience approach to study PD. We focus in particular on the role of inflammaging, the chronic, low-grade inflammation characteristic of elderly physiology, which can propagate and transmit both locally and systemically. We then describe PROPAG-AGEING design, which is based on the multi-omic characterization of peripheral samples from clinically characterized drug-naive and advanced PD, PD discordant twins, healthy controls and "super-controls", i.e. centenarians, who never showed clinical signs of motor disability, and their offspring. Omic results are then validated in a large number of samples, including in vitro models of dopaminergic neurons and healthy siblings of PD patients, who are at higher risk of developing PD, with the final aim of identifying the molecular perturbations that can deviate the trajectories of healthy ageing towards PD development.

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). The HPA axis is a dynamic system regulating homeostasis, especially the stress response, and is highly sensitive to adverse early life experiences. We review the evidence for the effects of PS on fetal programming of the HPA axis and the ANS. We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of these programming effects. Such approach would identify adverse postnatal brain developmental trajectories, a prerequisite for designing therapeutic interventions. The multiple scales include the biomarkers reflecting changes in the brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS. We conclude that studies into PS effects must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive biomarkers., Comment: Focused review, 13 pages, 5 figures

Fibrosis is the strongest predictor for disease-specific mortality in non-alcoholic fatty liver diseases (NAFLD), but the need for liver biopsy limits its diagnosis. We assessed the performance of plasma ficolin-2 (FCN-2) as a biomarker of fibrosis identified by an in silico discovery strategy. Two hundred and thirty-five morbidly obese (MO) subjects with biopsy-proven NAFLD stratified by fibrosis stage (F0, n = 44; F1, n = 134; F2, n = 46; F3/F4, n = 11) and 40 cirrhotic patients were enrolled. The cohort was subdivided into discovery (n = 76) and validation groups (n = 159). The plasma level of FCN-2 and other candidate markers was determined. FCN-2 was inversely correlated with the stage of liver fibrosis (ρ = −0.49, p < 0.001) independently of steatosis (p = 0.90), inflammation (p = 0.57), and ballooning (p = 0.59). In the global cohort, FCN-2 level decreased significantly in a stepwise fashion from F0/F1 (median 4753 ng/mL) to F2–F3–F4 (2760 ng/mL) and in cirrhotic subjects (1418 ng/mL). The diagnostic performance of FCN-2 in detecting F ≥ 2 was higher than other indexes (APRI, FIB-4) (AUROC 0.82, 0.68, and 0.6, respectively). The accuracy improved when combined with APRI score and HDL values (FCNscore, AUROC 0.85). Overall, the FCN-2 plasma level can accurately discriminate liver fibrosis status (minimal vs. moderate/advanced) significantly improving the fibrosis diagnostic algorithms.

The past few years observed a breakthrough of genome sequences of bacteria of Rhodococcus genus with significant biodegradation abilities. Invaluable knowledge from genome data and their functional analysis can be applied to develop and design strategies for attenuating damages caused by hydrocarbon contamination. With the advent of high-throughput -omic technologies, it is currently possible to utilize the functional properties of diverse catabolic genes, analyze an entire system at the level of molecule (DNA, RNA, protein, and metabolite), simultaneously predict and construct catabolic degradation pathways. In this review, the genes involved in the biodegradation of hydrocarbons and several emerging plasticizer compounds in Rhodococcus strains are described in detail (aliphatic, aromatics, PAH, phthalate, polyethylene, and polyisoprene). The metabolic biodegradation networks predicted from omics-derived data along with the catabolic enzymes exploited in diverse biotechnological and bioremediation applications are characterized.