Production de spiruline à la ferme : produire de la spiruline à la ferme grâce au digestat et à la chaleur excédentaire d’une installation de biogaz

The development of projects coupling an agricultural anaerobic digestion installation with the production of spirulina is an attractive concept, since the waste streams from the methanisation and from biogas valorization can be used to produce a high value product. This principle allows a better energetic valorization of surplus heat and of exhaust gases coming from the cogeneration unit. The limits of this configuration have been evaluated for Switzerland to study if the implementation of such coupling increases the competitiveness of agricultural anaerobic digestion. The thermal autonomy of the plant has been established as the main criterion to design the spirulina production units. For different working conditions (light radiation, nutrients source, size of methanisation units), the potential production of spirulina has been evaluated. The process energy yield, the environmental impact and the process economy show that 50% of surplus heat can be valorized, being 85-90% of heat contained in the exhaust gases; that the decrease in carbon dioxide emissions is not relevant and that, for the conditions tested, the operating costs are currently too high to allow the economic feasibility of the project

Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients

Multiple Sclerosis (MS) is an autoimmune disease of the central nervous system with prominent neurodegenerative components. The triggering and progression of MS is associated with transcriptional and epigenetic alterations in several tissues, including peripheral blood. The combined influence of transcriptional and epigenetic changes associated with MS has not been assessed in the same individuals. Here we generated paired transcriptomic (RNA-seq) and DNA methylation (Illumina 450 K array) profiles of CD4+ and CD8+ T cells (CD4, CD8), using clinically accessible blood from healthy donors and MS patients in the initial relapsing-remitting and subsequent secondary-progressive stage. By integrating the output of a differential expression test with a permutation-based non-parametric combination methodology, we identified 149 differentially expressed (DE) genes in both CD4 and CD8 cells collected from MS patients. Moreover, by leveraging the methylation-dependent regulation of gene expression, we identified the gene SH3YL1, which displayed significant correlated expression and methylation changes in MS patients. Importantly, silencing of SH3YL1 in primary human CD4 cells demonstrated its influence on T cell activation. Collectively, our strategy based on paired sampling of several cell-types provides a novel approach to increase sensitivity for identifying shared mechanisms altered in CD4 and CD8 cells of relevance in MS in small sized clinical materials

Molecularly determined total tumour load in lymph nodes of stage I–II colon cancer patients correlates with high-risk factors. A multicentre prospective study

Stage I–II (pN0) colorectal cancer patients are surgically treated although up to 25 % will eventually die from disease recurrence. Lymph node (LN) status is an independent prognostic factor in colorectal cancer (CRC), and molecular tumour detection in LN of early-stage CRC patients is associated with an increased risk of disease recurrence and poor survival. This prospective multicentre study aimed to determine the relationship between LN molecular tumour burden and conventional high-risk factors in stage I–II colon cancer patients. A total of 1940 LN from 149 pathologically assessed pN0 colon cancer patients were analysed for the amount of tumour cytokeratin 19 (CK19) messenger RNA (mRNA) with the quantitative reverse transcription loop-mediated isothermal amplification molecular assay One-Step Nucleic Acid Amplification. Patient’s total tumour load (TTL) resulted from the sum of all CK19 mRNA tumour copies/μL of each positive LN from the colectomy specimen. A median of 15 LN were procured per case (IQR 12;20). Molecular positivity correlated with high-grade (p < 0.01), mucinous/signet ring type (p = 0.017), male gender (p = 0.02), number of collected LN (p = 0.012) and total LN weight per case (p < 0.01). The TTL was related to pT stage (p = 0.01) and tumour size (p < 0.01) in low-grade tumours. Multivariate logistic regression showed independent correlation of molecular positivity with gender, tumour grade and number of fresh LN [AUC = 0.71 (95 % CI = 0.62–0.79)]. Our results show that lymph node CK19 mRNA detection correlates with classical high-risk factors in stage I–II colon cancer patients. Total tumour load is a quantitative and objective measure that may help to better stage early colon cancer patients.Work supported by the Banc de Tumors-Biobanc Hospital Clinic-IDIBAPS and Xarxa de Bancs de Tumors de Catalunya (XBTC), and by grants from the Fundación Científica de la Asociación Española Contra el Cáncer (GCB13131592CAST), Ministerio de Economía y Competitividad (SAF2014–54,453-R), Agència de Gestió d’Ajuts Universitaris i de Recerca (2014SGR135), and by Sysmex Coorp Spain (Sant Just Desvern, Spain). CIBERehd is funded by the Instituto de Salud Carlos II

STATegra: Multi-Omics Data Integration - A Conceptual Scheme With a Bioinformatics Pipeline

Technologies for profiling samples using different omics platforms have been at the forefront since the human genome project. Large-scale multi-omics data hold the promise of deciphering different regulatory layers. Yet, while there is a myriad of bioinformatics tools, each multi-omics analysis appears to start from scratch with an arbitrary decision over which tools to use and how to combine them. Therefore, it is an unmet need to conceptualize how to integrate such data and implement and validate pipelines in different cases. We have designed a conceptual framework (STATegra), aiming it to be as generic as possible for multi-omics analysis, combining available multi-omic anlaysis tools (machine learning component analysis, non-parametric data combination, and a multi-omics exploratory analysis) in a step-wise manner. While in several studies, we have previously combined those integrative tools, here, we provide a systematic description of the STATegra framework and its validation using two The Cancer Genome Atlas (TCGA) case studies. For both, the Glioblastoma and the Skin Cutaneous Melanoma (SKCM) cases, we demonstrate an enhanced capacity of the framework (and beyond the individual tools) to identify features and pathways compared to single-omics analysis. Such an integrative multi-omics analysis framework for identifying features and components facilitates the discovery of new biology. Finally, we provide several options for applying the STATegra framework when parametric assumptions are fulfilled and for the case when not all the samples are profiled for all omics. The STATegra framework is built using several tools, which are being integrated step-by-step as OpenSource in the STATegRa Bioconductor packag

Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

The historical lack of preclinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers the advance of therapeutic discoveries. To circumvent this limitation, we screened mice engineered to carry eight MM lesions (NF-κB, KRAS, MYC, TP53, BCL2, cyclin D1, MMSET/NSD2 and c-MAF) combinatorially activated in B lymphocytes following T cell-driven immunization. Fifteen genetically diverse models developed bone marrow (BM) tumors fulfilling MM pathogenesis. Integrative analyses of ∼500 mice and ∼1,000 patients revealed a common MAPK-MYC genetic pathway that accelerated time to progression from precursor states across genetically heterogeneous MM. MYC-dependent time to progression conditioned immune evasion mechanisms that remodeled the BM microenvironment differently. Rapid MYC-driven progressors exhibited a high number of activated/exhausted CD8+ T cells with reduced immunosuppressive regulatory T (Treg) cells, while late MYC acquisition in slow progressors was associated with lower CD8+ T cell infiltration and more abundant Treg cells. Single-cell transcriptomics and functional assays defined a high ratio of CD8+ T cells versus Treg cells as a predictor of response to immune checkpoint blockade (ICB). In clinical series, high CD8+ T/Treg cell ratios underlie early progression in untreated smoldering MM, and correlated with early relapse in newly diagnosed patients with MM under Len/Dex therapy. In ICB-refractory MM models, increasing CD8+ T cell cytotoxicity or depleting Treg cells reversed immunotherapy resistance and yielded prolonged MM control. Our experimental models enable the correlation of MM genetic and immunological traits with preclinical therapy responses, which may inform the next-generation immunotherapy trials