Biowaste valorisation through biorefinery system according to Circular Economy strategy

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Impact of constitutional copy number variants on biological pathway evolution

Background: Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data. Results: We implemented an enrichment analysis of pathways accounting for CNVs and genes sizes and detected significant enrichment not only in signal transduction and extracellular biological processes, but also in metabolism pathways. Upon the estimation of CNV population differentiation (CNVs with different polymorphism frequencies across populations), we evaluated that 22% of the pathways contain at least one gene that is proximal to a CNV (CNV-gene pair) that shows significant population differentiation. The majority of these CNV-gene pairs belong to signal transduction pathways and 6% of the CNV-gene pairs show statistical association between the copy number states and the transcript levels. Conclusions: The analysis suggested possible examples of positive selection within individual populations including NF-kB, MAPK signaling pathways, and Alu/L1 retrotransposition factors. Altogether, our results suggest that constitutional CNVs may modulate subtle pathway changes through specific pathway enzymes, which may become fixed in some populations

A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays

BACKGROUND: Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA) experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. RESULTS: We propose an extension of the well-known Naïve Bayes classifier, which accounts for biological heterogeneity in a probabilistic framework, relying on Bayesian hierarchical models. The model, which can be efficiently learned from the training dataset, exploits a closed-form of classification equation, thus providing no additional computational cost with respect to the standard Naïve Bayes classifier. We validated the approach on several simulated datasets comparing its performances with the Naïve Bayes classifier. Moreover, we demonstrated that explicitly dealing with heterogeneity can improve classification accuracy on a TMA prostate cancer dataset. CONCLUSION: The proposed Hierarchical Naïve Bayes classifier can be conveniently applied in problems where within sample heterogeneity must be taken into account, such as TMA experiments and biological contexts where several measurements (replicates) are available for the same biological sample. The performance of the new approach is better than the standard Naïve Bayes model, in particular when the within sample heterogeneity is different in the different classes

Direct production of lactic acid based on simultaneous saccharification and fermentation of mixed restaurant food waste

This study introduces to a one-step process for the fermentative production of L(+)-lactic acid from mixed restaurant food waste. Food waste was used as carbon and nitrogen source in simultaneous saccharification and fermentation (SSF) using Lactobacillus sp. or Streptococcus sp. strains for L(+)-lactic acid production. Waste consisted of (w/w) 33.5% starch, 14.8% proteins, 12.9% fat and 8.5% free sugars. Lactobacillus sp. strains showed a productivity of 0.27–0.53 g L−1 h−1 and a yield of 0.07–0.14 g g−1 of theoretically available sugars, while Streptococcus sp. more efficiently degraded the food waste material and produced lactic acid at a maximum rate of 2.16 g L−1 h−1 and a yield of 0.81 g g−1. For SSF, no enzymes were added or other hydrolytic treatments were carried out. Outcomes revealed a linear relationship between lactic acid concentration and solid-to-liquid ratio when Streptococcus sp. was applied. Statistically, from a 20% (w/w) dry food waste blend 52.4 g L−1 lactic acid can be produced. Experimentally, 58 g L−1 was achieved in presence of 20% (w/w), which was the highest solid-to-liquid ratio that could be treated using the equipment applied. Irrespective if SSF was performed at laboratory or technical scale, or under non-sterile conditions, Streptococcus sp. efficiently liquefied food waste and converted the released nutrients directly into lactic acid without considerable production of other organic acids, such as acetic acid. Downstream processing including micro- and nanofiltration, electrodialysis, chromatography and distillation gave a pure 702 g L−1 L(+)-lactic acid formulation

Direct production of lactic acid based on simultaneous saccharification and fermentation of mixed restaurant food waste

This study introduces to a one-step process for the fermentative production of L(+)-lactic acid from mixed restaurant food waste. Food waste was used as carbon and nitrogen source in simultaneous saccharification and fermentation (SSF) using Lactobacillus sp. or Streptococcus sp. strains for L(+)-lactic acid production. Waste consisted of (w/w) 33.5% starch, 14.8% proteins, 12.9% fat and 8.5% free sugars. Lactobacillus sp. strains showed a productivity of 0.27–0.53 g L−1 h−1 and a yield of 0.07–0.14 g g−1 of theoretically available sugars, while Streptococcus sp. more efficiently degraded the food waste material and produced lactic acid at a maximum rate of 2.16 g L−1 h−1 and a yield of 0.81 g g−1. For SSF, no enzymes were added or other hydrolytic treatments were carried out. Outcomes revealed a linear relationship between lactic acid concentration and solid-to-liquid ratio when Streptococcus sp. was applied. Statistically, from a 20% (w/w) dry food waste blend 52.4 g L−1 lactic acid can be produced. Experimentally, 58 g L−1 was achieved in presence of 20% (w/w), which was the highest solid-to-liquid ratio that could be treated using the equipment applied. Irrespective if SSF was performed at laboratory or technical scale, or under non-sterile conditions, Streptococcus sp. efficiently liquefied food waste and converted the released nutrients directly into lactic acid without considerable production of other organic acids, such as acetic acid. Downstream processing including micro- and nanofiltration, electrodialysis, chromatography and distillation gave a pure 702 g L−1 L(+)-lactic acid formulation

Review of biochar application in anaerobic digestion processes

Among a wide variety of promising uses, in recent years the possibility of using biochar (BC) as additive to improve anaerobic digestion (AD) processes has attracted a growing interest. AD is a well-established biochemical process converting biomasses into biogas, a renewable energy source that can be directly used in heating and power generation rather than upgraded to bio-methane. Further, digestate (i.e. AD solid residue) could be valorised as soil improver. However, despite a growing number of full-scale biogas plants in Europe, (from about 6,200 in 2009 to 17,600 in 2016, according to European Biogas Association), some challenges limiting optimal AD performances still exist. They mainly include risks of acidification and/or potential inhibition of methanogenesis, hazards of atmospheric and water pollution derived from digestate addition to soil, as well as high energetic and economic costs for cleaning and upgrading of biogas. Thereby, many inorganic and carbonaceous additives have been investigated to stabilize AD and enhance methane production. Among them, BC is cost-effective and doesn’t need to be separated from digestate at the end of the AD process. Actually BC can improve digestate quality in terms of nutrients retention, increase of carbon to nitrogen ratio and reduction of nutrient leaching to soil. In addition, BC production and AD do not appear as competing processes, since biomasses with high lignocellulosic and low moisture contents, optimal for BC generation, are scarcely biodegradable during AD. Although a growing number of studies has verified the possibility of increasing methane production by BC addition during AD, to date, a clear comprehension of potential interactions between BC and AD process has not been fully reached. Since BC can be produced with a wide variety of physico-chemical properties adapted to specific applications, a proper knowledge of these mechanisms and of the related BC properties represent crucial issues. Therefore, the present study aimed to: 1. analyse the mechanisms by which BC would counteract some of the main AD limitations; 2. to perform an economic and environmental assessment of BC production and application in AD. Around 200 studies were selected and analysed by means of an extensive literature review on Science Direct, Scopus, and other scientific databases. Based on the analysis of the reviewed literature, it can be observed that the positive influence of BC on AD processes may act through different potential mechanisms: (1) increase of the buffering capacity of the AD system; (2) mitigation of potential inhibitors (NH3/NH4+ and others); (3) acting as a support medium for biomass immobilization and acclimation; (4) promotion of interspecies electron transfer between microbial populations; (5) enhancement of digestate quality; (6) in-situ biogas cleaning and upgrading (depletion of CO2 and H2S). In general, some of the key properties of BC for the above-mentioned mechanisms are high alkalinity, adequate sorption capacity for specific compounds, high surface area and porous structure able to promote microbial population immobilization and inhibitors’ adsorption, varied functional groups and superficial chemical properties, large electrical conductivity and electron exchange capacity. The economic and environmental analysis suggested that BC environmental applications are encouraged by the net mitigation of carbon emissions; while the economic feasibility of BC production could be linked to the promising energy content of lignocellulosic feedstocks. Further, the environmental benefits related to BC application to AD processes can be synergistically improved by coupling the use of BC derived from lignocellulosic feedstocks to the carbon neutral AD to optimize biogas productio

Optimizing copy number variation analysis using genome-wide short sequence oligonucleotide arrays

The detection of copy number variants (CNV) by array-based platforms provides valuable insight into understanding human diversity. However, suboptimal study design and data processing negatively affect CNV assessment. We quantitatively evaluate their impact when short-sequence oligonucleotide arrays are applied (Affymetrix Genome-Wide Human SNP Array 6.0) by evaluating 42 HapMap samples for CNV detection. Several processing and segmentation strategies are implemented, and results are compared to CNV assessment obtained using an oligonucleotide array CGH platform designed to query CNVs at high resolution (Agilent). We quantitatively demonstrate that different reference models (e.g. single versus pooled sample reference) used to detect CNVs are a major source of inter-platform discrepancy (up to 30%) and that CNVs residing within segmental duplication regions (higher reference copy number) are significantly harder to detect (P < 0.0001). After adjusting Affymetrix data to mimic the Agilent experimental design (reference sample effect), we applied several common segmentation approaches and evaluated differential sensitivity and specificity for CNV detection, ranging 39–77% and 86–100% for non-segmental duplication regions, respectively, and 18–55% and 39–77% for segmental duplications. Our results are relevant to any array-based CNV study and provide guidelines to optimize performance based on study-specific objectives

Charting differentially methylated regions in cancer with Rocker-meth

Matteo Benelli et al. present Rocker-meth, a new Hidden Markov Model (HMM)-based method, to robustly identify differentially methylated regions (DMRs). They use Rocker-meth to analyse more than 6000 methylation profiles across 14 cancer types, providing a catalog of tumor-specific and shared DMRs

Assessment of the Treatment Performance of an Open-Air Green Wall Fed with Graywater under Winter Conditions

Graywater (GW), i.e., the portion of household wastewater that excludes toilet flushes, is an interesting wastewater type because it requires only mild treatment. Green walls have been proposed as example of a nature-based solution for GW treatment due to low energy requirement and high ecological/societal benefits; however, indications about their treatment performances remain limited. This work presents experimental results of a laboratory modular green wall for GW treatment. Experiments have been performed outdoors during the winter season for three months. Each panel included four vertical columns of planted pots, and it was fed with 100 L of synthetic GW per day. Removal efficiencies were as follows (average values): 40% chemical oxygen demand, 97% biochemical oxygen demand, 61% total Kjeldhal nitrogen, 56% NO3–-N, 57% total phosphorus, 99% Escherichia coli, and 63% anionic surfactants. This work proved the potential of an open-air green wall for treating GW, even under challenging conditions for biological treatment processes and with high hydraulic loading rates

SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines

Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use